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Showing results of 26

1 2 > >> (Page 1 of 2)
From: Julian I. <jul...@gm...> - 2016年01月31日 19:53:30
Thanks for your suggestion Oscar. I tried editing the ticks like this, but
this method removes both the tick marks and the labels.
I think I have found a decent solution. Unfortunately my solution required
a very particular order of operations. It is much less convenient than the
functions provided in the API like tick_params(), which don't care if you
have run plt.draw() ahead of time...
1) Run all of the setup for the plot and also the plotting commands
(ax.plot(), ax.hist()...whatever)
2) Run `plt.draw()` because this updates the tick objects contained in
your axes.
3) Grab your Tick objects: `ticks = ax.[x/y]axis.[major/minor]Ticks`
4) For each tick you want to hide do:
 `tick.tick1On = False`
 `tick.tick2On = False`
The `1` and `2` refer to the bottom, top (left, right) for the x (y) axis
respectively.
5) Run plt.show(), fig.show() or fig.savefig or whatever else you are using.
Ahhhhh, no messy ticks in the corner!
Julian
On Fri, Jan 29, 2016 at 10:49 AM, Oscar Benjamin <osc...@gm...
> wrote:
> On 28 January 2016 at 19:49, Julian Irwin <jul...@gm...> wrote:
> >
> >
> > 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).
>
> Try this:
>
> from matplotlib import pyplot as plt
> fig = plt.figure()
> ax = fig.add_subplot(1, 1, 1)
> ax.plot([0, 1], [0, 1])
> print(ax.get_xticks())
> ax.set_xticks(ax.get_xticks()[1:-1]) # Remove first and last ticks
> print(ax.get_xticks())
>
> --
> Oscar
>
From: Benjamin R. <ben...@gm...> - 2016年01月31日 02:04:09
You've already done it. But we encourage you to take a crack at it. I would
suggest just first factoring it out into a new file
lib/matplotlib/hexbin.py and have the current function utilize it. When
that is done, we can look to getting it into numpy as well. We will need a
copy of it ourselves for compatibility with older releases of numpy.
Let us know if you have questions!
Ben Root
On Jan 30, 2016 8:45 PM, "Sebastian" <se...@gm...> wrote:
> Ahhhh thats too bad (that we can't recover the original ids.)
> What could one (as user) do to officially request it be fixed/factored out
> to numpy?
>
>
>
> On Fri, Jan 29, 2016 at 7:30 PM, Thomas Caswell <tca...@gm...>
> wrote:
>
>> Factor it out and give it to numpy!
>>
>> On Fri, Jan 29, 2016, 17:27 Benjamin Root <ben...@gm...> wrote:
>>
>>> Hmm, you are right, there is no way to get back the information that
>>> hexbin computed. The hexbin function is massive (in
>>> lib/matplotlib/axes/_axes.py) and is a bit tangled up with the
>>> artist-handling code, too. I think it would make sense to factor out the
>>> hexbinning component into its own hexbin.py that others might be able to
>>> use separately.
>>>
>>> Ben Root
>>>
>>>
>>> On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote:
>>>
>>>> Is there a simple way to hexbin using "pyplot.hexbin" and to return
>>>> the ids of the set of
>>>> points in each hexbin? That is to output an array of n elements
>>>> (one for each hexbin), and each element itself an array with the point
>>>> ids? The sum
>>>> of the number of inner elements would be equal the sum of all points
>>>> (x,y).
>>>>
>>>> Is hexbin missing this simple feature?
>>>>
>>>> Or perhaps specifying C=N.arange(len(x)) then some specific
>>>> "reduced_C_function"
>>>> to return those elements. But I don't know if there is a
>>>> "reduced_C_function" available,
>>>> or perhaps one could be added?
>>>>
>>>> many thanks in advance...
>>>>
>>>> link:
>>>> http://stackoverflow
>>>> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the-
>>>> hexbin-reduce-c-function/35088073#35088073
>>>>
>>>>
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>> Site24x7 APM Insight: Get Deep Visibility into Application Performance
>>>> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
>>>> Monitor end-to-end web transactions and take corrective actions now
>>>> Troubleshoot faster and improve end-user experience. Signup Now!
>>>> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
>>>> _______________________________________________
>>>> Matplotlib-users mailing list
>>>> Mat...@li...
>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>
>>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Site24x7 APM Insight: Get Deep Visibility into Application Performance
>>> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
>>> Monitor end-to-end web transactions and take corrective actions now
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>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>
>
From: Sebastian <se...@gm...> - 2016年01月31日 01:46:05
Ahhhh thats too bad (that we can't recover the original ids.)
