using for loop to install conda package

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_collection.py

@@ -0,0 +1,154 @@
+import os
+
+import numpy as np
+import imageio
+from skimage import data_dir
+from skimage.io.collection import ImageCollection, MultiImage, alphanumeric_key
+from skimage.io import reset_plugins
+
+from skimage._shared import testing
+from skimage._shared.testing import assert_equal, assert_allclose, fetch
+
+import pytest
+
+
+try:
+    has_pooch = True
+except ModuleNotFoundError:
+    has_pooch = False
+
+
+def test_string_split():
+    test_string = 'z23a'
+    test_str_result = ['z', 23, 'a']
+    assert_equal(alphanumeric_key(test_string), test_str_result)
+
+
+def test_string_sort():
+    filenames = ['f9.10.png', 'f9.9.png', 'f10.10.png', 'f10.9.png',
+                 'e9.png', 'e10.png', 'em.png']
+    expected_filenames = ['e9.png', 'e10.png', 'em.png', 'f9.9.png',
+                          'f9.10.png', 'f10.9.png', 'f10.10.png']
+    sorted_filenames = sorted(filenames, key=alphanumeric_key)
+    assert_equal(expected_filenames, sorted_filenames)
+
+def test_imagecollection_input():
+    """Test function for ImageCollection. The new behavior (implemented
+    in 0.16) allows the `pattern` argument to accept a list of strings
+    as the input.
+
+    Notes
+    -----
+        If correct, `images` will receive three images.
+    """
+    # Ensure that these images are part of the legacy datasets
+    # this means they will always be available in the user's install
+    # regardless of the availability of pooch
+    pattern = [os.path.join(data_dir, pic)
+               for pic in ['coffee.png',
+                           'chessboard_GRAY.png',
+                           'rocket.jpg']]
+    images = ImageCollection(pattern)
+    assert len(images) == 3
+
+
+class TestImageCollection():
+    pattern = [os.path.join(data_dir, pic)
+               for pic in ['brick.png', 'color.png']]
+
+    pattern_matched = [os.path.join(data_dir, pic)
+                       for pic in ['brick.png', 'moon.png']]
+
+    def setup_method(self):
+        reset_plugins()
+        # Generic image collection with images of different shapes.
+        self.images = ImageCollection(self.pattern)
+        # Image collection with images having shapes that match.
+        self.images_matched = ImageCollection(self.pattern_matched)
+        # Same images as a collection of frames
+        self.frames_matched = MultiImage(self.pattern_matched)
+
+    def test_len(self):
+        assert len(self.images) == 2
+
+    def test_getitem(self):
+        num = len(self.images)
+        for i in range(-num, num):
+            assert isinstance(self.images[i], np.ndarray)
+        assert_allclose(self.images[0],
+                        self.images[-num])
+
+        def return_img(n):
+            return self.images[n]
+        with testing.raises(IndexError):
+            return_img(num)
+        with testing.raises(IndexError):
+            return_img(-num - 1)
+
+    def test_slicing(self):
+        assert type(self.images[:]) is ImageCollection
+        assert len(self.images[:]) == 2
+        assert len(self.images[:1]) == 1
+        assert len(self.images[1:]) == 1
+        assert_allclose(self.images[0], self.images[:1][0])
+        assert_allclose(self.images[1], self.images[1:][0])
+        assert_allclose(self.images[1], self.images[::-1][0])
+        assert_allclose(self.images[0], self.images[::-1][1])
+
+    def test_files_property(self):
+        assert isinstance(self.images.files, list)
+
+        def set_files(f):
+            self.images.files = f
+        with testing.raises(AttributeError):
+            set_files('newfiles')
+
+    @pytest.mark.skipif(not has_pooch, reason="needs pooch to download data")
+    def test_custom_load_func_sequence(self):
+        filename = fetch('data/no_time_for_that_tiny.gif')
+
+        def reader(frameno):
+            vid = imageio.get_reader(filename)
+            return vid.get_data(frameno)
+
+        ic = ImageCollection(range(24), load_func=reader)
+        # the length of ic should be that of the given load_pattern sequence
+        assert len(ic) == 24
+        # GIF file has frames of size 25x14 with 4 channels (RGBA)
+        assert ic[0].shape == (25, 14, 4)
+
+    @pytest.mark.skipif(not has_pooch, reason="needs pooch to download data")
+    def test_custom_load_func_w_kwarg(self):
+        load_pattern = fetch('data/no_time_for_that_tiny.gif')
+
+        def load_fn(f, step):
+            vid = imageio.get_reader(f)
+            seq = [v for v in vid.iter_data()]
+            return seq[::step]
+
+        ic = ImageCollection(load_pattern, load_func=load_fn, step=3)
+        # Each file should map to one image (array).
+        assert len(ic) == 1
+        # GIF file has 24 frames, so 24 / 3 equals 8.
+        assert len(ic[0]) == 8
+
+    def test_custom_load_func(self):
+
+        def load_fn(x):
+            return x
+
+        ic = ImageCollection(os.pathsep.join(self.pattern), load_func=load_fn)
+        assert_equal(ic[0], self.pattern[0])
+
+    def test_concatenate(self):
+        array = self.images_matched.concatenate()
+        expected_shape = (len(self.images_matched),) + self.images[0].shape
+        assert_equal(array.shape, expected_shape)
+
+    def test_concatenate_mismatched_image_shapes(self):
+        with testing.raises(ValueError):
+            self.images.concatenate()
+
+    def test_multiimage_imagecollection(self):
+        assert_equal(self.images_matched[0], self.frames_matched[0])
+        assert_equal(self.images_matched[1], self.frames_matched[1])

