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