repo_name
stringlengths 7
94
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stringlengths 4
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| repo_head_hexsha
stringlengths 40
40
| content
stringlengths 10
680k
| apis
stringlengths 2
680k
|
|---|---|---|---|---|
Dagmoores/ProjetoIntegradorIUnivesp | biblioteca/views.py | 86f5004c359b760cceec87bfa905db16e3375653 | from django.views.generic import DetailView, ListView, TemplateView
from .models import Books
class BooksListView(ListView):
model = Books
class BooksDeitalView(DetailView):
model = Books
class Home(TemplateView):
template_name = './biblioteca/index.html'
class TermsOfService(TemplateView):
template_name = './biblioteca/termsOfService.html' | [] |
scwangdyd/large_vocabulary_hoi_detection | choir/evaluation/__init__.py | db7a4397c3050b1bf9a3f7473edf125e2b1046c4 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from .evaluator import DatasetEvaluator, DatasetEvaluators, inference_context, inference_on_dataset
from .testing import print_csv_format, verify_results
from .hico_evaluation import HICOEvaluator
from .swig_evaluation import SWIGEvaluator
# from .doh_evaluation import DOHDetectionEvaluator
__all__ = [k for k in globals().keys() if not k.startswith("_")]
| [] |
LHLHLHE/api_yamdb | api_yamdb/reviews/models.py | bda83815a47f3fda03d54220dfe41e9263ff1b05 | import datetime as dt
from django.db import models
from django.core.validators import MinValueValidator, MaxValueValidator
from django.core.exceptions import ValidationError
from users.models import CustomUser
def validate_year(value):
"""
Год выпуска произведения не может быть больше текущего.
"""
if value > dt.datetime.now().year:
raise ValidationError(
'Год выпуска превышает текущий!')
return value
class Category(models.Model):
"""Модель категорий."""
name = models.CharField(max_length=256, verbose_name='Название')
slug = models.SlugField(
max_length=50,
unique=True,
verbose_name='Идентификатор')
class Meta:
ordering = ('name',)
verbose_name = 'Категория'
verbose_name_plural = 'Категории'
def __str__(self):
return self.slug
class Genre(models.Model):
"""Модель жанров."""
name = models.CharField(max_length=256, verbose_name='Название')
slug = models.SlugField(
max_length=50,
unique=True,
verbose_name='Идентификатор')
class Meta:
ordering = ('name',)
verbose_name = 'Жанр'
verbose_name_plural = 'Жанры'
def __str__(self):
return self.slug
class Title(models.Model):
"""Модель произведений."""
name = models.TextField(verbose_name='Название')
year = models.IntegerField(
validators=[validate_year],
verbose_name='Год выпуска')
description = models.TextField(
blank=True,
verbose_name='Описание')
genre = models.ManyToManyField(
Genre,
through='GenreTitle',
verbose_name='Жанры')
category = models.ForeignKey(
Category,
on_delete=models.SET_NULL,
blank=True,
null=True,
related_name='titles',
verbose_name='Категория')
class Meta:
ordering = ('name',)
verbose_name = 'Произведение'
verbose_name_plural = 'Произведения'
def __str__(self):
return (
f'name: {self.name}, '
f'year: {self.year}, '
)
class GenreTitle(models.Model):
"""Модель для связи произведений и жанров отношением многие ко многим."""
genre = models.ForeignKey(
Genre,
on_delete=models.SET_NULL,
blank=True,
null=True)
title = models.ForeignKey(Title, on_delete=models.CASCADE)
def __str__(self):
return f'{self.genre} --- {self.title}'
class Review(models.Model):
title = models.ForeignKey(
Title,
on_delete=models.CASCADE,
verbose_name='Произведение',
)
text = models.TextField(
verbose_name='текст',
)
author = models.ForeignKey(
CustomUser,
on_delete=models.CASCADE,
verbose_name='Автор'
)
score = models.IntegerField(
validators=[
MinValueValidator(1),
MaxValueValidator(10)
],
verbose_name='Оценка'
)
pub_date = models.DateTimeField(
auto_now_add=True,
verbose_name='Дата публикации'
)
class Meta:
constraints = [
models.UniqueConstraint(
fields=['author', 'title'],
name='unique review'
)
]
verbose_name = 'Отзыв'
verbose_name_plural = 'Отзывы'
default_related_name = 'reviews'
def __str__(self):
return self.text[:60]
class Comment(models.Model):
review = models.ForeignKey(
Review,
on_delete=models.CASCADE,
related_name='comments',
verbose_name='Отзыв',
)
text = models.TextField(verbose_name='Текст')
author = models.ForeignKey(
CustomUser,
on_delete=models.CASCADE,
related_name='comments',
verbose_name='Автор'
)
pub_date = models.DateTimeField(
auto_now_add=True,
verbose_name='Дата публикации'
)
class Meta:
verbose_name = 'Комментарий'
verbose_name_plural = 'Комментарии'
def __str__(self):
return self.text
| [((520, 577), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(256)', 'verbose_name': '"""Название"""'}), "(max_length=256, verbose_name='Название')\n", (536, 577), False, 'from django.db import models\n'), ((589, 663), 'django.db.models.SlugField', 'models.SlugField', ([], {'max_length': '(50)', 'unique': '(True)', 'verbose_name': '"""Идентификатор"""'}), "(max_length=50, unique=True, verbose_name='Идентификатор')\n", (605, 663), False, 'from django.db import models\n'), ((926, 983), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(256)', 'verbose_name': '"""Название"""'}), "(max_length=256, verbose_name='Название')\n", (942, 983), False, 'from django.db import models\n'), ((995, 1069), 'django.db.models.SlugField', 'models.SlugField', ([], {'max_length': '(50)', 'unique': '(True)', 'verbose_name': '"""Идентификатор"""'}), "(max_length=50, unique=True, verbose_name='Идентификатор')\n", (1011, 1069), False, 'from django.db import models\n'), ((1329, 1370), 'django.db.models.TextField', 'models.TextField', ([], {'verbose_name': '"""Название"""'}), "(verbose_name='Название')\n", (1345, 1370), False, 'from django.db import models\n'), ((1382, 1457), 'django.db.models.IntegerField', 'models.IntegerField', ([], {'validators': '[validate_year]', 'verbose_name': '"""Год выпуска"""'}), "(validators=[validate_year], verbose_name='Год выпуска')\n", (1401, 1457), False, 'from django.db import models\n'), ((1493, 1546), 'django.db.models.TextField', 'models.TextField', ([], {'blank': '(True)', 'verbose_name': '"""Описание"""'}), "(blank=True, verbose_name='Описание')\n", (1509, 1546), False, 'from django.db import models\n'), ((1576, 1649), 'django.db.models.ManyToManyField', 'models.ManyToManyField', (['Genre'], {'through': '"""GenreTitle"""', 'verbose_name': '"""Жанры"""'}), "(Genre, through='GenreTitle', verbose_name='Жанры')\n", (1598, 1649), False, 'from django.db import models\n'), ((1690, 1821), 'django.db.models.ForeignKey', 'models.ForeignKey', (['Category'], {'on_delete': 'models.SET_NULL', 'blank': '(True)', 'null': '(True)', 'related_name': '"""titles"""', 'verbose_name': '"""Категория"""'}), "(Category, on_delete=models.SET_NULL, blank=True, null=\n True, related_name='titles', verbose_name='Категория')\n", (1707, 1821), False, 'from django.db import models\n'), ((2240, 2314), 'django.db.models.ForeignKey', 'models.ForeignKey', (['Genre'], {'on_delete': 'models.SET_NULL', 'blank': '(True)', 'null': '(True)'}), '(Genre, on_delete=models.SET_NULL, blank=True, null=True)\n', (2257, 2314), False, 'from django.db import models\n'), ((2360, 2410), 'django.db.models.ForeignKey', 'models.ForeignKey', (['Title'], {'on_delete': 'models.CASCADE'}), '(Title, on_delete=models.CASCADE)\n', (2377, 2410), False, 'from django.db import models\n'), ((2527, 2606), 'django.db.models.ForeignKey', 'models.ForeignKey', (['Title'], {'on_delete': 'models.CASCADE', 'verbose_name': '"""Произведение"""'}), "(Title, on_delete=models.CASCADE, verbose_name='Произведение')\n", (2544, 2606), False, 'from django.db import models\n'), ((2649, 2687), 'django.db.models.TextField', 'models.TextField', ([], {'verbose_name': '"""текст"""'}), "(verbose_name='текст')\n", (2665, 2687), False, 'from django.db import models\n'), ((2716, 2793), 'django.db.models.ForeignKey', 'models.ForeignKey', (['CustomUser'], {'on_delete': 'models.CASCADE', 'verbose_name': '"""Автор"""'}), "(CustomUser, on_delete=models.CASCADE, verbose_name='Автор')\n", (2733, 2793), False, 'from django.db import models\n'), ((3008, 3079), 'django.db.models.DateTimeField', 'models.DateTimeField', ([], {'auto_now_add': '(True)', 'verbose_name': '"""Дата публикации"""'}), "(auto_now_add=True, verbose_name='Дата публикации')\n", (3028, 3079), False, 'from django.db import models\n'), ((3494, 3596), 'django.db.models.ForeignKey', 'models.ForeignKey', (['Review'], {'on_delete': 'models.CASCADE', 'related_name': '"""comments"""', 'verbose_name': '"""Отзыв"""'}), "(Review, on_delete=models.CASCADE, related_name='comments',\n verbose_name='Отзыв')\n", (3511, 3596), False, 'from django.db import models\n'), ((3643, 3681), 'django.db.models.TextField', 'models.TextField', ([], {'verbose_name': '"""Текст"""'}), "(verbose_name='Текст')\n", (3659, 3681), False, 'from django.db import models\n'), ((3695, 3802), 'django.db.models.ForeignKey', 'models.ForeignKey', (['CustomUser'], {'on_delete': 'models.CASCADE', 'related_name': '"""comments"""', 'verbose_name': '"""Автор"""'}), "(CustomUser, on_delete=models.CASCADE, related_name=\n 'comments', verbose_name='Автор')\n", (3712, 3802), False, 'from django.db import models\n'), ((3851, 3922), 'django.db.models.DateTimeField', 'models.DateTimeField', ([], {'auto_now_add': '(True)', 'verbose_name': '"""Дата публикации"""'}), "(auto_now_add=True, verbose_name='Дата публикации')\n", (3871, 3922), False, 'from django.db import models\n'), ((369, 418), 'django.core.exceptions.ValidationError', 'ValidationError', (['"""Год выпуска превышает текущий!"""'], {}), "('Год выпуска превышает текущий!')\n", (384, 418), False, 'from django.core.exceptions import ValidationError\n'), ((331, 348), 'datetime.datetime.now', 'dt.datetime.now', ([], {}), '()\n', (346, 348), True, 'import datetime as dt\n'), ((3155, 3228), 'django.db.models.UniqueConstraint', 'models.UniqueConstraint', ([], {'fields': "['author', 'title']", 'name': '"""unique review"""'}), "(fields=['author', 'title'], name='unique review')\n", (3178, 3228), False, 'from django.db import models\n'), ((2890, 2910), 'django.core.validators.MinValueValidator', 'MinValueValidator', (['(1)'], {}), '(1)\n', (2907, 2910), False, 'from django.core.validators import MinValueValidator, MaxValueValidator\n'), ((2924, 2945), 'django.core.validators.MaxValueValidator', 'MaxValueValidator', (['(10)'], {}), '(10)\n', (2941, 2945), False, 'from django.core.validators import MinValueValidator, 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matthewpruett/angr | angr/engines/pcode/arch/ArchPcode_PowerPC_LE_32_QUICC.py | bfba2af1ea2eb941001339f47a1264a685c60eec | ###
### This file was automatically generated
###
from archinfo.arch import register_arch, Endness, Register
from .common import ArchPcode
class ArchPcode_PowerPC_LE_32_QUICC(ArchPcode):
name = 'PowerPC:LE:32:QUICC'
pcode_arch = 'PowerPC:LE:32:QUICC'
description = 'PowerQUICC-III 32-bit little endian family'
bits = 32
ip_offset = 0x780
sp_offset = 0x4
bp_offset = sp_offset
instruction_endness = Endness.LE
register_list = [
Register('r0', 4, 0x0),
Register('r1', 4, 0x4),
Register('r2', 4, 0x8),
Register('r3', 4, 0xc),
Register('r4', 4, 0x10),
Register('r5', 4, 0x14),
Register('r6', 4, 0x18),
Register('r7', 4, 0x1c),
Register('r8', 4, 0x20),
Register('r9', 4, 0x24),
Register('r10', 4, 0x28),
Register('r11', 4, 0x2c),
Register('r12', 4, 0x30),
Register('r13', 4, 0x34),
Register('r14', 4, 0x38),
Register('r15', 4, 0x3c),
Register('r16', 4, 0x40),
Register('r17', 4, 0x44),
Register('r18', 4, 0x48),
Register('r19', 4, 0x4c),
Register('r20', 4, 0x50),
Register('r21', 4, 0x54),
Register('r22', 4, 0x58),
Register('r23', 4, 0x5c),
Register('r24', 4, 0x60),
Register('r25', 4, 0x64),
Register('r26', 4, 0x68),
Register('r27', 4, 0x6c),
Register('r28', 4, 0x70),
Register('r29', 4, 0x74),
Register('r30', 4, 0x78),
Register('r31', 4, 0x7c),
Register('xer_so', 1, 0x400),
Register('xer_ov', 1, 0x401),
Register('xer_ov32', 1, 0x402),
Register('xer_ca', 1, 0x403),
Register('xer_ca32', 1, 0x404),
Register('xer_count', 1, 0x405),
Register('fp_fx', 1, 0x500),
Register('fp_fex', 1, 0x501),
Register('fp_vx', 1, 0x502),
Register('fp_ox', 1, 0x503),
Register('fp_ux', 1, 0x504),
Register('fp_zx', 1, 0x505),
Register('fp_xx', 1, 0x506),
Register('fp_vxsnan', 1, 0x507),
Register('fp_vxisi', 1, 0x508),
Register('fp_vxidi', 1, 0x509),
Register('fp_vxzdz', 1, 0x50a),
Register('fp_vximz', 1, 0x50b),
Register('fp_vxvc', 1, 0x50c),
Register('fp_fr', 1, 0x50d),
Register('fp_fi', 1, 0x50e),
Register('fp_c', 1, 0x50f),
Register('fp_cc0', 1, 0x510),
Register('fp_cc1', 1, 0x511),
Register('fp_cc2', 1, 0x512),
Register('fp_cc3', 1, 0x513),
Register('fp_reserve1', 1, 0x514),
Register('fp_vxsoft', 1, 0x515),
Register('fp_vxsqrt', 1, 0x516),
Register('fp_vxcvi', 1, 0x517),
Register('fp_ve', 1, 0x518),
Register('fp_oe', 1, 0x519),
Register('fp_ue', 1, 0x51a),
Register('fp_ze', 1, 0x51b),
Register('fp_xe', 1, 0x51c),
Register('fp_ni', 1, 0x51d),
Register('fp_rn0', 1, 0x51e),
Register('fp_rn1', 1, 0x51f),
Register('msr', 4, 0x700),
Register('reserve_address', 4, 0x720),
Register('reserve', 1, 0x728),
Register('reserve_length', 1, 0x730),
Register('pc', 4, 0x780, alias_names=('ip',)),
Register('sr0', 4, 0x800),
Register('sr1', 4, 0x804),
Register('sr2', 4, 0x808),
Register('sr3', 4, 0x80c),
Register('sr4', 4, 0x810),
Register('sr5', 4, 0x814),
Register('sr6', 4, 0x818),
Register('sr7', 4, 0x81c),
Register('sr8', 4, 0x820),
Register('sr9', 4, 0x824),
Register('sr10', 4, 0x828),
Register('sr11', 4, 0x82c),
Register('sr12', 4, 0x830),
Register('sr13', 4, 0x834),
Register('sr14', 4, 0x838),
Register('sr15', 4, 0x83c),
Register('crall', 8, 0x900),
Register('cr0', 1, 0x900),
Register('cr1', 1, 0x901),
Register('cr2', 1, 0x902),
Register('cr3', 1, 0x903),
Register('cr4', 1, 0x904),
Register('cr5', 1, 0x905),
Register('cr6', 1, 0x906),
Register('cr7', 1, 0x907),
Register('tea', 4, 0x980),
Register('r2save', 4, 0x988),
Register('spr000', 4, 0x1000),
Register('xer', 4, 0x1004),
Register('spr002', 4, 0x1008),
Register('spr003', 4, 0x100c),
Register('spr004', 4, 0x1010),
Register('spr005', 4, 0x1014),
Register('spr006', 4, 0x1018),
Register('spr007', 4, 0x101c),
Register('lr', 4, 0x1020),
Register('ctr', 4, 0x1024),
Register('spr00a', 4, 0x1028),
Register('spr00b', 4, 0x102c),
Register('spr00c', 4, 0x1030),
Register('spr00d', 4, 0x1034),
Register('spr00e', 4, 0x1038),
Register('spr00f', 4, 0x103c),
Register('spr010', 4, 0x1040),
Register('spr011', 4, 0x1044),
Register('spr012', 4, 0x1048),
Register('spr013', 4, 0x104c),
Register('spr014', 4, 0x1050),
Register('spr015', 4, 0x1054),
Register('spr016', 4, 0x1058),
Register('spr017', 4, 0x105c),
Register('spr018', 4, 0x1060),
Register('spr019', 4, 0x1064),
Register('srr0', 4, 0x1068),
Register('srr1', 4, 0x106c),
Register('spr01c', 4, 0x1070),
Register('spr01d', 4, 0x1074),
Register('spr01e', 4, 0x1078),
Register('spr01f', 4, 0x107c),
Register('spr020', 4, 0x1080),
Register('spr021', 4, 0x1084),
Register('spr022', 4, 0x1088),
Register('spr023', 4, 0x108c),
Register('spr024', 4, 0x1090),
Register('spr025', 4, 0x1094),
Register('spr026', 4, 0x1098),
Register('spr027', 4, 0x109c),
Register('spr028', 4, 0x10a0),
Register('spr029', 4, 0x10a4),
Register('spr02a', 4, 0x10a8),
Register('spr02b', 4, 0x10ac),
Register('spr02c', 4, 0x10b0),
Register('spr02d', 4, 0x10b4),
Register('spr02e', 4, 0x10b8),
Register('spr02f', 4, 0x10bc),
Register('spr030', 4, 0x10c0),
Register('spr031', 4, 0x10c4),
Register('spr032', 4, 0x10c8),
Register('spr033', 4, 0x10cc),
Register('spr034', 4, 0x10d0),
Register('spr035', 4, 0x10d4),
Register('spr036', 4, 0x10d8),
Register('spr037', 4, 0x10dc),
Register('spr038', 4, 0x10e0),
Register('spr039', 4, 0x10e4),
Register('spr03a', 4, 0x10e8),
Register('spr03b', 4, 0x10ec),
Register('spr03c', 4, 0x10f0),
Register('spr03d', 4, 0x10f4),
Register('spr03e', 4, 0x10f8),
Register('spr03f', 4, 0x10fc),
Register('spr040', 4, 0x1100),
Register('spr041', 4, 0x1104),
Register('spr042', 4, 0x1108),
Register('spr043', 4, 0x110c),
Register('spr044', 4, 0x1110),
Register('spr045', 4, 0x1114),
Register('spr046', 4, 0x1118),
Register('spr047', 4, 0x111c),
Register('spr048', 4, 0x1120),
Register('spr049', 4, 0x1124),
Register('spr04a', 4, 0x1128),
Register('spr04b', 4, 0x112c),
Register('spr04c', 4, 0x1130),
Register('spr04d', 4, 0x1134),
Register('spr04e', 4, 0x1138),
Register('spr04f', 4, 0x113c),
Register('spr050', 4, 0x1140),
Register('spr051', 4, 0x1144),
Register('spr052', 4, 0x1148),
Register('spr053', 4, 0x114c),
Register('spr054', 4, 0x1150),
Register('spr055', 4, 0x1154),
Register('spr056', 4, 0x1158),
Register('spr057', 4, 0x115c),
Register('spr058', 4, 0x1160),
Register('spr059', 4, 0x1164),
Register('spr05a', 4, 0x1168),
Register('spr05b', 4, 0x116c),
Register('spr05c', 4, 0x1170),
Register('spr05d', 4, 0x1174),
Register('spr05e', 4, 0x1178),
Register('spr05f', 4, 0x117c),
Register('spr060', 4, 0x1180),
Register('spr061', 4, 0x1184),
Register('spr062', 4, 0x1188),
Register('spr063', 4, 0x118c),
Register('spr064', 4, 0x1190),
Register('spr065', 4, 0x1194),
Register('spr066', 4, 0x1198),
Register('spr067', 4, 0x119c),
Register('spr068', 4, 0x11a0),
Register('spr069', 4, 0x11a4),
Register('spr06a', 4, 0x11a8),
Register('spr06b', 4, 0x11ac),
Register('spr06c', 4, 0x11b0),
Register('spr06d', 4, 0x11b4),
Register('spr06e', 4, 0x11b8),
Register('spr06f', 4, 0x11bc),
Register('spr070', 4, 0x11c0),
Register('spr071', 4, 0x11c4),
Register('spr072', 4, 0x11c8),
Register('spr073', 4, 0x11cc),
Register('spr074', 4, 0x11d0),
Register('spr075', 4, 0x11d4),
Register('spr076', 4, 0x11d8),
Register('spr077', 4, 0x11dc),
Register('spr078', 4, 0x11e0),
Register('spr079', 4, 0x11e4),
Register('spr07a', 4, 0x11e8),
Register('spr07b', 4, 0x11ec),
Register('spr07c', 4, 0x11f0),
Register('spr07d', 4, 0x11f4),
Register('spr07e', 4, 0x11f8),
Register('spr07f', 4, 0x11fc),
Register('spr080', 4, 0x1200),
Register('spr081', 4, 0x1204),
Register('spr082', 4, 0x1208),
Register('spr083', 4, 0x120c),
Register('spr084', 4, 0x1210),
Register('spr085', 4, 0x1214),
Register('spr086', 4, 0x1218),
Register('spr087', 4, 0x121c),
Register('spr088', 4, 0x1220),
Register('spr089', 4, 0x1224),
Register('spr08a', 4, 0x1228),
Register('spr08b', 4, 0x122c),
Register('spr08c', 4, 0x1230),
Register('spr08d', 4, 0x1234),
Register('spr08e', 4, 0x1238),
Register('spr08f', 4, 0x123c),
Register('spr090', 4, 0x1240),
Register('spr091', 4, 0x1244),
Register('spr092', 4, 0x1248),
Register('spr093', 4, 0x124c),
Register('spr094', 4, 0x1250),
Register('spr095', 4, 0x1254),
Register('spr096', 4, 0x1258),
Register('spr097', 4, 0x125c),
Register('spr098', 4, 0x1260),
Register('spr099', 4, 0x1264),
Register('spr09a', 4, 0x1268),
Register('spr09b', 4, 0x126c),
Register('spr09c', 4, 0x1270),
Register('spr09d', 4, 0x1274),
Register('spr09e', 4, 0x1278),
Register('spr09f', 4, 0x127c),
Register('spr0a0', 4, 0x1280),
Register('spr0a1', 4, 0x1284),
Register('spr0a2', 4, 0x1288),
Register('spr0a3', 4, 0x128c),
Register('spr0a4', 4, 0x1290),
Register('spr0a5', 4, 0x1294),
Register('spr0a6', 4, 0x1298),
Register('spr0a7', 4, 0x129c),
Register('spr0a8', 4, 0x12a0),
Register('spr0a9', 4, 0x12a4),
Register('spr0aa', 4, 0x12a8),
Register('spr0ab', 4, 0x12ac),
Register('spr0ac', 4, 0x12b0),
Register('spr0ad', 4, 0x12b4),
Register('spr0ae', 4, 0x12b8),
Register('spr0af', 4, 0x12bc),
Register('spr0b0', 4, 0x12c0),
Register('spr0b1', 4, 0x12c4),
Register('spr0b2', 4, 0x12c8),
Register('spr0b3', 4, 0x12cc),
Register('spr0b4', 4, 0x12d0),
Register('spr0b5', 4, 0x12d4),
Register('spr0b6', 4, 0x12d8),
Register('spr0b7', 4, 0x12dc),
Register('spr0b8', 4, 0x12e0),
Register('spr0b9', 4, 0x12e4),
Register('spr0ba', 4, 0x12e8),
Register('spr0bb', 4, 0x12ec),
Register('spr0bc', 4, 0x12f0),
Register('spr0bd', 4, 0x12f4),
Register('spr0be', 4, 0x12f8),
Register('spr0bf', 4, 0x12fc),
Register('spr0c0', 4, 0x1300),
Register('spr0c1', 4, 0x1304),
Register('spr0c2', 4, 0x1308),
Register('spr0c3', 4, 0x130c),
Register('spr0c4', 4, 0x1310),
Register('spr0c5', 4, 0x1314),
Register('spr0c6', 4, 0x1318),
Register('spr0c7', 4, 0x131c),
Register('spr0c8', 4, 0x1320),
Register('spr0c9', 4, 0x1324),
Register('spr0ca', 4, 0x1328),
Register('spr0cb', 4, 0x132c),
Register('spr0cc', 4, 0x1330),
Register('spr0cd', 4, 0x1334),
Register('spr0ce', 4, 0x1338),
Register('spr0cf', 4, 0x133c),
Register('spr0d0', 4, 0x1340),
Register('spr0d1', 4, 0x1344),
Register('spr0d2', 4, 0x1348),
Register('spr0d3', 4, 0x134c),
Register('spr0d4', 4, 0x1350),
Register('spr0d5', 4, 0x1354),
Register('spr0d6', 4, 0x1358),
Register('spr0d7', 4, 0x135c),
Register('spr0d8', 4, 0x1360),
Register('spr0d9', 4, 0x1364),
Register('spr0da', 4, 0x1368),
Register('spr0db', 4, 0x136c),
Register('spr0dc', 4, 0x1370),
Register('spr0dd', 4, 0x1374),
Register('spr0de', 4, 0x1378),
Register('spr0df', 4, 0x137c),
Register('spr0e0', 4, 0x1380),
Register('spr0e1', 4, 0x1384),
Register('spr0e2', 4, 0x1388),
Register('spr0e3', 4, 0x138c),
Register('spr0e4', 4, 0x1390),
Register('spr0e5', 4, 0x1394),
Register('spr0e6', 4, 0x1398),
Register('spr0e7', 4, 0x139c),
Register('spr0e8', 4, 0x13a0),
Register('spr0e9', 4, 0x13a4),
Register('spr0ea', 4, 0x13a8),
Register('spr0eb', 4, 0x13ac),
Register('spr0ec', 4, 0x13b0),
Register('spr0ed', 4, 0x13b4),
Register('spr0ee', 4, 0x13b8),
Register('spr0ef', 4, 0x13bc),
Register('spr0f0', 4, 0x13c0),
Register('spr0f1', 4, 0x13c4),
Register('spr0f2', 4, 0x13c8),
Register('spr0f3', 4, 0x13cc),
Register('spr0f4', 4, 0x13d0),
Register('spr0f5', 4, 0x13d4),
Register('spr0f6', 4, 0x13d8),
Register('spr0f7', 4, 0x13dc),
Register('spr0f8', 4, 0x13e0),
Register('spr0f9', 4, 0x13e4),
Register('spr0fa', 4, 0x13e8),
Register('spr0fb', 4, 0x13ec),
Register('spr0fc', 4, 0x13f0),
Register('spr0fd', 4, 0x13f4),
Register('spr0fe', 4, 0x13f8),
Register('spr0ff', 4, 0x13fc),
Register('spr100', 4, 0x1400),
Register('spr101', 4, 0x1404),
Register('spr102', 4, 0x1408),
Register('spr103', 4, 0x140c),
Register('spr104', 4, 0x1410),
Register('spr105', 4, 0x1414),
Register('spr106', 4, 0x1418),
Register('spr107', 4, 0x141c),
Register('spr108', 4, 0x1420),
Register('spr109', 4, 0x1424),
Register('spr10a', 4, 0x1428),
Register('spr10b', 4, 0x142c),
Register('tblr', 4, 0x1430),
Register('tbur', 4, 0x1434),
Register('spr10e', 4, 0x1438),
Register('spr10f', 4, 0x143c),
Register('spr110', 4, 0x1440),
Register('spr111', 4, 0x1444),
Register('spr112', 4, 0x1448),
Register('spr113', 4, 0x144c),
Register('spr114', 4, 0x1450),
Register('spr115', 4, 0x1454),
Register('spr116', 4, 0x1458),
Register('spr117', 4, 0x145c),
Register('spr118', 4, 0x1460),
Register('spr119', 4, 0x1464),
Register('spr11a', 4, 0x1468),
Register('spr11b', 4, 0x146c),
Register('tblw', 4, 0x1470),
Register('tbuw', 4, 0x1474),
Register('spr11e', 4, 0x1478),
Register('spr11f', 4, 0x147c),
Register('spr120', 4, 0x1480),
Register('spr121', 4, 0x1484),
Register('spr122', 4, 0x1488),
Register('spr123', 4, 0x148c),
Register('spr124', 4, 0x1490),
Register('spr125', 4, 0x1494),
Register('spr126', 4, 0x1498),
Register('spr127', 4, 0x149c),
Register('spr128', 4, 0x14a0),
Register('spr129', 4, 0x14a4),
Register('spr12a', 4, 0x14a8),
Register('spr12b', 4, 0x14ac),
Register('spr12c', 4, 0x14b0),
Register('spr12d', 4, 0x14b4),
Register('spr12e', 4, 0x14b8),
Register('spr12f', 4, 0x14bc),
Register('spr130', 4, 0x14c0),
Register('spr131', 4, 0x14c4),
Register('spr132', 4, 0x14c8),
Register('spr133', 4, 0x14cc),
Register('spr134', 4, 0x14d0),
Register('spr135', 4, 0x14d4),
Register('spr136', 4, 0x14d8),
Register('spr137', 4, 0x14dc),
Register('spr138', 4, 0x14e0),
Register('spr139', 4, 0x14e4),
Register('spr13a', 4, 0x14e8),
Register('spr13b', 4, 0x14ec),
Register('spr13c', 4, 0x14f0),
Register('spr13d', 4, 0x14f4),
Register('spr13e', 4, 0x14f8),
Register('spr13f', 4, 0x14fc),
Register('spr140', 4, 0x1500),
Register('spr141', 4, 0x1504),
Register('spr142', 4, 0x1508),
Register('spr143', 4, 0x150c),
Register('spr144', 4, 0x1510),
Register('spr145', 4, 0x1514),
Register('spr146', 4, 0x1518),
Register('spr147', 4, 0x151c),
Register('spr148', 4, 0x1520),
Register('spr149', 4, 0x1524),
Register('spr14a', 4, 0x1528),
Register('spr14b', 4, 0x152c),
Register('spr14c', 4, 0x1530),
Register('spr14d', 4, 0x1534),
Register('spr14e', 4, 0x1538),
Register('spr14f', 4, 0x153c),
Register('spr150', 4, 0x1540),
Register('spr151', 4, 0x1544),
Register('spr152', 4, 0x1548),
Register('spr153', 4, 0x154c),
Register('spr154', 4, 0x1550),
Register('spr155', 4, 0x1554),
Register('spr156', 4, 0x1558),
Register('spr157', 4, 0x155c),
Register('spr158', 4, 0x1560),
Register('spr159', 4, 0x1564),
Register('spr15a', 4, 0x1568),
Register('spr15b', 4, 0x156c),
Register('spr15c', 4, 0x1570),
Register('spr15d', 4, 0x1574),
Register('spr15e', 4, 0x1578),
Register('spr15f', 4, 0x157c),
Register('spr160', 4, 0x1580),
Register('spr161', 4, 0x1584),
Register('spr162', 4, 0x1588),
Register('spr163', 4, 0x158c),
Register('spr164', 4, 0x1590),
Register('spr165', 4, 0x1594),
Register('spr166', 4, 0x1598),
Register('spr167', 4, 0x159c),
Register('spr168', 4, 0x15a0),
Register('spr169', 4, 0x15a4),
Register('spr16a', 4, 0x15a8),
Register('spr16b', 4, 0x15ac),
Register('spr16c', 4, 0x15b0),
Register('spr16d', 4, 0x15b4),
Register('spr16e', 4, 0x15b8),
Register('spr16f', 4, 0x15bc),
Register('spr170', 4, 0x15c0),
Register('spr171', 4, 0x15c4),
Register('spr172', 4, 0x15c8),
Register('spr173', 4, 0x15cc),
Register('spr174', 4, 0x15d0),
Register('spr175', 4, 0x15d4),
Register('spr176', 4, 0x15d8),
Register('spr177', 4, 0x15dc),
Register('spr178', 4, 0x15e0),
Register('spr179', 4, 0x15e4),
Register('spr17a', 4, 0x15e8),
Register('spr17b', 4, 0x15ec),
Register('spr17c', 4, 0x15f0),
Register('spr17d', 4, 0x15f4),
Register('spr17e', 4, 0x15f8),
Register('spr17f', 4, 0x15fc),
Register('spr180', 4, 0x1600),
Register('spr181', 4, 0x1604),
Register('spr182', 4, 0x1608),
Register('spr183', 4, 0x160c),
Register('spr184', 4, 0x1610),
Register('spr185', 4, 0x1614),
Register('spr186', 4, 0x1618),
Register('spr187', 4, 0x161c),
Register('spr188', 4, 0x1620),
Register('spr189', 4, 0x1624),
Register('spr18a', 4, 0x1628),
Register('spr18b', 4, 0x162c),
Register('spr18c', 4, 0x1630),
Register('spr18d', 4, 0x1634),
Register('spr18e', 4, 0x1638),
Register('spr18f', 4, 0x163c),
Register('spr190', 4, 0x1640),
Register('spr191', 4, 0x1644),
Register('spr192', 4, 0x1648),
Register('spr193', 4, 0x164c),
Register('spr194', 4, 0x1650),
Register('spr195', 4, 0x1654),
Register('spr196', 4, 0x1658),
Register('spr197', 4, 0x165c),
Register('spr198', 4, 0x1660),
Register('spr199', 4, 0x1664),
Register('spr19a', 4, 0x1668),
Register('spr19b', 4, 0x166c),
Register('spr19c', 4, 0x1670),
Register('spr19d', 4, 0x1674),
Register('spr19e', 4, 0x1678),
Register('spr19f', 4, 0x167c),
Register('spr1a0', 4, 0x1680),
Register('spr1a1', 4, 0x1684),
Register('spr1a2', 4, 0x1688),
Register('spr1a3', 4, 0x168c),
Register('spr1a4', 4, 0x1690),
Register('spr1a5', 4, 0x1694),
Register('spr1a6', 4, 0x1698),
Register('spr1a7', 4, 0x169c),
Register('spr1a8', 4, 0x16a0),
Register('spr1a9', 4, 0x16a4),
Register('spr1aa', 4, 0x16a8),
Register('spr1ab', 4, 0x16ac),
Register('spr1ac', 4, 0x16b0),
Register('spr1ad', 4, 0x16b4),
Register('spr1ae', 4, 0x16b8),
Register('spr1af', 4, 0x16bc),
Register('spr1b0', 4, 0x16c0),
Register('spr1b1', 4, 0x16c4),
Register('spr1b2', 4, 0x16c8),
Register('spr1b3', 4, 0x16cc),
Register('spr1b4', 4, 0x16d0),
Register('spr1b5', 4, 0x16d4),
Register('spr1b6', 4, 0x16d8),
Register('spr1b7', 4, 0x16dc),
Register('spr1b8', 4, 0x16e0),
Register('spr1b9', 4, 0x16e4),
Register('spr1ba', 4, 0x16e8),
Register('spr1bb', 4, 0x16ec),
Register('spr1bc', 4, 0x16f0),
Register('spr1bd', 4, 0x16f4),
Register('spr1be', 4, 0x16f8),
Register('spr1bf', 4, 0x16fc),
Register('spr1c0', 4, 0x1700),
Register('spr1c1', 4, 0x1704),
Register('spr1c2', 4, 0x1708),
Register('spr1c3', 4, 0x170c),
Register('spr1c4', 4, 0x1710),
Register('spr1c5', 4, 0x1714),
Register('spr1c6', 4, 0x1718),
Register('spr1c7', 4, 0x171c),
Register('spr1c8', 4, 0x1720),
Register('spr1c9', 4, 0x1724),
Register('spr1ca', 4, 0x1728),
Register('spr1cb', 4, 0x172c),
Register('spr1cc', 4, 0x1730),
Register('spr1cd', 4, 0x1734),
Register('spr1ce', 4, 0x1738),
Register('spr1cf', 4, 0x173c),
Register('spr1d0', 4, 0x1740),
Register('spr1d1', 4, 0x1744),
Register('spr1d2', 4, 0x1748),
Register('spr1d3', 4, 0x174c),
Register('spr1d4', 4, 0x1750),
Register('spr1d5', 4, 0x1754),
Register('spr1d6', 4, 0x1758),
Register('spr1d7', 4, 0x175c),
Register('spr1d8', 4, 0x1760),
Register('spr1d9', 4, 0x1764),
Register('spr1da', 4, 0x1768),
Register('spr1db', 4, 0x176c),
Register('spr1dc', 4, 0x1770),
Register('spr1dd', 4, 0x1774),
Register('spr1de', 4, 0x1778),
Register('spr1df', 4, 0x177c),
Register('spr1e0', 4, 0x1780),
Register('spr1e1', 4, 0x1784),
Register('spr1e2', 4, 0x1788),
Register('spr1e3', 4, 0x178c),
Register('spr1e4', 4, 0x1790),
Register('spr1e5', 4, 0x1794),
Register('spr1e6', 4, 0x1798),
Register('spr1e7', 4, 0x179c),
Register('spr1e8', 4, 0x17a0),
Register('spr1e9', 4, 0x17a4),
Register('spr1ea', 4, 0x17a8),
Register('spr1eb', 4, 0x17ac),
Register('spr1ec', 4, 0x17b0),
Register('spr1ed', 4, 0x17b4),
Register('spr1ee', 4, 0x17b8),
Register('spr1ef', 4, 0x17bc),
Register('spr1f0', 4, 0x17c0),
Register('spr1f1', 4, 0x17c4),
Register('spr1f2', 4, 0x17c8),
Register('spr1f3', 4, 0x17cc),
Register('spr1f4', 4, 0x17d0),
Register('spr1f5', 4, 0x17d4),
Register('spr1f6', 4, 0x17d8),
Register('spr1f7', 4, 0x17dc),
Register('spr1f8', 4, 0x17e0),
Register('spr1f9', 4, 0x17e4),
Register('spr1fa', 4, 0x17e8),
Register('spr1fb', 4, 0x17ec),
Register('spr1fc', 4, 0x17f0),
Register('spr1fd', 4, 0x17f4),
Register('spr1fe', 4, 0x17f8),
Register('spr1ff', 4, 0x17fc),
Register('spr200', 4, 0x1800),
Register('spr201', 4, 0x1804),
Register('spr202', 4, 0x1808),
Register('spr203', 4, 0x180c),
Register('spr204', 4, 0x1810),
Register('spr205', 4, 0x1814),
Register('spr206', 4, 0x1818),
Register('spr207', 4, 0x181c),
Register('spr208', 4, 0x1820),
Register('spr209', 4, 0x1824),
Register('spr20a', 4, 0x1828),
Register('spr20b', 4, 0x182c),
Register('spr20c', 4, 0x1830),
Register('spr20d', 4, 0x1834),
Register('spr20e', 4, 0x1838),
Register('spr20f', 4, 0x183c),
Register('spr210', 4, 0x1840),
Register('spr211', 4, 0x1844),
Register('spr212', 4, 0x1848),
Register('spr213', 4, 0x184c),
Register('spr214', 4, 0x1850),
Register('spr215', 4, 0x1854),
Register('spr216', 4, 0x1858),
Register('spr217', 4, 0x185c),
Register('spr218', 4, 0x1860),
Register('spr219', 4, 0x1864),
Register('spr21a', 4, 0x1868),
Register('spr21b', 4, 0x186c),
Register('spr21c', 4, 0x1870),
Register('spr21d', 4, 0x1874),
Register('spr21e', 4, 0x1878),
Register('spr21f', 4, 0x187c),
Register('spr220', 4, 0x1880),
Register('spr221', 4, 0x1884),
Register('spr222', 4, 0x1888),
Register('spr223', 4, 0x188c),
Register('spr224', 4, 0x1890),
Register('spr225', 4, 0x1894),
Register('spr226', 4, 0x1898),
Register('spr227', 4, 0x189c),
Register('spr228', 4, 0x18a0),
Register('spr229', 4, 0x18a4),
Register('spr22a', 4, 0x18a8),
Register('spr22b', 4, 0x18ac),
Register('spr22c', 4, 0x18b0),
Register('spr22d', 4, 0x18b4),
Register('spr22e', 4, 0x18b8),
Register('spr22f', 4, 0x18bc),
Register('spr230', 4, 0x18c0),
Register('spr231', 4, 0x18c4),
Register('spr232', 4, 0x18c8),
Register('spr233', 4, 0x18cc),
Register('spr234', 4, 0x18d0),
Register('spr235', 4, 0x18d4),
Register('spr236', 4, 0x18d8),
Register('spr237', 4, 0x18dc),
Register('spr238', 4, 0x18e0),
Register('spr239', 4, 0x18e4),
Register('spr23a', 4, 0x18e8),
Register('spr23b', 4, 0x18ec),
Register('spr23c', 4, 0x18f0),
Register('spr23d', 4, 0x18f4),
Register('spr23e', 4, 0x18f8),
Register('spr23f', 4, 0x18fc),
Register('spr240', 4, 0x1900),
Register('spr241', 4, 0x1904),
Register('spr242', 4, 0x1908),
Register('spr243', 4, 0x190c),
Register('spr244', 4, 0x1910),
Register('spr245', 4, 0x1914),
Register('spr246', 4, 0x1918),
Register('spr247', 4, 0x191c),
Register('spr248', 4, 0x1920),
Register('spr249', 4, 0x1924),
Register('spr24a', 4, 0x1928),
Register('spr24b', 4, 0x192c),
Register('spr24c', 4, 0x1930),
Register('spr24d', 4, 0x1934),
Register('spr24e', 4, 0x1938),
Register('spr24f', 4, 0x193c),
Register('spr250', 4, 0x1940),
Register('spr251', 4, 0x1944),
Register('spr252', 4, 0x1948),
Register('spr253', 4, 0x194c),
Register('spr254', 4, 0x1950),
Register('spr255', 4, 0x1954),
Register('spr256', 4, 0x1958),
Register('spr257', 4, 0x195c),
Register('spr258', 4, 0x1960),
Register('spr259', 4, 0x1964),
Register('spr25a', 4, 0x1968),
Register('spr25b', 4, 0x196c),
Register('spr25c', 4, 0x1970),
Register('spr25d', 4, 0x1974),
Register('spr25e', 4, 0x1978),
Register('spr25f', 4, 0x197c),
Register('spr260', 4, 0x1980),
Register('spr261', 4, 0x1984),
Register('spr262', 4, 0x1988),
Register('spr263', 4, 0x198c),
Register('spr264', 4, 0x1990),
Register('spr265', 4, 0x1994),
Register('spr266', 4, 0x1998),
Register('spr267', 4, 0x199c),
Register('spr268', 4, 0x19a0),
Register('spr269', 4, 0x19a4),
Register('spr26a', 4, 0x19a8),
Register('spr26b', 4, 0x19ac),
Register('spr26c', 4, 0x19b0),
Register('spr26d', 4, 0x19b4),
Register('spr26e', 4, 0x19b8),
Register('spr26f', 4, 0x19bc),
Register('spr270', 4, 0x19c0),
Register('spr271', 4, 0x19c4),
Register('spr272', 4, 0x19c8),
Register('spr273', 4, 0x19cc),
Register('spr274', 4, 0x19d0),
Register('spr275', 4, 0x19d4),
Register('spr276', 4, 0x19d8),
Register('spr277', 4, 0x19dc),
Register('spr278', 4, 0x19e0),
Register('spr279', 4, 0x19e4),
Register('spr27a', 4, 0x19e8),
Register('spr27b', 4, 0x19ec),
Register('spr27c', 4, 0x19f0),
Register('spr27d', 4, 0x19f4),
Register('spr27e', 4, 0x19f8),
Register('spr27f', 4, 0x19fc),
Register('spr280', 4, 0x1a00),
Register('spr281', 4, 0x1a04),
Register('spr282', 4, 0x1a08),
Register('spr283', 4, 0x1a0c),
Register('spr284', 4, 0x1a10),
Register('spr285', 4, 0x1a14),
Register('spr286', 4, 0x1a18),
Register('spr287', 4, 0x1a1c),
Register('spr288', 4, 0x1a20),
Register('spr289', 4, 0x1a24),
Register('spr28a', 4, 0x1a28),
Register('spr28b', 4, 0x1a2c),
Register('spr28c', 4, 0x1a30),
Register('spr28d', 4, 0x1a34),
Register('spr28e', 4, 0x1a38),
Register('spr28f', 4, 0x1a3c),
Register('spr290', 4, 0x1a40),
Register('spr291', 4, 0x1a44),
Register('spr292', 4, 0x1a48),
Register('spr293', 4, 0x1a4c),
Register('spr294', 4, 0x1a50),
Register('spr295', 4, 0x1a54),
Register('spr296', 4, 0x1a58),
Register('spr297', 4, 0x1a5c),
Register('spr298', 4, 0x1a60),
Register('spr299', 4, 0x1a64),
Register('spr29a', 4, 0x1a68),
Register('spr29b', 4, 0x1a6c),
Register('spr29c', 4, 0x1a70),
Register('spr29d', 4, 0x1a74),
Register('spr29e', 4, 0x1a78),
Register('spr29f', 4, 0x1a7c),
Register('spr2a0', 4, 0x1a80),
Register('spr2a1', 4, 0x1a84),
Register('spr2a2', 4, 0x1a88),
Register('spr2a3', 4, 0x1a8c),
Register('spr2a4', 4, 0x1a90),
Register('spr2a5', 4, 0x1a94),
Register('spr2a6', 4, 0x1a98),
Register('spr2a7', 4, 0x1a9c),
Register('spr2a8', 4, 0x1aa0),
Register('spr2a9', 4, 0x1aa4),
Register('spr2aa', 4, 0x1aa8),
Register('spr2ab', 4, 0x1aac),
Register('spr2ac', 4, 0x1ab0),
Register('spr2ad', 4, 0x1ab4),
Register('spr2ae', 4, 0x1ab8),
Register('spr2af', 4, 0x1abc),
Register('spr2b0', 4, 0x1ac0),
Register('spr2b1', 4, 0x1ac4),
Register('spr2b2', 4, 0x1ac8),
Register('spr2b3', 4, 0x1acc),
Register('spr2b4', 4, 0x1ad0),
Register('spr2b5', 4, 0x1ad4),
Register('spr2b6', 4, 0x1ad8),
Register('spr2b7', 4, 0x1adc),
Register('spr2b8', 4, 0x1ae0),
Register('spr2b9', 4, 0x1ae4),
Register('spr2ba', 4, 0x1ae8),
Register('spr2bb', 4, 0x1aec),
Register('spr2bc', 4, 0x1af0),
Register('spr2bd', 4, 0x1af4),
Register('spr2be', 4, 0x1af8),
Register('spr2bf', 4, 0x1afc),
Register('spr2c0', 4, 0x1b00),
Register('spr2c1', 4, 0x1b04),
Register('spr2c2', 4, 0x1b08),
Register('spr2c3', 4, 0x1b0c),
Register('spr2c4', 4, 0x1b10),
Register('spr2c5', 4, 0x1b14),
Register('spr2c6', 4, 0x1b18),
Register('spr2c7', 4, 0x1b1c),
Register('spr2c8', 4, 0x1b20),
Register('spr2c9', 4, 0x1b24),
Register('spr2ca', 4, 0x1b28),
Register('spr2cb', 4, 0x1b2c),
Register('spr2cc', 4, 0x1b30),
Register('spr2cd', 4, 0x1b34),
Register('spr2ce', 4, 0x1b38),
Register('spr2cf', 4, 0x1b3c),
Register('spr2d0', 4, 0x1b40),
Register('spr2d1', 4, 0x1b44),
Register('spr2d2', 4, 0x1b48),
Register('spr2d3', 4, 0x1b4c),
Register('spr2d4', 4, 0x1b50),
Register('spr2d5', 4, 0x1b54),
Register('spr2d6', 4, 0x1b58),
Register('spr2d7', 4, 0x1b5c),
Register('spr2d8', 4, 0x1b60),
Register('spr2d9', 4, 0x1b64),
Register('spr2da', 4, 0x1b68),
Register('spr2db', 4, 0x1b6c),
Register('spr2dc', 4, 0x1b70),
Register('spr2dd', 4, 0x1b74),
Register('spr2de', 4, 0x1b78),
Register('spr2df', 4, 0x1b7c),
Register('spr2e0', 4, 0x1b80),
Register('spr2e1', 4, 0x1b84),
Register('spr2e2', 4, 0x1b88),
Register('spr2e3', 4, 0x1b8c),
Register('spr2e4', 4, 0x1b90),
Register('spr2e5', 4, 0x1b94),
Register('spr2e6', 4, 0x1b98),
Register('spr2e7', 4, 0x1b9c),
Register('spr2e8', 4, 0x1ba0),
Register('spr2e9', 4, 0x1ba4),
Register('spr2ea', 4, 0x1ba8),
Register('spr2eb', 4, 0x1bac),
Register('spr2ec', 4, 0x1bb0),
Register('spr2ed', 4, 0x1bb4),
Register('spr2ee', 4, 0x1bb8),
Register('spr2ef', 4, 0x1bbc),
Register('spr2f0', 4, 0x1bc0),
Register('spr2f1', 4, 0x1bc4),
Register('spr2f2', 4, 0x1bc8),
Register('spr2f3', 4, 0x1bcc),
Register('spr2f4', 4, 0x1bd0),
Register('spr2f5', 4, 0x1bd4),
Register('spr2f6', 4, 0x1bd8),
Register('spr2f7', 4, 0x1bdc),
Register('spr2f8', 4, 0x1be0),
Register('spr2f9', 4, 0x1be4),
Register('spr2fa', 4, 0x1be8),
Register('spr2fb', 4, 0x1bec),
Register('spr2fc', 4, 0x1bf0),
Register('spr2fd', 4, 0x1bf4),
Register('spr2fe', 4, 0x1bf8),
Register('spr2ff', 4, 0x1bfc),
Register('spr300', 4, 0x1c00),
Register('spr301', 4, 0x1c04),
Register('spr302', 4, 0x1c08),
Register('spr303', 4, 0x1c0c),
Register('spr304', 4, 0x1c10),
Register('spr305', 4, 0x1c14),
Register('spr306', 4, 0x1c18),
Register('spr307', 4, 0x1c1c),
Register('spr308', 4, 0x1c20),
Register('spr309', 4, 0x1c24),
Register('spr30a', 4, 0x1c28),
Register('spr30b', 4, 0x1c2c),
Register('spr30c', 4, 0x1c30),
Register('spr30d', 4, 0x1c34),
Register('spr30e', 4, 0x1c38),
Register('spr30f', 4, 0x1c3c),
Register('spr310', 4, 0x1c40),
Register('spr311', 4, 0x1c44),
Register('spr312', 4, 0x1c48),
Register('spr313', 4, 0x1c4c),
Register('spr314', 4, 0x1c50),
Register('spr315', 4, 0x1c54),
Register('spr316', 4, 0x1c58),
Register('spr317', 4, 0x1c5c),
Register('spr318', 4, 0x1c60),
Register('spr319', 4, 0x1c64),
Register('spr31a', 4, 0x1c68),
Register('spr31b', 4, 0x1c6c),
Register('spr31c', 4, 0x1c70),
Register('spr31d', 4, 0x1c74),
Register('spr31e', 4, 0x1c78),
Register('spr31f', 4, 0x1c7c),
Register('spr320', 4, 0x1c80),
Register('spr321', 4, 0x1c84),
Register('spr322', 4, 0x1c88),
Register('spr323', 4, 0x1c8c),
Register('spr324', 4, 0x1c90),
Register('spr325', 4, 0x1c94),
Register('spr326', 4, 0x1c98),
Register('spr327', 4, 0x1c9c),
Register('spr328', 4, 0x1ca0),
Register('spr329', 4, 0x1ca4),
Register('spr32a', 4, 0x1ca8),
Register('spr32b', 4, 0x1cac),
Register('spr32c', 4, 0x1cb0),
Register('spr32d', 4, 0x1cb4),
Register('spr32e', 4, 0x1cb8),
Register('tar', 4, 0x1cbc),
Register('spr330', 4, 0x1cc0),
Register('spr331', 4, 0x1cc4),
Register('spr332', 4, 0x1cc8),
Register('spr333', 4, 0x1ccc),
Register('spr334', 4, 0x1cd0),
Register('spr335', 4, 0x1cd4),
Register('spr336', 4, 0x1cd8),
Register('spr337', 4, 0x1cdc),
Register('spr338', 4, 0x1ce0),
Register('spr339', 4, 0x1ce4),
Register('spr33a', 4, 0x1ce8),
Register('spr33b', 4, 0x1cec),
Register('spr33c', 4, 0x1cf0),
Register('spr33d', 4, 0x1cf4),
Register('spr33e', 4, 0x1cf8),
Register('spr33f', 4, 0x1cfc),
Register('spr340', 4, 0x1d00),
Register('spr341', 4, 0x1d04),
Register('spr342', 4, 0x1d08),
Register('spr343', 4, 0x1d0c),
Register('spr344', 4, 0x1d10),
Register('spr345', 4, 0x1d14),
Register('spr346', 4, 0x1d18),
Register('spr347', 4, 0x1d1c),
Register('spr348', 4, 0x1d20),
Register('spr349', 4, 0x1d24),
Register('spr34a', 4, 0x1d28),
Register('spr34b', 4, 0x1d2c),
Register('spr34c', 4, 0x1d30),
Register('spr34d', 4, 0x1d34),
Register('spr34e', 4, 0x1d38),
Register('spr34f', 4, 0x1d3c),
Register('spr350', 4, 0x1d40),
Register('spr351', 4, 0x1d44),
Register('spr352', 4, 0x1d48),
Register('spr353', 4, 0x1d4c),
Register('spr354', 4, 0x1d50),
Register('spr355', 4, 0x1d54),
Register('spr356', 4, 0x1d58),
Register('spr357', 4, 0x1d5c),
Register('spr358', 4, 0x1d60),
Register('spr359', 4, 0x1d64),
Register('spr35a', 4, 0x1d68),
Register('spr35b', 4, 0x1d6c),
Register('spr35c', 4, 0x1d70),
Register('spr35d', 4, 0x1d74),
Register('spr35e', 4, 0x1d78),
Register('spr35f', 4, 0x1d7c),
Register('spr360', 4, 0x1d80),
Register('spr361', 4, 0x1d84),
Register('spr362', 4, 0x1d88),
Register('spr363', 4, 0x1d8c),
Register('spr364', 4, 0x1d90),
Register('spr365', 4, 0x1d94),
Register('spr366', 4, 0x1d98),
Register('spr367', 4, 0x1d9c),
Register('spr368', 4, 0x1da0),
Register('spr369', 4, 0x1da4),
Register('spr36a', 4, 0x1da8),
Register('spr36b', 4, 0x1dac),
Register('spr36c', 4, 0x1db0),
Register('spr36d', 4, 0x1db4),
Register('spr36e', 4, 0x1db8),
Register('spr36f', 4, 0x1dbc),
Register('spr370', 4, 0x1dc0),
Register('spr371', 4, 0x1dc4),
Register('spr372', 4, 0x1dc8),
Register('spr373', 4, 0x1dcc),
Register('spr374', 4, 0x1dd0),
Register('spr375', 4, 0x1dd4),
Register('spr376', 4, 0x1dd8),
Register('spr377', 4, 0x1ddc),
Register('spr378', 4, 0x1de0),
Register('spr379', 4, 0x1de4),
Register('spr37a', 4, 0x1de8),
Register('spr37b', 4, 0x1dec),
Register('spr37c', 4, 0x1df0),
Register('spr37d', 4, 0x1df4),
Register('spr37e', 4, 0x1df8),
Register('spr37f', 4, 0x1dfc),
Register('spr380', 4, 0x1e00),
Register('spr381', 4, 0x1e04),
Register('spr382', 4, 0x1e08),
Register('spr383', 4, 0x1e0c),
Register('spr384', 4, 0x1e10),
Register('spr385', 4, 0x1e14),
Register('spr386', 4, 0x1e18),
Register('spr387', 4, 0x1e1c),
Register('spr388', 4, 0x1e20),
Register('spr389', 4, 0x1e24),
Register('spr38a', 4, 0x1e28),
Register('spr38b', 4, 0x1e2c),
Register('spr38c', 4, 0x1e30),
Register('spr38d', 4, 0x1e34),
Register('spr38e', 4, 0x1e38),
Register('spr38f', 4, 0x1e3c),
Register('spr390', 4, 0x1e40),
Register('spr391', 4, 0x1e44),
Register('spr392', 4, 0x1e48),
Register('spr393', 4, 0x1e4c),
Register('spr394', 4, 0x1e50),
Register('spr395', 4, 0x1e54),
Register('spr396', 4, 0x1e58),
Register('spr397', 4, 0x1e5c),
Register('spr398', 4, 0x1e60),
Register('spr399', 4, 0x1e64),
Register('spr39a', 4, 0x1e68),
Register('spr39b', 4, 0x1e6c),
Register('spr39c', 4, 0x1e70),
Register('spr39d', 4, 0x1e74),
Register('spr39e', 4, 0x1e78),
Register('spr39f', 4, 0x1e7c),
Register('spr3a0', 4, 0x1e80),
Register('spr3a1', 4, 0x1e84),
Register('spr3a2', 4, 0x1e88),
Register('spr3a3', 4, 0x1e8c),
Register('spr3a4', 4, 0x1e90),
Register('spr3a5', 4, 0x1e94),
Register('spr3a6', 4, 0x1e98),
Register('spr3a7', 4, 0x1e9c),
Register('spr3a8', 4, 0x1ea0),
Register('spr3a9', 4, 0x1ea4),
Register('spr3aa', 4, 0x1ea8),
Register('spr3ab', 4, 0x1eac),
Register('spr3ac', 4, 0x1eb0),
Register('spr3ad', 4, 0x1eb4),
Register('spr3ae', 4, 0x1eb8),
Register('spr3af', 4, 0x1ebc),
Register('spr3b0', 4, 0x1ec0),
Register('spr3b1', 4, 0x1ec4),
Register('spr3b2', 4, 0x1ec8),
Register('spr3b3', 4, 0x1ecc),
Register('spr3b4', 4, 0x1ed0),
Register('spr3b5', 4, 0x1ed4),
Register('spr3b6', 4, 0x1ed8),
Register('spr3b7', 4, 0x1edc),
Register('spr3b8', 4, 0x1ee0),
Register('spr3b9', 4, 0x1ee4),
Register('spr3ba', 4, 0x1ee8),
Register('spr3bb', 4, 0x1eec),
Register('spr3bc', 4, 0x1ef0),
Register('spr3bd', 4, 0x1ef4),
Register('spr3be', 4, 0x1ef8),
Register('spr3bf', 4, 0x1efc),
Register('spr3c0', 4, 0x1f00),
Register('spr3c1', 4, 0x1f04),
Register('spr3c2', 4, 0x1f08),
Register('spr3c3', 4, 0x1f0c),
Register('spr3c4', 4, 0x1f10),
Register('spr3c5', 4, 0x1f14),
Register('spr3c6', 4, 0x1f18),
Register('spr3c7', 4, 0x1f1c),
Register('spr3c8', 4, 0x1f20),
Register('spr3c9', 4, 0x1f24),
Register('spr3ca', 4, 0x1f28),
Register('spr3cb', 4, 0x1f2c),
Register('spr3cc', 4, 0x1f30),
Register('spr3cd', 4, 0x1f34),
Register('spr3ce', 4, 0x1f38),
Register('spr3cf', 4, 0x1f3c),
Register('spr3d0', 4, 0x1f40),
Register('spr3d1', 4, 0x1f44),
Register('spr3d2', 4, 0x1f48),
Register('spr3d3', 4, 0x1f4c),
Register('spr3d4', 4, 0x1f50),
Register('spr3d5', 4, 0x1f54),
Register('spr3d6', 4, 0x1f58),
Register('spr3d7', 4, 0x1f5c),
Register('spr3d8', 4, 0x1f60),
Register('spr3d9', 4, 0x1f64),
Register('spr3da', 4, 0x1f68),
Register('spr3db', 4, 0x1f6c),
Register('spr3dc', 4, 0x1f70),
Register('spr3dd', 4, 0x1f74),
Register('spr3de', 4, 0x1f78),
Register('spr3df', 4, 0x1f7c),
Register('spr3e0', 4, 0x1f80),
Register('spr3e1', 4, 0x1f84),
Register('spr3e2', 4, 0x1f88),
Register('spr3e3', 4, 0x1f8c),
Register('spr3e4', 4, 0x1f90),
Register('spr3e5', 4, 0x1f94),
Register('spr3e6', 4, 0x1f98),
Register('spr3e7', 4, 0x1f9c),
Register('spr3e8', 4, 0x1fa0),
Register('spr3e9', 4, 0x1fa4),
Register('spr3ea', 4, 0x1fa8),
Register('spr3eb', 4, 0x1fac),
Register('spr3ec', 4, 0x1fb0),
Register('spr3ed', 4, 0x1fb4),
Register('spr3ee', 4, 0x1fb8),
Register('spr3ef', 4, 0x1fbc),
Register('spr3f0', 4, 0x1fc0),
Register('spr3f1', 4, 0x1fc4),
Register('spr3f2', 4, 0x1fc8),
Register('spr3f3', 4, 0x1fcc),
Register('spr3f4', 4, 0x1fd0),
Register('spr3f5', 4, 0x1fd4),
Register('spr3f6', 4, 0x1fd8),
Register('spr3f7', 4, 0x1fdc),
Register('spr3f8', 4, 0x1fe0),
Register('spr3f9', 4, 0x1fe4),
Register('spr3fa', 4, 0x1fe8),
Register('spr3fb', 4, 0x1fec),
Register('spr3fc', 4, 0x1ff0),
Register('spr3fd', 4, 0x1ff4),
Register('spr3fe', 4, 0x1ff8),
Register('spr3ff', 4, 0x1ffc),
Register('vs0', 16, 0x4000),
Register('f0', 8, 0x4008),
Register('vs1', 16, 0x4010),
Register('f1', 8, 0x4018),
Register('vs2', 16, 0x4020),
Register('f2', 8, 0x4028),
Register('vs3', 16, 0x4030),
Register('f3', 8, 0x4038),
Register('vs4', 16, 0x4040),
Register('f4', 8, 0x4048),
Register('vs5', 16, 0x4050),
Register('f5', 8, 0x4058),
Register('vs6', 16, 0x4060),
Register('f6', 8, 0x4068),
Register('vs7', 16, 0x4070),
Register('f7', 8, 0x4078),
Register('vs8', 16, 0x4080),
Register('f8', 8, 0x4088),
Register('vs9', 16, 0x4090),
Register('f9', 8, 0x4098),
Register('vs10', 16, 0x40a0),
Register('f10', 8, 0x40a8),
Register('vs11', 16, 0x40b0),
Register('f11', 8, 0x40b8),
Register('vs12', 16, 0x40c0),
Register('f12', 8, 0x40c8),
Register('vs13', 16, 0x40d0),
Register('f13', 8, 0x40d8),
Register('vs14', 16, 0x40e0),
Register('f14', 8, 0x40e8),
Register('vs15', 16, 0x40f0),
Register('f15', 8, 0x40f8),
Register('vs16', 16, 0x4100),
Register('f16', 8, 0x4108),
Register('vs17', 16, 0x4110),
Register('f17', 8, 0x4118),
Register('vs18', 16, 0x4120),
Register('f18', 8, 0x4128),
Register('vs19', 16, 0x4130),
Register('f19', 8, 0x4138),
Register('vs20', 16, 0x4140),
Register('f20', 8, 0x4148),
Register('vs21', 16, 0x4150),
Register('f21', 8, 0x4158),
Register('vs22', 16, 0x4160),
Register('f22', 8, 0x4168),
Register('vs23', 16, 0x4170),
Register('f23', 8, 0x4178),
Register('vs24', 16, 0x4180),
Register('f24', 8, 0x4188),
Register('vs25', 16, 0x4190),
Register('f25', 8, 0x4198),
Register('vs26', 16, 0x41a0),
Register('f26', 8, 0x41a8),
Register('vs27', 16, 0x41b0),
Register('f27', 8, 0x41b8),
Register('vs28', 16, 0x41c0),
Register('f28', 8, 0x41c8),
Register('vs29', 16, 0x41d0),
Register('f29', 8, 0x41d8),
Register('vs30', 16, 0x41e0),
Register('f30', 8, 0x41e8),
Register('vs31', 16, 0x41f0),
Register('f31', 8, 0x41f8),
Register('vs32', 16, 0x4200),
Register('vr0_64_1', 8, 0x4200),
Register('vr0_32_3', 4, 0x4200),
Register('vr0_16_7', 2, 0x4200),
Register('vr0_8_15', 1, 0x4200),
Register('vr0_8_14', 1, 0x4201),
Register('vr0_16_6', 2, 0x4202),
Register('vr0_8_13', 1, 0x4202),
Register('vr0_8_12', 1, 0x4203),
Register('vr0_32_2', 4, 0x4204),
Register('vr0_16_5', 2, 0x4204),
Register('vr0_8_11', 1, 0x4204),
Register('vr0_8_10', 1, 0x4205),
Register('vr0_16_4', 2, 0x4206),
Register('vr0_8_9', 1, 0x4206),
Register('vr0_8_8', 1, 0x4207),
Register('vr0_64_0', 8, 0x4208),
Register('vr0_32_1', 4, 0x4208),
Register('vr0_16_3', 2, 0x4208),
Register('vr0_8_7', 1, 0x4208),
Register('vr0_8_6', 1, 0x4209),
Register('vr0_16_2', 2, 0x420a),
Register('vr0_8_5', 1, 0x420a),
Register('vr0_8_4', 1, 0x420b),
Register('vr0_32_0', 4, 0x420c),
Register('vr0_16_1', 2, 0x420c),
Register('vr0_8_3', 1, 0x420c),
Register('vr0_8_2', 1, 0x420d),
Register('vr0_16_0', 2, 0x420e),
Register('vr0_8_1', 1, 0x420e),
Register('vr0_8_0', 1, 0x420f),
Register('vs33', 16, 0x4210),
Register('vr1_64_1', 8, 0x4210),
Register('vr1_32_3', 4, 0x4210),
Register('vr1_16_7', 2, 0x4210),
Register('vr1_8_15', 1, 0x4210),
Register('vr1_8_14', 1, 0x4211),
Register('vr1_16_6', 2, 0x4212),
Register('vr1_8_13', 1, 0x4212),
Register('vr1_8_12', 1, 0x4213),
Register('vr1_32_2', 4, 0x4214),
Register('vr1_16_5', 2, 0x4214),
Register('vr1_8_11', 1, 0x4214),
Register('vr1_8_10', 1, 0x4215),
Register('vr1_16_4', 2, 0x4216),
Register('vr1_8_9', 1, 0x4216),
Register('vr1_8_8', 1, 0x4217),
Register('vr1_64_0', 8, 0x4218),
Register('vr1_32_1', 4, 0x4218),
Register('vr1_16_3', 2, 0x4218),
Register('vr1_8_7', 1, 0x4218),
Register('vr1_8_6', 1, 0x4219),
Register('vr1_16_2', 2, 0x421a),
Register('vr1_8_5', 1, 0x421a),
Register('vr1_8_4', 1, 0x421b),
Register('vr1_32_0', 4, 0x421c),
Register('vr1_16_1', 2, 0x421c),
Register('vr1_8_3', 1, 0x421c),
Register('vr1_8_2', 1, 0x421d),
Register('vr1_16_0', 2, 0x421e),
Register('vr1_8_1', 1, 0x421e),
Register('vr1_8_0', 1, 0x421f),
Register('vs34', 16, 0x4220),
Register('vr2_64_1', 8, 0x4220),
Register('vr2_32_3', 4, 0x4220),
Register('vr2_16_7', 2, 0x4220),
Register('vr2_8_15', 1, 0x4220),
Register('vr2_8_14', 1, 0x4221),
Register('vr2_16_6', 2, 0x4222),
Register('vr2_8_13', 1, 0x4222),
Register('vr2_8_12', 1, 0x4223),
Register('vr2_32_2', 4, 0x4224),
Register('vr2_16_5', 2, 0x4224),
Register('vr2_8_11', 1, 0x4224),
Register('vr2_8_10', 1, 0x4225),
Register('vr2_16_4', 2, 0x4226),
Register('vr2_8_9', 1, 0x4226),
Register('vr2_8_8', 1, 0x4227),
Register('vr2_64_0', 8, 0x4228),
Register('vr2_32_1', 4, 0x4228),
Register('vr2_16_3', 2, 0x4228),
Register('vr2_8_7', 1, 0x4228),
Register('vr2_8_6', 1, 0x4229),
Register('vr2_16_2', 2, 0x422a),
Register('vr2_8_5', 1, 0x422a),
Register('vr2_8_4', 1, 0x422b),
Register('vr2_32_0', 4, 0x422c),
Register('vr2_16_1', 2, 0x422c),
Register('vr2_8_3', 1, 0x422c),
Register('vr2_8_2', 1, 0x422d),
Register('vr2_16_0', 2, 0x422e),
Register('vr2_8_1', 1, 0x422e),
Register('vr2_8_0', 1, 0x422f),
Register('vs35', 16, 0x4230),
Register('vr3_64_1', 8, 0x4230),
Register('vr3_32_3', 4, 0x4230),
Register('vr3_16_7', 2, 0x4230),
Register('vr3_8_15', 1, 0x4230),
Register('vr3_8_14', 1, 0x4231),
Register('vr3_16_6', 2, 0x4232),
Register('vr3_8_13', 1, 0x4232),
Register('vr3_8_12', 1, 0x4233),
Register('vr3_32_2', 4, 0x4234),
Register('vr3_16_5', 2, 0x4234),
Register('vr3_8_11', 1, 0x4234),
Register('vr3_8_10', 1, 0x4235),
Register('vr3_16_4', 2, 0x4236),
Register('vr3_8_9', 1, 0x4236),
Register('vr3_8_8', 1, 0x4237),
Register('vr3_64_0', 8, 0x4238),
Register('vr3_32_1', 4, 0x4238),
Register('vr3_16_3', 2, 0x4238),
Register('vr3_8_7', 1, 0x4238),
Register('vr3_8_6', 1, 0x4239),
Register('vr3_16_2', 2, 0x423a),
Register('vr3_8_5', 1, 0x423a),
Register('vr3_8_4', 1, 0x423b),
Register('vr3_32_0', 4, 0x423c),
Register('vr3_16_1', 2, 0x423c),
Register('vr3_8_3', 1, 0x423c),
Register('vr3_8_2', 1, 0x423d),
Register('vr3_16_0', 2, 0x423e),
Register('vr3_8_1', 1, 0x423e),
Register('vr3_8_0', 1, 0x423f),
Register('vs36', 16, 0x4240),
Register('vr4_64_1', 8, 0x4240),
Register('vr4_32_3', 4, 0x4240),
Register('vr4_16_7', 2, 0x4240),
Register('vr4_8_15', 1, 0x4240),
Register('vr4_8_14', 1, 0x4241),
Register('vr4_16_6', 2, 0x4242),
Register('vr4_8_13', 1, 0x4242),
Register('vr4_8_12', 1, 0x4243),
Register('vr4_32_2', 4, 0x4244),
Register('vr4_16_5', 2, 0x4244),
Register('vr4_8_11', 1, 0x4244),
Register('vr4_8_10', 1, 0x4245),
Register('vr4_16_4', 2, 0x4246),
Register('vr4_8_9', 1, 0x4246),
Register('vr4_8_8', 1, 0x4247),
Register('vr4_64_0', 8, 0x4248),
Register('vr4_32_1', 4, 0x4248),
Register('vr4_16_3', 2, 0x4248),
Register('vr4_8_7', 1, 0x4248),
Register('vr4_8_6', 1, 0x4249),
Register('vr4_16_2', 2, 0x424a),
Register('vr4_8_5', 1, 0x424a),
Register('vr4_8_4', 1, 0x424b),
Register('vr4_32_0', 4, 0x424c),
Register('vr4_16_1', 2, 0x424c),
Register('vr4_8_3', 1, 0x424c),
Register('vr4_8_2', 1, 0x424d),
Register('vr4_16_0', 2, 0x424e),
Register('vr4_8_1', 1, 0x424e),
Register('vr4_8_0', 1, 0x424f),
Register('vs37', 16, 0x4250),
Register('vr5_64_1', 8, 0x4250),
Register('vr5_32_3', 4, 0x4250),
Register('vr5_16_7', 2, 0x4250),
Register('vr5_8_15', 1, 0x4250),
Register('vr5_8_14', 1, 0x4251),
Register('vr5_16_6', 2, 0x4252),
Register('vr5_8_13', 1, 0x4252),
Register('vr5_8_12', 1, 0x4253),
Register('vr5_32_2', 4, 0x4254),
Register('vr5_16_5', 2, 0x4254),
Register('vr5_8_11', 1, 0x4254),
Register('vr5_8_10', 1, 0x4255),
Register('vr5_16_4', 2, 0x4256),
Register('vr5_8_9', 1, 0x4256),
Register('vr5_8_8', 1, 0x4257),
Register('vr5_64_0', 8, 0x4258),
Register('vr5_32_1', 4, 0x4258),
Register('vr5_16_3', 2, 0x4258),
Register('vr5_8_7', 1, 0x4258),
Register('vr5_8_6', 1, 0x4259),
Register('vr5_16_2', 2, 0x425a),
Register('vr5_8_5', 1, 0x425a),
Register('vr5_8_4', 1, 0x425b),
Register('vr5_32_0', 4, 0x425c),
Register('vr5_16_1', 2, 0x425c),
Register('vr5_8_3', 1, 0x425c),
Register('vr5_8_2', 1, 0x425d),
Register('vr5_16_0', 2, 0x425e),
Register('vr5_8_1', 1, 0x425e),
Register('vr5_8_0', 1, 0x425f),
Register('vs38', 16, 0x4260),
Register('vr6_64_1', 8, 0x4260),
Register('vr6_32_3', 4, 0x4260),
Register('vr6_16_7', 2, 0x4260),
Register('vr6_8_15', 1, 0x4260),
Register('vr6_8_14', 1, 0x4261),
Register('vr6_16_6', 2, 0x4262),
Register('vr6_8_13', 1, 0x4262),
Register('vr6_8_12', 1, 0x4263),
Register('vr6_32_2', 4, 0x4264),
Register('vr6_16_5', 2, 0x4264),
Register('vr6_8_11', 1, 0x4264),
Register('vr6_8_10', 1, 0x4265),
Register('vr6_16_4', 2, 0x4266),
Register('vr6_8_9', 1, 0x4266),
Register('vr6_8_8', 1, 0x4267),
Register('vr6_64_0', 8, 0x4268),
Register('vr6_32_1', 4, 0x4268),
Register('vr6_16_3', 2, 0x4268),
Register('vr6_8_7', 1, 0x4268),
Register('vr6_8_6', 1, 0x4269),
Register('vr6_16_2', 2, 0x426a),
Register('vr6_8_5', 1, 0x426a),
Register('vr6_8_4', 1, 0x426b),
Register('vr6_32_0', 4, 0x426c),
Register('vr6_16_1', 2, 0x426c),
Register('vr6_8_3', 1, 0x426c),
Register('vr6_8_2', 1, 0x426d),
Register('vr6_16_0', 2, 0x426e),
Register('vr6_8_1', 1, 0x426e),
Register('vr6_8_0', 1, 0x426f),
Register('vs39', 16, 0x4270),
Register('vr7_64_1', 8, 0x4270),
Register('vr7_32_3', 4, 0x4270),
Register('vr7_16_7', 2, 0x4270),
Register('vr7_8_15', 1, 0x4270),
Register('vr7_8_14', 1, 0x4271),
Register('vr7_16_6', 2, 0x4272),
Register('vr7_8_13', 1, 0x4272),
Register('vr7_8_12', 1, 0x4273),
Register('vr7_32_2', 4, 0x4274),
Register('vr7_16_5', 2, 0x4274),
Register('vr7_8_11', 1, 0x4274),
Register('vr7_8_10', 1, 0x4275),
Register('vr7_16_4', 2, 0x4276),
Register('vr7_8_9', 1, 0x4276),
Register('vr7_8_8', 1, 0x4277),
Register('vr7_64_0', 8, 0x4278),
Register('vr7_32_1', 4, 0x4278),
Register('vr7_16_3', 2, 0x4278),
Register('vr7_8_7', 1, 0x4278),
Register('vr7_8_6', 1, 0x4279),
Register('vr7_16_2', 2, 0x427a),
Register('vr7_8_5', 1, 0x427a),
Register('vr7_8_4', 1, 0x427b),
Register('vr7_32_0', 4, 0x427c),
Register('vr7_16_1', 2, 0x427c),
Register('vr7_8_3', 1, 0x427c),
Register('vr7_8_2', 1, 0x427d),
Register('vr7_16_0', 2, 0x427e),
Register('vr7_8_1', 1, 0x427e),
Register('vr7_8_0', 1, 0x427f),
Register('vs40', 16, 0x4280),
Register('vr8_64_1', 8, 0x4280),
Register('vr8_32_3', 4, 0x4280),
Register('vr8_16_7', 2, 0x4280),
Register('vr8_8_15', 1, 0x4280),
Register('vr8_8_14', 1, 0x4281),
Register('vr8_16_6', 2, 0x4282),
Register('vr8_8_13', 1, 0x4282),
Register('vr8_8_12', 1, 0x4283),
Register('vr8_32_2', 4, 0x4284),
Register('vr8_16_5', 2, 0x4284),
Register('vr8_8_11', 1, 0x4284),
Register('vr8_8_10', 1, 0x4285),
Register('vr8_16_4', 2, 0x4286),
Register('vr8_8_9', 1, 0x4286),
Register('vr8_8_8', 1, 0x4287),
Register('vr8_64_0', 8, 0x4288),
Register('vr8_32_1', 4, 0x4288),
Register('vr8_16_3', 2, 0x4288),
Register('vr8_8_7', 1, 0x4288),
Register('vr8_8_6', 1, 0x4289),
Register('vr8_16_2', 2, 0x428a),
Register('vr8_8_5', 1, 0x428a),
Register('vr8_8_4', 1, 0x428b),
Register('vr8_32_0', 4, 0x428c),
Register('vr8_16_1', 2, 0x428c),
Register('vr8_8_3', 1, 0x428c),
Register('vr8_8_2', 1, 0x428d),
Register('vr8_16_0', 2, 0x428e),
Register('vr8_8_1', 1, 0x428e),
Register('vr8_8_0', 1, 0x428f),
Register('vs41', 16, 0x4290),
Register('vr9_64_1', 8, 0x4290),
Register('vr9_32_3', 4, 0x4290),
Register('vr9_16_7', 2, 0x4290),
Register('vr9_8_15', 1, 0x4290),
Register('vr9_8_14', 1, 0x4291),
Register('vr9_16_6', 2, 0x4292),
Register('vr9_8_13', 1, 0x4292),
Register('vr9_8_12', 1, 0x4293),
Register('vr9_32_2', 4, 0x4294),
Register('vr9_16_5', 2, 0x4294),
Register('vr9_8_11', 1, 0x4294),
Register('vr9_8_10', 1, 0x4295),
Register('vr9_16_4', 2, 0x4296),
Register('vr9_8_9', 1, 0x4296),
Register('vr9_8_8', 1, 0x4297),
Register('vr9_64_0', 8, 0x4298),
Register('vr9_32_1', 4, 0x4298),
Register('vr9_16_3', 2, 0x4298),
Register('vr9_8_7', 1, 0x4298),
Register('vr9_8_6', 1, 0x4299),
Register('vr9_16_2', 2, 0x429a),
Register('vr9_8_5', 1, 0x429a),
Register('vr9_8_4', 1, 0x429b),
Register('vr9_32_0', 4, 0x429c),
Register('vr9_16_1', 2, 0x429c),
Register('vr9_8_3', 1, 0x429c),
Register('vr9_8_2', 1, 0x429d),
Register('vr9_16_0', 2, 0x429e),
Register('vr9_8_1', 1, 0x429e),
Register('vr9_8_0', 1, 0x429f),
Register('vs42', 16, 0x42a0),
Register('vr10_64_1', 8, 0x42a0),
Register('vr10_32_3', 4, 0x42a0),
Register('vr10_16_7', 2, 0x42a0),
Register('vr10_8_15', 1, 0x42a0),
Register('vr10_8_14', 1, 0x42a1),
Register('vr10_16_6', 2, 0x42a2),
Register('vr10_8_13', 1, 0x42a2),
Register('vr10_8_12', 1, 0x42a3),
Register('vr10_32_2', 4, 0x42a4),
Register('vr10_16_5', 2, 0x42a4),
