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Fix marker overlap #10791

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Fix marker overlap #10791

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816807f
Fix marker overlap
xenoryt Mar 14, 2018
16509d7
Added: Image comparison tests for marker overlap
Gazing Mar 16, 2018
8f69f41
Fix PEP8 errors
xenoryt Mar 16, 2018
c790d25
Refactored do_projection to use starred expression
xenoryt Mar 24, 2018
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32 changes: 20 additions & 12 deletions lib/mpl_toolkits/mplot3d/art3d.py
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Original file line number Diff line number Diff line change
Expand Up @@ -455,18 +455,27 @@ def do_3d_projection(self, renderer):

fcs = (zalpha(self._facecolor3d, vzs) if self._depthshade else
self._facecolor3d)
fcs = mcolors.to_rgba_array(fcs, self._alpha)
self.set_facecolors(fcs)

ecs = (zalpha(self._edgecolor3d, vzs) if self._depthshade else
self._edgecolor3d)

# Sort the points based on z coordinates
# Put vzs first to sort based on z value
z_markers = sorted(zip(vzs, np.column_stack([vxs, vys]), fcs, ecs),
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I'm a bit worried that this could slow down the rendering when using many patches.

I know it's bad practice to base such an assumption on pure gut feeling. But before I'm going into any tests. Have you done benchmarking on the performance impact?

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Yes I had ran some benchmarking beforehand. I didn't notice any noticeable impact on performance.

I used the following script

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

import random as rand
SIZE=10000
x = np.array([rand.uniform(-50, 50) for i in range(SIZE)])
y = np.array([rand.uniform(-50, 50) for i in range(SIZE)])
z = np.array([rand.uniform(-50, 50) for i in range(SIZE)])
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
patches = ax.scatter(x, y, z, s=100, c=x)

plt.savefig("tmp.png")

Ran the script 5 times both before and after fix and didn't find any noticeable differences.
perf_fix.log
perf_vanilla.log

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These timings would have been swamped by all of the imports and figure creation and such. A real benchmark would involve seeing how long it would take to set up the plot, and then have it rotate around, like in one of the animation examples.

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I did a quick check on this part of the code, with numbers of points increased to 1000 000 (I think 100x100x100 is not unrealistic). With that the present sorting/zipping implementation is in the 100ms regime.

That's a size which gets relevant for performance in interactive use.

In a quick test, it's possible to get a roughly 10x speedup by using numpy.argsort on vzs and applying the index array to the other quantities.

reverse=True)

[zzs, vps, fcs, ecs] = zip(*z_markers)
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you'll need a check for an empty z_markers before trying to doing this.


fcs = mcolors.to_rgba_array(fcs, self._alpha)
ecs = mcolors.to_rgba_array(ecs, self._alpha)

self.set_edgecolors(ecs)
PathCollection.set_offsets(self, np.column_stack([vxs, vys]))
self.set_facecolors(fcs)

PathCollection.set_offsets(self, vps)

if vzs.size > 0 :
if vzs.size > 0:
return min(vzs)
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we don't need to do min(vzs) anymore. we now have the sorted zzs. Just return the last element (since you did a reversed sort).

else :
else:
return np.nan


Expand Down Expand Up @@ -634,17 +643,16 @@ def do_3d_projection(self, renderer):
else:
raise ValueError("whoops")

segments_2d = [s for z, s, fc, ec, idx in z_segments_2d]
[zzs, segments_2d, self._facecolors2d, self._edgecolors2d, idxs] = \
zip(*z_segments_2d)
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another check for empty z_segments_2d before doing this.


if self._codes3d is not None:
codes = [self._codes3d[idx] for z, s, fc, ec, idx in z_segments_2d]
codes = [self._codes3d[idx] for idx in idxs]
PolyCollection.set_verts_and_codes(self, segments_2d, codes)
else:
PolyCollection.set_verts(self, segments_2d, self._closed)

self._facecolors2d = [fc for z, s, fc, ec, idx in z_segments_2d]
if len(self._edgecolors3d) == len(cface):
self._edgecolors2d = [ec for z, s, fc, ec, idx in z_segments_2d]
else:
if len(self._edgecolors3d) != len(cface):
self._edgecolors2d = self._edgecolors3d
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edgecolors3d hasn't been sorted, if I understand this correctly.


# Return zorder value
Expand Down
Binary file added ..._toolkits/tests/baseline_images/test_mplot3d/scatter3d_overlap_markers_blue.png
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Binary file added ...oolkits/tests/baseline_images/test_mplot3d/scatter3d_overlap_markers_yellow.png
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24 changes: 24 additions & 0 deletions lib/mpl_toolkits/tests/test_mplot3d.py
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Expand Up @@ -175,6 +175,30 @@ def test_scatter3d_color():
color='b', marker='s')


@image_comparison(baseline_images=['scatter3d_overlap_markers_yellow'],
extensions=['png'], remove_text=True)
def test_overlap_markers_yellow_first():
fig = plt.figure()
x = np.array([-1, 1])
y = np.array([1, -1])
z = np.array([0, 0])
ax = fig.add_subplot(111, projection='3d')
patches = ax.scatter(x, y, z, s=3500, c=['b', 'y'])
ax.view_init(elev=0, azim=-50)


@image_comparison(baseline_images=['scatter3d_overlap_markers_blue'],
extensions=['png'], remove_text=True)
def test_overlap_markers_blue_first():
fig = plt.figure()
x = np.array([-1, 1])
y = np.array([1, -1])
z = np.array([0, 0])
ax = fig.add_subplot(111, projection='3d')
patches = ax.scatter(x, y, z, s=3500, c=['b', 'y'])
ax.view_init(elev=0, azim=130)


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Can you add a bit more to these tests? Make sure the edge colors are getting sorted properly, too?

@image_comparison(baseline_images=['plot_3d_from_2d'], remove_text=True,
extensions=['png'])
def test_plot_3d_from_2d():
Expand Down