Fixed database typo and removed unnecessary class identifier.

venv/Lib/site-packages/skimage/_shared/_geometry.py

@@ -0,0 +1,55 @@
+__all__ = ['polygon_clip', 'polygon_area']
+
+import numpy as np
+
+
+def polygon_clip(rp, cp, r0, c0, r1, c1):
+    """Clip a polygon to the given bounding box.
+
+    Parameters
+    ----------
+    rp, cp : (N,) ndarray of double
+        Row and column coordinates of the polygon.
+    (r0, c0), (r1, c1) : double
+        Top-left and bottom-right coordinates of the bounding box.
+
+    Returns
+    -------
+    r_clipped, c_clipped : (M,) ndarray of double
+        Coordinates of clipped polygon.
+
+    Notes
+    -----
+    This makes use of Sutherland-Hodgman clipping as implemented in
+    AGG 2.4 and exposed in Matplotlib.
+
+    """
+    from matplotlib import path, transforms
+
+    poly = path.Path(np.vstack((rp, cp)).T, closed=True)
+    clip_rect = transforms.Bbox([[r0, c0], [r1, c1]])
+    poly_clipped = poly.clip_to_bbox(clip_rect).to_polygons()[0]
+
+    # This should be fixed in matplotlib >1.5
+    if np.all(poly_clipped[-1] == poly_clipped[-2]):
+        poly_clipped = poly_clipped[:-1]
+
+    return poly_clipped[:, 0], poly_clipped[:, 1]
+
+
+def polygon_area(pr, pc):
+    """Compute the area of a polygon.
+
+    Parameters
+    ----------
+    pr, pc : (N,) array of float
+        Polygon row and column coordinates.
+
+    Returns
+    -------
+    a : float
+        Area of the polygon.
+    """
+    pr = np.asarray(pr)
+    pc = np.asarray(pc)
+    return 0.5 * np.abs(np.sum((pc[:-1] * pr[1:]) - (pc[1:] * pr[:-1])))

venv/Lib/site-packages/skimage/_shared/_tempfile.py

@@ -0,0 +1,27 @@
+from tempfile import NamedTemporaryFile
+from contextlib import contextmanager
+import os
+
+@contextmanager
+def temporary_file(suffix=''):
+    """Yield a writeable temporary filename that is deleted on context exit.
+
+    Parameters
+    ----------
+    suffix : string, optional
+        The suffix for the file.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from skimage import io
+    >>> with temporary_file('.tif') as tempfile:
+    ...     im = np.arange(25, dtype=np.uint8).reshape((5, 5))
+    ...     io.imsave(tempfile, im)
+    ...     assert np.all(io.imread(tempfile) == im)
+    """
+    tempfile_stream = NamedTemporaryFile(suffix=suffix, delete=False)
+    tempfile = tempfile_stream.name
+    tempfile_stream.close()
+    yield tempfile
+    os.remove(tempfile)

venv/Lib/site-packages/skimage/_shared/_warnings.py

@@ -0,0 +1,145 @@
+from contextlib import contextmanager
+import sys
+import warnings
+import re
+import functools
+import os
+
+__all__ = ['all_warnings', 'expected_warnings', 'warn']
+
+
+# A version of `warnings.warn` with a default stacklevel of 2.
+# functool is used so as not to increase the call stack accidentally
+warn = functools.partial(warnings.warn, stacklevel=2)
+
+
+@contextmanager
+def all_warnings():
+    """
+    Context for use in testing to ensure that all warnings are raised.
+
+    Examples
+    --------
+    >>> import warnings
+    >>> def foo():
+    ...     warnings.warn(RuntimeWarning("bar"), stacklevel=2)
+
+    We raise the warning once, while the warning filter is set to "once".
+    Hereafter, the warning is invisible, even with custom filters:
+
+    >>> with warnings.catch_warnings():
+    ...     warnings.simplefilter('once')
+    ...     foo()                         # doctest: +SKIP
+
+    We can now run ``foo()`` without a warning being raised:
+
+    >>> from numpy.testing import assert_warns
+    >>> foo()                             # doctest: +SKIP
+
+    To catch the warning, we call in the help of ``all_warnings``:
+
+    >>> with all_warnings():
+    ...     assert_warns(RuntimeWarning, foo)
+    """
+    # _warnings.py is on the critical import path.
+    # Since this is a testing only function, we lazy import inspect.
+    import inspect
+    # Whenever a warning is triggered, Python adds a __warningregistry__
+    # member to the *calling* module.  The exercize here is to find
+    # and eradicate all those breadcrumbs that were left lying around.
+    #
+    # We proceed by first searching all parent calling frames and explicitly
+    # clearing their warning registries (necessary for the doctests above to
+    # pass).  Then, we search for all submodules of skimage and clear theirs
+    # as well (necessary for the skimage test suite to pass).
+
+    frame = inspect.currentframe()
+    if frame:
+        for f in inspect.getouterframes(frame):
+            f[0].f_locals['__warningregistry__'] = {}
+    del frame
+
+    for mod_name, mod in list(sys.modules.items()):
+        try:
+            mod.__warningregistry__.clear()
+        except AttributeError:
+            pass
+
+    with warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter("always")
+        yield w
+
+
+@contextmanager
+def expected_warnings(matching):
+    r"""Context for use in testing to catch known warnings matching regexes
+
+    Parameters
+    ----------
+    matching : None or a list of strings or compiled regexes
+        Regexes for the desired warning to catch
+        If matching is None, this behaves as a no-op.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> image = np.random.randint(0, 2**16, size=(100, 100), dtype=np.uint16)
+    >>> # rank filters are slow when bit-depth exceeds 10 bits
+    >>> from skimage import filters
+    >>> with expected_warnings(['Bad rank filter performance']):
+    ...     median_filtered = filters.rank.median(image)
+
+    Notes
+    -----
+    Uses `all_warnings` to ensure all warnings are raised.
+    Upon exiting, it checks the recorded warnings for the desired matching
+    pattern(s).
+    Raises a ValueError if any match was not found or an unexpected
+    warning was raised.
+    Allows for three types of behaviors: `and`, `or`, and `optional` matches.
+    This is done to accommodate different build environments or loop conditions
+    that may produce different warnings.  The behaviors can be combined.
+    If you pass multiple patterns, you get an orderless `and`, where all of the
+    warnings must be raised.
+    If you use the `|` operator in a pattern, you can catch one of several
+    warnings.
+    Finally, you can use `|\A\Z` in a pattern to signify it as optional.
+
+    """
+    if isinstance(matching, str):
+        raise ValueError('``matching`` should be a list of strings and not '
+                         'a string itself.')
+
+    # Special case for disabling the context manager
+    if matching is None:
+        yield None
+        return
+
+    strict_warnings = os.environ.get('SKIMAGE_TEST_STRICT_WARNINGS', '1')
+    if strict_warnings.lower() == 'true':
+        strict_warnings = True
+    elif strict_warnings.lower() == 'false':
+        strict_warnings = False
+    else:
+        strict_warnings = bool(int(strict_warnings))
+
+    with all_warnings() as w:
+        # enter context
+        yield w
+        # exited user context, check the recorded warnings
+        # Allow users to provide None
+        while None in matching:
+            matching.remove(None)
+        remaining = [m for m in matching if r'\A\Z' not in m.split('|')]
+        for warn in w:
+            found = False
+            for match in matching:
+                if re.search(match, str(warn.message)) is not None:
+                    found = True
+                    if match in remaining:
+                        remaining.remove(match)
+            if strict_warnings and not found:
+                raise ValueError('Unexpected warning: %s' % str(warn.message))
+        if strict_warnings and (len(remaining) > 0):
+            msg = 'No warning raised matching:\n%s' % '\n'.join(remaining)
+            raise ValueError(msg)

