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[apps/probability] Comments to explain the 0.001 precision is proba

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Change-Id: Id5618802f9a08967b2fa0d68b35ff2a4f0b5a116
This commit is contained in:
Émilie Feral
2017-02-13 14:11:06 +01:00
parent 82f29ea2e4
commit 761be1c8c7
5 changed files with 5 additions and 3 deletions
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3
apps/probability/calculation/calculation.h
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@@ -17,6 +17,9 @@ public:
virtual float lowerBound();
virtual float upperBound();
protected:
/* Parameters in probability application are rounded to 3 decimals. This is
* due to the limited precision of some calculation (e. g. standard normal
* cumulative distributive function or inverse). */
constexpr static float k_precision = 0.001f;
virtual void compute(int indexKnownElement) = 0;
Law * m_law;

1
apps/probability/calculation/finite_integral_calculation.cpp
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@@ -32,7 +32,6 @@ const char * FiniteIntegralCalculation::legendForParameterAtIndex(int index) {
void FiniteIntegralCalculation::setParameterAtIndex(float f, int index) {
assert(index >= 0 && index < 3);
/* Parameters in probability application are rounder to 3 decimals */
float rf = roundf(f/k_precision)*k_precision;
if (index == 0) {
m_lowerBound = rf;

1
apps/probability/calculation/left_integral_calculation.cpp
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@@ -28,7 +28,6 @@ const char * LeftIntegralCalculation::legendForParameterAtIndex(int index) {
void LeftIntegralCalculation::setParameterAtIndex(float f, int index) {
assert(index >= 0 && index < 2);
/* Parameters in probability application are rounder to 3 decimals */
float rf = roundf(f/k_precision)*k_precision;
if (index == 0) {
m_upperBound = rf;

1
apps/probability/calculation/right_integral_calculation.cpp
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@@ -28,7 +28,6 @@ const char * RightIntegralCalculation::legendForParameterAtIndex(int index) {
void RightIntegralCalculation::setParameterAtIndex(float f, int index) {
assert(index >= 0 && index < 2);
/* Parameters in probability application are rounder to 3 decimals */
float rf = roundf(f/k_precision)*k_precision;
if (index == 0) {
m_lowerBound = rf;

2
apps/probability/law/normal_law.cpp
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@@ -107,6 +107,7 @@ float NormalLaw::standardNormalCumulativeDistributiveFunctionAtAbscissa(float ab
if (abscissa > k_boundStandardNormalDistribution) {
return 1.0f;
}
/* Waissi & Rossin's formula (error less than 0.0001) */
return 1.0f/(1.0f+expf(-sqrtf(M_PI)*(k_beta1*powf(abscissa,5)+k_beta2*powf(abscissa,3)+k_beta3*abscissa)));
}
@@ -120,6 +121,7 @@ float NormalLaw::standardNormalCumulativeDistributiveInverseForProbability(float
if (probability < 0.5f) {
return -standardNormalCumulativeDistributiveInverseForProbability(1-probability);
}
/* Soranzo & Epure (error less than 0.001) */
return (k_alpha3/logf(k_alpha2))*logf(1.0f - logf(-logf(probability)/logf(2.0f))/logf(k_alpha1));
}