What could one (as user) do to officially request it be fixed/factored out
to numpy?
On Fri, Jan 29, 2016 at 7:30 PM, Thomas Caswell <tca...@gm...> wrote:
> Factor it out and give it to numpy!
>
> On Fri, Jan 29, 2016, 17:27 Benjamin Root <ben...@gm...> wrote:
>
>> Hmm, you are right, there is no way to get back the information that
>> hexbin computed. The hexbin function is massive (in
>> lib/matplotlib/axes/_axes.py) and is a bit tangled up with the
>> artist-handling code, too. I think it would make sense to factor out the
>> hexbinning component into its own hexbin.py that others might be able to
>> use separately.
>>
>> Ben Root
>>
>>
>> On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote:
>>
>>> Is there a simple way to hexbin using "pyplot.hexbin" and to return the
>>> ids of the set of
>>> points in each hexbin? That is to output an array of n elements
>>> (one for each hexbin), and each element itself an array with the point
>>> ids? The sum
>>> of the number of inner elements would be equal the sum of all points
>>> (x,y).
>>>
>>> Is hexbin missing this simple feature?
>>>
>>> Or perhaps specifying C=N.arange(len(x)) then some specific
>>> "reduced_C_function"
>>> to return those elements. But I don't know if there is a
>>> "reduced_C_function" available,
>>> or perhaps one could be added?
>>>
>>> many thanks in advance...
>>>
>>> link:
>>> http://stackoverflow
>>> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the-
>>> hexbin-reduce-c-function/35088073#35088073
>>>
>>>
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Site24x7 APM Insight: Get Deep Visibility into Application Performance
>>> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
>>> Monitor end-to-end web transactions and take corrective actions now
>>> Troubleshoot faster and improve end-user experience. Signup Now!
>>> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>>
>>
>> ------------------------------------------------------------------------------
>> Site24x7 APM Insight: Get Deep Visibility into Application Performance
>> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
>> Monitor end-to-end web transactions and take corrective actions now
>> Troubleshoot faster and improve end-user experience. Signup Now!
>> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
From: Fernando P. <fpe...@gm...> - 2016年01月30日 01:20:19
On Fri, Jan 29, 2016 at 8:25 AM, Andreas Mueller <t3...@gm...> wrote:
> Thanks for your input Fernando.
> I thought about cross-posting to Jupyter, but I'm glad you also saw it
> here :)
> That would help, but not solve all problems.
> I guess the Figure could hold a tag for referencing, too. It would be nice
> to get a tag and caption from matplotlib.
> Maybe Benjamin's reply would help with that. But it sounds like the figure
> has a single string attached (which is more the tag).
> I guess I can do
> IPython.display.Figure(matplotlib_figure, caption="stuff", tag="tag")
> That would be acceptable, I think.
>
Yes, I'd forgotten about the label ("label" is the LaTeX name for what
you're calling "tag" here).
> But how do I reference that in a markup cell? [maybe I should move that
> question to the jupyter list, though]
>
Yup, this is the slightly trickier part. A sketch of the solution, we need
to:
- generate a local anchor element for the labeled output. That's the
easier part, it would be the job of the displayed output from this
hypothetical Figure() object.
It needs to wrap the output in `<a name=label>... </a>`.
- For markdown referencing, you simply do [link text](#label).
- The problem would be latex conversion: by default, the above is converted
to
\protect\hyperlink{label}{link text}
where as you want a \ref{label} call instead.
- You also want this to generate the
Internal cross-referencing is one of Markdown's main weaknesses for complex
more document-oriented workflows that aren't purely HTML oriented.
Markdown is really a thin wrapper around HTML, so it doesn't expose the
rich labeling/referencing semantics of rST or LaTeX.
I didn't say this was a done deal, and there might be some tricky edges to
it :)
Cheers
f
-- 
Fernando Perez (@fperez_org; http://fperez.org)
fperez.net-at-gmail: mailing lists only (I ignore this when swamped!)
fernando.perez-at-berkeley: contact me here for any direct mail
From: Thomas C. <tca...@gm...> - 2016年01月29日 22:31:06
Factor it out and give it to numpy!
