I have written a Javascript file of two algorithms. As shown in the code below, I am using a for loop to generate random values which are used by both algorithms as input.
At present, I am displaying output of the binarySearch and SearchSorted alternatively.
The problem I am facing is I have to pass the same array values generated by randomlyGenerateArray in the main program to both the algorithms for a meaningful comparison. But I don't know how to change the output format.
I have thought of adding them in different loops, but as I have explained above i need to use the same randomArray values for both the algorithms.
i.e., The below code produces output as shown below -
Binary Search Successful 1
Search Sorted Successful 5
Binary Search Successful 3
Search Sorted Successful 10
How do I display the output of Binary Search First and then display output of Search Sorted? it's something like this. Any help will be greatly appreciated.
Binary Search Successful 1
Binary Search Successful 3
Search Sorted Successful 5
Search Sorted Successful 10
// Binary Search Algorithm
function binarySearch(A,K)
{
var l = 0; // min
var r = A.length - 1; //max
var n = A.length;
var operations = 0;
while(l <= r)
{
var m = Math.floor((l + r)/2);
operations++;
if(K == A[m])
{
console.log('Binary Search Successful %d',operations);
return m;
}
else if(K < A[m])
{
r = m - 1;
}
else
{
l = m + 1;
}
}
operations++;
console.log('Binary Search Unsuccessful %d',operations);
return -1;
}
// Search Sorted Algorithm
function searchSorted(A, K)
{
var n = A.length;
var i = 0;
var operations = 0;
while (i < n)
{
operations++;
if (K < A[i])
{
return -1;
}
else if (K == A[i])
{
console.log('Search Sorted Successful %d', operations);
return i;
}
else
{
i = i + 1;
}
}
operations++;
console.log('Search Sorted Unsuccessful %d', operations);
return -1;
}
// Random Array generator
var randomlyGenerateArray = function(size)
{
var array = [];
for (var i = 0; i < size; i++)
{
var temp = Math.floor(Math.random() * maxArrayValue);
var final = array.splice(5, 0, 30);
array.push(final);
}
return array;
}
//Sort the Array
var sortNumber = function(a, b)
{
return a - b;
}
// Main Program
var program = function()
{
var incrementSize = largestArray / numberOfArrays;
for (var i = smallestArray; i <= largestArray; i += incrementSize)
{
var randomArray = randomlyGenerateArray(i);
var sort = randomArray.sort(sortNumber);
var randomKey = 30;
binarySearch(sort, randomKey);
searchSorted(sort, randomKey);
}
}
var smallestArray = 10;
var largestArray = 10000;
var numberOfArrays = 1000;
var minArrayValue = 1;
var maxArrayValue = 1000;
program();
You could store the sorted randomArrays in an array (which I've called sortedRandomArrays), then run a for loop for each search.
The Main Program would then look like:
// Main Program
var program = function()
{
var incrementSize = largestArray / numberOfArrays;
var sortedRandomArrays = [];
for (var i = smallestArray; i <= largestArray; i += incrementSize)
{
var randomArray = randomlyGenerateArray(i));
var sort = randomArray.sort(sortNumber);
sortedRandomArrays.push(sort);
var randomKey = 30;
}
for (var i = 0; i < sortedRandomArrays.length; i++)
{
binarySearch(sortedRandomArrays[i], randomKey);
}
for (var i = 0; i < sortedRandomArrays.length; i++)
{
searchSorted(sortedRandomArrays[i], randomKey);
}
}
Solution is simple: store the results and print with 2 separate loops (take out the printing from within the functions).
var program = function()
{
var binarySearchResults = [];
var sortedSearchResults = [];
var incrementSize = largestArray / numberOfArrays;
for (var i = smallestArray; i <= largestArray; i += incrementSize)
{
var randomArray = randomlyGenerateArray(i);
var sort = randomArray.sort(sortNumber);
var randomKey = 30;
binarySearchResults[i] = binarySearch(sort, randomKey);
sortedSearchResults[i] = searchSorted(sort, randomKey);
}
for (var i = smallestArray; i <= largestArray; i += incrementSize)
{
//print binary results
}
for (var i = smallestArray; i <= largestArray; i += incrementSize)
{
//print sorted results
}
}
Related
I am newbie in machine learning, but decided to make own js library for neural networks, everything went perfect until i tryed to train my NN. In My Mini Library i created some functions...
