Merge pull request #29 from FPAL-Stanford-University/parallel

Added explicit differentiator

floatpy/derivatives/__init__.py

@@ -1 +1,2 @@
+from explicit_differentiator import ExplicitDifferentiator
 from compact_differentiator import CompactDifferentiator

floatpy/tests/mpitest_differentiator_compact_2D.py

@@ -109,7 +109,7 @@ def testSecondDerivativeY(self):
 
     def testGradient(self):
         """
-        Test the gradient function
+        Test the gradient function.
         """
 
         dfdx, dfdy = self.der.gradient(self.f)
@@ -127,7 +127,7 @@ def testGradient(self):
 
     def testDivergence(self):
         """
-        Test the divergence function
+        Test the divergence function.
         """
 
         df = numpy.concatenate((self.dfdx_exact[..., numpy.newaxis], \
@@ -144,9 +144,28 @@ def testDivergence(self):
         self.assertLess(error[0], 5.0e-14, "Incorrect divergence!")
 
 
+    def testCurl(self):
+        """
+        Test the curl function.
+        """
+
+        df = numpy.concatenate((self.dfdx_exact[..., numpy.newaxis], \
+            self.dfdy_exact[..., numpy.newaxis]), axis=2)
+
+        curl = self.der.curl(df)
+
+        myerror = numpy.zeros(1)
+        myerror[0] = numpy.absolute(curl).max()
+
+        error = numpy.zeros(1)
+        self.comm.Allreduce(myerror, error, op=MPI.MAX)
+
+        self.assertLess(error[0], 5.0e-14, "Incorrect curl!")
+
+
     def testLaplacian(self):
         """
-        Test the laplacian function
+        Test the laplacian function.
         """
 
         laplacian = self.der.laplacian(self.f)

floatpy/tests/mpitest_differentiator_compact_3D.py

@@ -5,7 +5,7 @@
 from floatpy.parallel import _t3dmod
 from floatpy.derivatives import CompactDifferentiator
 
-class TestDerivativesCompact(unittest.TestCase):
+class TestDifferentiatorCompact(unittest.TestCase):
 
     def setUp(self):
         self.nx, self.ny, self.nz = 64, 64, 64
@@ -63,7 +63,7 @@ def testFirstDerivativeX(self):
         error = numpy.array([ myerror[0] ])
         self.comm.Allreduce(myerror, error, op=MPI.MAX)
 
-        self.assertLess(error[0], 5.0e-14, "Incorrect periodic first derivative in X!")
+        self.assertLess(error[0], 5.0e-14, "Incorrect periodic first derivative in the X direction!")
 
 
     def testFirstDerivativeY(self):
@@ -78,7 +78,7 @@ def testFirstDerivativeY(self):
         error = numpy.array([ myerror[0] ])
         self.comm.Allreduce(myerror, error, op=MPI.MAX)
 
-        self.assertLess(error[0], 5.0e-14, "Incorrect periodic first derivative in Y!")
+        self.assertLess(error[0], 5.0e-14, "Incorrect periodic first derivative in the Y direction!")
 
 
     def testFirstDerivativeZ(self):
@@ -93,7 +93,7 @@ def testFirstDerivativeZ(self):
         error = numpy.array([ myerror[0] ])
         self.comm.Allreduce(myerror, error, op=MPI.MAX)
 
-        self.assertLess(error[0], 5.0e-14, "Incorrect periodic first derivative in Z!")
+        self.assertLess(error[0], 5.0e-14, "Incorrect periodic first derivative in the Z direction!")
 
 
     def testSecondDerivativeX(self):
@@ -108,7 +108,7 @@ def testSecondDerivativeX(self):
         error = numpy.array([ myerror[0] ])
         self.comm.Allreduce(myerror, error, op=MPI.MAX)
 
-        self.assertLess(error[0], 5.0e-12, "Incorrect periodic second derivative in X!")
+        self.assertLess(error[0], 5.0e-12, "Incorrect periodic second derivative in the X direction!")
 
 
     def testSecondDerivativeY(self):
@@ -123,7 +123,7 @@ def testSecondDerivativeY(self):
         error = numpy.array([ myerror[0] ])
         self.comm.Allreduce(myerror, error, op=MPI.MAX)
 
