matplotlib-users Mailing List for matplotlib (Page 56)

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Best,
Ray

On Thu, Oct 16, 2014 at 4:22 PM, Almerindo Paiva <alo...@gm...> wrote:

> Dear Sirs,
>
> I would like to ask you to unsubscripte my account from
> mat...@li....
>
> Kind regards,
>
> Almerindo Paiva
>
>
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Dear Sirs,

I would like to ask you to unsubscripte my account from
mat...@li....

Kind regards,

Almerindo Paiva

Tobais,

In the future please send all messages like this to the user mailing list (cc'd)

Try using the 1.4.1rc1 release candidate, there are windows installers
on sourceforge.  If that does not work, please open a new github
issue.

Tom

On Thu, Oct 16, 2014 at 2:43 PM, Tobias Landwehr <Dol...@gm...> wrote:
> Greetings Thomas,
>
> I am sorry to disturb you, but I found on github, that you could've already
> provided a solution to my problem almost three weeks ago. I couldn't really
> understand the way how to solve the prob, which is the reason I decided to
> write you.
>
> I am currently working with Python 2.7.2 and want to import the matplotlib.
> Problems arise obviously since my username-folder contains a non-ascii sign
> (german Ä). I would prefer to not setup a second user and the user's folder
> shouldn't/can't be renamed.
>
> If you could find some time to deal with the problem over the weekend or
> give me a hint, how to solve it, I would be really grateful. Below you'll
> find the fail report.
>
> Many thanks in advance, Tobias
>
> Traceback (most recent call last):
>   File "C:\Python27\workspace\ITT\src\itt\statistics\block01\LandCover.py",
> line 7, in <module>
>     import matplotlib.pyplot as plt
>   File "C:\Python27\lib\site-packages\matplotlib\__init__.py", line 1048, in
> <module>
>     rcParams = rc_params()
>   File "C:\Python27\lib\site-packages\matplotlib\__init__.py", line 897, in
> rc_params
>     fname = matplotlib_fname()
>   File "C:\Python27\lib\site-packages\matplotlib\__init__.py", line 759, in
> matplotlib_fname
>     configdir = _get_configdir()
>   File "C:\Python27\lib\site-packages\matplotlib\__init__.py", line 630, in
> _get_configdir
>     return _get_config_or_cache_dir(_get_xdg_config_dir())
>   File "C:\Python27\lib\site-packages\matplotlib\__init__.py", line 555, in
> _get_xdg_config_dir
>     path = get_home()
>   File "C:\Python27\lib\site-packages\matplotlib\__init__.py", line 323, in
> wrapper
>     ret = func(*args, **kwargs)
>   File "C:\Python27\lib\site-packages\matplotlib\__init__.py", line 509, in
> _get_home
>     path = os.path.expanduser("~")
>   File "C:\Python27\lib\ntpath.py", line 310, in expanduser
>     return userhome + path[i:]
> UnicodeDecodeError: 'ascii' codec can't decode byte 0x84 in position 16:
> ordinal not in range(128)
>



-- 
Thomas Caswell
tca...@gm...

Thanks Ben. I'll take a look through the archive.

On 10/16/14, 9:43 AM, Benjamin Root wrote:
> What you are looking for is called "rasterization". Matplotlib does this
> deep within the codebase and is not accessible (believe me, I tried).
> However, there have been other discussions in this mailing list about
> how to use GDAL to rasterize a set of polygons (represented as paths),
> including some links to stack-overflow questions. It isn't a complete
> end-to-end solution, but the pieces are there.
>
> Cheers!
> Ben Root
>
>
> On Wed, Oct 15, 2014 at 2:09 PM, David Hoese <dh...@gm...
> <mailto:dh...@gm...>> wrote:
>
>     For the first question, if I save the figure (as a PNG I'm guessing,
>     unless you can save into a more array-like format), I'd have to make
>     sure that there were no labels or ticks and that the axes fit the whole
>     figure. I'd also have to get the dpi and size information correct, but I
>     suppose it would be possible that way. I was hoping for something a
>     little easier and in-memory. This might be the simplest answer the more
>     I think about it.
>
>     If I'm starting from the paths, I'd still have to write them to the
>     "grid" array. I thought maybe the backend could do that and I magically
>     get the image.
>
>     I'll look in to using savefig and getting the data out.
>
>     -Dave
>
>     On 10/15/14, 12:42 PM, Joy merwin monteiro wrote:
>     > pardon the query if it seems dumb, but why don't you do a savefig()
>     > after plotting the data and then convert it to any format you like?
>     >
>     > alternatively, contour() and contourf() both create paths that can
>     > be accessed:
>     >
>     > cf = contourf(.....)
>     >
>     > output = cf.collections.pop()
>     > paths = output.get_paths()[i] # for the various contours
>     >
>     > the x,y coordinates can then be accessed as
>     >
>     > xcoords = paths.vertices.transpose()[0]
>     > ycoords = paths.vertices.transpose()[1]
>     >
>     > you can then do whatever you wish with them.
>     >
>     > Joy
>     >
>     >
>     > On Wed, Oct 15, 2014 at 9:11 PM, David Hoese <dh...@gm... <mailto:dh...@gm...>
>      > <mailto:dh...@gm... <mailto:dh...@gm...>>> wrote:
>      >
>      >     I've been searching and reading through source code and
>     google searches
>      >     to see if this is possible, but no luck so far. I'm basically
>     trying to
>      >     map some data using Basemap, use contourf to map it to an
>     image, and
>      >     then put that image in a geotiff (or other format) for use in
>     other GIS
>      >     programs. I have other tools for remapping data and creating
>     geotiffs,
>      >     but the contour image looks better. All I would need to get
>     this to work
>      >     would be an array representing the image inside the axes of a
>     contourf
>      >     plot. I found a lot of geotiff -> Basemap png results, but I
>     would like
>      >     the reverse.
>      >
>      >     Since the plots are made using paths/patches I'm guessing I
>     would have
>      >     to have a backend render the image and then extract the image
>     somehow.
>      >     Does anyone have some tips or tricks to do something like
>     this? Or am I
>      >     thinking about this completely wrong?
>      >
>      >     Thanks for any help and if you could CC me in any replies it
>     would be
>      >     much appreciated.
>      >
>      >     -Dave
>      >
>      >
>       ------------------------------------------------------------------------------
>      >     Comprehensive Server Monitoring with Site24x7.
>      >     Monitor 10 servers for $9/Month.
>      >     Get alerted through email, SMS, voice calls or mobile push
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>      >     Take corrective actions from your mobile device.
>      > http://p.sf.net/sfu/Zoho
>      >     _______________________________________________
>      >     Matplotlib-users mailing list
>      > Mat...@li...
>     <mailto:Mat...@li...>
>      >     <mailto:Mat...@li...
>     <mailto:Mat...@li...>>
>      > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>      >
>      >
>      >
>      >
>      > --
>      > The best ruler, when he finishes his
>      > tasks and completes his affairs,
>      > the people say
>      > “It all happened naturally”
>      >
>      >                                           - Te Tao Ch'ing
>
>     ------------------------------------------------------------------------------
>     Comprehensive Server Monitoring with Site24x7.
>     Monitor 10 servers for $9/Month.
>     Get alerted through email, SMS, voice calls or mobile push
>     notifications.
>     Take corrective actions from your mobile device.
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>     _______________________________________________
>     Matplotlib-users mailing list
>     Mat...@li...
>     <mailto:Mat...@li...>
>     https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

What you are looking for is called "rasterization". Matplotlib does this
deep within the codebase and is not accessible (believe me, I tried).
However, there have been other discussions in this mailing list about how
to use GDAL to rasterize a set of polygons (represented as paths),
including some links to stack-overflow questions. It isn't a complete
end-to-end solution, but the pieces are there.

