From eee8b1f3790b243be19b015a37a2acd4e882b31e Mon Sep 17 00:00:00 2001 From: Sonja Galovic Date: Wed, 4 May 2022 20:46:59 +0200 Subject: Omogucena izmena eksperimenta. Popravljen bag kod izbora izlazne kolone kad se menja izabran dataset (reset inputa i outputa). --- .../column-table/column-table.component.html | 27 +++++++++++------ .../column-table/column-table.component.ts | 34 +++++++++++++++++----- 2 files changed, 44 insertions(+), 17 deletions(-) (limited to 'frontend/src/app/_elements/column-table') diff --git a/frontend/src/app/_elements/column-table/column-table.component.html b/frontend/src/app/_elements/column-table/column-table.component.html index 543a0018..43895863 100644 --- a/frontend/src/app/_elements/column-table/column-table.component.html +++ b/frontend/src/app/_elements/column-table/column-table.component.html @@ -186,7 +186,7 @@ - + @@ -225,15 +225,24 @@
-
- + + diff --git a/frontend/src/app/_elements/column-table/column-table.component.ts b/frontend/src/app/_elements/column-table/column-table.component.ts index c3d4f206..7cac3b27 100644 --- a/frontend/src/app/_elements/column-table/column-table.component.ts +++ b/frontend/src/app/_elements/column-table/column-table.component.ts @@ -10,6 +10,8 @@ import { CsvParseService } from 'src/app/_services/csv-parse.service'; import { ProblemType } from 'src/app/_data/Model'; import { ExperimentsService } from 'src/app/_services/experiments.service'; import { SaveExperimentDialogComponent } from 'src/app/_modals/save-experiment-dialog/save-experiment-dialog.component'; +import { AlertDialogComponent } from 'src/app/_modals/alert-dialog/alert-dialog.component'; +import Shared from 'src/app/Shared'; @Component({ selector: 'app-column-table', @@ -20,7 +22,6 @@ export class ColumnTableComponent implements AfterViewInit { @Input() dataset?: Dataset; @Input() experiment!: Experiment; - @ViewChildren("nullValMenu") nullValMenus!: ElementRef[]; @Output() okPressed: EventEmitter = new EventEmitter(); @Output() columnTableChanged = new EventEmitter(); @@ -49,10 +50,8 @@ export class ColumnTableComponent implements AfterViewInit { this.columnsChecked.push(true); }); - for (let i = 0; i < this.dataset?.columnInfo.length; i++) { - this.experiment.inputColumns.push(this.dataset.columnInfo[i].columnName); - } - this.experiment.outputColumn = this.experiment.inputColumns[0]; + this.resetInputColumns(); + this.resetOutputColumn(); this.resetColumnEncodings(Encoding.Label); this.setDeleteRowsForMissingValTreatment(); @@ -81,6 +80,18 @@ export class ColumnTableComponent implements AfterViewInit { } } + resetInputColumns() { + if (this.dataset != undefined) { + this.experiment.inputColumns = []; + for (let i = 0; i < this.dataset?.columnInfo.length; i++) { + this.experiment.inputColumns.push(this.dataset.columnInfo[i].columnName); + } + } + } + resetOutputColumn() { + this.experiment.outputColumn = this.experiment.inputColumns[0]; + } + setDeleteRowsForMissingValTreatment() { if (this.experiment != undefined) { this.experiment.nullValues = NullValueOptions.DeleteRows; @@ -212,13 +223,17 @@ export class ColumnTableComponent implements AfterViewInit { this.experiment.name = selectedName; //napravi odvojene dugmice za save i update -> za update nece da se otvara dijalog za ime this.experimentService.addExperiment(this.experiment).subscribe((response) => { - console.log(response); + this.experiment = response; this.okPressed.emit(); }); }); } - - + + openUpdateExperimentDialog() { + this.experimentService.updateExperiment(this.experiment).subscribe((response) => { + Shared.openDialog("Izmena eksperimenta", "Uspešno ste izmenili podatke o eksperimentu."); + }); + } MissValsDeleteClicked(event: Event, replacementType: NullValueOptions, index: number) { if (this.experiment != undefined && this.dataset != undefined) { @@ -272,6 +287,9 @@ export class ColumnTableComponent implements AfterViewInit { saveExperiment() { this.openSaveExperimentDialog(); } + updateExperiment() { + this.openUpdateExperimentDialog(); + } tabs = [ -- cgit v1.2.3 From ae29f2f27d680d4152d3f19eb1db284aa951d0cd Mon Sep 17 00:00:00 2001 From: Sonja Galovic Date: Wed, 4 May 2022 21:08:42 +0200 Subject: Izmena eksperimenta - uskladjeni back i front. --- backend/api/api/Controllers/ExperimentController.cs | 3 +-- backend/api/api/Interfaces/IExperimentService.cs | 2 +- backend/api/api/Services/ExperimentService.cs | 3 ++- frontend/src/app/_elements/column-table/column-table.component.ts | 1 + 4 files changed, 5 insertions(+), 4 deletions(-) (limited to 'frontend/src/app/_elements/column-table') diff --git a/backend/api/api/Controllers/ExperimentController.cs b/backend/api/api/Controllers/ExperimentController.cs index 1cac386a..6f1bbd42 100644 --- a/backend/api/api/Controllers/ExperimentController.cs +++ b/backend/api/api/Controllers/ExperimentController.cs @@ -108,9 +108,8 @@ namespace api.Controllers experiment.lastUpdated = DateTime.UtcNow; - _experimentService.Update(uploaderId, id, experiment); - return Ok($"Experiment with ID = {id} updated"); + return Ok(_experimentService.Update(uploaderId, id, experiment)); } // DELETE api//name diff --git a/backend/api/api/Interfaces/IExperimentService.cs b/backend/api/api/Interfaces/IExperimentService.cs index 311560e8..7e59ace3 100644 --- a/backend/api/api/Interfaces/IExperimentService.cs +++ b/backend/api/api/Interfaces/IExperimentService.cs @@ -9,7 +9,7 @@ namespace api.Services public List GetMyExperiments(string id); public Experiment Get(string uploaderId, string name); Experiment GetOneExperiment(string