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Matrix Multiplication returning wrong value

I am calculating values by using weights and bias from MATLAB trained ANN. trying to code a sigmoid simulation equation, but for some reason C# calculations vary too much than that of MATLAB. i.e. error is too high. I tried to check each step of the equation and found out the specific part that is creating the problem (Emphasized part), but I don't know how to solve this issue, if someone could help, would be a huge favour.
1+(purelin(net.LW{2}×(tansig(net.IW{1}×(1-(abs(2×([inputs]-1)))))+net.b{1}))+net.b{2}))/2
//Normalization of Data
public double Normalization(double x, double xMAx, double xMin)
{
double xNorm = 0.0;
xNorm = (x - xMin) / (xMAx - xMin);
if (xNorm < 0)
xNorm = 0;
if (xNorm > 1)
xNorm = 1;
xNorm = Math.Round(xNorm, 4);
return xNorm;
}
// Equation to calculate ANN based Output Values
public double MetrixCalc(double[] Pn, double[,] W1, double[] W2, double[] b1, double b2, double maxValue, double minValue)
{
double FinalValue = 0;
double[] PnCalc1 = new double[Pn.Length];
double[] PnCalc2 = new double[W1.Length / Pn.Length];
for (int i = 0; i < Pn.Length; i++)
{
PnCalc1[i] = 1 - Math.Abs(2 * (Pn[i] - 1));
}
for (int i = 0; i < (W1.Length / Pn.Length); i++)
{
double PnCalc = 0.0;
for (int j = 0; j < Pn.Length; j++)
{
PnCalc = PnCalc + (W1[i, j] * PnCalc1[j]);
}
PnCalc2[i] = PnCalc;
}
for (int i = 0; i < PnCalc2.Length; i++)
{
//PnCalc2[i] = Math.Tanh(PnCalc2[i] + b1[i]);
PnCalc2[i] = PnCalc2[i] + b1[i];
PnCalc2[i] = 2.0 / (1 + Math.Exp(-2 * (PnCalc2[i]))) - 1;
PnCalc2[i] = Math.Round(PnCalc2[i], 4);
}
double FinalCalc = 0.0;
for (int i = 0; i < PnCalc2.Length; i++)
{
*FinalCalc = FinalCalc + (W2[i] * (PnCalc2[i]));*
//FinalValue = FinalCalc;
}
FinalValue = FinalCalc + b2;
FinalValue = 1 + FinalValue;
FinalValue = (1 + FinalValue) / 2.0;
FinalValue = (FinalValue * (maxValue - minValue)) + minValue;
FinalValue = Math.Round(FinalValue, 4);
FinalValue = Math.Abs(FinalValue);
return FinalValue;
}

Problem is solved.
Problem was with the weights matrix copied from MATLAB. debugging mode saved my life. :)

Reorder digits in integer using C#

I want to ask how I can reorder the digits in an Int32 so they result in the biggest possible number.
Here is an example which visualizes what I am trying to do:
2927466 -> 9766422
12492771 -> 97742211
I want to perform the ordering of the digits without using the System.Linq namespace and without converting the integer into a string value.
This is what I got so far:
public static int ReorderInt32Digits(int v)
{
int n = Math.Abs(v);
int l = ((int)Math.Log10(n > 0 ? n : 1)) + 1;
int[] d = new int[l];
for (int i = 0; i < l; i++)
{
d[(l - i) - 1] = n % 10;
n /= 10;
}
if (v < 0)
d[0] *= -1;
Array.Sort(d);
Array.Reverse(d);
int h = 0;
for (int i = 0; i < d.Length; i++)
{
int index = d.Length - i - 1;
h += ((int)Math.Pow(10, index)) * d[i];
}
return h;
}
This algorithm works flawlessly but I think it is not very efficient.
I would like to know if there is a way to do the same thing more efficiently and how I could improve my algorithm.

