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Upsilon/apps/probability/distribution/student_distribution.cpp
Yaya-Cout 169fb7404e Fix spelling (#128)
* Fix spelling in .cpp files

* Fix spelling in all files
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62 lines
1.9 KiB
C++

#include "student_distribution.h"
#include <poincare/regularized_incomplete_beta_function.h>
#include "helper.h"
#include <cmath>
namespace Probability {
float StudentDistribution::xMin() const {
return -xMax();
}
float StudentDistribution::xMax() const {
return 5.0f;
}
float StudentDistribution::yMax() const {
return std::exp(lnCoefficient()) * (1.0f + k_displayTopMarginRatio);
}
float StudentDistribution::evaluateAtAbscissa(float x) const {
const float d = m_parameter1;
return std::exp(lnCoefficient() - (d + 1.0f) / 2.0f * std::log(1.0f + x * x / d));
}
bool StudentDistribution::authorizedValueAtIndex(float x, int index) const {
return x >= FLT_EPSILON && x <= 200.0f; // We cannot draw the curve for x > 200 (coefficient() is too small)
}
double StudentDistribution::cumulativeDistributiveFunctionAtAbscissa(double x) const {
if (x == 0.0) {
return 0.5;
}
if (std::isinf(x)) {
return x > 0 ? 1.0 : 0.0;
}
/* TODO There are some computation errors, where the probability falsy jumps to 1.
* k = 0.001 and P(x < 42000000) (for 41000000 it is around 0.5)
* k = 0.01 and P(x < 8400000) (for 41000000 it is around 0.6) */
const double k = m_parameter1;
const double sqrtXSquaredPlusK = std::sqrt(x*x + k);
double t = (x + sqrtXSquaredPlusK) / (2.0 * sqrtXSquaredPlusK);
return Poincare::RegularizedIncompleteBetaFunction(k/2.0, k/2.0, t);
}
double StudentDistribution::cumulativeDistributiveInverseForProbability(double * probability) {
if (*probability == 0.5) {
return 0.0;
}
const double small = DBL_EPSILON;
const double big = 1E10;
double xmin = *probability < 0.5 ? -big : small;
double xmax = *probability < 0.5 ? -small : big;
return cumulativeDistributiveInverseForProbabilityUsingIncreasingFunctionRoot(probability, xmin, xmax);
}
float StudentDistribution::lnCoefficient() const {
const float k = m_parameter1;
return std::lgamma((k+1.0f)/2.0f) - std::lgamma(k/2.0f) - ((float)M_PI+k)/2.0f;
}
}