[Matplotlib-users] matplotlib figure serialization

2010-03-24 Thread Rich Krauter
Hello,

I am a relatively new user of matplotlib; thank you to the matplotlib team
for this excellent package.

I have a question about serializing matplotlib figures.  I have searched for
serialization options for matplotlib figures but have not found much
information.  I am interested to hear about serialization use cases and the
approaches others use in these cases.

Here is the reason I am asking:

My use case for serialization is that I want to build a CouchDB database of
matplotlib figures.  The database could be accessed from a web application
(in my case I want to build a django app to create, edit and manage figures)
or desktop gui, or whatever.  For storage of the figures in CouchDB, I am
working on JSON representations of matplotlib figures.  The JSON could be
run through simple python functions to regenerate the matplotlib figures.  I
have very simple working examples, but to more completely test out this
approach I would attempt to recreate the plots in the matplotlib gallery
using JSON representations and a small set of (hopefully) very simple python
functions which would process the JSON markup.

Before I get too far, I wanted to see what others have done for similar use
cases, make sure I am not missing existing approaches, etc.  I am getting
ahead of myself now, but if there is broader interest in this approach, and
no other better solutions exist, I would set up a project on Google Code or
some other site to work on this.

Your feedback is very much appreciated.

Thanks!

Rich
--
Download Intel#174; Parallel Studio Eval
Try the new software tools for yourself. Speed compiling, find bugs
proactively, and fine-tune applications for parallel performance.
See why Intel Parallel Studio got high marks during beta.
http://p.sf.net/sfu/intel-sw-dev___
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users


Re: [Matplotlib-users] matplotlib figure serialization

2010-03-24 Thread Rich Krauter
 Rich Krauter wrote:

 Hello,

 I am a relatively new user of matplotlib; thank you to the matplotlib team 
 for this excellent package.
 I have a question about serializing matplotlib figures.  I have searched for 
 serialization options for matplotlib figures but have not found much 
 information.  I am interested to hear about serialization use cases and the 
 approaches others use in these cases.

 Here is the reason I am asking:

 My use case for serialization is that I want to build a CouchDB database of 
 matplotlib figures.  The database could be accessed from a web application 
 (in my case I want to build a django app to create, edit and manage figures) 
 or desktop gui, or whatever.  For storage of the figures in CouchDB, I am 
 working on JSON representations of matplotlib figures.  The JSON could be 
 run through simple python functions to regenerate the matplotlib figures.  I 
 have very simple working examples, but to more completely test out this 
 approach I would attempt to recreate the plots in the matplotlib gallery 
 using JSON representations and a small set of (hopefully) very simple python 
 functions which would process the JSON markup.

 Before I get too far, I wanted to see what others have done for similar use 
 cases, make sure I am not missing existing approaches, etc.  I am getting 
 ahead of myself now, but if there is broader interest in this approach, and 
 no other better solutions exist, I would set up a project on Google Code or 
 some other site to work on this.

On Wed, Mar 24, 2010 at 1:15 PM, Michael Droettboom md...@stsci.edu wrote:

 What is the advantage of JSON (is this specific case) over Python source 
 code?  matplotlib is designed around it and it's more flexible.  Unless 
 you're planning on automatically manipulating the JSON, I don't see why you 
 wouldn't just use Python source.

 Mike


Mike,

I don't know that there is much of a benefit to JSON outside of my use
case or similar use cases.  I want to manipulate the JSON
representation of a figure within a javascript-based web interface to
provide dynamic plotting through a web page.  I also want to be able
to store and query JSON representations using CouchDB.

I am probably not exactly clear on what you mean by using python
source to represent a figure.  Is there a standard agreed upon way to
do this?  I do have python source code representations of figures.
i.e. I have dict representations of matplotlib figures.  The dicts
have a required internal structure.  I feed the dict to a function
which regenerates the figure graphic from that structure.  If I want
to update the plot, I just change the contents of the dict data
structure representing the plot, not the source code that is used to
generate the figure. If I instead had a JSON object representation of
a figure, I would convert it to a python dict and use the same
function as before to produce the figure.