venv/Lib/site-packages/skimage/_shared/fft.py

@@ -0,0 +1,17 @@
+"""Prefer FFTs via the new scipy.fft module when available (SciPy 1.4+)
+
+Otherwise fall back to numpy.fft.
+
+Like numpy 1.15+ scipy 1.3+ is also using pocketfft, but a newer
+C++/pybind11 version called pypocketfft
+"""
+try:
+    import scipy.fft
+    from scipy.fft import next_fast_len
+    fftmodule = scipy.fft
+except ImportError:
+    import numpy.fft
+    fftmodule = numpy.fft
+    from scipy.fftpack import next_fast_len
+
+__all__ = ['fftmodule', 'next_fast_len']

venv/Lib/site-packages/skimage/_shared/setup.py

@@ -0,0 +1,37 @@
+#!/usr/bin/env python
+
+import os
+
+from skimage._build import cython
+
+base_path = os.path.abspath(os.path.dirname(__file__))
+
+
+def configuration(parent_package='', top_path=None):
+    from numpy.distutils.misc_util import Configuration, get_numpy_include_dirs
+
+    config = Configuration('_shared', parent_package, top_path)
+
+    cython(['geometry.pyx',
+            'transform.pyx',
+            'interpolation.pyx',
+            'fast_exp.pyx'], working_path=base_path)
+
+    config.add_extension('geometry', sources=['geometry.c'])
+    config.add_extension('transform', sources=['transform.c'],
+                         include_dirs=[get_numpy_include_dirs()])
+    config.add_extension('interpolation', sources=['interpolation.c'])
+    config.add_extension('fast_exp', sources=['fast_exp.c'])
+    return config
+
+
+if __name__ == '__main__':
+    from numpy.distutils.core import setup
+    setup(maintainer='scikit-image Developers',
+          author='scikit-image Developers',
+          maintainer_email='scikit-image@python.org',
+          description='Transforms',
+          url='https://github.com/scikit-image/scikit-image',
+          license='SciPy License (BSD Style)',
+          **(configuration(top_path='').todict())
+          )

