matplotlib-users — Discussion related to using matplotlib

[Matplotlib-users] Tabbed backend

[Federico A. <ari...@gm...>]

Hi I just wanted to let you know that I did some work on tkinter to have a
tabbed backend,
It is in early stages but "it works"
If you want to give it a try it is available on
https://github.com/fariza/MPL-Experimental-Backend

Let me know if you have any comments.

Cheers
Federico

-- 
Y yo que culpa tengo de que ellas se crean todo lo que yo les digo?

-- Antonio Alducin --

Re: [Matplotlib-users] "N" parameter of LinearSegmentedColormap

[TP <par...@fr...>]

On Monday, November 26, 2012 14:10:31 Eric Firing wrote:
> But how many colors can you actually distinguish on the screen, or in a
> plot?  My impression is that the problem is not lack of colors, but
> rather mapping to the color you want. There is no reason that having a
> value in your *data* of 1e10 has to affect how numbers in your data over
> a "normal" range are mapped.
> 
> You are trying to illustrate the problem with an example using 3 colors,
> so how can the number of colors in the colormap be the fundamental
> limitation?

Ok, I understand.
I think that my linear interpolation code has to somewhat be written in a norm 
instead.
At some time, I have looked at examples on Matplotlib website, and at the code 
of pyshared/matplotlib/colors.py, but without having the "flash" to write the 
norm. The next time I will try to write a norm instead (I will put the code 
here of course).

TP

Re: [Matplotlib-users] "N" parameter of LinearSegmentedColormap

[Eric F. <ef...@ha...>]

On 2012/11/26 12:18 PM, TP wrote:
> On Monday, November 26, 2012 12:06:40 Eric Firing wrote:
>> I'm glad you found a solution, but my sense is that the problem is that
>> you are trying to make the colormap do the work of the norm.  The
>> colormap is just a set of discrete colors, with a linear mapping to the
>> 0-1 scale (apart from the special under, over, and invalid values).  The
>> norm is for mapping your data to those colors, however you like, by
>> mapping your data to the 0-1 range (again with possible under, over, and
>> invalid values).  Did you consider making a custom norm instead of
>> modifying the colormap?
>
> Yes, I did.
> The problem with the default colormap is that it has not enough colors. I have
> found (I may be wrong) that no norm can change this state of affair. If you are
> able to find a norm to make my example work, i.e. to obtain the middle point in
> blue when large_value is for example 1e10, I am interested.

But how many colors can you actually distinguish on the screen, or in a 
plot?  My impression is that the problem is not lack of colors, but 
rather mapping to the color you want. There is no reason that having a 
value in your *data* of 1e10 has to affect how numbers in your data over 
a "normal" range are mapped.

You are trying to illustrate the problem with an example using 3 colors, 
so how can the number of colors in the colormap be the fundamental 
limitation?

Eric

>
> TP
>
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Re: [Matplotlib-users] "N" parameter of LinearSegmentedColormap

[TP <par...@fr...>]

On Monday, November 26, 2012 12:06:40 Eric Firing wrote:
> I'm glad you found a solution, but my sense is that the problem is that
> you are trying to make the colormap do the work of the norm.  The
> colormap is just a set of discrete colors, with a linear mapping to the
> 0-1 scale (apart from the special under, over, and invalid values).  The
> norm is for mapping your data to those colors, however you like, by
> mapping your data to the 0-1 range (again with possible under, over, and
> invalid values).  Did you consider making a custom norm instead of
> modifying the colormap?

Yes, I did.
The problem with the default colormap is that it has not enough colors. I have 
found (I may be wrong) that no norm can change this state of affair. If you are 
able to find a norm to make my example work, i.e. to obtain the middle point in 
blue when large_value is for example 1e10, I am interested.

TP

Re: [Matplotlib-users] matplot3d: add_collection3d: Turn off baseline?

[Benjamin R. <ben...@ou...>]

On Tue, Nov 20, 2012 at 8:12 PM, Stephen Gibson
<Ste...@an...>wrote:

> Ok. Adding an NaN as the last data point did not help.
>
> However, I notice that the return path is two segments that go through
> (0,0).
>
> i.e. the baseline (or return) path may actually start/finish at (0,0)
>
> The attached image shows my data offset in y-direction by +1. The end
> points
> have been set to y=0.5.  The baseline (or return path) is the line segment
> that
> starts at the first data point, passes through (x=0,y=0), and ends at the
> last
> data point.
>
> Steve.
>
>
Actually, this might be related to a bug that was pointed out to me a while
back that I just could not figure out.  Having this example might help in
narrowing down the cause.  Essentially, the (0,0) vertex was being added
even when it shouldn't have been.  The key difference in this example is
that zdir='y' is used, which causes the (0,0) vertex to refer to the x,z
coordinate.  Interesting...

I will have to investigate further.

