[apps/regression] Clean partialDerivate of the models

apps/regression/model/cubic_model.cpp

@@ -55,24 +55,21 @@ double CubicModel::evaluate(double * modelCoefficients, double x) const {
 }
 
 double CubicModel::partialDerivate(double * modelCoefficients, int derivateCoefficientIndex, double x) const {
-  if (derivateCoefficientIndex == 0) {
-    // Derivate: x^3
-    return x*x*x;
-  }
-  if (derivateCoefficientIndex == 1) {
-    // Derivate: x^2
-    return x*x;
-  }
-  if (derivateCoefficientIndex == 2) {
-    // Derivate: x
-    return x;
-  }
-  if (derivateCoefficientIndex == 3) {
-    // Derivate: 1
-    return 1;
-  }
-  assert(false);
-  return 0.0;
+  switch (derivateCoefficientIndex) {
+    case 0:
+      // Derivate with respect to a: x^3
+      return x*x*x;
+    case 1:
+      // Derivate with respect to b: x^2
+      return x*x;
+    case 2:
+      // Derivate with respect to c: x
+      return x;
+    default:
+      // Derivate with respect to d: 1
+      assert(derivateCoefficientIndex == 3);
+      return 1.0;
+  };
 }
 
 Expression CubicModel::expression(double * modelCoefficients) {

apps/regression/model/exponential_model.cpp

@@ -86,18 +86,15 @@ void ExponentialModel::fit(Store * store, int series, double * modelCoefficients
 }
 
 double ExponentialModel::partialDerivate(double * modelCoefficients, int derivateCoefficientIndex, double x) const {
-  double a = modelCoefficients[0];
-  double b = modelCoefficients[1];
+  const double b = modelCoefficients[1];
   if (derivateCoefficientIndex == 0) {
-    // Derivate: exp(b*x)
+    // Derivate with respect to a: exp(b*x)
     return exp(b*x);
   }
-  if (derivateCoefficientIndex == 1) {
-    // Derivate: a*x*exp(b*x)
-    return a*x*exp(b*x);
-  }
-  assert(false);
-  return 0.0;
+  assert(derivateCoefficientIndex == 1);
+  // Derivate with respect to b: a*x*exp(b*x)
+  double a = modelCoefficients[0];
+  return a*x*exp(b*x);
 }
 
 }

apps/regression/model/linear_model.cpp

@@ -38,15 +38,12 @@ void LinearModel::fit(Store * store, int series, double * modelCoefficients, Poi
 
 double LinearModel::partialDerivate(double * modelCoefficients, int derivateCoefficientIndex, double x) const {
   if (derivateCoefficientIndex == 0) {
-    // Derivate: x
+    // Derivate with respect to a: x
     return x;
   }
-  if (derivateCoefficientIndex == 1) {
-    // Derivate: 1;
-    return 1;
-  }
-  assert(false);
-  return 0.0;
+  assert(derivateCoefficientIndex == 1);
+  // Derivate with respect to b: 1
+  return 1.0;
 }
 
 }

apps/regression/model/logarithmic_model.cpp

@@ -33,16 +33,13 @@ double LogarithmicModel::levelSet(double * modelCoefficients, double xMin, doubl
 
 double LogarithmicModel::partialDerivate(double * modelCoefficients, int derivateCoefficientIndex, double x) const {
   if (derivateCoefficientIndex == 0) {
-    // Derivate: ln(x)
-    assert(x >0);
+    // Derivate with respect to a: ln(x)
+    assert(x > 0);
     return log(x);
   }
-  if (derivateCoefficientIndex == 1) {
-    // Derivate: 1
-    return 1;
-  }
-  assert(false);
-  return 0.0;
+  assert(derivateCoefficientIndex == 1);
+  // Derivate with respect to b: 1
+  return 1.0;
 }
 