You can use this code:
var digit = 2927466;
String.Join("", digit.ToString().ToCharArray().OrderBy(x => x));
Or
var res = String.Join("", digit.ToString().ToCharArray().OrderByDescending(x => x) );

Not that my answer may or may not be more "efficient", but when I read your code you calculated how many digits there are in your number so you can determine how large to make your array, and then you calculated how to turn your array back into a sorted integer.
It would seem to me that you would want to write your own code that did the sorting part without using built in functionality, which is what my sample does. Plus, I've added the ability to sort in ascending or descending order, which is easy to add in your code too.
UPDATED
The original algorithm sorted the digits, now it sorts the digits so that the end result is the largest or smallest depending on the second parameter passed in. However, when dealing with a negative number the second parameter is treated as opposite.
using System;
public class Program
{
public static void Main()
{
int number1 = 2927466;
int number2 = 12492771;
int number3 = -39284925;
Console.WriteLine(OrderDigits(number1, false));
Console.WriteLine(OrderDigits(number2, true));
Console.WriteLine(OrderDigits(number3, false));
}
private static int OrderDigits(int number, bool asc)
{
// Extract each digit into an array
int[] digits = new int[(int)Math.Floor(Math.Log10(Math.Abs(number)) + 1)];
for (int i = 0; i < digits.Length; i++)
{
digits[i] = number % 10;
number /= 10;
}
// Order the digits
for (int i = 0; i < digits.Length; i++)
{
for (int j = i + 1; j < digits.Length; j++)
{
if ((!asc && digits[j] > digits[i]) ||
(asc && digits[j] < digits[i]))
{
int temp = digits[i];
digits[i] = digits[j];
digits[j] = temp;
}
}
}
// Turn the array of digits back into an integer
int result = 0;
for (int i = digits.Length - 1; i >= 0; i--)
{
result += digits[i] * (int)Math.Pow(10, digits.Length - 1 - i);
}
return result;
}
}
Results:
9766422
11224779
-22345899
See working example here... https://dotnetfiddle.net/RWA4XV

public static int ReorderInt32Digits(int v)
{
var nums = Math.Abs(v).ToString().ToCharArray();
Array.Sort(nums);
bool neg = (v < 0);
if(!neg)
{
Array.Reverse(nums);
}
return int.Parse(new string(nums)) * (neg ? -1 : 1);
}

This code fragment below extracts the digits from variable v. You can modify it to store the digits in an array and sort/reverse.
int v = 2345;
while (v > 0) {
int digit = v % 10;
v = v / 10;
Console.WriteLine(digit);
}
You can use similar logic to reconstruct the number from (sorted) digits: Multiply by 10 and add next digit.

I'm posting this second answer because I think I got the most efficient algorithm of all (thanks for the help Atul) :)
void Main()
{
Console.WriteLine (ReorderInt32Digits2(2927466));
Console.WriteLine (ReorderInt32Digits2(12492771));
Console.WriteLine (ReorderInt32Digits2(-1024));
}
public static int ReorderInt32Digits2(int v)
{
bool neg = (v < 0);
int mult = neg ? -1 : 1;
int result = 0;
var counts = GetDigitCounts(v);
for (int i = 0; i < 10; i++)
{
int idx = neg ? 9 - i : i;
for (int j = 0; j < counts[idx]; j++)
{
result += idx * mult;
mult *= 10;
}
}
return result;
}
// From Atul Sikaria's answer
public static int[] GetDigitCounts(int n)
{
int v = Math.Abs(n);
var result = new int[10];
while (v > 0) {
int digit = v % 10;
v = v / 10;
result[digit]++;
}
return result;
}

Calculating exponential growth equation from data points c#

I am trying to analyse some data using a C# app and need to calculate trend lines. I am aware that there are multiple types of trend line but for now I am trying to calculate exponential growth; I am going to be using it to predict future values. The equation I have been working off is
x(t) = x(0) * ((1+r)^t)
And this is the code that I have written to try and replicate the graph:
public void ExponentialBestFit(List<DateTime> xvalues, List<double> yvalues)
{
//Find the first value of y (The start value) and the first value of x (The start date)
xzero = Convert.ToDouble(xvalues[0].ToOADate());
yzero = yvalues[0];
if (yzero == 0)
yzero += 0.1;
//For every value of x (exluding the 1st value) find the r value
//
// | y | Where t = the time sinse the start time (time period)
//Equation for r = t root|-------| - 1 Where y = the current y value
// | y[0] | Where y[0] = the first y value #IMPROVMENT - Average 1st y value in range
//
double r = 0;
//c is a count of how many r values are added; it is not equal to the count of all the values
int c = 0;
for (int i = 1; i < xvalues.Count; i++)
{
r += Math.Pow(yvalues[i]/yzero, 1/(Convert.ToDouble(xvalues[i].ToOADate()) - xzero)) - 1;
c++;
}
r = r / c;
}
The data I am passing in is over a period of time however the increments in which the time increases are not the same. When I created a chart in excel they use a different formula
x(t) = x(0)*(e^kt)
I think however I have no idea where the k value is being generated from. The two lists that I am passing in are Date and Value and each row in each list corresponds to the same row in the other list. The question is - Is there a better way of creating the equation and variables and are the variables I am getting the most accurate it can be for my data?

This is the c# version of the javascript provided.
// Calculate Exponential Trendline / Growth
IEnumerable<double> Growth(IList<double> knownY, IList<double> knownX, IList<double> newX, bool useConst)
{
// Credits: Ilmari Karonen
// Default values for optional parameters:
if (knownY == null) return null;
if (knownX == null)
{
knownX = new List<double>();
for (var i = 0; i<=knownY.Count; i++)
knownX.Add(i);
}
if (newX == null)
{
newX = new List<double>();
for (var i = 0; i <= knownY.Count; i++)
newX.Add(i);
}
int n = knownY.Count;
double avg_x = 0.0;
double avg_y = 0.0;
double avg_xy = 0.0;
double avg_xx = 0.0;
double beta = 0.0;
double alpha = 0.0;
for (var i = 0; i < n; i++)
{
var x = knownX[i];
var y = Math.Log(knownY[i]);
avg_x += x;
avg_y += y;
avg_xy += x * y;
avg_xx += x * x;
}
avg_x /= n;
avg_y /= n;
avg_xy /= n;
avg_xx /= n;
// Compute linear regression coefficients:
if (useConst)
{
beta = (avg_xy - avg_x * avg_y) / (avg_xx - avg_x * avg_x);
alpha = avg_y - beta * avg_x;
}
else
{
beta = avg_xy / avg_xx;
alpha = 0.0;
}
// Compute and return result array:
return newX.Select(t => Math.Exp(alpha + beta*t)).ToList();
}

The following JavaScript code should help. I used it to implement Excel's GROWTH function. It's written in JavaScript, but porting it to C# should be very easy. Please note that most of it was written by someone else (credits in the code).
function GROWTH(known_y, known_x, new_x, use_const) {
// Credits: Ilmari Karonen
// Default values for optional parameters:
if (typeof(known_x) == 'undefined') {
known_x = [];
for (var i = 1; i <= known_y.length; i++) known_x.push(i);
}
if (typeof(new_x) == 'undefined') {
new_x = [];
for (var i = 1; i <= known_y.length; i++) new_x.push(i);
}
if (typeof(use_const) == 'undefined') use_const = true;
// Calculate sums over the data:
var n = known_y.length;
var avg_x = 0;
var avg_y = 0;
var avg_xy = 0;
var avg_xx = 0;
for (var i = 0; i < n; i++) {
var x = known_x[i];
var y = Math.log(known_y[i]);
avg_x += x;
avg_y += y;
avg_xy += x*y;
avg_xx += x*x;
}
avg_x /= n;
avg_y /= n;
avg_xy /= n;
avg_xx /= n;
// Compute linear regression coefficients:
if (use_const) {
var beta = (avg_xy - avg_x*avg_y) / (avg_xx - avg_x*avg_x);
var alpha = avg_y - beta*avg_x;
} else {
var beta = avg_xy / avg_xx;
var alpha = 0;
}
// Compute and return result array:
var new_y = [];
for (var i = 0; i < new_x.length; i++) {
new_y.push(Math.exp(alpha + beta * new_x[i]));
}
return new_y;
}

Since x(t)=x(0)*e^{kt}, we can take logarithms to get ln x(t)=ln x(0) + kt. This means that to find ln x(0) and k, you can find the least squares fit for the data {(t,ln x(t))}. This will tell you that ln x(t) = b + at, so that k=a and x(0)=e^b.

How to compute ifft from fft?

