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Copy pathnew_report_summary-v2.1.py
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new_report_summary-v2.1.py
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#!/usr/bin/env python
import argparse
import pandas as pd
import os
import docx
import logging
import re
from multiprocessing import Pool
from docx.shared import RGBColor
from docx.shared import Pt
from docx.oxml.ns import qn
from docx.table import _Cell
from docx.oxml import OxmlElement
from docx.shared import Cm
from docx.enum.text import WD_ALIGN_PARAGRAPH
from docx.enum.table import WD_ALIGN_VERTICAL
from docxtpl import DocxTemplate, RichText
from docx.oxml.ns import nsdecls
from docx.oxml import parse_xml
from docx.shared import Inches
import datetime
import copy
# 打印出运行的时间
time1 = '运行时间：' + str(datetime.datetime.now())
print(time1)
# 设定监控日志输出文件名和内容形式
logging.basicConfig(format='%(asctime)s - %(message)s', filename='/mnt/c/Users/luping/Desktop/报告流程/TNP/OUTPUT/运行信息.txt', filemode='a', level=logging.INFO)
# 参数的导入与处理
parser = argparse.ArgumentParser()
parser.add_argument('-i', "--result_excel", required=True, help="the excel file with the result selected")
parser.add_argument('-b', "--database", type=str, default='/mnt/c/Users/luping/Desktop/报告流程/TNP/病原数据库/思可愈数据库-TNP-Seq病原菌测序项目2021.05.18.xlsx',help="database provided by the Ministry of Medicine")
parser.add_argument('-w', "--word_template_folder", type=str, default='/mnt/c/Users/luping/Desktop/报告流程/TNP/报告模板/word/',help="folder where all word report templates are located")
parser.add_argument('-e', "--excel_template_folder", type=str, default='/mnt/c/Users/luping/Desktop/报告流程/TNP/报告模板/excel/',help="folder where all excel report templates are located")
parser.add_argument('-n', "--processes_number", type=int, default=5,help="并行进程数目")
parser.add_argument('-c', "--complex_excel", type=str, default='/mnt/c/Users/luping/Desktop/报告流程/TNP/mycobacterium_tuberculosis_complex.xlsx',help="结核分支杆菌复合群包含微生物表格")
parser.add_argument('-s', "--summary_excel", type=str, default='/mnt/c/Users/luping/Desktop/报告流程/TNP/OUTPUT/',help="summary documents before processing")
parser.add_argument('-o', "--output_dir", type=str, default='/mnt/c/Users/luping/Desktop/报告流程/TNP/OUTPUT/',help="supplement sample result")
parser.add_argument('-B', "--barcode_picutre", type=str, default='/mnt/c/Users/luping/Desktop/报告流程/RD/barcode/',help="条形码图片所在")
args = parser.parse_args()
info_client = pd.read_excel(args.result_excel).fillna('NA')
Interpretation = pd.read_excel(args.result_excel, sheet_name='species_report').fillna('NA')
sheet = pd.read_excel(args.result_excel, sheet_name=None)
if 'resistance_report' in list(sheet.keys()):
drug_resistance_df = pd.read_excel(args.result_excel, sheet_name='resistance_report').fillna('NA')
if drug_resistance_df.shape[0] == 0:
drug_resistance_df = 0
else:
drug_resistance_df = 0
# print(drug_resistance_df)
picture_dtat_df = pd.read_excel(args.result_excel, sheet_name='length_report').fillna('NA')
medical_DB = pd.read_excel(args.database).fillna('NA')
result_file_name = args.result_excel.split("/")[-1].lower()
complex_df = pd.read_excel(args.complex_excel)
barcode_picture_path = args.barcode_picutre
####################################################
# 定义函数
# 判断是否为结核分枝杆菌复合群
def change_bacteria_list(bacteria_list: list):
new_bacteria_list = []
for bacteria in bacteria_list:
compare_bacteria: str = Nor(bacteria)
find_complex_df = complex_df[complex_df['name'] == compare_bacteria]
if find_complex_df.shape[0] == 0:
new_bacteria_list.append(bacteria)
else:
new_bacteria_list.append('Mycobacterium tuberculosis complex')
return new_bacteria_list
# 标准化输入内容名称所用函数(变小写)
def Nor(x: str
) -> str:
first: str = x.strip()
standardized_string: str = " ".join(first.split())
standardized_string: str = standardized_string.lower()
return standardized_string
# 标准化输入列名称所用函数
def Nor_col(x: str
) -> str:
first: str = str(x).strip()
standardized_string: str = " ".join(first.split())
return standardized_string
def make_picture(length_colname: str,
picture_dtat_df: pd.DataFrame,
) -> None:
R_out = length_colname + '.r'
rscript = f'''#! /path/to/Rscript
library(openxlsx)
library(ggplot2)
data<- read.xlsx('{args.result_excel}', sheet='length_report')
names(data)[names(data) == '{length_colname}'] <- 'Frequency'
data <- data[c(1:8),]
row.names(data) <- as.list(data)$length
read_length_hist <- ggplot(data, mapping=aes(x=rownames(data), y=Frequency)) +
geom_bar(stat="identity", fill="#E1EFF9", colour="#E1EFF9") +
scale_x_discrete(limits=factor(rownames(data))) +
