From b25af94d6df8854129e99f77638e4013a9c57086 Mon Sep 17 00:00:00 2001
From: Danijel Anđelković <adanijel99@gmail.com>
Date: Wed, 20 Apr 2022 00:04:19 +0200
Subject: Povezao metric view komponentu, chart, sa signalR tako da se
 iscrtavaju metrike modela kako se trenira. Ispravio neke bug-ove.

---
 frontend/src/app/training/training.component.html |  5 ++--
 frontend/src/app/training/training.component.ts   | 35 +++++++++++++++--------
 2 files changed, 25 insertions(+), 15 deletions(-)

(limited to 'frontend/src/app/training')

diff --git a/frontend/src/app/training/training.component.html b/frontend/src/app/training/training.component.html
index 2bee3b12..fa80089e 100644
--- a/frontend/src/app/training/training.component.html
+++ b/frontend/src/app/training/training.component.html
@@ -33,9 +33,8 @@
             <h2 class="mt-5">Rezultati treniranja</h2>
             <div class="m-3" *ngIf="trainingResult">
                 <h2 class="my-2">Rezultati treniranja:</h2>
-                <p>
-                    {{trainingResult}}
-                </p>
+                {{trainingResult}}
+                <app-metric-view *ngIf="trainingResult" [metrics]="trainingResult"></app-metric-view>
             </div>
         </div>
 
diff --git a/frontend/src/app/training/training.component.ts b/frontend/src/app/training/training.component.ts
index 4c38f166..6b5405cb 100644
--- a/frontend/src/app/training/training.component.ts
+++ b/frontend/src/app/training/training.component.ts
@@ -3,6 +3,7 @@ import { ActivatedRoute } from '@angular/router';
 import Shared from '../Shared';
 import Experiment from '../_data/Experiment';
 import Model, { ProblemType } from '../_data/Model';
+import { MetricViewComponent } from '../_elements/metric-view/metric-view.component';
 import { ModelLoadComponent } from '../_elements/model-load/model-load.component';
 import { AuthService } from '../_services/auth.service';
 import { ExperimentsService } from '../_services/experiments.service';
@@ -17,6 +18,7 @@ import { SignalRService } from '../_services/signal-r.service';
 export class TrainingComponent implements OnInit {
 
   @ViewChild(ModelLoadComponent) modelLoadComponent?: ModelLoadComponent;
+  @ViewChild(MetricViewComponent) metricViewComponent!: MetricViewComponent;
 
   myExperiments?: Experiment[];
   selectedExperiment?: Experiment;
@@ -24,16 +26,11 @@ export class TrainingComponent implements OnInit {
 
   trainingResult: any;
 
+  history: any[] = [];
+
   term: string = "";
 
   constructor(private modelsService: ModelsService, private route: ActivatedRoute, private experimentsService: ExperimentsService, private authService: AuthService, private signalRService: SignalRService) {
-    if (this.signalRService.hubConnection) {
-      this.signalRService.hubConnection.on("NotifyEpoch", (mName: string, mId: string, stat: string, totalEpochs: number, currentEpoch: number) => {
-        if (this.selectedModel?._id == mId) {
-          this.trainingResult = stat;
-        }
-      });
-    }
   }
 
   ngOnInit(): void {
@@ -45,17 +42,32 @@ export class TrainingComponent implements OnInit {
       this.authService.loggedInEvent.subscribe(_ => {
         this.fetchExperiments(experimentId);
 
-        this.signalRService.startConnection()
+        this.signalRService.startConnection();
       });
+
+      console.log(this.signalRService.hubConnection);
+      if (this.signalRService.hubConnection) {
+        this.signalRService.hubConnection.on("NotifyEpoch", (mName: string, mId: string, stat: string, totalEpochs: number, currentEpoch: number) => {
+          console.log(this.selectedModel?._id, mId);
+          if (this.selectedModel?._id == mId) {
+            stat = stat.replace(/'/g, '"');
+            this.trainingResult = JSON.parse(stat);
+            //console.log('JSON', this.trainingResult);
+            this.history.push(this.trainingResult);
+            this.metricViewComponent.update(this.history);
+          }
+        });
+      }
     });
   }
 
   fetchExperiments(andSelectWithId: string | null = '') {
     this.experimentsService.getMyExperiments().subscribe((experiments) => {
-      this.myExperiments = experiments;
+      this.myExperiments = experiments.reverse();
 
       this.selectedExperiment = this.myExperiments.filter(x => x._id == andSelectWithId)[0];
-      console.log("selektovan exp u training comp: ", this.selectedExperiment);
+      if (this.modelLoadComponent)
+        this.modelLoadComponent.newModel.type = this.selectedExperiment.type;
     });
   }
 
@@ -82,8 +94,7 @@ export class TrainingComponent implements OnInit {
     }
     this.modelsService.trainModel(this.selectedModel._id, this.selectedExperiment._id).subscribe((response: any) => {
       //console.log('Train model complete!', response);
-      Shared.openDialog("Obaveštenje", "Treniranje modela je uspešno završeno!");
-      this.trainingResult = response;
+      Shared.openDialog("Obaveštenje", "Treniranje modela je počelo!");
     });
   }
 }
-- 
cgit v1.2.3


From 61682b01751369307d7777f55be98d25d7fc10a9 Mon Sep 17 00:00:00 2001
From: TAMARA JERINIC <tamara.jerinic@gmail.com>
Date: Wed, 20 Apr 2022 01:04:11 +0200
Subject: Onemogućeno brisanje izlazne kolone koja ima null vrednosti ukoliko
 korisnik zatraži brisanje svih kolona sa null vrednostima.
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 backend/microservice/api/controller.py            | 15 +++++++-------
 backend/microservice/api/newmlservice.py          | 24 ++++++++++++-----------
 frontend/src/app/training/training.component.html |  1 -
 3 files changed, 21 insertions(+), 19 deletions(-)