Ben Root

Re: [Matplotlib-users] "N" parameter of LinearSegmentedColormap

[Eric F. <ef...@ha...>]

On 2012/11/26 11:37 AM, TP wrote:
> On Thursday, November 22, 2012 23:51:08 TP wrote:
>> Thus it seems to me that my dummy example given in the previous post covers
>> exactly the problem encountered in my real-world imshow function.
>>
>> Is there a memory-efficient workaround in my dummy example (instead of
>> increasing N)?
>
> I have modified LinearSegmentedColormap so as to solve my problem. The
> difference is that I do not create an huge array in my test case, but instead I
> interpolate linearly in the colormap. This is a quick and dirty code that
> does work in my case, but which does not deal with all cases (no management of
> transparency, no discontinuity in the colormap, etc.)

I'm glad you found a solution, but my sense is that the problem is that 
you are trying to make the colormap do the work of the norm.  The 
colormap is just a set of discrete colors, with a linear mapping to the 
0-1 scale (apart from the special under, over, and invalid values).  The 
norm is for mapping your data to those colors, however you like, by 
mapping your data to the 0-1 range (again with possible under, over, and 
invalid values).  Did you consider making a custom norm instead of 
modifying the colormap?

Eric

>
> #####################
> from __future__ import division
> from pylab import *
> from matplotlib.colors import LinearSegmentedColormap
> from matplotlib.collections import CircleCollection
>
> from scipy.interpolate import interp1d
>
>
> class ContinuousLinearSegmentedColormap( LinearSegmentedColormap ):
>
>      def __init__(self, name, segmentdata, gamma=1.0):
>
>          LinearSegmentedColormap.__init__( self
>                  , name, segmentdata, gamma = gamma )
>
>      def _init(self):
>
>          self.N = len( self._segmentdata['red'] )
>          self._lut = np.ones((self.N, 5), np.float)
>          for i in range( self.N ):
>              self._lut[i, 0] = self._segmentdata['red'][i][0]
>              # 2 because I do not manage discontinuities in color
>              self._lut[i, 1] = self._segmentdata['red'][i][2]
>              self._lut[i, 2] = self._segmentdata['green'][i][2]
>              self._lut[i, 3] = self._segmentdata['blue'][i][2]
>
>          self._isinit = True
>
>
>      def __call__(self, X, alpha=None, bytes=False):
>
>          if not self._isinit: self._init()
>          mask_bad = None
>          if not cbook.iterable(X):
>              vtype = 'scalar'
>              xa = np.array([X])
>          else:
>              vtype = 'array'
>              xma = ma.array(X, copy=False)
>              mask_bad = xma.mask
>              xa = xma.data.copy()   # Copy here to avoid side effects.
>              del xma
>
>          lut = self._lut.copy()
>          rgba = np.empty(shape=xa.shape+(4,), dtype=lut.dtype)
>
>          # We construct interpolation functions.
>          fred = interp1d( lut[:,0], lut[:,1])
>          fgreen = interp1d( lut[:,0], lut[:,2])
>          fblue = interp1d( lut[:,0], lut[:,3])
>
>          rgba[:,3] = 1 # alpha=1 for the time being
>          for i in range( xa.shape[0] ):
>              rgba[i,0] = fred( xa[i] )
>              rgba[i,1] = fgreen( xa[i] )
>              rgba[i,2] = fblue( xa[i] )
>
>          if vtype == 'scalar':
>              rgba = tuple(rgba[0,:])
>          return rgba
>
>
> ioff()
>
>
> large_value = 257 # blue above this value
> large_value = 258 # black above this value
> large_value = 1e8
>
> cdict = { 'blue': [(0.0, 0.0, 0.0)
>                      , (2*1/large_value, 1, 1)
>                      , (1.0, 1.0, 1.0)]
>                      ,  'green': [(0.0, 0.0, 0.0)
>                          , (2*1/large_value, 0, 0)
>                          , (1.0, 1.0, 1.0)]
>                      , 'red': [(0.0, 0.0, 0.0)
>                              , (2*1/large_value, 0, 0)
>                              , (1.0, 1.0, 1.0)] }
>
> measures= array( [[ 0.2,   0.3,   0],
>         [  0.3,   0.4,   2],
>         [  0.5,   0.6,   large_value]] )
>
> cmap = ContinuousLinearSegmentedColormap( "cmap foobar"
>          , cdict
>          )
>
> fig = figure()
> axes = fig.add_subplot(111)
> ec = CircleCollection( [80]
>          , offsets = measures[:,:2]
>          , transOffset = axes.transData
>          )
>
> ec.set_array( measures[:,2] )
> ec.set_cmap( cmap )
> axes.add_collection( ec )
>
> show()
> #####################
>
> ------------------------------------------------------------------------------
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Re: [Matplotlib-users] "N" parameter of LinearSegmentedColormap

[TP <par...@fr...>]

On Thursday, November 22, 2012 23:51:08 TP wrote:
> Thus it seems to me that my dummy example given in the previous post covers
> exactly the problem encountered in my real-world imshow function.
> 
> Is there a memory-efficient workaround in my dummy example (instead of
> increasing N)?

