[Toolbox] Changed the required parameters for normal_distributions

Changed the parameter σ2 to σ. This is now consistant with the
probability app

Change-Id: I96101ba158cebef972e536cfa5cc1b2da71b543d

apps/shared.universal.i18n

@@ -114,7 +114,7 @@ IntCommand = "int(\x11,x,\x11,\x11)"
 IntCommandWithArg = "int(f(x),x,a,b)"
 InvBinomialCommandWithArg = "invbinom(a,n,p)"
 InverseCommandWithArg = "inverse(M)"
-InvNormCommandWithArg = "invnorm(a,μ,σ2)"
+InvNormCommandWithArg = "invnorm(a,μ,σ)"
 InvSortCommandWithArg = "sort>(L)"
 K = "k"
 Lambda = "λ"
@@ -127,9 +127,9 @@ MaxCommandWithArg = "max(L)"
 MinCommandWithArg = "min(L)"
 Mu = "μ"
 N = "n"
-NormCDFCommandWithArg = "normcdf(a,μ,σ2)"
-NormCDF2CommandWithArg = "normcdf2(a,b,μ,σ2)"
-NormPDFCommandWithArg = "normpdf(x,μ,σ2)"
+NormCDFCommandWithArg = "normcdf(a,μ,σ)"
+NormCDF2CommandWithArg = "normcdf2(a,b,μ,σ)"
+NormPDFCommandWithArg = "normpdf(x,μ,σ)"
 PermuteCommandWithArg = "permute(n,r)"
 P = "p"
 Prediction95CommandWithArg = "prediction95(p,n)"

apps/toolbox.de.i18n

@@ -155,10 +155,10 @@ RandomAndApproximation = "Zufall und Näherung"
 RandomFloat = "Dezimalzahl in [0,1]"
 RandomInteger = "Zufällige ganze Zahl in [a,b]"
 PrimeFactorDecomposition = "Primfaktorzerlegung"
-NormCDF = "P(X<a) wo X folgt N(μ,σ2)"
-NormCDF2 = "P(a<X<b) wo X folgt N(μ,σ2)"
-InvNorm = "m wo P(X<m)=a und X folgt N(μ,σ2)"
-NormPDF = "Wahrscheinlichkeitsdichte N(μ,σ2)"
+NormCDF = "P(X<a) wo X folgt N(μ,σ)"
+NormCDF2 = "P(a<X<b) wo X folgt N(μ,σ)"
+InvNorm = "m wo P(X<m)=a und X folgt N(μ,σ)"
+NormPDF = "Wahrscheinlichkeitsdichte N(μ,σ)"
 BinomialPDF = "P(X=m) wo X folgt B(n,p)"
 BinomialCDF = "P(X<=m) wo X folgt B(n,p)"
 InvBinomial = "m wo P(X<=m)=a und X folgt B(n,p)"

apps/toolbox.en.i18n

@@ -155,10 +155,10 @@ RandomAndApproximation = "Random and approximation"
 RandomFloat = "Floating point number in [0,1["
 RandomInteger = "Random integer in [a,b]"
 PrimeFactorDecomposition = "Integer factorization"
-NormCDF = "P(X<a) where X follows N(μ,σ2)"
-NormCDF2 = "P(a<X<b) where X follows N(μ,σ2)"
-InvNorm = "m where P(X<m)=a, X follows N(μ,σ2)"
-NormPDF = "Probability density of N(μ,σ2)"
+NormCDF = "P(X<a) where X follows N(μ,σ)"
+NormCDF2 = "P(a<X<b) where X follows N(μ,σ)"
+InvNorm = "m where P(X<m)=a, X follows N(μ,σ)"
+NormPDF = "Probability density of N(μ,σ)"
 BinomialPDF = "P(X=m) where X follows B(n,p)"
 BinomialCDF = "P(X<=m) where X follows B(n,p)"
 InvBinomial = "m where P(X<=m)=a, X follows B(n,p)"

apps/toolbox.es.i18n

@@ -155,10 +155,10 @@ RandomAndApproximation = "Aleatorio y aproximación"
 RandomFloat = "Número decimal en [0,1["
 RandomInteger = "Entero aleatorio en [a,b]"
 PrimeFactorDecomposition = "Factorización de enteros"
-NormCDF = "P(X<a) donde X sigue N(μ,σ2)"
-NormCDF2 = "P(a<X<b) donde X sigue N(μ,σ2)"
-InvNorm = "m donde P(X<m)=a y X sigue N(μ,σ2)"
-NormPDF = "Densidad de probabilidad de N(μ,σ2)"
+NormCDF = "P(X<a) donde X sigue N(μ,σ)"
+NormCDF2 = "P(a<X<b) donde X sigue N(μ,σ)"
+InvNorm = "m donde P(X<m)=a y X sigue N(μ,σ)"
+NormPDF = "Densidad de probabilidad de N(μ,σ)"
 BinomialPDF = "P(X=m) donde X sigue B(n,p)"
 BinomialCDF = "P(X<=m) donde X sigue B(n,p)"
 InvBinomial = "m donde P(X<=m)=a y X sigue B(n,p)"

