python - 如何将标签对齐到极坐标条形图的内边缘

Question

我无法制作我想要的可视化效果。我还不能放图片，所以链接在下面。我几乎得到了我想要的。问题是标签放置不正确。

倒置极杆演示

我想让标签按原样旋转，但要让标签的右边缘刚好对齐到圆圈的外边缘内。

编辑澄清:
我在这个例子中使用的标签都是“测试”。对于实际数据，这些标签的长度会有所不同。我想移动标签的末端，以便它们的最后一个字母始终位于圆圈的外边缘旁边。所以在这种情况下，所有的“g”都会靠近外边缘。

import matplotlib.pyplot as mpl
import numpy as np
import random

bgcolor = '#222222'
barcolor = '#6699cc'
bottom = 15

N = 32
Values = np.random.random(N)*10
MetricLabels = ['testing' for _ in range(1, N+1)]

# Select the radii, thetas, and widths.
Radii = -5*np.ones(N)-Values
Theta = np.linspace(0.0, 2 * np.pi, N, endpoint=False)
width = 2*np.pi/N

# Make a list of shifted thetas to place the labels at.
ThetaShifted = np.copy(Theta)
for i in range(N-1):
    ThetaShifted[i] = (Theta[i] + Theta[i+1])/2.0
ThetaShifted[-1] = (Theta[-1] + 2.0*np.pi)/2.0

# Make the figure
fig = mpl.figure()
ax = fig.add_subplot(111, projection='polar')
bars = ax.bar(Theta, Radii, width=width, bottom=bottom)

# Set the outer ring to be invisible.
ax.spines["polar"].set_visible(False)

# Set the grid line locations but set the labels to be invisible.
ax.grid(False)
ax.set_thetagrids([], visible=False)
ax.set_rgrids([3], visible=False)

# Apply colors to bars based on the settings above.
for v, bar in zip(Values, bars):
        bar.set_facecolor(barcolor)
        bar.set_edgecolor(bar.get_facecolor())

# Show the metric and value labels
for counter in range(N):
    ax.text(ThetaShifted[counter], bottom-3, MetricLabels[counter], 
            horizontalalignment='center', verticalalignment='baseline', 
            rotation=(counter+.5)*360/N, color=bgcolor)
    ax.text(ThetaShifted[counter], bottom+0.75, np.round(Values[counter],2), 
            horizontalalignment='center', verticalalignment='center', 
            color=bars[counter].get_facecolor())

# Set the background color to be a dark grey,
ax.set_axis_bgcolor(bgcolor)
fig.set_facecolor(bgcolor)

# Show the figure.
mpl.show()

Answer 1

我实际上解决了我的问题。请参见下面的图像和代码。解决它的主要方法是使用等宽字体系列并使用 rjust 创建标签字符串，使其从一开始就固定长度并右对齐。之后，只需为每个标签选择正确的径向位置，当它们的字符数都相同时，这应该会容易得多。

import matplotlib.pyplot as mpl
import numpy as np
import random

bgcolor = '#222222'
barcolor = '#6699cc'
bottom = 15

N = 32
Values = np.random.random(N)*10
MetricLabels = [('A'*(4+int(8*random.random()))).rjust(10) for _ in range(1, N+1)]

# Select the radii, thetas, and widths.
Radii = -5*np.ones(N)-Values
Theta = np.linspace(0.0, 2 * np.pi, N, endpoint=False)
width = 2*np.pi/N

# Make a list of shifted thetas to place the labels at.
ThetaShifted = np.copy(Theta)
for i in range(N-1):
    ThetaShifted[i] = (Theta[i] + Theta[i+1])/2.0
ThetaShifted[-1] = (Theta[-1] + 2.0*np.pi)/2.0

# Make the figure
fig = mpl.figure()
ax = fig.add_subplot(111, projection='polar')
bars = ax.bar(Theta, Radii, width=width, bottom=bottom)

# Set the outer ring to be invisible.
ax.spines["polar"].set_visible(False)

# Set the grid line locations but set the labels to be invisible.
ax.grid(False)
ax.set_thetagrids([], visible=False)
ax.set_rgrids([3], visible=False)

# Apply colors to bars based on the settings above.
for v, bar in zip(Values, bars):
    bar.set_facecolor(barcolor)
    bar.set_edgecolor(bar.get_facecolor())

# Show the metric and value labels
for counter in range(N):
    ax.text(ThetaShifted[counter], bottom-.075*(10+len(MetricLabels[counter])), MetricLabels[counter]+' '*5, 
            horizontalalignment='center', verticalalignment='center', 
            rotation=(counter+.5)*360/N, color=bgcolor,
            family='monospace')
    ax.text(ThetaShifted[counter], bottom+1, np.round(Values[counter],2), 
            horizontalalignment='center', verticalalignment='center', 
            rotation=(counter+.5)*360/N, color=bars[counter].get_facecolor(),
            family='monospace')

# Set the background color to be a dark grey,
ax.set_axis_bgcolor(bgcolor)
fig.set_facecolor(bgcolor)

# Show the figure.
mpl.show()