I'm trying to create a plot of the light distribution. I want to do exactly what step one of this question asks: Statistical analysis on Bell shaped (Gaussian) curve.
Right now I have an array of values. I want the index number of the array element to be on the x axis of the plot and the actual value stored at the index to be the on the y axis. I'm trying to do this using OpenCV but OpenCV's histogram functions only seem to plot the frequency of values and nothing else.
I have found cvplot useful, although very limited: http://code.google.com/p/cvplot/
Also it is fairly easy to embed python and feed matplotlib it commands from c++. I have used this to produce nice looking graphs, which you definitely won't get from cvplot. Here is a quick and dirty class, followed by an example, but no doco (of course there is a heap of doco for matplotlib):
// Interface to Python's Matplotlib
#include <Python.h>
using namespace std;
class PyPlot
{
private:
// Singleton Constructor
PyPlot() : locked(false)
{
Py_SetProgramName("argv[0]"); /* optional but recommended */
Py_Initialize();
PyRun_SimpleString(
"import numpy as np\n"
"import matplotlib.pyplot as plt\n"
"import matplotlib.text as text\n"
"import matplotlib as mpl\n"
);
}
~PyPlot()
{
Py_Finalize();
}
// prevent copies of singleton
PyPlot(PyPlot const&); // No implemention
void operator=(PyPlot const&); // No implemention
string to_string(double dval)
{
return std::to_string(long double(dval));
}
string to_string(int ival)
{
return std::to_string(long long(ival));
}
public:
// get singleton instance
static PyPlot& getInstance()
{
static PyPlot instance; // Guaranteed to be destroyed.
// Instantiated on first use.
return instance;
}
// prevent reentry to Matplotlib's show()
bool locked;
inline void print_time()
{
PyRun_SimpleString("from time import time,ctime\n"
"print 'Today is',ctime(time())\n");
}
inline void exec(string command)
{
PyRun_SimpleString(command.c_str());
}
inline void show()
{
locked = true;
exec("plt.show()\n");
locked = false;
}
inline void title(string s, string args = "")
{
string command = "plt.title(r'" + s + "'";
if(args.length() != 0)
command += ", " + args;
command += ")\n";
exec(command);
}
inline void xlabel(string s, string args = "")
{
string command = "plt.xlabel(r'" + s + "'";
if(args.length() != 0)
command += ", " + args;
command += ")\n";
exec(command);
}
inline void ylabel(string s, string args = "")
{
string command = "plt.ylabel(r'" + s + "'";
if(args.length() != 0)
command += ", " + args;
command += ")\n";
exec(command);
}
inline void legend(string args = "")
{
string command = "plt.legend(";
if(args.length() != 0)
command += args;
command += ")\n";
exec(command);
}
template <typename T>
inline void define_vector(string name, vector<T> values)
{
string command = name + " = [";
vector<T>::iterator it;
for(it = values.begin(); it != values.end(); it++)
{
command += to_string(*it);
if(it + 1 != values.end())
command += ", ";
}
command += "]\n";
exec(command);
}
template <typename T>
inline void plot(vector<T> x, vector<T> y, string args = "")
{
define_vector("x", x);
define_vector("y", y);
string command = "plt.plot(x, y";
if(args.length() != 0)
command += ", " + args;
command += ")\n";
exec(command);
}
template <typename T>
inline void plot(vector<T> y, string args = "")
{
define_vector("y", y);
vector<int> x;
for(unsigned int i = 0; i < y.size(); i ++)
x.push_back(i);
define_vector("x", x);
string command = "plt.plot(x, y";
if(args.length() != 0)
command += ", " + args;
command += ")\n";
exec(command);
}
inline void example()
{
double xa[] = {0.5, 0.7, 0.9 , 1.3 , 1.7 , 1.8};
vector<double> x;
x.assign(xa, xa + 6);
double ya[] = {0.1 , 0.2 , 0.75 , 1.5 , 2.1 , 2.4};
vector<double> y;
y.assign(ya, ya + 6);
plot(x, y);
plot(x, y, "'go', markersize=20");
exec(
"plt.xticks( np.arange(0,3) )\n"
"plt.yticks( np.arange(0,2.5,0.2) )\n"
);
xlabel("x axis");
ylabel("y axis");
title("My Plot Example");
show();
}
};
#endif
Then use it like this:
PyPlot &plt = PyPlot::getInstance();
std::vector<int> values;
plt.exec("mpl.rcParams['font.family']='Times New Roman'\n"
"mpl.rcParams['lines.linewidth'] = 2\n"
"mpl.rcParams['axes.linewidth'] = 3\n"
"mpl.rc('xtick', labelsize=12)\n"
"mpl.rc('ytick', labelsize=12)\n"
"ax = plt.gca()\n"
"ax.set_ylim(0, 100)\n"
);
plt.plot(values, "'go-', label='values'");
plt.ylabel("Value", "fontsize=14");
plt.xlabel("Index", "fontsize=14");
plt.show();
This has the matplotlib commands need to to create a histogram: http://matplotlib.org/examples/api/histogram_demo.html
And of course you need Python installed. All works fine with Python 2.7.3 / Win 7/ VS2010/ OpenCV 2.4.4