venv/Lib/site-packages/skimage/_shared/testing.py

@@ -0,0 +1,270 @@
+"""
+Testing utilities.
+"""
+
+import os
+import re
+import struct
+import threading
+import functools
+from tempfile import NamedTemporaryFile
+
+import numpy as np
+from numpy import testing
+from numpy.testing import (assert_array_equal, assert_array_almost_equal,
+                           assert_array_less, assert_array_almost_equal_nulp,
+                           assert_equal, TestCase, assert_allclose,
+                           assert_almost_equal, assert_, assert_warns,
+                           assert_no_warnings)
+
+import warnings
+
+from .. import data, io
+from ..util import img_as_uint, img_as_float, img_as_int, img_as_ubyte
+import pytest
+from ._warnings import expected_warnings
+
+
+SKIP_RE = re.compile(r"(\s*>>>.*?)(\s*)#\s*skip\s+if\s+(.*)$")
+
+skipif = pytest.mark.skipif
+xfail = pytest.mark.xfail
+parametrize = pytest.mark.parametrize
+raises = pytest.raises
+fixture = pytest.fixture
+
+# true if python is running in 32bit mode
+# Calculate the size of a void * pointer in bits
+# https://docs.python.org/3/library/struct.html
+arch32 = struct.calcsize("P") * 8 == 32
+
+
+def assert_less(a, b, msg=None):
+    message = "%r is not lower than %r" % (a, b)
+    if msg is not None:
+        message += ": " + msg
+    assert a < b, message
+
+
+def assert_greater(a, b, msg=None):
+    message = "%r is not greater than %r" % (a, b)
+    if msg is not None:
+        message += ": " + msg
+    assert a > b, message
+
+
+def doctest_skip_parser(func):
+    """ Decorator replaces custom skip test markup in doctests
+
+    Say a function has a docstring::
+
+        >>> something, HAVE_AMODULE, HAVE_BMODULE = 0, False, False
+        >>> something # skip if not HAVE_AMODULE
+        0
+        >>> something # skip if HAVE_BMODULE
+        0
+
+    This decorator will evaluate the expression after ``skip if``.  If this
+    evaluates to True, then the comment is replaced by ``# doctest: +SKIP``. If
+    False, then the comment is just removed. The expression is evaluated in the
+    ``globals`` scope of `func`.
+
+    For example, if the module global ``HAVE_AMODULE`` is False, and module
+    global ``HAVE_BMODULE`` is False, the returned function will have docstring::
+
+        >>> something # doctest: +SKIP
+        >>> something + else # doctest: +SKIP
+        >>> something # doctest: +SKIP
+
+    """
+    lines = func.__doc__.split('\n')
+    new_lines = []
+    for line in lines:
+        match = SKIP_RE.match(line)
+        if match is None:
+            new_lines.append(line)
+            continue
+        code, space, expr = match.groups()
+
+        try:
+            # Works as a function decorator
+            if eval(expr, func.__globals__):
+                code = code + space + "# doctest: +SKIP"
+        except AttributeError:
+            # Works as a class decorator
+            if eval(expr, func.__init__.__globals__):
+                code = code + space + "# doctest: +SKIP"
+
+        new_lines.append(code)
+    func.__doc__ = "\n".join(new_lines)
+    return func
+
+
+def roundtrip(image, plugin, suffix):
+    """Save and read an image using a specified plugin"""
+    if '.' not in suffix:
+        suffix = '.' + suffix
+    temp_file = NamedTemporaryFile(suffix=suffix, delete=False)
+    fname = temp_file.name
+    temp_file.close()
+    io.imsave(fname, image, plugin=plugin)
+    new = io.imread(fname, plugin=plugin)
+    try:
+        os.remove(fname)
+    except Exception:
+        pass
+    return new
+
+
+def color_check(plugin, fmt='png'):
+    """Check roundtrip behavior for color images.
+
+    All major input types should be handled as ubytes and read
+    back correctly.
+    """
+    img = img_as_ubyte(data.chelsea())
+    r1 = roundtrip(img, plugin, fmt)
+    testing.assert_allclose(img, r1)
+
+    img2 = img > 128
+    r2 = roundtrip(img2, plugin, fmt)
+    testing.assert_allclose(img2, r2.astype(bool))
+
+    img3 = img_as_float(img)
+    r3 = roundtrip(img3, plugin, fmt)
+    testing.assert_allclose(r3, img)
+
+    img4 = img_as_int(img)
+    if fmt.lower() in (('tif', 'tiff')):
+        img4 -= 100
+        r4 = roundtrip(img4, plugin, fmt)
+        testing.assert_allclose(r4, img4)
+    else:
+        r4 = roundtrip(img4, plugin, fmt)
+        testing.assert_allclose(r4, img_as_ubyte(img4))
+
+    img5 = img_as_uint(img)
+    r5 = roundtrip(img5, plugin, fmt)
+    testing.assert_allclose(r5, img)
+
+
+def mono_check(plugin, fmt='png'):
+    """Check the roundtrip behavior for images that support most types.
+
+    All major input types should be handled.
+    """
+
+    img = img_as_ubyte(data.moon())
+    r1 = roundtrip(img, plugin, fmt)
+    testing.assert_allclose(img, r1)
+
+    img2 = img > 128
+    r2 = roundtrip(img2, plugin, fmt)
+    testing.assert_allclose(img2, r2.astype(bool))
+
+    img3 = img_as_float(img)
+    r3 = roundtrip(img3, plugin, fmt)
+    if r3.dtype.kind == 'f':
+        testing.assert_allclose(img3, r3)
+    else:
+        testing.assert_allclose(r3, img_as_uint(img))
+
+    img4 = img_as_int(img)
+    if fmt.lower() in (('tif', 'tiff')):
+        img4 -= 100
+        r4 = roundtrip(img4, plugin, fmt)
+        testing.assert_allclose(r4, img4)
+    else:
+        r4 = roundtrip(img4, plugin, fmt)
+        testing.assert_allclose(r4, img_as_uint(img4))
+
+    img5 = img_as_uint(img)
+    r5 = roundtrip(img5, plugin, fmt)
+    testing.assert_allclose(r5, img5)
+
+
+def setup_test():
+    """Default package level setup routine for skimage tests.
+
+    Import packages known to raise warnings, and then
+    force warnings to raise errors.
+
+    Also set the random seed to zero.
+    """
+    warnings.simplefilter('default')
+
+    from scipy import signal, ndimage, special, optimize, linalg
+    from scipy.io import loadmat
+    from skimage import viewer
+
+    np.random.seed(0)
+
+    warnings.simplefilter('error')
+
+
+def teardown_test():
+    """Default package level teardown routine for skimage tests.
+
+    Restore warnings to default behavior
+    """
+    warnings.simplefilter('default')
+
+
+def fetch(data_filename):
+    """Attempt to fetch data, but if unavailable, skip the tests."""
+    try:
+        return data._fetch(data_filename)
+    except (ConnectionError, ModuleNotFoundError):
+        pytest.skip(f'Unable to download {data_filename}')
+
+
+def test_parallel(num_threads=2, warnings_matching=None):
+    """Decorator to run the same function multiple times in parallel.
+
+    This decorator is useful to ensure that separate threads execute
+    concurrently and correctly while releasing the GIL.
+
+    Parameters
+    ----------
+    num_threads : int, optional
+        The number of times the function is run in parallel.
+
+    warnings_matching: list or None
+        This parameter is passed on to `expected_warnings` so as not to have
+        race conditions with the warnings filters. A single
+        `expected_warnings` context manager is used for all threads.
+        If None, then no warnings are checked.
+
+    """
+
+    assert num_threads > 0
+
+    def wrapper(func):
+        @functools.wraps(func)
+        def inner(*args, **kwargs):
+            with expected_warnings(warnings_matching):
+                threads = []
+                for i in range(num_threads - 1):
+                    thread = threading.Thread(target=func, args=args,
+                                              kwargs=kwargs)
+                    threads.append(thread)
+                for thread in threads:
+                    thread.start()
+
+                result = func(*args, **kwargs)
+
+                for thread in threads:
+                    thread.join()
+
+                return result
+
+        return inner
+
+    return wrapper
+
+
+if __name__ == '__main__':
+    color_check('pil')
+    mono_check('pil')
+    mono_check('pil', 'bmp')
+    mono_check('pil', 'tiff')

venv/Lib/site-packages/skimage/_shared/tests/__init__.py

@@ -0,0 +1,9 @@
+from ..testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def teardown():
+    teardown_test()

venv/Lib/site-packages/skimage/_shared/tests/test_fast_exp.py

@@ -0,0 +1,21 @@
+from ..fast_exp import fast_exp
+import numpy as np
+
+
+def test_fast_exp():
+
+    X = np.linspace(-5, 0, 5000, endpoint=True)
+
+    # Ground truth
+    Y = np.exp(X)
+
+    # Approximation at double precision
+    _y_f64 = np.array([fast_exp['float64_t'](x) for x in X])
+
+    # Approximation at single precision
+    _y_f32 = np.array([fast_exp['float32_t'](x) for x in X.astype('float32')],
+                      dtype='float32')
+
+    for _y in [_y_f64, _y_f32]:
+
+        assert np.abs(Y - _y).mean() < 3e-3

