Matplotlib 堆叠直方图标签

Question

这是我的照片。我需要为这些条形图制作标签，但是每个上层都包含下层 - 所以标签应该包含分组颜色，即蓝色 - 数据集 1，blue/orange - 数据集 2，blue/orange/绿色 - 数据集 3 和finally blue/orange/green/purple - dataset 4. 是否可行？谢谢。

enter image description here

binwidth = 1
n, bins, patches = ax1.hist(C, bins=range(81, 105, binwidth), 
                   density=False, histtype='barstacked' ,
                        edgecolor='gray', 
                        color=barvy_histogram,linewidth=0.3)

hatches = ['//','x','..','oo']
for patch_set, hatch in zip(patches, hatches):
    for patch in patch_set.patches:
        patch.set_hatch(hatch)
        patch.set_linewidth=0.1
        patch.set_color='gray'
mpl.rcParams['hatch.linewidth'] = 0.5

Answer 1

以下方法使用元组图例处理程序 (HandlerTuple) 来组合图例句柄。它产生水平布局，而垂直堆叠可能会更有趣。

代码从创建一些测试数据开始，假设 C 是一个 Nx4 整数数组。 bin 边缘设置为一半，以确保浮点精度不会将值放在错误的 bin 中。

import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.legend_handler import HandlerTuple
import numpy as np

# first, create some test data
C = (np.random.normal(0.001, 1, (100, 20)).cumsum(axis=0) * 1.2 + 90).astype(int).reshape(-1, 4)
c_min = C.min()
c_max = C.max()

mpl.rcParams['hatch.linewidth'] = 0.5
fig, ax1 = plt.subplots(figsize=(12, 5))
binwidth = 1
colors = plt.cm.Set2.colors[:C.shape[1]]
_, _, patches = ax1.hist(C, bins=np.arange(c_min - 0.5, c_max + binwidth, binwidth),
                         density=False, histtype='barstacked',
                         edgecolor='gray', color=colors, linewidth=0.3,
                         label=[f'N={p}' for p in range(25, 101, 25)])

hatches = ['//', 'x', '..', 'oo']
for patch_set, hatch in zip(patches, hatches):
     for patch in patch_set.patches:
          patch.set_hatch(hatch)
          patch.set_linewidth = 0.1

handles, labels = ax1.get_legend_handles_labels()
ax1.legend(handles=[tuple(handles[:i + 1]) for i in range(C.shape[1])], labels=labels,
           handlelength=6, handler_map={tuple: HandlerTuple(ndivide=None, pad=0)})
plt.show()

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