注意
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带有自动缩放的线、多边形和正多边形集合#
对于前两个子图，我们将使用螺旋线。它们的大小将以绘图单位设置，而不是数据单位。它们的位置将通过使用 LineCollection 和 PolyCollection 的 offsets 和 offset_transform 关键字参数以数据单位设置。
第三个子图将创建正多边形，与前两个子图具有相同的缩放和定位类型。
最后一个子图说明了使用 offsets=(xo, yo)，即单个元组而不是元组列表，来生成连续偏移的曲线，偏移以数据单位给出。此行为仅适用于 LineCollection。
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import collections, transforms
nverts = 50
npts = 100
# Make some spirals
r = np.arange(nverts)
theta = np.linspace(0, 2*np.pi, nverts)
xx = r * np.sin(theta)
yy = r * np.cos(theta)
spiral = np.column_stack([xx, yy])
# Fixing random state for reproducibility
rs = np.random.RandomState(19680801)
# Make some offsets
xyo = rs.randn(npts, 2)
# Make a list of colors cycling through the default series.
colors = plt.rcParams['axes.prop_cycle'].by_key()['color']
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
fig.subplots_adjust(top=0.92, left=0.07, right=0.97,
hspace=0.3, wspace=0.3)
col = collections.LineCollection(
[spiral], offsets=xyo, offset_transform=ax1.transData)
trans = fig.dpi_scale_trans + transforms.Affine2D().scale(1.0/72.0)
col.set_transform(trans) # the points to pixels transform
# Note: the first argument to the collection initializer
# must be a list of sequences of (x, y) tuples; we have only
# one sequence, but we still have to put it in a list.
ax1.add_collection(col, autolim=True)
# autolim=True enables autoscaling. For collections with
# offsets like this, it is neither efficient nor accurate,
# but it is good enough to generate a plot that you can use
# as a starting point. If you know beforehand the range of
# x and y that you want to show, it is better to set them
# explicitly, leave out the *autolim* keyword argument (or set it to False),
# and omit the 'ax1.autoscale_view()' call below.
# Make a transform for the line segments such that their size is
# given in points:
col.set_color(colors)
ax1.autoscale_view() # See comment above, after ax1.add_collection.
ax1.set_title('LineCollection using offsets')
# The same data as above, but fill the curves.
col = collections.PolyCollection(
[spiral], offsets=xyo, offset_transform=ax2.transData)
trans = transforms.Affine2D().scale(fig.dpi/72.0)
col.set_transform(trans) # the points to pixels transform
ax2.add_collection(col, autolim=True)
col.set_color(colors)
ax2.autoscale_view()
ax2.set_title('PolyCollection using offsets')
# 7-sided regular polygons
col = collections.RegularPolyCollection(
7, sizes=np.abs(xx) * 10.0, offsets=xyo, offset_transform=ax3.transData)
trans = transforms.Affine2D().scale(fig.dpi / 72.0)
col.set_transform(trans) # the points to pixels transform
ax3.add_collection(col, autolim=True)
col.set_color(colors)
ax3.autoscale_view()
ax3.set_title('RegularPolyCollection using offsets')
# Simulate a series of ocean current profiles, successively
# offset by 0.1 m/s so that they form what is sometimes called
# a "waterfall" plot or a "stagger" plot.
nverts = 60
ncurves = 20
offs = (0.1, 0.0)
yy = np.linspace(0, 2*np.pi, nverts)
ym = np.max(yy)
xx = (0.2 + (ym - yy) / ym) ** 2 * np.cos(yy - 0.4) * 0.5
segs = []
for i in range(ncurves):
xxx = xx + 0.02*rs.randn(nverts)
curve = np.column_stack([xxx, yy * 100])
segs.append(curve)
col = collections.LineCollection(segs, offsets=offs)
ax4.add_collection(col, autolim=True)
col.set_color(colors)
ax4.autoscale_view()
ax4.set_title('Successive data offsets')
ax4.set_xlabel('Zonal velocity component (m/s)')
ax4.set_ylabel('Depth (m)')
# Reverse the y-axis so depth increases downward
ax4.set_ylim(ax4.get_ylim()[::-1])
plt.show()
参考
此示例中展示了以下函数、方法、类和模块的使用