labs(x="length(bp)", y="ratio(%)") +
theme(panel.grid=element_blank(), panel.background=element_rect(color="black", fill="transparent")) +
theme(axis.text =element_text(size=7))
ggsave(file="{length_colname}.png",read_length_hist, width = 6, height = 3)
'''
out = open(R_out, 'w')
out.write(rscript)
out.close()
cmd = "Rscript " + R_out
os.system(cmd)
os.remove(R_out)
def move_picture(doc,
png_name: str
) -> None:
table = doc.add_table(rows=1, cols=3)
cell = table.cell(0, 1)
ph = cell.paragraphs[0]
run = ph.add_run()
run.add_picture(png_name)
target = None
for paragraph in doc.paragraphs:
paragraph_text = paragraph.text
if paragraph_text.endswith('序列长度统计'):
# print(paragraph_text)
target = paragraph
break
move_table_after(table, target)
# os.remove(png_name)
return doc
# 查询检测项目的简称
def project_shorthand(sample_code: str) -> str:
project_name = info_client.loc[info_client['样本编号'] == sample_code, '检测项目'].iloc[0].rstrip()
# print(project_name)
if '呼吸' in project_name:
hand: str = 'HX'
elif '血液' in project_name:
hand: str = 'XY'
elif '神经' in project_name:
hand: str = 'SJ'
elif '胸腹' in project_name:
hand: str = 'XF'
elif '泌尿' in project_name:
hand: str = 'MN'
elif '消化' in project_name:
hand: str = 'XH'
elif '创口' in project_name:
hand: str = 'CK'
elif '眼科' in project_name:
hand: str = 'YB'
else:
name = info_client.loc[info_client['样本编号'] == sample_code, '患者姓名'].iloc[0]
logging.info(f'{name}的检测项目填写错误导致报告生成失败！')
# print(hand)
return hand
# 在数据库中搜索表格信息
def find_info(
result_list: list,
sample_code: str,
Interpretation: pd.DataFrame,
info_client: pd.DataFrame,
medical_DB: pd.DataFrame,
all_bac: list,
mic_dict: dict,
supplementary_results: int
) -> list:
bac_list: list = []
sample_result_list: list = []
column_P = info_client.loc[info_client['样本编号'] == sample_code, 'barcode'].iloc[0] + '_P_' + project_shorthand(sample_code) + '_' + str(info_client.loc[info_client['样本编号'] == sample_code, '患者姓名'].iloc[0]) + '_' + sample_code
column_R = info_client.loc[info_client['样本编号'] == sample_code, 'barcode'].iloc[0] + '_R_' + project_shorthand(sample_code) + '_' + str(info_client.loc[info_client['样本编号'] == sample_code, '患者姓名'].iloc[0]) + '_' + sample_code
for bac_name in result_list:
compare_bac_name: str = Nor(bac_name)
dic_bac: dict = {}
try:
dic_bac['中文名'] = medical_DB.loc[medical_DB['英文名称'] == compare_bac_name, '种'].iloc[0]
except IndexError:
dic_bac['中文名'] = 'NA'
try:
dic_bac['分类'] = medical_DB.loc[medical_DB['英文名称'] == compare_bac_name, '分类'].iloc[0]
try:
dic_bac['分类顺序'] = mic_dict[dic_bac['分类']]
except KeyError:
dic_bac['分类顺序'] = 0
except IndexError:
dic_bac['分类'] = 'NA'
dic_bac['分类顺序'] = 0
if dic_bac['分类'] not in ['DNA病毒', 'RNA病毒', '病毒', '真菌', '细菌']:
dic_bac['分类'] = '其他病原'
try:
dic_bac['分类顺序'] = mic_dict[dic_bac['分类']]
except KeyError:
dic_bac['分类顺序'] = 0
try:
dic_bac['相对丰度'] = '%.2f' % float(Interpretation.loc[Interpretation['name'] == compare_bac_name, column_P].iloc[0])
except KeyError:
column_P = info_client.loc[info_client['样本编号'] == sample_code, 'barcode'].iloc[0] + '_P_' + str(info_client.loc[info_client['样本编号'] == sample_code, '患者姓名'].iloc[0]) + '_' + sample_code
dic_bac['相对丰度'] = '%.2f' % float(Interpretation.loc[Interpretation['name'] == compare_bac_name, column_P].iloc[0])
except IndexError:
dic_bac['相对丰度'] = 'NA'
try:
try:
dic_bac['序列数'] = int(Interpretation.loc[Interpretation['name'] == compare_bac_name, column_R].iloc[0].replace('*', ''))
except:
dic_bac['序列数'] = int(Interpretation.loc[Interpretation['name'] == compare_bac_name, column_R].iloc[0])
except KeyError:
try:
column_R = info_client.loc[info_client['样本编号'] == sample_code, 'barcode'].iloc[0] + '_R_' + str(info_client.loc[info_client['样本编号'] == sample_code, '患者姓名'].iloc[0]) + '_' + sample_code
dic_bac['序列数'] = int(Interpretation.loc[Interpretation['name'] == compare_bac_name, column_R].iloc[0].replace('*', ''))
except:
column_R = info_client.loc[info_client['样本编号'] == sample_code, 'barcode'].iloc[0] + '_R_' + str(info_client.loc[info_client['样本编号'] == sample_code, '患者姓名'].iloc[0]) + '_' + sample_code
dic_bac['序列数'] = int(Interpretation.loc[Interpretation['name'] == compare_bac_name, column_R].iloc[0])
except IndexError:
dic_bac['序列数'] = 'NA'
report_name = bac_name.replace("[", "")
dic_bac['微生物'] = report_name.replace("]", "")
try:
dic_bac['备注'] = medical_DB.loc[(medical_DB['英文名称'] == compare_bac_name) & (medical_DB.检测项目.str.contains(project_shorthand(sample_code), regex=True)), '备注'].iloc[0]
except IndexError:
dic_bac['备注'] = 'NA'
try:
bac_list.append(medical_DB.loc[medical_DB['英文名称'] == compare_bac_name, '分类'].iloc[0])
except IndexError:
pass