 bool LogarithmicModel::dataSuitableForFit(Store * store, int series) const {

apps/regression/model/logistic_model.cpp

@@ -61,21 +61,18 @@ double LogisticModel::partialDerivate(double * modelCoefficients, int derivateCo
   double a = modelCoefficients[0];
   double b = modelCoefficients[1];
   double c = modelCoefficients[2];
-  double denominator = 1.0+a*exp(-b*x);
+  double denominator = 1.0 + a * exp(-b * x);
   if (derivateCoefficientIndex == 0) {
-    // Derivate: exp(-b*x)*(-1 * c/(1.0+a*exp(-b*x))^2)
-    return -exp(-b*x) * c/(denominator * denominator);
+    // Derivate with respect to a: exp(-b*x)*(-1 * c/(1.0+a*exp(-b*x))^2)
+    return -exp(-b * x) * c / (denominator * denominator);
   }
   if (derivateCoefficientIndex == 1) {
-    // Derivate: (-x)*a*exp(-b*x)*(-1/(1.0+a*exp(-b*x))^2)
-    return x*a*exp(-b*x)*c/(denominator * denominator);
+    // Derivate with respect to b: (-x)*a*exp(-b*x)*(-1/(1.0+a*exp(-b*x))^2)
+    return x * a * exp(-b * x) * c / (denominator * denominator);
   }
-  if (derivateCoefficientIndex == 2) {
-    // Derivate: (-x)*a*exp(-b*x)*(-1/(1.0+a*exp(-b*x))^2)
-    return 1.0/denominator;
-  }
-  assert(false);
-  return 0.0;
+  assert(derivateCoefficientIndex == 2);
+  // Derivate with respect to c: (-x)*a*exp(-b*x)*(-1/(1.0+a*exp(-b*x))^2)
+  return 1.0 / denominator;
 }
 
 void LogisticModel::specializedInitCoefficientsForFit(double * modelCoefficients, double defaultValue, Store * store, int series) const {
@@ -86,7 +83,7 @@ void LogisticModel::specializedInitCoefficientsForFit(double * modelCoefficients
    * and c. Twice the standard vertical deviation is a rough estimate of c
    * that is "close enough" to c to seed the coefficient, without being too
    * dependent on outliers.*/
-  modelCoefficients[2] = 2.0*store->standardDeviationOfColumn(series, 1);
+  modelCoefficients[2] = 2.0 * store->standardDeviationOfColumn(series, 1);
 }
 
 

apps/regression/model/power_model.cpp

@@ -44,19 +44,16 @@ double PowerModel::partialDerivate(double * modelCoefficients, int derivateCoeff
   double a = modelCoefficients[0];
   double b = modelCoefficients[1];
   if (derivateCoefficientIndex == 0) {
-    // Derivate: pow(x,b)
+    // Derivate with respect to a: pow(x,b)
     return pow(x,b);
   }
-  if (derivateCoefficientIndex == 1) {
-    assert(x >= 0);
-    /* We assume all xi are positive.
-     * For x = 0, a*pow(x,b) = 0, the partial derivate along b is 0
-     * For x > 0, a*pow(x,b) = a*exp(b*ln(x)), the partial derivate along b is
-     *   ln(x)*a*pow(x,b) */
-    return x == 0 ? 0 : log(x)*a*pow(x, b);
-  }
-  assert(false);
-  return 0.0;
+  assert(derivateCoefficientIndex == 1);
+  assert(x >= 0);
+  /* We assume all xi are positive.
+   * For x = 0, a*pow(x,b) = 0, the partial derivate with respect to b is 0
+   * For x > 0, a*pow(x,b) = a*exp(b*ln(x)), the partial derivate with respect
+   *            to b is ln(x)*a*pow(x,b) */
+  return x == 0.0 ? 0.0 : log(x) * a * pow(x, b);
 }
 
 void PowerModel::fit(Store * store, int series, double * modelCoefficients, Poincare::Context * context) {

apps/regression/model/quadratic_model.cpp

@@ -47,19 +47,16 @@ double QuadraticModel::evaluate(double * modelCoefficients, double x) const {
 
 double QuadraticModel::partialDerivate(double * modelCoefficients, int derivateCoefficientIndex, double x) const {
   if (derivateCoefficientIndex == 0) {
-    // Derivate: x^2
+    // Derivate with respect to a: x^2
     return x*x;
   }
   if (derivateCoefficientIndex == 1) {
-    // Derivate: x
+    // Derivate with respect to b: x
     return x;
   }
-  if (derivateCoefficientIndex == 2) {
-    // Derivate: 1
-    return 1;
-  }
-  assert(false);
-  return 0.0;
+  assert(derivateCoefficientIndex == 2);
+  // Derivate with respect to c: 1
+  return 1.0;
 }
 
 Expression QuadraticModel::expression(double * modelCoefficients) {

apps/regression/model/quartic_model.cpp

@@ -64,28 +64,24 @@ double QuarticModel::evaluate(double * modelCoefficients, double x) const {
 }
 
 double QuarticModel::partialDerivate(double * modelCoefficients, int derivateCoefficientIndex, double x) const {
-  if (derivateCoefficientIndex == 0) {
-    // Derivate: x^4
-    return x*x*x*x;
-  }
-  if (derivateCoefficientIndex == 1) {
-    // Derivate: x^3
-    return x*x*x;
-  }
-  if (derivateCoefficientIndex == 2) {
-    // Derivate: x^2
-    return x*x;
-  }
-  if (derivateCoefficientIndex == 3) {
-    // Derivate: x
-    return x;
-  }
-  if (derivateCoefficientIndex == 4) {
-    // Derivate: 1
-    return 1;
-  }
-  assert(false);
-  return 0.0;
+  switch (derivateCoefficientIndex) {
+    case 0:
+      // Derivate with respect to a: x^4
+      return x*x*x*x;
+    case 1:
+      // Derivate with respect to b: x^3
+      return x*x*x;
+    case 2:
+      // Derivate with respect to c: x^2
+      return x*x;
+    case 3:
+      // Derivate with respect to d: x
+      return x;
+    default:
+      assert(derivateCoefficientIndex == 4);
+      // Derivate with respect to e: 1
+      return 1.0;
+  };
 }
 
 Expression QuarticModel::expression(double * modelCoefficients) {

apps/regression/model/trigonometric_model.cpp

@@ -46,28 +46,27 @@ double TrigonometricModel::evaluate(double * modelCoefficients, double x) const
 }
 
 double TrigonometricModel::partialDerivate(double * modelCoefficients, int derivateCoefficientIndex, double x) const {
+  if (derivateCoefficientIndex == 3) {
+    // Derivate with respect to d: 1
+    return 1.0;
+  }
+
   double a = modelCoefficients[0];
   double b = modelCoefficients[1];
   double c = modelCoefficients[2];
   double radianX = x * toRadians(Poincare::Preferences::sharedPreferences()->angleUnit());
+
   if (derivateCoefficientIndex == 0) {
-    // Derivate: sin(b*x+c)
-    return sin(b*radianX+c);
+    // Derivate with respect to a: sin(b*x+c)
+    return sin(b * radianX + c);
   }
   if (derivateCoefficientIndex == 1) {
-    // Derivate: x*a*cos(b*x+c);
-    return radianX*a*cos(b*radianX+c);
+    // Derivate with respect to b: x*a*cos(b*x+c);
+    return radianX * a * cos(b * radianX + c);
   }
-  if (derivateCoefficientIndex == 2) {
-    // Derivate: a*cos(b*x+c)
-    return a*cos(b*radianX+c);
-  }
-  if (derivateCoefficientIndex == 3) {
-    // Derivate: 1
-    return 1.0;
-  }
-  assert(false);
-  return 0.0;
+  assert(derivateCoefficientIndex == 2);
+  // Derivatewith respect to c: a*cos(b*x+c)
+  return a * cos(b * radianX + c);
 }
 
 void TrigonometricModel::specializedInitCoefficientsForFit(double * modelCoefficients, double defaultValue, Store * store, int series) const {