for loop calculates the same value each time - c++

I am trying to implement a recurrence relation that will return me the kth term. But I am receiving the same output when I change the k value. Here is my code:
int recurrence(int a, int b, int k, int u0, int u1) {
int u = u0;
int uu = u1;
for (int i = 0; i < k; i++)
uu = a*u1 + b*u0;
return uu;
}
int recurrence2(int a1, int b1, int k1, int u4, int u5) {
int u = u4;
int uu = u5;
for (int i = 0; i < k1; i++)
uu = a1*u5 + b1*u4;
return uu;
}
int main() {
int h;
h = recurrence(7, 1, 5, 3, 5 );
int g;
g = recurrence2(17, 11, 2, 1, 2);
cout << "The result is: " << h;
cout << "The result is : " << g;
}

You evaluate the same values in expression in the loop, so result would not change regardless how many times you execute it. Looks like this is what you need:
int recurrence(int a, int b, int k, int u0, int u1)
{
for (int i = 0; i < k; i++) {
auto tmp = a*u1 + b*u0;
u0 = u1;
u1 = tmp;
}
return u1;
}
or simpler:
int recurrence(int a, int b, int k, int u0, int u1)
{
for (int i = 0; i < k; i++) {
u0 = a*u1 + b*u0;
std::swap( u1, u0 );
}
return u1;
}
second function needs to be changed the same way.
PS you asked how could you maintain state of variables for further invocations, best way is to have class that maintains it:
class Recurrence {
int m_a;
int m_b;
int m_u0;
int m_u1;
public:
Recurrence( int a, int b, int u0, int u1 ) :
m_a( a ),
m_b( b ),
m_u0( u0 ),
m_u1( u1 )
{
}
int value() const { return m_u1; }
void interate()
{
m_u0 = m_a * m_u1 + m_b * m_u0;
std::swap( m_u0, m_u1 );
}
void interateN( int n )
{
for( int i = 0; i < n; ++i ) iterate();
}
};
int main()
{
Recurence recurence( 7, 1, 3, 5 );
recurence.iterateN( 5 );
int h = recurence.value();
recurence.iterateN( 5 ); // continue
...
}
In reality you may want to have that class more generic - for example use different number of arguments, different types, store them in array etc. This code just to show you the idea.

Related

How to find coefficients of polynomial equation?

Given two points in the x, y plane:
x, f(x)
1, 3
2, 5
I can interpolate them using Lagrange and find f(1.5), which result in 4. Thinking a little I managed to find a way to discover the coefficients of the equation:
void l1Coefficients(const vector<double> &x, const vector<double> &y) {
double a0 = y[0]/(x[0]-x[1]);
double a1 = y[1]/(x[1]-x[0]);
double b0 = (-x[1]*y[0])/(x[0]-x[1]);
double b1 = (-x[0]*y[1])/(x[1]-x[0]);
double a = a0 + a1;
double b = b0 + b1;
cout << "P1(x) = " << a << "x +" << b << endl;
}
That gives me P1(x) = 2x +1.
Thinking a little more I was able to extend that to 2nd order equations. So, given the points:
1, 1
2, 4
3, 9
I found the equation P2(x) = 1x^2 +0x +0 with the following:
void l2Coefficients(const vector<double> &x, const vector<double> &y) {
double a0 = y[0] / ((x[0]-x[1])*(x[0]-x[2]));
double a1 = y[1] / ((x[1]-x[0])*(x[1]-x[2]));
double a2 = y[2] / ((x[2]-x[0])*(x[2]-x[1]));
double b0 = -(x[1]+x[2])*y[0] / ((x[0]-x[1])*(x[0]-x[2]));
double b1 = -(x[0]+x[2])*y[1] / ((x[1]-x[0])*(x[1]-x[2]));
double b2 = -(x[0]+x[1])*y[2] / ((x[2]-x[0])*(x[2]-x[1]));
double c0 = (x[1]*x[2])*y[0] / ((x[0]-x[1])*(x[0]-x[2]));
double c1 = (x[0]*x[2])*y[1] / ((x[1]-x[0])*(x[1]-x[2]));
double c2 = (x[0]*x[1])*y[2] / ((x[2]-x[0])*(x[2]-x[1]));
double a = a0 + a1 + a2;
double b = b0 + b1 + b2;
double c = c0 + c1 + c2;
cout << "P2(x) = " << a << "x^2 +" << b << "x +" << c << endl;
}
Working hard I actually was able to find the coefficients for equations of order up to 4th.
