Vehicle-Anti-Theft-Face-Rec.../venv/Lib/site-packages/skimage/io/tests/test_mpl_imshow.py

135 lines
4.1 KiB
Python

import numpy as np
from skimage import io
from skimage._shared._warnings import expected_warnings
import matplotlib.pyplot as plt
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
if __name__ == '__main__':
np.testing.run_module_suite()