def test_arr2cell_array(self):
"""Test Numeric array to vtkCellArray conversion."""
# Test list of lists.
a = [[0], [1, 2], [3, 4, 5], [6, 7, 8, 9]]
cells = array_handler.array2vtkCellArray(a)
z = numpy.array([1, 0, 2, 1,2, 3, 3,4,5, 4, 6,7,8,9])
arr = array_handler.vtk2array(cells.GetData())
self.assertEqual(numpy.sum(arr - z), 0)
self.assertEqual(len(arr.shape), 1)
self.assertEqual(len(arr), 14)
# Test if optional argument stuff also works.
cells = vtk.vtkCellArray()
ident = id(cells)
cells = array_handler.array2vtkCellArray(a, cells)
self.assertEqual(id(cells), ident)
arr = array_handler.vtk2array(cells.GetData())
self.assertEqual(numpy.sum(arr - z), 0)
self.assertEqual(cells.GetNumberOfCells(), 4)
# Make sure this resets the cell array and does not add to the
# existing list!
cells = array_handler.array2vtkCellArray(a, cells)
self.assertEqual(cells.GetNumberOfCells(), 4)
# Test Numeric array handling.
N = 3
a = numpy.zeros((N,3), numpy.int)
a[:,1] = 1
a[:,2] = 2
cells = array_handler.array2vtkCellArray(a)
arr = array_handler.vtk2array(cells.GetData())
expect = numpy.array([3, 0, 1, 2]*3, numpy.int)
self.assertEqual(numpy.alltrue(numpy.equal(arr, expect)),
True)
self.assertEqual(cells.GetNumberOfCells(), N)
# Test if a list of Numeric arrays of different cell lengths works.
l_a = [a[:,:1], a, a[:2,:2]]
cells = array_handler.array2vtkCellArray(l_a)
arr = array_handler.vtk2array(cells.GetData())
expect = numpy.array([1, 0]*3 + [3, 0, 1, 2]*3 + [2, 0,1]*2, numpy.int)
self.assertEqual(numpy.alltrue(numpy.equal(arr, expect)),
True)
self.assertEqual(cells.GetNumberOfCells(), N*2 + 2)
# This should not take a long while. This merely tests if a
# million cells can be created rapidly.
N = int(1e6)
a = numpy.zeros((N,3), numpy.int)
a[:,1] = 1
a[:,2] = 2
cells = array_handler.array2vtkCellArray(a)
self.assertEqual(cells.GetNumberOfCells(), N)
def test_arr2cell_array(self):
"""Test Numeric array to vtkCellArray conversion."""
# Test list of lists.
a = [[0], [1, 2], [3, 4, 5], [6, 7, 8, 9]]
cells = array_handler.array2vtkCellArray(a)
z = numpy.array([1, 0, 2, 1, 2, 3, 3, 4, 5, 4, 6, 7, 8, 9])
arr = array_handler.vtk2array(cells.GetData())
self.assertEqual(numpy.sum(arr - z), 0)
self.assertEqual(len(arr.shape), 1)
self.assertEqual(len(arr), 14)
# Test if optional argument stuff also works.
cells = vtk.vtkCellArray()
ident = id(cells)
cells = array_handler.array2vtkCellArray(a, cells)
self.assertEqual(id(cells), ident)
arr = array_handler.vtk2array(cells.GetData())
self.assertEqual(numpy.sum(arr - z), 0)
self.assertEqual(cells.GetNumberOfCells(), 4)
# Make sure this resets the cell array and does not add to the
# existing list!
cells = array_handler.array2vtkCellArray(a, cells)
self.assertEqual(cells.GetNumberOfCells(), 4)
# Test Numeric array handling.
N = 3
a = numpy.zeros((N, 3), numpy.int)
a[:, 1] = 1
a[:, 2] = 2
cells = array_handler.array2vtkCellArray(a)
arr = array_handler.vtk2array(cells.GetData())
expect = numpy.array([3, 0, 1, 2] * 3, numpy.int)
self.assertEqual(numpy.alltrue(numpy.equal(arr, expect)), True)
self.assertEqual(cells.GetNumberOfCells(), N)
# Test if a list of Numeric arrays of different cell lengths works.
l_a = [a[:, :1], a, a[:2, :2]]
cells = array_handler.array2vtkCellArray(l_a)
arr = array_handler.vtk2array(cells.GetData())
expect = numpy.array([1, 0] * 3 + [3, 0, 1, 2] * 3 + [2, 0, 1] * 2,
numpy.int)
self.assertEqual(numpy.alltrue(numpy.equal(arr, expect)), True)
self.assertEqual(cells.GetNumberOfCells(), N * 2 + 2)
# This should not take a long while. This merely tests if a
# million cells can be created rapidly.
N = int(1e6)
a = numpy.zeros((N, 3), numpy.int)
a[:, 1] = 1
a[:, 2] = 2
cells = array_handler.array2vtkCellArray(a)
self.assertEqual(cells.GetNumberOfCells(), N)
def test_deref_array(self):
"""Test if dereferencing array args works correctly."""