I haven't found much discussion about serialization of matplotlib
figures, but I probably have not searched well enough, or maybe it is
not a high interest topic.  The discussion I have found seems to
suggest using the script you used to create the figure as the
serialization of that figure. To modify the figure, you modify the
script an rerun it.  What I would like to have (and what I have some
very preliminary examples for) are versioned data structures that can
be converted to matplotlib figures without modifying any python source
code (other than the structured representation of the figure itself.)
 However, I don't know how much the matplotlib API changes, and an
approach like this may be very sensitive to those changes.

Rich

--
Download Intel#174; Parallel Studio Eval
Try the new software tools for yourself. Speed compiling, find bugs
proactively, and fine-tune applications for parallel performance.
See why Intel Parallel Studio got high marks during beta.
http://p.sf.net/sfu/intel-sw-dev
___
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users


Re: [Matplotlib-users] matplotlib figure serialization

2010-03-24 Thread Rich Krauter
On Wed, Mar 24, 2010 at 1:37 PM, Chris Barker chris.bar...@noaa.gov wrote:
 Michael Droettboom wrote:
 What is the advantage of JSON (is this specific case) over Python source
 code?  matplotlib is designed around it and it's more flexible.  Unless
 you're planning on automatically manipulating the JSON, I don't see why
 you wouldn't just use Python source.

 Indeed. There have been a few threads about this topic, and I think the
 consensus is that the way to auto-generate figures is with python.

 I don't think that there is any technical reason that one couldn't
 create a serialized version of an MPL figure in XML, or JSON, (or, for
 that matter, a python data structure), but it would be a fair bit of
 effort to write the code, and I don't think you'd get any real advantage
 over just using scripts -- you need a python script to create a figure
 in the first place, why not serialize that?

Chris,

To answer your question, because I can't think of a way to build a
web-based user interface to let users make incremental changes to the
plot produced by that script. Or some other plot that was generated
using a different script.

ISTM if I have a defined serialization structure (whether it be in
XML, JSON, or a python data structure) I can more easily build a
web-based user interface for manipulating that structure.  Below is an
example figure structured as a python dict and a rendering function.
Not sure if this clarifies what I am trying to do ...


import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt


plot = {
'metadata': {
'description': 'This is a sample plot representation',
'matplotlib_version': '0.99.0',
'author': 'RMK',
'last_updated': [2010, 3, 24, 13, 25, 0],
'type': 'lineplot'
},

'figure':

{'methods':
[
  ['set_size_inches', [10,4], {} ]
]
},

'axes':

{
121:
{'datasets':[
{
 'data': [ [1,2,3], [4,5,6] ],
 'options': {'linewidth':4, 'label': 'Source 1'},
},

{

 'data': [ [1,2,3], [12,13,14] ],
 'options': {'linewidth':4, 'label': 'Source 2',
 'marker':'*', 'visible': True},

}
],

'methods': [
 ['set_xlabel', [Testing ...], {} ],
 ['legend',  [], {} ]
   ]
},

122:
{ 'datasets': [
{
 'data': [ [1,2,3], [7,8,9] ],
 'options':{'linewidth':4, 'label': 'Source 3'},

}

],
'methods': [
['set_xlabel', [Label ...], {} ],
['legend', [], {} ]
   ]

}
}
}

def generate(plot,figname):

fig = plt.figure()

methods = plot['figure']['methods']
for method, args, kwds in methods:
getattr(fig, method)(*args, **kwds)

for axes in plot['axes']:
ax = plt.subplot(axes)

datasets = plot['axes'][axes]['datasets']

for dataset in datasets:
plt.plot(*(dataset['data']), **(dataset['options']))

for method, args, kwds in plot['axes'][axes]['methods']:
getattr(ax, method)(*args, **kwds)

plt.savefig(figname)


if __name__ == '__main__':
generate(plot, 'junk.png')


Rich

--
Download Intel#174; Parallel Studio Eval
Try the new software tools for yourself. Speed compiling, find bugs
proactively, and fine-tune applications for parallel performance.
See why Intel Parallel Studio got high marks during beta.
http://p.sf.net/sfu/intel-sw-dev
___
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users


Re: [Matplotlib-users] matplotlib figure serialization

2010-03-24 Thread Rich Krauter
On Wed, Mar 24, 2010 at 4:19 PM, Michael Droettboom md...@stsci.edu wrote:
 Rich Krauter wrote:

 Rich Krauter wrote:


 Hello,

 I am a relatively new user of matplotlib; thank you to the matplotlib
 team for this excellent package.
 I have a question about serializing matplotlib figures.  I have searched
 for serialization options for matplotlib figures but have not found much
 information.  I am interested to hear about serialization use cases and the
 approaches others use in these cases.