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_fits.py

@@ -0,0 +1,32 @@
+import numpy as np
+import skimage.io as io
+from skimage._shared import testing
+
+testing.pytest.importorskip('astropy')
+
+
+def test_fits_plugin_import():
+    # Make sure we get an import exception if Astropy isn't there
+    # (not sure how useful this is, but it ensures there isn't some other
+    # error when trying to load the plugin)
+    try:
+        io.use_plugin('fits')
+    except ImportError:
+        raise()
+
+
+def teardown():
+    io.reset_plugins()
+
+
+def _same_ImageCollection(collection1, collection2):
+    """
+    Ancillary function to compare two ImageCollection objects, checking that
+    their constituent arrays are equal.
+    """
+    if len(collection1) != len(collection2):
+        return False
+    for ext1, ext2 in zip(collection1, collection2):
+        if not np.all(ext1 == ext2):
+            return False
+    return True

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_histograms.py

@@ -0,0 +1,25 @@
+import numpy as np
+from skimage.io._plugins._histograms import histograms
+
+from skimage._shared.testing import assert_array_equal, assert_equal, TestCase
+
+
+class TestHistogram(TestCase):
+    def test_basic(self):
+        img = np.ones((50, 50, 3), dtype=np.uint8)
+        r, g, b, v = histograms(img, 255)
+
+        for band in (r, g, b, v):
+            yield assert_equal, band.sum(), 50 * 50
+
+    def test_counts(self):
+        channel = np.arange(255).reshape(51, 5)
+        img = np.empty((51, 5, 3), dtype='uint8')
+        img[:, :, 0] = channel
+        img[:, :, 1] = channel
+        img[:, :, 2] = channel
+        r, g, b, v = histograms(img, 255)
+        assert_array_equal(r, g)
+        assert_array_equal(r, b)
+        assert_array_equal(r, v)
+        assert_array_equal(r, np.ones(255))

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_imageio.py

@@ -0,0 +1,80 @@
+from tempfile import NamedTemporaryFile
+
+import numpy as np
+from skimage.io import imread, imsave, use_plugin, reset_plugins
+
+from skimage._shared import testing
+from skimage._shared.testing import assert_array_almost_equal, TestCase, fetch
+from skimage._shared._warnings import expected_warnings
+
+
+def setup():
+    use_plugin('imageio')
+
+
+def teardown():
+    reset_plugins()
+
+
+def test_imageio_as_gray():
+
+    img = imread(fetch('data/color.png'), as_gray=True)
+    assert img.ndim == 2
+    assert img.dtype == np.float64
+    img = imread(fetch('data/camera.png'), as_gray=True)
+    # check that conversion does not happen for a gray image
+    assert np.sctype2char(img.dtype) in np.typecodes['AllInteger']
+
+
+def test_imageio_palette():
+    img = imread(fetch('data/palette_color.png'))
+    assert img.ndim == 3
+
+
+def test_imageio_truncated_jpg():
+    # imageio>2.0 uses Pillow / PIL to try and load the file.
+    # Oddly, PIL explicitly raises a SyntaxError when the file read fails.
+    # The exception type changed from SyntaxError to OSError in PIL 8.2.0, so
+    # allow for either to be raised.
+    with testing.raises((OSError, SyntaxError)):
+        imread(fetch('data/truncated.jpg'))
+
+
+class TestSave(TestCase):
+
+    def roundtrip(self, x, scaling=1):
+        with NamedTemporaryFile(suffix='.png') as f:
+            fname = f.name
+
+        imsave(fname, x)
+        y = imread(fname)
+
+        assert_array_almost_equal((x * scaling).astype(np.int32), y)
+
+    def test_imsave_roundtrip(self):
+        dtype = np.uint8
+        np.random.seed(0)
+        for shape in [(10, 10), (10, 10, 3), (10, 10, 4)]:
+            x = np.ones(shape, dtype=dtype) * np.random.rand(*shape)
+
+            if np.issubdtype(dtype, np.floating):
+                yield self.roundtrip, x, 255
+            else:
+                x = (x * 255).astype(dtype)
+                yield self.roundtrip, x
+
+    def test_bool_array_save(self):
+        with NamedTemporaryFile(suffix='.png') as f:
+            fname = f.name
+
+        with expected_warnings(['.* is a boolean image']):
+            a = np.zeros((5, 5), bool)
+            a[2, 2] = True
+            imsave(fname, a)
+
+
+def test_return_class():
+    testing.assert_equal(
+        type(imread(fetch('data/color.png'))),
+        np.ndarray
+    )

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_imread.py

@@ -0,0 +1,70 @@
+from tempfile import NamedTemporaryFile
+
+import numpy as np
+from skimage import io
+from skimage.io import imread, imsave, use_plugin, reset_plugins
+
+from skimage._shared import testing
+from skimage._shared.testing import (TestCase, assert_array_equal,
+                                     assert_array_almost_equal, fetch)
+
+from pytest import importorskip
+
+importorskip('imread')
+
+def setup():
+    use_plugin('imread')
+
+
+def teardown():
+    reset_plugins()
+
+
+def test_imread_as_gray():
+    img = imread(fetch('data/color.png'), as_gray=True)
+    assert img.ndim == 2
+    assert img.dtype == np.float64
+    img = imread(fetch('data/camera.png'), as_gray=True)
+    # check that conversion does not happen for a gray image
+    assert np.sctype2char(img.dtype) in np.typecodes['AllInteger']
+
+
+def test_imread_palette():
+    img = imread(fetch('data/palette_color.png'))
+    assert img.ndim == 3
+
+
+def test_imread_truncated_jpg():
+    with testing.raises(RuntimeError):
+        io.imread(fetch('data/truncated.jpg'))
+
+
+def test_bilevel():
+    expected = np.zeros((10, 10), bool)
+    expected[::2] = 1
+
+    img = imread(fetch('data/checker_bilevel.png'))
+    assert_array_equal(img.astype(bool), expected)
+
+
+class TestSave(TestCase):
+    def roundtrip(self, x, scaling=1):
+        with NamedTemporaryFile(suffix='.png') as f:
+            fname = f.name
+
+        imsave(fname, x)
+        y = imread(fname)
+
+        assert_array_almost_equal((x * scaling).astype(np.int32), y)
+
+    def test_imsave_roundtrip(self):
+        dtype = np.uint8
+        np.random.seed(0)
+        for shape in [(10, 10), (10, 10, 3), (10, 10, 4)]:
+            x = np.ones(shape, dtype=dtype) * np.random.rand(*shape)
+
+            if np.issubdtype(dtype, np.floating):
+                yield self.roundtrip, x, 255
+            else:
+                x = (x * 255).astype(dtype)
+                yield self.roundtrip, x

