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# First, we test adjustable='datalim'. Here, whether xlim or ylim are
# changed is up to Matplotlib.
fig = plt.figure(figsize=(6, 4))
ax = fig.add_axes([0, 0, 1, 1], aspect='equal')
ax.imshow(image, origin='lower')
# Since the axes has a landscape aspect ratio, the image should fit
# vertically and have white padding horizontally:
ax.set_adjustable('datalim')
ax.apply_aspect()
assert_allclose(ax.get_xlim(), [-1.75, 5.75])
assert_allclose(ax.get_ylim(), [-0.5, 4.5])
# Because of the way Matplotlib computes the aspect internally, it turns
# out that in this scenario ylim is the adjustable, so even if we change
# ylim, xlim will stay the same and ylim will get adjusted. This could be
# improved in future by checking in set_xlim and set_ylim whether
# adjustable='datalim' and try and make sure this value is respected.
ax.set_ylim(4, 5)
ax.apply_aspect()
assert_allclose(ax.get_xlim(), [-1.75, 5.75])
assert_allclose(ax.get_ylim(), [2, 7])
# Similarly, if xlim is changed, the values are not necessarily respected
# and in fact ylim is the one that stays constant. This behavior is the
# reason for adding explicit adjustable='xlim' and adjustable='ylim'
# options.
ax.set_xlim(1, 4)
ax.apply_aspect()
assert_allclose(ax.get_xlim(), [-1.25, 6.25])
assert_allclose(ax.get_ylim(), [2, 7])
# We now test adjustable='xlim', which should behave in a much more
# predictable way.
fig = plt.figure(figsize=(6, 4))
ax = fig.add_axes([0, 0, 1, 1], aspect='equal')
ax.imshow(image, origin='lower')
ax.set_adjustable('xlim')
ax.apply_aspect()
assert_allclose(ax.get_xlim(), [-1.75, 5.75])
assert_allclose(ax.get_ylim(), [-0.5, 4.5])
# Changing ylim results in ylim changing predictably and xlim getting
# adjusted
ax.set_ylim(4, 6)
ax.apply_aspect()
assert_allclose(ax.get_xlim(), [0.5, 3.5])
assert_allclose(ax.get_ylim(), [4, 6])
# Changing xlim results in xlim adjusting itself and ylim staying the same
ax.set_xlim(2, 4)
ax.apply_aspect()
assert_allclose(ax.get_xlim(), [1.5, 4.5])
assert_allclose(ax.get_ylim(), [4, 6])
# Finally we test adjustable='ylim', which should behave similarly to
# 'xlim'
fig = plt.figure(figsize=(6, 4))
ax = fig.add_axes([0, 0, 1, 1], aspect='equal')
ax.imshow(image, origin='lower')
# In the case where ylim is the adjustable, the image will fill the axes
# horizontally.
ax.set_adjustable('ylim')
ax.apply_aspect()
assert_allclose(ax.get_xlim(), [-0.5, 4.5])
assert_allclose(ax.get_ylim(), [1 / 3., 11 / 3.])
# Changing xlim results in xlim changing predictably and ylim getting
# adjusted
ax.set_xlim(4, 6)
ax.apply_aspect()
assert_allclose(ax.get_xlim(), [4, 6])
assert_allclose(ax.get_ylim(), [4 / 3., 8 / 3.])
# Changing ylim results in ylim adjusting itself and xlim staying the same
ax.set_ylim(2, 4)
ax.apply_aspect()
assert_allclose(ax.get_xlim(), [4, 6])
assert_allclose(ax.get_ylim(), [7 / 3., 11 / 3.])
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ENH: add two new modes for 'adjustable' option #8700
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ENH: add two new modes for 'adjustable' option #8700
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