# _*_ coding: utf-8 _*_

"""

radar_plot.py by HumanGenerator

"""

import numpy as np

import matplotlib.pyplot as plt

import matplotlib.font_manager as fm

import matplotlib.lines as mlines

import matplotlib.patches as mpathces

import matplotlib

def radar_plot(scores, *args, **kw):

# 生成测试数据

num = len(scores)

labels = [scores[i][0] for i in range(num)]

data = [scores[i][1] for i in range(num)]

theta = np.linspace(0, 2*np.pi, num, endpoint=False)

theta += np.pi/2

theta[theta>2*np.pi] = theta[theta>2*np.pi] - 2*np.pi

# 数据预处理

data = np.concatenate((data, [data[0]]))

theta = np.concatenate((theta, [theta[0]]))

# 画图方式

plt.subplot(111, polar=True)

plt.title("雷达图", fontproperties=myfont1)

# 设置"theta grid"/"radar grid"

plt.thetagrids(theta*(180/np.pi), labels=labels, fontproperties=myfont2)

plt.rgrids(np.arange(20, 100, 20), labels=np.arange(20, 100, 20), angle=90)

plt.ylim(0, 100)

# 分别获取plot()，fill()所接受的**kw

kw_plot = []

kw_fill = []

kw1 = {}

kw2 = {}

xdir = dir(mlines.Line2D)

for i in range(len(xdir)):

if xdir[i][0:4] == 'set_':

kw_plot.append(xdir[i][4:])

xdir = dir(mpathces.Polygon)

for i in range(len(xdir)):

if xdir[i][0:4] == 'set_':

kw_fill.append(xdir[i][4:])

for key in kw.keys():

if key in kw_plot:

kw1[key] = kw[key]

elif key in kw_fill:

kw2[key] = kw[key]

elif key == 'fill_alpha':

kw2['alpha'] = kw[key]

else:

raise AttributeError('Unknown property %s' % key)

# 画雷达图,并填充雷达图内部区域

plt.plot(theta, data, *args, **kw1)

plt.fill(theta, data, **kw2)

# 图形显示

plt.show()

return

# radar_plot()

# 设置字体，解决中文乱码

myfont1 = fm.FontProperties(fname="/Library/Fonts/Songti.ttc", size=12)

myfont2 = fm.FontProperties(fname="/Library/Fonts/Songti.ttc", size=10)

matplotlib.rcParams["axes.unicode_minus"] = False

if __name__ == '__main__':

scores = {'Physical Education ': 78, 'Economic Law': 96,

'Military Theory': 66, 'Electronics': 90,

'Political Economics': 76, 'Analogue Circuit':93, 'College English': 72}

# 设置排序方式：升序或降序；按值或按键。

scores = sorted(scores.items(), key = lambda x: x[0], reverse=0)

radar_plot(scores, 'y--o', fill_alpha=0.5, facecolor='y')