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Fri  1 Nov 15:55:16 GMT 2024 > Generating peptides on cn080
GNU bash, version 4.4.20(1)-release (x86_64-redhat-linux-gnu)
Copyright (C) 2016 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>

This is free software; you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.
Fri  1 Nov 15:55:16 GMT 2024 > Running /camp/apps/eb/software/Anaconda3/2023.03/bin/python : Python 3.10.10
Fri  1 Nov 15:55:16 GMT 2024 > Using Conda from .
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Fri  1 Nov 15:55:16 GMT 2024 > Seed = 1; length = 10; max. number = 100000000; slice = 14000000 to 15000000; output dir. = 20241101_peptides_6-12x100M
Fri  1 Nov 15:55:16 GMT 2024 > There are 10240000000000 peptides of length 10; generating 100000000 (0.000976563 %)
Fri  1 Nov 15:55:16 GMT 2024 > Saving a slice to 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz...
+ schemist enumerate --seed 1 --max-length 10 --prefix GY --suffix CGSGSGS --number 9.76563e-06 --slice 14000000 15000000
+ schemist convert --column cysteine_to_N_cyclization --to id inchikey scaffold mwt clogp tpsa --prefix cyclic_ --options prefix=SCB-
+ gzip --best
+ schemist react --column SMILES --reaction cysteine_to_N_cyclization
+ schemist split --type random --train 0.7 --test 0.15 --column cysteine_to_N_cyclization --seed 1
+ tr '	' ,
+ schemist convert --column SMILES --to id inchikey scaffold mwt clogp tpsa --prefix linear_ --options prefix=SCB-
🚀 Converting between string representations with the following parameters:
	subcommand: convert
	output: <_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>
	format: None
	input: <_io.TextIOWrapper name='<stdin>' mode='r' encoding='utf-8'>
	representation: SMILES
	column: SMILES
	prefix: linear_
	to: ['id', 'inchikey', 'scaffold', 'mwt', 'clogp', 'tpsa']
	options: ['prefix=SCB-']
	func: <function _convert at 0x7f272e0cb240>
🚀 Splitting table with the following parameters:
	subcommand: split
	output: <_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>
	format: None
	input: <_io.TextIOWrapper name='<stdin>' mode='r' encoding='utf-8'>
	representation: SMILES
	column: cysteine_to_N_cyclization
	prefix: None
	type: random
	train: 0.7
	test: 0.15
	seed: 1
	func: <function _split at 0x7f5fb37f74c0>
🚀 Enumerating peptides with the following parameters:
	subcommand: enumerate
	output: <_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>
	format: None
	to: SMILES
	options: None
	alphabet: GALVITSMCPFYWHKRDENQ
	max_length: 10
	min_length: None
	number: 9.76563e-06
	slice: ['14000000', '15000000']
	seed: 1
	prefix: GY
	suffix: CGSGSGS
	type: aa
	d_aa_only: False
	include_d_aa: False
	func: <function _enum at 0x7f2ed6333880>
Sampling 100000051 (0.000976562998046875 %) peptides from length 10 to 10 (10240000000000 combinations). Probability of collision if drawing randomly is 1.0, with 976.9924758407456 (0.000976991977574837 %) collisions on average.
> Executing naive sampling. 
🚀 Reacting peptides with the following parameters:
	subcommand: react
	output: <_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>
	format: None
	input: <_io.TextIOWrapper name='<stdin>' mode='r' encoding='utf-8'>
	representation: SMILES
	column: SMILES
	name: None
	reaction: ['cysteine_to_N_cyclization']
	func: <function _react at 0x7f6d9358b9c0>
🚀 Converting between string representations with the following parameters:
	subcommand: convert
	output: <_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>
	format: None
	input: <_io.TextIOWrapper name='<stdin>' mode='r' encoding='utf-8'>
	representation: SMILES
	column: cysteine_to_N_cyclization
	prefix: cyclic_
	to: ['id', 'inchikey', 'scaffold', 'mwt', 'clogp', 'tpsa']
	options: ['prefix=SCB-']
	func: <function _convert at 0x7faece25b240>

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819it [14:43,  1.01s/it]
820it [14:44,  1.01s/it]
821it [14:45,  1.01s/it]
822it [14:46,  1.01s/it]
823it [14:47,  1.01s/it]
824it [14:48,  1.02s/it]
825it [14:49,  1.02s/it]
826it [14:50,  1.01s/it]
827it [14:51,  1.01s/it]
828it [14:52,  1.00s/it]
829it [14:53,  1.00it/s]
830it [14:54,  1.00s/it]
831it [14:55,  1.00s/it]
832it [14:56,  1.00s/it]
833it [14:57,  1.01s/it]
834it [14:58,  1.01s/it]
835it [14:59,  1.01s/it]
