The original question was raised in a mpl ticket:
https://github.com/matplotlib/matplotlib/issues/1513
My original answer there (copied & pasted):
The bbox_inches='tight' option to savefig does some analysis on the artists
visible on your plot and figures out the minimum bounding box needed to fit
all of the artists on the plot. In doing so, *it will reduce the size of
the outputted image, rather than keeping the size and "zooming" in*. A
really simple example to show this (not using basemap):
>>> import matplotlib.pyplot as plt
>>> fig = plt.figure(figsize=(3, 4))
>>> ax = plt.axes([0.4, 0.4, 0.2, 0.2])
>>> ax.plot(range(10))
>>> plt.savefig('figsize_no_tight.png')
>>> plt.savefig('figsize_tight.png', bbox_inches='tight')
$> file figsize_*
figsize_no_tight.png: PNG image data, 300 x 400, 8-bit/color RGBA,
non-interlaced
figsize_tight.png: PNG image data, 98 x 123, 8-bit/color RGBA, non-interlaced
*Matt has said that he doesn't think this addresses the issue *so anyone
else with any ideas, please chip in!
My suspicion is that what is being described is a combination of
bbox_inches="tight" and a snapping issue relating to the fixed aspect
(snapping here could be literally mpl snapping, or could simply be floating
point problems).
Hope someone else has some ideas about what is going on.
Cheers,
Phil
On 20 November 2012 00:25, <sav...@nsidc.org> wrote:
>
> Hi there,
>
> I've boiled down a problem and while the following my look useless, I need
> to understand why matplotlib is behaving like it is.
>
> Below is code showing my issue. I don't believe the issue is with the
> "bbox_inches='tight'", if you leave that off, my image is indeed, 800x1400,
> but the last row is a row of transparent pixels(on linux/not mac). It's
> difficult to see unless you use the imagemagik command display.
>
> The basic problem is that when my data has an aspect ratio very close to
> 1.75, the image gets changed to one with an aspect of 1.74875.
>
> Correct figure info 8x14@100dpi = 800x1400 => 1.75 Aspect Ratio.
> Incorrect figure info => 800x1399 => 1.74875
>
> Data that works aspect ratio: 1.7499999999999998
> Data that fails aspect ratio: 1.7499999999999996
> ---> Srsly?! -------------------------------^
>
> It would be great if someone could explain to me what's happening if this
> is indeed working as expected. If it's not, it would be great if someone
> could fix it.
>
> Thanks in advance.
> Matt
>
>
> import matplotlib.pyplot as plt
>
> def create_image():
> # I want an 800x1400 image (aspect = 1400/800 = 1.75.
> fig = plt.figure(1, figsize=(8, 14), frameon=False, dpi=100)
>
> # Use the whole figure and fill with a patch.
> fig.add_axes([0, 0, 1, 1])
> ax = plt.gca()
> limb = ax.axesPatch
> limb.set_facecolor('#6587ad')
>
> # Set some bounds with Aspects very close to the desired aspect ratios.
> x1 = 0.0
> y1 = 0.0
> x2 = 16.
>
> # If you un-comment out this line (and comment the one below). I get
> an image I expect
> # y2 = 27.999999999999994671 # produces 800 x 1400 image
> # aspect = 1.7499999999999998 works
>
> # Use this line and I get and image the wrong size (or with
> transparent pixels.)
> y2 = 27.999999999999994670 # produces (wrong?) 800 x 1399 image
> # aspect = 1.7499999999999996 Fails? wat?
>
> corners = ((x1, y1), (x2, y2))
> ax.update_datalim(corners)
> ax.set_xlim((x1, x2))
> ax.set_ylim((y1, y2))
>
> ax.set_aspect('equal', anchor='C')
> ax.set_xticks([])
> ax.set_yticks([])
>
> plt.savefig('rectangle.png', pad_inches=0.0, bbox_inches='tight')
>
> # If you use this below, the file size is correct, but there is a
> single
> # line transparent pixels along the bottom of the image
>
> # plt.savefig('rectangle.png', pad_inches=0.0)
>
>
> if __name__ == '__main__':
> create_image()
>
>
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