SiLeBAT/FSK-Lab

/*
 * RAKIP Generic model
 * TODO
 *
 * OpenAPI spec version: 1.0.4
 * 
 *
 * NOTE: This class is auto generated by the swagger code generator program.
 * https://github.com/swagger-api/swagger-codegen.git
 * Do not edit the class manually.
 */


package de.bund.bfr.metadata.swagger;

import java.util.Objects;
import com.google.gson.TypeAdapter;
import com.google.gson.annotations.JsonAdapter;
import com.google.gson.annotations.SerializedName;
import com.google.gson.stream.JsonReader;
import com.google.gson.stream.JsonWriter;
import de.bund.bfr.metadata.swagger.ModelEquation;
import de.bund.bfr.metadata.swagger.Parameter;
import de.bund.bfr.metadata.swagger.QualityMeasures;
import io.swagger.annotations.ApiModel;
import io.swagger.annotations.ApiModelProperty;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

/**
 * PredictiveModelModelMath
 */
@javax.annotation.Generated(value = "io.swagger.codegen.languages.JavaClientCodegen", date = "2019-07-02T16:22:48.194+02:00")
public class PredictiveModelModelMath {
  @SerializedName("parameter")
  private List<Parameter> parameter = new ArrayList<Parameter>();

  @SerializedName("qualityMeasures")
  private List<QualityMeasures> qualityMeasures = null;

  @SerializedName("modelEquation")
  private List<ModelEquation> modelEquation = null;

  @SerializedName("fittingProcedure")
  private String fittingProcedure = null;

  @SerializedName("event")
  private List<String> event = null;

  public PredictiveModelModelMath parameter(List<Parameter> parameter) {
    this.parameter = parameter;
    return this;
  }

  public PredictiveModelModelMath addParameterItem(Parameter parameterItem) {
    this.parameter.add(parameterItem);
    return this;
  }

   /**
   * Get parameter
   * @return parameter
  **/
  @ApiModelProperty(required = true, value = "")
  public List<Parameter> getParameter() {
    return parameter;
  }

  public void setParameter(List<Parameter> parameter) {
    this.parameter = parameter;
  }

  public PredictiveModelModelMath qualityMeasures(List<QualityMeasures> qualityMeasures) {
    this.qualityMeasures = qualityMeasures;
    return this;
  }

  public PredictiveModelModelMath addQualityMeasuresItem(QualityMeasures qualityMeasuresItem) {
    if (this.qualityMeasures == null) {
      this.qualityMeasures = new ArrayList<QualityMeasures>();
    }
    this.qualityMeasures.add(qualityMeasuresItem);
    return this;
  }

   /**
   * Get qualityMeasures
   * @return qualityMeasures
  **/
  @ApiModelProperty(value = "")
  public List<QualityMeasures> getQualityMeasures() {
    return qualityMeasures;
  }

  public void setQualityMeasures(List<QualityMeasures> qualityMeasures) {
    this.qualityMeasures = qualityMeasures;
  }

  public PredictiveModelModelMath modelEquation(List<ModelEquation> modelEquation) {
    this.modelEquation = modelEquation;
    return this;
  }

  public PredictiveModelModelMath addModelEquationItem(ModelEquation modelEquationItem) {
    if (this.modelEquation == null) {
      this.modelEquation = new ArrayList<ModelEquation>();
    }
    this.modelEquation.add(modelEquationItem);
    return this;
  }

   /**
   * Get modelEquation
   * @return modelEquation
  **/
  @ApiModelProperty(value = "")
  public List<ModelEquation> getModelEquation() {
    return modelEquation;
  }

  public void setModelEquation(List<ModelEquation> modelEquation) {
    this.modelEquation = modelEquation;
  }

  public PredictiveModelModelMath fittingProcedure(String fittingProcedure) {
    this.fittingProcedure = fittingProcedure;
    return this;
  }

   /**
   * Get fittingProcedure
   * @return fittingProcedure
  **/
  @ApiModelProperty(value = "")
  public String getFittingProcedure() {
    return fittingProcedure;
  }

  public void setFittingProcedure(String fittingProcedure) {
    this.fittingProcedure = fittingProcedure;
  }

  public PredictiveModelModelMath event(List<String> event) {
    this.event = event;
    return this;
  }

  public PredictiveModelModelMath addEventItem(String eventItem) {
    if (this.event == null) {
      this.event = new ArrayList<String>();
    }
    this.event.add(eventItem);
    return this;
  }

   /**
   * Get event
   * @return event
  **/
  @ApiModelProperty(value = "")
  public List<String> getEvent() {
    return event;
  }

  public void setEvent(List<String> event) {
    this.event = event;
  }


  @Override
  public boolean equals(java.lang.Object o) {
    if (this == o) {
      return true;
    }
    if (o == null || getClass() != o.getClass()) {
      return false;
    }
    PredictiveModelModelMath predictiveModelModelMath = (PredictiveModelModelMath) o;
    return Objects.equals(this.parameter, predictiveModelModelMath.parameter) &&
        Objects.equals(this.qualityMeasures, predictiveModelModelMath.qualityMeasures) &&
        Objects.equals(this.modelEquation, predictiveModelModelMath.modelEquation) &&
        Objects.equals(this.fittingProcedure, predictiveModelModelMath.fittingProcedure) &&
        Objects.equals(this.event, predictiveModelModelMath.event);
  }

  @Override
  public int hashCode() {
    return Objects.hash(parameter, qualityMeasures, modelEquation, fittingProcedure, event);
  }


  @Override
  public String toString() {
    StringBuilder sb = new StringBuilder();
    sb.append("class PredictiveModelModelMath {\n");
    
    sb.append("    parameter: ").append(toIndentedString(parameter)).append("\n");
    sb.append("    qualityMeasures: ").append(toIndentedString(qualityMeasures)).append("\n");
    sb.append("    modelEquation: ").append(toIndentedString(modelEquation)).append("\n");
    sb.append("    fittingProcedure: ").append(toIndentedString(fittingProcedure)).append("\n");
    sb.append("    event: ").append(toIndentedString(event)).append("\n");
    sb.append("}");
    return sb.toString();
  }

  /**
   * Convert the given object to string with each line indented by 4 spaces
   * (except the first line).
   */
  private String toIndentedString(java.lang.Object o) {
    if (o == null) {
      return "null";
    }
    return o.toString().replace("\n", "\n    ");
  }

}