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ENH: Refactor xarray support into separate module
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| # ========================================================================== | ||
| # | ||
| # Copyright NumFOCUS | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0.txt | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| # | ||
| # ==========================================================================*/ | ||
|
|
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| # also test the import callback feature | ||
|
|
||
| import sys | ||
| import os | ||
| import numpy as np | ||
| import pathlib | ||
|
|
||
| import itk | ||
|
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| filename = sys.argv[1] | ||
|
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| # xarray conversion | ||
| try: | ||
| import xarray as xr | ||
|
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| print("Testing xarray conversion") | ||
|
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| image = itk.imread(filename) | ||
| image.SetSpacing((0.1, 0.2)) | ||
| image.SetOrigin((30.0, 44.0)) | ||
| theta = np.radians(30) | ||
| cosine = np.cos(theta) | ||
| sine = np.sin(theta) | ||
| rotation = np.array(((cosine, -sine), (sine, cosine))) | ||
| image.SetDirection(rotation) | ||
| image["MyMeta"] = 4.0 | ||
|
|
||
| data_array = itk.xarray_from_image(image) | ||
| # Default name | ||
| assert data_array.name == "image" | ||
| image.SetObjectName("test_image") | ||
| data_array = itk.xarray_from_image(image) | ||
| assert data_array.name == "test_image" | ||
| assert data_array.dims[0] == "y" | ||
| assert data_array.dims[1] == "x" | ||
| assert data_array.dims[2] == "c" | ||
| assert np.array_equal(data_array.values, itk.array_from_image(image)) | ||
| assert len(data_array.coords["x"]) == 256 | ||
| assert len(data_array.coords["y"]) == 256 | ||
| assert len(data_array.coords["c"]) == 3 | ||
| assert data_array.coords["x"][0] == 30.0 | ||
| assert data_array.coords["x"][1] == 30.1 | ||
| assert data_array.coords["y"][0] == 44.0 | ||
| assert data_array.coords["y"][1] == 44.2 | ||
| assert data_array.coords["c"][0] == 0 | ||
| assert data_array.coords["c"][1] == 1 | ||
| assert data_array.attrs["direction"][0, 0] == cosine | ||
| assert data_array.attrs["direction"][0, 1] == sine | ||
| assert data_array.attrs["direction"][1, 0] == -sine | ||
| assert data_array.attrs["direction"][1, 1] == cosine | ||
| assert data_array.attrs["MyMeta"] == 4.0 | ||
|
|
||
| round_trip = itk.image_from_xarray(data_array) | ||
| assert round_trip.GetObjectName() == "test_image" | ||
| assert np.array_equal(itk.array_from_image(round_trip), itk.array_from_image(image)) | ||
| spacing = round_trip.GetSpacing() | ||
| assert np.isclose(spacing[0], 0.1) | ||
| assert np.isclose(spacing[1], 0.2) | ||
| origin = round_trip.GetOrigin() | ||
| assert np.isclose(origin[0], 30.0) | ||
| assert np.isclose(origin[1], 44.0) | ||
| direction = round_trip.GetDirection() | ||
| assert np.isclose(direction(0, 0), cosine) | ||
| assert np.isclose(direction(0, 1), -sine) | ||
| assert np.isclose(direction(1, 0), sine) | ||
| assert np.isclose(direction(1, 1), cosine) | ||
| assert round_trip["MyMeta"] == 4.0 | ||
|
|
||
| wrong_order = data_array.swap_dims({"y": "z"}) | ||
| try: | ||
| round_trip = itk.image_from_xarray(wrong_order) | ||
| assert False | ||
| except ValueError: | ||
| pass | ||
|
|
||
| # Check empty array | ||
| empty_array = np.array([], dtype=np.uint8) | ||
| empty_array.shape = (0, 0, 0) | ||
| empty_image = itk.image_from_array(empty_array) | ||
| empty_da = itk.xarray_from_image(empty_image) | ||
| empty_image_round = itk.image_from_xarray(empty_da) | ||
|
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| # Check order | ||
| arr = np.random.randint(0, 255, size=(4, 5, 6), dtype=np.uint8) | ||
| data_array = xr.DataArray(arr, dims=["z", "y", "x"]) | ||
| image = itk.image_from_xarray(data_array) | ||
| assert np.allclose(arr, itk.array_view_from_image(image)) | ||
| assert np.allclose(arr.shape, itk.array_view_from_image(image).shape) | ||
|
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| data_array = xr.DataArray(arr, dims=["x", "y", "z"]) | ||
| image = itk.image_from_xarray(data_array) | ||
| assert np.allclose(arr.transpose(), itk.array_view_from_image(image)) | ||
| assert np.allclose(arr.shape[::-1], itk.array_view_from_image(image).shape) | ||
|
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| data_array = xr.DataArray(arr, dims=["y", "x", "c"]) | ||
| image = itk.image_from_xarray(data_array) | ||
| assert np.allclose(arr, itk.array_view_from_image(image)) | ||
| assert np.allclose(arr.shape, itk.array_view_from_image(image).shape) | ||
|
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| data_array = xr.DataArray(arr, dims=["c", "x", "y"]) | ||
| image = itk.image_from_xarray(data_array) | ||
| assert np.allclose(arr.transpose(), itk.array_view_from_image(image)) | ||
| assert np.allclose(arr.shape[::-1], itk.array_view_from_image(image).shape) | ||
|
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| data_array = xr.DataArray(arr, dims=["q", "x", "y"]) | ||
| try: | ||
| image = itk.image_from_xarray(data_array) | ||
| assert False | ||
| except ValueError: | ||
| pass | ||
|
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| if "(<itkCType unsigned char>, 4)" in itk.Image.GetTypesAsList(): | ||
| arr = np.random.randint(0, 255, size=(4, 5, 6, 3), dtype=np.uint8) | ||
| data_array = xr.DataArray(arr, dims=["t", "z", "y", "x"]) | ||
| image = itk.image_from_xarray(data_array) | ||
| assert np.allclose(arr, itk.array_view_from_image(image)) | ||
| assert np.allclose(arr.shape, itk.array_view_from_image(image).shape) | ||
|
|
||
| except ImportError: | ||
| print("xarray not imported. Skipping xarray conversion tests") | ||
| pass |
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