10000 Use np.nanmin/max to set ax limits in Axes.vlines · matplotlib/matplotlib@747c3cd · GitHub
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phobsonphobson
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Use np.nanmin/max to set ax limits in Axes.vlines
Closes GH #7406. Also applied fixes to Axes.hlines and wrote tests for both.
1 parent bdf2146 commit 747c3cd

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8 files changed

+104
-18
lines changed

8 files changed

+104
-18
lines changed

‎lib/matplotlib/axes/_axes.py

Lines changed: 20 additions & 18 deletions
Original file line numberDiff line numberDiff line change
@@ -965,6 +965,8 @@ def hlines(self, y, xmin, xmax, colors='k', linestyles='solid',
965965
xmin = self.convert_xunits(xmin)
966966
xmax = self.convert_xunits(xmax)
967967

968+
y, xmin, xmax = cbook.delete_masked_points(y, xmin, xmax)
969+
968970
if not iterable(y):
969971
y = [y]
970972
if not iterable(xmin):
@@ -973,20 +975,19 @@ def hlines(self, y, xmin, xmax, colors='k', linestyles='solid',
973975
xmax = [xmax]
974976

975977
y = np.ravel(y)
976-
977978
xmin = np.resize(xmin, y.shape)
978979
xmax = np.resize(xmax, y.shape)
979980

980981
verts = [((thisxmin, thisy), (thisxmax, thisy))
981982
for thisxmin, thisxmax, thisy in zip(xmin, xmax, y)]
982-
coll = mcoll.LineCollection(verts, colors=colors,
983-
linestyles=linestyles, label=label)
984-
self.add_collection(coll, autolim=False)
985-
coll.update(kwargs)
983+
lines = mcoll.LineCollection(verts, colors=colors,
984+
linestyles=linestyles, label=label)
985+
self.add_collection(lines, autolim=False)
986+
lines.update(kwargs)
986987

987988
if len(y) > 0:
988-
minx = min(xmin.min(), xmax.min())
989-
maxx = max(xmin.max(), xmax.max())
989+
minx = np.min([xmin.min(), xmax.min()])
990+
maxx = np.max([xmin.max(), xmax.max()])
990991
miny = y.min()
991992
maxy = y.max()
992993

@@ -995,7 +996,7 @@ def hlines(self, y, xmin, xmax, colors='k', linestyles='solid',
995996
self.update_datalim(corners)
996997
self.autoscale_view()
997998

998-
return coll
999+
return lines
9991000

10001001
@_preprocess_data(replace_names=["x", "ymin", "ymax", "colors"],
10011002
label_namer="x")
@@ -1046,6 +1047,8 @@ def vlines(self, x, ymin, ymax, colors='k', linestyles='solid',
10461047
ymin = self.convert_yunits(ymin)
10471048
ymax = self.convert_yunits(ymax)
10481049

1050+
x, ymin, ymax = cbook.delete_masked_points(x, ymin, ymax)
1051+
10491052
if not iterable(x):
10501053
x = [x]
10511054
if not iterable(ymin):
@@ -1060,23 +1063,22 @@ def vlines(self, x, ymin, ymax, colors='k', linestyles='solid',
10601063
verts = [((thisx, thisymin), (thisx, thisymax))
10611064
for thisx, thisymin, thisymax in zip(x, ymin, ymax)]
10621065
#print 'creating line collection'
1063-
coll = mcoll.LineCollection(verts, colors=colors,
1064-
linestyles=linestyles, label=label)
1065-
self.add_collection(coll, autolim=False)
1066-
coll.update(kwargs)
1066+
lines = mcoll.LineCollection(verts, colors=colors,
1067+
linestyles=linestyles, label=label)
1068+
self.add_collection(lines, autolim=False)
1069+
lines.update(kwargs)
10671070

10681071
if len(x) > 0:
1069-
minx = min(x)
1070-
maxx = max(x)
1071-
1072-
miny = min(min(ymin), min(ymax))
1073-
maxy = max(max(ymin), max(ymax))
1072+
minx = x.min()
1073+
maxx = x< B41A /span>.max()
1074+
miny = np.min([ymin.min(), ymax.min()])
1075+
maxy = np.max([ymin.max(), ymax.max()])
10741076

10751077
corners = (minx, miny), (maxx, maxy)
10761078
self.update_datalim(corners)
10771079
self.autoscale_view()
10781080

1079-
return coll
1081+
return lines
10801082

10811083
@_preprocess_data(replace_names=["positions", "lineoffsets",
10821084
"linelengths", "linewidths",

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

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

11.3 KB
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‎lib/matplotlib/tests/baseline_images/test_axes/hlines_with_nan.png

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

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

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

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‎lib/matplotlib/tests/test_axes.py

Lines changed: 84 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -2812,6 +2812,90 @@ def test_eb_line_zorder():
28122812
ax.set_title("errorbar zorder test")
28132813