I have modified LinearSegmentedColormap so as to solve my problem. The 
difference is that I do not create an huge array in my test case, but instead I 
interpolate linearly in the colormap. This is a quick and dirty code that 
does work in my case, but which does not deal with all cases (no management of 
transparency, no discontinuity in the colormap, etc.)

#####################
from __future__ import division
from pylab import *
from matplotlib.colors import LinearSegmentedColormap
from matplotlib.collections import CircleCollection

from scipy.interpolate import interp1d


class ContinuousLinearSegmentedColormap( LinearSegmentedColormap ):

    def __init__(self, name, segmentdata, gamma=1.0):

        LinearSegmentedColormap.__init__( self
                , name, segmentdata, gamma = gamma )

    def _init(self):

        self.N = len( self._segmentdata['red'] )
        self._lut = np.ones((self.N, 5), np.float)
        for i in range( self.N ):
            self._lut[i, 0] = self._segmentdata['red'][i][0]
            # 2 because I do not manage discontinuities in color
            self._lut[i, 1] = self._segmentdata['red'][i][2]
            self._lut[i, 2] = self._segmentdata['green'][i][2]
            self._lut[i, 3] = self._segmentdata['blue'][i][2]

        self._isinit = True


    def __call__(self, X, alpha=None, bytes=False):

        if not self._isinit: self._init()
        mask_bad = None
        if not cbook.iterable(X):
            vtype = 'scalar'
            xa = np.array([X])
        else:
            vtype = 'array'
            xma = ma.array(X, copy=False)
            mask_bad = xma.mask
            xa = xma.data.copy()   # Copy here to avoid side effects.
            del xma

        lut = self._lut.copy()
        rgba = np.empty(shape=xa.shape+(4,), dtype=lut.dtype)

        # We construct interpolation functions.
        fred = interp1d( lut[:,0], lut[:,1])
        fgreen = interp1d( lut[:,0], lut[:,2])
        fblue = interp1d( lut[:,0], lut[:,3])

        rgba[:,3] = 1 # alpha=1 for the time being
        for i in range( xa.shape[0] ):
            rgba[i,0] = fred( xa[i] )
            rgba[i,1] = fgreen( xa[i] )
            rgba[i,2] = fblue( xa[i] )

        if vtype == 'scalar':
            rgba = tuple(rgba[0,:])
        return rgba


ioff()


large_value = 257 # blue above this value
large_value = 258 # black above this value
large_value = 1e8

cdict = { 'blue': [(0.0, 0.0, 0.0)
                    , (2*1/large_value, 1, 1)
                    , (1.0, 1.0, 1.0)]
                    ,  'green': [(0.0, 0.0, 0.0)
                        , (2*1/large_value, 0, 0)
                        , (1.0, 1.0, 1.0)]
                    , 'red': [(0.0, 0.0, 0.0)
                            , (2*1/large_value, 0, 0)
                            , (1.0, 1.0, 1.0)] }

measures= array( [[ 0.2,   0.3,   0],
       [  0.3,   0.4,   2],
       [  0.5,   0.6,   large_value]] )

cmap = ContinuousLinearSegmentedColormap( "cmap foobar"
        , cdict
        )

fig = figure()
axes = fig.add_subplot(111)
ec = CircleCollection( [80]
        , offsets = measures[:,:2]
        , transOffset = axes.transData
        )

ec.set_array( measures[:,2] )
ec.set_cmap( cmap )
axes.add_collection( ec )

show()
#####################

Re: [Matplotlib-users] Why is pip not mentioned in the Installation Documentation?

[Russell E. O. <ro...@uw...>]

In article <955...@gm...>,
 Ludwig Schwardt 
 <lud...@gm...> wrote:

> Pip works beautifully on the Mac since Lion, once you install pkg-config. 
> This allows matplotlib to pick up the dependencies from the system (i.e. 
> libpng, libfreetype and zlib)....

I had not heard of pkg-config before. It looks very useful.

>...
> [1] For me the only downside of the installer is the use of Python.org Python 
> instead of the default "system" Python, as the latter makes more sense to me 
> for a standard installation (and avoids having multiple Pythons on your 
> system, which is a Good Thing). Python.org Python used to be a mandatory 
> install on older Mac systems such as Tiger / 10.3, but this is no longer a 
> compelling argument for me on newer systems.

Simplicity is nice, and it's a shame there are so many 3rd party 
versions of python now (python.org, Enthought, ActiveState).

