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Fix twoslopenorm colorbar #20582

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Merged
merged 2 commits into from
Jul 13, 2021
Merged

Fix twoslopenorm colorbar #20582

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9ef1caa
FIX: fix twoslope norm for colorbars
jklymak Jul 6, 2021
38ad08e
FIX: use left and right
jklymak Jul 7, 2021
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8 changes: 5 additions & 3 deletions lib/matplotlib/colors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1300,9 +1300,11 @@ def __call__(self, value, clip=None):

if not self.vmin <= self.vcenter <= self.vmax:
raise ValueError("vmin, vcenter, vmax must increase monotonically")
# note that we must extrapolate for tick locators:
result = np.ma.masked_array(
np.interp(result, [self.vmin, self.vcenter, self.vmax],
[0, 0.5, 1.]), mask=np.ma.getmask(result))
[0, 0.5, 1], left=-np.inf, right=np.inf),
mask=np.ma.getmask(result))
if is_scalar:
result = np.atleast_1d(result)[0]
return result
Expand All @@ -1313,8 +1315,8 @@ def inverse(self, value):
(vmin,), _ = self.process_value(self.vmin)
(vmax,), _ = self.process_value(self.vmax)
(vcenter,), _ = self.process_value(self.vcenter)

result = np.interp(value, [0, 0.5, 1.], [vmin, vcenter, vmax])
result = np.interp(value, [0, 0.5, 1], [vmin, vcenter, vmax],
left=-np.inf, right=np.inf)
return result


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Binary file modified lib/matplotlib/tests/baseline_images/test_colorbar/colorbar_twoslope.png
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5 changes: 3 additions & 2 deletions lib/matplotlib/tests/test_colorbar.py
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Expand Up @@ -776,11 +776,12 @@ def test_inset_colorbar_layout():
@image_comparison(['colorbar_twoslope.png'], remove_text=True,
style='mpl20')
def test_twoslope_colorbar():
# Note that the first tick = 20, and should be in the middle
# Note that the second tick = 20, and should be in the middle
# of the colorbar (white)
# There should be no tick right at the bottom, nor at the top.
fig, ax = plt.subplots()

norm = mcolors.TwoSlopeNorm(20, 0, 100)
norm = mcolors.TwoSlopeNorm(20, 5, 95)
pc = ax.pcolormesh(np.arange(1, 11), np.arange(1, 11),
np.arange(100).reshape(10, 10),
norm=norm, cmap='RdBu_r')
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20 changes: 15 additions & 5 deletions tutorials/colors/colormapnorms.py
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Expand Up @@ -277,7 +277,8 @@
# longitude depends on latitude.
ax.set_aspect(1 / np.cos(np.deg2rad(49)))
ax.set_title('TwoSlopeNorm(x)')
fig.colorbar(pcm, shrink=0.6)
cb = fig.colorbar(pcm, shrink=0.6)
cb.set_ticks([-500, 0, 1000, 2000, 3000, 4000])
plt.show()


Expand Down Expand Up @@ -312,7 +313,8 @@ def _inverse(x):
# ----------------------------------------------------------
#
# The `.TwoSlopeNorm` described above makes a useful example for
# defining your own norm.
# defining your own norm. Note for the colorbar to work, you must
# define an inverse for your norm:
Comment on lines +316 to +317
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I wonder if it would make sense to create an abstract base class for Norms that raises NotImplemented for inverse() so that it doesn't accidentally work with a colorbar? (I think right now it is inheriting the inverse from the standard "Linear" Normalize class. We could catch the NotImplemented in the Colorbar code and warn appropriately there that the inverse method needs to be implemented.

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I think that would be sensible.

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#7320 seems related to that.



class MidpointNormalize(colors.Normalize):
Expand All @@ -323,8 +325,14 @@ def __init__(self, vmin=None, vmax=None, vcenter=None, clip=False):
def __call__(self, value, clip=None):
# I'm ignoring masked values and all kinds of edge cases to make a
# simple example...
x, y = [self.vmin, self.vcenter, self.vmax], [0, 0.5, 1]
return np.ma.masked_array(np.interp(value, x, y))
# Note also that we must extrapolate beyond vmin/vmax
x, y = [self.vmin, self.vcenter, self.vmax], [0, 0.5, 1.]
return np.ma.masked_array(np.interp(value, x, y,
left=-np.inf, right=np.inf))

def inverse(self, value):
y, x = [self.vmin, self.vcenter, self.vmax], [0, 0.5, 1]
return np.interp(value, x, y, left=-np.inf, right=np.inf)


fig, ax = plt.subplots()
Expand All @@ -334,5 +342,7 @@ def __call__(self, value, clip=None):
cmap=terrain_map, shading='auto')
ax.set_aspect(1 / np.cos(np.deg2rad(49)))
ax.set_title('Custom norm')
fig.colorbar(pcm, shrink=0.6, extend='both')
cb = fig.colorbar(pcm, shrink=0.6, extend='both')
cb.set_ticks([-500, 0, 1000, 2000, 3000, 4000])

plt.show()