28142814

2815+
@image_comparison(
2816+
baseline_images=['vlines_basic', 'vlines_with_nan', 'vlines_masked'],
2817+
extensions=['png']
2818+
)
2819+
def test_vlines():
2820+
# normal
2821+
x1 = [2, 3, 4, 5, 7]
2822+
y1 = [2, -6, 3, 8, 2]
2823+
fig1, ax1 = plt.subplots()
2824+
ax1.vlines(x1, 0, y1, colors='g', linewidth=5)
2825+
2826+
# GH #7406
2827+
x2 = [2, 3, 4, 5, 6, 7]
2828+
y2 = [2, -6, 3, 8, np.nan, 2]
2829+
fig2, (ax2, ax3, ax4) = plt.subplots(nrows=3, figsize=(4, 8))
2830+
ax2.vlines(x2, 0, y2, colors='g', linewidth=5)
2831+
2832+
x3 = [2, 3, 4, 5, 6, 7]
2833+
y3 = [np.nan, 2, -6, 3, 8, 2]
2834+
ax3.vlines(x3, 0, y3, colors='r', linewidth=3, linestyle='--')
2835+
2836+
x4 = [2, 3, 4, 5, 6, 7]
2837+
y4 = [np.nan, 2, -6, 3, 8, np.nan]
2838+
ax4.vlines(x4, 0, y4, colors='k', linewidth=2)
2839+
2840+
# tweak the x-axis so we can see the lines better
2841+
for ax in [ax1, ax2, ax3, ax4]:
2842+
ax.set_xlim(0, 10)
2843+
2844+
# check that the y-lims are all automatically the same
2845+
assert ax1.get_ylim() == ax2.get_ylim()
2846+
assert ax1.get_ylim() == ax3.get_ylim()
2847+
assert ax1.get_ylim() == ax4.get_ylim()
2848+
2849+
fig3, ax5 = plt.subplots()
2850+
x5 = np.ma.masked_equal([2, 4, 6, 8, 10, 12], 8)
2851+
ymin5 = np.ma.masked_equal([0, 1, -1, 0, 2, 1], 2)
2852+
ymax5 = np.ma.masked_equal([13, 14, 15, 16, 17, 18], 18)
2853+
ax5.vlines(x5, ymin5, ymax5, colors='k', linewidth=2)
2854+
ax5.set_xlim(0, 15)
2855+
2856+
2857+
@image_comparison(
2858+
baseline_images=['hlines_basic', 'hlines_with_nan', 'hlines_masked'],
2859+
extensions=['png']
2860+
)
2861+
def test_hlines():
2862+
# normal
2863+
y1 = [2, 3, 4, 5, 7]
2864+
x1 = [2, -6, 3, 8, 2]
2865+
fig1, ax1 = plt.subplots()
2866+
ax1.hlines(y1, 0, x1, colors='g', linewidth=5)
2867+
2868+
# GH #7406
2869+
y2 = [2, 3, 4, 5, 6, 7]
2870+
x2 = [2, -6, 3, 8, np.nan, 2]
2871+
fig2, (ax2, ax3, ax4) = plt.subplots(nrows=3, figsize=(4, 8))
2872+
ax2.hlines(y2, 0, x2, colors='g', linewidth=5)
2873+
2874+
y3 = [2, 3, 4, 5, 6, 7]
2875+
x3 = [np.nan, 2, -6, 3, 8, 2]
2876+
ax3.hlines(y3, 0, x3, colors='r', linewidth=3, linestyle='--')
2877+
2878+
y4 = [2, 3, 4, 5, 6, 7]
2879+
x4 = [np.nan, 2, -6, 3, 8, np.nan]
2880+
ax4.hlines(y4, 0, x4, colors='k', linewidth=2)
2881+
2882+
# tweak the y-axis so we can see the lines better
2883+
for ax in [ax1, ax2, ax3, ax4]:
2884+
ax.set_ylim(0, 10)
2885+
2886+
# check that the x-lims are all automatically the same
2887+
assert ax1.get_xlim() == ax2.get_xlim()
2888+
assert ax1.get_xlim() == ax3.get_xlim()
2889+
assert ax1.get_xlim() == ax4.get_xlim()
2890+
2891+
fig3, ax5 = plt.subplots()
2892+
y5 = np.ma.masked_equal([2, 4, 6, 8, 10, 12], 8)
2893+
xmin5 = np.ma.masked_equal([0, 1, -1, 0, 2, 1], 2)
2894+
xmax5 = np.ma.masked_equal([13, 14, 15, 16, 17, 18], 18)
2895+
ax5.hlines(y5, xmin5, xmax5, colors='k', linewidth=2)
2896+
ax5.set_ylim(0, 15)
2897+
2898+
28152899
@image_comparison(baseline_images=['step_linestyle', 'step_linestyle'],
28162900
remove_text=True)
28172901
def test_step_linestyle():

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