Cheers!
Ben Root


On Wed, Oct 15, 2014 at 2:09 PM, David Hoese <dh...@gm...> wrote:

> For the first question, if I save the figure (as a PNG I'm guessing,
> unless you can save into a more array-like format), I'd have to make
> sure that there were no labels or ticks and that the axes fit the whole
> figure. I'd also have to get the dpi and size information correct, but I
> suppose it would be possible that way. I was hoping for something a
> little easier and in-memory. This might be the simplest answer the more
> I think about it.
>
> If I'm starting from the paths, I'd still have to write them to the
> "grid" array. I thought maybe the backend could do that and I magically
> get the image.
>
> I'll look in to using savefig and getting the data out.
>
> -Dave
>
> On 10/15/14, 12:42 PM, Joy merwin monteiro wrote:
> > pardon the query if it seems dumb, but why don't you do a savefig()
> > after plotting the data and then convert it to any format you like?
> >
> > alternatively, contour() and contourf() both create paths that can
> > be accessed:
> >
> > cf = contourf(.....)
> >
> > output = cf.collections.pop()
> > paths = output.get_paths()[i] # for the various contours
> >
> > the x,y coordinates can then be accessed as
> >
> > xcoords = paths.vertices.transpose()[0]
> > ycoords = paths.vertices.transpose()[1]
> >
> > you can then do whatever you wish with them.
> >
> > Joy
> >
> >
> > On Wed, Oct 15, 2014 at 9:11 PM, David Hoese <dh...@gm...
> > <mailto:dh...@gm...>> wrote:
> >
> >     I've been searching and reading through source code and google
> searches
> >     to see if this is possible, but no luck so far. I'm basically trying
> to
> >     map some data using Basemap, use contourf to map it to an image, and
> >     then put that image in a geotiff (or other format) for use in other
> GIS
> >     programs. I have other tools for remapping data and creating
> geotiffs,
> >     but the contour image looks better. All I would need to get this to
> work
> >     would be an array representing the image inside the axes of a
> contourf
> >     plot. I found a lot of geotiff -> Basemap png results, but I would
> like
> >     the reverse.
> >
> >     Since the plots are made using paths/patches I'm guessing I would
> have
> >     to have a backend render the image and then extract the image
> somehow.
> >     Does anyone have some tips or tricks to do something like this? Or
> am I
> >     thinking about this completely wrong?
> >
> >     Thanks for any help and if you could CC me in any replies it would be
> >     much appreciated.
> >
> >     -Dave
> >
> >
>  ------------------------------------------------------------------------------
> >     Comprehensive Server Monitoring with Site24x7.
> >     Monitor 10 servers for $9/Month.
> >     Get alerted through email, SMS, voice calls or mobile push
> >     notifications.
> >     Take corrective actions from your mobile device.
> >     http://p.sf.net/sfu/Zoho
> >     _______________________________________________
> >     Matplotlib-users mailing list
> >     Mat...@li...
> >     <mailto:Mat...@li...>
> >     https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >
> >
> >
> >
> > --
> > The best ruler, when he finishes his
> > tasks and completes his affairs,
> > the people say
> > “It all happened naturally”
> >
> >                                           - Te Tao Ch'ing
>
>
> ------------------------------------------------------------------------------
> Comprehensive Server Monitoring with Site24x7.
> Monitor 10 servers for $9/Month.
> Get alerted through email, SMS, voice calls or mobile push notifications.
> Take corrective actions from your mobile device.
> http://p.sf.net/sfu/Zoho
> _______________________________________________
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> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Awesome, thanks!

On Thu, Oct 16, 2014 at 8:14 AM, Sandro Tosi <mo...@de...> wrote:
> Hi!
> I just uploaded mpl 1.4.1-rc1 in Debian, so it can geta  bit of
> exposure even on the weird HW we still support.
>
> Cheers,
> Sandro
>
> On Tue, Oct 14, 2014 at 5:40 PM, Thomas Caswell <tca...@gm...> wrote:
>> I am happy to announce that I have tagged a release candidate for
>> 1.4.1.  This is a bug-fix release which fixes most of the bug that
>> popped up in 1.4.0 including:
>>
>>  - setup.py does not die when freetype is not installed
>>  - reverts the changes to interactive plotting so `ion` will work as expected
>>  - sundry unicode fixes (looking up user folders, importing
>> seaborn/pandas/networkx with macosx backend
>>  - fixed boxplot regressions
>>
>> The tarball is available from github, sourceforge and can be install via
>>
>>    pip install matplotlib==1.4.1rc1
>>
>> Tom
>>
>>
>>
>> --
>> Thomas Caswell
>> tca...@gm...
>>
>> ------------------------------------------------------------------------------
>> Comprehensive Server Monitoring with Site24x7.
>> Monitor 10 servers for $9/Month.
>> Get alerted through email, SMS, voice calls or mobile push notifications.
>> Take corrective actions from your mobile device.
>> http://p.sf.net/sfu/Zoho
>> _______________________________________________
>> Matplotlib-devel mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
>
>
>
> --
> Sandro Tosi (aka morph, morpheus, matrixhasu)
> My website: http://matrixhasu.altervista.org/
> Me at Debian: http://wiki.debian.org/SandroTosi



-- 
Thomas Caswell
tca...@gm...

Hi!
I just uploaded mpl 1.4.1-rc1 in Debian, so it can geta  bit of
exposure even on the weird HW we still support.

Cheers,
Sandro

On Tue, Oct 14, 2014 at 5:40 PM, Thomas Caswell <tca...@gm...> wrote:
> I am happy to announce that I have tagged a release candidate for
> 1.4.1.  This is a bug-fix release which fixes most of the bug that
> popped up in 1.4.0 including:
>
>  - setup.py does not die when freetype is not installed
>  - reverts the changes to interactive plotting so `ion` will work as expected
>  - sundry unicode fixes (looking up user folders, importing
> seaborn/pandas/networkx with macosx backend
>  - fixed boxplot regressions
>
> The tarball is available from github, sourceforge and can be install via
>
>    pip install matplotlib==1.4.1rc1
>
> Tom
>
>
>
> --
> Thomas Caswell
> tca...@gm...
>
> ------------------------------------------------------------------------------
> Comprehensive Server Monitoring with Site24x7.
> Monitor 10 servers for $9/Month.
> Get alerted through email, SMS, voice calls or mobile push notifications.
> Take corrective actions from your mobile device.
> http://p.sf.net/sfu/Zoho
> _______________________________________________
> Matplotlib-devel mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel



-- 
Sandro Tosi (aka morph, morpheus, matrixhasu)
My website: http://matrixhasu.altervista.org/
Me at Debian: http://wiki.debian.org/SandroTosi

Thanks for the reiteration/clarification...  Do you see any reason why a fail-safe check similar to what I proposed would be ill advised?