Register('vr10_8_11', 1, 0x42a4),
Register('vr10_8_10', 1, 0x42a5),
Register('vr10_16_4', 2, 0x42a6),
Register('vr10_8_9', 1, 0x42a6),
Register('vr10_8_8', 1, 0x42a7),
Register('vr10_64_0', 8, 0x42a8),
Register('vr10_32_1', 4, 0x42a8),
Register('vr10_16_3', 2, 0x42a8),
Register('vr10_8_7', 1, 0x42a8),
Register('vr10_8_6', 1, 0x42a9),
Register('vr10_16_2', 2, 0x42aa),
Register('vr10_8_5', 1, 0x42aa),
Register('vr10_8_4', 1, 0x42ab),
Register('vr10_32_0', 4, 0x42ac),
Register('vr10_16_1', 2, 0x42ac),
Register('vr10_8_3', 1, 0x42ac),
Register('vr10_8_2', 1, 0x42ad),
Register('vr10_16_0', 2, 0x42ae),
Register('vr10_8_1', 1, 0x42ae),
Register('vr10_8_0', 1, 0x42af),
Register('vs43', 16, 0x42b0),
Register('vr11_64_1', 8, 0x42b0),
Register('vr11_32_3', 4, 0x42b0),
Register('vr11_16_7', 2, 0x42b0),
Register('vr11_8_15', 1, 0x42b0),
Register('vr11_8_14', 1, 0x42b1),
Register('vr11_16_6', 2, 0x42b2),
Register('vr11_8_13', 1, 0x42b2),
Register('vr11_8_12', 1, 0x42b3),
Register('vr11_32_2', 4, 0x42b4),
Register('vr11_16_5', 2, 0x42b4),
Register('vr11_8_11', 1, 0x42b4),
Register('vr11_8_10', 1, 0x42b5),
Register('vr11_16_4', 2, 0x42b6),
Register('vr11_8_9', 1, 0x42b6),
Register('vr11_8_8', 1, 0x42b7),
Register('vr11_64_0', 8, 0x42b8),
Register('vr11_32_1', 4, 0x42b8),
Register('vr11_16_3', 2, 0x42b8),
Register('vr11_8_7', 1, 0x42b8),
Register('vr11_8_6', 1, 0x42b9),
Register('vr11_16_2', 2, 0x42ba),
Register('vr11_8_5', 1, 0x42ba),
Register('vr11_8_4', 1, 0x42bb),
Register('vr11_32_0', 4, 0x42bc),
Register('vr11_16_1', 2, 0x42bc),
Register('vr11_8_3', 1, 0x42bc),
Register('vr11_8_2', 1, 0x42bd),
Register('vr11_16_0', 2, 0x42be),
Register('vr11_8_1', 1, 0x42be),
Register('vr11_8_0', 1, 0x42bf),
Register('vs44', 16, 0x42c0),
Register('vr12_64_1', 8, 0x42c0),
Register('vr12_32_3', 4, 0x42c0),
Register('vr12_16_7', 2, 0x42c0),
Register('vr12_8_15', 1, 0x42c0),
Register('vr12_8_14', 1, 0x42c1),
Register('vr12_16_6', 2, 0x42c2),
Register('vr12_8_13', 1, 0x42c2),
Register('vr12_8_12', 1, 0x42c3),
Register('vr12_32_2', 4, 0x42c4),
Register('vr12_16_5', 2, 0x42c4),
Register('vr12_8_11', 1, 0x42c4),
Register('vr12_8_10', 1, 0x42c5),
Register('vr12_16_4', 2, 0x42c6),
Register('vr12_8_9', 1, 0x42c6),
Register('vr12_8_8', 1, 0x42c7),
Register('vr12_64_0', 8, 0x42c8),
Register('vr12_32_1', 4, 0x42c8),
Register('vr12_16_3', 2, 0x42c8),
Register('vr12_8_7', 1, 0x42c8),
Register('vr12_8_6', 1, 0x42c9),
Register('vr12_16_2', 2, 0x42ca),
Register('vr12_8_5', 1, 0x42ca),
Register('vr12_8_4', 1, 0x42cb),
Register('vr12_32_0', 4, 0x42cc),
Register('vr12_16_1', 2, 0x42cc),
Register('vr12_8_3', 1, 0x42cc),
Register('vr12_8_2', 1, 0x42cd),
Register('vr12_16_0', 2, 0x42ce),
Register('vr12_8_1', 1, 0x42ce),
Register('vr12_8_0', 1, 0x42cf),
Register('vs45', 16, 0x42d0),
Register('vr13_64_1', 8, 0x42d0),
Register('vr13_32_3', 4, 0x42d0),
Register('vr13_16_7', 2, 0x42d0),
Register('vr13_8_15', 1, 0x42d0),
Register('vr13_8_14', 1, 0x42d1),
Register('vr13_16_6', 2, 0x42d2),
Register('vr13_8_13', 1, 0x42d2),
Register('vr13_8_12', 1, 0x42d3),
Register('vr13_32_2', 4, 0x42d4),
Register('vr13_16_5', 2, 0x42d4),
Register('vr13_8_11', 1, 0x42d4),
Register('vr13_8_10', 1, 0x42d5),
Register('vr13_16_4', 2, 0x42d6),
Register('vr13_8_9', 1, 0x42d6),
Register('vr13_8_8', 1, 0x42d7),
Register('vr13_64_0', 8, 0x42d8),
Register('vr13_32_1', 4, 0x42d8),
Register('vr13_16_3', 2, 0x42d8),
Register('vr13_8_7', 1, 0x42d8),
Register('vr13_8_6', 1, 0x42d9),
Register('vr13_16_2', 2, 0x42da),
Register('vr13_8_5', 1, 0x42da),
Register('vr13_8_4', 1, 0x42db),
Register('vr13_32_0', 4, 0x42dc),
Register('vr13_16_1', 2, 0x42dc),
Register('vr13_8_3', 1, 0x42dc),
Register('vr13_8_2', 1, 0x42dd),
Register('vr13_16_0', 2, 0x42de),
Register('vr13_8_1', 1, 0x42de),
Register('vr13_8_0', 1, 0x42df),
Register('vs46', 16, 0x42e0),
Register('vr14_64_1', 8, 0x42e0),
Register('vr14_32_3', 4, 0x42e0),
Register('vr14_16_7', 2, 0x42e0),
Register('vr14_8_15', 1, 0x42e0),
Register('vr14_8_14', 1, 0x42e1),
Register('vr14_16_6', 2, 0x42e2),
Register('vr14_8_13', 1, 0x42e2),
Register('vr14_8_12', 1, 0x42e3),
Register('vr14_32_2', 4, 0x42e4),
Register('vr14_16_5', 2, 0x42e4),
Register('vr14_8_11', 1, 0x42e4),
Register('vr14_8_10', 1, 0x42e5),
Register('vr14_16_4', 2, 0x42e6),
Register('vr14_8_9', 1, 0x42e6),
Register('vr14_8_8', 1, 0x42e7),
Register('vr14_64_0', 8, 0x42e8),
Register('vr14_32_1', 4, 0x42e8),
Register('vr14_16_3', 2, 0x42e8),
Register('vr14_8_7', 1, 0x42e8),
Register('vr14_8_6', 1, 0x42e9),
Register('vr14_16_2', 2, 0x42ea),
Register('vr14_8_5', 1, 0x42ea),
Register('vr14_8_4', 1, 0x42eb),
Register('vr14_32_0', 4, 0x42ec),
Register('vr14_16_1', 2, 0x42ec),
Register('vr14_8_3', 1, 0x42ec),
Register('vr14_8_2', 1, 0x42ed),
Register('vr14_16_0', 2, 0x42ee),
Register('vr14_8_1', 1, 0x42ee),
Register('vr14_8_0', 1, 0x42ef),
Register('vs47', 16, 0x42f0),
Register('vr15_64_1', 8, 0x42f0),
Register('vr15_32_3', 4, 0x42f0),
Register('vr15_16_7', 2, 0x42f0),
Register('vr15_8_15', 1, 0x42f0),
Register('vr15_8_14', 1, 0x42f1),
Register('vr15_16_6', 2, 0x42f2),
Register('vr15_8_13', 1, 0x42f2),
Register('vr15_8_12', 1, 0x42f3),
Register('vr15_32_2', 4, 0x42f4),
Register('vr15_16_5', 2, 0x42f4),
Register('vr15_8_11', 1, 0x42f4),
Register('vr15_8_10', 1, 0x42f5),
Register('vr15_16_4', 2, 0x42f6),
Register('vr15_8_9', 1, 0x42f6),
Register('vr15_8_8', 1, 0x42f7),
Register('vr15_64_0', 8, 0x42f8),
Register('vr15_32_1', 4, 0x42f8),
Register('vr15_16_3', 2, 0x42f8),
Register('vr15_8_7', 1, 0x42f8),
Register('vr15_8_6', 1, 0x42f9),
Register('vr15_16_2', 2, 0x42fa),
Register('vr15_8_5', 1, 0x42fa),
Register('vr15_8_4', 1, 0x42fb),
Register('vr15_32_0', 4, 0x42fc),
Register('vr15_16_1', 2, 0x42fc),
Register('vr15_8_3', 1, 0x42fc),
Register('vr15_8_2', 1, 0x42fd),
Register('vr15_16_0', 2, 0x42fe),
Register('vr15_8_1', 1, 0x42fe),
Register('vr15_8_0', 1, 0x42ff),
Register('vs48', 16, 0x4300),
Register('vr16_64_1', 8, 0x4300),
Register('vr16_32_3', 4, 0x4300),
Register('vr16_16_7', 2, 0x4300),
Register('vr16_8_15', 1, 0x4300),
Register('vr16_8_14', 1, 0x4301),
Register('vr16_16_6', 2, 0x4302),
Register('vr16_8_13', 1, 0x4302),
Register('vr16_8_12', 1, 0x4303),
Register('vr16_32_2', 4, 0x4304),
Register('vr16_16_5', 2, 0x4304),
Register('vr16_8_11', 1, 0x4304),
Register('vr16_8_10', 1, 0x4305),
Register('vr16_16_4', 2, 0x4306),
Register('vr16_8_9', 1, 0x4306),
Register('vr16_8_8', 1, 0x4307),
Register('vr16_64_0', 8, 0x4308),
Register('vr16_32_1', 4, 0x4308),
Register('vr16_16_3', 2, 0x4308),
Register('vr16_8_7', 1, 0x4308),
Register('vr16_8_6', 1, 0x4309),
Register('vr16_16_2', 2, 0x430a),
Register('vr16_8_5', 1, 0x430a),
Register('vr16_8_4', 1, 0x430b),
Register('vr16_32_0', 4, 0x430c),
Register('vr16_16_1', 2, 0x430c),
Register('vr16_8_3', 1, 0x430c),
Register('vr16_8_2', 1, 0x430d),
Register('vr16_16_0', 2, 0x430e),
Register('vr16_8_1', 1, 0x430e),
Register('vr16_8_0', 1, 0x430f),
Register('vs49', 16, 0x4310),
Register('vr17_64_1', 8, 0x4310),
Register('vr17_32_3', 4, 0x4310),
Register('vr17_16_7', 2, 0x4310),
Register('vr17_8_15', 1, 0x4310),
Register('vr17_8_14', 1, 0x4311),
Register('vr17_16_6', 2, 0x4312),
Register('vr17_8_13', 1, 0x4312),
Register('vr17_8_12', 1, 0x4313),
Register('vr17_32_2', 4, 0x4314),
Register('vr17_16_5', 2, 0x4314),
Register('vr17_8_11', 1, 0x4314),
Register('vr17_8_10', 1, 0x4315),
Register('vr17_16_4', 2, 0x4316),
Register('vr17_8_9', 1, 0x4316),
Register('vr17_8_8', 1, 0x4317),
Register('vr17_64_0', 8, 0x4318),
Register('vr17_32_1', 4, 0x4318),
Register('vr17_16_3', 2, 0x4318),
Register('vr17_8_7', 1, 0x4318),
Register('vr17_8_6', 1, 0x4319),
Register('vr17_16_2', 2, 0x431a),
Register('vr17_8_5', 1, 0x431a),
Register('vr17_8_4', 1, 0x431b),
Register('vr17_32_0', 4, 0x431c),
Register('vr17_16_1', 2, 0x431c),
Register('vr17_8_3', 1, 0x431c),
Register('vr17_8_2', 1, 0x431d),
Register('vr17_16_0', 2, 0x431e),
Register('vr17_8_1', 1, 0x431e),
Register('vr17_8_0', 1, 0x431f),
Register('vs50', 16, 0x4320),
Register('vr18_64_1', 8, 0x4320),
Register('vr18_32_3', 4, 0x4320),
Register('vr18_16_7', 2, 0x4320),
Register('vr18_8_15', 1, 0x4320),
Register('vr18_8_14', 1, 0x4321),
Register('vr18_16_6', 2, 0x4322),
Register('vr18_8_13', 1, 0x4322),
Register('vr18_8_12', 1, 0x4323),
Register('vr18_32_2', 4, 0x4324),
Register('vr18_16_5', 2, 0x4324),
Register('vr18_8_11', 1, 0x4324),
Register('vr18_8_10', 1, 0x4325),
Register('vr18_16_4', 2, 0x4326),
Register('vr18_8_9', 1, 0x4326),
Register('vr18_8_8', 1, 0x4327),
Register('vr18_64_0', 8, 0x4328),
Register('vr18_32_1', 4, 0x4328),
Register('vr18_16_3', 2, 0x4328),
Register('vr18_8_7', 1, 0x4328),
Register('vr18_8_6', 1, 0x4329),
Register('vr18_16_2', 2, 0x432a),
Register('vr18_8_5', 1, 0x432a),
Register('vr18_8_4', 1, 0x432b),
Register('vr18_32_0', 4, 0x432c),
Register('vr18_16_1', 2, 0x432c),
Register('vr18_8_3', 1, 0x432c),
Register('vr18_8_2', 1, 0x432d),
Register('vr18_16_0', 2, 0x432e),
Register('vr18_8_1', 1, 0x432e),
Register('vr18_8_0', 1, 0x432f),
Register('vs51', 16, 0x4330),
Register('vr19_64_1', 8, 0x4330),
Register('vr19_32_3', 4, 0x4330),
Register('vr19_16_7', 2, 0x4330),
Register('vr19_8_15', 1, 0x4330),
Register('vr19_8_14', 1, 0x4331),
Register('vr19_16_6', 2, 0x4332),
Register('vr19_8_13', 1, 0x4332),
Register('vr19_8_12', 1, 0x4333),
Register('vr19_32_2', 4, 0x4334),
Register('vr19_16_5', 2, 0x4334),
Register('vr19_8_11', 1, 0x4334),
Register('vr19_8_10', 1, 0x4335),
Register('vr19_16_4', 2, 0x4336),
Register('vr19_8_9', 1, 0x4336),
Register('vr19_8_8', 1, 0x4337),
Register('vr19_64_0', 8, 0x4338),
Register('vr19_32_1', 4, 0x4338),
Register('vr19_16_3', 2, 0x4338),
Register('vr19_8_7', 1, 0x4338),
Register('vr19_8_6', 1, 0x4339),
Register('vr19_16_2', 2, 0x433a),
Register('vr19_8_5', 1, 0x433a),
Register('vr19_8_4', 1, 0x433b),
Register('vr19_32_0', 4, 0x433c),
Register('vr19_16_1', 2, 0x433c),
Register('vr19_8_3', 1, 0x433c),
Register('vr19_8_2', 1, 0x433d),
Register('vr19_16_0', 2, 0x433e),
Register('vr19_8_1', 1, 0x433e),
Register('vr19_8_0', 1, 0x433f),
Register('vs52', 16, 0x4340),
Register('vr20_64_1', 8, 0x4340),
Register('vr20_32_3', 4, 0x4340),
Register('vr20_16_7', 2, 0x4340),
Register('vr20_8_15', 1, 0x4340),
Register('vr20_8_14', 1, 0x4341),
Register('vr20_16_6', 2, 0x4342),
Register('vr20_8_13', 1, 0x4342),
Register('vr20_8_12', 1, 0x4343),
Register('vr20_32_2', 4, 0x4344),
Register('vr20_16_5', 2, 0x4344),
Register('vr20_8_11', 1, 0x4344),
Register('vr20_8_10', 1, 0x4345),
Register('vr20_16_4', 2, 0x4346),
Register('vr20_8_9', 1, 0x4346),
Register('vr20_8_8', 1, 0x4347),
Register('vr20_64_0', 8, 0x4348),
Register('vr20_32_1', 4, 0x4348),
Register('vr20_16_3', 2, 0x4348),
Register('vr20_8_7', 1, 0x4348),
Register('vr20_8_6', 1, 0x4349),
Register('vr20_16_2', 2, 0x434a),
Register('vr20_8_5', 1, 0x434a),
Register('vr20_8_4', 1, 0x434b),
Register('vr20_32_0', 4, 0x434c),
Register('vr20_16_1', 2, 0x434c),
Register('vr20_8_3', 1, 0x434c),
Register('vr20_8_2', 1, 0x434d),
Register('vr20_16_0', 2, 0x434e),
Register('vr20_8_1', 1, 0x434e),
Register('vr20_8_0', 1, 0x434f),
Register('vs53', 16, 0x4350),
Register('vr21_64_1', 8, 0x4350),
Register('vr21_32_3', 4, 0x4350),
Register('vr21_16_7', 2, 0x4350),
Register('vr21_8_15', 1, 0x4350),
Register('vr21_8_14', 1, 0x4351),
Register('vr21_16_6', 2, 0x4352),
Register('vr21_8_13', 1, 0x4352),
Register('vr21_8_12', 1, 0x4353),
Register('vr21_32_2', 4, 0x4354),
Register('vr21_16_5', 2, 0x4354),
Register('vr21_8_11', 1, 0x4354),
Register('vr21_8_10', 1, 0x4355),
Register('vr21_16_4', 2, 0x4356),
Register('vr21_8_9', 1, 0x4356),
Register('vr21_8_8', 1, 0x4357),
Register('vr21_64_0', 8, 0x4358),
Register('vr21_32_1', 4, 0x4358),
Register('vr21_16_3', 2, 0x4358),
Register('vr21_8_7', 1, 0x4358),
Register('vr21_8_6', 1, 0x4359),
Register('vr21_16_2', 2, 0x435a),
Register('vr21_8_5', 1, 0x435a),
Register('vr21_8_4', 1, 0x435b),
Register('vr21_32_0', 4, 0x435c),
Register('vr21_16_1', 2, 0x435c),
Register('vr21_8_3', 1, 0x435c),
Register('vr21_8_2', 1, 0x435d),
Register('vr21_16_0', 2, 0x435e),
Register('vr21_8_1', 1, 0x435e),
Register('vr21_8_0', 1, 0x435f),
Register('vs54', 16, 0x4360),
Register('vr22_64_1', 8, 0x4360),
Register('vr22_32_3', 4, 0x4360),
Register('vr22_16_7', 2, 0x4360),
Register('vr22_8_15', 1, 0x4360),
Register('vr22_8_14', 1, 0x4361),
Register('vr22_16_6', 2, 0x4362),
Register('vr22_8_13', 1, 0x4362),
Register('vr22_8_12', 1, 0x4363),
Register('vr22_32_2', 4, 0x4364),
Register('vr22_16_5', 2, 0x4364),
Register('vr22_8_11', 1, 0x4364),
Register('vr22_8_10', 1, 0x4365),
Register('vr22_16_4', 2, 0x4366),
Register('vr22_8_9', 1, 0x4366),
Register('vr22_8_8', 1, 0x4367),
Register('vr22_64_0', 8, 0x4368),
Register('vr22_32_1', 4, 0x4368),
Register('vr22_16_3', 2, 0x4368),
Register('vr22_8_7', 1, 0x4368),
Register('vr22_8_6', 1, 0x4369),
Register('vr22_16_2', 2, 0x436a),
Register('vr22_8_5', 1, 0x436a),
Register('vr22_8_4', 1, 0x436b),
Register('vr22_32_0', 4, 0x436c),
Register('vr22_16_1', 2, 0x436c),
Register('vr22_8_3', 1, 0x436c),
Register('vr22_8_2', 1, 0x436d),
Register('vr22_16_0', 2, 0x436e),
Register('vr22_8_1', 1, 0x436e),
Register('vr22_8_0', 1, 0x436f),
Register('vs55', 16, 0x4370),
Register('vr23_64_1', 8, 0x4370),
Register('vr23_32_3', 4, 0x4370),
Register('vr23_16_7', 2, 0x4370),
Register('vr23_8_15', 1, 0x4370),
Register('vr23_8_14', 1, 0x4371),
Register('vr23_16_6', 2, 0x4372),
Register('vr23_8_13', 1, 0x4372),
Register('vr23_8_12', 1, 0x4373),
Register('vr23_32_2', 4, 0x4374),
Register('vr23_16_5', 2, 0x4374),
Register('vr23_8_11', 1, 0x4374),
Register('vr23_8_10', 1, 0x4375),
Register('vr23_16_4', 2, 0x4376),
Register('vr23_8_9', 1, 0x4376),
Register('vr23_8_8', 1, 0x4377),
Register('vr23_64_0', 8, 0x4378),
Register('vr23_32_1', 4, 0x4378),
Register('vr23_16_3', 2, 0x4378),
Register('vr23_8_7', 1, 0x4378),
Register('vr23_8_6', 1, 0x4379),
Register('vr23_16_2', 2, 0x437a),
Register('vr23_8_5', 1, 0x437a),
Register('vr23_8_4', 1, 0x437b),
Register('vr23_32_0', 4, 0x437c),
Register('vr23_16_1', 2, 0x437c),
Register('vr23_8_3', 1, 0x437c),
Register('vr23_8_2', 1, 0x437d),
Register('vr23_16_0', 2, 0x437e),
Register('vr23_8_1', 1, 0x437e),
Register('vr23_8_0', 1, 0x437f),
Register('vs56', 16, 0x4380),
Register('vr24_64_1', 8, 0x4380),
Register('vr24_32_3', 4, 0x4380),
Register('vr24_16_7', 2, 0x4380),
Register('vr24_8_15', 1, 0x4380),
Register('vr24_8_14', 1, 0x4381),
Register('vr24_16_6', 2, 0x4382),
Register('vr24_8_13', 1, 0x4382),
Register('vr24_8_12', 1, 0x4383),
Register('vr24_32_2', 4, 0x4384),
Register('vr24_16_5', 2, 0x4384),
Register('vr24_8_11', 1, 0x4384),
Register('vr24_8_10', 1, 0x4385),
Register('vr24_16_4', 2, 0x4386),
Register('vr24_8_9', 1, 0x4386),
Register('vr24_8_8', 1, 0x4387),
Register('vr24_64_0', 8, 0x4388),
Register('vr24_32_1', 4, 0x4388),
Register('vr24_16_3', 2, 0x4388),
Register('vr24_8_7', 1, 0x4388),
Register('vr24_8_6', 1, 0x4389),
Register('vr24_16_2', 2, 0x438a),
Register('vr24_8_5', 1, 0x438a),
Register('vr24_8_4', 1, 0x438b),
Register('vr24_32_0', 4, 0x438c),
Register('vr24_16_1', 2, 0x438c),
Register('vr24_8_3', 1, 0x438c),
Register('vr24_8_2', 1, 0x438d),
Register('vr24_16_0', 2, 0x438e),
Register('vr24_8_1', 1, 0x438e),
Register('vr24_8_0', 1, 0x438f),
Register('vs57', 16, 0x4390),
Register('vr25_64_1', 8, 0x4390),
Register('vr25_32_3', 4, 0x4390),
Register('vr25_16_7', 2, 0x4390),
Register('vr25_8_15', 1, 0x4390),
Register('vr25_8_14', 1, 0x4391),
Register('vr25_16_6', 2, 0x4392),
Register('vr25_8_13', 1, 0x4392),
Register('vr25_8_12', 1, 0x4393),
Register('vr25_32_2', 4, 0x4394),
Register('vr25_16_5', 2, 0x4394),
Register('vr25_8_11', 1, 0x4394),
Register('vr25_8_10', 1, 0x4395),
Register('vr25_16_4', 2, 0x4396),
Register('vr25_8_9', 1, 0x4396),
Register('vr25_8_8', 1, 0x4397),
Register('vr25_64_0', 8, 0x4398),
Register('vr25_32_1', 4, 0x4398),
Register('vr25_16_3', 2, 0x4398),
Register('vr25_8_7', 1, 0x4398),
Register('vr25_8_6', 1, 0x4399),
Register('vr25_16_2', 2, 0x439a),
Register('vr25_8_5', 1, 0x439a),
Register('vr25_8_4', 1, 0x439b),
Register('vr25_32_0', 4, 0x439c),
Register('vr25_16_1', 2, 0x439c),
Register('vr25_8_3', 1, 0x439c),
Register('vr25_8_2', 1, 0x439d),
Register('vr25_16_0', 2, 0x439e),
Register('vr25_8_1', 1, 0x439e),
Register('vr25_8_0', 1, 0x439f),
Register('vs58', 16, 0x43a0),
Register('vr26_64_1', 8, 0x43a0),
Register('vr26_32_3', 4, 0x43a0),
Register('vr26_16_7', 2, 0x43a0),
Register('vr26_8_15', 1, 0x43a0),
Register('vr26_8_14', 1, 0x43a1),
Register('vr26_16_6', 2, 0x43a2),
Register('vr26_8_13', 1, 0x43a2),
Register('vr26_8_12', 1, 0x43a3),
Register('vr26_32_2', 4, 0x43a4),
Register('vr26_16_5', 2, 0x43a4),
Register('vr26_8_11', 1, 0x43a4),
Register('vr26_8_10', 1, 0x43a5),
Register('vr26_16_4', 2, 0x43a6),
Register('vr26_8_9', 1, 0x43a6),
Register('vr26_8_8', 1, 0x43a7),
Register('vr26_64_0', 8, 0x43a8),
Register('vr26_32_1', 4, 0x43a8),
Register('vr26_16_3', 2, 0x43a8),
Register('vr26_8_7', 1, 0x43a8),
Register('vr26_8_6', 1, 0x43a9),
Register('vr26_16_2', 2, 0x43aa),
Register('vr26_8_5', 1, 0x43aa),
Register('vr26_8_4', 1, 0x43ab),
Register('vr26_32_0', 4, 0x43ac),
Register('vr26_16_1', 2, 0x43ac),
Register('vr26_8_3', 1, 0x43ac),
Register('vr26_8_2', 1, 0x43ad),
Register('vr26_16_0', 2, 0x43ae),
Register('vr26_8_1', 1, 0x43ae),
Register('vr26_8_0', 1, 0x43af),
Register('vs59', 16, 0x43b0),
Register('vr27_64_1', 8, 0x43b0),
Register('vr27_32_3', 4, 0x43b0),
Register('vr27_16_7', 2, 0x43b0),
Register('vr27_8_15', 1, 0x43b0),
Register('vr27_8_14', 1, 0x43b1),
Register('vr27_16_6', 2, 0x43b2),
Register('vr27_8_13', 1, 0x43b2),
Register('vr27_8_12', 1, 0x43b3),
Register('vr27_32_2', 4, 0x43b4),
Register('vr27_16_5', 2, 0x43b4),
Register('vr27_8_11', 1, 0x43b4),
Register('vr27_8_10', 1, 0x43b5),
Register('vr27_16_4', 2, 0x43b6),
Register('vr27_8_9', 1, 0x43b6),
Register('vr27_8_8', 1, 0x43b7),
Register('vr27_64_0', 8, 0x43b8),
Register('vr27_32_1', 4, 0x43b8),
Register('vr27_16_3', 2, 0x43b8),
Register('vr27_8_7', 1, 0x43b8),
Register('vr27_8_6', 1, 0x43b9),
Register('vr27_16_2', 2, 0x43ba),
Register('vr27_8_5', 1, 0x43ba),
Register('vr27_8_4', 1, 0x43bb),
Register('vr27_32_0', 4, 0x43bc),
Register('vr27_16_1', 2, 0x43bc),
Register('vr27_8_3', 1, 0x43bc),
Register('vr27_8_2', 1, 0x43bd),
Register('vr27_16_0', 2, 0x43be),
Register('vr27_8_1', 1, 0x43be),
Register('vr27_8_0', 1, 0x43bf),
Register('vs60', 16, 0x43c0),
Register('vr28_64_1', 8, 0x43c0),
Register('vr28_32_3', 4, 0x43c0),
Register('vr28_16_7', 2, 0x43c0),
Register('vr28_8_15', 1, 0x43c0),
Register('vr28_8_14', 1, 0x43c1),
Register('vr28_16_6', 2, 0x43c2),
Register('vr28_8_13', 1, 0x43c2),
Register('vr28_8_12', 1, 0x43c3),
Register('vr28_32_2', 4, 0x43c4),
Register('vr28_16_5', 2, 0x43c4),
Register('vr28_8_11', 1, 0x43c4),
Register('vr28_8_10', 1, 0x43c5),
Register('vr28_16_4', 2, 0x43c6),
Register('vr28_8_9', 1, 0x43c6),
Register('vr28_8_8', 1, 0x43c7),
Register('vr28_64_0', 8, 0x43c8),
Register('vr28_32_1', 4, 0x43c8),
Register('vr28_16_3', 2, 0x43c8),
Register('vr28_8_7', 1, 0x43c8),
Register('vr28_8_6', 1, 0x43c9),
Register('vr28_16_2', 2, 0x43ca),
Register('vr28_8_5', 1, 0x43ca),
Register('vr28_8_4', 1, 0x43cb),
Register('vr28_32_0', 4, 0x43cc),
Register('vr28_16_1', 2, 0x43cc),
Register('vr28_8_3', 1, 0x43cc),
Register('vr28_8_2', 1, 0x43cd),
Register('vr28_16_0', 2, 0x43ce),
Register('vr28_8_1', 1, 0x43ce),
Register('vr28_8_0', 1, 0x43cf),
Register('vs61', 16, 0x43d0),
Register('vr29_64_1', 8, 0x43d0),
Register('vr29_32_3', 4, 0x43d0),
Register('vr29_16_7', 2, 0x43d0),
Register('vr29_8_15', 1, 0x43d0),
Register('vr29_8_14', 1, 0x43d1),
Register('vr29_16_6', 2, 0x43d2),
Register('vr29_8_13', 1, 0x43d2),
Register('vr29_8_12', 1, 0x43d3),
Register('vr29_32_2', 4, 0x43d4),
Register('vr29_16_5', 2, 0x43d4),
Register('vr29_8_11', 1, 0x43d4),
Register('vr29_8_10', 1, 0x43d5),
Register('vr29_16_4', 2, 0x43d6),
Register('vr29_8_9', 1, 0x43d6),
Register('vr29_8_8', 1, 0x43d7),
Register('vr29_64_0', 8, 0x43d8),
Register('vr29_32_1', 4, 0x43d8),
Register('vr29_16_3', 2, 0x43d8),
Register('vr29_8_7', 1, 0x43d8),
Register('vr29_8_6', 1, 0x43d9),
Register('vr29_16_2', 2, 0x43da),
Register('vr29_8_5', 1, 0x43da),
Register('vr29_8_4', 1, 0x43db),
Register('vr29_32_0', 4, 0x43dc),
Register('vr29_16_1', 2, 0x43dc),
Register('vr29_8_3', 1, 0x43dc),
Register('vr29_8_2', 1, 0x43dd),
Register('vr29_16_0', 2, 0x43de),
Register('vr29_8_1', 1, 0x43de),
Register('vr29_8_0', 1, 0x43df),
Register('vs62', 16, 0x43e0),
Register('vr30_64_1', 8, 0x43e0),
Register('vr30_32_3', 4, 0x43e0),
Register('vr30_16_7', 2, 0x43e0),
Register('vr30_8_15', 1, 0x43e0),
Register('vr30_8_14', 1, 0x43e1),
Register('vr30_16_6', 2, 0x43e2),
Register('vr30_8_13', 1, 0x43e2),
Register('vr30_8_12', 1, 0x43e3),
Register('vr30_32_2', 4, 0x43e4),
Register('vr30_16_5', 2, 0x43e4),
Register('vr30_8_11', 1, 0x43e4),
Register('vr30_8_10', 1, 0x43e5),
Register('vr30_16_4', 2, 0x43e6),
Register('vr30_8_9', 1, 0x43e6),
Register('vr30_8_8', 1, 0x43e7),
Register('vr30_64_0', 8, 0x43e8),
Register('vr30_32_1', 4, 0x43e8),
Register('vr30_16_3', 2, 0x43e8),
Register('vr30_8_7', 1, 0x43e8),
Register('vr30_8_6', 1, 0x43e9),
Register('vr30_16_2', 2, 0x43ea),
Register('vr30_8_5', 1, 0x43ea),
Register('vr30_8_4', 1, 0x43eb),
Register('vr30_32_0', 4, 0x43ec),
Register('vr30_16_1', 2, 0x43ec),
Register('vr30_8_3', 1, 0x43ec),
Register('vr30_8_2', 1, 0x43ed),
Register('vr30_16_0', 2, 0x43ee),
Register('vr30_8_1', 1, 0x43ee),
Register('vr30_8_0', 1, 0x43ef),
Register('vs63', 16, 0x43f0),
Register('vr31_64_1', 8, 0x43f0),
Register('vr31_32_3', 4, 0x43f0),
Register('vr31_16_7', 2, 0x43f0),
Register('vr31_8_15', 1, 0x43f0),
Register('vr31_8_14', 1, 0x43f1),
Register('vr31_16_6', 2, 0x43f2),
Register('vr31_8_13', 1, 0x43f2),
Register('vr31_8_12', 1, 0x43f3),
Register('vr31_32_2', 4, 0x43f4),
Register('vr31_16_5', 2, 0x43f4),
Register('vr31_8_11', 1, 0x43f4),
Register('vr31_8_10', 1, 0x43f5),
Register('vr31_16_4', 2, 0x43f6),
Register('vr31_8_9', 1, 0x43f6),
Register('vr31_8_8', 1, 0x43f7),
Register('vr31_64_0', 8, 0x43f8),
Register('vr31_32_1', 4, 0x43f8),
Register('vr31_16_3', 2, 0x43f8),
Register('vr31_8_7', 1, 0x43f8),
Register('vr31_8_6', 1, 0x43f9),
Register('vr31_16_2', 2, 0x43fa),
Register('vr31_8_5', 1, 0x43fa),
Register('vr31_8_4', 1, 0x43fb),
Register('vr31_32_0', 4, 0x43fc),
Register('vr31_16_1', 2, 0x43fc),
Register('vr31_8_3', 1, 0x43fc),
Register('vr31_8_2', 1, 0x43fd),
Register('vr31_16_0', 2, 0x43fe),
Register('vr31_8_1', 1, 0x43fe),
Register('vr31_8_0', 1, 0x43ff),
Register('contextreg', 4, 0x6000),
Register('dcr000', 4, 0x7000),
Register('dcr001', 4, 0x7004),
Register('dcr002', 4, 0x7008),
Register('dcr003', 4, 0x700c),
Register('dcr004', 4, 0x7010),
Register('dcr005', 4, 0x7014),
Register('dcr006', 4, 0x7018),
Register('dcr007', 4, 0x701c),
Register('dcr008', 4, 0x7020),
Register('dcr009', 4, 0x7024),
Register('dcr00a', 4, 0x7028),
Register('dcr00b', 4, 0x702c),
Register('dcr00c', 4, 0x7030),
Register('dcr00d', 4, 0x7034),
Register('dcr00e', 4, 0x7038),
Register('dcr00f', 4, 0x703c),
Register('dcr010', 4, 0x7040),
Register('dcr011', 4, 0x7044),
Register('dcr012', 4, 0x7048),
Register('dcr013', 4, 0x704c),
Register('dcr014', 4, 0x7050),
Register('dcr015', 4, 0x7054),
Register('dcr016', 4, 0x7058),
Register('dcr017', 4, 0x705c),
Register('dcr018', 4, 0x7060),
Register('dcr019', 4, 0x7064),
Register('dcr01a', 4, 0x7068),
Register('dcr01b', 4, 0x706c),
Register('dcr01c', 4, 0x7070),
Register('dcr01d', 4, 0x7074),
Register('dcr01e', 4, 0x7078),
Register('dcr01f', 4, 0x707c),
Register('dcr020', 4, 0x7080),
Register('dcr021', 4, 0x7084),
Register('dcr022', 4, 0x7088),
Register('dcr023', 4, 0x708c),
Register('dcr024', 4, 0x7090),
Register('dcr025', 4, 0x7094),
Register('dcr026', 4, 0x7098),
Register('dcr027', 4, 0x709c),
Register('dcr028', 4, 0x70a0),
Register('dcr029', 4, 0x70a4),
Register('dcr02a', 4, 0x70a8),
Register('dcr02b', 4, 0x70ac),
Register('dcr02c', 4, 0x70b0),
Register('dcr02d', 4, 0x70b4),
Register('dcr02e', 4, 0x70b8),
Register('dcr02f', 4, 0x70bc),
Register('dcr030', 4, 0x70c0),
Register('dcr031', 4, 0x70c4),
Register('dcr032', 4, 0x70c8),
Register('dcr033', 4, 0x70cc),
Register('dcr034', 4, 0x70d0),
Register('dcr035', 4, 0x70d4),
Register('dcr036', 4, 0x70d8),
Register('dcr037', 4, 0x70dc),
Register('dcr038', 4, 0x70e0),
Register('dcr039', 4, 0x70e4),
Register('dcr03a', 4, 0x70e8),
Register('dcr03b', 4, 0x70ec),
Register('dcr03c', 4, 0x70f0),
Register('dcr03d', 4, 0x70f4),
Register('dcr03e', 4, 0x70f8),
Register('dcr03f', 4, 0x70fc),
Register('dcr040', 4, 0x7100),
Register('dcr041', 4, 0x7104),
Register('dcr042', 4, 0x7108),
Register('dcr043', 4, 0x710c),
Register('dcr044', 4, 0x7110),
Register('dcr045', 4, 0x7114),
Register('dcr046', 4, 0x7118),
Register('dcr047', 4, 0x711c),
Register('dcr048', 4, 0x7120),
Register('dcr049', 4, 0x7124),
Register('dcr04a', 4, 0x7128),
Register('dcr04b', 4, 0x712c),
Register('dcr04c', 4, 0x7130),
Register('dcr04d', 4, 0x7134),
Register('dcr04e', 4, 0x7138),
Register('dcr04f', 4, 0x713c),
Register('dcr050', 4, 0x7140),
Register('dcr051', 4, 0x7144),
Register('dcr052', 4, 0x7148),
Register('dcr053', 4, 0x714c),
Register('dcr054', 4, 0x7150),
Register('dcr055', 4, 0x7154),
Register('dcr056', 4, 0x7158),
Register('dcr057', 4, 0x715c),
Register('dcr058', 4, 0x7160),
Register('dcr059', 4, 0x7164),
Register('dcr05a', 4, 0x7168),
Register('dcr05b', 4, 0x716c),
Register('dcr05c', 4, 0x7170),
Register('dcr05d', 4, 0x7174),
Register('dcr05e', 4, 0x7178),
Register('dcr05f', 4, 0x717c),
Register('dcr060', 4, 0x7180),
Register('dcr061', 4, 0x7184),
Register('dcr062', 4, 0x7188),
Register('dcr063', 4, 0x718c),
Register('dcr064', 4, 0x7190),
Register('dcr065', 4, 0x7194),
Register('dcr066', 4, 0x7198),
Register('dcr067', 4, 0x719c),
Register('dcr068', 4, 0x71a0),
Register('dcr069', 4, 0x71a4),
Register('dcr06a', 4, 0x71a8),
Register('dcr06b', 4, 0x71ac),
Register('dcr06c', 4, 0x71b0),
Register('dcr06d', 4, 0x71b4),
Register('dcr06e', 4, 0x71b8),
Register('dcr06f', 4, 0x71bc),
Register('dcr070', 4, 0x71c0),
Register('dcr071', 4, 0x71c4),
Register('dcr072', 4, 0x71c8),
Register('dcr073', 4, 0x71cc),
Register('dcr074', 4, 0x71d0),
Register('dcr075', 4, 0x71d4),
Register('dcr076', 4, 0x71d8),
Register('dcr077', 4, 0x71dc),
Register('dcr078', 4, 0x71e0),
Register('dcr079', 4, 0x71e4),
Register('dcr07a', 4, 0x71e8),
Register('dcr07b', 4, 0x71ec),
Register('dcr07c', 4, 0x71f0),
Register('dcr07d', 4, 0x71f4),
Register('dcr07e', 4, 0x71f8),
Register('dcr07f', 4, 0x71fc),
Register('dcr080', 4, 0x7200),
Register('dcr081', 4, 0x7204),
Register('dcr082', 4, 0x7208),
Register('dcr083', 4, 0x720c),
Register('dcr084', 4, 0x7210),
Register('dcr085', 4, 0x7214),
Register('dcr086', 4, 0x7218),
Register('dcr087', 4, 0x721c),
Register('dcr088', 4, 0x7220),
Register('dcr089', 4, 0x7224),
Register('dcr08a', 4, 0x7228),
Register('dcr08b', 4, 0x722c),
Register('dcr08c', 4, 0x7230),
Register('dcr08d', 4, 0x7234),
Register('dcr08e', 4, 0x7238),
Register('dcr08f', 4, 0x723c),
Register('dcr090', 4, 0x7240),
Register('dcr091', 4, 0x7244),
Register('dcr092', 4, 0x7248),
Register('dcr093', 4, 0x724c),
Register('dcr094', 4, 0x7250),
Register('dcr095', 4, 0x7254),
Register('dcr096', 4, 0x7258),
Register('dcr097', 4, 0x725c),
Register('dcr098', 4, 0x7260),
Register('dcr099', 4, 0x7264),
Register('dcr09a', 4, 0x7268),
Register('dcr09b', 4, 0x726c),
Register('dcr09c', 4, 0x7270),
Register('dcr09d', 4, 0x7274),
Register('dcr09e', 4, 0x7278),
Register('dcr09f', 4, 0x727c),
Register('dcr0a0', 4, 0x7280),
Register('dcr0a1', 4, 0x7284),
Register('dcr0a2', 4, 0x7288),
Register('dcr0a3', 4, 0x728c),
Register('dcr0a4', 4, 0x7290),
Register('dcr0a5', 4, 0x7294),
Register('dcr0a6', 4, 0x7298),
Register('dcr0a7', 4, 0x729c),
Register('dcr0a8', 4, 0x72a0),
Register('dcr0a9', 4, 0x72a4),
Register('dcr0aa', 4, 0x72a8),
Register('dcr0ab', 4, 0x72ac),
Register('dcr0ac', 4, 0x72b0),
Register('dcr0ad', 4, 0x72b4),
Register('dcr0ae', 4, 0x72b8),
Register('dcr0af', 4, 0x72bc),
Register('dcr0b0', 4, 0x72c0),
Register('dcr0b1', 4, 0x72c4),
Register('dcr0b2', 4, 0x72c8),
Register('dcr0b3', 4, 0x72cc),
Register('dcr0b4', 4, 0x72d0),
Register('dcr0b5', 4, 0x72d4),
Register('dcr0b6', 4, 0x72d8),
Register('dcr0b7', 4, 0x72dc),
Register('dcr0b8', 4, 0x72e0),
Register('dcr0b9', 4, 0x72e4),
Register('dcr0ba', 4, 0x72e8),
Register('dcr0bb', 4, 0x72ec),
Register('dcr0bc', 4, 0x72f0),
Register('dcr0bd', 4, 0x72f4),
Register('dcr0be', 4, 0x72f8),
Register('dcr0bf', 4, 0x72fc),
Register('dcr0c0', 4, 0x7300),
Register('dcr0c1', 4, 0x7304),
Register('dcr0c2', 4, 0x7308),
Register('dcr0c3', 4, 0x730c),
Register('dcr0c4', 4, 0x7310),
Register('dcr0c5', 4, 0x7314),
Register('dcr0c6', 4, 0x7318),
Register('dcr0c7', 4, 0x731c),
Register('dcr0c8', 4, 0x7320),
Register('dcr0c9', 4, 0x7324),
Register('dcr0ca', 4, 0x7328),
Register('dcr0cb', 4, 0x732c),
Register('dcr0cc', 4, 0x7330),
Register('dcr0cd', 4, 0x7334),
Register('dcr0ce', 4, 0x7338),
Register('dcr0cf', 4, 0x733c),
Register('dcr0d0', 4, 0x7340),
Register('dcr0d1', 4, 0x7344),
Register('dcr0d2', 4, 0x7348),
Register('dcr0d3', 4, 0x734c),
Register('dcr0d4', 4, 0x7350),
Register('dcr0d5', 4, 0x7354),
Register('dcr0d6', 4, 0x7358),
Register('dcr0d7', 4, 0x735c),
Register('dcr0d8', 4, 0x7360),
Register('dcr0d9', 4, 0x7364),
Register('dcr0da', 4, 0x7368),
Register('dcr0db', 4, 0x736c),
Register('dcr0dc', 4, 0x7370),
Register('dcr0dd', 4, 0x7374),
Register('dcr0de', 4, 0x7378),
Register('dcr0df', 4, 0x737c),
Register('dcr0e0', 4, 0x7380),
Register('dcr0e1', 4, 0x7384),
Register('dcr0e2', 4, 0x7388),
Register('dcr0e3', 4, 0x738c),
Register('dcr0e4', 4, 0x7390),
Register('dcr0e5', 4, 0x7394),
Register('dcr0e6', 4, 0x7398),
Register('dcr0e7', 4, 0x739c),
Register('dcr0e8', 4, 0x73a0),
Register('dcr0e9', 4, 0x73a4),
Register('dcr0ea', 4, 0x73a8),
Register('dcr0eb', 4, 0x73ac),
Register('dcr0ec', 4, 0x73b0),
Register('dcr0ed', 4, 0x73b4),
Register('dcr0ee', 4, 0x73b8),
Register('dcr0ef', 4, 0x73bc),
Register('dcr0f0', 4, 0x73c0),
Register('dcr0f1', 4, 0x73c4),
Register('dcr0f2', 4, 0x73c8),
Register('dcr0f3', 4, 0x73cc),
Register('dcr0f4', 4, 0x73d0),
Register('dcr0f5', 4, 0x73d4),
Register('dcr0f6', 4, 0x73d8),
Register('dcr0f7', 4, 0x73dc),
Register('dcr0f8', 4, 0x73e0),
Register('dcr0f9', 4, 0x73e4),
Register('dcr0fa', 4, 0x73e8),
Register('dcr0fb', 4, 0x73ec),
Register('dcr0fc', 4, 0x73f0),
Register('dcr0fd', 4, 0x73f4),
Register('dcr0fe', 4, 0x73f8),
Register('dcr0ff', 4, 0x73fc),
Register('dcr100', 4, 0x7400),
Register('dcr101', 4, 0x7404),
Register('dcr102', 4, 0x7408),
Register('dcr103', 4, 0x740c),
Register('dcr104', 4, 0x7410),
Register('dcr105', 4, 0x7414),
Register('dcr106', 4, 0x7418),
Register('dcr107', 4, 0x741c),
Register('dcr108', 4, 0x7420),
Register('dcr109', 4, 0x7424),
Register('dcr10a', 4, 0x7428),
Register('dcr10b', 4, 0x742c),
Register('dcr10c', 4, 0x7430),
Register('dcr10d', 4, 0x7434),
Register('dcr10e', 4, 0x7438),
Register('dcr10f', 4, 0x743c),
Register('dcr110', 4, 0x7440),
Register('dcr111', 4, 0x7444),
Register('dcr112', 4, 0x7448),
Register('dcr113', 4, 0x744c),
Register('dcr114', 4, 0x7450),
Register('dcr115', 4, 0x7454),
Register('dcr116', 4, 0x7458),
Register('dcr117', 4, 0x745c),
Register('dcr118', 4, 0x7460),
Register('dcr119', 4, 0x7464),
Register('dcr11a', 4, 0x7468),
Register('dcr11b', 4, 0x746c),
Register('dcr11c', 4, 0x7470),
Register('dcr11d', 4, 0x7474),
Register('dcr11e', 4, 0x7478),
Register('dcr11f', 4, 0x747c),
Register('dcr120', 4, 0x7480),
Register('dcr121', 4, 0x7484),
Register('dcr122', 4, 0x7488),
Register('dcr123', 4, 0x748c),
Register('dcr124', 4, 0x7490),
Register('dcr125', 4, 0x7494),
Register('dcr126', 4, 0x7498),
Register('dcr127', 4, 0x749c),
Register('dcr128', 4, 0x74a0),
Register('dcr129', 4, 0x74a4),
Register('dcr12a', 4, 0x74a8),
Register('dcr12b', 4, 0x74ac),
Register('dcr12c', 4, 0x74b0),
Register('dcr12d', 4, 0x74b4),
Register('dcr12e', 4, 0x74b8),
Register('dcr12f', 4, 0x74bc),
Register('dcr130', 4, 0x74c0),
Register('dcr131', 4, 0x74c4),
Register('dcr132', 4, 0x74c8),
Register('dcr133', 4, 0x74cc),
Register('dcr134', 4, 0x74d0),
Register('dcr135', 4, 0x74d4),
Register('dcr136', 4, 0x74d8),
Register('dcr137', 4, 0x74dc),
Register('dcr138', 4, 0x74e0),
Register('dcr139', 4, 0x74e4),
Register('dcr13a', 4, 0x74e8),
Register('dcr13b', 4, 0x74ec),
Register('dcr13c', 4, 0x74f0),
Register('dcr13d', 4, 0x74f4),
Register('dcr13e', 4, 0x74f8),
Register('dcr13f', 4, 0x74fc),
Register('dcr140', 4, 0x7500),
Register('dcr141', 4, 0x7504),
Register('dcr142', 4, 0x7508),
Register('dcr143', 4, 0x750c),
Register('dcr144', 4, 0x7510),
Register('dcr145', 4, 0x7514),
Register('dcr146', 4, 0x7518),
Register('dcr147', 4, 0x751c),
Register('dcr148', 4, 0x7520),
Register('dcr149', 4, 0x7524),
Register('dcr14a', 4, 0x7528),
Register('dcr14b', 4, 0x752c),
Register('dcr14c', 4, 0x7530),
Register('dcr14d', 4, 0x7534),
Register('dcr14e', 4, 0x7538),
Register('dcr14f', 4, 0x753c),
Register('dcr150', 4, 0x7540),
Register('dcr151', 4, 0x7544),
Register('dcr152', 4, 0x7548),
Register('dcr153', 4, 0x754c),
Register('dcr154', 4, 0x7550),
Register('dcr155', 4, 0x7554),
Register('dcr156', 4, 0x7558),
Register('dcr157', 4, 0x755c),
Register('dcr158', 4, 0x7560),
Register('dcr159', 4, 0x7564),
Register('dcr15a', 4, 0x7568),
Register('dcr15b', 4, 0x756c),
Register('dcr15c', 4, 0x7570),
Register('dcr15d', 4, 0x7574),
Register('dcr15e', 4, 0x7578),
Register('dcr15f', 4, 0x757c),
Register('dcr160', 4, 0x7580),
Register('dcr161', 4, 0x7584),
Register('dcr162', 4, 0x7588),
Register('dcr163', 4, 0x758c),
Register('dcr164', 4, 0x7590),
Register('dcr165', 4, 0x7594),
Register('dcr166', 4, 0x7598),
Register('dcr167', 4, 0x759c),
Register('dcr168', 4, 0x75a0),
Register('dcr169', 4, 0x75a4),
Register('dcr16a', 4, 0x75a8),
Register('dcr16b', 4, 0x75ac),
Register('dcr16c', 4, 0x75b0),
Register('dcr16d', 4, 0x75b4),
Register('dcr16e', 4, 0x75b8),
Register('dcr16f', 4, 0x75bc),
Register('dcr170', 4, 0x75c0),
Register('dcr171', 4, 0x75c4),
Register('dcr172', 4, 0x75c8),
Register('dcr173', 4, 0x75cc),
Register('dcr174', 4, 0x75d0),
Register('dcr175', 4, 0x75d4),
Register('dcr176', 4, 0x75d8),
Register('dcr177', 4, 0x75dc),
Register('dcr178', 4, 0x75e0),
Register('dcr179', 4, 0x75e4),
Register('dcr17a', 4, 0x75e8),
Register('dcr17b', 4, 0x75ec),
Register('dcr17c', 4, 0x75f0),
Register('dcr17d', 4, 0x75f4),
Register('dcr17e', 4, 0x75f8),
Register('dcr17f', 4, 0x75fc),
Register('dcr180', 4, 0x7600),
Register('dcr181', 4, 0x7604),
Register('dcr182', 4, 0x7608),
Register('dcr183', 4, 0x760c),
Register('dcr184', 4, 0x7610),
Register('dcr185', 4, 0x7614),
Register('dcr186', 4, 0x7618),
Register('dcr187', 4, 0x761c),
Register('dcr188', 4, 0x7620),
Register('dcr189', 4, 0x7624),
Register('dcr18a', 4, 0x7628),
Register('dcr18b', 4, 0x762c),
Register('dcr18c', 4, 0x7630),
Register('dcr18d', 4, 0x7634),
Register('dcr18e', 4, 0x7638),
Register('dcr18f', 4, 0x763c),
Register('dcr190', 4, 0x7640),
Register('dcr191', 4, 0x7644),
Register('dcr192', 4, 0x7648),
Register('dcr193', 4, 0x764c),
Register('dcr194', 4, 0x7650),
Register('dcr195', 4, 0x7654),
Register('dcr196', 4, 0x7658),
Register('dcr197', 4, 0x765c),
Register('dcr198', 4, 0x7660),
Register('dcr199', 4, 0x7664),
Register('dcr19a', 4, 0x7668),
Register('dcr19b', 4, 0x766c),
Register('dcr19c', 4, 0x7670),
Register('dcr19d', 4, 0x7674),
Register('dcr19e', 4, 0x7678),
Register('dcr19f', 4, 0x767c),
Register('dcr1a0', 4, 0x7680),
Register('dcr1a1', 4, 0x7684),
Register('dcr1a2', 4, 0x7688),
Register('dcr1a3', 4, 0x768c),
Register('dcr1a4', 4, 0x7690),
Register('dcr1a5', 4, 0x7694),
Register('dcr1a6', 4, 0x7698),
Register('dcr1a7', 4, 0x769c),
Register('dcr1a8', 4, 0x76a0),
Register('dcr1a9', 4, 0x76a4),
Register('dcr1aa', 4, 0x76a8),
Register('dcr1ab', 4, 0x76ac),
Register('dcr1ac', 4, 0x76b0),
Register('dcr1ad', 4, 0x76b4),
Register('dcr1ae', 4, 0x76b8),
Register('dcr1af', 4, 0x76bc),
Register('dcr1b0', 4, 0x76c0),
Register('dcr1b1', 4, 0x76c4),
Register('dcr1b2', 4, 0x76c8),
Register('dcr1b3', 4, 0x76cc),
Register('dcr1b4', 4, 0x76d0),
Register('dcr1b5', 4, 0x76d4),
Register('dcr1b6', 4, 0x76d8),
Register('dcr1b7', 4, 0x76dc),
Register('dcr1b8', 4, 0x76e0),
Register('dcr1b9', 4, 0x76e4),
Register('dcr1ba', 4, 0x76e8),
Register('dcr1bb', 4, 0x76ec),
Register('dcr1bc', 4, 0x76f0),
Register('dcr1bd', 4, 0x76f4),
Register('dcr1be', 4, 0x76f8),
Register('dcr1bf', 4, 0x76fc),
Register('dcr1c0', 4, 0x7700),
Register('dcr1c1', 4, 0x7704),
Register('dcr1c2', 4, 0x7708),
Register('dcr1c3', 4, 0x770c),
Register('dcr1c4', 4, 0x7710),
Register('dcr1c5', 4, 0x7714),
Register('dcr1c6', 4, 0x7718),
Register('dcr1c7', 4, 0x771c),
Register('dcr1c8', 4, 0x7720),
Register('dcr1c9', 4, 0x7724),
Register('dcr1ca', 4, 0x7728),
Register('dcr1cb', 4, 0x772c),
Register('dcr1cc', 4, 0x7730),
Register('dcr1cd', 4, 0x7734),
Register('dcr1ce', 4, 0x7738),
Register('dcr1cf', 4, 0x773c),
Register('dcr1d0', 4, 0x7740),
Register('dcr1d1', 4, 0x7744),
Register('dcr1d2', 4, 0x7748),
Register('dcr1d3', 4, 0x774c),
Register('dcr1d4', 4, 0x7750),
Register('dcr1d5', 4, 0x7754),
Register('dcr1d6', 4, 0x7758),
Register('dcr1d7', 4, 0x775c),
Register('dcr1d8', 4, 0x7760),
Register('dcr1d9', 4, 0x7764),
Register('dcr1da', 4, 0x7768),
Register('dcr1db', 4, 0x776c),
Register('dcr1dc', 4, 0x7770),
Register('dcr1dd', 4, 0x7774),
Register('dcr1de', 4, 0x7778),
Register('dcr1df', 4, 0x777c),
Register('dcr1e0', 4, 0x7780),
Register('dcr1e1', 4, 0x7784),
Register('dcr1e2', 4, 0x7788),
Register('dcr1e3', 4, 0x778c),
Register('dcr1e4', 4, 0x7790),
Register('dcr1e5', 4, 0x7794),
Register('dcr1e6', 4, 0x7798),
Register('dcr1e7', 4, 0x779c),
Register('dcr1e8', 4, 0x77a0),
Register('dcr1e9', 4, 0x77a4),
Register('dcr1ea', 4, 0x77a8),
Register('dcr1eb', 4, 0x77ac),
Register('dcr1ec', 4, 0x77b0),
Register('dcr1ed', 4, 0x77b4),
Register('dcr1ee', 4, 0x77b8),
Register('dcr1ef', 4, 0x77bc),
Register('dcr1f0', 4, 0x77c0),
Register('dcr1f1', 4, 0x77c4),
Register('dcr1f2', 4, 0x77c8),
Register('dcr1f3', 4, 0x77cc),
Register('dcr1f4', 4, 0x77d0),
Register('dcr1f5', 4, 0x77d4),
Register('dcr1f6', 4, 0x77d8),
Register('dcr1f7', 4, 0x77dc),
Register('dcr1f8', 4, 0x77e0),
Register('dcr1f9', 4, 0x77e4),
Register('dcr1fa', 4, 0x77e8),
Register('dcr1fb', 4, 0x77ec),
Register('dcr1fc', 4, 0x77f0),
Register('dcr1fd', 4, 0x77f4),
Register('dcr1fe', 4, 0x77f8),
Register('dcr1ff', 4, 0x77fc),
Register('dcr200', 4, 0x7800),
Register('dcr201', 4, 0x7804),
Register('dcr202', 4, 0x7808),
Register('dcr203', 4, 0x780c),
Register('dcr204', 4, 0x7810),
Register('dcr205', 4, 0x7814),
Register('dcr206', 4, 0x7818),
Register('dcr207', 4, 0x781c),
Register('dcr208', 4, 0x7820),
Register('dcr209', 4, 0x7824),
Register('dcr20a', 4, 0x7828),
Register('dcr20b', 4, 0x782c),
Register('dcr20c', 4, 0x7830),
Register('dcr20d', 4, 0x7834),
Register('dcr20e', 4, 0x7838),
Register('dcr20f', 4, 0x783c),
Register('dcr210', 4, 0x7840),
Register('dcr211', 4, 0x7844),
Register('dcr212', 4, 0x7848),
Register('dcr213', 4, 0x784c),
Register('dcr214', 4, 0x7850),
Register('dcr215', 4, 0x7854),
Register('dcr216', 4, 0x7858),
Register('dcr217', 4, 0x785c),
Register('dcr218', 4, 0x7860),
Register('dcr219', 4, 0x7864),
Register('dcr21a', 4, 0x7868),
Register('dcr21b', 4, 0x786c),
Register('dcr21c', 4, 0x7870),
Register('dcr21d', 4, 0x7874),
Register('dcr21e', 4, 0x7878),
Register('dcr21f', 4, 0x787c),
Register('dcr220', 4, 0x7880),
Register('dcr221', 4, 0x7884),
Register('dcr222', 4, 0x7888),
Register('dcr223', 4, 0x788c),
Register('dcr224', 4, 0x7890),
Register('dcr225', 4, 0x7894),
Register('dcr226', 4, 0x7898),
Register('dcr227', 4, 0x789c),
Register('dcr228', 4, 0x78a0),
Register('dcr229', 4, 0x78a4),
Register('dcr22a', 4, 0x78a8),
Register('dcr22b', 4, 0x78ac),
Register('dcr22c', 4, 0x78b0),
Register('dcr22d', 4, 0x78b4),
Register('dcr22e', 4, 0x78b8),
Register('dcr22f', 4, 0x78bc),
Register('dcr230', 4, 0x78c0),
Register('dcr231', 4, 0x78c4),
Register('dcr232', 4, 0x78c8),
Register('dcr233', 4, 0x78cc),
Register('dcr234', 4, 0x78d0),
Register('dcr235', 4, 0x78d4),
Register('dcr236', 4, 0x78d8),
Register('dcr237', 4, 0x78dc),
Register('dcr238', 4, 0x78e0),
Register('dcr239', 4, 0x78e4),
Register('dcr23a', 4, 0x78e8),
Register('dcr23b', 4, 0x78ec),
Register('dcr23c', 4, 0x78f0),
Register('dcr23d', 4, 0x78f4),
Register('dcr23e', 4, 0x78f8),
Register('dcr23f', 4, 0x78fc),
Register('dcr240', 4, 0x7900),
Register('dcr241', 4, 0x7904),
Register('dcr242', 4, 0x7908),
Register('dcr243', 4, 0x790c),
Register('dcr244', 4, 0x7910),
Register('dcr245', 4, 0x7914),
Register('dcr246', 4, 0x7918),
Register('dcr247', 4, 0x791c),
Register('dcr248', 4, 0x7920),
Register('dcr249', 4, 0x7924),
Register('dcr24a', 4, 0x7928),
Register('dcr24b', 4, 0x792c),
Register('dcr24c', 4, 0x7930),
Register('dcr24d', 4, 0x7934),
Register('dcr24e', 4, 0x7938),
Register('dcr24f', 4, 0x793c),
Register('dcr250', 4, 0x7940),
Register('dcr251', 4, 0x7944),
Register('dcr252', 4, 0x7948),
Register('dcr253', 4, 0x794c),
Register('dcr254', 4, 0x7950),
Register('dcr255', 4, 0x7954),
Register('dcr256', 4, 0x7958),
Register('dcr257', 4, 0x795c),
Register('dcr258', 4, 0x7960),
Register('dcr259', 4, 0x7964),
Register('dcr25a', 4, 0x7968),
Register('dcr25b', 4, 0x796c),
Register('dcr25c', 4, 0x7970),
Register('dcr25d', 4, 0x7974),
Register('dcr25e', 4, 0x7978),
Register('dcr25f', 4, 0x797c),
Register('dcr260', 4, 0x7980),
Register('dcr261', 4, 0x7984),
Register('dcr262', 4, 0x7988),
Register('dcr263', 4, 0x798c),
Register('dcr264', 4, 0x7990),
Register('dcr265', 4, 0x7994),
Register('dcr266', 4, 0x7998),
Register('dcr267', 4, 0x799c),
Register('dcr268', 4, 0x79a0),
Register('dcr269', 4, 0x79a4),
Register('dcr26a', 4, 0x79a8),
Register('dcr26b', 4, 0x79ac),
Register('dcr26c', 4, 0x79b0),
Register('dcr26d', 4, 0x79b4),
Register('dcr26e', 4, 0x79b8),
Register('dcr26f', 4, 0x79bc),
Register('dcr270', 4, 0x79c0),
Register('dcr271', 4, 0x79c4),
Register('dcr272', 4, 0x79c8),
Register('dcr273', 4, 0x79cc),
Register('dcr274', 4, 0x79d0),
Register('dcr275', 4, 0x79d4),
Register('dcr276', 4, 0x79d8),
Register('dcr277', 4, 0x79dc),
Register('dcr278', 4, 0x79e0),
Register('dcr279', 4, 0x79e4),
Register('dcr27a', 4, 0x79e8),
Register('dcr27b', 4, 0x79ec),
Register('dcr27c', 4, 0x79f0),
Register('dcr27d', 4, 0x79f4),
Register('dcr27e', 4, 0x79f8),
Register('dcr27f', 4, 0x79fc),
Register('dcr280', 4, 0x7a00),
Register('dcr281', 4, 0x7a04),
Register('dcr282', 4, 0x7a08),
Register('dcr283', 4, 0x7a0c),
Register('dcr284', 4, 0x7a10),
Register('dcr285', 4, 0x7a14),
Register('dcr286', 4, 0x7a18),
Register('dcr287', 4, 0x7a1c),
Register('dcr288', 4, 0x7a20),
Register('dcr289', 4, 0x7a24),
Register('dcr28a', 4, 0x7a28),
Register('dcr28b', 4, 0x7a2c),
Register('dcr28c', 4, 0x7a30),
Register('dcr28d', 4, 0x7a34),
Register('dcr28e', 4, 0x7a38),
Register('dcr28f', 4, 0x7a3c),
Register('dcr290', 4, 0x7a40),
Register('dcr291', 4, 0x7a44),
Register('dcr292', 4, 0x7a48),
Register('dcr293', 4, 0x7a4c),
Register('dcr294', 4, 0x7a50),
Register('dcr295', 4, 0x7a54),
Register('dcr296', 4, 0x7a58),
Register('dcr297', 4, 0x7a5c),
Register('dcr298', 4, 0x7a60),
Register('dcr299', 4, 0x7a64),
Register('dcr29a', 4, 0x7a68),
Register('dcr29b', 4, 0x7a6c),
Register('dcr29c', 4, 0x7a70),
Register('dcr29d', 4, 0x7a74),
Register('dcr29e', 4, 0x7a78),
Register('dcr29f', 4, 0x7a7c),
Register('dcr2a0', 4, 0x7a80),
Register('dcr2a1', 4, 0x7a84),
Register('dcr2a2', 4, 0x7a88),
Register('dcr2a3', 4, 0x7a8c),
Register('dcr2a4', 4, 0x7a90),
Register('dcr2a5', 4, 0x7a94),
Register('dcr2a6', 4, 0x7a98),
Register('dcr2a7', 4, 0x7a9c),
Register('dcr2a8', 4, 0x7aa0),
Register('dcr2a9', 4, 0x7aa4),
Register('dcr2aa', 4, 0x7aa8),
Register('dcr2ab', 4, 0x7aac),
Register('dcr2ac', 4, 0x7ab0),
Register('dcr2ad', 4, 0x7ab4),
Register('dcr2ae', 4, 0x7ab8),
Register('dcr2af', 4, 0x7abc),
Register('dcr2b0', 4, 0x7ac0),
Register('dcr2b1', 4, 0x7ac4),
Register('dcr2b2', 4, 0x7ac8),
Register('dcr2b3', 4, 0x7acc),
Register('dcr2b4', 4, 0x7ad0),
Register('dcr2b5', 4, 0x7ad4),
Register('dcr2b6', 4, 0x7ad8),
Register('dcr2b7', 4, 0x7adc),
Register('dcr2b8', 4, 0x7ae0),
Register('dcr2b9', 4, 0x7ae4),
Register('dcr2ba', 4, 0x7ae8),
Register('dcr2bb', 4, 0x7aec),
Register('dcr2bc', 4, 0x7af0),
Register('dcr2bd', 4, 0x7af4),
Register('dcr2be', 4, 0x7af8),
Register('dcr2bf', 4, 0x7afc),
Register('dcr2c0', 4, 0x7b00),
Register('dcr2c1', 4, 0x7b04),
Register('dcr2c2', 4, 0x7b08),
Register('dcr2c3', 4, 0x7b0c),
Register('dcr2c4', 4, 0x7b10),
Register('dcr2c5', 4, 0x7b14),
Register('dcr2c6', 4, 0x7b18),
Register('dcr2c7', 4, 0x7b1c),
Register('dcr2c8', 4, 0x7b20),
Register('dcr2c9', 4, 0x7b24),
Register('dcr2ca', 4, 0x7b28),
Register('dcr2cb', 4, 0x7b2c),
Register('dcr2cc', 4, 0x7b30),
Register('dcr2cd', 4, 0x7b34),
Register('dcr2ce', 4, 0x7b38),
Register('dcr2cf', 4, 0x7b3c),
Register('dcr2d0', 4, 0x7b40),
Register('dcr2d1', 4, 0x7b44),
Register('dcr2d2', 4, 0x7b48),
Register('dcr2d3', 4, 0x7b4c),
Register('dcr2d4', 4, 0x7b50),
Register('dcr2d5', 4, 0x7b54),
Register('dcr2d6', 4, 0x7b58),
Register('dcr2d7', 4, 0x7b5c),
Register('dcr2d8', 4, 0x7b60),
Register('dcr2d9', 4, 0x7b64),
Register('dcr2da', 4, 0x7b68),
Register('dcr2db', 4, 0x7b6c),
Register('dcr2dc', 4, 0x7b70),
Register('dcr2dd', 4, 0x7b74),
Register('dcr2de', 4, 0x7b78),
Register('dcr2df', 4, 0x7b7c),
Register('dcr2e0', 4, 0x7b80),
Register('dcr2e1', 4, 0x7b84),
Register('dcr2e2', 4, 0x7b88),
Register('dcr2e3', 4, 0x7b8c),
Register('dcr2e4', 4, 0x7b90),
Register('dcr2e5', 4, 0x7b94),
Register('dcr2e6', 4, 0x7b98),
Register('dcr2e7', 4, 0x7b9c),
Register('dcr2e8', 4, 0x7ba0),
Register('dcr2e9', 4, 0x7ba4),
Register('dcr2ea', 4, 0x7ba8),
Register('dcr2eb', 4, 0x7bac),
Register('dcr2ec', 4, 0x7bb0),
Register('dcr2ed', 4, 0x7bb4),
Register('dcr2ee', 4, 0x7bb8),
Register('dcr2ef', 4, 0x7bbc),
Register('dcr2f0', 4, 0x7bc0),
Register('dcr2f1', 4, 0x7bc4),
Register('dcr2f2', 4, 0x7bc8),
Register('dcr2f3', 4, 0x7bcc),
Register('dcr2f4', 4, 0x7bd0),
Register('dcr2f5', 4, 0x7bd4),
Register('dcr2f6', 4, 0x7bd8),
Register('dcr2f7', 4, 0x7bdc),
Register('dcr2f8', 4, 0x7be0),
Register('dcr2f9', 4, 0x7be4),
Register('dcr2fa', 4, 0x7be8),
Register('dcr2fb', 4, 0x7bec),
Register('dcr2fc', 4, 0x7bf0),
Register('dcr2fd', 4, 0x7bf4),
Register('dcr2fe', 4, 0x7bf8),
Register('dcr2ff', 4, 0x7bfc),
Register('dcr300', 4, 0x7c00),
Register('dcr301', 4, 0x7c04),
Register('dcr302', 4, 0x7c08),
Register('dcr303', 4, 0x7c0c),
Register('dcr304', 4, 0x7c10),
Register('dcr305', 4, 0x7c14),
Register('dcr306', 4, 0x7c18),
Register('dcr307', 4, 0x7c1c),
Register('dcr308', 4, 0x7c20),
Register('dcr309', 4, 0x7c24),
Register('dcr30a', 4, 0x7c28),
Register('dcr30b', 4, 0x7c2c),
Register('dcr30c', 4, 0x7c30),
Register('dcr30d', 4, 0x7c34),
Register('dcr30e', 4, 0x7c38),
Register('dcr30f', 4, 0x7c3c),
Register('dcr310', 4, 0x7c40),
Register('dcr311', 4, 0x7c44),
Register('dcr312', 4, 0x7c48),
Register('dcr313', 4, 0x7c4c),
Register('dcr314', 4, 0x7c50),
Register('dcr315', 4, 0x7c54),
Register('dcr316', 4, 0x7c58),
Register('dcr317', 4, 0x7c5c),
Register('dcr318', 4, 0x7c60),
Register('dcr319', 4, 0x7c64),
Register('dcr31a', 4, 0x7c68),
Register('dcr31b', 4, 0x7c6c),
Register('dcr31c', 4, 0x7c70),
Register('dcr31d', 4, 0x7c74),
Register('dcr31e', 4, 0x7c78),
Register('dcr31f', 4, 0x7c7c),
Register('dcr320', 4, 0x7c80),
Register('dcr321', 4, 0x7c84),
Register('dcr322', 4, 0x7c88),
Register('dcr323', 4, 0x7c8c),
Register('dcr324', 4, 0x7c90),
Register('dcr325', 4, 0x7c94),
Register('dcr326', 4, 0x7c98),
Register('dcr327', 4, 0x7c9c),
Register('dcr328', 4, 0x7ca0),
Register('dcr329', 4, 0x7ca4),
Register('dcr32a', 4, 0x7ca8),
Register('dcr32b', 4, 0x7cac),
Register('dcr32c', 4, 0x7cb0),
Register('dcr32d', 4, 0x7cb4),
Register('dcr32e', 4, 0x7cb8),
Register('dcr32f', 4, 0x7cbc),
Register('dcr330', 4, 0x7cc0),
Register('dcr331', 4, 0x7cc4),
Register('dcr332', 4, 0x7cc8),
Register('dcr333', 4, 0x7ccc),
Register('dcr334', 4, 0x7cd0),
Register('dcr335', 4, 0x7cd4),
Register('dcr336', 4, 0x7cd8),
Register('dcr337', 4, 0x7cdc),
Register('dcr338', 4, 0x7ce0),
Register('dcr339', 4, 0x7ce4),
Register('dcr33a', 4, 0x7ce8),
Register('dcr33b', 4, 0x7cec),
Register('dcr33c', 4, 0x7cf0),
Register('dcr33d', 4, 0x7cf4),
Register('dcr33e', 4, 0x7cf8),
Register('dcr33f', 4, 0x7cfc),
Register('dcr340', 4, 0x7d00),
Register('dcr341', 4, 0x7d04),
Register('dcr342', 4, 0x7d08),
Register('dcr343', 4, 0x7d0c),
Register('dcr344', 4, 0x7d10),
Register('dcr345', 4, 0x7d14),
Register('dcr346', 4, 0x7d18),
Register('dcr347', 4, 0x7d1c),
Register('dcr348', 4, 0x7d20),
Register('dcr349', 4, 0x7d24),
Register('dcr34a', 4, 0x7d28),
Register('dcr34b', 4, 0x7d2c),
Register('dcr34c', 4, 0x7d30),
Register('dcr34d', 4, 0x7d34),
Register('dcr34e', 4, 0x7d38),
Register('dcr34f', 4, 0x7d3c),
Register('dcr350', 4, 0x7d40),
Register('dcr351', 4, 0x7d44),
Register('dcr352', 4, 0x7d48),
Register('dcr353', 4, 0x7d4c),
Register('dcr354', 4, 0x7d50),
Register('dcr355', 4, 0x7d54),
Register('dcr356', 4, 0x7d58),
Register('dcr357', 4, 0x7d5c),
Register('dcr358', 4, 0x7d60),
Register('dcr359', 4, 0x7d64),
Register('dcr35a', 4, 0x7d68),
Register('dcr35b', 4, 0x7d6c),
Register('dcr35c', 4, 0x7d70),
Register('dcr35d', 4, 0x7d74),
Register('dcr35e', 4, 0x7d78),
Register('dcr35f', 4, 0x7d7c),
Register('dcr360', 4, 0x7d80),
Register('dcr361', 4, 0x7d84),
Register('dcr362', 4, 0x7d88),
Register('dcr363', 4, 0x7d8c),
Register('dcr364', 4, 0x7d90),
Register('dcr365', 4, 0x7d94),
Register('dcr366', 4, 0x7d98),
Register('dcr367', 4, 0x7d9c),
Register('dcr368', 4, 0x7da0),
Register('dcr369', 4, 0x7da4),
Register('dcr36a', 4, 0x7da8),
Register('dcr36b', 4, 0x7dac),
Register('dcr36c', 4, 0x7db0),
Register('dcr36d', 4, 0x7db4),
Register('dcr36e', 4, 0x7db8),
Register('dcr36f', 4, 0x7dbc),
Register('dcr370', 4, 0x7dc0),
Register('dcr371', 4, 0x7dc4),
Register('dcr372', 4, 0x7dc8),
Register('dcr373', 4, 0x7dcc),
Register('dcr374', 4, 0x7dd0),
Register('dcr375', 4, 0x7dd4),
Register('dcr376', 4, 0x7dd8),
Register('dcr377', 4, 0x7ddc),
Register('dcr378', 4, 0x7de0),
Register('dcr379', 4, 0x7de4),
Register('dcr37a', 4, 0x7de8),
Register('dcr37b', 4, 0x7dec),
Register('dcr37c', 4, 0x7df0),
Register('dcr37d', 4, 0x7df4),
Register('dcr37e', 4, 0x7df8),
Register('dcr37f', 4, 0x7dfc),
Register('dcr380', 4, 0x7e00),
Register('dcr381', 4, 0x7e04),
Register('dcr382', 4, 0x7e08),
Register('dcr383', 4, 0x7e0c),
Register('dcr384', 4, 0x7e10),
Register('dcr385', 4, 0x7e14),
Register('dcr386', 4, 0x7e18),
Register('dcr387', 4, 0x7e1c),
Register('dcr388', 4, 0x7e20),
Register('dcr389', 4, 0x7e24),
Register('dcr38a', 4, 0x7e28),
Register('dcr38b', 4, 0x7e2c),
Register('dcr38c', 4, 0x7e30),
Register('dcr38d', 4, 0x7e34),
Register('dcr38e', 4, 0x7e38),
Register('dcr38f', 4, 0x7e3c),
Register('dcr390', 4, 0x7e40),
Register('dcr391', 4, 0x7e44),
Register('dcr392', 4, 0x7e48),
Register('dcr393', 4, 0x7e4c),
Register('dcr394', 4, 0x7e50),
Register('dcr395', 4, 0x7e54),
Register('dcr396', 4, 0x7e58),
Register('dcr397', 4, 0x7e5c),
Register('dcr398', 4, 0x7e60),
Register('dcr399', 4, 0x7e64),
Register('dcr39a', 4, 0x7e68),
Register('dcr39b', 4, 0x7e6c),
Register('dcr39c', 4, 0x7e70),
Register('dcr39d', 4, 0x7e74),
Register('dcr39e', 4, 0x7e78),
Register('dcr39f', 4, 0x7e7c),
Register('dcr3a0', 4, 0x7e80),
Register('dcr3a1', 4, 0x7e84),
Register('dcr3a2', 4, 0x7e88),
Register('dcr3a3', 4, 0x7e8c),
Register('dcr3a4', 4, 0x7e90),
Register('dcr3a5', 4, 0x7e94),
Register('dcr3a6', 4, 0x7e98),
Register('dcr3a7', 4, 0x7e9c),
Register('dcr3a8', 4, 0x7ea0),
Register('dcr3a9', 4, 0x7ea4),
Register('dcr3aa', 4, 0x7ea8),
Register('dcr3ab', 4, 0x7eac),
Register('dcr3ac', 4, 0x7eb0),
Register('dcr3ad', 4, 0x7eb4),
Register('dcr3ae', 4, 0x7eb8),
Register('dcr3af', 4, 0x7ebc),
Register('dcr3b0', 4, 0x7ec0),
Register('dcr3b1', 4, 0x7ec4),
Register('dcr3b2', 4, 0x7ec8),
Register('dcr3b3', 4, 0x7ecc),
Register('dcr3b4', 4, 0x7ed0),
Register('dcr3b5', 4, 0x7ed4),
Register('dcr3b6', 4, 0x7ed8),
Register('dcr3b7', 4, 0x7edc),
Register('dcr3b8', 4, 0x7ee0),
Register('dcr3b9', 4, 0x7ee4),
Register('dcr3ba', 4, 0x7ee8),
Register('dcr3bb', 4, 0x7eec),
Register('dcr3bc', 4, 0x7ef0),
Register('dcr3bd', 4, 0x7ef4),
Register('dcr3be', 4, 0x7ef8),
Register('dcr3bf', 4, 0x7efc),
Register('dcr3c0', 4, 0x7f00),
Register('dcr3c1', 4, 0x7f04),
Register('dcr3c2', 4, 0x7f08),
Register('dcr3c3', 4, 0x7f0c),
Register('dcr3c4', 4, 0x7f10),
Register('dcr3c5', 4, 0x7f14),
Register('dcr3c6', 4, 0x7f18),
Register('dcr3c7', 4, 0x7f1c),
Register('dcr3c8', 4, 0x7f20),
Register('dcr3c9', 4, 0x7f24),
Register('dcr3ca', 4, 0x7f28),
Register('dcr3cb', 4, 0x7f2c),
Register('dcr3cc', 4, 0x7f30),
Register('dcr3cd', 4, 0x7f34),
Register('dcr3ce', 4, 0x7f38),
Register('dcr3cf', 4, 0x7f3c),
Register('dcr3d0', 4, 0x7f40),
Register('dcr3d1', 4, 0x7f44),
Register('dcr3d2', 4, 0x7f48),
Register('dcr3d3', 4, 0x7f4c),
Register('dcr3d4', 4, 0x7f50),
Register('dcr3d5', 4, 0x7f54),
Register('dcr3d6', 4, 0x7f58),
Register('dcr3d7', 4, 0x7f5c),
Register('dcr3d8', 4, 0x7f60),
Register('dcr3d9', 4, 0x7f64),
Register('dcr3da', 4, 0x7f68),
Register('dcr3db', 4, 0x7f6c),
Register('dcr3dc', 4, 0x7f70),
Register('dcr3dd', 4, 0x7f74),
Register('dcr3de', 4, 0x7f78),
Register('dcr3df', 4, 0x7f7c),
Register('dcr3e0', 4, 0x7f80),
Register('dcr3e1', 4, 0x7f84),
Register('dcr3e2', 4, 0x7f88),
Register('dcr3e3', 4, 0x7f8c),
Register('dcr3e4', 4, 0x7f90),
Register('dcr3e5', 4, 0x7f94),
Register('dcr3e6', 4, 0x7f98),
Register('dcr3e7', 4, 0x7f9c),
Register('dcr3e8', 4, 0x7fa0),
Register('dcr3e9', 4, 0x7fa4),
Register('dcr3ea', 4, 0x7fa8),
Register('dcr3eb', 4, 0x7fac),
Register('dcr3ec', 4, 0x7fb0),
Register('dcr3ed', 4, 0x7fb4),
Register('dcr3ee', 4, 0x7fb8),
Register('dcr3ef', 4, 0x7fbc),
Register('dcr3f0', 4, 0x7fc0),
Register('dcr3f1', 4, 0x7fc4),
Register('dcr3f2', 4, 0x7fc8),
Register('dcr3f3', 4, 0x7fcc),
Register('dcr3f4', 4, 0x7fd0),
Register('dcr3f5', 4, 0x7fd4),
Register('dcr3f6', 4, 0x7fd8),
Register('dcr3f7', 4, 0x7fdc),
Register('dcr3f8', 4, 0x7fe0),
Register('dcr3f9', 4, 0x7fe4),
Register('dcr3fa', 4, 0x7fe8),
Register('dcr3fb', 4, 0x7fec),
Register('dcr3fc', 4, 0x7ff0),
Register('dcr3fd', 4, 0x7ff4),
Register('dcr3fe', 4, 0x7ff8),
Register('dcr3ff', 4, 0x7ffc),
Register('acc', 8, 0x10000)
]
register_arch(['powerpc:le:32:quicc'], 32, Endness.LE, ArchPcode_PowerPC_LE_32_QUICC)
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(['"""dcr3f2"""', '(4)', '(32712)'], {}), "('dcr3f2', 4, 32712)\n", (126803, 126823), False, 'from archinfo.arch import register_arch, Endness, Register\n'), ((126834, 126862), 'archinfo.arch.Register', 'Register', (['"""dcr3f3"""', '(4)', '(32716)'], {}), "('dcr3f3', 4, 32716)\n", (126842, 126862), False, 'from archinfo.arch import register_arch, Endness, Register\n'), ((126873, 126901), 'archinfo.arch.Register', 'Register', (['"""dcr3f4"""', '(4)', '(32720)'], {}), "('dcr3f4', 4, 32720)\n", (126881, 126901), False, 'from archinfo.arch import register_arch, Endness, Register\n'), ((126912, 126940), 'archinfo.arch.Register', 'Register', (['"""dcr3f5"""', '(4)', '(32724)'], {}), "('dcr3f5', 4, 32724)\n", (126920, 126940), False, 'from archinfo.arch import register_arch, Endness, Register\n'), ((126951, 126979), 'archinfo.arch.Register', 'Register', (['"""dcr3f6"""', '(4)', '(32728)'], {}), "('dcr3f6', 4, 32728)\n", (126959, 126979), False, 'from archinfo.arch import register_arch, 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'archinfo.arch.Register', 'Register', (['"""acc"""', '(8)', '(65536)'], {}), "('acc', 8, 65536)\n", (127349, 127366), False, 'from archinfo.arch import register_arch, Endness, Register\n')] |
sieben/makesense | makesense/graph.py | 485e71903bcc9446482f21bb5d0c7a392ca1efca | # -*- coding: utf-8 -*-
import json
import pdb
import os
from os.path import join as pj
import networkx as nx
import pandas as pd
from networkx.readwrite.json_graph import node_link_data
def chain():
g = nx.Graph()
# Horizontal
for i in range(11, 15):
g.add_edge(i, i + 1)
for i in range(7, 10):
g.add_edge(i, i + 1)
for i in range(4, 6):
g.add_edge(i, i + 1)
for i in range(2, 3):
g.add_edge(i, i + 1)
g.add_node(1)
# Trans height
g.add_edge(1, 2)
g.add_edge(1, 3)
g.add_edge(2, 4)
g.add_edge(2, 5)
g.add_edge(3, 5)
g.add_edge(3, 6)
g.add_edge(4, 7)
g.add_edge(4, 8)
g.add_edge(5, 8)
g.add_edge(5, 9)
g.add_edge(6, 9)
g.add_edge(6, 10)
g.add_edge(7, 11)
g.add_edge(7, 12)
g.add_edge(8, 12)
g.add_edge(8, 13)
g.add_edge(9, 13)
g.add_edge(9, 14)
g.add_edge(10, 14)
g.add_edge(10, 15)
def tree():
with open("graph_radio.json", "w") as f:
f.write(json_graph.dumps(g,sort_keys=True,
indent=4, separators=(',', ': ') ))
# Drawing
pos = nx.spectral_layout(g)
nx.draw(g, pos, node_color="g")
nx.draw_networkx_nodes(g, pos, nodelist=[1], node_color="b")
plt.savefig("topology_tree.pdf", format="pdf")
plt.show()
def plot_graph_chain(folder):
g = nx.DiGraph()
N = 7
for i in range(1, N):
g.add_edge(i + 1, i)
g.add_node(1, root=True)
with open("radio_tree.json", "w") as f:
f.write(json_graph.dumps(g, sort_keys=True,
indent=4, separators=(',', ': ')))
pos = nx.circular_layout(g)
nx.draw(g, pos=pos)
nx.draw_networkx_nodes(g, pos, node_color='g')
nx.draw_networkx_nodes(g, pos, nodelist=[1], node_color='b')
nx.draw_networkx_edges(g, pos, edge_color="r", arrows=True)
plt.savefig(pj(folder, "topology_chain.pdf"), format="pdf")
def flower():
g = wheel_graph(7)
g.add_edge(6, 1)
g.add_edge(7, 6)
g.add_edge(8, 7)
with open("radio_graph.json", "w") as f:
f.write(json_graph.dumps(g, sort_keys=True,
indent=4, separators=(',', ': ')))
pos = nx.spring_layout(g)
nx.draw(g, pos=pos)
nx.draw_networkx_nodes(g,pos,
node_color='g')
nx.draw_networkx_nodes(g,pos,
nodelist=[8],
node_color='b')
#nx.draw_networkx_edges(g, pos, edge_color="r", arrows=True)
plt.savefig("topology_fleur.pdf", format="pdf")
plt.show()
def plot_graph(self):
"""
Plot the transmission graph of the simulation.