sigs = [[['vtkDataArray']],
[['vtkFloatArray']],
[['vtkCellArray']],
[['vtkPoints']],
[['int', 'vtkIdList']],
[['int', ('float', 'float'), 'vtkDataArray']],
[['Prop', 'int', 'vtkDataArray']],
[['Points', ('float', 'float', 'float')]]
]
args = [[[1,2,3]],
[[0,0,0]],
[[[1,2,3],[4,5,6]]],
[[[0.,0.,0.], [1.,1.,1.]]],
[1, [1,2,3]],
[1, (0.0, 0.0), [1.0, 1.0, 1.0]],
[Prop(), 1, numpy.array([1.0, 1.0, 1.0])],
[[[1,2,3]], [1,2,3]]
]
r = array_handler.deref_array(args[0], sigs[0])
self.assertEqual(mysum(array_handler.vtk2array(r[0]) -args[0]), 0)
r = array_handler.deref_array(args[1], sigs[1])
self.assertEqual(mysum(array_handler.vtk2array(r[0]) - args[1]), 0)
r = array_handler.deref_array(args[2], sigs[2])
self.assertEqual(r[0].GetNumberOfCells(), 2)
r = array_handler.deref_array(args[3], sigs[3])
self.assertEqual(mysum(array_handler.vtk2array(r[0].GetData()) -
numpy.array(args[3], 'f')), 0)
r = array_handler.deref_array(args[4], sigs[4])
self.assertEqual(r[0], 1)
self.assertEqual(r[1].__class__.__name__, 'vtkIdList')
r = array_handler.deref_array(args[5], sigs[5])
self.assertEqual(r[0], 1)
self.assertEqual(r[1], (0.0, 0.0))
self.assertEqual(mysum(array_handler.vtk2array(r[2]) -args[5][2]), 0)
r = array_handler.deref_array(args[6], sigs[6])
self.assertEqual(r[0].IsA('vtkProperty'), True)
self.assertEqual(r[1], 1)
self.assertEqual(mysum(array_handler.vtk2array(r[2]) -args[6][2]), 0)
r = array_handler.deref_array(args[7], sigs[7])
def test_id_array(self):
"""Test if a vtkIdTypeArray is converted correctly."""
arr = vtk.vtkIdTypeArray()
arr.SetNumberOfTuples(10)
for i in range(10):
arr.SetValue(i, i)
np = array_handler.vtk2array(arr)
self.assertEqual(numpy.all(np == range(10)), True)
def test_id_array(self):
"""Test if a vtkIdTypeArray is converted correctly."""
arr = vtk.vtkIdTypeArray()
arr.SetNumberOfTuples(10)
for i in range(10):
arr.SetValue(i, i)
np = array_handler.vtk2array(arr)
self.assertEqual(numpy.all(np == range(10)), True)
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 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 test_deref_array(self):
"""Test if dereferencing array args works correctly."""
sigs = [[['vtkDataArray']], [['vtkFloatArray']], [['vtkCellArray']],
[['vtkPoints']], [['int', 'vtkIdList']],
[['int', ('float', 'float'), 'vtkDataArray']],
[['Prop', 'int', 'vtkDataArray']],
[['Points', ('float', 'float', 'float')]]]
args = [[[1, 2, 3]], [[0, 0, 0]], [[[1, 2, 3], [4, 5, 6]]],
[[[0., 0., 0.], [1., 1., 1.]]], [1, [1, 2, 3]],
[1, (0.0, 0.0), [1.0, 1.0, 1.0]],
[Prop(), 1, numpy.array([1.0, 1.0, 1.0])],
[[[1, 2, 3]], [1, 2, 3]]]
r = array_handler.deref_array(args[0], sigs[0])
self.assertEqual(mysum(array_handler.vtk2array(r[0]) - args[0]), 0)
r = array_handler.deref_array(args[1], sigs[1])
self.assertEqual(mysum(array_handler.vtk2array(r[0]) - args[1]), 0)
r = array_handler.deref_array(args[2], sigs[2])
self.assertEqual(r[0].GetNumberOfCells(), 2)
r = array_handler.deref_array(args[3], sigs[3])
self.assertEqual(
mysum(
array_handler.vtk2array(r[0].GetData()) -
numpy.array(args[3], 'f')), 0)
r = array_handler.deref_array(args[4], sigs[4])
self.assertEqual(r[0], 1)
self.assertEqual(r[1].__class__.__name__, 'vtkIdList')
r = array_handler.deref_array(args[5], sigs[5])
self.assertEqual(r[0], 1)
self.assertEqual(r[1], (0.0, 0.0))
self.assertEqual(mysum(array_handler.vtk2array(r[2]) - args[5][2]), 0)
r = array_handler.deref_array(args[6], sigs[6])
self.assertEqual(r[0].IsA('vtkProperty'), True)
self.assertEqual(r[1], 1)
self.assertEqual(mysum(array_handler.vtk2array(r[2]) - args[6][2]), 0)
r = array_handler.deref_array(args[7], sigs[7])
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))