MJ

-----Original Message-----
From: Matthew Brett [mailto:mat...@gm...] 
Sent: Wednesday, October 15, 2014 3:44 PM
To: Mark Janikas
Cc: Thomas Caswell; Phil Elson; Benjamin Root; Matplotlib Users
Subject: Re: [Matplotlib-users] FW: traceback when import matplotlib.pyplot twice

Hi,

On Wed, Oct 15, 2014 at 2:56 PM, Mark Janikas <mja...@es...> wrote:
>
> When I replaced the file I got the 1st error below.   As you had pointed out earlier… this is strange.  It only occurs when you run it more than once… strange indeed… it is like a manager is being created and deleted but perhaps the reference hasn’t

Just to echo what Tom said, the error suggests that ``gc.collect()`` is being called after the gc module is most of the way through being torn down, so that the ``collect`` function has already been deleted...

Cheers,

Matthew

Hi,

On Wed, Oct 15, 2014 at 2:56 PM, Mark Janikas <mja...@es...> wrote:
>
> When I replaced the file I got the 1st error below.   As you had pointed out earlier… this is strange.  It only occurs when you run it more than once… strange indeed… it is like a manager is being created and deleted but perhaps the reference hasn’t

Just to echo what Tom said, the error suggests that ``gc.collect()``
is being called after the gc module is most of the way through being
torn down, so that the ``collect`` function has already been
deleted...

Cheers,

Matthew

I have a polar graph that works fine on linux but is blank on MacOS 
10.9. Here is a minimal working example (using the API because it is 
part of a larger Tkinter application):

#!/usr/bin/env python2
import Tkinter
import matplotlib
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg

root = Tkinter.Tk()
root["bg"] = "green" # the green should be hidden by the plot

plotFig = matplotlib.figure.Figure(figsize=(5, 5), frameon=False)
figCanvas = FigureCanvasTkAgg(plotFig, root)
figCanvas.get_tk_widget().pack()
axis = plotFig.add_subplot(1, 1, 1, polar=True, autoscale_on=True)

r = (0.1, 0.4, 0.6, 0.8)
theta = (0, 1.5, 3.0, 4.5) # radians, 0 to right. pi/2 up
axis.plot(theta, r, marker="o", markeredgecolor="black", markersize=3)
figCanvas.draw()

root.mainloop()


On MacOS 10.9 when I run this from Terminal I see a green window (rather 
than the plot I expect). When I click on the plot window to bring it to 
the front, the window turns white with a thin black border (presumably 
the plot, but with no content).

Details:
- matplotlib 1.3.1
- Tcl/Tk 8.5.11 (for good reasons, unfortunately)
- python.org python 2.7.6, running in 32-bit mode (due to a known issue 
with MacOS 10.9 and this old version of Tcl/Tk)

Any ideas how to get the plot to show?

-- Russell

When I replaced the file I got the 1st error below.   As you had pointed out earlier… this is strange.  It only occurs when you run it more than once… strange indeed… it is like a manager is being created and deleted but perhaps the reference hasn’t… so you get a no-op on the subsequent import.. but are then left with a manager that is None….?? Thanks for the tip BTW… I replaced all my None comparisons to “is” and “is not”.   I went ahead and added the comparisons to your changes and it works… but now you need to assure that you do not gc.collect unless you had at least one Non-None manager or else you get the 2nd traceback.  The code that works on my end is the last image… not sure if it passes your regression tests..??..??



Thanks so much for all of your help… please let me know if there is anything else I can do to help.



MJ





[cid:image001.png@01CFE881.FB6CCAF0]



[cid:image002.png@01CFE888.2A514840]



[cid:image003.png@01CFE888.2A514840]

-----Original Message-----

From: Thomas Caswell [mailto:tca...@gm...]

Sent: Saturday, October 11, 2014 2:18 PM

To: Phil Elson

Cc: Mark Janikas; Benjamin Root; Matplotlib Users

Subject: Re: [Matplotlib-users] FW: traceback when import matplotlib.pyplot twice



See https://github.com/matplotlib/matplotlib/pull/3638



That might help to make sure that things tear them selves down in the right order.



Tom



On Sat, Oct 11, 2014 at 10:12 AM, Phil Elson <pel...@gm...> wrote:

>

> On 10 October 2014 19:10, Thomas Caswell <tca...@gm...> wrote:

>>

>> I suspect a better fix is to change all of the staticmethods ->

>> classmethods

>

>

>

> +1







--

Thomas Caswell

tca...@gm...

For the first question, if I save the figure (as a PNG I'm guessing, 
unless you can save into a more array-like format), I'd have to make 
sure that there were no labels or ticks and that the axes fit the whole 
figure. I'd also have to get the dpi and size information correct, but I 
suppose it would be possible that way. I was hoping for something a 
little easier and in-memory. This might be the simplest answer the more 
I think about it.

If I'm starting from the paths, I'd still have to write them to the 
"grid" array. I thought maybe the backend could do that and I magically 
get the image.

I'll look in to using savefig and getting the data out.

-Dave

On 10/15/14, 12:42 PM, Joy merwin monteiro wrote:
> pardon the query if it seems dumb, but why don't you do a savefig()
> after plotting the data and then convert it to any format you like?
>
> alternatively, contour() and contourf() both create paths that can
> be accessed:
>
> cf = contourf(.....)
>
> output = cf.collections.pop()
> paths = output.get_paths()[i] # for the various contours
>
> the x,y coordinates can then be accessed as
>
> xcoords = paths.vertices.transpose()[0]
> ycoords = paths.vertices.transpose()[1]
>
> you can then do whatever you wish with them.
>
> Joy
>
>
> On Wed, Oct 15, 2014 at 9:11 PM, David Hoese <dh...@gm...
> <mailto:dh...@gm...>> wrote:
>
>     I've been searching and reading through source code and google searches
>     to see if this is possible, but no luck so far. I'm basically trying to
>     map some data using Basemap, use contourf to map it to an image, and
>     then put that image in a geotiff (or other format) for use in other GIS
>     programs. I have other tools for remapping data and creating geotiffs,
>     but the contour image looks better. All I would need to get this to work
>     would be an array representing the image inside the axes of a contourf
>     plot. I found a lot of geotiff -> Basemap png results, but I would like
>     the reverse.
>
>     Since the plots are made using paths/patches I'm guessing I would have
>     to have a backend render the image and then extract the image somehow.
>     Does anyone have some tips or tricks to do something like this? Or am I
>     thinking about this completely wrong?
>
>     Thanks for any help and if you could CC me in any replies it would be
>     much appreciated.
>
>     -Dave
>
>     ------------------------------------------------------------------------------
>     Comprehensive Server Monitoring with Site24x7.
>     Monitor 10 servers for $9/Month.
>     Get alerted through email, SMS, voice calls or mobile push
>     notifications.
>     Take corrective actions from your mobile device.
>     http://p.sf.net/sfu/Zoho
>     _______________________________________________
>     Matplotlib-users mailing list
>     Mat...@li...
>     <mailto:Mat...@li...>
>     https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
>
>
> --
> The best ruler, when he finishes his
> tasks and completes his affairs,
> the people say
> “It all happened naturally”
>
>                                           - Te Tao Ch'ing

pardon the query if it seems dumb, but why don't you do a savefig()
after plotting the data and then convert it to any format you like?