-        self.assertLess(error[0], 5.0e-12, "Incorrect periodic second derivative in X!")
+        self.assertLess(error[0], 5.0e-12, "Incorrect periodic second derivative in the Y direction!")
 
 
     def testSecondDerivativeZ(self):
@@ -138,12 +138,12 @@ def testSecondDerivativeZ(self):
         error = numpy.array([ myerror[0] ])
         self.comm.Allreduce(myerror, error, op=MPI.MAX)
 
-        self.assertLess(error[0], 5.0e-12, "Incorrect periodic second derivative in X!")
+        self.assertLess(error[0], 5.0e-12, "Incorrect periodic second derivative in the Z direction!")
 
 
     def testGradient(self):
         """
-        Test the gradient function
+        Test the gradient function.
         """
 
         dfdx, dfdy, dfdz = self.der.gradient(self.f)
@@ -162,7 +162,7 @@ def testGradient(self):
 
     def testDivergence(self):
         """
-        Test the divergence function
+        Test the divergence function.
         """
 
         df = numpy.concatenate((self.dfdx_exact[..., numpy.newaxis], \
@@ -179,9 +179,31 @@ def testDivergence(self):
         self.assertLess(error[0], 5.0e-14, "Incorrect divergence!")
 
 
+    def testCurl(self):
+        """
+        Test the curl function.
+        """
+
+        df = numpy.concatenate((self.dfdx_exact[..., numpy.newaxis], \
+            self.dfdy_exact[..., numpy.newaxis], self.dfdz_exact[..., numpy.newaxis]), axis=3)
+
+        curl = self.der.curl(df)
+
+        myerror = numpy.zeros(3)
+        myerror[0] = numpy.absolute(curl[:,:,:,0]).max()
+        myerror[1] = numpy.absolute(curl[:,:,:,1]).max()
+        myerror[2] = numpy.absolute(curl[:,:,:,2]).max()
+
+        error = numpy.zeros(3)
+        self.comm.Allreduce(myerror, error, op=MPI.MAX)
+
+        for i in range(3):
+            self.assertLess(error[i], 5.0e-14, "Incorrect curl!")
+
+
     def testLaplacian(self):
         """
-        Test the laplacian function
+        Test the laplacian function.
         """
 
         laplacian = self.der.laplacian(self.f)

floatpy/tests/test_derivatives_explicit_first_order.py → floatpy/tests/test_derivatives_explicit_first.py

@@ -1,7 +1,7 @@
 import numpy
 import unittest
 
-import floatpy.derivatives.explicit.first_order_differentiator
+import floatpy.derivatives.explicit.first as first_der
 
 class TestDerivativesFirst(unittest.TestCase):
 
@@ -17,13 +17,9 @@ def testFirstDirection(self):
         y = numpy.sin(x)
         y_prime_exact = numpy.cos(x)
 
-        dydx_2 = floatpy.derivatives.explicit.first_order_differentiator.FirstOrderDifferentiator('second_order', direction=0, data_order='C')
-        dydx_4 = floatpy.derivatives.explicit.first_order_differentiator.FirstOrderDifferentiator('fourth_order', direction=0, data_order='C')
-        dydx_6 = floatpy.derivatives.explicit.first_order_differentiator.FirstOrderDifferentiator('sixth_order', direction=0, data_order='C')
-
-        y_prime_2 = dydx_2.diff(y, dx, 0, True)
-        y_prime_4 = dydx_4.diff(y, dx, 0, True)
-        y_prime_6 = dydx_6.diff(y, dx, 0, True)
+        y_prime_2 = first_der.differentiateSecondOrderFiniteDifference(y, dx, 0, 0, True, 1, 'C')
+        y_prime_4 = first_der.differentiateFourthOrderFiniteDifference(y, dx, 0, 0, True, 1, 'C')
+        y_prime_6 = first_der.differentiateSixthOrderFiniteDifference(y, dx, 0, 0, True, 1, 'C')
 
         error_2 = numpy.linalg.norm(y_prime_exact[0, :] - y_prime_2[:])
         error_4 = numpy.linalg.norm(y_prime_exact[0, :] - y_prime_4[:])
@@ -46,13 +42,9 @@ def testSecondDirection(self):
         y = numpy.sin(x)
         y_prime_exact = numpy.cos(x)
 
