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Fri  1 Nov 15:59:42 GMT 2024 > Generating peptides on cn004
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 15:59:42 GMT 2024 > Running /camp/apps/eb/software/Anaconda3/2023.03/bin/python : Python 3.10.10
Fri  1 Nov 15:59:42 GMT 2024 > Using Conda from .
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Fri  1 Nov 15:59:42 GMT 2024 > Seed = 1; length = 10; max. number = 100000000; slice = 36000000 to 37000000; output dir. = 20241101_peptides_6-12x100M
Fri  1 Nov 15:59:42 GMT 2024 > There are 10240000000000 peptides of length 10; generating 100000000 (0.000976563 %)
Fri  1 Nov 15:59:42 GMT 2024 > Saving a slice to 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz...
+ schemist enumerate --seed 1 --max-length 10 --prefix GY --suffix CGSGSGS --number 9.76563e-06 --slice 36000000 37000000
+ schemist split --type random --train 0.7 --test 0.15 --column cysteine_to_N_cyclization --seed 1
+ tr '	' ,
+ schemist react --column SMILES --reaction cysteine_to_N_cyclization
+ schemist convert --column cysteine_to_N_cyclization --to id inchikey scaffold mwt clogp tpsa --prefix cyclic_ --options prefix=SCB-
+ schemist convert --column SMILES --to id inchikey scaffold mwt clogp tpsa --prefix linear_ --options prefix=SCB-
+ gzip --best
🚀 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 0x7fbd0281f240>
🚀 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 0x7f8eaf95b240>
🚀 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 0x7f0e523db9c0>
🚀 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: ['36000000', '37000000']
	seed: 1
	prefix: GY
	suffix: CGSGSGS
	type: aa
	d_aa_only: False
	include_d_aa: False
	func: <function _enum at 0x7f4932683880>
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. 
🚀 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 0x7fb0a94074c0>

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819it [13:54,  1.09it/s]
820it [13:55,  1.09it/s]
821it [13:56,  1.09it/s]
822it [13:56,  1.10it/s]
823it [13:57,  1.10it/s]
824it [13:58,  1.10it/s]
825it [13:59,  1.10it/s]
826it [14:00,  1.10it/s]
827it [14:01,  1.10it/s]
828it [14:02,  1.09it/s]
829it [14:03,  1.09it/s]
830it [14:04,  1.09it/s]
831it [14:05,  1.09it/s]
832it [14:06,  1.09it/s]
833it [14:07,  1.09it/s]
834it [14:07,  1.10it/s]
835it [14:08,  1.09it/s]
836it [14:09,  1.09it/s]
837it [14:10,  1.09it/s]
838it [14:11,  1.08it/s]
839it [14:12,  1.07it/s]
840it [14:13,  1.07it/s]
841it [14:14,  1.06it/s]
842it [14:15,  1.06it/s]
843it [14:16,  1.06it/s]
844it [14:17,  1.05it/s]
845it [14:18,  1.06it/s]
846it [14:19,  1.06it/s]
847it [14:20,  1.06it/s]
848it [14:21,  1.06it/s]
849it [14:22,  1.06it/s]
850it [14:22,  1.06it/s]
851it [14:23,  1.07it/s]
852it [14:24,  1.08it/s]
853it [14:25,  1.09it/s]
854it [14:26,  1.09it/s]
855it [14:27,  1.09it/s]
856it [14:28,  1.10it/s]
857it [14:29,  1.11it/s]
858it [14:30,  1.11it/s]
859it [14:31,  1.11it/s]
860it [14:32,  1.11it/s]
861it [14:32,  1.10it/s]
862it [14:33,  1.10it/s]
863it [14:34,  1.11it/s]
864it [14:35,  1.10it/s]
865it [14:36,  1.10it/s]
866it [14:37,  1.10it/s]
867it [14:38,  1.10it/s]
868it [14:39,  1.10it/s]
869it [14:40,  1.10it/s]
870it [14:41,  1.10it/s]
871it [14:41,  1.11it/s]
872it [14:42,  1.11it/s]
873it [14:43,  1.11it/s]
874it [14:44,  1.11it/s]
875it [14:45,  1.11it/s]
876it [14:46,  1.11it/s]
877it [14:47,  1.11it/s]
878it [14:48,  1.11it/s]
879it [14:49,  1.11it/s]
880it [14:50,  1.11it/s]
881it [14:50,  1.11it/s]
882it [14:51,  1.11it/s]
883it [14:52,  1.11it/s]
884it [14:53,  1.11it/s]
885it [14:54,  1.10it/s]
886it [14:55,  1.10it/s]
887it [14:56,  1.10it/s]
888it [14:57,  1.09it/s]
889it [14:58,  1.09it/s]
890it [14:59,  1.10it/s]
891it [15:00,  1.10it/s]
892it [15:00,  1.11it/s]
893it [15:01,  1.10it/s]
894it [15:02,  1.10it/s]
895it [15:03,  1.11it/s]
