#####
import pandas as pd
import xlrd
import os,sys
import argparse

####creat the analysis
def analis_dir(inputpath,laneid):
	#新建出报告的目录
	pancancer_dir = os.path.join('/cgdata/pancancer_report', laneid)
	if not os.path.exists(pancancer_dir):
		os.mkdir(pancancer_dir)
	svdir1 = os.path.join(inputpath, '1SV_varscan_pair')
	if not os.path.exists(svdir1):
		os.mkdir(svdir1)
	svdir2= os.path.join(inputpath, '1SV_vardict_pair')
	if not os.path.exists(svdir2):
		os.mkdir(svdir2)
	# for CNV
	CNVdir = os.path.join(inputpath, '2CNV_cnvkit_pair')
	if not os.path.exists(CNVdir):
		os.mkdir(CNVdir)
	# for MSI
	MSI_dir = os.path.join(inputpath, '3MSI_msisensor2_pair')
	if not os.path.exists(MSI_dir):
		os.mkdir(MSI_dir)
	# for germline result
	gemerlinedir = os.path.join(inputpath, '4Germline_unpair')
	if not os.path.exists(gemerlinedir):
		os.mkdir(gemerlinedir)
	# for HL result
	HLdir = os.path.join(inputpath, '5HL_gatk_unpair')
	if not os.path.exists(HLdir):
		os.mkdir(HLdir)
	# for fusion
	fusion_method1_dir = os.path.join(inputpath, '6Fusion_manta_pair')
	if not os.path.exists(fusion_method1_dir):
		os.mkdir(fusion_method1_dir)
	fusion_method2_dir = os.path.join(inputpath, '6Fusion_genefusion_unpair')
	if not os.path.exists(fusion_method2_dir):
		os.mkdir(fusion_method2_dir)
	#for HLA
	HLA_dir = os.path.join(inputpath, '7HLA-HD_unpair')
	if not os.path.exists(HLA_dir):
		os.mkdir(HLA_dir)
	# for qc
	qc_dir = os.path.join(inputpath, '8Fastqc')
	if not os.path.exists(qc_dir):
		os.mkdir(qc_dir)
	# for ontarget
	ontarget_dir = os.path.join(inputpath, '9Ontarget')
	if not os.path.exists(ontarget_dir):
		os.mkdir(ontarget_dir)
	# for coverage
	coverage_dir = os.path.join(inputpath, '10Coverage')
	if not os.path.exists(coverage_dir):
		os.mkdir(coverage_dir)
	# datasummary
	datasummary_dir = os.path.join(inputpath, 'datasummary')
	if not os.path.exists(datasummary_dir):
		os.mkdir(datasummary_dir)