836it [15:00,  1.01s/it]
837it [15:01,  1.00s/it]
838it [15:02,  1.00s/it]
839it [15:03,  1.00it/s]
840it [15:04,  1.00s/it]
841it [15:05,  1.01s/it]
842it [15:06,  1.00s/it]
843it [15:07,  1.00s/it]
844it [15:08,  1.00it/s]
845it [15:09,  1.00it/s]
846it [15:10,  1.00it/s]
847it [15:11,  1.00it/s]
848it [15:12,  1.01it/s]
849it [15:13,  1.01it/s]
850it [15:14,  1.01it/s]
851it [15:15,  1.01it/s]
852it [15:16,  1.01it/s]
853it [15:17,  1.02it/s]
854it [15:18,  1.01it/s]
855it [15:19,  1.01it/s]
856it [15:20,  1.00it/s]
857it [15:21,  1.00it/s]
858it [15:22,  1.01it/s]
859it [15:23,  1.00it/s]
860it [15:24,  1.00it/s]
861it [15:25,  1.01it/s]
862it [15:26,  1.01it/s]
863it [15:27,  1.02it/s]
864it [15:28,  1.01it/s]
865it [15:29,  1.01it/s]
866it [15:30,  1.01it/s]
867it [15:31,  1.00it/s]
868it [15:32,  1.00s/it]
869it [15:33,  1.00it/s]
870it [15:34,  1.01it/s]
871it [15:35,  1.01it/s]
872it [15:36,  1.00it/s]
873it [15:37,  1.00s/it]
874it [15:38,  1.01s/it]
875it [15:39,  1.00s/it]
876it [15:40,  1.00s/it]
877it [15:41,  1.00s/it]
878it [15:42,  1.01s/it]
879it [15:43,  1.01s/it]
880it [15:44,  1.01s/it]
881it [15:45,  1.00s/it]
882it [15:46,  1.00it/s]
883it [15:47,  1.00it/s]
884it [15:48,  1.01it/s]
885it [15:49,  1.01it/s]
886it [15:50,  1.00it/s]
887it [15:51,  1.00s/it]
888it [15:52,  1.00it/s]
889it [15:53,  1.00it/s]
890it [15:54,  1.00it/s]
891it [15:55,  1.00s/it]
892it [15:56,  1.00s/it]
893it [15:57,  1.00s/it]
894it [15:58,  1.00s/it]
895it [15:59,  1.01s/it]
896it [16:00,  1.02s/it]
897it [16:01,  1.02s/it]
898it [16:02,  1.02s/it]
899it [16:03,  1.02s/it]
900it [16:04,  1.03s/it]
901it [16:05,  1.03s/it]
902it [16:06,  1.03s/it]
903it [16:07,  1.03s/it]
904it [16:08,  1.03s/it]
905it [16:09,  1.02s/it]
906it [16:10,  1.02s/it]
907it [16:11,  1.02s/it]
908it [16:12,  1.02s/it]
909it [16:14,  1.02s/it]
910it [16:15,  1.02s/it]
911it [16:16,  1.03s/it]
912it [16:17,  1.03s/it]
913it [16:18,  1.04s/it]
914it [16:19,  1.05s/it]
915it [16:20,  1.06s/it]
916it [16:21,  1.05s/it]
917it [16:22,  1.04s/it]
918it [16:23,  1.03s/it]
919it [16:24,  1.02s/it]
920it [16:25,  1.02s/it]
921it [16:26,  1.02s/it]
922it [16:27,  1.03s/it]
923it [16:28,  1.03s/it]
924it [16:29,  1.03s/it]
925it [16:30,  1.03s/it]
926it [16:31,  1.03s/it]
927it [16:32,  1.03s/it]
928it [16:33,  1.02s/it]
929it [16:34,  1.02s/it]
930it [16:35,  1.03s/it]
931it [16:36,  1.03s/it]
932it [16:37,  1.02s/it]
933it [16:38,  1.02s/it]
934it [16:39,  1.03s/it]
935it [16:40,  1.03s/it]
936it [16:41,  1.02s/it]
937it [16:42,  1.01s/it]
938it [16:43,  1.02s/it]
939it [16:44,  1.02s/it]
940it [16:45,  1.03s/it]
941it [16:46,  1.03s/it]
942it [16:47,  1.03s/it]
943it [16:48,  1.02s/it]
944it [16:49,  1.03s/it]
945it [16:51,  1.03s/it]
946it [16:52,  1.03s/it]
947it [16:53,  1.04s/it]
948it [16:54,  1.04s/it]
949it [16:55,  1.05s/it]
950it [16:56,  1.05s/it]
951it [16:57,  1.04s/it]
952it [16:58,  1.02s/it]
953it [16:59,  1.02s/it]
954it [17:00,  1.02s/it]
955it [17:01,  1.01s/it]
956it [17:02,  1.00s/it]
957it [17:03,  1.01s/it]
958it [17:04,  1.01s/it]
959it [17:05,  1.00s/it]
960it [17:06,  1.00s/it]
961it [17:07,  1.01s/it]
962it [17:08,  1.01s/it]
963it [17:09,  1.00s/it]
964it [17:10,  1.01it/s]
965it [17:11,  1.00it/s]
966it [17:12,  1.00it/s]
967it [17:13,  1.00it/s]
968it [17:14,  1.00it/s]
969it [17:15,  1.00s/it]
970it [17:16,  1.00it/s]
971it [17:17,  1.01it/s]
972it [17:18,  1.01it/s]
973it [17:19,  1.01it/s]
974it [17:20,  1.00s/it]
975it [17:21,  1.01s/it]
976it [17:22,  1.01s/it]
977it [17:23,  1.01s/it]
978it [17:24,  1.01s/it]
979it [17:25,  1.01s/it]
980it [17:26,  1.01s/it]
981it [17:27,  1.00s/it]
982it [17:28,  1.01s/it]
983it [17:29,  1.01s/it]
984it [17:30,  1.02s/it]
985it [17:31,  1.02s/it]
986it [17:32,  1.02s/it]
987it [17:33,  1.03s/it]
988it [17:34,  1.03s/it]
989it [17:35,  1.02s/it]
990it [17:36,  1.01s/it]
991it [17:37,  1.01s/it]
992it [17:38,  1.02s/it]
993it [17:39,  1.02s/it]
994it [17:40,  1.03s/it]
995it [17:41,  1.03s/it]
996it [17:42,  1.03s/it]
997it [17:43,  1.03s/it]
998it [17:44,  1.03s/it]
999it [17:45,  1.02s/it]
1000it [17:46,  1.01s/it]
1000it [17:46,  1.07s/it]
Enumerated peptides:
	Number of peptides: 1000000
Conversion errors:
	SMILES: 0Completed process in 0:17:46.756938

