Individual alpha values in scatter plot
I'm wondering if it is possible to have individual alpha values for each point to be plotted using the scatter
function of Matplotlib. I need to plot a set of points, each one with its alpha value.
For example, I have this code to plot some points
def plot_singularities(points_x, p, alpha_point, file_path):
plt.figure()
plt.scatter(points_x, points_y, alpha=alpha_point)
plt.savefig(file_path + '.png', dpi=100)
plt.close()
All my points_x
, points_y
and alpha_point
have n values. However, I can't assign an array to the alpha
parameter in scatter()
. How can I have a different alpha value for each point? I can loop and plot point by point with each specific alpha value, but this doesn't seem like a good approach.
Solution 1:
New solution with matplotlib >= 3.4
Since matplotlib 3.4, alpha supports an iterable of multiple values: https://matplotlib.org/stable/users/whats_new.html#transparency-alpha-can-be-set-as-an-array-in-collections
import numpy as np
import matplotlib.pylab as plt
x = np.arange(10)
y = np.arange(10)
alphas = np.linspace(0.1, 1, 10)
plt.scatter(x, y, alpha=alphas)
plt.show()
Old solution for matplotlib < 3.4
tcaswell's suggestion is correct, you can do it like this:
import numpy as np
import matplotlib.pylab as plt
x = np.arange(10)
y = np.arange(10)
alphas = np.linspace(0.1, 1, 10)
rgba_colors = np.zeros((10,4))
# for red the first column needs to be one
rgba_colors[:,0] = 1.0
# the fourth column needs to be your alphas
rgba_colors[:, 3] = alphas
plt.scatter(x, y, color=rgba_colors)
plt.show()
Solution 2:
You can use the color argument and a colormap with alpha.
cmap
linearly increases the alpha value from 0 to 1.
import numpy as np
import matplotlib.pylab as plt
from matplotlib import colors
c='C0'
xs = np.arange(10)
fig, ax = plt.subplots(1, 1)
cmap = colors.LinearSegmentedColormap.from_list(
'incr_alpha', [(0, (*colors.to_rgb(c),0)), (1, c)])
ax.scatter(xs, xs, c=xs, cmap=cmap, ec=None, s=10**2)
plt.show()