userId, string id); - void Update(string userId, string id, Experiment experiment); + Experiment Update(string userId, string id, Experiment experiment); void Delete(string userId, string id); } diff --git a/backend/api/api/Services/ExperimentService.cs b/backend/api/api/Services/ExperimentService.cs index 2ad9d606..dde9111d 100644 --- a/backend/api/api/Services/ExperimentService.cs +++ b/backend/api/api/Services/ExperimentService.cs @@ -45,9 +45,10 @@ namespace api.Services return _experiment.Find(experiment => experiment.uploaderId == userId && experiment._id == id).FirstOrDefault(); } - public void Update(string userId, string id, Experiment experiment) + public Experiment Update(string userId, string id, Experiment experiment) { _experiment.ReplaceOne(experiment => experiment.uploaderId == userId && experiment._id == id, experiment); + return _experiment.Find(experiment => experiment.uploaderId == userId && experiment._id == id).FirstOrDefault(); } public void Delete(string userId, string id) diff --git a/frontend/src/app/_elements/column-table/column-table.component.ts b/frontend/src/app/_elements/column-table/column-table.component.ts index 7cac3b27..e6007d91 100644 --- a/frontend/src/app/_elements/column-table/column-table.component.ts +++ b/frontend/src/app/_elements/column-table/column-table.component.ts @@ -231,6 +231,7 @@ export class ColumnTableComponent implements AfterViewInit { openUpdateExperimentDialog() { this.experimentService.updateExperiment(this.experiment).subscribe((response) => { + this.experiment = response; Shared.openDialog("Izmena eksperimenta", "Uspešno ste izmenili podatke o eksperimentu."); }); } -- cgit v1.2.3 From f5b097930797f49a97d12c9885def67a22edf02e Mon Sep 17 00:00:00 2001 From: Danijel Anđelković Date: Wed, 4 May 2022 21:38:53 +0200 Subject: Promenio ispis korelacione matrice na prave vrednosti. --- backend/microservice/api/newmlservice.py | 4 +++- frontend/src/app/_data/Dataset.ts | 2 +- .../_elements/column-table/column-table.component.html | 8 ++++---- .../app/_elements/column-table/column-table.component.ts | 16 ++++++++-------- frontend/src/app/_elements/folder/folder.component.ts | 2 +- .../app/_elements/form-model/form-model.component.html | 2 +- frontend/src/app/_elements/graph/graph.component.html | 6 +++--- 7 files changed, 21 insertions(+), 19 deletions(-) (limited to 'frontend/src/app/_elements/column-table') diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index f5e5abcc..ad848fd9 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -130,7 +130,9 @@ def returnColumnsInfo(dataset): #print(NullRows) #print(len(NullRows)) allNullRows=len(NullRows) - return {'columnInfo':dict,'allNullColl':int(allNullCols),'allNullRows':int(allNullRows),'rowCount':int(rowCount),'colCount':int(colCount),'cMatrix':str(np.matrix(cMatrix))} + print(cMatrix.to_json(orient='index')) + #json.loads()['data'] + return {'columnInfo':dict,'allNullColl':int(allNullCols),'allNullRows':int(allNullRows),'rowCount':int(rowCount),'colCount':int(colCount),'cMatrix':json.loads(cMatrix.to_json(orient='split'))['data']} @dataclass class TrainingResultClassification: diff --git a/frontend/src/app/_data/Dataset.ts b/frontend/src/app/_data/Dataset.ts index 9efb9f9b..ca1a2a5e 100644 --- a/frontend/src/app/_data/Dataset.ts +++ b/frontend/src/app/_data/Dataset.ts @@ -18,7 +18,7 @@ export default class Dataset extends FolderFile { public rowCount: number = 0, public nullRows: number = 0, public nullCols: number = 0, - public cMatrix: string[][] = [[]] + public cMatrix: number[][] = [] ) { super(name, dateCreated, lastUpdated); } diff --git a/frontend/src/app/_elements/column-table/column-table.component.html b/frontend/src/app/_elements/column-table/column-table.component.html index 43895863..09ddffc6 100644 --- a/frontend/src/app/_elements/column-table/column-table.component.html +++ b/frontend/src/app/_elements/column-table/column-table.component.html @@ -64,15 +64,15 @@ - +
- {{colInfo.columnName}} + {{dataset.columnInfo[i].columnName}}
- +
- 0.1 + {{corrVal}}
diff --git a/frontend/src/app/_elements/column-table/column-table.component.ts b/frontend/src/app/_elements/column-table/column-table.component.ts index 7cac3b27..da451d55 100644 --- a/frontend/src/app/_elements/column-table/column-table.component.ts +++ b/frontend/src/app/_elements/column-table/column-table.component.ts @@ -36,7 +36,7 @@ export class ColumnTableComponent implements AfterViewInit { columnsChecked: boolean[] = []; //niz svih kolona loaded: boolean = false; - + constructor(private datasetService: DatasetsService, private experimentService: ExperimentsService, public csvParseService: CsvParseService, public dialog: MatDialog) { //ovo mi nece trebati jer primam dataset iz druge komponente } @@ -45,11 +45,11 @@ export class ColumnTableComponent implements AfterViewInit { this.dataset = dataset; this.setColumnTypeInitial(); - + this.dataset.columnInfo.forEach(column => { this.columnsChecked.push(true); }); - + this.resetInputColumns(); this.resetOutputColumn(); this.resetColumnEncodings(Encoding.Label); @@ -69,7 +69,7 @@ export class ColumnTableComponent implements AfterViewInit { } ngAfterViewInit(): void { - + } setColumnTypeInitial() { @@ -113,7 +113,7 @@ export class ColumnTableComponent implements AfterViewInit { columnTypeChanged(columnName: string) { if (this.experiment.outputColumn == columnName) this.changeOutputColumn(columnName); - else + else this.columnTableChangeDetected(); } @@ -147,7 +147,7 @@ export class ColumnTableComponent implements