apps/toolbox.fr.i18n

@@ -155,10 +155,10 @@ RandomAndApproximation = "Aléatoire et approximation"
 RandomFloat = "Nombre décimal dans [0;1["
 RandomInteger = "Entier aléatoire dans [a;b]"
 PrimeFactorDecomposition = "Décomposition en facteurs premiers"
-NormCDF = "P(X<a) où X suit N(μ,σ2)"
-NormCDF2 = "P(a<X<b) où X suit N(μ,σ2)"
-InvNorm = "m où P(X<m)=a et X suit N(μ,σ2)"
-NormPDF = "Fonction densité N(μ,σ2)"
+NormCDF = "P(X<a) où X suit N(μ,σ)"
+NormCDF2 = "P(a<X<b) où X suit N(μ,σ)"
+InvNorm = "m où P(X<m)=a et X suit N(μ,σ)"
+NormPDF = "Fonction densité N(μ,σ)"
 BinomialPDF = "P(X=m) où X suit B(n,p)"
 BinomialCDF = "P(X<=m) où X suit B(n,p)"
 InvBinomial = "m où P(X<=m)=a et X suit B(n,p)"

apps/toolbox.it.i18n

@@ -155,10 +155,10 @@ RandomAndApproximation = "Aleatorietà e approssimazione"
 RandomFloat = "Decimale aleatorio tra [0,1["
 RandomInteger = "Intero aleatorio tra [a,b]"
 PrimeFactorDecomposition = "Scomposizione in fattori primi"
-NormCDF = "P(X<a) dove X segue N(μ,σ2)"
-NormCDF2 = "P(a<X<b) dove X segue N(μ,σ2)"
-InvNorm = "m dove P(X<m)=a e X segue N(μ,σ2)"
-NormPDF = "Funzione di densità N(μ,σ2)"
+NormCDF = "P(X<a) dove X segue N(μ,)"
+NormCDF2 = "P(a<X<b) dove X segue N(μ,σ)"
+InvNorm = "m dove P(X<m)=a e X segue N(μ,σ)"
+NormPDF = "Funzione di densità N(μ,σ)"
 BinomialPDF = "P(X=m) dove X segue B(n,p)"
 BinomialCDF = "P(X<=m) dove X segue B(n,p)"
 InvBinomial = "m dove P(X<=m)=a e X segue B(n,p)"

apps/toolbox.nl.i18n

@@ -155,10 +155,10 @@ RandomAndApproximation = "Willekeurig en benadering"
 RandomFloat = "Zwevendekommagetal in [0,1["
 RandomInteger = "Willekeurig geheel getal in [a,b]"
 PrimeFactorDecomposition = "Ontbinden in factoren"
-NormCDF = "P(X<a) waar X volgt N(μ,σ2)"
-NormCDF2 = "P(a<X<b) waar X volgt N(μ,σ2)"
-InvNorm = "m waar P(X<m)=a, X volgt N(μ,σ2)"
-NormPDF = "Kansdichtheid van N(μ,σ2)"
+NormCDF = "P(X<a) waar X volgt N(μ,)"
+NormCDF2 = "P(a<X<b) waar X volgt N(μ,σ)"
+InvNorm = "m waar P(X<m)=a, X volgt N(μ,σ)"
+NormPDF = "Kansdichtheid van N(μ,σ)"
 BinomialPDF = "P(X=m) waar X volgt B(n,p)"
 BinomialCDF = "P(X<=m) waar X volgt B(n,p)"
 InvBinomial = "m waar P(X<=m)=a, X volgt B(n,p)"

apps/toolbox.pt.i18n

@@ -155,10 +155,10 @@ RandomAndApproximation = "Aleatório e aproximação"
 RandomFloat = "Número decimal em [0,1["
 RandomInteger = "Inteiro aleatório em [a,b]"
 PrimeFactorDecomposition = "Fatorização de inteiros"
-NormCDF = "P(X<a) onde X segue N(μ,σ2)"
-NormCDF2 = "P(a<X<b) onde X segue N(μ,σ2)"
-InvNorm = "m onde P(X<m)=a e X segue N(μ,σ2)"
-NormPDF = "Densidade de probabilidade de N(μ,σ2)"
+NormCDF = "P(X<a) onde X segue N(μ,σ)"
+NormCDF2 = "P(a<X<b) onde X segue N(μ,σ)"
+InvNorm = "m onde P(X<m)=a e X segue N(μ,σ)"
+NormPDF = "Densidade de probabilidade de N(μ,σ)"
 BinomialPDF = "P(X=m) onde X segue B(n,p)"
 BinomialCDF = "P(X<=m) onde X segue B(n,p)"
 InvBinomial = "m onde P(X<=m)=a e X segue B(n,p)"