venv/Lib/site-packages/skimage/_shared/tests/test_geometry.py

@@ -0,0 +1,75 @@
+from skimage._shared._geometry import polygon_clip, polygon_area
+
+import numpy as np
+from numpy.testing import assert_equal, assert_almost_equal
+
+
+hand = np.array(
+    [[ 1.64516129,  1.16145833 ],
+     [ 1.64516129,  1.59375    ],
+     [ 1.35080645,  1.921875   ],
+     [ 1.375     ,  2.18229167 ],
+     [ 1.68548387,  1.9375     ],
+     [ 1.60887097,  2.55208333 ],
+     [ 1.68548387,  2.69791667 ],
+     [ 1.76209677,  2.56770833 ],
+     [ 1.83064516,  1.97395833 ],
+     [ 1.89516129,  2.75       ],
+     [ 1.9516129 ,  2.84895833 ],
+     [ 2.01209677,  2.76041667 ],
+     [ 1.99193548,  1.99479167 ],
+     [ 2.11290323,  2.63020833 ],
+     [ 2.2016129 ,  2.734375   ],
+     [ 2.25403226,  2.60416667 ],
+     [ 2.14919355,  1.953125   ],
+     [ 2.30645161,  2.36979167 ],
+     [ 2.39112903,  2.36979167 ],
+     [ 2.41532258,  2.1875     ],
+     [ 2.1733871 ,  1.703125   ],
+     [ 2.07782258,  1.16666667 ]])
+
+
+def test_polygon_area():
+    x = [0, 0, 1, 1]
+    y = [0, 1, 1, 0]
+
+    assert_almost_equal(polygon_area(y, x), 1)
+
+    x = [0, 0, 1]
+    y = [0, 1, 1]
+
+    assert_almost_equal(polygon_area(y, x), 0.5)
+
+    x = [0, 0, 0.5, 1, 1, 0.5]
+    y = [0, 1, 0.5, 1, 0, 0.5]
+
+    assert_almost_equal(polygon_area(y, x), 0.5)
+
+
+def test_poly_clip():
+    x = [0,  1, 2, 1]
+    y = [0, -1, 0, 1]
+
+    yc, xc = polygon_clip(y, x, 0, 0, 1, 1)
+    assert_equal(polygon_area(yc, xc), 0.5)
+
+    x = [-1, 1.5, 1.5, -1]
+    y = [.5, 0.5, 1.5, 1.5]
+    yc, xc = polygon_clip(y, x, 0, 0, 1, 1)
+    assert_equal(polygon_area(yc, xc), 0.5)
+
+
+def test_hand_clip():
+    (r0, c0, r1, c1) = (1.0, 1.5, 2.1, 2.5)
+    clip_r, clip_c = polygon_clip(hand[:, 1], hand[:, 0], r0, c0, r1, c1)
+    assert_equal(clip_r.size, 19)
+    assert_equal(clip_r[0], clip_r[-1])
+    assert_equal(clip_c[0], clip_c[-1])
+
+    (r0, c0, r1, c1) = (1.0, 1.5, 1.7, 2.5)
+    clip_r, clip_c = polygon_clip(hand[:, 1], hand[:, 0], r0, c0, r1, c1)
+    assert_equal(clip_r.size, 6)
+
+    (r0, c0, r1, c1) = (1.0, 1.5, 1.5, 2.5)
+    clip_r, clip_c = polygon_clip(hand[:, 1], hand[:, 0], r0, c0, r1, c1)
+    assert_equal(clip_r.size, 5)

venv/Lib/site-packages/skimage/_shared/tests/test_interpolation.py

@@ -0,0 +1,27 @@
+from skimage._shared.interpolation import coord_map_py
+from skimage._shared.testing import assert_array_equal
+
+def test_coord_map():
+    symmetric = [coord_map_py(4, n, 'S') for n in range(-6, 6)]
+    expected_symmetric = [2, 3, 3, 2, 1, 0, 0, 1, 2, 3, 3, 2]
+    assert_array_equal(symmetric, expected_symmetric)
+
+    wrap = [coord_map_py(4, n, 'W') for n in range(-6, 6)]
+    expected_wrap = [2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1]
+    assert_array_equal(wrap, expected_wrap)
+
+    edge = [coord_map_py(4, n, 'E') for n in range(-6, 6)]
+    expected_edge = [0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 3, 3]
+    assert_array_equal(edge, expected_edge)
+
+    reflect = [coord_map_py(4, n, 'R') for n in range(-6, 6)]
+    expected_reflect = [0, 1, 2, 3, 2, 1, 0, 1, 2, 3, 2, 1]
+    assert_array_equal(reflect, expected_reflect)
+
+    reflect = [coord_map_py(1, n, 'R') for n in range(-6, 6)]
+    expected_reflect = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+    assert_array_equal(reflect, expected_reflect)
+
+    other = [coord_map_py(4, n, 'undefined') for n in range(-6, 6)]
+    expected_other = list(range(-6, 6))
+    assert_array_equal(other, expected_other)

venv/Lib/site-packages/skimage/_shared/tests/test_safe_as_int.py

@@ -0,0 +1,42 @@
+import numpy as np
+from skimage._shared.utils import safe_as_int
+from skimage._shared import testing
+
+
+def test_int_cast_not_possible():
+    with testing.raises(ValueError):
+        safe_as_int(7.1)
+    with testing.raises(ValueError):
+        safe_as_int([7.1, 0.9])
+    with testing.raises(ValueError):
+        safe_as_int(np.r_[7.1, 0.9])
+    with testing.raises(ValueError):
+        safe_as_int((7.1, 0.9))
+    with testing.raises(ValueError):
+        safe_as_int(((3,   4,   1),
+                     (2, 7.6, 289)))
+    with testing.raises(ValueError):
+        safe_as_int(7.1, 0.09)
+    with testing.raises(ValueError):
+        safe_as_int([7.1, 0.9], 0.09)
+    with testing.raises(ValueError):
+        safe_as_int(np.r_[7.1, 0.9], 0.09)
+    with testing.raises(ValueError):
+        safe_as_int((7.1, 0.9), 0.09)
+    with testing.raises(ValueError):
+        safe_as_int(((3,   4,   1),
+                     (2, 7.6, 289)), 0.25)
+
+
+def test_int_cast_possible():
+    testing.assert_equal(safe_as_int(7.1, atol=0.11), 7)
+    testing.assert_equal(safe_as_int(-7.1, atol=0.11), -7)
+    testing.assert_equal(safe_as_int(41.9, atol=0.11), 42)
+    testing.assert_array_equal(safe_as_int([2, 42, 5789234.0, 87, 4]),
+                               np.r_[2, 42, 5789234, 87, 4])
+    testing.assert_array_equal(safe_as_int(np.r_[[[3, 4,  1.000000001],
+                                                  [7, 2, -8.999999999],
+                                                  [6, 9, -4234918347.]]]),
+                               np.r_[[[3, 4,           1],
+                                      [7, 2,          -9],
+                                      [6, 9, -4234918347]]])

