20241101_peptides_6-12x100M_l-10_n-100000000_slice-100000000-101000000.log

Fri  1 Nov 16:08:12 GMT 2024 > Generating peptides on cn076
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 16:08:12 GMT 2024 > Running /camp/apps/eb/software/Anaconda3/2023.03/bin/python : Python 3.10.10
Fri  1 Nov 16:08:12 GMT 2024 > Using Conda from .
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Fri  1 Nov 16:08:12 GMT 2024 > Seed = 1; length = 10; max. number = 100000000; slice = 100000000 to 101000000; output dir. = 20241101_peptides_6-12x100M
Fri  1 Nov 16:08:12 GMT 2024 > There are 10240000000000 peptides of length 10; generating 100000000 (0.000976563 %)
Fri  1 Nov 16:08:12 GMT 2024 > Saving a slice to 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz...
+ schemist enumerate --seed 1 --max-length 10 --prefix GY --suffix CGSGSGS --number 9.76563e-06 --slice 100000000 101000000
+ schemist convert --column cysteine_to_N_cyclization --to id inchikey scaffold mwt clogp tpsa --prefix cyclic_ --options prefix=SCB-
+ tr '	' ,
+ 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
+ gzip --best
+ schemist convert --column SMILES --to id inchikey scaffold mwt clogp tpsa --prefix linear_ --options prefix=SCB-
🚀 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 0x7f95827af4c0>
🚀 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 0x7fd3c2bcf9c0>
🚀 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: ['100000000', '101000000']
	seed: 1
	prefix: GY
	suffix: CGSGSGS
	type: aa
	d_aa_only: False
	include_d_aa: False
	func: <function _enum at 0x7fbfdb37b880>
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. 
🚀 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 0x7f7703877240>
🚀 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 0x7fa10f0ef240>

0it [00:00, ?it/s]
1it [02:48, 168.59s/it]
1it [02:48, 168.59s/it]
Enumerated peptides:
	Number of peptides: 51
Conversion errors:
	SMILES: 0
⏰ Completed process in 0:02:48.599034

0it [00:00, ?it/s]
1it [00:00,  1.88it/s]
1it [00:00,  1.88it/s]
Error counts:
	linear_id: 0
	linear_inchikey: 0
	linear_scaffold: 0
	linear_mwt: 0
	linear_clogp: 0
	linear_tpsa: 0
⏰ Completed process in 0:02:49.321494

0it [00:00, ?it/s]
1it [00:00,  2.38it/s]
1it [00:00,  2.37it/s]
Error counts:
	cysteine_to_N_cyclization: 0
⏰ Completed process in 0:02:49.912195

0it [00:00, ?it/s]
1it [00:00,  1.81it/s]
1it [00:00,  1.81it/s]
Error counts:
	cyclic_id: 0
	cyclic_inchikey: 0
	cyclic_scaffold: 0
	cyclic_mwt: 0
	cyclic_clogp: 0
	cyclic_tpsa: 0
⏰ Completed process in 0:02:50.627683

0it [00:00, ?it/s]
1it [00:00, 152.87it/s]
Split counts:
	train: 35
	test: 10
	validation: 6
⏰ Completed process in 0:02:50.828585
++ date
+ echo 'Fri  1 Nov 16:11:11 GMT 2024 :: 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.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-100000000-101000000.csv.gz
+ split_dir=20241101_peptides_6-12x100M/train
++ basename 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz .csv.gz
+ split_file=20241101_peptides_6-12x100M/train/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz
+ mkdir -p 20241101_peptides_6-12x100M/train
++ date
+ echo 'Fri  1 Nov 16:11:11 GMT 2024 :: Saving train...'
Fri  1 Nov 16:11:11 GMT 2024 :: Saving train...
+ zcat 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.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 'Fri  1 Nov 16:11:11 GMT 2024 :: 20241101_peptides_6-12x100M/train/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz'
+ for split in train test validation
++ dirname 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz
+ split_dir=20241101_peptides_6-12x100M/test
++ basename 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz .csv.gz
+ split_file=20241101_peptides_6-12x100M/test/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz
+ mkdir -p 20241101_peptides_6-12x100M/test
++ date
+ echo 'Fri  1 Nov 16:11:11 GMT 2024 :: Saving test...'
Fri  1 Nov 16:11:11 GMT 2024 :: Saving test...
+ zcat 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.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 'Fri  1 Nov 16:11:11 GMT 2024 :: 20241101_peptides_6-12x100M/test/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz'
+ for split in train test validation
++ dirname 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz
+ split_dir=20241101_peptides_6-12x100M/validation
++ basename 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz .csv.gz
+ split_file=20241101_peptides_6-12x100M/validation/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz
+ mkdir -p 20241101_peptides_6-12x100M/validation
++ date
+ echo 'Fri  1 Nov 16:11:11 GMT 2024 :: Saving validation...'
Fri  1 Nov 16:11:11 GMT 2024 :: Saving validation...
+ zcat 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.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 'Fri  1 Nov 16:11:11 GMT 2024 :: 20241101_peptides_6-12x100M/validation/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz'
+ '[' -e 20241101_peptides_6-12x100M/validation/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz.success ']'
+ rm 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz 20241101_peptides_6-12x100M/peptides_length-10_n-100000000_slice-100000000-101000000.csv.gz.success
+ set +x
Fri  1 Nov 16:11:11 GMT 2024 > Peptide generation complete