예제 #1
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def set_arrays(dataset, particle_array):
    """ Code to add all the arrays to a dataset given a particle array."""
    props = set(particle_array.properties.keys())
    # Add the vector data.
    vec = numpy.empty((len(particle_array.x), 3), dtype=float)
    vec[:, 0] = particle_array.u
    vec[:, 1] = particle_array.v
    vec[:, 2] = particle_array.w
    va = tvtk.to_tvtk(array2vtk(vec))
    va.name = "velocity"
    dataset.data.point_data.add_array(vec)
    # Now add the scalar data.
    scalars = props - set(("u", "v", "w"))
    for sc in scalars:
        arr = particle_array.get(sc)
        va = tvtk.to_tvtk(array2vtk(arr))
        va.name = sc
        dataset.data.point_data.add_array(va)
    dataset._update_data()
예제 #2
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 def test_reference_to_array(self):
     """Does to_array return an existing array instead of a new copy."""
     arr = numpy.arange(0.0, 10.0, 0.1)
     arr  = numpy.reshape(arr, (25, 4))
     vtk_arr = array_handler.array2vtk(arr)
     arr1 = array_handler.vtk2array(vtk_arr)
     # Now make sure these are using the same memory.
     arr[0][0] = 100.0
     self.assertEqual(arr[0][0], arr1[0][0])
     self.assertEqual(arr.shape, arr1.shape)
예제 #3
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def set_arrays(dataset, particle_array):
    """ Code to add all the arrays to a dataset given a particle array."""
    props = set(particle_array.properties.keys())
    # Add the vector data.
    vec = numpy.empty((len(particle_array.x), 3), dtype=float)
    vec[:, 0] = particle_array.u
    vec[:, 1] = particle_array.v
    vec[:, 2] = particle_array.w
    va = tvtk.to_tvtk(array2vtk(vec))
    va.name = 'velocity'
    dataset.data.point_data.add_array(vec)
    # Now add the scalar data.
    scalars = props - set(('u', 'v', 'w'))
    for sc in scalars:
        arr = particle_array.get(sc)
        va = tvtk.to_tvtk(array2vtk(arr))
        va.name = sc
        dataset.data.point_data.add_array(va)
    dataset._update_data()
예제 #4
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 def test_reference_to_array(self):
     """Does to_array return an existing array instead of a new copy."""
     arr = numpy.arange(0.0, 10.0, 0.1)
     arr = numpy.reshape(arr, (25, 4))
     vtk_arr = array_handler.array2vtk(arr)
     arr1 = array_handler.vtk2array(vtk_arr)
     # Now make sure these are using the same memory.
     arr[0][0] = 100.0
     self.assertEqual(arr[0][0], arr1[0][0])
     self.assertEqual(arr.shape, arr1.shape)
예제 #5
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 def add_array(self, array, name, category='point'):
     """
     Add an array to the dataset to specified category ('point' or
     'cell').
     """
     assert len(array.shape) <= 2, "Only 2D arrays can be added."
     data = getattr(self.dataset, '%s_data' % category)
     if len(array.shape) == 2:
         assert array.shape[1] in [1, 3, 4, 9], \
                 "Only Nxm arrays where (m in [1,3,4,9]) are supported"
         va = tvtk.to_tvtk(array2vtk(array))
         va.name = name
         data.add_array(va)
         mapping = {1: 'scalars', 3: 'vectors', 4: 'scalars', 9: 'tensors'}
         dict = getattr(self, '%s_%s' % (category, mapping[array.shape[1]]))
         dict[name] = array
     else:
         va = tvtk.to_tvtk(array2vtk(array))
         va.name = name
         data.add_array(va)
         dict = getattr(self, '%s_scalars' % (category))
         dict[name] = array
예제 #6
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 def add_array(self, array, name, category='point'):
     """
     Add an array to the dataset to specified category ('point' or
     'cell').
     """
     assert len(array.shape) <= 2, "Only 2D arrays can be added."
     data = getattr(self.dataset, '%s_data'%category)
     if len(array.shape) == 2:
         assert array.shape[1] in [1, 3, 4, 9], \
                 "Only Nxm arrays where (m in [1,3,4,9]) are supported"
         va = tvtk.to_tvtk(array2vtk(array))
         va.name = name
         data.add_array(va)
         mapping = {1:'scalars', 3: 'vectors', 4: 'scalars', 
                    9: 'tensors'}
         dict = getattr(self, '%s_%s'%(category,
                                       mapping[array.shape[1]]))
         dict[name] = array
     else:
         va = tvtk.to_tvtk(array2vtk(array))
         va.name = name
         data.add_array(va)
         dict = getattr(self, '%s_scalars'%(category))
         dict[name] = array
예제 #7
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    def test_array2vtk(self):
        """Test Numeric array to VTK array conversion and vice-versa."""
        # Put all the test arrays here.
        t_z = []        