How to find the coefficients of order n equations? Where
Pn(x) = c_2x^2 + c_1x^1 + c_0x^0 + ...
It's a simple linear algebra problem.
We have a set of N samples of the form xk -> f(xk) and we know the general form of function f(x), which is:
f(x) = c0x0 + c1x1 + ... + cN-1xN-1
We want to find the coefficients c0 ... cN-1. To achieve that, we build a system of N equations of the form:
c0xk0 + c1xk1 + ... + cN-1xkN-1 = f(xk)
where k is the sample number. Since xk and f(xk) are constants rather than variables, we have a linear system of equations.
Expressed in terms of linear algebra, we have to solve:
Ac = b
where A is a Vandermonde matrix of powers of x and b is a vector of f(xk) values.
To solve such a system, you need a linear algebra library, such as Eigen. See here for example code.
The only thing that can go wrong with such an approach is the system of linear equations being under-determined, which will happen if your N samples can be fit with with a polynomial of degree less than N-1. In such a case you can still solve this system with Moore-Penrose pseudo inverse like this:
c = pinv(A)*b
Unfortunately, Eigen doesn't have a pinv() implementation, though it's pretty easy to code it by yourself in terms of Singular Value Decomposition (SVD).
I created a naive implementation of the matrix solution:
#include <iostream>
#include <vector>
#include <stdexcept>
class Matrix
{
private:
class RowIterator
{
public:
RowIterator(Matrix* mat, int rowNum) :_mat(mat), _rowNum(rowNum) {}
double& operator[] (int colNum) { return _mat->_data[_rowNum*_mat->_sizeX + colNum]; }
private:
Matrix* _mat;
int _rowNum;
};
int _sizeY, _sizeX;
std::vector<double> _data;
public:
Matrix(int sizeY, int sizeX) : _sizeY(sizeY), _sizeX(sizeX), _data(_sizeY*_sizeX){}
Matrix(std::vector<std::vector<double> > initList) : _sizeY(initList.size()), _sizeX(_sizeY>0 ? initList.begin()->size() : 0), _data()
{
_data.reserve(_sizeY*_sizeX);
for (const std::vector<double>& list : initList)
{
_data.insert(_data.end(), list.begin(), list.end());
}
}
RowIterator operator[] (int rowNum) { return RowIterator(this, rowNum); }
int getSize() { return _sizeX*_sizeY; }
int getSizeX() { return _sizeX; }
int getSizeY() { return _sizeY; }
Matrix reduce(int rowNum, int colNum)
{
Matrix mat(_sizeY-1, _sizeX-1);
int rowRem = 0;
for (int y = 0; y < _sizeY; y++)
{
if (rowNum == y)
{
rowRem = 1;
continue;
}
int colRem = 0;
for (int x = 0; x < _sizeX; x++)
{
if (colNum == x)
{
colRem = 1;
continue;
}
mat[y - rowRem][x - colRem] = (*this)[y][x];
}
}
return mat;
}
Matrix replaceCol(int colNum, std::vector<double> newCol)
{
Matrix mat = *this;
for (int y = 0; y < _sizeY; y++)
{
mat[y][colNum] = newCol[y];
}
return mat;
}
};
double solveMatrix(Matrix mat)
{
if (mat.getSizeX() != mat.getSizeY()) throw std::invalid_argument("Not square matrix");
if (mat.getSize() > 1)
{
double sum = 0.0;
int sign = 1;
for (int x = 0; x < mat.getSizeX(); x++)
{
sum += sign * mat[0][x] * solveMatrix(mat.reduce(0, x));
sign = -sign;
}
return sum;
}
return mat[0][0];
}
std::vector<double> solveEq(std::vector< std::pair<double, double> > points)
{
std::vector<std::vector<double> > xes(points.size());
for (int i = 0; i<points.size(); i++)
{
xes[i].push_back(1);
for (int j = 1; j<points.size(); j++)
{
