import sys,os,os.path
import pandas as pd
from pandas.core.frame import DataFrame
import argparse
import re

sys.path.append('/cgdata/liuxiangqiong/work62pancancer/Client/v0/script/20220705/')
import datafile_QC_v0_20220906_finish as qcsummary
#inputpath='/cgdata/bioproject/pancancer602gene/CGB0158_1'
#laneid='CGB0158_1'


def sampleQCcheck(inputpath,laneid):
	###读入样本表
	sampledir = os.path.join(inputpath, laneid + '_sample_infor_label.txt')
	sampletable = pd.read_table(sampledir, sep='\t', header=0)
	for i in range(len(sampletable)):
		tumor = sampletable.loc[i, 'tumor']
		try:
			qcsummary.qcrun(inputpath, tumor)
		except:
			print(tumor + ' qc data is wrong,please check!')

def qcsummary_tumor(inputpath,laneid):
	QCdir = os.path.join(inputpath, 'tempfile/QC')
	###读入样本表
	sampledir = os.path.join(inputpath, laneid + '_sample_infor_label.txt')
	sampletable = pd.read_table(sampledir, sep='\t', header=0)
	QCsummary_tumor = pd.DataFrame()
	for i in range(len(sampletable)):
		tumor = sampletable.loc[i, 'tumor']
		samplename = sampletable.loc[i, 'samplename']
		tumorQCdir = os.path.join(QCdir, tumor + '_qc_report.txt')
		if os.path.exists(tumorQCdir):
			tumorQCdata = pd.read_table(tumorQCdir, sep='\t', header=0)
			tumorQCdata.loc[0, 'samplename'] = samplename
			tumorQCdata.loc[0, 'laneid'] = laneid
		else:
			tumorQCdata = pd.DataFrame()
			tumorQCdata.loc[0, 'samplename'] = samplename
			tumorQCdata.loc[0, 'sampleid'] = tumor
			tumorQCdata.loc[0, 'laneid'] = laneid
		QCsummary_tumor = tumorQCdata.append(QCsummary_tumor)
	QCsummary_tumor['Total_base(G)'] = pd.DataFrame(round(QCsummary_tumor['Total_base'] / 1000000000, 2))
	del QCsummary_tumor['Total_base']
	titlelist = ['samplename', 'sampleid', 'Total_base(G)', 'Total_average_depth', 'Unique_average_depth',
				 'insert_size', 'coverge_uniform', 'Q30', 'QC_overall', 'laneid']
	QCsummary_tumor = QCsummary_tumor[titlelist]
	return QCsummary_tumor

def qcsummary_normal(inputpath,laneid):
	QCdir = os.path.join(inputpath, 'tempfile/QC')
	###读入样本表
	sampledir = os.path.join(inputpath, laneid + '_sample_infor_label.txt')
	sampletable = pd.read_table(sampledir, sep='\t', header=0)
	QCsummary_normal = pd.DataFrame()
	for i in range(len(sampletable)):
		normal = sampletable.loc[i, 'normal']
		samplename = sampletable.loc[i, 'samplename']
		tumorQCdir = os.path.join(QCdir, normal + '_qc_report.txt')
		if os.path.exists(tumorQCdir):
			tumorQCdata = pd.read_table(tumorQCdir, sep='\t', header=0)
			tumorQCdata.loc[0, 'samplename'] = samplename
			tumorQCdata.loc[0, 'laneid'] = laneid
		else:
			tumorQCdata = pd.DataFrame()
			tumorQCdata.loc[0, 'samplename'] = samplename
			tumorQCdata.loc[0, 'sampleid'] = tumor
			tumorQCdata.loc[0, 'laneid'] = laneid
		QCsummary_normal = tumorQCdata.append(QCsummary_normal)
	QCsummary_normal['Total_base(G)'] = pd.DataFrame(round(QCsummary_normal['Total_base'] / 1000000000, 2))
	del QCsummary_normal['Total_base']
	titlelist=['samplename', 'sampleid','Total_base(G)', 'Total_average_depth', 'Unique_average_depth', 'insert_size', 'coverge_uniform', 'Q30', 'QC_overall', 'laneid']
	QCsummary_normal=QCsummary_normal[titlelist]
	return QCsummary_normal


def QCSum_allsum_main(inputpath,laneid):
	#先对运行后的结果进行检验
	sampleQCcheck(inputpath, laneid)
	#进行qcsummary
	qctumor = qcsummary_tumor(inputpath, laneid)
	qcnormal = qcsummary_normal(inputpath, laneid)
	qcsummarydata = qctumor.append(qcnormal)
	outputdir = os.path.join(inputpath, 'datasummary')
	if not os.path.exists(outputdir):
		os.mkdir(outputdir)
	outputname = os.path.join(outputdir, laneid + '_' + 'table1_QCsummary.txt')
	qcsummarydata.to_csv(outputname, sep='\t', index=False, header=True)

if __name__=='__main__':
	parser = argparse.ArgumentParser(description='for the QCsum')
	parser.add_argument('-i', '--inputpath', type=str, help='the path of lane')
	parser.add_argument('-l', '--laneid', type=str, help='the laneid')
	args = parser.parse_args()
	Inputpath = args.inputpath
	Laneid = args.laneid
	QCSum_allsum_main(Inputpath,Laneid)