matplotlib-users Mailing List for matplotlib

Hi all.

This is about a joint jupyter-notebook / matplotlib problem I've been 
thinking about.
So I'm writing a book using jupyter-notebook, and all my figures are 
generated using matplotlib.

In books, there is usually a figure caption with a running number and 
some description.
 From what I read, the best way to add captions is just using plt.text. 
However, the caption should probably be in the markup,
not in a rendered PNG. I'm not sure if changing the backend might help, 
but that probably doesn't make the notebook happy?

The other problem is that I want to have running numbers that I can 
refer to by a tag (as you would in latex).
That is more of a notebook problem, though.

Any feedback would be very welcome.

Cheers,
Andy

Hello,

I am looking for a way to hide tick marks (not the labels!) that coincide
with axis lines. I think this is a problem for me because of the relative
line thicknesses of my axis lines and tick marks, but I want to leave those
thicknesses unchanged (I like the look of the thickness settings I am using
now).

Here is a screenshot of what I'm talking about:

[image: Inline image 1]

I know this looks minor, but it is quite obvious on some plots and I'd
really like to get rid of it.

Thanks,
Julian Irwin

Le mercredi 27 janvier 2016, Matteo Niccoli a écrit :
> Can something like this (which by the way I can't get to work):
> http://stackoverflow.com/questions/3114925/pil-convert-rgb-image-to-a
> -specific-8-bit-palette
> 
> What I would like to do is this:
> 1) Import an RGB image, which would have its own colormap - say this
> one for example:
> https://upload.wikimedia.org/wikipedia/commons/b/b3/Jupiter_new_hubble_view_above_pole.png

> 2) convert it to intensity, display the intensity color-mapped to the
> same colours the original RGB had.

According to the PNG header, this image does not have a palette (i.e. a
list of colors). The data chunks define the image as an array of NxMx3
values (N rows, M cols, 3 channels=no alpha), each value being defined
using 8 bits. I may however badly understand what you call the "own
colormap"...

You still can convert it to a grayscale img representing the intensity
(NxM values), but you then lose some information and you cannot display
it back with the same colors as originally. Because some different RGB
tuple are converted into the same intensity level, you can then not
discriminate them using the intensity image only.

Maybe there is some trick to convert to a grayscale image where those
RGB values are converted to almost-equal-but-different intensity levels
that would enable the later reconstruction, but I am not aware of...

Fabrice

You might have better luck asking the scikit-image people, or the Pillow
people. ImageMagick might also have what you are looking for.

Cheers!
Ben Root


On Wed, Jan 27, 2016 at 11:23 PM, Matteo Niccoli <ma...@my...> wrote:

> Can something like this (which by the way I can't get to work):
>
> http://stackoverflow.com/questions/3114925/pil-convert-rgb-image-to-a-specific-8-bit-palette
>
> What I would like to do is this:
> 1) Import an RGB image, which would have its own colormap - say this one
> for example:
>
> https://upload.wikimedia.org/wikipedia/commons/b/b3/Jupiter_new_hubble_view_above_pole.png
>
> 2) convert it to intensity, display the intensity color-mapped to the same
> colours the original RGB had.
>
> Any tips, or even better code or pseudocode would be greatly appreciated.
>
> Thanks
> Matteo
>
>
>
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Can something like this (which by the way I can't get to work):
http://stackoverflow.com/questions/3114925/pil-convert-rgb-image-to-a-specific-8-bit-palette

What I would like to do is this:
1) Import an RGB image, which would have its own colormap - say this one
for example:
https://upload.wikimedia.org/wikipedia/commons/b/b3/Jupiter_new_hubble_view_above_pole.png

2) convert it to intensity, display the intensity color-mapped to the same
colours the original RGB had.

Any tips, or even better code or pseudocode would be greatly appreciated.

Thanks
Matteo