venv/Lib/site-packages/skimage/_shared/tests/test_testing.py

@@ -0,0 +1,129 @@
+""" Testing decorators module
+"""
+
+import numpy as np
+from numpy.testing import assert_equal
+from skimage._shared.testing import doctest_skip_parser, test_parallel
+from skimage._shared import testing
+import pytest
+
+from skimage._shared._warnings import expected_warnings
+from warnings import warn
+
+
+def test_skipper():
+    def f():
+        pass
+
+    class c():
+
+        def __init__(self):
+            self.me = "I think, therefore..."
+
+    docstring = \
+        """ Header
+
+            >>> something # skip if not HAVE_AMODULE
+            >>> something + else
+            >>> a = 1 # skip if not HAVE_BMODULE
+            >>> something2   # skip if HAVE_AMODULE
+        """
+    f.__doc__ = docstring
+    c.__doc__ = docstring
+
+    global HAVE_AMODULE, HAVE_BMODULE
+    HAVE_AMODULE = False
+    HAVE_BMODULE = True
+
+    f2 = doctest_skip_parser(f)
+    c2 = doctest_skip_parser(c)
+    assert f is f2
+    assert c is c2
+
+    expected = \
+        """ Header
+
+            >>> something # doctest: +SKIP
+            >>> something + else
+            >>> a = 1
+            >>> something2
+        """
+    assert_equal(f2.__doc__, expected)
+    assert_equal(c2.__doc__, expected)
+
+    HAVE_AMODULE = True
+    HAVE_BMODULE = False
+    f.__doc__ = docstring
+    c.__doc__ = docstring
+    f2 = doctest_skip_parser(f)
+    c2 = doctest_skip_parser(c)
+
+    assert f is f2
+    expected = \
+        """ Header
+
+            >>> something
+            >>> something + else
+            >>> a = 1 # doctest: +SKIP
+            >>> something2   # doctest: +SKIP
+        """
+    assert_equal(f2.__doc__, expected)
+    assert_equal(c2.__doc__, expected)
+
+    del HAVE_AMODULE
+    f.__doc__ = docstring
+    c.__doc__ = docstring
+    with testing.raises(NameError):
+        doctest_skip_parser(f)
+    with testing.raises(NameError):
+        doctest_skip_parser(c)
+
+
+def test_test_parallel():
+    state = []
+
+    @test_parallel()
+    def change_state1():
+        state.append(None)
+    change_state1()
+    assert len(state) == 2
+
+    @test_parallel(num_threads=1)
+    def change_state2():
+        state.append(None)
+    change_state2()
+    assert len(state) == 3
+
+    @test_parallel(num_threads=3)
+    def change_state3():
+        state.append(None)
+    change_state3()
+    assert len(state) == 6
+
+
+def test_parallel_warning():
+    @test_parallel()
+    def change_state_warns_fails():
+        warn("Test warning for test parallel", stacklevel=2)
+
+    with expected_warnings(['Test warning for test parallel']):
+        change_state_warns_fails()
+
+    @test_parallel(warnings_matching=['Test warning for test parallel'])
+    def change_state_warns_passes():
+        warn("Test warning for test parallel", stacklevel=2)
+
+    change_state_warns_passes()
+
+
+def test_expected_warnings_noop():
+    # This will ensure the line beolow it behaves like a no-op
+    with expected_warnings(['Expected warnings test']):
+
+        # This should behave as a no-op
+        with expected_warnings(None):
+            warn('Expected warnings test')
+
+
+if __name__ == '__main__':
+    np.testing.run_module_suite()

venv/Lib/site-packages/skimage/_shared/tests/test_utils.py

@@ -0,0 +1,129 @@
+import sys
+import pytest
+import numpy as np
+import numpy.testing as npt
+from skimage._shared.utils import (check_nD, deprecate_kwarg,
+                                   _validate_interpolation_order,
+                                   change_default_value)
+from skimage._shared import testing
+from skimage._shared._warnings import expected_warnings
+
+
+def test_change_default_value():
+
+    @change_default_value('arg1', new_value=-1, changed_version='0.12')
+    def foo(arg0, arg1=0, arg2=1):
+        """Expected docstring"""
+        return arg0, arg1, arg2
+
+    @change_default_value('arg1', new_value=-1, changed_version='0.12',
+                          warning_msg="Custom warning message")
+    def bar(arg0, arg1=0, arg2=1):
+        """Expected docstring"""
+        return arg0, arg1, arg2
+
+    # Assert warning messages
+    with pytest.warns(FutureWarning) as record:
+        assert foo(0) == (0, 0, 1)
+        assert bar(0) == (0, 0, 1)
+
+    expected_msg = ("The new recommended value for arg1 is -1. Until "
+                    "version 0.12, the default arg1 value is 0. From "
+                    "version 0.12, the arg1 default value will be -1. "
+                    "To avoid this warning, please explicitly set arg1 value.")
+
+    assert str(record[0].message) == expected_msg
+    assert str(record[1].message) == "Custom warning message"
+
+    # Assert that nothing happens if arg1 is set
+    with pytest.warns(None) as record:
+        # No kwargs
+        assert foo(0, 2) == (0, 2, 1)
+        assert foo(0, arg1=0) == (0, 0, 1)
+
+        # Function name and doc is preserved
+        assert foo.__name__ == 'foo'
+        if sys.flags.optimize < 2:
+            # if PYTHONOPTIMIZE is set to 2, docstrings are stripped
+            assert foo.__doc__ == 'Expected docstring'
+
+    # Assert no warning was raised
+    assert not record.list
+
+
+def test_deprecated_kwarg():
+
+    @deprecate_kwarg({'old_arg1': 'new_arg1'})
+    def foo(arg0, new_arg1=1, arg2=None):
+        """Expected docstring"""
+        return arg0, new_arg1, arg2
+
+    @deprecate_kwarg({'old_arg1': 'new_arg1'},
+                     warning_msg="Custom warning message")
+    def bar(arg0, new_arg1=1, arg2=None):
+        """Expected docstring"""
+        return arg0, new_arg1, arg2
+
+    # Assert that the DeprecationWarning is raised when the deprecated
+    # argument name is used and that the reasult is valid
+    with pytest.warns(FutureWarning) as record:
+        assert foo(0, old_arg1=1) == (0, 1, None)
+        assert bar(0, old_arg1=1) == (0, 1, None)
+
+    msg = ("'old_arg1' is a deprecated argument name "
+           "for `foo`. Please use 'new_arg1' instead.")
+    assert str(record[0].message) == msg
+    assert str(record[1].message) == "Custom warning message"
+
+    # Assert that nothing happens when the function is called with the
+    # new API
+    with pytest.warns(None) as record:
+        # No kwargs
+        assert foo(0) == (0, 1, None)
+        assert foo(0, 2) == (0, 2, None)
+        assert foo(0, 1, 2) == (0, 1, 2)
+        # Kwargs without deprecated argument
+        assert foo(0, new_arg1=1, arg2=2) == (0, 1, 2)
+        assert foo(0, new_arg1=2) == (0, 2, None)
+        assert foo(0, arg2=2) == (0, 1, 2)
+        assert foo(0, 1, arg2=2) == (0, 1, 2)
+        # Function name and doc is preserved
+        assert foo.__name__ == 'foo'
+        if sys.flags.optimize < 2:
+            # if PYTHONOPTIMIZE is set to 2, docstrings are stripped
+            assert foo.__doc__ == 'Expected docstring'
+
+    # Assert no warning was raised
+    assert not record.list
+
+
+def test_check_nD():
+    z = np.random.random(200**2).reshape((200, 200))
+    x = z[10:30, 30:10]
+    with testing.raises(ValueError):
+        check_nD(x, 2)
+
+
+@pytest.mark.parametrize('dtype', [bool, int, np.uint8, np.uint16,
+                                   float, np.float32, np.float64])
+@pytest.mark.parametrize('order', [None, -1, 0, 1, 2, 3, 4, 5, 6])
+def test_validate_interpolation_order(dtype, order):
+    if order is None:
+        # Default order
+        assert (_validate_interpolation_order(dtype, None) == 0
+                if dtype == bool else 1)
+    elif order < 0 or order > 5:
+        # Order not in valid range
+        with testing.raises(ValueError):
+            _validate_interpolation_order(dtype, order)
+    elif dtype == bool and order != 0:
+        # Deprecated order for bool array
+        with expected_warnings(["Input image dtype is bool"]):
+            assert _validate_interpolation_order(bool, order) == order
+    else:
+        # Valid use case
+        assert _validate_interpolation_order(dtype, order) == order
+
+
+if __name__ == "__main__":
+    npt.run_module_suite()