896it [15:04,  1.11it/s]
897it [15:05,  1.11it/s]
898it [15:06,  1.11it/s]
899it [15:07,  1.11it/s]
900it [15:08,  1.10it/s]
901it [15:09,  1.09it/s]
902it [15:10,  1.09it/s]
903it [15:10,  1.09it/s]
904it [15:11,  1.09it/s]
905it [15:12,  1.10it/s]
906it [15:13,  1.09it/s]
907it [15:14,  1.10it/s]
908it [15:15,  1.09it/s]
909it [15:16,  1.10it/s]
910it [15:17,  1.08it/s]
911it [15:18,  1.09it/s]
912it [15:19,  1.09it/s]
913it [15:20,  1.09it/s]
914it [15:21,  1.09it/s]
915it [15:21,  1.11it/s]
916it [15:22,  1.11it/s]
917it [15:23,  1.11it/s]
918it [15:24,  1.11it/s]
919it [15:25,  1.10it/s]
920it [15:26,  1.11it/s]
921it [15:27,  1.11it/s]
922it [15:28,  1.10it/s]
923it [15:29,  1.10it/s]
924it [15:30,  1.10it/s]
925it [15:30,  1.10it/s]
926it [15:31,  1.10it/s]
927it [15:32,  1.11it/s]
928it [15:33,  1.11it/s]
929it [15:34,  1.11it/s]
930it [15:35,  1.11it/s]
931it [15:36,  1.11it/s]
932it [15:37,  1.10it/s]
933it [15:38,  1.10it/s]
934it [15:39,  1.10it/s]
935it [15:40,  1.10it/s]
936it [15:40,  1.11it/s]
937it [15:41,  1.10it/s]
938it [15:42,  1.10it/s]
939it [15:43,  1.11it/s]
940it [15:44,  1.11it/s]
941it [15:45,  1.11it/s]
942it [15:46,  1.11it/s]
943it [15:47,  1.11it/s]
944it [15:48,  1.11it/s]
945it [15:49,  1.11it/s]
946it [15:49,  1.11it/s]
947it [15:50,  1.11it/s]
948it [15:51,  1.11it/s]
949it [15:52,  1.11it/s]
950it [15:53,  1.11it/s]
951it [15:54,  1.11it/s]
952it [15:55,  1.11it/s]
953it [15:56,  1.11it/s]
954it [15:57,  1.12it/s]
955it [15:58,  1.12it/s]
956it [15:58,  1.11it/s]
957it [15:59,  1.11it/s]
958it [16:00,  1.11it/s]
959it [16:01,  1.11it/s]
960it [16:02,  1.11it/s]
961it [16:03,  1.11it/s]
962it [16:04,  1.11it/s]
963it [16:05,  1.11it/s]
964it [16:06,  1.11it/s]
965it [16:07,  1.11it/s]
966it [16:07,  1.11it/s]
967it [16:08,  1.11it/s]
968it [16:09,  1.11it/s]
969it [16:10,  1.12it/s]
970it [16:11,  1.11it/s]
971it [16:12,  1.11it/s]
972it [16:13,  1.11it/s]
973it [16:14,  1.10it/s]
974it [16:15,  1.09it/s]
975it [16:16,  1.10it/s]
976it [16:17,  1.10it/s]
977it [16:17,  1.10it/s]
978it [16:18,  1.10it/s]
979it [16:19,  1.11it/s]
980it [16:20,  1.10it/s]
981it [16:21,  1.10it/s]
982it [16:22,  1.10it/s]
983it [16:23,  1.10it/s]
984it [16:24,  1.10it/s]
985it [16:25,  1.10it/s]
986it [16:26,  1.11it/s]
987it [16:27,  1.10it/s]
988it [16:27,  1.10it/s]
989it [16:28,  1.09it/s]
990it [16:29,  1.08it/s]
991it [16:30,  1.08it/s]
992it [16:31,  1.09it/s]
993it [16:32,  1.08it/s]
994it [16:33,  1.08it/s]
995it [16:34,  1.08it/s]
996it [16:35,  1.09it/s]
997it [16:36,  1.09it/s]
998it [16:37,  1.09it/s]
999it [16:38,  1.09it/s]
1000it [16:38,  1.09it/s]
1000it [16:38,  1.00it/s]
Enumerated peptides:
	Number of peptides: 1000000
Conversion errors:
	SMILES: 0Completed process in 0:16:38.984637

0it [00:00, ?it/s]
1it [00:10, 10.36s/it]
2it [00:20, 10.29s/it]
3it [00:30, 10.32s/it]
4it [00:41, 10.28s/it]
5it [00:51, 10.26s/it]
6it [01:01, 10.25s/it]
7it [01:11, 10.25s/it]
8it [01:22, 10.25s/it]
9it [01:32, 10.26s/it]
10it [01:42, 10.24s/it]
11it [01:52, 10.22s/it]
12it [02:02, 10.20s/it]
13it [02:13, 10.20s/it]
14it [02:23, 10.24s/it]
15it [02:33, 10.29s/it]
16it [02:44, 10.24s/it]
17it [02:54, 10.30s/it]
18it [03:04, 10.32s/it]
19it [03:15, 10.31s/it]
20it [03:25, 10.28s/it]
21it [03:35, 10.28s/it]
22it [03:45, 10.26s/it]
23it [03:55, 10.24s/it]
24it [04:06, 10.25s/it]
25it [04:16, 10.33s/it]
26it [04:27, 10.40s/it]
27it [04:37, 10.44s/it]
28it [04:48, 10.48s/it]
29it [04:59, 10.51s/it]
30it [05:09, 10.52s/it]
31it [05:20, 10.53s/it]
32it [05:30, 10.48s/it]
33it [05:40, 10.43s/it]
34it [05:51, 10.41s/it]
35it [06:01, 10.38s/it]
36it [06:11, 10.34s/it]
37it [06:21, 10.30s/it]
38it [06:32, 10.30s/it]
39it [06:42, 10.31s/it]
40it [06:52, 10.34s/it]
41it [07:03, 10.34s/it]
42it [07:13, 10.33s/it]
43it [07:23, 10.33s/it]
44it [07:34, 10.30s/it]
45it [07:44, 10.39s/it]
