如何使两个标记使用matplotlib在图例中共享相同的标签？
我想要的是这样的： 
我得到的是这样的： 
那么如何将标记合并为一个标签呢？ 对于线条来说，对于线条，当然，你可以通过在使用相同线型时不将标签分配给第二行来实现，但对于标记，由于它们具有不同的形状，所以不能。
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差异？ 我会这样做：
但是，如果您真的想按照自己的方式进行操作，则可以使用本指南中显示的自定义图例。 您需要像创建自己的类一样创建自己的类，以定义legend_artist方法，然后根据需要添加正方形和圆。 以下是生成的图表和用于生成它的代码：
#!/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()
这是一个新的解决方案，它将绘制任何具有相同标签的标记集合。 我还没有想出如何使它与线图上的标记一起工作，但是如果需要的话，您可以在线图顶部绘制散点图。
from matplotlib import pyplot as plt
import matplotlib.collections as mcol
import matplotlib.transforms as mtransforms
import numpy as np
from matplotlib.legend_handler import HandlerPathCollection
from matplotlib import cm
class HandlerMultiPathCollection(HandlerPathCollection):
"""
Handler for PathCollections, which are used by scatter
"""
def create_collection(self, orig_handle, sizes, offsets, transOffset):
p = type(orig_handle)(orig_handle.get_paths(), sizes=sizes,
offsets=offsets,
transOffset=transOffset,
)
return p
fig, ax = plt.subplots()
#make some data to plot
x = np.arange(0, 100, 10)
models = [.05 * x, 8 * np.exp(- .1 * x), np.log(x + 1), .01 * x]
tests = [model + np.random.rand(len(model)) - .5 for model in models]
#make colors and markers
colors = cm.brg(np.linspace(0, 1, len(models)))
markers = ['o', 'D', '*', 's']
markersize = 50
plots = []
#plot points and lines
for i in xrange(len(models)):
line, = plt.plot(x, models[i], linestyle = 'dashed', color = 'black', label = 'Model')
plot = plt.scatter(x, tests[i], c = colors[i], s = markersize, marker = markers[i])
plots.append(plot)
#get attributes
paths = []
sizes = []
facecolors = []
edgecolors = []
for plot in plots:
paths.append(plot.get_paths()[0])
sizes.append(plot.get_sizes()[0])
edgecolors.append(plot.get_edgecolors()[0])
facecolors.append(plot.get_facecolors()[0])
#make proxy artist out of a collection of markers
PC = mcol.PathCollection(paths, sizes, transOffset = ax.transData, facecolors = colors, edgecolors = edgecolors)
PC.set_transform(mtransforms.IdentityTransform())
plt.legend([PC, line], ['Test', 'Model'], handler_map = {type(PC) : HandlerMultiPathCollection()}, scatterpoints = len(paths), scatteryoffsets = [.5], handlelength = len(paths))
plt.show()
如果您愿意使用所有圈子标记并仅通过颜色进行区分，那么我为您提供了一个解决方案。 您可以使用圆形集合来表示标记，然后为整个集合设置图例标签。
示例代码：
import matplotlib.pyplot as plt
import matplotlib.collections as collections
from matplotlib import cm
import numpy as np
#make some data to plot
x = np.arange(0, 100, 10)
models = [.05 * x, 8 * np.exp(- .1 * x), np.log(x + 1), .01 * x]
tests = [model + np.random.rand(len(model)) - .5 for model in models]
#make colors
colors = cm.brg(np.linspace(0, 1, len(models)))
markersize = 50
#plot points and lines
for i in xrange(len(models)):
line, = plt.plot(x, models[i], linestyle = 'dashed', color = 'black', label = 'Model')
plt.scatter(x, tests[i], c = colors[i], s = markersize)
#create collection of circles corresponding to markers
circles = collections.CircleCollection([markersize] * len(models), facecolor = colors)
#make the legend -- scatterpoints needs to be the same as the number
#of markers so that all the markers show up in the legend
plt.legend([circles, line], ['Test', 'Model'], scatterpoints = len(models), scatteryoffsets = [.5], handlelength = len(models))
plt.show()
我也发现这个链接非常有用（下面的代码），这是一个更简单的方法来处理这个问题。 它基本上使用图例句柄的列表来使第一个句柄的一个标记不可见，并用第二个句柄的标记对它进行重叠绘图。 通过这种方式，您可以使用一个标签将两个标记彼此相邻。
fig, ax = plt.subplots()
p1 = ax.scatter([0.1],[0.5],c='r',marker='s')
p2 = ax.scatter([0.3],[0.2],c='b',marker='o')
l = ax.legend([(p1,p2)],['points'],scatterpoints=2)
使用上面的代码， TupleHandler用于创建图例句柄，它只是TupleHandler两个句柄（如果你看起来很小心，那么在蓝色圆圈后面有红色方块）。你想要做的是制作第一个句柄的第二个标记，第二个句柄是不可见的，不幸的是， TupleHandler是一个相当新的添加，你需要一个特殊的函数来获得所有的句柄，否则你可以使用Legend.legendHandles属性（它只显示TupleHandler的第一个句柄）。
def get_handle_lists(l):
"""returns a list of lists of handles.
"""
tree = l._legend_box.get_children()[1]
for column in tree.get_children():
for row in column.get_children():
yield row.get_children()[0].get_children()
handles_list = list(get_handle_lists(l))
handles = handles_list[0] # handles is a list of two PathCollection.
# The first one is for red squares, and the second
# is for blue circles.
handles[0].set_facecolors(["r", "none"]) # for the fist
# PathCollection, make the
# second marker invisible by
# setting their facecolor and
# edgecolor to "none."
handles[0].set_edgecolors(["k", "none"])
handles[1].set_facecolors(["none", "b"])
handles[1].set_edgecolors(["none", "k"])
fig
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