1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
|
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.projections as mprojections
import matplotlib.transforms as mtransforms
from matplotlib.testing.decorators import image_comparison
from mpl_toolkits.axisartist.axislines import Subplot
from mpl_toolkits.axisartist.floating_axes import (
FloatingAxes, GridHelperCurveLinear)
from mpl_toolkits.axisartist.grid_finder import FixedLocator
from mpl_toolkits.axisartist import angle_helper
def test_subplot():
fig = plt.figure(figsize=(5, 5))
ax = Subplot(fig, 111)
fig.add_subplot(ax)
# Rather high tolerance to allow ongoing work with floating axes internals;
# remove when image is regenerated.
@image_comparison(['curvelinear3.png'], style='default', tol=5)
def test_curvelinear3():
fig = plt.figure(figsize=(5, 5))
tr = (mtransforms.Affine2D().scale(np.pi / 180, 1) +
mprojections.PolarAxes.PolarTransform(apply_theta_transforms=False))
grid_helper = GridHelperCurveLinear(
tr,
extremes=(0, 360, 10, 3),
grid_locator1=angle_helper.LocatorDMS(15),
grid_locator2=FixedLocator([2, 4, 6, 8, 10]),
tick_formatter1=angle_helper.FormatterDMS(),
tick_formatter2=None)
ax1 = fig.add_subplot(axes_class=FloatingAxes, grid_helper=grid_helper)
r_scale = 10
tr2 = mtransforms.Affine2D().scale(1, 1 / r_scale) + tr
grid_helper2 = GridHelperCurveLinear(
tr2,
extremes=(0, 360, 10 * r_scale, 3 * r_scale),
grid_locator2=FixedLocator([30, 60, 90]))
ax1.axis["right"] = axis = grid_helper2.new_fixed_axis("right", axes=ax1)
ax1.axis["left"].label.set_text("Test 1")
ax1.axis["right"].label.set_text("Test 2")
ax1.axis["left", "right"].set_visible(False)
axis = grid_helper.new_floating_axis(1, 7, axes=ax1,
axis_direction="bottom")
ax1.axis["z"] = axis
axis.toggle(all=True, label=True)
axis.label.set_text("z = ?")
axis.label.set_visible(True)
axis.line.set_color("0.5")
ax2 = ax1.get_aux_axes(tr)
xx, yy = [67, 90, 75, 30], [2, 5, 8, 4]
ax2.scatter(xx, yy)
l, = ax2.plot(xx, yy, "k-")
l.set_clip_path(ax1.patch)
# Rather high tolerance to allow ongoing work with floating axes internals;
# remove when image is regenerated.
@image_comparison(['curvelinear4.png'], style='default', tol=0.9)
def test_curvelinear4():
# Remove this line when this test image is regenerated.
plt.rcParams['text.kerning_factor'] = 6
fig = plt.figure(figsize=(5, 5))
tr = (mtransforms.Affine2D().scale(np.pi / 180, 1) +
mprojections.PolarAxes.PolarTransform(apply_theta_transforms=False))
grid_helper = GridHelperCurveLinear(
tr,
extremes=(120, 30, 10, 0),
grid_locator1=angle_helper.LocatorDMS(5),
grid_locator2=FixedLocator([2, 4, 6, 8, 10]),
tick_formatter1=angle_helper.FormatterDMS(),
tick_formatter2=None)
ax1 = fig.add_subplot(axes_class=FloatingAxes, grid_helper=grid_helper)
ax1.clear() # Check that clear() also restores the correct limits on ax1.
ax1.axis["left"].label.set_text("Test 1")
ax1.axis["right"].label.set_text("Test 2")
ax1.axis["top"].set_visible(False)
axis = grid_helper.new_floating_axis(1, 70, axes=ax1,
axis_direction="bottom")
ax1.axis["z"] = axis
axis.toggle(all=True, label=True)
axis.label.set_axis_direction("top")
axis.label.set_text("z = ?")
axis.label.set_visible(True)
axis.line.set_color("0.5")
ax2 = ax1.get_aux_axes(tr)
xx, yy = [67, 90, 75, 30], [2, 5, 8, 4]
ax2.scatter(xx, yy)
l, = ax2.plot(xx, yy, "k-")
l.set_clip_path(ax1.patch)
def test_axis_direction():
# Check that axis direction is propagated on a floating axis
fig = plt.figure()
ax = Subplot(fig, 111)
fig.add_subplot(ax)
ax.axis['y'] = ax.new_floating_axis(nth_coord=1, value=0,
axis_direction='left')
assert ax.axis['y']._axis_direction == 'left'
|