TODO: Draw arrows and have a directed graph.
http://goo.gl/Z697dH
TODO: Graph with big nodes for big transmissions
"""
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax1.set_title("Transmission / RPL tree")
ax1.axis("off")
val_color = {"udp_server": 0.5714285714285714}
pos = {node: data["pos"]
for node, data in self.radio_tree.nodes(data=True)}
# color for all nodes
node_color = [val_color.get(data["mote_type"], 0.25)
for node, data in self.radio_tree.nodes(data=True)]
# Drawing the nodes
nx.draw_networkx_nodes(self.radio_tree, pos, node_color=node_color, ax=ax1)
nx.draw_networkx_labels(self.radio_tree, pos, ax=ax1)
# Drawing radio edges
nx.draw_networkx_edges(self.radio_tree, pos, edgelist=self.radio_tree.edges(),
width=8, alpha=0.5, ax=ax1)
# Adding the depth of each node.
with open(PJ(self.result_dir, "depth.csv")) as depth_f:
reader = DictReader(depth_f)
for row in reader:
node = int(row["node"])
depth = row["depth"]
ax1.text(pos[node][0] + 5, pos[node][1] + 5, depth,
bbox=dict(facecolor='red', alpha=0.5),
horizontalalignment='center')
# Drawing RPL edges
nx.draw_networkx_edges(
self.rpl_tree, pos, edge_color='r', nodelist=[], arrows=True, ax=ax1)
img_path = PJ(self.img_dir, "graph.pdf")
fig.savefig(img_path, format="pdf")
update_report(self.result_dir, "plot_graph", {
"img_src": "img/graph.pdf",
"comment": """
When the edge is thick it means edges are in an RPL instance.
Otherwise it means that the two nodes can see each others.
""",
"text": """
We generate a random geometric graph then use information coming
to the RPL root to construct the gateway representation of the RPL
tree. We add into this tree representation the traffic generated.
"""})
def transmission_graph(self):
"""
Plot the transmission graph of the simulation.
"""
settings = self.settings["transmission_graph"]
output_path = pj(self.result_folder_path, *settings["output_path"])
fig_rplinfo, ax_transmission_graph = plt.subplots()
net = nx.Graph()
# nodes
mote_types = self.settings["mote_types"]
motes = self.settings["motes"]
position = {}
for mote in motes:
mote_type = mote["mote_type"]
mote_id = mote["mote_id"]
position[mote_id] = (mote["x"], mote["y"])
mote_types[mote_type] \
.setdefault("nodes", []) \
.append(mote["mote_id"])
# edges
transmitting_range = self.settings["transmitting_range"]
for couple in itertools.product(motes, motes):
if 0 < distance(couple) <= transmitting_range:
net.add_edge(couple[0]["mote_id"],
couple[1]["mote_id"])
for mote_type in mote_types:
color = mote_types[mote_type]["color"]
nodelist = mote_types[mote_type]["nodes"]
nx.draw_networkx_nodes(net, position,
nodelist=nodelist,
node_color=color,
ax=ax_transmission_graph)
nx.draw_networkx_edges(net, pos=position, ax=ax_transmission_graph)
# labels
nx.draw_networkx_labels(net, position, ax=ax_transmission_graph)
plt.axis('off')
plt.savefig(output_path) # save as PNG
return ax_transmission_graph
def rpl_graph(folder):
"""
Build up the RPL representation at the gateway
"""
output_folder = pj(folder, "results", "graph")
if not os.path.exists(output_folder):
os.makedirs(output_folder)
df = pd.read_csv(pj(folder, "results", "messages.csv"))
parent_df = df[df.message_type == "parent"]
rpl_graph = nx.DiGraph()
for c, p in parent_df.iterrows():
rpl_graph.add_edge(p["mote_id"], p["node"])
with open(pj(output_folder, "rpl_graph.json"), "w") as f:
f.write(json.dumps(node_link_data(rpl_graph),
sort_keys=True, indent=4))
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tdiprima/code | recipes/Python/52228_Remote_control_with_telnetlib/recipe-52228.py | 61a74f5f93da087d27c70b2efe779ac6bd2a3b4f | # auto_telnet.py - remote control via telnet
import os, sys, string, telnetlib
from getpass import getpass
class AutoTelnet:
def __init__(self, user_list, cmd_list, **kw):
self.host = kw.get('host', 'localhost')
self.timeout = kw.get('timeout', 600)
self.command_prompt = kw.get('command_prompt', "$ ")
self.passwd = {}
for user in user_list:
self.passwd[user] = getpass("Enter user '%s' password: " % user)
self.telnet = telnetlib.Telnet()
for user in user_list:
self.telnet.open(self.host)
ok = self.action(user, cmd_list)
if not ok:
print "Unable to process:", user
self.telnet.close()
def action(self, user, cmd_list):
t = self.telnet
t.write("\n")
login_prompt = "login: "
response = t.read_until(login_prompt, 5)
if string.count(response, login_prompt):
print response
else:
return 0
password_prompt = "Password:"
t.write("%s\n" % user)
response = t.read_until(password_prompt, 3)
if string.count(response, password_prompt):
print response
else:
return 0
t.write("%s\n" % self.passwd[user])
response = t.read_until(self.command_prompt, 5)
if not string.count(response, self.command_prompt):
return 0
for cmd in cmd_list:
t.write("%s\n" % cmd)
response = t.read_until(self.command_prompt, self.timeout)
if not string.count(response, self.command_prompt):
return 0
print response
return 1
if __name__ == '__main__':
basename = os.path.splitext(os.path.basename(sys.argv[0]))[0]
logname = os.environ.get("LOGNAME", os.environ.get("USERNAME"))
host = 'localhost'
import getopt
optlist, user_list = getopt.getopt(sys.argv[1:], 'c:f:h:')
usage = """
usage: %s [-h host] [-f cmdfile] [-c "command"] user1 user2 ...
-c command
-f command file
-h host (default: '%s')
Example: %s -c "echo $HOME" %s
""" % (basename, host, basename, logname)
if len(sys.argv) < 2:
print usage
sys.exit(1)
cmd_list = []
for (opt, optarg) in optlist:
if opt == '-f':
for r in open(optarg).readlines():
if string.rstrip(r):
cmd_list.append(r)
elif opt == '-c':
command = optarg
if command[0] == '"' and command[-1] == '"':
command = command[1:-1]
cmd_list.append(command)
elif opt == '-h':
host = optarg
autoTelnet = AutoTelnet(user_list, cmd_list, host=host)
| [] |
mimbres/FFTNet | FFTNet_dilconv.py | 3a6bfb4731bab2e0a59fc3a1ddb55f19f84aeba2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 7 09:46:10 2018
@author: sungkyun
FFTNet model using 2x1 dil-conv
"""
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
# Models with Preset (for convenience)
'''
dim_input: dimension of input (256 for 8-bit mu-law input)
num_layer: number of layers (11 in paper). receptive field = 2^11 (2,048)
io_ch: number of input(=output) channels in each fft layers
skip_ch: number of skip-channels, only required for fft-residual net.
Annotations:
B: batch dimension
C: channel dimension
L: length dimension
'''
def fftnet_base(input_dim=256, num_layer=11, io_ch=256):
return FFTNet(input_dim=input_dim, num_layer=num_layer, io_ch=io_ch, skip_ch=0, bias=True)
def fftnet_residual(input_dim=256, num_layer=11, io_ch=256, skip_ch=256):
return FFTNet(input_dim=input_dim, num_layer=num_layer, io_ch=io_ch, skip_ch=skip_ch, bais=True)
# FFT_Block: define a basic FFT Block
'''
FFT_Block:
- using 2x1 dilated-conv, instead of LR split 1x1 conv.
- described in the paper, section 2.2.
- in case of the first layer used in the first FFT_Block,
we use nn.embedding layer for one-hot index(0-255) entries.
'''
class FFT_Block(nn.Module):
def __init__(self, cond_dim=26, io_ch=int, recep_sz=int, bias=True):
super(FFT_Block, self).__init__()
self.cond_dim=cond_dim # Number of dimensions of condition input
self.io_ch = io_ch
self.recep_sz = recep_sz # Size of receptive field: i.e., the 1st layer has receptive field of 2^11(=2,048). 2nd has 2^10.
self.bias = bias # If True, use bias in 1x1 conv.
self.dilation = int(recep_sz / 2)
self.conv_2x1_LR = nn.Conv1d(in_channels=self.io_ch, out_channels=self.io_ch,
kernel_size=2, stride=1, dilation=self.dilation, bias=self.bias)
self.conv_2x1_VLR = nn.Conv1d(in_channels=self.cond_dim, out_channels=self.io_ch,
kernel_size=2, stride=1, dilation=self.dilation, bias=self.bias)
self.conv_1x1_last = nn.Conv1d(in_channels=self.io_ch, out_channels=self.io_ch,
kernel_size=1, stride=1, bias=self.bias)
return None
def forward(self, x, cond):
z = self.conv_2x1_LR(x) # Eq(1), z = w_L*x_L + w_R*x_R
z = z + self.conv_2x1_VLR(cond) # Eq(2), z = (WL ∗ xL + WR ∗ xR) + (VL ∗ hL + VR ∗ hR)
x = F.relu(self.conv_1x1_last(F.relu(z))) # x = ReLU(conv1x1(ReLU(z)))
return x
'''
FFTNet:
- [11 FFT_blocks] --> [FC_layer] --> [softmax]
'''
class FFTNet(nn.Module):
def __init__(self, input_dim=256, cond_dim=26, num_layer=11, io_ch=256, skip_ch=0, bias=True):
super(FFTNet, self).__init__()
self.input_dim = input_dim # 256 (=num_classes)
self.cond_dim = cond_dim # 26
self.num_layer = num_layer # 11
self.io_ch = io_ch # 256 ch. in the paper
self.skip_ch = skip_ch # Not implemented yet (no skip channel in the paper)
self.bias = bias # If True, use bias in 2x1 conv.
self.max_recep_sz = int(pow(2, self.num_layer)) # 2^11, max receptive field size
# Embedding layer: one-hot_index -> embedding -> 256ch output
self.input_embedding_layer = nn.Embedding(num_embeddings=self.input_dim,
embedding_dim=self.io_ch)
# Constructing FFT Blocks:
blocks = nn.ModuleList()
for l in range(self.num_layer):
recep_sz = int(pow(2, self.num_layer-l)) # 1024, 512, ... 2
blocks.append( FFT_Block(cond_dim=self.cond_dim,
io_ch=self.io_ch,
recep_sz=recep_sz,
bias=self.bias) )
self.fft_blocks=blocks
# Final FC layer:
self.fc = nn.Linear(in_features=self.io_ch, out_features=self.io_ch)
return None
def forward(self, x, cond, gen_mod=False):
# Padding x:
zpad_sz = int(self.max_recep_sz)
x = F.pad(x, (zpad_sz, 0), 'constant', 128) # 128? or 0?
# Embedding(x):
x = self.input_embedding_layer(x) # In : BxL, Out: BxLxC
x = x.permute(0,2,1) # Out: BxCxL
# FFT_Blocks:
for l in range(self.num_layer):
# Padding cond:
zpad_sz = int(self.max_recep_sz/pow(2, l))
padded_cond = F.pad(cond, (zpad_sz, 0), 'constant', 0)
x = self.fft_blocks[l](x, padded_cond)
if gen_mod is True:
x = x[:,:,-1] # In generator mode, take the last one sample only.
x = x.reshape(-1, 1, self.io_ch) # (BxC) --> (Bx1xC)
else:
x = x[:,:,:-1] # In training mode, right-omit 1 is required.
x = x.permute(0,2,1) # (BxCxL) --> (BxLxC)
x = self.fc(x) # (BxLxC)
# NOTE: in PyTorch, softmax() is included in CE loss.
return x
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SNEWS2/snewpdag | snewpdag/plugins/Copy.py | 57f886cf08e1acd8af48ee486a1c2400e2b77b8b | """
Copy - copy fields into other (possibly new) fields
configuration:
on: list of 'alert', 'revoke', 'report', 'reset' (optional: def 'alert' only)
cp: ( (in,out), ... )
Field names take the form of dir1/dir2/dir3,
which in the payload will be data[dir1][dir2][dir3]
"""
import logging
from snewpdag.dag import Node
class Copy(Node):
def __init__(self, cp, **kwargs):
self.cp = []
for op in cp:
src = op[0].split('/')
dst = op[1].split('/')
self.cp.append( [src, dst[:-1], dst[-1]] )
self.on = kwargs.pop('on', [ 'alert' ])
super().__init__(**kwargs)
def copy(self, data):
for op in self.cp:
v = data # should just follow references
for k in op[0]:
if k in v:
v = v[k]
else:
logging.warning('Field {} not found from source {}'.format(k, op[0]))
continue
# v should now hold the value to be copied
d = data
for k in op[1]:
if k not in d:
d[k] = {}
d = d[k]
d[op[2]] = v
return data
def alert(self, data):
return self.copy(data) if 'alert' in self.on else True
def revoke(self, data):
return self.copy(data) if 'revoke' in self.on else True
def reset(self, data):
return self.copy(data) if 'reset' in self.on else True
def report(self, data):
return self.copy(data) if 'report' in self.on else True
| [] |
BuildWeek-AirBnB-Optimal-Price/application | pages/aboutus.py | c65e1ec3db309dd3afbcf9429d16489ccda534d8 | '''
houses each team member's
link to personal GitHub io or
website or blog space
RJProctor
'''
# Imports from 3rd party libraries
import dash
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
from app import app
# 1 column layout
# https://dash-bootstrap-components.opensource.faculty.ai/l/components/layout
column1 = dbc.Col(
[
dcc.Markdown(
"""
## The Team:
Select a link to learn more about each of our
team members.
"""
),
],
)
# create footer
column2 = dbc.Col(
[
dcc.Markdown(
"""
**Debbie Cohen**
https://github.com/dscohen75/dscohen75.github.io
https://medium.com/@debbiecohen_22419
**Moe Fa**
---
**Eduardo Padilla**
https://medium.com/@eprecendez
---
**R. Jeannine Proctor**
https://jproctor-rebecca.github.io/
https://medium.com/@jproctor.m.ed.tn
---
**Code Review Team Members:**
Taylor Curran,
Regina Dircio,
Robert Giuffrie,
Ryan Herr,
Brendon Hoss,
Anika Nacey,
Tomas Phillips,
Raymond Tan,
and
Rebecca Duke-Wiesenberg
"""
),
],
)
layout = dbc.Row([column1, column2]) | [((1535, 1562), 'dash_bootstrap_components.Row', 'dbc.Row', (['[column1, column2]'], {}), '([column1, column2])\n', (1542, 1562), True, 'import dash_bootstrap_components as dbc\n'), ((450, 608), 'dash_core_components.Markdown', 'dcc.Markdown', (['"""\n ## The Team: \n Select a link to learn more about each of our \n team members. \n """'], {}), '(\n """\n ## The Team: \n Select a link to learn more about each of our \n team members. \n """\n )\n', (462, 608), True, 'import dash_core_components as dcc\n'), ((682, 1498), 'dash_core_components.Markdown', 'dcc.Markdown', (['"""\n **Debbie Cohen**\n\n https://github.com/dscohen75/dscohen75.github.io\n\n https://medium.com/@debbiecohen_22419\n \n **Moe Fa**\n\n ---\n \n **Eduardo Padilla**\n\n https://medium.com/@eprecendez\n\n ---\n\n **R. Jeannine Proctor**\n\n https://jproctor-rebecca.github.io/\n\n https://medium.com/@jproctor.m.ed.tn\n\n ---\n\n **Code Review Team Members:**\n\n Taylor Curran,\n Regina Dircio,\n Robert Giuffrie,\n Ryan Herr,\n Brendon Hoss,\n Anika Nacey,\n Tomas Phillips,\n Raymond Tan,\n and\n Rebecca Duke-Wiesenberg\n \n """'], {}), '(\n """\n **Debbie Cohen**\n\n https://github.com/dscohen75/dscohen75.github.io\n\n https://medium.com/@debbiecohen_22419\n \n **Moe Fa**\n\n ---\n \n **Eduardo Padilla**\n\n https://medium.com/@eprecendez\n\n ---\n\n **R. Jeannine Proctor**\n\n https://jproctor-rebecca.github.io/\n\n https://medium.com/@jproctor.m.ed.tn\n\n ---\n\n **Code Review Team Members:**\n\n Taylor Curran,\n Regina Dircio,\n Robert Giuffrie,\n Ryan Herr,\n Brendon Hoss,\n Anika Nacey,\n Tomas Phillips,\n Raymond Tan,\n and\n Rebecca Duke-Wiesenberg\n \n """\n )\n', (694, 1498), True, 'import dash_core_components as dcc\n')] |
eyantra/FireBird_Swiss_Knife | Codes/Python32/Lib/importlib/test/extension/test_path_hook.py | cac322cf28e2d690b86ba28a75e87551e5e47988 | from importlib import _bootstrap
from . import util
import collections
import imp
import sys
import unittest
class PathHookTests(unittest.TestCase):
"""Test the path hook for extension modules."""
# XXX Should it only succeed for pre-existing directories?
# XXX Should it only work for directories containing an extension module?
def hook(self, entry):
return _bootstrap._file_path_hook(entry)
def test_success(self):
# Path hook should handle a directory where a known extension module
# exists.
self.assertTrue(hasattr(self.hook(util.PATH), 'find_module'))
def test_main():
from test.support import run_unittest
run_unittest(PathHookTests)
if __name__ == '__main__':
test_main()
| [((682, 709), 'test.support.run_unittest', 'run_unittest', (['PathHookTests'], {}), '(PathHookTests)\n', (694, 709), False, 'from test.support import run_unittest\n'), ((389, 422), 'importlib._bootstrap._file_path_hook', '_bootstrap._file_path_hook', (['entry'], {}), '(entry)\n', (415, 422), False, 'from importlib import _bootstrap\n')] |
dcragusa/WeeklyPythonExerciseB2 | 3. count_words/solution.py | a7da3830e27891060dcfb0804c81f52b1f250ce8 | import os
from glob import iglob
from concurrent.futures import ThreadPoolExecutor
def count_words_file(path):
if not os.path.isfile(path):
return 0
with open(path) as file:
return sum(len(line.split()) for line in file)
def count_words_sequential(pattern):
return sum(map(count_words_file, iglob(pattern)))
def count_words_threading(pattern):
with ThreadPoolExecutor() as pool:
return sum(pool.map(count_words_file, iglob(pattern)))
| [((124, 144), 'os.path.isfile', 'os.path.isfile', (['path'], {}), '(path)\n', (138, 144), False, 'import os\n'), ((387, 407), 'concurrent.futures.ThreadPoolExecutor', 'ThreadPoolExecutor', ([], {}), '()\n', (405, 407), False, 'from concurrent.futures import ThreadPoolExecutor\n'), ((323, 337), 'glob.iglob', 'iglob', (['pattern'], {}), '(pattern)\n', (328, 337), False, 'from glob import iglob\n'), ((463, 477), 'glob.iglob', 'iglob', (['pattern'], {}), '(pattern)\n', (468, 477), False, 'from glob import iglob\n')] |
cirobarradov/kafka-connect-hdfs-datalab | kafka-connect-azblob/docs/autoreload.py | 7e2b23bdb78b34f9934b8d56618a8035b75f6f54 | #!/usr/bin/env python
from livereload import Server, shell
server = Server()
server.watch('*.rst', shell('make html'))
server.serve()
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atom-zh/Keras-TextClassification | keras_textclassification/conf/path_config.py | 26c549e8e23c6a10905c2dcef7eef557dc43c932 | # -*- coding: UTF-8 -*-
# !/usr/bin/python
# @time :2019/6/5 21:04
# @author :Mo
# @function :file of path
import os
import pathlib
import sys
# 项目的根目录
path_root = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir))
path_root = path_root.replace('\\', '/')
path_top = str(pathlib.Path(os.path.abspath(__file__)).parent.parent.parent)
path_top = path_top.replace('\\', '/')
# path of embedding
path_embedding_user_dict = path_root + '/data/embeddings/user_dict.txt'
path_embedding_random_char = path_root + '/data/embeddings/term_char.txt'
path_embedding_random_word = path_root + '/data/embeddings/term_word.txt'
path_embedding_bert = path_root + '/data/embeddings/chinese_L-12_H-768_A-12/'
path_embedding_xlnet = path_root + '/data/embeddings/chinese_xlnet_mid_L-24_H-768_A-12/'
path_embedding_albert = path_root + '/data/embeddings/albert_base_zh'
path_embedding_vector_word2vec_char = path_root + '/data/embeddings/multi_label_char.vec'
path_embedding_vector_word2vec_word = path_root + '/data/embeddings/multi_label_word.vec'
path_embedding_vector_word2vec_char_bin = path_root + '/data/embeddings/multi_label_char.bin'
path_embedding_vector_word2vec_word_bin = path_root + '/data/embeddings/multi_label_word.bin'
# classify data of baidu qa 2019
path_baidu_qa_2019_train = path_root + '/data/baidu_qa_2019/baike_qa_train.csv'
path_baidu_qa_2019_valid = path_root + '/data/baidu_qa_2019/baike_qa_valid.csv'
# 今日头条新闻多标签分类
path_byte_multi_news_train = path_root + '/data/byte_multi_news/train.csv'
path_byte_multi_news_valid = path_root + '/data/byte_multi_news/valid.csv'
path_byte_multi_news_label = path_root + '/data/byte_multi_news/labels.csv'
# classify data of baidu qa 2019
path_sim_webank_train = path_root + '/data/sim_webank/train.csv'
path_sim_webank_valid = path_root + '/data/sim_webank/valid.csv'
path_sim_webank_test = path_root + '/data/sim_webank/test.csv'
# classfiy multi labels 2021
path_multi_label_train = path_root + '/data/multi_label/train.csv'
path_multi_label_valid = path_root + '/data/multi_label/valid.csv'
path_multi_label_labels = path_root + '/data/multi_label/labels.csv'
path_multi_label_tests = path_root + '/data/multi_label/tests.csv'
# 路径抽象层
path_label = path_multi_label_labels
path_train = path_multi_label_train
path_valid = path_multi_label_valid
path_tests = path_multi_label_tests
path_edata = path_root + "/../out/error_data.csv"
# fast_text config
path_out = path_top + "/out/"
# 模型目录
path_model_dir = path_root + "/data/model/fast_text/"
# 语料地址
path_model = path_root + '/data/model/fast_text/model_fast_text.h5'
# 超参数保存地址
path_hyper_parameters = path_root + '/data/model/fast_text/hyper_parameters.json'
# embedding微调保存地址
path_fineture = path_root + "/data/model/fast_text/embedding_trainable.h5"
# 保持 分类-标签 索引
path_category = path_root + '/data/multi_label/category2labels.json'
# l2i_i2l
path_l2i_i2l = path_root + '/data/multi_label/l2i_i2l.json'
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robertopreste/apyhgnc | tests/test_apyhgnc.py | 26efa764a2262cfa12c8a2f0f077569e7f3e4e79 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
# Created by Roberto Preste
import pytest
import asyncio
from pandas.testing import assert_frame_equal
from apyhgnc import apyhgnc
# apyhgnc.info
def test_info_searchableFields(searchable_fields):
result = apyhgnc.info().searchableFields
assert result == searchable_fields
def test_info_storedFields(stored_fields):
result = apyhgnc.info().storedFields
assert result == stored_fields
def test_info_url():
result = apyhgnc.info().url
assert result == "http://rest.genenames.org/info"
# apyhgnc.fetch
def test_fetch_symbol_znf3(df_fetch_symbol_znf3):
result = apyhgnc.fetch("symbol", "ZNF3")
assert_frame_equal(result, df_fetch_symbol_znf3)
def test_fetch_symbol_znf3_async(df_fetch_symbol_znf3):
loop = asyncio.get_event_loop()
result = loop.run_until_complete(
apyhgnc.afetch("symbol", "ZNF3")
)
assert_frame_equal(result, df_fetch_symbol_znf3)
# apyhgnc.search
def test_search_all_braf(df_search_all_braf):
result = apyhgnc.search("BRAF")
assert_frame_equal(result, df_search_all_braf)
def test_search_all_braf_async(df_search_all_braf):
loop = asyncio.get_event_loop()
result = loop.run_until_complete(
apyhgnc.asearch("BRAF")
)
assert_frame_equal(result, df_search_all_braf)
def test_search_symbol_braf(df_search_symbol_braf):
result = apyhgnc.search("symbol", "BRAF")
assert_frame_equal(result, df_search_symbol_braf)
def test_search_symbol_braf_async(df_search_symbol_braf):
loop = asyncio.get_event_loop()
result = loop.run_until_complete(
apyhgnc.asearch("symbol", "BRAF")
)
assert_frame_equal(result, df_search_symbol_braf)
def test_search_symbols_braf_znf3(df_search_symbols_braf_znf3):
result = apyhgnc.search(symbol=["BRAF", "ZNF3"])
assert_frame_equal(result, df_search_symbols_braf_znf3)
def test_search_symbols_braf_znf3_async(df_search_symbols_braf_znf3):
loop = asyncio.get_event_loop()
result = loop.run_until_complete(
apyhgnc.asearch(symbol=["BRAF", "ZNF3"])
)
assert_frame_equal(result, df_search_symbols_braf_znf3)
def test_search_symbol_and_status(df_search_symbol_and_status):
result = apyhgnc.search(symbol="BRAF", status="Approved")
assert_frame_equal(result, df_search_symbol_and_status)
def test_search_symbol_and_status_async(df_search_symbol_and_status):
loop = asyncio.get_event_loop()
result = loop.run_until_complete(
apyhgnc.asearch(symbol="BRAF", status="Approved")
)
assert_frame_equal(result, df_search_symbol_and_status)
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'"""BRAF"""', 'status': '"""Approved"""'}), "(symbol='BRAF', status='Approved')\n", (2516, 2550), False, 'from apyhgnc import apyhgnc\n')] |
magnium/pybdaq | bdaq/tools/extract_enums.py | 8511cff42b7f953c105e7a78c8c62f6deb2430ec | import os.path
import argparse
from xml.etree import ElementTree as ET
class ExtractedEnum(object):
def __init__(self, tag_name, value_names):
self.tag_name = tag_name
self.value_names = value_names
def write_pxd(self, file_):
file_.write("\n ctypedef enum {}:\n".format(self.tag_name))
for name in self.value_names:
file_.write(" " * 8 + "{}\n".format(name))
def write_pyx(self, file_):
file_.write("\nclass {}(enum.Enum):\n".format(self.tag_name))
for name in self.value_names:
file_.write(" " * 4 + "{0} = _c.{0}\n".format(name))
@staticmethod
def from_xml(element, typedefs):
value_names = [v.attrib["name"] for v in element.findall("EnumValue")]
return ExtractedEnum(
typedefs[element.attrib["id"]],
value_names)
def find_enums(file_or_path):
# parse XML
tree = ET.parse(file_or_path)
# extract typedefs
typedefs = {}
for element in tree.findall("Typedef"):
typedefs[element.attrib["type"]] = element.attrib["name"]
# extract enums
enums = []
for element in tree.findall("Enumeration"):
enums.append(ExtractedEnum.from_xml(element, typedefs))
print "Found {} enums to extract.".format(len(enums))
return enums
def write_cython(pyx_file, pxd_file, enums):
# write pxd file header
pxd_file.write("# GENERATED FILE; DO NOT MODIFY\n\n")
pxd_file.write(
'cdef extern from "bdaqctrl.h" namespace "Automation::BDaq":')
# write pyx file header
pyx_file.write("# GENERATED FILE; DO NOT MODIFY\n\n")
pyx_file.write("import enum\n\n")
pyx_file.write("cimport wrapper_enums_c as _c\n\n")
# write enums
for extracted in enums:
print "Extracting definition of {}...".format(extracted.tag_name)
extracted.write_pyx(pyx_file)
extracted.write_pxd(pxd_file)
print "Done extracting definitions."
def main():
# parse script arguments
parser = argparse.ArgumentParser(
description="Extract enum definitions from header.")
parser.add_argument(
"--xml-in",
default="bdaqctrl.h.xml",
help="path to gccxml result")
parser.add_argument(
"--path-out",
default=".",
help="path to output directory")
args = parser.parse_args()
# extract enums
enums = find_enums(args.xml_in)
out_pyx_path = os.path.join(args.path_out, "wrapper_enums.pyx")
out_pxd_path = os.path.join(args.path_out, "wrapper_enums_c.pxd")
with open(out_pyx_path, "wb") as out_pyx_file:
with open(out_pxd_path, "wb") as out_pxd_file:
write_cython(out_pyx_file, out_pxd_file, enums)
if __name__ == "__main__":
main()
| [] |
SebaB29/Python | Objetos/biblioteca.py | 8fe7b375e200d2a629e3ef83a2356002621267a6 | class Libro:
def __init__(self, titulo, autor):
"""..."""
self.titulo = titulo
self.autor = autor
def obtener_titulo(self):
"""..."""
return str(self.titulo)
def obtener_autor(self):
"""..."""
return str(self.autor)
class Biblioteca:
def __init__(self):
"""..."""
self.coleccion = set()
def agregar_libro(self, libro):
"""..."""
self.coleccion.add((libro.titulo, libro.autor))
def sacar_libro(self, titulo, autor):
"""..."""
if not (titulo, autor) in self.coleccion:
raise Exception("El libro no esta en la colección")
self.coleccion.remove((titulo, autor))
return f"Libro: {titulo}, Autor: {autor}"
def contiene_libro(self, titulo, autor):
"""..."""
return (titulo, autor) in self.coleccion
libro = Libro("HyP", "JK")
libro1 = Libro("La Isla M", "JCortazar")
libro2 = Libro("El tunel", "Sabato")
biblio = Biblioteca()
biblio.agregar_libro(libro)
biblio.agregar_libro(libro1)
biblio.agregar_libro(libro2)
print(biblio.contiene_libro("HyP", "JK"))
print(biblio.sacar_libro("HyP", "JK"))
print(biblio.contiene_libro("HyP", "JK")) | [] |
Harvard-ATG/visualizing_russian_tools | parser_tool/tests/test_htmlgenerator.py | e8e5cf8c5b7eee0b6855594ad41b3ccd70a2d467 | # -*- coding: utf-8 -*-
import unittest
from xml.etree import ElementTree as ET
from parser_tool import tokenizer
from parser_tool import htmlgenerator
class TestHtmlGenerator(unittest.TestCase):
def _maketokendict(self, **kwargs):
token_text = kwargs.get("token", "")
token_dict = {
"token": token_text,
"index": kwargs.get("index", 0),
"offset": kwargs.get("offset", 0),
"tokentype": kwargs.get("tokentype", tokenizer.TOKEN_WORD),
"canonical": kwargs.get("canonical", tokenizer.canonical(token_text)),
"form_ids": kwargs.get("form_ids", []),
"level": kwargs.get("level", ""),
}
return token_dict
def test_render_token_russian_word(self):
token_text = "первоку́рсник"
token_dict = self._maketokendict(token=token_text, tokentype=tokenizer.TOKEN_RUS, level="3A", form_ids=["174128"])
rendered = htmlgenerator.render_token(token_dict)
node_type, el = rendered['node_type'], rendered['element']
self.assertEqual(htmlgenerator.ELEMENT_NODE, node_type)
self.assertEqual("span", el.tag)
self.assertEqual({
"class": "word parsed level3",
"data-form-ids": ",".join(token_dict['form_ids']),
"data-level": token_dict['level']
}, el.attrib)
self.assertEqual(token_text, el.text)
def test_render_token_english_word(self):
token_text = "hypothetical"
token_dict = self._maketokendict(token=token_text, tokentype=tokenizer.TOKEN_WORD)
rendered = htmlgenerator.render_token(token_dict)
node_type, el = rendered['node_type'], rendered['element']
self.assertEqual(htmlgenerator.ELEMENT_NODE, node_type)
self.assertEqual("span", el.tag)
self.assertEqual({"class": "word"}, el.attrib)
self.assertEqual(token_text, el.text)
def test_render_token_with_multiple_spaces(self):
token_text = " " * 3
expected_text = token_text.replace(" ", "\u00A0\u00A0")
token_dict = self._maketokendict(token=token_text, tokentype=tokenizer.TOKEN_SPACE)
rendered = htmlgenerator.render_token(token_dict)
self.assertEqual(htmlgenerator.TEXT_NODE, rendered['node_type'])
self.assertEqual(expected_text, rendered['text'])
def test_render_token_with_punctuation(self):
token_text = "')."
expected_text = token_text
token_dict = self._maketokendict(token=token_text, tokentype=tokenizer.TOKEN_SPACE)
rendered = htmlgenerator.render_token(token_dict)
self.assertEqual(htmlgenerator.TEXT_NODE, rendered['node_type'])
self.assertEqual(expected_text, rendered['text'])
def test_tokens_with_leading_punct_to_html(self):
# (собака) dog
tokens = [
self._maketokendict(token="(", tokentype=tokenizer.TOKEN_PUNCT),
self._maketokendict(token="собака", tokentype=tokenizer.TOKEN_RUS, level="1E", form_ids=["7599"]),
self._maketokendict(token=")", tokentype=tokenizer.TOKEN_RUS),
self._maketokendict(token=" ", tokentype=tokenizer.TOKEN_SPACE),
self._maketokendict(token="dog", tokentype=tokenizer.TOKEN_WORD),
]
html = htmlgenerator.tokens2html(tokens)
expected_html = '<pre class="words">(<span data-form-ids="7599" data-level="1E" class="word parsed level1">собака</span><span class="word">)</span> <span class="word">dog</span></pre>'
self.assertEqual(expected_html, html)
def test_tokens2html(self):
tokens = [
self._maketokendict(token="A", tokentype=tokenizer.TOKEN_WORD),
self._maketokendict(token=" ", tokentype=tokenizer.TOKEN_SPACE),
self._maketokendict(token="первоку́рсник", tokentype=tokenizer.TOKEN_RUS, level="3A", form_ids=["174128"]),
self._maketokendict(token=" ", tokentype=tokenizer.TOKEN_SPACE),
self._maketokendict(token="|", tokentype=tokenizer.TOKEN_PUNCT),
self._maketokendict(token="первоку́рсница", tokentype=tokenizer.TOKEN_RUS, level="3A", form_ids=["174128"]),
self._maketokendict(token=" ", tokentype=tokenizer.TOKEN_SPACE),
]
html = htmlgenerator.tokens2html(tokens)
root = ET.fromstring(html)
# Check the root element (e.g. container)
self.assertEqual("pre", root.tag)
self.assertEqual({"class": "words"}, root.attrib)
# Check that we have the expected number of child elements (1 element for each word or russian token)
expected_word_elements = sum([1 for t in tokens if t['tokentype'] in (tokenizer.TOKEN_WORD, tokenizer.TOKEN_RUS)])
self.assertEqual(expected_word_elements, len(root))
# Now check the first few tokens...
# 1) Check that the first child contains the text of the first token
self.assertEqual(tokens[0]['token'], root[0].text)
self.assertEqual("span", root[0].tag)
self.assertEqual({"class": "word"}, root[0].attrib)
# 2) Check that the first child's tail contains the text of the second token since it's a space token
self.assertEqual(tokens[1]['token'], root[0].tail)
# 3) Check that the second child contains the text of the third token
self.assertEqual(tokens[2]['token'], root[1].text)
self.assertEqual("span", root[1].tag)
self.assertEqual({'class': 'word parsed level3', 'data-form-ids': '174128', 'data-level': '3A'}, root[1].attrib)
| [((948, 986), 'parser_tool.htmlgenerator.render_token', 'htmlgenerator.render_token', (['token_dict'], {}), '(token_dict)\n', (974, 986), False, 'from parser_tool import htmlgenerator\n'), ((1600, 1638), 'parser_tool.htmlgenerator.render_token', 'htmlgenerator.render_token', (['token_dict'], {}), '(token_dict)\n', (1626, 1638), False, 'from parser_tool import htmlgenerator\n'), ((2173, 2211), 'parser_tool.htmlgenerator.render_token', 'htmlgenerator.render_token', (['token_dict'], {}), '(token_dict)\n', (2199, 2211), False, 'from parser_tool import htmlgenerator\n'), ((2568, 2606), 'parser_tool.htmlgenerator.render_token', 'htmlgenerator.render_token', (['token_dict'], {}), '(token_dict)\n', (2594, 2606), False, 'from parser_tool import htmlgenerator\n'), ((3283, 3316), 'parser_tool.htmlgenerator.tokens2html', 'htmlgenerator.tokens2html', (['tokens'], {}), '(tokens)\n', (3308, 3316), False, 'from parser_tool import htmlgenerator\n'), ((4266, 4299), 'parser_tool.htmlgenerator.tokens2html', 'htmlgenerator.tokens2html', (['tokens'], {}), '(tokens)\n', (4291, 4299), False, 'from parser_tool import htmlgenerator\n'), ((4315, 4334), 'xml.etree.ElementTree.fromstring', 'ET.fromstring', (['html'], {}), '(html)\n', (4328, 4334), True, 'from xml.etree import ElementTree as ET\n'), ((554, 585), 'parser_tool.tokenizer.canonical', 'tokenizer.canonical', (['token_text'], {}), '(token_text)\n', (573, 585), False, 'from parser_tool import tokenizer\n')] |
threefoldtech/Threefold-Circles | taiga/hooks/gitlab/migrations/0002_auto_20150703_1102.py | cbc433796b25cf7af9a295af65d665a4a279e2d6 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
from django.core.files import File
def update_gitlab_system_user_photo_to_v2(apps, schema_editor):
# We get the model from the versioned app registry;
# if we directly import it, it'll be the wrong version
User = apps.get_model("users", "User")
db_alias = schema_editor.connection.alias
try:
user = User.objects.using(db_alias).get(username__startswith="gitlab-",
is_active=False,
is_system=True)
f = open("taiga/hooks/gitlab/migrations/logo-v2.png", "rb")
user.photo.save("logo.png", File(f))
user.save()
except User.DoesNotExist:
pass
def update_gitlab_system_user_photo_to_v1(apps, schema_editor):
# We get the model from the versioned app registry;
# if we directly import it, it'll be the wrong version
User = apps.get_model("users", "User")
db_alias = schema_editor.connection.alias
try:
user = User.objects.using(db_alias).get(username__startswith="gitlab-",
is_active=False,
is_system=True)
f = open("taiga/hooks/gitlab/migrations/logo.png", "rb")
user.photo.save("logo.png", File(f))
user.save()
except User.DoesNotExist:
pass
class Migration(migrations.Migration):
dependencies = [
('gitlab', '0001_initial'),
('users', '0011_user_theme'),
]
operations = [
migrations.RunPython(update_gitlab_system_user_photo_to_v2,
update_gitlab_system_user_photo_to_v1),
]
| [((1637, 1739), 'django.db.migrations.RunPython', 'migrations.RunPython', (['update_gitlab_system_user_photo_to_v2', 'update_gitlab_system_user_photo_to_v1'], {}), '(update_gitlab_system_user_photo_to_v2,\n update_gitlab_system_user_photo_to_v1)\n', (1657, 1739), False, 'from django.db import models, migrations\n'), ((733, 740), 'django.core.files.File', 'File', (['f'], {}), '(f)\n', (737, 740), False, 'from django.core.files import File\n'), ((1394, 1401), 'django.core.files.File', 'File', (['f'], {}), '(f)\n', (1398, 1401), False, 'from django.core.files import File\n')] |
michalgagat/plugins_oauth | external_plugin_deps.bzl | 47cc344013bd43a4ac508c578f2d93f37a166ee6 | load("//tools/bzl:maven_jar.bzl", "maven_jar")
def external_plugin_deps(omit_commons_codec = True):
JACKSON_VERS = "2.10.2"
maven_jar(
name = "scribejava-core",
artifact = "com.github.scribejava:scribejava-core:6.9.0",
sha1 = "ed761f450d8382f75787e8fee9ae52e7ec768747",
)
maven_jar(
name = "jackson-annotations",
artifact = "com.fasterxml.jackson.core:jackson-annotations:" + JACKSON_VERS,
sha1 = "3a13b6105946541b8d4181a0506355b5fae63260",
)
maven_jar(
name = "jackson-databind",
artifact = "com.fasterxml.jackson.core:jackson-databind:" + JACKSON_VERS,
sha1 = "0528de95f198afafbcfb0c09d2e43b6e0ea663ec",
deps = [
"@jackson-annotations//jar",
],
)
if not omit_commons_codec:
maven_jar(
name = "commons-codec",
artifact = "commons-codec:commons-codec:1.4",
sha1 = "4216af16d38465bbab0f3dff8efa14204f7a399a",
)
| [] |
emiliocarcanobringas/11.-Operaciones_entero_con_float_python | 11.-Operaciones_entero_con_float_python.py | faf3bf2fae3b7a990e0d20483ac9ac219dcb7857 | # Este programa muestra la suma de dos variables, de tipo int y float
print("Este programa muestra la suma de dos variables, de tipo int y float")
print("También muestra que la variable que realiza la operación es de tipo float")
numero1 = 7
numero2 = 3.1416
sumadeambos = numero1 + numero2
print("El resultado de la suma es: ")
print(sumadeambos)
print(type(sumadeambos))
# Este programa fue escrito por Emilio Carcaño Bringas
| [] |
basiralab/RG-Select | main_gat.py | 074274f61667611205724c4423fc498ee4a0a9d0 | # -*- coding: utf-8 -*-
from sklearn import preprocessing
from torch.autograd import Variable
from models_gat import GAT
import os
import torch
import numpy as np
import argparse
import pickle
import sklearn.metrics as metrics
import cross_val
import time
import random
torch.manual_seed(0)
np.random.seed(0)
random.seed(0)
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
def evaluate(dataset, model_GAT, args, threshold_value, model_name):
"""
Parameters
----------
dataset : dataloader (dataloader for the validation/test dataset).
model_GCN : nn model (GAT model).
args : arguments
threshold_value : float (threshold for adjacency matrices).
Description
----------
This methods performs the evaluation of the model on test/validation dataset
Returns
-------
test accuracy.
"""
model_GAT.eval()
labels = []
preds = []
for batch_idx, data in enumerate(dataset):
adj = Variable(data['adj'].float(), requires_grad=False).to(device)
labels.append(data['label'].long().numpy())
adj = torch.squeeze(adj)
features = np.identity(adj.shape[0])
features = Variable(torch.from_numpy(features).float(), requires_grad=False).cpu()
if args.threshold in ["median", "mean"]:
adj = torch.where(adj > threshold_value, torch.tensor([1.0]), torch.tensor([0.0]))
ypred = model_GAT(features, adj)
_, indices = torch.max(ypred, 1)
preds.append(indices.cpu().data.numpy())
labels = np.hstack(labels)
preds = np.hstack(preds)
simple_r = {'labels':labels,'preds':preds}
with open("./gat/Labels_and_preds/"+model_name+".pickle", 'wb') as f:
pickle.dump(simple_r, f)
result = {'prec': metrics.precision_score(labels, preds, average='macro'),
'recall': metrics.recall_score(labels, preds, average='macro'),
'acc': metrics.accuracy_score(labels, preds),
'F1': metrics.f1_score(labels, preds, average="micro")}
if args.evaluation_method == 'model assessment':
name = 'Test'
if args.evaluation_method == 'model selection':
name = 'Validation'
print(name, " accuracy:", result['acc'])
return result['acc']
def minmax_sc(x):
min_max_scaler = preprocessing.MinMaxScaler()
x = min_max_scaler.fit_transform(x)
return x
def train(args, train_dataset, val_dataset, model_GAT, threshold_value, model_name):
"""
Parameters
----------
args : arguments
train_dataset : dataloader (dataloader for the validation/test dataset).
val_dataset : dataloader (dataloader for the validation/test dataset).
model_GAT : nn model (GAT model).
threshold_value : float (threshold for adjacency matrices).
Description
----------
This methods performs the training of the model on train dataset and calls evaluate() method for evaluation.
Returns
-------
test accuracy.
"""
params = list(model_GAT.parameters())
optimizer = torch.optim.Adam(params, lr=args.lr, weight_decay=args.weight_decay)
test_accs = []
train_loss=[]
val_acc=[]
for epoch in range(args.num_epochs):
print("Epoch ",epoch)
print("Size of Training Set:" + str(len(train_dataset)))
print("Size of Validation Set:" + str(len(val_dataset)))
model_GAT.train()
total_time = 0
avg_loss = 0.0
preds = []
labels = []
for batch_idx, data in enumerate(train_dataset):
begin_time = time.time()
adj = Variable(data['adj'].float(), requires_grad=False).to(device)
label = Variable(data['label'].long()).to(device)
#adj_id = Variable(data['id'].int()).to(device)
adj = torch.squeeze(adj)
features = np.identity(adj.shape[0])
features = Variable(torch.from_numpy(features).float(), requires_grad=False).cpu()
if args.threshold in ["median", "mean"]:
adj = torch.where(adj > threshold_value, torch.tensor([1.0]), torch.tensor([0.0]))
ypred = model_GAT(features, adj)
_, indices = torch.max(ypred, 1)
preds.append(indices.cpu().data.numpy())
labels.append(data['label'].long().numpy())
loss = model_GAT.loss(ypred, label)
model_GAT.zero_grad()
loss.backward()
#nn.utils.clip_grad_norm_(model_DIFFPOOL.parameters(), args.clip)
optimizer.step()
avg_loss += loss
elapsed = time.time() - begin_time
total_time += elapsed
if epoch == args.num_epochs-1:
model_GAT.is_trained = True
preds = np.hstack(preds)
labels = np.hstack(labels)
print("Train accuracy : ", np.mean( preds == labels ))
test_acc = evaluate(val_dataset, model_GAT, args, threshold_value, model_name)
print('Avg loss: ', avg_loss, '; epoch time: ', total_time)
test_accs.append(test_acc)
train_loss.append(avg_loss)
val_acc.append(test_acc)
path = './gat/weights/W_'+model_name+'.pickle'
if os.path.exists(path):
os.remove(path)
os.rename('GAT_W.pickle',path)
los_p = {'loss':train_loss}
with open("./gat/training_loss/Training_loss_"+model_name+".pickle", 'wb') as f:
pickle.dump(los_p, f)
torch.save(model_GAT,"./gat/models/GAT_"+model_name+".pt")
return test_acc
def load_data(args):
"""
Parameters
----------
args : arguments
Description
----------
This methods loads the adjacency matrices representing the args.view -th view in dataset
Returns
-------
List of dictionaries{adj, label, id}
"""
#Load graphs and labels
with open('data/'+args.dataset+'/'+args.dataset+'_edges','rb') as f:
multigraphs = pickle.load(f)
with open('data/'+args.dataset+'/'+args.dataset+'_labels','rb') as f:
labels = pickle.load(f)
adjacencies = [multigraphs[i][:,:,args.view] for i in range(len(multigraphs))]
#Normalize inputs
if args.NormalizeInputGraphs==True:
for subject in range(len(adjacencies)):
adjacencies[subject] = minmax_sc(adjacencies[subject])
#Create List of Dictionaries
G_list=[]
for i in range(len(labels)):
G_element = {"adj": adjacencies[i],"label": labels[i],"id": i,}
G_list.append(G_element)
return G_list
def arg_parse(dataset, view, num_shots=2, cv_number=5):
"""
arguments definition method
"""
parser = argparse.ArgumentParser(description='Graph Classification')
parser.add_argument('--mode', type=str, default='train', choices=['train', 'test'])
parser.add_argument('--v', type=str, default=1)
parser.add_argument('--data', type=str, default='Sample_dataset', choices = [ f.path[5:] for f in os.scandir("data") if f.is_dir() ])
parser.add_argument('--dataset', type=str, default=dataset,
help='Dataset')
parser.add_argument('--view', type=int, default=view,
help = 'view index in the dataset')
parser.add_argument('--num_epochs', type=int, default=1, #50
help='Training Epochs')
parser.add_argument('--num_shots', type=int, default=num_shots, #100
help='number of shots')
parser.add_argument('--cv_number', type=int, default=cv_number,
help='number of validation folds.')
parser.add_argument('--NormalizeInputGraphs', default=False, action='store_true',
help='Normalize Input adjacency matrices of graphs')
parser.add_argument('--evaluation_method', type=str, default='model assessment',
help='evaluation method, possible values : model selection, model assessment')
parser.add_argument('--threshold', dest='threshold', default='mean',
help='threshold the graph adjacency matrix. Possible values: no_threshold, median, mean')
parser.add_argument('--no-cuda', action='store_true', default=False,
help='Disables CUDA training.')
parser.add_argument('--num-classes', dest='num_classes', type=int, default=2,
help='Number of label classes')
parser.add_argument('--lr', type=float, default=0.001,
help='Initial learning rate.')
parser.add_argument('--weight_decay', type=float, default=5e-4,
help='Weight decay (L2 loss on parameters).')
parser.add_argument('--hidden', type=int, default=8,
help='Number of hidden units.')
parser.add_argument('--nb_heads', type=int, default=8,
help='Number of head attentions.')
parser.add_argument('--dropout', type=float, default=0.8,
help='Dropout rate (1 - keep probability).')
parser.add_argument('--alpha', type=float, default=0.2,
help='Alpha for the leaky_relu.')
return parser.parse_args()
def benchmark_task(args, model_name):
"""
Parameters
----------
args : Arguments
Description
----------
Initiates the model and performs train/test or train/validation splits and calls train() to execute training and evaluation.
Returns
-------
test_accs : test accuracies (list)
"""
G_list = load_data(args)
num_nodes = G_list[0]['adj'].shape[0]
test_accs = []
folds = cross_val.stratify_splits(G_list,args)
[random.shuffle(folds[i]) for i in range(len(folds))]
for i in range(args.cv_number):
train_set, validation_set, test_set = cross_val.datasets_splits(folds, args, i)
if args.evaluation_method =='model selection':
train_dataset, val_dataset, threshold_value = cross_val.model_selection_split(train_set, validation_set, args)
if args.evaluation_method =='model assessment':
train_dataset, val_dataset, threshold_value = cross_val.model_assessment_split(train_set, validation_set, test_set, args)
print("CV : ",i)
model_GAT = GAT(nfeat=num_nodes,
nhid=args.hidden,
nclass=args.num_classes,
dropout=args.dropout,
nheads=args.nb_heads,
alpha=args.alpha)
test_acc = train(args, train_dataset, val_dataset, model_GAT, threshold_value, model_name+"_CV_"+str(i)+"_view_"+str(args.view))
test_accs.append(test_acc)
return test_accs
def test_scores(dataset, view, model_name, cv_number):
args = arg_parse(dataset, view, cv_number=cv_number)
print("Main : ",args)
test_accs = benchmark_task(args, model_name)
print("test accuracies ",test_accs)
return test_accs
def two_shot_trainer(dataset, view, num_shots):
args = arg_parse(dataset, view, num_shots=num_shots)
torch.manual_seed(0)
np.random.seed(0)
random.seed(0)
start = time.time()
for i in range(args.num_shots):
model = "gat"
model_name = "Few_Shot_"+dataset+"_"+model + str(i)
print("Shot : ",i)
with open('./Two_shot_samples_views/'+dataset+'_view_'+str(view)+'_shot_'+str(i)+'_train','rb') as f:
train_set = pickle.load(f)
with open('./Two_shot_samples_views/'+dataset+'_view_'+str(view)+'_shot_'+str(i)+'_test','rb') as f:
test_set = pickle.load(f)
num_nodes = train_set[0]['adj'].shape[0]
model_GAT = GAT(nfeat=num_nodes,
nhid=args.hidden,
nclass=args.num_classes,
dropout=args.dropout,
nheads=args.nb_heads,
alpha=args.alpha)
train_dataset, val_dataset, threshold_value = cross_val.two_shot_loader(train_set, test_set, args)
test_acc = train(args, train_dataset, val_dataset, model_GAT, threshold_value, model_name+"_view_"+str(view))
print("Test accuracy:"+str(test_acc))
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jeikabu/lumberyard | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Python/piexif/_dump.py | 07228c605ce16cbf5aaa209a94a3cb9d6c1a4115 | import copy
import numbers
import struct
from ._common import *
from ._exif import *
TIFF_HEADER_LENGTH = 8
def dump(exif_dict_original):
"""
py:function:: piexif.load(data)
Return exif as bytes.
:param dict exif: Exif data({"0th":dict, "Exif":dict, "GPS":dict, "Interop":dict, "1st":dict, "thumbnail":bytes})
:return: Exif
:rtype: bytes
"""
exif_dict = copy.deepcopy(exif_dict_original)
header = b"Exif\x00\x00\x4d\x4d\x00\x2a\x00\x00\x00\x08"
exif_is = False
gps_is = False
interop_is = False
first_is = False
if "0th" in exif_dict:
zeroth_ifd = exif_dict["0th"]
else:
zeroth_ifd = {}
if (("Exif" in exif_dict) and len(exif_dict["Exif"]) or
("Interop" in exif_dict) and len(exif_dict["Interop"]) ):
zeroth_ifd[ImageIFD.ExifTag] = 1
exif_is = True
exif_ifd = exif_dict["Exif"]
if ("Interop" in exif_dict) and len(exif_dict["Interop"]):
exif_ifd[ExifIFD. InteroperabilityTag] = 1
interop_is = True
interop_ifd = exif_dict["Interop"]
elif ExifIFD. InteroperabilityTag in exif_ifd:
exif_ifd.pop(ExifIFD.InteroperabilityTag)
elif ImageIFD.ExifTag in zeroth_ifd:
zeroth_ifd.pop(ImageIFD.ExifTag)
if ("GPS" in exif_dict) and len(exif_dict["GPS"]):
zeroth_ifd[ImageIFD.GPSTag] = 1
gps_is = True
gps_ifd = exif_dict["GPS"]
elif ImageIFD.GPSTag in zeroth_ifd:
zeroth_ifd.pop(ImageIFD.GPSTag)
if (("1st" in exif_dict) and
("thumbnail" in exif_dict) and
(exif_dict["thumbnail"] is not None)):
first_is = True
exif_dict["1st"][ImageIFD.JPEGInterchangeFormat] = 1
exif_dict["1st"][ImageIFD.JPEGInterchangeFormatLength] = 1
first_ifd = exif_dict["1st"]
zeroth_set = _dict_to_bytes(zeroth_ifd, "0th", 0)
zeroth_length = (len(zeroth_set[0]) + exif_is * 12 + gps_is * 12 + 4 +
len(zeroth_set[1]))
if exif_is:
exif_set = _dict_to_bytes(exif_ifd, "Exif", zeroth_length)
exif_length = len(exif_set[0]) + interop_is * 12 + len(exif_set[1])
else:
exif_bytes = b""
exif_length = 0
if gps_is:
gps_set = _dict_to_bytes(gps_ifd, "GPS", zeroth_length + exif_length)
gps_bytes = b"".join(gps_set)
gps_length = len(gps_bytes)
else:
gps_bytes = b""
gps_length = 0
if interop_is:
offset = zeroth_length + exif_length + gps_length
interop_set = _dict_to_bytes(interop_ifd, "Interop", offset)
interop_bytes = b"".join(interop_set)
interop_length = len(interop_bytes)
else:
interop_bytes = b""
interop_length = 0
if first_is:
offset = zeroth_length + exif_length + gps_length + interop_length
first_set = _dict_to_bytes(first_ifd, "1st", offset)
thumbnail = _get_thumbnail(exif_dict["thumbnail"])
thumbnail_max_size = 64000
if len(thumbnail) > thumbnail_max_size:
raise ValueError("Given thumbnail is too large. max 64kB")
else:
first_bytes = b""
if exif_is:
pointer_value = TIFF_HEADER_LENGTH + zeroth_length
pointer_str = struct.pack(">I", pointer_value)
key = ImageIFD.ExifTag
key_str = struct.pack(">H", key)
type_str = struct.pack(">H", TYPES.Long)
length_str = struct.pack(">I", 1)
exif_pointer = key_str + type_str + length_str + pointer_str
else:
exif_pointer = b""
if gps_is:
pointer_value = TIFF_HEADER_LENGTH + zeroth_length + exif_length
pointer_str = struct.pack(">I", pointer_value)
key = ImageIFD.GPSTag
key_str = struct.pack(">H", key)
type_str = struct.pack(">H", TYPES.Long)
length_str = struct.pack(">I", 1)
gps_pointer = key_str + type_str + length_str + pointer_str
else:
gps_pointer = b""
if interop_is:
pointer_value = (TIFF_HEADER_LENGTH +
zeroth_length + exif_length + gps_length)
pointer_str = struct.pack(">I", pointer_value)
key = ExifIFD.InteroperabilityTag
key_str = struct.pack(">H", key)
type_str = struct.pack(">H", TYPES.Long)
length_str = struct.pack(">I", 1)
interop_pointer = key_str + type_str + length_str + pointer_str
else:
interop_pointer = b""
if first_is:
pointer_value = (TIFF_HEADER_LENGTH + zeroth_length +
exif_length + gps_length + interop_length)
first_ifd_pointer = struct.pack(">L", pointer_value)
thumbnail_pointer = (pointer_value + len(first_set[0]) + 24 +
4 + len(first_set[1]))
thumbnail_p_bytes = (b"\x02\x01\x00\x04\x00\x00\x00\x01" +
struct.pack(">L", thumbnail_pointer))
thumbnail_length_bytes = (b"\x02\x02\x00\x04\x00\x00\x00\x01" +
struct.pack(">L", len(thumbnail)))
first_bytes = (first_set[0] + thumbnail_p_bytes +
thumbnail_length_bytes + b"\x00\x00\x00\x00" +
first_set[1] + thumbnail)
else:
first_ifd_pointer = b"\x00\x00\x00\x00"
zeroth_bytes = (zeroth_set[0] + exif_pointer + gps_pointer +
first_ifd_pointer + zeroth_set[1])
if exif_is:
exif_bytes = exif_set[0] + interop_pointer + exif_set[1]
return (header + zeroth_bytes + exif_bytes + gps_bytes +
interop_bytes + first_bytes)
def _get_thumbnail(jpeg):
segments = split_into_segments(jpeg)
while (b"\xff\xe0" <= segments[1][0:2] <= b"\xff\xef"):
segments.pop(1)
thumbnail = b"".join(segments)
return thumbnail
def _pack_byte(*args):
return struct.pack("B" * len(args), *args)
def _pack_signed_byte(*args):
return struct.pack("b" * len(args), *args)
def _pack_short(*args):
return struct.pack(">" + "H" * len(args), *args)
def _pack_signed_short(*args):
return struct.pack(">" + "h" * len(args), *args)
def _pack_long(*args):
return struct.pack(">" + "L" * len(args), *args)
def _pack_slong(*args):
return struct.pack(">" + "l" * len(args), *args)
def _pack_float(*args):
return struct.pack(">" + "f" * len(args), *args)
def _pack_double(*args):
return struct.pack(">" + "d" * len(args), *args)
def _value_to_bytes(raw_value, value_type, offset):
four_bytes_over = b""
value_str = b""
if value_type == TYPES.Byte:
length = len(raw_value)
if length <= 4:
value_str = (_pack_byte(*raw_value) +
b"\x00" * (4 - length))
else:
value_str = struct.pack(">I", offset)
four_bytes_over = _pack_byte(*raw_value)
elif value_type == TYPES.Short:
length = len(raw_value)
if length <= 2:
value_str = (_pack_short(*raw_value) +
b"\x00\x00" * (2 - length))
else:
value_str = struct.pack(">I", offset)
four_bytes_over = _pack_short(*raw_value)
elif value_type == TYPES.Long:
length = len(raw_value)
if length <= 1:
value_str = _pack_long(*raw_value)
else:
value_str = struct.pack(">I", offset)
four_bytes_over = _pack_long(*raw_value)
elif value_type == TYPES.SLong:
length = len(raw_value)
if length <= 1:
value_str = _pack_slong(*raw_value)
else:
value_str = struct.pack(">I", offset)
four_bytes_over = _pack_slong(*raw_value)
elif value_type == TYPES.Ascii:
try:
new_value = raw_value.encode("latin1") + b"\x00"
except:
try:
new_value = raw_value + b"\x00"
except TypeError:
raise ValueError("Got invalid type to convert.")
length = len(new_value)
if length > 4:
value_str = struct.pack(">I", offset)
four_bytes_over = new_value
else:
value_str = new_value + b"\x00" * (4 - length)
elif value_type == TYPES.Rational:
if isinstance(raw_value[0], numbers.Integral):
length = 1
num, den = raw_value
new_value = struct.pack(">L", num) + struct.pack(">L", den)
elif isinstance(raw_value[0], tuple):
length = len(raw_value)
new_value = b""
for n, val in enumerate(raw_value):
num, den = val
new_value += (struct.pack(">L", num) +
struct.pack(">L", den))
value_str = struct.pack(">I", offset)
four_bytes_over = new_value
elif value_type == TYPES.SRational:
if isinstance(raw_value[0], numbers.Integral):
length = 1
num, den = raw_value
new_value = struct.pack(">l", num) + struct.pack(">l", den)
elif isinstance(raw_value[0], tuple):
length = len(raw_value)
new_value = b""
for n, val in enumerate(raw_value):
num, den = val
new_value += (struct.pack(">l", num) +
struct.pack(">l", den))
value_str = struct.pack(">I", offset)
four_bytes_over = new_value
elif value_type == TYPES.Undefined:
length = len(raw_value)
if length > 4:
value_str = struct.pack(">I", offset)
try:
four_bytes_over = b"" + raw_value
except TypeError:
raise ValueError("Got invalid type to convert.")
else:
try:
value_str = raw_value + b"\x00" * (4 - length)
except TypeError:
raise ValueError("Got invalid type to convert.")
elif value_type == TYPES.SByte: # Signed Byte
length = len(raw_value)
if length <= 4:
value_str = (_pack_signed_byte(*raw_value) +
b"\x00" * (4 - length))
else:
value_str = struct.pack(">I", offset)
four_bytes_over = _pack_signed_byte(*raw_value)
elif value_type == TYPES.SShort: # Signed Short
length = len(raw_value)
if length <= 2:
value_str = (_pack_signed_short(*raw_value) +
b"\x00\x00" * (2 - length))
else:
value_str = struct.pack(">I", offset)
four_bytes_over = _pack_signed_short(*raw_value)
elif value_type == TYPES.Float:
length = len(raw_value)
if length <= 1:
value_str = _pack_float(*raw_value)
else:
value_str = struct.pack(">I", offset)
four_bytes_over = _pack_float(*raw_value)
elif value_type == TYPES.DFloat: # Double
length = len(raw_value)
value_str = struct.pack(">I", offset)
four_bytes_over = _pack_double(*raw_value)
length_str = struct.pack(">I", length)
return length_str, value_str, four_bytes_over
def _dict_to_bytes(ifd_dict, ifd, ifd_offset):
tag_count = len(ifd_dict)
entry_header = struct.pack(">H", tag_count)
if ifd in ("0th", "1st"):
entries_length = 2 + tag_count * 12 + 4
else:
entries_length = 2 + tag_count * 12
entries = b""
values = b""
for n, key in enumerate(sorted(ifd_dict)):
if (ifd == "0th") and (key in (ImageIFD.ExifTag, ImageIFD.GPSTag)):
continue
elif (ifd == "Exif") and (key == ExifIFD.InteroperabilityTag):
continue
elif (ifd == "1st") and (key in (ImageIFD.JPEGInterchangeFormat, ImageIFD.JPEGInterchangeFormatLength)):
continue
raw_value = ifd_dict[key]
key_str = struct.pack(">H", key)
value_type = TAGS[ifd][key]["type"]
type_str = struct.pack(">H", value_type)
four_bytes_over = b""
if isinstance(raw_value, numbers.Integral) or isinstance(raw_value, float):
raw_value = (raw_value,)
offset = TIFF_HEADER_LENGTH + entries_length + ifd_offset + len(values)
try:
length_str, value_str, four_bytes_over = _value_to_bytes(raw_value,
value_type,
offset)
except ValueError:
raise ValueError(
'"dump" got wrong type of exif value.\n' +
'{0} in {1} IFD. Got as {2}.'.format(key, ifd, type(ifd_dict[key]))
)
entries += key_str + type_str + length_str + value_str
values += four_bytes_over
return (entry_header + entries, values)
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mrahman4782/portalhoop | portal.py | 29e87ccaca5544590aa9ed20096c3628c1ab57b1 | import pygame
import random
from pygame import *
pygame.init()
width, height = 740, 500
screen = pygame.display.set_mode((width, height))
player = [pygame.transform.scale(pygame.image.load("Resources/Balljump-1(2).png"), (100,100)), pygame.transform.scale(pygame.image.load("Resources/Balljump-1.png"),(100,100))]
launch = [pygame.transform.scale(pygame.image.load("Resources/Balljump-1.png"), (100,100)), pygame.transform.scale(pygame.image.load("Resources/Balljump-1(2).png"), (100,100)),pygame.transform.scale(pygame.image.load("Resources/Balljump-2.png"), (100,100)),pygame.transform.scale(pygame.image.load("Resources/Balljump-3.png"), (100,100)), pygame.transform.scale(pygame.image.load("Resources/Balljump-4.png"),(100,100))]
shoot = [pygame.transform.scale(pygame.image.load("Resources/Balljump-5.png"), (100, 100)), pygame.transform.scale(pygame.image.load("Resources/Balljump-6.png"), (100, 100))]
ball = pygame.transform.scale(pygame.image.load("Resources/ball.png"), (100,100))
blue = (0, 0, 128)
white = (255, 255, 255)
janimation, danimation, movable, motionactivate, limit_reached, nojump = False, False, False, False, False, False
jumplock = True
ballrelease, ballregain = False, False
fr = pygame.time.Clock()
c = 0
i = 0
p = 0
x, y = 0, 300
score = 0
a, b, rpos = 0, 0, 0
xpos, ypos = 17, 313
# Background image source: https://www.freepik.com/free-vector/floral-ornamental-abstract-background_6189902.htm#page=1&query=black%20background&position=40
background = pygame.image.load("Resources/back.jpg")
gamestart = False
def basketball():
#Draw basketball
global rpos, xpos, ypos, ballregain
if gamestart == True and ballrelease == False:
if nojump == True:
if c % 2 == 0:
screen.blit(ball, (xpos, ypos + 24))
if c % 2 == 1:
screen.blit(ball, (xpos + 2 , ypos ))
if nojump == False and motionactivate == True:
if p // 4 == 0:
screen.blit(ball, (xpos, ypos))
if p // 4 == 1:
screen.blit(ball, (xpos-2, ypos-5))
if p // 4 == 2:
screen.blit(ball, (xpos-2, ypos-7))
if p // 4 == 3:
screen.blit(ball, (xpos-2, ypos-11))
if p// 4 == 4:
screen.blit(ball, (xpos-2, ypos-13))
if janimation == True:
rpos = y -13
screen.blit(ball, (xpos, rpos))
rposNew = 400 - rpos
if gamestart == True and ballrelease == True:
if rpos <= 325:
screen.blit(ball, (xpos, rpos))
if xpos <= 700:
ballregain = False
xpos += (rposNew / 20)
print("rpos is: " + str(rpos) + " xpos is: " + str(xpos))
rpos = (-1*((xpos/600)**2))+((xpos)/150)+rpos
if xpos > 700 or rpos > 325:
xpos = 17
ballregain = True
def player_animations():
# Animations while the user makes no input
global c
global player
global i
if nojump == True:
if c % 2 == 0 and i<= 10:
if i<10:
screen.blit(player[c], (0, 300))
i += 1
if i == 10:
c += 1
i += 1
elif c % 2 == 1 and i<= 20:
if i>10 and i<20:
screen.blit(player[c], (0, 300))
i += 1
if i == 20:
c -= 1
i += 1
elif i>20:
i = 0
screen.blit(player[c], (0, 300))
if nojump == False:
screen.fill(0)
def screen_text():
global score
global nojump
global movable
if nojump == True:
font = pygame.font.Font("Resources/android.ttf", 16)
text2 = font.render("Hold space to throw the ball", True, white)
textRect2 = text2.get_rect()
textRect2.center = (width // 2, height // 2 + 200)
screen.blit(text2, textRect2)
movable = True
font = pygame.font.Font("Resources/android.ttf", 16)
text2 = font.render("Score: "+ str(score), True, white)
textRect2 = text2.get_rect()
textRect2.center = (width // 2 - 300, height // 2 - 200)
screen.blit(text2, textRect2)
def player_jump():
# Initial animations before the player jumps
global p, nojump, movable, x, y, janimation, danimation, a, b, motionactivate, limit_reached
global jumplock, ballrelease, ballregain
if movable == True and keypress[K_SPACE]:
#print(pygame.time.get_ticks())
motionactivate = True
#print(nojump)
#if p >= 19:
# p = 0
if motionactivate == True:
#screen.fill(0)
nojump = False
if p < 21:
screen.blit(launch[p // 4], (0, 300))
p += 1
if p == 20:
a = pygame.time.get_ticks()
janimation = True
p += 1
#elif keypress[K_SPACE]:
# what to do when jump is completed
if janimation == True and limit_reached == False:
if keypress[K_SPACE] and pygame.KEYDOWN and jumplock == True:
b = pygame.time.get_ticks()
if y > 239:
y = ((b - a) / -25) + 310
if y >= 305:
screen.fill(0)
screen.blit(shoot[0], (x, y))
if y < 305 and y > 240:
screen.blit(shoot[1], (x,y))
if y <= 239:
screen.blit(shoot[0], (x, y))
danimation = True
limit_reached = True
#print(danimation)
if event.type == pygame.KEYUP:
if event.key == K_SPACE:
danimation = True
motionactivate = False
ballrelease = True
if danimation == True:
jumplock = False
if danimation == True or limit_reached == True:
#print("poopc "+ str(y))
if y < 310:
screen.blit(shoot[0], (x, y))
y += 2
#
# print("zag")
#print("poop: " + str(pygame.KEYUP) + " key down is: " + str(pygame.KEYDOWN))
if y >= 310:
nojump = True
danimation = False
janimation = False
movable = False
limit_reached = False
p = 0
jumplock = True
if ballregain == True:
ballrelease = False
#print("y value is: "+ str(y)+ " a is: "+ str(a) + " b is: "+ str(b))
while 1:
keypress = pygame.key.get_pressed()
fr.tick(30)
screen.fill(0)
if keypress[K_RETURN]:
gamestart = True
if gamestart == False:
#screen.fill(0)
screen.blit(background, (0,0))
# Draw opening texts
font = pygame.font.Font("Resources/android.ttf", 64)
text = font.render("Portal Hoop", True, white)
textRect = text.get_rect()
textRect.center = (width // 2, height // 2 - 100)
screen.blit(text, textRect)
font = pygame.font.Font("Resources/android.ttf", 18)
text2 = font.render("Press Return to start", True, white)
textRect2 = text2.get_rect()
textRect2.center = (width // 2, height // 2 + 100)
screen.blit(text2, textRect2)
nojump = True
# Check if any
if gamestart == True:
#screen.fill(0)
player_animations()
player_jump()
basketball()
screen_text()
pygame.display.flip()
pygame.display.set_caption("Portal Hoop")
for event in pygame.event.get():
if event.type == pygame.QUIT:
pygame.quit()
exit(0)
| [((127, 140), 'pygame.init', 'pygame.init', ([], {}), '()\n', (138, 140), False, 'import pygame\n'), ((176, 216), 'pygame.display.set_mode', 'pygame.display.set_mode', (['(width, height)'], {}), '((width, height))\n', (199, 216), False, 'import pygame\n'), ((1288, 1307), 'pygame.time.Clock', 'pygame.time.Clock', ([], {}), '()\n', (1305, 1307), False, 'import pygame\n'), ((1564, 1603), 'pygame.image.load', 'pygame.image.load', (['"""Resources/back.jpg"""'], {}), "('Resources/back.jpg')\n", (1581, 1603), False, 'import pygame\n'), ((1018, 1057), 'pygame.image.load', 'pygame.image.load', (['"""Resources/ball.png"""'], {}), "('Resources/ball.png')\n", (1035, 1057), False, 'import pygame\n'), ((4238, 4283), 'pygame.font.Font', 'pygame.font.Font', (['"""Resources/android.ttf"""', '(16)'], {}), "('Resources/android.ttf', 16)\n", (4254, 4283), False, 'import pygame\n'), ((6834, 6858), 'pygame.key.get_pressed', 'pygame.key.get_pressed', ([], {}), '()\n', (6856, 6858), False, 'import pygame\n'), ((7807, 7828), 'pygame.display.flip', 'pygame.display.flip', ([], {}), '()\n', (7826, 7828), False, 'import pygame\n'), ((7833, 7874), 'pygame.display.set_caption', 'pygame.display.set_caption', (['"""Portal Hoop"""'], {}), "('Portal Hoop')\n", (7859, 7874), False, 'import pygame\n'), ((7892, 7910), 'pygame.event.get', 'pygame.event.get', ([], {}), '()\n', (7908, 7910), False, 'import pygame\n'), ((250, 298), 'pygame.image.load', 'pygame.image.load', (['"""Resources/Balljump-1(2).png"""'], {}), "('Resources/Balljump-1(2).png')\n", (267, 298), False, 'import pygame\n'), ((335, 380), 'pygame.image.load', 'pygame.image.load', (['"""Resources/Balljump-1.png"""'], {}), "('Resources/Balljump-1.png')\n", (352, 380), False, 'import pygame\n'), ((426, 471), 'pygame.image.load', 'pygame.image.load', (['"""Resources/Balljump-1.png"""'], {}), "('Resources/Balljump-1.png')\n", (443, 471), False, 'import pygame\n'), ((508, 556), 'pygame.image.load', 'pygame.image.load', (['"""Resources/Balljump-1(2).png"""'], {}), "('Resources/Balljump-1(2).png')\n", (525, 556), False, 'import pygame\n'), ((592, 637), 'pygame.image.load', 'pygame.image.load', (['"""Resources/Balljump-2.png"""'], {}), "('Resources/Balljump-2.png')\n", (609, 637), False, 'import pygame\n'), ((673, 718), 'pygame.image.load', 'pygame.image.load', (['"""Resources/Balljump-3.png"""'], {}), "('Resources/Balljump-3.png')\n", (690, 718), False, 'import pygame\n'), ((755, 800), 'pygame.image.load', 'pygame.image.load', (['"""Resources/Balljump-4.png"""'], {}), "('Resources/Balljump-4.png')\n", (772, 800), False, 'import pygame\n'), ((845, 890), 'pygame.image.load', 'pygame.image.load', (['"""Resources/Balljump-5.png"""'], {}), "('Resources/Balljump-5.png')\n", (862, 890), False, 'import pygame\n'), ((928, 973), 'pygame.image.load', 'pygame.image.load', (['"""Resources/Balljump-6.png"""'], {}), "('Resources/Balljump-6.png')\n", (945, 973), False, 'import pygame\n'), ((3950, 3995), 'pygame.font.Font', 'pygame.font.Font', (['"""Resources/android.ttf"""', '(16)'], {}), "('Resources/android.ttf', 16)\n", (3966, 3995), False, 'import pygame\n'), ((7083, 7128), 'pygame.font.Font', 'pygame.font.Font', (['"""Resources/android.ttf"""', '(64)'], {}), "('Resources/android.ttf', 64)\n", (7099, 7128), False, 'import pygame\n'), ((7329, 7374), 'pygame.font.Font', 'pygame.font.Font', (['"""Resources/android.ttf"""', '(18)'], {}), "('Resources/android.ttf', 18)\n", (7345, 7374), False, 'import pygame\n'), ((5095, 5118), 'pygame.time.get_ticks', 'pygame.time.get_ticks', ([], {}), '()\n', (5116, 5118), False, 'import pygame\n'), ((5427, 5450), 'pygame.time.get_ticks', 'pygame.time.get_ticks', ([], {}), '()\n', (5448, 5450), False, 'import pygame\n'), ((7962, 7975), 'pygame.quit', 'pygame.quit', ([], {}), '()\n', (7973, 7975), False, 'import pygame\n')] |
tdimnet/integrations-core | datadog_cluster_agent/tests/test_datadog_cluster_agent.py | a78133a3b71a1b8377fa214d121a98647031ab06 | # (C) Datadog, Inc. 2021-present
# All rights reserved
# Licensed under a 3-clause BSD style license (see LICENSE)
from typing import Any, Dict
from datadog_checks.base.stubs.aggregator import AggregatorStub
from datadog_checks.datadog_cluster_agent import DatadogClusterAgentCheck
from datadog_checks.dev.utils import get_metadata_metrics
NAMESPACE = 'datadog.cluster_agent'
METRICS = [
'admission_webhooks.certificate_expiry',
'admission_webhooks.mutation_attempts',
'admission_webhooks.mutation_errors',
'admission_webhooks.reconcile_errors',
'admission_webhooks.reconcile_success',
'admission_webhooks.webhooks_received',
'aggregator.flush',
'aggregator.processed',
'api_requests',
'cluster_checks.busyness',
'cluster_checks.configs_dangling',
'cluster_checks.configs_dispatched',
'cluster_checks.failed_stats_collection',
'cluster_checks.nodes_reporting',
'cluster_checks.rebalancing_decisions',
'cluster_checks.rebalancing_duration_seconds',
'cluster_checks.successful_rebalancing_moves',
'cluster_checks.updating_stats_duration_seconds',
'datadog.rate_limit_queries.limit',
'datadog.rate_limit_queries.period',
'datadog.rate_limit_queries.remaining',
'datadog.rate_limit_queries.reset',
'datadog.requests',
'external_metrics',
'external_metrics.datadog_metrics',
'external_metrics.delay_seconds',
'external_metrics.processed_value',
'secret_backend.elapsed',
'go.goroutines',
'go.memstats.alloc_bytes',
'go.threads',
]
def test_check(aggregator, instance, mock_metrics_endpoint):
# type: (AggregatorStub, Dict[str, Any]) -> None
check = DatadogClusterAgentCheck('datadog_cluster_agent', {}, [instance])
# dry run to build mapping for label joins
check.check(instance)
check.check(instance)
for metric in METRICS:
aggregator.assert_metric(NAMESPACE + '.' + metric)
aggregator.assert_metric_has_tag_prefix(NAMESPACE + '.' + metric, 'is_leader:')
aggregator.assert_all_metrics_covered()
aggregator.assert_metrics_using_metadata(get_metadata_metrics())
| [((1681, 1746), 'datadog_checks.datadog_cluster_agent.DatadogClusterAgentCheck', 'DatadogClusterAgentCheck', (['"""datadog_cluster_agent"""', '{}', '[instance]'], {}), "('datadog_cluster_agent', {}, [instance])\n", (1705, 1746), False, 'from datadog_checks.datadog_cluster_agent import DatadogClusterAgentCheck\n'), ((2113, 2135), 'datadog_checks.dev.utils.get_metadata_metrics', 'get_metadata_metrics', ([], {}), '()\n', (2133, 2135), False, 'from datadog_checks.dev.utils import get_metadata_metrics\n')] |
fameshpatel/olfactorybulb | prev_ob_models/KaplanLansner2014/plotting_and_analysis/plot_results.py | 8d7a644b4560309ef177c0590ff73ed4c2432604 | import pylab
import numpy
import sys
if (len(sys.argv) < 2):
fn = raw_input("Please enter data file to be plotted\n")
else:
fn = sys.argv[1]
data = np.loadtxt(fn)
# if the first line contains crap use skiprows=1
#data = np.loadtxt(fn, skiprows=1)
fig = pylab.figure()
ax = fig.add_subplot(111)
# if you want to use multiple figures in one, use
#ax1 = fig.add_subplot(211)
#ax2 = fig.add_subplot(212)
# and
if (data.ndim == 1):
x_axis = numpy.arange(data.size)
ax.plot(x_axis, data)
else:
# ax.errorbar(data[:,0], data[:,1], yerr=data[:, 2])
# print 'mean y-value:', data[:, 1].mean()
ax.plot(data[:, 0], data[:, 1], ls='-', lw=3, c='b')
# ax.scatter(data[:,0], data[:,2])
# ax.plot(data[:,3], data[:,6])
# saving:
# fig.savefig('output_figure.png')
# otherwise nothing is shown
pylab.show()
| [((265, 279), 'pylab.figure', 'pylab.figure', ([], {}), '()\n', (277, 279), False, 'import pylab\n'), ((830, 842), 'pylab.show', 'pylab.show', ([], {}), '()\n', (840, 842), False, 'import pylab\n'), ((458, 481), 'numpy.arange', 'numpy.arange', (['data.size'], {}), '(data.size)\n', (470, 481), False, 'import numpy\n')] |
ecmwf/pyeccodes | pyeccodes/defs/grib2/tables/15/3_11_table.py | dce2c72d3adcc0cb801731366be53327ce13a00b | def load(h):
return ({'abbr': 0, 'code': 0, 'title': 'There is no appended list'},
{'abbr': 1,
'code': 1,
'title': 'Numbers define number of points corresponding to full coordinate '
'circles (i.e. parallels), coordinate values on each circle are '
'multiple of the circle mesh, and extreme coordinate values given '
'in grid definition (i.e. extreme longitudes) may not be reached in '
'all rows'},
{'abbr': 2,
'code': 2,
'title': 'Numbers define number of points corresponding to coordinate lines '
'delimited by extreme coordinate values given in grid definition '
'(i.e. extreme longitudes) which are present in each row'},
{'abbr': 3,
'code': 3,
'title': 'Numbers define the actual latitudes for each row in the grid. The '
'list of numbers are integer values of the valid latitudes in '
'microdegrees (scaled by 10-6) or in unit equal to the ratio of the '
'basic angle and the subdivisions number for each row, in the same '
'order as specified in the scanning mode flag',
'units': 'bit no. 2'},
{'abbr': None, 'code': 255, 'title': 'Missing'})
| [] |
zacharyfrederick/deep_q_gaf | lib/take2/main.py | 6b712b17a6c89c1cba0d22e18fa336369c521d4e | from __future__ import division
from lib import env_config
from lib.senior_env import BetterEnvironment
from keras.optimizers import Adam
from rl.agents.dqn import DQNAgent
from rl.policy import LinearAnnealedPolicy, BoltzmannQPolicy, EpsGreedyQPolicy
from rl.memory import SequentialMemory
from lib import models
import random
choices = [0,1,2]
def gen_action():
return random.choice(choices)
if __name__ == '__main__':
config_ = env_config.EnvConfig('config/debug.json')
env = BetterEnvironment(config_)
INPUT_SHAPE = (30, 180)
WINDOW_LENGTH = 4
model = models.build_paper_model()
# Get the environment and extract the number of actions.
nb_actions = 3
# Next, we build our model. We use the same model that was described by Mnih et al. (2015).
input_shape = (WINDOW_LENGTH,) + INPUT_SHAPE
# Finally, we configure and compile our agent. You can use every built-in Keras optimizer and
# even the metrics!
memory = SequentialMemory(limit=10000000, window_length=WINDOW_LENGTH)
# Select a policy. We use eps-greedy action selection, which means that a random action is selected
# with probability eps. We anneal eps from 1.0 to 0.1 over the course of 1M steps. This is done so that
# the agent initially explores the environment (high eps) and then gradually sticks to what it knows
# (low eps). We also set a dedicated eps value that is used during testing. Note that we set it to 0.05
# so that the agent still performs some random actions. This ensures that the agent cannot get stuck.
policy = LinearAnnealedPolicy(EpsGreedyQPolicy(), attr='eps', value_max=1., value_min=.1, value_test=.05,
nb_steps=1000000)
# The trade-off between exploration and exploitation is difficult and an on-going research topic.
# If you want, you can experiment with the parameters or use a different policy. Another popular one
# is Boltzmann-style exploration:
# policy = BoltzmannQPolicy(tau=1.)
# Feel free to give it a try!
dqn = DQNAgent(model=model, nb_actions=nb_actions, policy=policy, memory=memory,
nb_steps_warmup=50000, gamma=.99, target_model_update=10000,
train_interval=4, delta_clip=1.)
dqn.compile(Adam(lr=.00025), metrics=['mae'])
# Okay, now it's time to learn something! We capture the interrupt exception so that training
# can be prematurely aborted. Notice that now you can use the built-in Keras callbacks!
weights_filename = 'dqn_{}_weights.h5f'.format('god_help_me.weights')
dqn.fit(env, nb_steps=100000, log_interval=10000)
print(env.portfolio.print_portfolio_results())
| [((378, 400), 'random.choice', 'random.choice', (['choices'], {}), '(choices)\n', (391, 400), False, 'import random\n'), ((443, 484), 'lib.env_config.EnvConfig', 'env_config.EnvConfig', (['"""config/debug.json"""'], {}), "('config/debug.json')\n", (463, 484), False, 'from lib import env_config\n'), ((495, 521), 'lib.senior_env.BetterEnvironment', 'BetterEnvironment', (['config_'], {}), '(config_)\n', (512, 521), False, 'from lib.senior_env import BetterEnvironment\n'), ((586, 612), 'lib.models.build_paper_model', 'models.build_paper_model', ([], {}), '()\n', (610, 612), False, 'from lib import models\n'), ((977, 1038), 'rl.memory.SequentialMemory', 'SequentialMemory', ([], {'limit': '(10000000)', 'window_length': 'WINDOW_LENGTH'}), '(limit=10000000, window_length=WINDOW_LENGTH)\n', (993, 1038), False, 'from rl.memory import SequentialMemory\n'), ((2064, 2242), 'rl.agents.dqn.DQNAgent', 'DQNAgent', ([], {'model': 'model', 'nb_actions': 'nb_actions', 'policy': 'policy', 'memory': 'memory', 'nb_steps_warmup': '(50000)', 'gamma': '(0.99)', 'target_model_update': '(10000)', 'train_interval': '(4)', 'delta_clip': '(1.0)'}), '(model=model, nb_actions=nb_actions, policy=policy, memory=memory,\n nb_steps_warmup=50000, gamma=0.99, target_model_update=10000,\n train_interval=4, delta_clip=1.0)\n', (2072, 2242), False, 'from rl.agents.dqn import DQNAgent\n'), ((1605, 1623), 'rl.policy.EpsGreedyQPolicy', 'EpsGreedyQPolicy', ([], {}), '()\n', (1621, 1623), False, 'from rl.policy import LinearAnnealedPolicy, BoltzmannQPolicy, EpsGreedyQPolicy\n'), ((2281, 2297), 'keras.optimizers.Adam', 'Adam', ([], {'lr': '(0.00025)'}), '(lr=0.00025)\n', (2285, 2297), False, 'from keras.optimizers import Adam\n')] |
ShepardPower/PyMCBuilder | src/clcore.py | b247151864cc6b7bca0dc23aa87cdbb44b52defc | # I'm just the one that executes the instructions!
import sys, math, json, operator, time
import mcpi.minecraft as minecraft
from PIL import Image as pillow
from blockid import get_block
import mcpi.block as block
import functions as pymc
from tqdm import tqdm
import tkinter as tk
# Functions
# Main code
mc = minecraft.Minecraft.create()
try:
json_file = open("blocks.json")
json_put = json.load(json_file)
except:
pymc.chat(mc, "blocks.json not found, exiting!", 0)
sys.exit(1)
try:
rim = pillow.open(sys.argv[1])
except:
pymc.chat(mc, "bad image, exiting!", 0)
sys.exit(1)
orders = []
used = []
imwid, imhei = rim.size
if imhei > 200:
maxheight = 200
rim.thumbnail((200, maxheight), pillow.ANTIALIAS)
imwid, imhei = rim.size
pymc.chat(mc, "image is over 200 pixels, reducing height.", 1)
rim.convert('RGB')
im = rim.load()
pbar = tqdm(total=imhei*imwid)
for hei in range(imhei):
for wid in range(imwid):
smal = pymc.comp_pixel((im[wid, hei][0], im[wid, hei][1], im[wid, hei][2]), json_put)
im[wid, hei] = smal[1]
used.append(str(smal[2]))
pbar.update(1)
pbar.close()
rim.save("result.GIF") # The result
json_file.close()
oldPos = mc.player.getPos()
playerPos = [round(oldPos.x), round(oldPos.y), round(oldPos.z)]
pymc.chat(mc, "Ready!")
pbar = tqdm(total=imhei*imwid)
num_temp = imhei*imwid-1
for hei in range(imhei):
for wid in range(imwid):
#print(used[wid + (imhei * hei)])
gblock = get_block(used[num_temp])
mc.setBlock(playerPos[0]+wid, playerPos[1]+hei, playerPos[2], gblock)
num_temp -= 1
pbar.update(1)
pbar.close()
pymc.chat(mc, "Done!!")
pymc.chat(mc, "Please star us on github if you like the result!", 2)
| [((313, 341), 'mcpi.minecraft.Minecraft.create', 'minecraft.Minecraft.create', ([], {}), '()\n', (339, 341), True, 'import mcpi.minecraft as minecraft\n'), ((883, 908), 'tqdm.tqdm', 'tqdm', ([], {'total': '(imhei * imwid)'}), '(total=imhei * imwid)\n', (887, 908), False, 'from tqdm import tqdm\n'), ((1304, 1327), 'functions.chat', 'pymc.chat', (['mc', '"""Ready!"""'], {}), "(mc, 'Ready!')\n", (1313, 1327), True, 'import functions as pymc\n'), ((1335, 1360), 'tqdm.tqdm', 'tqdm', ([], {'total': '(imhei * imwid)'}), '(total=imhei * imwid)\n', (1339, 1360), False, 'from tqdm import tqdm\n'), ((1659, 1682), 'functions.chat', 'pymc.chat', (['mc', '"""Done!!"""'], {}), "(mc, 'Done!!')\n", (1668, 1682), True, 'import functions as pymc\n'), ((1683, 1751), 'functions.chat', 'pymc.chat', (['mc', '"""Please star us on github if you like the result!"""', '(2)'], {}), "(mc, 'Please star us on github if you like the result!', 2)\n", (1692, 1751), True, 'import functions as pymc\n'), ((398, 418), 'json.load', 'json.load', (['json_file'], {}), '(json_file)\n', (407, 418), False, 'import sys, math, json, operator, time\n'), ((514, 538), 'PIL.Image.open', 'pillow.open', (['sys.argv[1]'], {}), '(sys.argv[1])\n', (525, 538), True, 'from PIL import Image as pillow\n'), ((776, 838), 'functions.chat', 'pymc.chat', (['mc', '"""image is over 200 pixels, reducing height."""', '(1)'], {}), "(mc, 'image is over 200 pixels, reducing height.', 1)\n", (785, 838), True, 'import functions as pymc\n'), ((431, 482), 'functions.chat', 'pymc.chat', (['mc', '"""blocks.json not found, exiting!"""', '(0)'], {}), "(mc, 'blocks.json not found, exiting!', 0)\n", (440, 482), True, 'import functions as pymc\n'), ((487, 498), 'sys.exit', 'sys.exit', (['(1)'], {}), '(1)\n', (495, 498), False, 'import sys, math, json, operator, time\n'), ((551, 590), 'functions.chat', 'pymc.chat', (['mc', '"""bad image, exiting!"""', '(0)'], {}), "(mc, 'bad image, exiting!', 0)\n", (560, 590), True, 'import functions as pymc\n'), ((595, 606), 'sys.exit', 'sys.exit', (['(1)'], {}), '(1)\n', (603, 606), False, 'import sys, math, json, operator, time\n'), ((976, 1054), 'functions.comp_pixel', 'pymc.comp_pixel', (['(im[wid, hei][0], im[wid, hei][1], im[wid, hei][2])', 'json_put'], {}), '((im[wid, hei][0], im[wid, hei][1], im[wid, hei][2]), json_put)\n', (991, 1054), True, 'import functions as pymc\n'), ((1497, 1522), 'blockid.get_block', 'get_block', (['used[num_temp]'], {}), '(used[num_temp])\n', (1506, 1522), False, 'from blockid import get_block\n')] |
987Frogh/project-makehuman | gaphor/tools/gaphorconvert.py | 3afc838b03c50f8e574d8c87cb71de4435a18a6d | #!/usr/bin/python
import optparse
import os
import re
import sys
import cairo
from gaphas.painter import Context, ItemPainter
from gaphas.view import View
import gaphor.UML as UML
from gaphor.application import Application
from gaphor.storage import storage
def pkg2dir(package):
"""
Return directory path from UML package class.
