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I'm fed up with manually creating graphs in excel and consequently, I'm trying to automate the process using Python to massage the .csv data into a workable form and matplotlib to plot the result.

Using matplotlib and generating them is no problem but I can't work out is how to set the aspect ration / resolution of the output.

Specifically, I'm trying to generate scatter plots and stacked area graphs. Everything I've tried seems to result in one or more of the following:

  • Cramped graph areas (small plot area covered with the legend, axes etc.).
  • The wrong aspect ratio.
  • Large spaces on the sides of the chart area (I want a very wide / not very tall image).

If anyone has some working examples showing how to achieve this result I'd be very grateful!

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  • But it's graphs are so easy / perdy! ;-) Commented Nov 16, 2011 at 8:41

3 Answers 3

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You can control the aspect ratio with ax.set_aspect:

import matplotlib.pyplot as plt
import numpy as np

fig = plt.figure()
ax=fig.add_subplot(1,1,1)
ax.set_aspect(0.3)
x,y=np.random.random((2,100))
plt.scatter(x,y)

Another way to set the aspect ratio (already mentioned by jterrace) is to use the figsize parameter in plt.figure: e.g. fig = plt.figure(figsize=(3,1)). The two methods are slightly different however: A figure can contain many axes. figsize controls the aspect ratio for the entire figure, while set_aspect controls the aspect ratio for a particular axis.

Next, you can trim unused space from around the plot with bbox_inches='tight':

plt.savefig('/tmp/test.png', bbox_inches='tight')

enter image description here

If you want to get rid of the excess empty space due to matplotlib's automated choice of x-range and y-range, you can manually set them with ax.set_xlim and ax.set_ylim:

ax.set_xlim(0, 1)
ax.set_ylim(0, 1)

enter image description here

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Aspect Ratio / Graph Size

The easiest way I've found to do this is to set the figsize parameter to the figure function when creating the figure. For example, this would set the figure to be 4 inches wide by 3 inches tall:

import matplotlib.pyplot as plt
fig = plt.figure(figsize=(4,3))

Adjusting Spacing

For this, there is a function called subplots_adjust that allows you to change the bounding region of the graph itself, leaving more room for the title, axes, and labels. Here's an example from one of my graphs:

plt.gcf().subplots_adjust(bottom=0.15, left=0.13, right=0.95, top=0.96)
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For resolution, you can use the dpi (dots per inch) argument when creating a figure, or in the savefig() function. For high quality prints of graphics dpi=600 or more is recommended.

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The problem with upping the DPI is that it scales all of the line thicknesses & fonts with that dimension :-/

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