venv/Lib/site-packages/skimage/_shared/tests/test_version_requirements.py

@@ -0,0 +1,41 @@
+"""Tests for the version requirement functions.
+
+"""
+import numpy as np
+from numpy.testing import assert_equal
+from skimage._shared import version_requirements as version_req
+from skimage._shared import testing
+
+
+def test_get_module_version():
+    assert version_req.get_module_version('numpy')
+    assert version_req.get_module_version('scipy')
+    with testing.raises(ImportError):
+        version_req.get_module_version('fakenumpy')
+
+
+def test_is_installed():
+    assert version_req.is_installed('python', '>=2.7')
+    assert not version_req.is_installed('numpy', '<1.0')
+
+
+def test_require():
+    # A function that only runs on Python >2.7 and numpy > 1.5 (should pass)
+    @version_req.require('python', '>2.7')
+    @version_req.require('numpy', '>1.5')
+    def foo():
+        return 1
+
+    assert_equal(foo(), 1)
+
+    # function that requires scipy < 0.1 (should fail)
+    @version_req.require('scipy', '<0.1')
+    def bar():
+        return 0
+
+    with testing.raises(ImportError):
+        bar()
+
+
+def test_get_module():
+    assert version_req.get_module("numpy") is np

venv/Lib/site-packages/skimage/_shared/tests/test_warnings.py

@@ -0,0 +1,37 @@
+import os
+from skimage._shared._warnings import expected_warnings
+import pytest
+
+
+@pytest.fixture(scope='function')
+def setup():
+    # Remove any environment variable if it exists
+    old_strictness = os.environ.pop('SKIMAGE_TEST_STRICT_WARNINGS', None)
+    yield
+    # Add the user's desired strictness
+    if old_strictness is not None:
+        os.environ['SKIMAGE_TEST_STRICT_WARNINGS'] = old_strictness
+
+
+def test_strict_warnigns_default(setup):
+    # By default we should fail on missing expected warnings
+    with pytest.raises(ValueError):
+        with expected_warnings(['some warnings']):
+            pass
+
+
+@pytest.mark.parametrize('strictness', ['1', 'true', 'True', 'TRUE'])
+def test_strict_warning_true(setup, strictness):
+    os.environ['SKIMAGE_TEST_STRICT_WARNINGS'] = strictness
+    with pytest.raises(ValueError):
+        with expected_warnings(['some warnings']):
+            pass
+
+
+@pytest.mark.parametrize('strictness', ['0', 'false', 'False', 'FALSE'])
+def test_strict_warning_false(setup, strictness):
+    # If the user doesnn't wish to be strict about warnigns
+    # the following shouldn't raise any error
+    os.environ['SKIMAGE_TEST_STRICT_WARNINGS'] = strictness
+    with expected_warnings(['some warnings']):
+        pass

