"高通 QXDM Log分析:网络适应性部分"

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"Log Analysis_Subs_V20.docx" is a document that focuses on network adaptability and QX log analysis, specifically analyzing 3/2G signaling. The analysis is conducted using the QXDM tool, which is a Qualcomm platform for log analysis. The document provides a detailed overview of the analysis process, including the creation date and version of the analysis tool. The main purpose of the analysis is to understand the network adaptability and performance of GSM and other 3/2G networks. The document includes a section on GSM call logs, with a specific focus on GSM originating mobile terminated call logs. It also covers OTA (Over-the-Air) important logs related to GSM main calls. Overall, the document serves as a guide for conducting network adaptability analysis using the QXDM tool, focusing on GSM and 3/2G networks. It also emphasizes the importance of internal learning and collaboration for the continuous improvement of log analysis processes. The document provides a comprehensive overview of the analysis process and the key insights that can be gained from the log data. In conclusion, "Log Analysis_Subs_V20.docx" is a valuable resource for professionals involved in network adaptability and QX log analysis, providing a detailed and insightful guide to analyzing 3/2G signaling and GSM call logs. It is an essential tool for improving network performance and adaptability in the telecommunications industry.

优化代码 def fault_classification_wrapper(vin, main_path, data_path, log_path, done_path): start_time = time.time() isc_path = os.path.join(done_path, vin, 'isc_cal_result', f'{vin}_report.xlsx') if not os.path.exists(isc_path): print('No isc detection input!') else: isc_input = isc_produce_alarm(isc_path, vin) ica_path = os.path.join(done_path, vin, 'ica_cal_result', f'ica_detection_alarm_{vin}.csv') if not os.path.exists(ica_path): print('No ica detection input!') else: ica_input = ica_produce_alarm(ica_path) soh_path = os.path.join(done_path, vin, 'SOH_cal_result', f'{vin}_sohAno.csv') if not os.path.exists(soh_path): print('No soh detection input!') else: soh_input = soh_produce_alarm(soh_path, vin) alarm_df = pd.concat([isc_input, ica_input, soh_input]) alarm_df.reset_index(drop=True, inplace=True) alarm_df['alarm_cell'] = alarm_df['alarm_cell'].apply(lambda _: str(_)) print(vin) module = AutoAnalysisMain(alarm_df, main_path, data_path, done_path) module.analysis_process() flags = os.O_WRONLY | os.O_CREAT modes = stat.S_IWUSR | stat.S_IRUSR with os.fdopen(os.open(os.path.join(log_path, 'log.txt'), flags, modes), 'w') as txt_file: for k, v in module.output.items(): txt_file.write(k + ':' + str(v)) txt_file.write('\n') for x, y in module.output_sub.items(): txt_file.write(x + ':' + str(y)) txt_file.write('\n\n') fc_result_path = os.path.join(done_path, vin, 'fc_result') if not os.path.exists(fc_result_path): os.makedirs(fc_result_path) pd.DataFrame(module.output).to_csv( os.path.join(fc_result_path, 'main_structure.csv')) df2 = pd.DataFrame() for subs in module.output_sub.keys(): sub_s = pd.Series(module.output_sub[subs]) df2 = df2.append(sub_s, ignore_index=True) df2.to_csv(os.path.join(fc_result_path, 'sub_structure.csv')) end_time = time.time() print("time cost of fault classification:", float(end_time - start_time) * 1000.0, "ms") return

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