如何创建ax。legend（）方法，用于不需要用户传递图例手柄的轮廓曲线图？

Question

我希望能打电话

ax.legend()

在包含contourf绘图的轴上，自动获取图例（参见下面的绘图示例）。

我知道如何使用代理为contourf图创建图例条目，请参阅下面的代码，这在本Q中已经讨论过

绘图生成（比本例中更复杂的绘图）发生在一个包中，用户可以访问图和轴，并且根据绘图的不同，可能更喜欢某些轴而不是其他轴来绘制图例。如果调用ax就好了。legend（）可以很简单，不需要使用代理和显式传递句柄。这会自动用于普通图、散点图、历史图等，但tourtf不接受label作为kwarg，并且没有自己的句柄，因此我需要创建一个代理（在这种情况下为矩形面片）。

但是我怎么能附加/属性/...代理旁边的标签到contourf情节或轴，这样ax.legend（）可以像其他类型一样自动访问它们的阴谋？

import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.colors import LinearSegmentedColormap


########################
# not accessed by User #
########################

def basic_cmap(color):
    return LinearSegmentedColormap.from_list(color, ['#ffffff', color])
cmap1 = basic_cmap('C0')
cmap2 = basic_cmap('C1')

x = np.linspace(0, 10, 50)
mvn1 = stats.multivariate_normal(mean=[4, 4])
mvn2 = stats.multivariate_normal(mean=[6, 7])
X, Y = np.meshgrid(x, x)
Z1 = [[mvn1.pdf([x1, x2]) for x1 in x] for x2 in x]
Z2 = [[mvn2.pdf([x1, x2]) for x1 in x] for x2 in x]
Z1 = Z1 / np.max(Z1)
Z2 = Z2 / np.max(Z2)

fig, axes = plt.subplots(2, 2, sharex='col', sharey='row')
for i, row in enumerate(axes):
    for j, ax in enumerate(row):
        cont1 = ax.contourf(X, Y, Z1, [0.05, 0.33, 1], cmap=cmap1, alpha=0.7)
        cont2 = ax.contourf(X, Y, Z2, [0.05, 0.33, 1], cmap=cmap2, alpha=0.7)


###################################
# User has access to fig and axes #
###################################

proxy1 = plt.Rectangle((0, 0), 1, 1, fc=cmap1(0.999), ec=cmap1(0.33), alpha=0.7, linewidth=3)
proxy2 = plt.Rectangle((0, 0), 1, 1, fc=cmap2(0.999), ec=cmap2(0.33), alpha=0.7, linewidth=3)

# would like this without passing of handles and labels
axes[0][-1].legend(handles=[proxy1, proxy2], labels=['foo', 'bar'])  


plt.savefig("contour_legend.png")
plt.show()

Answer 1

好吧，我做了更多的斑点，找到了一个解决方案，毕竟这非常简单，但我必须深入研究matplotlib。图例以获得正确的想法。在\u get\u legend\u handles中，它显示了如何收集句柄：

    for ax in axs:
        handles_original += (ax.lines + ax.patches +
                             ax.collections + ax.containers)

所以我所缺少的就是将标签传递给代理，并将代理传递给ax。修补程序

        # pass labels to proxies and place proxies in loop
        proxy1 = plt.Rectangle((0, 0), 1, 1, fc=cmap1(0.999), ec=cmap1(0.33), 
                               alpha=0.7, linewidth=3, label='foo')
        proxy2 = plt.Rectangle((0, 0), 1, 1, fc=cmap2(0.999), ec=cmap2(0.33), 
                               alpha=0.7, linewidth=3, label='bar')

        # pass proxies to ax.patches
        ax.patches += [proxy1, proxy2]


###################################
# User has access to fig and axes #
###################################

# no passing of handles and labels anymore
axes[0][-1].legend()

import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.colors import LinearSegmentedColormap


########################
# not accessed by User #
########################

def basic_cmap(color):
    return LinearSegmentedColormap.from_list(color, ['#ffffff', color])
cmap1 = basic_cmap('C0')
cmap2 = basic_cmap('C1')

x = np.linspace(0, 10, 50)
mvn1 = stats.multivariate_normal(mean=[4, 4])
mvn2 = stats.multivariate_normal(mean=[6, 7])
X, Y = np.meshgrid(x, x)
Z1 = [[mvn1.pdf([x1, x2]) for x1 in x] for x2 in x]
Z2 = [[mvn2.pdf([x1, x2]) for x1 in x] for x2 in x]
Z1 = Z1 / np.max(Z1)
Z2 = Z2 / np.max(Z2)

fig, axes = plt.subplots(2, 2, sharex='col', sharey='row')
for i, row in enumerate(axes):
    for j, ax in enumerate(row):
        cont1 = ax.contourf(X, Y, Z1, [0.05, 0.33, 1], cmap=cmap1, alpha=0.7)
        cont2 = ax.contourf(X, Y, Z2, [0.05, 0.33, 1], cmap=cmap2, alpha=0.7)

        # pass labels to proxies and place proxies in loop
        proxy1 = plt.Rectangle((0, 0), 1, 1, fc=cmap1(0.999), ec=cmap1(0.33), 
                               alpha=0.7, linewidth=3, label='foo')
        proxy2 = plt.Rectangle((0, 0), 1, 1, fc=cmap2(0.999), ec=cmap2(0.33), 
                               alpha=0.7, linewidth=3, label='bar')

        # pass proxies to ax.patches
        ax.patches += [proxy1, proxy2]


###################################
# User has access to fig and axes #
###################################

# no passing of handles and labels anymore
axes[0][-1].legend()  


plt.savefig("contour_legend_solved.png")
plt.show()

这将产生与问题中所示相同的图像。

对不起，毕竟我自己能想出一个解决方案，但也许这对将来的其他人会有帮助。