        # Test the different types of arrays.
        t_z.append(numpy.array([-128, 0, 127], numpy.int8))

        # FIXME: character arrays are a problem since there is no
        # unique mapping to a VTK data type and back.
        #t_z.append(numpy.array([-128, 0, 127], numpy.character))
        t_z.append(numpy.array([-32768, 0, 32767], numpy.int16))
        t_z.append(numpy.array([-2147483648, 0, 2147483647], numpy.int32))
        t_z.append(numpy.array([0, 255], numpy.uint8))
        t_z.append(numpy.array([0, 65535], numpy.uint16))
        t_z.append(numpy.array([0, 4294967295L], numpy.uint32))
        t_z.append(numpy.array([-1.0e38, 0, 1.0e38], 'f'))
        t_z.append(numpy.array([-1.0e299, 0, 1.0e299], 'd'))

        # Check multi-component arrays.
        t_z.append(numpy.array([[1], [2], [300]], 'd'))
        t_z.append(numpy.array([[1, 20], [300, 4000]], 'd'))
        t_z.append(numpy.array([[1, 2, 3], [4, 5, 6]], 'f'))
        t_z.append(numpy.array([[1, 2, 3],[4, 5, 6]], 'd'))
        t_z.append(numpy.array([[1, 2, 3, 400],[4, 5, 6, 700]],
                                 'd'))
        t_z.append(numpy.array([range(9),range(10,19)], 'f'))

        # Test if a Python list also works.
        t_z.append(numpy.array([[1., 2., 3., 400.],[4, 5, 6, 700]],
                                 'd'))

        # Test if arrays with number of components not in [1,2,3,4,9] work.
        t_z.append(numpy.array([[1, 2, 3, 400, 5000],
                                  [4, 5, 6, 700, 8000]], 'd'))
        t_z.append(numpy.array([range(10), range(10,20)], 'd'))

        for z in t_z:
            vtk_arr = array_handler.array2vtk(z)
            # Test for memory leaks.
            self.assertEqual(vtk_arr.GetReferenceCount(),
                             array_handler.BASE_REFERENCE_COUNT)
            self._check_arrays(z, vtk_arr)
            z1 = array_handler.vtk2array(vtk_arr)
            if len(z.shape) == 1:
                self.assertEqual(len(z1.shape), 1)
            if z.dtype.char != 'c':
                #print z1
                self.assertEqual(sum(numpy.ravel(z) - numpy.ravel(z1)), 0)
            else:
                #print z1.astype('c')
                self.assertEqual(z, z1.astype('c'))
        
        # Check if type conversion works correctly.
        z = numpy.array([-128, 0, 127], numpy.int8)
        vtk_arr = vtk.vtkDoubleArray()
        ident = id(vtk_arr)
        vtk_arr = array_handler.array2vtk(z, vtk_arr)
        # Make sure this is the same array!
        self.assertEqual(ident, id(vtk_arr))
        self._check_arrays(z, vtk_arr)

