#!/usr/bin/env python3
# -*- coding: utf-8 -*-
'''
Created on Tue Aug  6 12:56:03 2019

@author: tanu
'''
#=============================================================================
# Task: Residue depth (rd) processing to generate a df with residue_depth(rd)
# values

# FIXME
# Input: '.tsv' i.e residue depth txt file (output from .zip file manually
# downloaded from the website). 
# This should be integrated into the pipeline

# Output: .csv with 3 cols i.e position, rd_values & 3-letter wt aa code(caps)
#=============================================================================
#%% load packages
import sys, os
import argparse
import pandas as pd
#=============================================================================
#%% specify input and curr dir
homedir = os.path.expanduser('~')

# set working dir
os.getcwd()
os.chdir(homedir + '/git/LSHTM_analysis/meta_data_analysis')
os.getcwd()
#=======================================================================
#%% command line args
arg_parser = argparse.ArgumentParser()
#arg_parser.add_argument('-d', '--drug', help='drug name', default = 'pyrazinamide')
#arg_parser.add_argument('-g', '--gene', help='gene name', default = 'pncA') # case sensitive
arg_parser.add_argument('-d', '--drug', help='drug name', default = 'TESTDRUG')
arg_parser.add_argument('-g', '--gene', help='gene name (case sensitive)', default = 'testGene') # case sensitive
args = arg_parser.parse_args()
#=======================================================================
#%% variable assignment: input and output 
#drug = 'pyrazinamide'
#gene = 'pncA'
drug = args.drug
gene = args.gene
gene_match = gene + '_p.'

#==========
# data dir
#==========
datadir = homedir + '/' + 'git/Data'

#=======
# input
#=======
outdir = datadir + '/' + drug + '/' + 'output'
in_filename = '3pl1_rd.tsv'
infile = outdir + '/' + in_filename
print('Input filename:', in_filename
      , '\nInput path:', outdir
      , '\n=============================================================')
#=======
# output 
#=======
outdir =   datadir + '/' + drug + '/' + 'output'
out_filename = gene.lower() + '_rd.csv'
outfile =  outdir + '/' + out_filename
print('Output filename:', out_filename
      , '\nOutput path:', outdir
      , '\n=============================================================')
      
#%% end of variable assignment for input and output files
#=======================================================================
#%% rd values from <gene>_rd.tsv values
def rd_to_csv(inputtsv, outputrdcsv):
	"""
    Calculate kd (hydropathy values) from input fasta file

    @param inputtsv: tsv file downloaded from {INSERT LINK}
    @type inputtsv: string

    @param outputrdsv: csv file with rd values
    @type outfile: string

    @return:  none, writes rd values df as csv
    """
	#========================
	# read downloaded tsv file
	#========================
	#%%  Read input file
	rd_data  = pd.read_csv(inputtsv, sep = '\t')  
	print('Reading input file:', inputtsv
		  , '\nNo. of rows:', len(rd_data)
		  , '\nNo. of cols:', len(rd_data.columns))

	print('Column names:', rd_data.columns
		, '\n===============================================================')
	#========================
	# creating position col
	#========================
	# Extracting residue number from index and assigning 
	# the values to a column [position]. Then convert the position col to numeric.
	rd_data['position'] = rd_data.index.str.extract('([0-9]+)').values

	# converting position to numeric      
	rd_data['position'] = pd.to_numeric(rd_data['position'])
	rd_data['position'].dtype

	print('Extracted residue num from index and assigned as a column:'
		  , '\ncolumn name: position'
		  , '\ntotal no. of cols now:', len(rd_data.columns)
		  , '\n=============================================================')

	#========================
	# Renaming amino-acid 
	# and all-atom cols
	#========================
	print('Renaming columns:'
		  , '\ncolname==> # chain:residue: wt_3letter_caps'
		  , '\nYES... the column name *actually* contains a # ..!'
		  , '\ncolname==> all-atom: rd_values'
		  , '\n=============================================================')

	rd_data.rename(columns = {'# chain:residue':'wt_3letter_caps', 'all-atom':'rd_values'}, inplace = True)
	print('Column names:', rd_data.columns)

	#========================
	# extracting df with the
	# desired columns
	#========================
	print('Extracting relevant columns for writing df as csv')

	rd_df = rd_data[['position','rd_values','wt_3letter_caps']]

	if len(rd_df) == len(rd_data):
		print('PASS: extracted df has expected no. of rows'
		      ,'\nExtracted df dim:'
		      ,'\nNo. of rows:', len(rd_df)
		      ,'\nNo. of cols:', len(rd_df.columns))
	else:
		print('FAIL: no. of rows mimatch'
		      , '\nExpected no. of rows:', len(rd_data)
		      , '\nGot no. of rows:', len(rd_df)
		      , '\n=====================================================')

	#===============
	# writing file
	#===============
	print('Writing file:'
		  , '\nFilename:', outputrdcsv
#		  , '\nPath:',  outdir
#		  , '\nExpected no. of rows:', len(rd_df)
#		  , '\nExpected no. of cols:', len(rd_df.columns)
		  , '\n=========================================================')

	rd_df.to_csv(outputrdcsv, header = True, index = False)

#%% end of function
#=======================================================================
#%% call function
#rd_to_csv(infile, outfile)
#=======================================================================
def main():
	print('residue depth using the following params\n'
		, in_filename
		, '\noutfile:', out_filename)
		rd_to_csv(infile, outfile)
	print('Finished Writing file:'
		, '\nFilename:', out_filename
		, '\nPath:',  outdir
		, '\n=============================================================')

if __name__ == '__main__':
	main()
#%% end of script	
#=======================================================================