-        dydx_2 = floatpy.derivatives.explicit.first_order_differentiator.FirstOrderDifferentiator('second_order', direction=1, data_order='C')
-        dydx_4 = floatpy.derivatives.explicit.first_order_differentiator.FirstOrderDifferentiator('fourth_order', direction=1, data_order='C')
-        dydx_6 = floatpy.derivatives.explicit.first_order_differentiator.FirstOrderDifferentiator('sixth_order', direction=1, data_order='C')
-
-        y_prime_2 = dydx_2.diff(y, dx, 0, True)
-        y_prime_4 = dydx_4.diff(y, dx, 0, True)
-        y_prime_6 = dydx_6.diff(y, dx, 0, True)
+        y_prime_2 = first_der.differentiateSecondOrderFiniteDifference(y, dx, 1, 0, True, 2, 'C')
+        y_prime_4 = first_der.differentiateFourthOrderFiniteDifference(y, dx, 1, 0, True, 2, 'C')
+        y_prime_6 = first_der.differentiateSixthOrderFiniteDifference(y, dx, 1, 0, True, 2, 'C')
 
         error_2 = numpy.linalg.norm(y_prime_exact[0, 0, :] - y_prime_2[0, :])
         error_4 = numpy.linalg.norm(y_prime_exact[0, 0, :] - y_prime_4[0, :])
@@ -75,13 +67,9 @@ def testThirdDirection(self):
         y = numpy.sin(x)
         y_prime_exact = numpy.cos(x)
 
-        dydx_2 = floatpy.derivatives.explicit.first_order_differentiator.FirstOrderDifferentiator('second_order', direction=2, data_order='C')
-        dydx_4 = floatpy.derivatives.explicit.first_order_differentiator.FirstOrderDifferentiator('fourth_order', direction=2, data_order='C')
-        dydx_6 = floatpy.derivatives.explicit.first_order_differentiator.FirstOrderDifferentiator('sixth_order', direction=2, data_order='C')
-
-        y_prime_2 = dydx_2.diff(y, dx, 0, True)
-        y_prime_4 = dydx_4.diff(y, dx, 0, True)
-        y_prime_6 = dydx_6.diff(y, dx, 0, True)
+        y_prime_2 = first_der.differentiateSecondOrderFiniteDifference(y, dx, 2, 0, True, 3, 'C')
+        y_prime_4 = first_der.differentiateFourthOrderFiniteDifference(y, dx, 2, 0, True, 3, 'C')
+        y_prime_6 = first_der.differentiateSixthOrderFiniteDifference(y, dx, 2, 0, True, 3, 'C')
 
         error_2 = numpy.linalg.norm(y_prime_exact[0, 0, 0, :] - y_prime_2[0, 0, :])
         error_4 = numpy.linalg.norm(y_prime_exact[0, 0, 0, :] - y_prime_4[0, 0, :])

floatpy/tests/test_derivatives_explicit_second_order.py → floatpy/tests/test_derivatives_explicit_second.py

@@ -1,7 +1,7 @@
 import numpy
 import unittest
 
-import floatpy.derivatives.explicit.second_order_differentiator
+import floatpy.derivatives.explicit.second as second_der
 
 class TestDerivativesSecond(unittest.TestCase):
 
@@ -17,16 +17,9 @@ def testFirstDirection(self):
         y = numpy.sin(x)
         y_prime_exact = -numpy.sin(x)
 
