law.cpp
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#include "law.h"
#include <cmath>
#include <float.h>
namespace Probability {
Law::Law() :
Shared::CurveViewRange()
{
}
float Law::xGridUnit() {
return computeGridUnit(Axis::X, xMin(), xMax());
}
double Law::cumulativeDistributiveFunctionAtAbscissa(double x) const {
if (!isContinuous()) {
int end = std::round(x);
double result = 0.0;
for (int k = 0; k <=end; k++) {
result += evaluateAtDiscreteAbscissa(k);
/* Avoid too long loop */
if (k > k_maxNumberOfOperations) {
break;
}
if (result >= k_maxProbability) {
result = 1.0;
break;
}
}
return result;
}
return 0.0;
}
double Law::rightIntegralFromAbscissa(double x) const {
if (isContinuous()) {
return 1.0 - cumulativeDistributiveFunctionAtAbscissa(x);
}
return 1.0 - cumulativeDistributiveFunctionAtAbscissa(x-1.0);
}
double Law::finiteIntegralBetweenAbscissas(double a, double b) const {
if (b < a) {
return 0.0;
}
if (isContinuous()) {
return cumulativeDistributiveFunctionAtAbscissa(b) - cumulativeDistributiveFunctionAtAbscissa(a);
}
int start = std::round(a);
int end = std::round(b);
double result = 0.0;
for (int k = start; k <=end; k++) {
result += evaluateAtDiscreteAbscissa(k);
/* Avoid too long loop */
if (k-start > k_maxNumberOfOperations) {
break;
}
if (result >= k_maxProbability) {
result = 1.0;
break;
}
}
return result;
}
double Law::cumulativeDistributiveInverseForProbability(double * probability) {
if (*probability >= 1.0) {
return INFINITY;
}
if (isContinuous()) {
return 0.0;
}
if (*probability <= 0.0) {
return 0.0;
}
double p = 0.0;
int k = 0;
double delta = 0.0;
do {
delta = std::fabs(*probability-p);
p += evaluateAtDiscreteAbscissa(k++);
if (p >= k_maxProbability && std::fabs(*probability-1.0) <= delta) {
*probability = 1.0;
return k-1.0;
}
} while (std::fabs(*probability-p) <= delta && k < k_maxNumberOfOperations && p < 1.0);
p -= evaluateAtDiscreteAbscissa(--k);
if (k == k_maxNumberOfOperations) {
*probability = 1.0;
return INFINITY;
}
*probability = p;
if (std::isnan(*probability)) {
return NAN;
}
return k-1.0;
}
double Law::rightIntegralInverseForProbability(double * probability) {
if (isContinuous()) {
double f = 1.0 - *probability;
return cumulativeDistributiveInverseForProbability(&f);
}
if (*probability >= 1.0) {
return 0.0;
}
if (*probability <= 0.0) {
return INFINITY;
}
double p = 0.0;
int k = 0;
double delta = 0.0;
do {
delta = std::fabs(1.0-*probability-p);
p += evaluateAtDiscreteAbscissa(k++);
if (p >= k_maxProbability && std::fabs(1.0-*probability-p) <= delta) {
*probability = 0.0;
return k;
}
} while (std::fabs(1.0-*probability-p) <= delta && k < k_maxNumberOfOperations);
if (k == k_maxNumberOfOperations) {
*probability = 1.0;
return INFINITY;
}
*probability = 1.0 - (p - evaluateAtDiscreteAbscissa(k-1));
if (std::isnan(*probability)) {
return NAN;
}
return k-1.0;
}
double Law::evaluateAtDiscreteAbscissa(int k) const {
return 0.0;
}
}