xes[i].push_back(xes[i].back() * points[i].first);
}
}
Matrix mat(xes);
std::vector<double> ys(points.size());
for (int i = 0; i < points.size(); i++)
{
ys[i] = points[i].second;
}
double w = solveMatrix(mat);
std::vector<double> result(points.size(), 0.0);
if(w!=0)
for (int i = 0; i < ys.size(); i++)
{
result[i] = solveMatrix(mat.replaceCol(i, ys));
result[i] /= w;
}
return result;
}
void printCoe(std::vector<double> coe)
{
std::cout << "f(x)=";
bool notFirstSign = false;
for (int i = coe.size() - 1; i >= 0; i--)
{
if (coe[i] != 0.0)
{
if (coe[i] >= 0.0 && notFirstSign)
std::cout << "+";
notFirstSign = true;
if (coe[i] != 1.0)
if (coe[i] == -1.0)
std::cout << "-";
else
std::cout << coe[i];
if (i == 1)
std::cout << "x";
if (i>1)
std::cout << "x^" << i;
}
}
std::cout << std::endl;
}
int main()
{
std::vector< std::pair<double, double> > points1 = { {3,31}, {6,94}, {4,48}, {0,4} };
std::vector<double> coe = solveEq(points1);
printCoe(coe);
std::vector< std::pair<double, double> > points2 = { { 0,0 },{ 1,-1 },{ 2,-16 },{ 3,-81 },{ 4,-256 } };
printCoe(solveEq(points2));
printCoe(solveEq({ { 0,0 },{ 1,1 },{ 2,8 },{ 3,27 } }));
std::cin.ignore();
return 0;
}

How to change 4D dynamic allocated array into 1D vector?

this is a part of my original code, the code is too big to put it all in here,
anyway my question is only related to Sads 4D matrix,
I don't want to use the int**** like it was suggested to me in my previous question
int main()
{
//4D matrix
int**** Sads = new int***[inputImage->HeightLines];
for (size_t i = 0; i < inputImage->HeightLines; i++)
{
Sads[i] = new int**[inputImage->WidthColumns];
for (size_t j = 0; j < inputImage->WidthColumns; j++)
{
Sads[i][j] = new int*[W_SIZE];
for (size_t k = 0; k < W_SIZE; k++)
{
Sads[i][j][k] = new int[W_SIZE];
}
}
}
ProcessRowsLoop(20, 1904, Sads);
}
void ProcessRowsLoop(int m_support, int m_height, int**** sads)
{
for (int row_in = m_support - 1; row_in < m_Height_in; row_in += BNLM_OUT_SZ)
{
ProcessRow( &Sads[indexRow]);
}
}
void ProcessRow(int**** sads)
{
int m_SAD_00[W_SIZE][W_SIZE];
int m_SAD_01[W_SIZE][W_SIZE];
int m_SAD_10[W_SIZE][W_SIZE];
int m_SAD_11[W_SIZE][W_SIZE];
RunAlgo(m_support, m_SAD_00, m_SAD_01, m_SAD_10, m_SAD_11, m_CP_00, m_CP_01, m_CP_10, m_CP_11, m_ColumnSADUp, m_ColumnSADDown);
for (size_t i = 0; i < W_SIZE; i++)
{
for (size_t j = 0; j < W_SIZE; j++)
{
Sads[0][m_col_out][i][j] = (m_SAD_00[i][j] + color_penalty_weight * m_CP_00[i][j]) / (sqrt(m_sigma_patch[0][0] / pow(mnm, 2)));
Sads[0][m_col_out + 1][i][j] = (m_SAD_01[i][j] + color_penalty_weight * m_CP_01[i][j]) / (sqrt(m_sigma_patch[0][1] / pow(mnm, 2)));
Sads[1][m_col_out][i][j] = (m_SAD_10[i][j] + color_penalty_weight + m_CP_10[i][j]) / (sqrt(m_sigma_patch[1][0] / pow(mnm, 2)));
Sads[1][m_col_out + 1][i][j] = (m_SAD_11[i][j] + color_penalty_weight + m_CP_11[i][j]) / (sqrt(m_sigma_patch[1][1] / pow(mnm, 2)));
}
}
}
In my new code I would like to replace the 4D matrix int**** Sads, with
struct VectorFourD
{
private:
int _width, _height;
int _w_size;
std::vector<int> _vec;
public:
VectorFourD(int width, int height, int size) : _width(width), _height(height), _w_size(size), _vec(totalSize())
{
}
auto totalSize() const-> int
{
return _width * _height * _w_size * _w_size;
}
int* at(int a)
{
