Files
Upsilon/apps/probability/law/poisson_law.cpp
Émilie Feral fff1371133 [apps/probability] Clip parameters
Change-Id: Ifb966b97afb15b2e876c506aff097999d012ec17
2017-03-29 11:35:30 +02:00

74 lines
1.5 KiB
C++

#include "poisson_law.h"
#include <assert.h>
#include <math.h>
#include <ion.h>
namespace Probability {
PoissonLaw::PoissonLaw() :
OneParameterLaw(4.0f)
{
}
I18n::Message PoissonLaw::title() {
return I18n::Message::PoissonLaw;
}
Law::Type PoissonLaw::type() const {
return Type::Poisson;
}
bool PoissonLaw::isContinuous() const {
return false;
}
I18n::Message PoissonLaw::parameterNameAtIndex(int index) {
assert(index == 0);
return I18n::Message::Lambda;
}
I18n::Message PoissonLaw::parameterDefinitionAtIndex(int index) {
assert(index == 0);
return I18n::Message::LambdaPoissonDefinition;
}
float PoissonLaw::xMin() {
return -k_displayLeftMarginRatio*xMax();
}
float PoissonLaw::xMax() {
assert(m_parameter1 != 0);
return (m_parameter1 + 5.0f*sqrtf(m_parameter1))*(1.0f+k_displayRightMarginRatio);
}
float PoissonLaw::yMin() {
return - k_displayBottomMarginRatio * yMax();
}
float PoissonLaw::yMax() {
int maxAbscissa = (int)m_parameter1;
assert(maxAbscissa >= 0.0f);
float result = evaluateAtAbscissa(maxAbscissa);
if (result <= 0.0f) {
result = 1.0f;
}
return result*(1.0f+ k_displayTopMarginRatio);
}
float PoissonLaw::evaluateAtAbscissa(float x) const {
if (x < 0.0f) {
return NAN;
}
float lResult = -m_parameter1+(int)x*logf(m_parameter1)-lgammaf((int)x+1);
return expf(lResult);
}
bool PoissonLaw::authorizedValueAtIndex(float x, int index) const {
if (x <= 0.0f || x > 999.0f) {
return false;
}
return true;
}
}