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I'm trying to create a scatter plot with x and y errors that have different marker and errorbar colors in four sections (e.g. red for x=0 to x=2, blue for x=2 to c=5, etc.). I have used a colormap with bounds for the markers, but I haven't been able to do something similar for the errorbars. I've tried to set the markers, errorbars, and caps as the same color in the scatter colormap using this answer to a similar question, but I wasn't able to get it to work for my code (comes up with an error about lengths of data not matching or unable to convert to tuple). I think I haven't been able to correctly modify it for the colormap I use for the markers, or this isn't the best way to go about getting the right result.

This is an example with some made up data:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors

bounds = [0,1.5,3,4.5,5]
colors = ["r", "b", "g", "y"]
cmap = matplotlib.colors.ListedColormap(colors)
norm = matplotlib.colors.BoundaryNorm(bounds, len(colors))

x = np.array([0.0, 0.0, 1.0, 2.0, 2.0, 3.0,  4.0,  4.0, 5.0, 5.0])
y = np.array([0.0, 0.1, 0.8, 0.9, 0.7, 0.1, -0.8, -0.5, -1.0, -0.7])
x_err = np.array([0.05, 0.06, 0.04, 0.045, 0.04, 0.06, 0.05, 0.055, 0.02, 0.05])
y_err = np.array([0.04, 0.05, 0.03, 0.055, 0.145, 0.065, 0.045, 0.15, 0.015, 0.17])

plt.scatter(x, y, marker='D', c=x, cmap=cmap, norm=norm)
plt.errorbar(x, y, xerr=x_err, yerr=y_err, fmt='.', lw=2, capsize=3, alpha=0.7, zorder=0)

plt.show()

which gives

this.

How can I get the errorbars to have the same colormap as the one used in the scatter plot?

murphy
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1 Answers1

1

This is certainly not the fastest method but it works: get the colors for each x-value using to_rgba and then plot the error bars pointwise (probably slow for large data arrays):

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors
import matplotlib.cm

bounds = [0,1.5,3,4.5,5]
colors = ["r", "b", "g", "y"]
cmap = matplotlib.colors.ListedColormap(colors)
norm = matplotlib.colors.BoundaryNorm(bounds, len(colors))

x = np.array([0.0, 0.0, 1.0, 2.0, 2.0, 3.0,  4.0,  4.0, 5.0, 5.0])
y = np.array([0.0, 0.1, 0.8, 0.9, 0.7, 0.1, -0.8, -0.5, -1.0, -0.7])
x_err = np.array([0.05, 0.06, 0.04, 0.045, 0.04, 0.06, 0.05, 0.055, 0.02, 0.05])
y_err = np.array([0.04, 0.05, 0.03, 0.055, 0.145, 0.065, 0.045, 0.15, 0.015, 0.17])

plt.scatter(x, y, marker='D', c=x, cmap=cmap, norm=norm)

colors = matplotlib.cm.ScalarMappable(norm,cmap).to_rgba(x)
for i,_ in enumerate(x):
  plt.errorbar(x[i], y[i], xerr=x_err[i], yerr=y_err[i], fmt='.', lw=2, capsize=3, alpha=0.7, zorder=0, ecolor=colors[i])  

plt.show()

enter image description here

Stef
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