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from __future__ import annotations
import re
from unittest import mock
import numpy as np
import pandas as pd
import pytest
import vtk as _vtk
from pyvista import examples
from pyvista import pyvista_ndarray
from pyvista import vtk_points
@pytest.fixture
def pyvista_ndarray_1d():
return pyvista_ndarray([1.0, 2.0, 3.0])
def test_slices_are_associated():
dataset = examples.load_structured()
points = pyvista_ndarray(dataset.GetPoints().GetData(), dataset=dataset)
# check that slices of pyvista_ndarray are associated correctly
assert points[1, :].VTKObject == points.VTKObject
assert points[1, :].dataset.Get() == points.dataset.Get()
assert points[1, :].association == points.association
def test_copies_are_not_associated():
dataset = examples.load_structured()
points = pyvista_ndarray(dataset.GetPoints().GetData(), dataset=dataset)
points_2 = points.copy()
# check that copies of pyvista_ndarray are dissociated from the original dataset
assert points_2.VTKObject is None
assert points_2.dataset is None
assert points_2.association.name == 'NONE'
assert not np.shares_memory(points, points_2)
def test_modifying_modifies_dataset():
dataset = examples.load_structured()
points = pyvista_ndarray(dataset.GetPoints().GetData(), dataset=dataset)
dataset_modified = mock.Mock()
array_modified = mock.Mock()
dataset.AddObserver(_vtk.vtkCommand.ModifiedEvent, dataset_modified)
points.AddObserver(_vtk.vtkCommand.ModifiedEvent, array_modified)
# __setitem__ calls dataset.Modified() and points.Modified()
points[:] *= 0.5
assert dataset_modified.call_count == 1
assert array_modified.call_count == 1
# __setitem__ with single-indices works does same
points[0, 0] = 0.5
assert dataset_modified.call_count == 2
assert array_modified.call_count == 2
# setting all new points calls dataset.Modified()
dataset.points = points.copy()
assert dataset_modified.call_count == 3
assert array_modified.call_count == 2
# TODO: This currently doesn't work for single element indexing operations!
# in these cases, the __array_finalize__ method is not called
@pytest.mark.skip
def test_slices_are_associated_single_index():
dataset = examples.load_structured()
points = pyvista_ndarray(dataset.GetPoints().GetData(), dataset=dataset)
assert points[1, 1].VTKObject == points.VTKObject
assert points[1, 1].dataset.Get() == points.dataset.Get()
assert points[1, 1].association == points.association
def test_min(pyvista_ndarray_1d):
arr = np.array(pyvista_ndarray_1d)
assert pyvista_ndarray_1d.min() == arr.min()
# also ensure that methods return float-like values just like numpy
assert isinstance(pyvista_ndarray_1d.min(), type(arr.min()))
def test_squeeze(pyvista_ndarray_1d):
reshaped_pvarr = pyvista_ndarray_1d.reshape((3, 1))
assert np.array_equal(reshaped_pvarr.squeeze(), np.array(reshaped_pvarr.squeeze()))
def test_tobytes(pyvista_ndarray_1d):
assert pyvista_ndarray_1d.tobytes() == np.array(pyvista_ndarray_1d).tobytes()
def test_add_1d():
# ensure that 1d single value arrays match numpy
pv_arr = pyvista_ndarray([1]) + pyvista_ndarray([1])
np_arr = np.array([1]) + np.array([1])
assert np.array_equal(pv_arr, np_arr)
@pytest.mark.parametrize('val', [1, True, None])
def test_raises(val):
match = re.escape(
f'pyvista_ndarray got an invalid type {type(val)}. '
f'Expected an Iterable or vtk.vtkAbstractArray'
)
with pytest.raises(TypeError, match=match):
pyvista_ndarray(val)
@pytest.mark.parametrize('obj_in', [np.eye(3), vtk_points(np.eye(3)).GetData()])
def test_wrap_pandas(obj_in):
array = pyvista_ndarray(obj_in)
df = pd.DataFrame(array)
assert np.shares_memory(df.values, array)
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