Matplotlib: scatter plot with color maps for edgecolor but no facecolor
I want to have a scatterplot with colormap for edgecolors, but no facecolors. When I use it facecolor='None'
, it doesn't work.
import numpy as np
import matplotlib.pyplot as plt
N = 50
x = np.random.rand(N)
y = np.random.rand(N)
colors = np.random.rand(N)
area = np.pi * (15 * np.random.rand(N))**2 # 0 to 15 point radii
plt.scatter(x, y, s=area,c=colors,facecolors='None',cmap="gist_rainbow", alpha=0.5)
plt.show()
Any solution?
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The argument c
will affect both facecolor and edgecolor, so arguments facecolor
and are edgecolor
ignored.
The solution would not be to use the argument c
along with colormap, but instead only use facecolors
and edgecolors
. In this case, it facecolors
can be set to "None"
, or a edgecolors
list of colors for use can be provided.
To create this list, the same color palette can be applied.
c = plt.cm.gist_rainbow(colors)
plt.scatter(x, y, s=area,facecolors="None", edgecolors=c, lw=1,alpha=0.5)
Complete example:
import numpy as np
import matplotlib.pyplot as plt
N = 50
x = np.random.rand(N)
y = np.random.rand(N)
colors = np.random.rand(N)
area = np.pi * (15 * np.random.rand(N))**2 # 0 to 15 point radii
c = plt.cm.gist_rainbow(colors)
plt.scatter(x, y, s=area,facecolors="None", edgecolors=c, lw=2,alpha=0.5)
plt.show()
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The problem is what color=
overrides the argument facecolors=
.
The solution I came across is to revert PathCollection
returned pyplot.scatter()
and then directly modify facecolor
. Note that you probably need to increase the line width to see the edges better.
import numpy as np
import matplotlib.pyplot as plt
N = 50
x = np.random.rand(N)
y = np.random.rand(N)
colors = np.random.rand(N)
area = np.pi * (15 * np.random.rand(N))**2 # 0 to 15 point radii
a = plt.scatter(x, y, s=area,c=colors,facecolor='none',lw=2,cmap="gist_rainbow", alpha=0.5)
a.set_facecolor('none')
plt.show()
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