return _vec.data() + (a * _height * _w_size * _w_size);
}
int* at(int a, int b)
{
return at(a) + (b * _w_size * _w_size);
}
int *at(int a, int b, int c)
{
return at(a, b) + (c* _w_size);
}
int& at(int a, int b, int c, int d)
{
return *(at(a, b, c) + d);
}
};
you can see that i'm iterating two lines at the same time in the function processrow()
running over
Sads[0][m_col_out][i][j], Sads[0][m_col_out + 1][i][j],
Sads[1][m_col_out][i][j], Sads[1][m_col_out + 1][i][j]
at the same time, my question is how do I change my code to work with the new 4dvector for example
int main()
{
VectorFourD SadsVec = VectorFourD(inputImage->HeightLines, inputImage->WidthColumns, W_SIZE);
ProcessRowsLoop(20, 1904, SadsVec);
}
also change the function void ProcessRowsLoop(int m_support, int m_height, VectorFourD* SadsVec)
but i don't know how to continue from here, can you please help?

Runtime error in c++ when analysing time [closed]

Closed. This question needs debugging details. It is not currently accepting answers.
Edit the question to include desired behavior, a specific problem or error, and the shortest code necessary to reproduce the problem. This will help others answer the question.
Closed 6 years ago.
Improve this question
I'm trying to check how much time passes with each 3 solutions for a problem, but sometimes I get a runtime error and can't see the passed time for 3rd solution, but sometimes it works. I think the solutions.h file is correct but i put it here anyway.
#include <iostream>
#include <cstdlib>
#include <ctime>
#include "solutions.h"
using namespace std;
int main()
{
cout << "Hello world!" << endl;
int* input1 = new int[10000];
int* input2 = new int[20000];
int* input3 = new int[40000];
int* input4 = new int[80000];
int* input5 = new int[100000];
for(int i = 0; i<100000; i++)
{
input1[i]= rand();
input2[i]= rand();
input3[i]= rand();
input4[i]= rand();
input5[i]= rand();
}
int* output1= new int[1000];
double duration;
clock_t startTime1 = clock();
solution1(input1,10000,1000,output1);
duration = 1000 * double( clock() - startTime1 ) / CLOCKS_PER_SEC;
cout << "Solution 1 with 10000 inputs took " << duration << " milliseconds." << endl;
startTime1 = clock();
solution2(input1,10000,1000,output1);
duration = 1000 * double( clock() - startTime1 ) / CLOCKS_PER_SEC;
cout << "Solution 2 with 10000 inputs took " << duration<< " milliseconds." << endl;
startTime1 = clock();
solution3(input1,10000,1000,output1);
duration = 1000 * double( clock() - startTime1 ) / CLOCKS_PER_SEC;
cout << "Solution 3 with 10000 inputs took " << duration << " milliseconds." << endl<<endl<<endl;
return 0;
}
And the solutions.h is
#ifndef SOLUTIONS_H_INCLUDED
#define SOLUTIONS_H_INCLUDED
#include <cmath>
void solution1( int input[], const int n, const int k, int output[] );
void solution2( int input[], const int n, const int k, int output[] );
void solution3( int input[], const int n, const int k, int output[] );
void swap( int &n1, int &n2 ) {
int temp = n1;
n1 = n2;
n2 = temp;
}
void solution1( int input[], const int n, const int k, int output[] ) {
int maxIndex, maxValue;
for( int i = 0; i < k; i++ ) {
maxIndex = i;
maxValue = input[i];
for( int j = i+1; j < n; j++ ) {
if( input[j] >= maxValue ) {
maxIndex = j;
maxValue = input[ j ];
}
}