0it [00:00, ?it/s]
1it [00:11, 11.36s/it]
2it [00:22, 11.13s/it]
3it [00:33, 11.08s/it]
4it [00:44, 11.08s/it]
5it [00:55, 11.09s/it]
6it [01:06, 11.15s/it]
7it [01:17, 11.09s/it]
8it [01:28, 11.04s/it]
9it [01:39, 10.88s/it]
10it [01:50, 10.87s/it]
11it [02:00, 10.86s/it]
12it [02:11, 10.86s/it]
13it [02:22, 10.85s/it]
14it [02:33, 10.88s/it]
15it [02:44, 10.94s/it]
16it [02:55, 10.94s/it]
17it [03:06, 10.94s/it]
18it [03:17, 10.99s/it]
19it [03:28, 11.01s/it]
20it [03:39, 11.00s/it]
21it [03:50, 10.96s/it]
22it [04:01, 10.95s/it]
23it [04:12, 10.94s/it]
24it [04:23, 10.94s/it]
25it [04:34, 10.98s/it]
26it [04:45, 11.00s/it]
27it [04:56, 11.03s/it]
28it [05:07, 11.06s/it]
29it [05:18, 11.14s/it]
30it [05:30, 11.15s/it]
31it [05:41, 11.14s/it]
32it [05:52, 11.08s/it]
33it [06:03, 11.07s/it]
34it [06:14, 11.08s/it]
35it [06:25, 11.08s/it]
36it [06:36, 11.08s/it]
37it [06:47, 11.05s/it]
38it [06:58, 11.05s/it]
39it [07:09, 11.04s/it]
40it [07:20, 11.05s/it]
41it [07:31, 11.07s/it]
42it [07:42, 11.08s/it]
43it [07:53, 11.06s/it]
44it [08:04, 11.04s/it]
45it [08:15, 11.01s/it]
46it [08:26, 11.01s/it]
47it [08:37, 11.00s/it]
48it [08:48, 10.98s/it]
49it [08:59, 10.96s/it]
50it [09:10, 11.00s/it]
51it [09:21, 10.97s/it]
52it [09:32, 10.98s/it]
53it [09:43, 10.98s/it]
54it [09:54, 10.97s/it]
55it [10:05, 10.98s/it]
56it [10:16, 10.95s/it]
57it [10:27, 10.93s/it]
58it [10:38, 10.96s/it]
59it [10:49, 10.94s/it]
60it [11:00, 10.93s/it]
61it [11:10, 10.89s/it]
62it [11:21, 10.87s/it]
63it [11:32, 10.87s/it]
64it [11:43, 10.89s/it]
65it [11:54, 10.92s/it]
66it [12:05, 10.87s/it]
67it [12:16, 10.89s/it]
68it [12:27, 10.90s/it]
69it [12:38, 10.90s/it]
70it [12:49, 10.94s/it]
71it [13:00, 10.94s/it]
72it [13:10, 10.91s/it]
73it [13:21, 10.90s/it]
74it [13:32, 10.86s/it]
75it [13:43, 10.87s/it]
76it [13:54, 10.87s/it]
77it [14:05, 10.83s/it]
78it [14:15, 10.76s/it]
79it [14:26, 10.74s/it]
80it [14:37, 10.72s/it]
81it [14:47, 10.75s/it]
82it [14:58, 10.73s/it]
83it [15:09, 10.72s/it]
84it [15:19, 10.72s/it]
85it [15:30, 10.71s/it]
86it [15:41, 10.73s/it]
87it [15:52, 10.78s/it]
88it [16:03, 10.81s/it]
89it [16:13, 10.79s/it]
90it [16:24, 10.79s/it]
91it [16:35, 10.81s/it]
92it [16:46, 10.82s/it]
93it [16:57, 10.83s/it]
94it [17:08, 10.83s/it]
95it [17:18, 10.80s/it]
96it [17:29, 10.81s/it]
97it [17:40, 10.77s/it]
98it [17:51, 10.80s/it]
99it [18:02, 10.82s/it]
100it [18:12, 10.83s/it]
101it [18:23, 10.80s/it]
102it [18:34, 10.79s/it]
103it [18:45, 10.81s/it]
104it [18:56, 10.78s/it]
105it [19:06, 10.78s/it]
106it [19:17, 10.73s/it]
107it [19:28, 10.72s/it]
108it [19:38, 10.75s/it]
109it [19:49, 10.74s/it]
110it [20:00, 10.77s/it]
111it [20:11, 10.83s/it]
112it [20:22, 10.85s/it]
113it [20:33, 10.83s/it]
114it [20:43, 10.77s/it]
115it [20:54, 10.78s/it]
116it [21:05, 10.79s/it]
117it [21:15, 10.75s/it]
118it [21:26, 10.76s/it]
119it [21:37, 10.74s/it]
120it [21:48, 10.73s/it]
121it [21:58, 10.72s/it]
122it [22:09, 10.75s/it]
123it [22:20, 10.78s/it]
124it [22:31, 10.74s/it]
125it [22:41, 10.74s/it]
126it [22:52, 10.71s/it]
127it [23:03, 10.71s/it]
128it [23:14, 10.73s/it]
129it [23:24, 10.72s/it]
130it [23:35, 10.72s/it]
131it [23:46, 10.85s/it]
132it [23:57, 10.92s/it]
133it [24:08, 10.93s/it]
134it [24:19, 11.03s/it]
135it [24:31, 11.11s/it]
136it [24:42, 11.10s/it]
137it [24:53, 11.12s/it]
138it [25:04, 11.11s/it]
139it [25:15, 11.16s/it]
140it [25:27, 11.16s/it]
141it [25:38, 11.20s/it]
142it [25:49, 11.15s/it]
143it [26:00, 11.11s/it]
144it [26:11, 11.07s/it]
145it [26:22, 11.02s/it]
146it [26:33, 11.07s/it]
147it [26:44, 11.08s/it]
148it [26:55, 11.11s/it]
149it [27:06, 11.07s/it]
150it [27:17, 11.04s/it]
151it [27:28, 11.04s/it]
152it [27:39, 11.02s/it]
153it [27:50, 11.04s/it]
154it [28:01, 11.03s/it]
155it [28:12, 11.01s/it]
156it [28:23, 10.99s/it]
157it [28:34, 10.96s/it]
158it [28:45, 10.95s/it]
159it [28:56, 10.98s/it]
160it [29:07, 11.01s/it]
161it [29:18, 11.05s/it]
162it [29:29, 11.03s/it]
163it [29:40, 10.99s/it]
164it [29:51, 10.92s/it]
165it [30:02, 10.89s/it]
166it [30:13, 10.92s/it]
167it [30:24, 10.99s/it]
168it [30:35, 11.00s/it]
169it [30:46, 10.98s/it]
170it [30:57, 10.96s/it]
171it [31:08, 10.92s/it]
172it [31:18, 10.92s/it]
173it [31:30, 10.96s/it]
174it [31:41, 11.02s/it]
