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/*
 * 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.
 */

package tech.tablesaw.api.ml.features;

import smile.projection.PCA;
import tech.tablesaw.api.NumericColumn;
import tech.tablesaw.util.DoubleArrays;

public class PrincipalComponents {

    private final PCA pca;

    private PrincipalComponents(double[][] data, boolean useCorrelationMatrix) {
        this.pca = new PCA(data, useCorrelationMatrix);
    }

    public static PrincipalComponents create(boolean useCorrelationMatrix, NumericColumn... columns) {
        double[][] data = DoubleArrays.to2dArray(columns);
        return new PrincipalComponents(data, useCorrelationMatrix);
    }

    public double[] getCenter() {
        return pca.getCenter();
    }

    public double[] getCumulativeVarianceProportion() {
        return pca.getCumulativeVarianceProportion();
    }

    public double[] getVarianceProportion() {
        return pca.getVarianceProportion();
    }

    public double[] getVariance() {
        return pca.getVariance();
    }

    public double[] project(double[] x) {
        return pca.project(x);
    }

    public double[][] project(double[][] x) {
        return pca.project(x);
    }

    public double[][] getLoadings() {
        return pca.getLoadings().array();
    }

    public double[][] getProjection() {
        return pca.getProjection().array();
    }

    public PCA setProjection(int p) {
        return pca.setProjection(p);
    }

    public PCA setProjection(double p) {
        return pca.setProjection(p);
    }
}