poincare/src/inv_norm.cpp

@@ -29,11 +29,11 @@ template<typename T>
 Evaluation<T> InvNormNode::templatedApproximate(Context * context, Preferences::ComplexFormat complexFormat, Preferences::AngleUnit angleUnit) const {
   Evaluation<T> aEvaluation = childAtIndex(0)->approximate(T(), context, complexFormat, angleUnit);
   Evaluation<T> muEvaluation = childAtIndex(1)->approximate(T(), context, complexFormat, angleUnit);
-  Evaluation<T> varEvaluation = childAtIndex(2)->approximate(T(), context, complexFormat, angleUnit);
+  Evaluation<T> sigmaEvaluation = childAtIndex(2)->approximate(T(), context, complexFormat, angleUnit);
 
   T a = aEvaluation.toScalar();
   T mu = muEvaluation.toScalar();
-  T sigma = std::sqrt(varEvaluation.toScalar());
+  T sigma = sigmaEvaluation.toScalar();
 
   // CumulativeDistributiveInverseForProbability handles bad mu and var values
   return Complex<T>::Builder(NormalDistribution::CumulativeDistributiveInverseForProbability<T>(a, mu, sigma));

poincare/src/norm_cdf.cpp

@@ -27,11 +27,11 @@ template<typename T>
 Evaluation<T> NormCDFNode::templatedApproximate(Context * context, Preferences::ComplexFormat complexFormat, Preferences::AngleUnit angleUnit) const {
   Evaluation<T> aEvaluation = childAtIndex(0)->approximate(T(), context, complexFormat, angleUnit);
   Evaluation<T> muEvaluation = childAtIndex(1)->approximate(T(), context, complexFormat, angleUnit);
-  Evaluation<T> varEvaluation = childAtIndex(2)->approximate(T(), context, complexFormat, angleUnit);
+  Evaluation<T> sigmaEvaluation = childAtIndex(2)->approximate(T(), context, complexFormat, angleUnit);
 
   const T a = aEvaluation.toScalar();
   const T mu = muEvaluation.toScalar();
-  const T sigma = std::sqrt(varEvaluation.toScalar());
+  const T sigma = sigmaEvaluation.toScalar();
 
   // CumulativeDistributiveFunctionAtAbscissa handles bad mu and var values
   return Complex<T>::Builder(NormalDistribution::CumulativeDistributiveFunctionAtAbscissa(a, mu, sigma));

poincare/src/norm_cdf2.cpp

@@ -28,12 +28,12 @@ Evaluation<T> NormCDF2Node::templatedApproximate(Context * context, Preferences:
   Evaluation<T> aEvaluation = childAtIndex(0)->approximate(T(), context, complexFormat, angleUnit);
   Evaluation<T> bEvaluation = childAtIndex(1)->approximate(T(), context, complexFormat, angleUnit);
   Evaluation<T> muEvaluation = childAtIndex(2)->approximate(T(), context, complexFormat, angleUnit);
-  Evaluation<T> varEvaluation = childAtIndex(3)->approximate(T(), context, complexFormat, angleUnit);
+  Evaluation<T> sigmaEvaluation = childAtIndex(3)->approximate(T(), context, complexFormat, angleUnit);
 
   T a = aEvaluation.toScalar();
   T b = bEvaluation.toScalar();
   T mu = muEvaluation.toScalar();
-  T sigma = std::sqrt(varEvaluation.toScalar());
+  T sigma = sigmaEvaluation.toScalar();
 
   if (std::isnan(a) || std::isnan(b) || !NormalDistribution::MuAndSigmaAreOK(mu,sigma)) {
     return Complex<T>::Undefined();

poincare/src/norm_pdf.cpp

@@ -27,11 +27,11 @@ template<typename T>
 Evaluation<T> NormPDFNode::templatedApproximate(Context * context, Preferences::ComplexFormat complexFormat, Preferences::AngleUnit angleUnit) const {
   Evaluation<T> xEvaluation = childAtIndex(0)->approximate(T(), context, complexFormat, angleUnit);
   Evaluation<T> muEvaluation = childAtIndex(1)->approximate(T(), context, complexFormat, angleUnit);
-  Evaluation<T> varEvaluation = childAtIndex(2)->approximate(T(), context, complexFormat, angleUnit);
+  Evaluation<T> sigmaEvaluation = childAtIndex(2)->approximate(T(), context, complexFormat, angleUnit);
 