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_io.py

@@ -0,0 +1,120 @@
+import os
+import pathlib
+import tempfile
+
+import numpy as np
+import pytest
+
+from skimage import io
+from skimage._shared.testing import assert_array_equal, fetch
+from skimage.data import data_dir
+
+
+one_by_one_jpeg = (
+    b'\xff\xd8\xff\xe0\x00\x10JFIF\x00\x01\x01\x00\x00\x01'
+    b'\x00\x01\x00\x00\xff\xdb\x00C\x00\x03\x02\x02\x02\x02'
+    b'\x02\x03\x02\x02\x02\x03\x03\x03\x03\x04\x06\x04\x04'
+    b'\x04\x04\x04\x08\x06\x06\x05\x06\t\x08\n\n\t\x08\t\t'
+    b'\n\x0c\x0f\x0c\n\x0b\x0e\x0b\t\t\r\x11\r\x0e\x0f\x10'
+    b'\x10\x11\x10\n\x0c\x12\x13\x12\x10\x13\x0f\x10\x10'
+    b'\x10\xff\xc0\x00\x0b\x08\x00\x01\x00\x01\x01\x01\x11'
+    b'\x00\xff\xc4\x00\x14\x00\x01\x00\x00\x00\x00\x00\x00'
+    b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\t\xff\xc4\x00'
+    b'\x14\x10\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
+    b'\x00\x00\x00\x00\x00\x00\xff\xda\x00\x08\x01\x01\x00'
+    b'\x00?\x00*\x9f\xff\xd9'
+)
+
+
+def test_stack_basic():
+    x = np.arange(12).reshape(3, 4)
+    io.push(x)
+
+    assert_array_equal(io.pop(), x)
+
+
+def test_stack_non_array():
+    with pytest.raises(ValueError):
+        io.push([[1, 2, 3]])
+
+
+def test_imread_file_url():
+    # tweak data path so that file URI works on both unix and windows.
+    data_path = str(fetch('data/camera.png'))
+    data_path = data_path.replace(os.path.sep, '/')
+    image_url = f'file:///{data_path}'
+    image = io.imread(image_url)
+    assert image.shape == (512, 512)
+
+
+def test_imread_http_url(httpserver):
+    # httpserver is a fixture provided by pytest-localserver
+    # https://bitbucket.org/pytest-dev/pytest-localserver/
+    httpserver.serve_content(one_by_one_jpeg)
+    # it will serve anything you provide to it on its url.
+    # we add a /test.jpg so that we can identify the content
+    # by extension
+    image = io.imread(httpserver.url + '/test.jpg' + '?' + 's' * 266)
+    assert image.shape == (1, 1)
+
+
+def test_imread_pathlib_tiff():
+    """Tests reading from Path object (issue gh-5545)."""
+
+    # read via fetch
+    expected = io.imread(fetch('data/multipage.tif'))
+
+    # read by passing in a pathlib.Path object
+    fname = os.path.join(data_dir, 'multipage.tif')
+    path = pathlib.Path(fname)
+    img = io.imread(path)
+
+    assert img.shape == (2, 15, 10)
+    assert_array_equal(expected, img)
+
+
+def _named_tempfile_func(error_class):
+    """Create a mock function for NamedTemporaryFile that always raises.
+
+    Parameters
+    ----------
+    error_class : exception class
+        The error that should be raised when asking for a NamedTemporaryFile.
+
+    Returns
+    -------
+    named_temp_file : callable
+        A function that always raises the desired error.
+
+    Notes
+    -----
+    Although this function has general utility for raising errors, it is
+    expected to be used to raise errors that ``tempfile.NamedTemporaryFile``
+    from the Python standard library could raise. As of this writing, these
+    are ``FileNotFoundError``, ``FileExistsError``, ``PermissionError``, and
+    ``BaseException``. See
+    `this comment <https://github.com/scikit-image/scikit-image/issues/3785#issuecomment-486598307>`__  # noqa
+    for more information.
+    """
+    def named_temp_file(*args, **kwargs):
+        raise error_class()
+    return named_temp_file
+
+
+@pytest.mark.parametrize(
+    'error_class', [
+        FileNotFoundError, FileExistsError, PermissionError, BaseException
+    ]
+)
+def test_failed_temporary_file(monkeypatch, error_class):
+    fetch('data/camera.png')
+    # tweak data path so that file URI works on both unix and windows.
+    data_path = data_dir.lstrip(os.path.sep)
+    data_path = data_path.replace(os.path.sep, '/')
+    image_url = f'file:///{data_path}/camera.png'
+    with monkeypatch.context():
+        monkeypatch.setattr(
+            tempfile, 'NamedTemporaryFile', _named_tempfile_func(error_class)
+        )
+        with pytest.raises(error_class):
+            io.imread(image_url)