sample_result_list.append(dic_bac)
if supplementary_results == 1:
return sample_result_list
bac_list = list(set(bac_list))
if 'DNA病毒' in bac_list:
bac_list.append('DNA病毒')
if '病毒' in bac_list or 'RNA病毒' in bac_list:
bac_list.append('RNA病毒')
for non_bac in all_bac:
if non_bac not in bac_list:
dic_bac = {}
dic_bac['分类'] = non_bac
dic_bac['分类顺序'] = mic_dict[non_bac]
dic_bac['相对丰度'] = '--'
dic_bac['序列数'] = '--'
dic_bac['微生物'] = '--'
dic_bac['备注'] = '--'
dic_bac['中文名'] = '--'
sample_result_list.append(dic_bac)
sample_result_list: list = sorted(sample_result_list, key=lambda x: x['分类顺序'])
return sample_result_list
# 分类正式报告结果
def microbial_classification(bacteria_list: list,
medical_DB: pd.DataFrame) -> list:
result1_list = []
result2_list = []
result3_list = []
result4_list = []
result5_list = []
result6_list = []
result7_list = []
for microbial in bacteria_list:
compare_bac_name: str = Nor(microbial)
try:
kingdom = medical_DB.loc[medical_DB['英文名称'] == compare_bac_name, '分类'].iloc[0]
genus = medical_DB.loc[medical_DB['英文名称'] == compare_bac_name, '属'].iloc[0]
except IndexError:
kingdom = 'NA'
genus = 'NA'
if genus == '分枝杆菌属':
result1_list.append(microbial)
elif kingdom == '细菌':
result2_list.append(microbial)
elif kingdom == '真菌':
result3_list.append(microbial)
elif kingdom == 'DNA病毒':
result4_list.append(microbial)
elif kingdom == '病毒' or kingdom == 'RNA病毒':
result5_list.append(microbial)
elif kingdom == '古菌' or kingdom == '其他病原':
result6_list.append(microbial)
elif kingdom == '寄生虫':
result7_list.append(microbial)
else:
logging.info(f"{microbial}没有在数据库中找到，导致报告中未显示！")
return [result1_list, result2_list, result3_list, result4_list, result5_list, result6_list, result7_list]
# 表格信息的生成1
def table_context(sample_code: str,
info_client: pd.DataFrame,
Interpretation: pd.DataFrame,
formal_report: str,
supplementary_report: str,
medical_DB: pd.DataFrame) -> list:
# print(sample_code)
if 'RNA' in info_client.loc[info_client['样本编号'] == sample_code, '检测项目'].iloc[0] and 'DNA' not in info_client.loc[info_client['样本编号'] == sample_code, '检测项目'].iloc[0]:
all_bac: list = ['RNA病毒']
mic_dict: dict = {'RNA病毒': 1}
elif 'RNA' in info_client.loc[info_client['样本编号'] == sample_code, '检测项目'].iloc[0]:
all_bac: list = ['细菌', '真菌', 'DNA病毒', 'RNA病毒', '其他病原']
mic_dict: dict = {'细菌': 1, '真菌': 2, 'DNA病毒': 3, 'RNA病毒': 4, '其他病原': 5}
else:
all_bac: list = ['细菌', '真菌', 'DNA病毒', '其他病原']
mic_dict: dict = {'细菌': 1, '真菌': 2, 'DNA病毒': 3, '其他病原': 4}
bacteria_list: list = []
if formal_report != 'NA':
bacteria_list: list = formal_report.split(',')
# print(bacteria_list)
# bacteria_list = change_bacteria_list(bacteria_list)
supplementary_results = 0
table1_list = []
table1_list = find_info(result_list=bacteria_list, sample_code=sample_code, Interpretation=Interpretation, info_client=info_client, medical_DB=medical_DB, all_bac=all_bac, mic_dict=mic_dict, supplementary_results=supplementary_results)
table2_list = []
if supplementary_report != 'NA':
supplementary_results = 1
bacteria_list: list = supplementary_report.split(',')
# bacteria_list = change_bacteria_list(bacteria_list)
table2_list: list = find_info(result_list=bacteria_list, sample_code=sample_code, Interpretation=Interpretation, info_client=info_client, medical_DB=medical_DB, all_bac=all_bac, mic_dict=mic_dict, supplementary_results=supplementary_results)
else:
table2_list = [{'中文名': '--', '分类': '--', '分类顺序': 1, '相对丰度': '--', '序列数': '--', '微生物': '--', '备注': '--'}]
return [table1_list, table2_list]
# 表格信息的生成2
def table2_context(sample_code: str,
info_client: pd.DataFrame,
Interpretation: pd.DataFrame,
formal_report: str,
supplementary_report: str,
medical_DB: pd.DataFrame) -> list:
# print(sample_code)
all_bac_list: list = [['细菌'], ['细菌'], ['真菌'], ['DNA病毒'], ['RNA病毒'], ['其他病原'], ['寄生虫']]
mic_dict_list: dict = [{'细菌': 1}, {'细菌': 1}, {'真菌': 1}, {'DNA病毒': 1, }, {'RNA病毒': 1}, {'其他病原': 1}, {'寄生虫': 1}]
bacteria_list: list = []
if formal_report != 'NA':
bacteria_list: list = formal_report.split(',')
# print(bacteria_list)
# bacteria_list = change_bacteria_list(bacteria_list)
all_kinds_list = microbial_classification(bacteria_list=bacteria_list, medical_DB=medical_DB)
supplementary_results = 0
table1_list = []
for index, result_list in enumerate(all_kinds_list):
# print(result_list)
table1_list.append(find_info(result_list=result_list, sample_code=sample_code, Interpretation=Interpretation, info_client=info_client, medical_DB=medical_DB, all_bac=all_bac_list[index], mic_dict=mic_dict_list[index], supplementary_results=supplementary_results))
# print(table1_list)
table2_list = []
if supplementary_report != 'NA':
