isc_corev1.0.1.js

isc_corev1.0.1.js是一个软件技术中常用的JavaScript库，它主要用于创建和处理用户界面，并提供了许多常用的界面组件和功能。这个库的目标是提供一个快速、灵活和易于使用的方式来构建交互式用户界面。

isc_corev1.0.1.js提供了许多功能，包括数据绑定、事件处理、表单验证以及动态用户界面的创建和管理等。它支持各种浏览器，并提供了跨浏览器兼容性的解决方案。

这个JavaScript库的使用非常简单，你只需要在网页的头部引入该库的脚本文件，然后就可以在网页中使用它提供的各种功能和组件了。它的文档详细地描述了每个组件的用法和配置选项。

isc_corev1.0.1.js还提供了一些高级功能，如数据表格、图表和文本编辑器等，可以帮助开发人员更加方便地处理复杂的数据和交互逻辑。

总的来说，isc_corev1.0.1.js是一个功能强大、易于使用和高度可定制的JavaScript库，可以帮助开发人员快速构建现代化的交互式用户界面。无论是开发Web应用程序还是移动应用程序，使用这个库可以极大地提高开发效率，并提供出色的用户体验。

相关问题

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

Here are some suggestions to optimize the code:

1. Use list comprehension to simplify the code:

   alarm_df = pd.concat([isc_input, ica_input, soh_input]).reset_index(drop=True)
   alarm_df['alarm_cell'] = alarm_df['alarm_cell'].apply(str)

2. Use context manager to simplify file operation:

   with open(os.path.join(log_path, 'log.txt'), 'w') as txt_file:
       for k, v in module.output.items():
           txt_file.write(f"{k}:{v}\n")
       for x, y in module.output_sub.items():
           txt_file.write(f"{x}:{y}\n\n")

3. Use `Pathlib` to simplify path operation:

   fc_result_path = Path(done_path) / vin / 'fc_result'
   fc_result_path.mkdir(parents=True, exist_ok=True)
   pd.DataFrame(module.output).to_csv(fc_result_path / 'main_structure.csv')
   pd.DataFrame(module.output_sub).to_csv(fc_result_path / 'sub_structure.csv')

4. Use f-string to simplify string formatting:

   print(f"time cost of fault classification: {(end_time - start_time) * 1000.0} ms")

Here's the optimized code:

def fault_classification_wrapper(vin, main_path, data_path, log_path, done_path):
    start_time = time.time()

    isc_path = Path(done_path) / vin / 'isc_cal_result' / f'{vin}_report.xlsx'
    if not isc_path.exists():
        print('No isc detection input!')
        isc_input = pd.DataFrame()
    else:
        isc_input = isc_produce_alarm(isc_path, vin)

    ica_path = Path(done_path) / vin / 'ica_cal_result' / f'ica_detection_alarm_{vin}.csv'
    if not ica_path.exists():
        print('No ica detection input!')
        ica_input = pd.DataFrame()
    else:
        ica_input = ica_produce_alarm(ica_path)

    soh_path = Path(done_path) / vin / 'SOH_cal_result' / f'{vin}_sohAno.csv'
    if not soh_path.exists():
        print('No soh detection input!')
        soh_input = pd.DataFrame()
    else:
        soh_input = soh_produce_alarm(soh_path, vin)

    alarm_df = pd.concat([isc_input, ica_input, soh_input]).reset_index(drop=True)
    alarm_df['alarm_cell'] = alarm_df['alarm_cell'].apply(str)

    print(vin)
    module = AutoAnalysisMain(alarm_df, main_path, data_path, done_path)
    module.analysis_process()

    with open(Path(log_path) / 'log.txt', 'w') as txt_file:
        for k, v in module.output.items():
            txt_file.write(f"{k}:{v}\n")
        for x, y in module.output_sub.items():
            txt_file.write(f"{x}:{y}\n\n")

    fc_result_path = Path(done_path) / vin / 'fc_result'
    fc_result_path.mkdir(parents=True, exist_ok=True)
    pd.DataFrame(module.output).to_csv(fc_result_path / 'main_structure.csv')
    pd.DataFrame(module.output_sub).to_csv(fc_result_path / 'sub_structure.csv')

    end_time = time.time()
    print(f"time cost of fault classification: {(end_time - start_time) * 1000.0} ms")