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_mpl_imshow.py

@@ -0,0 +1,133 @@
+import numpy as np
+import pytest
+
+from skimage import io
+from skimage._shared._warnings import expected_warnings
+
+plt = pytest.importorskip("matplotlib.pyplot")
+
+
+def setup():
+    io.reset_plugins()
+
+# test images. Note that they don't have their full range for their dtype,
+# but we still expect the display range to equal the full dtype range.
+im8 = np.array([[0, 64], [128, 240]], np.uint8)
+im16 = im8.astype(np.uint16) * 256
+im64 = im8.astype(np.uint64)
+imf = im8 / 255
+im_lo = imf / 1000
+im_hi = imf + 10
+
+imshow_expected_warnings = [
+    r"tight_layout : falling back to Agg|\A\Z",
+    r"tight_layout: falling back to Agg|\A\Z",  # formatting change in mpl
+    # Maptlotlib 2.2.3 seems to use np.asscalar which issues a warning
+    # with numpy 1.16
+    # Matplotlib 2.2.3 is the last supported version for python 2.7
+    r"np.asscalar|\A\Z"
+]
+
+
+def n_subplots(ax_im):
+    """Return the number of subplots in the figure containing an ``AxesImage``.
+
+    Parameters
+    ----------
+    ax_im : matplotlib.pyplot.AxesImage object
+        The input ``AxesImage``.
+
+    Returns
+    -------
+    n : int
+        The number of subplots in the corresponding figure.
+
+    Notes
+    -----
+    This function is intended to check whether a colorbar was drawn, in
+    which case two subplots are expected. For standard imshows, one
+    subplot is expected.
+    """
+    return len(ax_im.get_figure().get_axes())
+
+
+def test_uint8():
+    plt.figure()
+    with expected_warnings(imshow_expected_warnings +
+                           [r"CObject type is marked|\A\Z"]):
+        ax_im = io.imshow(im8)
+    assert ax_im.cmap.name == 'gray'
+    assert ax_im.get_clim() == (0, 255)
+    assert n_subplots(ax_im) == 1
+    assert ax_im.colorbar is None
+
+
+def test_uint16():
+    plt.figure()
+    with expected_warnings(imshow_expected_warnings +
+                           [r"CObject type is marked|\A\Z"]):
+        ax_im = io.imshow(im16)
+    assert ax_im.cmap.name == 'gray'
+    assert ax_im.get_clim() == (0, 65535)
+    assert n_subplots(ax_im) == 1
+    assert ax_im.colorbar is None
+
+
+def test_float():
+    plt.figure()
+    with expected_warnings(imshow_expected_warnings +
+                           [r"CObject type is marked|\A\Z"]):
+        ax_im = io.imshow(imf)
+    assert ax_im.cmap.name == 'gray'
+    assert ax_im.get_clim() == (0, 1)
+    assert n_subplots(ax_im) == 1
+    assert ax_im.colorbar is None
+
+
+def test_low_data_range():
+    with expected_warnings(imshow_expected_warnings +
+                           ["Low image data range|CObject type is marked"]):
+        ax_im = io.imshow(im_lo)
+    assert ax_im.get_clim() == (im_lo.min(), im_lo.max())
+    # check that a colorbar was created
+    assert ax_im.colorbar is not None
+
+
+def test_outside_standard_range():
+    plt.figure()
+    # Warning raised by matplotlib on Windows:
+    # "The CObject type is marked Pending Deprecation in Python 2.7.
+    #  Please use capsule objects instead."
+    # Ref: https://docs.python.org/2/c-api/cobject.html
+    with expected_warnings(imshow_expected_warnings +
+                           ["out of standard range|CObject type is marked"]):
+        ax_im = io.imshow(im_hi)
+    assert ax_im.get_clim() == (im_hi.min(), im_hi.max())
+    assert n_subplots(ax_im) == 2
+    assert ax_im.colorbar is not None
+
+
+def test_nonstandard_type():
+    plt.figure()
+    # Warning raised by matplotlib on Windows:
+    # "The CObject type is marked Pending Deprecation in Python 2.7.
+    #  Please use capsule objects instead."
+    # Ref: https://docs.python.org/2/c-api/cobject.html
+    with expected_warnings(imshow_expected_warnings +
+                           ["Low image data range|CObject type is marked"]):
+        ax_im = io.imshow(im64)
+    assert ax_im.get_clim() == (im64.min(), im64.max())
+    assert n_subplots(ax_im) == 2
+    assert ax_im.colorbar is not None
+
+
+def test_signed_image():
+    plt.figure()
+    im_signed = np.array([[-0.5, -0.2], [0.1, 0.4]])
+
+    with expected_warnings(imshow_expected_warnings +
+                           [r"CObject type is marked|\A\Z"]):
+        ax_im = io.imshow(im_signed)
+    assert ax_im.get_clim() == (-0.5, 0.5)
+    assert n_subplots(ax_im) == 2
+    assert ax_im.colorbar is not None