On Fri, Jan 29, 2016, 17:27 Benjamin Root <ben...@gm...> wrote:
> Hmm, you are right, there is no way to get back the information that
> hexbin computed. The hexbin function is massive (in
> lib/matplotlib/axes/_axes.py) and is a bit tangled up with the
> artist-handling code, too. I think it would make sense to factor out the
> hexbinning component into its own hexbin.py that others might be able to
> use separately.
>
> Ben Root
>
>
> On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote:
>
>> Is there a simple way to hexbin using "pyplot.hexbin" and to return the
>> ids of the set of
>> points in each hexbin? That is to output an array of n elements
>> (one for each hexbin), and each element itself an array with the point
>> ids? The sum
>> of the number of inner elements would be equal the sum of all points
>> (x,y).
>>
>> Is hexbin missing this simple feature?
>>
>> Or perhaps specifying C=N.arange(len(x)) then some specific
>> "reduced_C_function"
>> to return those elements. But I don't know if there is a
>> "reduced_C_function" available,
>> or perhaps one could be added?
>>
>> many thanks in advance...
>>
>> link:
>> http://stackoverflow
>> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the-
>> hexbin-reduce-c-function/35088073#35088073
>>
>>
>>
>>
>> ------------------------------------------------------------------------------
>> Site24x7 APM Insight: Get Deep Visibility into Application Performance
>> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
>> Monitor end-to-end web transactions and take corrective actions now
>> Troubleshoot faster and improve end-user experience. Signup Now!
>> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
> Monitor end-to-end web transactions and take corrective actions now
> Troubleshoot faster and improve end-user experience. Signup Now!
> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
From: Benjamin R. <ben...@gm...> - 2016年01月29日 22:27:13
Hmm, you are right, there is no way to get back the information that hexbin
computed. The hexbin function is massive (in lib/matplotlib/axes/_axes.py)
and is a bit tangled up with the artist-handling code, too. I think it
would make sense to factor out the hexbinning component into its own
hexbin.py that others might be able to use separately.
Ben Root
On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote:
> Is there a simple way to hexbin using "pyplot.hexbin" and to return the
> ids of the set of
> points in each hexbin? That is to output an array of n elements
> (one for each hexbin), and each element itself an array with the point
> ids? The sum
> of the number of inner elements would be equal the sum of all points (x,y).
>
> Is hexbin missing this simple feature?
>
> Or perhaps specifying C=N.arange(len(x)) then some specific
> "reduced_C_function"
> to return those elements. But I don't know if there is a
> "reduced_C_function" available,
> or perhaps one could be added?
>
> many thanks in advance...
>
> link:
> http://stackoverflow
> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the-
> hexbin-reduce-c-function/35088073#35088073
>
>
>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
> Monitor end-to-end web transactions and take corrective actions now
> Troubleshoot faster and improve end-user experience. Signup Now!
> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
From: Sebastian <se...@gm...> - 2016年01月29日 22:16:02
Is there a simple way to hexbin using "pyplot.hexbin" and to return the ids
of the set of
points in each hexbin? That is to output an array of n elements
(one for each hexbin), and each element itself an array with the point ids?
The sum
of the number of inner elements would be equal the sum of all points (x,y).
Is hexbin missing this simple feature?
Or perhaps specifying C=N.arange(len(x)) then some specific
"reduced_C_function"
to return those elements. But I don't know if there is a
"reduced_C_function" available,
or perhaps one could be added?
many thanks in advance...
link:
http://stackoverflow
.com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the-
hexbin-reduce-c-function/35088073#35088073
From: Oscar B. <osc...@gm...> - 2016年01月29日 16:50:10
On 28 January 2016 at 19:49, Julian Irwin <jul...@gm...> wrote:
>
>
> 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).
Try this:
from matplotlib import pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot([0, 1], [0, 1])
print(ax.get_xticks())
ax.set_xticks(ax.get_xticks()[1:-1]) # Remove first and last ticks
print(ax.get_xticks())
--
Oscar
From: Andreas M. <t3...@gm...> - 2016年01月29日 16:25:50
Thanks for your input Fernando.
I thought about cross-posting to Jupyter, but I'm glad you also saw it 
here :)
That would help, but not solve all problems.
I guess the Figure could hold a tag for referencing, too. It would be 
nice to get a tag and caption from matplotlib.
Maybe Benjamin's reply would help with that. But it sounds like the 
figure has a single string attached (which is more the tag).
I guess I can do
IPython.display.Figure(matplotlib_figure, caption="stuff", tag="tag")
That would be acceptable, I think.
