Viewing File: /home/ubuntu/combine_ai/combine/lib/python3.10/site-packages/skimage/io/tests/test_tifffile.py
import pathlib
from tempfile import NamedTemporaryFile
import numpy as np
import pytest
from numpy.testing import assert_array_almost_equal, assert_array_equal
from skimage._shared.testing import fetch
from skimage.io import imread, imsave, reset_plugins, use_plugin
def setup():
use_plugin('tifffile')
np.random.seed(0)
def teardown():
reset_plugins()
def test_imread_uint16():
expected = np.load(fetch('data/chessboard_GRAY_U8.npy'))
img = imread(fetch('data/chessboard_GRAY_U16.tif'))
assert img.dtype == np.uint16
assert_array_almost_equal(img, expected)
def test_imread_uint16_big_endian():
expected = np.load(fetch('data/chessboard_GRAY_U8.npy'))
img = imread(fetch('data/chessboard_GRAY_U16B.tif'))
assert img.dtype == np.uint16
assert_array_almost_equal(img, expected)
def test_imread_multipage_rgb_tif():
img = imread(fetch('data/multipage_rgb.tif'))
assert img.shape == (2, 10, 10, 3), img.shape
def test_tifffile_kwarg_passthrough ():
img = imread(fetch('data/multipage.tif'), key=[1], is_ome=True)
assert img.shape == (15, 10), img.shape
def test_imread_handle():
expected = np.load(fetch('data/chessboard_GRAY_U8.npy'))
with open(fetch('data/chessboard_GRAY_U16.tif'), 'rb') as fh:
img = imread(fh)
assert img.dtype == np.uint16
assert_array_almost_equal(img, expected)
class TestSave:
def roundtrip(self, dtype, x, use_pathlib=False, **kwargs):
with NamedTemporaryFile(suffix='.tif') as f:
fname = f.name
if use_pathlib:
fname = pathlib.Path(fname)
imsave(fname, x, check_contrast=False, **kwargs)
y = imread(fname)
assert_array_equal(x, y)
shapes = ((10, 10), (10, 10, 3), (10, 10, 4))
dtypes = (np.uint8, np.uint16, np.float32, np.int16, np.float64)
@pytest.mark.parametrize("shape", shapes)
@pytest.mark.parametrize("dtype", dtypes)
@pytest.mark.parametrize("use_pathlib", [False, True])
@pytest.mark.parametrize('explicit_photometric_kwarg', [False, True])
def test_imsave_roundtrip(self, shape, dtype, use_pathlib,
explicit_photometric_kwarg):
x = np.random.rand(*shape)
if not np.issubdtype(dtype, np.floating):
x = (x * np.iinfo(dtype).max).astype(dtype)
else:
x = x.astype(dtype)
if explicit_photometric_kwarg and x.shape[-1] in [3, 4]:
kwargs = {'photometric': 'rgb'}
else:
kwargs = {}
self.roundtrip(dtype, x, use_pathlib, **kwargs)
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