117 lines
3.7 KiB
Python
Executable file
117 lines
3.7 KiB
Python
Executable file
#!/usr/bin/env python3
|
|
# -*- coding: utf-8 -*-
|
|
"""
|
|
Created on Fri Jun 24 11:07:05 2022
|
|
|
|
@author: tanu
|
|
"""
|
|
import re
|
|
import argparse
|
|
import os, sys
|
|
###############################################################################
|
|
# gene = 'pncA'
|
|
# drug = 'pyrazinamide'
|
|
#total_mtblineage_uc = 8
|
|
|
|
# #%% command line args: case sensitive
|
|
# arg_parser = argparse.ArgumentParser()
|
|
# arg_parser.add_argument('-d', '--drug', help = 'drug name', default = '')
|
|
# arg_parser.add_argument('-g', '--gene', help = 'gene name', default = '')
|
|
# args = arg_parser.parse_args()
|
|
|
|
# drug = args.drug
|
|
# gene = args.gene
|
|
|
|
###############################################################################
|
|
homedir = os.path.expanduser("~")
|
|
sys.path.append(homedir + '/git/LSHTM_analysis/scripts/ml')
|
|
|
|
###############################################################################
|
|
#==================
|
|
# Import data
|
|
#==================
|
|
from ml_data_7030 import *
|
|
setvars(gene,drug)
|
|
from ml_data_7030 import *
|
|
|
|
# from YC run_all_ML: run locally
|
|
#from UQ_yc_RunAllClfs import run_all_ML
|
|
|
|
#====================
|
|
# Import ML functions
|
|
#====================
|
|
from MultClfs import *
|
|
|
|
#==================
|
|
# other vars
|
|
#==================
|
|
tts_split_7030 = '70_30'
|
|
OutFile_suffix = '7030'
|
|
#==================
|
|
# Specify outdir
|
|
#==================
|
|
outdir_ml = outdir + 'ml/tts_7030/'
|
|
print('\nOutput directory:', outdir_ml)
|
|
|
|
#outFile_wf = outdir_ml + gene.lower() + '_baselineC_' + OutFile_suffix + '.csv'
|
|
#outFile_lf = outdir_ml + gene.lower() + '_baselineC_ext_' + OutFile_suffix + '.csv'
|
|
|
|
###############################################################################
|
|
print('\n#####################################################################\n'
|
|
, '\nRunning ML analysis: Multiple models'
|
|
, '\nGene name:', gene
|
|
, '\nDrug name:', drug)
|
|
|
|
###############################################################################
|
|
#%% Test MultModelsCL WITHOUT returning formatted output
|
|
#================
|
|
# MultModelsCl: without formatted output
|
|
#================
|
|
mmD = MultModelsCl_noBT(input_df = X_smnc
|
|
, target = y_smnc
|
|
, var_type = 'mixed'
|
|
, tts_split_type = tts_split_7030
|
|
, resampling_type = 'smnc'
|
|
, skf_cv = skf_cv
|
|
, blind_test_df = X_bts
|
|
, blind_test_target = y_bts
|
|
, add_cm = True
|
|
, add_yn = True
|
|
, run_blind_test = True
|
|
, return_formatted_output = False)
|
|
|
|
#================
|
|
# MultModelsCl: WITH formatted output
|
|
#================
|
|
mmDF3 = MultModelsCl_noBT(input_df = X_smnc
|
|
, target = y_smnc
|
|
, var_type = 'mixed'
|
|
, tts_split_type = tts_split_7030
|
|
, resampling_type = 'smnc'
|
|
, skf_cv = skf_cv
|
|
, blind_test_df = X_bts
|
|
, blind_test_target = y_bts
|
|
, add_cm = True
|
|
, add_yn = True
|
|
, run_blind_test = True
|
|
, return_formatted_output= True )
|
|
|
|
mmDF9= MultModelsCl_noBT(input_df = X
|
|
, target = y
|
|
, var_type = 'mixed'
|
|
, tts_split_type = tts_split_7030
|
|
, resampling_type = 'none'
|
|
, skf_cv = None
|
|
, blind_test_df = X_bts
|
|
, blind_test_target = y_bts
|
|
, add_cm = True
|
|
, add_yn = True
|
|
, run_blind_test = True
|
|
, return_formatted_output= True )
|
|
#=================
|
|
# test function
|
|
#=================
|
|
# output from function call
|
|
ProcessMultModelsCl(mmD)
|
|
ProcessMultModelsCl(testD)
|
|
|