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On Fri, Jul 31, 2015 at 2:14 PM, Jouni K. Seppänen <jk...@ik...> wrote:
> Neal Becker <ndb...@gm...> writes:
>
> > I read via gmane: I guess this will need to be updated?
>
> I attempted to send a message to gmane.discuss to request this, but it
> seems there is some problem with that mailing list - the latest message
> is from July 17 when viewed via NNTP, and usually there are at several
> messages per week. I have emailed the gmane.org administrator to ask
> about the status.
>
> --
> Jouni K. Seppänen
> http://www.iki.fi/jks
>
>
>
> ------------------------------------------------------------------------------
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> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
>

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​

Thank you! We are always happy to have new contributors!

Thank you all for your replies. It's not an urgent problem:
1. Jens gave us a link to an existing third party lib, althought it's 
not clear to me how it will work without pytest (i.e. with standard 
unittest).
2. My workaround is simply to use top level test functions as you 
suggest, and the rest works just fine.
It's already awesome enough to be able to test my plots in such an easy 
way!!!
Thanks a lot,
Fabien
On 07/30/2015 04:29 PM, Paul Hobson wrote:
> Fabien,
>
> The @image_comparison operator is still somehwat of a black box for me.
> But I can confirm your observation that it only works on top-level test
> functions, not within a class.
>
> It's on my long, and slowly shifting backlog of things to try to improve.
> -paul
>
>
> On Thu, Jul 30, 2015 at 6:47 AM, Jens Nielsen
> <jen...@gm...
> <mailto:jen...@gm...>> wrote:
>
> Thomas Robitailles pytest image comparison plugin might also be of
> interest
> https://github.com/astrofrog/pytest-mpl
>
> Jens
>
> tor. 30. jul. 2015 kl. 14.43 skrev Thomas Caswell
> <tca...@gm...
> <mailto:tca...@gm...>>:
>
>
> Paul Hobson expressed interest in making it easier to use the
> image comparison tests out side of the mpl test suite
>
> Tom
>
>
> On Thu, Jul 30, 2015, 9:28 AM Fabien
> <fab...@gm...
> <mailto:fab...@gm...>> wrote:
>
> Hi all,
>
> is it possible to use the @image_comparison decorator for tests
> generated within a unittest.TestCase class?
>
> With my attempts so far the decorator was indeed
> instanicated at run
> time but the test was not called, i.e. the test would
> allways pass...
> Running the test with decorator from outside the class works
> fine.
>
> Any idea? Thanks,
>
> Fabien
>
>
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>
>
>
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>
>
> _______________________________________________
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>

Fabien,
The @image_comparison operator is still somehwat of a black box for me. But
I can confirm your observation that it only works on top-level test
functions, not within a class.
It's on my long, and slowly shifting backlog of things to try to improve.
-paul
On Thu, Jul 30, 2015 at 6:47 AM, Jens Nielsen <jen...@gm...>
wrote:
> Thomas Robitailles pytest image comparison plugin might also be of
> interest
> https://github.com/astrofrog/pytest-mpl
>
> Jens
>
> tor. 30. jul. 2015 kl. 14.43 skrev Thomas Caswell <tca...@gm...>:
>
>>
>> Paul Hobson expressed interest in making it easier to use the image
>> comparison tests out side of the mpl test suite
>>
>> Tom
>>
>> On Thu, Jul 30, 2015, 9:28 AM Fabien <fab...@gm...> wrote:
>>
>>> Hi all,
>>>
>>> is it possible to use the @image_comparison decorator for tests
>>> generated within a unittest.TestCase class?
>>>
>>> With my attempts so far the decorator was indeed instanicated at run
>>> time but the test was not called, i.e. the test would allways pass...
>>> Running the test with decorator from outside the class works fine.
>>>
>>> Any idea? Thanks,
>>>
>>> Fabien
>>>
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>
>> ------------------------------------------------------------------------------
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>

Have u tried ?
plt.ylabel(r'$\alpha$')
--
View this message in context: http://matplotlib.1069221.n5.nabble.com/Tex-error-in-plot-label-tp45964p45979.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Thomas Robitailles pytest image comparison plugin might also be of
interest
https://github.com/astrofrog/pytest-mpl
Jens
tor. 30. jul. 2015 kl. 14.43 skrev Thomas Caswell <tca...@gm...>:
>
> Paul Hobson expressed interest in making it easier to use the image
> comparison tests out side of the mpl test suite
>
> Tom
>
> On Thu, Jul 30, 2015, 9:28 AM Fabien <fab...@gm...> wrote:
>
>> Hi all,
>>
>> is it possible to use the @image_comparison decorator for tests
>> generated within a unittest.TestCase class?
>>
>> With my attempts so far the decorator was indeed instanicated at run
>> time but the test was not called, i.e. the test would allways pass...
>> Running the test with decorator from outside the class works fine.
>>
>> Any idea? Thanks,
>>
>> Fabien
>>
>>
>>
>> ------------------------------------------------------------------------------
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
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> _______________________________________________
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>

