Use Commons Numbers Erf implementation

gdsc-smlm/src/main/java/uk/ac/sussex/gdsc/smlm/function/Erf.java

@@ -108,7 +108,7 @@ public static double erf0(double x1, double x2) {
    * @return the error function erf(x)
    */
   public static double erf(double x) {
-    // return org.apache.commons.math3.special.Erf.erf(x);
+    // return org.apache.commons.numbers.gamma.Erf.value(x);
 
     final boolean negative = (x < 0);
     if (negative) {

gdsc-smlm/src/main/java/uk/ac/sussex/gdsc/smlm/function/PoissonGammaGaussianFunction.java

@@ -484,7 +484,7 @@ public double logLikelihood(final double obs, final double exp) {
    * @return the cumulative density
    */
   double gaussianCdf(final double x) {
-    // return 0.5 * (1 + org.apache.commons.math3.special.Erf.erf(x / sqrt2sigma2));
+    // return 0.5 * org.apache.commons.numbers.gamma.Erfc.value(-x / sqrt2sigma2);
     // This may not be precise enough.
     // Absolute error is <3e-7. Not sure what relative error is.
     // The standard Erf is much slower.
@@ -499,7 +499,7 @@ public double logLikelihood(final double obs, final double exp) {
    * @return the cumulative density
    */
   double gaussianCdf(final double x, final double x2) {
-    // return 0.5 * (org.apache.commons.math3.special.Erf.erf(x / sqrt2sigma2, x2 / sqrt2sigma2));
+    // return 0.5 * org.apache.commons.numbers.gamma.ErfDifference.value(x / sqrt2sigma2, x2 / sqrt2sigma2);
     // This may not be precise enough.
     // Absolute error is <3e-7. Not sure what relative error is.
     // The standard Erf is much slower.
@@ -513,7 +513,7 @@ public double logLikelihood(final double obs, final double exp) {
    * @return the cumulative density
    */
   double gaussianErf(final double x) {
-    // return org.apache.commons.math3.special.Erf.erf(x / sqrt2sigma2);
+    // return org.apache.commons.numbers.gamma.Erf.value(x / sqrt2sigma2);
     // This may not be precise enough.
     // Absolute error is <3e-7. Not sure what relative error is.
     // The standard Erf is much slower.

gdsc-smlm/src/main/java/uk/ac/sussex/gdsc/smlm/function/PoissonGaussianConvolutionFunction.java

@@ -215,7 +215,7 @@ private double getX(final double D, int q) {
    * @return the cumulative density
    */
   double gaussianCdf(final double x) {
-    // return org.apache.commons.math3.special.Erf.erf(x / sqrt_var_by_2)
+    // return org.apache.commons.numbers.gamma.Erf.value(x / sqrt_var_by_2)
     // This may not be precise enough.
     // Absolute error is <3e-7. Not sure what relative error is.
     // The standard CDF is much slower.

gdsc-smlm/src/main/java/uk/ac/sussex/gdsc/smlm/function/gaussian/erf/ErfGaussian2DFunction.java

@@ -102,7 +102,9 @@ public enum ErfFunction {
     /** Use a fast approximation for the Error function. */
     FAST,
 
-    /** Use the Apache commons math library Error function. */
+    /** Use the Apache Commons library Error function.
+     * <p>As of version 1.2 this uses the implementation in Commons Numbers
+     * (replacing the Commons Math implementation). */
     COMMONS_MATH;
   }
 
@@ -130,14 +132,14 @@ public double erf(double x) {
   }
 
   /**
-   * Compute the error function using the Commons Math implementation.
+   * Compute the error function using the Commons Numbers implementation.
    */
-  private static class CommontsMathErrorFunction implements ErrorFunction {
-    static final CommontsMathErrorFunction INSTANCE = new CommontsMathErrorFunction();
+  private static class CommontsNumbersErrorFunction implements ErrorFunction {
+    static final CommontsNumbersErrorFunction INSTANCE = new CommontsNumbersErrorFunction();
 
     @Override
     public double erf(double x) {
-      return org.apache.commons.math3.special.Erf.erf(x);
+      return org.apache.commons.numbers.gamma.Erf.value(x);
     }
   }
 
@@ -265,7 +267,7 @@ public ErfFunction getErfFunction() {
   public void setErfFunction(ErfFunction erfFunction) {
     switch (erfFunction) {
       case COMMONS_MATH:
-        errorFunction = CommontsMathErrorFunction.INSTANCE;
+        errorFunction = CommontsNumbersErrorFunction.INSTANCE;
         break;
       case FAST:
         errorFunction = FastErrorFunction.INSTANCE;

gdsc-smlm/src/main/java/uk/ac/sussex/gdsc/smlm/model/GaussianPsfModel.java

@@ -25,7 +25,7 @@
 package uk.ac.sussex.gdsc.smlm.model;
 
 import org.apache.commons.lang3.tuple.Pair;
-import org.apache.commons.math3.special.Erf;
+import org.apache.commons.numbers.gamma.Erf;
 import org.apache.commons.rng.UniformRandomProvider;
 import org.apache.commons.rng.sampling.distribution.NormalizedGaussianSampler;
 import uk.ac.sussex.gdsc.core.utils.MathUtils;
@@ -289,11 +289,11 @@ public double[] gaussian2D(int x0range, int x1range, double sum, double x0, doub
     // Note: The 0.5 factors are moved to reduce computations
     for (int x = 0; x <= x0range; x++) {
       // erf0[x] = 0.5 * Erf.erf((x - x0) * denom0);
-      erf0[x] = Erf.erf((x - x0) * denom0);
+      erf0[x] = Erf.value((x - x0) * denom0);
     }
     for (int y = 0; y <= x1range; y++) {
       // erf1[y] = 0.5 * Erf.erf((y - x1) * denom1);
-      erf1[y] = Erf.erf((y - x1) * denom1);
+      erf1[y] = Erf.value((y - x1) * denom1);
     }
     sum *= 0.5; // Incorporate the 0.5 factor for Y into the sum
 

gdsc-smlm/src/main/java/uk/ac/sussex/gdsc/smlm/utils/GaussianKernel.java

@@ -413,10 +413,10 @@ public static double[] makeErfGaussianKernel(double sigma, double range) {
     final double sqrtTwoVar = Math.sqrt(sigma * sigma * 2);
 
     // Use erfc to reach into the long tail at sigma <= 38
-    double lower = org.apache.commons.math3.special.Erf.erfc(-0.5 / sqrtTwoVar);
+    double lower = org.apache.commons.numbers.gamma.Erfc.value(-0.5 / sqrtTwoVar);
     for (int i = 0; i < kradius; i++) {
       final double upper = lower;
-      lower = org.apache.commons.math3.special.Erf.erfc((i + 0.5) / sqrtTwoVar);
+      lower = org.apache.commons.numbers.gamma.Erfc.value((i + 0.5) / sqrtTwoVar);
       kernel[i] = (upper - lower) * 0.5;
       if (kernel[i] == 0) {
         break;