venv/Lib/site-packages/skimage/_shared/utils.py

@@ -0,0 +1,375 @@
+import inspect
+import warnings
+import functools
+import sys
+import numpy as np
+import numbers
+
+from ..util import img_as_float
+from ._warnings import all_warnings, warn
+
+__all__ = ['deprecated', 'get_bound_method_class', 'all_warnings',
+           'safe_as_int', 'check_nD', 'check_shape_equality', 'warn']
+
+
+class skimage_deprecation(Warning):
+    """Create our own deprecation class, since Python >= 2.7
+    silences deprecations by default.
+
+    """
+    pass
+
+
+class change_default_value:
+    """Decorator for changing the default value of an argument.
+
+    Parameters
+    ----------
+    arg_name: str
+        The name of the argument to be updated.
+    new_value: any
+        The argument new value.
+    changed_version : str
+        The package version in which the change will be introduced.
+    warning_msg: str
+        Optional warning message. If None, a generic warning message
+        is used.
+
+    """
+
+    def __init__(self, arg_name, *, new_value, changed_version,
+                 warning_msg=None):
+        self.arg_name = arg_name
+        self.new_value = new_value
+        self.warning_msg = warning_msg
+        self.changed_version = changed_version
+
+    def __call__(self, func):
+        parameters = inspect.signature(func).parameters
+        arg_idx = list(parameters.keys()).index(self.arg_name)
+        old_value = parameters[self.arg_name].default
+
+        if self.warning_msg is None:
+            self.warning_msg = (
+                f"The new recommended value for {self.arg_name} is "
+                f"{self.new_value}. Until version {self.changed_version}, "
+                f"the default {self.arg_name} value is {old_value}. "
+                f"From version {self.changed_version}, the {self.arg_name} "
+                f"default value will be {self.new_value}. To avoid "
+                f"this warning, please explicitly set {self.arg_name} value.")
+
+        @functools.wraps(func)
+        def fixed_func(*args, **kwargs):
+            if len(args) < arg_idx + 1 and self.arg_name not in kwargs.keys():
+                # warn that arg_name default value changed:
+                warnings.warn(self.warning_msg, FutureWarning, stacklevel=2)
+            return func(*args, **kwargs)
+
+        return fixed_func
+
+
+class deprecate_kwarg:
+    """Decorator ensuring backward compatibility when argument names are
+    modified in a function definition.
+
+    Parameters
+    ----------
+    arg_mapping: dict
+        Mapping between the function's old argument names and the new
+        ones.
+    warning_msg: str
+        Optional warning message. If None, a generic warning message
+        is used.
+    removed_version : str
+        The package version in which the deprecated argument will be
+        removed.
+
+    """
+
+    def __init__(self, kwarg_mapping, warning_msg=None, removed_version=None):
+        self.kwarg_mapping = kwarg_mapping
+        if warning_msg is None:
+            self.warning_msg = ("'{old_arg}' is a deprecated argument name "
+                                "for `{func_name}`. ")
+            if removed_version is not None:
+                self.warning_msg += ("It will be removed in version {}. "
+                                     .format(removed_version))
+            self.warning_msg += "Please use '{new_arg}' instead."
+        else:
+            self.warning_msg = warning_msg
+
+    def __call__(self, func):
+        @functools.wraps(func)
+        def fixed_func(*args, **kwargs):
+            for old_arg, new_arg in self.kwarg_mapping.items():
+                if old_arg in kwargs:
+                    #  warn that the function interface has changed:
+                    warnings.warn(self.warning_msg.format(
+                        old_arg=old_arg, func_name=func.__name__,
+                        new_arg=new_arg), FutureWarning, stacklevel=2)
+                    # Substitute new_arg to old_arg
+                    kwargs[new_arg] = kwargs.pop(old_arg)
+
+            # Call the function with the fixed arguments
+            return func(*args, **kwargs)
+        return fixed_func
+
+
+class deprecated(object):
+    """Decorator to mark deprecated functions with warning.
+
+    Adapted from <http://wiki.python.org/moin/PythonDecoratorLibrary>.
+
+    Parameters
+    ----------
+    alt_func : str
+        If given, tell user what function to use instead.
+    behavior : {'warn', 'raise'}
+        Behavior during call to deprecated function: 'warn' = warn user that
+        function is deprecated; 'raise' = raise error.
+    removed_version : str
+        The package version in which the deprecated function will be removed.
+    """
+
+    def __init__(self, alt_func=None, behavior='warn', removed_version=None):
+        self.alt_func = alt_func
+        self.behavior = behavior
+        self.removed_version = removed_version
+
+    def __call__(self, func):
+
+        alt_msg = ''
+        if self.alt_func is not None:
+            alt_msg = ' Use ``%s`` instead.' % self.alt_func
+        rmv_msg = ''
+        if self.removed_version is not None:
+            rmv_msg = (' and will be removed in version %s' %
+                       self.removed_version)
+
+        msg = ('Function ``%s`` is deprecated' % func.__name__ +
+               rmv_msg + '.' + alt_msg)
+
+        @functools.wraps(func)
+        def wrapped(*args, **kwargs):
+            if self.behavior == 'warn':
+                func_code = func.__code__
+                warnings.simplefilter('always', skimage_deprecation)
+                warnings.warn_explicit(msg,
+                                       category=skimage_deprecation,
+                                       filename=func_code.co_filename,
+                                       lineno=func_code.co_firstlineno + 1)
+            elif self.behavior == 'raise':
+                raise skimage_deprecation(msg)
+            return func(*args, **kwargs)
+
+        # modify doc string to display deprecation warning
+        doc = '**Deprecated function**.' + alt_msg
+        if wrapped.__doc__ is None:
+            wrapped.__doc__ = doc
+        else:
+            wrapped.__doc__ = doc + '\n\n    ' + wrapped.__doc__
+
+        return wrapped
+
+
+def get_bound_method_class(m):
+    """Return the class for a bound method.
+
+    """
+    return m.im_class if sys.version < '3' else m.__self__.__class__
+
+
+def safe_as_int(val, atol=1e-3):
+    """
+    Attempt to safely cast values to integer format.
+
+    Parameters
+    ----------
+    val : scalar or iterable of scalars
+        Number or container of numbers which are intended to be interpreted as
+        integers, e.g., for indexing purposes, but which may not carry integer
+        type.
+    atol : float
+        Absolute tolerance away from nearest integer to consider values in
+        ``val`` functionally integers.
+
+    Returns
+    -------
+    val_int : NumPy scalar or ndarray of dtype `np.int64`
+        Returns the input value(s) coerced to dtype `np.int64` assuming all
+        were within ``atol`` of the nearest integer.
+
+    Notes
+    -----
+    This operation calculates ``val`` modulo 1, which returns the mantissa of
+    all values. Then all mantissas greater than 0.5 are subtracted from one.
+    Finally, the absolute tolerance from zero is calculated. If it is less
+    than ``atol`` for all value(s) in ``val``, they are rounded and returned
+    in an integer array. Or, if ``val`` was a scalar, a NumPy scalar type is
+    returned.
+
+    If any value(s) are outside the specified tolerance, an informative error
+    is raised.
+
+    Examples
+    --------
+    >>> safe_as_int(7.0)
+    7
+
+    >>> safe_as_int([9, 4, 2.9999999999])
+    array([9, 4, 3])
+
+    >>> safe_as_int(53.1)
+    Traceback (most recent call last):
+        ...
+    ValueError: Integer argument required but received 53.1, check inputs.
+
+    >>> safe_as_int(53.01, atol=0.01)
+    53
+
+    """
+    mod = np.asarray(val) % 1                # Extract mantissa
+
+    # Check for and subtract any mod values > 0.5 from 1
+    if mod.ndim == 0:                        # Scalar input, cannot be indexed
+        if mod > 0.5:
+            mod = 1 - mod
+    else:                                    # Iterable input, now ndarray
+        mod[mod > 0.5] = 1 - mod[mod > 0.5]  # Test on each side of nearest int
+
+    try:
+        np.testing.assert_allclose(mod, 0, atol=atol)
+    except AssertionError:
+        raise ValueError("Integer argument required but received "
+                         "{0}, check inputs.".format(val))
+
+    return np.round(val).astype(np.int64)
+
+
+def check_shape_equality(im1, im2):
+    """Raise an error if the shape do not match."""
+    if not im1.shape == im2.shape:
+        raise ValueError('Input images must have the same dimensions.')
+    return
+
+
+def check_nD(array, ndim, arg_name='image'):
+    """
+    Verify an array meets the desired ndims and array isn't empty.
+
+    Parameters
+    ----------
+    array : array-like
+        Input array to be validated
+    ndim : int or iterable of ints
+        Allowable ndim or ndims for the array.
+    arg_name : str, optional
+        The name of the array in the original function.
+
+    """
+    array = np.asanyarray(array)
+    msg_incorrect_dim = "The parameter `%s` must be a %s-dimensional array"
+    msg_empty_array = "The parameter `%s` cannot be an empty array"
+    if isinstance(ndim, int):
+        ndim = [ndim]
+    if array.size == 0:
+        raise ValueError(msg_empty_array % (arg_name))
+    if not array.ndim in ndim:
+        raise ValueError(msg_incorrect_dim % (arg_name, '-or-'.join([str(n) for n in ndim])))
+
+
+def check_random_state(seed):
+    """Turn seed into a `np.random.RandomState` instance.
+
+    Parameters
+    ----------
+    seed : None, int or np.random.RandomState
+           If `seed` is None, return the RandomState singleton used by `np.random`.
+           If `seed` is an int, return a new RandomState instance seeded with `seed`.
+           If `seed` is already a RandomState instance, return it.
+
+    Raises
+    ------
+    ValueError
+        If `seed` is of the wrong type.
+
+    """
+    # Function originally from scikit-learn's module sklearn.utils.validation
+    if seed is None or seed is np.random:
+        return np.random.mtrand._rand
+    if isinstance(seed, (numbers.Integral, np.integer)):
+        return np.random.RandomState(seed)
+    if isinstance(seed, np.random.RandomState):
+        return seed
+    raise ValueError('%r cannot be used to seed a numpy.random.RandomState'
+                     ' instance' % seed)
+
+
+def convert_to_float(image, preserve_range):
+    """Convert input image to float image with the appropriate range.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    preserve_range : bool
+        Determines if the range of the image should be kept or transformed
+        using img_as_float. Also see
+        https://scikit-image.org/docs/dev/user_guide/data_types.html
+
+    Notes:
+    ------
+    * Input images with `float32` data type are not upcast.
+
+    Returns
+    -------
+    image : ndarray
+        Transformed version of the input.
+
+    """
+    if preserve_range:
+        # Convert image to double only if it is not single or double
+        # precision float
+        if image.dtype.char not in 'df':
+            image = image.astype(float)
+    else:
+        image = img_as_float(image)
+    return image
+
+
+def _validate_interpolation_order(image_dtype, order):
+    """Validate and return spline interpolation's order.
+
+    Parameters
+    ----------
+    image_dtype : dtype
+        Image dtype.
+    order : int, optional
+        The order of the spline interpolation. The order has to be in
+        the range 0-5. See `skimage.transform.warp` for detail.
+
+    Returns
+    -------
+    order : int
+        if input order is None, returns 0 if image_dtype is bool and 1
+        otherwise. Otherwise, image_dtype is checked and input order
+        is validated accordingly (order > 0 is not supported for bool
+        image dtype)
+
+    """
+
+    if order is None:
+        return 0 if image_dtype == bool else 1
+
+    if order < 0 or order > 5:
+        raise ValueError("Spline interpolation order has to be in the "
+                         "range 0-5.")
+
+    if image_dtype == bool and order != 0:
+        warn("Input image dtype is bool. Interpolation is not defined "
+             "with bool data type. Please set order to 0 or explicitely "
+             "cast input image to another data type. Starting from version "
+             "0.19 a ValueError will be raised instead of this warning.",
+             FutureWarning, stacklevel=2)
+
+    return order

