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CPU Upgrade
Jan Mühlnikel
commited on
Commit
•
c8e0175
1
Parent(s):
21b6daa
added single matching result table
Browse files- __pycache__/similarity_page.cpython-310.pyc +0 -0
- functions/__pycache__/calc_matches.cpython-310.pyc +0 -0
- functions/__pycache__/single_similar.cpython-310.pyc +0 -0
- functions/single_similar.py +15 -0
- modules/{result_table.py → multimatch_result_table.py} +1 -2
- modules/singlematch_result_table.py +83 -0
- similarity_page.py +12 -2
__pycache__/similarity_page.cpython-310.pyc
CHANGED
Binary files a/__pycache__/similarity_page.cpython-310.pyc and b/__pycache__/similarity_page.cpython-310.pyc differ
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functions/__pycache__/calc_matches.cpython-310.pyc
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Binary files a/functions/__pycache__/calc_matches.cpython-310.pyc and b/functions/__pycache__/calc_matches.cpython-310.pyc differ
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functions/__pycache__/single_similar.cpython-310.pyc
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Binary file (675 Bytes). View file
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functions/single_similar.py
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@@ -0,0 +1,15 @@
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import pandas as pd
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import numpy as np
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def find_similar(p_index, similarity_matrix, projects_df, top_x):
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selected_row = similarity_matrix[p_index]
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top_indexes = np.argsort(selected_row)[-10:][::-1]
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top_values = selected_row[top_indexes]
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top_projects_df = projects_df.iloc[top_indexes]
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top_projects_df["similarity"] = top_values
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return top_projects_df
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modules/{result_table.py → multimatch_result_table.py}
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@@ -1,8 +1,7 @@
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import streamlit as st
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-
from st_aggrid import AgGrid, GridOptionsBuilder
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import pandas as pd
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-
def
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st.write("------------------")
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p1_df = p1_df.reset_index(drop=True)
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import streamlit as st
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import pandas as pd
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def show_multi_table(p1_df, p2_df):
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st.write("------------------")
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p1_df = p1_df.reset_index(drop=True)
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modules/singlematch_result_table.py
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@@ -0,0 +1,83 @@
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import streamlit as st
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import pandas as pd
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def show_single_table(result_df):
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result_df = result_df.reset_index(drop=True)
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# Transformations
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result_df["crs_3_code_list"] = result_df['crs_3_code'].str.split(";").apply(lambda x: x[:-1] if x else [])
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result_df["crs_5_code_list"] = result_df['crs_5_code'].str.split(";").apply(lambda x: x[:-1] if x else [])
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result_df["sdg_list"] = result_df['sgd_pred_code'].apply(lambda x: [x] if pd.notna(x) else [])
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result_df["flag"] = result_df['country'].apply(lambda x: f"https://flagicons.lipis.dev/flags/4x3/{x[:2].lower()}.svg" if pd.notna(x) else "https://flagicons.lipis.dev/flags/4x3/xx.svg")
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st.dataframe(
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result_df[["similarity", "iati_id", "title_main", "orga_abbreviation", "client", "description_main", "country", "flag", "sdg_list", "crs_3_code_list", "crs_5_code_list"]],
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use_container_width = True,
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height = 35 + 35 * len(result_df),
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column_config={
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"similarity": st.column_config.TextColumn(
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"Similarity",
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help="similarity to selected project",
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disabled=True,
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width="small"
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),
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"iati_id": st.column_config.TextColumn(
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"IATI ID",
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help="IATI Project ID",
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disabled=True,
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width="small"
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),
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"orga_abbreviation": st.column_config.TextColumn(
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"Organization",
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help="If description not in English, description in other language provided",
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disabled=True,
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width="small"
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),
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"client": st.column_config.TextColumn(
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"Client",
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help="Client organization of customer",
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disabled=True,
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width="small"
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),
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"title_main": st.column_config.TextColumn(
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"Title",
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help="If title not in English, title in other language provided",
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disabled=True,
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width="large"
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),
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"description_main": st.column_config.TextColumn(
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"Description",
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help="If description not in English, description in other language provided",
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disabled=True,
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width="large"
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),
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"country": st.column_config.TextColumn(
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"Country",
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help="Country of project",
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disabled=True,
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width="small"
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),
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"flag": st.column_config.ImageColumn(
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"Flag",
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help="country flag",
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width="small"
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),
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"sdg_list": st.column_config.ListColumn(
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"SDG Prediction",
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help="Prediction of SDG's",
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width="small"
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),
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"crs_3_code_list": st.column_config.ListColumn(
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"CRS 3",
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help="CRS 3 code given by organization",
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width="small"
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),
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"crs_5_code_list": st.column_config.ListColumn(
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"CRS 5",
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help="CRS 5 code given by organization",
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width="small"
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),
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},
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hide_index=True,
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)
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similarity_page.py
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@@ -10,10 +10,12 @@ import pandas as pd
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from scipy.sparse import load_npz
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import pickle
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from sentence_transformers import SentenceTransformer
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from modules.
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from functions.filter_projects import filter_projects
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from functions.calc_matches import calc_matches
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from functions.same_country_filter import same_country_filter
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import psutil
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import os
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import gc
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p1_df, p2_df = calc_matches(filtered_df, compare_df, sim_matrix, TOP_X_PROJECTS)
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# SHOW THE RESULT
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-
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del p1_df, p2_df
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else:
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st.write("Select at least on CRS 3, SDG or type in a query")
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placeholder = " ",
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options = search_list,
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)
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from scipy.sparse import load_npz
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import pickle
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from sentence_transformers import SentenceTransformer
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from modules.multimatch_result_table import show_multi_table
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from modules.singlematch_result_table import show_single_table
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from functions.filter_projects import filter_projects
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from functions.calc_matches import calc_matches
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from functions.same_country_filter import same_country_filter
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from functions.single_similar import find_similar
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import psutil
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import os
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import gc
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p1_df, p2_df = calc_matches(filtered_df, compare_df, sim_matrix, TOP_X_PROJECTS)
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# SHOW THE RESULT
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show_multi_table(p1_df, p2_df)
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del p1_df, p2_df
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else:
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st.write("Select at least on CRS 3, SDG or type in a query")
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placeholder = " ",
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options = search_list,
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)
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if project_option:
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selected_index = search_list.index(project_option)
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top_projects_df = find_similar(selected_index, sim_matrix, projects_df, 10)
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show_single_table(top_projects_df)
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