"""
name = []
while package:
name.insert(0, package.name)
package = package.package
return "/".join(name)
def paint(view, cr):
view.painter.paint(Context(cairo=cr, items=view.canvas.get_all_items(), area=None))
def main(argv=sys.argv[1:]):
def message(msg):
"""
Print message if user set verbose mode.
"""
if options.verbose:
print(msg, file=sys.stderr)
usage = "usage: %prog [options] file1 file2..."
parser = optparse.OptionParser(usage=usage)
parser.add_option(
"-v", "--verbose", dest="verbose", action="store_true", help="verbose output"
)
parser.add_option(
"-u",
"--use-underscores",
dest="underscores",
action="store_true",
help="use underscores instead of spaces for output filenames",
)
parser.add_option(
"-d", "--dir", dest="dir", metavar="directory", help="output to directory"
)
parser.add_option(
"-f",
"--format",
dest="format",
metavar="format",
help="output file format, default pdf",
default="pdf",
choices=["pdf", "svg", "png"],
)
parser.add_option(
"-r",
"--regex",
dest="regex",
metavar="regex",
help="process diagrams which name matches given regular expresion;"
" name includes package name; regular expressions are case insensitive",
)
(options, args) = parser.parse_args(argv)
if not args:
parser.print_help()
Application.init(
services=["event_manager", "component_registry", "element_factory"]
)
factory = Application.get_service("element_factory")
name_re = None
if options.regex:
name_re = re.compile(options.regex, re.I)
# we should have some gaphor files to be processed at this point
for model in args:
message(f"loading model {model}")
storage.load(model, factory)
message("ready for rendering")
for diagram in factory.select(lambda e: e.isKindOf(UML.Diagram)):
odir = pkg2dir(diagram.package)
# just diagram name
dname = diagram.name
# full diagram name including package path
pname = f"{odir}/{dname}"
if options.underscores:
odir = odir.replace(" ", "_")
dname = dname.replace(" ", "_")
if name_re and not name_re.search(pname):
message(f"skipping {pname}")
continue
if options.dir:
odir = f"{options.dir}/{odir}"
outfilename = f"{odir}/{dname}.{options.format}"
if not os.path.exists(odir):
message(f"creating dir {odir}")
os.makedirs(odir)
message(f"rendering: {pname} -> {outfilename}...")
view = View(diagram.canvas)
view.painter = ItemPainter()
tmpsurface = cairo.ImageSurface(cairo.FORMAT_ARGB32, 0, 0)
tmpcr = cairo.Context(tmpsurface)
view.update_bounding_box(tmpcr)
tmpcr.show_page()
tmpsurface.flush()
w, h = view.bounding_box.width, view.bounding_box.height
if options.format == "pdf":
surface = cairo.PDFSurface(outfilename, w, h)
elif options.format == "svg":
surface = cairo.SVGSurface(outfilename, w, h)
elif options.format == "png":
surface = cairo.ImageSurface(
cairo.FORMAT_ARGB32, int(w + 1), int(h + 1)
)
else:
assert False, f"unknown format {options.format}"
cr = cairo.Context(surface)
view.matrix.translate(-view.bounding_box.x, -view.bounding_box.y)
paint(view, cr)
cr.show_page()
if options.format == "png":
surface.write_to_png(outfilename)
surface.flush()
surface.finish()
| [((852, 886), 'optparse.OptionParser', 'optparse.OptionParser', ([], {'usage': 'usage'}), '(usage=usage)\n', (873, 886), False, 'import optparse\n'), ((1901, 1990), 'gaphor.application.Application.init', 'Application.init', ([], {'services': "['event_manager', 'component_registry', 'element_factory']"}), "(services=['event_manager', 'component_registry',\n 'element_factory'])\n", (1917, 1990), False, 'from gaphor.application import Application\n'), ((2015, 2057), 'gaphor.application.Application.get_service', 'Application.get_service', (['"""element_factory"""'], {}), "('element_factory')\n", (2038, 2057), False, 'from gaphor.application import Application\n'), ((2118, 2149), 're.compile', 're.compile', (['options.regex', 're.I'], {}), '(options.regex, re.I)\n', (2128, 2149), False, 'import re\n'), ((2293, 2321), 'gaphor.storage.storage.load', 'storage.load', (['model', 'factory'], {}), '(model, factory)\n', (2305, 2321), False, 'from gaphor.storage import storage\n'), ((3241, 3261), 'gaphas.view.View', 'View', (['diagram.canvas'], {}), '(diagram.canvas)\n', (3245, 3261), False, 'from gaphas.view import View\n'), ((3289, 3302), 'gaphas.painter.ItemPainter', 'ItemPainter', ([], {}), '()\n', (3300, 3302), False, 'from gaphas.painter import Context, ItemPainter\n'), ((3329, 3374), 'cairo.ImageSurface', 'cairo.ImageSurface', (['cairo.FORMAT_ARGB32', '(0)', '(0)'], {}), '(cairo.FORMAT_ARGB32, 0, 0)\n', (3347, 3374), False, 'import cairo\n'), ((3395, 3420), 'cairo.Context', 'cairo.Context', (['tmpsurface'], {}), '(tmpsurface)\n', (3408, 3420), False, 'import cairo\n'), ((4072, 4094), 'cairo.Context', 'cairo.Context', (['surface'], {}), '(surface)\n', (4085, 4094), False, 'import cairo\n'), ((3053, 3073), 'os.path.exists', 'os.path.exists', (['odir'], {}), '(odir)\n', (3067, 3073), False, 'import os\n'), ((3139, 3156), 'os.makedirs', 'os.makedirs', (['odir'], {}), '(odir)\n', (3150, 3156), False, 'import os\n'), ((3662, 3697), 'cairo.PDFSurface', 'cairo.PDFSurface', (['outfilename', 'w', 'h'], {}), '(outfilename, w, h)\n', (3678, 3697), False, 'import cairo\n'), ((3766, 3801), 'cairo.SVGSurface', 'cairo.SVGSurface', (['outfilename', 'w', 'h'], {}), '(outfilename, w, h)\n', (3782, 3801), False, 'import cairo\n')] |
prettyirrelevant/zeta-python-sdk | zeta_python_sdk/exceptions.py | 536967259c89d380b8853b1cfd0621c50143b8b9 | class InvalidSideException(Exception):
"""Invalid side"""
class NotSupportedException(Exception):
"""Not supported by dummy wallet"""
class InvalidProductException(Exception):
"""Invalid product type"""
class OutOfBoundsException(Exception):
"""Attempt to access memory outside buffer bounds"""
| [] |
a-buntjer/tsib | test/test_ID.py | 9d6ddcdca55c9b8afb5324c0da8d0910cb1a326e | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 08 11:33:01 2016
@author: Leander Kotzur
"""
import tsib
def test_get_ID():
# parameterize a building
bdgcfg = tsib.BuildingConfiguration(
{
"refurbishment": False,
"nightReduction": False,
"occControl": False,
"capControl": True,
"n_persons": 2,
"roofOrientation": 0.0,
"n_apartments": 1,
"latitude": 49.,
"longitude": 12.,
}
)
bdgObj = tsib.Building(configurator=bdgcfg)
print('ID is : ' + str(bdgObj.ID))
return
def test_set_ID():
# parameterize a building
bdgcfg = tsib.BuildingConfiguration(
{
"buildingYear": 1980,
"n_persons": 2,
"roofOrientation": 0.0,
"n_apartments": 2,
"a_ref": 300.,
"surrounding": "Detached",
"latitude": 52.,
"longitude": 13.,
}
)
bdgObj = tsib.Building(configurator=bdgcfg)
bdgObj.ID = 'custom'
if not bdgObj.ID == 'custom':
raise ValueError()
return
| [((170, 396), 'tsib.BuildingConfiguration', 'tsib.BuildingConfiguration', (["{'refurbishment': False, 'nightReduction': False, 'occControl': False,\n 'capControl': True, 'n_persons': 2, 'roofOrientation': 0.0,\n 'n_apartments': 1, 'latitude': 49.0, 'longitude': 12.0}"], {}), "({'refurbishment': False, 'nightReduction': False,\n 'occControl': False, 'capControl': True, 'n_persons': 2,\n 'roofOrientation': 0.0, 'n_apartments': 1, 'latitude': 49.0,\n 'longitude': 12.0})\n", (196, 396), False, 'import tsib\n'), ((530, 564), 'tsib.Building', 'tsib.Building', ([], {'configurator': 'bdgcfg'}), '(configurator=bdgcfg)\n', (543, 564), False, 'import tsib\n'), ((680, 877), 'tsib.BuildingConfiguration', 'tsib.BuildingConfiguration', (["{'buildingYear': 1980, 'n_persons': 2, 'roofOrientation': 0.0,\n 'n_apartments': 2, 'a_ref': 300.0, 'surrounding': 'Detached',\n 'latitude': 52.0, 'longitude': 13.0}"], {}), "({'buildingYear': 1980, 'n_persons': 2,\n 'roofOrientation': 0.0, 'n_apartments': 2, 'a_ref': 300.0,\n 'surrounding': 'Detached', 'latitude': 52.0, 'longitude': 13.0})\n", (706, 877), False, 'import tsib\n'), ((1001, 1035), 'tsib.Building', 'tsib.Building', ([], {'configurator': 'bdgcfg'}), '(configurator=bdgcfg)\n', (1014, 1035), False, 'import tsib\n')] |
alexbarcelo/dislib | dislib/model_selection/_search.py | 989f81f235ae30b17410a8d805df258c7d931b38 | from abc import ABC, abstractmethod
from collections import defaultdict
from collections.abc import Sequence
from functools import partial
from itertools import product
import numpy as np
from pycompss.api.api import compss_wait_on
from scipy.stats import rankdata
from sklearn import clone
from sklearn.model_selection import ParameterGrid, ParameterSampler
from numpy.ma import MaskedArray
from dislib.model_selection._split import infer_cv
from dislib.model_selection._validation import check_scorer, fit_and_score, \
validate_score, aggregate_score_dicts
class BaseSearchCV(ABC):
"""Abstract base class for hyper parameter search with cross-validation."""
def __init__(self, estimator, scoring=None, cv=None, refit=True):
self.estimator = estimator
self.scoring = scoring
self.cv = cv
self.refit = refit
@abstractmethod
def _run_search(self, evaluate_candidates):
"""Abstract method to perform the search. The parameter
`evaluate_candidates` is a function that evaluates a ParameterGrid at a
time """
pass
def fit(self, x, y=None, **fit_params):
"""Run fit with all sets of parameters.
Parameters
----------
x : ds-array
Training data samples.
y : ds-array, optional (default = None)
Training data labels or values.
**fit_params : dict of string -> object
Parameters passed to the ``fit`` method of the estimator
"""
estimator = self.estimator
cv = infer_cv(self.cv)
scorers, refit_metric = self._infer_scorers()
base_estimator = clone(estimator)
n_splits = None
all_candidate_params = []
all_out = []
def evaluate_candidates(candidate_params):
"""Evaluate some parameters"""
candidate_params = list(candidate_params)
out = [fit_and_score(clone(base_estimator), train, validation,
scorer=scorers, parameters=parameters,
fit_params=fit_params)
for parameters, (train, validation)
in product(candidate_params, cv.split(x, y))]
nonlocal n_splits
n_splits = cv.get_n_splits()
all_candidate_params.extend(candidate_params)
all_out.extend(out)
self._run_search(evaluate_candidates)
for params_result in all_out:
scores = params_result[0]
for scorer_name, score in scores.items():
score = compss_wait_on(score)
scores[scorer_name] = validate_score(score, scorer_name)
results = self._format_results(all_candidate_params, scorers,
n_splits, all_out)
# For multi-metric evaluation, store the best_index_, best_params_ and
# best_score_ iff refit is one of the scorer names
# In single metric evaluation, refit_metric is "score"
if self.refit or not self.multimetric_:
# If callable, refit is expected to return the index of the best
# parameter set.
if callable(self.refit):
self.best_index_ = self.refit(results)
if not isinstance(self.best_index_, (int, np.integer)):
raise TypeError('best_index_ returned is not an integer')
if (self.best_index_ < 0 or
self.best_index_ >= len(results["params"])):
raise IndexError('best_index_ index out of range')
else:
self.best_index_ = results["rank_test_%s"
% refit_metric].argmin()
self.best_score_ = results["mean_test_%s" % refit_metric][
self.best_index_]
self.best_params_ = results["params"][self.best_index_]
if self.refit:
self.best_estimator_ = clone(base_estimator).set_params(
**self.best_params_)
self.best_estimator_.fit(x, y, **fit_params)
# Store the only scorer not as a dict for single metric evaluation
self.scorer_ = scorers if self.multimetric_ else scorers['score']
self.cv_results_ = results
self.n_splits_ = n_splits
return self
@staticmethod
def _format_results(candidate_params, scorers, n_splits, out):
n_candidates = len(candidate_params)
(test_score_dicts,) = zip(*out)
test_scores = aggregate_score_dicts(test_score_dicts)
results = {}
def _store(key_name, array, splits=False, rank=False):
"""A small helper to store the scores/times to the cv_results_"""
array = np.array(array, dtype=np.float64).reshape(n_candidates,
n_splits)
if splits:
for split_i in range(n_splits):
# Uses closure to alter the results
results["split%d_%s"
% (split_i, key_name)] = array[:, split_i]
array_means = np.mean(array, axis=1)
results['mean_%s' % key_name] = array_means
array_stds = np.std(array, axis=1)
results['std_%s' % key_name] = array_stds
if rank:
results["rank_%s" % key_name] = np.asarray(
rankdata(-array_means, method='min'), dtype=np.int32)
# Use one MaskedArray and mask all the places where the param is not
# applicable for that candidate. Use defaultdict as each candidate may
# not contain all the params
param_results = defaultdict(partial(MaskedArray,
np.empty(n_candidates, ),
mask=True,
dtype=object))
for cand_i, params in enumerate(candidate_params):
for name, value in params.items():
# An all masked empty array gets created for the key
# `"param_%s" % name` at the first occurrence of `name`.
# Setting the value at an index also unmasks that index
param_results["param_%s" % name][cand_i] = value
results.update(param_results)
# Store a list of param dicts at the key 'params'
results['params'] = candidate_params
for scorer_name in scorers.keys():
_store('test_%s' % scorer_name, test_scores[scorer_name],
splits=True, rank=True)
return results
def _infer_scorers(self):
estimator = self.estimator
scoring = self.scoring
refit = self.refit
if scoring is None or callable(scoring):
scorers = {"score": check_scorer(estimator, scoring)}
refit_metric = 'score'
self.multimetric_ = False
elif isinstance(scoring, dict):
scorers = {key: check_scorer(estimator, scorer)
for key, scorer in scoring.items()}
if refit is not False and (
not isinstance(refit, str) or
refit not in scorers) and not callable(refit):
raise ValueError("For multi-metric scoring, the parameter "
"refit must be set to a scorer key or a "
"callable to refit an estimator with the "
"best parameter setting on the whole "
"data and make the best_* attributes "
"available for that metric. If this is "
"not needed, refit should be set to "
"False explicitly. %r was passed."
% refit)
refit_metric = refit
self.multimetric_ = True
else:
raise ValueError('scoring is not valid')
return scorers, refit_metric
class GridSearchCV(BaseSearchCV):
"""Exhaustive search over specified parameter values for an estimator.
GridSearchCV implements a "fit" and a "score" method.
The parameters of the estimator used to apply these methods are optimized
by cross-validated grid-search over a parameter grid.
Parameters
----------
estimator : estimator object.
This is assumed to implement the scikit-learn estimator interface.
Either estimator needs to provide a ``score`` function,
or ``scoring`` must be passed.
param_grid : dict or list of dictionaries
Dictionary with parameters names (string) as keys and lists of
parameter settings to try as values, or a list of such
dictionaries, in which case the grids spanned by each dictionary
in the list are explored. This enables searching over any sequence
of parameter settings.
scoring : callable, dict or None, optional (default=None)
A callable to evaluate the predictions on the test set. It should take
3 parameters, estimator, x and y, and return a score (higher meaning
better). For evaluating multiple metrics, give a dict with names as
keys and callables as values. If None, the estimator's score method is
used.
cv : int or cv generator, optional (default=None)
Determines the cross-validation splitting strategy.
Possible inputs for cv are:
- None, to use the default 5-fold cross validation,
- integer, to specify the number of folds in a `KFold`,
- custom cv generator.
refit : boolean, string, or callable, optional (default=True)
Refit an estimator using the best found parameters on the whole
dataset.
For multiple metric evaluation, this needs to be a string denoting the
scorer that would be used to find the best parameters for refitting
the estimator at the end.
Where there are considerations other than maximum score in
choosing a best estimator, ``refit`` can be set to a function which
returns the selected ``best_index_`` given ``cv_results_``.
The refitted estimator is made available at the ``best_estimator_``
attribute and permits using ``predict`` directly on this
``GridSearchCV`` instance.
Also for multiple metric evaluation, the attributes ``best_index_``,
``best_score_`` and ``best_params_`` will only be available if
``refit`` is set and all of them will be determined w.r.t this specific
scorer. ``best_score_`` is not returned if refit is callable.
See ``scoring`` parameter to know more about multiple metric
evaluation.
Examples
--------
>>> import dislib as ds
>>> from dislib.model_selection import GridSearchCV
>>> from dislib.classification import RandomForestClassifier
>>> import numpy as np
>>> from sklearn import datasets
>>>
>>>
>>> if __name__ == '__main__':
>>> x_np, y_np = datasets.load_iris(return_X_y=True)
>>> x = ds.array(x_np, (30, 4))
>>> y = ds.array(y_np[:, np.newaxis], (30, 1))
>>> param_grid = {'n_estimators': (2, 4), 'max_depth': range(3, 5)}
>>> rf = RandomForestClassifier()
>>> searcher = GridSearchCV(rf, param_grid)
>>> searcher.fit(x, y)
>>> searcher.cv_results_
Attributes
----------
cv_results_ : dict of numpy (masked) ndarrays
A dict with keys as column headers and values as columns, that can be
imported into a pandas ``DataFrame``.
For instance the below given table:
+------------+------------+-----------------+---+---------+
|param_kernel|param_degree|split0_test_score|...|rank_t...|
+============+============+=================+===+=========+
| 'poly' | 2 | 0.80 |...| 2 |
+------------+------------+-----------------+---+---------+
| 'poly' | 3 | 0.70 |...| 4 |
+------------+------------+-----------------+---+---------+
| 'rbf' | -- | 0.80 |...| 3 |
+------------+------------+-----------------+---+---------+
| 'rbf' | -- | 0.93 |...| 1 |
+------------+------------+-----------------+---+---------+
will be represented by a ``cv_results_`` dict of::
{
'param_kernel': masked_array(data = ['poly', 'poly', 'rbf', 'rbf'],
mask = [False False False False]...),
'param_degree': masked_array(data = [2.0 3.0 -- --],
mask = [False False True True]...),
'split0_test_score' : [0.80, 0.70, 0.80, 0.93],
'split1_test_score' : [0.82, 0.50, 0.68, 0.78],
'split2_test_score' : [0.79, 0.55, 0.71, 0.93],
...
'mean_test_score' : [0.81, 0.60, 0.75, 0.85],
'std_test_score' : [0.01, 0.10, 0.05, 0.08],
'rank_test_score' : [2, 4, 3, 1],
'params' : [{'kernel': 'poly', 'degree': 2}, ...],
}
NOTES:
The key ``'params'`` is used to store a list of parameter
settings dicts for all the parameter candidates.
The ``mean_fit_time``, ``std_fit_time``, ``mean_score_time`` and
``std_score_time`` are all in seconds.
For multi-metric evaluation, the scores for all the scorers are
available in the ``cv_results_`` dict at the keys ending with that
scorer's name (``'_<scorer_name>'``) instead of ``'_score'`` shown
above ('split0_test_precision', 'mean_train_precision' etc.).
best_estimator_ : estimator or dict
Estimator that was chosen by the search, i.e. estimator
which gave highest score (or smallest loss if specified)
on the left out data. Not available if ``refit=False``.
See ``refit`` parameter for more information on allowed values.
best_score_ : float
Mean cross-validated score of the best_estimator
For multi-metric evaluation, this is present only if ``refit`` is
specified.
best_params_ : dict
Parameter setting that gave the best results on the hold out data.
For multi-metric evaluation, this is present only if ``refit`` is
specified.
best_index_ : int
The index (of the ``cv_results_`` arrays) which corresponds to the best
candidate parameter setting.
The dict at ``search.cv_results_['params'][search.best_index_]`` gives
the parameter setting for the best model, that gives the highest
mean score (``search.best_score_``).
For multi-metric evaluation, this is present only if ``refit`` is
specified.
scorer_ : function or a dict
Scorer function used on the held out data to choose the best
parameters for the model.
For multi-metric evaluation, this attribute holds the validated
``scoring`` dict which maps the scorer key to the scorer callable.
n_splits_ : int
The number of cross-validation splits (folds/iterations).
"""
def __init__(self, estimator, param_grid, scoring=None, cv=None,
refit=True):
super().__init__(estimator=estimator, scoring=scoring, cv=cv,
refit=refit)
self.param_grid = param_grid
self._check_param_grid(param_grid)
def _run_search(self, evaluate_candidates):
evaluate_candidates(ParameterGrid(self.param_grid))
@staticmethod
def _check_param_grid(param_grid):
if hasattr(param_grid, 'items'):
param_grid = [param_grid]
for p in param_grid:
for name, v in p.items():
if isinstance(v, np.ndarray) and v.ndim > 1:
raise ValueError("Parameter array should be "
"one-dimensional.")
if (isinstance(v, str) or
not isinstance(v, (np.ndarray, Sequence))):
raise ValueError(
"Parameter values for parameter ({0}) need "
"to be a sequence (but not a string) or"
" np.ndarray.".format(name))
if len(v) == 0:
raise ValueError(
"Parameter values for parameter ({0}) need "
"to be a non-empty sequence.".format(name))
class RandomizedSearchCV(BaseSearchCV):
"""Randomized search on hyper parameters.
RandomizedSearchCV implements a "fit" and a "score" method.
The parameters of the estimator used to apply these methods are optimized
by cross-validated search over parameter settings.
In contrast to GridSearchCV, not all parameter values are tried out, but
rather a fixed number of parameter settings is sampled from the specified
distributions. The number of parameter settings that are tried is
given by n_iter.
If all parameters are presented as a list,
sampling without replacement is performed. If at least one parameter
is given as a distribution, sampling with replacement is used.
Parameters
----------
estimator : estimator object.
This is assumed to implement the scikit-learn estimator interface.
Either estimator needs to provide a ``score`` function,
or ``scoring`` must be passed.
param_distributions : dict
Dictionary with parameters names (string) as keys and distributions
or lists of parameters to try. Distributions must provide a ``rvs``
method for sampling (such as those from scipy.stats.distributions).
If a list is given, it is sampled uniformly.
n_iter : int, optional (default=10)
Number of parameter settings that are sampled.
scoring : callable, dict or None, optional (default=None)
A callable to evaluate the predictions on the test set. It should take
3 parameters, estimator, x and y, and return a score (higher meaning
better). For evaluating multiple metrics, give a dict with names as
keys and callables as values. If None, the estimator's score method is
used.
cv : int or cv generator, optional (default=None)
Determines the cross-validation splitting strategy.
Possible inputs for cv are:
- None, to use the default 5-fold cross validation,
- integer, to specify the number of folds in a `KFold`,
- custom cv generator.
refit : boolean, string, or callable, optional (default=True)
Refit an estimator using the best found parameters on the whole
dataset.
For multiple metric evaluation, this needs to be a string denoting the
scorer that would be used to find the best parameters for refitting
the estimator at the end.
Where there are considerations other than maximum score in
choosing a best estimator, ``refit`` can be set to a function which
returns the selected ``best_index_`` given ``cv_results_``.
The refitted estimator is made available at the ``best_estimator_``
attribute and permits using ``predict`` directly on this
``GridSearchCV`` instance.
Also for multiple metric evaluation, the attributes ``best_index_``,
``best_score_`` and ``best_params_`` will only be available if
``refit`` is set and all of them will be determined w.r.t this specific
scorer. ``best_score_`` is not returned if refit is callable.
See ``scoring`` parameter to know more about multiple metric
evaluation.
random_state : int, RandomState instance or None, optional, default=None
Pseudo random number generator state used for random sampling of params
in param_distributions. This is not passed to each estimator.
If int, random_state is the seed used by the random number generator;
If RandomState instance, random_state is the random number generator;
If None, the random number generator is the RandomState instance used
by `np.random`.
Examples
--------
>>> import dislib as ds
>>> from dislib.model_selection import RandomizedSearchCV
>>> from dislib.classification import CascadeSVM
>>> import numpy as np
>>> import scipy.stats as stats
>>> from sklearn import datasets
>>>
>>>
>>> if __name__ == '__main__':
>>> x_np, y_np = datasets.load_iris(return_X_y=True)
>>> # Pre-shuffling required for CSVM
>>> p = np.random.permutation(len(x_np))
>>> x = ds.array(x_np[p], (30, 4))
>>> y = ds.array((y_np[p] == 0)[:, np.newaxis], (30, 1))
>>> param_distributions = {'c': stats.expon(scale=0.5),
>>> 'gamma': stats.expon(scale=10)}
>>> csvm = CascadeSVM()
>>> searcher = RandomizedSearchCV(csvm, param_distributions, n_iter=10)
>>> searcher.fit(x, y)
>>> searcher.cv_results_
Attributes
----------
cv_results_ : dict of numpy (masked) ndarrays
A dict with keys as column headers and values as columns, that can be
imported into a pandas ``DataFrame``.
For instance the below given table
+---------+-------------+-------------------+---+---------------+
| param_c | param_gamma | split0_test_score |...|rank_test_score|
+=========+=============+===================+===+===============+
| 0.193 | 1.883 | 0.82 |...| 3 |
+---------+-------------+-------------------+---+---------------+
| 1.452 | 0.327 | 0.81 |...| 2 |
+---------+-------------+-------------------+---+---------------+
| 0.926 | 3.452 | 0.94 |...| 1 |
+---------+-------------+-------------------+---+---------------+
will be represented by a ``cv_results_`` dict of::
{
'param_kernel' : masked_array(data = ['rbf', 'rbf', 'rbf'],
mask = False),
'param_gamma' : masked_array(data = [0.1 0.2 0.3], mask = False),
'split0_test_score' : [0.82, 0.81, 0.94],
'split1_test_score' : [0.66, 0.75, 0.79],
'split2_test_score' : [0.82, 0.87, 0.84],
...
'mean_test_score' : [0.76, 0.84, 0.86],
'std_test_score' : [0.01, 0.20, 0.04],
'rank_test_score' : [3, 2, 1],
'params' : [{'c' : 0.193, 'gamma' : 1.883}, ...],
}
NOTE
The key ``'params'`` is used to store a list of parameter
settings dicts for all the parameter candidates.
The ``mean_fit_time``, ``std_fit_time``, ``mean_score_time`` and
``std_score_time`` are all in seconds.
For multi-metric evaluation, the scores for all the scorers are
available in the ``cv_results_`` dict at the keys ending with that
scorer's name (``'_<scorer_name>'``) instead of ``'_score'`` shown
above. ('split0_test_precision', 'mean_train_precision' etc.)
best_estimator_ : estimator or dict
Estimator that was chosen by the search, i.e. estimator
which gave highest score (or smallest loss if specified)
on the left out data. Not available if ``refit=False``.
For multi-metric evaluation, this attribute is present only if
``refit`` is specified.
See ``refit`` parameter for more information on allowed values.
best_score_ : float
Mean cross-validated score of the best_estimator.
For multi-metric evaluation, this is not available if ``refit`` is
``False``. See ``refit`` parameter for more information.
best_params_ : dict
Parameter setting that gave the best results on the hold out data.
For multi-metric evaluation, this is not available if ``refit`` is
``False``. See ``refit`` parameter for more information.
best_index_ : int
The index (of the ``cv_results_`` arrays) which corresponds to the best
candidate parameter setting.
The dict at ``search.cv_results_['params'][search.best_index_]`` gives
the parameter setting for the best model, that gives the highest
mean score (``search.best_score_``).
For multi-metric evaluation, this is not available if ``refit`` is
``False``. See ``refit`` parameter for more information.
scorer_ : function or a dict
Scorer function used on the held out data to choose the best
parameters for the model.
For multi-metric evaluation, this attribute holds the validated
``scoring`` dict which maps the scorer key to the scorer callable.
n_splits_ : int
The number of cross-validation splits (folds/iterations).
"""
def __init__(self, estimator, param_distributions, n_iter=10, scoring=None,
cv=None, refit=True, random_state=None):
super().__init__(estimator=estimator, scoring=scoring, cv=cv,
refit=refit)
self.param_distributions = param_distributions
self.n_iter = n_iter
self.random_state = random_state
def _run_search(self, evaluate_candidates):
"""Search n_iter candidates from param_distributions"""
ps = ParameterSampler(self.param_distributions, self.n_iter,
random_state=self.random_state)
evaluate_candidates(ps)
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robseed/botanist | webapp/ui/tests/test_parse_search_results.py | 2f4fbab5d26499105a5057c86e0e6e37a2e8a727 | import os
from django.test import TestCase
from mock import patch
from ui.views import parse_search_results
FIXTURES_ROOT = os.path.join(os.path.dirname(__file__), 'fixtures')
FX = lambda *relpath: os.path.join(FIXTURES_ROOT, *relpath)
@patch('ui.views.get_repo_type')
@patch('ui.views.CODE_ROOT', '/opt/botanist/repos')
class ParseSearchResults(TestCase):
def test_duplicate_repositories_in_github_and_bitbucket(self, get_repo_type):
def se(filepath):
if 'bitbucket' in filepath:
return 'hg'
elif 'github' in filepath:
return 'git'
else:
raise Exception('thats odd')
get_repo_type.side_effect = se
with open(FX('duplicate_repositories_in_github_and_bitbucket.results.txt')) as f:
output = f.read()
results, count = parse_search_results(output, 'AbstractSendTimeJob', True)
self.assertEqual(2, count)
self.assertListEqual(['bitbucket', 'github'], results['sproutjobs'].keys())
self.assertEqual('public abstract class AbstractJob implements Job {', results['sproutjobs']['bitbucket']['files']['src/main/java/com/sproutsocial/AbstractJob.java'][0]['srcline'])
self.assertEqual('public abstract class AbstractJob implements Job {', results['sproutjobs']['github']['files']['src/main/java/com/sproutsocial/AbstractJob.java'][0]['srcline']) | [((242, 273), 'mock.patch', 'patch', (['"""ui.views.get_repo_type"""'], {}), "('ui.views.get_repo_type')\n", (247, 273), False, 'from mock import patch\n'), ((275, 325), 'mock.patch', 'patch', (['"""ui.views.CODE_ROOT"""', '"""/opt/botanist/repos"""'], {}), "('ui.views.CODE_ROOT', '/opt/botanist/repos')\n", (280, 325), False, 'from mock import patch\n'), ((141, 166), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (156, 166), False, 'import os\n'), ((202, 239), 'os.path.join', 'os.path.join', (['FIXTURES_ROOT', '*relpath'], {}), '(FIXTURES_ROOT, *relpath)\n', (214, 239), False, 'import os\n'), ((856, 913), 'ui.views.parse_search_results', 'parse_search_results', (['output', '"""AbstractSendTimeJob"""', '(True)'], {}), "(output, 'AbstractSendTimeJob', True)\n", (876, 913), False, 'from ui.views import parse_search_results\n')] |
Clariteia/api_gateway_common | minos/api_gateway/common/exceptions.py | e68095f31091699fc6cc4537bd6acf97a8dc6c3e | """
Copyright (C) 2021 Clariteia SL
This file is part of minos framework.
Minos framework can not be copied and/or distributed without the express permission of Clariteia SL.
"""
from typing import (
Any,
Type,
)
class MinosException(Exception):
"""Exception class for import packages or modules"""
__slots__ = "_message"
def __init__(self, error_message: str):
self._message = error_message
def __repr__(self):
return f"{type(self).__name__}(message={repr(self._message)})"
def __str__(self) -> str:
"""represent in a string format the error message passed during the instantiation"""
return self._message
class MinosImportException(MinosException):
pass
class MinosProtocolException(MinosException):
pass
class MinosMessageException(MinosException):
pass
class MinosConfigException(MinosException):
"""Base config exception."""
class MinosConfigDefaultAlreadySetException(MinosConfigException):
"""Exception to be raised when some config is already set as default."""
class MinosRepositoryException(MinosException):
"""Base repository exception."""
class MinosRepositoryAggregateNotFoundException(MinosRepositoryException):
"""Exception to be raised when some aggregate is not found on the repository."""
class MinosRepositoryDeletedAggregateException(MinosRepositoryException):
"""Exception to be raised when some aggregate is already deleted from the repository."""
class MinosRepositoryManuallySetAggregateIdException(MinosRepositoryException):
"""Exception to be raised when some aggregate is trying to be created with a manually set id."""
class MinosRepositoryManuallySetAggregateVersionException(MinosRepositoryException):
"""Exception to be raised when some aggregate is trying to be created with a manually set version."""
class MinosRepositoryUnknownActionException(MinosRepositoryException):
"""Exception to be raised when some entry tries to perform an unknown action."""
class MinosRepositoryNonProvidedException(MinosRepositoryException):
"""Exception to be raised when a repository is needed but none is set."""
class MinosModelException(MinosException):
"""Exception to be raised when some mandatory condition is not satisfied by a model."""
pass
class EmptyMinosModelSequenceException(MinosModelException):
"""Exception to be raised when a sequence must be not empty, but it is empty."""
pass
class MultiTypeMinosModelSequenceException(MinosModelException):
"""Exception to be raised when a sequence doesn't satisfy the condition to have the same type for each item."""
pass
class MinosModelAttributeException(MinosException):
"""Base model attributes exception."""
pass
class MinosReqAttributeException(MinosModelAttributeException):
"""Exception to be raised when some required attributes are not provided."""
pass
class MinosTypeAttributeException(MinosModelAttributeException):
"""Exception to be raised when there are any mismatching between the expected and observed attribute type."""
def __init__(self, name: str, target_type: Type, value: Any):
self.name = name
self.target_type = target_type
self.value = value
super().__init__(
f"The {repr(target_type)} expected type for {repr(name)} does not match with "
f"the given data type: {type(value)}"
)
class MinosMalformedAttributeException(MinosModelAttributeException):
"""Exception to be raised when there are any kind of problems with the type definition."""
pass
class MinosParseAttributeException(MinosModelAttributeException):
"""Exception to be raised when there are any kind of problems with the parsing logic."""
def __init__(self, name: str, value: Any, exception: Exception):
self.name = name
self.value = value
self.exception = exception
super().__init__(f"{repr(exception)} was raised while parsing {repr(name)} field with {repr(value)} value.")
class MinosAttributeValidationException(MinosModelAttributeException):
"""Exception to be raised when some fields are not valid."""
def __init__(self, name: str, value: Any):
self.name = name
self.value = value
super().__init__(f"{repr(value)} value does not pass the {repr(name)} field validation.")
| [] |
burgerdev/hostload | tsdl/tools/extensions.py | 93142628bb32923c5e6f3a8b791488d72a5c9077 | """
Extensions for pylearn2 training algorithms. Those are either reimplemented to
suit the execution model of this package, or new ones for recording metrics.
"""
import os
import cPickle as pkl
import numpy as np
from pylearn2.train_extensions import TrainExtension
from .abcs import Buildable
class BuildableTrainExtension(TrainExtension, Buildable):
"""
makes a pylearn2 TrainExtension buildable
"""
@classmethod
def build(cls, config, parent=None, graph=None, workingdir=None):
"""
build an instance of this class with given configuration dict
"""
config_copy = config.copy()
if "wd" not in config_copy:
config_copy["wd"] = workingdir
obj = super(BuildableTrainExtension, cls).build(config_copy)
return obj
def __init__(self, **kwargs):
if "workingdir" in kwargs:
self._wd = kwargs["workingdir"]
super(BuildableTrainExtension, self).__init__()
@classmethod
def get_default_config(cls):
"""
override to provide your own default configuration
"""
conf = super(BuildableTrainExtension, cls).get_default_config()
conf["wd"] = None
return conf
class PersistentTrainExtension(BuildableTrainExtension):
"""
abstract extension that can store its results (on disk, probably)
"""
def store(self):
"""
store the findings of this extension
"""
pass
class WeightKeeper(PersistentTrainExtension):
"""
keeps track of the model's weights at each monitor step
This model stores weights *per monitor step* - the list grows large pretty
quickly.
"""
_weights = []
def on_monitor(self, model, dataset, algorithm):
"""
save the model's weights
"""
self._weights.append(model.get_param_values())
def setup(self, model, dataset, algorithm):
"""
initialize the weight list
"""
self._weights = []
def get_weights(self):
"""
get weights history
"""
return self._weights
def store(self):
path = os.path.join(self._wd, "weightkeeper.pkl")
with open(path, "w") as file_:
pkl.dump(self._weights, file_)
class ProgressMonitor(PersistentTrainExtension):
"""
Makes the monitor channel's history accessible to us.
"""
_progress = np.NaN
@classmethod
def get_default_config(cls):
config = super(ProgressMonitor, cls).get_default_config()
config["channel"] = "valid_objective"
return config
def on_monitor(self, model, dataset, algorithm):
"""
save the desired channel
"""
monitor = model.monitor
channels = monitor.channels
channel = channels[self._channel]
self._progress = channel.val_record
def get_progress(self):
"""
get the value's history
"""
return self._progress
def store(self):
filename = "progress_{}.pkl".format(self._channel)
path = os.path.join(self._wd, filename)
with open(path, "w") as file_:
pkl.dump(self._progress, file_)
class MonitorBasedSaveBest(BuildableTrainExtension):
"""
similar to pylearn2's MonitorBasedSaveBest, but avoids memory hogging
(see https://github.com/lisa-lab/pylearn2/issues/1567)
"""
best_cost = np.inf
best_params = None
@classmethod
def get_default_config(cls):
config = super(MonitorBasedSaveBest, cls).get_default_config()
config["channel"] = "valid_objective"
return config
def setup(self, model, dataset, algorithm):
self.best_cost = np.inf
self.best_params = model.get_param_values()
def on_monitor(self, model, dataset, algorithm):
"""
Looks whether the model performs better than earlier. If it's the
case, saves the model.
Parameters
----------
model : pylearn2.models.model.Model
model.monitor must contain a channel with name given by
self.channel_name
dataset : pylearn2.datasets.dataset.Dataset
Not used
algorithm : TrainingAlgorithm
Not used
"""
monitor = model.monitor
channels = monitor.channels
channel = channels[self._channel]
val_record = channel.val_record
new_cost = val_record[-1]
if new_cost < self.best_cost:
self.best_cost = new_cost
self.best_params = model.get_param_values()
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Cooomma/nogi-backup-blog | nogi/utils/post_extractor.py | 19868511d2b0f0c4d06bf4a88981bbfadc4121e4 | import asyncio
from io import BytesIO
import logging
import os
import random
import time
from typing import List
from urllib.parse import urlparse
import aiohttp
from aiohttp import ClientSession, TCPConnector
import requests
from requests import Response
from tqdm import tqdm
from nogi import REQUEST_HEADERS
from nogi.db.nogi_blog_content import NogiBlogContent
from nogi.db.nogi_blog_summary import NogiBlogSummary
from nogi.storages.gcs import GCS
from nogi.utils.parsers import PostParser, generate_post_key
logger = logging.getLogger()
HEADERS = {
'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.163 Safari/537.36'
}
class PostExecutor:
def __init__(self, member: dict, summary_db: NogiBlogSummary, content_db: NogiBlogContent, gcs_client: GCS, bucket: str, concurrent: int = 4):
self._waiting_limit = concurrent
self.member = member
# DB
self.summary_db = summary_db
self.content_db = content_db
# GCS Storage
self.bucket = bucket
self.storage = gcs_client
self.storage_blog_post_prefix = os.path.join(member['roma_name'], 'post')
self.storage_blog_image_prefix = os.path.join(member['roma_name'], 'img')
# Tasks
self.todos = self.summary_db.get_missing_blog_url(member['id'])
@staticmethod
def db_transform(post_url: str, obj: dict, **kwargs) -> dict:
return dict(
member_id=kwargs.get('member_id'),
blog_key=generate_post_key(post_url),
url=post_url,
title=obj['title'],
content=obj['content'],
image_gcs_paths=kwargs.get('image_gcs_paths'),
post_gcs_path=kwargs.get('post_gcs_path'),
blog_created_at=int(obj['created_at'].timestamp()))
@staticmethod
def _get_hd_image(url: str) -> BytesIO:
first_layer_response: Response = requests.get(url, headers=HEADERS)
logger.debug(first_layer_response.cookies)
resp = requests.get(
url=url.replace('http://dcimg.awalker.jp/v/', 'http://dcimg.awalker.jp/i/'),
cookies=first_layer_response.cookies)
logger.debug(resp.status_code)
logger.debug(resp.headers)
return BytesIO(resp.content) if resp.status_code == 200 else BytesIO(bytes=b'')
def backup_images(self, image_urls: List[dict]) -> List[str]:
downloaded_image_urls = list()
for url in image_urls:
image_gcs_path = os.path.join(self.storage_blog_image_prefix,
'/'.join(urlparse(url['image_url']).path.split('/')[-5:]))
if url['high_resolution_url'] != url['image_url']:
hd_image = self._get_hd_image(url['high_resolution_url'])
if hd_image:
self.storage.upload_stream(
bucket=self.bucket,
blob_name=image_gcs_path,
content=hd_image.read(),
content_type='image/jpeg'
)
else:
image = requests.get(url=url['image_url'])
if image.status_code != 200:
logger.warning('Image Request Fail: %s', url)
continue
self.storage.upload_stream(
bucket=self.bucket,
blob_name=image_gcs_path,
content=image.content,
content_type='image/jpeg'
)
downloaded_image_urls.append(url)
return downloaded_image_urls
async def backup_content(self, session: ClientSession, post_url: str) -> str:
post_gcs_path = os.path.join(self.storage_blog_post_prefix, '/'.join(urlparse(post_url).path.split('/')[-3:]))
try:
async with session.get(url=post_url, headers=REQUEST_HEADERS) as response:
self.storage.upload_stream(
bucket=self.bucket, blob_name=post_gcs_path,
content=await response.read(), content_type='text/html')
return post_gcs_path
except aiohttp.client_exceptions.InvalidURL:
print('Invalid URL: %s' % post_url)
except aiohttp.client_exceptions.ClientConnectorError:
print('Client Connector Error: %s' % post_url)
@staticmethod
def crawl_post(url: str) -> None:
return PostParser(requests.get(url, headers=REQUEST_HEADERS).text).to_dict()
async def _run(self, url: str):
try:
async with aiohttp.ClientSession(connector=TCPConnector(verify_ssl=False)) as session:
post_gcs_path = await self.backup_content(session, url)
post = self.crawl_post(url)
images_gcs_paths = self.backup_images(post['image_urls'])
result = self.db_transform(
post_url=url, obj=post, member_id=self.member['id'], image_gcs_paths=images_gcs_paths, post_gcs_path=post_gcs_path)
self.content_db.upsert_crawled_post(result)
self.summary_db.update_crawled_result(result)
except aiohttp.client_exceptions.InvalidURL:
print('Invalid URL: %s' % url)
except aiohttp.client_exceptions.ClientConnectorError:
print('Client Connector Error: %s' % url)
except Exception:
import traceback
print('Error URL: %s' % url)
print(traceback.format_exc())
def run(self):
loop = asyncio.get_event_loop()
if self.todos:
tasks = []
for url in tqdm(self.todos, desc='Current Member: {}'.format(self.member['kanji_name']), ncols=120):
tasks.append(asyncio.ensure_future(self._run(url)))
if len(tasks) > self._waiting_limit:
loop.run_until_complete(asyncio.gather(*tasks))
tasks = []
if tasks:
loop.run_until_complete(asyncio.gather(*tasks))
slepp_second = random.randint(1, 15)
print('Sleep for %s second' % slepp_second)
time.sleep(slepp_second)
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threefoldtech/threebot_prebuilt | sandbox/lib/jumpscale/JumpscaleLibsExtra/sal_zos/gateway/dhcp.py | 1f0e1c65c14cef079cd80f73927d7c8318755c48 | from Jumpscale import j
import signal
from .. import templates
DNSMASQ = "/bin/dnsmasq --conf-file=/etc/dnsmasq.conf -d"
class DHCP:
def __init__(self, container, domain, networks):
self.container = container
self.domain = domain
self.networks = networks
def apply_config(self):
dnsmasq = templates.render("dnsmasq.conf", domain=self.domain, networks=self.networks)
self.container.upload_content("/etc/dnsmasq.conf", dnsmasq)
dhcp = templates.render("dhcp", networks=self.networks)
self.container.upload_content("/etc/dhcp", dhcp)
self.stop()
self.container.client.system(DNSMASQ, id="dhcp.{}".format(self.container.name))
# check if command is listening for dhcp
if not j.tools.timer.execute_until(self.is_running, 10):
raise j.exceptions.Base("Failed to run dnsmasq")
def is_running(self):
for port in self.container.client.info.port():
if port["network"] == "udp" and port["port"] == 53:
return True
def stop(self):
for process in self.container.client.process.list():
if "dnsmasq" in process["cmdline"]:
self.container.client.process.kill(process["pid"], signal.SIGKILL)
if not j.tools.timer.execute_until(lambda: not self.is_running(), 10):
raise j.exceptions.Base("Failed to stop DNSMASQ")
| [((774, 822), 'Jumpscale.j.tools.timer.execute_until', 'j.tools.timer.execute_until', (['self.is_running', '(10)'], {}), '(self.is_running, 10)\n', (801, 822), False, 'from Jumpscale import j\n'), ((842, 884), 'Jumpscale.j.exceptions.Base', 'j.exceptions.Base', (['"""Failed to run dnsmasq"""'], {}), "('Failed to run dnsmasq')\n", (859, 884), False, 'from Jumpscale import j\n'), ((1385, 1428), 'Jumpscale.j.exceptions.Base', 'j.exceptions.Base', (['"""Failed to stop DNSMASQ"""'], {}), "('Failed to stop DNSMASQ')\n", (1402, 1428), False, 'from Jumpscale import j\n')] |
breeze-shared-inc/python_training_01 | answer/a4_type.py | 7e918b37adbce062ae279f060bc25cfacda2fb85 | hensu_int = 17 #数字
hensu_float = 1.7 #小数点(浮動小数点)
hensu_str = "HelloWorld" #文字列
hensu_bool = True #真偽
hensu_list = [] #リスト
hensu_tuple = () #タプル
hensu_dict = {} #辞書（ディクト）型
print(type(hensu_int))
print(type(hensu_float))
print(type(hensu_str))
print(type(hensu_bool))
print(type(hensu_list))
print(type(hensu_tuple))
print(type(hensu_dict))
| [] |
UrsaLeo/LEDdebug | LEDdebug/examples/led-demo.py | 228af02468e4f3b617a50e6195931a623a4ad848 | #!/usr/bin/env python3
"""UrsaLeo LEDdebug board LED demo
Turn the LED's on one at a time, then all off"""
import time
ON = 1
OFF = 0
DELAY = 0.5 # seconds
try:
from LEDdebug import LEDdebug
except ImportError:
try:
import sys
import os
sys.path.append("..")
sys.path.append(os.path.join(os.path.dirname(__file__), '..',
'LEDdebug'))
from LEDdebug import LEDdebug
except ImportError:
print('LEDdebug import failed')
exit(0)
def main():
# Create device
device = LEDdebug()
# Turn on each LED in succession
for led in range(1, 7):
device.set_led(led, ON)
print(f'Turning LED{led} on')
time.sleep(DELAY)
print('Turning all LEDs off')
# Turn all the lights of before leaving!
device.set_leds(OFF)
if __name__ == '__main__':
main()
| [((570, 580), 'LEDdebug.LEDdebug', 'LEDdebug', ([], {}), '()\n', (578, 580), False, 'from LEDdebug import LEDdebug\n'), ((725, 742), 'time.sleep', 'time.sleep', (['DELAY'], {}), '(DELAY)\n', (735, 742), False, 'import time\n'), ((276, 297), 'sys.path.append', 'sys.path.append', (['""".."""'], {}), "('..')\n", (291, 297), False, 'import sys\n'), ((335, 360), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (350, 360), False, 'import os\n')] |
Nitin-Mane/SARS-CoV-2-xDNN-Classifier | modules/server.py | abb6a82b8ee89a041b0e26e14ec1e416c4561266 | #!/usr/bin/env python
###################################################################################
##
## Project: COVID -19 xDNN Classifier 2020
## Version: 1.0.0
## Module: Server
## Desription: The COVID -19 xDNN Classifier 2020 server.
## License: MIT
## Copyright: 2021, Asociacion De Investigacion En Inteligencia Artificial Para
## La Leucemia Peter Moss.
## Author: Nitin Mane
## Maintainer: Nitin Mane
##
## Modified: 2021-2-19
##
###################################################################################
##
## Permission is hereby granted, free of charge, to any person obtaining a copy
## of this software and associated documentation files(the "Software"), to deal
## in the Software without restriction, including without limitation the rights
## to use, copy, modify, merge, publish, distribute, sublicense, and / or sell
## copies of the Software, and to permit persons to whom the Software is
## furnished to do so, subject to the following conditions:
##
## The above copyright notice and this permission notice shall be included in all
## copies or substantial portions of the Software.
##
## THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
## IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
## FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
## AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
## LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
## OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
## SOFTWARE.
##
###################################################################################
import cv2
import json
import jsonpickle
import os
import requests
import time
import numpy as np
import tensorflow as tf
from modules.AbstractServer import AbstractServer
from flask import Flask, request, Response
from io import BytesIO
from PIL import Image
from tensorflow.keras.preprocessing import image
from tensorflow.keras.applications.vgg16 import preprocess_input
class server(AbstractServer):
""" COVID 19 xDNN Classifier 2020 Server.
This object represents the COVID 19 xDNN Classifier 2020 Server.
"""
def predict(self, req):
""" Classifies an image sent via HTTP. """
if len(req.files) != 0:
img = Image.open(req.files['file'].stream).convert('RGB')
else:
img = Image.open(BytesIO(req.data)).convert('RGB')
img = img.resize((224, 224), Image.ANTIALIAS)
np_img = tf.keras.preprocessing.image.img_to_array(img)
np_img.transpose(1, 2, 0)
#img = keras.preprocessing.image.img_to_array(img)
#img = np.array([img]) # Convert single image to a batch.
img = np.expand_dims(np_img, axis=0)
img = preprocess_input(img)
#prediction = self.predict(img)
#img = img.resize((224, 224), Image.ANTIALIAS)
#img = image.img_to_array(img)
#img = np.expand_dims(img, axis=0)
#img = preprocess_input(img)
#img = img.reshape((1,224,224,3))
return self.model.predict(img)
def request(self, img_path):
""" Sends image to the inference API endpoint. """
self.helpers.logger.info("Sending request for: " + img_path)
_, img_encoded = cv2.imencode('.png', cv2.imread(img_path))
response = requests.post(
self.addr, data=img_encoded.tostring(), headers=self.headers)
response = json.loads(response.text)
return response
def start(self):
""" Starts the server. """
app = Flask(self.helpers.credentials["iotJumpWay"]["name"])
@app.route('/Inference', methods=['POST'])
def Inference():
""" Responds to HTTP POST requests. """
self.mqtt.publish("States", {
"Type": "Prediction",
"Name": self.helpers.credentials["iotJumpWay"]["name"],
"State": "Processing",
"Message": "Processing data"
})
message = ""
prediction = self.predict(request)
print(prediction)
if prediction == 1:
message = "Acute Lymphoblastic Leukemia detected!"
diagnosis = "Positive"
elif prediction == 0:
message = "Acute Lymphoblastic Leukemia not detected!"
diagnosis = "Negative"
self.mqtt.publish("States", {
"Type": "Prediction",
"Name": self.helpers.credentials["iotJumpWay"]["name"],
"State": diagnosis,
"Message": message
})
resp = jsonpickle.encode({
'Response': 'OK',
'Message': message,
'Diagnosis': diagnosis
})
return Response(response=resp, status=200, mimetype="application/json")
app.run(host=self.helpers.credentials["server"]["ip"],
port=self.helpers.credentials["server"]["port"])
def test(self):
""" Tests the trained model via HTTP. """
totaltime = 0
files = 0
tp = 0
fp = 0
tn = 0
fn = 0
self.addr = "http://" + self.helpers.credentials["server"]["ip"] + \
':'+str(self.helpers.credentials["server"]["port"]) + '/Inference'
self.headers = {'content-type': 'image/jpeg'}
for testFile in os.listdir(self.model.testing_dir):
if os.path.splitext(testFile)[1] in self.model.valid:
start = time.time()
prediction = self.request(self.model.testing_dir + "/" + testFile)
print(prediction)
end = time.time()
benchmark = end - start
totaltime += benchmark
msg = ""
status = ""
outcome = ""
if prediction["Diagnosis"] == "Positive" and "Non-Covid" in testFile:
fp += 1
status = "incorrectly"
outcome = "(False Positive)"
elif prediction["Diagnosis"] == "Negative" and "Non-Covid" in testFile:
tn += 1
status = "correctly"
outcome = "(True Negative)"
elif prediction["Diagnosis"] == "Positive" and "Covid" in testFile:
tp += 1
status = "correctly"
outcome = "(True Positive)"
elif prediction["Diagnosis"] == "Negative" and "Covid" in testFile:
fn += 1
status = "incorrectly"
outcome = "(False Negative)"
files += 1
self.helpers.logger.info("COVID-19 xDNN Classifier " + status +
" detected " + outcome + " in " + str(benchmark) + " seconds.")
self.helpers.logger.info("Images Classified: " + str(files))
self.helpers.logger.info("True Positives: " + str(tp))
self.helpers.logger.info("False Positives: " + str(fp))
self.helpers.logger.info("True Negatives: " + str(tn))
self.helpers.logger.info("False Negatives: " + str(fn))
self.helpers.logger.info("Total Time Taken: " + str(totaltime))
| [((2531, 2577), 'tensorflow.keras.preprocessing.image.img_to_array', 'tf.keras.preprocessing.image.img_to_array', (['img'], {}), '(img)\n', (2572, 2577), True, 'import tensorflow as tf\n'), ((2728, 2758), 'numpy.expand_dims', 'np.expand_dims', (['np_img'], {'axis': '(0)'}), '(np_img, axis=0)\n', (2742, 2758), True, 'import numpy as np\n'), ((2767, 2788), 'tensorflow.keras.applications.vgg16.preprocess_input', 'preprocess_input', (['img'], {}), '(img)\n', (2783, 2788), False, 'from tensorflow.keras.applications.vgg16 import preprocess_input\n'), ((3361, 3386), 'json.loads', 'json.loads', (['response.text'], {}), '(response.text)\n', (3371, 3386), False, 'import json\n'), ((3463, 3516), 'flask.Flask', 'Flask', (["self.helpers.credentials['iotJumpWay']['name']"], {}), "(self.helpers.credentials['iotJumpWay']['name'])\n", (3468, 3516), False, 'from flask import Flask, request, Response\n'), ((4911, 4945), 'os.listdir', 'os.listdir', (['self.model.testing_dir'], {}), '(self.model.testing_dir)\n', (4921, 4945), False, 'import os\n'), ((3233, 3253), 'cv2.imread', 'cv2.imread', (['img_path'], {}), '(img_path)\n', (3243, 3253), False, 'import cv2\n'), ((4288, 4373), 'jsonpickle.encode', 'jsonpickle.encode', (["{'Response': 'OK', 'Message': message, 'Diagnosis': diagnosis}"], {}), "({'Response': 'OK', 'Message': message, 'Diagnosis':\n diagnosis})\n", (4305, 4373), False, 'import jsonpickle\n'), ((4398, 4462), 'flask.Response', 'Response', ([], {'response': 'resp', 'status': '(200)', 'mimetype': '"""application/json"""'}), "(response=resp, status=200, mimetype='application/json')\n", (4406, 4462), False, 'from flask import Flask, request, Response\n'), ((5017, 5028), 'time.time', 'time.time', ([], {}), '()\n', (5026, 5028), False, 'import time\n'), ((5132, 5143), 'time.time', 'time.time', ([], {}), '()\n', (5141, 5143), False, 'import time\n'), ((2357, 2393), 'PIL.Image.open', 'Image.open', (["req.files['file'].stream"], {}), "(req.files['file'].stream)\n", (2367, 2393), False, 'from PIL import Image\n'), ((4953, 4979), 'os.path.splitext', 'os.path.splitext', (['testFile'], {}), '(testFile)\n', (4969, 4979), False, 'import os\n'), ((2437, 2454), 'io.BytesIO', 'BytesIO', (['req.data'], {}), '(req.data)\n', (2444, 2454), False, 'from io import BytesIO\n')] |
all-of-us/raw-data-repository | rdr_service/lib_fhir/fhirclient_3_0_0/models/allergyintolerance_tests.py | d28ad957557587b03ff9c63d55dd55e0508f91d8 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Generated from FHIR 3.0.0.11832 on 2017-03-22.
# 2017, SMART Health IT.
import io
import json
import os
import unittest
from . import allergyintolerance
from .fhirdate import FHIRDate
class AllergyIntoleranceTests(unittest.TestCase):
def instantiate_from(self, filename):
datadir = os.environ.get('FHIR_UNITTEST_DATADIR') or ''
with io.open(os.path.join(datadir, filename), 'r', encoding='utf-8') as handle:
js = json.load(handle)
self.assertEqual("AllergyIntolerance", js["resourceType"])
return allergyintolerance.AllergyIntolerance(js)
def testAllergyIntolerance1(self):
inst = self.instantiate_from("allergyintolerance-example.json")
self.assertIsNotNone(inst, "Must have instantiated a AllergyIntolerance instance")
self.implAllergyIntolerance1(inst)
js = inst.as_json()
self.assertEqual("AllergyIntolerance", js["resourceType"])
inst2 = allergyintolerance.AllergyIntolerance(js)
self.implAllergyIntolerance1(inst2)
def implAllergyIntolerance1(self, inst):
self.assertEqual(inst.assertedDate.date, FHIRDate("2014-10-09T14:58:00+11:00").date)
self.assertEqual(inst.assertedDate.as_json(), "2014-10-09T14:58:00+11:00")
self.assertEqual(inst.category[0], "food")
self.assertEqual(inst.clinicalStatus, "active")
self.assertEqual(inst.code.coding[0].code, "227493005")
self.assertEqual(inst.code.coding[0].display, "Cashew nuts")
self.assertEqual(inst.code.coding[0].system, "http://snomed.info/sct")
self.assertEqual(inst.criticality, "high")
self.assertEqual(inst.id, "example")
self.assertEqual(inst.identifier[0].system, "http://acme.com/ids/patients/risks")
self.assertEqual(inst.identifier[0].value, "49476534")
self.assertEqual(inst.lastOccurrence.date, FHIRDate("2012-06").date)
self.assertEqual(inst.lastOccurrence.as_json(), "2012-06")
self.assertEqual(inst.note[0].text, "The criticality is high becasue of the observed anaphylactic reaction when challenged with cashew extract.")
self.assertEqual(inst.onsetDateTime.date, FHIRDate("2004").date)
self.assertEqual(inst.onsetDateTime.as_json(), "2004")
self.assertEqual(inst.reaction[0].description, "Challenge Protocol. Severe reaction to subcutaneous cashew extract. Epinephrine administered")
self.assertEqual(inst.reaction[0].exposureRoute.coding[0].code, "34206005")
self.assertEqual(inst.reaction[0].exposureRoute.coding[0].display, "Subcutaneous route")
self.assertEqual(inst.reaction[0].exposureRoute.coding[0].system, "http://snomed.info/sct")
self.assertEqual(inst.reaction[0].manifestation[0].coding[0].code, "39579001")
self.assertEqual(inst.reaction[0].manifestation[0].coding[0].display, "Anaphylactic reaction")
self.assertEqual(inst.reaction[0].manifestation[0].coding[0].system, "http://snomed.info/sct")
self.assertEqual(inst.reaction[0].onset.date, FHIRDate("2012-06-12").date)
self.assertEqual(inst.reaction[0].onset.as_json(), "2012-06-12")
self.assertEqual(inst.reaction[0].severity, "severe")
self.assertEqual(inst.reaction[0].substance.coding[0].code, "1160593")
self.assertEqual(inst.reaction[0].substance.coding[0].display, "cashew nut allergenic extract Injectable Product")
self.assertEqual(inst.reaction[0].substance.coding[0].system, "http://www.nlm.nih.gov/research/umls/rxnorm")
self.assertEqual(inst.reaction[1].manifestation[0].coding[0].code, "64305001")
self.assertEqual(inst.reaction[1].manifestation[0].coding[0].display, "Urticaria")
self.assertEqual(inst.reaction[1].manifestation[0].coding[0].system, "http://snomed.info/sct")
self.assertEqual(inst.reaction[1].note[0].text, "The patient reports that the onset of urticaria was within 15 minutes of eating cashews.")
self.assertEqual(inst.reaction[1].onset.date, FHIRDate("2004").date)
self.assertEqual(inst.reaction[1].onset.as_json(), "2004")
self.assertEqual(inst.reaction[1].severity, "moderate")
self.assertEqual(inst.text.status, "generated")
self.assertEqual(inst.type, "allergy")
self.assertEqual(inst.verificationStatus, "confirmed")
| [((351, 390), 'os.environ.get', 'os.environ.get', (['"""FHIR_UNITTEST_DATADIR"""'], {}), "('FHIR_UNITTEST_DATADIR')\n", (365, 390), False, 'import os\n'), ((502, 519), 'json.load', 'json.load', (['handle'], {}), '(handle)\n', (511, 519), False, 'import json\n'), ((418, 449), 'os.path.join', 'os.path.join', (['datadir', 'filename'], {}), '(datadir, filename)\n', (430, 449), False, 'import os\n')] |
PyDee/Spiders | jsparse/meijiexia/meijiexia.py | 6fc0a414060032b5ba4332302285e3fcc9a6113e | import time
import random
import requests
from lxml import etree
import pymongo
from .url_file import mjx_weibo, mjx_dy, mjx_ks, mjx_xhs
class DBMongo:
def __init__(self):
self.my_client = pymongo.MongoClient("mongodb://localhost:27017/")
# 连接数据库
self.db = self.my_client["mcn"]
def insert_2_xt(self, success_item, collection_name):
try:
collection = self.db[collection_name]
collection.insert_one(success_item) # 数据写入mongoDB
print('success!!!')
