test_class.file: deepnetts-core/src/test/java/deepnetts/net/layers/ActivationFunctionsTest.java
test_class.identifier: ActivationFunctionsTest
test_case.body: @Test
      public void testSigmoidPrime() {
          float[] x = {0.000911051f,  0.00100677f,  0.00111254f,  0.0012294f,  0.00135852f,  0.00150118f,  0.0016588f,  0.00183294f,  0.00202532f,  0.00223785f,  0.00247262f,  0.00273196f,  0.00301841f,  0.0033348f,  0.00368424f,  0.00407013f,  0.00449627f,  0.00496679f,  0.00548629f,  0.00605979f,  0.00669284f,  0.00739153f,  0.00816255f,  0.00901328f,  0.00995178f,  0.0109869f,  0.0121284f,  0.0133869f,  0.014774f,  0.0163025f,  0.0179862f,  0.0198402f,  0.0218812f,  0.0241269f,  0.0265969f,  0.0293121f,  0.0322954f,  0.0355711f,  0.0391656f,  0.0431071f,  0.0474257f,  0.0521534f,  0.057324f,  0.0629731f,  0.0691381f,  0.0758579f,  0.0831724f,  0.0911226f,  0.0997501f,  0.109096f,  0.119202f,  0.130108f,  0.14185f,  0.154465f,  0.167981f,  0.182425f,  0.197815f,  0.214164f,  0.231474f,  0.249739f,  0.26894f,  0.289049f,  0.310024f,  0.331811f,  0.354342f,  0.377539f,  0.401311f,  0.425556f,  0.450164f,  0.475019f,  0.499998f,  0.524978f,  0.549832f,  0.574441f,  0.598686f,  0.622458f,  0.645655f,  0.668186f,  0.689973f,  0.710948f,  0.731057f,  0.750259f,  0.768523f,  0.785834f,  0.802183f,  0.817573f,  0.832017f,  0.845534f,  0.858148f,  0.869891f,  0.880796f,  0.890902f,  0.900249f,  0.908876f,  0.916827f,  0.924141f,  0.930861f,  0.937026f,  0.942675f,  0.947846f,  0.952574f,  0.956892f,  0.960834f,  0.964428f,  0.967704f,  0.970688f,  0.973403f,  0.975873f,  0.978118f,  0.98016f,  0.982014f,  0.983697f,  0.985226f,  0.986613f,  0.987871f,  0.989013f,  0.990048f,  0.990987f,  0.991837f,  0.992608f,  0.993307f,  0.99394f,  0.994514f,  0.995033f,  0.995504f,  0.99593f,  0.996316f,  0.996665f,  0.996982f,  0.997268f,  0.997527f,  0.997762f,  0.997975f,  0.998167f,  0.998341f,  0.998499f,  0.998641f,  0.998771f,  0.998887f,  0.998993f,  0.999089f};
          float[] y = {0.000910221f,  0.00100576f,  0.0011113f,  0.00122789f,  0.00135667f,  0.00149893f,  0.00165605f,  0.00182958f,  0.00202122f,  0.00223284f,  0.00246651f,  0.00272449f,  0.0030093f,  0.00332368f,  0.00367066f,  0.00405357f,  0.00447605f,  0.00494212f,  0.00545619f,  0.00602307f,  0.00664804f,  0.00733689f,  0.00809593f,  0.00893204f,  0.00985274f,  0.0108662f,  0.0119813f,  0.0132077f,  0.0145557f,  0.0160367f,  0.0176627f,  0.0194466f,  0.0214024f,  0.0235448f,  0.0258895f,  0.0284529f,  0.0312524f,  0.0343058f,  0.0376316f,  0.0412489f,  0.0451765f,  0.0494334f,  0.0540379f,  0.0590075f,  0.0643581f,  0.0701035f,  0.0762547f,  0.0828193f,  0.0898f,  0.0971944f,  0.104993f,  0.11318f,  0.121729f,  0.130605f,  0.139763f,  0.149146f,  0.158684f,  0.168298f,  0.177894f,  0.187369f,  0.196611f,  0.2055f,  0.213909f,  0.221712f,  0.228784f,  0.235003f,  0.24026f,  0.244458f,  0.247516f,  0.249376f,  0.25f,  0.249376f,  0.247517f,  0.244459f,  0.240261f,  0.235004f,  0.228785f,  0.221713f,  0.21391f,  0.205501f,  0.196613f,  0.187371f,  0.177895f,  0.168299f,  0.158686f,  0.149147f,  0.139765f,  0.130607f,  0.12173f,  0.113181f,  0.104994f,  0.0971954f,  0.089801f,  0.0828201f,  0.0762556f,  0.0701043f,  0.0643588f,  0.0590082f,  0.0540386f,  0.049434f,  0.045177f,  0.0412494f,  0.0376321f,  0.0343062f,  0.0312528f,  0.0284533f,  0.0258898f,  0.0235451f,  0.0214027f,  0.0194469f,  0.0176629f,  0.0160369f,  0.0145559f,  0.0132078f,  0.0119815f,  0.0108664f,  0.00985287f,  0.00893215f,  0.00809603f,  0.00733699f,  0.00664813f,  0.00602315f,  0.00545626f,  0.00494219f,  0.00447611f,  0.00405362f,  0.00367071f,  0.00332373f,  0.00300934f,  0.00272453f,  0.00246654f,  0.00223287f,  0.00202124f,  0.0018296f,  0.00165607f,  0.00149895f,  0.00135669f,  0.0012279f,  0.00111131f,  0.00100577f,  0.000910233f};
  
          for (int i = 0; i < x.length; i++) {
              float expResult = y[i];
              float result = ActivationFunctions.sigmoidPrime(x[i]);
              assertEquals(expResult, result, 1e-6);
          }    
      }
test_case.class_method_signature: ActivationFunctionsTest.testSigmoidPrime()
test_case.full_signature: @Test public void testSigmoidPrime()
test_case.identifier: testSigmoidPrime
test_case.invocations: sigmoidPrime assertEquals
test_case.modifiers: @Test public
test_case.parameters: ()
test_case.return: void
test_case.signature: void testSigmoidPrime()
focal_class.file: deepnetts-core/src/main/java/deepnetts/net/layers/ActivationFunctions.java