175it [31:52, 10.96s/it]
176it [32:02, 10.94s/it]
177it [32:13, 10.92s/it]
178it [32:24, 10.91s/it]
179it [32:35, 10.93s/it]
180it [32:46, 10.94s/it]
181it [32:57, 11.00s/it]
182it [33:08, 10.94s/it]
183it [33:19, 10.88s/it]
184it [33:30, 10.82s/it]
185it [33:40, 10.83s/it]
186it [33:51, 10.88s/it]
187it [34:02, 10.88s/it]
188it [34:13, 10.94s/it]
189it [34:24, 10.99s/it]
190it [34:35, 10.94s/it]
191it [34:46, 10.93s/it]
192it [34:57, 10.94s/it]
193it [35:08, 10.91s/it]
194it [35:19, 10.95s/it]
195it [35:30, 10.97s/it]
196it [35:41, 10.94s/it]
197it [35:52, 10.89s/it]
198it [36:03, 10.91s/it]
199it [36:14, 10.92s/it]
200it [36:24, 10.89s/it]
201it [36:35, 10.93s/it]
202it [36:46, 10.97s/it]
203it [36:57, 10.97s/it]
204it [37:08, 10.91s/it]
205it [37:19, 10.88s/it]
206it [37:30, 10.87s/it]
207it [37:41, 10.85s/it]
208it [37:52, 10.88s/it]
209it [38:03, 10.93s/it]
210it [38:14, 10.91s/it]
211it [38:24, 10.89s/it]
212it [38:35, 10.85s/it]
213it [38:46, 10.86s/it]
214it [38:57, 10.88s/it]
215it [39:08, 10.91s/it]
216it [39:19, 10.95s/it]
217it [39:30, 10.90s/it]
218it [39:41, 10.87s/it]
219it [39:51, 10.85s/it]
220it [40:02, 10.85s/it]
221it [40:13, 10.82s/it]
222it [40:24, 10.85s/it]
223it [40:35, 10.82s/it]
224it [40:45, 10.77s/it]
225it [40:56, 10.77s/it]
226it [41:07, 10.76s/it]
227it [41:17, 10.72s/it]
228it [41:28, 10.74s/it]
229it [41:39, 10.81s/it]
230it [41:50, 10.84s/it]
231it [42:01, 10.78s/it]
232it [42:11, 10.76s/it]
233it [42:22, 10.75s/it]
234it [42:33, 10.75s/it]
235it [42:44, 10.77s/it]
236it [42:55, 10.84s/it]
237it [43:06, 10.86s/it]
238it [43:16, 10.84s/it]
239it [43:27, 10.84s/it]
240it [43:38, 10.84s/it]
241it [43:49, 10.83s/it]
242it [44:00, 10.88s/it]
243it [44:11, 10.88s/it]
244it [44:22, 10.86s/it]
245it [44:32, 10.85s/it]
246it [44:43, 10.82s/it]
247it [44:54, 10.82s/it]
248it [45:05, 10.88s/it]
249it [45:16, 10.93s/it]
250it [45:27, 10.93s/it]
251it [45:38, 10.88s/it]
252it [45:48, 10.84s/it]
253it [45:59, 10.83s/it]
254it [46:10, 10.83s/it]
255it [46:21, 10.86s/it]
256it [46:32, 10.88s/it]
257it [46:43, 10.85s/it]
258it [46:54, 10.82s/it]
259it [47:04, 10.83s/it]
260it [47:15, 10.81s/it]
261it [47:26, 10.83s/it]
262it [47:37, 10.87s/it]
263it [47:48, 10.89s/it]
264it [47:59, 10.83s/it]
265it [48:09, 10.80s/it]
266it [48:20, 10.78s/it]
267it [48:31, 10.79s/it]
268it [48:42, 10.83s/it]
269it [48:53, 10.90s/it]
270it [49:04, 10.88s/it]
271it [49:15, 10.87s/it]
272it [49:25, 10.84s/it]
273it [49:36, 10.82s/it]
274it [49:47, 10.86s/it]
275it [49:58, 10.89s/it]
276it [50:09, 10.91s/it]
277it [50:20, 10.88s/it]
278it [50:31, 10.87s/it]
279it [50:41, 10.85s/it]
280it [50:52, 10.80s/it]
281it [51:03, 10.80s/it]
282it [51:14, 10.80s/it]
283it [51:25, 10.80s/it]
284it [51:35, 10.72s/it]
285it [51:46, 10.70s/it]
286it [51:56, 10.70s/it]
287it [52:07, 10.69s/it]
288it [52:18, 10.73s/it]
289it [52:29, 10.76s/it]
290it [52:40, 10.80s/it]
291it [52:50, 10.76s/it]
292it [53:01, 10.75s/it]
293it [53:12, 10.75s/it]
294it [53:22, 10.73s/it]
295it [53:33, 10.74s/it]
296it [53:44, 10.78s/it]
297it [53:55, 10.79s/it]
298it [54:06, 10.76s/it]
299it [54:16, 10.74s/it]
300it [54:27, 10.73s/it]
301it [54:38, 10.71s/it]
302it [54:48, 10.71s/it]
303it [54:59, 10.72s/it]
304it [55:10, 10.71s/it]
305it [55:20, 10.70s/it]
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1000it [3:00:24, 10.82s/it]
Error counts:
	linear_id: 0
	linear_inchikey: 0
	linear_scaffold: 0
	linear_mwt: 0
	linear_clogp: 0
	linear_tpsa: 0Completed process in 3:18:11.497881

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664it [1:37:32,  8.82s/it]
665it [1:37:41,  8.83s/it]
666it [1:37:49,  8.82s/it]
667it [1:37:58,  8.83s/it]
668it [1:38:07,  8.84s/it]
669it [1:38:16,  8.84s/it]
670it [1:38:25,  8.84s/it]
671it [1:38:34,  8.86s/it]
672it [1:38:43,  8.86s/it]
673it [1:38:51,  8.83s/it]
674it [1:39:00,  8.84s/it]
675it [1:39:09,  8.85s/it]
676it [1:39:18,  8.83s/it]
677it [1:39:27,  8.81s/it]
678it [1:39:36,  8.81s/it]
679it [1:39:44,  8.81s/it]
680it [1:39:53,  8.82s/it]
681it [1:40:02,  8.81s/it]
682it [1:40:11,  8.81s/it]
683it [1:40:20,  8.81s/it]
684it [1:40:28,  8.80s/it]
685it [1:40:37,  8.83s/it]
686it [1:40:46,  8.86s/it]
687it [1:40:55,  8.87s/it]
688it [1:41:04,  8.85s/it]
689it [1:41:13,  8.90s/it]