swap( input[i], input[maxIndex] );
output[i] = input[i];
}
}
int partition( int input[], int p, int r ) {
int x = input[ r ], i = p - 1;
for( int j = p; j < r; j++ ) {
if( input[ j ] >= x ) {
i = i + 1;
swap( input[i], input[j] );
}
}
swap( input[i+1], input[r] );
return i + 1;
}
void quickSort( int input[], int p, int r ) {
int q;
if( p < r ) {
q = partition( input, p, r );
quickSort( input, p, q - 1 );
quickSort( input, q + 1, r );
}
}
void solution2( int input[], const int n, const int k, int output[] ) {
quickSort( input, 0, n - 1 );
for( int i = 0; i < k; i++ ) {
output[i] = input[i];
}
}
int partition2( int input[], int a, int p, int r ) {
int x = a, i = p - 1;
for( int j = p; j < r; j++ ) {
if( input[ j ] == x ) {
swap( input[ j ], input[ r ] );
}
if( input[ j ] >= x ) {
i = i + 1;
swap( input[i], input[j] );
}
}
swap( input[ i + 1 ], input[ r ] );
return i + 1;
}
void quickSort2( int input[], int p, int r ) {
int q;
if( p < r ) {
q = partition2( input, input[ r ], p, r );
quickSort2( input, p, q - 1 );
quickSort2( input, q + 1, r );
}
}
int findMin( int n1, int n2 ) {
if( n1 <= n2 )
return n1;
else
return n2;
}
int select( int input[], int n, int k, int start, int end, int flag ) {
if( n <= 5 ) {
quickSort2( input, start, end );
return input[ start + k - 1 ];
}
int i = start, numGroups = (int) ceil( ( double ) n / 5 ), numElements, j = 0;
int *medians = new int[numGroups];
while( i <= end ) {
numElements = findMin( 5, end - i + 1 );
medians[( i - start ) / 5] = select( input, numElements, (int) ceil( ( double ) numElements / 2 ), i, i + numElements - 1, 1 );
i = i + 5;
}
int M = select( medians, numGroups, (int) ceil( ( double ) numGroups / 2 ), 0, numGroups - 1, 1 );
delete[] medians;
if( flag == 1 )
return M;
int q = partition2( input, M, start, end );
int m = q - start + 1;
if( k == m )
return M;
else if( k < m )
return select( input, m - 1, k, start, q - 1, 0 );
else
return select( input, end - q, k - m, q + 1, end, 0 );
}
void solution3( int input[], const int n, const int k, int output[] ) {
select( input, n, k, 0, n - 1, 0 );
for( int i = 0; i < k; i++ )
output[i] = input[i];
}
#endif // SOLUTIONS_H_INCLUDED
Building your program with address sanitizer (clang++ clock.cxx -std=c++11 -O1 -g -fsanitize=address -fno-omit-frame-pointer) reveals the problem:
$ ./a.out
Hello world!
=================================================================
==8175==ERROR: AddressSanitizer: heap-buffer-overflow on address 0x62e00000a040 at pc 0x000104dbd912 bp 0x7fff5ae43970 sp 0x7fff5ae43968
WRITE of size 4 at 0x62e00000a040 thread T0
#0 0x104dbd911 in main clock.cxx:18
#1 0x7fff88cd85fc in start (libdyld.dylib+0x35fc)
#2 0x0 (<unknown module>)
0x62e00000a040 is located 0 bytes to the right of 40000-byte region [0x62e000000400,0x62e00000a040)
And there is your code:
int* input1 = new int[10000];
int* input2 = new int[20000];
int* input3 = new int[40000];
int* input4 = new int[80000];
int* input5 = new int[100000];
for(int i = 0; i<100000; i++)
{
input1[i]= rand();
input2[i]= rand();
input3[i]= rand();
input4[i]= rand();
input5[i]= rand();
}
As you can see, size of input1, input2, ..., input4 is 10K, 20K, 40K, 80K elements, but in the loop we are accessing to elements out of this array so this can lead to the heap corruption.
