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);

        

    }
}

@@ -300,17 +300,16 @@
 Array nd
-2
  = Nd4j.
@@ -408,11 +408,314 @@
 y nd
-v;%0A
+2 = Nd4j.create(new float%5B%5D%7B15,16,17,18,19,20,21,22,23,24,25,26,27,28%7D, new int%5B%5D%7B2, 7%7D);%0A        INDArray ndv; // a placeholder variable to print out and leave the original data unchanged%0A%0A        //this normalizes data and helps activate artificial neurons in deep-learning nets and assigns it to var ndv
 %0A   
@@ -735,17 +735,16 @@
 gmoid(nd
-2
 );%0A     
@@ -780,17 +780,460 @@
         
-%0A
+//this gives you absolute value%0A        ndv = abs(nd);%0A        System.out.println(ndv);%0A%0A        //a hyperbolic function to transform data much like sigmoid.%0A        ndv = tanh(nd);%0A        System.out.println(ndv);%0A%0A        // ndv = hardTanh(nd);%0A        // System.out.println(ndv);%0A%0A        //exponentiation%0A        ndv = exp(nd);%0A        System.out.println(ndv);%0A%0A        //square root%0A        ndv = sqrt(nd);%0A        System.out.println(ndv);
 %0A    %7D%0A%7D

Update FunctionsExample.java