But how do I reference that in a markup cell? [maybe I should move that 
question to the jupyter list, though]
On 01/28/2016 10:17 PM, Fernando Perez wrote:
> On Thu, Jan 28, 2016 at 3:23 PM, Andreas Mueller <t3...@gm... 
> <mailto:t3...@gm...>> wrote:
>
> 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
>
>
> I've been wanting to do something about this problem for a while, but 
> haven't had the cycles to work on it... Here's my current idea, 
> perhaps I can goad you into implementing it :)
>
> I think that IPython.display should provide a Figure object, capable 
> of wrapping any input image (with nice code to automatically swallow a 
> matplotlib figure without asking the user to convert it to an image 
> first), and taking an optional caption.
>
> Figure() would then produce as output the displayed image but with a 
> bit of nice CSS to center it on the page, along with the caption.
>
> The trick is to send the entire data bundle correctly structured so 
> that, at the other end, nbconvert could recognize these figures as 
> such, and not only produce nice HTML, but more importantly, push them 
> into the LaTeX output with the correct call to \figure, including 
> \caption as well as size and placement specifiers.
>
> The signature of Figure() might be something like
>
> def Figure(fig, caption=None, width=None, height=None,
> latex_placement=None):
>
>
> I would try implementing this first as a standalone tool, and once 
> it's been tested enough in real-world usage with both HTML and LaTeX 
> output from nbconvert, it could be merged in. I suspect it's going to 
> take a few iterations to get it right.
>
> But it's not particularly hard, and someone working on a book would be 
> the perfect candidate to have enough test cases to be able to iterate 
> until happy ;)
>
> If you think you want to take a stab at this, don't hesitate to ping 
> us on the jupyter list. We can help with some of the more obscure 
> parts of getting this to work on nbconvert (and there may be things 
> I've overlooked in the sketch above).
>
> Cheers,
>
> f
>
> -- 
> Fernando Perez (@fperez_org; http://fperez.org)
> fperez.net-at-gmail: mailing lists only (I ignore this when swamped!)
> fernando.perez-at-berkeley: contact me here for any direct mail
From: Benjamin R. <ben...@gm...> - 2016年01月29日 04:03:21
In mpl, our figure objects get numbers assigned to them by default, but
they can also be strings. These labels are used in the figure window title
bar. Perhaps that existing data could be hijacked? Admittedly, most people
use the string name to give nice short names to their figures, so maybe
those names could be the "tag" name in latex? So, all we would need is some
way to supply the actual caption string.
Ben Root
On Thu, Jan 28, 2016 at 10:17 PM, Fernando Perez <fpe...@gm...>
wrote:
> On Thu, Jan 28, 2016 at 3:23 PM, Andreas Mueller <t3...@gm...> wrote:
>
>> 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
>>
>
> I've been wanting to do something about this problem for a while, but
> haven't had the cycles to work on it... Here's my current idea, perhaps I
> can goad you into implementing it :)
>
> I think that IPython.display should provide a Figure object, capable of
> wrapping any input image (with nice code to automatically swallow a
> matplotlib figure without asking the user to convert it to an image first),
> and taking an optional caption.
>
> Figure() would then produce as output the displayed image but with a bit
> of nice CSS to center it on the page, along with the caption.
>
> The trick is to send the entire data bundle correctly structured so that,
> at the other end, nbconvert could recognize these figures as such, and not
> only produce nice HTML, but more importantly, push them into the LaTeX
> output with the correct call to \figure, including \caption as well as size
> and placement specifiers.
>
> The signature of Figure() might be something like
>
> def Figure(fig, caption=None, width=None, height=None,
> latex_placement=None):
>
>
> I would try implementing this first as a standalone tool, and once it's
> been tested enough in real-world usage with both HTML and LaTeX output from
> nbconvert, it could be merged in. I suspect it's going to take a few
> iterations to get it right.
>
> But it's not particularly hard, and someone working on a book would be the
> perfect candidate to have enough test cases to be able to iterate until
> happy ;)
>
> If you think you want to take a stab at this, don't hesitate to ping us on
> the jupyter list. We can help with some of the more obscure parts of
> getting this to work on nbconvert (and there may be things I've overlooked
> in the sketch above).
>
> Cheers,
>
> f
>
> --
> Fernando Perez (@fperez_org; http://fperez.org)
> fperez.net-at-gmail: mailing lists only (I ignore this when swamped!)