except:
print('写入数据失败')
class MJX:
def __init__(self):
self.db = DBMongo()
self.headers = {
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9',
'Accept-Encoding': 'gzip, deflate, br',
'Accept-Language': 'zh-CN,zh;q=0.9',
'Cache-Control': 'max-age=0',
'Connection': 'keep-alive',
'Cookie': 'accessId=defba4d0-9ab2-11e8-b156-7b8f577687be; qimo_seokeywords_defba4d0-9ab2-11e8-b156-7b8f577687be=; href=https%3A%2F%2Fwww.meijiexia.com%2Fmedias-118.html; ci_session=ccb97bb846cd5e0ce6538c2cc8f11ca7abc296ee; Hm_lvt_c96abf7da979015953d1d22702db6de8=1591685037,1592274339,1592278224; qimo_seosource_defba4d0-9ab2-11e8-b156-7b8f577687be=%E7%AB%99%E5%86%85; Hm_lpvt_c96abf7da979015953d1d22702db6de8=1592278238; pageViewNum=34',
'Host': 'www.meijiexia.com',
'Referer': 'https://www.meijiexia.com/medias-118.html',
'Sec-Fetch-Dest': 'document',
'Sec-Fetch-Mode': 'navigate',
'Sec-Fetch-Site': 'same-origin',
'Sec-Fetch-User': '?1',
'Upgrade-Insecure-Requests': '1',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36',
}
def get_response(self, url, collection):
proxy = self.get_proxy()
proxies = {
"http": "http://{}:{}".format(proxy.get('IP'), proxy.get('Port')),
"https": "http://{}:{}".format(proxy.get('IP'), proxy.get('Port')),
}
ret = requests.get(url, headers=self.headers, proxies=proxies)
response = etree.HTML(ret.text)
tr_list = response.xpath('//tbody[@id="qu-con"]/tr')
for tr in tr_list:
item = dict()
user_id = tr.xpath('./td[@class="td1"]/input/@value')[0]
nick_name = tr.xpath('./td[@class="td2"]/div[@class="itemMsg"]//a/text()')[0]
place = tr.xpath('./td[@class="td3"]/text()')[0]
fans_num = tr.xpath('./td[@class="td6"]/p[@class="num"]/text()')[0]
price_list = tr.xpath('./td[@class="td4"]/p')
for price_element in price_list:
classify = price_element.xpath(
'./span[@class="money"]/preceding-sibling::span[1]/text()')[0]
price = price_element.xpath('./span[@class="money"]/text()')[0]
item[classify.strip()] = price.strip()
item['fans_num'] = fans_num.strip()
item['user_id'] = user_id.strip()
item['nick_name'] = nick_name.strip()
item['place'] = place.strip()
item['plant'] = collection.split('mjx_')[1]
self.db.insert_2_xt(item, collection)
@staticmethod
def get_proxy():
proxy = [{"IP": "180.123.199.105", "Port": 21730}]
return random.choice(proxy)
def run(self):
urls = ''
for item in {'mjx_weibo': mjx_weibo, 'mjx_dy': mjx_dy, 'mjx_ks': mjx_ks, 'mjx_xhs': mjx_xhs}.keys():
if item == 'mjx_weibo':
urls = mjx_weibo
if item == 'mjx_dy':
urls = mjx_dy
if item == 'mjx_ks':
urls = mjx_ks
if item == 'mjx_xhs':
urls = mjx_xhs
for url in urls:
time.sleep(3)
print(url)
self.get_response(url, item)
if __name__ == '__main__':
mjx = MJX()
mjx.run()
| [((203, 252), 'pymongo.MongoClient', 'pymongo.MongoClient', (['"""mongodb://localhost:27017/"""'], {}), "('mongodb://localhost:27017/')\n", (222, 252), False, 'import pymongo\n'), ((2201, 2257), 'requests.get', 'requests.get', (['url'], {'headers': 'self.headers', 'proxies': 'proxies'}), '(url, headers=self.headers, proxies=proxies)\n', (2213, 2257), False, 'import requests\n'), ((2278, 2298), 'lxml.etree.HTML', 'etree.HTML', (['ret.text'], {}), '(ret.text)\n', (2288, 2298), False, 'from lxml import etree\n'), ((3488, 3508), 'random.choice', 'random.choice', (['proxy'], {}), '(proxy)\n', (3501, 3508), False, 'import random\n'), ((3962, 3975), 'time.sleep', 'time.sleep', (['(3)'], {}), '(3)\n', (3972, 3975), False, 'import time\n')] |
jamster112233/ICS_IDS | MLModules/ABD/B_PCAQDA.py | dac6abc3c8d6e840a21adedcb9e8dcfaa304b499 | import numpy as np
from keras.utils import np_utils
import pandas as pd
import sys
from sklearn.preprocessing import LabelEncoder
from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis as QDA
from sklearn.decomposition import PCA
import os
from sklearn.externals import joblib
from sklearn.metrics import f1_score
trainName = sys.argv[1]
testName = sys.argv[2]
# Create an object called iris with the iris Data
dftrain = pd.read_csv(filepath_or_buffer=trainName, header=None, sep=',')
dftest = pd.read_csv(filepath_or_buffer=testName, header=None, sep=',')
cols = ['Proto']
for i in range(1,dftrain.shape[1]):
cols.append('Byte' + str(i))
dftrain.columns=cols
dftrain.dropna(how="all", inplace=True)
dftrain.tail()
dftest.columns=cols
dftest.dropna(how="all", inplace=True)
dftest.tail()
Xtrain = dftrain.ix[:,1:dftrain.shape[1]].values
Ytrain = dftrain.ix[:,0].values
Xtest = dftest.ix[:,1:dftrain.shape[1]].values
Ytest = dftest.ix[:,0].values
encoder = LabelEncoder()
encoder.fit(Ytrain)
encYtrain = encoder.transform(Ytrain)
encoder = LabelEncoder()
encoder.fit(Ytest)
encYtest = encoder.transform(Ytest)
directory = "models/ABD/QDA/"
if not os.path.exists(directory):
os.makedirs(directory)
logfile = directory + "log-0.csv"
with open(logfile, "w") as file:
file.write("PCAlevel,acc,val_acc,f1\n")
fscores = []
accs = []
for q in xrange(1,151):
pca = PCA(n_components=q)
Xtrain_pca = pca.fit_transform(Xtrain)
Xtest_pca = pca.transform(Xtest)
clf = QDA(priors=None, reg_param=0.0)
clf.fit(Xtrain_pca, encYtrain)
trainPred = clf.predict(Xtrain_pca)
testPred = clf.predict(Xtest_pca)
score = 0.0
for i in xrange(0, len(trainPred)):
if trainPred[i] == encYtrain[i]:
score += 1
trainAcc = float(score) / len(trainPred)
score = 0.0
for i in xrange(0, len(testPred)):
if testPred[i] == encYtest[i]:
score += 1
testAcc = float(score) / len(testPred)
f1 = f1_score(encYtest, testPred)
accs.append(testAcc)
fscores.append(f1)
print("Train " + str(trainAcc))
print("Test " + str(testAcc))
print("F1 " + str(f1))
with open(logfile, "a") as file:
file.write(str(q) + "," + str(trainAcc) + "," + str(testAcc) + "," + str(f1) + "\n")
if q == 2:
joblib.dump(clf, 'QDA2.pkl')
print("Val Acc max" + str(max(accs)))
print("FMAX " + str(max(fscores)))
# print(str(q) + ":" + str((float(score)/len(classesPred)*100)) + "%")
#
# preds = classesPred
# if(len(preds) > 0):
# preds = np.array(list(encoder.inverse_transform(preds)))
#
# df = pd.crosstab(dftest['Proto'], preds, rownames=['Actual Protocol'], colnames=['Predicted Protocol'])
# df.to_csv('ConfusionMatrixLDA.csv')
| [((440, 503), 'pandas.read_csv', 'pd.read_csv', ([], {'filepath_or_buffer': 'trainName', 'header': 'None', 'sep': '""","""'}), "(filepath_or_buffer=trainName, header=None, sep=',')\n", (451, 503), True, 'import pandas as pd\n'), ((513, 575), 'pandas.read_csv', 'pd.read_csv', ([], {'filepath_or_buffer': 'testName', 'header': 'None', 'sep': '""","""'}), "(filepath_or_buffer=testName, header=None, sep=',')\n", (524, 575), True, 'import pandas as pd\n'), ((984, 998), 'sklearn.preprocessing.LabelEncoder', 'LabelEncoder', ([], {}), '()\n', (996, 998), False, 'from sklearn.preprocessing import LabelEncoder\n'), ((1068, 1082), 'sklearn.preprocessing.LabelEncoder', 'LabelEncoder', ([], {}), '()\n', (1080, 1082), False, 'from sklearn.preprocessing import LabelEncoder\n'), ((1176, 1201), 'os.path.exists', 'os.path.exists', (['directory'], {}), '(directory)\n', (1190, 1201), False, 'import os\n'), ((1207, 1229), 'os.makedirs', 'os.makedirs', (['directory'], {}), '(directory)\n', (1218, 1229), False, 'import os\n'), ((1400, 1419), 'sklearn.decomposition.PCA', 'PCA', ([], {'n_components': 'q'}), '(n_components=q)\n', (1403, 1419), False, 'from sklearn.decomposition import PCA\n'), ((1511, 1542), 'sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis', 'QDA', ([], {'priors': 'None', 'reg_param': '(0.0)'}), '(priors=None, reg_param=0.0)\n', (1514, 1542), True, 'from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis as QDA\n'), ((1994, 2022), 'sklearn.metrics.f1_score', 'f1_score', (['encYtest', 'testPred'], {}), '(encYtest, testPred)\n', (2002, 2022), False, 'from sklearn.metrics import f1_score\n'), ((2324, 2352), 'sklearn.externals.joblib.dump', 'joblib.dump', (['clf', '"""QDA2.pkl"""'], {}), "(clf, 'QDA2.pkl')\n", (2335, 2352), False, 'from sklearn.externals import joblib\n')] |
203Null/Gravity-Rush-2-Save-Loader | GR2-Save-Loader.py | 40cf8a1748449c0e019a2e57ac2b8eccd50d8917 | import struct
import json
from collections import OrderedDict
file_path = "data0002.bin"
show_offset = True
show_hash = False
loaded_data = 0
def unpack(upstream_data_set):
global loaded_data
loaded_data = loaded_data + 1
currentCursor = file.tell()
print(hex(file.tell()))
file.seek(int.from_bytes(file.read(4), byteorder='little'), 0)
variable_name = file.read(200).split(b'\x00')[0].decode('UTF8') #Use UTF8 because some strings are in Japanese
print(hex(file.tell()))
print(variable_name)
file.seek(currentCursor + 4, 0)
type = int.from_bytes(file.read(4), byteorder='little')
data_location = file.tell()
if type == 0x08: # List
list_length = int.from_bytes(file.read(4), byteorder='little')
name_hash = file.read(4).hex()
data_location = file.tell()
value = {}
for i in range(0, list_length):
unpack(value)
value = OrderedDict(sorted(value.items()))
else:
if type % 0x10 == 0x0b: # String
string_length = int.from_bytes(file.read(4), byteorder='little') - 1
data_location = type // 0x10
file.seek(data_location, 0)
try:
value = file.read(string_length).decode('UTF8')
except:
value = "ERROR EXTRACTING STRING"
file.seek(currentCursor + 0x0c, 0)
elif type == 0x09: # Float
value = struct.unpack('f', file.read(4))[0]
elif type == 0x0C: # Boolean
value = int.from_bytes(file.read(1), byteorder='little') > 0
file.seek(3, 1)
else:
value = file.read(4).hex()
print("Warring!!! Unknow type!!! %s at %s with value %s" % (hex(type), hex(file.tell()-8), value))
print()
name_hash = file.read(4).hex()
if variable_name == None:
variable_name = hex(data_location)
else:
if show_hash:
variable_name = variable_name = "%s %s" % (variable_name, name_hash)
if show_offset:
variable_name = variable_name = "%s %s" % (variable_name, hex(data_location))
print(value)
upstream_data_set[variable_name] = value
file = open(file_path, mode='rb')
data = file.read()
data_set = OrderedDict()
if len(data) > 0x40 and data[0:4] == b'ggdL':
file.seek(0x0c, 0)
numOfData = int.from_bytes(file.read(4), byteorder='little')
while loaded_data < numOfData:
unpack(data_set)
print()
print(data_set)
print()
print("Complete with %i/%i data" % (loaded_data, numOfData))
with open(r"%s.txt" % (file_path.split('.')[0]), 'w', encoding='utf-8') as json_file:
json.dump(data_set, json_file, indent=4, ensure_ascii=False)
else:
print("File Incorrect") | [((2328, 2341), 'collections.OrderedDict', 'OrderedDict', ([], {}), '()\n', (2339, 2341), False, 'from collections import OrderedDict\n'), ((2754, 2814), 'json.dump', 'json.dump', (['data_set', 'json_file'], {'indent': '(4)', 'ensure_ascii': '(False)'}), '(data_set, json_file, indent=4, ensure_ascii=False)\n', (2763, 2814), False, 'import json\n')] |
itzsoumyadip/vs | python/Recursion.py | acf32cd0bacb26e62854060e0acf5eb41b7a68c8 | ## to change recursion limit
import sys
print(sys.getrecursionlimit()) #Return the current value of the recursion limit
#1000
## change the limit
sys.setrecursionlimit(2000) # change value of the recursion limit
#2000
i=0
def greet():
global i
i+=1
print('hellow',i)
greet()
greet() # hellow 1996 then error
| [((152, 179), 'sys.setrecursionlimit', 'sys.setrecursionlimit', (['(2000)'], {}), '(2000)\n', (173, 179), False, 'import sys\n'), ((49, 72), 'sys.getrecursionlimit', 'sys.getrecursionlimit', ([], {}), '()\n', (70, 72), False, 'import sys\n')] |
andywar65/starter-fullstack | pages/tests/test_views.py | 683d6282eb02a9b967d15cd254976e67549672e9 | from django.test import TestCase, override_settings
from django.urls import reverse
from pages.models import Article, HomePage
@override_settings(USE_I18N=False)
class PageViewTest(TestCase):
@classmethod
def setUpTestData(cls):
print("\nTest page views")
# Set up non-modified objects used by all test methods
HomePage.objects.create(title="Title")
Article.objects.create(title="First", date="2022-04-09")
def test_homepage_view(self):
response = self.client.get(reverse("home"))
self.assertEqual(response.status_code, 200)
print("\n-Test Homepage status 200")
self.assertTemplateUsed(response, "pages/home.html")
print("\n-Test Homepage template")
def test_no_homepage(self):
HomePage.objects.all().delete()
response = self.client.get(reverse("home"))
self.assertEqual(response.status_code, 404)
print("\n-Test Homepage status 404")
def test_article_template(self):
response = self.client.get(
reverse(
"pages:article_detail",
kwargs={"year": 2022, "month": 4, "day": 9, "slug": "first"},
)
)
self.assertEqual(response.status_code, 200)
print("\n-Test Article status 200")
self.assertTemplateUsed(response, "pages/article_detail.html")
print("\n-Test Article template")
| [((131, 164), 'django.test.override_settings', 'override_settings', ([], {'USE_I18N': '(False)'}), '(USE_I18N=False)\n', (148, 164), False, 'from django.test import TestCase, override_settings\n'), ((346, 384), 'pages.models.HomePage.objects.create', 'HomePage.objects.create', ([], {'title': '"""Title"""'}), "(title='Title')\n", (369, 384), False, 'from pages.models import Article, HomePage\n'), ((393, 449), 'pages.models.Article.objects.create', 'Article.objects.create', ([], {'title': '"""First"""', 'date': '"""2022-04-09"""'}), "(title='First', date='2022-04-09')\n", (415, 449), False, 'from pages.models import Article, HomePage\n'), ((520, 535), 'django.urls.reverse', 'reverse', (['"""home"""'], {}), "('home')\n", (527, 535), False, 'from django.urls import reverse\n'), ((846, 861), 'django.urls.reverse', 'reverse', (['"""home"""'], {}), "('home')\n", (853, 861), False, 'from django.urls import reverse\n'), ((1046, 1143), 'django.urls.reverse', 'reverse', (['"""pages:article_detail"""'], {'kwargs': "{'year': 2022, 'month': 4, 'day': 9, 'slug': 'first'}"}), "('pages:article_detail', kwargs={'year': 2022, 'month': 4, 'day': 9,\n 'slug': 'first'})\n", (1053, 1143), False, 'from django.urls import reverse\n'), ((779, 801), 'pages.models.HomePage.objects.all', 'HomePage.objects.all', ([], {}), '()\n', (799, 801), False, 'from pages.models import Article, HomePage\n')] |
sunliwen/poco | poco/services/batch/server.py | a4b8c4ede63711eea42a444fb9d922c350855364 | #!/usr/bin/env python
import logging
import sys
sys.path.append("../../")
sys.path.append("pylib")
import time
import datetime
import pymongo
import uuid
import os
import subprocess
import os.path
import settings
from common.utils import getSiteDBCollection
sys.path.insert(0, "../../")
class LoggingManager:
def __init__(self):
self.h_console = None
self.h_file = None
logging.getLogger('').setLevel(logging.INFO)
def reconfig_h_console(self, site_id, calculation_id):
if self.h_console is not None:
self.h_console.flush()
logging.getLogger('').removeHandler(self.h_console)
self.h_console = logging.StreamHandler()
self.h_console.setLevel(logging.INFO)
formatter = logging.Formatter("%(asctime)s|" + calculation_id +
"|%(levelname)s|%(name)s|%(message)s", datefmt="%Y-%m-%d %H:%M:%S")
self.h_console.setFormatter(formatter)
logging.getLogger('').addHandler(self.h_console)
def getLogFilePath(self, site_id, calculation_id):
site_log_dir = os.path.join(settings.log_dir, site_id)
if not os.path.isdir(site_log_dir):
os.makedirs(site_log_dir)
formatted_date_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
log_file_name = "%s_%s.log" % (formatted_date_time, calculation_id)
log_file_path = os.path.join(site_log_dir, log_file_name)
return log_file_path
def reconfig_h_file(self, site_id, calculation_id):
if self.h_file is not None:
self.h_file.flush()
self.h_file.close()
logging.getLogger('').removeHandler(self.h_file)
self.h_file = logging.FileHandler(
self.getLogFilePath(site_id, calculation_id))
self.h_file.setLevel(logging.INFO)
formatter = logging.Formatter(
"%(asctime)s|%(levelname)s|%(name)s|%(message)s", datefmt="%Y-%m-%d %H:%M:%S")
self.h_file.setFormatter(formatter)
logging.getLogger('').addHandler(self.h_file)
def reconfig(self, site_id, calculation_id):
self.reconfig_h_console(site_id, calculation_id)
self.reconfig_h_file(site_id, calculation_id)
logging_manager = LoggingManager()
def getLogger():
return logging.getLogger("Batch Server")
def getBaseWorkDir(site_id, calculation_id):
site_work_dir = os.path.join(settings.work_dir, site_id)
formatted_date_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
calculation_work_dir_name = "%s_%s" % (formatted_date_time, calculation_id)
calculation_work_dir_path = os.path.join(
site_work_dir, calculation_work_dir_name)
os.makedirs(calculation_work_dir_path)
return calculation_work_dir_path
def getConnection():
if(settings.replica_set):
return pymongo.MongoReplicaSetClient(settings.mongodb_host, replicaSet=settings.replica_set)
else:
return pymongo.Connection(settings.mongodb_host)
connection = getConnection()
class ShellExecutionError(Exception):
pass
class BaseFlow:
def __init__(self, name):
self.name = name
self.jobs = []
self.dependencies = []
def dependOn(self, flow):
self.parent = flow
flow.dependencies.append(self)
def getWorkDir(self):
work_dir = os.path.join(BASE_WORK_DIR, self.name)
if not os.path.exists(work_dir):
os.makedirs(work_dir)
return work_dir
def getWorkFile(self, file_name):
return os.path.join(self.getWorkDir(), file_name)
def __call__(self):
global CALC_SUCC
writeFlowBegin(SITE_ID, self.__class__.__name__)
if self.__class__.__name__ in DISABLEDFLOWS:
getLogger().info("Flow Skipped: %s" % self.__class__.__name__)
writeFlowEnd(SITE_ID, self.__class__.__name__,
is_successful=True, is_skipped=True)
return True
else:
for job_callable in self.jobs:
if not self._execJob(job_callable):
writeFlowEnd(
SITE_ID, self.__class__.__name__, is_successful=False, is_skipped=False,
err_msg="SOME_JOBS_FAILED")
CALC_SUCC = False
return False
writeFlowEnd(SITE_ID, self.__class__.__name__,
is_successful=True, is_skipped=False)
# execute downlines
for dependency in self.dependencies:
dependency()
return True
def _exec_shell(self, command):
getLogger().info("Execute %s" % command)
#ret_code = os.system(command)
# if ret_code != 0:
# raise ShellExecutionError("Shell Execution Failed, ret_code=%s" % ret_code)
ret_code = subprocess.call(command, shell=True)
if ret_code != 0:
getLogger().error("Failed %s" % sys.stderr)
raise ShellExecutionError(
"Shell Execution Failed, ret_code=%s" % ret_code)
def _execJob(self, callable):
try:
getLogger().info("Start Job: %s.%s" %
(self.__class__.__name__, callable.__name__))
callable()
getLogger().info("Job Succ: %s.%s" %
(self.__class__.__name__, callable.__name__))
return True
except:
getLogger(
).critical("An Exception happened while running Job: %s" % callable,
exc_info=True)
# TODO: send message (email, sms)
# TODO: record exception info.
writeFailedJob(SITE_ID, self.__class__.__name__, callable.__name__)
return False
class PreprocessingFlow(BaseFlow):
def __init__(self):
BaseFlow.__init__(self, "preprocessing")
self.jobs += [self.do_backfill,
self.do_reverse_reversed_backfilled_raw_logs]
def do_backfill(self):
from preprocessing import backfiller
last_ts = None # FIXME: load correct last_ts from somewhere
bf = backfiller.BackFiller(connection, SITE_ID, last_ts,
self.getWorkFile("reversed_backfilled_raw_logs"))
last_ts = bf.start() # FIXME: save last_ts somewhere
def do_reverse_reversed_backfilled_raw_logs(self):
input_path = self.getWorkFile("reversed_backfilled_raw_logs")
output_path = self.getWorkFile("backfilled_raw_logs")
self._exec_shell("%s <%s >%s" %
(settings.tac_command, input_path, output_path))
class HiveBasedStatisticsFlow(BaseFlow):
def __init__(self):
BaseFlow.__init__(self, "hive-based-statistics")
self.jobs += [self.do_hive_based_calculations]
# Begin Hive Based Calculations
def do_hive_based_calculations(self):
from statistics.hive_based_calculations import hive_based_calculations
backfilled_raw_logs_path = self.parent.getWorkFile(
"backfilled_raw_logs")
hive_based_calculations(
connection, SITE_ID, self.getWorkDir(), backfilled_raw_logs_path)
#
# End Hive Based Calculations
class BaseSimilarityCalcFlow(BaseFlow):
def __init__(self, type):
BaseFlow.__init__(self, "similarities-calc:%s" % type)
self.type = type
self.jobs += self.getExtractUserItemMatrixJobs(
) + [self.do_sort_user_item_matrix,
self.do_calc_item_prefer_count,
self.do_calc_user_count,
self.do_emit_cooccurances,
self.do_sort_cooccurances,
self.do_count_cooccurances,
self.do_format_cooccurances_counts,
self.do_calc_item_similarities,
self.do_make_item_similarities_bi_directional,
self.do_sort_item_similarities_bi_directional,
self.do_extract_top_n,
self.do_upload_item_similarities_result]
def do_sort_user_item_matrix(self):
input_path = self.getWorkFile("user_item_matrix")
output_path = self.getWorkFile("user_item_matrix_sorted")
self._exec_shell("sort -T /cube/services/batch/temp %s > %s" %
(input_path, output_path))
def do_calc_item_prefer_count(self):
if SITE["algorithm_type"] == "llh":
input_path = self.getWorkFile("user_item_matrix_sorted")
output_path = self.getWorkFile("item_prefer_count")
self._exec_shell(
"cut -d , -f 2 %s | sort -T /cube/services/batch/temp | uniq -c > %s" %
(input_path, output_path))
def do_calc_user_count(self):
if SITE["algorithm_type"] == "llh":
input_path = self.getWorkFile("user_item_matrix_sorted")
output_path = self.getWorkFile("user_count")
self._exec_shell("cut -d , -f 1 %s | uniq | wc -l > %s" %
(input_path, output_path))
def do_emit_cooccurances(self):
from similarity_calculation.amazon.emit_cooccurances import emit_cooccurances
input_path = self.getWorkFile("user_item_matrix_sorted")
output_path = self.getWorkFile("cooccurances_not_sorted")
emit_cooccurances(input_path, output_path)
def do_sort_cooccurances(self):
input_path = self.getWorkFile("cooccurances_not_sorted")
output_path = self.getWorkFile("cooccurances_sorted")
self._exec_shell("sort -T /cube/services/batch/temp %s > %s" %
(input_path, output_path))
def do_count_cooccurances(self):
input_path = self.getWorkFile("cooccurances_sorted")
output_path = self.getWorkFile("cooccurances_counts_raw")
self._exec_shell("uniq -c %s > %s" % (input_path, output_path))
def do_format_cooccurances_counts(self):
from similarity_calculation.amazon.format_item_similarities import format_item_similarities
input_path = self.getWorkFile("cooccurances_counts_raw")
output_path = self.getWorkFile("cooccurances_counts_formatted")
format_item_similarities(input_path, output_path)
def do_calc_item_similarities(self):
if SITE["algorithm_type"] == "llh":
from similarity_calculation.loglikelihood.calc_loglikelihood import calc_loglikelihood
cooccurances_counts_path = self.getWorkFile(
"cooccurances_counts_formatted")
user_counts_path = self.getWorkFile("user_count")
item_prefer_count_path = self.getWorkFile("item_prefer_count")
output_path = self.getWorkFile("item_similarities_formatted")
calc_loglikelihood(cooccurances_counts_path,
user_counts_path, item_prefer_count_path, output_path)
else:
input_path = self.getWorkFile("cooccurances_counts_formatted")
output_path = self.getWorkFile("item_similarities_formatted")
self._exec_shell("mv %s %s" % (input_path, output_path))
def do_make_item_similarities_bi_directional(self):
from similarity_calculation.make_similarities_bidirectional import make_similarities_bidirectional
input_path = self.getWorkFile("item_similarities_formatted")
output_path = self.getWorkFile("item_similarities_bi_directional")
make_similarities_bidirectional(input_path, output_path)
def do_sort_item_similarities_bi_directional(self):
input_path = self.getWorkFile("item_similarities_bi_directional")
output_path = self.getWorkFile(
"item_similarities_bi_directional_sorted")
self._exec_shell("sort -T /cube/services/batch/temp %s > %s" %
(input_path, output_path))
def do_extract_top_n(self):
from similarity_calculation.extract_top_n import extract_top_n
input_path = self.getWorkFile(
"item_similarities_bi_directional_sorted")
output_path = self.getWorkFile("item_similarities_top_n")
n = 20
extract_top_n(input_path, output_path, n)
def do_upload_item_similarities_result(self):
from common.utils import UploadItemSimilarities
input_path = self.getWorkFile("item_similarities_top_n")
uis = UploadItemSimilarities(connection, SITE_ID, self.type)
uis(input_path)
class VSimiliarityCalcFlow(BaseSimilarityCalcFlow):
def __init__(self):
BaseSimilarityCalcFlow.__init__(self, "V")
def getExtractUserItemMatrixJobs(self):
return [self.do_extract_user_item_matrix,
self.do_de_duplicate_user_item_matrix]
def do_extract_user_item_matrix(self):
from preprocessing.extract_user_item_matrix import v_extract_user_item_matrix
input_path = self.parent.getWorkFile("backfilled_raw_logs")
output_path = self.getWorkFile("user_item_matrix_maybe_dup")
v_extract_user_item_matrix(input_path, output_path)
def do_de_duplicate_user_item_matrix(self):
input_path = self.getWorkFile("user_item_matrix_maybe_dup")
output_path = self.getWorkFile("user_item_matrix")
self._exec_shell("sort -T /cube/services/batch/temp < %s | uniq > %s" %
(input_path, output_path))
class PLOSimilarityCalcFlow(BaseSimilarityCalcFlow):
def __init__(self):
BaseSimilarityCalcFlow.__init__(self, "PLO")
def getExtractUserItemMatrixJobs(self):
return [self.do_extract_user_item_matrix,
self.do_de_duplicate_user_item_matrix]
def do_extract_user_item_matrix(self):
from preprocessing.extract_user_item_matrix import plo_extract_user_item_matrix
input_path = self.parent.getWorkFile("backfilled_raw_logs")
output_path = self.getWorkFile("user_item_matrix_maybe_dup")
plo_extract_user_item_matrix(input_path, output_path)
def do_de_duplicate_user_item_matrix(self):
input_path = self.getWorkFile("user_item_matrix_maybe_dup")
output_path = self.getWorkFile("user_item_matrix")
self._exec_shell("sort -T /cube/services/batch/temp < %s | uniq > %s" %
(input_path, output_path))
class BuyTogetherSimilarityFlow(BaseSimilarityCalcFlow):
def __init__(self):
BaseSimilarityCalcFlow.__init__(self, "BuyTogether")
def getExtractUserItemMatrixJobs(self):
return [self.do_extract_user_item_matrix,
self.do_de_duplicate_user_item_matrix]
def do_extract_user_item_matrix(self):
from preprocessing.extract_user_item_matrix import buytogether_extract_user_item_matrix
input_path = self.parent.getWorkFile("backfilled_raw_logs")
output_path = self.getWorkFile("user_item_matrix_maybe_dup")
buytogether_extract_user_item_matrix(input_path, output_path)
def do_de_duplicate_user_item_matrix(self):
input_path = self.getWorkFile("user_item_matrix_maybe_dup")
output_path = self.getWorkFile("user_item_matrix")
self._exec_shell("sort -T /cube/services/batch/temp < %s | uniq > %s" %
(input_path, output_path))
class ViewedUltimatelyBuyFlow(BaseFlow):
def __init__(self):
BaseFlow.__init__(self, "ViewedUltimatelyBuy")
self.jobs += [self.do_extract_user_view_buy_logs,
self.do_sort_user_view_buy_logs,
self.do_pair_view_buy,
self.count_pairs,
self.do_extract_user_item_matrix,
self.do_de_duplicate_user_item_matrix,
self.count_item_view,
self.upload_viewed_ultimately_buy]
def do_extract_user_view_buy_logs(self):
from viewed_ultimately_buy.extract_user_view_buy_logs import extract_user_view_buy_logs
input_path = self.parent.getWorkFile("backfilled_raw_logs")
output_path = self.getWorkFile("user_view_buy_logs")
extract_user_view_buy_logs(input_path, output_path)
def do_sort_user_view_buy_logs(self):
input_path = self.getWorkFile("user_view_buy_logs")
output_path = self.getWorkFile("user_view_buy_logs_sorted")
self._exec_shell("sort -T /cube/services/batch/temp <%s >%s" %
(input_path, output_path))
def do_pair_view_buy(self):
from viewed_ultimately_buy.pair_view_buy import pair_view_buy
input_path = self.getWorkFile("user_view_buy_logs_sorted")
output_path = self.getWorkFile("view_buy_pairs")
pair_view_buy(input_path, output_path)
def count_pairs(self):
input_path = self.getWorkFile("view_buy_pairs")
output_path = self.getWorkFile("view_buy_pairs_counted")
self._exec_shell("sort -T /cube/services/batch/temp <%s | uniq -c >%s" %
(input_path, output_path))
def do_extract_user_item_matrix(self):
from preprocessing.extract_user_item_matrix import v_extract_user_item_matrix
input_path = self.parent.getWorkFile("backfilled_raw_logs")
output_path = self.getWorkFile("user_item_matrix_maybe_dup")
v_extract_user_item_matrix(input_path, output_path)
def do_de_duplicate_user_item_matrix(self):
input_path = self.getWorkFile("user_item_matrix_maybe_dup")
output_path = self.getWorkFile("user_item_matrix")
self._exec_shell("sort -T /cube/services/batch/temp < %s | uniq > %s" %
(input_path, output_path))
def count_item_view(self):
# FIXME a hack
input_path = self.getWorkFile("user_item_matrix")
output_path = self.getWorkFile("item_view_times")
self._exec_shell(
"cut -d , -f 2 <%s | sort -T /cube/services/batch/temp | uniq -c >%s" %
(input_path, output_path))
def upload_viewed_ultimately_buy(self):
from viewed_ultimately_buy.upload_viewed_ultimately_buy import upload_viewed_ultimately_buy
item_view_times_path = self.getWorkFile("item_view_times")
view_buy_pairs_counted_path = self.getWorkFile(
"view_buy_pairs_counted")
upload_viewed_ultimately_buy(
connection, SITE_ID, item_view_times_path, view_buy_pairs_counted_path)
class EDMRelatedPreprocessingFlow(BaseFlow):
def __init__(self):
BaseFlow.__init__(self, "ViewedUltimatelyBuy")
self.jobs += [self.do_update_user_orders_collection,
self.do_generate_edm_emailing_list]
def do_update_user_orders_collection(self):
from edm_calculations import doUpdateUserOrdersCollection
doUpdateUserOrdersCollection(connection, SITE_ID)
def do_generate_edm_emailing_list(self):
from edm_calculations import generateEdmEmailingList
generateEdmEmailingList(connection, SITE_ID)
class BeginFlow(BaseFlow):
def __init__(self):
BaseFlow.__init__(self, "Root")
self.jobs += [self.begin]
def begin(self):
pass
# TODO: removed items' similarities should also be removed.
begin_flow = BeginFlow()
preprocessing_flow = PreprocessingFlow()
preprocessing_flow.dependOn(begin_flow)
hive_based_statistics_flow = HiveBasedStatisticsFlow()
hive_based_statistics_flow.dependOn(preprocessing_flow)
v_similarity_calc_flow = VSimiliarityCalcFlow()
v_similarity_calc_flow.dependOn(preprocessing_flow)
plo_similarity_calc_flow = PLOSimilarityCalcFlow()
plo_similarity_calc_flow.dependOn(preprocessing_flow)
buy_together_similarity_flow = BuyTogetherSimilarityFlow()
buy_together_similarity_flow.dependOn(preprocessing_flow)
viewed_ultimately_buy_flow = ViewedUltimatelyBuyFlow()
viewed_ultimately_buy_flow.dependOn(preprocessing_flow)
#edm_related_preprocessing_flow = EDMRelatedPreprocessingFlow()
# edm_related_preprocessing_flow.dependOn(preprocessing_flow)
def createCalculationRecord(site_id):
calculation_id = str(uuid.uuid4())
record = {
"calculation_id": calculation_id, "begin_datetime": datetime.datetime.now(),
"flows": {}}
calculation_records = getSiteDBCollection(
connection, site_id, "calculation_records")
calculation_records.save(record)
return calculation_id
def getCalculationRecord(site_id, calculation_id):
calculation_records = getSiteDBCollection(
connection, site_id, "calculation_records")
return calculation_records.find_one({"calculation_id": calculation_id})
def updateCalculationRecord(site_id, record):
calculation_records = getSiteDBCollection(
connection, site_id, "calculation_records")
calculation_records.save(record)
def writeFailedJob(site_id, flow_name, failed_job_name):
record = getCalculationRecord(SITE_ID, CALCULATION_ID)
flow_record = record["flows"][flow_name]
flow_record["failed_job_name"] = failed_job_name
updateCalculationRecord(SITE_ID, record)
def writeFlowBegin(site_id, flow_name):
record = getCalculationRecord(SITE_ID, CALCULATION_ID)
logging.info("FlowBegin: %s" % (flow_name, ))
record["flows"][flow_name] = {"begin_datetime": datetime.datetime.now()}
updateCalculationRecord(SITE_ID, record)
def writeFlowEnd(site_id, flow_name, is_successful, is_skipped, err_msg=None):
record = getCalculationRecord(SITE_ID, CALCULATION_ID)
logging.info("FlowEnd: %s" % (flow_name, ))
flow_record = record["flows"][flow_name]
flow_record["end_datetime"] = datetime.datetime.now()
flow_record["is_successful"] = is_successful
flow_record["is_skipped"] = is_skipped
if not is_successful:
flow_record["err_msg"] = err_msg
updateCalculationRecord(SITE_ID, record)
def writeCalculationEnd(site_id, is_successful, err_msg=None):
record = getCalculationRecord(SITE_ID, CALCULATION_ID)
record["end_datetime"] = datetime.datetime.now()
record["is_successful"] = is_successful
if not is_successful:
record["err_msg"] = err_msg
updateCalculationRecord(SITE_ID, record)
def getManualCalculationSites():
result = []
for site in loadSites(connection):
manual_calculation_list = connection[
"tjb-db"]["manual_calculation_list"]
record_in_db = manual_calculation_list.find_one(
{"site_id": site["site_id"]})
if record_in_db is not None:
result.append(site)
return result
def updateSiteLastUpdateTs(site_id):
sites = connection["tjb-db"]["sites"]
sites.update({"site_id": site_id},
{"$set": {"last_update_ts": time.time()}})
def is_time_okay_for_automatic_calculation():
now = datetime.datetime.now()
return now.hour >= 0 and now.hour < 6
def loadSites(connection, site_ids=None):
c_sites = connection["tjb-db"]["sites"]
if site_ids:
return [site for site in c_sites.find({'available': 'on'}) if site["site_id"] in site_ids]
else:
return [site for site in c_sites.find({'available': 'on'})]
def workOnSite(site, is_manual_calculation=False):
calculation_result = None
# Pop a job
manual_calculation_list = connection["tjb-db"]["manual_calculation_list"]
record_in_db = manual_calculation_list.find_one(
{"site_id": site["site_id"]})
if record_in_db is not None:
manual_calculation_list.remove(record_in_db)
# Proceed the job
now = time.time()
is_time_interval_okay_for_auto = (site.get("last_update_ts", None) is None
or now - site.get("last_update_ts") > site["calc_interval"])
# print site["site_id"], is_time_interval_okay_for_auto,
# is_time_okay_for_automatic_calculation()
is_automatic_calculation_okay = is_time_okay_for_automatic_calculation(
) and is_time_interval_okay_for_auto
if is_manual_calculation or is_automatic_calculation_okay:
global SITE
global SITE_ID
global DISABLEDFLOWS
global CALCULATION_ID
global CALC_SUCC
global BASE_WORK_DIR
SITE = site
SITE_ID = site["site_id"]
DISABLEDFLOWS = site.get("disabledFlows", [])
CALC_SUCC = True
CALCULATION_ID = createCalculationRecord(SITE_ID)
logging_manager.reconfig(SITE_ID, CALCULATION_ID)
BASE_WORK_DIR = getBaseWorkDir(SITE_ID, CALCULATION_ID)
try:
try:
getLogger().info("BEGIN CALCULATION ON:%s, CALCULATION_ID:%s" %
(SITE_ID, CALCULATION_ID))
# Begin workflow to do calculations
begin_flow()
writeCalculationEnd(
SITE_ID, CALC_SUCC, err_msg="SOME_FLOWS_FAILED")
if CALC_SUCC:
calculation_result = "SUCC"
else:
calculation_result = "FAIL"
except:
getLogger().critical("Unexpected Exception:", exc_info=True)
writeCalculationEnd(SITE_ID, False, "UNEXPECTED_EXCEPTION")
calculation_result = "FAIL"
finally:
getLogger(
).info("END CALCULATION ON:%s, RESULT:%s, CALCULATION_ID:%s" %
(SITE_ID, calculation_result, CALCULATION_ID))
# FIXME: save last_update_ts
updateSiteLastUpdateTs(site["site_id"])
return calculation_result
def workOnSiteWithRetries(site, is_manual_calculation=False, max_attempts=2):
current_attempts = 0
while current_attempts < max_attempts:
calculation_result = workOnSite(site, is_manual_calculation)
if calculation_result != "FAIL":
break
current_attempts += 1
if __name__ == "__main__":
os.environ["PATH"] = "%s:%s" % (getattr(settings, "extra_shell_path", ""), os.environ["PATH"])
while True:
#site_ids = ["test_with_gdian_data"]
for site in loadSites(connection):
for site in getManualCalculationSites():
workOnSiteWithRetries(site, is_manual_calculation=True)
workOnSiteWithRetries(site)
sleep_seconds = 1
time.sleep(sleep_seconds)
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makielab/django-oscar | tests/integration/basket/model_tests.py | 0a325cd0f04a4278201872b2e163868b72b6fabe | from decimal import Decimal as D
from django.test import TestCase
from oscar.apps.basket.models import Basket
from oscar.apps.partner import strategy
from oscar.test import factories
from oscar.apps.catalogue.models import Option
class TestAddingAProductToABasket(TestCase):
def setUp(self):
self.basket = Basket()
self.basket.strategy = strategy.Default()
self.product = factories.create_product()
self.record = factories.create_stockrecord(
currency='GBP',
product=self.product, price_excl_tax=D('10.00'))
self.stockinfo = factories.create_stockinfo(self.record)
self.basket.add(self.product)
def test_creates_a_line(self):
self.assertEqual(1, self.basket.num_lines)
def test_sets_line_prices(self):
line = self.basket.lines.all()[0]
self.assertEqual(line.price_incl_tax, self.stockinfo.price.incl_tax)
self.assertEqual(line.price_excl_tax, self.stockinfo.price.excl_tax)
def test_means_another_currency_product_cannot_be_added(self):
product = factories.create_product()
factories.create_stockrecord(
currency='USD', product=product, price_excl_tax=D('20.00'))
with self.assertRaises(ValueError):
self.basket.add(product)
class TestANonEmptyBasket(TestCase):
def setUp(self):
self.basket = Basket()
self.basket.strategy = strategy.Default()
self.product = factories.create_product()
self.record = factories.create_stockrecord(
self.product, price_excl_tax=D('10.00'))
self.stockinfo = factories.create_stockinfo(self.record)
self.basket.add(self.product, 10)
def test_can_be_flushed(self):
self.basket.flush()
self.assertEqual(self.basket.num_items, 0)
def test_returns_correct_product_quantity(self):
self.assertEqual(10, self.basket.product_quantity(
self.product))
def test_returns_correct_line_quantity_for_existing_product_and_stockrecord(self):
self.assertEqual(10, self.basket.line_quantity(
self.product, self.record))
def test_returns_zero_line_quantity_for_alternative_stockrecord(self):
record = factories.create_stockrecord(
self.product, price_excl_tax=D('5.00'))
self.assertEqual(0, self.basket.line_quantity(
self.product, record))
def test_returns_zero_line_quantity_for_missing_product_and_stockrecord(self):
product = factories.create_product()
record = factories.create_stockrecord(
product, price_excl_tax=D('5.00'))
self.assertEqual(0, self.basket.line_quantity(
product, record))
def test_returns_correct_quantity_for_existing_product_and_stockrecord_and_options(self):
product = factories.create_product()
record = factories.create_stockrecord(
product, price_excl_tax=D('5.00'))
option = Option.objects.create(name="Message")
options = [{"option": option, "value": "2"}]
self.basket.add(product, options=options)
self.assertEqual(0, self.basket.line_quantity(
product, record))
self.assertEqual(1, self.basket.line_quantity(
product, record, options))
class TestMergingTwoBaskets(TestCase):
def setUp(self):
self.product = factories.create_product()
self.record = factories.create_stockrecord(
self.product, price_excl_tax=D('10.00'))
self.stockinfo = factories.create_stockinfo(self.record)
self.main_basket = Basket()
self.main_basket.strategy = strategy.Default()
self.main_basket.add(self.product, quantity=2)
self.merge_basket = Basket()
self.merge_basket.strategy = strategy.Default()
self.merge_basket.add(self.product, quantity=1)
self.main_basket.merge(self.merge_basket)
def test_doesnt_sum_quantities(self):
self.assertEquals(1, self.main_basket.num_lines)
def test_changes_status_of_merge_basket(self):
self.assertEquals(Basket.MERGED, self.merge_basket.status)
class TestASubmittedBasket(TestCase):
def setUp(self):
self.basket = Basket()
self.basket.strategy = strategy.Default()
self.basket.submit()
def test_has_correct_status(self):
self.assertTrue(self.basket.is_submitted)
def test_can_be_edited(self):
self.assertFalse(self.basket.can_be_edited)
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code-watch/meltano | tests/fixtures/db/sqlite.py | 2afff73ed43669b5134dacfce61814f7f4e77a13 | import pytest
import os
import sqlalchemy
import contextlib
@pytest.fixture(scope="session")
def engine_uri(test_dir):
database_path = test_dir.joinpath("pytest_meltano.db")
try:
database_path.unlink()
except FileNotFoundError:
pass
return f"sqlite:///{database_path}"
| [((63, 94), 'pytest.fixture', 'pytest.fixture', ([], {'scope': '"""session"""'}), "(scope='session')\n", (77, 94), False, 'import pytest\n')] |
piotr-karon/realworld-starter-kit | experiments/render-tests-avg.py | 6285e4b5913fe5e99d72e9178eb4b1db246d02c9 | #!/usr/bin/env python3
import json
import os
from pathlib import Path
import numpy as np
from natsort import natsorted
try:
from docopt import docopt
from marko.ext.gfm import gfm
import pygal
from pygal.style import Style, DefaultStyle
except ImportError as e:
raise Exception('Some external dependencies not found, install them using: pip install -r requirements.txt') from e
def render():
suffix = '.avg.checks.bench.json'
suites = {}
for filepath in Path('').glob(f'*{suffix}'):
name = filepath.name[:-len(suffix)]
print(f'Loading {filepath} as {name}.')
with open(filepath) as fp:
suites[name] = json.load(fp)
names = natsorted(suites.keys())
figure_filenames = render_figures(names, suites)
out_filename = Path('bench-results.md')
with open(out_filename, 'w') as out:
cwd = os.getcwd().split(os.sep)[-2:]
print(f'# Benchmark of {", ".join(names)} in {cwd}', file=out)
notes_file = Path('notes.md')
if notes_file.exists():
print(f'Including {notes_file} in resulting Markdown.')
with notes_file.open() as fp:
out.write(fp.read())
else:
print(f'File {notes_file} does not exist, create it to include it in resulting Markdown.')
# print('## General Info & Checks', file=out)
# render_checks(names, suites, out)
print('## Graphs', file=out)
print('*The graphs are interactive, view the rendered HTML locally to enjoy it.*\n', file=out)
for filename in figure_filenames:
# Use HTML instead of Markdown image to specify the width
print(f'<img type="image/svg+xml" src="{filename}" alt="{filename}" width="49%"/>', file=out)
print(f'Markdown output written to {out_filename}.')
render_html(out_filename, Path('bench-results.html'))
def render_checks(names, suites, out):
print(f'|Check|{"|".join(names)}|', file=out)
print(f'|{"|".join(["---"] * (len(names) + 1))}|', file=out)
per_impl_checks = {name: suite['checks'] for name, suite in suites.items()}
check_names = sorted(set().union(*(checks.keys() for checks in per_impl_checks.values())))
def sanitize(value):
if type(value) is float:
value = float(f'{value:.3g}') # round to 3 significant figures
return str(int(value) if value >= 100 else value)
return str(value)
for check_name in check_names:
values = [sanitize(per_impl_checks[name].get(check_name)) for name in names]
if len(values) > 1 and len(set(values)) > 1:
values = [f'**{value}**' for value in values]
print(f'|{check_name}|{"|".join(values)}|', file=out)
FIGURE_FUNCS = []
def figure(func):
"""Simple decorator to mark a function as a figure generator."""
FIGURE_FUNCS.append(func)
return func
def render_figures(names, suites):
filenames = []
config = pygal.Config(legend_at_bottom=True, style=DefaultStyle)
for figure_func in FIGURE_FUNCS:
chart = figure_func(names, suites, config.copy())
filename = f'bench-results.{figure_func.__name__}.svg'
chart.render_to_file(filename)
filenames.append(filename)
return filenames
@figure
def startup_time_figure(names, suites, config):
all_vals = [suites[name]['startup_max'] for name in names]
mx = np.max(all_vals)
config.range = (0, mx + 0.1)
chart = pygal.Bar(config, value_formatter=lambda x: "{:0.2f}s".format(x))
chart.title = 'Czas uruchomienia (s)'
for name in names:
vals = [{'value': suites[name]['startup_avg'],
'ci': {'low': suites[name]['startup_min'], 'high': suites[name]['startup_max']}}]
# print(vals)
chart.add(name, vals)
return chart
@figure
def errors_vs_connections_figure(names, suites, config):
all_vals = [suites[name]['stats'] for name in names]
flat = [item for sublist in all_vals for item in sublist]
print(flat)
all_rates = [
div_or_none(s['request_errors_new_avg'], s['request_errors_new_avg'] + s['requests_new_avg'], scale=100) for s
in flat]
mx = np.max(all_rates)
config.range = (0, mx + mx * 0.1)
chart = pygal.Line(config, value_formatter=lambda x: "{:0.2f}%".format(x))
chart.title = 'Współczynnik liczby błędów względem liczby połączeń (%)'
connections_x_labels(chart, suites, skip=0)
for name in names:
chart.add(name, [
div_or_none(s['request_errors_new_avg'], s['request_errors_new_avg'] + s['requests_new_avg'], scale=100)
for s in suites[name]['stats'][0:]])
return chart
@figure
def requests_vs_connections_figure(names, suites, config):
vals = [[x['requests_per_s_avg'] for x in suites[name]['stats']] for name in names]
print(vals)
mx = np.max(vals)
config.range = (0, mx + mx * 0.1)
config.min_scale = 6
chart = pygal.Line(config, value_formatter=lambda x: "{:0.0f}".format(x))
chart.title = 'Liczba sukcesów na sekundę względem liczby połączeń (Zapytań/s)'
connections_x_labels(chart, suites, skip=0)
for name in names:
# print(suites[name]['stats'])
# vals = [{'value': x['requests_per_s_avg'], 'ci': {'low': x['requests_per_s_min'], 'high': x['requests_per_s_max']}} for x in suites[name]['stats']]
vals = [{'value': x['requests_per_s_avg']} for x in suites[name]['stats']]
chart.add(name, vals)
return chart
@figure
def latency_vs_connections_50_figure(names, suites, config):
return latency_vs_connections_figure(50, names, suites, config)
@figure
def latency_vs_connections_90_figure(names, suites, config):
return latency_vs_connections_figure(90, names, suites, config)
@figure
def latency_vs_connections_99_figure(names, suites, config):
return latency_vs_connections_figure(99, names, suites, config)
def latency_vs_connections_figure(percentile, names, suites, config):
all_vals = [[s[f'latency_{percentile}p_ms_avg'] for s in suites[name]['stats'][0:]] for name in names]
mx = np.max(all_vals)
mn = np.min(all_vals)
config.range = (mn - mn * .5, mx + mx * .5)
chart = pygal.Line(config, logarithmic=True, value_formatter=lambda x: "{:0.0f}".format(x))
chart.title = f'{percentile}. centyl czasu odpowiedzi względem liczby połączeń (ms)'
connections_x_labels(chart, suites, skip=0)
for name in names:
chart.add(name, [s[f'latency_{percentile}p_ms_avg']
for s in suites[name]['stats'][0:]])
return chart
@figure
def max_mem_usage_figure(names, suites, config):
all_vals = [[s['mem_usage_mb_avg'] for s in suites[name]['stats']] for name in names]
mx = np.max(all_vals)
config.range = (0, mx + .1 * mx)
chart = pygal.Line(config, value_formatter=lambda x: "{:0.0f}".format(x))
chart.title = 'Maksymalne zużycie pamięci względem liczby połączeń (MiB)'
connections_x_labels(chart, suites)
for name in names:
chart.add(name, [s['mem_usage_mb_avg'] for s in suites[name]['stats']])
return chart
@figure
def max_mem_usage_per_requests_figure(names, suites, config):
all_vals = [[div_or_none(s['mem_usage_mb_avg'], s['requests_per_s_avg']) for s in suites[name]['stats'][0:]] for name in names]
mx = np.max(all_vals)
config.range = (0, mx + .1 * mx)
config.min_scale = 6
chart = pygal.Line(config, value_formatter=lambda x: "{:0.3f}".format(x))
chart.title = 'Maksymalne zużycie pamięci per liczba sukcesów na sekundę (MiB-sekunda/Zapytanie)'
connections_x_labels(chart, suites, skip=0)
for name in names:
chart.add(name,
[div_or_none(s['mem_usage_mb_avg'], s['requests_per_s_avg']) for s in suites[name]['stats'][0:]])
return chart
@figure
def cpu_figure(names, suites, config):
mx = np.max([[s['cpu_new_s_avg'] for s in suites[name]['stats'][0:]] for name in names])
config.range = (0, mx + mx * 0.1)
chart = pygal.Line(config, value_formatter=lambda x: "{:0.3f}".format(x))
chart.title = 'Wykorzystanie czasu procesora w czasie rundy testów (sekundy CPU)'
connections_x_labels(chart, suites, skip=0)
for name in names:
chart.add(name, [s['cpu_new_s_avg'] for s in suites[name]['stats'][0:]])
return chart
@figure
def cpu_per_request_figure(names, suites, config):
mx = np.max([[div_or_none(s['cpu_new_s_avg'], s['requests_new_avg'], scale=1000) for s in
suites[name]['stats'][0:]] for name in names])
config.range = (0, mx + mx * 0.1)
chart = pygal.Line(config, value_formatter=lambda x: "{:0.3f}".format(x))
chart.title = 'Wykorzystanie czasu procesora per poprawna odpowiedź (milisekundy CPU/Req)'
connections_x_labels(chart, suites, skip=0)
for name in names:
chart.add(name, [div_or_none(s['cpu_new_s_avg'], s['requests_new_avg'], scale=1000) for s in
suites[name]['stats'][0:]])
return chart
@figure
def cpu_vs_requests_figure(names, suites, config):
all_vls = [[s['requests_total_avg'] for s in suites[name]['stats']] for name in names]
mx = np.max(all_vls)
config.range = (0, mx + mx * 0.1)
config.min_scale = 6
chart = pygal.XY(config, value_formatter=lambda x: "{:0.0f}".format(x), series_formatter=lambda x: "{:0.2f}".format(x))
chart.title = 'Skumulowana liczba poprawnych odpowiedzi względem skumulowanego czasu CPU'
chart.x_title = 'sekundy CPU'
chart.y_title = 'skumulowana liczba poprawnych odpowiedzi'
for name in names:
chart.add(name, [
{'value': (s['cpu_total_s_avg'], s['requests_total_avg']),
'label': f'After {s["connections"]} connections round.'}
for s in suites[name]['stats']
])
return chart
def connections_x_labels(chart, suites, skip=0):
chart.x_labels = [f"{s['connections']} conn's" if s['connections'] else s['message']
for s in next(iter(suites.values()))['stats']][skip:]
chart.x_label_rotation = -30
def div_or_none(numerator, denominator, scale=1):
if not denominator:
return None
return scale * numerator / denominator
HTML_PREFIX = '''<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Benchmark Report</title>
</head>
<body>
'''
HTML_SUFFIX = ''' </body>
</html>
'''
def render_html(md_file, html_file):
with open(md_file) as in_fp, open(html_file, 'w') as out_fp:
rs = in_fp.read()
html = gfm(rs)
# Replace <img> by <embed> for pygal interactivity, http://www.pygal.org/en/latest/documentation/web.html
html = html.replace('<img', '<embed')
# Replace link to md with link to .html for better browsability at HTML level.
html = html.replace('/README.md">full benchmark', '/README.html">full benchmark')
out_fp.write(HTML_PREFIX)
out_fp.write(html)
out_fp.write(HTML_SUFFIX)
print(f'HTML output written to {html_file.resolve().as_uri()}.')
if __name__ == '__main__':
# args = docopt(__doc__)
render()
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osterwood/litex | litex/build/altera/quartus.py | db20cb172dc982c5879aa8080ec7aa18de181cc5 | #
# This file is part of LiteX.
#
# Copyright (c) 2014-2019 Florent Kermarrec <florent@enjoy-digital.fr>
# Copyright (c) 2019 msloniewski <marcin.sloniewski@gmail.com>
# Copyright (c) 2019 vytautasb <v.buitvydas@limemicro.com>
# SPDX-License-Identifier: BSD-2-Clause
import os
import subprocess
import sys
import math
from shutil import which
from migen.fhdl.structure import _Fragment
from litex.build.generic_platform import Pins, IOStandard, Misc
from litex.build import tools
# IO/Placement Constraints (.qsf) ------------------------------------------------------------------
def _format_constraint(c, signame, fmt_r):
# IO location constraints
if isinstance(c, Pins):
tpl = "set_location_assignment -comment \"{name}\" -to {signame} Pin_{pin}"
return tpl.format(signame=signame, name=fmt_r, pin=c.identifiers[0])
# IO standard constraints
elif isinstance(c, IOStandard):
tpl = "set_instance_assignment -name io_standard -comment \"{name}\" \"{std}\" -to {signame}"
return tpl.format(signame=signame, name=fmt_r, std=c.name)
# Others constraints
elif isinstance(c, Misc):
if not isinstance(c.misc, str) and len(c.misc) == 2:
tpl = "set_instance_assignment -comment \"{name}\" -name {misc[0]} \"{misc[1]}\" -to {signame}"
return tpl.format(signame=signame, name=fmt_r, misc=c.misc)
else:
tpl = "set_instance_assignment -comment \"{name}\" -name {misc} -to {signame}"
return tpl.format(signame=signame, name=fmt_r, misc=c.misc)
def _format_qsf_constraint(signame, pin, others, resname):
fmt_r = "{}:{}".format(*resname[:2])
if resname[2] is not None:
fmt_r += "." + resname[2]
fmt_c = [_format_constraint(c, signame, fmt_r) for c in ([Pins(pin)] + others)]
return '\n'.join(fmt_c)
def _build_qsf_constraints(named_sc, named_pc):
qsf = []
for sig, pins, others, resname in named_sc:
if len(pins) > 1:
for i, p in enumerate(pins):
qsf.append(_format_qsf_constraint("{}[{}]".format(sig, i), p, others, resname))
else:
qsf.append(_format_qsf_constraint(sig, pins[0], others, resname))
if named_pc:
qsf.append("\n\n".join(named_pc))
return "\n".join(qsf)
# Timing Constraints (.sdc) ------------------------------------------------------------------------
def _build_sdc(clocks, false_paths, vns, named_sc, build_name, additional_sdc_commands):
sdc = []
# Clock constraints
for clk, period in sorted(clocks.items(), key=lambda x: x[0].duid):
is_port = False
for sig, pins, others, resname in named_sc:
if sig == vns.get_name(clk):
is_port = True
if is_port:
tpl = "create_clock -name {clk} -period {period} [get_ports {{{clk}}}]"
sdc.append(tpl.format(clk=vns.get_name(clk), period=str(period)))
else:
tpl = "create_clock -name {clk} -period {period} [get_nets {{{clk}}}]"
sdc.append(tpl.format(clk=vns.get_name(clk), period=str(period)))
# False path constraints
for from_, to in sorted(false_paths, key=lambda x: (x[0].duid, x[1].duid)):
tpl = "set_false_path -from [get_clocks {{{from_}}}] -to [get_clocks {{{to}}}]"
sdc.append(tpl.format(from_=vns.get_name(from_), to=vns.get_name(to)))
# Add additional commands
sdc += additional_sdc_commands
# Generate .sdc
tools.write_to_file("{}.sdc".format(build_name), "\n".join(sdc))
# Project (.qsf) -----------------------------------------------------------------------------------
def _build_qsf(device, ips, sources, vincpaths, named_sc, named_pc, build_name, additional_qsf_commands):
qsf = []
# Set device
qsf.append("set_global_assignment -name DEVICE {}".format(device))
# Add sources
for filename, language, library in sources:
if language == "verilog": language = "systemverilog" # Enforce use of SystemVerilog
tpl = "set_global_assignment -name {lang}_FILE {path} -library {lib}"
# Do not add None type files
if language is not None:
qsf.append(tpl.format(lang=language.upper(), path=filename.replace("\\", "/"), lib=library))
# Check if the file is a header. Those should not be explicitly added to qsf,
# but rather included in include search_path
else:
if filename.endswith(".svh") or filename.endswith(".vh"):
fpath = os.path.dirname(filename)
if fpath not in vincpaths:
vincpaths.append(fpath)
# Add ips
for filename in ips:
tpl = "set_global_assignment -name QSYS_FILE {filename}"
qsf.append(tpl.replace(filename=filename.replace("\\", "/")))
# Add include paths
for path in vincpaths:
qsf.append("set_global_assignment -name SEARCH_PATH {}".format(path.replace("\\", "/")))
# Set top level
qsf.append("set_global_assignment -name top_level_entity " + build_name)
# Add io, placement constraints
qsf.append(_build_qsf_constraints(named_sc, named_pc))
# Set timing constraints
qsf.append("set_global_assignment -name SDC_FILE {}.sdc".format(build_name))
# Add additional commands
qsf += additional_qsf_commands
# Generate .qsf
tools.write_to_file("{}.qsf".format(build_name), "\n".join(qsf))
# Script -------------------------------------------------------------------------------------------
def _build_script(build_name, create_rbf):
if sys.platform in ["win32", "cygwin"]:
script_contents = "REM Autogenerated by LiteX / git: " + tools.get_litex_git_revision()
script_file = "build_" + build_name + ".bat"
else:
script_contents = "# Autogenerated by LiteX / git: " + tools.get_litex_git_revision()
script_file = "build_" + build_name + ".sh"
script_contents += """
quartus_map --read_settings_files=on --write_settings_files=off {build_name} -c {build_name}
quartus_fit --read_settings_files=off --write_settings_files=off {build_name} -c {build_name}
quartus_asm --read_settings_files=off --write_settings_files=off {build_name} -c {build_name}
quartus_sta {build_name} -c {build_name}"""
if create_rbf:
script_contents += """
if [ -f "{build_name}.sof" ]
then
quartus_cpf -c {build_name}.sof {build_name}.rbf
fi
"""
script_contents = script_contents.format(build_name=build_name)
tools.write_to_file(script_file, script_contents, force_unix=True)
return script_file
def _run_script(script):
if sys.platform in ["win32", "cygwin"]:
shell = ["cmd", "/c"]
else:
shell = ["bash"]
if which("quartus_map") is None:
msg = "Unable to find Quartus toolchain, please:\n"
msg += "- Add Quartus toolchain to your $PATH."
raise OSError(msg)
if subprocess.call(shell + [script]) != 0:
raise OSError("Error occured during Quartus's script execution.")
# AlteraQuartusToolchain ---------------------------------------------------------------------------
class AlteraQuartusToolchain:
attr_translate = {}
def __init__(self):
self.clocks = dict()
self.false_paths = set()
self.additional_sdc_commands = []
self.additional_qsf_commands = []
def build(self, platform, fragment,
build_dir = "build",
build_name = "top",
run = True,
**kwargs):
# Create build directory
cwd = os.getcwd()
os.makedirs(build_dir, exist_ok=True)
os.chdir(build_dir)
# Finalize design
if not isinstance(fragment, _Fragment):
fragment = fragment.get_fragment()
platform.finalize(fragment)
# Generate verilog
v_output = platform.get_verilog(fragment, name=build_name, **kwargs)
named_sc, named_pc = platform.resolve_signals(v_output.ns)
v_file = build_name + ".v"
v_output.write(v_file)
platform.add_source(v_file)
# Generate design timing constraints file (.sdc)
_build_sdc(
clocks = self.clocks,
false_paths = self.false_paths,
vns = v_output.ns,
named_sc = named_sc,
build_name = build_name,
additional_sdc_commands = self.additional_sdc_commands)
# Generate design project and location constraints file (.qsf)
_build_qsf(
device = platform.device,
ips = platform.ips,
sources = platform.sources,
vincpaths = platform.verilog_include_paths,
named_sc = named_sc,
named_pc = named_pc,
build_name = build_name,
additional_qsf_commands = self.additional_qsf_commands)
# Generate build script
script = _build_script(build_name, platform.create_rbf)
# Run
if run:
_run_script(script)
os.chdir(cwd)
return v_output.ns
def add_period_constraint(self, platform, clk, period):
clk.attr.add("keep")
period = math.floor(period*1e3)/1e3 # round to lowest picosecond
if clk in self.clocks:
if period != self.clocks[clk]:
raise ValueError("Clock already constrained to {:.2f}ns, new constraint to {:.2f}ns"
.format(self.clocks[clk], period))
self.clocks[clk] = period
def add_false_path_constraint(self, platform, from_, to):
from_.attr.add("keep")
to.attr.add("keep")
if (to, from_) not in self.false_paths:
self.false_paths.add((from_, to))
| [((6459, 6525), 'litex.build.tools.write_to_file', 'tools.write_to_file', (['script_file', 'script_contents'], {'force_unix': '(True)'}), '(script_file, script_contents, force_unix=True)\n', (6478, 6525), False, 'from litex.build import tools\n'), ((6693, 6713), 'shutil.which', 'which', (['"""quartus_map"""'], {}), "('quartus_map')\n", (6698, 6713), False, 'from shutil import which\n'), ((6874, 6907), 'subprocess.call', 'subprocess.call', (['(shell + [script])'], {}), '(shell + [script])\n', (6889, 6907), False, 'import subprocess\n'), ((7526, 7537), 'os.getcwd', 'os.getcwd', ([], {}), '()\n', (7535, 7537), False, 'import os\n'), ((7546, 7583), 'os.makedirs', 'os.makedirs', (['build_dir'], {'exist_ok': '(True)'}), '(build_dir, exist_ok=True)\n', (7557, 7583), False, 'import os\n'), ((7592, 7611), 'os.chdir', 'os.chdir', (['build_dir'], {}), '(build_dir)\n', (7600, 7611), False, 'import os\n'), ((9154, 9167), 'os.chdir', 'os.chdir', (['cwd'], {}), '(cwd)\n', (9162, 9167), False, 'import os\n'), ((5650, 5680), 'litex.build.tools.get_litex_git_revision', 'tools.get_litex_git_revision', ([], {}), '()\n', (5678, 5680), False, 'from litex.build import tools\n'), ((5807, 5837), 'litex.build.tools.get_litex_git_revision', 'tools.get_litex_git_revision', ([], {}), '()\n', (5835, 5837), False, 'from litex.build import tools\n'), ((9303, 9330), 'math.floor', 'math.floor', (['(period * 1000.0)'], {}), '(period * 1000.0)\n', (9313, 9330), False, 'import math\n'), ((4497, 4522), 'os.path.dirname', 'os.path.dirname', (['filename'], {}), '(filename)\n', (4512, 4522), False, 'import os\n'), ((1787, 1796), 'litex.build.generic_platform.Pins', 'Pins', (['pin'], {}), '(pin)\n', (1791, 1796), False, 'from litex.build.generic_platform import Pins, IOStandard, Misc\n')] |
arXiv/arxiv-canonical | arxiv/canonical/util.py | a758ed88a568f23a834288aed4dcf7039c1340cf | """Various helpers and utilities that don't belong anywhere else."""
from typing import Dict, Generic, TypeVar
KeyType = TypeVar('KeyType')
ValueType = TypeVar('ValueType')
class GenericMonoDict(Dict[KeyType, ValueType]):
"""A dict with specific key and value types."""
def __getitem__(self, key: KeyType) -> ValueType: ... | [((123, 141), 'typing.TypeVar', 'TypeVar', (['"""KeyType"""'], {}), "('KeyType')\n", (130, 141), False, 'from typing import Dict, Generic, TypeVar\n'), ((154, 174), 'typing.TypeVar', 'TypeVar', (['"""ValueType"""'], {}), "('ValueType')\n", (161, 174), False, 'from typing import Dict, Generic, TypeVar\n')] |
Glucemy/Glucemy-back | records/urls.py | c9fcf7996b3f13c67697aadd449e3e32afb1fa1b | from rest_framework.routers import DefaultRouter
from records.views import RecordViewSet
router = DefaultRouter()
router.register('', RecordViewSet, basename='records')
urlpatterns = router.urls
| [((100, 115), 'rest_framework.routers.DefaultRouter', 'DefaultRouter', ([], {}), '()\n', (113, 115), False, 'from rest_framework.routers import DefaultRouter\n')] |
polyaxon/polystores | polystores/stores/azure_store.py | 141789ef75622c80d1f3875cec6952ad3c2d5ec7 | # -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function
import os
from rhea import RheaError
from rhea import parser as rhea_parser
from azure.common import AzureHttpError
from azure.storage.blob.models import BlobPrefix
from polystores.clients.azure_client import get_blob_service_connection
from polystores.exceptions import PolyaxonStoresException
from polystores.stores.base_store import BaseStore
from polystores.utils import append_basename, check_dirname_exists, get_files_in_current_directory
# pylint:disable=arguments-differ
class AzureStore(BaseStore):
"""
Azure store Service.
"""
STORE_TYPE = BaseStore._AZURE_STORE # pylint:disable=protected-access
def __init__(self, connection=None, **kwargs):
self._connection = connection
self._account_name = kwargs.get('account_name') or kwargs.get('AZURE_ACCOUNT_NAME')
self._account_key = kwargs.get('account_key') or kwargs.get('AZURE_ACCOUNT_KEY')
self._connection_string = (
kwargs.get('connection_string') or kwargs.get('AZURE_CONNECTION_STRING'))
@property
def connection(self):
if self._connection is None:
self.set_connection(account_name=self._account_name,
account_key=self._account_key,
connection_string=self._connection_string)
return self._connection
def set_connection(self, account_name=None, account_key=None, connection_string=None):
"""
Sets a new Blob service connection.
Args:
account_name: `str`. The storage account name.
account_key: `str`. The storage account key.
connection_string: `str`. If specified, this will override all other parameters besides
request session.
Returns:
BlockBlobService instance
"""
self._connection = get_blob_service_connection(account_name=account_name,
account_key=account_key,
connection_string=connection_string)
def set_env_vars(self):
if self._account_name:
os.environ['AZURE_ACCOUNT_NAME'] = self._account_name
if self._account_key:
os.environ['AZURE_ACCOUNT_KEY'] = self._account_key
if self._connection_string:
os.environ['AZURE_CONNECTION_STRING'] = self._connection_string
@staticmethod
def parse_wasbs_url(wasbs_url):
"""
Parses and validates a wasbs url.
Returns:
tuple(container, storage_account, path).
"""
try:
spec = rhea_parser.parse_wasbs_path(wasbs_url)
return spec.container, spec.storage_account, spec.path
except RheaError as e:
raise PolyaxonStoresException(e)
def check_blob(self, blob, container_name=None):
"""
Checks if a blob exists.
Args:
blob: `str`. Name of existing blob.
container_name: `str`. Name of existing container.
Returns:
bool
"""
if not container_name:
container_name, _, blob = self.parse_wasbs_url(blob)
try:
return self.connection.get_blob_properties(
container_name,
blob
)
except AzureHttpError:
return None
def ls(self, path):
results = self.list(key=path)
return {'files': results['blobs'], 'dirs': results['prefixes']}
def list(self, key, container_name=None, path=None, delimiter='/', marker=None):
"""
Checks if a blob exists.
Args:
key: `str`. key prefix.
container_name: `str`. Name of existing container.
path: `str`. an extra path to append to the key.
delimiter: `str`. the delimiter marks key hierarchy.
marker: `str`. An opaque continuation token.
"""
if not container_name:
container_name, _, key = self.parse_wasbs_url(key)
if key and not key.endswith('/'):
key += '/'
prefix = key
if path:
prefix = os.path.join(prefix, path)
if prefix and not prefix.endswith('/'):
prefix += '/'
list_blobs = []
list_prefixes = []
while True:
results = self.connection.list_blobs(container_name,
prefix=prefix,
delimiter=delimiter,
marker=marker)
for r in results:
if isinstance(r, BlobPrefix):
name = r.name[len(key):]
list_prefixes.append(name)
else:
name = r.name[len(key):]
list_blobs.append((name, r.properties.content_length))
if results.next_marker:
marker = results.next_marker
else:
break
return {
'blobs': list_blobs,
'prefixes': list_prefixes
}
def upload_file(self, filename, blob, container_name=None, use_basename=True):
"""
Uploads a local file to Google Cloud Storage.
Args:
filename: `str`. the file to upload.
blob: `str`. blob to upload to.
container_name: `str`. the name of the container.
use_basename: `bool`. whether or not to use the basename of the filename.
"""
if not container_name:
container_name, _, blob = self.parse_wasbs_url(blob)
if use_basename:
blob = append_basename(blob, filename)
self.connection.create_blob_from_path(container_name, blob, filename)
def upload_dir(self, dirname, blob, container_name=None, use_basename=True):
"""
Uploads a local directory to to Google Cloud Storage.
Args:
dirname: `str`. name of the directory to upload.
blob: `str`. blob to upload to.
container_name: `str`. the name of the container.
use_basename: `bool`. whether or not to use the basename of the directory.
"""
if not container_name:
container_name, _, blob = self.parse_wasbs_url(blob)
if use_basename:
blob = append_basename(blob, dirname)
# Turn the path to absolute paths
dirname = os.path.abspath(dirname)
with get_files_in_current_directory(dirname) as files:
for f in files:
file_blob = os.path.join(blob, os.path.relpath(f, dirname))
self.upload_file(filename=f,
blob=file_blob,
container_name=container_name,
use_basename=False)
def download_file(self, blob, local_path, container_name=None, use_basename=True):
"""
Downloads a file from Google Cloud Storage.
Args:
blob: `str`. blob to download.
local_path: `str`. the path to download to.
container_name: `str`. the name of the container.
use_basename: `bool`. whether or not to use the basename of the blob.
"""
if not container_name:
container_name, _, blob = self.parse_wasbs_url(blob)
local_path = os.path.abspath(local_path)
if use_basename:
local_path = append_basename(local_path, blob)
check_dirname_exists(local_path)
try:
self.connection.get_blob_to_path(container_name, blob, local_path)
except AzureHttpError as e:
raise PolyaxonStoresException(e)
def download_dir(self, blob, local_path, container_name=None, use_basename=True):
"""
Download a directory from Google Cloud Storage.
Args:
blob: `str`. blob to download.
local_path: `str`. the path to download to.
container_name: `str`. the name of the container.
use_basename: `bool`. whether or not to use the basename of the key.
"""
if not container_name:
container_name, _, blob = self.parse_wasbs_url(blob)
local_path = os.path.abspath(local_path)
if use_basename:
local_path = append_basename(local_path, blob)
try:
check_dirname_exists(local_path, is_dir=True)
except PolyaxonStoresException:
os.makedirs(local_path)
results = self.list(container_name=container_name, key=blob, delimiter='/')
# Create directories
for prefix in sorted(results['prefixes']):
direname = os.path.join(local_path, prefix)
prefix = os.path.join(blob, prefix)
# Download files under
self.download_dir(blob=prefix,
local_path=direname,
container_name=container_name,
use_basename=False)
# Download files
for file_key in results['blobs']:
file_key = file_key[0]
filename = os.path.join(local_path, file_key)
file_key = os.path.join(blob, file_key)
self.download_file(blob=file_key,
local_path=filename,
container_name=container_name,
use_basename=False)
def delete(self, blob, container_name=None):
if not container_name:
container_name, _, blob = self.parse_wasbs_url(blob)
results = self.list(container_name=container_name, key=blob, delimiter='/')
if not any([results['prefixes'], results['blobs']]):
self.delete_file(blob=blob, container_name=container_name)
# Delete directories
for prefix in sorted(results['prefixes']):
prefix = os.path.join(blob, prefix)
# Download files under
self.delete(blob=prefix, container_name=container_name)
# Delete files
for file_key in results['blobs']:
file_key = file_key[0]
file_key = os.path.join(blob, file_key)
self.delete_file(blob=file_key, container_name=container_name)
def delete_file(self, blob, container_name=None):
"""
Deletes if a blob exists.
Args:
blob: `str`. Name of existing blob.
container_name: `str`. Name of existing container.
"""
if not container_name:
container_name, _, blob = self.parse_wasbs_url(blob)
try:
self.connection.delete_blob(container_name, blob)
except AzureHttpError:
pass
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dataplumber/nexus | analysis/webservice/NexusHandler.py | f25a89e85eba098da9c6db1ff3d408dae8a6b310 | """
Copyright (c) 2016 Jet Propulsion Laboratory,
California Institute of Technology. All rights reserved
"""
import sys
import numpy as np
import logging
import time
import types
from datetime import datetime
from netCDF4 import Dataset
from nexustiles.nexustiles import NexusTileService
from webservice.webmodel import NexusProcessingException
AVAILABLE_HANDLERS = []
AVAILABLE_INITIALIZERS = []
def nexus_initializer(clazz):
log = logging.getLogger(__name__)
try:
wrapper = NexusInitializerWrapper(clazz)
log.info("Adding initializer '%s'" % wrapper.clazz())
AVAILABLE_INITIALIZERS.append(wrapper)
except Exception as ex:
log.warn("Initializer '%s' failed to load (reason: %s)" % (clazz, ex.message), exc_info=True)
return clazz
def nexus_handler(clazz):
log = logging.getLogger(__name__)
try:
wrapper = AlgorithmModuleWrapper(clazz)
log.info("Adding algorithm module '%s' with path '%s' (%s)" % (wrapper.name(), wrapper.path(), wrapper.clazz()))
AVAILABLE_HANDLERS.append(wrapper)
except Exception as ex:
log.warn("Handler '%s' is invalid and will be skipped (reason: %s)" % (clazz, ex.message), exc_info=True)
return clazz
DEFAULT_PARAMETERS_SPEC = {
"ds": {
"name": "Dataset",
"type": "string",
"description": "One or more comma-separated dataset shortnames"
},
"minLat": {
"name": "Minimum Latitude",
"type": "float",
"description": "Minimum (Southern) bounding box Latitude"
},
"maxLat": {
"name": "Maximum Latitude",
"type": "float",
"description": "Maximum (Northern) bounding box Latitude"
},
"minLon": {
"name": "Minimum Longitude",
"type": "float",
"description": "Minimum (Western) bounding box Longitude"
},
"maxLon": {
"name": "Maximum Longitude",
"type": "float",
"description": "Maximum (Eastern) bounding box Longitude"
},
"startTime": {
"name": "Start Time",
"type": "long integer",
"description": "Starting time in milliseconds since midnight Jan. 1st, 1970 UTC"
},
"endTime": {
"name": "End Time",
"type": "long integer",
"description": "Ending time in milliseconds since midnight Jan. 1st, 1970 UTC"
},
"lowPassFilter": {
"name": "Apply Low Pass Filter",
"type": "boolean",
"description": "Specifies whether to apply a low pass filter on the analytics results"
},
"seasonalFilter": {
"name": "Apply Seasonal Filter",
"type": "boolean",
"description": "Specified whether to apply a seasonal cycle filter on the analytics results"
}
}
class NexusInitializerWrapper:
def __init__(self, clazz):
self.__log = logging.getLogger(__name__)
self.__hasBeenRun = False
self.__clazz = clazz
self.validate()
def validate(self):
if "init" not in self.__clazz.__dict__ or not type(self.__clazz.__dict__["init"]) == types.FunctionType:
raise Exception("Method 'init' has not been declared")
def clazz(self):
return self.__clazz
def hasBeenRun(self):
return self.__hasBeenRun
def init(self, config):
if not self.__hasBeenRun:
self.__hasBeenRun = True
instance = self.__clazz()
instance.init(config)
else:
self.log("Initializer '%s' has already been run" % self.__clazz)
class AlgorithmModuleWrapper:
def __init__(self, clazz):
self.__instance = None
self.__clazz = clazz
self.validate()
def validate(self):
if "calc" not in self.__clazz.__dict__ or not type(self.__clazz.__dict__["calc"]) == types.FunctionType:
raise Exception("Method 'calc' has not been declared")
if "path" not in self.__clazz.__dict__:
raise Exception("Property 'path' has not been defined")
if "name" not in self.__clazz.__dict__:
raise Exception("Property 'name' has not been defined")
if "description" not in self.__clazz.__dict__:
raise Exception("Property 'description' has not been defined")
if "params" not in self.__clazz.__dict__:
raise Exception("Property 'params' has not been defined")
def clazz(self):
return self.__clazz
def name(self):
return self.__clazz.name
def path(self):
return self.__clazz.path
def description(self):
return self.__clazz.description
def params(self):
return self.__clazz.params
def instance(self, algorithm_config=None, sc=None):
if "singleton" in self.__clazz.__dict__ and self.__clazz.__dict__["singleton"] is True:
if self.__instance is None:
self.__instance = self.__clazz()
try:
self.__instance.set_config(algorithm_config)
except AttributeError:
pass
try:
self.__instance.set_spark_context(sc)
except AttributeError:
pass
return self.__instance
else:
instance = self.__clazz()
try:
instance.set_config(algorithm_config)
except AttributeError:
pass
try:
self.__instance.set_spark_context(sc)
except AttributeError:
pass
return instance
def isValid(self):
try:
self.validate()
return True
except Exception as ex:
return False
class CalcHandler(object):
def calc(self, computeOptions, **args):
raise Exception("calc() not yet implemented")
class NexusHandler(CalcHandler):
def __init__(self, skipCassandra=False, skipSolr=False):
CalcHandler.__init__(self)
self.algorithm_config = None
self._tile_service = NexusTileService(skipCassandra, skipSolr)
def set_config(self, algorithm_config):
self.algorithm_config = algorithm_config
def _mergeDicts(self, x, y):
z = x.copy()
z.update(y)
return z
def _now(self):
millis = int(round(time.time() * 1000))
return millis
def _mergeDataSeries(self, resultsData, dataNum, resultsMap):
for entry in resultsData:
#frmtdTime = datetime.fromtimestamp(entry["time"] ).strftime("%Y-%m")
frmtdTime = entry["time"]
if not frmtdTime in resultsMap:
resultsMap[frmtdTime] = []
entry["ds"] = dataNum
resultsMap[frmtdTime].append(entry)
def _resultsMapToList(self, resultsMap):
resultsList = []
for key, value in resultsMap.iteritems():
resultsList.append(value)
resultsList = sorted(resultsList, key=lambda entry: entry[0]["time"])
return resultsList
def _mergeResults(self, resultsRaw):
resultsMap = {}
for i in range(0, len(resultsRaw)):
resultsSeries = resultsRaw[i]
resultsData = resultsSeries[0]
self._mergeDataSeries(resultsData, i, resultsMap)
resultsList = self._resultsMapToList(resultsMap)
return resultsList
class SparkHandler(NexusHandler):
class SparkJobContext(object):
class MaxConcurrentJobsReached(Exception):
def __init__(self, *args, **kwargs):
Exception.__init__(self, *args, **kwargs)
def __init__(self, job_stack):
self.spark_job_stack = job_stack
self.job_name = None
self.log = logging.getLogger(__name__)
def __enter__(self):
try:
self.job_name = self.spark_job_stack.pop()
self.log.debug("Using %s" % self.job_name)
except IndexError:
raise SparkHandler.SparkJobContext.MaxConcurrentJobsReached()
return self
def __exit__(self, exc_type, exc_val, exc_tb):
if self.job_name is not None:
self.log.debug("Returning %s" % self.job_name)
self.spark_job_stack.append(self.job_name)
def __init__(self, **kwargs):
import inspect
NexusHandler.__init__(self, **kwargs)
self._sc = None
self.spark_job_stack = []
def with_spark_job_context(calc_func):
from functools import wraps
@wraps(calc_func)
def wrapped(*args, **kwargs1):
try:
with SparkHandler.SparkJobContext(self.spark_job_stack) as job_context:
# TODO Pool and Job are forced to a 1-to-1 relationship
calc_func.im_self._sc.setLocalProperty("spark.scheduler.pool", job_context.job_name)
calc_func.im_self._sc.setJobGroup(job_context.job_name, "a spark job")
return calc_func(*args, **kwargs1)
except SparkHandler.SparkJobContext.MaxConcurrentJobsReached:
raise NexusProcessingException(code=503,
reason="Max concurrent requests reached. Please try again later.")
return wrapped
for member in inspect.getmembers(self, predicate=inspect.ismethod):
if member[0] == "calc":
setattr(self, member[0], with_spark_job_context(member[1]))
def set_spark_context(self, sc):
self._sc = sc
def set_config(self, algorithm_config):
max_concurrent_jobs = algorithm_config.getint("spark", "maxconcurrentjobs") if algorithm_config.has_section(
"spark") and algorithm_config.has_option("spark", "maxconcurrentjobs") else 10
self.spark_job_stack = list(["Job %s" % x for x in xrange(1, max_concurrent_jobs + 1)])
self.algorithm_config = algorithm_config
def _setQueryParams(self, ds, bounds, start_time=None, end_time=None,
start_year=None, end_year=None, clim_month=None,
fill=-9999., spark_master=None, spark_nexecs=None,
spark_nparts=None):
self._ds = ds
self._minLat, self._maxLat, self._minLon, self._maxLon = bounds
self._startTime = start_time
self._endTime = end_time
self._startYear = start_year
self._endYear = end_year
self._climMonth = clim_month
self._fill = fill
self._spark_master = spark_master
self._spark_nexecs = spark_nexecs
self._spark_nparts = spark_nparts
def _find_global_tile_set(self):
if type(self._ds) in (list,tuple):
ds = self._ds[0]
else:
ds = self._ds
ntiles = 0
##################################################################
# Temporary workaround until we have dataset metadata to indicate
# temporal resolution.
if "monthly" in ds.lower():
t_incr = 2592000 # 30 days
else:
t_incr = 86400 # 1 day
##################################################################
t = self._endTime
self._latRes = None
self._lonRes = None
while ntiles == 0:
nexus_tiles = self._tile_service.get_tiles_bounded_by_box(self._minLat, self._maxLat, self._minLon, self._maxLon, ds=ds, start_time=t-t_incr, end_time=t)
ntiles = len(nexus_tiles)
self.log.debug('find_global_tile_set got {0} tiles'.format(ntiles))
if ntiles > 0:
for tile in nexus_tiles:
self.log.debug('tile coords:')
self.log.debug('tile lats: {0}'.format(tile.latitudes))
self.log.debug('tile lons: {0}'.format(tile.longitudes))
if self._latRes is None:
lats = tile.latitudes.data
if (len(lats) > 1):
self._latRes = abs(lats[1]-lats[0])
if self._lonRes is None:
lons = tile.longitudes.data
if (len(lons) > 1):
self._lonRes = abs(lons[1]-lons[0])
if ((self._latRes is not None) and
(self._lonRes is not None)):
break
if (self._latRes is None) or (self._lonRes is None):
ntiles = 0
else:
lats_agg = np.concatenate([tile.latitudes.compressed()
for tile in nexus_tiles])
lons_agg = np.concatenate([tile.longitudes.compressed()
for tile in nexus_tiles])
self._minLatCent = np.min(lats_agg)
self._maxLatCent = np.max(lats_agg)
self._minLonCent = np.min(lons_agg)
self._maxLonCent = np.max(lons_agg)
t -= t_incr
return nexus_tiles
def _find_tile_bounds(self, t):
lats = t.latitudes
lons = t.longitudes
if (len(lats.compressed()) > 0) and (len(lons.compressed()) > 0):
min_lat = np.ma.min(lats)
max_lat = np.ma.max(lats)
min_lon = np.ma.min(lons)
max_lon = np.ma.max(lons)
good_inds_lat = np.where(lats.mask == False)[0]
good_inds_lon = np.where(lons.mask == False)[0]
min_y = np.min(good_inds_lat)
max_y = np.max(good_inds_lat)
min_x = np.min(good_inds_lon)
max_x = np.max(good_inds_lon)
bounds = (min_lat, max_lat, min_lon, max_lon,
min_y, max_y, min_x, max_x)
else:
self.log.warn('Nothing in this tile!')
bounds = None
return bounds
@staticmethod
def query_by_parts(tile_service, min_lat, max_lat, min_lon, max_lon,
dataset, start_time, end_time, part_dim=0):
nexus_max_tiles_per_query = 100
#print 'trying query: ',min_lat, max_lat, min_lon, max_lon, \
# dataset, start_time, end_time
try:
tiles = \
tile_service.find_tiles_in_box(min_lat, max_lat,
min_lon, max_lon,
dataset,
start_time=start_time,
end_time=end_time,
fetch_data=False)
assert(len(tiles) <= nexus_max_tiles_per_query)
except:
#print 'failed query: ',min_lat, max_lat, min_lon, max_lon, \
# dataset, start_time, end_time
if part_dim == 0:
# Partition by latitude.
mid_lat = (min_lat + max_lat) / 2
nexus_tiles = SparkHandler.query_by_parts(tile_service,
min_lat, mid_lat,
min_lon, max_lon,
dataset,
start_time, end_time,
part_dim=part_dim)
nexus_tiles.extend(SparkHandler.query_by_parts(tile_service,
mid_lat,
max_lat,
min_lon,
max_lon,
dataset,
start_time,
end_time,
part_dim=part_dim))
elif part_dim == 1:
# Partition by longitude.
mid_lon = (min_lon + max_lon) / 2
nexus_tiles = SparkHandler.query_by_parts(tile_service,
min_lat, max_lat,
min_lon, mid_lon,
dataset,
start_time, end_time,
part_dim=part_dim)
nexus_tiles.extend(SparkHandler.query_by_parts(tile_service,
min_lat,
max_lat,
mid_lon,
max_lon,
dataset,
start_time,
end_time,
part_dim=part_dim))
elif part_dim == 2:
# Partition by time.
mid_time = (start_time + end_time) / 2
nexus_tiles = SparkHandler.query_by_parts(tile_service,
min_lat, max_lat,
min_lon, max_lon,
dataset,
start_time, mid_time,
part_dim=part_dim)
nexus_tiles.extend(SparkHandler.query_by_parts(tile_service,
min_lat,
max_lat,
min_lon,
max_lon,
dataset,
mid_time,
end_time,
part_dim=part_dim))
else:
# No exception, so query Cassandra for the tile data.
#print 'Making NEXUS query to Cassandra for %d tiles...' % \
# len(tiles)
#t1 = time.time()
#print 'NEXUS call start at time %f' % t1
#sys.stdout.flush()
nexus_tiles = list(tile_service.fetch_data_for_tiles(*tiles))
nexus_tiles = list(tile_service.mask_tiles_to_bbox(min_lat, max_lat,
min_lon, max_lon,
nexus_tiles))
#t2 = time.time()
#print 'NEXUS call end at time %f' % t2
#print 'Seconds in NEXUS call: ', t2-t1
#sys.stdout.flush()
#print 'Returning %d tiles' % len(nexus_tiles)
return nexus_tiles
@staticmethod
def _prune_tiles(nexus_tiles):
del_ind = np.where([np.all(tile.data.mask) for tile in nexus_tiles])[0]
for i in np.flipud(del_ind):
del nexus_tiles[i]
def _lat2ind(self,lat):
return int((lat-self._minLatCent)/self._latRes)
def _lon2ind(self,lon):
return int((lon-self._minLonCent)/self._lonRes)
def _ind2lat(self,y):
return self._minLatCent+y*self._latRes
def _ind2lon(self,x):
return self._minLonCent+x*self._lonRes
def _create_nc_file_time1d(self, a, fname, varname, varunits=None,
fill=None):
self.log.debug('a={0}'.format(a))
self.log.debug('shape a = {0}'.format(a.shape))
assert len(a.shape) == 1
time_dim = len(a)
rootgrp = Dataset(fname, "w", format="NETCDF4")
rootgrp.createDimension("time", time_dim)
vals = rootgrp.createVariable(varname, "f4", dimensions=("time",),
fill_value=fill)
times = rootgrp.createVariable("time", "f4", dimensions=("time",))
vals[:] = [d['mean'] for d in a]
times[:] = [d['time'] for d in a]
if varunits is not None:
vals.units = varunits
times.units = 'seconds since 1970-01-01 00:00:00'
rootgrp.close()
def _create_nc_file_latlon2d(self, a, fname, varname, varunits=None,
fill=None):
self.log.debug('a={0}'.format(a))
self.log.debug('shape a = {0}'.format(a.shape))
assert len(a.shape) == 2
lat_dim, lon_dim = a.shape
rootgrp = Dataset(fname, "w", format="NETCDF4")
rootgrp.createDimension("lat", lat_dim)
rootgrp.createDimension("lon", lon_dim)
vals = rootgrp.createVariable(varname, "f4",
dimensions=("lat","lon",),
fill_value=fill)
lats = rootgrp.createVariable("lat", "f4", dimensions=("lat",))
lons = rootgrp.createVariable("lon", "f4", dimensions=("lon",))
vals[:,:] = a
lats[:] = np.linspace(self._minLatCent,
self._maxLatCent, lat_dim)
lons[:] = np.linspace(self._minLonCent,
self._maxLonCent, lon_dim)
if varunits is not None:
vals.units = varunits
lats.units = "degrees north"
lons.units = "degrees east"
rootgrp.close()
def _create_nc_file(self, a, fname, varname, **kwargs):
self._create_nc_file_latlon2d(a, fname, varname, **kwargs)
def executeInitializers(config):
[wrapper.init(config) for wrapper in AVAILABLE_INITIALIZERS]
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ming71/SLA | utils/box/metric.py | 7024b093bc0d456b274314ebeae3bc500c2db65a | import numpy as np
from collections import defaultdict, Counter
from .rbbox_np import rbbox_iou
def get_ap(recall, precision):
recall = [0] + list(recall) + [1]
precision = [0] + list(precision) + [0]
for i in range(len(precision) - 1, 0, -1):
precision[i - 1] = max(precision[i - 1], precision[i])
ap = sum((recall[i] - recall[i - 1]) * precision[i] for i in range(1, len(recall)) if recall[i] != recall[i - 1])
return ap * 100
def get_ap_07(recall, precision):
ap = 0.
for t in np.linspace(0, 1, 11, endpoint=True):
mask = recall >= t
if np.any(mask):
ap += np.max(precision[mask]) / 11
return ap * 100
def get_det_aps(detect, target, num_classes, iou_thresh=0.5, use_07_metric=False):
# [[index, bbox, score, label], ...]
aps = []
for c in range(num_classes):
target_c = list(filter(lambda x: x[3] == c, target))
detect_c = filter(lambda x: x[3] == c, detect)
detect_c = sorted(detect_c, key=lambda x: x[2], reverse=True)
tp = np.zeros(len(detect_c))
fp = np.zeros(len(detect_c))
target_count = Counter([x[0] for x in target_c])
target_count = {index: np.zeros(count) for index, count in target_count.items()}
target_lut = defaultdict(list)
for index, bbox, conf, label in target_c:
target_lut[index].append(bbox)
detect_lut = defaultdict(list)
for index, bbox, conf, label in detect_c:
detect_lut[index].append(bbox)
iou_lut = dict()
for index, bboxes in detect_lut.items():
if index in target_lut:
iou_lut[index] = rbbox_iou(np.stack(bboxes), np.stack(target_lut[index]))
counter = defaultdict(int)
for i, (index, bbox, conf, label) in enumerate(detect_c):
count = counter[index]
counter[index] += 1
iou_max = -np.inf
hit_j = 0
if index in iou_lut:
for j, iou in enumerate(iou_lut[index][count]):
if iou > iou_max:
iou_max = iou
hit_j = j
if iou_max > iou_thresh and target_count[index][hit_j] == 0:
tp[i] = 1
target_count[index][hit_j] = 1
else:
fp[i] = 1
tp_sum = np.cumsum(tp)
fp_sum = np.cumsum(fp)
npos = len(target_c)
recall = tp_sum / npos
precision = tp_sum / (tp_sum + fp_sum)
aps.append((get_ap_07 if use_07_metric else get_ap)(recall, precision))
return aps
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winstonschroeder/setlistmanager | app.py | 3c177a8da4bd56049964076f6ead51e3fffff5fa |
import logging
import pygame
from app import *
from pygame.locals import *
from werkzeug.serving import run_simple
from web import webapp as w
import data_access as da
logging.basicConfig(filename='setlistmanager.log', level=logging.DEBUG)
SCREEN_WIDTH = 160
SCREEN_HEIGHT = 128
class Button:
pass
class Text():
"""Create a text object."""
def __init__(self, surface, text, pos, **options):
self.text = text
self.surface = surface
self.pos = pos
self.bold = True
self.italic = False
self.underline = False
self.background = None # Color('white')
self.font = pygame.font.SysFont('Arial', 64)
self.fontname = None # 'Free Sans'
self.fontsize = 40
self.fontcolor = Color('black')
self.set_font()
da.connect_db('db.db')
songs = da.get_all_songs_as_json()
print (songs)
# self.words = [word.split(' ') for word in self.text.splitlines()] # 2D array where each row is a list of words.
# self.space = self.font.size(' ')[0] # The width of a space.
# max_width, max_height = self.surface.get_size()
# x, y = self.pos
# for line in self.words:
# for word in line:
# word_surface = self.font.render(word, 0, self.fontcolor)
# # print(word)
# word_width, word_height = word_surface.get_size()
# if x + word_width >= max_width:
# x = pos[0] # Reset the x.
# y += word_height # Start on new row.
# surface.blit(word_surface, (x, y))
# x += word_width + self.space
# x = pos[0] # Reset the x.
# y += word_height # Start on new row.
self.render()
def set_font(self):
"""Set the font from its name and size."""
self.font = pygame.font.Font(self.fontname, self.fontsize)
self.font.set_bold(self.bold)
self.font.set_italic(self.italic)
self.font.set_underline(self.underline)
def render(self):
"""Render the text into an image."""
self.img = self.font.render(self.text, True, self.fontcolor, self.background)
self.rect = self.img.get_rect()
self.rect.size = self.img.get_size()
self.rect.topleft = self.pos
def draw(self):
"""Draw the text image to the screen."""