supplementary_results += 1
bacteria_list: list = supplementary_report.split(',')
# bacteria_list = change_bacteria_list(bacteria_list)
table2_list: list = find_info(result_list=bacteria_list, sample_code=sample_code, Interpretation=Interpretation, info_client=info_client, medical_DB=medical_DB, all_bac=all_bac_list[0], mic_dict=mic_dict_list[0], supplementary_results=supplementary_results)
else:
table2_list = [{'中文名': '--', '分类': '--', '分类顺序': 1, '相对丰度': '--', '序列数': '--', '微生物': '--', '备注': '--'}]
return [table1_list, table2_list]
# 表格信息的生成2
def table7_make(sample_code: str,
info_client: pd.DataFrame,
drug_resistance_df: pd.DataFrame
) -> list:
handle_df = info_client[info_client['样本编号'] == sample_code]
pat_name = handle_df['患者姓名'].iloc[0]
drug_resistance_info = info_client[(info_client['患者姓名'] == pat_name) & (info_client['备注'].str.contains('普通耐药'))]
# print(drug_resistance_info)
table_list = []
if drug_resistance_info.shape[0] != 0:
compare_sample_code = drug_resistance_info['样本编号'].iloc[0]
# print(compare_sample_code)
drug_resistance_colname = drug_resistance_info.loc[drug_resistance_info['样本编号'] == compare_sample_code, 'barcode'].iloc[0] + '_' + project_shorthand(compare_sample_code) + '_' + str(drug_resistance_info.loc[drug_resistance_info['样本编号'] == compare_sample_code, '患者姓名'].iloc[0]) + '_' + compare_sample_code + '_num'
# print(drug_resistance_colname)
# print(drug_resistance_df)
try:
drug_resistance_result = drug_resistance_df[drug_resistance_colname]
except KeyError:
drug_resistance_colname = drug_resistance_info.loc[drug_resistance_info['样本编号'] == compare_sample_code, 'barcode'].iloc[0] + '_' + str(drug_resistance_info.loc[drug_resistance_info['样本编号'] == compare_sample_code, '患者姓名'].iloc[0]) + '_' + compare_sample_code + '_num'
drug_resistance_result = drug_resistance_df[drug_resistance_colname]
gene_list = drug_resistance_df['gene'].tolist()
for gene in gene_list:
number = drug_resistance_df.query('gene == @gene').iloc[0, :][drug_resistance_colname]
if int(number) != 0:
dic_bac = {}
dic_bac['基因'] = gene
dic_bac['药物'] = drug_resistance_df.query('gene == @gene').iloc[0, :]['drug']
table_list.append(dic_bac)
if len(table_list) == 0:
dic_bac = {}
dic_bac['基因'] = '--'
dic_bac['药物'] = '--'
table_list.append(dic_bac)
return table_list
# 临床解析的生成
def clinical(sample_code: str,
info_client: pd.DataFrame,
medical_DB: pd.DataFrame,
formal_report: str,
supplementary_report: str,
manufacturer: str):
rt = RichText('')
if manufacturer == 'beagle':
bacteria_list: list = formal_report.split(',')
elif manufacturer == 'seegene' or 'boruilin' or 'beijing':
if supplementary_report != 'NA':
bacteria_list: list = supplementary_report.split(',')
else:
return rt
# bacteria_list = change_bacteria_list(bacteria_list)
# print('bacteria_list',bacteria_list)
dic_number: dict = {1: '一', 2: '二', 3: '三', 4: '四', 5: '五', 6: '六', 7: '七', 8: '八', 9: '九', 10: '十', 11: '十一', 12: '十二', 13: '十三', 14: '十四', 15: '十五', 16: '十六', 17: '十七', 18: '十八', 19: '十九', 20: '二十', 21: '二十一', 22: '二十二', 23: '二十三', 24: '二十四', 25: '二十五', 26: '二十六', 27: '二十七', 28: '二十八', 29: '二十九', 30: '三十'}
drug_indication_value: int = 0
for index, bac_name in enumerate(bacteria_list):
compare_bac_name: str = Nor(bac_name)
try:
new_name = medical_DB.loc[medical_DB['英文名称'] == compare_bac_name, '种'].iloc[0]
if str(medical_DB.loc[medical_DB['英文名称'] == compare_bac_name, '种'].iloc[0]) != 'NA':
chinese_name: str = str(medical_DB.loc[medical_DB['英文名称'] == compare_bac_name, '种'].iloc[0])
else:
chinese_name = ''
rt.add(dic_number[index + 1] + ' ' + chinese_name, bold=True)
rt.add('(', bold=True)
report_name: str = bac_name.replace("[", "")
report_name: str = report_name.replace("]", "")
rt.add(report_name, italic=True, bold=True)
rt.add(')\n', bold=True)
if manufacturer == 'beagle':
try:
if str(medical_DB.loc[(medical_DB['英文名称'] == compare_bac_name) & (medical_DB.检测项目.str.contains(project_shorthand(sample_code), regex=True)), '常用药物'].iloc[0]) != 'NA':
rt.add(' ' + '1 临床意义', bold=True)
rt.add('\n' + ' ' + medical_DB.loc[(medical_DB['英文名称'] == compare_bac_name) & (medical_DB.检测项目.str.contains(project_shorthand(sample_code), regex=True)), '临床意义'].iloc[0])
rt.add('\n' + ' ' + '2 常用药物', bold=True)
rt.add('\n' + ' ' + str(medical_DB.loc[(medical_DB['英文名称'] == compare_bac_name) & (medical_DB.检测项目.str.contains(project_shorthand(sample_code), regex=True)), '常用药物'].iloc[0]) + '\n')
drug_indication_value += 1
elif str(medical_DB.loc[(medical_DB['英文名称'] == compare_bac_name) & (medical_DB.检测项目.str.contains(project_shorthand(sample_code), regex=True)), '临床意义'].iloc[0]) != 'NA':