alternatively, contour() and contourf() both create paths that can
be accessed:

cf = contourf(.....)

output = cf.collections.pop()
paths = output.get_paths()[i] # for the various contours

the x,y coordinates can then be accessed as

xcoords = paths.vertices.transpose()[0]
ycoords = paths.vertices.transpose()[1]

you can then do whatever you wish with them.

Joy


On Wed, Oct 15, 2014 at 9:11 PM, David Hoese <dh...@gm...> wrote:

> I've been searching and reading through source code and google searches
> to see if this is possible, but no luck so far. I'm basically trying to
> map some data using Basemap, use contourf to map it to an image, and
> then put that image in a geotiff (or other format) for use in other GIS
> programs. I have other tools for remapping data and creating geotiffs,
> but the contour image looks better. All I would need to get this to work
> would be an array representing the image inside the axes of a contourf
> plot. I found a lot of geotiff -> Basemap png results, but I would like
> the reverse.
>
> Since the plots are made using paths/patches I'm guessing I would have
> to have a backend render the image and then extract the image somehow.
> Does anyone have some tips or tricks to do something like this? Or am I
> thinking about this completely wrong?
>
> Thanks for any help and if you could CC me in any replies it would be
> much appreciated.
>
> -Dave
>
>
> ------------------------------------------------------------------------------
> Comprehensive Server Monitoring with Site24x7.
> Monitor 10 servers for $9/Month.
> Get alerted through email, SMS, voice calls or mobile push notifications.
> Take corrective actions from your mobile device.
> http://p.sf.net/sfu/Zoho
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>



-- 
The best ruler, when he finishes his
tasks and completes his affairs,
the people say
“It all happened naturally”

                                         - Te Tao Ch'ing

I've been searching and reading through source code and google searches 
to see if this is possible, but no luck so far. I'm basically trying to 
map some data using Basemap, use contourf to map it to an image, and 
then put that image in a geotiff (or other format) for use in other GIS 
programs. I have other tools for remapping data and creating geotiffs, 
but the contour image looks better. All I would need to get this to work 
would be an array representing the image inside the axes of a contourf 
plot. I found a lot of geotiff -> Basemap png results, but I would like 
the reverse.

Since the plots are made using paths/patches I'm guessing I would have 
to have a backend render the image and then extract the image somehow. 
Does anyone have some tips or tricks to do something like this? Or am I 
thinking about this completely wrong?

Thanks for any help and if you could CC me in any replies it would be 
much appreciated.

-Dave

On this documentation page: http://matplotlib.org/api/figure_api.html. 

It says: 
    The following classes are definedSubplotParams
        control the default spacing of the subplots
    Figure
        top level container for all plot elements 

But actually there are three. The third one is: AxesStack. Or did I
misunderstand smth?



--
View this message in context: http://matplotlib.1069221.n5.nabble.com/Docs-mention-two-classes-but-actually-has-three-tp44115.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

So, you need to know what tools to use to read in grib2 data? There are two
particular grib readers that I am familiar with: PyNIO and pygrib2. PyNIO
actually isn't a grib reader, as much as a swiss army knife of file
readers. It is very similar to the netcdf4 interface, so if you are
familiar with that, then PyNIO is very nice in that respect. Unfortunately,
PyNIO is not available through pypi. You have to go directly to their
website, sign up and download it directly from them.

Oh, and may god have mercy on your soul if you have to build from source
for either PyNIO or pygrib2... try the binaries if possible.

Ben Root

On Tue, Oct 14, 2014 at 1:09 AM, Sourav Chatterjee <sr...@gm...>
wrote:

> Can somebody help me to plot the wind vectors in spstere projection
> reading data from a grb2 file *without using Dataset (netcdf4*)?
>
> Thanks
> Sourav
>
>
> ------------------------------------------------------------------------------
> Comprehensive Server Monitoring with Site24x7.
> Monitor 10 servers for $9/Month.
> Get alerted through email, SMS, voice calls or mobile push notifications.
> Take corrective actions from your mobile device.
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> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Hi Chris,

Thanks for that tip.  I'll give it a try.  They are big images (2048 x
2048) so it seems like your suggestion should work.

Jon

On Tue, Oct 14, 2014 at 12:18 PM, Chris Beaumont <cbe...@cf...>
wrote:

> I've found that, for big images, the *first* draw is very slow, due to the
> intensity scaling of the image, which happens at full resolution. Panning
> and zooming afterwards is fast because the intensity scaling is cached, but
> changing the data array or updating the norm kwarg is slow again. I made
> ModestImage (https://github.com/ChrisBeaumont/mpl-modest-image) to deal
> with this -- it dynamically downsamples images to screen resolution. This
> makes the first draw after updating the data or norm much faster, while
> slowing down subsequent redraws. Perhaps this could help you out?
>
> cheers,
> chris
>
> On Tue, Oct 14, 2014 at 12:08 PM, Benjamin Root <ben...@ou...> wrote:
>
>> Only if there are multiple figures (plt.draw() operates on the current
>> active figure, while fig.draw() explicitly operates upon that figure).
>> Another possibility is that the bottleneck truly is the IO. Depending on
>> exactly how fits work, it might be lazily loading data for you, so the test
>> without the display of the images might not actually be loading any data
>> into memory.
>>
>> Ben Root
>>
>> On Tue, Oct 14, 2014 at 11:22 AM, Slavin, Jonathan <
>> js...@cf...> wrote:
>>
>>> Hmm.  I just saw that you suggest fig.draw().  Is there a difference
>>> with plt.draw()?
>>>
>>> Jon
>>>
>>> On Tue, Oct 14, 2014 at 11:20 AM, Slavin, Jonathan <
>>> js...@cf...> wrote:
>>>
>>>> Hi Ben,
>>>>
>>>> Sorry, in my little example, I left out a few things.  I do update
>>>> first after the first call.  And I do call draw() after other calls.  So
>>>> here is a more accurate representation of what I do:
>>>>
>>>> first = True
>>>> fig = plt.figure()
>>>> for file in files:
>>>>     hdu = fits.open(file)
>>>>     image = hdu[0].data
>>>>     hdu.close()
>>>>     if first:
>>>>         ax = fig,add_subplot(1,1,1)
>>>>         im = ax.imshow(image)
>>>>         plt.show()
>>>>         first = False
>>>>     else:
>>>>         im.set_data(image)
>>>>         plt.draw()
>>>>     ans = raw_input('continue?')
>>>>     if ans == 'n':
>>>>         break
>>>>
>>>> Jon
>>>>
>>>>
>>>> On Tue, Oct 14, 2014 at 10:42 AM, Benjamin Root <ben...@ou...>
>>>> wrote:
>>>>
>>>>> Also, you aren't updating "first" after the first call, so it is
>>>>> constantly making new axes and recalling imshow().
>>>>>
>>>>> Ben Root
>>>>>
>>>>> On Tue, Oct 14, 2014 at 10:41 AM, Benjamin Root <ben...@ou...>
>>>>> wrote:
>>>>>
>>>>>> What is happening is that you are not telling the image to redraw, so
>>>>>> you are only seeing it refresh for other reasons. Try adding a fig.draw()
>>>>>> call prior to the raw_input() call.
>>>>>>
>>>>>> Cheers!
>>>>>> Ben Root
>>>>>>
>>>>>> On Tue, Oct 14, 2014 at 10:03 AM, Slavin, Jonathan <
>>>>>> js...@cf...> wrote:
>>>>>>
>>>>>>> Hi all,
>>>>>>>
>>>>>>> In my work lately I have often wanted to browse through a series of
>>>>>>> images.  This means displaying the image(s), looking at it/them and then
>>>>>>> continuing.  I have coded this in a few different ways, but it is generally
>>>>>>> pretty slow -- which is to say that the image display takes more than a
>>>>>>> couple seconds (~4) after I tell it to continue to the next image.  I
>>>>>>> tested the loop without image display and it was a factor of ~80 times
>>>>>>> faster than it was with image display, so it's doesn't have anything to do
>>>>>>> with reading the images from disk.  My latest approach is basically:
>>>>>>> first = True
>>>>>>> fig = plt.figure()
>>>>>>> for file in imagefiles:
>>>>>>>     # read in image data (fits files)
>>>>>>>     if first:
>>>>>>>         ax = fig.add_suplot(1,1,1)
>>>>>>>         im = ax.imshow(image)
>>>>>>>     else:
>>>>>>>         im.set_data(image)
>>>>>>>     ans = raw_input('continue?')
>>>>>>>     if ans == 'n':
>>>>>>>         break
>>>>>>>
>>>>>>> Is there a more efficient way to do this?
>>>>>>>
>>>>>>> Regards,
>>>>>>> Jon
>>>>>>>
>>>>>>> --
>>>>>>> ________________________________________________________
>>>>>>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>>>>>>> js...@cf...       60 Garden Street, MS 83
>>>>>>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>>>>>>> fax: (617) 496-7577            USA
>>>>>>> ________________________________________________________
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> ------------------------------------------------------------------------------
>>>>>>> Comprehensive Server Monitoring with Site24x7.
>>>>>>> Monitor 10 servers for $9/Month.
>>>>>>> Get alerted through email, SMS, voice calls or mobile push
>>>>>>> notifications.
>>>>>>> Take corrective actions from your mobile device.
>>>>>>> http://p.sf.net/sfu/Zoho
>>>>>>> _______________________________________________
>>>>>>> Matplotlib-users mailing list
>>>>>>> Mat...@li...
>>>>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>>
>>>> --
>>>> ________________________________________________________
>>>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>>>> js...@cf...       60 Garden Street, MS 83
>>>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>>>> fax: (617) 496-7577            USA
>>>> ________________________________________________________
>>>>
>>>>
>>>
>>>
>>> --
>>> ________________________________________________________
>>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>>> js...@cf...       60 Garden Street, MS 83
>>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>>> fax: (617) 496-7577            USA
>>> ________________________________________________________
>>>
>>>
>>
>>
>> ------------------------------------------------------------------------------
>> Comprehensive Server Monitoring with Site24x7.
>> Monitor 10 servers for $9/Month.
>> Get alerted through email, SMS, voice calls or mobile push notifications.
>> Take corrective actions from your mobile device.
>> http://p.sf.net/sfu/Zoho
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>
>
> --
> *************************************
> Chris Beaumont
> Senior Software Engineer
> Harvard Center for Astrophysics
> 60 Garden Street, MS 42
> Cambridge, MA 02138
> chrisbeaumont.org
> *************************************
>



-- 
________________________________________________________
Jonathan D. Slavin                 Harvard-Smithsonian CfA
js...@cf...       60 Garden Street, MS 83
phone: (617) 496-7981       Cambridge, MA 02138-1516
fax: (617) 496-7577            USA
________________________________________________________

I am happy to announce that I have tagged a release candidate for
1.4.1.  This is a bug-fix release which fixes most of the bug that
popped up in 1.4.0 including:

 - setup.py does not die when freetype is not installed
 - reverts the changes to interactive plotting so `ion` will work as expected
 - sundry unicode fixes (looking up user folders, importing
seaborn/pandas/networkx with macosx backend
 - fixed boxplot regressions

The tarball is available from github, sourceforge and can be install via

   pip install matplotlib==1.4.1rc1

Tom



-- 
Thomas Caswell
tca...@gm...

I've found that, for big images, the *first* draw is very slow, due to the
intensity scaling of the image, which happens at full resolution. Panning
and zooming afterwards is fast because the intensity scaling is cached, but
changing the data array or updating the norm kwarg is slow again. I made
ModestImage (https://github.com/ChrisBeaumont/mpl-modest-image) to deal
with this -- it dynamically downsamples images to screen resolution. This
makes the first draw after updating the data or norm much faster, while
slowing down subsequent redraws. Perhaps this could help you out?

cheers,
chris

On Tue, Oct 14, 2014 at 12:08 PM, Benjamin Root <ben...@ou...> wrote:

> Only if there are multiple figures (plt.draw() operates on the current
> active figure, while fig.draw() explicitly operates upon that figure).
> Another possibility is that the bottleneck truly is the IO. Depending on
> exactly how fits work, it might be lazily loading data for you, so the test
> without the display of the images might not actually be loading any data
> into memory.
>
> Ben Root
>
> On Tue, Oct 14, 2014 at 11:22 AM, Slavin, Jonathan <
> js...@cf...> wrote:
>
>> Hmm.  I just saw that you suggest fig.draw().  Is there a difference with
>> plt.draw()?
>>
>> Jon
>>
>> On Tue, Oct 14, 2014 at 11:20 AM, Slavin, Jonathan <
>> js...@cf...> wrote:
>>
>>> Hi Ben,
>>>
>>> Sorry, in my little example, I left out a few things.  I do update first
>>> after the first call.  And I do call draw() after other calls.  So here is
>>> a more accurate representation of what I do:
>>>
>>> first = True
>>> fig = plt.figure()
>>> for file in files:
>>>     hdu = fits.open(file)
>>>     image = hdu[0].data
>>>     hdu.close()
>>>     if first:
>>>         ax = fig,add_subplot(1,1,1)
>>>         im = ax.imshow(image)
>>>         plt.show()
>>>         first = False
>>>     else:
>>>         im.set_data(image)
>>>         plt.draw()
>>>     ans = raw_input('continue?')
>>>     if ans == 'n':
>>>         break
>>>
>>> Jon
>>>
>>>
>>> On Tue, Oct 14, 2014 at 10:42 AM, Benjamin Root <ben...@ou...> wrote:
>>>
>>>> Also, you aren't updating "first" after the first call, so it is
>>>> constantly making new axes and recalling imshow().
>>>>
>>>> Ben Root
>>>>
>>>> On Tue, Oct 14, 2014 at 10:41 AM, Benjamin Root <ben...@ou...>
>>>> wrote:
>>>>
>>>>> What is happening is that you are not telling the image to redraw, so
>>>>> you are only seeing it refresh for other reasons. Try adding a fig.draw()
>>>>> call prior to the raw_input() call.
>>>>>
>>>>> Cheers!
>>>>> Ben Root
>>>>>
>>>>> On Tue, Oct 14, 2014 at 10:03 AM, Slavin, Jonathan <
>>>>> js...@cf...> wrote:
>>>>>
>>>>>> Hi all,
>>>>>>
>>>>>> In my work lately I have often wanted to browse through a series of
>>>>>> images.  This means displaying the image(s), looking at it/them and then
>>>>>> continuing.  I have coded this in a few different ways, but it is generally
>>>>>> pretty slow -- which is to say that the image display takes more than a
>>>>>> couple seconds (~4) after I tell it to continue to the next image.  I
>>>>>> tested the loop without image display and it was a factor of ~80 times
>>>>>> faster than it was with image display, so it's doesn't have anything to do
>>>>>> with reading the images from disk.  My latest approach is basically:
>>>>>> first = True
>>>>>> fig = plt.figure()
>>>>>> for file in imagefiles:
>>>>>>     # read in image data (fits files)
>>>>>>     if first:
>>>>>>         ax = fig.add_suplot(1,1,1)
>>>>>>         im = ax.imshow(image)
>>>>>>     else:
>>>>>>         im.set_data(image)
>>>>>>     ans = raw_input('continue?')
>>>>>>     if ans == 'n':
>>>>>>         break
>>>>>>
>>>>>> Is there a more efficient way to do this?
>>>>>>
>>>>>> Regards,
>>>>>> Jon
>>>>>>
>>>>>> --
>>>>>> ________________________________________________________
>>>>>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>>>>>> js...@cf...       60 Garden Street, MS 83
>>>>>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>>>>>> fax: (617) 496-7577            USA
>>>>>> ________________________________________________________
>>>>>>
>>>>>>
>>>>>>
>>>>>> ------------------------------------------------------------------------------
>>>>>> Comprehensive Server Monitoring with Site24x7.
>>>>>> Monitor 10 servers for $9/Month.
>>>>>> Get alerted through email, SMS, voice calls or mobile push
>>>>>> notifications.
>>>>>> Take corrective actions from your mobile device.
>>>>>> http://p.sf.net/sfu/Zoho
>>>>>> _______________________________________________
>>>>>> Matplotlib-users mailing list
>>>>>> Mat...@li...
>>>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>>
>>> --
>>> ________________________________________________________
>>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>>> js...@cf...       60 Garden Street, MS 83
>>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>>> fax: (617) 496-7577            USA
>>> ________________________________________________________
>>>
>>>
>>
>>
>> --
>> ________________________________________________________
>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>> js...@cf...       60 Garden Street, MS 83
>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>> fax: (617) 496-7577            USA
>> ________________________________________________________
>>
>>
>
>
> ------------------------------------------------------------------------------
> Comprehensive Server Monitoring with Site24x7.
> Monitor 10 servers for $9/Month.
> Get alerted through email, SMS, voice calls or mobile push notifications.
> Take corrective actions from your mobile device.
> http://p.sf.net/sfu/Zoho
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>


-- 
*************************************
Chris Beaumont
Senior Software Engineer
Harvard Center for Astrophysics
60 Garden Street, MS 42
Cambridge, MA 02138
chrisbeaumont.org
*************************************

Only if there are multiple figures (plt.draw() operates on the current
active figure, while fig.draw() explicitly operates upon that figure).
Another possibility is that the bottleneck truly is the IO. Depending on
exactly how fits work, it might be lazily loading data for you, so the test
without the display of the images might not actually be loading any data
into memory.

Ben Root

On Tue, Oct 14, 2014 at 11:22 AM, Slavin, Jonathan <js...@cf...>
wrote:

> Hmm.  I just saw that you suggest fig.draw().  Is there a difference with
> plt.draw()?
>
> Jon
>
> On Tue, Oct 14, 2014 at 11:20 AM, Slavin, Jonathan <
> js...@cf...> wrote:
>
>> Hi Ben,
>>
>> Sorry, in my little example, I left out a few things.  I do update first
>> after the first call.  And I do call draw() after other calls.  So here is
>> a more accurate representation of what I do:
>>
>> first = True
>> fig = plt.figure()
>> for file in files:
>>     hdu = fits.open(file)
>>     image = hdu[0].data
>>     hdu.close()
>>     if first:
>>         ax = fig,add_subplot(1,1,1)
>>         im = ax.imshow(image)
>>         plt.show()
>>         first = False
>>     else:
>>         im.set_data(image)
>>         plt.draw()
>>     ans = raw_input('continue?')
>>     if ans == 'n':
>>         break
>>
>> Jon
>>
>>
>> On Tue, Oct 14, 2014 at 10:42 AM, Benjamin Root <ben...@ou...> wrote:
>>
>>> Also, you aren't updating "first" after the first call, so it is
>>> constantly making new axes and recalling imshow().
>>>
>>> Ben Root
>>>
>>> On Tue, Oct 14, 2014 at 10:41 AM, Benjamin Root <ben...@ou...> wrote:
>>>
>>>> What is happening is that you are not telling the image to redraw, so
>>>> you are only seeing it refresh for other reasons. Try adding a fig.draw()
>>>> call prior to the raw_input() call.
>>>>
>>>> Cheers!
>>>> Ben Root
>>>>
>>>> On Tue, Oct 14, 2014 at 10:03 AM, Slavin, Jonathan <
>>>> js...@cf...> wrote:
>>>>
>>>>> Hi all,
>>>>>
>>>>> In my work lately I have often wanted to browse through a series of
>>>>> images.  This means displaying the image(s), looking at it/them and then
>>>>> continuing.  I have coded this in a few different ways, but it is generally
>>>>> pretty slow -- which is to say that the image display takes more than a
>>>>> couple seconds (~4) after I tell it to continue to the next image.  I
>>>>> tested the loop without image display and it was a factor of ~80 times
>>>>> faster than it was with image display, so it's doesn't have anything to do
>>>>> with reading the images from disk.  My latest approach is basically:
>>>>> first = True
>>>>> fig = plt.figure()
>>>>> for file in imagefiles:
>>>>>     # read in image data (fits files)
>>>>>     if first:
>>>>>         ax = fig.add_suplot(1,1,1)
>>>>>         im = ax.imshow(image)
>>>>>     else:
>>>>>         im.set_data(image)
>>>>>     ans = raw_input('continue?')
>>>>>     if ans == 'n':
>>>>>         break
>>>>>
>>>>> Is there a more efficient way to do this?
>>>>>
>>>>> Regards,
>>>>> Jon
>>>>>
>>>>> --
>>>>> ________________________________________________________
>>>>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>>>>> js...@cf...       60 Garden Street, MS 83
>>>>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>>>>> fax: (617) 496-7577            USA
>>>>> ________________________________________________________
>>>>>
>>>>>
>>>>>
>>>>> ------------------------------------------------------------------------------
>>>>> Comprehensive Server Monitoring with Site24x7.
>>>>> Monitor 10 servers for $9/Month.
>>>>> Get alerted through email, SMS, voice calls or mobile push
>>>>> notifications.
>>>>> Take corrective actions from your mobile device.
>>>>> http://p.sf.net/sfu/Zoho
>>>>> _______________________________________________
>>>>> Matplotlib-users mailing list
>>>>> Mat...@li...
>>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>>
>>>>>
>>>>
>>>
>>
>>
>> --
>> ________________________________________________________
>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>> js...@cf...       60 Garden Street, MS 83
>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>> fax: (617) 496-7577            USA
>> ________________________________________________________
>>
>>
>
>
> --
> ________________________________________________________
> Jonathan D. Slavin                 Harvard-Smithsonian CfA
> js...@cf...       60 Garden Street, MS 83
> phone: (617) 496-7981       Cambridge, MA 02138-1516
> fax: (617) 496-7577            USA
> ________________________________________________________
>
>