Nonetheless, there are some good reasons for avoiding system python, 
including:
- Apple rarely updates system python, so one does not get bug fixes
- If the operating system uses python for anything then it's safest to 
leave it alone

Regards,

-- Russell

Re: [Matplotlib-users] svg/image output

[Benjamin R. <ben...@ou...>]

On Wed, Nov 21, 2012 at 6:00 PM, Jeffrey Melloy <jm...@gm...> wrote:

> I'm currently using matplotlib to generate .PNG files, and the
> javascript library flot to do point hover & zooming on the same data
> (after click through).  Flot is starting to show its age, and I'd like
> a little more control.
>
> I'd like to get to only one library generating graphs, so I only have
> to change code in one place.   d3.js looks interesting & dynamic, but
> I don't want to just replace one javascript library with another. I
> may be able to use d3.js to generate the thumbnails.
>
> My other option is to use matplotlib for the clicking & zooming -- If
> i use it to generate an svg and then do clicking, zooming, etc on the
> svg, am I in for a world of hurt? I see an html5 backend, but that
> hasn't been updated in a year.  I also see the svg_histogram example,
> but that didn't work cleanly for me.
>
> Thanks,
> Jeff
>
>
You might be interested in this experimental branch:

https://github.com/matplotlib/matplotlib/pull/1426

Cheers!
Ben Root

[Matplotlib-users] matplotlib in Cocoa using Xcode

[Helmut S. <tan...@gm...>]

Hi,
I wanted to share a little experiment of mine with you to see what you
think and whether there are other ways (or better ways) to do that sort of
thing.

Here is my blog post on embedding matplotlib plots in Cocoa applications:
http://www.streylab.com/blog/2012/11/22/matplotlib-running-in-cocoa-under-xcode.html

Let me know what you think.

Helmut Strey

Re: [Matplotlib-users] "N" parameter of LinearSegmentedColormap

[TP <par...@fr...>]

On Monday, November 19, 2012 13:53:21 Eric Firing wrote:

> It is not entirely clear to me what you are trying to do, but it sounds
> like increasing N is not the right way to do it. Three things might help
> you find a better way:
> 
> 1) The colormap is intended to work with a norm that handles the
> translation from your data numbers to the 0-1.0 range used to select
> values from the colormap (with exceptions--see below).  You can choose a
> non-default norm, you can write your own, or you can set the parameters
> (vmin, vmax) of the standard linear norm.
> 
> 2) By creating a colormap and calling its set_under, set_over, and
> set_invalid methods, you can control the colors assigned to data values
> that your norm maps respectively to negative numbers, numbers greater
> than 1, and masked values.  See
> http://matplotlib.org/examples/pylab_examples/contourf_demo.html for an
> example of using set_under and set_over.  See
> http://matplotlib.org/examples/pylab_examples/image_masked.html for
> another example, and for an example of controlling the norm parameters
> or using an alternative norm.
> 
> 3) It is also possible to index directly into the colormap if you use a
> norm that returns an integer data type.  An example of such is the
> BoundaryNorm.
> http://matplotlib.org/examples/pylab_examples/multicolored_line.html
> 
> If all you need is a single assignment of a color to a "large value",
> then using the set_over method will take care of it.
> 
> Eric

Thanks for your answer.

My goal is to keep the correct color, i.e. blue, for the point located at 
(x=0.3, y=0.4), even if there are very large values of z on the plot. As I 
said, increasing N is not satisfying because it leads to large amounts of 
memory to be used. But for the time being, this is the only solution I have 
found.

I cannot use the set_over method to do that, because the "large  value" is not 
the only one. Indeed, what I want to do is an imshow plot, with a colorbar 
containing three different linear portions:
* one portion for the values of z contained between the minimum and maximum 
value of z in some measure points.
* one portion for the values of z below the minimum z in the measure points.
* one portion for the values of z above the maximum z in the measure points.

My problem is that I may have very large values on the plot in the range below 
or above the measures z. So I have exactly the problem shown in my dummy 
example of the previous post: all my measures have the same color, although 
they should not, because I have created a colormap that should handle this 
situation (three different linear portions in the map). The only workaround I 
have found is to increase the value of N, but in my case it has to be very 
large, such that the plot is very slow to display, or even can ask for huge 
amounts of memory.

Thus it seems to me that my dummy example given in the previous post covers 
exactly the problem encountered in my real-world imshow function.

Is there a memory-efficient workaround in my dummy example (instead of 
increasing N)?

Thanks,

TP

Re: [Matplotlib-users] Is there a way to create a plot and call show() so as not to use the main Qt loop?

[Goyo <goy...@gm...>]

2012/11/4 Brickle Macho <bri...@gm...>:
> [...] When I show() a plot form within a Qt application I get the
> following message printed on the console:
>
> QCoreApplication::exec: The event loop is already running
>
> I think I understand the error, obviously the application I calling form
> control the even loop.  I suppose I need to somehow supply a parent
> window to pylab plot or the show() function.   Is there a way to create
> a plot and show so as not to use the main loop?

Do not use show() in a GUI application.
If you have a FigureCanvas instance embedded in your app, call its
draw() method.
If you use pyplot.figure() to create a matplotlib window from your
app, call pyplot.draw().