focal_class.identifier: ActivationFunctions
focal_class.class_method_signature: ActivationFunctions.ActivationFunctions()
focal_class.full_signature: private  ActivationFunctions()
focal_class.identifier: ActivationFunctions
focal_class.modifiers: private
focal_class.parameters: ()
focal_class.signature:  ActivationFunctions()
focal_class.class_method_signature: ActivationFunctions.calc(final ActivationType type, final float x)
focal_class.full_signature: public static final float calc(final ActivationType type, final float x)
focal_class.identifier: calc
focal_class.modifiers: public static final
focal_class.parameters: (final ActivationType type, final float x)
focal_class.return: float
focal_class.signature: float calc(final ActivationType type, final float x)
focal_class.class_method_signature: ActivationFunctions.prime(ActivationType type, float y)
focal_class.full_signature: public static final float prime(ActivationType type, float y)
focal_class.identifier: prime
focal_class.modifiers: public static final
focal_class.parameters: (ActivationType type, float y)
focal_class.return: float
focal_class.signature: float prime(ActivationType type, float y)
focal_class.class_method_signature: ActivationFunctions.sigmoid(final float x)
focal_class.full_signature: public static final float sigmoid(final float x)
focal_class.identifier: sigmoid
focal_class.modifiers: public static final
focal_class.parameters: (final float x)
focal_class.return: float
focal_class.signature: float sigmoid(final float x)
focal_class.class_method_signature: ActivationFunctions.sigmoidPrime(final float y)
focal_class.full_signature: public static final float sigmoidPrime(final float y)
focal_class.identifier: sigmoidPrime
focal_class.modifiers: public static final
focal_class.parameters: (final float y)
focal_class.return: float
focal_class.signature: float sigmoidPrime(final float y)
focal_class.class_method_signature: ActivationFunctions.tanh(final float x)
focal_class.full_signature: public static final float tanh(final float x)
focal_class.identifier: tanh
focal_class.modifiers: public static final
focal_class.parameters: (final float x)
focal_class.return: float
focal_class.signature: float tanh(final float x)
focal_class.class_method_signature: ActivationFunctions.tanhPrime(final float y)
focal_class.full_signature: public static final float tanhPrime(final float y)
focal_class.identifier: tanhPrime
focal_class.modifiers: public static final
focal_class.parameters: (final float y)
focal_class.return: float
focal_class.signature: float tanhPrime(final float y)
focal_class.class_method_signature: ActivationFunctions.relu(final float x)
focal_class.full_signature: public static final float relu(final float x)
focal_class.identifier: relu
focal_class.modifiers: public static final
focal_class.parameters: (final float x)
focal_class.return: float
focal_class.signature: float relu(final float x)
focal_class.class_method_signature: ActivationFunctions.reluPrime(final float y)
focal_class.full_signature: public static final float reluPrime(final float y)
focal_class.identifier: reluPrime
focal_class.modifiers: public static final
focal_class.parameters: (final float y)
focal_class.return: float
focal_class.signature: float reluPrime(final float y)
focal_class.class_method_signature: ActivationFunctions.linear(final float x)
focal_class.full_signature: public static final float linear(final float x)
focal_class.identifier: linear
focal_class.modifiers: public static final
focal_class.parameters: (final float x)
focal_class.return: float
focal_class.signature: float linear(final float x)
focal_class.class_method_signature: ActivationFunctions.linearPrime(final float y)
focal_class.full_signature: public static final float linearPrime(final float y)
focal_class.identifier: linearPrime
focal_class.modifiers: public static final
focal_class.parameters: (final float y)
focal_class.return: float
focal_class.signature: float linearPrime(final float y)
focal_method.body: public static final float sigmoidPrime(final float y) {
         return y*(1-y);
      }
focal_method.class_method_signature: ActivationFunctions.sigmoidPrime(final float y)
focal_method.full_signature: public static final float sigmoidPrime(final float y)
focal_method.identifier: sigmoidPrime
focal_method.modifiers: public static final
focal_method.parameters: (final float y)
focal_method.return: float
focal_method.signature: float sigmoidPrime(final float y)