io.github.ericmedvet.jgea.experimenter.builders.NumericalDatasets Maven / Gradle / Ivy

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/*-
 * ========================LICENSE_START=================================
 * jgea-experimenter
 * %%
 * Copyright (C) 2018 - 2023 Eric Medvet
 * %%
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =========================LICENSE_END==================================
 */
package io.github.ericmedvet.jgea.experimenter.builders;

import io.github.ericmedvet.jgea.problem.regression.LazyNumericalDataset;
import io.github.ericmedvet.jgea.problem.regression.ListNumericalDataset;
import io.github.ericmedvet.jgea.problem.regression.NumericalDataset;
import io.github.ericmedvet.jgea.problem.regression.univariate.UnivariateRegressionFitness;
import io.github.ericmedvet.jgea.problem.regression.univariate.UnivariateRegressionProblem;
import io.github.ericmedvet.jnb.core.Param;
import java.io.IOException;
import java.util.List;
import java.util.function.Supplier;

public class NumericalDatasets {
  private NumericalDatasets() {}

  @SuppressWarnings("unused")
  public static Supplier empty(
      @Param("xVars") List xVarNames, @Param("yVars") List yVarNames) {
    return () -> new ListNumericalDataset(List.of(), xVarNames, yVarNames);
  }

  @SuppressWarnings("unused")
  public static Supplier fromFile(
      @Param("filePath") String filePath,
      @Param(
              value = "folds",
              dIs = {0})
          List folds,
      @Param(value = "nFolds", dI = 1) int nFolds,
      @Param(value = "xVarNamePattern", dS = "x.*") String xVarNamePattern,
      @Param(value = "yVarNamePattern", dS = "y.*") String yVarNamePattern) {
    return () -> {
      try {
        return new LazyNumericalDataset(filePath, xVarNamePattern, yVarNamePattern)
            .folds(folds, nFolds);
      } catch (IOException e) {
        throw new RuntimeException(e);
      }
    };
  }

  @SuppressWarnings("unused")
  public static Supplier fromProblem(
      @Param("problem") UnivariateRegressionProblem problem) {
    return () -> problem.qualityFunction().getDataset();
  }
}