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_multi_image.py

@@ -0,0 +1,88 @@
+import os
+
+import numpy as np
+from skimage.io import use_plugin, reset_plugins
+from skimage.io.collection import MultiImage
+
+from skimage._shared import testing
+from skimage._shared.testing import assert_equal, assert_allclose
+
+from pytest import fixture
+
+@fixture
+def imgs():
+    use_plugin('pil')
+
+    paths = [testing.fetch('data/multipage_rgb.tif'),
+             testing.fetch('data/no_time_for_that_tiny.gif')]
+    imgs = [MultiImage(paths[0]),
+            MultiImage(paths[0], conserve_memory=False),
+            MultiImage(paths[1]),
+            MultiImage(paths[1], conserve_memory=False),
+            MultiImage(os.pathsep.join(paths))]
+    yield imgs
+
+    reset_plugins()
+
+def test_shapes(imgs):
+    imgs = imgs[-1]
+    assert imgs[0][0].shape == imgs[0][1].shape
+    assert imgs[0][0].shape == (10, 10, 3)
+
+def test_len(imgs):
+    assert len(imgs[0][0]) == len(imgs[1][0]) == 2
+    assert len(imgs[2][0]) == len(imgs[3][0]) == 24
+    assert len(imgs[-1]) == 2, len(imgs[-1])
+
+def test_slicing(imgs):
+    img = imgs[-1]
+    assert type(img[:]) is MultiImage
+    assert len(img[0][:]) + len(img[1][:]) == 26, len(img[:])
+    assert len(img[0][:1]) == 1
+    assert len(img[1][1:]) == 23
+    assert_allclose(img[0], img[:1][0])
+    assert_allclose(img[1], img[1:][0])
+    assert_allclose(img[-1], img[::-1][0])
+    assert_allclose(img[0], img[::-1][-1])
+
+def test_getitem(imgs):
+    for img in imgs[0]:
+        num = len(img)
+
+        for i in range(-num, num):
+            assert type(img[i]) is np.ndarray
+        assert_allclose(img[0], img[-num])
+
+        with testing.raises(AssertionError):
+            assert_allclose(img[0], img[1])
+
+        with testing.raises(IndexError):
+            img[num]
+        with testing.raises(IndexError):
+            img[-num - 1]
+
+def test_files_property(imgs):
+    for img in imgs:
+        if isinstance(img, MultiImage):
+            continue
+
+        assert isinstance(img.filename, str)
+
+        with testing.raises(AttributeError):
+            img.filename = "newfile"
+
+def test_conserve_memory_property(imgs):
+    for img in imgs:
+        assert isinstance(img.conserve_memory, bool)
+
+        with testing.raises(AttributeError):
+            img.conserve_memory = True
+
+def test_concatenate(imgs):
+    for img in imgs:
+        if img[0].shape != img[-1].shape:
+            with testing.raises(ValueError):
+                img.concatenate()
+            continue
+        array = img.concatenate()
+        assert_equal(array.shape, (len(img),) + img[0].shape)