46it [07:55, 10.39s/it]
47it [08:05, 10.34s/it]
48it [08:15, 10.35s/it]
49it [08:26, 10.35s/it]
50it [08:36, 10.34s/it]
51it [08:46, 10.33s/it]
52it [08:57, 10.33s/it]
53it [09:07, 10.40s/it]
54it [09:18, 10.44s/it]
55it [09:28, 10.46s/it]
56it [09:39, 10.49s/it]
57it [09:49, 10.51s/it]
58it [10:00, 10.52s/it]
59it [10:10, 10.51s/it]
60it [10:21, 10.50s/it]
61it [10:31, 10.54s/it]
62it [10:42, 10.59s/it]
63it [10:53, 10.58s/it]
64it [11:03, 10.56s/it]
65it [11:14, 10.54s/it]
66it [11:24, 10.45s/it]
67it [11:34, 10.35s/it]
68it [11:44, 10.30s/it]
69it [11:54, 10.28s/it]
70it [12:05, 10.28s/it]
71it [12:15, 10.26s/it]
72it [12:25, 10.24s/it]
73it [12:35, 10.22s/it]
74it [12:46, 10.24s/it]
75it [12:56, 10.25s/it]
76it [13:06, 10.24s/it]
77it [13:16, 10.24s/it]
78it [13:27, 10.23s/it]
79it [13:37, 10.23s/it]
80it [13:47, 10.22s/it]
81it [13:57, 10.24s/it]
82it [14:07, 10.22s/it]
83it [14:18, 10.20s/it]
84it [14:28, 10.20s/it]
85it [14:38, 10.19s/it]
86it [14:48, 10.19s/it]
87it [14:58, 10.19s/it]
88it [15:09, 10.20s/it]
89it [15:19, 10.22s/it]
90it [15:29, 10.22s/it]
91it [15:39, 10.22s/it]
92it [15:49, 10.21s/it]
93it [16:00, 10.20s/it]
94it [16:10, 10.21s/it]
95it [16:20, 10.22s/it]
96it [16:30, 10.20s/it]
97it [16:40, 10.20s/it]
98it [16:51, 10.19s/it]
99it [17:01, 10.30s/it]
100it [17:12, 10.35s/it]
101it [17:22, 10.40s/it]
102it [17:33, 10.46s/it]
103it [17:43, 10.48s/it]
104it [17:54, 10.51s/it]
105it [18:04, 10.52s/it]
106it [18:15, 10.46s/it]
107it [18:25, 10.37s/it]
108it [18:35, 10.31s/it]
109it [18:45, 10.30s/it]
110it [18:56, 10.28s/it]
111it [19:06, 10.28s/it]
112it [19:16, 10.26s/it]
113it [19:26, 10.24s/it]
114it [19:37, 10.27s/it]
115it [19:47, 10.25s/it]
116it [19:57, 10.23s/it]
117it [20:07, 10.22s/it]
118it [20:17, 10.20s/it]
119it [20:28, 10.22s/it]
120it [20:38, 10.21s/it]
121it [20:48, 10.21s/it]
122it [20:58, 10.29s/it]
123it [21:09, 10.35s/it]
124it [21:19, 10.34s/it]
125it [21:29, 10.30s/it]
126it [21:40, 10.27s/it]
127it [21:50, 10.27s/it]
128it [22:00, 10.25s/it]
129it [22:10, 10.28s/it]
130it [22:21, 10.36s/it]
131it [22:32, 10.42s/it]
132it [22:42, 10.49s/it]
133it [22:53, 10.57s/it]
134it [23:03, 10.47s/it]
135it [23:13, 10.38s/it]
136it [23:24, 10.37s/it]
137it [23:34, 10.37s/it]
138it [23:44, 10.34s/it]
139it [23:55, 10.36s/it]
140it [24:05, 10.38s/it]
141it [24:16, 10.43s/it]
142it [24:26, 10.43s/it]
143it [24:36, 10.38s/it]
144it [24:47, 10.33s/it]
145it [24:57, 10.29s/it]
146it [25:07, 10.29s/it]
147it [25:17, 10.29s/it]
148it [25:28, 10.29s/it]
149it [25:38, 10.31s/it]
150it [25:48, 10.33s/it]
151it [25:59, 10.32s/it]
152it [26:09, 10.38s/it]
153it [26:20, 10.42s/it]
154it [26:30, 10.41s/it]
155it [26:41, 10.41s/it]
156it [26:51, 10.40s/it]
157it [27:02, 10.44s/it]
158it [27:12, 10.47s/it]
159it [27:23, 10.48s/it]
160it [27:33, 10.45s/it]
161it [27:44, 10.50s/it]
162it [27:54, 10.52s/it]
163it [28:05, 10.53s/it]
164it [28:15, 10.53s/it]
165it [28:26, 10.51s/it]
166it [28:36, 10.54s/it]
167it [28:47, 10.54s/it]
168it [28:57, 10.56s/it]
169it [29:08, 10.55s/it]
170it [29:19, 10.57s/it]
171it [29:29, 10.57s/it]
172it [29:39, 10.50s/it]
173it [29:50, 10.51s/it]
174it [30:01, 10.52s/it]
175it [30:11, 10.51s/it]
176it [30:22, 10.53s/it]
177it [30:32, 10.54s/it]
178it [30:43, 10.54s/it]
179it [30:53, 10.53s/it]
180it [31:04, 10.58s/it]
181it [31:15, 10.63s/it]
182it [31:25, 10.63s/it]
183it [31:36, 10.68s/it]
184it [31:47, 10.70s/it]
185it [31:57, 10.66s/it]
186it [32:08, 10.58s/it]
187it [32:18, 10.46s/it]
188it [32:28, 10.40s/it]
189it [32:38, 10.34s/it]
190it [32:49, 10.35s/it]
191it [32:59, 10.35s/it]
192it [33:10, 10.38s/it]
193it [33:20, 10.39s/it]
194it [33:30, 10.37s/it]
195it [33:41, 10.36s/it]
196it [33:51, 10.36s/it]
197it [34:01, 10.38s/it]
198it [34:12, 10.39s/it]
199it [34:22, 10.38s/it]
200it [34:33, 10.42s/it]
201it [34:43, 10.44s/it]