690it [1:41:22,  8.90s/it]
691it [1:41:31,  8.93s/it]
692it [1:41:40,  8.96s/it]
693it [1:41:49,  8.98s/it]
694it [1:41:58,  8.99s/it]
695it [1:42:07,  9.01s/it]
696it [1:42:16,  9.02s/it]
697it [1:42:25,  9.01s/it]
698it [1:42:34,  9.01s/it]
699it [1:42:43,  9.01s/it]
700it [1:42:52,  9.01s/it]
701it [1:43:01,  9.01s/it]
702it [1:43:10,  9.01s/it]
703it [1:43:19,  9.03s/it]
704it [1:43:28,  9.03s/it]
705it [1:43:37,  9.01s/it]
706it [1:43:46,  9.00s/it]
707it [1:43:55,  9.00s/it]
708it [1:44:04,  9.00s/it]
709it [1:44:13,  8.98s/it]
710it [1:44:22,  8.98s/it]
711it [1:44:31,  8.99s/it]
712it [1:44:40,  8.98s/it]
713it [1:44:49,  8.98s/it]
714it [1:44:58,  8.99s/it]
715it [1:45:07,  8.98s/it]
716it [1:45:16,  8.97s/it]
717it [1:45:25,  8.97s/it]
718it [1:45:34,  8.96s/it]
719it [1:45:43,  8.98s/it]
720it [1:45:52,  8.96s/it]
721it [1:46:01,  8.98s/it]
722it [1:46:10,  8.96s/it]
723it [1:46:19,  8.96s/it]
724it [1:46:28,  8.96s/it]
725it [1:46:37,  8.96s/it]
726it [1:46:45,  8.95s/it]
727it [1:46:54,  8.96s/it]
728it [1:47:03,  8.94s/it]
729it [1:47:12,  8.94s/it]
730it [1:47:21,  8.94s/it]
731it [1:47:30,  8.92s/it]
732it [1:47:39,  8.91s/it]
733it [1:47:48,  8.91s/it]
734it [1:47:57,  8.93s/it]
735it [1:48:06,  8.93s/it]
736it [1:48:15,  8.92s/it]
737it [1:48:24,  8.90s/it]
738it [1:48:32,  8.88s/it]
739it [1:48:41,  8.87s/it]
740it [1:48:50,  8.85s/it]
741it [1:48:59,  8.83s/it]
742it [1:49:08,  8.85s/it]
743it [1:49:17,  8.86s/it]
744it [1:49:25,  8.86s/it]
745it [1:49:34,  8.87s/it]
746it [1:49:43,  8.84s/it]
747it [1:49:52,  8.83s/it]
748it [1:50:01,  8.85s/it]
749it [1:50:10,  8.86s/it]
750it [1:50:19,  8.89s/it]
751it [1:50:28,  8.90s/it]
752it [1:50:36,  8.89s/it]
753it [1:50:45,  8.87s/it]
754it [1:50:54,  8.85s/it]
755it [1:51:03,  8.86s/it]
756it [1:51:12,  8.85s/it]
757it [1:51:21,  8.84s/it]
758it [1:51:29,  8.84s/it]
759it [1:51:38,  8.84s/it]
760it [1:51:47,  8.84s/it]
761it [1:51:56,  8.84s/it]
762it [1:52:05,  8.83s/it]
763it [1:52:14,  8.83s/it]
764it [1:52:22,  8.84s/it]
765it [1:52:31,  8.85s/it]
766it [1:52:40,  8.84s/it]
767it [1:52:49,  8.82s/it]
768it [1:52:58,  8.83s/it]
769it [1:53:07,  8.81s/it]
770it [1:53:15,  8.81s/it]
771it [1:53:24,  8.77s/it]
772it [1:53:33,  8.79s/it]
773it [1:53:42,  8.80s/it]
774it [1:53:50,  8.78s/it]
775it [1:53:59,  8.81s/it]
776it [1:54:08,  8.80s/it]
777it [1:54:17,  8.78s/it]
778it [1:54:26,  8.78s/it]
779it [1:54:34,  8.77s/it]
780it [1:54:43,  8.77s/it]
781it [1:54:52,  8.78s/it]
782it [1:55:01,  8.81s/it]
783it [1:55:10,  8.82s/it]
784it [1:55:19,  8.83s/it]
785it [1:55:27,  8.83s/it]
786it [1:55:36,  8.84s/it]
787it [1:55:45,  8.83s/it]
788it [1:55:54,  8.83s/it]
789it [1:56:03,  8.83s/it]
790it [1:56:11,  8.81s/it]
791it [1:56:20,  8.83s/it]
792it [1:56:29,  8.85s/it]
793it [1:56:38,  8.85s/it]
794it [1:56:47,  8.82s/it]
795it [1:56:56,  8.82s/it]
796it [1:57:04,  8.78s/it]
797it [1:57:13,  8.74s/it]
798it [1:57:22,  8.72s/it]
799it [1:57:30,  8.71s/it]
800it [1:57:39,  8.73s/it]
801it [1:57:48,  8.72s/it]
802it [1:57:57,  8.72s/it]
803it [1:58:05,  8.71s/it]
804it [1:58:14,  8.69s/it]
805it [1:58:23,  8.71s/it]
806it [1:58:31,  8.71s/it]
807it [1:58:40,  8.74s/it]
808it [1:58:49,  8.71s/it]
809it [1:58:57,  8.71s/it]
810it [1:59:06,  8.72s/it]
811it [1:59:15,  8.71s/it]
812it [1:59:24,  8.73s/it]
813it [1:59:32,  8.74s/it]
814it [1:59:41,  8.74s/it]
815it [1:59:50,  8.74s/it]
816it [1:59:59,  8.76s/it]
817it [2:00:07,  8.75s/it]
818it [2:00:16,  8.73s/it]
819it [2:00:25,  8.75s/it]
820it [2:00:34,  8.73s/it]
821it [2:00:42,  8.73s/it]
822it [2:00:51,  8.71s/it]
823it [2:01:00,  8.70s/it]
824it [2:01:08,  8.69s/it]
825it [2:01:17,  8.66s/it]
826it [2:01:26,  8.67s/it]
827it [2:01:34,  8.69s/it]
828it [2:01:43,  8.71s/it]
829it [2:01:52,  8.69s/it]
830it [2:02:01,  8.70s/it]
831it [2:02:09,  8.70s/it]
832it [2:02:18,  8.67s/it]
833it [2:02:27,  8.68s/it]
834it [2:02:35,  8.68s/it]
835it [2:02:44,  8.65s/it]
836it [2:02:52,  8.63s/it]
837it [2:03:01,  8.64s/it]
838it [2:03:10,  8.66s/it]
839it [2:03:18,  8.67s/it]
840it [2:03:27,  8.68s/it]
841it [2:03:36,  8.67s/it]
842it [2:03:45,  8.69s/it]
843it [2:03:53,  8.68s/it]
844it [2:04:02,  8.66s/it]
845it [2:04:10,  8.66s/it]
846it [2:04:19,  8.67s/it]
847it [2:04:28,  8.66s/it]
