feat: 数据预测

src/views/data/train/modelTraining.vue

@@ -370,7 +370,6 @@ const handleChangeStep = (type: string) => {
       if (props.modelForm.status === ModelStatus.NoStart) {
         beginRefreshLog();
       } else {
-        initCurveLog();
         getTrainingResultFun();
       }
     }
@@ -381,11 +380,6 @@ const handleChangeStep = (type: string) => {
       emit('back');
     } else {
       currentStep.value--;
-      // if (currentStep.value === 0) {
-      //   nextTick(() => {
-      //     initCurveSource();
-      //   });
-      // }
     }
   }
 };
@@ -416,24 +410,7 @@ const importFileFun = async (file: any) => {
     ElMessage.success('文件上传成功，正在处理数据，请稍后...');
     createConnection();
   }
-  // if (file.status !== 'error') return;
-  // if (props.modelForm.status !== ModelStatus.NoStart) {
-  //   ElMessage.warning('当前代理模型无法导入数据！');
-  //   return;
-  // }
-  // if (props.modelForm.algorithmType === AlgorithmType.Steady) {
-  //   sourceFileList.value = file;
-  //   if (props.modelForm?.files?.length > 0) {
-  //     delModelTrainingFileApi([props.modelForm?.files[0].id]);
-  //   }
-  // } else {
-  //   sourceFileList.value.push(file);
-  // }
   currentFileName.value = file.name;
-  getSourceData();
-  // const path = ModelFile.getSourceFilePath(props.modelForm.id);
-  // await fragmentUpload(false, file.originFileObj, path, file.name);
-  // addModelTrainingFileApi({ fileName: file.name, fileType: FileUtil.getSuffixName(file.name), fileSize: file.size, path: path });
 };
 const getImportedFileResultFun = async () => {
   const req = {
@@ -466,45 +443,9 @@ const setTableColumnsFun = (sourceTitle: any) => {
   });
   columns.value = cols;
 };
-// 渲染记录的文件信息
-const renderOldInfo = () => {
-  // 回显文件信息
-  if (props.modelForm?.files?.length > 0) {
-    sourceFileList.value = props.modelForm.files.map((item) => {
-      return {
-        ...item,
-        name: item.fileName,
-      };
-    });
-    currentFileName.value = props.modelForm.files[0].fileName;
-    getSourceData();
-  }
 
-  // 回显训练数据
-  if (props.modelForm.columnParam?.length > 2) {
-    const oldColumnParam = JSON.parse(props.modelForm.columnParam);
-    disposeForm.inputColumn = oldColumnParam.inputColumn;
-    disposeForm.outputColumn = oldColumnParam.outputColumn;
-  }
-  console.log('disposeForm', disposeForm);
-};
-const getSourceData = () => {
-  // setColumns();
-  trainDataTableRef.value.setDataFun(sourceData);
-  // trainingSourceData.value = sourceData;
-  nextTick(() => {
-    if (props.modelForm.algorithmType === AlgorithmType.Steady) {
-      getSteadyAverageData();
-      // reloadSourceTable();
-    } else {
-      initCurveSource();
-    }
-  });
-};
 const steadyAverageData = ref<any[]>([]);
-const getSteadyAverageData = () => {
-  steadyAverageData.value = averageData;
-};
+
 const disposeForm = reactive({
   inputColumn: [], // 输入列
   outputColumn: [], // 输出列
@@ -555,47 +496,6 @@ const confirmSetColumnFun = async () => {
 };
 /** 数据处理 */
 
-const sourceChartRef = ref<HTMLDivElement | null>(null);
-// const { setOptions: sourceSetOptions } = useECharts(sourceChartRef as Ref<HTMLDivElement>);
-// 数据源曲线
-const initCurveSource = () => {
-  // sourceSetOptions({
-  //   title: {
-  //     text: '',
-  //   },
-  //   tooltip: {
-  //     trigger: 'axis',
-  //   },
-  //   legend: {
-  //     data: sourceCurveData.legend,
-  //   },
-  //   grid: {
-  //     left: '3%',
-  //     right: '4%',
-  //     bottom: '3%',
-  //     containLabel: true,
-  //   },
-  //   xAxis: {
-  //     type: 'category',
-  //     boundaryGap: false,
-  //     data: sourceCurveData.xAxis,
-  //   },
-  //   yAxis: {
-  //     type: 'value',
-  //   },
-  //   series: sourceCurveData.series.map((item) => {
-  //     return {
-  //       name: item.name,
-  //       type: 'line',
-  //       stack: 'Total',
-  //       smooth: true,
-  //       data: item.data,
-  //       symbol: 'none',
-  //     };
-  //   }),
-  // });
-};
-
 // const algorithmParamForm = reactive({
 //   /** 算法名 */
 //   algorithm: '',
@@ -628,18 +528,7 @@ const initCurveSource = () => {
 // });
 // #endregion
 const algorithmParamForm = reactive<any>({});
-// const basicModelList = [
-//   {
-//     label: 'xxx模型1',
-//     value: '1',
-//   },
-//   {
-//     label: 'xxxx模型2',
-//     value: '2',
-//   },
-// ];
 
-// #region 训练板块
 const paramSettingRef: any = ref(null);
 const beginTrainingFun = async () => {
   const formData = await paramSettingRef.value?.getFormDataFun();
@@ -667,46 +556,6 @@ const stopTrainingFun = async () => {
 // #region 训练板块 训练曲线
 const logChartRef = ref<HTMLDivElement | null>(null);
 
-const initCurveLog = () => {
-  // logSetOptions({
-  //   title: {
-  //     text: '',
-  //   },
-  //   tooltip: {
-  //     trigger: 'axis',
-  //   },
-  //   legend: {
-  //     data: logCurveData.legend,
-  //   },
-  //   grid: {
-  //     left: '3%',
-  //     right: '4%',
-  //     bottom: '3%',
-  //     containLabel: true,
-  //   },
-  //   xAxis: {
-  //     type: 'category',
-  //     boundaryGap: false,
-  //     data: logCurveData.xAxis,
-  //   },
-  //   yAxis: {
-  //     type: 'value',
-  //   },
-  //   series: logCurveData.series.map((item) => {
-  //     return {
-  //       name: item.name,
-  //       type: 'line',
-  //       stack: 'Total',
-  //       smooth: true,
-  //       data: item.data,
-  //       symbol: 'none',
-  //     };
-  //   }),
-  // });
-};
-// #endregion
-// #region 训练板块 训练日志
-
 const lastLogContent = ref('');
 const allLogContent = ref('');
 const logStatus = ref('refresh');
@@ -856,6 +705,7 @@ const renderCurveFun = (curveData: any) => {
       trigger: 'axis',
     },
     legend: {
+      top: 0,
       data: curveData.legend,
     },
     grid: {