import { Component, OnInit ,Input, ViewChild, Output, EventEmitter} from '@angular/core';
import {FormControl, Validators} from '@angular/forms';
import Shared from 'src/app/Shared';
import Experiment from 'src/app/_data/Experiment';
import Model, {Layer, ActivationFunction, LossFunction, LossFunctionBinaryClassification, LossFunctionMultiClassification, LossFunctionRegression, Metrics, MetricsBinaryClassification, MetricsMultiClassification, MetricsRegression, NullValueOptions, Optimizer, ProblemType } from 'src/app/_data/Model';
import { GraphComponent } from '../graph/graph.component';
import {FormGroupDirective, NgForm} from '@angular/forms';
import {ErrorStateMatcher} from '@angular/material/core';
@Component({
  selector: 'app-form-model',
  templateUrl: './form-model.component.html',
  styleUrls: ['./form-model.component.css']
})
export class FormModelComponent implements OnInit {
  @ViewChild(GraphComponent) graph!: GraphComponent;
  @Input() forExperiment?: Experiment;
  @Output() selectedModelChangeEvent = new EventEmitter<Model>();

  constructor() { 
  this.newModel.epochs=1;
  this.newModel.batchSize=1;
}
  
  ngOnInit(): void {
  }
  selectFormControl = new FormControl('', Validators.required);
  nameFormControl = new FormControl('', [Validators.required, Validators.email]);
  selectTypeFormControl=new FormControl('', Validators.required);
  selectOptFormControl=new FormControl('', Validators.required);
  selectLFFormControl=new FormControl('', Validators.required);
  selectLRFormControl=new FormControl('', Validators.required);
  selectEpochFormControl=new FormControl('', Validators.required);
  selectAFFormControl=new FormControl('', Validators.required);
  selectBSFormControl=new FormControl('', Validators.required);
  selectActivationFormControl = new FormControl('', Validators.required);
  selectRegularisationFormControl = new FormControl('', Validators.required);
  selectRRateFormControl = new FormControl('', Validators.required);
  newModel: Model = new Model();
  myModels?: Model[];
  selectedModel?: Model;

  ProblemType = ProblemType;
  ActivationFunction = ActivationFunction;
  metrics: any = Metrics;
  LossFunction = LossFunction;
  Optimizer = Optimizer;
  Object = Object;
  document = document;
  shared = Shared;

  term: string = "";
  selectedMetrics = [];
  lossFunction: any = LossFunction;

  showMyModels: boolean = true;
  
  hiddenLayers=[];
  
 


  updateGraph() {
    this.graph.update();
  }
  removeLayer(){
    if(this.newModel.hiddenLayers>1)
    {
      this.newModel.layers.splice(this.newModel.layers.length-1,1);
      this.newModel.hiddenLayers-=1;
      this.updateGraph();
    }
  }
  addLayer(){
    if(this.newModel.hiddenLayers<12)
    {
      this.newModel.layers.push(new Layer(this.newModel.layers.length));

      this.newModel.hiddenLayers+=1;
      this.updateGraph();
    }
  
  }
  removeBatch(){
    if(this.newModel.batchSize>1)
    {
      this.newModel.batchSize=this.newModel.batchSize/2;
    }
    else
    {
      this.newModel.batchSize=this.newModel.batchSize;
    }
    
  }
  addBatch(){
    if(this.newModel.batchSize<600)
    {
      this.newModel.batchSize=this.newModel.batchSize*2;
    }
    else
    {
      this.newModel.batchSize=this.newModel.batchSize;
      
    }
  }
  removeEpoch(){
    if(this.newModel.epochs>1)
    {
      this.newModel.epochs=this.newModel.epochs-1;
    }
    else
    {
      this.newModel.epochs=this.newModel.epochs;
    }
    
  }
  addEpoch(){
    if(this.newModel.epochs<100)
    {
      this.newModel.epochs=this.newModel.epochs+1;
    }
    else
    {
      this.newModel.epochs=this.newModel.epochs;
      
    }
  }
  /*
  setNeurons()
  {
    for(let i=0;i<this.newModel.hiddenLayers;i++){
      this.newModel.hiddenLayerNeurons[i]=1;
    }
  }*/
  numSequence(n: number): Array<number> {
    return Array(n);
  }
  
  removeNeuron(index:number){
    if(this.newModel.layers[index].neurons>1)
    {
      this.newModel.layers[index].neurons-=1;
      this.updateGraph();
    }
  }
  addNeuron(index:number){
    if(this.newModel.layers[index].neurons<100)
    {
      this.newModel.layers[index].neurons+=1;
      this.updateGraph();
    }
  }
}