> fernando.perez-at-berkeley: contact me here for any direct mail
>
>
> ------------------------------------------------------------------------------
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>
>
From: Fernando P. <fpe...@gm...> - 2016年01月29日 03:18:10
On Thu, Jan 28, 2016 at 3:23 PM, Andreas Mueller <t3...@gm...> wrote:
> 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
>
I've been wanting to do something about this problem for a while, but
haven't had the cycles to work on it... Here's my current idea, perhaps I
can goad you into implementing it :)
I think that IPython.display should provide a Figure object, capable of
wrapping any input image (with nice code to automatically swallow a
matplotlib figure without asking the user to convert it to an image first),
and taking an optional caption.
Figure() would then produce as output the displayed image but with a bit of
nice CSS to center it on the page, along with the caption.
The trick is to send the entire data bundle correctly structured so that,
at the other end, nbconvert could recognize these figures as such, and not
only produce nice HTML, but more importantly, push them into the LaTeX
output with the correct call to \figure, including \caption as well as size
and placement specifiers.
The signature of Figure() might be something like
def Figure(fig, caption=None, width=None, height=None,
 latex_placement=None):
I would try implementing this first as a standalone tool, and once it's
been tested enough in real-world usage with both HTML and LaTeX output from
nbconvert, it could be merged in. I suspect it's going to take a few
iterations to get it right.
But it's not particularly hard, and someone working on a book would be the
perfect candidate to have enough test cases to be able to iterate until
happy ;)
If you think you want to take a stab at this, don't hesitate to ping us on
the jupyter list. We can help with some of the more obscure parts of
getting this to work on nbconvert (and there may be things I've overlooked
in the sketch above).
Cheers,
f
-- 
Fernando Perez (@fperez_org; http://fperez.org)
fperez.net-at-gmail: mailing lists only (I ignore this when swamped!)
fernando.perez-at-berkeley: contact me here for any direct mail
From: Andreas M. <t3...@gm...> - 2016年01月28日 23:23:54
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
From: Julian I. <jul...@gm...> - 2016年01月28日 19:49:59
Attachments: overlapping_ticks.PNG
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
From: Fabrice S. <si...@lm...> - 2016年01月28日 17:03:39
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
From: Benjamin R. <ben...@gm...> - 2016年01月28日 15:39:52
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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>
From: Matteo N. <ma...@my...> - 2016年01月28日 04:59:58
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
From: Benjamin R. <ben...@gm...> - 2016年01月20日 20:00:13
Add "blit=False" in the instantiation for multicursor to get around the
copy_from_bbox issue.
I wonder if the use of fig.axes might be a problem?
On Jan 20, 2016 2:27 PM, "Bilheux, Jean-Christophe" <bil...@or...>
wrote:
> HI all,
>
> I wanted to help (for a change) but running the script on mac (with the
> multi cursor code commented out), I got the following error. If anyone can
> figure out why !
>
> File
> "/Users/j35/anaconda/lib/python3.4/site-packages/matplotlib/widgets.py",
> line 1046, in clear
> self.canvas.copy_from_bbox(self.canvas.figure.bbox))
> AttributeError: 'FigureCanvasMac' object has no attribute ‘copy_from_bbox'
>
> I’m using python 3.4 and matplotlib 1.4.3
>
> Thanks
>
> Jean
>
>
>
> > On Jan 20, 2016, at 1:26 PM, Michael Kaufman <kau...@or...> wrote:
> >
> > Hi Gurus:
> >
> > I'm having a serious problem with MultiCursor and autoscaling...
> >
> > If I do the code below with both MultiCursor instantiations commented
> out, then all plots are xscaled to [50,55] and yscaled to each plot's
> appropriate ylimits.
> >
> > If I uncomment the top MultiCursor instantiation, then both the xlimits
> and ylimits are screwed up: xlim=[0,60] and ylim is all over the place,
> certainly not autoscaled tight.
> >
> > If I uncomment the bottom MultiCursor instantiation, then the xlimit
> appears to be scaled correctly, [50,55], but two of the four plots (lower
> left and upper right) are not autoscaled in y.
> >
> > How to I instantiate MultiCursor to get the normal and expected
> autoscaling behavior?