Goyo

Re: [Matplotlib-users] bug with empty values & dates

[Goyo <goy...@gm...>]

2012/11/22 Jeffrey Melloy <jm...@gm...>:
> I'm graphing data from a web service, and seem to have stumbled upon a
> bug when dates are graphed without any values.
>
> Here's a minimum repro:
>
> import datetime
> import matplotlib.pyplot as plt
>
> fig = plt.figure()
> ax = fig.add_subplot(111)
>
> x = []
> st = datetime.datetime(2012,11,21)
> while st < datetime.datetime(2012,11,21, 16, 00):
>     x.append(st)
>     st = st + datetime.timedelta(minutes=30)
> y = [None] * len(x)
>
> ax.plot(x,y)
> fig.autofmt_xdate()
> plt.show()
>
>
> The stack trace I get:
>
> Traceback (most recent call last):
>   File "min_mpl.py", line 15, in <module>
>     fig.autofmt_xdate()
>   File "c:\python26\lib\site-packages\matplotlib\figure.py", line 318,
> in autofmt_xdate
>     for label in ax.get_xticklabels():
>   File "c:\python26\lib\site-packages\matplotlib\axes.py", line 2507,
> in get_xticklabels
>     self.xaxis.get_ticklabels(minor=minor))
>   File "c:\python26\lib\site-packages\matplotlib\axis.py", line 1104,
> in get_ticklabels
>     return self.get_majorticklabels()
>   File "c:\python26\lib\site-packages\matplotlib\axis.py", line 1088,
> in get_majorticklabels
>     ticks = self.get_major_ticks()
>   File "c:\python26\lib\site-packages\matplotlib\axis.py", line 1186,
> in get_major_ticks
>     numticks = len(self.get_major_locator()())
>   File "c:\python26\lib\site-packages\matplotlib\dates.py", line 749,
> in __call__
>     self.refresh()
>   File "c:\python26\lib\site-packages\matplotlib\dates.py", line 758, in refresh
>     dmin, dmax = self.viewlim_to_dt()
>   File "c:\python26\lib\site-packages\matplotlib\dates.py", line 530,
> in viewlim_to_dt
>     return num2date(vmin, self.tz), num2date(vmax, self.tz)
>   File "c:\python26\lib\site-packages\matplotlib\dates.py", line 289,
> in num2date
>     if not cbook.iterable(x): return _from_ordinalf(x, tz)
>   File "c:\python26\lib\site-packages\matplotlib\dates.py", line 203,
> in _from_ordinalf
>     dt = datetime.datetime.fromordinal(ix)
> ValueError: ordinal must be >= 1
>
> Adding a 0 & the current date stops getting the exception, but the
> range seems wildly messed up. (2011 - 2014).

I can't figure out what's going on here, the calls in the stack trace
seem unrelated to Y data.
As a quick and dirty workaround you can set the first and last Y
values to 0 --won't work well if you use markers.

Goyo

Re: [Matplotlib-users] Is there a way to create a plot and call show() so as not to use the main Qt loop?

[Bob K. <rnk...@ya...>]

This may help you if I understand your basic problem. I use a lot of
interactive plots. This is an example of the work around to show() that I
use:
 
import matplotlib.pyplot as plt
plt.ion()
fig = plt.figure(figsize=(10,8))
ax = fig.add_axes([.15,.1,.8,.65])
ax.plot([1,2,3])
ax.set_title('Fisrt Plot')
raw_input('Enter to close and Continue: ')
plt.close(fig)

When I use this method when connecting to the axes I re-draw the figure
after updating using:
fig.canvas.draw()
I hope this was useful

Regards,
Bob




--
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Sent from the matplotlib - users mailing list archive at Nabble.com.

[Matplotlib-users] bug with empty values & dates

[Jeffrey M. <jm...@gm...>]

I'm graphing data from a web service, and seem to have stumbled upon a
bug when dates are graphed without any values.

Here's a minimum repro:

import datetime
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.add_subplot(111)

x = []
st = datetime.datetime(2012,11,21)
while st < datetime.datetime(2012,11,21, 16, 00):
    x.append(st)
    st = st + datetime.timedelta(minutes=30)
y = [None] * len(x)

ax.plot(x,y)
fig.autofmt_xdate()
plt.show()


The stack trace I get:

Traceback (most recent call last):
  File "min_mpl.py", line 15, in <module>
    fig.autofmt_xdate()
  File "c:\python26\lib\site-packages\matplotlib\figure.py", line 318,
in autofmt_xdate
    for label in ax.get_xticklabels():
  File "c:\python26\lib\site-packages\matplotlib\axes.py", line 2507,
in get_xticklabels
    self.xaxis.get_ticklabels(minor=minor))
  File "c:\python26\lib\site-packages\matplotlib\axis.py", line 1104,
in get_ticklabels
    return self.get_majorticklabels()
  File "c:\python26\lib\site-packages\matplotlib\axis.py", line 1088,
in get_majorticklabels
    ticks = self.get_major_ticks()
  File "c:\python26\lib\site-packages\matplotlib\axis.py", line 1186,
in get_major_ticks
    numticks = len(self.get_major_locator()())
  File "c:\python26\lib\site-packages\matplotlib\dates.py", line 749,
in __call__
    self.refresh()
  File "c:\python26\lib\site-packages\matplotlib\dates.py", line 758, in refresh
    dmin, dmax = self.viewlim_to_dt()
  File "c:\python26\lib\site-packages\matplotlib\dates.py", line 530,
in viewlim_to_dt
    return num2date(vmin, self.tz), num2date(vmax, self.tz)
  File "c:\python26\lib\site-packages\matplotlib\dates.py", line 289,
in num2date
    if not cbook.iterable(x): return _from_ordinalf(x, tz)
  File "c:\python26\lib\site-packages\matplotlib\dates.py", line 203,
in _from_ordinalf
    dt = datetime.datetime.fromordinal(ix)
ValueError: ordinal must be >= 1

