Setting the size of the plotting canvas in Matplotlib

Question

I would like Matplotlib/Pyplot to generate plots with a consistent canvas size. That is, the figures can well have different sizes to accomodate the axis descriptions, but t

Answer 1

You can specify the following settings in Matplotlib rc:

import matplotlib
matplotlib.rcParams['figure.figsize'] = [10, 10] # for square canvas
matplotlib.rcParams['figure.subplot.left'] = 0
matplotlib.rcParams['figure.subplot.bottom'] = 0
matplotlib.rcParams['figure.subplot.right'] = 1
matplotlib.rcParams['figure.subplot.top'] = 1

Answer 2

This is one of my biggest frustrations with Matplotlib. I often work with raster data where for example i want to add a colormap, legend and some title. Any simple example from the matplotlib gallery doing so will result in a different resolution and therefore resampled data. Especially when doing image analysis you dont want any (unwanted) resampling.

Here is what i usually do, although i would love to know if there are simpler or better ways.

Lets start with loading a picture and outputting it just as it is with the same resolution:

import matplotlib.pyplot as plt
import urllib2

# load the image
img = plt.imread(urllib2.urlopen('http://upload.wikimedia.org/wikipedia/en/thumb/5/56/Matplotlib_logo.svg/500px-Matplotlib_logo.svg.png'))

# get the dimensions
ypixels, xpixels, bands = img.shape

# get the size in inches
dpi = 72.
xinch = xpixels / dpi
yinch = ypixels / dpi

# plot and save in the same size as the original
fig = plt.figure(figsize=(xinch,yinch))

ax = plt.axes([0., 0., 1., 1.], frameon=False, xticks=[],yticks=[])
ax.imshow(img, interpolation='none')

plt.savefig('D:\\mpl_logo.png', dpi=dpi, transparent=True)

Note that i manually defined the axes position so that spans the entire figure.

In a similar way as above you could add some margin around the image to allow for labels or colorbars etc.

This example adds a 20% margin above the image, which is then used for plotting a title:

fig = plt.figure(figsize=(xinch,yinch/.8))

ax = plt.axes([0., 0., 1., .8], frameon=False, xticks=[],yticks=[])
ax.imshow(img, interpolation='none')
ax.set_title('Matplotlib is fun!', size=16, weight='bold')

plt.savefig('D:\\mpl_logo_with_title.png', dpi=dpi)

So the figure y-size (height) is increased and the y-size of the axes is decreased equally. This gives a larger (overall) output image, but the axes area will still be the same size.

It might be nice the have a figure or axes property like .set_scale() to force a true 1-on-x output.