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"""Test if the NumPy array support for VTK data arrays works correctly.
The test requires that numpy (http://numpy.scipy.org) work.
Run this test like so:
$ vtkpython TestNumpySupport.py
or
$ python TestNumpySupport.py
"""
import sys
import vtk
from vtk.test import Testing
try:
import numpy
except ImportError:
print("Numpy (http://numpy.scipy.org) not found.")
print("This test requires numpy!")
Testing.skip()
from vtk.util.numpy_support import numpy_to_vtk, vtk_to_numpy
import vtk.numpy_interface.dataset_adapter as dsa
class TestNumpySupport(Testing.vtkTest):
def _check_arrays(self, arr, vtk_arr):
"""Private method to check array.
"""
self.assertEqual(vtk_arr.GetNumberOfTuples(), len(arr))
if len(arr.shape) == 2:
dim1 = arr.shape[1]
self.assertEqual(vtk_arr.GetNumberOfComponents(), dim1)
for i in range(len(arr)):
if dim1 in [1,2,3,4,9]:
res = getattr(vtk_arr, 'GetTuple%s'%dim1)(i)
self.assertEqual(numpy.sum(res - arr[i]), 0)
else:
res = [vtk_arr.GetComponent(i, j) for j in range(dim1)]
self.assertEqual(numpy.sum(res - arr[i]), 0)
else:
for i in range(len(arr)):
self.assertEqual(vtk_arr.GetTuple1(i), arr[i])
def testNumpy2VTK(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, 4294967295], 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 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 = numpy_to_vtk(z)
# Test for memory leaks.
self.assertEqual(vtk_arr.GetReferenceCount(), 1)
self._check_arrays(z, vtk_arr)
z1 = vtk_to_numpy(vtk_arr)
if len(z.shape) == 1:
self.assertEqual(len(z1.shape), 1)
self.assertEqual(sum(numpy.ravel(z) - numpy.ravel(z1)), 0)
def testNumpyView(self):
"Test if the numpy and VTK array share the same data."
# ----------------------------------------
# Test if the array is copied or not.
a = numpy.array([[1, 2, 3],[4, 5, 6]], 'd')
vtk_arr = numpy_to_vtk(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.))
def testNumpyConversion(self):
"Test that converting data copies data properly."
# ----------------------------------------
# Test if the array is copied or not.
a = numpy.array([[1, 2, 3],[4, 5, 6]], 'd')
vtk_arr = numpy_to_vtk(a, 0, vtk.VTK_INT)
# 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), (1., 2., 3.))
def testExceptions(self):
"Test if the right assertion errors are raised."
# Test if bit arrays raise an exception.
vtk_arr = vtk.vtkBitArray()
vtk_arr.InsertNextValue(0)
vtk_arr.InsertNextValue(1)
self.assertRaises(AssertionError, vtk_to_numpy, vtk_arr)
def testNonContiguousArray(self):
"Test if the non contiguous array are supported"
a = numpy.array(range(1, 19), 'd')
a.shape = (3, 6)
x = a[::2, ::2]
vtk_array = numpy_to_vtk(x)
self.assertEqual(vtk_array.GetTuple3(0), (1., 3., 5.))
self.assertEqual(vtk_array.GetTuple3(1), (13., 15., 17.))
def testNumpyReferenceWhenDelete(self):
"Test if the vtk array keeps the numpy reference in memory"
np_array = numpy.array([[1., 3., 5.], [13., 15., 17.]], 'd')
vtk_array = numpy_to_vtk(np_array)
del np_array
np_array = numpy.array([])
import gc
gc.collect()
self.assertEqual(vtk_array.GetTuple3(0), (1., 3., 5.))
self.assertEqual(vtk_array.GetTuple3(1), (13., 15., 17.))
def testNumpyReduce(self):
"Test that reducing methods return scalars."
vtk_array = vtk.vtkLongArray()
for i in range(0, 10):
vtk_array.InsertNextValue(i)
numpy_vtk_array = dsa.vtkDataArrayToVTKArray(vtk_array)
s = numpy_vtk_array.sum()
self.assertEqual(s, 45)
self.assertTrue(isinstance(s, numpy.signedinteger))
m = numpy_vtk_array.mean()
self.assertEqual(m, 4.5)
self.assertTrue(isinstance(m, numpy.floating))
if __name__ == "__main__":
Testing.main([(TestNumpySupport, 'test')])
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