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
|
"""
======================
Whats New 0.98.4 Fancy
======================
Create fancy box and arrow styles.
"""
import matplotlib.patches as mpatch
import matplotlib.pyplot as plt
figheight = 8
fig = plt.figure(1, figsize=(9, figheight), dpi=80)
fontsize = 0.4 * fig.dpi
def make_boxstyles(ax):
styles = mpatch.BoxStyle.get_styles()
for i, (stylename, styleclass) in enumerate(sorted(styles.items())):
ax.text(0.5, (float(len(styles)) - 0.5 - i)/len(styles), stylename,
ha="center",
size=fontsize,
transform=ax.transAxes,
bbox=dict(boxstyle=stylename, fc="w", ec="k"))
def make_arrowstyles(ax):
styles = mpatch.ArrowStyle.get_styles()
ax.set_xlim(0, 4)
ax.set_ylim(0, figheight)
for i, (stylename, styleclass) in enumerate(sorted(styles.items())):
y = (float(len(styles)) -0.25 - i) # /figheight
p = mpatch.Circle((3.2, y), 0.2, fc="w")
ax.add_patch(p)
ax.annotate(stylename, (3.2, y),
(2., y),
#xycoords="figure fraction", textcoords="figure fraction",
ha="right", va="center",
size=fontsize,
arrowprops=dict(arrowstyle=stylename,
patchB=p,
shrinkA=5,
shrinkB=5,
fc="w", ec="k",
connectionstyle="arc3,rad=-0.05",
),
bbox=dict(boxstyle="square", fc="w"))
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
ax1 = fig.add_subplot(121, frameon=False, xticks=[], yticks=[])
make_boxstyles(ax1)
ax2 = fig.add_subplot(122, frameon=False, xticks=[], yticks=[])
make_arrowstyles(ax2)
plt.show()
#############################################################################
#
# ------------
#
# References
# """"""""""
#
# The use of the following functions, methods, classes and modules is shown
# in this example:
import matplotlib
matplotlib.patches
matplotlib.patches.BoxStyle
matplotlib.patches.BoxStyle.get_styles
matplotlib.patches.ArrowStyle
matplotlib.patches.ArrowStyle.get_styles
matplotlib.axes.Axes.text
matplotlib.axes.Axes.annotate
|
