Python 散点图中的单个 alpha 值
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/24767355/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Individual alpha values in scatter plot
提问by pceccon
I'm wondering if it is possible to have individual alpha values for each point to be plotted using the scatterfunction of Matplotlib. I need to plot a set of points, each one with its alpha value.
我想知道是否可以使用scatterMatplotlib的函数为要绘制的每个点绘制单独的 alpha 值。我需要绘制一组点，每个点都有它的 alpha 值。
For example, I have this code to plot some points
例如，我有这个代码来绘制一些点
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_yand alpha_pointhave n values. However, I can't assign an array to the alphaparameter 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.
所有 my points_x,points_y并且alpha_point有 n 个值。然而，我不能分配一个阵列到alpha在参数scatter()。如何为每个点设置不同的 alpha 值？我可以使用每个特定的 alpha 值逐点循环和绘制，但这似乎不是一个好方法。
采纳答案by MaxNoe
tcaswell's suggestion is correct, you can do it like this:
tcaswell 的建议是正确的，你可以这样做：
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()
回答by Markus Dutschke
You can use the color argument and a colormap with alpha.
cmaplinearly increases the alpha value from 0 to 1.
您可以使用颜色参数和带有 alpha 的颜色图。
cmap将 alpha 值从 0 线性增加到 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()