202it [34:54, 10.43s/it]
203it [35:04, 10.42s/it]
204it [35:14, 10.38s/it]
205it [35:25, 10.37s/it]
206it [35:35, 10.35s/it]
207it [35:45, 10.36s/it]
208it [35:56, 10.35s/it]
209it [36:06, 10.44s/it]
210it [36:17, 10.51s/it]
211it [36:27, 10.47s/it]
212it [36:38, 10.44s/it]
213it [36:48, 10.41s/it]
214it [36:58, 10.38s/it]
215it [37:09, 10.33s/it]
216it [37:19, 10.32s/it]
217it [37:29, 10.30s/it]
218it [37:40, 10.38s/it]
219it [37:50, 10.35s/it]
220it [38:01, 10.39s/it]
221it [38:11, 10.41s/it]
222it [38:21, 10.35s/it]
223it [38:32, 10.39s/it]
224it [38:42, 10.41s/it]
225it [38:53, 10.47s/it]
226it [39:03, 10.53s/it]
227it [39:14, 10.45s/it]
228it [39:24, 10.40s/it]
229it [39:34, 10.36s/it]
230it [39:44, 10.32s/it]
231it [39:55, 10.30s/it]
232it [40:05, 10.29s/it]
233it [40:15, 10.31s/it]
234it [40:26, 10.32s/it]
235it [40:36, 10.34s/it]
236it [40:46, 10.37s/it]
237it [40:57, 10.39s/it]
238it [41:07, 10.40s/it]
239it [41:18, 10.41s/it]
240it [41:28, 10.39s/it]
241it [41:38, 10.35s/it]
242it [41:49, 10.31s/it]
243it [41:59, 10.29s/it]
244it [42:09, 10.31s/it]
245it [42:19, 10.30s/it]
246it [42:30, 10.29s/it]
247it [42:40, 10.30s/it]
248it [42:50, 10.28s/it]
249it [43:01, 10.30s/it]
250it [43:11, 10.29s/it]
251it [43:21, 10.31s/it]
252it [43:32, 10.30s/it]
253it [43:42, 10.30s/it]
254it [43:52, 10.31s/it]
255it [44:03, 10.33s/it]
256it [44:13, 10.34s/it]
257it [44:23, 10.34s/it]
258it [44:34, 10.33s/it]
259it [44:44, 10.31s/it]
260it [44:54, 10.34s/it]
261it [45:05, 10.33s/it]
262it [45:15, 10.33s/it]
263it [45:25, 10.33s/it]
264it [45:35, 10.30s/it]
265it [45:46, 10.32s/it]
266it [45:56, 10.31s/it]
267it [46:06, 10.33s/it]
268it [46:17, 10.32s/it]
269it [46:27, 10.29s/it]
270it [46:37, 10.30s/it]
271it [46:48, 10.30s/it]
272it [46:58, 10.30s/it]
273it [47:08, 10.28s/it]
274it [47:18, 10.26s/it]
275it [47:29, 10.24s/it]
276it [47:39, 10.24s/it]
277it [47:49, 10.28s/it]
278it [48:00, 10.36s/it]
279it [48:10, 10.37s/it]
280it [48:20, 10.39s/it]
281it [48:31, 10.40s/it]
282it [48:42, 10.51s/it]
283it [48:52, 10.60s/it]
284it [49:03, 10.66s/it]
285it [49:14, 10.73s/it]
286it [49:25, 10.75s/it]
287it [49:36, 10.77s/it]
288it [49:46, 10.71s/it]
289it [49:57, 10.60s/it]
290it [50:07, 10.56s/it]
291it [50:18, 10.51s/it]
292it [50:28, 10.60s/it]
293it [50:39, 10.67s/it]
294it [50:50, 10.74s/it]
295it [51:01, 10.79s/it]
296it [51:12, 10.72s/it]
297it [51:22, 10.71s/it]
298it [51:33, 10.62s/it]
299it [51:43, 10.51s/it]
300it [51:54, 10.54s/it]
301it [52:04, 10.61s/it]
302it [52:15, 10.64s/it]
303it [52:26, 10.65s/it]
304it [52:36, 10.66s/it]
305it [52:47, 10.69s/it]
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Error counts:
	linear_id: 0
	linear_inchikey: 0
	linear_scaffold: 0
	linear_mwt: 0
	linear_clogp: 0
	linear_tpsa: 0Completed process in 3:06:58.214728

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663it [1:32:26,  8.32s/it]
664it [1:32:34,  8.32s/it]
665it [1:32:42,  8.32s/it]
666it [1:32:51,  8.31s/it]
667it [1:32:59,  8.33s/it]
668it [1:33:07,  8.33s/it]
669it [1:33:16,  8.33s/it]
670it [1:33:24,  8.32s/it]
671it [1:33:32,  8.31s/it]
672it [1:33:41,  8.33s/it]
673it [1:33:49,  8.33s/it]
674it [1:33:57,  8.32s/it]
675it [1:34:06,  8.32s/it]
676it [1:34:14,  8.32s/it]
677it [1:34:22,  8.35s/it]
678it [1:34:31,  8.35s/it]
679it [1:34:39,  8.39s/it]
680it [1:34:48,  8.42s/it]
681it [1:34:56,  8.45s/it]
682it [1:35:05,  8.42s/it]
683it [1:35:13,  8.41s/it]
684it [1:35:21,  8.43s/it]
685it [1:35:30,  8.41s/it]
686it [1:35:38,  8.42s/it]
687it [1:35:47,  8.43s/it]
688it [1:35:55,  8.44s/it]
689it [1:36:04,  8.46s/it]
690it [1:36:12,  8.45s/it]
691it [1:36:21,  8.47s/it]
692it [1:36:29,  8.47s/it]
693it [1:36:38,  8.45s/it]
694it [1:36:46,  8.45s/it]
695it [1:36:54,  8.41s/it]
696it [1:37:03,  8.36s/it]
697it [1:37:11,  8.35s/it]
698it [1:37:19,  8.33s/it]
699it [1:37:28,  8.33s/it]