 Here is the reason I am asking:

 My use case for serialization is that I want to build a CouchDB database
 of matplotlib figures.  The database could be accessed from a web
 application (in my case I want to build a django app to create, edit and
 manage figures) or desktop gui, or whatever.  For storage of the figures in
 CouchDB, I am working on JSON representations of matplotlib figures.  The
 JSON could be run through simple python functions to regenerate the
 matplotlib figures.  I have very simple working examples, but to more
 completely test out this approach I would attempt to recreate the plots in
 the matplotlib gallery using JSON representations and a small set of
 (hopefully) very simple python functions which would process the JSON
 markup.

 Before I get too far, I wanted to see what others have done for similar
 use cases, make sure I am not missing existing approaches, etc.  I am
 getting ahead of myself now, but if there is broader interest in this
 approach, and no other better solutions exist, I would set up a project on
 Google Code or some other site to work on this.


 On Wed, Mar 24, 2010 at 1:15 PM, Michael Droettboom md...@stsci.edu
 wrote:


 What is the advantage of JSON (is this specific case) over Python source
 code?  matplotlib is designed around it and it's more flexible.  Unless
 you're planning on automatically manipulating the JSON, I don't see why you
 wouldn't just use Python source.

 Mike



 Mike,

 I don't know that there is much of a benefit to JSON outside of my use
 case or similar use cases.  I want to manipulate the JSON
 representation of a figure within a javascript-based web interface to
 provide dynamic plotting through a web page.  I also want to be able
 to store and query JSON representations using CouchDB.

 I am probably not exactly clear on what you mean by using python
 source to represent a figure.  Is there a standard agreed upon way to
 do this?

 In general, most matplotlib users write Python scripts to generate their
 plots.  These scripts usually read in data from an external file in any
 number of formats (the format tends to be domain-specific, but matplotlib
 provides support for a number of CSV formats, Numpy itself supports a number
 of ways of reading arrays etc.)  matplotlib tends to be agnostic about data
 (as long as you can convert it to a Numpy array somehow, it's happy), but
 has a clearly defined API for plot types and styles.

  I do have python source code representations of figures.
 i.e. I have dict representations of matplotlib figures.  The dicts
 have a required internal structure.  I feed the dict to a function
 which regenerates the figure graphic from that structure.  If I want
 to update the plot, I just change the contents of the dict data
 structure representing the plot, not the source code that is used to
 generate the figure. If I instead had a JSON object representation of
 a figure, I would convert it to a python dict and use the same
 function as before to produce the figure.


 I guess I have trouble seeing why a dictionary representation which is then
 interpreted to convert it to function calls is better than just making the
 function calls directly.  That's the interface to matplotlib that is known
 and tested.


Here are my reasons why a structured representation (dict, JSON, XML,
...)  is useful:

- I want to access the same plot representation through both python
and through javascript.  I need to access it in python to run MPL and
create plot images, and I want to use javascript to build the user
interface.

- I want to separate the plot content from the plot generation.   I
can serialize a data structure containing plot contents more easily
than I can record the commands a user might call to generate a plot.
The content of the plot is not python specific, only the generation of
the MPL plot is.  I need to be able to serialize the content to
support later modifications.



 The only use case I can imagine where a dictionary might be preferable would
 be if an external tool needs to read in the dictionary, modify it and spit
 it back out.  Reading arbitrary Python code is of course extremely hairy,
 whereas the JSON dictionary could be defined to be a more limited and
 manageable subset.  Another possible advantage may be security related -- if
 you need to run untrusted plot code, you certainly don't want to be running
 untrusted Python code.

 I haven't found much discussion about serialization of matplotlib