CODEWITHSUNDEEP
pythonmatplotlib
Andrew Griffin
Andrew Griffin

Reputation: 23

Reducing file size of scatter plot

I am currently trying to reduce the file size of a scatter plot. My code looks like:

plt.scatter(a1,b1)
plt.savefig('test.ps')

where a1,b1 are arrays of size 400,000 or so, and it gives a file size of 7.8MB.

I have tried adding 

plt.rcParams['path.simplify'] = True

before this chunk of code, but the file is still 7.8MB. Is this an issue with how it saves as a ".ps" file or another issue?

Upvotes: 2

Views: 3685

Answers (2)

Bart
Bart

Reputation: 10248

You could consider using e.g. hexbin -- I particularly like this when you have a dense collection of points, since it better indicates where your data is concentrated. For example:

import numpy as np
import matplotlib.pylab as pl

x = np.random.normal(size=40000)
y = np.random.normal(size=40000)

pl.figure()

pl.subplot(121)
pl.scatter(x, y)
pl.xlim(-4,4)
pl.ylim(-4,4)

pl.subplot(122)
pl.hexbin(x, y, gridsize=40)
pl.xlim(-4,4)
pl.ylim(-4,4)

enter image description here

From the left figure, I would have concluded that the distribution of points between x,y = {-3,3} is roughly equal, which clearly is not the case.

(http://matplotlib.org/examples/pylab_examples/hexbin_demo.html)

Upvotes: 6

Angus Williams
Angus Williams

Reputation: 2334

One approach is to use plot instead of scatter (you can still produce scatter plots using plot by using the 'o' argument), and use the rasterized keyword argument, like so:

import numpy as np 
import matplotlib.pyplot as plt

a1,b1 = np.random.randn(400000,2).T #mock data of similar size to yours
plt.plot(a1,b1,'o',rasterized=True)
plt.savefig("test.ps")

This should significantly reduce the size of the output file. The text and line art will remain vector, only the points are rasterized, so it is a nice compromise.

Depending on what you're looking to achieve, however, it might be better to histogram your data and plot that instead (e.g. pyplot.hist2d or pyplot.hexbin).

Upvotes: 7

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