Paul Hobson expressed interest in making it easier to use the image
comparison tests out side of the mpl test suite
Tom
On Thu, Jul 30, 2015, 9:28 AM Fabien <fab...@gm...> wrote:
> Hi all,
>
> is it possible to use the @image_comparison decorator for tests
> generated within a unittest.TestCase class?
>
> With my attempts so far the decorator was indeed instanicated at run
> time but the test was not called, i.e. the test would allways pass...
> Running the test with decorator from outside the class works fine.
>
> Any idea? Thanks,
>
> Fabien
>
>
>
> ------------------------------------------------------------------------------
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hi all,
is it possible to use the @image_comparison decorator for tests 
generated within a unittest.TestCase class?
With my attempts so far the decorator was indeed instanicated at run 
time but the test was not called, i.e. the test would allways pass... 
Running the test with decorator from outside the class works fine.
Any idea? Thanks,
Fabien

On 07/30/2015 10:07 AM, Eric Firing wrote:
> Forcing the scalar to be a 1-element array would still leave the API
> inconsistent with what you show for Normalize. One solution is to
> flag a scalar at the start, and then de-reference at the end. Would
> you like to submit a PR to take care of this?
Hi,
my very first PR here:
https://github.com/matplotlib/matplotlib/pull/4824
Thanks,
Fabien

Forcing the scalar to be a 1-element array would still leave the API
inconsistent with what you show for Normalize. One solution is to
flag a scalar at the start, and then de-reference at the end. Would
you like to submit a PR to take care of this?

On 07/29/2015 10:34 PM, Paul Hobson wrote:
> See the following example:
>
> import matplotlib as mpl
> c = mpl.cm.get_cmap()
> bnorm = mpl.colors.BoundaryNorm([0,1,2], c.N)
> nnorm = mpl.colors.Normalize(0, 2)
>
> # This works:
> In [8]: c(nnorm(1.1))
> Out[8]: (0.64199873497786197, 1.0, 0.32574320050600891, 1.0)
>
> # This doesn't:
> In [9]: c(bnorm(1.1))
> (...)
> TypeError: 'numpy.int16' object does not support item assignment
>
> # But this works:
> In [10]: c(bnorm([1.1]))
> Out[10]: array([[ 0.5, 0. , 0. , 1. ]])
>
> From the doc I would expect BoundaryNorm and Normalize to work the
> same
> way. I find the error sent by BoundaryNorm quite misleading.
>
> Should I fill a bug report for this?
>
>
> Fabien,
>
> What happens if your force the boundaries to floats? By that I mean:
> bnorm = mpl.colors.BoundaryNorm([0.0, 1.0, 2.0], c.N)
> -Paul
Thanks Paul,
it doesn't change anything. The problem is related to the variable iret 
which is of shape (): the assignment fails at L1281 in colors.py. Here 
is the code:
 def __call__(self, x, clip=None):
 if clip is None:
 clip = self.clip
 x = ma.asarray(x) # <--- doesnt guarantee 1D
 mask = ma.getmaskarray(x)
 xx = x.filled(self.vmax + 1)
 if clip:
 np.clip(xx, self.vmin, self.vmax)
 iret = np.zeros(x.shape, dtype=np.int16) # <--- x.shape = ()
 for i, b in enumerate(self.boundaries):
 iret[xx >= b] = i
 if self._interp:
 scalefac = float(self.Ncmap - 1) / (self.N - 2)
 iret = (iret * scalefac).astype(np.int16)
 iret[xx < self.vmin] = -1 # <--- error
 iret[xx >= self.vmax] = self.Ncmap
 ret = ma.array(iret, mask=mask)
 if ret.shape == () and not mask:
 ret = int(ret)
 return ret
It should be easy to fix by changing
 iret = np.zeros(x.shape, dtype=np.int16)
to:
 iret = np.atleast1d(np.zeros(x.shape, dtype=np.int16))
But this would lead to an output which is never a scalar even if a 
scalar is given as input. Is that a problem?
Cheers,
Fabien