        # Check the vtkBitArray.
        vtk_arr = vtk.vtkBitArray()
        vtk_arr.InsertNextValue(0)
        vtk_arr.InsertNextValue(1)
        vtk_arr.InsertNextValue(0)
        vtk_arr.InsertNextValue(1)
        arr = array_handler.vtk2array(vtk_arr)
        self.assertEqual(numpy.sum(arr - [0,1,0,1]), 0)
        vtk_arr = array_handler.array2vtk(arr, vtk_arr)
        self.assertEqual(vtk_arr.GetValue(0), 0)
        self.assertEqual(vtk_arr.GetValue(1), 1)
        self.assertEqual(vtk_arr.GetValue(2), 0)
        self.assertEqual(vtk_arr.GetValue(3), 1)

        # ----------------------------------------
        # Test if the array is copied or not.
        a = numpy.array([[1, 2, 3],[4, 5, 6]], 'd')
        vtk_arr = array_handler.array2vtk(a)
        # Change the numpy array and see if the changes are
        # reflected in the VTK array.
        a[0] = [10.0, 20.0, 30.0]
        self.assertEqual(vtk_arr.GetTuple3(0), (10., 20., 30.))

        # Make sure the cache is doing its job.
        key = vtk_arr.__this__
        z = array_handler._array_cache.get(vtk_arr)
        self.assertEqual(numpy.sum(z - numpy.ravel(a)), 0.0)

        l1 = len(array_handler._array_cache)
        # del the Numeric array and see if this still works.
        del a
        self.assertEqual(vtk_arr.GetTuple3(0), (10., 20., 30.))
        # Check the cache -- just making sure.
        self.assertEqual(len(array_handler._array_cache), l1)

        # Delete the VTK array and see if the cache is cleared.
        del vtk_arr
        self.assertEqual(len(array_handler._array_cache), l1-1)
        self.assertEqual(array_handler._array_cache._cache.has_key(key),
                         False)

        # Make sure bit arrays are copied.
        vtk_arr = vtk.vtkBitArray()
        a = numpy.array([0,1,0,1], numpy.int32)
        vtk_arr = array_handler.array2vtk(a, vtk_arr)
        del a
        self.assertEqual(vtk_arr.GetValue(0), 0)
        self.assertEqual(vtk_arr.GetValue(1), 1)
        self.assertEqual(vtk_arr.GetValue(2), 0)
        self.assertEqual(vtk_arr.GetValue(3), 1)
        
        # Make sure the code at least runs for all the non-complex 
        # numerical dtypes in numpy.
        for dtype in (numpy.sctypes['int'] + numpy.sctypes['uint'] +
                            numpy.sctypes['float']):
            array_handler.array2vtk(numpy.zeros((1,), dtype=dtype))
예제 #8
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    def test_array2vtk(self):
        """Test Numeric array to VTK array conversion and vice-versa."""
        # Put all the test arrays here.
        t_z = []

        # Test the different types of arrays.
        t_z.append(numpy.array([-128, 0, 127], numpy.int8))

        # FIXME: character arrays are a problem since there is no
        # unique mapping to a VTK data type and back.
        #t_z.append(numpy.array([-128, 0, 127], numpy.character))
        t_z.append(numpy.array([-32768, 0, 32767], numpy.int16))
        t_z.append(numpy.array([-2147483648, 0, 2147483647], numpy.int32))
        t_z.append(numpy.array([0, 255], numpy.uint8))
        t_z.append(numpy.array([0, 65535], numpy.uint16))
        t_z.append(numpy.array([0, 4294967295L], numpy.uint32))
        t_z.append(numpy.array([-1.0e38, 0, 1.0e38], 'f'))
        t_z.append(numpy.array([-1.0e299, 0, 1.0e299], 'd'))

        # Check multi-component arrays.
        t_z.append(numpy.array([[1], [2], [300]], 'd'))
        t_z.append(numpy.array([[1, 20], [300, 4000]], 'd'))
        t_z.append(numpy.array([[1, 2, 3], [4, 5, 6]], 'f'))
        t_z.append(numpy.array([[1, 2, 3], [4, 5, 6]], 'd'))
        t_z.append(numpy.array([[1, 2, 3, 400], [4, 5, 6, 700]], 'd'))
        t_z.append(numpy.array([range(9), range(10, 19)], 'f'))

