clang formatted

Author: crapxxi

src/main/java/com/thealgorithms/maths/SigmoidActivation.java

@@ -17,21 +17,25 @@ public class SigmoidActivation {
      */
     public static double activate(double x) {
         // If the number x is NaN then, returning NaN to saving from unexpected output.
-        if(Double.isNaN(x)) return Double.NaN;
+        if (Double.isNaN(x)) {
+            return Double.NaN;
+        }
         // Saving from unnecessary and heavy calculations.
         // lim x->-inf sigmoid(x) will return number very close to 0
-        if(x < -745) return 0.0;
+        if (x < -745) return 0.0;
         // lim x->inf sigmoid(x) will return number very close to 1
-        if(x > 745) return 1.0;
+        if (x > 745) return 1.0;
         // sigmoid function's formula
-        return 1.0 / ( 1 + Math.exp((-1) * x));
+        return 1.0 / (1 + Math.exp((-1) * x));
     }
 
     public static double[][] activate(double[][] x) {
         // apply calculation to every value in batch.
         double[][] activatedNumbers = new double[x.length][x[0].length];
-        for(int i = 0; i < x.length; i++) {
-            for (int j = 0; j < x[0].length; j++) activatedNumbers[i][j] = activate(x[i][j]);
+        for (int i = 0; i < x.length; i++) {
+            for (int j = 0; j < x[0].length; j++) {
+                activatedNumbers[i][j] = activate(x[i][j]);
+            }
         }
         return activatedNumbers;
     }
@@ -50,10 +54,11 @@ public static double grad(double y) {
     public static double[][] grad(double[][] y) {
         // apply calculation to every value in batch.
         double[][] grads = new double[y.length][y[0].length];
-        for(int i = 0; i < y.length; i++) {
-            for (int j = 0; j < y[0].length; j++) grads[i][j] = grad(y[i][j]);
+        for (int i = 0; i < y.length; i++) {
+            for (int j = 0; j < y[0].length; j++) {
+                grads[i][j] = grad(y[i][j]);
+            }
         }
         return grads;
     }
-
 }

src/test/java/com/thealgorithms/maths/SigmoidActivationTest.java

@@ -1,45 +1,52 @@
 package com.thealgorithms.maths;
 
-import org.junit.jupiter.api.Test;
-
-import java.util.Arrays;
-
 import static org.junit.jupiter.api.Assertions.assertEquals;
 import static org.junit.jupiter.api.Assertions.assertTrue;
 
+import java.util.Arrays;
+import org.junit.jupiter.api.Test;
+
 public class SigmoidActivationTest {
 
     @Test
     public void calculationTest() {
-        assertEquals(0.5,SigmoidActivation.activate(0), 0.01,"1 case correct" );
-        assertEquals(0.73,SigmoidActivation.activate(1),0.01,"2 case correct");
-        assertEquals(0.26,SigmoidActivation.activate(-1),0.01, "3 case correct");
-        assertEquals(0.88,SigmoidActivation.activate(2),0.01,"4 case correct");
-        assertEquals(0.11,SigmoidActivation.activate(-2),0.01,"5 case correct");
+        assertEquals(0.5, SigmoidActivation.activate(0), 0.01, "1 case correct");
+        assertEquals(0.73, SigmoidActivation.activate(1), 0.01, "2 case correct");
+        assertEquals(0.26, SigmoidActivation.activate(-1), 0.01, "3 case correct");
+        assertEquals(0.88, SigmoidActivation.activate(2), 0.01, "4 case correct");
+        assertEquals(0.11, SigmoidActivation.activate(-2), 0.01, "5 case correct");
 
         double[][] xBatch = new double[4][3];
         double[][] expectedX = new double[4][3];
 
-        for(int i = 0; i < 4; i++) {
-            for(int j = 0; j < 3; j++) xBatch[i][j] = 0;
+        for (int i = 0; i < 4; i++) {
+            for (int j = 0; j < 3; j++) {
+                xBatch[i][j] = 0;
+            }
         }
 
-        for(int i = 0; i < 4; i++) {
-            for(int j = 0; j < 3; j++) expectedX[i][j] = 0.5;
+        for (int i = 0; i < 4; i++) {
+            for (int j = 0; j < 3; j++) {
+                expectedX[i][j] = 0.5;
+            }
         }
 
         assertTrue(Arrays.deepEquals(expectedX, SigmoidActivation.activate(xBatch)), "batch case correct");
 
         assertEquals(0.25, SigmoidActivation.grad(0.5), 0.01, "grad calculation correct");
 
         double[][] yBatch = new double[4][3];
-        for(int i = 0; i < 4; i++) {
-            for(int j = 0; j < 3; j++) yBatch[i][j] = 0.5;
+        for (int i = 0; i < 4; i++) {
+            for (int j = 0; j < 3; j++) {
+                yBatch[i][j] = 0.5;
+            }
         }
 
         double[][] expectedY = new double[4][3];
-        for(int i = 0; i < 4; i++) {
-            for(int j = 0; j < 3; j++) expectedY[i][j] = 0.25;
+        for (int i = 0; i < 4; i++) {
+            for (int j = 0; j < 3; j++) {
+                expectedY[i][j] = 0.25;
+            }
         }
         assertTrue(Arrays.deepEquals(expectedY, SigmoidActivation.grad(yBatch)), "grad batch case correct");
     }