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()
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)
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()
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)
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
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
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))
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))