我不确定是否polar plot
可以这样调整。但这里有一个变通方法,基于此处给出的最后一个示例:浮动轴。
我在代码中包含了解释性注释,如果您复制/粘贴它,它应该按原样运行:
import mpl_toolkits.axisartist.floating_axes as floating_axes
from matplotlib.projections import PolarAxes
from mpl_toolkits.axisartist.grid_finder import FixedLocator, \
MaxNLocator, DictFormatter
import numpy as np
import matplotlib.pyplot as plt
# generate 100 random data points
# order the theta coordinates
# theta between 0 and 2*pi
theta = np.random.rand(100)*2.*np.pi
theta = np.sort(theta)
# "radius" between 0 and a max value of 40,000
# as roughly in your example
# normalize the r coordinates and offset by 1 (will be clear later)
MAX_R = 40000.
radius = np.random.rand(100)*MAX_R
radius = radius/np.max(radius) + 1.
# initialize figure:
fig = plt.figure()
# set up polar axis
tr = PolarAxes.PolarTransform()
# define angle ticks around the circumference:
angle_ticks = [(0, r"$0$"),
(.25*np.pi, r"$\frac{1}{4}\pi$"),
(.5*np.pi, r"$\frac{1}{2}\pi$"),
(.75*np.pi, r"$\frac{3}{4}\pi$"),
(1.*np.pi, r"$\pi$"),
(1.25*np.pi, r"$\frac{5}{4}\pi$"),
(1.5*np.pi, r"$\frac{3}{2}\pi$"),
(1.75*np.pi, r"$\frac{7}{4}\pi$")]
# set up ticks and spacing around the circle
grid_locator1 = FixedLocator([v for v, s in angle_ticks])
tick_formatter1 = DictFormatter(dict(angle_ticks))
# set up grid spacing along the 'radius'
radius_ticks = [(1., '0.0'),
(1.5, '%i' % (MAX_R/2.)),
(2.0, '%i' % (MAX_R))]
grid_locator2 = FixedLocator([v for v, s in radius_ticks])
tick_formatter2 = DictFormatter(dict(radius_ticks))
# set up axis:
# tr: the polar axis setup
# extremes: theta max, theta min, r max, r min
# the grid for the theta axis
# the grid for the r axis
# the tick formatting for the theta axis
# the tick formatting for the r axis
grid_helper = floating_axes.GridHelperCurveLinear(tr,
extremes=(2.*np.pi, 0, 2, 1),
grid_locator1=grid_locator1,
grid_locator2=grid_locator2,
tick_formatter1=tick_formatter1,
tick_formatter2=tick_formatter2)
ax1 = floating_axes.FloatingSubplot(fig, 111, grid_helper=grid_helper)
fig.add_subplot(ax1)
# create a parasite axes whose transData in RA, cz
aux_ax = ax1.get_aux_axes(tr)
aux_ax.patch = ax1.patch # for aux_ax to have a clip path as in ax
ax1.patch.zorder=0.9 # but this has a side effect that the patch is
# drawn twice, and possibly over some other
# artists. So, we decrease the zorder a bit to
# prevent this.
# plot your data:
aux_ax.plot(theta, radius)
plt.show()
这将生成以下图:
您必须调整轴标签以满足您的需求。
我缩放了数据,因为否则会发生与您的绘图相同的问题 - 内部的空圆圈将被缩放为一个点。您可以尝试使用极坐标图进行缩放,只需将自定义标签放在径向轴上即可达到类似的效果。