Process returned -1073741819 (0xC0000005)
This means "memory access violation" or SEGFAULT.
Hope this will help.

Passing Extra Data Into a Function

I am using the dlib optimization library for C++ specifically the following function:
template <
typename search_strategy_type,
typename stop_strategy_type,
typename funct,
typename funct_der,
typename T
>
double find_max (
search_strategy_type search_strategy,
stop_strategy_type stop_strategy,
const funct& f,
const funct_der& der,
T& x,
double max_f
);
Functions f and der are designed to take a vector of the data parameters being modified to obtain the maximum value of my function. However my function being maximized has four parameters (one is my dataset and the other is fixed by me). However I can't pass these as inputs to my f and der functions because of the format they are supposed to have. How do I get this data into my functions? I am currently trying the below (I hard set variable c but for vector xgrequ I read data from a file each time I process the function.
//Function to be minimized
double mleGPD(const column_vector& p)
{
std::ifstream infile("Xm-EVT.csv");
long double swapRet;
std::string closeStr;
std::vector<double> histRet;
//Read in historical swap data file
if (infile.is_open())
{
while (!infile.eof())
{
infile >> swapRet;
histRet.push_back(swapRet);
}
}
sort(histRet.begin(), histRet.end());
std::vector<double> negRet;
//separate out losses
for (unsigned c = 0; c < histRet.size(); c++)
{
if (histRet[c] < 0)
{
negRet.push_back(histRet[c]);
}
}
std::vector<double> absValRet;
//make all losses positive to fit with EVT convention
for (unsigned s = 0; s < negRet.size(); s++)
{
absValRet.push_back(abs(negRet[s]));
}
std::vector<double> xminusu, xmu, xgrequ;
int count = absValRet.size();
double uPercent = .9;
int uValIndex = ceil((1 - uPercent)*count);
int countAbove = count - uValIndex;
double c = (double)absValRet[uValIndex - 1];
//looking at returns above u
for (unsigned o = 0; o < uValIndex; ++o)
{
xmu.push_back(absValRet[o] - c);
if (xmu[o] >= 0)
{
xgrequ.push_back(absValRet[o]);
xminusu.push_back(xmu[o]);
}
}
double nu = xgrequ.size();
double sum = 0.0;
double a = p(0);
double b = p(1);
for (unsigned h = 0; h < nu; ++h)
{
sum += log((1 / b)*pow(1 - a*((xgrequ[h] - c) / b), -1 + (1 / a)));
}
return sum;
}
//Derivative of function to be minimized
const column_vector mleGPDDer(const column_vector& p)
{
std::ifstream infile("Xm-EVT.csv");
long double swapRet;
std::string closeStr;
std::vector<double> histRet;
//Read in historical swap data file
if (infile.is_open())
{
while (!infile.eof())
{
infile >> swapRet;
histRet.push_back(swapRet);
}
}
sort(histRet.begin(), histRet.end());
std::vector<double> negRet;
//separate out losses
for (unsigned c = 0; c < histRet.size(); c++)
{
if (histRet[c] < 0)
{
negRet.push_back(histRet[c]);
}
}
std::vector<double> absValRet;
//make all losses positive to fit with EVT convention
for (unsigned s = 0; s < negRet.size(); s++)
{
absValRet.push_back(abs(negRet[s]));
}
std::vector<double> xminusu, xmu, xgrequ;
int count = absValRet.size();
double uPercent = .9;
int uValIndex = ceil((1 - uPercent)*count);
int countAbove = count - uValIndex;
double c = (double)absValRet[uValIndex - 1];
//looking at returns above u
for (unsigned o = 0; o < uValIndex; ++o)
{
xmu.push_back(absValRet[o] - c);
if (xmu[o] >= 0)
{
xgrequ.push_back(absValRet[o]);
xminusu.push_back(xmu[o]);
}
}
column_vector res(2);
const double a = p(0);
const double b = p(1);
double nu = xgrequ.size();
double sum1 = 0.0;
double sum2 = 0.0;
for (unsigned h = 0; h < nu; ++h)
{
sum1 += ((xgrequ[h]-c)/b)/(1-a*((xgrequ[h]-c)/b));
sum2 += log(1 - a*((xgrequ[h] - c) / b));
}
res(0) = sum1;//df/da
res(1) = sum2;//df/db
return res;
}
Here is what my actual function call looks like:
//Dlib max finding
column_vector start(2);
start = .1, .1; //starting point for a and b
find_max(bfgs_search_strategy(), objective_delta_stop_strategy(1e-6), mleGPD, mleGPDDer, start,100);
std::cout << "solution" << start << std::endl;
This kind of API is very common. It's almost always possible to for f and der to any callable, not just static functions. that is, you can pass a custom class object with operator () to it.