(limited to 'frontend/src/app/training')

diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py
index 9b83b8e7..f870b2b1 100644
--- a/backend/microservice/api/controller.py
+++ b/backend/microservice/api/controller.py
@@ -53,7 +53,7 @@ class train_callback(tf.keras.callbacks.Callback):
 
 @app.route('/train', methods = ['POST'])
 def train():
-    print("******************************TRAIN*************************************************")
+    #print("******************************TRAIN*************************************************")
     
     f = request.files.get("file")
     data = pd.read_csv(f)
@@ -88,10 +88,11 @@ def train():
         "h5FileId" : fileId,
         "metrics" : m
     }
-    print(predictor)
+    #print(predictor)
+    #print('\n')
     url = config.api_url + "/Predictor/add"
     r = requests.post(url, json=predictor).text
-    print(r)
+    #print(r)
     return r
 
 @app.route('/predict', methods = ['POST'])
@@ -100,13 +101,13 @@ def predict():
     model = tf.keras.models.load_model(h5)
     paramsExperiment = json.loads(request.form["experiment"])
     paramsPredictor = json.loads(request.form["predictor"])
-    print("********************************model loaded*******************************")
+    #print("********************************model loaded*******************************")
     result = newmlservice.predict(paramsExperiment, paramsPredictor, model)
     return result
 
 @app.route('/preprocess',methods=['POST'])
 def returnColumnsInfo():
-    print("********************************PREPROCESS*******************************")
+    #print("********************************PREPROCESS*******************************")
     dataset = json.loads(request.form["dataset"])
     file = request.files.get("file")
     data=pd.read_csv(file)
@@ -126,8 +127,8 @@ def returnColumnsInfo():
     dataset["colCount"] = preprocess["colCount"]
     dataset["rowCount"] = preprocess["rowCount"]
     dataset["isPreProcess"] = True
-    print(dataset)
+    #print(dataset)
     return jsonify(dataset)
     
-print("App loaded.")
+#print("App loaded.")
 app.run()
\ No newline at end of file
diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py
index 6cbda69c..6e65c876 100644
--- a/backend/microservice/api/newmlservice.py
+++ b/backend/microservice/api/newmlservice.py
@@ -129,7 +129,8 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
     ###NULL
     null_value_options = paramsExperiment["nullValues"]
     null_values_replacers = paramsExperiment["nullValuesReplacers"]
-
+    kategorijskekolone=data.select_dtypes(include=['object']).columns.copy()
+    #print(kategorijskekolone)
     if(null_value_options=='replace'):
         #print("replace null") #
         dict=null_values_replacers
@@ -143,11 +144,18 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
                     val = np.int64(val)
                 elif(data[col].dtype == 'float64'):
                     val = np.float64(val)
-                #elif(data[col].dtype == 'object'):
                 data[col]=data[col].fillna(val)
     elif(null_value_options=='delete_rows'):
         data=data.dropna()
     elif(null_value_options=='delete_columns'):
+        if(data[output_column].isnull().sum()>0):
+            if(output_column in kategorijskekolone):
+                replace=data[output_column].value_counts().index[0]
+                #print(replace)
+            else:
+                replace=data[output_column].mean()
+            data[output_column]=data[output_column].fillna(replace)
+            #print(data[output_column].isnull().sum())
         data=data.dropna(axis=1)
     #print(data.shape)
     
@@ -175,7 +183,8 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
     encodings=paramsExperiment["encodings"]
     datafront=dataset.copy()
     svekolone=datafront.columns
-    kategorijskekolone=datafront.select_dtypes(include=['object']).columns
+
+    
     for kolonaEncoding in encodings:
         
         kolona = kolonaEncoding["columnName"]
@@ -237,13 +246,6 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
     #print(x_columns)
     x = data[x_columns].values
     y = data[output_column].values
-    print('-----------------dfghfhgfhfg-------------------------------')
-    print(x)
-    print('-----------------dfghfhgfhfg-------------------------------')
-    print(y)
-    print('-----------------dfghfhgfhfg-------------------------------')
-    print(output_column)
-    print('-----------------dfghfhgfhfg-------------------------------')
 
     #
     # Podela na test i trening skupove
@@ -360,7 +362,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
             classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][i+1]))#i-ti skriveni sloj
         classifier.add(tf.keras.layers.Dense(units=1, activation=paramsModel['outputLayerActivationFunction']))#izlazni sloj
 
-        classifier.compile(loss =paramsModel["lossFunction"] , optimizer = paramsModel['optimizer'] , metrics =['accuracy','mae','mse'])
+        classifier.compile(loss =paramsModel["lossFunction"] , optimizer = paramsModel['optimizer'] , metrics =['accuracy'])
 
         history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=paramsModel['batchSize'],callbacks=callback(x_test, y_test,paramsModel['_id']))
         hist=history.history
diff --git a/frontend/src/app/training/training.component.html b/frontend/src/app/training/training.component.html
index fa80089e..66f77c37 100644
--- a/frontend/src/app/training/training.component.html
+++ b/frontend/src/app/training/training.component.html
@@ -33,7 +33,6 @@
             <h2 class="mt-5">Rezultati treniranja</h2>
             <div class="m-3" *ngIf="trainingResult">
                 <h2 class="my-2">Rezultati treniranja:</h2>
-                {{trainingResult}}
                 <app-metric-view *ngIf="trainingResult" [metrics]="trainingResult"></app-metric-view>
             </div>
         </div>
-- 
cgit v1.2.3