-        d2ydx2_2 = floatpy.derivatives.explicit.second_order_differentiator.SecondOrderDifferentiator('second_order', direction=0, \
-                                                                                               data_order='C')
-        d2ydx2_4 = floatpy.derivatives.explicit.second_order_differentiator.SecondOrderDifferentiator('fourth_order', direction=0, \
-                                                                                               data_order='C')
-        d2ydx2_6 = floatpy.derivatives.explicit.second_order_differentiator.SecondOrderDifferentiator('sixth_order', direction=0, \
-                                                                                               data_order='C')
-
-        y_prime_2 = d2ydx2_2.diff(y, dx, 0, True)
-        y_prime_4 = d2ydx2_4.diff(y, dx, 0, True)
-        y_prime_6 = d2ydx2_6.diff(y, dx, 0, True)
+        y_prime_2 = second_der.differentiateSecondOrderFiniteDifference(y, dx, 0, 0, True, 1, 'C')
+        y_prime_4 = second_der.differentiateFourthOrderFiniteDifference(y, dx, 0, 0, True, 1, 'C')
+        y_prime_6 = second_der.differentiateSixthOrderFiniteDifference(y, dx, 0, 0, True, 1, 'C')
 
         error_2 = numpy.linalg.norm(y_prime_exact[0, :] - y_prime_2[:])
         error_4 = numpy.linalg.norm(y_prime_exact[0, :] - y_prime_4[:])
@@ -49,16 +42,9 @@ def testSecondDirection(self):
         y = numpy.sin(x)
         y_prime_exact = -numpy.sin(x)
 
-        d2ydx2_2 = floatpy.derivatives.explicit.second_order_differentiator.SecondOrderDifferentiator('second_order', direction=1, \
-                                                                                               data_order='C')
-        d2ydx2_4 = floatpy.derivatives.explicit.second_order_differentiator.SecondOrderDifferentiator('fourth_order', direction=1, \
-                                                                                               data_order='C')
-        d2ydx2_6 = floatpy.derivatives.explicit.second_order_differentiator.SecondOrderDifferentiator('sixth_order', direction=1, \
-                                                                                               data_order='C')
-
-        y_prime_2 = d2ydx2_2.diff(y, dx, 0, True)
-        y_prime_4 = d2ydx2_4.diff(y, dx, 0, True)
-        y_prime_6 = d2ydx2_6.diff(y, dx, 0, True)
+        y_prime_2 = second_der.differentiateSecondOrderFiniteDifference(y, dx, 1, 0, True, 2, 'C')
+        y_prime_4 = second_der.differentiateFourthOrderFiniteDifference(y, dx, 1, 0, True, 2, 'C')
+        y_prime_6 = second_der.differentiateSixthOrderFiniteDifference(y, dx, 1, 0, True, 2, 'C')
 
         error_2 = numpy.linalg.norm(y_prime_exact[0, 0, :] - y_prime_2[0, :])
         error_4 = numpy.linalg.norm(y_prime_exact[0, 0, :] - y_prime_4[0, :])
@@ -81,16 +67,9 @@ def testThirdDirection(self):
         y = numpy.sin(x)
         y_prime_exact = -numpy.sin(x)
 
-        d2ydx2_2 = floatpy.derivatives.explicit.second_order_differentiator.SecondOrderDifferentiator('second_order', direction=2, \
-                                                                                               data_order='C')
-        d2ydx2_4 = floatpy.derivatives.explicit.second_order_differentiator.SecondOrderDifferentiator('fourth_order', direction=2, \
-                                                                                               data_order='C')
-        d2ydx2_6 = floatpy.derivatives.explicit.second_order_differentiator.SecondOrderDifferentiator('sixth_order', direction=2, \
-                                                                                               data_order='C')
-
-        y_prime_2 = d2ydx2_2.diff(y, dx, 0, True)
-        y_prime_4 = d2ydx2_4.diff(y, dx, 0, True)
-        y_prime_6 = d2ydx2_6.diff(y, dx, 0, True)
+        y_prime_2 = second_der.differentiateSecondOrderFiniteDifference(y, dx, 2, 0, True, 3, 'C')
+        y_prime_4 = second_der.differentiateFourthOrderFiniteDifference(y, dx, 2, 0, True, 3, 'C')
+        y_prime_6 = second_der.differentiateSixthOrderFiniteDifference(y, dx, 2, 0, True, 3, 'C')
 
         error_2 = numpy.linalg.norm(y_prime_exact[0, 0, 0, :] - y_prime_2[0, 0, :])
         error_4 = numpy.linalg.norm(y_prime_exact[0, 0, 0, :] - y_prime_4[0, 0, :])