Hmm.  I just saw that you suggest fig.draw().  Is there a difference with
plt.draw()?

Jon

On Tue, Oct 14, 2014 at 11:20 AM, Slavin, Jonathan <js...@cf...>
wrote:

> Hi Ben,
>
> Sorry, in my little example, I left out a few things.  I do update first
> after the first call.  And I do call draw() after other calls.  So here is
> a more accurate representation of what I do:
>
> first = True
> fig = plt.figure()
> for file in files:
>     hdu = fits.open(file)
>     image = hdu[0].data
>     hdu.close()
>     if first:
>         ax = fig,add_subplot(1,1,1)
>         im = ax.imshow(image)
>         plt.show()
>         first = False
>     else:
>         im.set_data(image)
>         plt.draw()
>     ans = raw_input('continue?')
>     if ans == 'n':
>         break
>
> Jon
>
>
> On Tue, Oct 14, 2014 at 10:42 AM, Benjamin Root <ben...@ou...> wrote:
>
>> Also, you aren't updating "first" after the first call, so it is
>> constantly making new axes and recalling imshow().
>>
>> Ben Root
>>
>> On Tue, Oct 14, 2014 at 10:41 AM, Benjamin Root <ben...@ou...> wrote:
>>
>>> What is happening is that you are not telling the image to redraw, so
>>> you are only seeing it refresh for other reasons. Try adding a fig.draw()
>>> call prior to the raw_input() call.
>>>
>>> Cheers!
>>> Ben Root
>>>
>>> On Tue, Oct 14, 2014 at 10:03 AM, Slavin, Jonathan <
>>> js...@cf...> wrote:
>>>
>>>> Hi all,
>>>>
>>>> In my work lately I have often wanted to browse through a series of
>>>> images.  This means displaying the image(s), looking at it/them and then
>>>> continuing.  I have coded this in a few different ways, but it is generally
>>>> pretty slow -- which is to say that the image display takes more than a
>>>> couple seconds (~4) after I tell it to continue to the next image.  I
>>>> tested the loop without image display and it was a factor of ~80 times
>>>> faster than it was with image display, so it's doesn't have anything to do
>>>> with reading the images from disk.  My latest approach is basically:
>>>> first = True
>>>> fig = plt.figure()
>>>> for file in imagefiles:
>>>>     # read in image data (fits files)
>>>>     if first:
>>>>         ax = fig.add_suplot(1,1,1)
>>>>         im = ax.imshow(image)
>>>>     else:
>>>>         im.set_data(image)
>>>>     ans = raw_input('continue?')
>>>>     if ans == 'n':
>>>>         break
>>>>
>>>> Is there a more efficient way to do this?
>>>>
>>>> Regards,
>>>> Jon
>>>>
>>>> --
>>>> ________________________________________________________
>>>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>>>> js...@cf...       60 Garden Street, MS 83
>>>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>>>> fax: (617) 496-7577            USA
>>>> ________________________________________________________
>>>>
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>> Comprehensive Server Monitoring with Site24x7.
>>>> Monitor 10 servers for $9/Month.
>>>> Get alerted through email, SMS, voice calls or mobile push
>>>> notifications.
>>>> Take corrective actions from your mobile device.
>>>> http://p.sf.net/sfu/Zoho
>>>> _______________________________________________
>>>> Matplotlib-users mailing list
>>>> Mat...@li...
>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>
>>>>
>>>
>>
>
>
> --
> ________________________________________________________
> Jonathan D. Slavin                 Harvard-Smithsonian CfA
> js...@cf...       60 Garden Street, MS 83
> phone: (617) 496-7981       Cambridge, MA 02138-1516
> fax: (617) 496-7577            USA
> ________________________________________________________
>
>


-- 
________________________________________________________
Jonathan D. Slavin                 Harvard-Smithsonian CfA
js...@cf...       60 Garden Street, MS 83
phone: (617) 496-7981       Cambridge, MA 02138-1516
fax: (617) 496-7577            USA
________________________________________________________

Hi Ben,

Sorry, in my little example, I left out a few things.  I do update first
after the first call.  And I do call draw() after other calls.  So here is
a more accurate representation of what I do:

first = True
fig = plt.figure()
for file in files:
    hdu = fits.open(file)
    image = hdu[0].data
    hdu.close()
    if first:
        ax = fig,add_subplot(1,1,1)
        im = ax.imshow(image)
        plt.show()
        first = False
    else:
        im.set_data(image)
        plt.draw()
    ans = raw_input('continue?')
    if ans == 'n':
        break

Jon


On Tue, Oct 14, 2014 at 10:42 AM, Benjamin Root <ben...@ou...> wrote:

> Also, you aren't updating "first" after the first call, so it is
> constantly making new axes and recalling imshow().
>
> Ben Root
>
> On Tue, Oct 14, 2014 at 10:41 AM, Benjamin Root <ben...@ou...> wrote:
>
>> What is happening is that you are not telling the image to redraw, so you
>> are only seeing it refresh for other reasons. Try adding a fig.draw() call
>> prior to the raw_input() call.
>>
>> Cheers!
>> Ben Root
>>
>> On Tue, Oct 14, 2014 at 10:03 AM, Slavin, Jonathan <
>> js...@cf...> wrote:
>>
>>> Hi all,
>>>
>>> In my work lately I have often wanted to browse through a series of
>>> images.  This means displaying the image(s), looking at it/them and then
>>> continuing.  I have coded this in a few different ways, but it is generally
>>> pretty slow -- which is to say that the image display takes more than a
>>> couple seconds (~4) after I tell it to continue to the next image.  I
>>> tested the loop without image display and it was a factor of ~80 times
>>> faster than it was with image display, so it's doesn't have anything to do
>>> with reading the images from disk.  My latest approach is basically:
>>> first = True
>>> fig = plt.figure()
>>> for file in imagefiles:
>>>     # read in image data (fits files)
>>>     if first:
>>>         ax = fig.add_suplot(1,1,1)
>>>         im = ax.imshow(image)
>>>     else:
>>>         im.set_data(image)
>>>     ans = raw_input('continue?')
>>>     if ans == 'n':
>>>         break
>>>
>>> Is there a more efficient way to do this?
>>>
>>> Regards,
>>> Jon
>>>
>>> --
>>> ________________________________________________________
>>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>>> js...@cf...       60 Garden Street, MS 83
>>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>>> fax: (617) 496-7577            USA
>>> ________________________________________________________
>>>
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Comprehensive Server Monitoring with Site24x7.
>>> Monitor 10 servers for $9/Month.
>>> Get alerted through email, SMS, voice calls or mobile push notifications.
>>> Take corrective actions from your mobile device.
>>> http://p.sf.net/sfu/Zoho
>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>>
>>
>


-- 
________________________________________________________
Jonathan D. Slavin                 Harvard-Smithsonian CfA
js...@cf...       60 Garden Street, MS 83
phone: (617) 496-7981       Cambridge, MA 02138-1516
fax: (617) 496-7577            USA
________________________________________________________

Also, you aren't updating "first" after the first call, so it is constantly
making new axes and recalling imshow().

Ben Root

On Tue, Oct 14, 2014 at 10:41 AM, Benjamin Root <ben...@ou...> wrote:

> What is happening is that you are not telling the image to redraw, so you
> are only seeing it refresh for other reasons. Try adding a fig.draw() call
> prior to the raw_input() call.
>
> Cheers!
> Ben Root
>
> On Tue, Oct 14, 2014 at 10:03 AM, Slavin, Jonathan <
> js...@cf...> wrote:
>
>> Hi all,
>>
>> In my work lately I have often wanted to browse through a series of
>> images.  This means displaying the image(s), looking at it/them and then
>> continuing.  I have coded this in a few different ways, but it is generally
>> pretty slow -- which is to say that the image display takes more than a
>> couple seconds (~4) after I tell it to continue to the next image.  I
>> tested the loop without image display and it was a factor of ~80 times
>> faster than it was with image display, so it's doesn't have anything to do
>> with reading the images from disk.  My latest approach is basically:
>> first = True
>> fig = plt.figure()
>> for file in imagefiles:
>>     # read in image data (fits files)
>>     if first:
>>         ax = fig.add_suplot(1,1,1)
>>         im = ax.imshow(image)
>>     else:
>>         im.set_data(image)
>>     ans = raw_input('continue?')
>>     if ans == 'n':
>>         break
>>
>> Is there a more efficient way to do this?
>>
>> Regards,
>> Jon
>>
>> --
>> ________________________________________________________
>> Jonathan D. Slavin                 Harvard-Smithsonian CfA
>> js...@cf...       60 Garden Street, MS 83
>> phone: (617) 496-7981       Cambridge, MA 02138-1516
>> fax: (617) 496-7577            USA
>> ________________________________________________________
>>
>>
>>
>> ------------------------------------------------------------------------------
>> Comprehensive Server Monitoring with Site24x7.
>> Monitor 10 servers for $9/Month.
>> Get alerted through email, SMS, voice calls or mobile push notifications.
>> Take corrective actions from your mobile device.
>> http://p.sf.net/sfu/Zoho
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>

What is happening is that you are not telling the image to redraw, so you
are only seeing it refresh for other reasons. Try adding a fig.draw() call
prior to the raw_input() call.

Cheers!
Ben Root

On Tue, Oct 14, 2014 at 10:03 AM, Slavin, Jonathan <js...@cf...>
wrote:

> Hi all,
>
> In my work lately I have often wanted to browse through a series of
> images.  This means displaying the image(s), looking at it/them and then
> continuing.  I have coded this in a few different ways, but it is generally
> pretty slow -- which is to say that the image display takes more than a
> couple seconds (~4) after I tell it to continue to the next image.  I
> tested the loop without image display and it was a factor of ~80 times
> faster than it was with image display, so it's doesn't have anything to do
> with reading the images from disk.  My latest approach is basically:
> first = True
> fig = plt.figure()
> for file in imagefiles:
>     # read in image data (fits files)
>     if first:
>         ax = fig.add_suplot(1,1,1)
>         im = ax.imshow(image)
>     else:
>         im.set_data(image)
>     ans = raw_input('continue?')
>     if ans == 'n':
>         break
>
> Is there a more efficient way to do this?
>
> Regards,
> Jon
>
> --
> ________________________________________________________
> Jonathan D. Slavin                 Harvard-Smithsonian CfA
> js...@cf...       60 Garden Street, MS 83
> phone: (617) 496-7981       Cambridge, MA 02138-1516
> fax: (617) 496-7577            USA
> ________________________________________________________
>
>
>
> ------------------------------------------------------------------------------
> Comprehensive Server Monitoring with Site24x7.
> Monitor 10 servers for $9/Month.
> Get alerted through email, SMS, voice calls or mobile push notifications.
> Take corrective actions from your mobile device.
> http://p.sf.net/sfu/Zoho
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Hi all,

In my work lately I have often wanted to browse through a series of
images.  This means displaying the image(s), looking at it/them and then
continuing.  I have coded this in a few different ways, but it is generally
pretty slow -- which is to say that the image display takes more than a
couple seconds (~4) after I tell it to continue to the next image.  I
tested the loop without image display and it was a factor of ~80 times
faster than it was with image display, so it's doesn't have anything to do
with reading the images from disk.  My latest approach is basically:
first = True
fig = plt.figure()
for file in imagefiles:
    # read in image data (fits files)
    if first:
        ax = fig.add_suplot(1,1,1)
        im = ax.imshow(image)
    else:
        im.set_data(image)
    ans = raw_input('continue?')
    if ans == 'n':
        break

Is there a more efficient way to do this?

Regards,
Jon

-- 
________________________________________________________
Jonathan D. Slavin                 Harvard-Smithsonian CfA
js...@cf...       60 Garden Street, MS 83
phone: (617) 496-7981       Cambridge, MA 02138-1516
fax: (617) 496-7577            USA
________________________________________________________