# Put the center of surf at the center of the display
surf_center = (
(SCREEN_WIDTH - self.rect.width)/2,
(SCREEN_HEIGHT - self.rect.height)/2
)
App.screen.blit(self.img, surf_center)
# App.screen.blit(self.img, self.rect)
class App:
"""Create a single-window app with multiple scenes."""
def __init__(self):
"""Initialize pygame and the application."""
logging.debug('Initializing App')
pygame.init()
pygame.mouse.set_cursor((8, 8), (0, 0), (0, 0, 0, 0, 0, 0, 0, 0), (0, 0, 0, 0, 0, 0, 0, 0))
self.shortcuts = {
(K_x, KMOD_LMETA): 'print("cmd+X")',
(K_x, KMOD_LALT): 'print("alt+X")',
(K_x, KMOD_LCTRL): 'print("ctrl+X")',
(K_x, KMOD_LMETA + KMOD_LSHIFT): 'print("cmd+shift+X")',
(K_x, KMOD_LMETA + KMOD_LALT): 'print("cmd+alt+X")',
(K_x, KMOD_LMETA + KMOD_LALT + KMOD_LSHIFT): 'print("cmd+alt+shift+X")',
}
self.color = Color('green')
self.flags = RESIZABLE
self.rect = Rect(0, 0, SCREEN_WIDTH, SCREEN_HEIGHT)
App.screen = pygame.display.set_mode(self.rect.size, self.flags)
App.t = Text(App.screen, 'Chorus', pos=(0, 0))
App.running = True
def run(self):
"""Run the main event loop."""
logging.debug('entering method run')
app = w.create_app()
run_simple('127.0.0.1', 5000, app, use_debugger=True, use_reloader=True)
logging.debug('after start of flask')
while App.running:
logging.debug('.')
for event in pygame.event.get():
if event.type == QUIT:
App.running = False
if event.type == KEYDOWN:
self.do_shortcut(event)
App.screen.fill(self.color)
App.t.draw()
pygame.display.update()
logging.debug('exiting setlistmanager')
pygame.quit()
def do_shortcut(self, event):
"""Find the the key/mod combination in the dictionary and execute the cmd."""
k = event.key
m = event.mod
if (k, m) in self.shortcuts:
exec(self.shortcuts[k, m])
def toggle_fullscreen(self):
"""Toggle between full screen and windowed screen."""
self.flags ^= FULLSCREEN
pygame.display.set_mode((0, 0), self.flags)
def toggle_resizable(self):
"""Toggle between resizable and fixed-size window."""
self.flags ^= RESIZABLE
pygame.display.set_mode(self.rect.size, self.flags)
def toggle_frame(self):
"""Toggle between frame and noframe window."""
self.flags ^= NOFRAME
pygame.display.set_mode(self.rect.size, self.flags)
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Praznat/annotationmodeling | sim_keypoints.py | 014b8b94b2225f947691c18b26eb8a4b148d2c8a | import json
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
import simulation
from eval_functions import oks_score_multi
import utils
def alter_location(points, x_offset, y_offset):
x, y = points.T
return np.array([x + x_offset, y + y_offset]).T
def alter_rotation(points, radians):
centroid = np.mean(points, axis=0)
return utils.rotate_via_numpy((points - centroid).T, radians) + centroid
def alter_magnitude(points, percent_diff):
centroid = np.mean(points, axis=0)
return (points - centroid) * np.exp(percent_diff) + centroid
def alter_normal_jump(points, scale):
return points + np.random.normal(0, scale, points.shape)
def alter_cauchy_jump(points, scale, abs_bound):
return points + utils.bounded_cauchy(scale, points.shape, abs_bound)
def disappear(points, p_disappear):
return None if np.random.uniform() < p_disappear else points
def shift_by_uerr(annotation, uerr):
shifts = [
alter_rotation(annotation, np.random.normal(0, 0.5 * uerr) * np.pi / 8),
alter_magnitude(annotation, np.random.normal(0, 0.3 * uerr)),
alter_normal_jump(annotation, 30 * uerr),
alter_cauchy_jump(annotation, 30 * uerr, 100),
]
return np.mean(shifts, axis=0) * np.abs(np.sign(annotation))
def create_user_data(uid, df, pct_items, u_err, difficulty_dict=None, extraarg=None):
items = df["item"].unique()
n_items_labeled = int(np.round(pct_items * len(items)))
items_labeled = sorted(np.random.choice(items, n_items_labeled, replace=False))
labels = []
for item in items_labeled:
gold = df[df["item"] == item]["gold"].values[0]
shifted_kpobjs = [shift_by_uerr(kpobj, u_err) for kpobj in gold]
kpobjs = [shifted_kpobjs[0]] + [disappear(kp, u_err / 2) for kp in shifted_kpobjs[1:]]
kpobjs = [kp for kp in kpobjs if kp is not None]
labels.append(kpobjs)
dfdict = {
"uid": [uid] * len(items_labeled),
"item": items_labeled,
"annotation": labels,
}
return pd.DataFrame(dfdict)
class KeypointSimulator(simulation.Simulator):
def __init__(self, rawdata_dir='data/coco/person_keypoints_train2017.json', max_items=500, minlabelsperitem=4):
with open(rawdata_dir) as f:
dataset = json.load(f)
self.category_id_skeletons = {c["id"]: np.array(c["skeleton"])-1 for c in iter(dataset["categories"])}
img_label = {}
for dataset_annotation in iter(dataset["annotations"]):
v = img_label.setdefault(dataset_annotation["image_id"], [])
v.append(dataset_annotation)
img_label_minlen = {k: v for k, v in img_label.items() if len(v) >= minlabelsperitem}
i = 0
rows = []
item = []
annotation = []
category = []
for dataset_annotations in iter(img_label_minlen.values()):
for dataset_annotation in dataset_annotations:
kp = np.reshape(dataset_annotation["keypoints"], (-1,3))
kp = kp[kp[:,2]>-90][:,:2]
if len(kp) == 0:
continue
item.append(dataset_annotation["image_id"])
annotation.append(kp)
category.append(dataset_annotation["category_id"])
i += 1
if i > max_items:
break
kp_df = pd.DataFrame({"item":item, "gold":annotation, "category":category})
self.df = kp_df.groupby("item")["gold"].apply(list).reset_index()
self.itemdict = utils.make_categorical(self.df, "item")
def create_stan_data(self, n_users, pct_items, err_rates, difficulty_dict):
self.err_rates = err_rates
self.difficulty_dict = difficulty_dict
self.sim_df = simulation.create_sim_df(create_user_data, self.df, n_users, pct_items, err_rates, difficulty_dict)
stan_data = utils.calc_distances(self.sim_df, (lambda x,y: 1 - oks_score_multi(x, y)), label_colname="annotation", item_colname="item")
return stan_data
def sim_uerr_fn(self, uerr_a, uerr_b, n_users):
z = np.abs(np.random.normal(uerr_a, uerr_b, 10000))
return np.quantile(z, np.linspace(0,1,n_users+2)[1:-1])
def sim_diff_fn(self, difficulty_a, difficulty_b):
z = 1 * np.random.beta(difficulty_a, difficulty_b, 10000)
n_items = len(self.df["item"].unique())
return dict(zip(np.arange(n_items), np.quantile(z, np.linspace(0,1,n_items+2)[1:-1]))) | [((336, 359), 'numpy.mean', 'np.mean', (['points'], {'axis': '(0)'}), '(points, axis=0)\n', (343, 359), True, 'import numpy as np\n'), ((496, 519), 'numpy.mean', 'np.mean', (['points'], {'axis': '(0)'}), '(points, axis=0)\n', (503, 519), True, 'import numpy as np\n'), ((2047, 2067), 'pandas.DataFrame', 'pd.DataFrame', (['dfdict'], {}), '(dfdict)\n', (2059, 2067), True, 'import pandas as pd\n'), ((242, 280), 'numpy.array', 'np.array', (['[x + x_offset, y + y_offset]'], {}), '([x + x_offset, y + y_offset])\n', (250, 280), True, 'import numpy as np\n'), ((371, 425), 'utils.rotate_via_numpy', 'utils.rotate_via_numpy', (['(points - centroid).T', 'radians'], {}), '((points - centroid).T, radians)\n', (393, 425), False, 'import utils\n'), ((644, 684), 'numpy.random.normal', 'np.random.normal', (['(0)', 'scale', 'points.shape'], {}), '(0, scale, points.shape)\n', (660, 684), True, 'import numpy as np\n'), ((755, 807), 'utils.bounded_cauchy', 'utils.bounded_cauchy', (['scale', 'points.shape', 'abs_bound'], {}), '(scale, points.shape, abs_bound)\n', (775, 807), False, 'import utils\n'), ((1236, 1259), 'numpy.mean', 'np.mean', (['shifts'], {'axis': '(0)'}), '(shifts, axis=0)\n', (1243, 1259), True, 'import numpy as np\n'), ((1496, 1551), 'numpy.random.choice', 'np.random.choice', (['items', 'n_items_labeled'], {'replace': '(False)'}), '(items, n_items_labeled, replace=False)\n', (1512, 1551), True, 'import numpy as np\n'), ((3383, 3453), 'pandas.DataFrame', 'pd.DataFrame', (["{'item': item, 'gold': annotation, 'category': category}"], {}), "({'item': item, 'gold': annotation, 'category': category})\n", (3395, 3453), True, 'import pandas as pd\n'), ((3549, 3588), 'utils.make_categorical', 'utils.make_categorical', (['self.df', '"""item"""'], {}), "(self.df, 'item')\n", (3571, 3588), False, 'import utils\n'), ((3774, 3877), 'simulation.create_sim_df', 'simulation.create_sim_df', (['create_user_data', 'self.df', 'n_users', 'pct_items', 'err_rates', 'difficulty_dict'], {}), '(create_user_data, self.df, n_users, pct_items,\n err_rates, difficulty_dict)\n', (3798, 3877), False, 'import simulation\n'), ((553, 573), 'numpy.exp', 'np.exp', (['percent_diff'], {}), '(percent_diff)\n', (559, 573), True, 'import numpy as np\n'), ((864, 883), 'numpy.random.uniform', 'np.random.uniform', ([], {}), '()\n', (881, 883), True, 'import numpy as np\n'), ((1080, 1111), 'numpy.random.normal', 'np.random.normal', (['(0)', '(0.3 * uerr)'], {}), '(0, 0.3 * uerr)\n', (1096, 1111), True, 'import numpy as np\n'), ((1269, 1288), 'numpy.sign', 'np.sign', (['annotation'], {}), '(annotation)\n', (1276, 1288), True, 'import numpy as np\n'), ((2291, 2303), 'json.load', 'json.load', (['f'], {}), '(f)\n', (2300, 2303), False, 'import json\n'), ((4115, 4154), 'numpy.random.normal', 'np.random.normal', (['uerr_a', 'uerr_b', '(10000)'], {}), '(uerr_a, uerr_b, 10000)\n', (4131, 4154), True, 'import numpy as np\n'), ((4296, 4345), 'numpy.random.beta', 'np.random.beta', (['difficulty_a', 'difficulty_b', '(10000)'], {}), '(difficulty_a, difficulty_b, 10000)\n', (4310, 4345), True, 'import numpy as np\n'), ((2351, 2374), 'numpy.array', 'np.array', (["c['skeleton']"], {}), "(c['skeleton'])\n", (2359, 2374), True, 'import numpy as np\n'), ((2974, 3026), 'numpy.reshape', 'np.reshape', (["dataset_annotation['keypoints']", '(-1, 3)'], {}), "(dataset_annotation['keypoints'], (-1, 3))\n", (2984, 3026), True, 'import numpy as np\n'), ((4186, 4216), 'numpy.linspace', 'np.linspace', (['(0)', '(1)', '(n_users + 2)'], {}), '(0, 1, n_users + 2)\n', (4197, 4216), True, 'import numpy as np\n'), ((4418, 4436), 'numpy.arange', 'np.arange', (['n_items'], {}), '(n_items)\n', (4427, 4436), True, 'import numpy as np\n'), ((998, 1029), 'numpy.random.normal', 'np.random.normal', (['(0)', '(0.5 * uerr)'], {}), '(0, 0.5 * uerr)\n', (1014, 1029), True, 'import numpy as np\n'), ((3945, 3966), 'eval_functions.oks_score_multi', 'oks_score_multi', (['x', 'y'], {}), '(x, y)\n', (3960, 3966), False, 'from eval_functions import oks_score_multi\n'), ((4453, 4483), 'numpy.linspace', 'np.linspace', (['(0)', '(1)', '(n_items + 2)'], {}), '(0, 1, n_items + 2)\n', (4464, 4483), True, 'import numpy as np\n')] |
Loptt/home-automation-system | local/controller.py | f1878596905e022d1d626d485d1a29dc7212f480 | import requests
import time
import os
import sys
import json
import threading
from getpass import getpass
import schedule
import event as e
import configuration as c
import RPi.GPIO as GPIO
#SERVER_URL = "https://home-automation-289621.uc.r.appspot.com"
#SERVER_URL = "http://127.0.0.1:4747"
SERVER_URL = "http://192.168.11.117:4747"
pins = [2, 3, 4, 7, 8, 9, 10, 11, 14, 15, 17, 18, 22, 23, 24, 27]
def calculate_max_duration(time):
hours = 23 - time.hour
minutes = 60 - time.minute
return hours * 60 + minutes
def turn_on(pin):
print("Turn on " + str(pin))
GPIO.output(pin, GPIO.HIGH)
def turn_off(pin):
print("Turn off " + str(pin))
GPIO.output(pin, GPIO.LOW)
def schedule_off(time, day, duration, pin):
new_day = day
end_time = e.Time(0, 0)
if duration > calculate_max_duration(time):
# Next day calculation
new_day = day + 1
off_duration = duration - calculate_max_duration(time)
end_time.hour = off_duration // 60
end_time.minute = off_duration % 60
else:
# Same day calculation
end_time.hour = time.hour + \
(duration // 60) + (time.minute + (duration % 60)) // 60
end_time.minute = (time.minute + duration % 60) % 60
if new_day > 7:
new_day = 1
if new_day == 1:
schedule.every().monday.at(str(end_time)).do(turn_off, pin)
elif new_day == 2:
schedule.every().tuesday.at(str(end_time)).do(turn_off, pin)
elif new_day == 3:
schedule.every().wednesday.at(str(end_time)).do(turn_off, pin)
elif new_day == 4:
schedule.every().thursday.at(str(end_time)).do(turn_off, pin)
elif new_day == 5:
schedule.every().friday.at(str(end_time)).do(turn_off, pin)
elif new_day == 6:
schedule.every().saturday.at(str(end_time)).do(turn_off, pin)
elif new_day == 7:
schedule.every().sunday.at(str(end_time)).do(turn_off, pin)
def schedule_job(event):
GPIO.setup(event.pin, GPIO.OUT)
if len(event.days) == 0 or len(event.days) == 7:
schedule.every().day.at(str(event.time)).do(turn_on, event.pin)
else:
if 1 in event.days:
schedule.every().monday.at(str(event.time)).do(turn_on, event.pin)
schedule_off(event.time, 1, event.duration, event.pin)
if 2 in event.days:
schedule.every().tuesday.at(str(event.time)).do(turn_on, event.pin)
schedule_off(event.time, 2, event.duration, event.pin)
if 3 in event.days:
schedule.every().wednesday.at(str(event.time)).do(turn_on, event.pin)
schedule_off(event.time, 3, event.duration, event.pin)
if 4 in event.days:
schedule.every().thursday.at(str(event.time)).do(turn_on, event.pin)
schedule_off(event.time, 4, event.duration, event.pin)
if 5 in event.days:
schedule.every().friday.at(str(event.time)).do(turn_on, event.pin)
schedule_off(event.time, 5, event.duration, event.pin)
if 6 in event.days:
schedule.every().saturday.at(str(event.time)).do(turn_on, event.pin)
schedule_off(event.time, 6, event.duration, event.pin)
if 7 in event.days:
schedule.every().sunday.at(str(event.time)).do(turn_on, event.pin)
schedule_off(event.time, 7, event.duration, event.pin)
def run_scheduling():
while True:
schedule.run_pending()
time.sleep(1)
def initial_setup():
username = input("Enter your username: ")
password = getpass("Enter your password: ")
pload = json.dumps({"username": username, "password": password})
r = requests.post(SERVER_URL + "/login", data=pload,
headers={'Content-type': 'application/json'})
r_dict = r.json()
if not r_dict["valid"]:
print("Invalid username/password")
print("Run program again to try again")
sys.exit()
print("Successful login...")
print("Saving configuration...")
f = open("config.txt", "w")
f.write(r_dict["user"])
f.close()
return r_dict["user"]
def get_user():
f = open("config.txt", "r")
user = f.readline()
r = requests.get(SERVER_URL + "/users/" + user)
if r.status_code == 200:
print("Successful login...")
return user
else:
print("Invalid user... Reinitializing configuration")
return initial_setup()
def get_configuration(user):
r = requests.get(SERVER_URL + "/configurations/by-user/" + user)
if r.status_code != 200:
print("Error retrieving configuration, check internet connection.")
sys.exit()
r_dict = r.json()
return c.Configuration(
r_dict["systemStatus"], r_dict["rainPercentage"], r_dict["defaultDuration"], r_dict["update"], r_dict["_id"])
def set_update_off(configuration):
r = requests.put(
SERVER_URL + "/configurations/set-off-update/" + configuration.id)
if r.status_code >= 400:
print(
"Error updating configuration status... Possible reconfiguration on next cycle")
else:
print("Update set off.")
def update_schedules(user):
r = requests.get(
SERVER_URL + "/devices/by-user-with-events/" + user)
devices = r.json()
schedule.clear()
GPIO.cleanup()
for device in devices:
for event in device["events"]:
print(event)
schedule_job(e.Event(
device["pin"], event["days"], e.Time(event["time"]["hour"], event["time"]["minute"]), e.Repetition(event["repetition"]["times"], event["repetition"]["date"], event["repetition"]["current"]), event["duration"]))
def setup():
GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)
for pin in pins:
GPIO.setup(pin, GPIO.OUT, initial=GPIO.LOW)
GPIO.cleanup()
def main():
setup()
user = ""
if not os.path.isfile("./config.txt"):
print("No configuration found... Initializing configuration")
user = initial_setup()
else:
print("Validating user...")
user = get_user()
print("Initializing routine...")
# Initialize separate thread to run scheduling jobs
thread = threading.Thread(None, run_scheduling, "Schedule")
thread.start()
print("Schedule running.")
while True:
configuration = get_configuration(user)
if configuration.update:
print("Updating schedule...")
update_schedules(user)
set_update_off(configuration)
time.sleep(1)
thread.join()
if __name__ == "__main__":
main()
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gzzo/graphql-sqlalchemy | src/graphql_sqlalchemy/graphql_types.py | 54a30d0b2fe2d5a1eb3668f0f7bc6ec3cb366ec4 | from typing import Dict, Union
from graphql import (
GraphQLBoolean,
GraphQLFloat,
GraphQLInputField,
GraphQLInt,
GraphQLList,
GraphQLNonNull,
GraphQLScalarType,
GraphQLString,
)
from sqlalchemy import ARRAY, Boolean, Float, Integer
from sqlalchemy.dialects.postgresql import ARRAY as PGARRAY
from sqlalchemy.types import TypeEngine
def get_graphql_type_from_column(column_type: TypeEngine) -> Union[GraphQLScalarType, GraphQLList]:
if isinstance(column_type, Integer):
return GraphQLInt
if isinstance(column_type, Float):
return GraphQLFloat
if isinstance(column_type, Boolean):
return GraphQLBoolean
if isinstance(column_type, (ARRAY, PGARRAY)):
return GraphQLList(get_graphql_type_from_column(column_type.item_type))
return GraphQLString
def get_base_comparison_fields(graphql_type: Union[GraphQLScalarType, GraphQLList]) -> Dict[str, GraphQLInputField]:
return {
"_eq": GraphQLInputField(graphql_type),
"_neq": GraphQLInputField(graphql_type),
"_in": GraphQLInputField(GraphQLList(GraphQLNonNull(graphql_type))),
"_nin": GraphQLInputField(GraphQLList(GraphQLNonNull(graphql_type))),
"_lt": GraphQLInputField(graphql_type),
"_gt": GraphQLInputField(graphql_type),
"_gte": GraphQLInputField(graphql_type),
"_lte": GraphQLInputField(graphql_type),
"_is_null": GraphQLInputField(GraphQLBoolean),
}
def get_string_comparison_fields() -> Dict[str, GraphQLInputField]:
return {"_like": GraphQLInputField(GraphQLString), "_nlike": GraphQLInputField(GraphQLString)}
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byterubpay/mininero1 | Knapsack.py | ea6b8017cdbab82011d7f329e7726cc52d1ef431 | import Crypto.Random.random as rand
import itertools
import math #for log
import sys
def decomposition(i):
#from stack exchange, don't think it's uniform
while i > 0:
n = rand.randint(1, i)
yield n
i -= n
def Decomposition(i):
while True:
l = list(decomposition(i))
if len(set(l)) == len(l):
return l
def decomposition2(n, s, d, k):
#home-brewed, returns no duplicates, includes the number d
s = s - 1
n = n
while True:
a = [d]
nn = n
#a.append(d)
for i in range(0, s):
a.append(rand.randint(0, n))
a.sort()
#print("a", a)
b = []
c = []
while len(a) > 0:
t = a.pop()
#print(t, a)
if t >= d:
b.append(nn - t)
else:
c.append(nn - t)
nn = t
c.append(nn)
tot = b[:] + c[:]
#print("b", b)
if sum(set(tot)) == n and len(c) > int(k):
return sorted(c), sorted(b)
def decomposition3(n, s, d, k):
#a combination of both methods, designed to get some smaller values
send, change = decomposition2(n, s, d, k)
for i in send:
if i > n / s:
send.remove(i)
send = send + list(Decomposition(i))
for i in change:
if i > n / (s - 1):
change.remove(i)
change = change + list(Decomposition(i))
return send, change
def divv(l, m):
return [a /float( m) for a in l]
def frexp10(x):
exp = int(math.log10(x))
return x / 10**exp, exp
def decideAmounts(totalInputs, toSend, Partitions, k, fuzz):
#fuzz is an optional amount to fuzz the transaction by
#so if you start with a big obvious number like 2000, it might be fuzzed by up to "fuzz" amount
fz = rand.randint(0, int(fuzz * 1000) ) / 1000.0
toSend += fz
g, ii =frexp10(totalInputs)
ii = 10 ** (-1 * min(ii - 2, 0))
print("ii", ii)
M = 10 ** (int(math.log(2 ** Partitions) / math.log(10))) * ii
#M = 10 ** M
print("multiplier:", M)
totalInputs = int(totalInputs * M)
toSend = int(toSend * M)
change = totalInputs - toSend
send_amounts, change_amounts = decomposition3(totalInputs, Partitions, toSend, k)
all_amounts = send_amounts[:] + change_amounts[:]
rand.shuffle(all_amounts)
print("")
print("change amounts:", divv(change_amounts, M))
print("send amounts:", divv(send_amounts, M))
print("now from the following, how much is sent?")
print("all amounts:", sorted(divv(all_amounts, M)))
print("possible sent amounts:")
amounts = []
for L in range(0, len(all_amounts)+1):
for subset in itertools.combinations(all_amounts, L):
amounts.append(sum(subset))
print("number of possible sent amounts:")
print(len(amounts))
print("2^N:", 2 ** len(all_amounts))
print("number of possible sent amounts duplicates removed:")
print(len(list(set(amounts))))
if len(sys.argv) > 2:
kk = 2
parts = 7
kk = rand.randint(1, int(parts / 4)) #how many sends to demand
fuzz = 1
decideAmounts(float(sys.argv[1]), float(sys.argv[2]), parts, kk, fuzz)
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rudolfwilliam/satellite_image_forecasting | drought_impact_forecasting/models/model_parts/Conv_Transformer.py | 164ee7e533e1a8d730a0ee9c0062fd9b32e0bcdc | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from einops import rearrange
from .shared import Conv_Block
from ..utils.utils import zeros, mean_cube, last_frame, ENS
class Residual(nn.Module):
def __init__(self, fn):
super().__init__()
self.fn = fn
def forward(self, x, **kwargs):
return self.fn(x, **kwargs) + x
class PreNorm(nn.Module):
def __init__(self, dim, fn):
super().__init__()
self.norm = nn.LayerNorm(dim)
self.fn = fn
def forward(self, x, **kwargs):
return self.fn(torch.stack([self.norm(x[..., i]) for i in range(x.size()[-1])], dim=-1), **kwargs)
class FeedForward(nn.Module):
def __init__(self, kernel_size, num_hidden, dilation_rate, num_conv_layers):
super().__init__()
self.kernel_size = kernel_size
self.num_hidden = num_hidden
self.num_conv_layers = num_conv_layers
self.dilation_rate = dilation_rate
self.conv = Conv_Block(self.num_hidden, self.num_hidden, kernel_size=self.kernel_size,
dilation_rate=self.dilation_rate, num_conv_layers=self.num_conv_layers)
def forward(self, x):
return torch.stack([self.conv(x[..., i]) for i in range(x.size()[-1])], dim=-1)
class ConvAttention(nn.Module):
def __init__(self, num_hidden, kernel_size, enc=True, mask=False):
super(ConvAttention, self).__init__()
self.enc = enc
self.mask = mask
self.kernel_size = kernel_size
self.num_hidden = num_hidden
# important note: shared convolution is intentional here
if self.enc:
# 3 times num_hidden for out_channels due to queries, keys & values
self.conv1 = nn.Sequential(
nn.Conv2d(in_channels=self.num_hidden, out_channels=3*self.num_hidden, kernel_size=1, padding="same", padding_mode="reflect")
)
else:
# only 2 times num_hidden for keys & values
self.conv1 = nn.Sequential(
nn.Conv2d(in_channels=self.num_hidden, out_channels=2*self.num_hidden, kernel_size=1, padding="same", padding_mode="reflect")
)
self.conv2 = nn.Sequential(
nn.Conv2d(in_channels=self.num_hidden*2, out_channels=1, kernel_size=self.kernel_size, padding="same", padding_mode="reflect")
)
def forward(self, x, enc_out=None):
# s is num queries, t is num keys/values
b, _, _, _, s = x.shape
if self.enc:
t = s
qkv_set = torch.stack([self.conv1(x[..., i]) for i in range(t)], dim=-1)
Q, K, V = torch.split(qkv_set, self.num_hidden, dim=1)
else:
# x correspond to queries
t = enc_out.size()[-1]
kv_set = torch.stack([self.conv1(enc_out[..., i]) for i in range(t)], dim=-1)
K, V = torch.split(kv_set, self.num_hidden, dim=1)
Q = x
K_rep = torch.stack([K] * s, dim=-2)
V_rep = torch.stack([V] * s, dim=-1)
Q_rep = torch.stack([Q] * t, dim=-1)
# concatenate queries and keys for cross-channel convolution
Q_K = torch.concat((Q_rep, K_rep), dim=1)
if self.mask:
# only feed in 'previous' keys & values for computing softmax
V_out = []
# for each query
for i in range(t):
Q_K_temp = rearrange(Q_K[..., :i+1, i], 'b c h w t -> (b t) c h w')
extr_feat = rearrange(torch.squeeze(self.conv2(Q_K_temp), dim=1), '(b t) h w -> b h w t', b=b, t=i+1)
attn_mask = F.softmax(extr_feat, dim=-1)
# convex combination over values using weights from attention mask, per channel c
V_out.append(torch.stack([torch.sum(torch.mul(attn_mask, V_rep[:, c, :, :, i, :i+1]), dim=-1) for c in range(V_rep.size()[1])], dim=1))
V_out = torch.stack(V_out, dim=-1)
else:
Q_K = rearrange(Q_K, 'b c h w s t -> (b s t) c h w') # no convolution across time dim!
extr_feat = rearrange(torch.squeeze(self.conv2(Q_K), dim=1), '(b s t) h w -> b h w t s', b=b, t=t)
attn_mask = F.softmax(extr_feat, dim=-2)
V_out = torch.stack([torch.sum(torch.mul(attn_mask, V_rep[:, c, ...]), dim=-2) for c in range(V_rep.size()[1])], dim=1)
return V_out
class PositionalEncoding(nn.Module):
def __init__(self, num_hidden, img_width):
# no differentiation should happen with respect to the params in here!
super(PositionalEncoding, self).__init__()
self.num_hidden = num_hidden
self.img_width = img_width
def _get_sinusoid_encoding_table(self, t, device):
''' Sinusoid position encoding table '''
sinusoid_table = torch.stack([self._get_position_angle_vec(pos_i) for pos_i in range(t)], dim=0)
sinusoid_table[:, :, 0::2] = torch.sin(sinusoid_table[:, :, 0::2]) # even dim
sinusoid_table[:, :, 1::2] = torch.cos(sinusoid_table[:, :, 1::2]) # odd dim
return torch.moveaxis(sinusoid_table, 0, -1)
def _get_position_angle_vec(self, position):
return_list = [torch.ones((1,
self.img_width,
self.img_width),
device=torch.device("cuda:0" if torch.cuda.is_available() else "cpu")) *
(position / np.power(10000, 2 * (hid_j // 2) / self.num_hidden[-1])) for hid_j in range(self.num_hidden[-1])]
return torch.stack(return_list, dim=1)
def forward(self, x, t, single=False):
"""Returns entire positional encoding until step T if not single, otherwise only encoding of time step T."""
if not single:
self.register_buffer('pos_table', self._get_sinusoid_encoding_table(t, x.get_device()))
return torch.squeeze(x + self.pos_table.clone().detach(), dim=0)
else:
if t % 2 == 0:
return x + torch.unsqueeze(torch.sin(self._get_position_angle_vec(t)), dim=-1).clone().detach()
else:
return x + torch.unsqueeze(torch.cos(self._get_position_angle_vec(t)), dim=-1).clone().detach()
class Encoder(nn.Module):
def __init__(self, num_hidden, depth, dilation_rate, num_conv_layers, kernel_size, img_width):
super().__init__()
self.num_hidden = num_hidden
self.depth = depth
self.dilation_rate = dilation_rate
self.num_conv_layers = num_conv_layers
self.kernel_size = kernel_size
self.img_width = img_width
self.layers = nn.ModuleList([])
self.num_hidden = self.num_hidden
for _ in range(self.depth):
self.layers.append(nn.ModuleList([
Residual(PreNorm([self.num_hidden[-1], self.img_width, self.img_width],
ConvAttention(kernel_size=self.kernel_size, num_hidden=self.num_hidden[-1], enc=True))),
Residual(PreNorm([self.num_hidden[-1], self.img_width, self.img_width],
FeedForward(kernel_size=self.kernel_size, num_hidden=self.num_hidden[-1],
dilation_rate=self.dilation_rate, num_conv_layers=self.num_conv_layers)))
]))
def forward(self, x):
for attn, ff in self.layers:
x = attn(x)
x = ff(x)
return x
class Decoder(nn.Module):
def __init__(self, num_hidden, depth, dilation_rate, num_conv_layers, kernel_size, img_width, non_pred_channels):
super().__init__()
self.layers = nn.ModuleList([])
self.dilation_rate = dilation_rate
self.num_conv_layers = num_conv_layers
self.depth = depth
self.kernel_size = kernel_size
self.img_width = img_width
self.num_hidden = num_hidden
self.num_non_pred_feat = non_pred_channels
for _ in range(self.depth):
self.layers.append(nn.ModuleList([
# (masked) query self-attention
Residual(PreNorm([self.num_hidden[-1], self.img_width, self.img_width],
ConvAttention(num_hidden=self.num_hidden[-1], kernel_size=self.kernel_size, mask=True))),
# encoder-decoder attention
Residual(PreNorm([self.num_hidden[-1], self.img_width, self.img_width],
ConvAttention(num_hidden=self.num_hidden[-1], kernel_size=self.kernel_size, enc=False))),
# feed forward
Residual(PreNorm([self.num_hidden[-1], self.img_width, self.img_width],
FeedForward(num_hidden=self.num_hidden[-1], kernel_size=self.kernel_size, dilation_rate=self.dilation_rate, num_conv_layers=self.num_conv_layers)))
]))
def forward(self, queries, enc_out):
for query_attn, attn, ff in self.layers:
queries = query_attn(queries)
x = attn(queries, enc_out=enc_out)
x = ff(x)
return x
class Conv_Transformer(nn.Module):
"""Standard, single-headed ConvTransformer like in https://arxiv.org/pdf/2011.10185.pdf"""
def __init__(self, num_hidden, depth, dilation_rate, num_conv_layers, kernel_size, img_width, non_pred_channels, num_layers_query_feat, in_channels):
super(Conv_Transformer, self).__init__()
self.num_hidden = num_hidden
self.depth = depth
self.num_layers_query_feat = num_layers_query_feat
self.dilation_rate = dilation_rate
self.num_conv_layers = num_conv_layers
self.kernel_size = kernel_size
self.img_width = img_width
self.in_channels = in_channels
self.non_pred_channels = non_pred_channels
self.pos_embedding = PositionalEncoding(self.num_hidden, self.img_width)
self.Encoder = Encoder(num_hidden=self.num_hidden, depth=self.depth, dilation_rate=self.dilation_rate,
num_conv_layers=self.num_conv_layers, kernel_size=self.kernel_size, img_width=self.img_width)
self.Decoder = Decoder(num_hidden=self.num_hidden, depth=self.depth, dilation_rate=self.dilation_rate,
num_conv_layers=self.num_conv_layers, kernel_size=self.kernel_size, img_width=self.img_width, non_pred_channels=self.non_pred_channels)
self.input_feat_gen = Conv_Block(self.in_channels, self.num_hidden[-1], num_conv_layers=self.num_conv_layers, kernel_size=self.kernel_size)
# TODO (optionally): replace this by SFFN
self.back_to_pixel = nn.Sequential(
nn.Conv2d(self.num_hidden[-1], 4, kernel_size=1)
)
def forward(self, frames, n_predictions):
_, _, _, _, T = frames.size()
feature_map = self.feature_embedding(img=frames, network=self.input_feat_gen)
enc_in = self.pos_embedding(feature_map, T)
# encode all input values
enc_out = torch.concat(self.Encoder(enc_in), dim=-1)
out_list = []
queries = self.feature_embedding(img=feature_map[..., -1], network=self.query_feat_gen)
for _ in range(n_predictions):
dec_out = self.Decoder(queries, enc_out)
pred = self.feature_embedding(dec_out)
out_list.append(pred)
queries = torch.concat((queries, pred), dim=-1)
x = torch.stack(out_list, dim=-1)
return x
def feature_embedding(self, img, network):
generator = network
gen_img = []
for i in range(img.shape[-1]):
gen_img.append(generator(img[..., i]))
gen_img = torch.stack(gen_img, dim=-1)
return gen_img
class ENS_Conv_Transformer(Conv_Transformer):
"""ConvTransformer that employs delta model and can read in non-pred future features, hence taylored to the ENS challenge."""
def __init__(self, num_hidden, output_dim, depth, dilation_rate, num_conv_layers, kernel_size, img_width, non_pred_channels, num_layers_query_feat, in_channels, baseline):
super(ENS_Conv_Transformer, self).__init__(num_hidden, depth, dilation_rate, num_conv_layers, kernel_size, img_width, non_pred_channels, num_layers_query_feat, in_channels - 1)
# remove cloud mask
self.in_channels = self.in_channels - 1
self.baseline = baseline
self.output_dim = output_dim
def forward(self, input_tensor, non_pred_feat=None, prediction_count=1):
baseline = eval(self.baseline + "(input_tensor[:, 0:5, :, :, :], 4)")
b, _, width, height, T = input_tensor.size()
pred_deltas = torch.zeros((b, self.output_dim, height, width, prediction_count), device = self._get_device())
preds = torch.zeros((b, self.output_dim, height, width, prediction_count), device = self._get_device())
baselines = torch.zeros((b, self.output_dim, height, width, prediction_count), device = self._get_device())
# remove cloud mask channel for feature embedding
feature_map = torch.concat((input_tensor[:, :4, ...], input_tensor[:, 5:, ...]), dim=1)
features = self.feature_embedding(img=feature_map, network=self.input_feat_gen)
enc_in = torch.stack([self.pos_embedding(features[i, ...], T) for i in range(b)], dim=0)
enc_out = self.Encoder(enc_in)
# first query stems from last input frame
queries = features[..., -1:]
baselines[..., 0] = baseline
pred_deltas[..., 0] = self.back_to_pixel(self.Decoder(queries, enc_out)[..., 0])
preds[..., 0] = pred_deltas[..., 0] + baselines[..., 0]
for t in range(1, prediction_count):
if self.baseline == "mean_cube":
baselines[..., t] = (preds[..., t - 1] + (baselines[..., t - 1] * (T + t)))/(T + t + 1)
if self.baseline == "zeros":
pass
else:
baselines[..., t] = preds[..., t - 1]
# concatenate with non-pred features & feature embedding & do positional encoding
query = self.pos_embedding(self.feature_embedding(torch.concat((preds[..., t-1:t], non_pred_feat[..., t-1:t]), dim=1), network=self.input_feat_gen), t, single=True)
queries = torch.concat((queries, query), dim=-1)
pred_deltas[..., :t] = torch.stack([self.back_to_pixel(self.Decoder(queries, enc_out)[..., i]) for i in range(t)], dim=-1)
preds[..., t] = pred_deltas[..., t] + baselines[..., t]
return preds, pred_deltas, baselines
def _get_device(self):
return next(self.parameters()).device | [((494, 511), 'torch.nn.LayerNorm', 'nn.LayerNorm', (['dim'], {}), '(dim)\n', (506, 511), True, 'import torch.nn as nn\n'), ((2972, 3000), 'torch.stack', 'torch.stack', (['([K] * s)'], {'dim': '(-2)'}), '([K] * s, dim=-2)\n', (2983, 3000), False, 'import torch\n'), ((3017, 3045), 'torch.stack', 'torch.stack', (['([V] * s)'], {'dim': '(-1)'}), '([V] * s, dim=-1)\n', (3028, 3045), False, 'import torch\n'), ((3062, 3090), 'torch.stack', 'torch.stack', (['([Q] * t)'], {'dim': '(-1)'}), '([Q] * t, dim=-1)\n', (3073, 3090), False, 'import torch\n'), ((3174, 3209), 'torch.concat', 'torch.concat', (['(Q_rep, K_rep)'], {'dim': '(1)'}), '((Q_rep, K_rep), dim=1)\n', (3186, 3209), False, 'import torch\n'), ((4911, 4948), 'torch.sin', 'torch.sin', (['sinusoid_table[:, :, 0::2]'], {}), '(sinusoid_table[:, :, 0::2])\n', (4920, 4948), False, 'import torch\n'), ((4998, 5035), 'torch.cos', 'torch.cos', (['sinusoid_table[:, :, 1::2]'], {}), '(sinusoid_table[:, :, 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'import torch\n'), ((3978, 4024), 'einops.rearrange', 'rearrange', (['Q_K', '"""b c h w s t -> (b s t) c h w"""'], {}), "(Q_K, 'b c h w s t -> (b s t) c h w')\n", (3987, 4024), False, 'from einops import rearrange\n'), ((4194, 4222), 'torch.nn.functional.softmax', 'F.softmax', (['extr_feat'], {'dim': '(-2)'}), '(extr_feat, dim=-2)\n', (4203, 4222), True, 'import torch.nn.functional as F\n'), ((10637, 10685), 'torch.nn.Conv2d', 'nn.Conv2d', (['self.num_hidden[-1]', '(4)'], {'kernel_size': '(1)'}), '(self.num_hidden[-1], 4, kernel_size=1)\n', (10646, 10685), True, 'import torch.nn as nn\n'), ((11332, 11369), 'torch.concat', 'torch.concat', (['(queries, pred)'], {'dim': '(-1)'}), '((queries, pred), dim=-1)\n', (11344, 11369), False, 'import torch\n'), ((14235, 14273), 'torch.concat', 'torch.concat', (['(queries, query)'], {'dim': '(-1)'}), '((queries, query), dim=-1)\n', (14247, 14273), False, 'import torch\n'), ((1792, 1923), 'torch.nn.Conv2d', 'nn.Conv2d', ([], {'in_channels': 'self.num_hidden', 'out_channels': '(3 * self.num_hidden)', 'kernel_size': '(1)', 'padding': '"""same"""', 'padding_mode': '"""reflect"""'}), "(in_channels=self.num_hidden, out_channels=3 * self.num_hidden,\n kernel_size=1, padding='same', padding_mode='reflect')\n", (1801, 1923), True, 'import torch.nn as nn\n'), ((2058, 2189), 'torch.nn.Conv2d', 'nn.Conv2d', ([], {'in_channels': 'self.num_hidden', 'out_channels': '(2 * self.num_hidden)', 'kernel_size': '(1)', 'padding': '"""same"""', 'padding_mode': '"""reflect"""'}), "(in_channels=self.num_hidden, out_channels=2 * self.num_hidden,\n kernel_size=1, padding='same', padding_mode='reflect')\n", (2067, 2189), True, 'import torch.nn as nn\n'), ((3417, 3479), 'einops.rearrange', 'rearrange', (['Q_K[(...), :i + 1, (i)]', '"""b c h w t -> (b t) c h w"""'], {}), "(Q_K[(...), :i + 1, (i)], 'b c h w t -> (b t) c h w')\n", (3426, 3479), False, 'from einops import rearrange\n'), ((3620, 3648), 'torch.nn.functional.softmax', 'F.softmax', (['extr_feat'], {'dim': '(-1)'}), '(extr_feat, dim=-1)\n', (3629, 3648), True, 'import torch.nn.functional as F\n'), ((5452, 5507), 'numpy.power', 'np.power', (['(10000)', '(2 * (hid_j // 2) / self.num_hidden[-1])'], {}), '(10000, 2 * (hid_j // 2) / self.num_hidden[-1])\n', (5460, 5507), True, 'import numpy as np\n'), ((14098, 14173), 'torch.concat', 'torch.concat', (['(preds[(...), t - 1:t], non_pred_feat[(...), t - 1:t])'], {'dim': '(1)'}), '((preds[(...), t - 1:t], non_pred_feat[(...), t - 1:t]), dim=1)\n', (14110, 14173), False, 'import torch\n'), ((4266, 4308), 'torch.mul', 'torch.mul', (['attn_mask', 'V_rep[:, (c), (...)]'], {}), '(attn_mask, V_rep[:, (c), (...)])\n', (4275, 4308), False, 'import torch\n'), ((3799, 3853), 'torch.mul', 'torch.mul', (['attn_mask', 'V_rep[:, (c), :, :, (i), :i + 1]'], {}), '(attn_mask, V_rep[:, (c), :, :, (i), :i + 1])\n', (3808, 3853), False, 'import torch\n'), ((5363, 5388), 'torch.cuda.is_available', 'torch.cuda.is_available', ([], {}), '()\n', (5386, 5388), False, 'import torch\n')] |
rodrigoapereira/python-hydra-sdk | tests/test_clients.py | ea3d61ed6f7ef1bc1990c442548d21b10155d075 | # Copyright (C) 2017 O.S. Systems Software LTDA.
# This software is released under the MIT License
import unittest
from hydra import Hydra, Client
class ClientsTestCase(unittest.TestCase):
def setUp(self):
self.hydra = Hydra('http://localhost:4444', 'client', 'secret')
self.client = Client(
name='new-client',
secret='client-secret',
scopes=['devices', 'products'],
redirect_uris=['http://localhost/callback'],
)
def test_can_create_client(self):
client = self.hydra.clients.create(self.client)
self.addCleanup(self.hydra.clients.delete, client_id=client.id)
self.assertEqual(client.name, 'new-client')
self.assertEqual(client.secret, 'client-secret')
self.assertEqual(client.scopes, ['devices', 'products'])
self.assertEqual(client.redirect_uris, ['http://localhost/callback'])
def test_can_get_client(self):
client_id = self.hydra.clients.create(self.client).id
self.addCleanup(self.hydra.clients.delete, client_id=client_id)
client = self.hydra.clients.get(client_id)
self.assertEqual(client.id, client_id)
def test_can_update_client(self):
client = self.hydra.clients.create(self.client)
self.addCleanup(self.hydra.clients.delete, client_id=client.id)
self.assertEqual(client.name, 'new-client')
client.name = 'new-client-name'
self.hydra.clients.update(client)
self.assertEqual(client.name, 'new-client-name')
def test_can_delete_client(self):
client = self.hydra.clients.create(self.client)
self.addCleanup(self.hydra.clients.delete, client_id=client.id)
self.assertIsNotNone(self.hydra.clients.get(client.id))
self.hydra.clients.delete(client.id)
self.assertIsNone(self.hydra.clients.get(client.id))
def test_can_list_all_clients(self):
client1 = self.hydra.clients.create(self.client)
self.addCleanup(self.hydra.clients.delete, client_id=client1.id)
client2 = self.hydra.clients.create(self.client)
self.addCleanup(self.hydra.clients.delete, client_id=client2.id)
clients = [c.id for c in self.hydra.clients.all()]
self.assertIn(client1.id, clients)
self.assertIn(client2.id, clients)
| [((236, 286), 'hydra.Hydra', 'Hydra', (['"""http://localhost:4444"""', '"""client"""', '"""secret"""'], {}), "('http://localhost:4444', 'client', 'secret')\n", (241, 286), False, 'from hydra import Hydra, Client\n'), ((309, 439), 'hydra.Client', 'Client', ([], {'name': '"""new-client"""', 'secret': '"""client-secret"""', 'scopes': "['devices', 'products']", 'redirect_uris': "['http://localhost/callback']"}), "(name='new-client', secret='client-secret', scopes=['devices',\n 'products'], redirect_uris=['http://localhost/callback'])\n", (315, 439), False, 'from hydra import Hydra, Client\n')] |
Phillistan16/fastestimator | test/PR_test/unit_test/backend/test_binary_crossentropy.py | 54c9254098aee89520814ed54b6e6016b821424f | # Copyright 2020 The FastEstimator Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
import unittest
import numpy as np
import tensorflow as tf
import torch
import fastestimator as fe
class TestBinarayCrossEntropy(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.tf_true = tf.constant([[1], [0], [1], [0]])
cls.tf_pred = tf.constant([[0.9], [0.3], [0.8], [0.1]])
cls.torch_true = torch.tensor([[1], [0], [1], [0]])
cls.torch_pred = torch.tensor([[0.9], [0.3], [0.8], [0.1]])
def test_binaray_crossentropy_average_loss_true_tf(self):
obj1 = fe.backend.binary_crossentropy(y_pred=self.tf_pred, y_true=self.tf_true).numpy()
obj2 = 0.19763474
self.assertTrue(np.allclose(obj1, obj2))
def test_binaray_crossentropy_average_loss_false_tf(self):
obj1 = fe.backend.binary_crossentropy(y_pred=self.tf_pred, y_true=self.tf_true, average_loss=False).numpy()
obj2 = np.array([0.10536041, 0.3566748, 0.22314338, 0.10536041])
self.assertTrue(np.allclose(obj1, obj2))
def test_binaray_crossentropy_average_from_logit_average_loss_true_tf(self):
obj1 = fe.backend.binary_crossentropy(y_pred=self.tf_pred,
y_true=self.tf_true,
from_logits=True,
average_loss=True).numpy()
obj2 = 0.57775164
self.assertTrue(np.allclose(obj1, obj2))
def test_binaray_crossentropy_average_from_logit_average_loss_false_tf(self):
obj1 = fe.backend.binary_crossentropy(y_pred=self.tf_pred,
y_true=self.tf_true,
from_logits=True,
average_loss=False).numpy()
obj2 = np.array([0.34115386, 0.8543553, 0.37110066, 0.7443967])
self.assertTrue(np.allclose(obj1, obj2))
def test_binaray_crossentropy_average_loss_true_torch(self):
obj1 = fe.backend.binary_crossentropy(y_pred=self.torch_pred, y_true=self.torch_true).numpy()
obj2 = 0.19763474
self.assertTrue(np.allclose(obj1, obj2))
def test_binaray_crossentropy_average_loss_false_torch(self):
obj1 = fe.backend.binary_crossentropy(y_pred=self.torch_pred, y_true=self.torch_true,
average_loss=False).numpy()
obj2 = np.array([0.10536041, 0.3566748, 0.22314338, 0.10536041])
self.assertTrue(np.allclose(obj1, obj2))
def test_binaray_crossentropy_average_from_logit_average_loss_true_torch(self):
obj1 = fe.backend.binary_crossentropy(y_pred=self.torch_pred,
y_true=self.torch_true,
from_logits=True,
average_loss=True).numpy()
obj2 = 0.57775164
self.assertTrue(np.allclose(obj1, obj2))
def test_binaray_crossentropy_average_from_logit_average_loss_false_torch(self):
obj1 = fe.backend.binary_crossentropy(y_pred=self.torch_pred,
y_true=self.torch_true,
from_logits=True,
average_loss=False).numpy()
obj2 = np.array([0.34115386, 0.8543553, 0.37110066, 0.7443967])
self.assertTrue(np.allclose(obj1, obj2))
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((2793, 2816), 'numpy.allclose', 'np.allclose', (['obj1', 'obj2'], {}), '(obj1, obj2)\n', (2804, 2816), True, 'import numpy as np\n'), ((3150, 3173), 'numpy.allclose', 'np.allclose', (['obj1', 'obj2'], {}), '(obj1, obj2)\n', (3161, 3173), True, 'import numpy as np\n'), ((3587, 3610), 'numpy.allclose', 'np.allclose', (['obj1', 'obj2'], {}), '(obj1, obj2)\n', (3598, 3610), True, 'import numpy as np\n'), ((4072, 4095), 'numpy.allclose', 'np.allclose', (['obj1', 'obj2'], {}), '(obj1, obj2)\n', (4083, 4095), True, 'import numpy as np\n'), ((1213, 1285), 'fastestimator.backend.binary_crossentropy', 'fe.backend.binary_crossentropy', ([], {'y_pred': 'self.tf_pred', 'y_true': 'self.tf_true'}), '(y_pred=self.tf_pred, y_true=self.tf_true)\n', (1243, 1285), True, 'import fastestimator as fe\n'), ((1448, 1544), 'fastestimator.backend.binary_crossentropy', 'fe.backend.binary_crossentropy', ([], {'y_pred': 'self.tf_pred', 'y_true': 'self.tf_true', 'average_loss': '(False)'}), '(y_pred=self.tf_pred, y_true=self.tf_true,\n average_loss=False)\n', (1478, 1544), True, 'import fastestimator as fe\n'), ((1768, 1881), 'fastestimator.backend.binary_crossentropy', 'fe.backend.binary_crossentropy', ([], {'y_pred': 'self.tf_pred', 'y_true': 'self.tf_true', 'from_logits': '(True)', 'average_loss': '(True)'}), '(y_pred=self.tf_pred, y_true=self.tf_true,\n from_logits=True, average_loss=True)\n', (1798, 1881), True, 'import fastestimator as fe\n'), ((2197, 2311), 'fastestimator.backend.binary_crossentropy', 'fe.backend.binary_crossentropy', ([], {'y_pred': 'self.tf_pred', 'y_true': 'self.tf_true', 'from_logits': '(True)', 'average_loss': '(False)'}), '(y_pred=self.tf_pred, y_true=self.tf_true,\n from_logits=True, average_loss=False)\n', (2227, 2311), True, 'import fastestimator as fe\n'), ((2656, 2734), 'fastestimator.backend.binary_crossentropy', 'fe.backend.binary_crossentropy', ([], {'y_pred': 'self.torch_pred', 'y_true': 'self.torch_true'}), '(y_pred=self.torch_pred, y_true=self.torch_true)\n', (2686, 2734), True, 'import fastestimator as fe\n'), ((2900, 3003), 'fastestimator.backend.binary_crossentropy', 'fe.backend.binary_crossentropy', ([], {'y_pred': 'self.torch_pred', 'y_true': 'self.torch_true', 'average_loss': '(False)'}), '(y_pred=self.torch_pred, y_true=self.\n torch_true, average_loss=False)\n', (2930, 3003), True, 'import fastestimator as fe\n'), ((3275, 3395), 'fastestimator.backend.binary_crossentropy', 'fe.backend.binary_crossentropy', ([], {'y_pred': 'self.torch_pred', 'y_true': 'self.torch_true', 'from_logits': '(True)', 'average_loss': '(True)'}), '(y_pred=self.torch_pred, y_true=self.\n torch_true, from_logits=True, average_loss=True)\n', (3305, 3395), True, 'import fastestimator as fe\n'), ((3713, 3834), 'fastestimator.backend.binary_crossentropy', 'fe.backend.binary_crossentropy', ([], {'y_pred': 'self.torch_pred', 'y_true': 'self.torch_true', 'from_logits': '(True)', 'average_loss': '(False)'}), '(y_pred=self.torch_pred, y_true=self.\n torch_true, from_logits=True, average_loss=False)\n', (3743, 3834), True, 'import fastestimator as fe\n')] |
kyeser/scTools | ats_hex.py | c4c7dee0c41c8afe1da6350243df5f9d9b929c7f | #!/usr/bin/env python
from scTools import interval, primeForm
from scTools.rowData import ats
from scTools.scData import *
count = 1
for w in ats:
prime = primeForm(w[0:6])
print '%3d\t' % count,
for x in w:
print '%X' % x,
print ' ',
intervals = interval(w)
for y in intervals:
print '%X' % y,
print '\t%2d\t' % sc6.index(prime),
if prime == sc6[1] or prime == sc6[7] or prime == sc6[8] or \
prime == sc6[20] or prime == sc6[32] or prime == sc6[35]:
print 'AC'
elif prime == sc6[17]:
print 'AT'
else:
print
count += 1
| [] |
Albert-91/precon | src/precon/commands.py | aaded1d6a5f743b3539ea46b19a37a7bf9930e05 | import asyncio
import click
from precon.devices_handlers.distance_sensor import show_distance as show_distance_func
from precon.remote_control import steer_vehicle, Screen
try:
import RPi.GPIO as GPIO
except (RuntimeError, ModuleNotFoundError):
import fake_rpi
GPIO = fake_rpi.RPi.GPIO
@click.command(name="rc")
def remote_control() -> None:
loop = asyncio.get_event_loop()
try:
with Screen() as screen:
loop.run_until_complete(steer_vehicle(screen))
except KeyboardInterrupt:
print("Finishing remote control...")
except Exception as e:
print("Raised unexpected error: %s" % e)
finally:
GPIO.cleanup()
@click.command(name="show-distance")
def show_distance() -> None:
loop = asyncio.get_event_loop()
try:
loop.run_until_complete(show_distance_func())
except KeyboardInterrupt:
print("Finishing measuring distance...")
except Exception as e:
print("Raised unexpected error: %s" % e)
finally:
GPIO.cleanup()
| [((305, 329), 'click.command', 'click.command', ([], {'name': '"""rc"""'}), "(name='rc')\n", (318, 329), False, 'import click\n'), ((687, 722), 'click.command', 'click.command', ([], {'name': '"""show-distance"""'}), "(name='show-distance')\n", (700, 722), False, 'import click\n'), ((371, 395), 'asyncio.get_event_loop', 'asyncio.get_event_loop', ([], {}), '()\n', (393, 395), False, 'import asyncio\n'), ((763, 787), 'asyncio.get_event_loop', 'asyncio.get_event_loop', ([], {}), '()\n', (785, 787), False, 'import asyncio\n'), ((669, 683), 'RPi.GPIO.cleanup', 'GPIO.cleanup', ([], {}), '()\n', (681, 683), True, 'import RPi.GPIO as GPIO\n'), ((1027, 1041), 'RPi.GPIO.cleanup', 'GPIO.cleanup', ([], {}), '()\n', (1039, 1041), True, 'import RPi.GPIO as GPIO\n'), ((418, 426), 'precon.remote_control.Screen', 'Screen', ([], {}), '()\n', (424, 426), False, 'from precon.remote_control import steer_vehicle, Screen\n'), ((829, 849), 'precon.devices_handlers.distance_sensor.show_distance', 'show_distance_func', ([], {}), '()\n', (847, 849), True, 'from precon.devices_handlers.distance_sensor import show_distance as show_distance_func\n'), ((474, 495), 'precon.remote_control.steer_vehicle', 'steer_vehicle', (['screen'], {}), '(screen)\n', (487, 495), False, 'from precon.remote_control import steer_vehicle, Screen\n')] |
sjtichenor/midway-ford | midway.py | 43bf8770f2edd483d7c27dede8b9ac1fb8f10152 | import csv
import string
import ftplib
import math
import time
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import sqlite3
from lxml import html
import requests
import sys
import midwords
import facebook
import hd_images
import adwords_feeds
import sheets
import random
import sales_specials
import scrape
from pprint import pprint
from pyvirtualdisplay import Display
import locale
locale.setlocale(locale.LC_ALL, 'en_US.utf8')
# Misc stuff
def isNumber(s):
try:
float(s)
return True
except ValueError:
return False
def start_chromedriver():
display = Display(visible=0, size=(800, 800))
display.start()
path_to_chromedriver = 'chromedriver'
browser = webdriver.Chrome(executable_path=path_to_chromedriver)
return browser
# FMC Dealer Scrapes
def randomInterval(): #returns random float roughly between 1.5 and 2.75
return 1.75+1*random.random()-.25*random.random()
def switchDefaultSearch(browser) : # Switch between MyLot/States
#Switch default search back to Dealership Proximity
print('Switching default search...')
browser.get('https://www.vlplus.dealerconnection.com/Search?&searchType=quicksearch')
time.sleep(3)
browser.find_element_by_xpath('//a[@id="ActivateSettings"]').click()
time.sleep(3)
browser.find_element_by_xpath('//a[text()="Search Settings"]').click()
time.sleep(3)
# Check what default is currently set to
tree = html.fromstring(browser.page_source)
currentSetting = tree.xpath('//option[@selected]/text()')
print('Setting Before:', currentSetting)
if 'My Lot' in currentSetting:
print('Switching default search from My Lot to Proximity')
browser.find_element_by_xpath('//select[@id="searchSettingsDefaultSearchMode"]').click()
time.sleep(2)
browser.find_element_by_xpath('//option[@value="6"]').click()
time.sleep(2)
elif 'States' in currentSetting :
print('Switching default search from States to My Lot')
browser.find_element_by_xpath('//select[@id="searchSettingsDefaultSearchMode"]').click()
time.sleep(2)
browser.find_element_by_xpath('//option[@value="1"]').click()
time.sleep(2)
currentSetting = tree.xpath('//option[@selected]/text()')
#print('Setting After:', currentSetting) This doesn't work..
browser.find_element_by_xpath('//a[@id="saveSearchSettings"]').click()
time.sleep(2)
browser.get('https://www.vlplus.dealerconnection.com/Search?&searchType=quicksearch')
time.sleep(2)
print('Finished switching default search...')
return browser
def getVinList() :
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
vinList = []
c.execute('SELECT vin FROM masterInventory where invType = ?', ('New',))
vinTupleList = c.fetchall()
for vinTuple in vinTupleList :
vin = vinTuple[0]
vinList.append(vin)
numVehicles = len(vinList)
conn.commit()
conn.close()
return vinList
def fmcLogin(browser) : #Logs into fmcdealer and returns browser
# Fire up ChomeDriver
# path_to_chromedriver = '/Users/spencertichenor/PycharmProjects/midway/chromedriver'
# browser = webdriver.Chrome(executable_path = path_to_chromedriver)
# Log into FMC Dealer
url = 'https://fmcdealer.com'
browser.get(url)
username = browser.find_element_by_id('DEALER-WSLXloginUserIdInput')
password = browser.find_element_by_id('DEALER-WSLXloginPasswordInput')
username.send_keys('t-spen29')
password.send_keys('Tichenor5')
browser.find_element_by_xpath('//div[@id="DEALER-WSLXloginWSLSubmitButton"]/input').click()
time.sleep(5)
return browser
def navigateToVincent(browser, vin) :
print('\nNavigating to Vincent page for VIN: ' + vin + '...\n\n')
#print('\nSearching for rebate info for vehicle ' + str(k+1) + '/' + str(len(vinList)) + '...')
#print('\n\tVIN: ' + vin + '\n')
browser.get('https://www.vlplus.dealerconnection.com/Search?&searchType=quicksearch')
time.sleep(3)
try :
vinField = browser.find_element_by_id('txtVIN')
vinField.send_keys(vin)
browser.find_element_by_xpath('//input[@value="Search"]').click()
time.sleep(2)
except :
print('VIN FIELD ERROR:')
print(sys.exc_info()[0])
#errorList.append(vin)
#pass this was pass but i think it should be return
return browser
source = browser.page_source
if 'Please broaden your search.' not in source : # Check if vehicle was not found in dealership proximity search
# Click on Vincent button
#source = browser.page_source
try :
vincentUrl = vincentUrl[0]
browser.get(vincentUrl)
time.sleep(4)
except :
print('Vincent Url Error:')
print(sys.exc_info()[0])
#errorList.append(vin)
#pass
return browser
source = browser.page_source
tree = html.fromstring(source)
if 'Please click the "Close" button to continue with the Sales Process.' in source : # Check for recall warning
browser.find_element_by_xpath('//input[@value="Close"]').click()
time.sleep(2)
if 'value="Certificate Inquiry"' not in source : # Check if vehicle already sold
# Enter ZIP code and click next
try :
zipField = browser.find_element_by_xpath('//div/input[@name="customerZip"]')
zipField.send_keys('55113')
browser.find_element_by_id('primaryButtonId').click()
time.sleep(2)
except :
print('ZIP FIELD ERROR:')
print(sys.exc_info()[0])
#errorList.append(vin)
pass
# Get rebate info
#rebateInfo = scrapeRebateInfo(browser)
else :
#soldList.append(vin)
print('\tIt looks like this vehicle has already been sold.\n\n')
else : # Vehicle not found in Dealership Proximity search
print('\tVehicle not found after searching Dealership Proximity.')
#Switch default search to My Lot
browser = switchDefaultSearch(browser)
try :
vinField = browser.find_element_by_id('txtVIN')
vinField.send_keys(vin)
browser.find_element_by_xpath('//input[@value="Search"]').click()
time.sleep(2)
except :
#errorList.append(vin)
print('VIN FIELD ERROR:')
print(sys.exc_info()[0])
#switchToProximity(browser)
return browser
# Click on Vincent button
source = browser.page_source
tree = html.fromstring(source)
vincentUrl = tree.xpath('//a[@title="Smart Vincent"]/@href')
try :
vincentUrl = vincentUrl[0]
browser.get(vincentUrl)
time.sleep(4)
except :
#errorList.append(vin)
print('Vincent Url Error:')
print(sys.exc_info()[0])
#switchToProximity(browser)
#return browser
source = browser.page_source
tree = html.fromstring(source)
if 'Please click the "Close" button to continue with the Sales Process.' in source : # Check for recall warning
browser.find_element_by_xpath('//input[@value="Close"]').click()
time.sleep(2)
if 'value="Certificate Inquiry"' not in source : # Check if vehicle already sold
# Enter ZIP code and click next
try :
zipField = browser.find_element_by_xpath('//div/input[@name="customerZip"]')
zipField.send_keys('55113')
browser.find_element_by_id('primaryButtonId').click()
time.sleep(2)
except :
#errorList.append(vin)
print('ZIP FIELD ERROR:')
print(sys.exc_info()[0])
#switchToProximity(browser)
#return browser
# Get rebate info
#rebateInfo = scrapeRebateInfo(browser)
else :
#soldList.append(vin)
print('\tIt looks like this vehicle has already been sold.\n\n')
#Switch default search back to Dealership Proximity
#switchToProximity(browser)
#pass
return browser
# print('\nNumber of vehicles appear to have been sold: ' + str(len(soldList)))
# print('Sold List:')
# print(soldList)
# print('\nNumber of vehicles that ran into errors: ' + str(len(errorList)))
# print('Error List:')
# print(errorList)
#print('\n\nFinished getting rebate information.')
def scrapeRebateInfo(page_source) : #input browser of vincent page, return tuple with unconditional rebate info
# Get rebate info
#source = browser.page_source
tree = html.fromstring(page_source)
vin = tree.xpath('//dt[.="VIN:"]/following-sibling::dd/text()')
vin = vin[0].replace('\xa0', ' ').replace('\t', '').replace('\n', '')
rowspans = tree.xpath('//table[@summary="This table displays and lets you choose public program bundles."]/tbody/tr/td[@class="textC altRow"]/@rowspan | //table[@summary="This table displays and lets you choose public program bundles."]/tbody/tr/td[@class="textC "]/@rowspan')
conditions = tree.xpath('//table[@summary="This table displays and lets you choose public program bundles."]/tbody/tr[@class="programTableHeader"]/td[@style="{border-right:none;}"]/text()')
nums = tree.xpath('//table[@summary="This table displays and lets you choose public program bundles."]/tbody/tr/td[@class="textL txtCol "]/a/text() | //table[@summary="This table displays and lets you choose public program bundles."]/tbody/tr/td[@class="textL txtCol altRow "]/a/text()')
names = tree.xpath('//table[@summary="This table displays and lets you choose public program bundles."]/tbody/tr/td[@class="textL txtCol "]/text() | //table[@summary="This table displays and lets you choose public program bundles."]/tbody/tr/td[@class="textL txtCol altRow "]/text()')
amounts = tree.xpath('//table[@summary="This table displays and lets you choose public program bundles."]/tbody/tr/td[@class="textR "]/text() | //table[@summary="This table displays and lets you choose public program bundles."]/tbody/tr/td[@class="textR altRow"]/text()')
expirations = tree.xpath('//table[@summary="This table displays and lets you choose public program bundles."]/tbody/tr/td[@class="textC highlight noWrap"]/text()')
to_db = (vin,)
if rowspans == [] : # No unconditional rebates
print('No rebates found for this vehicle.\n')
print('Updating rebate info...')
while len(to_db) < 43 :
to_db += (None,)
else : # Yah, it has unconditional rebates
# Clean up Condition info
condition = conditions[0]
condition = condition.replace('\n', '').replace('\t', '').replace(' ', '').replace(':C', ': C')
condition = condition[1:]
condition = removeWeirdChars(condition)
if 'Cash Payment' in condition :
print('\tUnconditional Rebates:\n')
i=0
for i in range(i, int(rowspans[0])) :
num = nums[i].replace('\n', '').replace('\t', '').replace(' ', '')
name = names[i*2+1].replace('\n', '').replace('\t', '').replace(' - ', '').replace('s C', 's C').replace(' ', '').replace('"', '')
amount = amounts[i].replace('\n', '').replace('\t', '').replace(' ', '')
expiration = expirations[i].replace('\n', '').replace('\t', '').replace(' ', '')
if 'SIRIUS' in name : #Fix for the stupid 6-month extra Sirius incentive
amount = '$0'
if ' - ' not in amount and 'Amount Not Available' not in amount : # stupid fix for Oct 2016 rebate and anotehr fix for Dec 2016 rebate
print('\t\tProgram: #' + num)
print('\t\tName: ' + name)
print('\t\tAmount: ' + amount)
print('\t\tExpiration: ' + expiration + '\n')
to_db += (num,) + (name,) + (condition,) + (amount,) + (expiration,) + (condition,) #fix double header
while len(to_db) < 43 :
to_db += (None,)
return to_db
time.sleep(2)
def scrapeLeaseInfo(page_source) :
# Connect to database
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
to_db = ()
# Get rebate info
tree = html.fromstring(page_source)
vin = tree.xpath('//dt[.="VIN:"]/following-sibling::dd/text()')
vin = vin[0].replace('\xa0', ' ').replace('\t', '').replace('\n', '')
vehDesc = tree.xpath('//dt[.="Description:"]/following-sibling::dd/text()')
residualTable = tree.xpath('//table[@class="rateTable"]/tbody/tr/td/text() | //table[@class="rateTable"]/thead/tr/th/text()')
#rclRebateRow = tree.xpath('//tr[td[contains(., "RCL Customer Cash")]]/td/text()')
rclFactorsRow = tree.xpath('//tr[td[contains(., "RCL Factors")]]/td/text()')
rclTermLengths = tree.xpath('//tr[td[contains(., "RCL Factors")]]//th/text()')
rclFactors = tree.xpath('//tr[td[contains(., "RCL Factors")]]//td/text()')
rebateCells = tree.xpath('//tr[td[contains(., "LEASE")]]/following-sibling::*/td/text()')
#print('rebateCells:', rebateCells)
#print('length of rebateCells:', len(rebateCells))
if rebateCells != [] :
print('Lease Rebates:')
rebateDict = {}
for i, cell in enumerate(rebateCells) :
if 'Cash' in cell and 'Fast Cash Certificate' not in cell:
rebateName = cell.replace('\t', '').replace('\n', '').replace(' - ', '')
if '$' in rebateCells[i+2] :
rebateAmount = int(rebateCells[i+2].replace('\t', '').replace('\n', '').replace(' ', '').replace('$', '').replace(',', ''))
rebateExpiration = rebateCells[i+3].replace('\t', '').replace('\n', '').replace(' ', '')
elif '$' in rebateCells[i+3] :
rebateAmount = int(rebateCells[i+3].replace('\t', '').replace('\n', '').replace(' ', '').replace('$', '').replace(',', ''))
rebateExpiration = rebateCells[i+4].replace('\t', '').replace('\n', '').replace(' ', '')
rebateDict[rebateName] = [rebateAmount, rebateExpiration]
print('\tRebate Name:', rebateName)
print('\tRebate Amount:', rebateAmount)
print('\tRebate Expiration:', rebateExpiration)
print('\n')
print('rebateDict:', rebateDict)
totalRebates = 0
for rebateName in rebateDict :
totalRebates += rebateDict[rebateName][0]
vehDesc = vehDesc[0].replace('\xa0', ' ').replace('\t', '').replace('\n', '')
rclResiduals = {}
for i, leaseTerm in enumerate(residualTable[0:4]) :
rclResiduals[leaseTerm + ' Month'] = float(residualTable[i+5])/100
#rclRebateName = rclRebateRow[5].replace('\t', '').replace('\n', '').replace(' - ', '')
#rclRebateAmount = rclRebateRow[8].replace('\t', '').replace('\n', '').replace(' ', '').replace('$', '').replace(',', '')
#rclRebateExpiration = rclRebateRow[9].replace('\t', '').replace('\n', '').replace(' ', '')
rclTermLengths = rclTermLengths[:-1]
for i, termLength in enumerate(rclTermLengths) :
rclTermLengths[i] = int(termLength)
rclFactorsExpiration = rclFactorsRow[8].replace('\t', '').replace('\n', '').replace(' ', '')
factors = {}
for e in rclFactors :
if 'Tier' in e :
tierIndex = rclFactors.index(e)
tier = rclFactors[tierIndex]
tierFactors = rclFactors[tierIndex+1:tierIndex+5]
for i, factor in enumerate(tierFactors) :
tierFactors[i] = float(factor)
factors[tier] = tierFactors
print('VIN:', vin)
print('Vehicle Description:', vehDesc)
#print('RCL Rebate Name:', rclRebateName)
print('Total Rebates:', totalRebates)
#print('RCL Rebate Expiration:', rclRebateExpiration)
print('RCL Lengths:', rclTermLengths)
print('RCL Factors: ', factors) #used to be factors but too hard to deal with everything
print('RCL Factors Expiration:', rclFactorsExpiration)
print('RCL Residual:', rclResiduals)
c.execute('SELECT stock, year, model, vehTrim FROM masterInventory WHERE vin = ?', (vin,))
vehInfo = c.fetchall()
vehInfo = vehInfo[0]
print('vehInfo:', vehInfo)
to_db = (vin,) + vehInfo + (str(rebateDict), totalRebates, str(rclTermLengths), str(factors), rclFactorsExpiration, str(rclResiduals))
#to_db = (vin, str(rebateDict), totalRebates, str(rclTermLengths), str(factors), rclFactorsExpiration, str(rclResiduals))
else :
print('No lease info found.')
to_db = (vin, None, None, None, None, None, None, None, None, None, None)
# Close connection to database
conn.commit()
conn.close()
return to_db
time.sleep(2)
def calculateLeasePayment(vin, termLength, mileage, tier) : # outputs monthly payments. input example: ('1FAHP1231', 36, 15000, 'Tier 0-1')
print('Calculating lease payments for VIN: ' + vin)
leaseParameters = getLeaseParameters(vin)
#print('leaseParameters:', leaseParameters)
if leaseParameters[5] == None : # if there are no lease deals
paymentOptions = (None, None, None, None, None, vin)
else :
msrp = leaseParameters[0]
dealerDiscount = leaseParameters[1]
rebateAmount = leaseParameters[2]
termLengths = leaseParameters[3]
interestRates = leaseParameters[4]
residuals = leaseParameters[5]
termLengthIndex = termLengths.index(termLength)
apr = interestRates[tier][termLengthIndex]
apr += 1 # Juicing the apr by 1%
residual = residuals[str(termLength) + ' Month']
# Adjust residual for mileage
residual += (15000 - mileage)/1500 * .01
residual = round(residual, 2)
taxRate = .07125 # plus any local taxes i guess
aquisitionFee = 645 # need to figure out better way
moneyFactor = apr/2400
salesTax = round(msrp * taxRate, 2) # dunno if this should be here
salesTax = 0
signAndDrive = 0 - aquisitionFee - salesTax
downPayments = [signAndDrive, 0, 1000, 2000, 3000]
print('MSRP:', msrp)
print('Dealer Discount:', dealerDiscount)
print('Rebate Amount:', rebateAmount)
print('Term Length:', str(termLength) + ' Month')
print('APR:', apr)
print('Money Factor:', moneyFactor)
print('Residual:', residual)
print('\n\n')
paymentOptions = ()
for downPayment in downPayments :
sellingPrice = msrp - dealerDiscount - rebateAmount
#taxableAmount = sellingPrice - residualValue - downPayment + rentCharge # not accurate
#salesTax = msrp * taxRate
#salesTax = 0
grossCapCost = msrp - dealerDiscount + aquisitionFee + salesTax
capCostReduction = rebateAmount + downPayment
netCapCost = round(grossCapCost - capCostReduction, 2)
residualValue = round(msrp * residual, 2)
depreciation = round(netCapCost - residualValue, 2)
basePayment = round(depreciation/termLength, 2)
rentPayment = round((netCapCost + residualValue) * moneyFactor, 2)
rentCharge = rentPayment*termLength
totalPayment = round(basePayment + rentPayment, 2)
print('Down Payment:', downPayment)
print('\n')
print('Gross Cap. Cost:', grossCapCost)
print('Cap. Cost Reduction:', capCostReduction)
print('Net Cap. Cost:', netCapCost)
print('Residual Value:', residualValue)
print('Depreciation:', depreciation)
print('Base Payment:', basePayment)
print('Rent Payment:', rentPayment)
print('Total Monthly Payment:', totalPayment)
print('\n\n\n')
paymentOptions += (totalPayment,)
paymentOptions += (vin,)
#print('Payment Options:', paymentOptions)
return paymentOptions
def scrapeFMC(): # Gets rebate and lease info from FMC Dealer
vinList = getVinList()
#vinList = ['3FA6P0VP1HR195216', '3FA6P0H77HR187150']
#path_to_chromedriver = 'chromedriver'
#browser = webdriver.Chrome(executable_path=path_to_chromedriver)
browser = start_chromedriver()
browser = fmcLogin(browser)
errorList = []
for i, vin in enumerate(vinList) :
print('Vehicle ' + str(i+1) + '/' + str(len(vinList)) + ':\n')
browser = navigateToVincent(browser, vin)
try :
to_db = scrapeRebateInfo(browser.page_source)
updateRebateTable(to_db)
to_db = scrapeLeaseInfo(browser.page_source)
updateLeaseTable(to_db)
#to_db = calculateLeasePayment(vin, 36, 10500, 'Tier 0-1')
#updateLeaseTable(to_db)
except Exception as e:
template = "An exception of type {0} occurred. Arguments:\n{1!r}"
message = template.format(type(e).__name__, e.args)
message += '\nError on line {}'.format(sys.exc_info()[-1].tb_lineno)
print(message)
errorList.append(vin)
continue
print('Error List:', errorList)
print('Number of Errors:', len(errorList))
doubleErrorList = []
for i, vin in enumerate(errorList) : # Re-run all VINs that had errors
print('Vehicle ' + str(i+1) + '/' + str(len(errorList)) + ':\n')
browser = navigateToVincent(browser, vin)
try :
to_db = scrapeRebateInfo(browser.page_source)
updateRebateTable(to_db)
to_db = scrapeLeaseInfo(browser.page_source)
updateLeaseTable(to_db)
except Exception as e:
template = "An exception of type {0} occurred. Arguments:\n{1!r}"
message = template.format(type(e).__name__, e.args)
message += '\nError on line {}'.format(sys.exc_info()[-1].tb_lineno)
print(message)
doubleErrorList.append(vin)
continue
print('Double Error List:', errorList)
print('Number of Double Errors:', len(errorList))
print(20*'\n')
def updateVLPlusInventoryTable():
print('Scraping Vehicle Locator..')