1) A Function That Creates My Neuron-Object:
this.Node = function (conns) {
var output = {};
output.b = hyth.Random({type: "TanH"});
output.w = [];
for (var a = 0; a < conns; a++){
output.w[a] = hyth.Random({type: "TanH"});
}
output.Value = function (i) {
if (i.length == conns) {
var sum = 0;
for (var a = 0; a < conns; a++){
sum += i[a] * output.w[a];
}
sum += output.b;
return myMath.Activate(sum, {type: "Sigmoid"});
}
}
return output;
}
This function has one argument , which is the amount of wanted weights from neuron, and it returns an object with two properties - "b" the float (bias), and "w" the 1D Array which contains floats, and one method - which calculates the activation of neuron-object.
2) A Function That Creates My Neural Net
this.Network = function () {
var p = arguments;
var arr = [];
for (var a = 0; a < p.length-1; a++){
arr[a] = [];
for (var b = 0; b < p[a+1]; b++){
arr[a][b] = this.Node(p[a]);
}
}
return arr;
}
This Function Returns A 2D Array with Neuron-Object as It's final value, using argument array as settings for layer count and node count for each layer.
3) A Function That Feeds Forward The NN
this.Forward = function (network, input) {
if (network[0][0].w.length == input.length) {
var activations = [];
for (var a = 0; a < network.length; a++){
activations[a] = [];
for (var c = 0; c < network[a].length; c++){
if (a == 0){
activations[0][c] = network[0][c].Value(input);
continue;
}
activations[a][c] = network[a][c].Value(activations[a-1]);
}
}
return activations;
}
}
This Function Returns 2D array with an activation float for every neuron as it's final value. It uses 2 agruments - the output of 2nd function, input array.
4) And Final Function That Backpropagates
this.Backward = function (network, input, target) {
if (network[0][0].w.length == input.length && network[network.length-1].length == target.length) {
var activations = this.Forward(network, input, true);
var predictions = activations[activations.length-1];
var errors = [];
for (var v = 0; v < network.length; v++) {
errors[v] = [];
}
for (var a = network.length-1; a > -1; a--){
for (var x = 0; x < network[a].length; x++) {
var deract = hyth.Deractivate(activations[a][x]);
if (a == network.length-1) {
errors[a][x] = (predictions[x] - target[x]) * deract;
} else {
errors[a][x] = 0;
for (var y = 0; y < network[a+1].length; y++) {
errors[a][x] += network[a+1][y].w[x] * errors[a+1][y];
}
errors[a][x] *= deract;
}
}
}
return errors;
}
}
This Function Returns 2D array with the rror float for every neuron as it's final value. Arguments are 3 - the nnet , input and wanted output.
So I can make a neural network, feed forward and and backpropagate, receive activations and errors, but i always fail to train my net with my errors and activations to work perfect , last time it was outputing same result for every type of input. I want to understand training algorithm from zero , so i need someone's help.
P.S. - i dont want someone say that i need to use famous libraries , i want to understand and make it myself.
I experience a strange differences in performance of simple task depending of array I am working with. The task is to calculate sum of those elements in array which are greater than 5. Task is performed on arrays with equal lenghts.
I try the very same approach on three different array objects:
1) var hugeArray1 - array with all elemenets randomly picked from 0:10 range
2) var hugeArray2 - copy of hugeArray1 sorted with Array.prototype.sort()
3) var hugeArray3 - handcrafted but sorted array with values from 0:10 range, spread to equaly cover this interval.
I try to calculate sum of elements greater than 5 many times for each Array and then average them. What is strange, time needed varies a lot for those three arrays.
1) hugeArray1: 5.805ms
2) hugeArray2: 15.738ms
3) hugeArray3: 3.753ms
Result for array sorted with sort() is extreamly poor. Why is that? it looks like sort() returns some kind of wraper/proxy instead of 'native' Array, which affects performance. I tried it on 2 computers. Also i tried to change order of testing.
I include code below, please tell me what is happening here.
