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parallelization, improved accuracy calculation
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,77 @@ | ||
| import sstar | ||
| import utils | ||
| import os | ||
| import demes | ||
| import numpy as np | ||
| import pandas as pd | ||
| from scipy.stats import norm | ||
| from scipy.stats import nbinom | ||
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| import train | ||
| import infer | ||
| import preprocess | ||
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| import argparse, os, sys, signal | ||
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| #def main(args=None): | ||
| def main(demo_model_file, nrep, nref, ntgt, ref_id, tgt_id, src_id, seq_len, mut_rate, rec_rate, thread, output_prefix, output_dir, seed, model_name): | ||
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| ref_ind_file = str(demo_model_file) + "_new_sim" + "_nref" + str(nref) + "_ntgt" + str(ntgt) + ".ref.ind.list" | ||
| tgt_ind_file = str(demo_model_file) + "_new_sim" + "_nref" + str(nref) + "_ntgt" + str(ntgt) + ".tgt.ind.list" | ||
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| #ref_ind_file = os.path.join("config", "simulation", "nref_" + str(nref), "ntgt_" + str(ntgt), "ref.scr1.list") | ||
| #tgt_ind_file = os.path.join("config", "simulation", "nref_" + str(nref), "ntgt_" + str(ntgt), "sim.src1.list") | ||
| scikitfile = output_prefix + ".scikit.pickle" | ||
| statsmodelsfile = output_prefix + ".statsmodels.pickle" | ||
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| final_folders = infer.get_all_folders(model_name, os.path.join("nref_" + str(nref), "ntgt_" + str(ntgt))) | ||
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| sample_name = "nref_" + str(nref) + "_ntgt_" + str(ntgt) | ||
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| #infer.predict_introgression_folders(nrep, nref, ntgt, seq_len, thread, output_prefix+ "test", final_folders, statsmodel=statsmodelsfile, scikitmodel=scikitfile, sample_name=sample_name, ref_ind_file=ref_ind_file, tgt_ind_file=tgt_ind_file, model_name=model_name, drop_dynamic_cols=False, evaluate=False, simulated=True, average_for_inference=False, compute_cutoffs=True, win_step_50k = False) | ||
| #without ref_ and tgt_ind_file (are created within infer) | ||
| infer.predict_introgression_folders(nrep, nref, ntgt, seq_len, thread, output_prefix+ "test", final_folders, statsmodel=statsmodelsfile, scikitmodel=scikitfile, sample_name=sample_name, ref_ind_file=ref_ind_file, tgt_ind_file=tgt_ind_file, model_name=model_name, drop_dynamic_cols=False, evaluate=False, simulated=True, average_for_inference=False, compute_cutoffs=True, win_step_50k = False) | ||
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| if __name__ == "__main__": | ||
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| parser = argparse.ArgumentParser() | ||
| parser.add_argument('--demo_model_file',type=str, required=True) | ||
| parser.add_argument('--nrep', type=int, required=True) | ||
| parser.add_argument('--nref', type=int, required=True) | ||
| parser.add_argument('--ntgt',type=int, required=True) | ||
| parser.add_argument('--ref_id',type=str, required=True) | ||
| parser.add_argument('--tgt_id', type=str, required=True) | ||
| parser.add_argument('--src_id', type=str, required=True) | ||
| parser.add_argument('--seq_len', type=int, required=True) | ||
| parser.add_argument('--mut_rate',type=float, required=True) | ||
| parser.add_argument('--rec_rate',type=float, required=True) | ||
| parser.add_argument('--thread',type=int, required=True) | ||
| parser.add_argument('--output_prefix',type=str, required=True) | ||
| parser.add_argument('--output_dir',type=str, required=True) | ||
| parser.add_argument('--seed',required=True) | ||
| parser.add_argument('--model_name',type=str,required=True) | ||
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| args = parser.parse_args() | ||
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| demo_model_file = args.demo_model_file | ||
| nrep = args.nrep | ||
| nref = args.nref | ||
| ntgt = args.ntgt | ||
| ref_id = args.ref_id | ||
| tgt_id = args.tgt_id | ||
| src_id = args.src_id | ||
| seq_len = args.seq_len | ||
| mut_rate = args.mut_rate | ||
| rec_rate = args.rec_rate | ||
| thread = args.thread | ||
| output_prefix = args.output_prefix | ||
