Promenio dodavanje fajla u folderu da ne menja naslov tab-a. Podesio form-model komponentu da setuje tip problema modela na tip problema eksperimenta i ispravio da se uvak prikazuju korektne funkcije gubitka za taj tip problema. Popravio forme za dodavanje/pregled fajlova u arhivi.

2 files changed, 30 insertions, 37 deletions

diff --git a/frontend/src/app/_elements/form-model/form-model.component.html b/frontend/src/app/_elements/form-model/form-model.component.html
index 97e38cf1..1b4eb834 100644
--- a/frontend/src/app/_elements/form-model/form-model.component.html
+++ b/frontend/src/app/_elements/form-model/form-model.component.html
@@ -11,12 +11,7 @@
             <div class="ns-col">
                 <mat-form-field appearance="fill" class="mat-fix">
                     <mat-label>Tip problema</mat-label>
-                    <mat-select [(ngModel)]="newModel.type" (selectionChange)="filterLossFunction()" *ngIf="this.hideProblemType" disabled="true">
-                        <mat-option *ngFor="let option of Object.keys(ProblemType); let optionName of Object.values(ProblemType)" [value]="option">
-                            {{ optionName }}
-                        </mat-option>
-                    </mat-select>
-                    <mat-select [(ngModel)]="newModel.type" (selectionChange)="filterLossFunction()" *ngIf="!this.hideProblemType" disabled="false">
+                    <mat-select [(ngModel)]="forProblemType" [disabled]="this.hideProblemType">
                         <mat-option *ngFor="let option of Object.keys(ProblemType); let optionName of Object.values(ProblemType)" [value]="option">
                             {{ optionName }}
                         </mat-option>
@@ -41,7 +36,7 @@
                 <mat-form-field appearance="fill" class="mat-fix">
                     <mat-label>Funkcija troška</mat-label>
                     <mat-select [(ngModel)]="newModel.lossFunction">
-                        <mat-option *ngFor="let option of Object.keys(lossFunction); let optionName of Object.values(lossFunction)" [value]="option">
+                        <mat-option *ngFor="let option of Object.keys(lossFunctions[forProblemType]); let optionName of Object.values(lossFunctions[forProblemType])" [value]="option">
                             {{ optionName }}
                         </mat-option>
                     </mat-select>
@@ -118,8 +113,7 @@
 
             <div class="col-sm-9">
                 <!-- {{forExperiment._columnsSelected}} -->
-                <app-graph [model]="newModel" *ngIf="forExperiment._columnsSelected" [inputColumns]="getInputColumns()"></app-graph>
-                <app-graph [model]="newModel" *ngIf="!forExperiment._columnsSelected" [inputColumns]="['Nisu odabrane ulazne kolone']"></app-graph>
+                <app-graph [model]="newModel" [inputColumns]="getInputColumns()"></app-graph>
             </div>
         </div>
     </div>
diff --git a/frontend/src/app/_elements/form-model/form-model.component.ts b/frontend/src/app/_elements/form-model/form-model.component.ts
index c8822992..c9e2fc8e 100644
--- a/frontend/src/app/_elements/form-model/form-model.component.ts
+++ b/frontend/src/app/_elements/form-model/form-model.component.ts
@@ -15,13 +15,13 @@ export class FormModelComponent implements AfterViewInit {
   @ViewChild(GraphComponent) graph!: GraphComponent;
   @Input() forExperiment!: Experiment;
   @Output() selectedModelChangeEvent = new EventEmitter<Model>();
-  @Input() hideProblemType:boolean;
-  @Input() forProblemType:ProblemType;
+  @Input() hideProblemType: boolean;
+  @Input() forProblemType: ProblemType;
   testSetDistribution: number = 70;
-  validationSize:number=15;
-  constructor() { 
-    this.hideProblemType=false;
-    this.forProblemType=ProblemType.BinaryClassification;
+  validationSize: number = 15;
+  constructor() {
+    this.hideProblemType = false;
+    this.forProblemType = ProblemType.BinaryClassification;
   }
 
   ngAfterViewInit(): void { }
@@ -59,10 +59,15 @@ export class FormModelComponent implements AfterViewInit {
 
   term: string = "";
   selectedMetrics = [];
-  lossFunction: any = LossFunction;
+  lossFunctions: { [index: string]: LossFunction[] } = {
+    [ProblemType.Regression]: LossFunctionRegression,
+    [ProblemType.BinaryClassification]: LossFunctionBinaryClassification,
+    [ProblemType.MultiClassification]: LossFunctionMultiClassification
+  };
 
   loadModel(model: Model) {
     this.newModel = model;
+    this.forProblemType = model.type;
   }
 
   updateGraph() {
@@ -77,6 +82,7 @@ export class FormModelComponent implements AfterViewInit {
       this.updateGraph();
     }
   }
+
   addLayer() {
     if (this.newModel.hiddenLayers < 128) {
       this.newModel.layers.push(new Layer(this.newModel.layers.length, this.selectedActivation, this.selectedNumberOfNeurons, this.selectedRegularisation, this.selectedRegularisationRate));
@@ -84,8 +90,8 @@ export class FormModelComponent implements AfterViewInit {
       this.newModel.hiddenLayers += 1;
       this.updateGraph();
     }
-
   }
+
   numSequence(n: number): Array<number> {
     return Array(n);
   }
@@ -96,12 +102,14 @@ export class FormModelComponent implements AfterViewInit {
       this.updateGraph();
     }
   }
+
   addNeuron(index: number) {
     if (this.newModel.layers[index].neurons < 18) {
       this.newModel.layers[index].neurons += 1;
       this.updateGraph();
     }
   }
+
   selectedActivation: ActivationFunction = ActivationFunction.Sigmoid;
   selectedRegularisationRate: RegularisationRate = RegularisationRate.RR1;
   selectedRegularisation: Regularisation = Regularisation.L1;
@@ -131,24 +139,15 @@ export class FormModelComponent implements AfterViewInit {
   updateTestSet(event: MatSliderChange) {
     this.testSetDistribution = event.value!;
   }
-  filterLossFunction() {
-  if(this.newModel.type==ProblemType.Regression){
-    this.lossFunction = LossFunctionRegression;
-    this.newModel.lossFunction=LossFunction.MeanSquaredError;
-    }
-  else if(this.newModel.type==ProblemType.BinaryClassification){
-    this.lossFunction= LossFunctionBinaryClassification;
-    this.newModel.lossFunction=LossFunction.BinaryCrossEntropy;
-    }
-  else if(this.newModel.type==ProblemType.MultiClassification){
-    this.lossFunction = LossFunctionMultiClassification;
-    this.newModel.lossFunction=LossFunction.SparseCategoricalCrossEntropy;
-    }
-  
-}
-getInputColumns() {
-    return this.forExperiment.inputColumns.filter(x => x != this.forExperiment.outputColumn);
+
+  getInputColumns() {
+    if (this.forExperiment)
+      return this.forExperiment.inputColumns.filter(x => x != this.forExperiment.outputColumn);
+    else
+      return ['Nisu odabrane ulazne kolone.']
+  }
+
+  updateValidation(event: MatSliderChange) {
+    this.validationSize = event.value!;
+  }
 }
-updateValidation(event: MatSliderChange) {
-  this.validationSize = event.value!;
-}}