diff --git a/tools/t7.py b/tools/t7.py index c3e6c0f..3935a8e 100644 --- a/tools/t7.py +++ b/tools/t7.py @@ -76,6 +76,9 @@ class AutoLayout: self.return_log = list() self.no_assign_data = list() + # 包lane处理 + self.order_assign_data = list() + self.need_cols = self.read_cols() self.is_use_balance = is_use_balance @@ -483,8 +486,6 @@ class AutoLayout: def assign_samples(self): - # if '未测' not in self.ori_data.keys(): - # raise UserWarning('提供excel没有 未测 sheet ,请核查！') ori_library_df = pd.DataFrame(self.ori_data) # 数据标准格式 @@ -494,18 +495,23 @@ class AutoLayout: # 非正常barcode barcode_mask = ori_library_df['indexi5i7'].str.len() != 16 ori_library_df.loc[barcode_mask, 'indexi5i7'] = ori_library_df.loc[barcode_mask, 'indexi5'].str[-8:] + \ - ori_library_df.loc[barcode_mask, 'indexi7'].str[-8:] + ori_library_df.loc[barcode_mask, 'indexi7'].str[-8:] ori_library_df['note'] = '' ori_library_df.loc[~numeric_mask, 'note'] = 'data_needed 列非数字' ori_library_df.loc[~time_mask, 'note'] = 'time 列非日期' - # ori_library_df.loc[barcode_mask, 'note'] = '非16位barcode' + ori_library_df.loc[barcode_mask, 'note'] = '非16位barcode，已修改' no_ori_data = ori_library_df[~(numeric_mask & time_mask)] self.no_assign_data.extend(no_ori_data.to_dict('records')) + # 包lane的剔除 + orderlane_mask = ori_library_df['productname'].str.contains('包lane') + + self.order_assign_data = ori_library_df[orderlane_mask].to_dict('records') + # 使用布尔索引筛选出不是数字和非日期的行，并且不是暂不排样的行, 以及非16位置barcode - ori_library_df = ori_library_df[(numeric_mask & time_mask) & ~barcode_mask] + ori_library_df = ori_library_df[(numeric_mask & time_mask) & (~orderlane_mask)] # 时间格式化 ori_library_df['receivedtime'] = pd.to_datetime(ori_library_df['receivedtime'], errors='coerce') @@ -539,6 +545,7 @@ class AutoLayout: self.ori_lib_data.append(dict( library=library, + sample_code=library_df['sampleCode'].values[0], is_balance_lib=library_df['librarybalancedflag'].values[0], size=library_df['orderdatavolume'].sum(), split_method=library_df['cycletype'].values[0], @@ -557,6 +564,7 @@ class AutoLayout: self.return_log.append(f'文库{library} 已做拆分处理, 请注意！！！ ') self.ori_lib_data.append(dict( library=library, + sample_code=library_df['sampleCode'].values[0], is_balance_lib=library_df['librarybalancedflag'].values[0], size=library_df['orderdatavolume'].sum(), split_method=library_df['cycletype'].values[0], @@ -569,6 +577,7 @@ class AutoLayout: self.ori_lib_data.append(dict( library=library, + sample_code=library_df['sampleCode'].values[0], is_balance_lib=library_df['librarybalancedflag'].values[0], size=library_df['orderdatavolume'].sum(), split_method=library_df['cycletype'].values[0], @@ -581,7 +590,6 @@ class AutoLayout: self.combinations_same_barcode() self.ori_lib_data = sorted(self.ori_lib_data, key=lambda x: (x['level'], x['time'])) - # self.ori_lib_data = sorted(self.ori_lib_data, key=lambda x: (x['level'] != 100000, -x['size'])) while self.ori_lib_data: library_data = self.ori_lib_data[0] @@ -694,8 +702,6 @@ class AutoLayout: outputpath = os.path.join(self.output, 'result', outputname) writer = pd.ExcelWriter(outputpath) - res = list() - sum_res = list() chip_loc = 1 librarynum = 0 for chip_idx, chip_assignments in self.index_assignments.items(): @@ -722,43 +728,44 @@ class AutoLayout: self.dec_barcode_radio(chip_idx) chipname = addname + chip_idx + other_name - df['lanepackcode'] = chipname - # df = pd.concat([pd.DataFrame(self.items), df]).reset_index(drop=True) - # - # df.to_excel(writer, sheet_name=chipname, index=False) - res.extend(df.to_dict('records')) - chip_loc += 1 - sum_list = list() for library, library_df in df.groupby('samplename'): sum_list.append(dict( + 预排文库编号=library_df['sampleCode'].values[0], 二次拆分=library, 客户=library_df['companynamea'].values[0], - 类型=library_df['classification'].values[0], + 类型=library_df['librarystructure'].values[0], 打折前=library_df['orderdatavolume'].sum() )) df_sum = pd.DataFrame(sum_list) - sum_res.append({'sheetname': chipname, 'data': df_sum}) + res_df = pd.concat([df, df_sum], axis=1) + res_df.to_excel(writer, sheet_name=chipname, index=False) + chip_loc += 1 - res_df = pd.DataFrame(res) - res_df = pd.concat([pd.DataFrame(self.items), res_df]).reset_index(drop=True) - res_df.to_excel(writer, sheet_name='assignment', index=False) + # res_df = pd.DataFrame(res) + # res_df = pd.concat([pd.DataFrame(self.items), res_df]).reset_index(drop=True) + # res_df.to_excel(writer, sheet_name='assignment', index=False) - for sum_sheet in sum_res: - sheetname = sum_sheet.get('sheetname') - df_data = sum_sheet.get('data') - df_data.to_excel(writer, sheet_name=sheetname, index=False) + # for sum_sheet in sum_res: + # sheetname = sum_sheet.get('sheetname') + # df_data = sum_sheet.get('data') + # df_data.to_excel(writer, sheet_name=sheetname, index=False) no_assign_df = pd.DataFrame(self.no_assign_data) if not no_assign_df.empty: no_assign_df = no_assign_df.applymap(lambda x: format_date(x) if isinstance(x, pd.Timestamp) else x) - no_assign_df_not_balance = ','.join(set([lib for lib in no_assign_df['samplename'] if lib in self.split_lib])) + no_assign_df_not_balance = ','.join( + set([lib for lib in no_assign_df['samplename'] if lib in self.split_lib])) if no_assign_df_not_balance: self.return_log.append(f'文库{no_assign_df_not_balance}有做不平衡文库拆分处理，并且没有排完，请核查！') # if not no_assign_df.empty: # no_assign_df = no_assign_df[self.need_cols] no_assign_df = pd.concat([pd.DataFrame(self.items), no_assign_df]).reset_index(drop=True) no_assign_df.to_excel(writer, sheet_name='未测', index=False) + order_assign_df = pd.DataFrame(self.order_assign_data) + if not order_assign_df.empty: + order_assign_df = pd.concat([pd.DataFrame(self.items), order_assign_df]).reset_index(drop=True) + order_assign_df.to_excel(writer, sheet_name='包lane', index=False) if self.return_log: pd.DataFrame(self.return_log).to_excel(writer, sheet_name='log', index=False) writer.close()