rt.add(' ' + '临床意义', bold=True)
rt.add('\n' + ' ' + medical_DB.loc[(medical_DB['英文名称'] == compare_bac_name) & (medical_DB.检测项目.str.contains(project_shorthand(sample_code), regex=True)), '临床意义'].iloc[0] + '\n')
except IndexError:
logging.info(f"正式结果中的{bac_name}在数据库中的检测项目信息有问题，影响临床解析的生成")
elif manufacturer == 'seegene' or 'boruilin' or 'beijing':
try:
rt.add(' ' + medical_DB.loc[(medical_DB['英文名称'] == compare_bac_name) & (medical_DB.检测项目.str.contains(project_shorthand(sample_code), regex=True)), '临床意义'].iloc[0] + '\n')
except IndexError:
logging.info(f"正式结果中的{bac_name}在数据库中的检测项目信息有问题，影响临床解析的生成")
except IndexError:
logging.info(f"正式结果中的{bac_name}在数据库中没有找到，影响临床解析的生成")
if drug_indication_value != 0 and manufacturer == 'beagle':
rt.add('\n注：常用药物为临床常规药物，且无法覆盖药敏结果，具体用药请结合临床药敏结果或医院耐药监测数据酌情用药。', bold=True)
return rt
# 参考文献的生成
def reference(sample_code: str,
formal_report: str,
supplementary_report: str):
bacteria_list: list = formal_report.split(',')
dic_number: dict = {1: '一', 2: '二', 3: '三', 4: '四', 5: '五', 6: '六', 7: '七', 8: '八', 9: '九', 10: '十', 11: '十一', 12: '十二', 13: '十三', 14: '十四', 15: '十五', 16: '十六', 17: '十七', 18: '十八', 19: '十九', 20: '二十', 21: '二十一', 22: '二十二', 23: '二十三', 24: '二十四', 25: '二十五', 26: '二十六', 27: '二十七', 28: '二十八', 29: '二十九', 30: '三十'}
index_str: int = len(bacteria_list) + 1
rt = RichText(dic_number[index_str] + '、' + '参考文献\n')
all_reference_list: list = []
reference_list: list = []
for bac_name in bacteria_list:
compare_bac_name: str = Nor(bac_name)
try:
new_reference: str = medical_DB.loc[(medical_DB['英文名称'] == compare_bac_name) & (medical_DB.检测项目.str.contains(project_shorthand(sample_code), regex=True)), '参考文献'].iloc[0]
for literature in new_reference.split("\n"):
all_reference_list.append(literature[2:])
reference_list: list = list(set(all_reference_list))
except IndexError:
pass
for index, val in enumerate(reference_list):
rt.add(str(index + 1) + '.' + str(val) + '\n')
return rt
# seegene报告修改表格
def form_modification(doc,
dic_client: dict,
sample_code: str):
# table = doc.tables[3]
# if len(doc.tables[3].rows) != 2:
table = doc.tables[4]
if len(doc.tables[4].rows) != 2:
add_dict = {'number_1': [], 'number_2': [], 'number_3': [], 'number_4': [], 'number_5': [], 'number_6': [], 'number_7': []}
for line_info in dic_client[sample_code]['表9信息']:
if line_info['分类'] == '细菌':
add_dict['number_2'].append(line_info)
elif line_info['分类'] == '真菌':
add_dict['number_3'].append(line_info)
elif line_info['分类'] == 'DNA病毒':
add_dict['number_4'].append(line_info)
elif line_info['分类'] == '病毒' or line_info['分类'] == 'RNA病毒':
add_dict['number_5'].append(line_info)
elif line_info['分类'] == '古菌' or line_info['分类'] == '其他病原':
add_dict['number_6'].append(line_info)
elif line_info['分类'] == '寄生虫':
add_dict['number_7'].append(line_info)
number = 1
while number < 8:
table_info_name = f'表{number}信息'
table_info = dic_client[sample_code][table_info_name]
change_color_table = doc.tables[4 + number]
if table_info[0]['微生物'] != '--':
for i, line in enumerate(table_info):
row = i + 2
col = len(change_color_table.columns)
for col_number in range(col):
run = change_color_table.cell(row, col_number).paragraphs[0]
content = run.text
run.text = ''
run = run.add_run(content)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(10)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
if col_number == 1:
run.italic = True
else:
run = change_color_table.cell(2, 1).paragraphs[0]
run.text = ''
run = run.add_run('--')
run.font.color.rgb = RGBColor(0, 0, 0)
run.font.size = Pt(10)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
add_key = f'number_{number}'
table_info.extend(add_dict[add_key])
result_list = []
if len(table_info) != 1 or table_info[0]['微生物'] != '--':
add_number = 0
for input_dict in table_info:
if input_dict['备注'] == '人体共生菌':
add_number += 1
elif input_dict['中文名'] != 'NA' and input_dict['中文名'] != '--':
if input_dict in add_dict[add_key]:
result_list.append(input_dict['中文名'] + '（补充报告部分）')
else:
result_list.append(input_dict['中文名'])
elif input_dict['中文名'] == 'NA' and input_dict['微生物'] != '--':
if input_dict in add_dict[add_key]:
result_list.append(input_dict['微生物'] + '（补充报告部分）')
else:
result_list.append(input_dict['微生物'])
if len(result_list) != 0:
result_info = "，".join(result_list)
run = table.cell(number, 1).paragraphs[0]
run.text = ''
run = run.add_run(result_info)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(11)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
if add_number != 0:
p = table.cell(number, 1).paragraphs[0]
if p.text != '未检出疑似病原体':
run = p.add_run('，疑似微生态菌群')
else:
p.text = ''
run = p.add_run('疑似微生态菌群')