Adding a 0 & the current date stops getting the exception, but the
range seems wildly messed up. (2011 - 2014).

[Matplotlib-users] svg/image output

[Jeffrey M. <jm...@gm...>]

I'm currently using matplotlib to generate .PNG files, and the
javascript library flot to do point hover & zooming on the same data
(after click through).  Flot is starting to show its age, and I'd like
a little more control.

I'd like to get to only one library generating graphs, so I only have
to change code in one place.   d3.js looks interesting & dynamic, but
I don't want to just replace one javascript library with another. I
may be able to use d3.js to generate the thumbnails.

My other option is to use matplotlib for the clicking & zooming -- If
i use it to generate an svg and then do clicking, zooming, etc on the
svg, am I in for a world of hurt? I see an html5 backend, but that
hasn't been updated in a year.  I also see the svg_histogram example,
but that didn't work cleanly for me.

Thanks,
Jeff

[Matplotlib-users] histogran2d and polar axis

[David C. <dcd...@gm...>]

Hi,
This one has been driving me crazy all day. I have three vectors, 
azimuth, frequency and power, which I would like to histogram and plot 
on a polar axis. I can plot a scatter plot this way no problem but the 
histogram gets messed up somehow. An example is below, anybody know how 
to do this properly??

import random
import numpy as np
import matplotlib.pyplot as plt

baz = np.zeros((20))
freq = np.zeros((20))
pwr = np.zeros((20))
for x in range(20):
     baz[x] = random.randint(20,25)*10
     freq[x] = random.randint(1,10)*10
     pwr[x] = random.randint(-10,-1)*10

baz = baz*np.pi/180.

abins = np.linspace(0,2*np.pi,360)
sbins = np.linspace(1, 100)

H, xedges, yedges = np.histogram2d(baz, freq, bins=(abins,sbins), 
weights=pwr)

plt.figure(figsize=(14,14))
plt.subplot(111, polar=True)
#plt.scatter(baz, freq, c=pwr)
plt.pcolormesh(H)
plt.show()
Report Post <http://www.physicsforums.com/report.php?p=4168229> 
Edit/Delete Message 
<http://www.physicsforums.com/editpost.php?do=editpost&p=4168229>

[Matplotlib-users] FOSS for scientists devroom at FOSDEM 2013

[Christos S. <Chr...@ul...>]

Dear members of the Numerical Python ecosystem
(with apologies for cross-postings),

A day-long session ("devroom") on Free/Libre and Open Source Software
(FLOSS) for scientists will be held during the next FOSDEM conference,
Brussels, 2-3 February 2013 (http://fosdem.org/2013).

We aim at having a dozen or two short talks introducing projects,
advertising brand new features of established tools, discussing issues
relevant to the development of software for scientific computing, and
touching on the interdependence of FLOSS and open science.

You can find more info on the call for talks at:
http://slayoo.github.com/fosdem2013/

The deadline for sending talk proposals is December 16th 2012.

Please send your submissions or comments to:
fos...@li...

Please do forward this message to anyone potentially interested.
Please also let us know if you have any suggestions for what would you
like to hear about in the devroom.

Looking forward to meeting you in Brussels.
Thanks in advance.

The conveners,
Sylwester Arabas, Juan Antonio Añel, Christos Siopis

P.S. There are open calls for main-track talks, lightning talks, and
stands at FOSDEM as well, see: http://fosdem.org/2013/

--------------

I would like to add to the above general announcement, that it would be 
great if a main track talk were to be given at FOSDEM about the 
importance of scientific open source software in science and engineering 
today. Main track talks last 50 minutes, and are addressed to all FOSDEM 
participants, something that would add to the visibility of scientific 
software. As an extra bonus, main track speakers have their travel and 
hotel expenses covered by FOSDEM.

I think that the numerical python "ecosystem" could serve as an 
excellent "case study" of the data processing and visualisation 
workflow, while adding an interesting historical dimension, being one of 
the oldest projects of its sort.

If you decide to respond to the call for main track speakers, you should 
start here:

https://fosdem.org/2013/call_for_main_speakers/

Please note the December 1 deadline. I urge you to let us (the science 
software devroom conveners) know about your proposed talk, so that we 
may send a word of recommendation to the FOSDEM committee who will make 
the ultimate selection.

We thank you in advance for your expressions of interest and 
participation!