On Wed, Jul 29, 2015 at 3:18 AM, Fabien <fab...@gm...> wrote:
> Folks,
>
> still in my exploring phase of Matplotlib's ecosystem I ran into
> following mismatch between the APIs of BoundaryNorm and Normalize.
>
> See the following example:
>
> import matplotlib as mpl
> c = mpl.cm.get_cmap()
> bnorm = mpl.colors.BoundaryNorm([0,1,2], c.N)
> nnorm = mpl.colors.Normalize(0, 2)
>
> # This works:
> In [8]: c(nnorm(1.1))
> Out[8]: (0.64199873497786197, 1.0, 0.32574320050600891, 1.0)
>
> # This doesn't:
> In [9]: c(bnorm(1.1))
> (...)
> TypeError: 'numpy.int16' object does not support item assignment
>
> # But this works:
> In [10]: c(bnorm([1.1]))
> Out[10]: array([[ 0.5, 0. , 0. , 1. ]])
>
> From the doc I would expect BoundaryNorm and Normalize to work the same
> way. I find the error sent by BoundaryNorm quite misleading.
>
> Should I fill a bug report for this?
>
Fabien,
What happens if your force the boundaries to floats? By that I mean:
bnorm = mpl.colors.BoundaryNorm([0.0, 1.0, 2.0], c.N)
-Paul

Folks,
still in my exploring phase of Matplotlib's ecosystem I ran into 
following mismatch between the APIs of BoundaryNorm and Normalize.
See the following example:
import matplotlib as mpl
c = mpl.cm.get_cmap()
bnorm = mpl.colors.BoundaryNorm([0,1,2], c.N)
nnorm = mpl.colors.Normalize(0, 2)
# This works:
In [8]: c(nnorm(1.1))
Out[8]: (0.64199873497786197, 1.0, 0.32574320050600891, 1.0)
# This doesn't:
In [9]: c(bnorm(1.1))
(...)
TypeError: 'numpy.int16' object does not support item assignment
# But this works:
In [10]: c(bnorm([1.1]))
Out[10]: array([[ 0.5, 0. , 0. , 1. ]])
 From the doc I would expect BoundaryNorm and Normalize to work the same 
way. I find the error sent by BoundaryNorm quite misleading.
Should I fill a bug report for this?
Thanks!
Fabien

On 2015年07月28日 10:31, (by way of c....@po...) wrote:
> I try to use a dates on the x-aches. With pure Python3 code it works
> fine. BUt when I try to use this inside wxPython application on a
> FigureCanvas it doesn't work. And I don't understand the difference
> here.
>
> This is the error
> [err]
> plot.plot([datetime.date(2015, 1, 7),
> TypeError: descriptor 'date' requires a 'datetime.datetime' object but
> received a 'int'
> [/err]
>
> This is the fine working pure Python3 code.
<snip>
> import datetime
<snip>
> This is the piece of wxPython code that cause the error
<snip>
> from datetime import datetime
	There is the problem. The error has nothing to do with matplotlib. In 
one case you did "import datetime" and imported the datetime library. 
In the other you did "from datetime import datetime", thus importing the 
datetime type from that library. If your first version is working, 
change the second version to use the same import.
-- 
Brendan Barnwell
"Do not follow where the path may lead. Go, instead, where there is no 
path, and leave a trail."
 --author unknown

I try to use a dates on the x-aches. With pure Python3 code it works
fine. BUt when I try to use this inside wxPython application on a
FigureCanvas it doesn't work. And I don't understand the difference
here.
This is the error
[err]
 plot.plot([datetime.date(2015, 1, 7),
TypeError: descriptor 'date' requires a 'datetime.datetime' object but
received a 'int'
[/err]
This is the fine working pure Python3 code.
[code]
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import datetime
plt.plot([datetime.date(2015, 1, 7),
	 datetime.date(2015, 2, 5),
	 datetime.date(2015, 6, 2)],
	 [70.3, 60.1, 68.8])
plt.show()
[/code]
This is the piece of wxPython code that cause the error
[code]
# -*- coding: utf-8 -*-
import matplotlib.pyplot as pyplot
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as
FigureCanvas
from datetime import datetime
#...
class StatisticTab(wx.Panel):
 def __init__(self, parent):
 super(StatisticTab, self).__init__(parent)
 panel = wx.Panel(self)
 fig = pyplot.figure()
 plot = self.fig.add_subplot(1,1,1)
 plot.plot([datetime.date(2015, 1, 7),
 datetime.date(2015, 2, 5),
 datetime.date(2015, 6, 2)],
 [70.3, 60.1, 68.8])
 self.canvas = FigureCanvas(self, -1, fig)
 sizer = wx.BoxSizer(wx.VERTICAL)
 sizer.Add(panel)
 self.SetSizer(sizer)
[/code]