AfterViewInit { else { if (column.uniqueValues!.length == 2) this.experiment.type = ProblemType.BinaryClassification; - else + else this.experiment.type = ProblemType.MultiClassification; } this.columnTableChangeDetected(); @@ -199,7 +199,7 @@ export class ColumnTableComponent implements AfterViewInit { value: "" }); let numOfRowsToDelete = (this.dataset.columnInfo.filter(x => x.columnName == this.experiment!.inputColumns[i])[0]).numNulls; - this.nullValOption[i] = "Obriši redove (" + numOfRowsToDelete + ")"; + this.nullValOption[i] = "Obriši redove (" + numOfRowsToDelete + ")"; } } this.columnTableChangeDetected(); @@ -228,7 +228,7 @@ export class ColumnTableComponent implements AfterViewInit { }); }); } - + openUpdateExperimentDialog() { this.experimentService.updateExperiment(this.experiment).subscribe((response) => { Shared.openDialog("Izmena eksperimenta", "Uspešno ste izmenili podatke o eksperimentu."); diff --git a/frontend/src/app/_elements/folder/folder.component.ts b/frontend/src/app/_elements/folder/folder.component.ts index ffce3fb1..a99c6a9d 100644 --- a/frontend/src/app/_elements/folder/folder.component.ts +++ b/frontend/src/app/_elements/folder/folder.component.ts @@ -169,7 +169,7 @@ export class FolderComponent implements AfterViewInit { this.formDataset!.uploadDataset((dataset: Dataset) => { this.newFile = undefined; Shared.openDialog("Obaveštenje", "Uspešno ste dodali novi izvor podataka u kolekciju. Molimo sačekajte par trenutaka da se procesira."); - this.refreshFiles(dataset._id); + this.refreshFiles(null); }, () => { Shared.openDialog("Neuspeo pokušaj!", "Izvor podataka sa unetim nazivom već postoji u Vašoj kolekciji. Izmenite naziv ili iskoristite postojeći dataset."); 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 bf4aa0e3..96a5e1b6 100644 --- a/frontend/src/app/_elements/form-model/form-model.component.html +++ b/frontend/src/app/_elements/form-model/form-model.component.html @@ -109,7 +109,7 @@
- +
diff --git a/frontend/src/app/_elements/graph/graph.component.html b/frontend/src/app/_elements/graph/graph.component.html index a021431d..35753d40 100644 --- a/frontend/src/app/_elements/graph/graph.component.html +++ b/frontend/src/app/_elements/graph/graph.component.html @@ -1,8 +1,8 @@
- + -
\ No newline at end of file + \ No newline at end of file -- cgit v1.2.3 From 75f0fca5f9e7e74979f63d73741512ea2e58e9e6 Mon Sep 17 00:00:00 2001 From: Danijel Anđelković Date: Wed, 4 May 2022 22:33:10 +0200 Subject: Promenio nazive ulaza na ML u za treniranje modela. --- backend/microservice/api/newmlservice.py | 47 +++++++++++++--------- .../column-table/column-table.component.ts | 2 +- .../src/app/_elements/folder/folder.component.ts | 5 ++- .../_pages/experiment/experiment.component.html | 4 +- .../app/_pages/experiment/experiment.component.ts | 36 +++++++++++++++-- 5 files changed, 65 insertions(+), 29 deletions(-) (limited to 'frontend/src/app/_elements/column-table') diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index ad848fd9..d84d9567 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -282,8 +282,8 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): # # Podela na test i trening skupove # - test=paramsExperiment["randomTestSetDistribution"] - randomOrder = paramsExperiment["randomOrder"] + test=paramsModel["randomTestSetDistribution"] + randomOrder = paramsModel["randomOrder"] if(randomOrder): random=123 else: @@ -329,8 +329,8 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): if(problem_type=='multi-klasifikacioni'): #print('multi') - reg=paramsModel['regularisation'][0] - regRate=float(paramsModel['regularisationRate'][0]) + reg=paramsModel['layers'][0]['regularisation'] + regRate=float(paramsModel['layers'][0]['regularisationRate']) if(reg=='l1'): kernelreg=tf.keras.regularizers.l1(regRate) biasreg=tf.keras.regularizers.l1(regRate) @@ -341,12 +341,12 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): activityreg=tf.keras.regularizers.l2(regRate) classifier=tf.keras.Sequential() - classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][0],input_dim=x_train.shape[1], kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#prvi skriveni + definisanje prethodnog-ulaznog + classifier.add(tf.keras.layers.Dense(units=paramsModel['layers'][0]['neurons'], activation=paramsModel['layers'][0]['activationFunction'],input_dim=x_train.shape[1], kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#prvi skriveni + definisanje prethodnog-ulaznog for i in range(paramsModel['hiddenLayers']-1):#ako postoji vise od jednog skrivenog sloja ###Kernel - reg=paramsModel['regularisation'][i+1] - regRate=float(paramsModel['regularisationRate'][i+1]) + reg=paramsModel['layers'][i+1]['regularisation'] + regRate=float(paramsModel['layers'][i+1]['regularisationRate']) if(reg=='l1'): kernelreg=tf.keras.regularizers.l1(regRate) biasreg=tf.keras.regularizers.l1(regRate) @@ -356,7 +356,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): biasreg=tf.keras.regularizers.l2(regRate) activityreg=tf.keras.regularizers.l2(regRate) - classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][i+1],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#i-ti skriveni sloj + classifier.add(tf.keras.layers.Dense(units=paramsModel['layers'][i+1]['neurons'], activation=paramsModel['layers'][i+1]['activationFunction'],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#i-ti skriveni sloj classifier.add(tf.keras.layers.Dense(units=5, activation=paramsModel['outputLayerActivationFunction']))#izlazni sloj @@ -386,8 +386,8 