Browse Source

added stub of analyser

master
Joshua Moerman 12 years ago
parent
commit
5ba18cd1d8
  1. 119
      AwesomeAttract0r.xcodeproj/project.pbxproj
  2. 22
      Logger.hpp
  3. 72
      aatester.cpp
  4. 47
      analyse.hpp
  5. 2
      kernels/Polynomial.hpp
  6. 4
      main.cpp

119
AwesomeAttract0r.xcodeproj/project.pbxproj

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42CA52C1151F93E40098800C /* aatester.cpp */,
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42CA52A7151F70F00098800C /* analyse.hpp */,
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42CA52BC151F93AB0098800C /* Projection.cpp in Sources */,
42CA52BD151F93AE0098800C /* Normalizer.cpp in Sources */,
42CA52BE151F93B30098800C /* AttractorKernel.cpp in Sources */,
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42CA52C2151F93E40098800C /* aatester.cpp in Sources */,
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@ -330,6 +397,50 @@
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22
Logger.hpp

@ -10,24 +10,24 @@
extern int verbose;
enum LoggingLevels {
LOG_ERROR,
LOG_INFO,
LOG_VERBOSE,
LOG_DEBUG
};
#define LogDebug(s, ...) \
if ( verbose >= 3 ) printf(s, ##__VA_ARGS__);
if ( verbose >= LOG_DEBUG ) printf(s, ##__VA_ARGS__);
#define LogMoreInfo(s, ...) \
if ( verbose >= 2 ) printf(s, ##__VA_ARGS__);
if ( verbose >= LOG_VERBOSE ) printf(s, ##__VA_ARGS__);
#define LogInfo(s, ...) \
if ( verbose >= 1 ) printf(s, ##__VA_ARGS__);
if ( verbose >= LOG_INFO ) printf(s, ##__VA_ARGS__);
#define LogError(s, ...) \
if ( verbose >= 0 ) { printf("%s, %s(), %d: ", __FILE__, __func__, __LINE__); printf(s, ##__VA_ARGS__); }
enum LoggingLevels {
LOG_ERROR,
LOG_INFO,
LOG_VERBOSE,
LOG_DEBUG
};
if ( verbose >= LOG_ERROR ) { printf("%s, %s(), %d: ", __FILE__, __func__, __LINE__); printf(s, ##__VA_ARGS__); }
/*
Imported from Astrant:

72
aatester.cpp

@ -0,0 +1,72 @@
//
// aatester.cpp
// AwesomeAttract0r
//
// Created by Joshua Moerman on 3/25/12.
// Copyright (c) 2012 Vadovas. All rights reserved.
//
#include <iostream>
#include <vector>
#include "Logger.hpp"
#include "analyse.hpp"
#define LOG(s, p) \
logger.start(s); \
p \
logger.stop()
int verbose = 0;
Logger logger(std::cout, LOG_VERBOSE);
inline double test(const int dimension, const double doubling, const double percentage){
LOG("making vector",
srand(time(0));
std::vector<double *> buffer(1000000);
);
LOG("making random data",
for(auto & p : buffer){
p = new double[dimension];
for(unsigned int i = 2;i < dimension; ++i){
p[i] = rand() / (double) RAND_MAX - 0.5;
}
p[0] = p[1]*p[1];
p[1] = std::sin(5.0*p[2]);
});
LOG("calculate fractal dimension",
double f = fractal_dimension(buffer.begin(), buffer.end(), dimension, doubling, percentage);
);
LOG("freeing data",
for(auto & p : buffer){
delete[] p;
p = 0;
});
return f;
}
int main(){
double percentages[] = {0.00015, 0.00010, 0.00006, 0.00004, 0.000015};
std::cout << "... |";
for(auto p : percentages) std::cout << "\t" << p;
std::cout << std::endl << "----------------------------------------------" << std::endl;
for (double doubling = 2.0; doubling <= 3.0; doubling += 0.1){
std::cout << doubling << " |";
for (auto p : percentages){
double sse = 0;
for (int i = 3; i <= 6; ++i) {
for(int j = 0; j < 20; ++j) {
double e = (i-2) - test(i, doubling, p);
sse += e*e;
}
}
std::cout << "\t" << sse;
}
std::cout << std::endl;
}
}

47
analyse.hpp

@ -0,0 +1,47 @@
//
// analyse.hpp
// AwesomeAttract0r
//
// Created by Joshua Moerman on 3/25/12.
// Copyright (c) 2012 Vadovas. All rights reserved.
//
#ifndef AwesomeAttract0r_analyse_hpp
#define AwesomeAttract0r_analyse_hpp
#include <cmath>
inline double distance_squared(double * p1, double * p2, size_t dimension){
double s = 0;
for(unsigned int i = 0; i < dimension; ++i){
s += (p1[i] - p2[i]) * (p1[i] - p2[i]);
}
return s;
}
template <typename Iterator>
double fractal_dimension(Iterator begin, Iterator end, size_t const dimension, const double doubling = 2.4, const double percentage = 0.00004) {
const double size = std::pow(percentage, 1.0 / 3.0);
//const double size = std::pow(percentage, 1.0 / dimension);
const double totalSize = std::sqrt(dimension);
unsigned int counts[2] = {};
double r = size * totalSize;
while(begin != end){
auto x0 = *begin++;
for(unsigned int i = 0; i < 200 && begin != end; ++i){
auto x = *begin++;
auto d = distance_squared(x, x0, dimension);
if( d <= r*r )
++counts[0];
if( d <= doubling*doubling*r*r )
++counts[1];
}
}
return std::log((double) counts[1] / (double) counts[0]) / std::log(doubling);
}
#endif

2
kernels/Polynomial.hpp

@ -3,7 +3,7 @@
#include "../AttractorKernel.hpp"
unsigned int calculateNumberOfParameters(const unsigned int dimension, const unsigned int orde) {
inline unsigned int calculateNumberOfParameters(const unsigned int dimension, const unsigned int orde) {
double n_coef = orde + 1;
for(unsigned int i = 2; i <= dimension; i++) {
n_coef = n_coef*(orde + i)/(i - 1);

4
main.cpp

@ -17,7 +17,7 @@ namespace po = boost::program_options;
#include "render.hpp"
int verbose = 4;
int verbose = LOG_DEBUG;
Logger logger(std::cout, LOG_VERBOSE);
std::string generate_filename(){
@ -31,7 +31,7 @@ std::string generate_filename(){
void save_stf(stfu::node & stf_output, std::string const & filename){
stf_output.addValue("version") = __DATE__" "__TIME__;
stf_output.addValue("notes") = "This is the version with `cheap` blur and random colours";
stf_output.addValue("notes") = "This is the version with somewhat better blur (circle) and random colours";
std::string path(filename + ".stf");
std::ofstream file(path.c_str());
file << stf_output << std::endl;