| output_dir = args.output_dir | ||
| if args.seed == "None": | ||
| seed = None | ||
| else: | ||
| seed = int(args.seed) | ||
| model_name=args.model_name | ||
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| main(demo_model_file, nrep, nref, ntgt, ref_id, tgt_id, src_id, seq_len, mut_rate, rec_rate, thread, output_prefix, output_dir, seed,model_name) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,77 @@ | ||
| import sstar | ||
| import utils | ||
| import os | ||
| import demes | ||
| import numpy as np | ||
| import pandas as pd | ||
| from scipy.stats import norm | ||
| from scipy.stats import nbinom | ||
|
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||
| import train | ||
| import infer | ||
| import preprocess | ||
|
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| import argparse, os, sys, signal | ||
|
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| #def main(args=None): | ||
| def main(demo_model_file, nrep, nref, ntgt, ref_id, tgt_id, src_id, seq_len, mut_rate, rec_rate, thread, output_prefix, output_dir, seed, model_name): | ||
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| ref_ind_file = str(demo_model_file) + "_new_sim" + "_nref" + str(nref) + "_ntgt" + str(ntgt) + ".ref.ind.list" | ||
| tgt_ind_file = str(demo_model_file) + "_new_sim" + "_nref" + str(nref) + "_ntgt" + str(ntgt) + ".tgt.ind.list" | ||
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| #ref_ind_file = os.path.join("config", "simulation", "nref_" + str(nref), "ntgt_" + str(ntgt), "ref.scr1.list") | ||
| #tgt_ind_file = os.path.join("config", "simulation", "nref_" + str(nref), "ntgt_" + str(ntgt), "sim.src1.list") | ||
| scikitfile = output_prefix + ".scikit.pickle" | ||
| statsmodelsfile = output_prefix + ".statsmodels.pickle" | ||
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| final_folders = infer.get_all_folders(model_name, os.path.join("nref_" + str(nref), "ntgt_" + str(ntgt))) | ||
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| sample_name = "nref_" + str(nref) + "_ntgt_" + str(ntgt) | ||
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| #infer.predict_introgression_folders(nrep, nref, ntgt, seq_len, thread, output_prefix+ "test", final_folders, statsmodel=statsmodelsfile, scikitmodel=scikitfile, sample_name=sample_name, ref_ind_file=ref_ind_file, tgt_ind_file=tgt_ind_file, model_name=model_name, drop_dynamic_cols=False, evaluate=False, simulated=True, average_for_inference=False, compute_cutoffs=True, win_step_50k = False) | ||
| #without ref_ and tgt_ind_file (are created within infer) | ||
| infer.predict_introgression_folders_allmodeltypes(nrep, nref, ntgt, seq_len, thread, output_prefix+ "test", final_folders, statsmodel=statsmodelsfile, scikitmodel=scikitfile, sample_name=sample_name, ref_ind_file=ref_ind_file, tgt_ind_file=tgt_ind_file, model_name=model_name, drop_dynamic_cols=False, evaluate=False, simulated=True, average_for_inference=False, compute_cutoffs=True, win_step_50k = False) | ||
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| if __name__ == "__main__": | ||
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| parser = argparse.ArgumentParser() | ||
| parser.add_argument('--demo_model_file',type=str, required=True) | ||
| parser.add_argument('--nrep', type=int, required=True) | ||
| parser.add_argument('--nref', type=int, required=True) | ||
| parser.add_argument('--ntgt',type=int, required=True) | ||
| parser.add_argument('--ref_id',type=str, required=True) | ||
| parser.add_argument('--tgt_id', type=str, required=True) | ||
| parser.add_argument('--src_id', type=str, required=True) | ||
| parser.add_argument('--seq_len', type=int, required=True) | ||
| parser.add_argument('--mut_rate',type=float, required=True) | ||
| parser.add_argument('--rec_rate',type=float, required=True) | ||
| parser.add_argument('--thread',type=int, required=True) | ||
| parser.add_argument('--output_prefix',type=str, required=True) | ||
| parser.add_argument('--output_dir',type=str, required=True) | ||
| parser.add_argument('--seed',required=True) | ||
| parser.add_argument('--model_name',type=str,required=True) | ||
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| args = parser.parse_args() | ||
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| demo_model_file = args.demo_model_file | ||
| nrep = args.nrep | ||
| nref = args.nref | ||
| ntgt = args.ntgt | ||