venv/Lib/site-packages/skimage/_shared/version_requirements.py

@@ -0,0 +1,180 @@
+import sys
+
+
+def ensure_python_version(min_version):
+    if not isinstance(min_version, tuple):
+        min_version = (min_version, )
+    if sys.version_info < min_version:
+        # since ensure_python_version is in the critical import path,
+        # we lazy import it.
+        from platform import python_version
+
+        raise ImportError("""
+
+You are running scikit-image on an unsupported version of Python.
+
+Unfortunately, scikit-image 0.15 and above no longer work with your installed
+version of Python (%s).  You therefore have two options: either upgrade to
+Python %s, or install an older version of scikit-image.
+
+For Python 2.7 or Python 3.4, use
+
+ $ pip install 'scikit-image<0.15'
+
+Please also consider updating `pip` and `setuptools`:
+
+ $ pip install pip setuptools --upgrade
+
+Newer versions of these tools avoid installing packages incompatible
+with your version of Python.
+""" % (python_version(), '.'.join([str(v) for v in min_version])))
+
+
+def _check_version(actver, version, cmp_op):
+    """
+    Check version string of an active module against a required version.
+
+    If dev/prerelease tags result in TypeError for string-number comparison,
+    it is assumed that the dependency is satisfied.
+    Users on dev branches are responsible for keeping their own packages up to
+    date.
+
+    Copyright (C) 2013  The IPython Development Team
+
+    Distributed under the terms of the BSD License.
+    """
+    # since version_requirements.py is in the critical import path, we
+    # lazy import it
+    from distutils.version import LooseVersion
+
+    try:
+        if cmp_op == '>':
+            return LooseVersion(actver) > LooseVersion(version)
+        elif cmp_op == '>=':
+            return LooseVersion(actver) >= LooseVersion(version)
+        elif cmp_op == '=':
+            return LooseVersion(actver) == LooseVersion(version)
+        elif cmp_op == '<':
+            return LooseVersion(actver) < LooseVersion(version)
+        else:
+            return False
+    except TypeError:
+        return True
+
+
+def get_module_version(module_name):
+    """Return module version or None if version can't be retrieved."""
+    mod = __import__(module_name,
+                     fromlist=[module_name.rpartition('.')[-1]])
+    return getattr(mod, '__version__', getattr(mod, 'VERSION', None))
+
+
+def is_installed(name, version=None):
+    """Test if *name* is installed.
+
+    Parameters
+    ----------
+    name : str
+        Name of module or "python"
+    version : str, optional
+        Version string to test against.
+        If version is not None, checking version
+        (must have an attribute named '__version__' or 'VERSION')
+        Version may start with =, >=, > or < to specify the exact requirement
+
+    Returns
+    -------
+    out : bool
+        True if `name` is installed matching the optional version.
+
+    Notes
+    -----
+    Original Copyright (C) 2009-2011 Pierre Raybaut
+    Licensed under the terms of the MIT License.
+    """
+    if name.lower() == 'python':
+        actver = sys.version[:6]
+    else:
+        try:
+            actver = get_module_version(name)
+        except ImportError:
+            return False
+    if version is None:
+        return True
+    else:
+        # since version_requirements is in the critical import path,
+        # we lazy import re
+        import re
+
+        match = re.search('[0-9]', version)
+        assert match is not None, "Invalid version number"
+        symb = version[:match.start()]
+        if not symb:
+            symb = '='
+        assert symb in ('>=', '>', '=', '<'),\
+            "Invalid version condition '%s'" % symb
+        version = version[match.start():]
+        return _check_version(actver, version, symb)
+
+
+def require(name, version=None):
+    """Return decorator that forces a requirement for a function or class.
+
+    Parameters
+    ----------
+    name : str
+        Name of module or "python".
+    version : str, optional
+        Version string to test against.
+        If version is not None, checking version
+        (must have an attribute named '__version__' or 'VERSION')
+        Version may start with =, >=, > or < to specify the exact requirement
+
+    Returns
+    -------
+    func : function
+        A decorator that raises an ImportError if a function is run
+        in the absence of the input dependency.
+    """
+    # since version_requirements is in the critical import path, we lazy import
+    # functools
+    import functools
+
+    def decorator(obj):
+        @functools.wraps(obj)
+        def func_wrapped(*args, **kwargs):
+            if is_installed(name, version):
+                return obj(*args, **kwargs)
+            else:
+                msg = '"%s" in "%s" requires "%s'
+                msg = msg % (obj, obj.__module__, name)
+                if not version is None:
+                    msg += " %s" % version
+                raise ImportError(msg + '"')
+        return func_wrapped
+    return decorator
+
+
+def get_module(module_name, version=None):
+    """Return a module object of name *module_name* if installed.
+
+    Parameters
+    ----------
+    module_name : str
+        Name of module.
+    version : str, optional
+        Version string to test against.
+        If version is not None, checking version
+        (must have an attribute named '__version__' or 'VERSION')
+        Version may start with =, >=, > or < to specify the exact requirement
+
+    Returns
+    -------
+    mod : module or None
+        Module if *module_name* is installed matching the optional version
+        or None otherwise.
+    """
+    if not is_installed(module_name, version):
+        return None
+    return __import__(module_name,
+                      fromlist=[module_name.rpartition('.')[-1]])