I've done a fft to get fundamental frequency in real time and to implement high and low pass filters.
Now I want to be able to record to a .wav file after I apply a filter.
First I'll have to invert the fft and that is my question.
What are the steps to do this?
I use the FFT defined in this project.
Here is the code for it:
using System;
using System.Collections.Generic;
using System.Text;
namespace SoundLog
{
public class FourierTransform
{
static private int n, nu;
static private int BitReverse(int j)
{
int j2;
int j1 = j;
int k = 0;
for (int i = 1; i <= nu; i++)
{
j2 = j1 / 2;
k = 2 * k + j1 - 2 * j2;
j1 = j2;
}
return k;
}
static public double[] FFT(ref double[] x)
{
// Assume n is a power of 2
n = x.Length;
nu = (int)(Math.Log(n) / Math.Log(2));
int n2 = n / 2;
int nu1 = nu - 1;
double[] xre = new double[n];
double[] xim = new double[n];
double[] magnitude = new double[n2];
double[] decibel = new double[n2];
double tr, ti, p, arg, c, s;
for (int i = 0; i < n; i++)
{
xre[i] = x[i];
xim[i] = 0.0f;
}
int k = 0;
for (int l = 1; l <= nu; l++)
{
while (k < n)
{
for (int i = 1; i <= n2; i++)
{
p = BitReverse(k >> nu1);
arg = 2 * (double)Math.PI * p / n;
c = (double)Math.Cos(arg);
s = (double)Math.Sin(arg);
tr = xre[k + n2] * c + xim[k + n2] * s;
ti = xim[k + n2] * c - xre[k + n2] * s;
xre[k + n2] = xre[k] - tr;
xim[k + n2] = xim[k] - ti;
xre[k] += tr;
xim[k] += ti;
k++;
}
k += n2;
}
k = 0;
nu1--;
n2 = n2 / 2;
}
k = 0;
int r;
while (k < n)
{
r = BitReverse(k);
if (r > k)
{
tr = xre[k];
ti = xim[k];
xre[k] = xre[r];
xim[k] = xim[r];
xre[r] = tr;
xim[r] = ti;
}
k++;
}
for (int i = 0; i < n / 2; i++)
//magnitude[i] = (float)(Math.Sqrt((xre[i] * xre[i]) + (xim[i] * xim[i])));
decibel[i] = 10.0 * Math.Log10((float)(Math.Sqrt((xre[i] * xre[i]) + (xim[i] * xim[i]))));
//return magnitude;
return decibel;
}
}
}

There are so many really good fft implementations around such as FFTW that I highly recommend using one. They come with ifft as well. Yours, as implemented, will be excruciatingly slow.

C# FFT Implementation not producing expected results

I'm trying to implement, in C#, for my own learning, an FFT algorithm described here:
https://en.wikipedia.org/wiki/Cooley%E2%80%93Tukey_FFT_algorithm
under "Data reordering, bit reversal, and in-place algorithms".
My code is as follows, with some background operator overloading for the "cplx" structure to allow me to do arithmetic on these objects.
Bitreverse seems to work fine, and so does the "twiddle factor" calculation, so I'm not sure where I've gone wrong. The code looks awfully similar to the pseudocode given on the wiki page.
public cplx[] FFT(cplx[] x)
{
//Bitreverse Copy
cplx[] a = BitReverse(x);
//Number of points
int n = a.Length;
for (int s = 1; s <= Math.Log(n); s++)
{
int m = (int)Math.Pow(2,s);
cplx w_m = Omega(m);
for (int k = 0; k < n; k += m)
{
cplx w = new cplx(1, 0);
for(int j = 0; j < m/2; j++)
{
cplx t = w * a[k + j + (m / 2)];
cplx u = a[k + j];
a[k + j] = u + t;
a[k + j + (m / 2)] = u - t;
w = w * w_m;
}
}
}
return a;
}
I'm testing it with an input array of an origin-impulse with 8 samples, which should produce a constant output.
Instead, I'm getting 4 ones and 4 zeros, in that order.
As an aside, I assume that in the pseudocode:
for k = 0 to n-1 by m
Refers to for(k = 0; k < n; k += m) although I'm not sure that's right.
Hopefully someone can shed some light on my incompetence!
Cheers.
Here's the code for bitreversal and the omega calculation.
private int Rev(int x, int k)
{
int reversed = 0;
for (int i = 0; i < k; i++)
{
reversed |= (x & (1 << i)) != 0 ? 1 << (k - 1 - i) : 0;
}
return reversed;
}
public cplx[] BitReverse(cplx[] x)
{
cplx[] r = new cplx[x.Length];
int bits = (int)Math.Log(x.Length, 2);
for(int k = 0; k < x.Length; k++)
{
r[Rev(k, bits)] = x[k];
}
return r;
}
private cplx Omega(int m)
{
float x = (- 2 * (float)Math.PI) / m;
return new cplx((float)Math.Cos(x), (float)(Math.Sin(x)));
}

I should have been using log2(n) when I was using Math.Log().