Individual alpha values in scatter plot

Question

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.

Answer 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() 

Answer 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()