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(11)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
number += 1
table_info = dic_client[sample_code]['表8信息']
if table_info[0]['基因'] != '--':
for infp_dict in table_info:
result_list.append(infp_dict['基因'])
result_info = ",".join(result_list)
run = table.cell(number, 1).paragraphs[0]
run.text = ''
run = run.add_run(result_info)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(11)
run.font.name = 'Arial'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
run.italic = True
else:
table_info = dic_client[sample_code]['表5信息']
change_color_table = doc.tables[5]
if table_info[0]['微生物'] != '--':
for i, line in enumerate(table_info):
row = i + 2
col = len(change_color_table.columns)
for col_number in range(col):
run = change_color_table.cell(row, col_number).paragraphs[0]
content = run.text
run.text = ''
run = run.add_run(content)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(10)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
if col_number == 1:
run.italic = True
else:
run = change_color_table.cell(2, 1).paragraphs[0]
run.text = ''
run = run.add_run('--')
run.font.color.rgb = RGBColor(0, 0, 0)
run.font.size = Pt(10)
run.font.name = 'Times New Roman'
result_list = []
if len(table_info) != 1 or table_info[0]['微生物'] != '--':
add_number = 0
for input_dict in table_info:
if input_dict['中文名'] != 'NA' and input_dict['中文名'] != '--':
result_list.append(input_dict['中文名'])
elif input_dict['中文名'] == 'NA' and input_dict['微生物'] != '--':
result_list.append(input_dict['微生物'])
# print(result_list)
if len(result_list) != 0:
result_info = "，".join(result_list)
run = table.cell(1, 1).paragraphs[0]
run.text = ''
run = run.add_run(result_info)
# print(run.text)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(11)
run.font.name = 'Arial'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
def form_modification2(doc,
dic_client: dict,
sample_code: str):
# table = doc.tables[3]
# if len(doc.tables[3].rows) != 2:
table = doc.tables[4]
if len(doc.tables[4].rows) != 2:
add_dict = {'number_1': [], 'number_2': [], 'number_3': [], 'number_4': [], 'number_5': [], 'number_6': []}
for line_info in dic_client[sample_code]['表9信息']:
if line_info['分类'] == '细菌':
add_dict['number_2'].append(line_info)
elif line_info['分类'] == '真菌':
add_dict['number_3'].append(line_info)
elif line_info['分类'] == 'DNA病毒':
add_dict['number_4'].append(line_info)
# elif line_info['分类'] == '病毒' or line_info['分类'] == 'RNA病毒':
# add_dict['number_5'].append(line_info)
elif line_info['分类'] == '古菌' or line_info['分类'] == '其他病原':
add_dict['number_5'].append(line_info)
elif line_info['分类'] == '寄生虫':
add_dict['number_6'].append(line_info)
# print('add_dict',add_dict)
number = 1
while number < 7:
if number < 5:
table_info_name = f'表{number}信息'
# print('table_info_name',table_info_name)
table_info = dic_client[sample_code][table_info_name]
change_color_table = doc.tables[4 + number]
# print('doc.tables[3+number]',3+number)
# print('table_info[0][微生物]',table_info)
if table_info[0]['微生物'] != '--':
for i, line in enumerate(table_info):
# print(i,line)
row = i + 2
col = len(change_color_table.columns)
for col_number in range(col):
run = change_color_table.cell(row, col_number).paragraphs[0]
content = run.text
# print(content)
run.text = ''
run = run.add_run(content)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(10)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
if col_number == 1:
run.italic = True
else:
run = change_color_table.cell(2, 1).paragraphs[0]
run.text = ''
run = run.add_run('--')
run.font.color.rgb = RGBColor(0, 0, 0)
run.font.size = Pt(10)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
add_key = f'number_{number}'
table_info.extend(add_dict[add_key])
result_list = []
if len(table_info) != 1 or table_info[0]['微生物'] != '--':
add_number = 0
for input_dict in table_info:
if input_dict['备注'] == '人体共生菌':
add_number += 1
elif input_dict['中文名'] != 'NA' and input_dict['中文名'] != '--':
if input_dict in add_dict[add_key]:
result_list.append(input_dict['中文名'] + '（补充报告部分）')
else:
result_list.append(input_dict['中文名'])
elif input_dict['中文名'] == 'NA' and input_dict['微生物'] != '--':
if input_dict in add_dict[add_key]:
result_list.append(input_dict['微生物'] + '（补充报告部分）')
else:
result_list.append(input_dict['微生物'])
if len(result_list) != 0:
result_info = "，".join(result_list)
run = table.cell(number, 1).paragraphs[0]
run.text = ''
run = run.add_run(result_info)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(11)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
if add_number != 0:
p = table.cell(number, 1).paragraphs[0]
if p.text != '未检出疑似病原体':
run = p.add_run('，疑似微生态菌群')
else:
p.text = ''
run = p.add_run('疑似微生态菌群')
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(11)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
number += 1
elif number == 5:
pass
number += 1
else:
table_info_name = f'表{number}信息'
# print('table_info_name',table_info_name)
table_info = dic_client[sample_code][table_info_name]
change_color_table = doc.tables[3 + number]
# print('doc.tables[3+number]',3+number)
if table_info[0]['微生物'] != '--':
for i, line in enumerate(table_info):
row = i + 2
col = len(change_color_table.columns)
for col_number in range(col):
run = change_color_table.cell(row, col_number).paragraphs[0]
content = run.text
run.text = ''
run = run.add_run(content)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(10)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
if col_number == 1:
run.italic = True
else:
run = change_color_table.cell(2, 1).paragraphs[0]
run.text = ''
run = run.add_run('--')
run.font.color.rgb = RGBColor(0, 0, 0)
run.font.size = Pt(10)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
add_key = f'number_{number - 1}'
table_info.extend(add_dict[add_key])
result_list = []
if len(table_info) != 1 or table_info[0]['微生物'] != '--':
add_number = 0
for input_dict in table_info:
if input_dict['备注'] == '人体共生菌':
add_number += 1
elif input_dict['中文名'] != 'NA' and input_dict['中文名'] != '--':
if input_dict in add_dict[add_key]:
result_list.append(input_dict['中文名'] + '（补充报告部分）')
else:
result_list.append(input_dict['中文名'])
elif input_dict['中文名'] == 'NA' and input_dict['微生物'] != '--':
if input_dict in add_dict[add_key]:
result_list.append(input_dict['微生物'] + '（补充报告部分）')
else:
result_list.append(input_dict['微生物'])
if len(result_list) != 0:
result_info = "，".join(result_list)
run = table.cell(number - 1, 1).paragraphs[0]
run.text = ''
run = run.add_run(result_info)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(11)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
if add_number != 0:
p = table.cell(number - 1, 1).paragraphs[0]
if p.text != '未检出疑似病原体':
run = p.add_run('，疑似微生态菌群')
else:
p.text = ''
run = p.add_run('疑似微生态菌群')
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(11)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
number += 1
table_info = dic_client[sample_code]['表8信息']
if table_info[0]['基因'] != '--':
for infp_dict in table_info:
result_list.append(infp_dict['基因'])
result_info = ",".join(result_list)
run = table.cell(number, 1).paragraphs[0]
run.text = ''
run = run.add_run(result_info)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(11)
run.font.name = 'Arial'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
run.italic = True
else:
table_info = dic_client[sample_code]['表4信息']
change_color_table = doc.tables[4]
if table_info[0]['微生物'] != '--':
for i, line in enumerate(table_info):
row = i + 2
col = len(change_color_table.columns)
for col_number in range(col):
run = change_color_table.cell(row, col_number).paragraphs[0]
content = run.text
run.text = ''
run = run.add_run(content)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(10)
run.font.name = 'Times New Roman'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
if col_number == 1:
run.italic = True
else:
run = change_color_table.cell(2, 1).paragraphs[0]
run.text = ''
run = run.add_run('--')
run.font.color.rgb = RGBColor(0, 0, 0)
run.font.size = Pt(10)
run.font.name = 'Times New Roman'
result_list = []
if len(table_info) != 1 or table_info[0]['微生物'] != '--':
add_number = 0
for input_dict in table_info:
if input_dict['中文名'] != 'NA' and input_dict['中文名'] != '--':
result_list.append(input_dict['中文名'])
elif input_dict['中文名'] == 'NA' and input_dict['微生物'] != '--':
result_list.append(input_dict['微生物'])
# print(result_list)
if len(result_list) != 0:
result_info = "，".join(result_list)
run = table.cell(1, 1).paragraphs[0]
run.text = ''
run = run.add_run(result_info)
# print(run.text)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(11)
run.font.name = 'Arial'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
# 检出微生物添加到附录中
def add_micro(df: pd.DataFrame,
chinese_name: str,
genus_name: str,
micro_type: str,
pathogenicity_info: str,
col_numbers: int,
classification: str
) -> pd.DataFrame:
# print('df',df)
appendix_list = df.iloc[:, 1].apply(Nor).tolist()
# print(appendix_list)
# print(Nor(chinese_name))
# print(Nor(genus_name))
if (Nor(chinese_name) in appendix_list) and (Nor(genus_name) in appendix_list):
micro_row = df[df.iloc[:, 1].apply(Nor) == chinese_name].index.tolist()[0]