700it [1:37:36,  8.33s/it]
701it [1:37:44,  8.33s/it]
702it [1:37:53,  8.35s/it]
703it [1:38:01,  8.34s/it]
704it [1:38:09,  8.33s/it]
705it [1:38:18,  8.33s/it]
706it [1:38:26,  8.33s/it]
707it [1:38:34,  8.32s/it]
708it [1:38:42,  8.33s/it]
709it [1:38:51,  8.33s/it]
710it [1:38:59,  8.32s/it]
711it [1:39:07,  8.32s/it]
712it [1:39:16,  8.33s/it]
713it [1:39:24,  8.32s/it]
714it [1:39:32,  8.32s/it]
715it [1:39:41,  8.33s/it]
716it [1:39:49,  8.36s/it]
717it [1:39:58,  8.38s/it]
718it [1:40:06,  8.39s/it]
719it [1:40:14,  8.38s/it]
720it [1:40:23,  8.40s/it]
721it [1:40:31,  8.40s/it]
722it [1:40:40,  8.40s/it]
723it [1:40:48,  8.41s/it]
724it [1:40:56,  8.41s/it]
725it [1:41:05,  8.40s/it]
726it [1:41:13,  8.40s/it]
727it [1:41:22,  8.42s/it]
728it [1:41:30,  8.40s/it]
729it [1:41:38,  8.41s/it]
730it [1:41:47,  8.42s/it]
731it [1:41:55,  8.43s/it]
732it [1:42:04,  8.42s/it]
733it [1:42:12,  8.42s/it]
734it [1:42:21,  8.41s/it]
735it [1:42:29,  8.39s/it]
736it [1:42:37,  8.38s/it]
737it [1:42:46,  8.38s/it]
738it [1:42:54,  8.37s/it]
739it [1:43:02,  8.35s/it]
740it [1:43:11,  8.35s/it]
741it [1:43:19,  8.34s/it]
742it [1:43:27,  8.34s/it]
743it [1:43:36,  8.35s/it]
744it [1:43:44,  8.33s/it]
745it [1:43:52,  8.34s/it]
746it [1:44:01,  8.33s/it]
747it [1:44:09,  8.32s/it]
748it [1:44:17,  8.31s/it]
749it [1:44:25,  8.29s/it]
750it [1:44:34,  8.28s/it]
751it [1:44:42,  8.31s/it]
752it [1:44:50,  8.32s/it]
753it [1:44:59,  8.31s/it]
754it [1:45:07,  8.34s/it]
755it [1:45:16,  8.35s/it]
756it [1:45:24,  8.35s/it]
757it [1:45:32,  8.34s/it]
758it [1:45:40,  8.32s/it]
759it [1:45:49,  8.32s/it]
760it [1:45:57,  8.31s/it]
761it [1:46:05,  8.31s/it]
762it [1:46:14,  8.30s/it]
763it [1:46:22,  8.30s/it]
764it [1:46:30,  8.30s/it]
765it [1:46:39,  8.29s/it]
766it [1:46:47,  8.29s/it]
767it [1:46:55,  8.30s/it]
768it [1:47:03,  8.29s/it]
769it [1:47:12,  8.28s/it]
770it [1:47:20,  8.29s/it]
771it [1:47:28,  8.32s/it]
772it [1:47:37,  8.34s/it]
773it [1:47:45,  8.34s/it]
774it [1:47:53,  8.35s/it]
775it [1:48:02,  8.38s/it]
776it [1:48:10,  8.37s/it]
777it [1:48:19,  8.39s/it]
778it [1:48:27,  8.40s/it]
779it [1:48:36,  8.40s/it]
780it [1:48:44,  8.39s/it]
781it [1:48:52,  8.38s/it]
782it [1:49:01,  8.37s/it]
783it [1:49:09,  8.36s/it]
784it [1:49:17,  8.39s/it]
785it [1:49:26,  8.37s/it]
786it [1:49:34,  8.39s/it]
787it [1:49:43,  8.41s/it]
788it [1:49:51,  8.41s/it]
789it [1:49:59,  8.41s/it]
790it [1:50:08,  8.41s/it]
791it [1:50:16,  8.40s/it]
792it [1:50:25,  8.39s/it]
793it [1:50:33,  8.39s/it]
794it [1:50:41,  8.38s/it]
795it [1:50:50,  8.38s/it]
796it [1:50:58,  8.39s/it]
797it [1:51:07,  8.39s/it]
798it [1:51:15,  8.41s/it]
799it [1:51:24,  8.44s/it]
800it [1:51:32,  8.45s/it]
801it [1:51:40,  8.45s/it]
802it [1:51:49,  8.45s/it]
803it [1:51:57,  8.44s/it]
804it [1:52:06,  8.41s/it]
805it [1:52:14,  8.41s/it]
806it [1:52:22,  8.41s/it]
807it [1:52:31,  8.41s/it]
808it [1:52:39,  8.40s/it]
809it [1:52:48,  8.40s/it]
810it [1:52:56,  8.41s/it]
811it [1:53:04,  8.39s/it]
812it [1:53:13,  8.44s/it]
813it [1:53:22,  8.50s/it]
814it [1:53:30,  8.49s/it]
815it [1:53:39,  8.54s/it]
816it [1:53:48,  8.61s/it]
817it [1:53:56,  8.66s/it]
818it [1:54:05,  8.63s/it]
819it [1:54:14,  8.67s/it]
820it [1:54:22,  8.70s/it]
821it [1:54:31,  8.69s/it]
822it [1:54:39,  8.62s/it]
823it [1:54:48,  8.56s/it]
824it [1:54:56,  8.52s/it]
825it [1:55:05,  8.49s/it]
826it [1:55:13,  8.47s/it]
827it [1:55:22,  8.44s/it]
828it [1:55:30,  8.42s/it]
829it [1:55:38,  8.42s/it]
830it [1:55:47,  8.41s/it]
831it [1:55:55,  8.41s/it]
832it [1:56:04,  8.42s/it]
833it [1:56:12,  8.49s/it]
834it [1:56:21,  8.45s/it]
835it [1:56:29,  8.43s/it]
836it [1:56:37,  8.44s/it]
837it [1:56:46,  8.43s/it]
838it [1:56:54,  8.41s/it]
839it [1:57:03,  8.42s/it]
840it [1:57:11,  8.41s/it]
841it [1:57:19,  8.41s/it]
842it [1:57:28,  8.40s/it]
