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jklymakjklymak
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TST: fix tests for hist2d
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‎doc/api/next_api_changes/2017-12-12-JMK.rst

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`.Axes.hist2d` now uses `~.pcolormesh` instead of `~.pcolorfast`
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------------------------------------------------------------
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`.Axes.hist2d` now uses `~.pcolormesh` instead of `~.pcolorfast`,
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which will improve the handling of log-axes. Note that the
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returned *image* now is of type `~.matplotlib.collections.QuadMesh`
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instead of `~.matplotlib.image.AxesImage`.

‎lib/matplotlib/axes/_axes.py

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@@ -6505,7 +6505,7 @@ def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
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The bin edges along the x axis.
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yedges : 1D array
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The bin edges along the y axis.
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image : AxesImage
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image : `~.matplotlib.collections.QuadMesh`
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Other Parameters
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----------------
@@ -6545,7 +6545,7 @@ def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
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if cmax is not None:
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h[h > cmax] = None
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pc = self.pcolorfast(xedges, yedges, h.T, **kwargs)
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pc = self.pcolormesh(xedges, yedges, h.T, **kwargs)
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self.set_xlim(xedges[0], xedges[-1])
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self.set_ylim(yedges[0], yedges[-1])
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‎lib/matplotlib/tests/baseline_images/test_axes/hist2d.pdf

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‎lib/matplotlib/tests/baseline_images/test_axes/hist2d.png

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‎lib/matplotlib/tests/baseline_images/test_axes/hist2d.svg

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‎lib/matplotlib/tests/baseline_images/test_axes/hist2d_transpose.pdf

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‎lib/matplotlib/tests/baseline_images/test_axes/hist2d_transpose.png

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‎lib/matplotlib/tests/baseline_images/test_axes/hist2d_transpose.svg

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‎lib/matplotlib/tests/test_axes.py

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@@ -1646,24 +1646,26 @@ def test_contour_colorbar():
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cbar.add_lines(cs2, erase=False)
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@image_comparison(baseline_images=['hist2d', 'hist2d'])
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@image_comparison(baseline_images=['hist2d', 'hist2d'],
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remove_text=True, style='mpl20')
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def test_hist2d():
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np.random.seed(0)
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# make it not symmetric in case we switch x and y axis
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x = np.random.randn(100)*2+5
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y = np.random.randn(100)-2
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fig = plt.figure()
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ax = fig.add_subplot(111)
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ax.hist2d(x, y, bins=10)
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ax.hist2d(x, y, bins=10, rasterized=True)
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# Reuse testcase from above for a labeled data test
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data = {"x": x, "y": y}
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fig = plt.figure()
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ax = fig.add_subplot(111)
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ax.hist2d("x", "y", bins=10, data=data)
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ax.hist2d("x", "y", bins=10, data=data, rasterized=True)
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@image_comparison(baseline_images=['hist2d_transpose'])
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@image_comparison(baseline_images=['hist2d_transpose'],
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remove_text=True, style='mpl20')
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def test_hist2d_transpose():
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np.random.seed(0)
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# make sure the output from np.histogram is transposed before
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y = np.random.randn(100)-2
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fig = plt.figure()
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ax = fig.add_subplot(111)
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ax.hist2d(x, y, bins=10)
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ax.hist2d(x, y, bins=10, rasterized=True)
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@image_comparison(baseline_images=['scatter', 'scatter'])

‎lib/matplotlib/tests/test_image.py

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@@ -586,12 +586,6 @@ def test_pcolorimage_setdata():
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assert im._A[0, 0] == im._Ax[0] == im._Ay[0] == 0, 'value changed'
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def test_pcolorimage_extent():
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im = plt.hist2d([1, 2, 3], [3, 5, 6],
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bins=[[0, 3, 7], [1, 2, 3]])[-1]
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assert im.get_extent() == (0, 7, 1, 3)
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def test_minimized_rasterized():
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# This ensures that the rasterized content in the colorbars is
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# only as thick as the colorbar, and doesn't extend to other parts

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