[Matplotlib-users] odd behavior with 'nearest' interpolation

[Warren Weckesser]

On 11/19/15, Smit, Christine E. (GSFC-610.2)[TELOPHASE CORP]
<christine.e.smit at nasa.gov> wrote:
> Thanks! I have. https://github.com/matplotlib/matplotlib/issues/5520
>


FYI:  If you want to write a numpy array directly to a PNG file, you
can use numpngw:

* github: https://github.com/WarrenWeckesser/numpngw
* pypi: https://pypi.python.org/pypi/numpngw/


Warren

(Christine, sorry for the double email.  I forgot to "reply all".)

> From: Jens Nielsen <jenshnielsen at gmail.com<mailto:jenshnielsen at gmail.com>>
> Date: Thursday, November 19, 2015 at 9:34 AM
> To: csmit <christine.e.smit at nasa.gov<mailto:christine.e.smit at nasa.gov>>,
> Nathan Goldbaum <nathan12343 at gmail.com<mailto:nathan12343 at gmail.com>>
> Cc: "matplotlib-users at python.org<mailto:matplotlib-users at python.org>"
> <matplotlib-users at python.org<mailto:matplotlib-users at python.org>>
> Subject: Re: [Matplotlib-users] odd behavior with 'nearest' interpolation
>
> It seem like this is a genuine bug but I am not sure how to fix it. Can you
> submit a bug report at Github so we are sure that this is captured? At
> github you can attach pictures
>
> Best Jens
>
>
> On Thu, 19 Nov 2015 at 14:25 Smit, Christine E. (GSFC-610.2)[TELOPHASE CORP]
> <christine.e.smit at nasa.gov<mailto:christine.e.smit at nasa.gov>> wrote:
> Yes. It works with 'none.' The problem is that sometimes we need to create
> images with low inflation factors. So, our data is nxm data points and we
> want a 2nx2m image or a 3nx3m image. We're currently getting around this bug
> by using 'none' to create an nxm image and then using imagemagick's convert
> to resize.
>
> From: Jens Nielsen <jenshnielsen at gmail.com<mailto:jenshnielsen at gmail.com>>
> Date: Wednesday, November 18, 2015 at 6:28 AM
> To: Nathan Goldbaum <nathan12343 at gmail.com<mailto:nathan12343 at gmail.com>>,
> csmit <christine.e.smit at nasa.gov<mailto:christine.e.smit at nasa.gov>>
> Cc: "matplotlib-users at python.org<mailto:matplotlib-users at python.org>"
> <matplotlib-users at python.org<mailto:matplotlib-users at python.org>>
> Subject: Re: [Matplotlib-users] odd behavior with 'nearest' interpolation
>
> I can confirm this. The issue is notable with a dpi lower than 10 or so and
> seems to get worse as it is lowered towards 1.
> Can you try plotting the image with interpolation='none' If I do that I get
> the correct behaviour. 'none' is probably the correct setting if you wish to
> match
> image matrix 1to1 to png coords anyway.
>
> @nathan The image in the notebook is plotted with a different dpi and works
> correctly.
>
> best Jens
>
> On Tue, 17 Nov 2015 at 22:38 Nathan Goldbaum
> <nathan12343 at gmail.com<mailto:nathan12343 at gmail.com>> wrote:
> This seems to be working ok for me:
> https://gist.github.com/faa6b4008a8e3db68f46
>
> On Tue, Nov 17, 2015 at 4:22 PM, Smit, Christine E. (GSFC-610.2)[TELOPHASE
> CORP] <christine.e.smit at nasa.gov<mailto:christine.e.smit at nasa.gov>> wrote:
> Hi! I am using matplotlib v 1.4.3 with Python 2.7.10 :: Anaconda 2.4.0
> (64-bit).
>
> What I am doing here is creating a 7x7 pixel image from a 7x7 matrix. I
> expect to see one pixel per data point, but that's not what I'm seeing.
> Instead of a diagonal make up of single pixels, I get an odd 2x2 pixel blob
> in the middle of the correct one pixel diagonal.
>
> ---------------------------------------------------------------------------
> import numpy as np
> import matplotlib.pylab as plt
>
>
> if __name__ == "__main__":
>     n = 7
>     data = np.identity(n, float)
>
>     # Create an nxn size figure with no frame
>     fig = plt.figure(figsize=(n, n), frameon=False)
>
>     # make the axes to the edge of the figure
>     ax = plt.Axes(fig, [0.0, 0.0, 1.0, 1.0])
>     # turn the axes off
>     ax.set_axis_off()
>     # add the axes to this figure
>     fig.add_axes(ax)
>     # show the data. Don't do any interpolation.
>     ax.imshow(data, interpolation='nearest', origin='lower',aspect='auto')
>     # Save the figure at 1 dot per inch, which should mean 1 data point per
>     # pixel
>     fig.savefig("image.png", dpi=1)
>
> ---------------------------------------------------------------------------
>
> Since I'm not sure that if I can attach the png image I get, here is a ppm
> version of the image I get (between the ------). Save this image.ppm minus
> the dashes and you should be able to open it in something like gimp.
>
> ---------------------------------------------------------------------------
> P3
> # CREATOR: GIMP PNM Filter Version 1.1
> 7 7
> 255
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 127
> 0
> 0
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 127
> 0
> 0
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 127
> 0
> 0
> 127
> 0
> 0
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 127
> 0
> 0
> 127
> 0
> 0
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 127
> 0
> 0
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 127
> 0
> 0
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 127
> 0
> 0
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> 0
> 0
> 127
> ---------------------------------------------------------------------------
>
> Thanks.
> Christine
>
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