> >
> > Not that it should matter, but I'm using here Tk and Python3 with MPL
> 1.5dev1 (91ca2a3724ae91d28d97)
> >
> > Thanks for any help,
> >
> > M
> >
> > =============
> >
> > from matplotlib import pyplot as pl
> > from matplotlib.widgets import MultiCursor
> > from matplotlib import gridspec
> > import numpy as np
> >
> > if __name__ == "__main__":
> >
> > fig = pl.gcf()
> > gs = gridspec.GridSpec(2,2)
> >
> > ax = None
> > for g in gs:
> > ax = pl.subplot(g, sharex=ax)
> >
> > #multi = MultiCursor(fig.canvas, tuple(fig.axes),
> > # useblit=True, horizOn=True, color='k', lw=1)
> >
> > x = np.arange(50,55,0.01)
> > y1 = np.sin(x)
> > y2 = np.cos(x) + 4
> > y3 = 0.2*np.cos(x) - 4
> > y4 = np.cos(2*x) - 1
> >
> > for ax,y in zip(fig.axes, [y1,y2,y3,y4]):
> > ax.plot(x,y)
> >
> > for ax in fig.axes:
> > ax.grid()
> >
> > #multi = MultiCursor(fig.canvas, tuple(fig.axes),
> > # useblit=True, horizOn=True, color='k', lw=1)
> >
> > pl.draw()
> > pl.show()
> >
> <multicursor_limtest.py>------------------------------------------------------------------------------
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> >
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> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
> ------------------------------------------------------------------------------
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> APM + Mobile APM + RUM: Monitor 3 App instances at just 35ドル/Month
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> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
From: Bilheux, Jean-C. <bil...@or...> - 2016年01月20日 19:24:14
HI all,
I wanted to help (for a change) but running the script on mac (with the multi cursor code commented out), I got the following error. If anyone can figure out why !
File "/Users/j35/anaconda/lib/python3.4/site-packages/matplotlib/widgets.py", line 1046, in clear
 self.canvas.copy_from_bbox(self.canvas.figure.bbox))
AttributeError: 'FigureCanvasMac' object has no attribute ‘copy_from_bbox'
I’m using python 3.4 and matplotlib 1.4.3
Thanks
Jean
> On Jan 20, 2016, at 1:26 PM, Michael Kaufman <kau...@or...> wrote:
> 
> Hi Gurus:
> 
> I'm having a serious problem with MultiCursor and autoscaling...
> 
> If I do the code below with both MultiCursor instantiations commented out, then all plots are xscaled to [50,55] and yscaled to each plot's appropriate ylimits.
> 
> If I uncomment the top MultiCursor instantiation, then both the xlimits and ylimits are screwed up: xlim=[0,60] and ylim is all over the place, certainly not autoscaled tight.
> 
> If I uncomment the bottom MultiCursor instantiation, then the xlimit appears to be scaled correctly, [50,55], but two of the four plots (lower left and upper right) are not autoscaled in y.
> 
> How to I instantiate MultiCursor to get the normal and expected autoscaling behavior?
> 
> Not that it should matter, but I'm using here Tk and Python3 with MPL 1.5dev1 (91ca2a3724ae91d28d97)
> 
> Thanks for any help,
> 
> M
> 
> =============
> 
> from matplotlib import pyplot as pl
> from matplotlib.widgets import MultiCursor
> from matplotlib import gridspec
> import numpy as np
> 
> if __name__ == "__main__":
> 
> fig = pl.gcf()
> gs = gridspec.GridSpec(2,2)
> 
> ax = None
> for g in gs:
> ax = pl.subplot(g, sharex=ax)
> 
> #multi = MultiCursor(fig.canvas, tuple(fig.axes),
> # useblit=True, horizOn=True, color='k', lw=1)
> 
> x = np.arange(50,55,0.01)
> y1 = np.sin(x)
> y2 = np.cos(x) + 4
> y3 = 0.2*np.cos(x) - 4
> y4 = np.cos(2*x) - 1
> 
> for ax,y in zip(fig.axes, [y1,y2,y3,y4]):
> ax.plot(x,y)
> 
> for ax in fig.axes:
> ax.grid()
> 
> #multi = MultiCursor(fig.canvas, tuple(fig.axes),
> # useblit=True, horizOn=True, color='k', lw=1)
> 
> pl.draw()
> pl.show()
> <multicursor_limtest.py>------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
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From: Michael K. <kau...@or...> - 2016年01月20日 18:26:13
Attachments: multicursor_limtest.py
Hi Gurus:
I'm having a serious problem with MultiCursor and autoscaling...
If I do the code below with both MultiCursor instantiations commented 
out, then all plots are xscaled to [50,55] and yscaled to each plot's 
appropriate ylimits.
If I uncomment the top MultiCursor instantiation, then both the xlimits 
and ylimits are screwed up: xlim=[0,60] and ylim is all over the place, 
certainly not autoscaled tight.