848it [2:04:36,  8.65s/it]
849it [2:04:45,  8.65s/it]
850it [2:04:54,  8.64s/it]
851it [2:05:02,  8.64s/it]
852it [2:05:11,  8.64s/it]
853it [2:05:20,  8.65s/it]
854it [2:05:28,  8.62s/it]
855it [2:05:37,  8.63s/it]
856it [2:05:46,  8.66s/it]
857it [2:05:54,  8.71s/it]
858it [2:06:03,  8.72s/it]
859it [2:06:12,  8.72s/it]
860it [2:06:21,  8.72s/it]
861it [2:06:29,  8.74s/it]
862it [2:06:38,  8.76s/it]
863it [2:06:47,  8.75s/it]
864it [2:06:56,  8.74s/it]
865it [2:07:04,  8.74s/it]
866it [2:07:13,  8.74s/it]
867it [2:07:22,  8.71s/it]
868it [2:07:31,  8.72s/it]
869it [2:07:39,  8.72s/it]
870it [2:07:48,  8.71s/it]
871it [2:07:57,  8.71s/it]
872it [2:08:05,  8.70s/it]
873it [2:08:14,  8.71s/it]
874it [2:08:23,  8.70s/it]
875it [2:08:31,  8.69s/it]
876it [2:08:40,  8.68s/it]
877it [2:08:49,  8.67s/it]
878it [2:08:57,  8.69s/it]
879it [2:09:06,  8.68s/it]
880it [2:09:15,  8.66s/it]
881it [2:09:23,  8.67s/it]
882it [2:09:32,  8.68s/it]
883it [2:09:41,  8.70s/it]
884it [2:09:50,  8.69s/it]
885it [2:09:58,  8.69s/it]
886it [2:10:07,  8.70s/it]
887it [2:10:16,  8.68s/it]
888it [2:10:24,  8.69s/it]
889it [2:10:33,  8.69s/it]
890it [2:10:42,  8.66s/it]
891it [2:10:50,  8.66s/it]
892it [2:10:59,  8.65s/it]
893it [2:11:08,  8.68s/it]
894it [2:11:16,  8.68s/it]
895it [2:11:25,  8.72s/it]
896it [2:11:34,  8.73s/it]
897it [2:11:42,  8.70s/it]
898it [2:11:51,  8.72s/it]
899it [2:12:00,  8.73s/it]
900it [2:12:09,  8.75s/it]
901it [2:12:18,  8.74s/it]
902it [2:12:26,  8.77s/it]
903it [2:12:35,  8.77s/it]
904it [2:12:44,  8.76s/it]
905it [2:12:53,  8.76s/it]
906it [2:13:01,  8.77s/it]
907it [2:13:10,  8.76s/it]
908it [2:13:19,  8.76s/it]
909it [2:13:28,  8.78s/it]
910it [2:13:36,  8.77s/it]
911it [2:13:45,  8.82s/it]
912it [2:13:54,  8.79s/it]
913it [2:14:03,  8.78s/it]
914it [2:14:12,  8.79s/it]
915it [2:14:20,  8.78s/it]
916it [2:14:29,  8.78s/it]
917it [2:14:38,  8.78s/it]
918it [2:14:47,  8.77s/it]
919it [2:14:55,  8.75s/it]
920it [2:15:04,  8.76s/it]
921it [2:15:13,  8.77s/it]
922it [2:15:22,  8.77s/it]
923it [2:15:31,  8.78s/it]
924it [2:15:39,  8.79s/it]
925it [2:15:48,  8.76s/it]
926it [2:15:57,  8.75s/it]
927it [2:16:06,  8.75s/it]
928it [2:16:14,  8.76s/it]
929it [2:16:23,  8.75s/it]
930it [2:16:32,  8.76s/it]
931it [2:16:41,  8.76s/it]
932it [2:16:49,  8.77s/it]
933it [2:16:58,  8.76s/it]
934it [2:17:07,  8.75s/it]
935it [2:17:16,  8.75s/it]
936it [2:17:24,  8.72s/it]
937it [2:17:33,  8.72s/it]
938it [2:17:42,  8.70s/it]
939it [2:17:50,  8.70s/it]
940it [2:17:59,  8.69s/it]
941it [2:18:08,  8.73s/it]
942it [2:18:17,  8.72s/it]
943it [2:18:25,  8.71s/it]
944it [2:18:34,  8.71s/it]
945it [2:18:43,  8.70s/it]
946it [2:18:51,  8.69s/it]
947it [2:19:00,  8.68s/it]
948it [2:19:09,  8.68s/it]
949it [2:19:17,  8.67s/it]
950it [2:19:26,  8.66s/it]
951it [2:19:35,  8.66s/it]
952it [2:19:43,  8.67s/it]
953it [2:19:52,  8.65s/it]
954it [2:20:01,  8.65s/it]
955it [2:20:09,  8.66s/it]
956it [2:20:18,  8.68s/it]
957it [2:20:27,  8.67s/it]
958it [2:20:35,  8.69s/it]
959it [2:20:44,  8.69s/it]
960it [2:20:53,  8.66s/it]
961it [2:21:01,  8.65s/it]
962it [2:21:10,  8.66s/it]
963it [2:21:19,  8.67s/it]
964it [2:21:27,  8.68s/it]
965it [2:21:36,  8.69s/it]
966it [2:21:45,  8.70s/it]
967it [2:21:53,  8.69s/it]
968it [2:22:02,  8.69s/it]
969it [2:22:11,  8.72s/it]
970it [2:22:20,  8.74s/it]
971it [2:22:29,  8.77s/it]
972it [2:22:37,  8.76s/it]
973it [2:22:46,  8.77s/it]
974it [2:22:55,  8.77s/it]
975it [2:23:04,  8.79s/it]
976it [2:23:13,  8.81s/it]
977it [2:23:21,  8.82s/it]
978it [2:23:30,  8.79s/it]
979it [2:23:39,  8.79s/it]
980it [2:23:48,  8.79s/it]
981it [2:23:56,  8.78s/it]
982it [2:24:05,  8.76s/it]
983it [2:24:14,  8.75s/it]
984it [2:24:23,  8.74s/it]
985it [2:24:31,  8.71s/it]
986it [2:24:40,  8.71s/it]
987it [2:24:49,  8.69s/it]
988it [2:24:57,  8.70s/it]
989it [2:25:06,  8.69s/it]
990it [2:25:15,  8.69s/it]
991it [2:25:23,  8.69s/it]
992it [2:25:32,  8.68s/it]
993it [2:25:41,  8.66s/it]
994it [2:25:49,  8.66s/it]
995it [2:25:58,  8.63s/it]
996it [2:26:06,  8.63s/it]
997it [2:26:15,  8.63s/it]
998it [2:26:24,  8.63s/it]
999it [2:26:32,  8.63s/it]
1000it [2:26:41,  8.64s/it]
1000it [2:26:41,  8.80s/it]
Error counts:
	cysteine_to_N_cyclization: 0Completed process in 5:44:53.696427

0it [00:00, ?it/s]
1it [00:10, 10.98s/it]