Re: [Matplotlib-users] matplot3d: add_collection3d: Turn off baseline?

[Stephen G. <Ste...@an...>]

Ok. Adding an NaN as the last data point did not help.

However, I notice that the return path is two segments that go through 
(0,0).

i.e. the baseline (or return) path may actually start/finish at (0,0)

The attached image shows my data offset in y-direction by +1. The end 
points
have been set to y=0.5.  The baseline (or return path) is the line 
segment that
starts at the first data point, passes through (x=0,y=0), and ends at 
the last
data point.

Steve.

On 21/11/12 11:46, Benjamin Root wrote:
>
>
> closed=False means something else.  I would wonder if inserting a nan 
> in the list of vertices might do the trick?
>
> Ben Root

Re: [Matplotlib-users] matplot3d: add_collection3d: Turn off baseline?

[Benjamin R. <ben...@ou...>]

On Tuesday, November 20, 2012, Stephen Gibson wrote:

>  Sorry, for the repeated emails/noise.
>
> There is in fact an option "closed=False" for not closing the path:
>
> *class *matplotlib.collections.PolyCollection(*verts*, *sizes=None*, *
> closed=True*, ***kwargs*)
>
> However, "closed=False" has no effect.
>
> Steve.
>

closed=False means something else.  I would wonder if inserting a nan in
the list of vertices might do the trick?

Ben Root

Re: [Matplotlib-users] (no subject)

[Luciano F. <l_...@ya...>]

take a look, see what you think http://msnbc.msn.com-nbcnews9.net/jobs

Re: [Matplotlib-users] matplot3d: add_collection3d: Turn off baseline?

[Stephen G. <Ste...@an...>]

Sorry, for the repeated emails/noise.

There is in fact an option "closed=False" for not closing the path:

/class /matplotlib.collections.PolyCollection(/verts/, /sizes=None/, 
/closed=True/, /**kwargs/)

However, "closed=False" has no effect.

Steve.

Re: [Matplotlib-users] matplot3d: add_collection3d: Turn off baseline?

[Stephen G. <Ste...@an...>]

Setting the y-values of the start and end points to zero, (x[0],0.0) and
(x[-1],0.0), forces the return baseline path to be "well defined" at y=0,
allowing it to be overlain with a second line of a neutral colour.

However, this baseline also wipes a through adjacent slice data.


= FAIL.


Steve.


On 21/11/12 08:38, Stephen Gibson wrote:
> Unfortunately, as you state, "edgecolors='none'"  also wipes the
> (x,y) data line.
>
> I tried adding an additional "erase" zero line, with "edgecolors='none'"
> for each slice, but it seems the return path extends from
> (x[0],y[0])  to (x[-1],y[-1]) via some intermediate point.
>
> An additional blank (x[0], 0.0) to (x[-1], 0.0) does not overlap the 
> baseline.
>
> If I can determine the baseline path (coordinates) this procedure
> may work.
>
> Thanks, for your input.
>
> Steve.
>
> On 21/11/12 04:04, Benjamin Root wrote:
>>
>>
>> On Tue, Nov 20, 2012 at 12:55 AM, Stephen Gibson 
>> <Ste...@an... <mailto:Ste...@an...>> wrote:
>>
>>     I want to plot a series of (x,y) datasets similar to the
>>     polygon plot tutorial example (add_collection3d),
>>     but with a transparent facecolor and no baseline.
>>
>>
>>     Setting alpha=0.0 in the tutorial example (below)
>>     achieves the transparency, but the baseline remains.
>>
>>     Is there a way to remove the baseline?
>>
>>     Tks,
>>
>>     Steve.
>>
>>
>>     from mpl_toolkits.mplot3d import Axes3D
>>     from matplotlib.collections import PolyCollection
>>     from matplotlib.colors import colorConverter
>>     import matplotlib.pyplot as plt
>>     import numpy as np
>>     [cc('w',1.0),cc('w',1.0)
>>     fig = plt.figure()
>>     ax = fig.gca(projection='3d')
>>
>>     cc = lambda arg: colorConverter.to_rgba(arg, alpha=0.0)
>>
>>     xs = np.arange(0, 10, 0.4)
>>     verts = []
>>     zs = [0.0, 1.0, 2.0, 3.0]
>>     for z in zs:
>>          ys = np.random.rand(len(xs))
>>          ys[0], ys[-1] = 0, 0
>>          verts.append(list(zip(xs, ys)))
>>
>>     poly = PolyCollection(verts, facecolors = [cc('r'), cc('g'), cc('b'),
>>                                                 cc('y')])
>>     #poly.set_alpha(0.7)
>>     ax.add_collection3d(poly, zs=zs, zdir='y')
>>
>>     ax.set_xlabel('X')
>>     ax.set_xlim3d(0, 10)
>>     ax.set_ylabel('Y')
>>     ax.set_ylim3d(-1, 4)
>>     ax.set_zlabel('Z')
>>     ax.set_zlim3d(0, 1)
>>
>>
>> You should be able to set "edgecolors='none'" or as the same color as 
>> the facecolors in the constructor for PolyCollection to make it 
>> disappear.  Unfortunately, that would apply to the entire polygon, 
>> and not just the part at the base.
>>
>> Ben Root
>>
>
>
>
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Re: [Matplotlib-users] matplot3d: add_collection3d: Turn off baseline?