If I uncomment the bottom MultiCursor instantiation, then the xlimit 
appears to be scaled correctly, [50,55], but two of the four plots 
(lower left and upper right) are not autoscaled in y.
How to I instantiate MultiCursor to get the normal and expected 
autoscaling behavior?
Not that it should matter, but I'm using here Tk and Python3 with MPL 
1.5dev1 (91ca2a3724ae91d28d97)
Thanks for any help,
M
=============
from matplotlib import pyplot as pl
from matplotlib.widgets import MultiCursor
from matplotlib import gridspec
import numpy as np
if __name__ == "__main__":
 fig = pl.gcf()
 gs = gridspec.GridSpec(2,2)
 ax = None
 for g in gs:
 ax = pl.subplot(g, sharex=ax)
 #multi = MultiCursor(fig.canvas, tuple(fig.axes),
 # useblit=True, horizOn=True, color='k', lw=1)
 x = np.arange(50,55,0.01)
 y1 = np.sin(x)
 y2 = np.cos(x) + 4
 y3 = 0.2*np.cos(x) - 4
 y4 = np.cos(2*x) - 1
 for ax,y in zip(fig.axes, [y1,y2,y3,y4]):
 ax.plot(x,y)
 for ax in fig.axes:
 ax.grid()
 #multi = MultiCursor(fig.canvas, tuple(fig.axes),
 # useblit=True, horizOn=True, color='k', lw=1)
 pl.draw()
 pl.show()
From: Sudheer J. <sud...@ya...> - 2016年01月07日 09:37:44
Dear experts,
I tried to use the matplotlib function plt.xcorr for calculating cross correlation between to check its 
functionality using the data from a standard example given in R web site example.
https://onlinecourses.science.psu.edu/stat510/node/74
However when the example given above is replicated using python I get a totally different graph.
Any idea why this happens?
I tried normed=True but do not appears to have any effect. Any advice on this will be of extreme help
import urllib as web
from matplotlib import pylab as plt
f=web.urlopen('http://anson.ucdavis.edu/~shumway/soi.dat')
soi=[]
for line in f: soi.append(float(line.strip()))
f.close()
rec=[]
f=web.urlopen('http://anson.ucdavis.edu/~shumway/recruit.dat')
for line in f: rec.append(float(line.strip()))
ax=plt.figure()
anl_ccf=plt.xcorr(soi,rec,maxlags=30)
plt.show()
With best regards,
Sudheer 
From: Sudheer J. <sud...@ya...> - 2016年01月07日 09:32:53
*************************************************************** Sudheer Joseph Indian National Centre for Ocean Information Services Ministry of Earth Sciences, Govt. of India POST BOX NO: 21, IDA Jeedeemetla P.O. Via Pragathi Nagar,Kukatpally, Hyderabad; Pin:5000 55 Tel:+91-40-23886047(O),Fax:+91-40-23895011(O), Tel:+91-40-23044600(R),Tel:+91-40-9440832534(Mobile) E-mail:sjo...@gm...;sud...@ya... Web- http://oppamthadathil.tripod.com ***************************************************************
From: Eric F. <ef...@ha...> - 2016年01月05日 20:23:15
On 2016年01月05日 9:48 AM, Martin McGlensey wrote:
> Arnaldo,
>
> Thanks for the response. I figured it out. Figsize although the units
> are inches it does not correspond to inches on the display. I had to go
> up to 23 X 12 to get a large image on the display. If I want to fill the
> display what parameters should I use? I’m looking for a large map not a
> large frame size. Maybe I’m not understanding the functions of the
> various arguments used.
Rather than using a large size in inches, increase the value of the 
"dpi" kwarg to "figure()". When it matches your actual screen dpi, the 
display on the screen should be correct in the specified dimensions in 
inches, *provided* those dimensions plus the margins (toolbar etc.) fit 
on your screen. If they don't, then decrease the dpi (scaling the 
displayed figure down) until they do.
Eric
>
> Regards,
>
> Marty
>
> *From:*Arnaldo Russo [mailto:arn...@gm...]
> *Sent:* Monday, January 4, 2016 6:43 AM
> *To:* Martin McGlensey <mmc...@fr...>
> *Cc:* mat...@li...
> *Subject:* Re: [Matplotlib-users] How do I make a Mercator map larger
>
> Hi Martin,
>
> Have you tried to save your figure and check if it does not enlarge your
> figure?
