Allow viscosity number predictions to be saved
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@ -40,7 +40,7 @@
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</div>
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<div class="file-input space-below">
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<rb-form-file name="spectrum-upload" label="spectrum file" maxSize="10000000" class="space-below" multiple
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<rb-form-file name="spectrum-upload" label="Spectrum File" maxSize="10000000" class="space-below" multiple
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(ngModelChange)="fileToArray($event)" placeholder="Select file or drag and drop" dragDrop ngModel>
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</rb-form-file>
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@ -72,6 +72,20 @@
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Export to PDF
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</rb-icon-button>
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<!-- Save Prediction -->
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<!-- Only available for single sample viscosity number predictions -->
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<div *ngIf="spectrumNames.length && !multipleSamples && activeGroup.group === 'Viscosity Number'">
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<rb-form-input name="prediction-name" label="Prediction Name" [(ngModel)]="predictionName"></rb-form-input>
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<rb-icon-button icon="forward-right" mode="secondary" (click)="savePrediction()" [rbModal]="modalSuccess">
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Save Prediction
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</rb-icon-button>
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<ng-template #modalSuccess>
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<rb-alert alertTitle="Success" type="success" okBtnLabel="Got it">
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Prediction saved!
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</rb-alert>
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</ng-template>
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</div>
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<div class="dpt-chart space-below">
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<canvas baseChart
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class="dpt-chart"
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@ -39,8 +39,11 @@ export class PredictionComponent implements OnInit {
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loading = false;
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activeGroup: ModelItemModel = new ModelItemModel();
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activeModelIndex = 0;
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predictionName: String;
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// If true, spectra belong to different samples, otherwise multiple spectra from the same sample are given
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multipleSamples = false;
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spectrumNames: string[] = [];
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spectrum: string[][] = [[]];
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flattenedSpectra = [];
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@ -122,20 +125,28 @@ export class PredictionComponent implements OnInit {
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});
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}
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groupChange(index) { // Group was changed
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// Group was changed
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groupChange(index) {
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this.activeGroup = this.d.arr.modelGroups[index];
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this.activeModelIndex = 0;
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this.result = undefined;
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}
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// Save prediction to database
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// This is not suited for multiple samples
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savePrediction() {
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let prediction = { name: this.predictionName, value: this.result.mean[0].value };
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this.api.post<any>('/prediction/new', prediction);
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}
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// Aggregates spectrum names and prediction values into an associative array
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prepareExport() {
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const zip = (a, b) => a.map((k, i) => [k, b[i]]);
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const values = this.result.predictions
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.map(prediction => prediction
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.filter(field => field.category === 'Prediction')
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.map(field => field.value));
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return zip(this.spectrumNames, values);
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.map(prediction => prediction
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.filter(field => field.category === 'Prediction')
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.map(field => field.value));
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return zip(this.spectrumNames, values);
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}
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// Generates a timestamp suitable for file naming
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