| ref_id = args.ref_id | ||
| tgt_id = args.tgt_id | ||
| src_id = args.src_id | ||
| seq_len = args.seq_len | ||
| mut_rate = args.mut_rate | ||
| rec_rate = args.rec_rate | ||
| thread = args.thread | ||
| output_prefix = args.output_prefix | ||
| output_dir = args.output_dir | ||
| if args.seed == "None": | ||
| seed = None | ||
| else: | ||
| seed = int(args.seed) | ||
| model_name=args.model_name | ||
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| main(demo_model_file, nrep, nref, ntgt, ref_id, tgt_id, src_id, seq_len, mut_rate, rec_rate, thread, output_prefix, output_dir, seed,model_name) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,77 @@ | ||
| import sstar | ||
| import utils | ||
| import os | ||
| import demes | ||
| import numpy as np | ||
| import pandas as pd | ||
| from scipy.stats import norm | ||
| from scipy.stats import nbinom | ||
|
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| import train | ||
| import infer | ||
| import preprocess | ||
|
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| import argparse, os, sys, signal | ||
|
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| #def main(args=None): | ||
| def main(demo_model_file, nrep, nref, ntgt, ref_id, tgt_id, src_id, seq_len, mut_rate, rec_rate, thread, output_prefix, output_dir, seed, model_name): | ||
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| ref_ind_file = str(demo_model_file) + "_new_sim" + "_nref" + str(nref) + "_ntgt" + str(ntgt) + ".ref.ind.list" | ||
| tgt_ind_file = str(demo_model_file) + "_new_sim" + "_nref" + str(nref) + "_ntgt" + str(ntgt) + ".tgt.ind.list" | ||
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| #ref_ind_file = os.path.join("config", "simulation", "nref_" + str(nref), "ntgt_" + str(ntgt), "ref.scr1.list") | ||
| #tgt_ind_file = os.path.join("config", "simulation", "nref_" + str(nref), "ntgt_" + str(ntgt), "sim.src1.list") | ||
| scikitfile = output_prefix + ".scikit.pickle" | ||
| statsmodelsfile = output_prefix + ".statsmodels.pickle" | ||
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| final_folders = infer.get_all_folders(model_name, os.path.join("nref_" + str(nref), "ntgt_" + str(ntgt))) | ||
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| sample_name = "nref_" + str(nref) + "_ntgt_" + str(ntgt) | ||
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| #infer.predict_introgression_folders(nrep, nref, ntgt, seq_len, thread, output_prefix+ "test", final_folders, statsmodel=statsmodelsfile, scikitmodel=scikitfile, sample_name=sample_name, ref_ind_file=ref_ind_file, tgt_ind_file=tgt_ind_file, model_name=model_name, drop_dynamic_cols=False, evaluate=False, simulated=True, average_for_inference=False, compute_cutoffs=True, win_step_50k = False) | ||
| #without ref_ and tgt_ind_file (are created within infer) | ||
| infer.predict_introgression_folders(nrep, nref, ntgt, seq_len, thread, output_prefix+ "test", final_folders, statsmodel=statsmodelsfile, scikitmodel=scikitfile, sample_name=sample_name, ref_ind_file=ref_ind_file, tgt_ind_file=tgt_ind_file, model_name=model_name, drop_dynamic_cols=False, evaluate=False, simulated=True, average_for_inference=False, compute_cutoffs=True, win_step_50k = False, use_haplotype_acc=True) | ||
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| if __name__ == "__main__": | ||
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| parser = argparse.ArgumentParser() | ||
| parser.add_argument('--demo_model_file',type=str, required=True) | ||
| parser.add_argument('--nrep', type=int, required=True) | ||
| parser.add_argument('--nref', type=int, required=True) | ||
| parser.add_argument('--ntgt',type=int, required=True) | ||
| parser.add_argument('--ref_id',type=str, required=True) | ||
| parser.add_argument('--tgt_id', type=str, required=True) | ||
| parser.add_argument('--src_id', type=str, required=True) | ||
| parser.add_argument('--seq_len', type=int, required=True) | ||
| parser.add_argument('--mut_rate',type=float, required=True) | ||
| parser.add_argument('--rec_rate',type=float, required=True) | ||
| parser.add_argument('--thread',type=int, required=True) | ||
| parser.add_argument('--output_prefix',type=str, required=True) | ||
| parser.add_argument('--output_dir',type=str, required=True) | ||
| parser.add_argument('--seed',required=True) | ||
| parser.add_argument('--model_name',type=str,required=True) | ||
