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| from matplotlib import pyplot as plt
import numpy as np
size = 0.25
base = 50
plt.rcParams['font.family'] = 'SimHei'
fig, ax = plt.subplots(figsize = (10, 10))
vals_middle = np.array([
[47.5,11.7,15.2,9.6],
[0,44.8,7.5,0],
[9.2, 68.5 , 0, 0],
[1.2, 7.2, 0, 0],
[80,0, 0, 0],
[1.7, 18.9, 0, 0]
])
vals_outer = np.array([
[47.5,11.7,15.2,9.6],
[0,36.6,8.2,7.5],
[9.2,38.1,30.4, 0],
[1.2, 5.8, 1.4, 0],
[80,0, 0, 0],
[1.7, 18.9, 0, 0]
])
vals_inner = vals_middle.sum(axis=1)
vals_first = vals_inner + base
'''
第二圈使用的数值, 因为最内圈每个类别都加上了base, 所以为了确保第二圈的数值和内圈相匹配, 第二圈的各类别要按照各自所占的比例分配各类的总数值.
'''
vals_second = np.zeros((6, 4))
for i in range(6):
s_a = vals_first[i]
s_b = vals_middle[i].sum()
if s_b == 0.0:
vals_second[i][1] = base
continue
for j in range(4):
vals_second[i][j] = (vals_middle[i][j] / s_b) * s_a
vals_third = np.zeros((6, 4))
for i in range(6):
s_a = vals_first[i]
s_b = vals_outer[i].sum()
if s_b == 0.0:
vals_third[i][1] = base
continue
for j in range(4):
vals_third[i][j] = (vals_outer[i][j] / s_b) * s_a
cmap_c = plt.get_cmap("tab20c")
cmap_b = plt.get_cmap("tab20b")
cmap_1 = cmap_c(np.arange(20))
cmap_2 = cmap_b(np.array([4, 5, 6, 7]))
inner_colors = np.vstack((cmap_1[::4], cmap_2[0]))
outer_colors = np.vstack((cmap_1, cmap_2))
labels_first=["餐厨废弃物\n{}万吨".format(vals_inner[0]),
"农业秸秆\n{}万吨".format(vals_inner[1]),
"水草\n151.2万吨",
"园林绿化\n废弃物\n{}万吨".format(vals_inner[3]),
"淤泥\n432.0万吨",
"畜禽粪便\n21.6万吨"
]
labels_seocnd=[
"未分类收集\n67.6万吨",
"生物干化\n3.7万吨",
"厌氧发酵\n10.2万吨",
"油水分离\n2.6万吨",
"",
"粉碎\n46.8万吨",
"好氧发酵\n3.5万吨",
"",
"未处理\n4.2万吨",
"藻水分离\n147.0万吨",
"",
"",
"未处理\n1.2万吨",
"粉碎\n7.2万吨",
"",
"",
"堆放\n432.0万吨",
"",
"",
"",
"未处理\n0.7万吨",
"好氧发酵\n19.9万吨",
"",
"",
]
labels_third=[
"未处理\n67.5万吨",
"肥料化、发电\n3.7万吨",
"沼气、沼渣发电\n10.2万吨",
"焚烧\n2.6万吨",
"",
"还田\n42.6万吨",
"燃料化\n4.2万吨",
"肥料化\n3.5万吨",
"未利用\n4.2万吨",
"燃料化\n80.2万吨",
"肥料化\n66.8万吨",
"",
"未利用\n1.2万吨",
"肥料化\n5.8万吨",
"燃料化\n1.4万吨",
"",
"未利用\n432.0万吨",
"",
"",
"",
"未利用\n0.7万吨",
"肥料化\n19.9万吨",
"",
"",
]
handles, labels = ax.pie(vals_first, radius=1-size-size,
labels=labels_first,
labeldistance=0.5, rotatelabels=True, textprops={'fontsize': 11},
colors=inner_colors, wedgeprops=dict(width=size, edgecolor='w'))
ax.pie(vals_second.flatten(), radius=1-size, colors=outer_colors,
labels=labels_seocnd,
labeldistance=0.7, rotatelabels=True, textprops={'fontsize': 11},
wedgeprops=dict(width=size, edgecolor='w'))
ax.pie(vals_third.flatten(), radius=1, colors=outer_colors,
labels=labels_third,
labeldistance=0.8, rotatelabels=True, textprops={'fontsize': 11},
wedgeprops=dict(width=size, edgecolor='w'))
plt.title('某市有机废弃物产生、处理、利用情况', fontsize=25)
plt.legend(handles=handles, labels=[
"餐厨废弃物",
"农业秸秆",
"水草",
"园林绿化废弃物",
"淤泥",
"畜禽粪便"],
loc = 1
)
plt.show()
|