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_pil.py

@@ -0,0 +1,304 @@
+import os
+from io import BytesIO
+from tempfile import NamedTemporaryFile
+
+import numpy as np
+import pytest
+from PIL import Image
+from skimage._shared import testing
+from skimage._shared._tempfile import temporary_file
+from skimage._shared._warnings import expected_warnings
+from skimage._shared.testing import (assert_allclose,
+                                     assert_array_almost_equal,
+                                     assert_array_equal, assert_equal,
+                                     color_check, fetch, mono_check)
+from skimage.metrics import structural_similarity
+
+from ... import img_as_float
+from ...color import rgb2lab
+from .. import imread, imsave, reset_plugins, use_plugin
+from .._plugins.pil_plugin import (_palette_is_grayscale, ndarray_to_pil,
+                                   pil_to_ndarray)
+
+
+def setup():
+    use_plugin('pil')
+
+
+def teardown():
+    reset_plugins()
+
+
+def setup_module(self):
+    """The effect of the `plugin.use` call may be overridden by later imports.
+    Call `use_plugin` directly before the tests to ensure that PIL is used.
+    """
+    try:
+        use_plugin('pil')
+    except ImportError:
+        pass
+
+
+def test_png_round_trip():
+    with NamedTemporaryFile(suffix='.png') as f:
+        fname = f.name
+
+    I = np.eye(3)
+    imsave(fname, I)
+    Ip = img_as_float(imread(fname))
+    os.remove(fname)
+    assert np.sum(np.abs(Ip-I)) < 1e-3
+
+
+def test_imread_as_gray():
+    img = imread(fetch('data/color.png'), as_gray=True)
+    assert img.ndim == 2
+    assert img.dtype == np.float64
+    img = imread(fetch('data/camera.png'), as_gray=True)
+    # check that conversion does not happen for a gray image
+    assert np.sctype2char(img.dtype) in np.typecodes['AllInteger']
+
+
+@pytest.mark.parametrize('explicit_kwargs', [False, True])
+def test_imread_separate_channels(explicit_kwargs):
+    # Test that imread returns RGB(A) values contiguously even when they are
+    # stored in separate planes.
+    x = np.random.rand(3, 16, 8)
+    with NamedTemporaryFile(suffix='.tif') as f:
+        fname = f.name
+
+    # Tifffile is used as backend whenever suffix is .tif or .tiff
+    # To avoid pending changes to tifffile defaults, we must specify this is an
+    # RGB image with separate planes (i.e., channel_axis=0).
+    if explicit_kwargs:
+        pass
+    else:
+        pass
+
+    imsave(fname, x)
+    img = imread(fname)
+    os.remove(fname)
+    assert img.shape == (16, 8, 3), img.shape
+
+
+def test_imread_multipage_rgb_tif():
+    img = imread(fetch('data/multipage_rgb.tif'))
+    assert img.shape == (2, 10, 10, 3), img.shape
+
+
+def test_imread_palette():
+    img = imread(fetch('data/palette_gray.png'))
+    assert img.ndim == 2
+    img = imread(fetch('data/palette_color.png'))
+    assert img.ndim == 3
+
+
+def test_imread_index_png_with_alpha():
+    # The file `foo3x5x4indexed.png` was created with this array
+    # (3x5 is (height)x(width)):
+    dfoo = np.array([[[127, 0, 255, 255],
+                      [127, 0, 255, 255],
+                      [127, 0, 255, 255],
+                      [127, 0, 255, 255],
+                      [127, 0, 255, 255]],
+                     [[192, 192, 255, 0],
+                      [192, 192, 255, 0],
+                      [0, 0, 255, 0],
+                      [0, 0, 255, 0],
+                      [0, 0, 255, 0]],
+                     [[0, 31, 255, 255],
+                      [0, 31, 255, 255],
+                      [0, 31, 255, 255],
+                      [0, 31, 255, 255],
+                      [0, 31, 255, 255]]], dtype=np.uint8)
+    img = imread(fetch('data/foo3x5x4indexed.png'))
+    assert_array_equal(img, dfoo)
+
+
+def test_palette_is_gray():
+    gray = Image.open(fetch('data/palette_gray.png'))
+    assert _palette_is_grayscale(gray)
+    color = Image.open(fetch('data/palette_color.png'))
+    assert not _palette_is_grayscale(color)
+
+
+def test_bilevel():
+    expected = np.zeros((10, 10))
+    expected[::2] = 255
+
+    img = imread(fetch('data/checker_bilevel.png'))
+    assert_array_equal(img, expected)
+
+
+def test_imread_uint16():
+    expected = np.load(fetch('data/chessboard_GRAY_U8.npy'))
+    img = imread(fetch('data/chessboard_GRAY_U16.tif'))
+    assert np.issubdtype(img.dtype, np.uint16)
+    assert_array_almost_equal(img, expected)
+
+
+def test_imread_truncated_jpg():
+    with testing.raises(IOError):
+        imread(fetch('data/truncated.jpg'))
+
+
+def test_jpg_quality_arg():
+    chessboard = np.load(fetch('data/chessboard_GRAY_U8.npy'))
+    with temporary_file(suffix='.jpg') as jpg:
+        imsave(jpg, chessboard, quality=95)
+        im = imread(jpg)
+        sim = structural_similarity(
+            chessboard, im,
+            data_range=chessboard.max() - chessboard.min())
+        assert sim > 0.99
+
+
+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)
+
+
+class TestSave:
+    def roundtrip_file(self, x):
+        with temporary_file(suffix='.png') as fname:
+            imsave(fname, x)
+            y = imread(fname)
+            return y
+
+    def roundtrip_pil_image(self, x):
+        pil_image = ndarray_to_pil(x)
+        y = pil_to_ndarray(pil_image)
+        return y
+
+    def verify_roundtrip(self, dtype, x, y, scaling=1):
+        assert_array_almost_equal((x * scaling).astype(np.int32), y)
+
+    def verify_imsave_roundtrip(self, roundtrip_function):
+        for shape in [(10, 10), (10, 10, 3), (10, 10, 4)]:
+            for dtype in (np.uint8, np.uint16, np.float32, np.float64):
+                x = np.ones(shape, dtype=dtype) * np.random.rand(*shape)
+
+                if np.issubdtype(dtype, np.floating):
+                    yield (self.verify_roundtrip, dtype, x,
+                           roundtrip_function(x), 255)
+                else:
+                    x = (x * 255).astype(dtype)
+                    yield (self.verify_roundtrip, dtype, x,
+                           roundtrip_function(x))
+
+    def test_imsave_roundtrip_file(self):
+        self.verify_imsave_roundtrip(self.roundtrip_file)
+
+    def test_imsave_roundtrip_pil_image(self):
+        self.verify_imsave_roundtrip(self.roundtrip_pil_image)
+
+
+def test_imsave_incorrect_dimension():
+    with temporary_file(suffix='.png') as fname:
+        with testing.raises(ValueError):
+            with expected_warnings([fname + ' is a low contrast image']):
+                imsave(fname, np.zeros((2, 3, 3, 1)))
+        with testing.raises(ValueError):
+            with expected_warnings([fname + ' is a low contrast image']):
+                imsave(fname, np.zeros((2, 3, 2)))
+        # test that low contrast check is ignored
+        with testing.raises(ValueError):
+            with expected_warnings([]):
+                imsave(fname, np.zeros((2, 3, 2)), check_contrast=False)
+
+
+def test_imsave_filelike():
+    shape = (2, 2)
+    image = np.zeros(shape)
+    s = BytesIO()
+
+    # save to file-like object
+    with expected_warnings(['is a low contrast image']):
+        imsave(s, image)
+
+    # read from file-like object
+    s.seek(0)
+    out = imread(s)
+    assert_equal(out.shape, shape)
+    assert_allclose(out, image)
+
+
+def test_imsave_boolean_input():
+    shape = (2, 2)
+    image = np.eye(*shape, dtype=bool)
+    s = BytesIO()
+
+    # save to file-like object
+    with expected_warnings(
+            ['is a boolean image: setting True to 255 and False to 0']):
+        imsave(s, image)
+
+    # read from file-like object
+    s.seek(0)
+    out = imread(s)
+    assert_equal(out.shape, shape)
+    assert_allclose(out.astype(bool), image)
+
+
+def test_imexport_imimport():
+    shape = (2, 2)
+    image = np.zeros(shape)
+    pil_image = ndarray_to_pil(image)
+    out = pil_to_ndarray(pil_image)
+    assert_equal(out.shape, shape)
+
+
+def test_all_color():
+    with expected_warnings(['.* is a boolean image']):
+        color_check('pil')
+    with expected_warnings(['.* is a boolean image']):
+        color_check('pil', 'bmp')
+
+
+def test_all_mono():
+    with expected_warnings(['.* is a boolean image']):
+        mono_check('pil')
+
+
+def test_multi_page_gif():
+    img = imread(fetch('data/no_time_for_that_tiny.gif'))
+    assert img.shape == (24, 25, 14, 3), img.shape
+    img2 = imread(fetch('data/no_time_for_that_tiny.gif'),
+                  img_num=5)
+    assert img2.shape == (25, 14, 3)
+    assert_allclose(img[5], img2)
+
+
+def test_cmyk():
+    ref = imread(fetch('data/color.png'))
+
+    img = Image.open(fetch('data/color.png'))
+    img = img.convert('CMYK')
+
+    with NamedTemporaryFile(suffix='.jpg') as f:
+        fname = f.name
+
+    img.save(fname)
+    try:
+        img.close()
+    except AttributeError:  # `close` not available on PIL
+        pass
+
+    new = imread(fname)
+
+    ref_lab = rgb2lab(ref)
+    new_lab = rgb2lab(new)
+
+    for i in range(3):
+        newi = np.ascontiguousarray(new_lab[:, :, i])
+        refi = np.ascontiguousarray(ref_lab[:, :, i])
+        sim = structural_similarity(refi, newi,
+                                    data_range=refi.max() - refi.min())
+        assert sim > 0.99
+
+
+def test_extreme_palette():
+    img = imread(fetch('data/green_palette.png'))
+    assert_equal(img.ndim, 3)