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| args = parser.parse_args() | ||
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| demo_model_file = args.demo_model_file | ||
| nrep = args.nrep | ||
| nref = args.nref | ||
| ntgt = args.ntgt | ||
| ref_id = args.ref_id | ||
| tgt_id = args.tgt_id | ||
| src_id = args.src_id | ||
| seq_len = args.seq_len | ||
| mut_rate = args.mut_rate | ||
| rec_rate = args.rec_rate | ||
| thread = args.thread | ||
| output_prefix = args.output_prefix | ||
| output_dir = args.output_dir | ||
| if args.seed == "None": | ||
| seed = None | ||
| else: | ||
| seed = int(args.seed) | ||
| model_name=args.model_name | ||
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| main(demo_model_file, nrep, nref, ntgt, ref_id, tgt_id, src_id, seq_len, mut_rate, rec_rate, thread, output_prefix, output_dir, seed,model_name) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,137 @@ | ||
| import sstar | ||
| import utils | ||
| import os | ||
| import demes | ||
| import numpy as np | ||
| import pandas as pd | ||
| from scipy.stats import norm | ||
| from scipy.stats import nbinom | ||
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| import train | ||
| import infer | ||
| import preprocess | ||
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| import argparse, os, sys, signal | ||
| import shutil | ||
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| def main(demo_model_file, nrep, nref, ntgt, ref_id, tgt_id, src_id, seq_len, mut_rate, rec_rate, thread, output_prefix, output_dir, seed, folder_partitions, create_testdirs = False, train_file_name=None): | ||
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| if train_file_name == None: | ||
| train_file_name = str(demo_model_file) + "_nref" + str(nref) + "_ntgt" + str(ntgt) + "_finalfeaturefile.csv" | ||
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| train_df = pd.read_csv(train_file_name) | ||
| #drop_dynamic_cols indicate whether non-fixed size features should be dropped | ||
| train_df_reduced = train_df.copy() | ||
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| train_df_no_kurtosis = train_df.copy() | ||
| train_df_no_paired_dist = train_df.copy() | ||
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| train_df_target_full_reduced = train_df.copy() | ||
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| dynamic_cols = [col for col in train_df.columns if ('-ton' in col or col.startswith("pairwised_dist"))] | ||
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| no_kurtosis_cols = [col for col in train_df.columns if ('kurtosis_pairwised_dist' in col or col.startswith("pairwised_dist")) ] | ||
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| no_paired_cols = [col for col in train_df.columns if (col.startswith("pairwised_dist"))] | ||
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| full_reduced_cols = [col for col in train_df.columns if ('-ton' in col or 'pairwised_dist' in col )] | ||
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| train_df_reduced.drop(dynamic_cols, axis=1, inplace = True, errors='ignore') | ||
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| train_df_no_kurtosis.drop(no_kurtosis_cols, axis=1, inplace = True, errors='ignore') | ||
| train_df_no_paired_dist.drop(no_paired_cols, axis=1, inplace = True, errors='ignore') | ||
| train_df_target_full_reduced.drop(full_reduced_cols, axis=1, inplace = True, errors='ignore') | ||
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| #train_df.to_csv(str(demo_model_file) + "_nref" + str(nref) + "_ntgt" + str(ntgt) + "_finalfeaturefile.csv") | ||
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| train_df_reduced.to_csv(str(demo_model_file) + "_nref" + str(nref) + "_ntgt" + str(ntgt) + "_finalfeaturefile_fixed.csv") | ||
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| train_df_no_kurtosis.to_csv(str(demo_model_file) + "_nref" + str(nref) + "_ntgt" + str(ntgt) + "_finalfeaturefile_nokurtosis.csv") | ||
| train_df_no_paired_dist.to_csv(str(demo_model_file) + "_nref" + str(nref) + "_ntgt" + str(ntgt) + "_finalfeaturefile_nopaired.csv") | ||
| train_df_target_full_reduced.to_csv(str(demo_model_file) + "_nref" + str(nref) + "_ntgt" + str(ntgt) + "_finalfeaturefile_tgtfullreduced.csv") | ||
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| scikit_file = output_prefix + ".scikit.pickle" | ||