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): elif(problem_type=='binarni-klasifikacioni'): #print('*************************************************************************binarni') - reg=paramsModel['regularisation'][0] - regRate=float(paramsModel['regularisationRate'][0]) + reg=paramsModel['layers'][0]['regularisation'] + regRate=float(paramsModel['layers'][0]['regularisationRate']) if(reg=='l1'): kernelreg=tf.keras.regularizers.l1(regRate) biasreg=tf.keras.regularizers.l1(regRate) @@ -398,12 +398,12 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): activityreg=tf.keras.regularizers.l2(regRate) classifier=tf.keras.Sequential() - classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][0],input_dim=x_train.shape[1],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#prvi skriveni + definisanje prethodnog-ulaznog + classifier.add(tf.keras.layers.Dense(units=paramsModel['layers'][0]['neurons'], activation=paramsModel['layers'][0]['activationFunction'],input_dim=x_train.shape[1],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#prvi skriveni + definisanje prethodnog-ulaznog for i in range(paramsModel['hiddenLayers']-1):#ako postoji vise od jednog skrivenog sloja #print(i) - reg=paramsModel['regularisation'][i+1] - regRate=float(paramsModel['regularisationRate'][i+1]) + reg=paramsModel['layers'][i+1]['regularisation'] + regRate=float(paramsModel['layers'][0]['regularisationRate']) if(reg=='l1'): kernelreg=tf.keras.regularizers.l1(regRate) biasreg=tf.keras.regularizers.l1(regRate) @@ -412,12 +412,19 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): kernelreg=tf.keras.regularizers.l2(regRate) biasreg=tf.keras.regularizers.l2(regRate) activityreg=tf.keras.regularizers.l2(regRate) - classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][i+1],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#i-ti skriveni sloj + classifier.add(tf.keras.layers.Dense(units=paramsModel['layers'][i+1]['neurons'], activation=paramsModel['layers'][i+1]['activationFunction'],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#i-ti skriveni sloj classifier.add(tf.keras.layers.Dense(units=1, activation=paramsModel['outputLayerActivationFunction']))#izlazni sloj classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics =paramsModel['metrics']) + print('AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA') + print(x_train) + print('AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA') + print(y_train) + print('AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA') + + history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=float(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) hist=history.history y_pred=classifier.predict(x_test) @@ -434,8 +441,8 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): return filepath,hist elif(problem_type=='regresioni'): - reg=paramsModel['regularisation'][0] - regRate=float(paramsModel['regularisationRate'][0]) + reg=paramsModel['layers'][0]['regularisation'] + regRate=float(paramsModel['layers'][0]['regularisationRate']) if(reg=='l1'): kernelreg=tf.keras.regularizers.l1(regRate) biasreg=tf.keras.regularizers.l1(regRate) @@ -446,12 +453,12 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): activityreg=tf.keras.regularizers.l2(regRate) classifier=tf.keras.Sequential() - classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][0],input_dim=x_train.shape[1],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#prvi skriveni + definisanje prethodnog-ulaznog + classifier.add(tf.keras.layers.Dense(units=paramsModel['layers'][0]['neurons'], activation=paramsModel['layers'][0]['activationFunction'],input_dim=x_train.shape[1],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#prvi skriveni + definisanje prethodnog-ulaznog for i in range(paramsModel['hiddenLayers']-1):#ako postoji vise od jednog skrivenog sloja #print(i) - reg=paramsModel['regularisation'][i+1] - regRate=float(paramsModel['regularisationRate'][i+1]) + reg=paramsModel['layers'][i+1]['regularisation'] + regRate=float(paramsModel['layers'][i+1]['regularisationRate']) if(reg=='l1'): kernelreg=tf.keras.regularizers.l1(regRate) biasreg=tf.keras.regularizers.l1(regRate) @@ -461,7 +468,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): biasreg=tf.keras.regularizers.l2(regRate) activityreg=tf.keras.regularizers.l2(regRate) - classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][i+1],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#i-ti skriveni sloj + classifier.add(tf.keras.layers.Dense(units=paramsModel['layers'][i+1]['neurons'], activation=paramsModel['layers'][i+1]['activationFunction'],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#i-ti skriveni sloj classifier.add(tf.keras.layers.Dense(units=1),activation=paramsModel['outputLayerActivationFunction']) diff --git a/frontend/src/app/_elements/column-table/column-table.component.ts b/frontend/src/app/_elements/column-table/column-table.component.ts index 13828a2c..b99a3be0 100644 --- a/frontend/src/app/_elements/column-table/column-table.component.ts +++ b/frontend/src/app/_elements/column-table/column-table.component.ts @@ -223,7 +223,7 @@ export class ColumnTableComponent implements AfterViewInit { this.experiment.name = selectedName; //napravi odvojene dugmice za save i update -> za update nece da se otvara dijalog za ime this.experimentService.addExperiment(this.experiment).subscribe((response) => { - this.experiment = response; + this.experiment._id = response._id; this.okPressed.emit(); }); }); diff --git a/frontend/src/app/_elements/folder/folder.component.ts