Python – Colormap for errorbars in x-y scatter plot using matplotlib

color-mappingmatplotlibpythonscatter-plot

I have a time series of data for which I have the quantity, y, and its error, yerr. I would now like to create a plot that shows y against phase (i.e. time / period % 1) with vertical errorbars (yerr). For this, I typically use pyplot.errorbar(time, y, yerr=yerr, …)

However, I would like to use a colorbar/map to indicate the value of time in this same plot.

What I thus do is the following:

pylab.errorbar( phase, y, yerr=err, fmt=None, marker=None, mew=0 )
pylab.scatter( phase, y, c=time, cmap=cm )

Unfortunately, this will plot unicolored errorbars (default is blue). Since I have ~1600 points per plot, this makes the colormap of the scatter plot disappear behind the error bars. Here's a picture shows what I mean:

enter image description here

Is there a way that I can get the error bars to be plotted using the same colormap as the one used in the scatter plot? I don't want to call errorbar 1600 times…

Best Answer

In addition to changing the color, another suggestion is to change the zorder of the error bars versus the scatter plot. This focuses the user on the data and draws out the general shape of the errors (which I think is your intention).

from pylab import *

# Generate some random data that looks like yours
N = 1000
X = random(N)
Y = sin(X*5) + X*random(N)*.8
Z = random(N)
ERR = X*random(N)

# These are the new arguments that I used
scatter_kwargs = {"zorder":100}
error_kwargs = {"lw":.5, "zorder":0}

scatter(X,Y,c=Z,**scatter_kwargs)
errorbar(X,Y,yerr=ERR,fmt=None, marker=None, mew=0,**error_kwargs )
xlim(0,1)
show()

enter image description here

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for key in d:

will simply loop over the keys in the dictionary, rather than the keys and values. To loop over both key and value you can use the following:

For Python 3.x:

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For Python 2.x:

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To test for yourself, change the word key to poop.

In Python 3.x, iteritems() was replaced with simply items(), which returns a set-like view backed by the dict, like iteritems() but even better. This is also available in 2.7 as viewitems().

The operation items() will work for both 2 and 3, but in 2 it will return a list of the dictionary's (key, value) pairs, which will not reflect changes to the dict that happen after the items() call. If you want the 2.x behavior in 3.x, you can call list(d.items()).

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