For example
struct MyF {
//int m_state;
// or other state variables, such as
std::vector<double> m_histRet;
// (default constructors will do)
double operator()(const column_vector& p) const {
return some_function_of(p, m_state);
}
};
int main(){
. . .
MyF myf{42};
// or
MyF myf{someVectorContainingHistRet};
// then use myf as you would have used mleGPD
}
You need to initiate MyF and MyDer with the same state (std::vector<double> histRet I presume.) Either as copies or (const) references to the same state.
Edit: More full example:
struct MLGDPG_State {
std::vector<double> xgrequ;
// . . . and more you need in f or fder
}
MLGDPG_State makeMLGDPG_State(const std::string& filename){
std::ifstream infile(filename);
std::ifstream infile("Xm-EVT.csv");
long double swapRet;
std::string closeStr;
std::vector<double> histRet;
//Read in historical swap data file
if (infile.is_open())
{
while (!infile.eof())
{
infile >> swapRet;
histRet.push_back(swapRet);
}
}
sort(histRet.begin(), histRet.end());
std::vector<double> negRet;
//separate out losses
for (unsigned c = 0; c < histRet.size(); c++)
{
if (histRet[c] < 0)
{
negRet.push_back(histRet[c]);
}
}
std::vector<double> absValRet;
//make all losses positive to fit with EVT convention
for (unsigned s = 0; s < negRet.size(); s++)
{
absValRet.push_back(abs(negRet[s]));
}
std::vector<double> xminusu, xmu, xgrequ;
int count = absValRet.size();
double uPercent = .9;
int uValIndex = ceil((1 - uPercent)*count);
int countAbove = count - uValIndex;
double c = (double)absValRet[uValIndex - 1];
//looking at returns above u
for (unsigned o = 0; o < uValIndex; ++o)
{
xmu.push_back(absValRet[o] - c);
if (xmu[o] >= 0)
{
xgrequ.push_back(absValRet[o]);
xminusu.push_back(xmu[o]);
}
}
return {std::move(xgrequ)};
// Or just 'return MleGPD(xgrequ)' if you are scared of {} and move
}
//Functor Class, for ion to be minimized
struct MleGPD{
MLGDPG_State state;
double operator()(const column_vector& p) const {
auto mu = state.xgrequ.size();
double sum = 0.0;
double a = p(0);
double b = p(1);
for (unsigned h = 0; h < nu; ++h)
{
sum += log((1 / b)*pow(1 - a*((xgrequ[h] - c) / b), -1 + (1 / a)));
}
return sum;
};
Use the same pattern for a struct MleGPD_Derivative.
Usage:
const auto state = makeMLGDPG_State("Xm-EVT.csv");
const auto f = MleGPD{state};
const auto der = MleGPD_Derivative{state};
start = .1, .1; //starting point for a and b
find_max(bfgs_search_strategy(), objective_delta_stop_strategy(1e-6), f, der, start,100);
std::cout << "solution" << start << std::endl;
Note, that for simple structs like these, it's often fine to use the default constructors, copy constructor etc. Also note http://en.cppreference.com/w/cpp/language/aggregate_initialization

RSA Algorithm For Numbers and Char values

I'm not a programming expert. I'm new to cryptography and I had gone through the security algorithm RSA. I wrote the code like this:
#include<math.h>
#include<iostream>
#include<cmath>
#include<Windows.h>
using namespace std;
class rsacrypto
{
long publickey;
long privatekey;
long modl; //Modulus
public :
rsacrypto(); //To be used to just generate private and public keys.
rsacrypto(long &,long &,long &);//To be used just to generate private and public keys.
rsacrypto(long key,long modulus) // Should be used when a data is to be encrypted or decrypted using a key.