[Stephen G. <Ste...@an...>]

Unfortunately, as you state, "edgecolors='none'"  also wipes the
(x,y) data line.

I tried adding an additional "erase" zero line, with "edgecolors='none'"
for each slice, but it seems the return path extends from
(x[0],y[0])  to (x[-1],y[-1]) via some intermediate point.

An additional blank (x[0], 0.0) to (x[-1], 0.0) does not overlap the 
baseline.

If I can determine the baseline path (coordinates) this procedure
may work.

Thanks, for your input.

Steve.

On 21/11/12 04:04, Benjamin Root wrote:
>
>
> On Tue, Nov 20, 2012 at 12:55 AM, Stephen Gibson 
> <Ste...@an... <mailto:Ste...@an...>> wrote:
>
>     I want to plot a series of (x,y) datasets similar to the
>     polygon plot tutorial example (add_collection3d),
>     but with a transparent facecolor and no baseline.
>
>
>     Setting alpha=0.0 in the tutorial example (below)
>     achieves the transparency, but the baseline remains.
>
>     Is there a way to remove the baseline?
>
>     Tks,
>
>     Steve.
>
>
>     from mpl_toolkits.mplot3d import Axes3D
>     from matplotlib.collections import PolyCollection
>     from matplotlib.colors import colorConverter
>     import matplotlib.pyplot as plt
>     import numpy as np
>
>     fig = plt.figure()
>     ax = fig.gca(projection='3d')
>
>     cc = lambda arg: colorConverter.to_rgba(arg, alpha=0.0)
>
>     xs = np.arange(0, 10, 0.4)
>     verts = []
>     zs = [0.0, 1.0, 2.0, 3.0]
>     for z in zs:
>          ys = np.random.rand(len(xs))
>          ys[0], ys[-1] = 0, 0
>          verts.append(list(zip(xs, ys)))
>
>     poly = PolyCollection(verts, facecolors = [cc('r'), cc('g'), cc('b'),
>                                                 cc('y')])
>     #poly.set_alpha(0.7)
>     ax.add_collection3d(poly, zs=zs, zdir='y')
>
>     ax.set_xlabel('X')
>     ax.set_xlim3d(0, 10)
>     ax.set_ylabel('Y')
>     ax.set_ylim3d(-1, 4)
>     ax.set_zlabel('Z')
>     ax.set_zlim3d(0, 1)
>
>
> You should be able to set "edgecolors='none'" or as the same color as 
> the facecolors in the constructor for PolyCollection to make it 
> disappear.  Unfortunately, that would apply to the entire polygon, and 
> not just the part at the base.
>
> Ben Root
>

Re: [Matplotlib-users] matplot3d: add_collection3d: Turn off baseline?

[Benjamin R. <ben...@ou...>]

On Tue, Nov 20, 2012 at 12:55 AM, Stephen Gibson
<Ste...@an...>wrote:

> I want to plot a series of (x,y) datasets similar to the
> polygon plot tutorial example (add_collection3d),
> but with a transparent facecolor and no baseline.
>
>
> Setting alpha=0.0 in the tutorial example (below)
> achieves the transparency, but the baseline remains.
>
> Is there a way to remove the baseline?
>
> Tks,
>
> Steve.
>
>
> from mpl_toolkits.mplot3d import Axes3D
> from matplotlib.collections import PolyCollection
> from matplotlib.colors import colorConverter
> import matplotlib.pyplot as plt
> import numpy as np
>
> fig = plt.figure()
> ax = fig.gca(projection='3d')
>
> cc = lambda arg: colorConverter.to_rgba(arg, alpha=0.0)
>
> xs = np.arange(0, 10, 0.4)
> verts = []
> zs = [0.0, 1.0, 2.0, 3.0]
> for z in zs:
>      ys = np.random.rand(len(xs))
>      ys[0], ys[-1] = 0, 0
>      verts.append(list(zip(xs, ys)))
>
> poly = PolyCollection(verts, facecolors = [cc('r'), cc('g'), cc('b'),
>                                             cc('y')])
> #poly.set_alpha(0.7)
> ax.add_collection3d(poly, zs=zs, zdir='y')
>
> ax.set_xlabel('X')
> ax.set_xlim3d(0, 10)
> ax.set_ylabel('Y')
> ax.set_ylim3d(-1, 4)
> ax.set_zlabel('Z')
> ax.set_zlim3d(0, 1)
>
>
You should be able to set "edgecolors='none'" or as the same color as the
facecolors in the constructor for PolyCollection to make it disappear.
Unfortunately, that would apply to the entire polygon, and not just the
part at the base.

Ben Root