// random array with elements 0-10 of size n
function randomArray(n) {
var arr = [];
for (var i = 0; i < n; ++i) {
arr.push(Math.random() * 10);
}
return arr;
};
// measures time of execution
function measureTime(f) {
var start = new Date().getTime();
f();
var stop = new Date().getTime();
return stop - start;
};
// enumerate ofer array and calculate sum of elementsgreater than 5
function sumGreaterThan5(arr) {
var sum = 0;
for (var i = 0; i < arr.length; ++i) {
if (arr[i] > 5.0)
sum += arr[i];
}
return sum;
}
// generate array os size 'size' with elements with constant step to fill interval 0:10
function generateSortedArr(size) {
var arr = [];
for (var i = 0; i < size; ++i) {
arr.push(i * 10 / size);
}
return arr;
}
var huge = 1000000;
var hugeArray1 = randomArray(huge);
var hugeArray2 = hugeArray1.slice(0).sort();
var hugeArray3 = generateSortedArr(huge);
var hugeArrays = [hugeArray1, hugeArray2, hugeArray3];
hugeArrays.forEach(x=> {
var res = [];
for (var i = 0; i < 1000; ++i) {
res.push(measureTime(function () {
sumGreaterThan5(x);
}));
}
console.log(res.reduce((prev, curr)=> prev + curr) / res.length);
});
// random array with elements 0-10 of size n
function randomArray(n) {
var arr = [];
for (var i = 0; i < n; ++i) {
arr.push(Math.random() * 10);
}
return arr;
};
// measures time of execution
function measureTime(f) {
var start = new Date().getTime();
f();
var stop = new Date().getTime();
return stop - start;
};
// enumerate ofer array and calculate sum of elementsgreater than 5
function sumGreaterThan5(arr) {
var sum = 0;
for (var i = 0; i < arr.length; ++i) {
if (arr[i] > 5.0)
sum += arr[i];
}
return sum;
}
// generate array os size 'size' with elements with constant step to fill interval 0:10
function generateSortedArr(size) {
var arr = [];
for (var i = 0; i < size; ++i) {
arr.push(i * 10 / size);
}
return arr;
}
var huge = 1000000;
var hugeArray1 = randomArray(huge);
var hugeArray2 = hugeArray1.slice(0).sort();
var hugeArray3 = generateSortedArr(huge);
var hugeArrays = [hugeArray1, hugeArray2, hugeArray3];
hugeArrays.forEach(function(x){
var res = [];
for (var i = 0; i < 1000; ++i) {
res.push(measureTime(function () {
sumGreaterThan5(x);
}));
}
console.log(res.reduce(function(prev, curr){return prev + curr},0) / res.length);
});
I have implemented Binary Search Algorithm using Node.js. I am recording the time taken by the algorithm to search for a number in a random generated array. I am able to output the time taken by the algorithm for an unsuccessful search.
But I am not able to figure out how to measure the time taken by the algorithm to successfully search a number in an array.
Here is my code -
function binarySearch(A,K)
{
var l = 0; // min
var r = A.length - 1; //max
var n = A.length;
var time = process.hrtime();
while(l <= r)
{
var m = Math.floor((l + r)/2);
if(K == A[m])
{
return m;
}
else if(K < A[m])
{
r = m - 1;
}
else
{
l = m + 1;
}
}
time = process.hrtime(time);
console.log('%d',time[1]/1000000);
return -1;
}
var randomlyGenerateArray = function(size)
{
var array = [];
for (var i = 0; i < size; i++)
{
var temp = Math.floor(Math.random() * maxArrayValue);
array.push(temp);
}
return array;
}
var sortNumber = function(a, b)
{
return a - b;
}
var program = function()
{
for (var i = 0; i <= 10000; i += 10)
{
var randomArray = randomlyGenerateArray(i);
var sort = randomArray.sort(sortNumber);
var randomKey = 100;
var result = binarySearch(sort, randomKey);
if(result < 0)
{
console.log("Element not found");
}
else
{
console.log('Element found in position ',result);
}
}
}
var maxArrayValue = 1000;
program();
I am using var time = process.hrtime(); to start the timer at the beginning of the algorithm and using time = process.hrtime(time); to end the timer and output it in the console.
How can I measure the time taken by the algorithm to successfully search a number in an array.
Any help would be greatly appreciated.
Start your timer before calling the binary search function and end it after the call .. regardless of whether the search is successful or not, you will get the time ..
var time = process.hrtime();
var result = binarySearch(sort, randomKey);
time = process.hrtime(time);
......
I must be doing something stupid. The array newArea needs to add up data from all regions, i.e. be global. Regions are represented by variable p. But when I try to get newArea array to add to itself, e.g. newArea[p] += otherArray, it outputs NaNs. Even newArea[p] += 1 outputs NaNs.