# Open connection to database
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
# Delete old data
query = 'DELETE FROM VLPlusInventory'
c.execute(query)
# all the xpath that we're gonna need
vin_list_xpath = '//tr[contains(@class, "vehiclerow")]/@vin'
msrp_list_xpath = '//td[contains(@class, "price")]/a[@class="pdfWindowSticker"]/span/text()'
invoice_list_xpath = '//tr[contains(@class, "vehiclerow")]/td[11]/a/span/text()'
pep_list_xpath = '//tr[contains(@class, "vehiclerow")]/td[7]/span[3]/text()'
order_type_list_xpath = '//a[@onclick="showOrderTypeInfo();"]/span/text()'
engine_list_xpath = '//tr[contains(@class, "vehiclerow")]/td[8]/span[1]/text()'
status_list_xpath = '//tr[contains(@class, "vehiclerow")]/td[1]/@class'
# Log into FMC Dealer
#path_to_chromedriver = 'chromedriver'
#browser = webdriver.Chrome(executable_path=path_to_chromedriver)
browser = start_chromedriver()
browser = fmcLogin(browser)
wait = WebDriverWait(browser, 10)
browser.get('https://www.vlplus.dealerconnection.com/InvMgt/')
time.sleep(randomInterval() * 2)
source = browser.page_source
tree = html.fromstring(source)
vehicle_count = tree.xpath('//th[@class="resultcount"]/text()')
print(vehicle_count)
vehicle_count = vehicle_count[1].split(' ')
vehicle_count_index = vehicle_count.index('vehicles') - 1
vehicle_count = vehicle_count[vehicle_count_index]
vehicle_count = int(vehicle_count)
page_count = math.ceil(vehicle_count/25)
print('Total pages:', page_count)
for j in range(0, page_count-1):
tree = html.fromstring(browser.page_source)
vin_list = tree.xpath(vin_list_xpath)
ugly_msrp_list = tree.xpath(msrp_list_xpath)
ugly_invoice_list = tree.xpath(invoice_list_xpath)
ugly_pep_list = tree.xpath(pep_list_xpath)
ugly_order_type_list = tree.xpath(order_type_list_xpath)
ugly_engine_list = tree.xpath(engine_list_xpath)
ugly_status_list = tree.xpath(status_list_xpath)
# Clean up PEP Codes
msrp_list = []
invoice_list = []
pep_list = []
order_type_list = []
engine_list = []
status_list = []
for k in range(0, len(vin_list)):
msrp_list.append(ugly_msrp_list[k].replace('$', '').replace(',', ''))
if msrp_list[k] != 'n/a':
msrp_list[k] = int(msrp_list[k])
else:
msrp_list[k] = ''
invoice_list.append(ugly_invoice_list[k].replace('$', '').replace(',', ''))
if invoice_list[k] != 'n/a':
invoice_list[k] = int(invoice_list[k])
else:
invoice_list[k] = ''
for pep_code in ugly_pep_list:
pep_list.append(pep_code)
for order_type in ugly_order_type_list:
order_type_list.append(order_type)
for engine in ugly_engine_list:
engine = engine.split('<br>')[0].replace(' ', '').replace('\n', '')
if 'L ' in engine and 'SPD' not in engine and 'SPEED' not in engine:
engine_list.append(engine)
for status in ugly_status_list:
if 'transit' in status:
status_list.append('In Transit')
elif 'plant' in status:
status_list.append('In Plant')
else:
status_list.append('In Stock')
if len(msrp_list) != len(invoice_list):
print('len msrp != invoice')
raise ValueError
if len(pep_list) != len(msrp_list):
print('len pep != msrp')
print(msrp_list)
print(ugly_pep_list)
raise ValueError
print('msrp_list len: ', len(msrp_list))
print('msrp_list: ', msrp_list)
print('invoice_list: ', invoice_list)
print('pep_list: ', pep_list)
print('order_type_list: ', order_type_list)
print('engine_list: ', engine_list)
print('status_list: ', status_list)
to_db = []
for k, vin in enumerate(vin_list):
print('VIN: ', vin)
print('msrp: ', msrp_list[k])
print('invoice: ', invoice_list[k])
print('pep: ', pep_list[k])
print('order_type: ', order_type_list[k])
print('engine: ', engine_list[k], '\n')
if msrp_list[k] < invoice_list[k]:
raise ValueError
to_db.append((vin, msrp_list[k], invoice_list[k], pep_list[k], order_type_list[k], engine_list[k], status_list[k]))
query = 'INSERT OR REPLACE INTO VLPlusInventory (vin, msrp, invoice, pepCode, orderType, engine, status) VALUES (?, ?, ?, ?, ?, ?, ?)'
c.executemany(query, to_db)
conn.commit()
time.sleep(randomInterval())
next_page_xpath = '//a[@page="{}"]'.format(str(j+2))
next_page_link = wait.until(EC.element_to_be_clickable((By.XPATH, next_page_xpath)))
next_page_link.click()
#browser.find_element_by_xpath(next_page_xpath).click()
time.sleep(randomInterval()*2)
conn.close()
def updateMasterInventoryStockStatus():
# Open connection to database
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
# Get all vin in master inv
query = 'SELECT vin FROM masterInventory'
c.execute(query)
master_results = c.fetchall()
master_vin_list = []
for r in master_results:
master_vin_list.append(r[0])
# Get all retail veh in vlplus inv
query = 'SELECT vin, status FROM VLPlusInventory WHERE orderType = ? OR orderType = ?'
to_db = ('1', '2')
c.execute(query, to_db)
vlplus_results = c.fetchall()
for r in vlplus_results:
vin = r[0]
vlpus_status = r[1]
print('\n', vin, ':\n\n')
if vin in master_vin_list:
query = 'SELECT status, dateInStock FROM masterInventory WHERE vin = ?'
to_db = (vin,)
c.execute(query, to_db)
result = c.fetchall()
master_status = result[0][0]
date_in_stock = result[0][1]
print(master_status)
if date_in_stock and master_status == 'In Stock':
print('Stock status already set')
continue
elif date_in_stock and master_status != 'In Stock':
print('Updating stock status')
query = 'UPDATE masterInventory SET status = ? WHERE vin = ?'
to_db = ('In Stock', vin)
c.execute(query, to_db)
else:
print('Adding veh to master')
query = 'INSERT OR REPLACE INTO masterInventory (vin, status, invType) VALUES (?, ?, ?)'
to_db = (vin, vlpus_status, 'New')
c.execute(query, to_db)
conn.commit()
conn.close()
# Data stuff
def get_incoming_homenet_file(): # Logs into Homenet FTP server and downloads inventory file
print('Getting CSV file from Homenet feed...')
#autouplinkFilePath = 'spencertichenor.com/home/sjtichenor/public_ftp/incoming/RosevilleMidwayFord' + YEAR + MO + DAY
ftp = ftplib.FTP('spencertichenor.com')
ftp.login(user='ftpbot@spencertichenor.com', passwd='M4lonePovolny')
homenetFileName = 'homenet_feed.csv'
localFilePath = 'data/local_homenet_file.csv'
localFile = open(localFilePath, 'wb')
ftp.retrbinary('RETR ' + homenetFileName, localFile.write, 1024)
print('CSV file from Homenet feed saved at: data/local_homenet_file.csv')
ftp.quit()
localFile.close()
def update_incoming_homenet_table(): # Gets data from local_homenet_file.csv then updates homenetInventory and masterInventory tables
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
print('Updating homenetInventory table with data sent from Homenet FTP feed...')
with open('data/local_homenet_file.csv', 'r') as homenetFile:
# csv.DictReader uses first line in file for column headings by default
dr = csv.DictReader(homenetFile) # comma is default delimiter
to_db = []
homenetVinList = []
## Clean out weird characters
valid_chars = string.ascii_letters + string.digits + ' ' + ':' + '-' + ',' + '&' + '$' + '/' + '.' + '_' + '!'
for i in dr:
for key in i.keys():
s = i[key]
clean = ''.join(c for c in s if c in valid_chars)
i[key] = clean
#print(key + ': ' + i[key])
#print('\n' + 50*'*' + '\n')
to_db.append((
i['VIN'],
i['Stock'],
i['Type'],
i['Year'],
i['Make'],
i['Model'],
i['Trim'],
i['Body'],
i['MSRP'],
i['SellingPrice'],
i['InternetPrice'],
i['Invoice'],
i['BookValue'],
i['Certified'],
i['ModelNumber'],
i['Doors'],
i['ExteriorColor'],
i['InteriorColor'],
i['EngineCylinders'],
i['EngineDisplacement'],
i['Transmission'],
i['Miles'],
i['DateInStock'],
i['Description'],
i['Options'],
i['Categorized Options'],
i['ImageList'],
i['Style Description'],
i['Drive type'],
i['Wheelbase Code'],
i['Engine Description'],
i['Market Class'],
i['Factory_Codes']
))
homenetVinList.append(i['VIN']) #used later to delete vehicles that aren't in stock anymore, index of 0 because it is a tuple
query = ("""
INSERT OR REPLACE INTO homenetInventory (vin, stock, invType, year, make, model, vehTrim, cabStyle, intMSRP, intPrice, intInternetPrice, intInvoice, intGeneralLedger, cpo, modelNumber, doors, exteriorColor, interiorColor, engineCylinders, engineDisplacement, transmission, miles, dateInStock, description, options, optionsCategorized, imageUrls, style, drive, wheelbase, engine, marketClass, factCodes)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""")
c.executemany(query, to_db)
#c.executemany("INSERT OR REPLACE INTO masterInventory (vin, stock, invType, year, make, model, vehTrim, cabStyle, intMSRP, intPrice, intInternetPrice, intInvoice, intGeneralLedger, cpo, modelNumber, doors, exteriorColor, interiorColor, engineCylinders, engineDisplacement, transmission, miles, dateInStock, description, options, optionsCategorized, imageUrls, style, drive, wheelbase, engine, marketClass, factCodes) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", to_db)
# that was redundent i think ^^
# Delete vehicles that aren't in stock anymore from Homenet table
currentVinList = []
c.execute('SELECT vin FROM homenetInventory')
tupleVinList = c.fetchall()
for tupleVin in tupleVinList: # Convert tuples to strings in order to compare later
vin = tupleVin[0]
currentVinList.append(vin)
for vin in currentVinList:
if vin not in homenetVinList:
c.execute('DELETE FROM homenetInventory WHERE vin = ?', (vin,))
print('Deleted VIN ' + vin + ' from Homenet Inventory Table.')
conn.commit()
print('Finished updating homenetInventory table.\n')
# Update masterInventory table
print('Updating masterInventory table with data from homenetInventory table...')
query = 'INSERT OR REPLACE INTO masterInventory (vin, stock, invType, year, make, model, vehTrim, cabStyle, intMSRP, intPrice, intInternetPrice, intInvoice, intGeneralLedger, cpo, modelNumber, doors, exteriorColor, interiorColor, engineCylinders, engineDisplacement, transmission, miles, dateInStock, description, options, optionsCategorized, imageUrls, style, drive, wheelbase, engine, marketClass, factCodes) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)'
c.executemany(query, to_db)
c.execute('SELECT vin from masterInventory')
masterVinTupleList = c.fetchall()
for vinTuple in masterVinTupleList:
vin = vinTuple[0]
if vin not in homenetVinList:
c.execute('DELETE FROM masterInventory WHERE vin = ?', (vin,))
print('Deleted VIN ' + vin + ' from Master Inventory Table.')
conn.commit()
conn.close()
def updateMasterTable() :
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
c.execute('SELECT * FROM homenetInventory')
vehTupleList = c.fetchall()
to_db = vehTupleList
print(to_db)
print(len(to_db))
for i in to_db:
print(i)
print(len(i))
c.executemany("INSERT OR REPLACE INTO masterInventory (vin, stock, invType, year, make, model, vehTrim, bodyStyle, intMSRP, intPrice, intInternetPrice, intInvoice, intGeneralLedger, cpo, modelNumber, doors, exteriorColor, interiorColor, engineCylinders, engineDisplacement, transmission, miles, dateinStock, description, options, optionsCategorized, imageUrls) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?);", to_db)
conn.commit()
# Delete vehicles that are no longer in stock from masterInventory
homenetVinList = []
c.execute('SELECT vin from homenetInventory')
homenetVinTupleList = c.fetchall()
for homenetVinTuple in homenetVinTupleList :
homenetVin = homenetVinTuple[0]
homenetVinList.append(homenetVin)
c.execute('SELECT vin from masterInventory')
masterVinTupleList = c.fetchall()
for vinTuple in masterVinTupleList :
vin = vinTuple[0]
if vin not in homenetVinList :
c.execute('DELETE FROM masterInventory WHERE vin = ?', (vin,))
print('Deleted VIN ' + vin + ' from Master Inventory Table.')
conn.commit()
conn.close()
def removeOldVins(table): #DOES NOT WORK removes VINs that are no longer in masterInventory from supplied table
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
masterVinList = []
c.execute('SELECT vin FROM masterInventory')
masterVinTupleList = c.fetchall()
for masterVinTuple in masterVinTupleList :
vin = masterVinTuple[0]
masterVinList.append(vin)
c.execute('SELECT vin FROM ?', (table,))
rebateVinTupleList = c.fetchall()
for rebateVinTuple in rebateVinTupleList :
vin = rebateVinTuple[0]
if vin not in masterVinList :
c.execute('DELETE FROM rebateInfo WHERE vin = ?', (vin,))
print('\t' + vin + ' deleted from rebateInfo table.')
conn.commit()
conn.close()
def compute_highlights(): # Gets masterInventory 'options' field for each veh then finds highlights then adds them to highlights column separated by commas
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
c.execute('SELECT vin, options, year, invType, description, cpo, engine, drive, stock, make, model, marketClass FROM masterInventory')
optionsTupleList = c.fetchall()
for optionsTuple in optionsTupleList:
highlightList = []
highlightStr = ''
vin = optionsTuple[0]
options = optionsTuple[1].lower()
year = optionsTuple[2]
invType = optionsTuple[3]
description = optionsTuple[4].lower()
cpo = optionsTuple[5]
engine = optionsTuple[6]
drive = optionsTuple[7]
stock = optionsTuple[8]
make = optionsTuple[9]
model = optionsTuple[10]
marketClass = optionsTuple[11]
# Get coolest options
if cpo == 'True':
highlightList.append('Certified Pre-Owned')
highlightList.append('100,000-Mile Warranty')
#if year == 2017 and invType == 'New' :
#highlightList.append('Apple CarPlay')
#highlightList.append('Android Auto')
# Highlight Idicators - List of dictionaries where the key is the highlight name and the value is a list of indicator phrases
indicatorList = [
{'One-Owner': ['one owner', 'one-owner']},
{'Low Miles': ['low mile']},
{'Remote Start': ['remote start', 'remote engine start', 'remote auto start']},
{'Technology Package': ['technology package', 'technology pkg']},
{'Cold Weather Package': ['cold weather package']},
{'Appearance Package': ['appearance package']},
{'Moonroof': ['vista roof', 'moonroof', 'glass roof', 'panoramic roof']},
{'Rear Camera': ['rear view camera', 'back-up camera', 'rear-view camera']},
{'Rear Camera w/ Hitch Assist': ['rear view camera w/dynamic hitch assist']},
{'Heated Seats': ['heated leather', 'heated front seats', 'heated bucket']},
{'Heated/Cooled Seats': ['heated & cooled', 'heated and cooled', 'heated/cooled']},
{'Heated Steering Wheel': ['heated steering wheel']},
{'Heated Mirrors': ['heated mirrors']},
{'Tow Package': ['tow package', 'Towing', 'Trailer Hitch']},
{'Trailer Brake Controller': ['trailer brake controller']},
{'Premium Audio System': ['premium audio system', 'premium 9 speaker']},
{'Leather Interior': ['leather seats', 'leather-trimmed', 'leather trimmed']},
{'Bluetooth': ['bluetooth']},
{'USB Connectivity': ['usb']},
{'Apple CarPlay': ['apple carplay']},
{'Android Auto': ['android auto']},
{'Snow Plow Package': ['snow plow package']},
{'Lane-Keeping System': ['lane-keeping system']},
{'Rain-Sensing Wipers': ['rain-sensing wipers']},
{'Park Assist System': ['park assist system']},
{'Sirius': ['sirius', 'satellite radio']},
{'Power Liftgate': ['pwr liftgate', 'power liftgate']},
{'Remote Tailgate': ['remote tailgate']},
{'Push Button Start': ['push button start']},
{'Navigation': ['navigation']},
{'Bedliner': ['bedliner']},
{'Extended Range Fuel Tank': ['extended range']},
{'2nd Row Bucket Seats': ['2nd row bucket seats']},
{'3rd Row Seat': ['3rd row seat', '3rd seat']},
{'Touchscreen': ['touchscreen', 'touch-screen', 'myford touch', 'sync 3']},
{'Keyless Entry': ['keyless', 'keypad entry']},
{'Cruise Control': ['cruise control']},
{'Auto Start-Stop Technology': ['auto start-stop technology']},
{'LED Box Lighting': ['led box lighting']},
]
for i in indicatorList:
highlight = list(i.keys())[0]
phraseList = list(i.values())[0]
for phrase in phraseList:
if phrase in options or phrase in description:
highlightList.append(highlight)
break
highlightList.append(engine)
highlightList.append(drive)
# Remove redundant highlights
redundantList = [
['Heated Seats', 'Heated/Cooled Seats'],
['Rear Camera', 'Rear Camera w/ Hitch Assist'],
['USB Connectivity', 'Bluetooth'],
['Bluetooth', 'Apple CarPlay'],
['Tow Package', 'Trailer Brake Controller']
]
for i in redundantList:
if i[0] in highlightList and i[1] in highlightList:
highlightList.remove(i[0])
for highlight in highlightList:
highlightStr += highlight + ','
if len(highlightStr) > 0: # Get rid of unnecessary comma on end of string
highlightStr = highlightStr[:-1]
# Set Body Style (not really a highlight) - Had to switch to ghetto version below because vans were getting marked as cars because iterating throguh dict is not ordered
# indicatorDict = {
# 'Car': ['Car'],
# 'Truck': ['Truck'],
# 'Van': ['Van', 'van'],
# 'SUV': ['Sport Utility Vehicles']
# }
# bodyStyles = indicatorDict.keys()
# for bodyStyle in bodyStyles :
# for indicator in indicatorDict[bodyStyle] :
# if indicator in marketClass :
# style = bodyStyle
if 'Car' in marketClass: # has to come first so cargo van gets listed as Van
style = 'Car'
if 'Truck' in marketClass:
style = 'Truck'
if 'Van' in marketClass or 'van' in marketClass :
style = 'Van'
if 'Sport Utility Vehicles' in marketClass :
style = 'SUV'
# Clean up Model
model = model.replace(' Commercial Cutaway', '').replace(' Sport Fleet', '').replace(' Cutaway', '')
# Clean up Engine
engine = engine.replace(' L', 'L')
print('Vehicle: ' + stock + ' ' + make + ' ' + model)
print('Highlights:', highlightList)
print('BodyStyle:', style)
print('\n')
# Set Status to In Stock
status = 'In Stock'
# Update database
c.execute('UPDATE masterInventory SET highlights = ?, bodyStyle = ?, model = ?, engine = ?, status = ? WHERE vin = ?', (highlightStr, style, model, engine, status, vin,))
conn.commit()
conn.close()
def calculate_pricing():
print('Calculating max discount for each vehicle...\n')
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
# Set dealer discount and total discount
query = ('SELECT vin, intMSRP, intInternetPrice, intTotalRebates, totalConditionalRebates '
'FROM masterInventory '
'WHERE invType = "New" AND intMSRP != 0')
c.execute(query)
results = c.fetchall()
for r in results:
print('r:', r)
vin = r[0]
msrp = r[1]
price_before_rebates = r[2]
unconditional_rebates = r[3]
conditional_rebates = r[4]
dealer_discount = msrp - price_before_rebates
if unconditional_rebates:
best_discount = dealer_discount + unconditional_rebates + conditional_rebates
else:
best_discount = dealer_discount
# Print results
print('\t\tVIN:', vin)
print('\t\tMSRP:', msrp)
print('\t\tPrice before rebates:', price_before_rebates)
print('\t\tDealer Discount:', dealer_discount)
print('\t\tUnconditional Rebates:', unconditional_rebates)
print('\t\tConditional Rebates:', conditional_rebates)
print('\t\tBest Discount:', best_discount, '\n\n')
# Update database
query = 'UPDATE masterInventory SET intTotalDiscount = ? WHERE vin = ?'
to_db = (best_discount, vin)
c.execute(query, to_db)
conn.commit()
conn.close()
print('Finished calculating max discount for each vehicle.\n')
def create_outgoing_homenet_table():
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
query = ("""
CREATE TABLE IF NOT EXISTS outgoingHomenet
(VIN TEXT UNIQUE, comment1 TEXT, misc_price1 INTEGER, comment2 TEXT, misc_price2 INTEGER, comment3 TEXT, misc_price3 INTEGER, comment5 TEXT)
""")
c.execute(query)
conn.commit()
conn.close()
def update_outgoing_homenet_table():
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
c.execute('DELETE FROM outgoingHomenet')
to_db = []
c.execute('SELECT vin, highlights, intTotalRebates, totalConditionalRebates FROM masterInventory')
results = c.fetchall()
for r in results:
vin = r[0]
highlights = r[1]
unconditional_rebates = r[2]
conditional_rebates = r[3]
if not unconditional_rebates:
unconditional_rebates = 0
if not conditional_rebates:
conditional_rebates = 0
to_db.append((vin, highlights, 0, None, unconditional_rebates, None, conditional_rebates, ''))
print('\n\nVIN:', vin)
print('Highlights:', highlights)
print('Unconditional Rebates:', unconditional_rebates)
print('Conditional Rebates:', conditional_rebates)
query = ("""
INSERT OR REPLACE INTO outgoingHomenet (vin, comment1, misc_price1, comment2, misc_price2, comment3, misc_price3, comment5)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""")
c.executemany(query, to_db)
conn.commit()
conn.close()
def update_outgoing_homenet_file():
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
c.execute('SELECT vin, comment1, misc_price1, comment2, misc_price2, comment3, misc_price3, comment5 FROM outgoingHomenet')
with open('data/homenet-incentive-feed.csv', 'w') as csv_file:
csv_writer = csv.writer(csv_file, dialect='excel')
csv_writer.writerow([i[0] for i in c.description]) # write headers
csv_writer.writerows(c)
conn.commit()
conn.close()
def upload_outgoing_homenet_file():
print('\nUploading inventory to FTP server for Homenet...')
file_path = 'data/homenet-incentive-feed.csv'
file_name = file_path.split('/')
file_name = file_name[-1]
print('Uploading ' + file_name + ' to FTP server...\n')
file = open(file_path, 'rb')
ftp = ftplib.FTP('iol.homenetinc.com')
ftp.login('hndatafeed', 'gx8m6')
ftp.storbinary('STOR ' + file_name, file, 1024)
file.close()
ftp.quit()
print('Successfully uploaded ' + file_name + ' to homenet folder on FTP server.\n')
def send_feeds_from_homenet():
print('Navigating to Homenet.com and send out feeds to cars.com, cargurus, etc..')
# Fire up ChromeDriver
browser = start_chromedriver()
wait = WebDriverWait(browser, 10)
# Log into Homenet
#url = 'https://www.homenetiol.com/marketplace/overview'
url = 'https://www.homenetiol.com/login?RedirectUrl=%2fmarketplace%2foverview'
browser.get(url)
username = browser.find_element_by_xpath('//input[@class="username text-value"]')
password = browser.find_element_by_xpath('//input[@class="password text-value"]')
username.send_keys('spencer@rosevillemidwayford.com')
password.send_keys('G3nericwords')
wait.until(EC.element_to_be_clickable((By.XPATH, '//a[@class="login-action button"]'))).click()
wait.until(EC.element_to_be_clickable((By.XPATH, '//a[@class="run-all-button button"]'))).click()
time.sleep(10)
print('Finished sending out feeds.')
def vacuum_db():
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
c.execute("VACUUM")
conn.close()
def figureManagerSpecials():
# Open connection to database
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
url = 'http://www.rosevillemidwayford.com/new-car-sales-roseville-mn'
page = requests.get(url)
tree = html.fromstring(page.content)
stockResults = tree.xpath('//span[contains(@class, "spec-value-stocknumber")]/text()')
specialStockList = []
for specialStock in stockResults :
specialStock = specialStock.replace('#', '')
specialStockList.append(specialStock)
print(specialStockList)
c.execute('SELECT stock FROM masterInventory')
results = c.fetchall()
for r in results:
stock = r[0]
if stock in specialStockList :
print('looks like stock #' + stock + ' is a special!')
query = 'UPDATE masterInventory SET managerSpecial = ? WHERE stock = ?'
to_db = ('True', stock)
c.execute(query, to_db)
else :
print('looks like stock #' + stock + ' is NOT a special!')
query = 'UPDATE masterInventory SET managerSpecial = ? WHERE stock = ?'
to_db = ('False', stock)
c.execute(query, to_db)
conn.commit()
conn.close()
def figureLeaseSpecials():
# Open connection to database
conn = sqlite3.connect('data/inventory.db')
c = conn.cursor()
lease_specials = []
c.execute('SELECT DISTINCT year FROM masterInventory')
year_results = c.fetchall()
for y in year_results:
year = y[0]
# print(year)
query = 'SELECT DISTINCT model FROM masterInventory WHERE year = ? AND leasePayment != ?'
to_db = (year, '')
c.execute(query, to_db)
model_results = c.fetchall()
for m in model_results:
model = m[0]
query = 'SELECT min(leasePayment) FROM masterInventory WHERE year = ? AND model = ?'
to_db = (year, model)
c.execute(query, to_db)
payment_results = c.fetchall()
min_payment = payment_results[0][0]
query = 'SELECT vin, stock, vehTrim, intMSRP, intPrice, leaseRebateExpiration FROM masterInventory WHERE year = ? AND model = ? AND leasePayment = ?'
to_db = (year, model, minPayment)
c.execute(query, to_db)
veh_results = c.fetchall()
v = veh_results[0] # Just get first vehicle even if there are many
print(v)
vin = v[0]
stock = v[1]
vehTrim = v[2]
msrp = v[3]
price = v[4]
term = 36
residual = v[5]
downPayment = v[6]
totalLeaseRebates = v[7]
dueAtSigning = v[8]
expiration = v[9]
# Get data from masterInventory table for rest of required info
c.execute('SELECT bodyStyle, imageUrls, imageUrlsHD, vdp_url, drive FROM masterInventory WHERE vin = ?', (vin,)) # add option codes to this later
master_results = c.fetchall()
if not master_results:
continue
bodyStyle = master_results[0][0] # just getting that matched the else query, could maybe hone this to get one with pic later??
imageUrls = master_results[0][1]
imageUrlsHD = master_results[0][2]
vdp = master_results[0][3]
drive = master_results[0][4]
# option_codes = masterResults[0][4]
# Set image to HD version if available
if imageUrlsHD:
imageUrl = imageUrlsHD
elif imageUrls:
imageUrl = imageUrls.split(',')[0]
else:
continue
minPayment = locale.currency(minPayment, grouping=True).replace('.00', '')
#downPayment = locale.currency(downPayment, grouping=True).replace('.00', '')
#dueAtSigning = locale.currency(dueAtSigning, grouping=True).replace('.00', '')
msrp = locale.currency(msrp, grouping=True).replace('.00', '')
price = locale.currency(price, grouping=True).replace('.00', '')
# offer = '<p>' + minPayment + '/month with ' + downPayment + ' down payment.<br><br>Just ' + dueAtSigning + ' due at signing.<br><br>Based on MSRP of ' + msrp + '.</p>'
# title = minPayment + '/month with {} down.'.format(downPayment)
# description = 'Lease term of {} months. Based on MSRP of {} and selling price of {}. Requires {} due at signing.'.format(term, msrp, price, dueAtSigning)
# disclaimer = 'Must take new retail delivery from dealer stock by {}. Requires {} due at signing. Based on MSRP of {} and selling price of {}. See Subject to credit approval. Assumes 10,500 miles/year and Tier 0-1 credit. Tax, title, and license not included. Some restrictions apply. See sales representative for details.'.format(expiration, minPayment, msrp, price)
lease_specials.append({
'vin': vin,
'stock': stock,
'year': year,
'model': model,
'vehTrim': vehTrim,
# 'title': title,
# 'description': description,
'expiration': expiration,
'monthlyPayment': minPayment,
'dueAtSigning': dueAtSigning,
'vdp': vdp,
'imageUrl': imageUrl,
'bodyStyle': bodyStyle,
'msrp': msrp,
'price': price,
# 'disclaimer': disclaimer,
'drive': drive,
# 'option_codes': option_codes
})
print('\nFresh Specials:')
for s in lease_specials:
print('\n')
# print('\n\n', s, '\n')
for k in s.keys():
print(k + ': ' + str(s[k]))
print('\n\n')
# Close connection to database
conn.close()
return lease_specials
def wait_for_next_run(minutes_to_wait):
print('Finished running program. Waiting 30 minutes to rerun.')
minutes_to_wait = int(minutes_to_wait)
for i in range(minutes_to_wait, 1, -1):
time.sleep(60)
print('Waiting {} minutes until next run.'.format(i))
def main():
while True:
get_incoming_homenet_file()
update_incoming_homenet_table()
scrape.scrape_cdk()
calculate_pricing()
compute_highlights()
create_outgoing_homenet_table()
update_outgoing_homenet_table()
update_outgoing_homenet_file()
upload_outgoing_homenet_file()
send_feeds_from_homenet()
sales_specials.main()
midwords.main()
hd_images.main()
facebook.main()
#adwords_feeds.main()
sheets.main()
# maybe add something to check if any dealer discounts are negative then re run (and if model isnt raptor)
vacuum_db()
wait_for_next_run(30)
if __name__ == '__main__':
main()
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'()\n', (6027, 6029), False, 'import sys\n'), ((8336, 8350), 'sys.exc_info', 'sys.exc_info', ([], {}), '()\n', (8348, 8350), False, 'import sys\n'), ((22352, 22366), 'sys.exc_info', 'sys.exc_info', ([], {}), '()\n', (22364, 22366), False, 'import sys\n'), ((23196, 23210), 'sys.exc_info', 'sys.exc_info', ([], {}), '()\n', (23208, 23210), False, 'import sys\n')] |
edwinfeener/monolithe | monolithe/generators/sdkgenerator.py | 0f024b2ec7d4c5a2229612280e5e559bf2667ba5 | # -*- coding: utf-8 -*-
#
# Copyright (c) 2015, Alcatel-Lucent Inc
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of the copyright holder nor the names of its contributors
# may be used to endorse or promote products derived from this software without
# specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
# DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from __future__ import unicode_literals
import os
import shutil
from monolithe.lib import Printer
from monolithe.generators.lib import Generator
from monolithe.generators.managers import MainManager, CLIManager, VanillaManager
from .sdkapiversiongenerator import SDKAPIVersionGenerator
class SDKGenerator(Generator):
def cleanup(self):
output = self.config.get_option("output", "transformer")
language = self.config.language
overrides_path = "%s/%s/__overrides" % (output, language)
if os.path.exists(overrides_path):
shutil.rmtree(overrides_path)
attrs_defaults_path = "%s/%s/__attributes_defaults" % (output, language)
if os.path.exists(attrs_defaults_path):
shutil.rmtree(attrs_defaults_path)
code_header_path = "%s/%s/__code_header" % (output, language)
if os.path.exists(code_header_path):
os.remove(code_header_path)
def generate(self, specification_info):
user_vanilla = self.config.get_option("user_vanilla", "transformer")
output = self.config.get_option("output", "transformer")
name = self.config.get_option("name", "transformer")
lang = self.config.language
if not os.path.exists(os.path.join(output, lang)):
os.makedirs(os.path.join(output, lang))
vanilla_manager = VanillaManager(monolithe_config=self.config)
vanilla_manager.execute(output_path="%s/%s" % (output, lang))
self.install_user_vanilla(user_vanilla_path=user_vanilla, output_path="%s/%s" % (output, lang))
version_generator = SDKAPIVersionGenerator(self.config)
apiversions = []
for info in specification_info:
Printer.log("transforming specifications into %s for version %s..." % (lang, info["api"]["version"]))
apiversions.append(info["api"]["version"])
version_generator.generate(specification_info=specification_info)
Printer.log("assembling...")
manager = MainManager(monolithe_config=self.config)
manager.execute(apiversions=apiversions)
cli_manager = CLIManager(monolithe_config=self.config)
cli_manager.execute()
self.cleanup()
Printer.success("%s generation complete and available in \"%s/%s\"" % (name, output, self.config.language))
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kyuhoJeong11/GrewRL | rllab-taewoo/rllab/plotter/plotter.py | a514698df8d38df34de0bd1667d99927f0aa3885 | import atexit
import sys
if sys.version_info[0] == 2:
from Queue import Empty
else:
from queue import Empty
from multiprocessing import Process, Queue
from rllab.sampler.utils import rollout
import numpy as np
__all__ = [
'init_worker',
'init_plot',
'update_plot'
]
process = None
queue = None
def _worker_start():
env = None
policy = None
max_length = None
try:
while True:
msgs = {}
# Only fetch the last message of each type
while True:
try:
msg = queue.get_nowait()
msgs[msg[0]] = msg[1:]
except Empty:
break
if 'stop' in msgs:
break
elif 'update' in msgs:
env, policy = msgs['update']
# env.start_viewer()
elif 'demo' in msgs:
param_values, max_length = msgs['demo']
policy.set_param_values(param_values)
rollout(env, policy, max_path_length=max_length, animated=True, speedup=5)
else:
if max_length:
rollout(env, policy, max_path_length=max_length, animated=True, speedup=5)
except KeyboardInterrupt:
pass
def _shutdown_worker():
if process:
queue.put(['stop'])
queue.close()
process.join()
def init_worker():
print("####################init_worker")
global process, queue
queue = Queue()
process = Process(target=_worker_start)
process.start()
atexit.register(_shutdown_worker)
def init_plot(env, policy):
queue.put(['update', env, policy])
def update_plot(policy, max_length=np.inf):
queue.put(['demo', policy.get_param_values(), max_length])
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fotavio16/PycharmProjects | OpenCV/bookIntroCV_008_binarizacao.py | f5be49db941de69159ec543e8a6dde61f9f94d86 | '''
Livro-Introdução-a-Visão-Computacional-com-Python-e-OpenCV-3
Repositório de imagens
https://github.com/opencv/opencv/tree/master/samples/data
'''
import cv2
import numpy as np
from matplotlib import pyplot as plt
#import mahotas
VERMELHO = (0, 0, 255)
VERDE = (0, 255, 0)
AZUL = (255, 0, 0)
AMARELO = (0, 255, 255)
BRANCO = (255,255,255)
CIANO = (255, 255, 0)
PRETO = (0, 0, 0)
img = cv2.imread('ponte2.jpg') # Flag 1 = Color, 0 = Gray, -1 = Unchanged
img = img[::2,::2] # Diminui a imagem
#Binarização com limiar
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
suave = cv2.GaussianBlur(img, (7, 7), 0) # aplica blur
(T, bin) = cv2.threshold(suave, 160, 255, cv2.THRESH_BINARY)
(T, binI) = cv2.threshold(suave, 160, 255, cv2.THRESH_BINARY_INV)
'''
resultado = np.vstack([
np.hstack([suave, bin]),
np.hstack([binI, cv2.bitwise_and(img, img, mask = binI)])
])
'''
resultado = np.vstack([
np.hstack([img, suave]),
np.hstack([bin, binI])
])
cv2.imshow("Binarização da imagem", resultado)
cv2.waitKey(0)
#Threshold adaptativo
bin1 = cv2.adaptiveThreshold(suave, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV, 21, 5)
bin2 = cv2.adaptiveThreshold(suave, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 21, 5)
resultado = np.vstack([
np.hstack([img, suave]),
np.hstack([bin1, bin2])
])
cv2.imshow("Binarização adaptativa da imagem", resultado)
cv2.waitKey(0)
#Threshold com Otsu e Riddler-Calvard
'''
T = mahotas.thresholding.otsu(suave)
temp = img.copy()
temp[temp > T] = 255
temp[temp < 255] = 0
temp = cv2.bitwise_not(temp)
T = mahotas.thresholding.rc(suave)
temp2 = img.copy()
temp2[temp2 > T] = 255
temp2[temp2 < 255] = 0
temp2 = cv2.bitwise_not(temp2)
resultado = np.vstack([
np.hstack([img, suave]),
np.hstack([temp, temp2])
])
cv2.imshow("Binarização com método Otsu e Riddler-Calvard", resultado)
cv2.waitKey(0)
'''
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mechanicbuddy/djangito | djangito/backends.py | 07c08a83c57577cbf945bba461219bc0ef2a7695 | import base64
import json
import jwt
import requests
from django.conf import settings
from django.contrib.auth import get_user_model
from django.contrib.auth.backends import ModelBackend
USER_MODEL = get_user_model()
class ALBAuth(ModelBackend):
def authenticate(self, request, **kwargs):
if request:
self.encoded_jwt = request.META.get('HTTP_X_AMZN_OIDC_DATA')
if self.encoded_jwt:
self.payload = self.decode_alb_jwt()
return self.get_or_create_for_alb()
def decode_alb_jwt(self):
# Step 1: Get the key id from JWT headers (the kid field)
jwt_headers = self.encoded_jwt.split('.')[0]
decoded_jwt_headers = base64.b64decode(jwt_headers)
decoded_jwt_headers = decoded_jwt_headers.decode("utf-8")
decoded_json = json.loads(decoded_jwt_headers)
kid = decoded_json['kid']
# Step 2: Get the public key from regional endpoint
url = f'https://public-keys.auth.elb.us-east-1.amazonaws.com/{kid}'
req = requests.get(url)
pub_key = req.text
# Step 3: Get the payload
return jwt.decode(
self.encoded_jwt,
pub_key,
algorithms=['ES256']
)
def get_or_create_for_alb(self):
user_info = {'username': self.payload['sub'][:150]}
if 'given_name' in self.payload:
user_info['first_name'] = self.payload['given_name'][:30]
elif 'name' in self.payload:
user_info['first_name'] = self.payload['name'][:30]
if 'family_name' in self.payload:
user_info['last_name'] = self.payload['family_name'][:30]
self.user, created = USER_MODEL.objects.get_or_create(
email=self.payload['email'],
defaults=user_info
)
if created:
self.setup_user_profile()
return self.user
def setup_user_profile(self):
pass
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gme5078/data-profiler | data_profiler/labelers/regex_model.py | 602cc5e4f4463f9b807000abf3893815918d0723 | import json
import os
import sys
import re
import copy
import numpy as np
from data_profiler.labelers.base_model import BaseModel
from data_profiler.labelers.base_model import AutoSubRegistrationMeta
_file_dir = os.path.dirname(os.path.abspath(__file__))
sys.path.append(_file_dir)
class RegexModel(BaseModel, metaclass=AutoSubRegistrationMeta):
def __init__(self, label_mapping=None, parameters=None):
"""
Regex Model Initializer.
Example regex_patterns:
regex_patterns = {
"LABEL_1": [
"LABEL_1_pattern_1",
"LABEL_1_pattern_2",
...
],
"LABEL_2": [
"LABEL_2_pattern_1",
"LABEL_2_pattern_2",
...
],
...
}
Example encapsulators:
encapsulators = {
'start': r'(?<![\w.\$\%\-])',
'end': r'(?:(?=(\b|[ ]))|(?=[^\w\%\$]([^\w]|$))|$)',
}
:param label_mapping: maps labels to their encoded integers
:type label_mapping: dict
:param parameters: Contains all the appropriate parameters for the model.
Possible parameters are:
max_length, max_num_chars, dim_embed
:type parameters: dict
:return: None
"""
# parameter initialization
if not parameters:
parameters = {}
parameters.setdefault('regex_patterns', {})
parameters.setdefault('encapsulators', {'start': '', 'end': ''})
parameters.setdefault('ignore_case', True)
parameters.setdefault('default_label', 'BACKGROUND')
self._epoch_id = 0
# initialize class
self.set_label_mapping(label_mapping)
self._validate_parameters(parameters)
self._parameters = parameters
def _validate_parameters(self, parameters):
"""
Validate the parameters sent in. Raise error if invalid parameters are
present.
:param parameters: parameter dict containing the following parameters:
regex_patterns: patterns associated with each label_mapping
Example regex_patterns:
regex_patterns = {
"LABEL_1": [
"LABEL_1_pattern_1",
"LABEL_1_pattern_2",
...
],
"LABEL_2": [
"LABEL_2_pattern_1",
"LABEL_2_pattern_2",
...
],
...
}
encapsulators: regex to add to start and end of each regex
(used to capture entities inside of text).
Example encapsulators:
encapsulators = {
'start': r'(?<![\w.\$\%\-])',
'end': r'(?:(?=(\b|[ ]))|(?=[^\w\%\$]([^\w]|$))|$)',
}
ignore_case: whether or not to set the regex ignore case flag
default_label: default label to assign when no regex found
:type parameters: dict
:return: None
"""
_retype = type(re.compile('pattern for py 3.6 & 3.7'))
errors = []
list_of_necessary_params = ['encapsulators', 'regex_patterns',
'ignore_case', 'default_label']
# Make sure the necessary parameters are present and valid.
for param in parameters:
value = parameters[param]
if param == 'encapsulators' and (
not isinstance(value, dict)
or 'start' not in value
or 'end' not in value):
errors.append(
"`{}` must be a dict with keys 'start' and 'end'".format(
param
))
elif param == 'regex_patterns':
if not isinstance(value, dict):
errors.append('`{}` must be a dict of regex pattern lists.'.
format(param))
continue
for key in value:
if key not in self.label_mapping:
errors.append(
"`{}` was a regex pattern not found in the "
"label_mapping".format(key))
elif not isinstance(value[key], list):
errors.append(
"`{}` must be a list of regex patterns, i.e."
"[pattern_1, pattern_2, ...]".format(key))
else:
for i in range(len(value[key])):
if not isinstance(value[key][i], (_retype, str)):
errors.append(
"`{}`, pattern `{}' was not a valid regex "
"pattern (re.Pattern, str)".format(key, i))
elif isinstance(value[key][i], str):
try:
re.compile(value[key][i])
except re.error as e:
errors.append(
"`{}`, pattern {} was not a valid regex"
" pattern: {}".format(key, i, str(e)))
elif param == 'ignore_case' \
and not isinstance(parameters[param], bool):
errors.append("`{}` must be a bool.".format(param))
elif param == 'default_label' \
and not isinstance(parameters[param], str):
errors.append("`{}` must be a string.".format(param))
elif param not in list_of_necessary_params:
errors.append("`{}` is not an accepted parameter.".format(
param))
if errors:
raise ValueError('\n'.join(errors))
def _construct_model(self):
pass
def _reconstruct_model(self):
pass
def _need_to_reconstruct_model(self):
pass
def reset_weights(self):
pass
def predict(self, data, batch_size=None, show_confidences=False,
verbose=True):
"""
Applies the regex patterns (within regex_model) to the input_string,
create predictions for all matching patterns. Each pattern has an
associated entity and the predictions of each character within the
string are given a True or False identification for each entity. All
characters not identified by ANY of the regex patterns in the
pattern_dict are considered background characters, and are replaced with
the default_label value.
:param data: list of strings to predict upon
:type data: iterator
:param batch_size: does not impact this model and should be fixed to not
be required.
:type batch_size: N/A
:param show_confidences: whether user wants prediction confidences
:type show_confidences:
:param verbose: Flag to determine whether to print status or not
:type verbose: bool
:return: char level predictions and confidences
:rtype: dict
"""
start_pattern = ''
end_pattern = ''
regex_patterns = self._parameters['regex_patterns']
default_ind = self.label_mapping[self._parameters['default_label']]
encapsulators = self._parameters['encapsulators']
re_flags = re.IGNORECASE if self._parameters['ignore_case'] else 0
if encapsulators:
start_pattern = encapsulators['start']
end_pattern = encapsulators['end']
pre_compiled_patterns = copy.deepcopy(regex_patterns)
for entity_label, entity_patterns in pre_compiled_patterns.items():
for i in range(len(entity_patterns)):
pattern = (start_pattern
+ pre_compiled_patterns[entity_label][i]
+ end_pattern)
pre_compiled_patterns[entity_label][i] = re.compile(
pattern, flags=re_flags)
# Construct array initial regex predictions where background is
# predicted.
predictions = [np.empty((0,))] * 100
i = 0
for i, input_string in enumerate(data):
# Double array size
if len(predictions) <= i:
predictions.extend([np.empty((0,))] * len(predictions))
pred = np.zeros((len(input_string), self.num_labels), dtype=int)
pred[:, default_ind] = 1
for entity_label, entity_patterns in pre_compiled_patterns.items():
entity_id = self.label_mapping[entity_label]
for re_pattern in entity_patterns:
for each_find in re_pattern.finditer(input_string):
indices = each_find.span(0)
pred[indices[0]:indices[1], default_ind] = 0
pred[indices[0]:indices[1], entity_id] = 1
if verbose:
sys.stdout.flush()
sys.stdout.write(
"\rData Samples Processed: {:d} ".format(i))
predictions[i] = pred
if verbose:
print()
# Trim array size to number of samples
if len(predictions) > i+1:
del predictions[i+1:]
if show_confidences:
conf = copy.deepcopy(predictions)
for i in range(len(conf)):
conf[i] = conf[i] / \
np.linalg.norm(conf[i], axis=1, ord=1, keepdims=True)
return {"pred": predictions, 'conf': conf}
return {"pred": predictions}
@classmethod
def load_from_disk(cls, dirpath):
"""
Loads whole model from disk with weights
:param dirpath: directory path where you want to load the model from
:type dirpath: str
:return: None
"""
# load parameters
model_param_dirpath = os.path.join(dirpath, "model_parameters.json")
with open(model_param_dirpath, 'r') as fp:
parameters = json.load(fp)
# load label_mapping
labels_dirpath = os.path.join(dirpath, "label_mapping.json")
with open(labels_dirpath, 'r') as fp:
label_mapping = json.load(fp)
loaded_model = cls(label_mapping, parameters)
return loaded_model
def save_to_disk(self, dirpath):
"""
Saves whole model to disk with weights.
:param dirpath: directory path where you want to save the model to
:type dirpath: str
:return: None
"""
if not os.path.isdir(dirpath):
os.makedirs(dirpath)
model_param_dirpath = os.path.join(dirpath, "model_parameters.json")
with open(model_param_dirpath, 'w') as fp:
json.dump(self._parameters, fp)
labels_dirpath = os.path.join(dirpath, "label_mapping.json")
with open(labels_dirpath, 'w') as fp:
json.dump(self.label_mapping, fp)
| [((258, 284), 'sys.path.append', 'sys.path.append', (['_file_dir'], {}), '(_file_dir)\n', (273, 284), False, 'import sys\n'), ((231, 256), 'os.path.abspath', 'os.path.abspath', (['__file__'], {}), '(__file__)\n', (246, 256), False, 'import os\n'), ((7934, 7963), 'copy.deepcopy', 'copy.deepcopy', (['regex_patterns'], {}), '(regex_patterns)\n', (7947, 7963), False, 'import copy\n'), ((10257, 10303), 'os.path.join', 'os.path.join', (['dirpath', '"""model_parameters.json"""'], {}), "(dirpath, 'model_parameters.json')\n", (10269, 10303), False, 'import os\n'), ((10449, 10492), 'os.path.join', 'os.path.join', (['dirpath', '"""label_mapping.json"""'], {}), "(dirpath, 'label_mapping.json')\n", (10461, 10492), False, 'import os\n'), ((11002, 11048), 'os.path.join', 'os.path.join', (['dirpath', '"""model_parameters.json"""'], {}), "(dirpath, 'model_parameters.json')\n", (11014, 11048), False, 'import os\n'), ((11170, 11213), 'os.path.join', 'os.path.join', (['dirpath', '"""label_mapping.json"""'], {}), "(dirpath, 'label_mapping.json')\n", (11182, 11213), False, 'import os\n'), ((3327, 3365), 're.compile', 're.compile', (['"""pattern for py 3.6 & 3.7"""'], {}), "('pattern for py 3.6 & 3.7')\n", (3337, 3365), False, 'import re\n'), ((9669, 9695), 'copy.deepcopy', 'copy.deepcopy', (['predictions'], {}), '(predictions)\n', (9682, 9695), False, 'import copy\n'), ((10380, 10393), 'json.load', 'json.load', (['fp'], {}), '(fp)\n', (10389, 10393), False, 'import json\n'), ((10567, 10580), 'json.load', 'json.load', (['fp'], {}), '(fp)\n', (10576, 10580), False, 'import json\n'), ((10914, 10936), 'os.path.isdir', 'os.path.isdir', (['dirpath'], {}), '(dirpath)\n', (10927, 10936), False, 'import os\n'), ((10950, 10970), 'os.makedirs', 'os.makedirs', (['dirpath'], {}), '(dirpath)\n', (10961, 10970), False, 'import os\n'), ((11112, 11143), 'json.dump', 'json.dump', (['self._parameters', 'fp'], {}), '(self._parameters, fp)\n', (11121, 11143), False, 'import json\n'), ((11272, 11305), 'json.dump', 'json.dump', (['self.label_mapping', 'fp'], {}), '(self.label_mapping, fp)\n', (11281, 11305), False, 'import json\n'), ((8298, 8333), 're.compile', 're.compile', (['pattern'], {'flags': 're_flags'}), '(pattern, flags=re_flags)\n', (8308, 8333), False, 'import re\n'), ((8472, 8486), 'numpy.empty', 'np.empty', (['(0,)'], {}), '((0,))\n', (8480, 8486), True, 'import numpy as np\n'), ((9308, 9326), 'sys.stdout.flush', 'sys.stdout.flush', ([], {}), '()\n', (9324, 9326), False, 'import sys\n'), ((9799, 9852), 'numpy.linalg.norm', 'np.linalg.norm', (['conf[i]'], {'axis': '(1)', 'ord': '(1)', 'keepdims': '(True)'}), '(conf[i], axis=1, ord=1, keepdims=True)\n', (9813, 9852), True, 'import numpy as np\n'), ((8663, 8677), 'numpy.empty', 'np.empty', (['(0,)'], {}), '((0,))\n', (8671, 8677), True, 'import numpy as np\n'), ((5276, 5301), 're.compile', 're.compile', (['value[key][i]'], {}), '(value[key][i])\n', (5286, 5301), False, 'import re\n')] |
JMosqueraM/algoritmos_y_programacion | taller_estructuras_de_control_selectivas/ejercicio_13.py | 30dc179b976f1db24401b110496250fbcb98938e | # Desarrolle un un programa que reciba la fecha de nacimiento
# de una persona, y como salida, indique el nombre del signo del
# zodiaco correspondiente, ademas de su edad
def zodiaco(DD, MM):
if (((DD >= 22) and (MM == 11)) or ((DD <=21) and (MM == 12))):
return("Sagitario")
if (((DD >= 22) and (MM == 12)) or ((DD <=20) and (MM == 1))):
return("Capricornio")
if (((DD >= 21) and (MM == 1)) or ((DD <=19) and (MM == 2))):
return("Acuario")
if (((DD >= 20) and (MM == 2)) or ((DD <=19) and (MM == 3))):
return("Piscis")
if (((DD >= 21) and (MM == 3)) or ((DD <=20) and (MM == 4))):
return("Aries")
if (((DD >= 21) and (MM == 4)) or ((DD <=21) and (MM == 5))):
return("Tauro")
if (((DD >= 22) and (MM == 5)) or ((DD <=21) and (MM == 6))):
return("Geminis")
if (((DD >= 22) and (MM == 6)) or ((DD <=22) and (MM == 7))):
return("Cancer")
if (((DD >= 23) and (MM == 7)) or ((DD <=23) and (MM == 8))):
return("Leo")
if (((DD >= 24) and (MM == 8)) or ((DD <=22) and (MM == 9))):
return("Virgo")
if (((DD >= 23) and (MM == 9)) or ((DD <=22) and (MM == 10))):
return("Libra")
if (((DD >= 23) and (MM == 10)) or ((DD <=21) and (MM == 11))):
return("Escorpion")
fecha_str = input("Ingrese la fecha de nacimiento (DD/MM/AAAA): ")
fecha = fecha_str.split("/")
fecha_int = []
for elemento in fecha:
fecha_int.append(int(elemento))
dia = fecha_int[0]
mes = fecha_int[1]
ano = fecha_int[2]
signo = zodiaco(dia, mes)
print(f"Siendo que su fecha de nacimiento es {fecha_str}, su signo zodiacal corresponde a {signo} y tiene {abs(ano - 2021)} años") | [] |
vhazali/cs5331 | assignment3/crawler/spiders/benchmark_spider.py | 3b3618aaa17199ebcd3c01bc6c25ddbdbe4f3d0f | import re, scrapy
from crawler.items import *
class BenchmarkSpider(scrapy.Spider):
drop_params = True
# Spider name, for use with the scrapy crawl command
name = "benchmarks"
# Constants to get url parts
FULL, PROTOCOL, USER, PASSWORD, SUBDOMAIN, DOMAIN, TOP_LEVEL_DOMAIN, PORT_NUM, PATH, PAGE, GET_PARAMS, HASHTAGS = range(12)
# List of start urls to start crawling
start_urls = [
# 'https://app1.com',
# 'https://app2.com',
# 'https://app3.com',
# 'https://app4.com',
# 'https://app5.com',
# 'https://app6.com',
# 'https://app7.com',
# 'https://app8.com',
# 'https://app9.com',
# 'https://app10.com',
# 'https://app11.com',
'http://ec2-54-255-215-139.ap-southeast-1.compute.amazonaws.com/'
]
allowed_domains = [
"app1.com",
"app2.com",
"app3.com",
"app4.com",
"app5.com",
"app6.com",
"app7.com",
"app8.com",
"app9.com",
"app10.com",
"app11.com",
"app12.com",
"app13.com",
"app14.com",
"app15.com",
"app16.com",
"app17.com",
"app18.com",
"app19.com",
"app20.com",
"app21.com"
]
# Set to keep track of visited urls
visited_urls = set(start_urls)
"""
Uses Regex to split up url into components. Groups and what they are:
0 : the full url
1 : Protocol
2 : User
3 : Password
4 : Subdomain
5 : Domain
6 : Top level domain (.com .net etc)
7 : Port number
8 : Path
9 : Page
10: Get parameters
11: Hashtags
"""
def splitUrlIntoParts(self, url, index):
pattern = '(?:([^\:]*)\:\/\/)?(?:([^\:\@]*)(?:\:([^\@]*))?\@)?(?:([^\/\:]*)\.(?=[^\.\/\:]*\.[^\.\/\:]*))?([^\.\/\:]*)(?:\.([^\/\.\:#]*))?(?:\:([0-9]*))?(\/[^\?#]*(?=.*?\/)\/)?([^\?#]*)?(?:\?([^#]*))?(?:#(.*))?'
match = re.search(pattern, url)
if match:
if match.group(index):
return match.group(index)
return ''
def populateURLItem(self, item, url):
item['url'] = url
item['protocol'] = self.splitUrlIntoParts(url, self.PROTOCOL)
item['domain'] = self.splitUrlIntoParts(url, self.DOMAIN)
item['path'] = self.splitUrlIntoParts(url, self.PATH)
item['page'] = self.splitUrlIntoParts(url, self.PAGE)
item['get_params'] = self.splitUrlIntoParts(url, self.GET_PARAMS)
def getUrlWithoutParams(self, url):
# Pattern looks out for a question mark that marks start of params
# Assumption is that url is already valid
pattern = '([^? ]+).*'
match = re.search(pattern, url)
if match:
if match.group(1):
return match.group(1)
else:
return ''
def isVisited(self, url):
if self.drop_params:
truncated_url = self.getUrlWithoutParams(url)
return truncated_url in self.visited_urls
else :
return url in self.visited_urls
def markAsVisited(self, url):
if self.drop_params:
truncated_url = self.getUrlWithoutParams(url)
self.visited_urls.add(truncated_url)
else:
self.visited_urls.add(url)
# The default method that's called by scrapy for each url in the start_url list
def parse(self, response):
# Get URL item
item = URLItem()
# Get parts of URL item
self.populateURLItem(item, response.url)
yield item
# Look for Forms
# Assumption: forms will have id attribute
# We will be using this id and url to uniquely identify each form
forms = response.css('form')
for form in forms:
formItem = FormItem()
formItem['url'] = response.url
form_id = form.css('::attr(id)').extract_first()
if form_id is None:
form_id = ''
formItem['id_attr'] = form_id
yield formItem
inputs = form.css('input')
for a in inputs:
inputItem = InputItem()
inputItem['url'] = response.url
inputItem['form_id'] = form_id
inputItem['complete'] = a.extract()
inputItem['type_attr'] = a.css('::attr(type)').extract_first()
yield inputItem
# Get url to visit next
links = response.css('a::attr(href)').extract()
for next_page in links:
# Check that url exist
if next_page is not None:
# Handle weirdass cases where hrefs has scheme:///domain
next_page = next_page.replace("///", "//", 1)
next_page = response.urljoin(next_page)
# Check that url is not visited yet
if not self.isVisited(next_page):
self.markAsVisited(next_page)
yield scrapy.Request(next_page, callback=self.parse) | [((2021, 2044), 're.search', 're.search', (['pattern', 'url'], {}), '(pattern, url)\n', (2030, 2044), False, 'import re, scrapy\n'), ((2776, 2799), 're.search', 're.search', (['pattern', 'url'], {}), '(pattern, url)\n', (2785, 2799), False, 'import re, scrapy\n'), ((5064, 5110), 'scrapy.Request', 'scrapy.Request', (['next_page'], {'callback': 'self.parse'}), '(next_page, callback=self.parse)\n', (5078, 5110), False, 'import re, scrapy\n')] |
NeCTAR-RC/octavia-tempest-plugin | octavia_tempest_plugin/services/load_balancer/v2/listener_client.py | 5506c00b8d8972e6223499dd5a5da4c85c1ff836 | # Copyright 2017 GoDaddy
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
from oslo_serialization import jsonutils
from tempest import config
from octavia_tempest_plugin.services.load_balancer.v2 import base_client
CONF = config.CONF
Unset = base_client.Unset
class ListenerClient(base_client.BaseLBaaSClient):
root_tag = 'listener'
list_root_tag = 'listeners'
def create_listener(self, protocol, protocol_port, loadbalancer_id,
name=Unset, description=Unset, admin_state_up=Unset,
connection_limit=Unset, timeout_client_data=Unset,
timeout_member_connect=Unset,
timeout_member_data=Unset, timeout_tcp_inspect=Unset,
insert_headers=Unset, default_pool_id=Unset,
default_tls_container_ref=Unset,
sni_container_refs=Unset, client_authentication=Unset,
client_ca_tls_container_ref=Unset,
client_crl_container_ref=Unset,
return_object_only=True):
"""Create a listener.
:param protocol: The protocol for the resource.
:param protocol_port: The protocol port number for the resource.
:param loadbalancer_id: The ID of the load balancer.
:param name: Human-readable name of the resource.
:param description: A human-readable description for the resource.
:param admin_state_up: The administrative state of the resource, which
is up (true) or down (false).
:param connection_limit: The maximum number of connections permitted
for this listener. Default value is -1 which
represents infinite connections.
:param timeout_client_data: Frontend client inactivity timeout in
milliseconds.
:param timeout_member_connect: Backend member connection timeout in
milliseconds.
:param timeout_member_data: Backend member inactivity timeout in
milliseconds.
:param timeout_tcp_inspect: Time, in milliseconds, to wait for
additional TCP packets for content
inspection.
:param insert_headers: A dictionary of optional headers to insert into
the request before it is sent to the backend
member.
:param default_pool_id: The ID of the pool used by the listener if no
L7 policies match.
:param default_tls_container_ref: The URI of the key manager service
secret containing a PKCS12 format
certificate/key bundle for
TERMINATED_TLS listeners.
:param sni_container_refs: A list of URIs to the key manager service
secrets containing PKCS12 format
certificate/key bundles for TERMINATED_TLS
listeners.
:param client_authentication: The TLS client authentication mode. One
of the options NONE, OPTIONAL or
MANDATORY.
:param client_ca_tls_container_ref: The ref of the key manager service
secret containing a PEM format
client CA certificate bundle for
TERMINATED_HTTPS listeners.
:param client_crl_container_ref: The URI of the key manager service
secret containing a PEM format CA
revocation list file for
TERMINATED_HTTPS listeners.
:param return_object_only: If True, the response returns the object
inside the root tag. False returns the full
response from the API.
:raises AssertionError: if the expected_code isn't a valid http success
response code
:raises BadRequest: If a 400 response code is received
:raises Conflict: If a 409 response code is received
:raises Forbidden: If a 403 response code is received
:raises Gone: If a 410 response code is received
:raises InvalidContentType: If a 415 response code is received
:raises InvalidHTTPResponseBody: The response body wasn't valid JSON
:raises InvalidHttpSuccessCode: if the read code isn't an expected
http success code
:raises NotFound: If a 404 response code is received
:raises NotImplemented: If a 501 response code is received
:raises OverLimit: If a 413 response code is received and over_limit is
not in the response body
:raises RateLimitExceeded: If a 413 response code is received and
over_limit is in the response body
:raises ServerFault: If a 500 response code is received
:raises Unauthorized: If a 401 response code is received
:raises UnexpectedContentType: If the content-type of the response
isn't an expect type
:raises UnexpectedResponseCode: If a response code above 400 is
received and it doesn't fall into any
of the handled checks
:raises UnprocessableEntity: If a 422 response code is received and
couldn't be parsed
:returns: A listener object.
"""
kwargs = {arg: value for arg, value in locals().items()
if arg != 'self' and value is not Unset}
return self._create_object(**kwargs)
def show_listener(self, listener_id, query_params=None,
return_object_only=True):
"""Get listener details.
:param listener_id: The listener ID to query.
:param query_params: The optional query parameters to append to the
request. Ex. fields=id&fields=name
:param return_object_only: If True, the response returns the object
inside the root tag. False returns the full
response from the API.
:raises AssertionError: if the expected_code isn't a valid http success
response code
:raises BadRequest: If a 400 response code is received
:raises Conflict: If a 409 response code is received
:raises Forbidden: If a 403 response code is received
:raises Gone: If a 410 response code is received
:raises InvalidContentType: If a 415 response code is received
:raises InvalidHTTPResponseBody: The response body wasn't valid JSON
:raises InvalidHttpSuccessCode: if the read code isn't an expected
http success code
:raises NotFound: If a 404 response code is received
:raises NotImplemented: If a 501 response code is received
:raises OverLimit: If a 413 response code is received and over_limit is
not in the response body
:raises RateLimitExceeded: If a 413 response code is received and
over_limit is in the response body
:raises ServerFault: If a 500 response code is received
:raises Unauthorized: If a 401 response code is received
:raises UnexpectedContentType: If the content-type of the response
isn't an expect type
:raises UnexpectedResponseCode: If a response code above 400 is
received and it doesn't fall into any
of the handled checks
:raises UnprocessableEntity: If a 422 response code is received and
couldn't be parsed
:returns: A listener object.
"""
return self._show_object(obj_id=listener_id,
query_params=query_params,
return_object_only=return_object_only)
def list_listeners(self, query_params=None, return_object_only=True):
"""Get a list of listener objects.
:param query_params: The optional query parameters to append to the
request. Ex. fields=id&fields=name
:param return_object_only: If True, the response returns the object
inside the root tag. False returns the full
response from the API.
:raises AssertionError: if the expected_code isn't a valid http success
response code
:raises BadRequest: If a 400 response code is received
:raises Conflict: If a 409 response code is received
:raises Forbidden: If a 403 response code is received
:raises Gone: If a 410 response code is received
:raises InvalidContentType: If a 415 response code is received
:raises InvalidHTTPResponseBody: The response body wasn't valid JSON
:raises InvalidHttpSuccessCode: if the read code isn't an expected
http success code
:raises NotFound: If a 404 response code is received
:raises NotImplemented: If a 501 response code is received
:raises OverLimit: If a 413 response code is received and over_limit is
not in the response body
:raises RateLimitExceeded: If a 413 response code is received and
over_limit is in the response body
:raises ServerFault: If a 500 response code is received
:raises Unauthorized: If a 401 response code is received
:raises UnexpectedContentType: If the content-type of the response
isn't an expect type
:raises UnexpectedResponseCode: If a response code above 400 is
received and it doesn't fall into any
of the handled checks
:raises UnprocessableEntity: If a 422 response code is received and
couldn't be parsed
:returns: A list of listener objects.
"""
return self._list_objects(query_params=query_params,
return_object_only=return_object_only)
def update_listener(self, listener_id, name=Unset, description=Unset,
admin_state_up=Unset, connection_limit=Unset,
timeout_client_data=Unset,
timeout_member_connect=Unset,
timeout_member_data=Unset, timeout_tcp_inspect=Unset,
insert_headers=Unset, default_pool_id=Unset,
default_tls_container_ref=Unset,
sni_container_refs=Unset, client_authentication=Unset,
client_ca_tls_container_ref=Unset,
client_crl_container_ref=Unset,
return_object_only=True):
"""Update a listener.
:param listener_id: The listener ID to update.
:param name: Human-readable name of the resource.
:param description: A human-readable description for the resource.
:param admin_state_up: The administrative state of the resource, which
is up (true) or down (false).
:param connection_limit: The maximum number of connections permitted
for this listener. Default value is -1 which
represents infinite connections.
:param timeout_client_data: Frontend client inactivity timeout in
milliseconds.
:param timeout_member_connect: Backend member connection timeout in
milliseconds.
:param timeout_member_data: Backend member inactivity timeout in
milliseconds.
:param timeout_tcp_inspect: Time, in milliseconds, to wait for
additional TCP packets for content
inspection.
:param insert_headers: A dictionary of optional headers to insert into
the request before it is sent to the backend
member.
:param default_pool_id: The ID of the pool used by the listener if no
L7 policies match.
:param default_tls_container_ref: The URI of the key manager service
secret containing a PKCS12 format
certificate/key bundle for
TERMINATED_TLS listeners.
:param sni_container_refs: A list of URIs to the key manager service
secrets containing PKCS12 format
certificate/key bundles for TERMINATED_TLS
listeners.
:param client_authentication: The TLS client authentication mode. One
of the options NONE, OPTIONAL or
MANDATORY.
:param client_ca_tls_container_ref: The ref of the key manager service
secret containing a PEM format
client CA certificate bundle for
TERMINATED_HTTPS listeners.
:param client_crl_container_ref: The URI of the key manager service
secret containing a PEM format CA
revocation list file for
TERMINATED_HTTPS listeners.
:param return_object_only: If True, the response returns the object
inside the root tag. False returns the full
response from the API.
:raises AssertionError: if the expected_code isn't a valid http success
response code
:raises BadRequest: If a 400 response code is received
:raises Conflict: If a 409 response code is received
:raises Forbidden: If a 403 response code is received
:raises Gone: If a 410 response code is received
:raises InvalidContentType: If a 415 response code is received
:raises InvalidHTTPResponseBody: The response body wasn't valid JSON
:raises InvalidHttpSuccessCode: if the read code isn't an expected
http success code
:raises NotFound: If a 404 response code is received
:raises NotImplemented: If a 501 response code is received
:raises OverLimit: If a 413 response code is received and over_limit is
not in the response body
:raises RateLimitExceeded: If a 413 response code is received and
over_limit is in the response body
:raises ServerFault: If a 500 response code is received
:raises Unauthorized: If a 401 response code is received
:raises UnexpectedContentType: If the content-type of the response
isn't an expect type
:raises UnexpectedResponseCode: If a response code above 400 is
received and it doesn't fall into any
of the handled checks
:raises UnprocessableEntity: If a 422 response code is received and
couldn't be parsed
:returns: A listener object.
"""
kwargs = {arg: value for arg, value in locals().items()
if arg != 'self' and value is not Unset}
kwargs['obj_id'] = kwargs.pop('listener_id')
return self._update_object(**kwargs)
def delete_listener(self, listener_id, ignore_errors=False):
"""Delete a listener.
:param listener_id: The listener ID to delete.
:param ignore_errors: True if errors should be ignored.
:raises AssertionError: if the expected_code isn't a valid http success
response code
:raises BadRequest: If a 400 response code is received
:raises Conflict: If a 409 response code is received
:raises Forbidden: If a 403 response code is received
:raises Gone: If a 410 response code is received
:raises InvalidContentType: If a 415 response code is received
:raises InvalidHTTPResponseBody: The response body wasn't valid JSON
:raises InvalidHttpSuccessCode: if the read code isn't an expected
http success code
:raises NotFound: If a 404 response code is received
:raises NotImplemented: If a 501 response code is received
:raises OverLimit: If a 413 response code is received and over_limit is
not in the response body
:raises RateLimitExceeded: If a 413 response code is received and
over_limit is in the response body
:raises ServerFault: If a 500 response code is received
:raises Unauthorized: If a 401 response code is received
:raises UnexpectedContentType: If the content-type of the response
isn't an expect type
:raises UnexpectedResponseCode: If a response code above 400 is
received and it doesn't fall into any
of the handled checks
:raises UnprocessableEntity: If a 422 response code is received and
couldn't be parsed
:returns: None if ignore_errors is True, the response status code
if not.
"""
return self._delete_obj(obj_id=listener_id,
ignore_errors=ignore_errors)
def get_listener_stats(self, listener_id, query_params=None,
return_object_only=True):
"""Get listener statistics.
:param listener_id: The listener ID to query.
:param query_params: The optional query parameters to append to the
request. Ex. fields=id&fields=name
:param return_object_only: If True, the response returns the object
inside the root tag. False returns the full
response from the API.
:raises AssertionError: if the expected_code isn't a valid http success
response code
:raises BadRequest: If a 400 response code is received
:raises Conflict: If a 409 response code is received
:raises Forbidden: If a 403 response code is received
:raises Gone: If a 410 response code is received
:raises InvalidContentType: If a 415 response code is received
:raises InvalidHTTPResponseBody: The response body wasn't valid JSON
:raises InvalidHttpSuccessCode: if the read code isn't an expected
http success code
:raises NotFound: If a 404 response code is received
:raises NotImplemented: If a 501 response code is received
:raises OverLimit: If a 413 response code is received and over_limit is
not in the response body
:raises RateLimitExceeded: If a 413 response code is received and
over_limit is in the response body
:raises ServerFault: If a 500 response code is received
:raises Unauthorized: If a 401 response code is received
:raises UnexpectedContentType: If the content-type of the response
isn't an expect type
:raises UnexpectedResponseCode: If a response code above 400 is
received and it doesn't fall into any
of the handled checks
:raises UnprocessableEntity: If a 422 response code is received and
couldn't be parsed
:returns: A listener statistics object.
"""
if query_params:
request_uri = '{0}/{1}/stats?{2}'.format(self.uri, listener_id,
query_params)
else:
request_uri = '{0}/{1}/stats'.format(self.uri, listener_id)
response, body = self.get(request_uri)
self.expected_success(200, response.status)
if return_object_only:
return jsonutils.loads(body.decode('utf-8'))['stats']
else:
return jsonutils.loads(body.decode('utf-8'))
| [] |
isams1/Thesis | ryu/gui/views/router_address_delete.py | dfe03ce60169bd4e5b2eb6f1068a1c89fc9d9fd3 | import re
import logging
import httplib
import view_base
from models import rt_proxy
LOG = logging.getLogger('ryu.gui')
class RtAddrDel(view_base.ViewBase):
def __init__(self, host, port, dpid, address_id, status=None):
super(RtAddrDel, self).__init__()
self.host = host
self.port = port
self.dpid = dpid
self.address_id = address_id
self.status = status
def run(self):
LOG.debug('Router Address Delete Rule running')
if not self.status:
# set rule
return self._delete_address()
def _delete_address(self):
address = '%s:%s' % (self.host, self.port)
res = {'host': self.host,
'port': self.port,
'status': None}
address_no = {}
address_no['address_id'] = self.address_id
status = rt_proxy.delete_router_address(address, address_no, self.dpid)
if status[0]['command_result']:
command_result = status[0]['command_result']
res['status'] = command_result
else:
res['status'] = status
res['status'] = status
return self.json_response(res) | [((93, 121), 'logging.getLogger', 'logging.getLogger', (['"""ryu.gui"""'], {}), "('ryu.gui')\n", (110, 121), False, 'import logging\n'), ((855, 917), 'models.rt_proxy.delete_router_address', 'rt_proxy.delete_router_address', (['address', 'address_no', 'self.dpid'], {}), '(address, address_no, self.dpid)\n', (885, 917), False, 'from models import rt_proxy\n')] |
TobiasRasbold/pywrangler | tests/util/test_helper.py | 3f4ba5891a75430e0882b223bda4c6c7f55dbd51 | """This module contains tests for the helper module.
"""
from pywrangler.util.helper import get_param_names
def test_get_param_names():
def func():
pass
assert get_param_names(func) == []
def func1(a, b=4, c=6):
pass
assert get_param_names(func1) == ["a", "b", "c"]
assert get_param_names(func1, ["a"]) == ["b", "c"]
| [((182, 203), 'pywrangler.util.helper.get_param_names', 'get_param_names', (['func'], {}), '(func)\n', (197, 203), False, 'from pywrangler.util.helper import get_param_names\n'), ((264, 286), 'pywrangler.util.helper.get_param_names', 'get_param_names', (['func1'], {}), '(func1)\n', (279, 286), False, 'from pywrangler.util.helper import get_param_names\n'), ((317, 346), 'pywrangler.util.helper.get_param_names', 'get_param_names', (['func1', "['a']"], {}), "(func1, ['a'])\n", (332, 346), False, 'from pywrangler.util.helper import get_param_names\n')] |
jcgeo9/ML-For-Fish-Recognition | Python-Files/model_conversion/convert_to_tflite.py | 0b5faba77d0b2c5452950637f047882c80fa6fb7 | # =============================================================================
# Created By : Giannis Kostas Georgiou
# Project : Machine Learning for Fish Recognition (Individual Project)
# =============================================================================
# Description : File in order to convert saved models to .tflite instances.
# To be used after the desired model are trained and saved
# How to use : Replace variables in CAPS according to needs of the dataset
# =============================================================================
import tensorflow as tf
model_path='PATH TO SAVED MODEL'
tflite_model_name='NAME OF THE NEWLY CREATED TFLITE MODEL'
#convert the model by loading the saved model to the converter
converter = tf.lite.TFLiteConverter.from_saved_model(model_path)
tflite_model = converter.convert()
#save the tflite model
with open(tflite_model_name+'.tflite', 'wb') as f:
f.write(tflite_model)
| [((777, 829), 'tensorflow.lite.TFLiteConverter.from_saved_model', 'tf.lite.TFLiteConverter.from_saved_model', (['model_path'], {}), '(model_path)\n', (817, 829), True, 'import tensorflow as tf\n')] |
hedibejaoui/spark-timeseries | python3/sparkts/test/test_datetimeindex.py | 9112dcbbba4e095b5eb46c568e1c72e13e1f251a | from .test_utils import PySparkTestCase
from sparkts.datetimeindex import *
import pandas as pd
class DateTimeIndexTestCase(PySparkTestCase):
def test_frequencies(self):
bd = BusinessDayFrequency(1, 1, self.sc)
self.assertEqual(bd.days(), 1)
hf = HourFrequency(4, self.sc)
self.assertEqual(hf.hours(), 4)
def test_uniform(self):
freq = DayFrequency(3, self.sc)
self.assertEqual(freq.days(), 3)
start = '2015-04-10'
index = uniform(start, periods=5, freq=freq, sc=self.sc)
index2 = uniform(start, end='2015-04-22', freq=freq, sc=self.sc)
self.assertEqual(index, index2)
self.assertEqual(len(index), 5)
self.assertEqual(index.first(), pd.to_datetime('2015-04-10'))
self.assertEqual(index.last(), pd.to_datetime('2015-04-22'))
subbydate = index[pd.to_datetime('2015-04-13'):pd.to_datetime('2015-04-19')]
subbyloc = index.islice(1, 4)
self.assertEqual(subbydate, subbyloc)
self.assertEqual(subbydate.first(), pd.to_datetime('2015-04-13'))
self.assertEqual(subbydate.last(), pd.to_datetime('2015-04-19'))
self.assertEqual(subbydate.datetime_at_loc(0), pd.to_datetime('2015-04-13'))
self.assertEqual(subbydate[pd.to_datetime('2015-04-13')], 0)
def test_irregular(self):
pd_index = pd.date_range('2015-04-10', periods=5, freq='3D')
dt_index = irregular(pd_index, self.sc)
self.assertEqual(len(dt_index), 5)
self.assertEqual(dt_index.first(), pd.to_datetime('2015-04-10'))
self.assertEqual(dt_index.last(), pd.to_datetime('2015-04-22'))
subbydate = dt_index[pd.to_datetime('2015-04-13'):pd.to_datetime('2015-04-19')]
subbyloc = dt_index.islice(1, 4)
self.assertEqual(subbydate, subbyloc)
self.assertEqual(subbydate.first(), pd.to_datetime('2015-04-13'))
self.assertEqual(subbydate.last(), pd.to_datetime('2015-04-19'))
self.assertEqual(subbydate.datetime_at_loc(0), pd.to_datetime('2015-04-13'))
self.assertEqual(subbydate[pd.to_datetime('2015-04-13')], 0)
pd_index2 = dt_index.to_pandas_index()
self.assertTrue(pd_index.equals(pd_index2), str(pd_index) + "!=" + str(pd_index2))
| [((1380, 1429), 'pandas.date_range', 'pd.date_range', (['"""2015-04-10"""'], {'periods': '(5)', 'freq': '"""3D"""'}), "('2015-04-10', periods=5, freq='3D')\n", (1393, 1429), True, 'import pandas as pd\n'), ((761, 789), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-10"""'], {}), "('2015-04-10')\n", (775, 789), True, 'import pandas as pd\n'), ((830, 858), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-22"""'], {}), "('2015-04-22')\n", (844, 858), True, 'import pandas as pd\n'), ((1073, 1101), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-13"""'], {}), "('2015-04-13')\n", (1087, 1101), True, 'import pandas as pd\n'), ((1146, 1174), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-19"""'], {}), "('2015-04-19')\n", (1160, 1174), True, 'import pandas as pd\n'), ((1231, 1259), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-13"""'], {}), "('2015-04-13')\n", (1245, 1259), True, 'import pandas as pd\n'), ((1565, 1593), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-10"""'], {}), "('2015-04-10')\n", (1579, 1593), True, 'import pandas as pd\n'), ((1637, 1665), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-22"""'], {}), "('2015-04-22')\n", (1651, 1665), True, 'import pandas as pd\n'), ((1886, 1914), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-13"""'], {}), "('2015-04-13')\n", (1900, 1914), True, 'import pandas as pd\n'), ((1959, 1987), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-19"""'], {}), "('2015-04-19')\n", (1973, 1987), True, 'import pandas as pd\n'), ((2044, 2072), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-13"""'], {}), "('2015-04-13')\n", (2058, 2072), True, 'import pandas as pd\n'), ((886, 914), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-13"""'], {}), "('2015-04-13')\n", (900, 914), True, 'import pandas as pd\n'), ((915, 943), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-19"""'], {}), "('2015-04-19')\n", (929, 943), True, 'import pandas as pd\n'), ((1696, 1724), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-13"""'], {}), "('2015-04-13')\n", (1710, 1724), True, 'import pandas as pd\n'), ((1725, 1753), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-19"""'], {}), "('2015-04-19')\n", (1739, 1753), True, 'import pandas as pd\n'), ((1296, 1324), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-13"""'], {}), "('2015-04-13')\n", (1310, 1324), True, 'import pandas as pd\n'), ((2109, 2137), 'pandas.to_datetime', 'pd.to_datetime', (['"""2015-04-13"""'], {}), "('2015-04-13')\n", (2123, 2137), True, 'import pandas as pd\n')] |
rajitbanerjee/leetcode | src/listIntersect/inter.py | 720fcdd88d371e2d6592ceec8370a6760a77bb89 | # Definition for singly-linked list.
class ListNode:
def __init__(self, x):
self.val = x
self.next = None
class Solution:
def getIntersectionNode(self, headA: ListNode, headB: ListNode) -> ListNode:
seen = set()
curr = headA
while curr:
seen.add(curr)
curr = curr.next
curr = headB
while curr:
if curr in seen:
return curr
curr = curr.next
return None
| [] |
fact-project/photon_stream_production | photon_stream_production/tests/test_drs_run_assignment.py | ca2f946976c9a9717cfcd9364f2361ef385b45aa | import numpy as np
import photon_stream as ps
import photon_stream_production as psp
import pkg_resources
import os
runinfo_path = pkg_resources.resource_filename(
'photon_stream_production',
os.path.join('tests', 'resources', 'runinfo_20161115_to_20170103.csv')
)
drs_fRunID_for_obs_run = psp.drs_run._drs_fRunID_for_obs_run
def test_drs_run_assignment():
ri = psp.runinfo.read(runinfo_path)
ro = psp.drs_run.assign_drs_runs(ri)
ri = ri[(ri.fNight > 20161229) & (ri.fNight <= 20170102)]
ro = ro[(ro.fNight > 20161229) & (ro.fNight <= 20170102)]
for i, row in ri.iterrows():
assert row.fNight == ro.loc[i, 'fNight']
assert row.fRunID == ro.loc[i, 'fRunID']
if row.fRunTypeKey == psp.runinfo.OBSERVATION_RUN_TYPE_KEY:
first_method_drs_run_id = drs_fRunID_for_obs_run(
runinfo=ri,
fNight=row.fNight,
fRunID=row.fRunID
)
second_method_drs_run_id = ro.loc[i, 'DrsRunID']
if np.isnan(first_method_drs_run_id):
assert np.isnan(second_method_drs_run_id)
else:
assert first_method_drs_run_id == second_method_drs_run_id
| [((201, 271), 'os.path.join', 'os.path.join', (['"""tests"""', '"""resources"""', '"""runinfo_20161115_to_20170103.csv"""'], {}), "('tests', 'resources', 'runinfo_20161115_to_20170103.csv')\n", (213, 271), False, 'import os\n'), ((379, 409), 'photon_stream_production.runinfo.read', 'psp.runinfo.read', (['runinfo_path'], {}), '(runinfo_path)\n', (395, 409), True, 'import photon_stream_production as psp\n'), ((419, 450), 'photon_stream_production.drs_run.assign_drs_runs', 'psp.drs_run.assign_drs_runs', (['ri'], {}), '(ri)\n', (446, 450), True, 'import photon_stream_production as psp\n'), ((1028, 1061), 'numpy.isnan', 'np.isnan', (['first_method_drs_run_id'], {}), '(first_method_drs_run_id)\n', (1036, 1061), True, 'import numpy as np\n'), ((1086, 1120), 'numpy.isnan', 'np.isnan', (['second_method_drs_run_id'], {}), '(second_method_drs_run_id)\n', (1094, 1120), True, 'import numpy as np\n')] |
vikifox/CMDB | accounts/migrations/0001_initial.py | bac9b7da204c3eee344f55bb2187df38ef3b3d4c | # -*- coding: utf-8 -*-
# Generated by Django 1.11.20 on 2019-04-18 05:56
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
('cmdb', '0001_initial'),
('appconf', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='UserInfo',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('password', models.CharField(max_length=128, verbose_name='password')),
('last_login', models.DateTimeField(blank=True, null=True, verbose_name='last login')),
('username', models.CharField(db_index=True, max_length=40, unique=True)),
('email', models.EmailField(max_length=255)),
('is_active', models.BooleanField(default=False)),
('is_superuser', models.BooleanField(default=False)),
('nickname', models.CharField(blank=True, max_length=64, null=True)),
('ldap_name', models.CharField(blank=True, max_length=64)),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='PermissionList',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=64)),
('url', models.CharField(max_length=255)),
],
),
migrations.CreateModel(
name='RoleList',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=64)),
('delivery', models.ManyToManyField(blank=True, to='appconf.Project')),
('permission', models.ManyToManyField(blank=True, to='accounts.PermissionList')),
('webssh', models.ManyToManyField(blank=True, to='cmdb.HostGroup')),
],
),
migrations.AddField(
model_name='userinfo',
name='role',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='accounts.RoleList'),
),
]
| [((2316, 2430), 'django.db.models.ForeignKey', 'models.ForeignKey', ([], {'blank': '(True)', 'null': '(True)', 'on_delete': 'django.db.models.deletion.CASCADE', 'to': '"""accounts.RoleList"""'}), "(blank=True, null=True, on_delete=django.db.models.\n deletion.CASCADE, to='accounts.RoleList')\n", (2333, 2430), False, 'from django.db import migrations, models\n'), ((474, 567), 'django.db.models.AutoField', 'models.AutoField', ([], {'auto_created': '(True)', 'primary_key': '(True)', 'serialize': '(False)', 'verbose_name': '"""ID"""'}), "(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')\n", (490, 567), False, 'from django.db import migrations, models\n'), ((595, 652), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(128)', 'verbose_name': '"""password"""'}), "(max_length=128, verbose_name='password')\n", (611, 652), False, 'from django.db import migrations, models\n'), ((686, 756), 'django.db.models.DateTimeField', 'models.DateTimeField', ([], {'blank': '(True)', 'null': '(True)', 'verbose_name': '"""last login"""'}), "(blank=True, null=True, verbose_name='last login')\n", (706, 756), False, 'from django.db import migrations, models\n'), ((788, 847), 'django.db.models.CharField', 'models.CharField', ([], {'db_index': '(True)', 'max_length': '(40)', 'unique': '(True)'}), '(db_index=True, max_length=40, unique=True)\n', (804, 847), False, 'from django.db import migrations, models\n'), ((876, 909), 'django.db.models.EmailField', 'models.EmailField', ([], {'max_length': '(255)'}), '(max_length=255)\n', (893, 909), False, 'from django.db import migrations, models\n'), ((942, 976), 'django.db.models.BooleanField', 'models.BooleanField', ([], {'default': '(False)'}), '(default=False)\n', (961, 976), False, 'from django.db import migrations, models\n'), ((1012, 1046), 'django.db.models.BooleanField', 'models.BooleanField', ([], {'default': '(False)'}), '(default=False)\n', (1031, 1046), False, 'from django.db import migrations, models\n'), ((1078, 1132), 'django.db.models.CharField', 'models.CharField', ([], {'blank': '(True)', 'max_length': '(64)', 'null': '(True)'}), '(blank=True, max_length=64, null=True)\n', (1094, 1132), False, 'from django.db import migrations, models\n'), ((1165, 1208), 'django.db.models.CharField', 'models.CharField', ([], {'blank': '(True)', 'max_length': '(64)'}), '(blank=True, max_length=64)\n', (1181, 1208), False, 'from django.db import migrations, models\n'), ((1420, 1513), 'django.db.models.AutoField', 'models.AutoField', ([], {'auto_created': '(True)', 'primary_key': '(True)', 'serialize': '(False)', 'verbose_name': '"""ID"""'}), "(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')\n", (1436, 1513), False, 'from django.db import migrations, models\n'), ((1537, 1568), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(64)'}), '(max_length=64)\n', (1553, 1568), False, 'from django.db import migrations, models\n'), ((1595, 1627), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(255)'}), '(max_length=255)\n', (1611, 1627), False, 'from django.db import migrations, models\n'), ((1761, 1854), 'django.db.models.AutoField', 'models.AutoField', ([], {'auto_created': '(True)', 'primary_key': '(True)', 'serialize': '(False)', 'verbose_name': '"""ID"""'}), "(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')\n", (1777, 1854), False, 'from django.db import migrations, models\n'), ((1878, 1909), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(64)'}), '(max_length=64)\n', (1894, 1909), False, 'from django.db import migrations, models\n'), ((1941, 1997), 'django.db.models.ManyToManyField', 'models.ManyToManyField', ([], {'blank': '(True)', 'to': '"""appconf.Project"""'}), "(blank=True, to='appconf.Project')\n", (1963, 1997), False, 'from django.db import migrations, models\n'), ((2031, 2095), 'django.db.models.ManyToManyField', 'models.ManyToManyField', ([], {'blank': '(True)', 'to': '"""accounts.PermissionList"""'}), "(blank=True, to='accounts.PermissionList')\n", (2053, 2095), False, 'from django.db import migrations, models\n'), ((2125, 2180), 'django.db.models.ManyToManyField', 'models.ManyToManyField', ([], {'blank': '(True)', 'to': '"""cmdb.HostGroup"""'}), "(blank=True, to='cmdb.HostGroup')\n", (2147, 2180), False, 'from django.db import migrations, models\n')] |
gabrieladt/kops-ec2-autoscaler | autoscaler/azure.py | 8b90fa23caaacf9cf0a4310b65667769906af777 | import http
import logging
from typing import List, Tuple, MutableMapping
from datetime import datetime
import re
from requests.packages.urllib3 import Retry
import autoscaler.utils as utils
from autoscaler.autoscaling_groups import AutoScalingGroup
from autoscaler.azure_api import AzureApi, AzureScaleSet, AzureScaleSetInstance
from autoscaler.utils import TransformingFuture, AllCompletedFuture, CompletedFuture
logger = logging.getLogger(__name__)
_RETRY_TIME_LIMIT = 30
class AzureBoundedRetry(Retry):
"""
XXX: Azure sometimes sends us a Retry-After: 1200, even when we still have quota, causing our client to appear to hang.
