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
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
|
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.path import Path
from matplotlib.projections import PolarAxes
from matplotlib.ticker import FuncFormatter
from matplotlib.transforms import Affine2D, Transform
from matplotlib.testing.decorators import image_comparison
from mpl_toolkits.axisartist import SubplotHost
from mpl_toolkits.axes_grid1.parasite_axes import host_axes_class_factory
from mpl_toolkits.axisartist import angle_helper
from mpl_toolkits.axisartist.axislines import Axes
from mpl_toolkits.axisartist.grid_helper_curvelinear import \
GridHelperCurveLinear
@image_comparison(['custom_transform.png'], style='default', tol=0.2)
def test_custom_transform():
class MyTransform(Transform):
input_dims = output_dims = 2
def __init__(self, resolution):
"""
Resolution is the number of steps to interpolate between each input
line segment to approximate its path in transformed space.
"""
Transform.__init__(self)
self._resolution = resolution
def transform(self, ll):
x, y = ll.T
return np.column_stack([x, y - x])
transform_non_affine = transform
def transform_path(self, path):
ipath = path.interpolated(self._resolution)
return Path(self.transform(ipath.vertices), ipath.codes)
transform_path_non_affine = transform_path
def inverted(self):
return MyTransformInv(self._resolution)
class MyTransformInv(Transform):
input_dims = output_dims = 2
def __init__(self, resolution):
Transform.__init__(self)
self._resolution = resolution
def transform(self, ll):
x, y = ll.T
return np.column_stack([x, y + x])
def inverted(self):
return MyTransform(self._resolution)
fig = plt.figure()
SubplotHost = host_axes_class_factory(Axes)
tr = MyTransform(1)
grid_helper = GridHelperCurveLinear(tr)
ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
fig.add_subplot(ax1)
ax2 = ax1.get_aux_axes(tr, viewlim_mode="equal")
ax2.plot([3, 6], [5.0, 10.])
ax1.set_aspect(1.)
ax1.set_xlim(0, 10)
ax1.set_ylim(0, 10)
ax1.grid(True)
@image_comparison(['polar_box.png'], style='default', tol=0.04)
def test_polar_box():
fig = plt.figure(figsize=(5, 5))
# PolarAxes.PolarTransform takes radian. However, we want our coordinate
# system in degree
tr = (Affine2D().scale(np.pi / 180., 1.) +
PolarAxes.PolarTransform(apply_theta_transforms=False))
# polar projection, which involves cycle, and also has limits in
# its coordinates, needs a special method to find the extremes
# (min, max of the coordinate within the view).
extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
lon_cycle=360,
lat_cycle=None,
lon_minmax=None,
lat_minmax=(0, np.inf))
grid_helper = GridHelperCurveLinear(
tr,
extreme_finder=extreme_finder,
grid_locator1=angle_helper.LocatorDMS(12),
tick_formatter1=angle_helper.FormatterDMS(),
tick_formatter2=FuncFormatter(lambda x, p: "eight" if x == 8 else f"{int(x)}"),
)
ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
ax1.axis["right"].major_ticklabels.set_visible(True)
ax1.axis["top"].major_ticklabels.set_visible(True)
# let right axis shows ticklabels for 1st coordinate (angle)
ax1.axis["right"].get_helper().nth_coord_ticks = 0
# let bottom axis shows ticklabels for 2nd coordinate (radius)
ax1.axis["bottom"].get_helper().nth_coord_ticks = 1
fig.add_subplot(ax1)
ax1.axis["lat"] = axis = grid_helper.new_floating_axis(0, 45, axes=ax1)
axis.label.set_text("Test")
axis.label.set_visible(True)
axis.get_helper().set_extremes(2, 12)
ax1.axis["lon"] = axis = grid_helper.new_floating_axis(1, 6, axes=ax1)
axis.label.set_text("Test 2")
axis.get_helper().set_extremes(-180, 90)
# A parasite axes with given transform
ax2 = ax1.get_aux_axes(tr, viewlim_mode="equal")
assert ax2.transData == tr + ax1.transData
# Anything you draw in ax2 will match the ticks and grids of ax1.
ax2.plot(np.linspace(0, 30, 50), np.linspace(10, 10, 50))
ax1.set_aspect(1.)
ax1.set_xlim(-5, 12)
ax1.set_ylim(-5, 10)
ax1.grid(True)
# Remove tol & kerning_factor when this test image is regenerated.
@image_comparison(['axis_direction.png'], style='default', tol=0.13)
def test_axis_direction():
plt.rcParams['text.kerning_factor'] = 6
fig = plt.figure(figsize=(5, 5))
# PolarAxes.PolarTransform takes radian. However, we want our coordinate
# system in degree
tr = (Affine2D().scale(np.pi / 180., 1.) +
PolarAxes.PolarTransform(apply_theta_transforms=False))
# polar projection, which involves cycle, and also has limits in
# its coordinates, needs a special method to find the extremes
# (min, max of the coordinate within the view).
# 20, 20 : number of sampling points along x, y direction
extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
lon_cycle=360,
lat_cycle=None,
lon_minmax=None,
lat_minmax=(0, np.inf),
)
grid_locator1 = angle_helper.LocatorDMS(12)
tick_formatter1 = angle_helper.FormatterDMS()
grid_helper = GridHelperCurveLinear(tr,
extreme_finder=extreme_finder,
grid_locator1=grid_locator1,
tick_formatter1=tick_formatter1)
ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
for axis in ax1.axis.values():
axis.set_visible(False)
fig.add_subplot(ax1)
ax1.axis["lat1"] = axis = grid_helper.new_floating_axis(
0, 130,
axes=ax1, axis_direction="left")
axis.label.set_text("Test")
axis.label.set_visible(True)
axis.get_helper().set_extremes(0.001, 10)
ax1.axis["lat2"] = axis = grid_helper.new_floating_axis(
0, 50,
axes=ax1, axis_direction="right")
axis.label.set_text("Test")
axis.label.set_visible(True)
axis.get_helper().set_extremes(0.001, 10)
ax1.axis["lon"] = axis = grid_helper.new_floating_axis(
1, 10,
axes=ax1, axis_direction="bottom")
axis.label.set_text("Test 2")
axis.get_helper().set_extremes(50, 130)
axis.major_ticklabels.set_axis_direction("top")
axis.label.set_axis_direction("top")
grid_helper.grid_finder.grid_locator1.set_params(nbins=5)
grid_helper.grid_finder.grid_locator2.set_params(nbins=5)
ax1.set_aspect(1.)
ax1.set_xlim(-8, 8)
ax1.set_ylim(-4, 12)
ax1.grid(True)
|