Can anyone spot what I'm doing wrong? It's driving me mad and I'm working to a deadline.
mm=0
var maxVolume = 0;
var tempCAGR = 0;
var maxCAGR = 0;
var newArray = [];
var newRegions = [];
var newConsValues = [];
var newArea = [];
for (var p=0; p<arrayRef[mm].length; p++) {//9 regions
newArray[p] = [];
for (var q=0; q<arrayRef[mm][p].length; q++) {//4 scenarios
newArea[q] = [];
if (q==0) {
newRegions.push(arrayRef[mm][p][q][0]);
newConsValues.push(arrayRef[mm][p][q][1]);
}
for (var r=0; r<dates.length; r++) {//time
//console.log('p: '+p+', q: '+q+', r: '+r);
if (p==0) {
newArea[q][r] = 1;
} else {
newArea[q][r] += 1;
}
}
arrayRef[mm][p][q].shift();
tempCAGR = Math.pow(( arrayRef[mm][p][q][len] / arrayRef[mm][p][q][1] ),(1/len))-1;
//console.log(newRegions[p]+', num: '+arrayRef[mm][p][q][len-1]+', denom: '+arrayRef[mm][p][q][0]+', len: '+len+', cagr: '+tempCAGR);
newArray[p][q] = tempCAGR;
maxCAGR = Math.max(maxCAGR,tempCAGR);
}
}
console.log(newArea);
You are cleaning the array in newArea everytime you loop through it:
...loop q ...
newArea[q] = []; // <-- resets the array at q pos
... loop r ...
if (p==0) {
newArea[q][r] = 1;
} else {
newArea[q][r] += 1;
}
So when p === 0 it will fill an array at q pos of your newArea array. However, next iteration of p will clear them out, so there's nothing there to sum.
You probably want to keep the old array or create a new one if there isn't one.
newArea[q] = newArea[q] || [];
It looks like you do not have the variable initialised. With adding something to undefined, you get NaN.
You can change the art of incrementing with a default value:
if (p == 0) {
newArea[q][r] = 1;
} else {
newArea[q][r] = (newArea[q][r] || 0) + 1;
}
I was teaching myself how to make a binary genetic algorithm the other day. The goal was to make it so that it would match a randomly generated 35 length binary string. I ran into a problem where methods were editing variables that I did not think were in its scope. This caused my solution to slowly degrade in fitness instead of increase! After I found out where this was happening I fixed it by newP[0].join('').split('') so that newP[0] itself would not be edited. For convenience I've marked where the problem was happening below in comments.
While I have fixed this problem I'd like to hopefully get an understanding as to why this happens and also prevent without doing the join/split silliness.
Here is the code:
var GeneticAlgorithm = function () {};
GeneticAlgorithm.prototype.mutate = function(chromosome, p) {
for(var i = 0; i < chromosome.length; i++) {
if(Math.random() < p) {
chromosome[i] = (chromosome[i] == 0) ? 1 : 0;
}
}
return chromosome;
};
GeneticAlgorithm.prototype.crossover = function(chromosome1, chromosome2) {
var split = Math.round(Math.random() * chromosome1.length);
var c1 = chromosome1;
var c2 = chromosome2;
for(var i = 0; i < split; i++) {
c1[i] = chromosome2[i];
c2[i] = chromosome1[i];
}
return [c1, c2];
};
// fitness = function for finding fitness score of an individual/chromosome (0-1)
// length = length of string (35)
// p_c = percentage chance of crossover (0.6)
// p_m = percentage change of mutation (0.002)
GeneticAlgorithm.prototype.run = function(fitness, length, p_c, p_m, iterations) {
var iterations = 100;
var size = 100;
// p = population, f = fitnesses
var p = [];
var f = [];
for(var i = 0; i < size; i++) {
p.push(this.generate(length));
f.push(fitness(p[i].join('')));
}
while( iterations > 0 && Math.max.apply(Math, f) < 0.999 ) {
var mates = [];
var newP = [];
var newF = [];
mates = this.select(p, f);
newP.push(mates[0], mates[1]);
while(newP.length < size) {
/*-------------------> Problem! <-------------------*/
mates = [newP[0].join('').split(''), newP[1].join('').split('')];
/*
* If I passed newP[0] when mates[0] changed newP[0] would also change
*/
if(Math.random() < p_c) {
mates = this.crossover(mates[0], mates[1]);
}
mates[0] = this.mutate(mates[0], p_m);
mates[1] = this.mutate(mates[1], p_m);
newP.push(mates[0], mates[1]);
}
for(var i = 0; i < size; i++) {
newF.push(fitness(newP[i].join('')));
}
p = newP;
f = newF;
iterations--;
}
return p[f.indexOf(Math.max.apply(Math, f))].join('');
};