def pancancer_project(inputpath,laneid):
	#inputpath = '/cgdata/liuxiangqiong/work62pancancer/pipelinetest-CGB0158'
	#laneid = 'CGB0158'
	###1.从项目表提取出当前大panel的样本表
	project = pd.read_excel('/cgdata/liuxiangqiong/work62pancancer/Project_table/阅尔基因项目信息总表-0606.xlsx')
	###2.获得当前的项目，更新当前的样本表
	projectsample = project[project['检测项目1'] == '阅全-泛癌种602基因检测']
	outputfile1 = os.path.join('/cgdata/pancancer/project/pancancer_602gene_samples.xlsx')
	writer = pd.ExcelWriter(outputfile1)
	projectsample.to_excel(writer, sheet_name='QC', index=False)
	writer.save()
	writer.close()
	####3.提取出当前我们panel分析样本的信息
	selectlist = ['样本编号', '样本类型', '临床诊断']
	selectsample = projectsample[selectlist]
	selectsample.reset_index(drop=True, inplace=True)
	selectsample['样本编号'] = selectsample['样本编号'].str.replace("^A", "Lib")
	###3.1 我们从底层表中获取疾病的名称
	tumordbdir = '/cgdata/liuxiangqiong/work62pancancer/pipeline/v0/refdata/TCGA_tumor_list_20220915.txt'
	tumordblist = pd.read_table(tumordbdir, sep='\t', header=0, encoding='gbk')
	# 添加TCGA的名称
	selectsample.rename(columns={'临床诊断': 'tumor_name', '样本编号': 'sampleid', '样本类型': 'sampletype'}, inplace=True)
	selectsample_TCGA = pd.merge(selectsample, tumordblist, on=['tumor_name'], how='left')
	# 将不在TCGA的癌症名称标为unknown
	selectsample_TCGA['tumor_name'] = selectsample_TCGA['tumor_name'].fillna('unknown')
	# 3.2 获得当前的样本对应的信息
	####提取出当前lane的样本对应的信息
	lane_sampelelist = pd.read_table(os.path.join(inputpath, laneid + '_sample.txt'), sep='\t', header=None, names=['sampleid'])
	lane_sampleinfor = pd.merge(lane_sampelelist, selectsample_TCGA, on=['sampleid'], how='left')
	# 输出原始信息表
	outputfile2 = os.path.join(inputpath, laneid + '_sampleinfor_raw.xlsx')
	writer = pd.ExcelWriter(outputfile2)
	lane_sampleinfor.to_excel(writer, sheet_name='sampleinfor', index=False)
	writer.save()
	writer.close()
	return lane_sampleinfor

#####################制作配对数据样本表
def samplepair(inputpath,laneid,lane_sampleinfor):
	###4.1获得样本名
	samplenamelist = pd.DataFrame()
	for i in range(len(lane_sampleinfor)):
		sample = lane_sampleinfor.loc[i, 'sampleid'][:-1]
		samplenamelist.loc[i, 'samplename'] = sample
	samplenamelist_uq = samplenamelist.drop_duplicates().reset_index(drop=True)
	###4.2制作配对样本表
	sample_pair = pd.DataFrame()
	for j in range(len(samplenamelist_uq)):
		sample = samplenamelist_uq.loc[j, 'samplename']
		# sample_pair.loc[j, 'samplename'] = sample
		for k in range(len(lane_sampleinfor)):
			sampleid = lane_sampleinfor.loc[k, 'sampleid']
			sampletype1 = lane_sampleinfor.loc[k, 'sampletype']
			tumortype = lane_sampleinfor.loc[k, 'Abbr']
			print(sampleid)
			label = sampleid.find(sample)
			# print(label)
			if label != -1:
				# 修改样本名
				sample_pair.loc[j, 'samplename'] = sample + 'T'
				if (sampletype1 == '外周血') and (sampleid[-1] == 'N'):
					sample_pair.loc[j, 'normal'] = sample + 'T' + 'CN'
				elif sampletype1 == '血浆':
					sample_pair.loc[j, 'tumor'] = sample + 'T' + 'CT'
					sample_pair.loc[j, 'sampletype'] = 'blood'
					sample_pair.loc[j, 'tumortype'] = tumortype
				else:
					sample_pair.loc[j, 'tumor'] = sample + 'T' + 'TT'
					sample_pair.loc[j, 'sampletype'] = 'FFPE'
					sample_pair.loc[j, 'tumortype'] = tumortype
	# output
	outputfile3 = os.path.join(inputpath, laneid + '_sample_infor_label.txt')
	sample_pair.to_csv(outputfile3, index=False, header=True, encoding='gbk', sep='\t')


def sheetrunmain(inputpath,laneid):
	analis_dir(inputpath,laneid)
	lane_sampleinfor=pancancer_project(inputpath,laneid)
	samplepair(inputpath, laneid, lane_sampleinfor)


#inputpath='/cgdata/liuxiangqiong/work62pancancer/pipelinetest-CGB0158'
#laneid='CGB0158'
#sheetrun(inputpath,laneid)

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