843it [1:57:36,  8.40s/it]
844it [1:57:45,  8.37s/it]
845it [1:57:53,  8.40s/it]
846it [1:58:01,  8.38s/it]
847it [1:58:10,  8.37s/it]
848it [1:58:18,  8.35s/it]
849it [1:58:26,  8.36s/it]
850it [1:58:35,  8.36s/it]
851it [1:58:43,  8.38s/it]
852it [1:58:52,  8.37s/it]
853it [1:59:00,  8.37s/it]
854it [1:59:08,  8.38s/it]
855it [1:59:17,  8.38s/it]
856it [1:59:25,  8.38s/it]
857it [1:59:33,  8.36s/it]
858it [1:59:42,  8.35s/it]
859it [1:59:50,  8.37s/it]
860it [1:59:58,  8.36s/it]
861it [2:00:07,  8.40s/it]
862it [2:00:15,  8.41s/it]
863it [2:00:24,  8.40s/it]
864it [2:00:32,  8.41s/it]
865it [2:00:41,  8.40s/it]
866it [2:00:49,  8.40s/it]
867it [2:00:57,  8.40s/it]
868it [2:01:06,  8.38s/it]
869it [2:01:14,  8.39s/it]
870it [2:01:23,  8.39s/it]
871it [2:01:31,  8.37s/it]
872it [2:01:39,  8.40s/it]
873it [2:01:48,  8.40s/it]
874it [2:01:56,  8.42s/it]
875it [2:02:05,  8.44s/it]
876it [2:02:13,  8.43s/it]
877it [2:02:21,  8.40s/it]
878it [2:02:30,  8.39s/it]
879it [2:02:38,  8.38s/it]
880it [2:02:47,  8.39s/it]
881it [2:02:55,  8.38s/it]
882it [2:03:03,  8.42s/it]
883it [2:03:12,  8.42s/it]
884it [2:03:20,  8.42s/it]
885it [2:03:29,  8.41s/it]
886it [2:03:37,  8.40s/it]
887it [2:03:45,  8.38s/it]
888it [2:03:54,  8.38s/it]
889it [2:04:02,  8.40s/it]
890it [2:04:11,  8.40s/it]
891it [2:04:19,  8.39s/it]
892it [2:04:27,  8.39s/it]
893it [2:04:36,  8.39s/it]
894it [2:04:44,  8.37s/it]
895it [2:04:52,  8.38s/it]
896it [2:05:01,  8.39s/it]
897it [2:05:09,  8.37s/it]
898it [2:05:18,  8.37s/it]
899it [2:05:26,  8.38s/it]
900it [2:05:34,  8.40s/it]
901it [2:05:43,  8.42s/it]
902it [2:05:51,  8.41s/it]
903it [2:06:00,  8.39s/it]
904it [2:06:08,  8.39s/it]
905it [2:06:16,  8.37s/it]
906it [2:06:25,  8.37s/it]
907it [2:06:33,  8.34s/it]
908it [2:06:41,  8.35s/it]
909it [2:06:50,  8.37s/it]
910it [2:06:58,  8.38s/it]
911it [2:07:06,  8.36s/it]
912it [2:07:15,  8.35s/it]
913it [2:07:23,  8.35s/it]
914it [2:07:31,  8.34s/it]
915it [2:07:40,  8.33s/it]
916it [2:07:48,  8.34s/it]
917it [2:07:56,  8.34s/it]
918it [2:08:05,  8.34s/it]
919it [2:08:13,  8.34s/it]
920it [2:08:21,  8.35s/it]
921it [2:08:30,  8.33s/it]
922it [2:08:38,  8.34s/it]
923it [2:08:47,  8.36s/it]
924it [2:08:55,  8.35s/it]
925it [2:09:03,  8.33s/it]
926it [2:09:11,  8.33s/it]
927it [2:09:20,  8.33s/it]
928it [2:09:28,  8.35s/it]
929it [2:09:37,  8.34s/it]
930it [2:09:45,  8.33s/it]
931it [2:09:53,  8.34s/it]
932it [2:10:02,  8.33s/it]
933it [2:10:10,  8.35s/it]
934it [2:10:18,  8.34s/it]
935it [2:10:27,  8.33s/it]
936it [2:10:35,  8.34s/it]
937it [2:10:43,  8.33s/it]
938it [2:10:52,  8.33s/it]
939it [2:11:00,  8.33s/it]
940it [2:11:08,  8.32s/it]
941it [2:11:17,  8.33s/it]
942it [2:11:25,  8.35s/it]
943it [2:11:33,  8.34s/it]
944it [2:11:42,  8.34s/it]
945it [2:11:50,  8.32s/it]
946it [2:11:58,  8.31s/it]
947it [2:12:06,  8.31s/it]
948it [2:12:15,  8.31s/it]
949it [2:12:23,  8.31s/it]
950it [2:12:31,  8.30s/it]
951it [2:12:40,  8.30s/it]
952it [2:12:48,  8.31s/it]
953it [2:12:56,  8.29s/it]
954it [2:13:05,  8.31s/it]
955it [2:13:13,  8.32s/it]
956it [2:13:21,  8.29s/it]
957it [2:13:29,  8.30s/it]
958it [2:13:38,  8.30s/it]
959it [2:13:46,  8.34s/it]
960it [2:13:55,  8.34s/it]
961it [2:14:03,  8.34s/it]
962it [2:14:11,  8.32s/it]
963it [2:14:19,  8.32s/it]
964it [2:14:28,  8.32s/it]
965it [2:14:36,  8.31s/it]
966it [2:14:44,  8.33s/it]
967it [2:14:53,  8.33s/it]
968it [2:15:01,  8.32s/it]
969it [2:15:09,  8.34s/it]
970it [2:15:18,  8.32s/it]
971it [2:15:26,  8.33s/it]
972it [2:15:34,  8.34s/it]
973it [2:15:43,  8.34s/it]
974it [2:15:51,  8.35s/it]
975it [2:15:59,  8.34s/it]
976it [2:16:08,  8.35s/it]
977it [2:16:16,  8.35s/it]
978it [2:16:24,  8.34s/it]
979it [2:16:33,  8.37s/it]
980it [2:16:41,  8.36s/it]
981it [2:16:50,  8.38s/it]
982it [2:16:58,  8.41s/it]
983it [2:17:07,  8.41s/it]
984it [2:17:15,  8.39s/it]