        # Test if a Python list also works.
        t_z.append(numpy.array([[1., 2., 3., 400.], [4, 5, 6, 700]], 'd'))

        # Test if arrays with number of components not in [1,2,3,4,9] work.
        t_z.append(
            numpy.array([[1, 2, 3, 400, 5000], [4, 5, 6, 700, 8000]], 'd'))
        t_z.append(numpy.array([range(10), range(10, 20)], 'd'))

        for z in t_z:
            vtk_arr = array_handler.array2vtk(z)
            # Test for memory leaks.
            self.assertEqual(vtk_arr.GetReferenceCount(),
                             array_handler.BASE_REFERENCE_COUNT)
            self._check_arrays(z, vtk_arr)
            z1 = array_handler.vtk2array(vtk_arr)
            if len(z.shape) == 1:
                self.assertEqual(len(z1.shape), 1)
            if z.dtype.char != 'c':
                #print z1
                self.assertEqual(sum(numpy.ravel(z) - numpy.ravel(z1)), 0)
            else:
                #print z1.astype('c')
                self.assertEqual(z, z1.astype('c'))

        # Check if type conversion works correctly.
        z = numpy.array([-128, 0, 127], numpy.int8)
        vtk_arr = vtk.vtkDoubleArray()
        ident = id(vtk_arr)
        vtk_arr = array_handler.array2vtk(z, vtk_arr)
        # Make sure this is the same array!
        self.assertEqual(ident, id(vtk_arr))
        self._check_arrays(z, vtk_arr)

        # Check the vtkBitArray.
        vtk_arr = vtk.vtkBitArray()
        vtk_arr.InsertNextValue(0)
        vtk_arr.InsertNextValue(1)
        vtk_arr.InsertNextValue(0)
        vtk_arr.InsertNextValue(1)
        arr = array_handler.vtk2array(vtk_arr)
        self.assertEqual(numpy.sum(arr - [0, 1, 0, 1]), 0)
        vtk_arr = array_handler.array2vtk(arr, vtk_arr)
        self.assertEqual(vtk_arr.GetValue(0), 0)
        self.assertEqual(vtk_arr.GetValue(1), 1)
        self.assertEqual(vtk_arr.GetValue(2), 0)
        self.assertEqual(vtk_arr.GetValue(3), 1)

        # ----------------------------------------
        # Test if the array is copied or not.
        a = numpy.array([[1, 2, 3], [4, 5, 6]], 'd')
        vtk_arr = array_handler.array2vtk(a)
        # Change the numpy array and see if the changes are
        # reflected in the VTK array.
        a[0] = [10.0, 20.0, 30.0]
        self.assertEqual(vtk_arr.GetTuple3(0), (10., 20., 30.))

        # Make sure the cache is doing its job.
        key = vtk_arr.__this__
        z = array_handler._array_cache.get(vtk_arr)
        self.assertEqual(numpy.sum(z - numpy.ravel(a)), 0.0)

        l1 = len(array_handler._array_cache)
        # del the Numeric array and see if this still works.
        del a
        self.assertEqual(vtk_arr.GetTuple3(0), (10., 20., 30.))
        # Check the cache -- just making sure.
        self.assertEqual(len(array_handler._array_cache), l1)

        # Delete the VTK array and see if the cache is cleared.
        del vtk_arr
        self.assertEqual(len(array_handler._array_cache), l1 - 1)
        self.assertEqual(array_handler._array_cache._cache.has_key(key), False)

        # Make sure bit arrays are copied.
        vtk_arr = vtk.vtkBitArray()
        a = numpy.array([0, 1, 0, 1], numpy.int32)
        vtk_arr = array_handler.array2vtk(a, vtk_arr)
        del a
        self.assertEqual(vtk_arr.GetValue(0), 0)
        self.assertEqual(vtk_arr.GetValue(1), 1)
        self.assertEqual(vtk_arr.GetValue(2), 0)
        self.assertEqual(vtk_arr.GetValue(3), 1)

        # Make sure the code at least runs for all the non-complex
        # numerical dtypes in numpy.
        for dtype in (numpy.sctypes['int'] + numpy.sctypes['uint'] +
                      numpy.sctypes['float']):
            array_handler.array2vtk(numpy.zeros((1, ), dtype=dtype))