   T x = xEvaluation.toScalar();
   T mu = muEvaluation.toScalar();
-  T sigma = std::sqrt(varEvaluation.toScalar());
+  T sigma = sigmaEvaluation.toScalar();
 
   // EvaluateAtAbscissa handles bad mu and var values
   return Complex<T>::Builder(NormalDistribution::EvaluateAtAbscissa(x, mu, sigma));

poincare/test/approximation.cpp

@@ -295,8 +295,8 @@ QUIZ_CASE(poincare_approximation_function) {
   assert_expression_approximates_to<float>("invbinom(0.9647324002, 15, 0.7)", "13");
   assert_expression_approximates_to<double>("invbinom(0.9647324002, 15, 0.7)", "13");
 
-  assert_expression_approximates_to<float>("invnorm(0.56, 1.3, 5.76)", "1.662326");
-  //assert_expression_approximates_to<double>("invnorm(0.56, 1.3, 5.76)", "1.6623258450088"); FIXME precision error
+  assert_expression_approximates_to<float>("invnorm(0.56, 1.3, 2.4)", "1.662326");
+  //assert_expression_approximates_to<double>("invnorm(0.56, 1.3, 2.4)", "1.6623258450088"); FIXME precision error
 
   assert_expression_approximates_to<float>("ln(2)", "0.6931472");
   assert_expression_approximates_to<double>("ln(2)", "6.9314718055995ᴇ-1");
@@ -304,17 +304,19 @@ QUIZ_CASE(poincare_approximation_function) {
   assert_expression_approximates_to<float>("log(2)", "0.30103");
   assert_expression_approximates_to<double>("log(2)", "3.0102999566398ᴇ-1");
 
-  assert_expression_approximates_to<float>("normcdf(1.2, 3.4, 31.36)", "0.3472125");
-  assert_expression_approximates_to<double>("normcdf(1.2, 3.4, 31.36)", "3.4721249841587ᴇ-1");
-  assert_expression_approximates_to<float>("normcdf(-1ᴇ99,3.4,31.36)", "0");
-  assert_expression_approximates_to<float>("normcdf(1ᴇ99,3.4,31.36)", "1");
+  assert_expression_approximates_to<float>("normcdf(5, 7, 0.3162)", "1.265256ᴇ-10");
+
+  assert_expression_approximates_to<float>("normcdf(1.2, 3.4, 5.6)", "0.3472125");
+  assert_expression_approximates_to<double>("normcdf(1.2, 3.4, 5.6)", "3.4721249841587ᴇ-1");
+  assert_expression_approximates_to<float>("normcdf(-1ᴇ99,3.4,5.6)", "0");
+  assert_expression_approximates_to<float>("normcdf(1ᴇ99,3.4,5.6)", "1");
   assert_expression_approximates_to<float>("normcdf(-6,0,1)", "0");
   assert_expression_approximates_to<float>("normcdf(6,0,1)", "1");
 
-  assert_expression_approximates_to<float>("normcdf2(0.5, 3.6, 1.3, 11.56)", "0.3436388");
-  assert_expression_approximates_to<double>("normcdf2(0.5, 3.6, 1.3, 11.56)", "3.4363881299147ᴇ-1");
+  assert_expression_approximates_to<float>("normcdf2(0.5, 3.6, 1.3, 3.4)", "0.3436388");
+  assert_expression_approximates_to<double>("normcdf2(0.5, 3.6, 1.3, 3.4)", "3.4363881299147ᴇ-1");
 
-  assert_expression_approximates_to<float>("normpdf(1.2, 3.4, 31.36)", "0.06594901");
+  assert_expression_approximates_to<float>("normpdf(1.2, 3.4, 5.6)", "0.06594901");
 
   assert_expression_approximates_to<float>("permute(10, 4)", "5040");
   assert_expression_approximates_to<double>("permute(10, 4)", "5040");

poincare/test/simplification.cpp

@@ -344,7 +344,7 @@ QUIZ_CASE(poincare_simplification_units) {
   assert_parsed_expression_simplify_to("inf×_s", "inf×_s");
   assert_parsed_expression_simplify_to("-inf×_s", "-inf×_s");
   assert_parsed_expression_simplify_to("2_s+3_s-5_s", "0×_s");
-  assert_parsed_expression_simplify_to("normcdf(0,20,3)×_s", "0×_s");
+  assert_parsed_expression_simplify_to("normcdf(0,20,3)×_s", "13.083978345207×_ps");
   assert_parsed_expression_simplify_to("log(0)×_s", "-inf×_s");
   assert_parsed_expression_simplify_to("log(undef)*_s", "undef");