2it [00:21, 10.80s/it]
3it [00:32, 10.75s/it]
4it [00:43, 10.75s/it]
5it [00:53, 10.76s/it]
6it [01:04, 10.80s/it]
7it [01:15, 10.81s/it]
8it [01:26, 10.81s/it]
9it [01:37, 10.83s/it]
10it [01:48, 10.90s/it]
11it [01:59, 10.92s/it]
12it [02:10, 10.95s/it]
13it [02:21, 10.95s/it]
14it [02:32, 10.96s/it]
15it [02:43, 10.97s/it]
16it [02:54, 10.99s/it]
17it [03:05, 10.98s/it]
18it [03:16, 10.98s/it]
19it [03:27, 10.99s/it]
20it [03:38, 10.97s/it]
21it [03:49, 10.94s/it]
22it [03:59, 10.93s/it]
23it [04:10, 10.90s/it]
24it [04:21, 10.88s/it]
25it [04:32, 10.92s/it]
26it [04:43, 10.94s/it]
27it [04:54, 10.96s/it]
28it [05:05, 10.95s/it]
29it [05:16, 10.93s/it]
30it [05:27, 10.95s/it]
31it [05:38, 10.93s/it]
32it [05:49, 10.90s/it]
33it [06:00, 10.91s/it]
34it [06:10, 10.91s/it]
35it [06:21, 10.88s/it]
36it [06:32, 10.89s/it]
37it [06:43, 10.89s/it]
38it [06:54, 10.91s/it]
39it [07:05, 10.90s/it]
40it [07:16, 10.87s/it]
41it [07:26, 10.84s/it]
42it [07:37, 10.85s/it]
43it [07:48, 10.85s/it]
44it [07:59, 10.85s/it]
45it [08:10, 10.87s/it]
46it [08:21, 10.89s/it]
47it [08:32, 10.90s/it]
48it [08:43, 10.91s/it]
49it [08:54, 10.93s/it]
50it [09:05, 10.95s/it]
51it [09:16, 10.94s/it]
52it [09:26, 10.90s/it]
53it [09:37, 10.86s/it]
54it [09:48, 10.86s/it]
55it [09:59, 10.86s/it]
56it [10:10, 10.84s/it]
57it [10:21, 10.83s/it]
58it [10:31, 10.84s/it]
59it [10:42, 10.83s/it]
60it [10:53, 10.84s/it]
61it [11:04, 10.81s/it]
62it [11:15, 10.81s/it]
63it [11:25, 10.81s/it]
64it [11:36, 10.82s/it]
65it [11:47, 10.82s/it]
66it [11:58, 10.82s/it]
67it [12:09, 10.81s/it]
68it [12:20, 10.83s/it]
69it [12:30, 10.85s/it]
70it [12:41, 10.84s/it]
71it [12:52, 10.84s/it]
72it [13:03, 10.82s/it]
73it [13:14, 10.82s/it]
74it [13:25, 10.83s/it]
75it [13:36, 10.87s/it]
76it [13:46, 10.87s/it]
77it [13:57, 10.87s/it]
78it [14:08, 10.85s/it]
79it [14:19, 10.83s/it]
80it [14:30, 10.84s/it]
81it [14:41, 10.85s/it]
82it [14:51, 10.82s/it]
83it [15:02, 10.83s/it]
84it [15:13, 10.84s/it]
85it [15:24, 10.80s/it]
86it [15:35, 10.82s/it]
87it [15:45, 10.81s/it]
88it [15:56, 10.81s/it]
89it [16:07, 10.82s/it]
90it [16:18, 10.84s/it]
91it [16:29, 10.84s/it]
92it [16:40, 10.84s/it]
93it [16:51, 10.84s/it]
94it [17:01, 10.84s/it]
95it [17:12, 10.86s/it]
96it [17:23, 10.83s/it]
97it [17:34, 10.80s/it]
98it [17:45, 10.82s/it]
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930it [2:46:46, 10.40s/it]
931it [2:46:57, 10.39s/it]
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934it [2:47:28, 10.39s/it]
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951it [2:50:24, 10.38s/it]
952it [2:50:35, 10.39s/it]
953it [2:50:45, 10.38s/it]
954it [2:50:56, 10.36s/it]
955it [2:51:06, 10.37s/it]
956it [2:51:16, 10.38s/it]
957it [2:51:27, 10.39s/it]
958it [2:51:37, 10.40s/it]
959it [2:51:48, 10.42s/it]
960it [2:51:58, 10.41s/it]
961it [2:52:08, 10.40s/it]
962it [2:52:19, 10.40s/it]
963it [2:52:29, 10.40s/it]
964it [2:52:40, 10.43s/it]
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966it [2:53:01, 10.43s/it]
967it [2:53:11, 10.41s/it]
968it [2:53:21, 10.41s/it]
969it [2:53:32, 10.41s/it]
970it [2:53:42, 10.40s/it]
971it [2:53:53, 10.41s/it]
972it [2:54:03, 10.39s/it]
973it [2:54:13, 10.39s/it]
974it [2:54:24, 10.38s/it]
975it [2:54:34, 10.39s/it]
976it [2:54:44, 10.38s/it]
977it [2:54:55, 10.40s/it]
978it [2:55:05, 10.39s/it]
979it [2:55:16, 10.40s/it]
980it [2:55:26, 10.40s/it]
981it [2:55:36, 10.39s/it]
982it [2:55:47, 10.37s/it]
983it [2:55:57, 10.35s/it]
984it [2:56:07, 10.36s/it]
985it [2:56:18, 10.38s/it]
986it [2:56:28, 10.37s/it]
987it [2:56:39, 10.37s/it]
988it [2:56:49, 10.41s/it]
989it [2:57:00, 10.41s/it]
990it [2:57:10, 10.39s/it]
991it [2:57:20, 10.43s/it]
992it [2:57:31, 10.45s/it]
993it [2:57:41, 10.44s/it]
994it [2:57:52, 10.44s/it]
995it [2:58:02, 10.43s/it]
996it [2:58:13, 10.44s/it]
997it [2:58:23, 10.43s/it]
998it [2:58:33, 10.42s/it]
999it [2:58:44, 10.38s/it]
1000it [2:58:54, 10.38s/it]
1000it [2:58:54, 10.73s/it]
Error counts:
	cyclic_id: 0
	cyclic_inchikey: 0
	cyclic_scaffold: 0
	cyclic_mwt: 0
	cyclic_clogp: 0
	cyclic_tpsa: 0Completed process in 8:43:49.286749

0it [00:00, ?it/s]
1it [00:00,  9.11it/s]
2it [00:00,  9.31it/s]
3it [00:00,  9.41it/s]
4it [00:00,  9.42it/s]