985it [2:17:23,  8.38s/it]
986it [2:17:32,  8.39s/it]
987it [2:17:40,  8.37s/it]
988it [2:17:48,  8.36s/it]
989it [2:17:57,  8.35s/it]
990it [2:18:05,  8.38s/it]
991it [2:18:13,  8.36s/it]
992it [2:18:22,  8.34s/it]
993it [2:18:30,  8.33s/it]
994it [2:18:38,  8.34s/it]
995it [2:18:47,  8.45s/it]
996it [2:18:56,  8.49s/it]
997it [2:19:04,  8.48s/it]
998it [2:19:13,  8.50s/it]
999it [2:19:21,  8.57s/it]
1000it [2:19:30,  8.52s/it]
1000it [2:19:30,  8.37s/it]
Error counts:
	cysteine_to_N_cyclization: 0Completed process in 5:26:29.153023

0it [00:00, ?it/s]
1it [00:10, 10.76s/it]
2it [00:21, 10.59s/it]
3it [00:31, 10.61s/it]
4it [00:42, 10.58s/it]
5it [00:52, 10.56s/it]
6it [01:03, 10.62s/it]
7it [01:14, 10.61s/it]
8it [01:24, 10.64s/it]
9it [01:35, 10.69s/it]
10it [01:46, 10.73s/it]
11it [01:57, 10.67s/it]
12it [02:07, 10.65s/it]
13it [02:18, 10.66s/it]
14it [02:29, 10.68s/it]
15it [02:39, 10.67s/it]
16it [02:50, 10.62s/it]
17it [03:00, 10.62s/it]
18it [03:11, 10.69s/it]
19it [03:22, 10.75s/it]
20it [03:33, 10.69s/it]
21it [03:43, 10.66s/it]
22it [03:54, 10.62s/it]
23it [04:04, 10.59s/it]
24it [04:15, 10.56s/it]
25it [04:25, 10.54s/it]
26it [04:36, 10.55s/it]
27it [04:46, 10.55s/it]
28it [04:57, 10.54s/it]
29it [05:07, 10.52s/it]
30it [05:18, 10.52s/it]
31it [05:28, 10.52s/it]
32it [05:39, 10.52s/it]
33it [05:50, 10.52s/it]
34it [06:00, 10.54s/it]
35it [06:11, 10.56s/it]
36it [06:21, 10.55s/it]
37it [06:32, 10.55s/it]
38it [06:42, 10.55s/it]
39it [06:53, 10.56s/it]
40it [07:03, 10.54s/it]
41it [07:14, 10.55s/it]
42it [07:25, 10.68s/it]
43it [07:36, 10.67s/it]
44it [07:46, 10.60s/it]
45it [07:57, 10.58s/it]
46it [08:07, 10.58s/it]
47it [08:18, 10.56s/it]
48it [08:28, 10.56s/it]
49it [08:39, 10.57s/it]
50it [08:49, 10.58s/it]
51it [09:00, 10.57s/it]
52it [09:11, 10.57s/it]
53it [09:21, 10.63s/it]
54it [09:32, 10.75s/it]
55it [09:43, 10.81s/it]
56it [09:54, 10.82s/it]
57it [10:05, 10.87s/it]
58it [10:16, 10.91s/it]
59it [10:27, 10.79s/it]
60it [10:37, 10.73s/it]
61it [10:48, 10.69s/it]
62it [10:59, 10.69s/it]
63it [11:09, 10.67s/it]
64it [11:20, 10.63s/it]
65it [11:30, 10.60s/it]
66it [11:41, 10.61s/it]
67it [11:51, 10.61s/it]
68it [12:02, 10.58s/it]
69it [12:13, 10.58s/it]
70it [12:23, 10.58s/it]
71it [12:34, 10.55s/it]
72it [12:44, 10.54s/it]
73it [12:55, 10.59s/it]
74it [13:06, 10.75s/it]
75it [13:17, 10.74s/it]
76it [13:27, 10.68s/it]
77it [13:38, 10.63s/it]
78it [13:48, 10.61s/it]
79it [13:59, 10.59s/it]
80it [14:10, 10.64s/it]
81it [14:21, 10.82s/it]
82it [14:32, 10.91s/it]
83it [14:43, 10.89s/it]
84it [14:53, 10.80s/it]
85it [15:04, 10.87s/it]
86it [15:15, 10.93s/it]
87it [15:26, 10.82s/it]
88it [15:37, 10.75s/it]
89it [15:48, 10.80s/it]
90it [15:58, 10.82s/it]
91it [16:09, 10.87s/it]
92it [16:20, 10.79s/it]
93it [16:31, 10.72s/it]
94it [16:41, 10.67s/it]
95it [16:52, 10.66s/it]
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930it [2:44:43, 10.62s/it]
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966it [2:51:03, 10.51s/it]
967it [2:51:14, 10.50s/it]
968it [2:51:24, 10.49s/it]
969it [2:51:35, 10.49s/it]
970it [2:51:45, 10.47s/it]
971it [2:51:56, 10.48s/it]
972it [2:52:06, 10.49s/it]
973it [2:52:17, 10.50s/it]
974it [2:52:27, 10.50s/it]
975it [2:52:38, 10.50s/it]
976it [2:52:48, 10.51s/it]
977it [2:52:59, 10.51s/it]
978it [2:53:09, 10.49s/it]
979it [2:53:20, 10.51s/it]
980it [2:53:30, 10.49s/it]
981it [2:53:41, 10.49s/it]
982it [2:53:51, 10.48s/it]
983it [2:54:02, 10.50s/it]
984it [2:54:12, 10.49s/it]
985it [2:54:22, 10.47s/it]
986it [2:54:33, 10.47s/it]
987it [2:54:43, 10.46s/it]
988it [2:54:54, 10.45s/it]
989it [2:55:04, 10.45s/it]
990it [2:55:15, 10.47s/it]
991it [2:55:25, 10.46s/it]
992it [2:55:36, 10.45s/it]
993it [2:55:46, 10.45s/it]
994it [2:55:56, 10.44s/it]
995it [2:56:07, 10.46s/it]
996it [2:56:17, 10.45s/it]
997it [2:56:28, 10.45s/it]
998it [2:56:38, 10.45s/it]