b/frontend/src/app/_elements/folder/folder.component.ts index a99c6a9d..d5a7a85c 100644 --- a/frontend/src/app/_elements/folder/folder.component.ts +++ b/frontend/src/app/_elements/folder/folder.component.ts @@ -53,8 +53,9 @@ export class FolderComponent implements AfterViewInit { if (this.signalRService.hubConnection) { this.signalRService.hubConnection.on("NotifyDataset", (dName: string, dId: string) => { - this.refreshFiles(dId); - + if (this.type == FolderType.Dataset) { + this.refreshFiles(dId); + } }); } else { console.warn("Dataset-Load: No connection!"); diff --git a/frontend/src/app/_pages/experiment/experiment.component.html b/frontend/src/app/_pages/experiment/experiment.component.html index 83c45405..2b32db81 100644 --- a/frontend/src/app/_pages/experiment/experiment.component.html +++ b/frontend/src/app/_pages/experiment/experiment.component.html @@ -37,12 +37,12 @@
- +
- +
diff --git a/frontend/src/app/_pages/experiment/experiment.component.ts b/frontend/src/app/_pages/experiment/experiment.component.ts index 3c8d8651..c4d6063c 100644 --- a/frontend/src/app/_pages/experiment/experiment.component.ts +++ b/frontend/src/app/_pages/experiment/experiment.component.ts @@ -10,6 +10,8 @@ import { ModelsService } from 'src/app/_services/models.service'; import Model from 'src/app/_data/Model'; import Dataset from 'src/app/_data/Dataset'; import { ColumnTableComponent } from 'src/app/_elements/column-table/column-table.component'; +import { SignalRService } from 'src/app/_services/signal-r.service'; +import { MetricViewComponent } from 'src/app/_elements/metric-view/metric-view.component'; @Component({ selector: 'app-experiment', @@ -26,11 +28,11 @@ export class ExperimentComponent implements AfterViewInit { experiment: Experiment; dataset?: Dataset; @ViewChild("folderDataset") folderDataset!: FolderComponent; - @ViewChild("folderModel") folderModel!: FolderComponent; @ViewChild(ColumnTableComponent) columnTable!: ColumnTableComponent; + @ViewChild("folderModel") folderModel!: FolderComponent; + @ViewChild("metricView") metricView!: MetricViewComponent; - - constructor(private experimentsService: ExperimentsService, private modelsService: ModelsService) { + constructor(private experimentsService: ExperimentsService, private modelsService: ModelsService, private signalRService: SignalRService) { this.experiment = new Experiment("exp1"); } @@ -43,7 +45,11 @@ export class ExperimentComponent implements AfterViewInit { } trainModel() { - this.modelsService.trainModel((this.folderModel.selectedFile)._id, this.experiment._id).subscribe(() => { console.log("pocelo treniranje") }) + if (!this.modelToTrain) { + Shared.openDialog('Greška', 'Morate odabrati konfiguraciju neuronske mreže'); + } else { + this.modelsService.trainModel(this.modelToTrain._id, this.experiment._id).subscribe(() => { console.log("pocelo treniranje") }); + } } stepHeight = this.calcStepHeight(); @@ -65,8 +71,23 @@ export class ExperimentComponent implements AfterViewInit { this.stepsContainer.nativeElement.addEventListener('scroll', (event: Event) => { Shared.emitBGScrollEvent(this.stepsContainer.nativeElement.scrollTop); }); + + if (this.signalRService.hubConnection) { + this.signalRService.hubConnection.on("NotifyEpoch", (mName: string, mId: string, stat: string, totalEpochs: number, currentEpoch: number) => { + console.log(this.modelToTrain?._id, mId); + if (this.modelToTrain?._id == mId) { + stat = stat.replace(/'/g, '"'); + //console.log('JSON', this.trainingResult); + this.history.push(JSON.parse(stat)); + this.metricView.update(this.history); + } + }); + + } } + history: any[] = []; + updatePageIfScrolled() { if (this.scrolling) return; const currentPage = Math.round(this.stepsContainer.nativeElement.scrollTop / this.stepHeight) @@ -130,4 +151,11 @@ export class ExperimentComponent implements AfterViewInit { this.columnTable.loadDataset(this.dataset); } + + modelToTrain?: Model; + + setModel(model: FolderFile) { + const m = model; + this.modelToTrain = m; + } } -- cgit v1.2.3 From 2fcd4358c32ea8d62343f137651ef80b15e3d433 Mon Sep 17 00:00:00 2001 From: Sonja Galovic Date: Thu, 5 May 2022 00:03:26 +0200 Subject: ColumnTypes pomeren iz Dataset klase u Experiment klasu. --- backend/api/api/Models/ColumnInfo.cs | 4 +- backend/api/api/Models/Experiment.cs | 2 +- backend/api/api/Services/FillAnEmptyDb.cs | 66 ++++++++++++---------- frontend/src/app/_data/Dataset.ts | 5 -- frontend/src/app/_data/Experiment.ts | 13 +++-- .../column-table/column-table.component.html | 10 ++-- .../column-table/column-table.component.ts | 12 ++-- 7 files changed, 56 insertions(+), 56 deletions(-) (limited to 'frontend/src/app/_elements/column-table') diff --git a/backend/api/api/Models/ColumnInfo.cs b/backend/api/api/Models/ColumnInfo.cs index dcf5171c..46aeadb6 100644 --- a/backend/api/api/Models/ColumnInfo.cs +++ b/backend/api/api/Models/ColumnInfo.cs @@ -4,10 +4,9 @@ { public ColumnInfo() { } - public ColumnInfo(string columnName, string columnType, bool isNumber, int numNulls, float mean, float min, float max, float median, string[] uniqueValues, int[]uniqueValuesCount, float[] uniqueValuesPercent, float q1, float q3) + public ColumnInfo(string columnName, bool isNumber, int numNulls, float mean, float min, float max, float median, string[] uniqueValues, int[]uniqueValuesCount, float[] uniqueValuesPercent, float q1, float q3) { this.columnName = columnName; - this.columnType = columnType; this.isNumber = isNumber; this.numNulls = numNulls; this.mean = mean; @@ -22,7 +21,6 @@ } public string columnName { get; set; } - public string columnType { get; set; } public bool isNumber { get; set; } public int numNulls { get; set; } public float mean { get; set; } diff --git a/backend/api/api/Models/Experiment.cs b/backend/api/api/Models/Experiment.cs index 3af063be..d98e6cfc 100644 --- a/backend/api/api/Models/Experiment.cs +++ b/backend/api/api/Models/Experiment.cs @@ -21,6 +21,6 @@ namespace api.Models public DateTime lastUpdated { get; set; } public NullValues[] nullValuesReplacers { get; set; } public ColumnEncoding[] encodings { get; set; } - + public string[] columnTypes { get; set; } } } diff --git a/backend/api/api/Services/FillAnEmptyDb.cs b/backend/api/api/Services/FillAnEmptyDb.cs index d8c53bab..520f3461 100644 --- a/backend/api/api/Services/FillAnEmptyDb.cs +++ b/backend/api/api/Services/FillAnEmptyDb.cs @@ -66,18 +66,18 @@ namespace api.Services dataset.columnInfo = new[] { - new ColumnInfo( "PassengerId", "columnType", true, 0, 446, 1, 891, 446, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "Survived", "columnType", true, 0, 0.38383838534355164f, 0, 1, 0, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "Pclass", "columnType", true, 0, 2.3086419105529785f, 1, 3, 3, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "Name", "columnType", false, 0, 0, 0, 0, 0, new string[]{"Braund, Mr. Owen Harris", "Boulos, Mr. Hanna", "Frolicher-Stehli, Mr. Maxmillian", "Gilinski, Mr. Eliezer", "Murdlin, Mr. Joseph", "Rintamaki, Mr. Matti", "Stephenson, Mrs. Walter Bertram (Martha Eustis)", "Elsbury, Mr. William James", "Bourke, Miss. Mary", "Chapman, Mr. John Henry"}, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "Sex", "columnType", false, 0, 0, 0, 0, 0, new string[]{ "male", "female" }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "Age", "columnType", true, 177, 29.69911766052246f, 0.41999998688697815f, 80, 28, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "SibSp", "columnType", true, 0, 0.523007869720459f, 0, 8, 0, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "Parch", "columnType", true, 0, 0.3815937042236328f, 0, 6, 0, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "Ticket", "columnType", false, 0, 0, 0, 0, 0, new string[]{ "347082", "CA. 2343", "1601", "3101295", "CA 2144", "347088", "S.O.C. 14879", "382652", "LINE", "PC 17757" }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "Fare", "columnType", true, 0, 32.20420837402344f, 0, 512.3292236328125f, 14.45419979095459f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "Cabin", "columnType", false, 687, 0, 0, 0, 0, new string[]{ "B96 B98", "G6", "C23 C25 C27", "C22 C26", "F33", "F2", "E101", "D", "C78", "C93" }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "Embarked", "columnType", false, 2, 0.3815937042236328f, 0, 6, 0, new string[]{ "S", "C", "Q" }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "PassengerId", true, 0, 446, 1, 891, 446, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "Survived", true, 0, 0.38383838534355164f, 0, 1, 0, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "Pclass", true, 0, 2.3086419105529785f, 1, 3, 3, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "Name", false, 0, 0, 0, 0, 0, new string[]{"Braund, Mr. Owen Harris", "Boulos, Mr. Hanna", "Frolicher-Stehli, Mr. Maxmillian", "Gilinski, Mr. Eliezer", "Murdlin, Mr. Joseph", "Rintamaki, Mr. Matti", "Stephenson, Mrs. Walter Bertram (Martha Eustis)", "Elsbury, Mr. William James", "Bourke, Miss. Mary", "Chapman, Mr. John Henry"}, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "Sex", false, 0, 0, 0, 0, 0, new string[]{ "male", "female" }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "Age", true, 177, 29.69911766052246f, 0.41999998688697815f, 80, 28, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "SibSp", true, 0, 0.523007869720459f, 0, 8, 0, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "Parch", true, 0, 0.3815937042236328f, 0, 6, 0, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "Ticket", false, 0, 0, 0, 0, 0, new string[]{ "347082", "CA. 2343", "1601", "3101295", "CA 2144", "347088", "S.O.C. 14879", "382652", "LINE", "PC 17757" }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "Fare", true, 0, 32.20420837402344f, 0, 512.3292236328125f, 14.45419979095459f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "Cabin", false, 687, 0, 0, 0, 0, new string[]{ "B96 B98", "G6", "C23 C25 C27", "C22 C26", "F33", "F2", "E101", "D", "C78", "C93" }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "Embarked", false, 2, 0.3815937042236328f, 0, 6, 0, new string[]{ "S", "C", "Q" }, new int[] {}, new float[] {}, 0.01f,0.1f ), }; dataset.rowCount = 891; dataset.nullCols = 3; @@ -118,7 +118,7 @@ namespace api.Services experiment.ModelIds = new string[] { }.ToList(); experiment.datasetId = _datasetService.GetDatasetId(dataset.fileId); experiment.uploaderId = "000000000000000000000000"; - experiment.inputColumns = new string[] { "Embarked" }; + experiment.inputColumns = new string[] { "Embarked", "Survived" }; experiment.outputColumn = "Survived"; experiment.dateCreated = DateTime.Now; experiment.lastUpdated = DateTime.Now; @@ -129,6 +129,7 @@ namespace api.Services new ColumnEncoding( "Survived", "label" ), new ColumnEncoding("Embarked", "label" ) }; + experiment.columnTypes = new string[] {"categorical"}; _experimentService.Create(experiment); @@ -179,17 +180,17 @@ namespace api.Services dataset.delimiter = ""; dataset.columnInfo = new[] { - new ColumnInfo( "Unnamed: 0", "columnType", true, 0, 26969.5f, 0, 53939, 