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_plugin.py

@@ -0,0 +1,74 @@
+from contextlib import contextmanager
+import numpy as np
+import pytest
+
+from skimage._shared._dependency_checks import has_mpl
+from skimage import io
+from skimage.io import manage_plugins
+
+
+priority_plugin = 'pil'
+
+
+def setup():
+    io.use_plugin('pil')
+
+
+def teardown_module():
+    io.reset_plugins()
+
+
+@contextmanager
+def protect_preferred_plugins():
+    """Contexts where `preferred_plugins` can be modified w/o side-effects."""
+    preferred_plugins = manage_plugins.preferred_plugins.copy()
+    try:
+        yield
+    finally:
+        manage_plugins.preferred_plugins = preferred_plugins
+
+
+def test_failed_use():
+    with pytest.raises(ValueError):
+        manage_plugins.use_plugin('asd')
+
+
+@pytest.mark.skipif(not has_mpl, reason="matplotlib not installed")
+def test_use_priority():
+    manage_plugins.use_plugin(priority_plugin)
+    plug, func = manage_plugins.plugin_store['imread'][0]
+    np.testing.assert_equal(plug, priority_plugin)
+
+    manage_plugins.use_plugin('matplotlib')
+    plug, func = manage_plugins.plugin_store['imread'][0]
+    np.testing.assert_equal(plug, 'matplotlib')
+
+
+@pytest.mark.skipif(not has_mpl, reason="matplotlib not installed")
+def test_load_preferred_plugins_all():
+    from skimage.io._plugins import pil_plugin, matplotlib_plugin
+
+    with protect_preferred_plugins():
+        manage_plugins.preferred_plugins = {'all': ['pil'],
+                                            'imshow': ['matplotlib']}
+        manage_plugins.reset_plugins()
+
+        for plugin_type in ('imread', 'imsave'):
+            plug, func = manage_plugins.plugin_store[plugin_type][0]
+            assert func == getattr(pil_plugin, plugin_type)
+        plug, func = manage_plugins.plugin_store['imshow'][0]
+        assert func == getattr(matplotlib_plugin, 'imshow')
+
+
+@pytest.mark.skipif(not has_mpl, reason="matplotlib not installed")
+def test_load_preferred_plugins_imread():
+    from skimage.io._plugins import pil_plugin, matplotlib_plugin
+
+    with protect_preferred_plugins():
+        manage_plugins.preferred_plugins['imread'] = ['pil']
+        manage_plugins.reset_plugins()
+
+        plug, func = manage_plugins.plugin_store['imread'][0]
+        assert func == pil_plugin.imread
+        plug, func = manage_plugins.plugin_store['imshow'][0]
+        assert func == matplotlib_plugin.imshow, func.__module__

