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MNT: hist2d now uses pcolormesh instead of pcolorfast #9987

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Merged
merged 1 commit into from
Apr 10, 2018
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MNT: hist2d now uses pcolormesh instead of pcolorfast #9987

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7 changes: 7 additions & 0 deletions doc/api/next_api_changes/2017-12-12-JMK.rst
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Original file line number Diff line number Diff line change
@@ -0,0 +1,7 @@
`.Axes.hist2d` now uses `~.Axes.pcolormesh` instead of `~.Axes.pcolorfast`
--------------------------------------------------------------------------

`.Axes.hist2d` now uses `~.Axes.pcolormesh` instead of `~.Axes.pcolorfast`,
which will improve the handling of log-axes. Note that the
returned *image* now is of type `~.matplotlib.collections.QuadMesh`
instead of `~.matplotlib.image.AxesImage`.
4 changes: 2 additions & 2 deletions lib/matplotlib/axes/_axes.py
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Expand Up @@ -6505,7 +6505,7 @@ def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
The bin edges along the x axis.
yedges : 1D array
The bin edges along the y axis.
image : AxesImage
image : `~.matplotlib.collections.QuadMesh`

Other Parameters
----------------
Expand Down Expand Up @@ -6545,7 +6545,7 @@ def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
if cmax is not None:
h[h > cmax] = None

pc = self.pcolorfast(xedges, yedges, h.T, **kwargs)
pc = self.pcolormesh(xedges, yedges, h.T, **kwargs)
self.set_xlim(xedges[0], xedges[-1])
self.set_ylim(yedges[0], yedges[-1])

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421 changes: 54 additions & 367 deletions lib/matplotlib/tests/baseline_images/test_axes/hist2d.svg
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459 changes: 54 additions & 405 deletions lib/matplotlib/tests/baseline_images/test_axes/hist2d_transpose.svg
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12 changes: 7 additions & 5 deletions lib/matplotlib/tests/test_axes.py
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Expand Up @@ -1646,24 +1646,26 @@ def test_contour_colorbar():
cbar.add_lines(cs2, erase=False)


@image_comparison(baseline_images=['hist2d', 'hist2d'])
@image_comparison(baseline_images=['hist2d', 'hist2d'],
remove_text=True, style='mpl20')
def test_hist2d():
np.random.seed(0)
# make it not symmetric in case we switch x and y axis
x = np.random.randn(100)*2+5
y = np.random.randn(100)-2
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist2d(x, y, bins=10)
ax.hist2d(x, y, bins=10, rasterized=True)
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Why the rasterized=True argument?


# Reuse testcase from above for a labeled data test
data = {"x": x, "y": y}
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist2d("x", "y", bins=10, data=data)
ax.hist2d("x", "y", bins=10, data=data, rasterized=True)


@image_comparison(baseline_images=['hist2d_transpose'])
@image_comparison(baseline_images=['hist2d_transpose'],
remove_text=True, style='mpl20')
def test_hist2d_transpose():
np.random.seed(0)
# make sure the output from np.histogram is transposed before
Expand All @@ -1672,7 +1674,7 @@ def test_hist2d_transpose():
y = np.random.randn(100)-2
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist2d(x, y, bins=10)
ax.hist2d(x, y, bins=10, rasterized=True)


@image_comparison(baseline_images=['scatter', 'scatter'])
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6 changes: 0 additions & 6 deletions lib/matplotlib/tests/test_image.py
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Expand Up @@ -586,12 +586,6 @@ def test_pcolorimage_setdata():
assert im._A[0, 0] == im._Ax[0] == im._Ay[0] == 0, 'value changed'


def test_pcolorimage_extent():
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Not sure if this was a bad thing to do....

im = plt.hist2d([1, 2, 3], [3, 5, 6],
bins=[[0, 3, 7], [1, 2, 3]])[-1]
assert im.get_extent() == (0, 7, 1, 3)


def test_minimized_rasterized():
# This ensures that the rasterized content in the colorbars is
# only as thick as the colorbar, and doesn't extend to other parts
Expand Down