global data_all

# data_all = {}

# 录入文件，输出文件

path_dir = indir

out_dir = outdir

for filename in os.walk(path_dir).__next__()[2]:

data_all[filename] = {}

path = path_dir + '/' + filename

workbook = xlrd.open_workbook(path)

for sheet_name in workbook.sheet_names():

data_all[filename][sheet_name] = []

sheet = workbook.sheet_by_name(sheet_name)

nrows = sheet.nrows

ncols = sheet.ncols

headers = {}

if True:

for col_index in range(ncols):

# value = sheet.cell_value(0, col_index).encode('utf-8')

value = sheet.cell_value(0, col_index)

headers[col_index] = value

for row_index in range(1, nrows):

line = {}

for col_index in range(ncols):

# value = sheet.cell_value(row_index, col_index).encode('utf-8')

try:

value = sheet.cell_value(row_index, col_index)

except Exception as e:

print('filename:', filename, ' sheet_name:', sheet_name, ' row_index:', row_index, ' col_index:', col_index)

header = headers[col_index]

line[header] = value

data_all[filename][sheet_name].append(line)

# out_file_name = out_dir + '/' + filename

# f = open(out_file_name, 'w')

# f.write(json.dumps(data_all[filename]))

# f.close()

f = open(out_dir + '/' + name, 'w')

f.write(json.dumps(data_all))

name_map = {'1360': 'ABVD', '1363': 'CHOP', '1414': 'Gemox', '1416': 'R+OBP', '1536': 'CHOP-B', '1537': 'R-Gemox',

'1603': 'AVD',

'1605': 'ECOP', '1606': 'GP', '1643': 'EP', '1672': 'R-CHOP', '1673': 'RGL', '2039': 'R-COP',

'2066': 'R-ABVD',

'2141': 'BVD', '2647': '盐酸米托蒽醌脂质体试验'}

for pid, vls in cure_type.items():

for k, v in vls.items():

if pid not in merge_map.keys():

new_dict = [''] * 11

merge_map[pid] = new_dict

else:

new_dict = merge_map[pid]

# 按照名字排列,格式

if k in names.keys():

if v in name_map.keys():

v = name_map[v]

cs = cscobc.Cscobc(data_all)

# base_dict = cs.direct_p()

# head = ['pid', '性别', '医院-科室', '出生日期', '是否绝经', '月经史', '病理报告日期（索引）', '手术日期', '首次确诊年龄', '临床N分期']

# wr = writeExcel.WriteExcel(base_dict.keys(), '基本信息')

# wr.write_arr(head, base_dict)

# wr.last('基本信息')

qian_map = cs.qian_shao()

# dict_16_23 = cs.undirect_16_23()

head1 = ['pid', '前哨阳性个数']

# , '新辅助AI内分泌治疗', '辅助AI内分泌治疗', '是否复发转移', '复发转移后是否内分泌治疗',

# '微转移', '临床病理类型不为肉瘤', '初诊颅外病灶', '腋窝临床检查阳性', '一线内分泌治疗'

wr = writeExcel.WriteExcel(data_all, [['cscobc.xlsx', '基本信息_jibenxinxi_4578'], ['bc-s_new.xlsx', '基本信息-基本信息']],'qianshao_num')

wr.write_excel(head1, qian_map)

# 进行操作

read = abvd.Parameter(data_all)

# 性别年龄，数组字典

sex_old_dict = read.sex_age()

# orr,化疗线数，治疗方案， pd,非pd

orr, pd, npd, cure_type = read.orr_pd()

for pid, v in orr.items():

if len(v) < 1:

orr[pid] = ''

else:

for l in v:

if l in ['3', 3]: orr[pid] = 'SD'

elif l in [2, '2']: orr[pid] = 'PR'

elif l in [1, '1']: orr[pid] = 'CR'

elif l in [4, '4']: orr[pid] = 'PD'

else: orr[pid] = l

# pip评估

pip_grade = read.pip_()

# 基线的临床分期,一般字典

clinical_stage = {}

read.clinical_stages(clinical_stage, 'ABVD.xls', '入院诊断-临床诊断')

read.clinical_stages(clinical_stage, 'ABVD4S.xlsx', '--临床诊断与分期')

# 进行间隔的提取,一般字典

abvd_gap = {}

read.time_gap(abvd_gap, 'ABVD4S.xlsx', '--系统治疗', '治疗方案', '本周期开始时间', 'ABVD')

read.time_gap(abvd_gap, 'ABVD.xls', '治疗-化疗', '化疗方案', '化疗时间', 'ABVD')

abvd_two = read.gap_two(abvd_gap)

# 免疫组化结果取值 字典跟着字典形式

immune_dict = {}

read.immune('ABVD4S.xlsx', '病理检查lym--淋巴结或组织活检', immune_dict)

read.immune_307('ABVD.xls', '入院诊断-病理诊断', immune_dict)

pfs_dict = read.pfs()

# 将数转变为数组形式4+6

merge_map = {}

names = {'一线': 0, '1': 0, '二线': 1, 2: 1, '三线': 2, '3': 2, '四线': 3, '4': 3, '四线及以上': 4, 'CD3': 5, 'CD5': 6, 'CD15': 7, 'CD20': 8, 'BCL-6': 9, 'Ki67':10, 'KI-67':10}

merge_dicts(merge_map, cure_type, names)

merge_dicts(merge_map, immune_dict, names)

head1 = ['pid', '性别', '年龄', 'pfs', 'orr', 'pd', '非pd', 'IPI评估(分数)', '时间间隔', '临床分期', '一线', '二线', '三线', '四线', '四线及以上','CD3', 'CD5', 'CD15', 'CD20', 'BCL-6', 'Ki67']

# 写入

wr = writeExcel.WriteExcel(data_all, [['ABVD4S.xlsx', '--基本信息'], ['ABVD.xls', '基本信息-基本信息']], 'abvd')

wr.write_excel(head1, sex_old_dict, pfs_dict, orr, pd, npd, pip_grade, abvd_two, clinical_stage, merge_map)