{
publickey = privatekey = key;
modl = modulus;
}
long ret_publickey()
{
return publickey;
}
long ret_privatekey()
{
return privatekey;
}
long ret_modulus()
{
return modl;
}
void encrypt(char *);
void decrypt(char *);
int genrndprimes(int, int);
int genrndnum(int, int);
int totient(int);
int gcd (int, int);
int mulinv(int, int);
boolean isPrime(long);
};
rsacrypto::rsacrypto()
{
long p1,p2; //Prime numbers
long n = 0; //Modulus
long phi =0; //Totient value.
long e = 0; //Public key exponent.
long d = 0; //Private key exponent.
p1 = genrndprimes(1,10);
Sleep(1000);
p2 = genrndprimes(1,10);
n = p1*p2;
phi = (p1-1)*(p2-1);
e = genrndnum(2,(phi-1));
while(gcd(e,phi)!=1)
{
e = genrndnum(2,(phi-1));
}
d = mulinv(e, phi);
cout<<"Public Key=("<<e<<","<<n<<")"<<"\n";
cout<<"Private Key=("<<d<<","<<n<<")"<<"\n";
privatekey = e;
publickey = d;
modl = n;
int m=11;
int en=0, decr=0;
//Encryption
en=(long)pow((double)m,d)%n;
cout<<en<<"\n";
//Decryption
decr=(long)pow((double)en,e)%n;
cout<<decr;
}
/*
void rsacrypto::encrypt(char *dat)
{
long siz = strlen(dat);
for(long i=0;i<siz;i++)
{
dat[i]=(long)pow((double)dat[i],publickey)%modl;
cout<<i<<"="<<dat[i]<<"\n";
}
}
void rsacrypto::decrypt(char *datn)
{
long sizz = strlen(datn);
for(long i=0;i<sizz;i++)
{
datn[i]=(long)pow((double)datn[i],privatekey)%modl;
}
cout<<datn;
}*/
int rsacrypto::mulinv(int a, int b)
{
int b0 = b, t, q;
int x0 = 0, x1 = 1;
if (b == 1) return 1;
while (a > 1) {
q = a / b;
t = b, b = a % b, a = t;
t = x0, x0 = x1 - q * x0, x1 = t;
}
if (x1 < 0) x1 += b0;
return x1;
}
int rsacrypto::genrndprimes(int a, int b){
long pivot;
do{
pivot= rand() % b + a;
if (isPrime(pivot))
return pivot;
} while (1==1);
}
boolean rsacrypto::isPrime(long pivot) {
if(pivot <= 1)
return false;
int root = sqrt((double)pivot);
//start at 2 because all numbers are divisible by 1
for(int x = 2; x <= root; x++) //You only need to check up to and including the root
{
if(pivot % x == 0)
return false;
}
return true;
}
int rsacrypto::genrndnum(int a, int b){
long pivot;
pivot= rand() % b + a;
return pivot;
}
int rsacrypto::gcd ( int a, int b )
{
int c;
while ( a != 0 ) {
c = a; a = b%a; b = c;
}
return b;
}
void main()
{
rsacrypto m;
system("pause");
}
But I would like to make this code work for hexa decimal values. I don't know how to do that. I'm not a programming expert. Any help would be sinscierly appreciated. Thankyou.
I guess your problem is to transfer the double values (hex decimal values) into char values first. Then you can use the existing code to encrypt/decrypt the char values.
There are two ways to convert the double values into char values:
Convert each double into two char's as its printable/readable form, e.g., 123.455 -> "123.456";
I refer some code from this discussion:
#include <sstream>
stringstream ss;
ss << myDouble;
const char* str = ss.str().c_str();
ss >> myOtherDouble;
Convert each double into two char's as its byte form;
Please see this discussion:
Use a union:
union {
double d[2];
char b[sizeof(double) * 2];
};
Or reinterpret_cast:
char* b = reinterpret_cast<double*>(d);
Now, after converting your double values into char values, we can directly utilize the existing code to encrypt our data.