ColumnTypes pomeren iz Dataset klase u Experiment klasu.

7 files changed, 56 insertions, 56 deletions

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 @@
                             <td *ngFor="let colInfo of dataset.columnInfo; let i = index" class="pad-fix" [ngClass]="{'text-disabled' : !columnsChecked[i]}">
                                 <p class="verticalAlign text-left" style="font-size:13px;" *ngIf="!colInfo.isNumber">Kategorijski</p>
                                 <mat-form-field *ngIf="colInfo.isNumber">
-                                    <mat-select matNativeControl [(value)]="colInfo.columnType" [disabled]="!columnsChecked[i]" (selectionChange)="columnTypeChanged(colInfo.columnName);">
+                                    <mat-select matNativeControl [(value)]="this.experiment.columnTypes[i]" [disabled]="!columnsChecked[i]" (selectionChange)="columnTypeChanged(colInfo.columnName);">
                                         <mat-option [value]="ColumnType.categorical">Kategorijski</mat-option>
                                         <mat-option [value]="ColumnType.numerical">Numerički</mat-option>
                                     </mat-select>
@@ -113,14 +113,14 @@
                         <tr class="graphics-row">
                             <th class="no-pad">Grafik</th>
                             <td class="no-pad" *ngFor="let colInfo of dataset.columnInfo; let i = index" [ngClass]="{'graphic-class' : !columnsChecked[i]}">
-                                <app-box-plot *ngIf="colInfo.columnType == ColumnType.numerical" [width]="150" [height]="150"></app-box-plot>
-                                <app-pie-chart *ngIf="colInfo.columnType == ColumnType.categorical" [width]="150" [height]="150"></app-pie-chart>
+                                <app-box-plot *ngIf="this.experiment.columnTypes[i] == ColumnType.numerical" [width]="150" [height]="150"></app-box-plot>
+                                <app-pie-chart *ngIf="this.experiment.columnTypes[i] == ColumnType.categorical" [width]="150" [height]="150"></app-pie-chart>
                             </td>
                         </tr>
                         <tr>
                             <th class="border-bottom">Statistika</th>
                             <td *ngFor="let colInfo of dataset.columnInfo; let i = index" [ngClass]="{'text-disabled' : !columnsChecked[i]}" class="text-left">
-                                <span *ngIf="colInfo.columnType == ColumnType.numerical">
+                                <span *ngIf="this.experiment.columnTypes[i] == ColumnType.numerical">
                                 Mean: {{colInfo.mean}}<br>
                                 Median: {{colInfo.median}}<br>
                                 Min: {{colInfo.min}}<br>
@@ -128,7 +128,7 @@
                                 Q1: {{colInfo.q1}}<br>
                                 Q3: {{colInfo.q3}}<br>
                             </span>
-                                <div class="text-overflow" *ngIf="colInfo.columnType == ColumnType.categorical && colInfo.uniqueValuesPercent">
+                                <div class="text-overflow" *ngIf="this.experiment.columnTypes[i] == ColumnType.categorical && colInfo.uniqueValuesPercent">
                                     <span *ngFor="let uniqueValue of colInfo.uniqueValues | slice:0:6; let i = index">
                                     ({{(colInfo.uniqueValuesPercent[i] * 100).toFixed(2)}}%) {{uniqueValue}}<br>
                                 </span>
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;