bug修复
parent
cc63ef71e5
commit
8e864c820f
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@ -212,10 +212,10 @@ log/*
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example/*
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!example/readme.md
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xlsx/*
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/xlsx/
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!xlsx/readme.md
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result/*docx
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/result/
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!result/readme.md
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/.report/
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Binary file not shown.
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@ -172,109 +172,6 @@ class Parse(BaseAssignment):
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def msi(self):
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self._to_dicts('MSI')
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# def chemo(self):
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# data = pd.DataFrame(self.sampledata['chemo'])
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#
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# project = data['project'].to_list()[0]
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#
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# # 分类汇总 同位点，药物合并 drug.infos.txt
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# drugrsid = data[['drugname', 'genename', 'rsid', 'result', 'level', 'tips', 'drugsort']]
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# drugrsid = drugrsid.drop_duplicates()
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# resdrugrsid = drugrsid.groupby(['drugname', 'genename', 'rsid', 'result', 'level', 'drugsort'])['tips'].agg(
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# ','.join).reset_index()
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# resdrugrsid.rename(columns=
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# {'drugname': '药物', 'genename': '检测基因', 'rsid': '检测位点', 'result': '基因型',
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# 'level': '证据等级', 'tips': '用药提示'},
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# inplace=True)
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# resdrugrsid = resdrugrsid.sort_values(by=['drugsort', '药物', '检测基因'])
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# self.result['chemo']['druginfo'] = resdrugrsid.to_dict('records')
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#
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# # 药物 药物疗效 推荐程度合并 drug.res.txt
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# drugtypesum = data[['drugname', 'drugtype', 'rsid', 'weights']]
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# drugtypesum = drugtypesum.drop_duplicates()
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# drugtyperes = list()
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# drugsum = dict()
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# for drug, drugdata in drugtypesum.groupby('drugname'):
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# tipsnum = drugdata.groupby(['drugtype']).agg({'weights': 'sum'}).to_dict('index')
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# sumlist = list()
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# if 'LX' in tipsnum:
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# LX = tipsnum['LX']['weights']
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# if LX > 0:
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# lxdes = '疗效较好'
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# lxnum = 1
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# elif LX == 0:
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# lxdes = '疗效一般'
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# lxnum = 0
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# else:
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# lxdes = '疗效较差'
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# lxnum = -1
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# sumlist.append(lxdes)
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# else:
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# LX = 0
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# lxnum = 0
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# if 'DF' in tipsnum:
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# DF = tipsnum['DF']['weights']
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# if DF > 0:
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# dfdes = '毒副较低'
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# dfnum = 1
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# elif DF == 0:
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# dfdes = '毒副一般'
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# dfnum = 0
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# else:
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# dfdes = '毒副较高'
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# dfnum = -1
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# sumlist.append(dfdes)
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# else:
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# DF = 0
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# dfnum = 0
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#
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# # 评价方式 疗效 1 0 -1, 毒副 1 0 -1 ，可形成9宫格
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# sumnum = lxnum + dfnum
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# if sumnum > 0:
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# sumdes = '推荐'
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# elif sumnum == 0:
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# sumdes = '常规'
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# else:
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# sumdes = '谨慎'
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#
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# # 特别药物处理
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# if (drug == "氟尿嘧啶" or drug == "卡培他滨") and DF < 0:
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# sumdes = '谨慎'
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#
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# drugtyperes.append(dict(
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# 药物名称=drug,
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# 疗效=LX,
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# 毒副=DF,
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# 推荐程度=sumdes,
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# 疗效和毒副总结=','.join(sumlist)
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# ))
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# drugsum[drug] = sumdes
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#
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# # 报告中展示药物有顺序
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# drugsort = data[['drugname', 'drugsort']].drop_duplicates()
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# drugsort_dict = drugsort.set_index('drugname')['drugsort'].to_dict()
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# drugtyperes_sort = sorted(drugtyperes, key=lambda x: (
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# drugsort_dict[x['药物名称']] if x['药物名称'] in drugsort_dict else 100, x['药物名称']))
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#
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# drugtyperes_sort_df = pd.DataFrame(drugtyperes_sort)
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# self.result['chemo']['sum'] = drugtyperes_sort_df.groupby('推荐程度')['药物名称'].apply(','.join).to_dict()
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# self.result['chemo']['drugres'] = drugtyperes_sort_df.to_dict('records')
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#
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# # 联合用药
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# drug_combine_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'database',
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# 'chemo_drug_combine.csv')
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# drug_combine = pd.read_csv(drug_combine_path, sep='\t')
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# drug_combine.fillna('.', inplace=True)
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# drug_combine_data = drug_combine[drug_combine['source'].str.contains(project)]
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# drug_combine_data = drug_combine_data.reset_index()
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# if not drug_combine_data.empty:
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# drug_combine_data['临床提示'] = drug_combine_data['用药方案'].apply(self._get_drug_plan, args=(drugsum,))
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# self.result['chemo']['combine'] = drug_combine_data.groupby('癌种').apply(
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# lambda group: group.set_index('癌种').to_dict('records')).to_dict()
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# else:
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# self.result['chemo']['combine'] = dict()
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# self.result['sum']['chemo_drug_num'] = len(drugsum.keys())
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def chemo(self):
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chemo_res = self._to_records('chemo_res', need=True)
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@ -354,7 +251,7 @@ class Parse(BaseAssignment):
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if not data.empty:
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data = data.dropna()
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data = data[data['drug_detail'] != '.']
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data = data.applymap(lambda x: str(x).replace('\\\\', '\n') if ' \\\\' in str(x) else x)
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data = data.applymap(lambda x: str(x).replace('||', '\n') if '||' in str(x) else x)
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res = data.set_index('drug_name')['drug_detail'].to_dict()
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self.result['drugs']['drugs_detail'] = res
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@ -449,24 +346,6 @@ class Parse(BaseAssignment):
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# self.drugs_record['drugs'].update({match.group(1).strip(): match.group(2).strip()})
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return drug_category_res
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@staticmethod
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def _get_drug_plan(x, drugsum):
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tlist = x.split('+')
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tdeslist = list()
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for tdes in tlist:
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if tdes.strip() in drugsum:
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t1_des = drugsum[tdes.strip()]
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tdeslist.append(t1_des)
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if '慎用' in tdeslist or '谨慎' in tdeslist:
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return '慎用'
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elif '推荐' in tdeslist:
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return '推荐'
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elif '常规' in tdeslist:
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return '可选'
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else:
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return '可选'
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def collect(self):
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self.cms()
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self.target()
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