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7it [00:00,  9.48it/s]
8it [00:00,  9.45it/s]
9it [00:00,  9.47it/s]
10it [00:01,  9.49it/s]
11it [00:01,  9.43it/s]
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14it [00:01,  9.46it/s]
15it [00:01,  9.49it/s]
16it [00:01,  9.49it/s]
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971it [01:43,  9.36it/s]
972it [01:43,  9.42it/s]
973it [01:43,  9.38it/s]
974it [01:43,  9.39it/s]
975it [01:43,  9.35it/s]
976it [01:43,  9.36it/s]
977it [01:43,  9.38it/s]
978it [01:44,  9.38it/s]
979it [01:44,  9.42it/s]
980it [01:44,  9.40it/s]
981it [01:44,  9.38it/s]
982it [01:44,  9.35it/s]
983it [01:44,  9.39it/s]
984it [01:44,  9.32it/s]
985it [01:44,  9.32it/s]
986it [01:44,  9.37it/s]
987it [01:45,  9.40it/s]
988it [01:45,  9.42it/s]
989it [01:45,  9.42it/s]
990it [01:45,  9.40it/s]
991it [01:45,  9.36it/s]
992it [01:45,  9.34it/s]
993it [01:45,  9.36it/s]
994it [01:45,  9.36it/s]
995it [01:45,  9.37it/s]
996it [01:45,  9.40it/s]
997it [01:46,  9.37it/s]
998it [01:46,  9.38it/s]
999it [01:46,  9.39it/s]
1000it [01:46,  9.41it/s]
1000it [01:46,  9.40it/s]
Split counts:
	train: 674000
	test: 164000
	validation: 162000Completed process in 8:45:36.893053
++ date
+ echo 'Sat  2 Nov 00:41:03 GMT 2024 :: 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz'
+ AWK_SCRIPT='NR == 1 { n=split($0,h); for(i=1;i<=n;i++) col[h[i]]=i; print $0 }; ( NR > 1 && $col[c1] == "True" ) { print $0 }'
+ for split in train test validation
++ dirname 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz
+ split_dir=20241101_peptides_6-12x100M/train
++ basename 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz .csv.gz
+ split_file=20241101_peptides_6-12x100M/train/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz
+ mkdir -p 20241101_peptides_6-12x100M/train
++ date
+ echo 'Sat  2 Nov 00:41:03 GMT 2024 :: Saving train...'
Sat  2 Nov 00:41:03 GMT 2024 :: Saving train...
+ zcat 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz
+ gzip --best
+ awk -F, -v OFS=, -v c1=is_train 'NR == 1 { n=split($0,h); for(i=1;i<=n;i++) col[h[i]]=i; print $0 }; ( NR > 1 && $col[c1] == "True" ) { print $0 }'
++ date
+ echo 'Sat  2 Nov 00:42:01 GMT 2024 :: 20241101_peptides_6-12x100M/train/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz'
+ for split in train test validation
++ dirname 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz
+ split_dir=20241101_peptides_6-12x100M/test
++ basename 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz .csv.gz
+ split_file=20241101_peptides_6-12x100M/test/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz
+ mkdir -p 20241101_peptides_6-12x100M/test
++ date
+ echo 'Sat  2 Nov 00:42:01 GMT 2024 :: Saving test...'
Sat  2 Nov 00:42:01 GMT 2024 :: Saving test...
+ zcat 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz
+ gzip --best
+ awk -F, -v OFS=, -v c1=is_test 'NR == 1 { n=split($0,h); for(i=1;i<=n;i++) col[h[i]]=i; print $0 }; ( NR > 1 && $col[c1] == "True" ) { print $0 }'
++ date
+ echo 'Sat  2 Nov 00:42:26 GMT 2024 :: 20241101_peptides_6-12x100M/test/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz'
+ for split in train test validation
++ dirname 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz
+ split_dir=20241101_peptides_6-12x100M/validation
++ basename 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz .csv.gz
+ split_file=20241101_peptides_6-12x100M/validation/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz
+ mkdir -p 20241101_peptides_6-12x100M/validation
++ date
+ echo 'Sat  2 Nov 00:42:26 GMT 2024 :: Saving validation...'
Sat  2 Nov 00:42:26 GMT 2024 :: Saving validation...
+ zcat 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz
+ gzip --best
+ awk -F, -v OFS=, -v c1=is_validation 'NR == 1 { n=split($0,h); for(i=1;i<=n;i++) col[h[i]]=i; print $0 }; ( NR > 1 && $col[c1] == "True" ) { print $0 }'
++ date
+ echo 'Sat  2 Nov 00:42:51 GMT 2024 :: 20241101_peptides_6-12x100M/validation/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz'
+ '[' -e 20241101_peptides_6-12x100M/validation/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz.success ']'
+ rm 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-14000000-15000000.csv.gz.success
+ set +x
Sat  2 Nov 00:42:51 GMT 2024 > Peptide generation complete