genus_row = df[df.iloc[:, 1].apply(Nor) == genus_name].index.tolist()[0]
df.loc[micro_row, '结果'] = '检出'
df.loc[genus_row, '结果'] = '检出'
elif (Nor(genus_name) in appendix_list):
genus_row = df[df.iloc[:, 1].apply(Nor) == genus_name].index.tolist()[0]
df1 = df.loc[:genus_row]
df2 = df.loc[(genus_row + 1):]
if col_numbers == 3:
df3 = pd.DataFrame({df.columns.tolist()[0]: [micro_type], df.columns.tolist()[1]: [' ' + chinese_name], df.columns.tolist()[2]: ['检出']})
else:
df3 = pd.DataFrame({df.columns.tolist()[0]: [micro_type], df.columns.tolist()[1]: [' ' + chinese_name], df.columns.tolist()[2]: [pathogenicity_info], df.columns.tolist()[3]: ['检出']})
df = df1.append(df3, ignore_index=True).append(df2, ignore_index=True)
df.loc[genus_row, '结果'] = '检出'
elif '病毒' not in classification:
if col_numbers == 3:
df4 = pd.DataFrame({df.columns.tolist()[0]: [micro_type], df.columns.tolist()[1]: [genus_name], df.columns.tolist()[2]: ['检出']})
df5 = pd.DataFrame({df.columns.tolist()[0]: [micro_type], df.columns.tolist()[1]: [' ' + chinese_name], df.columns.tolist()[2]: ['检出']})
else:
df4 = pd.DataFrame({df.columns.tolist()[0]: [micro_type], df.columns.tolist()[1]: [genus_name], df.columns.tolist()[2]: [pathogenicity_info], df.columns.tolist()[3]: ['检出']})
df5 = pd.DataFrame({df.columns.tolist()[0]: [micro_type], df.columns.tolist()[1]: [' ' + chinese_name], df.columns.tolist()[2]: [pathogenicity_info], df.columns.tolist()[3]: ['检出']})
df = df.append(df4, ignore_index=True).append(df5, ignore_index=True)
if '病毒' in classification:
if (Nor(chinese_name) in appendix_list):
micro_row = df[df.iloc[:, 1].apply(Nor) == chinese_name].index.tolist()[0]
df.loc[micro_row, '结果'] = '检出'
else:
if col_numbers == 3:
df6 = pd.DataFrame({df.columns.tolist()[0]: [micro_type], df.columns.tolist()[1]: [chinese_name], df.columns.tolist()[2]: ['检出']})
else:
df6 = pd.DataFrame({df.columns.tolist()[0]: [micro_type], df.columns.tolist()[1]: [chinese_name], df.columns.tolist()[2]: [pathogenicity_info], df.columns.tolist()[3]: ['检出']})
df = df.append(df6, ignore_index=True)
return df
# 添加表格框线
def Set_cell_border(cell: _Cell, **kwargs):
"""
设置单元格边框函数
使用方法:
Set_cell_border(
cell,
top={"sz": 12, "val": "single", "color": "#FF0000", "space": "0"},
bottom={"sz": 12, "color": "#00FF00", "val": "single"},
start={"sz": 24, "val": "dashed", "shadow": "true"},
end={"sz": 12, "val": "dashed"},
)
传入参数有cell, 即单元格；top指上边框；bottom指下边框；start指左边框；end指右边框。
"sz"指线的粗细程度；"val"指线型，比如单线，虚线等；"color"指颜色，颜色编码可百度；
"space"指间隔，一般不设置，设置的值大于0会导致线错开；"shadow"指边框阴影
"""
tc = cell._tc
tcPr = tc.get_or_add_tcPr()
tcBorders = tcPr.first_child_found_in("w:tcBorders")
if tcBorders is None:
tcBorders = OxmlElement('w:tcBorders')
tcPr.append(tcBorders)
for edge in ('start', 'top', 'end', 'bottom', 'insideH', 'insideV'):
edge_data = kwargs.get(edge)
if edge_data:
tag = 'w:{}'.format(edge)
element = tcBorders.find(qn(tag))
if element is None:
element = OxmlElement(tag)
tcBorders.append(element)
for key in ["sz", "val", "color", "space", "shadow"]:
if key in edge_data:
element.set(qn('w:{}'.format(key)), str(edge_data[key]))
# 将表格添加到特定的字后面
def move_table_after(table, paragraph):
tbl, p = table._tbl, paragraph._p
p.addnext(tbl)
# 定义表格的文字特征
def change_format(table,
row: int,
col: int
):
run = table.cell(row, col).paragraphs[0]
content = run.text
run.text = ''
run = run.add_run(content)
run.font.color.rgb = RGBColor(0, 0, 0)
run.font.size = Pt(9)
run.font.name = 'Arial'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '微软雅黑')
if run.text == '检出':
run.font.color.rgb = RGBColor(255, 0, 0)
run = table.cell(row, col - 1).paragraphs[0]
content = run.text
run.text = ''
run = run.add_run(content)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(9)
run.font.name = 'Arial'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '微软雅黑')
run = table.cell(row, col - 2).paragraphs[0]
content = run.text
run.text = ''
run = run.add_run(content)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(9)
run.font.name = 'Arial'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '微软雅黑')
if len(table.columns) != 6:
run = table.cell(row, col - 3).paragraphs[0]
content = run.text
run.text = ''
run = run.add_run(content)
run.font.color.rgb = RGBColor(255, 0, 0)
run.font.size = Pt(9)
run.font.name = 'Arial'
run.element.rPr.rFonts.set(qn('w:eastAsia'), '微软雅黑')
# 将excel中的数据框转化为docx中的表格
def change_type(df: pd.DataFrame,
table,
col_width_dic: dict
):
for col in list(range(len(table.columns))):
for row in list(range(len(table.rows))):
table.cell(row, col).width = col_width_dic[col]
if row == 0:
try:
table.cell(row, col).text = list(df.columns)[col]