如何使用matplotlib使图例中的两个标记共享相同的标签? [英] How to make two markers share the same label in the legend using matplotlib?

问题描述

我想要的是这样的:

What I want is like this:

我得到的是:

那么如何将标记合并为一个标签? 当然，对于线，对于线，您也可以通过在使用相同线型时不将标签分配给第二条线来实现，但是对于标记，则不能，因为它们的形状不同.

So how to merge the markers into one label? also for the lines, for the lines, of course, u can realize it by not assigning label to the second line while using the same linetype, but for the markers, you can not, since they are of different shapes.

推荐答案

我认为最好使用完整的图例-否则，您的读者将如何知道两个模型或两个数据集之间的区别?我会这样:

I think it's best to use a full legend - otherwise, how will your readers know the difference between the two models, or the two datasets? I would do it this way:

但是，如果您确实想按照自己的方式做，则可以使用自定义图例，如

But, if you really want to do it your way, you can use a custom legend as shown in this guide. You'll need to create your own class, like they do, that defines the legend_artist method, which then adds squares and circles as appropriate. Here is the plot generated and the code used to generate it:

#!/usr/bin/env python
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import numpy as np


# ==================================
# Define the form of the function
# ==================================
def model(x, A=190, k=1):
    return A * np.exp(-k*x/50)

# ==================================
# How many data points are generated
# ==================================
num_samples = 15

# ==================================
# Create data for plots
# ==================================
x_model = np.linspace(0, 130, 200)

x_data1 = np.random.rand(num_samples) * 130
x_data1.sort()

x_data2 = np.random.rand(num_samples) * 130
x_data2.sort()

data1 = model(x_data1, k=1) * (1 + np.random.randn(num_samples) * 0.2)
data2 = model(x_data2, k=2) * (1 + np.random.randn(num_samples) * 0.15)

model1 = model(x_model, k=1)
model2 = model(x_model, k=2)

# ==================================
# Plot everything normally
# ==================================
fig = plt.figure()
ax = fig.add_subplot('111')
ax.plot(x_data1, data1, 'ok', markerfacecolor='none', label='Data (k=1)')
ax.plot(x_data2, data2, 'sk', markeredgecolor='0.5', markerfacecolor='0.5', label='Data (k=2)')
ax.plot(x_model, model1, '-k', label='Model (k=1)')
ax.plot(x_model, model2, '--k', label='Model (k=2)')

# ==================================
# Format plot
# ==================================
ax.set_xlabel('Distance from heated face($10^{-2}$ m)')
ax.set_ylabel('Temperature ($^\circ$C)')
ax.set_xlim((0, 130))
ax.set_title('Normal way to plot')
ax.legend()
fig.tight_layout()

plt.show()


# ==================================
# ==================================
# Do it again, but with custom
# legend
# ==================================
# ==================================
class AnyObject(object):
    pass


class data_handler(object):
    def legend_artist(self, legend, orig_handle, fontsize, handlebox):
        scale = fontsize / 22
        x0, y0 = handlebox.xdescent, handlebox.ydescent
        width, height = handlebox.width, handlebox.height
        patch_sq = mpatches.Rectangle([x0, y0 + height/2 * (1 - scale) ], height * scale, height * scale, facecolor='0.5',
                edgecolor='0.5', transform=handlebox.get_transform())
        patch_circ = mpatches.Circle([x0 + width - height/2, y0 + height/2], height/2 * scale, facecolor='none',
                edgecolor='black', transform=handlebox.get_transform())

        handlebox.add_artist(patch_sq)
        handlebox.add_artist(patch_circ)
        return patch_sq

# ==================================
# Plot everything
# ==================================
fig = plt.figure()
ax = fig.add_subplot('111')
d1 = ax.plot(x_data1, data1, 'ok', markerfacecolor='none', label='Data (k=2)')
d2 = ax.plot(x_data2, data2, 'sk', markeredgecolor='0.5', markerfacecolor='0.5', label='Data (k=1)')
m1 = ax.plot(x_model, model1, '-k', label='Model (k=1)')
m2 = ax.plot(x_model, model2, '-k', label='Model (k=2)')

# ax.legend([d1], handler_map={ax.plot: data_handler()})
ax.legend([AnyObject(), m1[0]], ['Data', 'Model'], handler_map={AnyObject: data_handler()})

# ==================================
# Format plot
# ==================================
ax.set_xlabel('Distance from heated face($10^{-2}$ m)')
ax.set_ylabel('Temperature ($^\circ$C)')
ax.set_xlim((0, 130))
ax.set_title('Custom legend')
fig.tight_layout()

plt.show()

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