| statsmodels_file = output_prefix + ".statsmodels.pickle" | ||
| scikit_file_reduced = "fixed_" + output_prefix + ".scikit.pickle" | ||
| statsmodels_file_reduced = "fixed_" + output_prefix + ".statsmodels.pickle" | ||
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| scikit_file_no_kurtosis = "nokurt_" + output_prefix + ".scikit.pickle" | ||
| statsmodels_file_no_kurtosis = "nokurt_" + output_prefix + ".statsmodels.pickle" | ||
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| scikit_file_no_paired_dist = "nopaired_" + output_prefix + ".scikit.pickle" | ||
| statsmodels_file_no_paired_dist = "nopaired_" + output_prefix + ".statsmodels.pickle" | ||
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| scikit_file_full_reduced = "fullreduced_" + output_prefix + ".scikit.pickle" | ||
| statsmodels_file_full_reduced = "fullreduced_" + output_prefix + ".statsmodels.pickle" | ||
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| scikit_file_reduced = "fixed_" + output_prefix + ".scikit.pickle" | ||
| statsmodels_file_reduced = "fixed_" + output_prefix + ".statsmodels.pickle" | ||
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| #call training functions | ||
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| train.train_statsmodels(train_df, statsmodels_file) | ||
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| train.train_scikit(train_df, scikit_file) | ||
| train.train_statsmodels(train_df_reduced, statsmodels_file_reduced) | ||
| train.train_scikit(train_df_reduced, scikit_file_reduced) | ||
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| train.train_statsmodels(train_df_no_kurtosis, statsmodels_file_no_kurtosis) | ||
| train.train_scikit(train_df_no_kurtosis, scikit_file_no_kurtosis) | ||
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| train.train_statsmodels(train_df_no_paired_dist, statsmodels_file_no_paired_dist) | ||
| train.train_scikit(train_df_no_paired_dist, scikit_file_no_paired_dist) | ||
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| train.train_statsmodels(train_df_target_full_reduced, statsmodels_file_full_reduced) | ||
| train.train_scikit(train_df_target_full_reduced, scikit_file_full_reduced) | ||
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| if __name__ == "__main__": | ||
|
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| parser = argparse.ArgumentParser() | ||
| parser.add_argument('--demo_model_file',type=str, required=True) | ||
| parser.add_argument('--nrep', type=int, required=True) | ||
| parser.add_argument('--nref', type=int, required=True) | ||
| parser.add_argument('--ntgt',type=int, required=True) | ||
| parser.add_argument('--ref_id',type=str, required=True) | ||
| parser.add_argument('--tgt_id', type=str, required=True) | ||
| parser.add_argument('--src_id', type=str, required=True) | ||
| parser.add_argument('--seq_len', type=int, required=True) | ||
| parser.add_argument('--mut_rate',type=float, required=True) | ||
| parser.add_argument('--rec_rate',type=float, required=True) | ||
| parser.add_argument('--thread',type=int, required=True) | ||
| parser.add_argument('--output_prefix',type=str, required=True) | ||
| parser.add_argument('--output_dir',type=str, required=True) | ||
| parser.add_argument('--seed',required=True) | ||
|
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| parser.add_argument('--folder_partitions',type=int,required=True) | ||
|
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| args = parser.parse_args() | ||
| demo_model_file = args.demo_model_file | ||
| nrep = args.nrep | ||
| nref = args.nref | ||
| ntgt = args.ntgt | ||
| ref_id = args.ref_id | ||
| tgt_id = args.tgt_id | ||
| src_id = args.src_id | ||
| seq_len = args.seq_len | ||
| mut_rate = args.mut_rate | ||
| rec_rate = args.rec_rate | ||
| thread = args.thread | ||
| output_prefix = args.output_prefix | ||
| output_dir = args.output_dir | ||
| if args.seed == "None": | ||
| seed = None | ||
| else: | ||
| seed = int(args.seed) | ||
|
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| folder_partitions = args.folder_partitions | ||
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| main(demo_model_file, nrep, nref, ntgt, ref_id, tgt_id, src_id, seq_len, mut_rate, rec_rate, thread, output_prefix, output_dir, seed, folder_partitions) |
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