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_sift.py

@@ -0,0 +1,66 @@
+import os
+from tempfile import NamedTemporaryFile
+
+from skimage.io import load_sift, load_surf
+
+from skimage._shared.testing import assert_equal
+
+
+def test_load_sift():
+    with NamedTemporaryFile(delete=False) as f:
+        fname = f.name
+
+    with open(fname, 'wb') as f:
+        f.write(b'''2 128
+    133.92 135.88 14.38 -2.732
+    3 12 23 38 10 15 78 20 39 67 42 8 12 8 39 35 118 43 17 0
+    0 1 12 109 9 2 6 0 0 21 46 22 14 18 51 19 5 9 41 52
+    65 30 3 21 55 49 26 30 118 118 25 12 8 3 2 60 53 56 72 20
+    7 10 16 7 88 23 13 15 12 11 11 71 45 7 4 49 82 38 38 91
+    118 15 2 16 33 3 5 118 98 38 6 19 36 1 0 15 64 22 1 2
+    6 11 18 61 31 3 0 6 15 23 118 118 13 0 0 35 38 18 40 96
+    24 1 0 13 17 3 24 98
+    132.36 99.75 11.45 -2.910
+    94 32 7 2 13 7 5 23 121 94 13 5 0 0 4 59 13 30 71 32
+    0 6 32 11 25 32 13 0 0 16 51 5 44 50 0 3 33 55 11 9
+    121 121 12 9 6 3 0 18 55 60 48 44 44 9 0 2 106 117 13 2
+    1 0 1 1 37 1 1 25 80 35 15 41 121 3 0 2 14 3 2 121
+    51 11 0 20 93 6 0 20 109 57 3 4 5 0 0 28 21 2 0 5
+    13 12 75 119 35 0 0 13 28 14 37 121 12 0 0 21 46 5 11 93
+    29 0 0 3 14 4 11 99''')
+
+    # Check whether loading by filename works
+    load_sift(fname)
+
+    with open(fname) as f:
+        features = load_sift(f)
+    os.remove(fname)
+
+    assert_equal(len(features), 2)
+    assert_equal(len(features['data'][0]), 128)
+    assert_equal(features['row'][0], 133.92)
+    assert_equal(features['column'][1], 99.75)
+
+
+def test_load_surf():
+    with NamedTemporaryFile(delete=False) as f:
+        fname = f.name
+
+    with open(fname, 'wb') as f:
+        f.write(b'''65
+2
+38.3727 62.0491 0.0371343 0 0.0371343 -1 -0.0705589 0.0130983 -0.00460534 0.132168 -0.0718833 0.0320583 -0.0134032 0.0988654 -0.0542241 0.0171002 -0.00135754 0.105755 -0.0362088 0.0151748 -0.00694272 0.0610017 -0.247091 0.109605 -0.0337623 0.0813307 -0.24185 0.278548 -0.0494523 0.107804 -0.166312 0.0691584 -0.0288199 0.138476 -0.110956 0.0280772 -0.0752509 0.0736344 -0.22667 0.164226 -0.0544717 0.0388139 -0.30194 0.33065 -0.0537507 0.0596398 -0.245395 0.110925 -0.0603322 0.0239389 -0.18726 0.0374145 -0.0355872 0.0140762 -0.129022 0.135104 -0.0703396 0.0374049 -0.24256 0.222544 -0.0536354 0.0501252 -0.209004 0.0971316 -0.0550094 0.0229767 -0.125547 0.0317879 -0.0291574 0.0124569
+68.5773 61.474 0.0313267 0 0.0313267 1 -0.10198 0.130987 -0.0321845 0.0487543 -0.0900435 0.121113 -0.100917 0.0444702 -0.0151742 0.107604 -0.0542035 0.014069 -0.00594097 0.0339933 -0.00994295 0.0127262 -0.125613 0.192551 -0.0174399 0.0433488 -0.272698 0.164641 -0.0676735 0.0467444 -0.0527907 0.258005 -0.0818114 0.0440569 -0.0104433 0.0548934 -0.0323454 0.0145296 -0.112357 0.199223 -0.0532903 0.0332622 -0.342481 0.207469 -0.0526129 0.0741355 -0.256234 0.402708 -0.108296 0.117362 -0.0560274 0.128856 -0.123509 0.0510046 -0.0198793 0.0775934 -0.103863 0.00406679 -0.10264 0.1312 -0.108244 0.0812913 -0.127868 0.182924 -0.0680942 0.071913 -0.0858004 0.144806 -0.0176522 0.0686146''')
+
+
+    # Check whether loading by filename works
+    load_surf(fname)
+
+    with open(fname) as f:
+        features = load_surf(f)
+    os.remove(fname)
+
+    assert_equal(len(features), 2)
+    assert_equal(len(features['data'][0]), 64)
+    assert_equal(features['column'][1], 68.5773)
+    assert_equal(features['row'][0], 62.0491)

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_simpleitk.py

@@ -0,0 +1,83 @@
+import numpy as np
+import unittest
+
+from tempfile import NamedTemporaryFile
+
+from skimage.io import imread, imsave, use_plugin, reset_plugins
+from skimage._shared import testing
+
+from pytest import importorskip, raises, fixture
+
+importorskip('SimpleITK')
+
+np.random.seed(0)
+
+
+def teardown():
+    reset_plugins()
+
+
+@fixture(autouse=True)
+def setup_plugin():
+    """This ensures that `use_plugin` is directly called before all tests to
+    ensure that SimpleITK is used.
+    """
+    use_plugin('simpleitk')
+    yield
+
+
+def test_imread_as_gray():
+    img = imread(testing.fetch('data/color.png'), as_gray=True)
+    assert img.ndim == 2
+    assert img.dtype == np.float64
+    img = imread(testing.fetch('data/camera.png'), as_gray=True)
+    # check that conversion does not happen for a gray image
+    assert np.sctype2char(img.dtype) in np.typecodes['AllInteger']
+
+
+def test_bilevel():
+    expected = np.zeros((10, 10))
+    expected[::2] = 255
+
+    img = imread(testing.fetch('data/checker_bilevel.png'))
+    np.testing.assert_array_equal(img, expected)
+
+
+def test_imread_truncated_jpg():
+    with raises(RuntimeError):
+        imread(testing.fetch('data/truncated.jpg'))
+
+
+def test_imread_uint16():
+    expected = np.load(testing.fetch('data/chessboard_GRAY_U8.npy'))
+    img = imread(testing.fetch('data/chessboard_GRAY_U16.tif'))
+    assert np.issubdtype(img.dtype, np.uint16)
+    np.testing.assert_array_almost_equal(img, expected)
+
+
+def test_imread_uint16_big_endian():
+    expected = np.load(testing.fetch('data/chessboard_GRAY_U8.npy'))
+    img = imread(testing.fetch('data/chessboard_GRAY_U16B.tif'))
+    np.testing.assert_array_almost_equal(img, expected)
+
+
+class TestSave(unittest.TestCase):
+    def roundtrip(self, dtype, x):
+        with NamedTemporaryFile(suffix='.mha') as f:
+            fname = f.name
+
+        imsave(fname, x)
+        y = imread(fname)
+
+        np.testing.assert_array_almost_equal(x, y)
+
+    def test_imsave_roundtrip(self):
+        for shape in [(10, 10), (10, 10, 3), (10, 10, 4)]:
+            for dtype in (np.uint8, np.uint16, np.float32, np.float64):
+                x = np.ones(shape, dtype=dtype) * np.random.rand(*shape)
+
+                if np.issubdtype(dtype, np.floating):
+                    yield self.roundtrip, dtype, x
+                else:
+                    x = (x * 255).astype(dtype)
+                    yield self.roundtrip, dtype, x

.CondaPkg/env/Lib/site-packages/skimage/io/tests/test_tifffile.py

@@ -0,0 +1,83 @@
+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)