999it [2:56:49, 10.46s/it]
1000it [2:56:59, 10.45s/it]
1000it [2:56:59, 10.62s/it]
Error counts:
	cyclic_id: 0
	cyclic_inchikey: 0
	cyclic_scaffold: 0
	cyclic_mwt: 0
	cyclic_clogp: 0
	cyclic_tpsa: 0Completed process in 8:23:29.802625

0it [00:00, ?it/s]
1it [00:00,  9.70it/s]
2it [00:00,  9.51it/s]
3it [00:00,  9.59it/s]
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8it [00:00,  9.57it/s]
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970it [01:41,  9.50it/s]
971it [01:41,  9.53it/s]
972it [01:42,  9.49it/s]
973it [01:42,  9.51it/s]
974it [01:42,  9.52it/s]
975it [01:42,  9.47it/s]
976it [01:42,  9.51it/s]
977it [01:42,  9.50it/s]
978it [01:42,  9.50it/s]
979it [01:42,  9.50it/s]
980it [01:42,  9.49it/s]
981it [01:42,  9.48it/s]
982it [01:43,  9.50it/s]
983it [01:43,  9.52it/s]
984it [01:43,  9.50it/s]
985it [01:43,  9.51it/s]
986it [01:43,  9.52it/s]
987it [01:43,  9.55it/s]
988it [01:43,  9.58it/s]
989it [01:43,  9.54it/s]
990it [01:43,  9.53it/s]
991it [01:44,  9.57it/s]
992it [01:44,  9.59it/s]
993it [01:44,  9.54it/s]
994it [01:44,  9.55it/s]
995it [01:44,  9.56it/s]
996it [01:44,  9.60it/s]
997it [01:44,  9.58it/s]
998it [01:44,  9.56it/s]
999it [01:44,  9.56it/s]
1000it [01:44,  9.50it/s]
1000it [01:44,  9.53it/s]
Split counts:
	train: 674000
	test: 164000
	validation: 162000Completed process in 8:25:15.727317
++ date
+ echo 'Sat  2 Nov 00:25:14 GMT 2024 :: 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.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-36000000-37000000.csv.gz
+ split_dir=20241101_peptides_6-12x100M/train
++ basename 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz .csv.gz
+ split_file=20241101_peptides_6-12x100M/train/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz
+ mkdir -p 20241101_peptides_6-12x100M/train
++ date
+ echo 'Sat  2 Nov 00:25:14 GMT 2024 :: Saving train...'
Sat  2 Nov 00:25:14 GMT 2024 :: Saving train...
+ zcat 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.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 00:26:12 GMT 2024 :: 20241101_peptides_6-12x100M/train/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz'
+ for split in train test validation
++ dirname 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz
+ split_dir=20241101_peptides_6-12x100M/test
++ basename 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz .csv.gz
+ split_file=20241101_peptides_6-12x100M/test/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz
+ mkdir -p 20241101_peptides_6-12x100M/test
++ date
+ echo 'Sat  2 Nov 00:26:12 GMT 2024 :: Saving test...'
Sat  2 Nov 00:26:12 GMT 2024 :: Saving test...
+ zcat 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.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 00:26:37 GMT 2024 :: 20241101_peptides_6-12x100M/test/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz'
+ for split in train test validation
++ dirname 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz
+ split_dir=20241101_peptides_6-12x100M/validation
++ basename 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz .csv.gz
+ split_file=20241101_peptides_6-12x100M/validation/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz
+ mkdir -p 20241101_peptides_6-12x100M/validation
++ date
+ echo 'Sat  2 Nov 00:26:37 GMT 2024 :: Saving validation...'
Sat  2 Nov 00:26:37 GMT 2024 :: Saving validation...
+ zcat 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.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 00:27:02 GMT 2024 :: 20241101_peptides_6-12x100M/validation/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz'
+ '[' -e 20241101_peptides_6-12x100M/validation/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz.success ']'
+ rm 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-36000000-37000000.csv.gz.success
+ set +x
Sat  2 Nov 00:27:02 GMT 2024 > Peptide generation complete