Ignore them and just retry after 30secs
"""
def __init__(self, **kwargs):
super().__init__(**kwargs)
@staticmethod
def from_retry(retry):
new_retry = AzureBoundedRetry()
new_retry.total = retry.total
new_retry.connect = retry.connect
new_retry.read = retry.read
new_retry.backoff_factor = retry.backoff_factor
new_retry.BACKOFF_MAX = retry.BACKOFF_MAX
new_retry.status_forcelist = retry.status_forcelist
new_retry.method_whitelist = retry.method_whitelist
return new_retry
def get_retry_after(self, response):
retry_after = super().get_retry_after(response)
if response.status != http.HTTPStatus.TOO_MANY_REQUESTS or retry_after <= _RETRY_TIME_LIMIT:
return retry_after
headers = {}
for header in ['Retry-After',
'x-ms-ratelimit-remaining-subscription-reads',
'x-ms-ratelimit-remaining-subscription-writes',
'x-ms-ratelimit-remaining-tenant-reads',
'x-ms-ratelimit-remaining-tenant-writes',
'x-ms-ratelimit-remaining-subscription-resource-requests',
'x-ms-ratelimit-remaining-subscription-resource-entities-read',
'x-ms-ratelimit-remaining-tenant-resource-requests',
'x-ms-ratelimit-remaining-tenant-resource-entities-read']:
value = response.getheader(header)
if value is not None:
headers[header] = value
logger.warn("Azure request throttled: {}".format(headers))
return _RETRY_TIME_LIMIT
class AzureGroups(object):
def __init__(self, resource_groups, slow_scale_classes, client: AzureApi):
self.resource_groups = resource_groups
self.slow_scale_classes = slow_scale_classes
self.client = client
def get_all_groups(self, kube_nodes):
groups = []
if self.client:
for resource_group in self.resource_groups:
scale_sets_by_type = {}
for scale_set in self.client.list_scale_sets(resource_group.name):
scale_sets_by_type.setdefault((scale_set.location, scale_set.instance_type), []).append(scale_set)
for key, scale_sets in scale_sets_by_type.items():
location, instance_type = key
slow_scale = _get_azure_class(instance_type) in self.slow_scale_classes
groups.append(AzureVirtualScaleSet(location, resource_group.name, self.client, instance_type, slow_scale, scale_sets, kube_nodes))
return groups
_CLASS_PAT = re.compile(r'\w+_(?P<class>[A-Z]+).+')
def _get_azure_class(type_):
m = _CLASS_PAT.match(type_)
return m.group('class')
_SCALE_SET_SIZE_LIMIT = 100
# Appears as an unbounded scale set. Currently, Azure Scale Sets have a limit of 100 hosts.
class AzureVirtualScaleSet(AutoScalingGroup):
provider = 'azure'
def __init__(self, region, resource_group, client: AzureApi, instance_type, slow_scale: bool, scale_sets: List[AzureScaleSet], kube_nodes):
self.client = client
self.instance_type = instance_type
self.tags = {}
self.name = 'virtual_scale_set_' + instance_type + '_' + region + '_' + resource_group
self.scale_sets = dict((scale_set.name, scale_set) for scale_set in scale_sets)
self.desired_capacity = sum(scale_set.capacity for scale_set in scale_sets)
self.region = region
self.resource_group = resource_group
self.selectors = dict(self.tags)
# HACK: for matching node selectors
self.selectors['azure/type'] = self.instance_type
self.selectors['azure/class'] = _get_azure_class(self.instance_type)
self.slow_scale = slow_scale
self.min_size = 0
self.max_size = 10000
self.is_spot = False
self.vm_id_to_instance: MutableMapping[str, Tuple[str, AzureScaleSetInstance]] = {}
self.instances = {}
self.timeout_until = None
self.timeout_reason = None
self._global_priority = None
self.no_schedule_taints = {}
for scale_set in scale_sets:
if scale_set.timeout_until is not None:
if self.timeout_until is None or self.timeout_until < scale_set.timeout_until:
self.timeout_until = scale_set.timeout_until
self.timeout_reason = scale_set.name + ": " + scale_set.timeout_reason
if scale_set.priority is not None:
if self._global_priority is None:
self._global_priority = scale_set.priority
else:
self._global_priority = min(scale_set.priority, self._global_priority)
if not self.no_schedule_taints:
self.no_schedule_taints = scale_set.no_schedule_taints
if scale_set.capacity == 0:
continue
for instance in self.client.list_scale_set_instances(scale_set):
self.vm_id_to_instance[instance.vm_id] = (scale_set.name, instance)
self.instances[instance.vm_id] = AzureInstance(instance.vm_id, self.instance_type, instance.launch_time, self.tags)
self.nodes = [node for node in kube_nodes if node.instance_id in self.vm_id_to_instance]
self.unschedulable_nodes = [n for n in self.nodes if n.unschedulable]
self._id = (self.region, self.name)
def is_timed_out(self):
if self.timeout_until and datetime.now(self.timeout_until.tzinfo) < self.timeout_until:
logger.warn("{} is timed out until {} because {}".format(self._id, self.timeout_until, self.timeout_reason))
return True
return False
@property
def global_priority(self):
if self._global_priority is None:
return super().global_priority
return self._global_priority
def get_azure_instances(self):
return self.instances.values()
@property
def instance_ids(self):
return self.vm_id_to_instance.keys()
def set_desired_capacity(self, new_desired_capacity):
"""
sets the desired capacity of the underlying ASG directly.
note that this is for internal control.
for scaling purposes, please use scale() instead.
"""
scale_out = new_desired_capacity - self.desired_capacity
assert scale_out >= 0
if scale_out == 0:
return CompletedFuture(False)
futures = []
for scale_set in sorted(self.scale_sets.values(), key=lambda x: (x.priority, x.name)):
if scale_set.capacity < _SCALE_SET_SIZE_LIMIT:
if self.slow_scale:
new_group_capacity = scale_set.capacity + 1
else:
new_group_capacity = min(_SCALE_SET_SIZE_LIMIT, scale_set.capacity + scale_out)
scale_out -= (new_group_capacity - scale_set.capacity)
if scale_set.provisioning_state == 'Updating':
logger.warn("Update of {} already in progress".format(scale_set.name))
continue
if scale_set.provisioning_state == 'Failed':
logger.error("{} failed provisioning. Skipping it for scaling.".format(scale_set.name))
continue
# Update our cached version
self.scale_sets[scale_set.name].capacity = new_group_capacity
futures.append(self.client.update_scale_set(scale_set, new_group_capacity))
logger.info("Scaling Azure Scale Set {} to {}".format(scale_set.name, new_group_capacity))
if scale_out == 0:
break
if scale_out > 0:
logger.error("Not enough scale sets to reach desired capacity {} for {}".format(new_desired_capacity, self))
self.desired_capacity = new_desired_capacity - scale_out
logger.info("ASG: {} new_desired_capacity: {}".format(self, new_desired_capacity))
return TransformingFuture(True, AllCompletedFuture(futures))
def terminate_instances(self, vm_ids):
vm_ids = list(vm_ids)
instances = {}
for vm_id in vm_ids:
scale_set_name, instance = self.vm_id_to_instance[vm_id]
# Update our cached copy of the Scale Set
self.scale_sets[scale_set_name].capacity -= 1
instances.setdefault(scale_set_name, []).append(instance)
logger.info('Terminated instances %s', vm_ids)
futures = []
for scale_set_name, scale_set_instances in instances.items():
futures.append(self.client.terminate_scale_set_instances(self.scale_sets[scale_set_name], scale_set_instances))
return AllCompletedFuture(futures)
def scale_nodes_in(self, nodes):
"""
scale down asg by terminating the given node.
returns a future indicating when the request completes.
"""
for node in nodes:
self.nodes.remove(node)
return self.terminate_instances(node.instance_id for node in nodes)
def __str__(self):
return 'AzureVirtualScaleSet({name}, {selectors_hash})'.format(name=self.name, selectors_hash=utils.selectors_to_hash(self.selectors))
def __repr__(self):
return str(self)
class AzureInstance(object):
provider = 'azure'
def __init__(self, instance_id, instance_type, launch_time, tags):
self.id = instance_id
self.instance_type = instance_type
self.launch_time = launch_time
self.tags = tags
def __str__(self):
return 'AzureInstance({}, {})'.format(self.id, self.instance_type)
def __repr__(self):
return str(self) | [((427, 454), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (444, 454), False, 'import logging\n'), ((3351, 3389), 're.compile', 're.compile', (['"""\\\\w+_(?P<class>[A-Z]+).+"""'], {}), "('\\\\w+_(?P<class>[A-Z]+).+')\n", (3361, 3389), False, 'import re\n'), ((9475, 9502), 'autoscaler.utils.AllCompletedFuture', 'AllCompletedFuture', (['futures'], {}), '(futures)\n', (9493, 9502), False, 'from autoscaler.utils import TransformingFuture, AllCompletedFuture, CompletedFuture\n'), ((7190, 7212), 'autoscaler.utils.CompletedFuture', 'CompletedFuture', (['(False)'], {}), '(False)\n', (7205, 7212), False, 'from autoscaler.utils import TransformingFuture, AllCompletedFuture, CompletedFuture\n'), ((8783, 8810), 'autoscaler.utils.AllCompletedFuture', 'AllCompletedFuture', (['futures'], {}), '(futures)\n', (8801, 8810), False, 'from autoscaler.utils import TransformingFuture, AllCompletedFuture, CompletedFuture\n'), ((6235, 6274), 'datetime.datetime.now', 'datetime.now', (['self.timeout_until.tzinfo'], {}), '(self.timeout_until.tzinfo)\n', (6247, 6274), False, 'from datetime import datetime\n'), ((9948, 9987), 'autoscaler.utils.selectors_to_hash', 'utils.selectors_to_hash', (['self.selectors'], {}), '(self.selectors)\n', (9971, 9987), True, 'import autoscaler.utils as utils\n')] |
rachitmishra/45 | sort_insertion.py | c38650f4fa2ea1857848b95320cdc37929b39197 | """
Insertion Sort
Approach: Loop
Complexity: O(n2)
"""
def sort_insertion(input_arr):
print("""""""""""""""""""""""""")
print("input " + str(input_arr))
print("""""""""""""""""""""""""")
ln = len(input_arr)
i = 1 # Assuming first element is sorted
while i < ln: # n times
c = input_arr[i]
p = i
while p > 0 and input_arr[p - 1] > c: # n times
input_arr[p] = input_arr[p - 1]
p -= 1
input_arr[p] = c
i += 1
print("pass " + str(i) + " " + str(input_arr))
print("""""""""""""""""""""""""")
print("result " + str(input_arr))
print("""""""""""""""""""""""""")
if __name__ == '__main__':
arr = [21, 4, 1, 3, 9, 20, 25, 6, 21, 14]
sort_insertion(arr)
| [] |
eveiramirez/python_class | Python2/tareas/tarea_7.py | 7a3830cc92dc842b853b243c6b01e06993faa97e | """
NAME
tarea_7.py
VERSION
[1.0]
AUTHOR
Ignacio Emmanuel Ramirez Bernabe
CONTACT
iramirez@lcg.unam.mx
GITHUB
https://github.com/eveiramirez/python_class/blob/master/Python2/tareas/tarea_7.py
DESCRIPTION
Este programa contiene arrays estructurados para los arrays
creados en el ejercicio 1, los cuales son:
Produccion
Costos
Costos por g/L
CATEGORY
Numpy
"""
import numpy as np
# Crear array con la produccion de cada gen para cada temperatura
production = np.array([("Gen1", 5, 3), ("Gen2", 11, 7),
("Gen3", 4, 9), ("Gen4", 2, 6)],
dtype=[("name", (np.str_, 10)),
("production_cond1", np.int32),
("production_cond2", np.int32)])
# Crear array con los costos de induccion
costs = np.array([("Gen1", 3.5), ("Gen2", 5), ("Gen3", 7),
("Gen4", 4.3)], dtype=[("name", (np.str_, 10)),
("cost", np.float64)])
# Crear array con los costos por g/L para condicion 1
pc_cond1 = production["production_cond1"]/costs["cost"]
# Crear array con los costos por g/L para temperatura 2
pc_cond2 = production["production_cond2"]/costs["cost"]
# Crear lista con los costos por g/L para cada gene guardados en una
# tupla
gene_list = []
for gene in range(0, 4):
gene_list.append((f"Gen{gene+1}", pc_cond1[gene], pc_cond2[gene]))
# Crear array con los costos por g/L
prod_costs = np.array(gene_list, dtype=[("name", (np.str_, 10)),
("pc_cond1", np.float64),
("pc_cond2", np.float64)])
# Imprimir array de los costos por g/L
print(prod_costs)
| [((565, 746), 'numpy.array', 'np.array', (["[('Gen1', 5, 3), ('Gen2', 11, 7), ('Gen3', 4, 9), ('Gen4', 2, 6)]"], {'dtype': "[('name', (np.str_, 10)), ('production_cond1', np.int32), (\n 'production_cond2', np.int32)]"}), "([('Gen1', 5, 3), ('Gen2', 11, 7), ('Gen3', 4, 9), ('Gen4', 2, 6)],\n dtype=[('name', (np.str_, 10)), ('production_cond1', np.int32), (\n 'production_cond2', np.int32)])\n", (573, 746), True, 'import numpy as np\n'), ((892, 1018), 'numpy.array', 'np.array', (["[('Gen1', 3.5), ('Gen2', 5), ('Gen3', 7), ('Gen4', 4.3)]"], {'dtype': "[('name', (np.str_, 10)), ('cost', np.float64)]"}), "([('Gen1', 3.5), ('Gen2', 5), ('Gen3', 7), ('Gen4', 4.3)], dtype=[(\n 'name', (np.str_, 10)), ('cost', np.float64)])\n", (900, 1018), True, 'import numpy as np\n'), ((1537, 1646), 'numpy.array', 'np.array', (['gene_list'], {'dtype': "[('name', (np.str_, 10)), ('pc_cond1', np.float64), ('pc_cond2', np.float64)]"}), "(gene_list, dtype=[('name', (np.str_, 10)), ('pc_cond1', np.float64\n ), ('pc_cond2', np.float64)])\n", (1545, 1646), True, 'import numpy as np\n')] |
paypal/Iguanas | iguanas/pipeline/_base_pipeline.py | 166ea81b7d370eb4281a27aa449719ed1d38a74a | """
Base pipeline class. Main rule generator classes inherit from this one.
"""
from copy import deepcopy
from typing import List, Tuple, Union, Dict
from iguanas.pipeline.class_accessor import ClassAccessor
from iguanas.utils.typing import PandasDataFrameType, PandasSeriesType
import iguanas.utils.utils as utils
from iguanas.exceptions import DataFrameSizeError
class _BasePipeline:
"""
Base pipeline class. Main pipeline classes inherit from this one.
Parameters
----------
steps : List[Tuple[str, object]]
The steps to be applied as part of the pipeline.
verbose : int, optional
Controls the verbosity - the higher, the more messages. >0 : gives
the overall progress of the training of the pipeline; >1 : shows the
current step being trained.
Attributes
----------
steps_ : List[Tuple[str, object]]
The steps corresponding to the fitted pipeline.
rules : Rules
The Rules object containing the rules produced from fitting the
pipeline.
"""
def __init__(self,
steps: List[Tuple[str, object]],
verbose: int) -> None:
self.steps = steps
self.verbose = verbose
self.steps_ = None
self.rules = None
def get_params(self) -> dict:
"""
Returns the parameters of each step in the pipeline.
Returns
-------
dict
The parameters of each step in the pipeline.
"""
pipeline_params = {}
steps_ = self.steps if self.steps_ is None else self.steps_
for step_tag, step in steps_:
step_param_dict = deepcopy(step.__dict__)
pipeline_params[step_tag] = step_param_dict
# If step inherits from _BasePipeline, call its get_params to get
# the parameters each class in the pipeline
if issubclass(step.__class__, _BasePipeline):
step_param_dict = step.get_params()
pipeline_params.update(step_param_dict)
return pipeline_params
def _update_kwargs(self,
params: dict) -> None:
"""
Updates the given parameters of the given steps in the pipeline.
Parameters
----------
params : dict
A dictionary where each key corresponds to the tag used for the
pipeline step. Each value should be a dictionary of the parameters
(keys) and their new values (values).
"""
for step_tag, step in self.steps:
# If step inherits from _BasePipeline, call its _update_kwargs
if issubclass(step.__class__, _BasePipeline):
step._update_kwargs(params)
if step_tag in params.keys():
# If a parameter in `params` is not in the keyword arguments
# of the class (excl when kwargs is present), raise exception
for param in params[step_tag].keys():
if param not in step.__dict__.keys() and 'kwargs' not in step.__dict__.keys():
raise ValueError(
f'Parameter `{param}` not found in keyword arguments for class in step `{step_tag}`'
)
step.__dict__.update(params[step_tag])
def _pipeline_fit(self,
step_tag: str,
step: object,
X: Union[PandasDataFrameType, dict],
y: Union[PandasSeriesType, dict],
sample_weight: Union[PandasSeriesType, dict]) -> None:
"""
Runs the following before applying the `fit` method of `step`:
1. Checks the parameters of `step` for `ClassAccessor` objects. If a
`ClassAccessor` object is found, the parameter in `step` is updated
with the class attribute denoted by the `ClassAccessor` object.
2. Checks if `X`, `y` or `sample_weight` are dictionaries. If so,
then the dataset aligned to `step_tag` is extracted.
Parameters
----------
step_tag : str
The tag corresponding to the step.
step : object
The step in the pipeline.
X : Union[PandasDataFrameType, dict]
The dataset or dictionary of datasets for each pipeline step.
y : Union[PandasSeriesType, dict]
The binary target column or dictionary of binary target columns
for each pipeline step.
sample_weight : Union[PandasSeriesType, dict], optional
Row-wise weights or dictionary of row-wise weights for each
pipeline step. Defaults to None.
"""
step = self._check_accessor(step)
X, y, sample_weight = [
utils.return_dataset_if_dict(
step_tag=step_tag, df=df
) for df in (X, y, sample_weight)
]
step.fit(X, y, sample_weight)
def _pipeline_transform(self,
step_tag: str,
step: object,
X: Union[PandasDataFrameType, dict]) -> PandasDataFrameType:
"""
Runs the following before applying the `transform` method of `step`:
1. Checks the parameters of `step` for `ClassAccessor` objects. If a
`ClassAccessor` object is found, the parameter in `step` is updated
with the class attribute denoted by the `ClassAccessor` object.
2. Checks if `X`, `y` or `sample_weight` are dictionaries. If so,
then the dataset aligned to `step_tag` is extracted.
Parameters
----------
step_tag : str
The tag corresponding to the step.
step : object
The step in the pipeline.
X : Union[PandasDataFrameType, dict]
The dataset or dictionary of datasets for each pipeline step.
Returns
-------
PandasDataFrameType
The transformed dataset.
"""
step = self._check_accessor(step)
X = utils.return_dataset_if_dict(step_tag=step_tag, df=X)
X = step.transform(X)
self._exception_if_no_cols_in_X(X, step_tag)
return X
def _pipeline_predict(self,
step: object,
X: Union[PandasDataFrameType, dict]) -> PandasSeriesType:
"""
Runs the following before applying the `predict` method of `step`:
1. Checks the parameters of `step` for `ClassAccessor` objects. If a
`ClassAccessor` object is found, the parameter in `step` is updated
with the class attribute denoted by the `ClassAccessor` object.
Parameters
----------
step : object
The step in the pipeline.
X : Union[PandasDataFrameType, dict]
The dataset or dictionary of datasets for each pipeline step.
Returns
-------
PandasSeriesType
The prediction of the final step.
"""
step = self._check_accessor(step)
return step.predict(X)
def _pipeline_fit_transform(self,
step_tag: str,
step: object,
X: Union[PandasDataFrameType, dict],
y: Union[PandasSeriesType, dict],
sample_weight: Union[PandasSeriesType, dict]) -> PandasDataFrameType:
"""
Runs the following before applying the `fit_transform` method of `step`:
1. Checks the parameters of `step` for `ClassAccessor` objects. If a
`ClassAccessor` object is found, the parameter in `step` is updated
with the class attribute denoted by the `ClassAccessor` object.
2. Checks if `X`, `y` or `sample_weight` are dictionaries. If so,
then the dataset aligned to `step_tag` is extracted.
Parameters
----------
step_tag : str
The tag corresponding to the step.
step : object
The step in the pipeline.
X : Union[PandasDataFrameType, dict]
The dataset or dictionary of datasets for each pipeline step.
y : Union[PandasSeriesType, dict]
The binary target column or dictionary of binary target columns
for each pipeline step.
sample_weight : Union[PandasSeriesType, dict], optional
Row-wise weights or dictionary of row-wise weights for each
pipeline step. Defaults to None.
Returns
-------
PandasDataFrameType
The transformed dataset.
"""
step = self._check_accessor(step)
X, y, sample_weight = [
utils.return_dataset_if_dict(
step_tag=step_tag, df=df
) for df in (X, y, sample_weight)
]
X = step.fit_transform(X, y, sample_weight)
self._exception_if_no_cols_in_X(X, step_tag)
return X
def _check_accessor(self,
step: object) -> object:
"""
Checks whether the any of the parameters in the given `step` is of type
ClassAccessor. If so, then it runs the ClassAccessor's `get` method,
which extracts the given attribute from the given step in the pipeline,
and injects it into the parameter.
"""
def _check_accessor_iterable(iterable: Union[list, tuple],
pipeline_params: Dict[str, dict]) -> None:
"""
Iterates through an iterable - if the element is another iterable,
_check_accessor_iterable is called again. If the the element is a
CheckAccessor, its `get` method is called (which extracts the given
attribute from the given step in the pipeline) - this attribute is
then assigned in place of the original element.
"""
for idx, value in enumerate(iterable):
if isinstance(value, (list, tuple)):
_check_accessor_iterable(value, pipeline_params)
elif isinstance(value, ClassAccessor):
try:
iterable[idx] = value.get(pipeline_params)
except TypeError:
raise TypeError(
'`ClassAccessor` object must be within a mutable iterable.'
)
step_param_dict = step.__dict__
for param, value in step_param_dict.items():
# If parameter value is an instantiated class, but not a
# ClassAccessor, call _check_accessor again
if hasattr(value, '__dict__') and value.__dict__ and not isinstance(value, ClassAccessor):
self._check_accessor(value)
# If parameter value is a list or tuple, call
# _check_accessor_iterable
elif isinstance(value, (list, tuple)):
pipeline_params = self.get_params()
_check_accessor_iterable(value, pipeline_params)
# If the parameter value is a ClassAccessor, call its get method
elif isinstance(value, ClassAccessor):
pipeline_params = self.get_params()
step.__dict__[param] = value.get(pipeline_params)
return step
@staticmethod
def _exception_if_no_cols_in_X(X: PandasDataFrameType,
step_tag: str) -> Union[None, DataFrameSizeError]:
"""Raises an exception if `X` has no columns."""
if X.shape[1] == 0:
raise DataFrameSizeError(
f'`X` has been reduced to zero columns after the `{step_tag}` step in the pipeline.'
)
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AlexanderMakarov/activitywatch-ets | test_activity_merger.py | 36e5ac92c7834b9515a54c5d633ae5e45d6928bc | import unittest
import datetime
from parameterized import parameterized
from activity_merger import Interval
from aw_core.models import Event
from typing import List, Tuple
def _build_datetime(seed: int) -> datetime.datetime:
return datetime.datetime(2000, 1, seed, seed, 0, 0).astimezone(datetime.timezone.utc)
def _build_timedelta(seed: int) -> datetime.timedelta:
return _build_datetime(seed + 1) - _build_datetime(1)
def build_intervals_linked_list(data: List[Tuple[int, bool, int]]) -> Interval:
"""
Builds intervals linked list from the list of tuples. Doesn't check parameters.
:param data: List of tuples (day of start, flag to return `Interval` from the function, duration).
:return: Chosen interval.
"""
result = None
previous = None
for (seed, is_target, duration) in data:
if not previous:
previous = Interval(_build_datetime(seed), _build_datetime(seed + duration))
else:
tmp = Interval(_build_datetime(seed), _build_datetime(seed + duration), previous)
previous.next = tmp
previous = tmp
if is_target:
assert result is None, f"Wrong parameters - '{seed}' interval is marked as result but is not first."
result = previous
return result
class TestInterval(unittest.TestCase):
@parameterized.expand([
(
"Simple the only interval",
build_intervals_linked_list([
(1, True, 1)
]),
1
),
(
"The same interval",
build_intervals_linked_list([
(1, False, 1),
(5, True, 1),
(6, False, 1)
]),
5
),
(
"Exact Interval right before",
build_intervals_linked_list([
(5, False, 1),
(6, True, 1),
(7, False, 1)
]),
5
),
(
"Exact Interval right after",
build_intervals_linked_list([
(3, False, 1),
(4, True, 1),
(5, False, 1)
]),
5
),
(
"Exact Interval far after",
build_intervals_linked_list([
(3, True, 1),
(4, False, 1),
(5, False, 1),
(6, False, 1),
]),
5
),
(
"Exact Interval far before",
build_intervals_linked_list([
(4, False, 1),
(5, False, 1),
(6, False, 1),
(7, True, 1),
]),
5
),
])
def test_find_closest_by_start(self, test_name, interval, expected_start_seed):
target = _build_datetime(5)
actual: Interval = interval.find_closest(target, datetime.timedelta(0), False)
expected = _build_datetime(expected_start_seed)
self.assertEqual(actual.start_time, expected, f"'{test_name}' case failed.")
@parameterized.expand([
(
"Simple the only interval",
build_intervals_linked_list([
(1, True, 1)
]),
1
),
(
"The same interval",
build_intervals_linked_list([
(1, False, 1),
(4, True, 1),
(6, False, 1),
]),
4
),
(
"Exact Interval right before",
build_intervals_linked_list([
(4, False, 1),
(6, True, 1),
(7, False, 1),
]),
4
),
(
"Exact Interval right after",
build_intervals_linked_list([
(1, False, 1),
(2, True, 1),
(4, False, 1),
]),
4
),
(
"Exact Interval far after",
build_intervals_linked_list([
(2, True, 1),
(3, False, 1),
(4, False, 1),
(5, False, 1),
]),
4
),
(
"Exact Interval far before",
build_intervals_linked_list([
(3, False, 1),
(4, False, 1),
(6, False, 1),
(7, True, 1),
]),
4
),
])
def test_find_closest_by_end(self, test_name, interval: Interval, expected_start_seed):
target = _build_datetime(5)
actual: Interval = interval.find_closest(target, datetime.timedelta(0), True)
expected = _build_datetime(expected_start_seed)
self.assertEqual(actual.start_time, expected, f"'{test_name}' case failed.")
@parameterized.expand([
(
"Event at middle",
build_intervals_linked_list([
(3, True, 5),
]),
Event(1, _build_datetime(5), _build_timedelta(1)),
build_intervals_linked_list([
(3, True, 2),
(5, False, 1),
(6, False, 2),
]),
),
(
"Event start equal interval start",
build_intervals_linked_list([
(5, True, 5),
]),
Event(1, _build_datetime(5), _build_timedelta(1)),
build_intervals_linked_list([
(5, True, 1),
(6, False, 4),
]),
),
(
"Event end equal interval end",
build_intervals_linked_list([
(4, True, 2),
]),
Event(1, _build_datetime(5), _build_timedelta(1)),
build_intervals_linked_list([
(4, True, 1),
(5, False, 1),
]),
),
])
def test_separate_new_at_middle(self, test_name: str, interval: Interval, event: Event,
expected_interval_offset_2_num_4: Interval):
actual: Interval = interval.separate_new_at_middle(event, datetime.timedelta(0))
self.assertListEqual(actual.get_range(-2, 4), expected_interval_offset_2_num_4.get_range(-2, 4),
f"'{test_name}' case failed.")
if __name__ == '__main__':
unittest.main()
| [((6290, 6305), 'unittest.main', 'unittest.main', ([], {}), '()\n', (6303, 6305), False, 'import unittest\n'), ((239, 283), 'datetime.datetime', 'datetime.datetime', (['(2000)', '(1)', 'seed', 'seed', '(0)', '(0)'], {}), '(2000, 1, seed, seed, 0, 0)\n', (256, 283), False, 'import datetime\n'), ((2894, 2915), 'datetime.timedelta', 'datetime.timedelta', (['(0)'], {}), '(0)\n', (2912, 2915), False, 'import datetime\n'), ((4634, 4655), 'datetime.timedelta', 'datetime.timedelta', (['(0)'], {}), '(0)\n', (4652, 4655), False, 'import datetime\n'), ((6082, 6103), 'datetime.timedelta', 'datetime.timedelta', (['(0)'], {}), '(0)\n', (6100, 6103), False, 'import datetime\n')] |
alekseynp/playground | pommerman/agents/player_agent.py | 523cc924fe9fd269a8eb3e29c45ace1c5c85b12c | """
NOTE:
There are a few minor complications to fluid human control which make this
code a little more involved than trivial.
1. Key press-release cycles can be, and often are, faster than one tick of
the game/simulation, but the player still wants that cycle to count, i.e.
to lay a bomb!
2. When holding down a key, the player expects that action to be repeated,
at least after a slight delay.
3. But when holding a key down (say, move left) and simultaneously doing a
quick press-release cycle (put a bomb), we want the held-down key to keep
being executed, but the cycle should have happened in-between.
The way we solve this problem is by separating key-state and actions-to-do.
We hold the actions that need be executed in a queue (`self._action_q`) and
a state for all considered keys.
1. When a key is pressed down, we note the time and mark it as down.
2. If it is released quickly thereafter, before a game tick could happen,
we add its action into the queue. This often happens when putting bombs.
3. If it's still pressed down as we enter a game tick, we do some math to see
if it's time for a "repeat" event and, if so, push an action to the queue.
4. Just work off one item from the queue each tick.
This way, the input is "natural" and things like dropping a bomb while doing
a diagonal walk from one end to the other "just work".
"""
from time import time
from . import BaseAgent
from .. import characters
REPEAT_DELAY = 0.2 # seconds
REPEAT_INTERVAL = 0.1
class Keystate:
def __init__(self):
self.keydown_time = time()
self.last_repeat_time = None
self.fired = False
def should_fire(self):
if self.last_repeat_time is None:
# The first repetition:
if time() - self.keydown_time > REPEAT_DELAY:
return True
else:
# A repetition after the first:
if time() - self.last_repeat_time > REPEAT_INTERVAL:
return True
# No repetition yet
return False
def mark_fired(self):
self.last_repeat_time = time()
self.fired = True
class PlayerAgent(BaseAgent):
"""The Player Agent that lets the user control a character."""
def __init__(self, character=characters.Bomber, agent_control='arrows'):
super(PlayerAgent, self).__init__(character)
##
# @NOTE: DO NOT move this import outside the constructor. It will
# not work in headless environments like a Docker container
# and prevents Pommerman from running.
#
from pyglet.window import key
CONTROLS = {
'arrows': {
key.UP: 1,
key.DOWN: 2,
key.LEFT: 3,
key.RIGHT: 4,
key.SPACE: 5,
key.M: 6 # In Pommerman, this will freeze the game.
},
'wasd': {
key.W: 1,
key.S: 2,
key.A: 3,
key.D: 4,
key.E: 5,
key.Q: 6 # In Pommerman, this will freeze the game.
}
}
assert agent_control in CONTROLS, "Unknown control: {}".format(
agent_control)
self._key2act = CONTROLS[agent_control]
self._action_q = []
self._keystate = {}
def act(self, obs, action_space):
# Go through the keys and fire for those that needs repetition (because they're held down)
for k, state in self._keystate.items():
if state.should_fire():
self._action_q.append(k)
state.mark_fired()
act = 0
if self._action_q: # Work off the keys that are queued.
act = self._key2act[self._action_q.pop(0)]
return act
@staticmethod
def has_user_input():
return True
def on_key_press(self, k, mod):
# Ignore if we're not handling the key. Avoids "shadowing" ticks in
# multiplayer mode.
if k in self._key2act:
self._keystate[k] = Keystate()
def on_key_release(self, k, mod):
# We only need to act on keys for which we did something in the
# `key_press` event, and ignore any other key releases.
if k in self._keystate:
# Only mark this as a "press" upon release if it was a quick one,
# i.e. not held down and executed already
if not self._keystate[k].fired:
self._action_q.append(k)
del self._keystate[k]
| [((1575, 1581), 'time.time', 'time', ([], {}), '()\n', (1579, 1581), False, 'from time import time\n'), ((2098, 2104), 'time.time', 'time', ([], {}), '()\n', (2102, 2104), False, 'from time import time\n'), ((1767, 1773), 'time.time', 'time', ([], {}), '()\n', (1771, 1773), False, 'from time import time\n'), ((1911, 1917), 'time.time', 'time', ([], {}), '()\n', (1915, 1917), False, 'from time import time\n')] |
sapshah-cisco/cobra | tests/rest/test_rest.py | e2b5a75495931844180b05d776c15829e63f0dab | # Copyright 2015 Cisco Systems, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import print_function
from future import standard_library
standard_library.install_aliases()
from builtins import str
from builtins import range
from builtins import object
import http.client
import os
import pytest
import random
import string
import time
import xml.etree.ElementTree as ET
import logging
from cobra.internal.codec.jsoncodec import toJSONStr, fromJSONStr
from cobra.internal.codec.xmlcodec import toXMLStr, fromXMLStr
import cobra.mit.access
import cobra.mit.request
import cobra.mit.session
cobra = pytest.importorskip("cobra")
cobra.model = pytest.importorskip("cobra.model")
cobra.model.fv = pytest.importorskip("cobra.model.fv")
import cobra.model.pol
import cobra.model.infra
import cobra.services
pytestmark = pytest.mark.skipif(pytest.config.getvalue('apic') == [],
reason="You must specify at least one --apic " +
"option on the CLI")
slow = pytest.mark.slow
http.client.HTTPConnection.debuglevel = 1
logging.basicConfig(level=logging.DEBUG)
fakeDevicePackageZip = 'Archive.zip'
realDevicePackageZip = 'asa-device-pkg.zip'
@pytest.fixture(params=pytest.config.getvalue('apic'))
def moDir(request):
url, user, password, secure = request.param
secure = False if secure == 'False' else True
session = cobra.mit.session.LoginSession(url, user, password,
secure=secure)
md = cobra.mit.access.MoDirectory(session)
md.login()
return md
class Test_rest_configrequest(object):
def test_createtenant(self, moDir, tenantname):
"""
create a tenant and commit it
"""
dcid = str(time.time()).replace('.', '')
polUni = cobra.model.pol.Uni('')
tenant = cobra.model.fv.Tenant(polUni, tenantname[0])
configRequest = cobra.mit.request.ConfigRequest()
configRequest.addMo(tenant)
configRequest.subtree = 'full'
configRequest.id = dcid
mos = moDir.commit(configRequest)
assert mos
mo = mos[0]
assert len(mos) > 0
assert str(mo.dn) == str(tenant.dn)
assert len(list(mo.children)) >= 1
def test_lookupcreatedtenant(self, moDir, tenantname):
tenant = moDir.lookupByDn('uni/tn-{0}'.format(tenantname[0]))
assert tenant
def test_deletetenant(self, moDir, tenantname):
tenant = moDir.lookupByDn('uni/tn-{0}'.format(tenantname[0]))
tenant.delete()
configRequest = cobra.mit.request.ConfigRequest()
configRequest.addMo(tenant)
r = moDir.commit(configRequest)
assert r == []
tenant = moDir.lookupByDn('uni/tn-{0}'.format(tenantname[0]))
assert not tenant
class Test_rest_classquery(object):
def test_classquery_shorthand_filter(self, moDir):
"""
check that lookupByClass is able to lookup tenant common and only one
item is returned
"""
commonTn = moDir.lookupByClass(
'fvTenant', propFilter='eq(fvTenant.name, "common")')
assert len(commonTn) == 1
commonTn = commonTn[0]
assert str(commonTn.dn) == 'uni/tn-common'
def test_classquery_normal(self, moDir):
"""
check that a class query with no special properties succeeds
we should get at least three tenants (infra, mgmt, common)
"""
classQuery = cobra.mit.request.ClassQuery('fvTenant')
commonTn = moDir.query(classQuery)
def findtn(tnlist, tnname):
for tn in tnlist:
if tn.name == tnname:
return True
return False
assert findtn(commonTn, 'common')
assert findtn(commonTn, 'infra')
assert findtn(commonTn, 'mgmt')
def test_classquery_filter(self, moDir):
"""
check that a class query with a property filter works
"""
classQuery = cobra.mit.request.ClassQuery('fvTenant')
classQuery.propFilter = 'eq(fvTenant.name, "common")'
commonTn = moDir.query(classQuery)
commonTn = commonTn[0]
assert str(commonTn.dn) == 'uni/tn-common'
def test_classquery_subtree(self, moDir):
"""
check that a class query with a subtree response
"""
classQuery = cobra.mit.request.ClassQuery('fvTenant')
classQuery.subtree = 'full'
classQuery.propFilter = 'eq(fvTenant.name, "common")'
commonTn = moDir.query(classQuery)
commonTn = commonTn[0]
assert str(commonTn.dn) == 'uni/tn-common'
# expect at least 3 child objects
assert len(list(commonTn.children)) >= 3
assert str(commonTn.BD['default'].dn) == 'uni/tn-common/BD-default'
@pytest.mark.parametrize("cls,subtree", [
pytest.mark.skipif(pytest.config.getvalue('apic') == [],
reason="no --apic")(('fvTenant', 'full')),
pytest.mark.skipif(pytest.config.getvalue('apic') == [],
reason="no --apic")(('infraInfra', 'no')),
pytest.mark.skipif(pytest.config.getvalue('apic') == [],
reason="no --apic")(('fvAEPg', 'full')),
pytest.mark.skipif(pytest.config.getvalue('apic') == [],
reason="no --apic")(('infraFuncP', 'full')),
pytest.mark.skipif(pytest.config.getvalue('apic') == [],
reason="no --apic")(('fabricNode', 'no')),
pytest.mark.skipif(pytest.config.getvalue('apic') == [],
reason="no --apic")(('topSystem', 'full')),
])
def test_classquery_many(self, moDir, cls, subtree):
classQuery = cobra.mit.request.ClassQuery(cls)
classQuery.subtree = subtree
# classQuery.propFilter='eq(fvTenant.name, "common")'
mos = moDir.query(classQuery)
assert len(mos) > 0
def test_classquery_verifyxml(self, moDir):
"""
verify that the XML returned by lookupByClass is valid
"""
commonTn = moDir.lookupByClass(
'fvTenant', propFilter='eq(fvTenant.name, "common")')
commonTn = commonTn[0]
xml = ET.fromstring(toXMLStr(commonTn))
assert xml.tag == 'fvTenant'
def test_classquery_negative(self, moDir):
"""
generate a random tenant name and ensure that we dont find a match for it
"""
tenantName = ''.join(random.choice(string.ascii_lowercase)
for i in range(64))
tenant = moDir.lookupByClass(
'fvTenant', propFilter='eq(fvTenant.name, "{0}")'.format(tenantName))
assert len(tenant) == 0
class Test_rest_dnquery(object):
def test_dnquery_normal(self, moDir, dn):
dnQuery = cobra.mit.request.DnQuery(dn)
dnQuery.subtree = 'full'
commonTn = moDir.query(dnQuery)
assert len(commonTn) == 1
commonTn = commonTn[0]
assert str(commonTn.dn) == str(dn)
# expect at least 3 child objects
assert len(list(commonTn.children)) >= 3
assert str(commonTn.BD['default'].dn) == 'uni/tn-common/BD-default'
def test_dnquery_shorthand(self, moDir, dn):
commonTn = moDir.lookupByDn(dn)
assert str(commonTn.dn) == str(dn)
class Test_rest_getLoginDomains(object):
def test_getDomains(self, apic):
"""Verify that the getLoginDomains() method works.
"""
url, user, password, secure = apic
secure = False if secure == 'False' else True
session = cobra.mit.session.LoginSession(url, user, password,
secure=secure)
session.getLoginDomains()
assert session.domains != []
def test_loginDomains_setting(self, apic):
"""Verify that the loginDomain can be set."""
url, user, password, secure = apic
secure = False if secure == 'False' else True
session = cobra.mit.session.LoginSession(url, user, password,
secure=secure)
session.getLoginDomains()
session.loginDomain = session.domains[0]
assert session.loginDomain == session.domains[0]
class Test_rest_login(object):
def test_login_positive(self, apic):
"""
verify that the login function works
"""
url, user, password, secure = apic
secure = False if secure == 'False' else True
session = cobra.mit.session.LoginSession(url, user, password,
secure=secure)
moDir = cobra.mit.access.MoDirectory(session)
moDir.login()
assert moDir._session
def test_login_negative(self, apic):
"""
verify that the invalid logins throw an exception
"""
url, user, password, secure = apic
secure = False if secure == 'False' else True
session = cobra.mit.session.LoginSession(url, user, 'wrongpassword',
secure=secure)
moDir = cobra.mit.access.MoDirectory(session)
with pytest.raises(cobra.mit.session.LoginError):
moDir.login()
@slow
def test_login_timeout(self, apic):
"""
verify that the session times out properly
"""
url, user, password, secure = apic
secure = False if secure == 'False' else True
session = cobra.mit.session.LoginSession(url, user, password,
secure=secure)
moDir = cobra.mit.access.MoDirectory(session)
moDir.login()
start = time.time()
pki = moDir.lookupByDn('uni/userext/pkiext/webtokendata')
refreshTime = pki.webtokenTimeoutSeconds
sleepTime = float(refreshTime) - (time.time() - start)
sleepTime += 1.0 # one second buffer, for good measure
time.sleep(sleepTime)
with pytest.raises(cobra.mit.request.QueryError):
moDir.lookupByClass('pkiWebTokenData')
def test_login_get_timeout(self, apic):
"""
verify that the session times out properly
"""
url, user, password, secure = apic
secure = False if secure == 'False' else True
session = cobra.mit.session.LoginSession(url, user, password,
secure=secure)
moDir = cobra.mit.access.MoDirectory(session)
moDir.login()
assert moDir._session.refreshTime > int(time.time())
assert moDir._session.refreshTimeoutSeconds > 0
def test_rest_login_reauth(self, apic):
"""Verify that the reauth call returns a different session cookie."""
url, user, password, secure = apic
secure = False if secure == 'False' else True
session = cobra.mit.session.LoginSession(url, user, password,
secure=secure)
moDir = cobra.mit.access.MoDirectory(session)
moDir.login()
orig_cookie = session.cookie
# sleep for 5 seconds to ensure we get a different cookie.
time.sleep(5)
moDir.reauth()
assert orig_cookie != session.cookie
class Test_rest_tracequery(object):
@pytest.mark.parametrize("cls", [
pytest.mark.skipif(pytest.config.getvalue('apic') == [],
reason="no --apic")('fvEpP'),
pytest.mark.skipif(pytest.config.getvalue('apic') == [],
reason="no --apic")('vlanCktEp'),
pytest.mark.skipif(pytest.config.getvalue('apic') == [],
reason="no --apic")('actrlRule'),
])
def test_tracequery(self, moDir, cls):
"""
Query every leaf in the fabric for some concrete objects and try to
find at least one response. If we don't get that, we fail
"""
traceResponse = 0
nodes = moDir.lookupByClass(
'fabricNode', propFilter='eq(fabricNode.role,"leaf"')
assert len(nodes) > 0
for node in nodes:
a = cobra.mit.request.TraceQuery(node.dn, cls)
print(a.getUrl(moDir._session))
mos = moDir.query(a)
for mo in mos:
print(mo.dn)
traceResponse += len(mos)
assert traceResponse > 0
class Test_services_devicepackage(object):
fakePackage = os.path.join(os.path.dirname(os.path.realpath(__file__)),
fakeDevicePackageZip)
realPackage = os.path.join(os.path.dirname(os.path.realpath(__file__)),
realDevicePackageZip)
def test_packagevalidate(self):
"""
Make sure that invalid device packages throw an exception when validation
is enabled
"""
with pytest.raises(AttributeError):
cobra.services.UploadPackage(self.fakePackage, validate=True)
def test_packagedonotvalidate(self):
"""
Make sure that if validation is not enabled, no exception is thrown
"""
packageUpload = cobra.services.UploadPackage(self.fakePackage)
assert packageUpload.devicePackagePath == self.fakePackage
def test_uploadpackage(self, moDir):
"""
ensure that the device package upload returns a 200
"""
packageUpload = cobra.services.UploadPackage(self.realPackage,
validate=True)
r = moDir.commit(packageUpload)
assert r == []
def test_validateupload(self, moDir):
"""
make sure that the uploaded device package is found
"""
uni = cobra.model.pol.Uni('')
infra = cobra.model.infra.Infra(uni)
vnsQuery = cobra.mit.request.DnQuery(infra.dn)
vnsQuery.propFilter = 'eq(vnsMDev.vendor,"CISCO")'
vnsQuery.queryTarget = 'subtree'
vnsQuery.classFilter = 'vnsMDev'
packages = moDir.query(vnsQuery)
assert len(packages) > 0
package = packages[0]
assert package.vendor == 'CISCO'
assert package.model == 'ASA'
# for package in packages:
# print '\n'.join(['%s:\t%s' % (k,getattr(package,k)) for k in package.meta.props.names])
# print package.dn
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omaraljazairy/FedalAPI | spanglish/tests/fixtures/models/language.py | 2be0a19bb2629be9e2a0477f99477e4bfbd8901e | """ fixtures that return an sql statement with a list of values to be inserted."""
def load_language():
""" return the sql and values of the insert queuery."""
sql = """
INSERT INTO Spanglish_Test.Language
(
`name`, `iso-639-1`
)
VALUES (%s, %s)
"""
values = [
(
'English', 'EN'
),
(
'Spanish', 'ES'
),
(
'Dutch', 'NL'
)
]
return {
'sql': sql,
'values': values
}
| [] |
tradewartracker/phase-one-product-hs2 | main-hs2.py | 38dd328a8211695c31f09a34832535dc2c82a5c2 | import datetime as dt
from os.path import dirname, join
import numpy as np
import pandas as pd
import pyarrow as pa
import pyarrow.parquet as pq
from bokeh.io import curdoc
from bokeh.layouts import column, gridplot, row
from bokeh.models import ColumnDataSource, DataRange1d, Select, HoverTool, Panel, Tabs, LinearColorMapper, Range1d
from bokeh.models import NumeralTickFormatter, Title, Label, Paragraph, Div, CustomJSHover, BoxAnnotation
from bokeh.models import ColorBar
from bokeh.palettes import brewer, Spectral6
from bokeh.plotting import figure
from bokeh.embed import server_document
from bokeh.transform import factor_cmap
#################################################################################
# This just loads in the data...
# Alot of this was built of this "cross-fire demo"
# https://github.com/bokeh/bokeh/blob/branch-2.3/examples/app/crossfilter/main.py
start_date = dt.datetime(2017,7,1)
end_date = dt.datetime(2022,1,1)
background = "#ffffff"
file = "./data"+ "/data.parquet"
df = pq.read_table(file).to_pandas()
df.sort_index(inplace=True)
options = df.index.unique(0).to_list()
#print(options)
product = "HS CODE 72, IRON AND STEEL"
level = "US Dollars"
#################################################################################
#These are functions used in the plot...
def growth_trade(foo):
# what this function does is take a dataframe and create a relative
return 100*((foo["china_exports"]/foo["china_exports"].shift(12)) - 1)
def cum_trade(foo):
outdf = pd.DataFrame([])
outdf["cuml_trade_2017"] = foo["china_exports"].loc["2017"].cumsum()
outdf.index = pd.date_range(start="2020-01-01", end="2020-12-01", freq = "MS")
outdf["cuml_trade_2020"] = foo["china_exports"].loc["2020"].cumsum()
return outdf
#################################################################################
# Then this makes the simple plots:
def make_plot():
height = int(1.15*533)
width = int(1.15*750)
foo = df.loc[product_select.value]
#foo = df.query("@a < a")
# below there is an object of selections which will be one of the values in
# the list of options. So the .value then grabs that particular option selected.
x = foo.index
if level_select.value == 'US Dollars':
y = foo['china_exports']
if level_select.value == 'Year over Year % Change':
y = growth_trade(foo)
if level_select.value == "Cumulative Purchases 2020 vs 2017":
cuml = cum_trade(foo)
x = cuml.index
y2017 = cuml["cuml_trade_2017"]
y2020 = cuml["cuml_trade_2020"]
title = "US Exports to China of " + product_select.value.title().upper()
if level_select.value != "Cumulative Purchases 2020 vs 2017":
# This is standard bokeh stuff so far
plot = figure(x_axis_type="datetime", plot_height = height, plot_width=width, toolbar_location = 'below',
tools = "box_zoom, reset, pan, xwheel_zoom", title = title,
x_range = (start_date,end_date) )
plot.line(x = x,
y = y, line_width=3.5, line_alpha=0.75, line_color = "slategray")
if level_select.value == "Cumulative Purchases 2020 vs 2017":
plot = figure(x_axis_type="datetime", plot_height = height, plot_width=width, toolbar_location = 'below',
tools = "box_zoom, reset, pan", title = title,
x_range = (dt.datetime(2020,1,1),dt.datetime(2021,2,1)) )
plot.line(x = x,
y = y2017, line_width=3.5, line_alpha=0.5, line_color = "red", line_dash = "dashed"
, legend_label= "2017")
plot.line(x = x,
y = y2020, line_width=3.5, line_alpha=0.75, line_color = "darkblue"
, legend_label= "2020")
plot.legend.title = 'Cumulative Purchases'
plot.legend.location = "top_left"
plot.legend.title_text_font_style = "bold"
# fixed attributes
plot.xaxis.axis_label = None
plot.yaxis.axis_label = ""
plot.axis.axis_label_text_font_style = "bold"
plot.grid.grid_line_alpha = 0.3
TIMETOOLTIPS = """
<div style="background-color:#F5F5F5; opacity: 0.95; border: 15px 15px 15px 15px;">
<div style = "text-align:left;">"""
if level_select.value == 'Year over Year % Change':
TIMETOOLTIPS = TIMETOOLTIPS + """
<span style="font-size: 13px; font-weight: bold"> $data_x{%b %Y}: $data_y{0}%</span>
</div>
</div>
"""
plot.add_tools(HoverTool(tooltips = TIMETOOLTIPS, line_policy='nearest', formatters={'$data_x': 'datetime'}))
if level_select.value == 'US Dollars':
TIMETOOLTIPS = TIMETOOLTIPS + """
<span style="font-size: 13px; font-weight: bold"> $data_x{%b %Y}: $data_y{$0.0a}</span>
</div>
</div>
"""
plot.add_tools(HoverTool(tooltips = TIMETOOLTIPS, line_policy='nearest', formatters={'$data_x': 'datetime'}))
if level_select.value == "Cumulative Purchases 2020 vs 2017":
#################################################################################
singlesource2020 = ColumnDataSource({
'xs': x.values,
'ys': y2020.values,
"dates": np.array(x),
})
c2020 = plot.circle(x="xs", y="ys", size=35,
source = singlesource2020, color = "crimson",alpha=0.0)
singlesource2017 = ColumnDataSource({
'xs': x.values,
'ys': y2017.values,
"dates": np.array(pd.date_range(start="2017-01-01", end="2017-12-01", freq = "MS")),
})
c2017 = plot.circle(x="xs", y="ys", size=35,
source = singlesource2017, color = "darkblue",alpha=0.0)
TIMETOOLTIPS = TIMETOOLTIPS + """
<span style="font-size: 13px; font-weight: bold"> @dates{%b %Y}: $data_y{$0.0a}</span>
</div>
</div>
"""
plot.add_tools(HoverTool(tooltips = TIMETOOLTIPS, line_policy='nearest', formatters={'@dates': 'datetime'}, renderers = [c2017,c2020]))
if level_select.value == 'Year over Year % Change':
if y.max() > 1500:
plot.y_range.end = 1500
plot.title.text_font_size = '13pt'
plot.background_fill_color = background
plot.background_fill_alpha = 0.75
plot.border_fill_color = background
tradewar_box = BoxAnnotation(left=dt.datetime(2018,7,1), right=dt.datetime(2019,10,11), fill_color='red', fill_alpha=0.1)
plot.add_layout(tradewar_box)
tradewar_box = BoxAnnotation(left=dt.datetime(2020,1,1), right=dt.datetime(2021,12,31), fill_color='blue', fill_alpha=0.1)
plot.add_layout(tradewar_box)
#p.yaxis.axis_label =
plot.yaxis.axis_label_text_font_style = 'bold'
plot.yaxis.axis_label_text_font_size = "13px"
plot.sizing_mode= "scale_both"
if level_select.value != 'Year over Year % Change':
plot.yaxis.formatter = NumeralTickFormatter(format="($0. a)")
plot.yaxis.axis_label = "US Dollars"
if level_select.value == 'Year over Year % Change':
plot.yaxis.axis_label = level_select.value
plot.max_height = height
plot.max_width = width
plot.min_height = int(0.25*height)
plot.min_width = int(0.25*width)
return plot
def update_plot(attrname, old, new):
layout.children[0] = make_plot()
# This part is still not clear to me. but it tells it what to update and where to put it
# so it updates the layout and [0] is the first option (see below there is a row with the
# first entry the plot, then the controls)
level_select = Select(value=level, title='Tranformations', options=['US Dollars', 'Year over Year % Change', "Cumulative Purchases 2020 vs 2017"])
level_select.on_change('value', update_plot)
#print(sorted(options))
product_select = Select(value=product, title='Product', options=sorted(options), width=400)
# This is the key thing that creates teh selection object
product_select.on_change('value', update_plot)
# Change the value upone selection via the update plot
div0 = Div(text = """Categories are at both the HS2 and HS4 level. Only Phase One covered products as defined in Annex 6-1 of The Agreement within that HS Code are shown. Red marks the period of Section 301 tariffs and retaliation. Blue is period of agreement.\n
\n
\n
""", width=400, background = background, style={"justify-content": "space-between", "display": "flex"} )
div1 = Div(text = """Transformations: US Dollars, year over year growth rate and cumulative purchases in 2017 vs 2020.\n The later transformation cumulates Chinese purchases over each month in 2017 and 2020 and compares each. Because 2017 is the benchmark year for The Agreement, this measure provides a sense, for each product category, China's progress towards meeting their purchase commitments.\n
""", width=400, background = background, style={"justify-content": "space-between", "display": "flex"} )
controls = column(product_select, div0, level_select, div1)
height = int(1.95*533)
width = int(1.95*675)
layout = row(make_plot(), controls, sizing_mode = "scale_height", max_height = height, max_width = width,
min_height = int(0.25*height), min_width = int(0.25*width))
curdoc().add_root(layout)
curdoc().title = "us-china-products"
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Blue is period of agreement.\n\n \n\n \n\n """\n , width=400, background=background, style={\'justify-content\':\n \'space-between\', \'display\': \'flex\'})\n', (8454, 8835), False, 'from bokeh.models import NumeralTickFormatter, Title, Label, Paragraph, Div, CustomJSHover, BoxAnnotation\n'), ((8838, 9347), 'bokeh.models.Div', 'Div', ([], {'text': '"""Transformations: US Dollars, year over year growth rate and cumulative purchases in 2017 vs 2020.\n The later transformation cumulates Chinese purchases over each month in 2017 and 2020 and compares each. 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alxpy/aiohttp-middlewares | aiohttp_middlewares/https.py | 377740d21cdaf3142523eb81b0cee4c6dd01f6b5 | """
================
HTTPS Middleware
================
Change scheme for current request when aiohttp application deployed behind
reverse proxy with HTTPS enabled.
Usage
=====
.. code-block:: python
from aiohttp import web
from aiohttp_middlewares import https_middleware
# Basic usage
app = web.Application(middlewares=[https_middleware()])
# Specify custom headers to match, not `X-Forwarded-Proto: https`
app = web.Application(
middlewares=https_middleware({"Forwarded": "https"})
)
"""
import logging
from aiohttp import web
from aiohttp.web_middlewares import _Handler, _Middleware
from .annotations import DictStrStr
DEFAULT_MATCH_HEADERS = {"X-Forwarded-Proto": "https"}
logger = logging.getLogger(__name__)
def https_middleware(match_headers: DictStrStr = None) -> _Middleware:
"""
Change scheme for current request when aiohttp application deployed behind
reverse proxy with HTTPS enabled.
This middleware is required to use, when your aiohttp app deployed behind
nginx with HTTPS enabled, after aiohttp discounted
``secure_proxy_ssl_header`` keyword argument in
https://github.com/aio-libs/aiohttp/pull/2299.
:param match_headers:
Dict of header(s) from reverse proxy to specify that aiohttp run behind
HTTPS. By default:
.. code-block:: python
{"X-Forwarded-Proto": "https"}
"""
@web.middleware
async def middleware(
request: web.Request, handler: _Handler
) -> web.StreamResponse:
"""Change scheme of current request when HTTPS headers matched."""
headers = DEFAULT_MATCH_HEADERS
if match_headers is not None:
headers = match_headers
matched = any(
request.headers.get(key) == value for key, value in headers.items()
)
if matched:
logger.debug(
"Substitute request URL scheme to https",
extra={
"headers": headers,
"request_headers": dict(request.headers),
},
)
request = request.clone(scheme="https")
return await handler(request)
return middleware
| [((736, 763), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (753, 763), False, 'import logging\n')] |
nohamanona/poke-auto-fuka | show/drawing.py | 9d355694efa0168738795afb403fc89264dcaeae | import cv2
import numpy as np
class DrawingClass(object):
def __init__(self):
self.draw_command ='None'
self.frame_count = 0
def drawing(self, frame, fps, num_egg, htc_egg, state):
cv2.putText(frame, 'FPS: {:.2f}'.format(fps),
(10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 0), thickness=2)
cv2.putText(frame, 'Possessed EGG: {}'.format(num_egg),
(10, 100), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 255), thickness=2)
cv2.putText(frame, 'Hatched EGG: {}'.format(htc_egg),
(10, 130), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 255), thickness=2)
cv2.putText(frame, 'State: {}'.format(state),
(250, 30), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 255), thickness=2)
return frame
def draw_controler(self, frame, command):
#print('draw',command)
if command =='LX MIN':
self.draw_command = 'LX MIN'
elif command =='LX MAX':
self.draw_command = 'LX MAX'
elif command =='LY MIN':
self.draw_command = 'LY MIN'
elif command =='LY MAX':
self.draw_command = 'LY MAX'
elif command =='Button A':
self.draw_command = 'Button A'
elif command =='Button B':
self.draw_command = 'Button B'
elif command =='Button X':
self.draw_command = 'Button X'
elif command =='Button Y':
self.draw_command = 'Button Y'
elif command =='HAT TOP':
self.draw_command = 'HAT TOP'
elif command =='HAT RIGHT':
self.draw_command = 'HAT RIGHT'
elif command =='HAT BOTTOM':
self.draw_command = 'HAT BOTTOM'
elif command =='HAT LEFT':
self.draw_command = 'HAT LEFT'
elif command =='Button START':
self.draw_command = 'Button START'
elif command =='STOP':
self.draw_command = 'STOP'
#stick
if self.draw_command =='LX MIN' or self.draw_command =='HAT LEFT':
cv2.circle(frame, (970, 490), 20, (0, 0, 255), thickness=-1)
elif self.draw_command =='LX MAX' or self.draw_command =='HAT RIGHT':
cv2.circle(frame, (1030, 490), 20, (0, 0, 255), thickness=-1)
elif self.draw_command =='LY MIN' or self.draw_command =='HAT TOP':
cv2.circle(frame, (1000, 460), 20, (0, 0, 255), thickness=-1)
elif self.draw_command =='LY MAX' or self.draw_command =='HAT BOTTOM':
cv2.circle(frame, (1000, 520), 20, (0, 0, 255), thickness=-1)
else:
cv2.circle(frame, (1000, 490), 20, (0, 0, 255), thickness=-1)
cv2.circle(frame, (1000, 490), 50, (0, 0, 255), thickness=2)
#button
if self.draw_command =='Button X':
cv2.circle(frame, (1180, 460), 15, (0, 0, 255), thickness=-1)
cv2.putText(frame, 'X',(1172, 468), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), thickness=2)
self.frame_count +=1
elif self.frame_count == 6:
cv2.circle(frame, (1180, 460), 15, (0, 0, 255), thickness=2)
cv2.putText(frame, 'X',(1172, 468), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), thickness=2)
self.frame_count =0
self.draw_command = 'None'
else:
cv2.circle(frame, (1180, 460), 15, (0, 0, 255), thickness=2)
cv2.putText(frame, 'X',(1172, 468), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), thickness=2)
if self.draw_command =='Button B':
cv2.circle(frame, (1180, 520), 15, (0, 0, 255), thickness=-1)
cv2.putText(frame, 'B',(1172, 528), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), thickness=2)
self.frame_count +=1
elif self.frame_count == 6:
cv2.circle(frame, (1180, 520), 15, (0, 0, 255), thickness=2)
cv2.putText(frame, 'B',(1172, 528), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), thickness=2)
self.frame_count =0
self.draw_command = 'None'
else:
cv2.circle(frame, (1180, 520), 15, (0, 0, 255), thickness=2)
cv2.putText(frame, 'B',(1172, 528), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), thickness=2)
if self.draw_command =='Button Y':
cv2.circle(frame, (1150, 490), 15, (0, 0, 255), thickness=-1)
cv2.putText(frame, 'Y',(1142, 498), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), thickness=2)
self.frame_count +=1
elif self.frame_count == 6:
cv2.circle(frame, (1150, 490), 15, (0, 0, 255), thickness=2)
cv2.putText(frame, 'Y',(1142, 498), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), thickness=2)
self.frame_count =0
self.draw_command = 'None'
else:
cv2.circle(frame, (1150, 490), 15, (0, 0, 255), thickness=2)
cv2.putText(frame, 'Y',(1142, 498), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), thickness=2)
if self.draw_command =='Button A':
cv2.circle(frame, (1210, 490), 15, (0, 0, 255), thickness=-1)
cv2.putText(frame, 'A',(1202, 498), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), thickness=2)
self.frame_count +=1
elif self.frame_count == 6:
cv2.circle(frame, (1210, 490), 15, (0, 0, 255), thickness=2)
cv2.putText(frame, 'A',(1202, 498), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), thickness=2)
self.frame_count =0
self.draw_command = 'None'
else:
cv2.circle(frame, (1210, 490), 15, (0, 0, 255), thickness=2)
cv2.putText(frame, 'A',(1202, 498), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), thickness=2)
if self.draw_command =='Button START':
cv2.circle(frame, (1130, 423), 10, (0, 0, 255), thickness=-1)
cv2.putText(frame, '+',(1120, 430), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), thickness=2)
self.frame_count +=1
elif self.frame_count == 6:
cv2.circle(frame, (1130, 423), 10, (0, 0, 255), thickness=1)
cv2.putText(frame, '+',(1120, 430), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), thickness=2)
self.frame_count =0
self.draw_command = 'None'
else:
cv2.circle(frame, (1130, 423), 10, (0, 0, 255), thickness=1)
cv2.putText(frame, '+',(1120, 430), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), thickness=2)
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YangTaoCN/IntroNeuralNetworks | backtest.py | 45b0311f85c9cdd9d3f0806e0059201e2655697f | import pandas_datareader.data as pdr
import yfinance as fix
import numpy as np
fix.pdr_override()
def back_test(strategy, seq_len, ticker, start_date, end_date, dim):
"""
A simple back test for a given date period
:param strategy: the chosen strategy. Note to have already formed the model, and fitted with training data.
:param seq_len: length of the days used for prediction
:param ticker: company ticker
:param start_date: starting date
:type start_date: "YYYY-mm-dd"
:param end_date: ending date
:type end_date: "YYYY-mm-dd"
:param dim: dimension required for strategy: 3dim for LSTM and 2dim for MLP
:type dim: tuple
:return: Percentage errors array that gives the errors for every test in the given date range
"""
data = pdr.get_data_yahoo(ticker, start_date, end_date)
stock_data = data["Adj Close"]
errors = []
for i in range((len(stock_data) // 10) * 10 - seq_len - 1):
x = np.array(stock_data.iloc[i: i + seq_len, 1]).reshape(dim) / 200
y = np.array(stock_data.iloc[i + seq_len + 1, 1]) / 200
predict = strategy.predict(x)
while predict == 0:
predict = strategy.predict(x)
error = (predict - y) / 100
errors.append(error)
total_error = np.array(errors)
print(f"Average error = {total_error.mean()}")
# If you want to see the full error list then print the following statement
# print(errors)
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jbueck/tespy | src/tespy/components/subsystems.py | dd7a2633ce12f33b4936ae902f4fe5df29191690 | # -*- coding: utf-8
"""Module for custom component groups.
It is possible to create subsystems of component groups in tespy. The subsystem
class is the base class for custom subsystems.
This file is part of project TESPy (github.com/oemof/tespy). It's copyrighted
by the contributors recorded in the version control history of the file,
available from its original location tespy/components/subsystems.py
SPDX-License-Identifier: MIT
"""
import logging
# %%
class subsystem:
r"""
Class subsystem is the base class of all TESPy subsystems.
Parameters
----------
label : str
The label of the subsystem.
Example
-------
Basic example for a setting up a tespy.components.subsystems.subsystem
object. This example does not run a tespy calculation!
>>> from tespy.components import subsystem
>>> mysub = subsystem('mySubsystem')
>>> type(mysub)
<class 'tespy.components.subsystems.subsystem'>
>>> mysub.get_attr('label')
'mySubsystem'
"""
def __init__(self, label):
if not isinstance(label, str):
msg = 'Subsystem label must be of type str!'
logging.error(msg)
raise ValueError(msg)
elif len([x for x in [';', ', ', '.'] if x in label]) > 0:
msg = 'Can\'t use ' + str([';', ', ', '.']) + ' in label.'
logging.error(msg)
raise ValueError(msg)
else:
self.label = label
self.comps = {}
self.conns = {}
self.create_comps()
self.create_conns()
def get_attr(self, key):
r"""
Get the value of a subsystem's attribute.
Parameters
----------
key : str
The attribute you want to retrieve.
Returns
-------
out :
Value of specified attribute.
"""
if key in self.__dict__:
return self.__dict__[key]
else:
msg = 'Subsystem ' + self.label + ' has no attribute ' + key + '.'
logging.error(msg)
raise KeyError(msg)
def create_comps(self):
"""Create the subsystem's components."""
return
def create_conns(self):
"""Create the subsystem's connections."""
return
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blefaudeux/fairscale | fairscale/optim/oss.py | aa5850107a37c7d5644b6079516e7ae1079ff5e8 | # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import copy
import logging
from typing import TYPE_CHECKING, Any, Callable, List, Optional, Type
import torch
import torch.distributed as dist
from torch.optim import SGD, Optimizer
from .utils import broadcast_object, recursive_copy_to_device
if TYPE_CHECKING:
from torch.optim.optimizer import _params_t
else:
_params_t = Any
class OSS(Optimizer):
"""Wraps an arbitrary :class:`optim.Optimizer <torch.optim.Optimizer>`
optimizer and shards its state as described by ZeRO_.
::
opt = OSS(params, optim=torch.optim.Adam, lr=0.01)
.. _ZeRO: https://arxiv.org/abs/1910.02054
Pipe combines pipeline parallelism with checkpointing to reduce peak
memory required to train while minimizing device under-utilization.
You should determine the balance when defining a :class:`Pipe` module, as
balancing will not be done automatically. The module will be partitioned
into multiple devices according to the given balance. You may rely on
heuristics to find your own optimal configuration.
Args:
params (list of tensors):
parameters to be optimized
Keyword Args:
optim (torch.nn.Optimizer):
optimizer to shard (default: SGD)
group (group):
torch.distributed group (default: group.WORLD)
"""
optim: Optimizer
in_super_constructor: bool
def __init__(
self,
params: _params_t,
optim: Type[Optimizer] = SGD,
group: Any = dist.group.WORLD,
**defaults: Any
):
self.in_super_constructor = True
super().__init__(params, defaults)
self.in_super_constructor = False
self.group = group
self.rank = dist.get_rank(group)
param_groups = self.partition_parameters()
self.optim = optim(param_groups[self.rank], **defaults)
# Optional consolidated optimizer state
self._global_state_dict = []
def partition_parameters(self) -> List[List[dict]]:
"""Partitions parameters across distributed ranks.
Returns a list of param_groups (which is a list of dict) where each
element of the list contains the param_groups for a rank. Element 0
corresponds to rank 0, etc. We need all the ranks for the broadcast
inside step().
"""
world_size = dist.get_world_size(self.group)
param_groups: List[List] = [list() for _ in range(world_size)]
sizes = [0] * world_size
for param_group in self.param_groups:
param_lists: List[List] = [list() for _ in range(world_size)]
for param in param_group["params"]:
# Add this param to rank with smallest size.
rank = sizes.index(min(sizes))
param_lists[rank].append(param)
sizes[rank] += param.numel()
for rank, params in enumerate(param_lists):
if len(params) > 0:
pg = copy.copy(param_group)
pg["params"] = params
param_groups[rank].append(pg)
return param_groups
def step(self, closure: Optional[Callable[[], float]] = None) -> Optional[float]:
loss = self.optim.step(closure=closure)
for rank, param_groups in enumerate(self.partition_parameters()):
for param_group in param_groups:
for param in param_group["params"]:
dist.broadcast(param, rank, group=self.group)
return loss
def state_dict(self) -> dict:
""" Gets this rank's state_dict. """
return self.optim.state_dict()
def _collect_state_dict(self) -> List[dict]:
"""
Collect all the state shards
"""
empty_buffer = torch.empty([1], dtype=torch.uint8)
global_optim_state = []
local_state = self.state_dict()
if len(local_state["state"]) == 0:
return []
for rank in range(dist.get_world_size(group=self.group)):
if rank == self.rank:
logging.info("Saving self state")
global_optim_state.append(
recursive_copy_to_device(
local_state, non_blocking=True, device=torch.device("cpu")
)
)
# Sync with other replicas
broadcast_object(empty_buffer, src_rank=rank)
else:
# Reuse the param_groups from this rank, these are shared across replicas
logging.info("Receiving state from rank %s ", rank)
replica_state = {
"state": broadcast_object(empty_buffer, src_rank=rank),
"param_groups": local_state["param_groups"],
}
# Fetch from the other replicas
global_optim_state.append(
recursive_copy_to_device(
replica_state, non_blocking=True, device=torch.device("cpu")
)
)
logging.info("State from rank %s received", rank)
return global_optim_state
def _broadcast_state_dict(self) -> None:
"""
Broadcast this rank's state shard, discard others
"""
empty_buffer = torch.empty([1], dtype=torch.uint8)
local_state = self.state_dict()
if len(local_state["state"]) == 0:
return
for rank in range(dist.get_world_size(group=self.group)):
if rank == self.rank:
# Send the state to the reference replica
logging.info(
"Sending the sharded SGD state to the reference replica from rank %s",
rank,
)
broadcast_object(local_state["state"], src_rank=rank)
else:
# Discard this tensor/rank, broadcast necessary for syncing
logging.info("Discarding broadcast from rank %s", rank)
broadcast_object(empty_buffer, src_rank=rank)
def consolidate_state_dict(self, recipient_rank: int = 0) -> List[dict]:
""" Update the consolidated state_dict list, one per rank.
This needs to be called on all replicas """
if self.rank == recipient_rank:
# Pull the sharded state from all the other replicas
# Store all the states in order, rank by rank
logging.info("Pulling the sharded SGD state from all replicas")
self._global_state_dict = self._collect_state_dict()
else:
# Acknowledge broadcasts, and send this rank's shard when needed
self._broadcast_state_dict()
@property
def global_state_dict(self):
"""
Return the last known global optimizer state, which consist of a list of the shards.
NOTE: This is limited to the replica which was responsible for the consolidation.
The state may also not be up to date, depending on when `consolidate_state_dict` was last called
"""
assert (
len(self._global_state_dict) > 0
), "The optimizer state is not materialized, please call consolidate_state_dict on every replica beforehand"
return self._global_state_dict
def load_state_dict(self, state_dict: dict) -> None:
""" Loads this rank's state_dict. """
self.optim.load_state_dict(state_dict)
def add_param_group(self, param_group: dict) -> None:
super().add_param_group(param_group)
if not self.in_super_constructor:
param_groups = self.partition_parameters()[self.rank]
if len(param_groups) == len(self.optim.param_groups) + 1:
self.optim.add_param_group(param_groups[-1])
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ninezerozeronine/raytracing-one-weekend | setup.py | 22ca36dcec679cbd78a7711734ca22e01ef06ef2 | from setuptools import setup, find_packages
setup(
name="raytracing-one-weekend",
version="0.0.0",
author="Andy Palmer",
author_email="contactninezerozeronine@gmail.com",
description="A raytracer achievable in a weekend.",
url="https://github.com/ninezerozeronine/raytracing-one-weekend",
install_requires=[
"Pillow",
"numpy",
],
packages=find_packages('src'),
package_dir={'': 'src'},
)
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r0kym/SNI-backend | homepage/urls.py | 5fdc25df21846fadb313d439acba73782a6248c3 | """
URLconf of the homepage
"""
from django.urls import path, include
from . import views
urlpatterns = [
path('', views.home, name='home'),
path('auth', views.auth, name='auth'),
path('auth/public', views.auth_public, name='auth-public'),
path('auth/full', views.auth_full, name='auth-full'),
path('auth/invite', views.auth_invite, name='auth-invite'),
path('callback/sni', views.sni_callback, name='sni_callback'),
path('logout', views.logout, name='logout'),
path('403', views.no_perm, name='no-permission'),
path('404', views.not_found, name='not-found'),
]
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mas90/srcf-python | srcflib/email/__init__.py | 09ce45c65d2ddbec2cdfc559a7b5983398dbdfa0 | """
Notification email machinery, for tasks to send credentials and instructions to users.
Email templates placed inside the `templates` directory of this module should:
- extend from `layout`
- provide `subject` and `body` blocks
"""
from enum import Enum
import os.path
from jinja2 import Environment, FileSystemLoader
from sqlalchemy.orm import Session as SQLASession
from srcf.database import Member, Society
from srcf.mail import send_mail
from ..plumbing import Owner, owner_desc, owner_name, owner_website
ENV = Environment(loader=FileSystemLoader(os.path.join(os.path.dirname(__file__), "templates")),
trim_blocks=True, lstrip_blocks=True)
ENV.filters.update({"is_member": lambda mem: isinstance(mem, Member),
"is_society": lambda soc: isinstance(soc, Society),
"owner_name": owner_name,
"owner_desc": owner_desc,
"owner_website": owner_website})
CURRENT_WRAPPER = None
class Layout(Enum):
"""
Base layout template to be inherited by an email-specific template.
"""
SUBJECT = "/common/subject.j2"
"""
Subject line of the email.
"""
BODY = "/common/body.j2"
"""
Main content of the email.
"""
class EmailWrapper:
"""
Context manager for email sending, used to augment emails with additional metadata.
"""
def __init__(self, subject: str = None, body: str = None, context: dict = None):
self._layouts = {Layout.SUBJECT: subject,
Layout.BODY: body}
self._context = context
def render(self, template: str, layout: Layout, target: Owner, context: dict = None):
"""
Render an email template with Jinja using the provided context.
"""
context = dict(context or (), layout=layout.value, target=target)
out = ENV.get_template(template).render(context)
custom = self._layouts.get(layout)
if custom:
if self._context:
context.update(self._context)
out = custom.format(out, **context)
if layout == Layout.SUBJECT:
out = " ".join(out.split())
return out
def __enter__(self):
global CURRENT_WRAPPER
if CURRENT_WRAPPER:
raise RuntimeError("Another context is already active")
CURRENT_WRAPPER = self
def __exit__(self, exception_type, exception_value, traceback):
global CURRENT_WRAPPER
CURRENT_WRAPPER = None
DEFAULT_WRAPPER = EmailWrapper(subject="[SRCF] {}")
def send(target: Owner, template: str, context: dict = None, session: SQLASession = None):
"""
Render and send an email to the target member or society.
"""
wrapper = CURRENT_WRAPPER or DEFAULT_WRAPPER
subject = wrapper.render(template, Layout.SUBJECT, target, context)
body = wrapper.render(template, Layout.BODY, target, context)
recipient = (owner_desc(target, True), target.email)
send_mail(recipient, subject, body, copy_sysadmins=False, session=session)
| [((2983, 3057), 'srcf.mail.send_mail', 'send_mail', (['recipient', 'subject', 'body'], {'copy_sysadmins': '(False)', 'session': 'session'}), '(recipient, subject, body, copy_sysadmins=False, session=session)\n', (2992, 3057), False, 'from srcf.mail import send_mail\n')] |
dolfandringa/PythonProjectStructureDemo | nose2_example/my_package/myapp.py | 8bdd72b94d3b830e9e9dce548cca1cdb16601d0d | from .operations import Multiply, Add, Substract
class MyApp(object):
def __init__(self):
self.operations={'multiply': Multiply,
'add': Add,
'substract': Substract}
def do(self, operation, number1, number2):
return self.operations[operation.lower()].do(number1, number2)
| [] |