26969.5f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "carat", "columnType", true, 0, 0.7979397773742676f, 0.20000000298023224f, 5.010000228881836f, 0.699999988079071f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "cut", "columnType", false, 0, 0, 0, 0, 0, new string[]{ "Ideal", "Premium", "Very Good", "Good", "Fair" }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "color", "columnType", false, 0, 0, 0, 0, 0, new string[]{"G", "E", "F", "H", "D", "I", "I", "J"}, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "clarity", "columnType", false, 0, 0, 0, 0, 0, new string[]{ "SI1", "VS2","SI2", "VS1", "VVS2", "VVS1", "IF", "I1" }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "depth", "columnType", true, 0, 61.74940490722656f, 43, 79, 61.79999923706055f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "table", "columnType", true, 0, 57.457183837890625f, 43, 95, 57, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "price", "columnType", true, 0, 3932.7998046875f, 326, 18823, 2401, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "x", "columnType", true, 0, 5.731157302856445f, 0, 10.739999771118164f, 5.699999809265137f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "y", "columnType", true, 0, 5.73452615737915f, 0, 58.900001525878906f, 5.710000038146973f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "z", "columnType", true, 0, 3.538733720779419f, 0, 31.799999237060547f, 3.5299999713897705f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ) + new ColumnInfo( "Unnamed: 0", true, 0, 26969.5f, 0, 53939, 26969.5f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "carat", true, 0, 0.7979397773742676f, 0.20000000298023224f, 5.010000228881836f, 0.699999988079071f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "cut", false, 0, 0, 0, 0, 0, new string[]{ "Ideal", "Premium", "Very Good", "Good", "Fair" }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "color", false, 0, 0, 0, 0, 0, new string[]{"G", "E", "F", "H", "D", "I", "I", "J"}, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "clarity", false, 0, 0, 0, 0, 0, new string[]{ "SI1", "VS2","SI2", "VS1", "VVS2", "VVS1", "IF", "I1" }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "depth", true, 0, 61.74940490722656f, 43, 79, 61.79999923706055f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "table", true, 0, 57.457183837890625f, 43, 95, 57, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "price", true, 0, 3932.7998046875f, 326, 18823, 2401, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "x", true, 0, 5.731157302856445f, 0, 10.739999771118164f, 5.699999809265137f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "y", true, 0, 5.73452615737915f, 0, 58.900001525878906f, 5.710000038146973f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "z", true, 0, 3.538733720779419f, 0, 31.799999237060547f, 3.5299999713897705f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ) }; dataset.rowCount = 53940; dataset.nullCols = 0; @@ -231,7 +232,7 @@ namespace api.Services experiment.ModelIds = new string[] { }.ToList(); experiment.datasetId = _datasetService.GetDatasetId(dataset.fileId); experiment.uploaderId = "000000000000000000000000"; - experiment.inputColumns = new string[] { "Unnamed: 0", "carat", "cut", "color", "clarity", "depth", "table", "x", "y", "z" }; + experiment.inputColumns = new string[] { "Unnamed: 0", "carat", "cut", "color", "clarity", "depth", "table", "x", "y", "z", "price" }; experiment.outputColumn = "price"; experiment.dateCreated = DateTime.Now; experiment.lastUpdated = DateTime.Now; @@ -251,6 +252,7 @@ namespace api.Services new ColumnEncoding( "y", "label" ), new ColumnEncoding( "z", "label" ) }; + experiment.columnTypes = new string[] { "categorical", "numerical", "numerical", "categorical", "categorical", "categorical", "numerical", "numerical", "numerical", "numerical", "numerical" }; _experimentService.Create(experiment); /* @@ -295,11 +297,11 @@ namespace api.Services dataset.delimiter = ""; dataset.columnInfo = new[] { - new ColumnInfo( "sepal_length", "columnType", true, 0, 5.8433332443237305f, 4.300000190734863f, 7.900000095367432f, 5.800000190734863f, new string[]{ }, new int[] {}, new float[] {}, 0.01f, 0.1f ), - new ColumnInfo( "sepal_width", "columnType", true, 0, 3.053999900817871f, 2, 4.400000095367432f, 3, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "petal_length", "columnType", true, 0, 3.758666753768921f, 1, 6.900000095367432f, 4.349999904632568f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "petal_width", "columnType", true, 0, 1.1986666917800903f, 0.10000000149011612f, 2.5f, 1.2999999523162842f, new string[]{}, new int[] {}, new float[] {}, 0.01f,0.1f ), - new ColumnInfo( "class", "columnType", false, 0, 0, 0, 0, 0, new string[]{ "Iris-setosa", "Iris-versicolor", "Iris-virginica" }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "sepal_length", true, 0, 5.8433332443237305f, 4.300000190734863f, 7.900000095367432f, 5.800000190734863f, new string[]{ }, new int[] {}, new float[] {}, 0.01f, 0.1f ), + new ColumnInfo( "sepal_width", true, 0, 3.053999900817871f, 2, 4.400000095367432f, 3, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "petal_length", true, 0, 3.758666753768921f, 1, 6.900000095367432f, 4.349999904632568f, new string[]{ }, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "petal_width", true, 0, 1.1986666917800903f, 0.10000000149011612f, 2.5f, 1.2999999523162842f, new string[]{}, new int[] {}, new float[] {}, 0.01f,0.1f ), + new ColumnInfo( "class", false, 0, 0, 0, 0, 0, new string[]{ "Iris-setosa", "Iris-versicolor", "Iris-virginica" }, new int[] {}, new float[] {}, 0.01f,0.1f ), }; dataset.nullCols = 150; dataset.nullRows = 0; @@ -339,7 +341,7 @@ namespace api.Services experiment.ModelIds = new string[] { }.ToList(); experiment.datasetId = _datasetService.GetDatasetId(dataset.fileId); experiment.uploaderId = "000000000000000000000000"; - experiment.inputColumns = new string[] { "sepal_length", "sepal_width", "petal_length", "petal_width" }; + experiment.inputColumns = new string[] { "sepal_length", "sepal_width", "petal_length", "petal_width", "class" }; experiment.outputColumn = "class"; experiment.dateCreated = DateTime.Now; experiment.lastUpdated = DateTime.Now; @@ -353,6 +355,8 @@ namespace api.Services new ColumnEncoding( "petal_width", "label" ), new ColumnEncoding( "class", "label" ) }; + experiment.columnTypes = new string[] { "categorical", "numerical", "numerical", "numerical", "categorical" }; + _experimentService.Create(experiment); /* diff --git a/frontend/src/app/_data/Dataset.ts b/frontend/src/app/_data/Dataset.ts index ca1a2a5e..4ff0a471 100644 --- a/frontend/src/app/_data/Dataset.ts +++ b/frontend/src/app/_data/Dataset.ts @@ -27,7 +27,6 @@ export default class Dataset extends FolderFile { export class ColumnInfo { constructor( public columnName: string = '', - public columnType: ColumnType, public isNumber: boolean = false, public numNulls: number = 0, public uniqueValues?: string[], @@ -48,7 +47,3 @@ export class ColumnInfo { } -export enum ColumnType { - categorical = "Kategorijski", - numerical = "Numerički" -} \ No newline at end of file diff --git a/frontend/src/app/_data/Experiment.ts b/frontend/src/app/_data/Experiment.ts index 05336495..828431cc 100644 --- a/frontend/src/app/_data/Experiment.ts +++ b/frontend/src/app/_data/Experiment.ts @@ -15,9 +15,7 @@ export default class Experiment { public dateCreated: Date = new Date(), public lastUpdated: Date = new Date(), public modelIds: string[] = [], - - - + public columnTypes: ColumnType[] = [], public encodings: ColumnEncoding[] = []//[{columnName: "", columnEncoding: Encoding.Label}] ) { } @@ -47,11 +45,11 @@ export class NullValReplacer { export enum Encoding { Label = 'label', OneHot = 'onehot', - Ordinal = 'ordinal', + /*Ordinal = 'ordinal', Hashing = 'hashing', Binary = 'binary', BaseN = 'baseN' - /* + BackwardDifference = 'backward difference', CatBoost = 'cat boost', Count = 'count', @@ -73,4 +71,9 @@ export class ColumnEncoding { public columnName: string, public encoding: Encoding ) { } +} + +export enum ColumnType { + categorical = "categorical", + numerical = "numerical" } \ No newline at end of file diff --git a/frontend/src/app/_elements/column-table/column-table.component.html b/frontend/src/app/_elements/column-table/column-table.component.html index 09ddffc6..efc093d2 100644 --- a/frontend/src/app/_elements/column-table/column-table.component.html +++ b/frontend/src/app/_elements/column-table/column-table.component.html @@ -103,7 +103,7 @@

Kategorijski

- + Kategorijski Numerički @@ -113,14 +113,14 @@ Grafik - - + + Statistika - + Mean: {{colInfo.mean}}
Median: {{colInfo.median}}
Min: {{colInfo.min}}
@@ -128,7 +128,7 @@ Q1: {{colInfo.q1}}
Q3: {{colInfo.q3}}
 -
+
({{(colInfo.uniqueValuesPercent[i] * 100).toFixed(2)}}%) {{uniqueValue}}
 diff --git a/frontend/src/app/_elements/column-table/column-table.component.ts b/frontend/src/app/_elements/column-table/column-table.component.ts index b99a3be0..c200e674 100644 --- a/frontend/src/app/_elements/column-table/column-table.component.ts +++ b/frontend/src/app/_elements/column-table/column-table.component.ts @@ -1,6 +1,6 @@ import { AfterViewInit, Component, ElementRef, EventEmitter, Input, OnInit, Output, ViewChildren } from '@angular/core'; -import Dataset, { ColumnType } from 'src/app/_data/Dataset'; -import Experiment, { ColumnEncoding, Encoding, NullValReplacer, NullValueOptions } from 'src/app/_data/Experiment'; +import Dataset from 'src/app/_data/Dataset'; +import Experiment, { ColumnEncoding, Encoding, ColumnType, NullValueOptions } from 'src/app/_data/Experiment'; import { DatasetsService } from 'src/app/_services/datasets.service'; import { EncodingDialogComponent } from 'src/app/_modals/encoding-dialog/encoding-dialog.component'; import { MatDialog } from '@angular/material/dialog'; @@ -75,7 +75,7 @@ export class ColumnTableComponent implements AfterViewInit { setColumnTypeInitial() { if (this.dataset != undefined) { for (let i = 0; i < this.dataset.columnInfo.length; i++) { - this.dataset.columnInfo[i].columnType = (this.dataset.columnInfo[i].isNumber) ? ColumnType.numerical : ColumnType.categorical; + this.experiment.columnTypes[i] = (this.dataset.columnInfo[i].isNumber) ? ColumnType.numerical : ColumnType.categorical; } } } @@ -140,12 +140,12 @@ export class ColumnTableComponent implements AfterViewInit { changeOutputColumn(columnName: string) { if (this.experiment != undefined && this.dataset != undefined) { - let column = this.dataset.columnInfo.filter(x => x.columnName == this.experiment!.outputColumn)[0]; - if (column.columnType == ColumnType.numerical) { + let i = this.dataset.columnInfo.findIndex(x => x.columnName == this.experiment!.outputColumn); + if (this.experiment.columnTypes[i] == ColumnType.numerical) { this.experiment.type = ProblemType.Regression; } else { - if (column.uniqueValues!.length == 2) + if (this.dataset.columnInfo[i].uniqueValues!.length == 2) this.experiment.type = ProblemType.BinaryClassification; else this.experiment.type = ProblemType.MultiClassification; -- cgit v1.2.3