soundmasteraj

int[][] result;
float t, c;

float ease(float p) {
  return 3*p*p - 2*p*p*p;
}

float ease(float p, float g) {
  if (p < 0.5) 
    return 0.5 * pow(2*p, g);

soundmasteraj

int[][] result;
float t, c;

float ease(float p) {
  return 3*p*p - 2*p*p*p;
}

float ease(float p, float g) {
  if (p < 0.5) 
    return 0.5 * pow(2*p, g);

soundmasteraj

int[][] result;
float t, c;

float ease(float p) {
  return 3*p*p - 2*p*p*p;
}

float ease(float p, float g) {
  if (p < 0.5) 
    return 0.5 * pow(2*p, g);

soundmasteraj

int[][] result;
float t, c;

float ease(float p) {
  return 3*p*p - 2*p*p*p;
}

float ease(float p, float g) {
  if (p < 0.5) 
    return 0.5 * pow(2*p, g);

soundmasteraj

int numFrames = 100;

PVector field(float x,float y){
  float amount = 2.5;
  float scale = 0.03;
  float radius = 0.45;
  double value1 = 400.0*noise.eval(scale*x,scale*y,radius*cos(TWO_PI*1.0*(frameCount-1)/numFrames),radius*sin(TWO_PI*1.0*(frameCount-1)/numFrames));
  double value2 = 400.0*noise.eval(1000+scale*x,scale*y,radius*cos(TWO_PI*1.0*(frameCount-1)/numFrames),radius*sin(TWO_PI*1.0*(frameCount-1)/numFrames));
  //int value2 = (int) Math.round(value);
  float parameter1 = (int) Math.round(value1)/100.0;

soundmasteraj

OpenSimplexNoise noise;

int[][] result;
float t, c;

float ease(float p) {
  return 3*p*p - 2*p*p*p;
}

float ease(float p, float g) {

soundmasteraj

/*
 * OpenSimplex Noise in Java.
 * by Kurt Spencer
 * 
 * v1.1 (October 5, 2014)
 * - Added 2D and 4D implementations.
 * - Proper gradient sets for all dimensions, from a
 *   dimensionally-generalizable scheme with an actual
 *   rhyme and reason behind it.
 * - Removed default permutation array in favor of

soundmasteraj

from numpy import exp, array, random, dot
training_set_inputs = array([[0, 0, 1], [1, 1, 1], [1, 0, 1], [0, 1, 1]])
training_set_outputs = array([[0, 1, 1, 0]]).T
random.seed(1)
synaptic_weights = 2 * random.random((3, 1)) - 1
for iteration in xrange(10000):
    output = 1 / (1 + exp(-(dot(training_set_inputs, synaptic_weights))))
    synaptic_weights += dot(training_set_inputs.T, (training_set_outputs - output) * output * (1 - output))
print 1 / (1 + exp(-(dot(array([1, 0, 0]), synaptic_weights))))

soundmasteraj

var BASE64_MARKER = ';base64,';

function convertDataURIToBinary(dataURI) {
  var base64Index = dataURI.indexOf(BASE64_MARKER) + BASE64_MARKER.length;
  var base64 = dataURI.substring(base64Index);
  var raw = window.atob(base64);
  var rawLength = raw.length;
  var array = new Uint8Array(new ArrayBuffer(rawLength));

  for(i = 0; i < rawLength; i++) {

soundmasteraj

Hey, I incorporated some of these helpful comments from other users, this compiles on Dev C++ and now runs without causing abnormal termination on Windows 10

Thanks everybody! Hope this is helpful in some way. :)

https://code.activestate.com/recipes/users/4192555/
https://code.activestate.com/recipes/users/4180055/

// Astar.cpp
// http://en.wikipedia.org/wiki/A*// Compiler: Dev-C++ 4.9.9.2// FB - 201012256
#include <cstdlib>  // new