package org.nd4j.examples;

import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;

import static org.nd4j.linalg.ops.transforms.Transforms.*;


/**
 * Created by cvn on 9/7/14.
 */
public class FunctionsExample {

    public static void main(String[] args) {

        INDArray nd2 = Nd4j.create(new float[]{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}, new int[]{2, 6});
        INDArray ndv;

        ndv = sigmoid(nd2);
        System.out.println(ndv);

        

    }
}

package org.nd4j.examples;

import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;

import static org.nd4j.linalg.ops.transforms.Transforms.*;


/**
 * Created by cvn on 9/7/14.
 */
public class FunctionsExample {

    public static void main(String[] args) {

        INDArray nd = Nd4j.create(new float[]{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}, new int[]{2, 6});
        INDArray nd2 = Nd4j.create(new float[]{15,16,17,18,19,20,21,22,23,24,25,26,27,28}, new int[]{2, 7});
        INDArray ndv; // a placeholder variable to print out and leave the original data unchanged

        //this normalizes data and helps activate artificial neurons in deep-learning nets and assigns it to var ndv
        ndv = sigmoid(nd);
        System.out.println(ndv);

        //this gives you absolute value
        ndv = abs(nd);
        System.out.println(ndv);

        //a hyperbolic function to transform data much like sigmoid.
        ndv = tanh(nd);
        System.out.println(ndv);

        // ndv = hardTanh(nd);
        // System.out.println(ndv);

        //exponentiation
        ndv = exp(nd);
        System.out.println(ndv);

        //square root
        ndv = sqrt(nd);
        System.out.println(ndv);
    }
}

Update FunctionsExample.java