当标记设置为像素时，如何在图例中更改标记大小/比例

Question

I am scatter ploting data points with a very small marker (see screengrab below). When I use the very small marker ',' the legend is very hard to read (example code taken from here ).
(Python 3, Jupyter lab)

How can I increase the size of the marker in the legend. The two versions shown on the above mentioned site do not work:

legend = ax.legend(frameon=True)  
for legend_handle in legend.legendHandles:  
    legend_handle._legmarker.set_markersize(9)

and

ax.legend(markerscale=6)

The two solutions do however work when the marker is set to '.'.
How can I show bigger makers in the legend?

Sample Code from intoli.com :

import numpy as np
import matplotlib.pyplot as plt
np.random.seed(12)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)

for i in range(5):
    mean = [np.random.random()*10, np.random.random()*10]
    covariance = [ [1 + np.random.random(), np.random.random() - 1],  [0, 1 + np.random.random()], ]
    covariance[1][0] = covariance[0][1]  # must be symmetric
    x, y = np.random.multivariate_normal(mean, covariance, 3000).T
    plt.plot(x, y, ',', label=f'Cluster {i + 1}')

ax.legend(markerscale=12)

fig.tight_layout()
plt.show()

Answer 1

You can get 1 pixel sized markers for a plot by setting the markersize to 1 pixel. This would look like

plt.plot(x, y, marker='s', markersize=72./fig.dpi, mec="None", ls="None")

What the above does is set the marker to a square, set the markersize to the ppi (points per inch) divided by dpi (dots per inch) == dots == pixels, and removes lines and edges.

Then the solution you tried using markerscale in the legend works nicely.

Complete example:

import numpy as np
import matplotlib.pyplot as plt
np.random.seed(12)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)

for i in range(5):
    mean = [np.random.random()*10, np.random.random()*10]
    covariance = [ [1 + np.random.random(), np.random.random() - 1],  [0, 1 + np.random.random()], ]
    covariance[1][0] = covariance[0][1]  # must be symmetric
    x, y = np.random.multivariate_normal(mean, covariance, 3000).T
    plt.plot(x, y, marker='s', markersize=72./fig.dpi, mec="None", ls="None", 
             label=f'Cluster {i + 1}')

ax.legend(markerscale=12)

fig.tight_layout()
plt.show()

Answer 2

According to this discussion , the markersize has no effect when using pixels ( , ) as marker. How about generating a custom legend instead? For example, by adapting the first example in this tutorial , one can get a pretty decent legend:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches

np.random.seed(12)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)

for i in range(5):
    mean = [np.random.random()*10, np.random.random()*10]
    covariance = [ [1 + np.random.random(), np.random.random() - 1],  [0, 1 + np.random.random()], ]
    covariance[1][0] = covariance[0][1]  # must be symmetric
    x, y = np.random.multivariate_normal(mean, covariance, 3000).T
    plt.plot(x, y, ',', label=f'Cluster {i + 1}')



##generating custom legend
handles, labels = ax.get_legend_handles_labels()
patches = []
for handle, label in zip(handles, labels):
    patches.append(mpatches.Patch(color=handle.get_color(), label=label))

legend = ax.legend(handles=patches)

fig.tight_layout()
plt.show()

The output would look like this: