Question

Today I was doing a report for a course and I needed to include a figure of a contour plot of some field. I did this with matplotlib (ignore the chaotic header):

import numpy as np
import matplotlib
from matplotlib import rc
rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
## for Palatino and other serif fonts use:
#rc('font',**{'family':'serif','serif':['Palatino']})
rc('text', usetex=True)
from matplotlib.mlab import griddata
import matplotlib.pyplot as plt
import numpy.ma as ma
from numpy.random import uniform
from matplotlib.colors import LogNorm
fig = plt.figure()
data = np.genfromtxt('Isocurvas.txt')
matplotlib.rcParams['xtick.direction'] = 'out'
matplotlib.rcParams['ytick.direction'] = 'out'
rc('text', usetex=True)
rc('font', family='serif')
x = data[:,0]
y = data[:,1]
z = data[:,2]
# define grid.
xi = np.linspace(0.02,1, 100)
yi = np.linspace(0.02,1.3, 100)
# grid the data.
zi = griddata(x,y,z,xi,yi)
# contour the gridded data.
CS = plt.contour(xi,yi,zi,25,linewidths=0,colors='k')
CS = plt.contourf(xi,yi,zi,25,cmap=plt.cm.jet)
plt.colorbar() # draw colorbar
# plot data points.
plt.scatter(x,y,marker='o',c='b',s=0)
plt.xlim(0.01,1)
plt.ylim(0.01,1.3)
plt.ylabel(r'$t$')
plt.xlabel(r'$x$')
plt.title(r' Contour de $\rho(x,t)$')
plt.savefig("Isocurvas.eps", format="eps")
plt.show()

where “Isocurvas.txt” is a 3 column file, which I really don’t want to touch (eliminate data, or something like that, wouldn’t work for me). My problem was that the figure size was 1.8 Mb, which is too much for me. The figure itself was bigger than the whole rest of the report, and when I opened the pdf it wasn’t very smooth .

So , my question is :

Are there any ways of reducing this size without a sacrifice on the quality of the figure?. I’m looking for any solution, not necessarily python related.

This is the .png figure, with a slight variation on parameters. using .png you can see the pixels, which i don’t like very much, so it is preferable pdf or eps.

Thank you.

Answer 1

The scatter plot is what’s causing your large size. Using the EPS backend, I used your data to create the figures. Here’s the filesizes that I got:

• Straight from your example: 1.5Mb
• Without the scatter plot: 249Kb
• With a raster scatter plot: 249Kb

In your particular example it’s unclear why you want the scatter (not visible). But for future problems, you can use the rasterized=True keyword on the call to plt.scatter to activate a raster mode. In your example you have 12625 points in the scatter plot, and in vector mode that’s going to take a bit of space.

Another trick that I use to trim down vector images from matplotlib is the following:

1. Save figure as EPS
2. Run epstopdf (available with a TeX distribution) on the resulting file

This will generally give you a smaller pdf than matplotlib’s default, and the quality is unchanged. For your example, using the EPS file without the scatter, it produced a pdf with 73 Kb, which seems quite reasonable. If you really want a vector scatter command, running epstopdf on the original 1.5 Mb EPS file produced a pdf with 198 Kb in my system.