    return

帮我解析一下这个java错误，Caused by: org.h2.jdbc.JdbcSQLSyntaxErrorException: Syntax error in SQL statement "SELECT C.PERIOD_NO, C.BILL_MONTH, C.LOCAL_AIR_CODE, C.INT_DOM_INDICATOR, 'GLOBAL' AS CHECK_CODE, CASE WHEN COUPON_COUNT_GLOBAL = COUPON_COUNT_REPORT AND TAX_AMT_GLOBAL = TAX_AMT_REPORT AND ISC_AMT_GLOBAL = ISC_AMT_REPORT AND UATP_AMT_GLOBAL = UATP_AMT_REPORT AND GROSS_AMT_GLOBAL = GROSS_AMT_REPORT THEN 'S' ELSE 'F' END AS CHECK_RESULT_IND, TAX_AMT_GLOBAL AS TAX_AMT_ACTUAL, TAX_AMT_REPORT AS TAX_AMT_EXPECTED, ISC_AMT_GLOBAL AS ISC_AMT_ACTUAL, ISC_AMT_REPORT AS ISC_AMT_EXPECTED, UATP_AMT_GLOBAL AS UATP_AMT_ACTUAL, UATP_AMT_REPORT AS UATP_AMT_EXPECTED, GROSS_AMT_GLOBAL AS GROSS_AMT_ACTUAL, GROSS_AMT_REPORT AS GROSS_AMT_EXPECTED, COUPON_COUNT_GLOBAL AS COUPON_COUNT_ACTUAL, COUPON_COUNT_REPORT AS COUPON_COUNT_EXPECTED FROM ( ( SELECT BILL_MONTH, PERIOD_NO, LOCAL_AIR_CODE, INT_DOM_INDICATOR, SUM(COUPON_COUNT) AS COUPON_COUNT_GLOBAL, CASE WHEN SUM(GROSS_AMT_BILLING) IS NULL THEN 0 ELSE SUM(GROSS_AMT_BILLING) END AS GROSS_AMT_GLOBAL, CASE WHEN SUM(BILL_TAX_BILLING) IS NULL THEN 0 ELSE SUM(BILL_TAX_BILLING) END AS TAX_AMT_GLOBAL, CASE WHEN SUM(ISC_AMT_BILLING) IS NULL THEN 0 ELSE SUM(ISC_AMT_BILLING) END AS ISC_AMT_GLOBAL, CASE WHEN SUM(UATP_AMT_BILLING) IS NULL THEN 0 ELSE SUM(UATP_AMT_BILLING) END AS UATP_AMT_GLOBAL FROM OWB_GLOBAL_REPORT WHERE REPORT_TYPE = 'R' AND DELETE_IND IS NULL AND PERIOD_NO = ? AND BILL_MONTH = ? AND INT_DOM_INDICATOR = ? AND LOCAL_AIR_CODE = ? GROUP BY BILL_MONTH, PERIOD_NO, LOCAL_AIR_CODE, INT_DOM_INDICATOR) C[*] INNER JOIN ( SELECT BILL_MONTH, PERIOD_NO, LOCAL_AIR_CODE, INT_DOM_INDICATOR, SUM(COUPON_COUNT) AS COUPON_COUNT_REPORT, CASE WHEN SUM(GROSS_AMT_BILLING) IS NULL THEN 0 ELSE SUM(GROSS_AMT_BILLING) END AS GROSS_AMT_REPORT, CASE WHEN SUM(BILL_TAX_BILLING) IS NULL THEN 0 ELSE SUM(BILL_TAX_BILLING) END AS TAX_AMT_REPORT, CASE WHEN SUM(ISC_AMT_BILLING) IS NULL THEN 0 ELSE SUM(ISC_AMT_BILLING) END AS ISC_AMT_REPORT, CASE WHEN SUM(UATP_AMT_BILLING) IS NULL THEN 0 ELSE SUM(UATP_AMT_BILLING) END AS UATP_AMT_REPORT FROM OWB_REPORT WHERE ADJ_MONTH IS NULL AND PERIOD_NO = ? AND BILL_MONTH = ? AND INT_DOM_INDICATOR = ? AND LOCAL_AIR_CODE = ? GROUP BY BILL_MONTH, PERIOD_NO, LOCAL_AIR_CODE, INT_DOM_INDICATOR) R ON C.BILL_MONTH = R.BILL_MONTH AND C.PERIOD_NO = R.PERIOD_NO AND C.LOCAL_AIR_CODE = R.LOCAL_AIR_CODE AND C.INT_DOM_INDICATOR = R.INT_DOM_INDICATOR )"; expected "UNION, EXCEPT, MINUS, INTERSECT, ORDER, OFFSET, FETCH, LIMIT, SAMPLE_SIZE, FOR, )";

这个错误是由于Java程序中的SQL语句存在语法错误导致的。根据错误信息，语法错误出现在SQL查询语句的最后部分。错误提示指出在预期的位置上应该是"UNION, EXCEPT, MINUS, INTERSECT, ORDER, OFFSET, FETCH, LIMIT, SAMPLE_SIZE, FOR, )"中的一个。

根据提供的代码片段，可以看到查询语句的最后部分缺少了一些关键字或者可能存在其他的语法错误。请检查您的查询语句，并确保在合适的位置添加必要的关键字。如果可以提供完整的查询语句，我可以更详细地帮助您找到问题所在。