>
> plt.savefig("mercator.png")
>
> Cheers,
>
> Arnaldo.
>
> ---
>
> Arnaldo D'Amaral Pereira Granja Russo
>
> Universidade do Estado de Santa Catarina - UDESC
>
> Pesquisador - Instituto Ambiental Boto Flipper
>
> institutobotoflipper.org
>
> 2016年01月03日 20:20 GMT-02:00 Martin McGlensey <mmc...@fr...
> <mailto:mmc...@fr...>>:
>
> Hello,
>
> I’m a new user to both python and basemap. I’ve got my map working
> OK, but would like to make it larger on the display. I’ve tried the
> height and width parameters in the map definition (m=basemap(...) and
> plt.figure(figuresize=(x,y)). Neither appear to have any effect on
> the size of the map.
>
> Is there an easy way to convert map coordinates to inches?
>
> Thanks,
>
> Marty
>
>
> ------------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> <mailto:Mat...@li...>
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
>
> ------------------------------------------------------------------------------
>
>
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
From: Martin M. <mmc...@fr...> - 2016年01月05日 19:48:32
Arnaldo,
 
Thanks for the response. I figured it out. Figsize although the units are inches it does not correspond to inches on the display. I had to go up to 23 X 12 to get a large image on the display. If I want to fill the display what parameters should I use? I’m looking for a large map not a large frame size. Maybe I’m not understanding the functions of the various arguments used.
 
Regards,
Marty
 
From: Arnaldo Russo [mailto:arn...@gm...] 
Sent: Monday, January 4, 2016 6:43 AM
To: Martin McGlensey <mmc...@fr...>
Cc: mat...@li...
Subject: Re: [Matplotlib-users] How do I make a Mercator map larger
 
Hi Martin,
 
Have you tried to save your figure and check if it does not enlarge your figure?
 
 plt.savefig("mercator.png")
 
Cheers,
Arnaldo.
 
---
Arnaldo D'Amaral Pereira Granja Russo
Universidade do Estado de Santa Catarina - UDESC
Pesquisador - Instituto Ambiental Boto Flipper
institutobotoflipper .org
 
2016年01月03日 20:20 GMT-02:00 Martin McGlensey <mmc...@fr... <mailto:mmc...@fr...> >:
Hello,
 
I’m a new user to both python and basemap. I’ve got my map working OK, but would like to make it larger on the display. I’ve tried the height and width parameters in the map definition (m=basemap(...) and plt.figure(figuresize=(x,y)). Neither appear to have any effect on the size of the map.
 
Is there an easy way to convert map coordinates to inches?
 
Thanks,
Marty
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From: Benjamin R. <ben...@gm...> - 2016年01月04日 16:44:09
Without seeing the code, it would be hard to tell what is wrong. Setting
the figure size should work. I do this all the time myself.
As for converting map coordinates to inches, are you talking about inches
of the display? or inches of the map (as opposed to km or miles)?
Ben Root
On Sun, Jan 3, 2016 at 5:20 PM, Martin McGlensey <mmc...@fr...>
wrote:
> Hello,
>
>
>
> I’m a new user to both python and basemap. I’ve got my map working OK, but
> would like to make it larger on the display. I’ve tried the height and
> width parameters in the map definition (m=basemap(...) and
> plt.figure(figuresize=(x,y)). Neither appear to have any effect on the size
> of the map.
>
>
>
> Is there an easy way to convert map coordinates to inches?
>
>
>
> Thanks,
>
> Marty
>
>
> ------------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
From: Arnaldo R. <arn...@gm...> - 2016年01月04日 11:43:15
Hi Martin,
Have you tried to save your figure and check if it does not enlarge your
figure?
 plt.savefig("mercator.png")
Cheers,
Arnaldo.
---
Arnaldo D'Amaral Pereira Granja Russo
Universidade do Estado de Santa Catarina - UDESC
Pesquisador - Instituto Ambiental Boto Flipper
institutobotoflipper .org
2016年01月03日 20:20 GMT-02:00 Martin McGlensey <mmc...@fr...>:
> Hello,
>
>
>
> I’m a new user to both python and basemap. I’ve got my map working OK, but
> would like to make it larger on the display. I’ve tried the height and
> width parameters in the map definition (m=basemap(...) and
> plt.figure(figuresize=(x,y)). Neither appear to have any effect on the size
> of the map.
>
>
>
> Is there an easy way to convert map coordinates to inches?
>
>
>
> Thanks,
>
> Marty
>
>
> ------------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

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