That makes sense. Thank you.
João
> On 28 Jul 2015, at 16:08, Oscar Benjamin <osc...@gm...> wrote:
> 
> 
> 
> On 2015年7月28日 at 16:01 Joao Quinta da Fonseca <Joa...@ma...> wrote:
> I am trying to use LaTeX on the ylabel of a plot using:
> 
> plt.ylabel("$\alpha$")
> 
> and I am seeing very inconsistent behaviour. If I use $\alpha$ I get an error (see below), but \gamma is fine. $\tau does not give an error but plots a strange character.
> 
> Can you help? thanks
> 
> This is to do with how Python handles strings and is not a matplotlib issue. The \ is an escape character in Python strings but only for certain letters e.g. \t is a tab character etc:
> 
> In [3]: print('$\tau$')
> $ au$
> 
> In [4]: print('$\alpha$')
> $lpha$
> 
> \g is not an escape so:
> 
> In [5]: print('$\gamma$')
> $\gamma$
> 
> To include slashes in your string you either need to double them up or use raw strings:
> 
> In [8]: print(r'$\alpha$')
> $\alpha$
> 
> In [9]: print('$\\alpha$')
> $\alpha$
> 
> --
> Oscar

On 2015年7月28日 at 16:01 Joao Quinta da Fonseca <
Joa...@ma...> wrote:
> I am trying to use LaTeX on the ylabel of a plot using:
>
> plt.ylabel("$\alpha$")
>
> and I am seeing very inconsistent behaviour. If I use $\alpha$ I get an
> error (see below), but \gamma is fine. $\tau does not give an error but
> plots a strange character.
>
Can you help? thanks
>
This is to do with how Python handles strings and is not a matplotlib
issue. The \ is an escape character in Python strings but only for certain
letters e.g. \t is a tab character etc:
In [3]: print('$\tau$')
$ au$
In [4]: print('$\alpha$')
$lpha$
\g is not an escape so:
In [5]: print('$\gamma$')
$\gamma$
To include slashes in your string you either need to double them up or use
raw strings:
In [8]: print(r'$\alpha$')
$\alpha$
In [9]: print('$\\alpha$')
$\alpha$
--
Oscar

I think you either need to escape the \ as \\ or use a raw string .i.e do
r'$\alpha$' otherwise \a gets interpreted as control character.
try entering '\alpha' in a regular python prompt and you will se what
happens.
Best
Jens
tir. 28. jul. 2015 kl. 16.01 skrev Joao Quinta da Fonseca <
Joa...@ma...>:
> I am trying to use LaTeX on the ylabel of a plot using:
>
> plt.ylabel("$\alpha$")
>
> and I am seeing very inconsistent behaviour. If I use $\alpha$ I get an
> error (see below), but \gamma is fine. $\tau does not give an error but
> plots a strange character.
>
> Can you help? thanks
>
> Joao
>
>
> Using $\alpha$ like above gives a long error message:
>
> ---------------------------------------------------------------------------
> ValueError
> Traceback (most recent call last)
>
> /Users/joao/anaconda/lib/python2.7/site-packages/IPython/core/formatters.pyc
> in __call__(self, obj)
> 328 pass
> 329 else:
> --> 330 return printer(obj)
> 331 # Finally look for special method names
> 332 method = _safe_get_formatter_method(obj,
> self.print_method)
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/IPython/core/pylabtools.pyc
> in <lambda>(fig)
> 205
> 206 if 'png' in formats:
> --> 207 png_formatter.for_type(Figure, lambda fig:
> print_figure(fig, 'png', **kwargs))
> 208 if 'retina' in formats or 'png2x' in formats:
> 209 png_formatter.for_type(Figure, lambda fig:
> retina_figure(fig, **kwargs))
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/IPython/core/pylabtools.pyc
> in print_figure(fig, fmt, bbox_inches, **kwargs)
> 115
> 116 bytes_io = BytesIO()
> --> 117 fig.canvas.print_figure(bytes_io, **kw)
> 118 data = bytes_io.getvalue()
> 119 if fmt == 'svg':
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/backend_bases.pyc
> in print_figure(self, filename, dpi, facecolor, edgecolor, orientation,
> format, **kwargs)
> 2156 orientation=orientation,
> 2157 dryrun=True,
> -> 2158
> **kwargs)
>
> 2159 renderer = self.figure._cachedRenderer
> 2160 bbox_inches = self.figure.get_tightbbox(renderer)
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/backends/backend_agg.pyc
> in print_png(self, filename_or_obj, *args, **kwargs)
> 519
> 520 def print_png(self, filename_or_obj, *args, **kwargs):
> --> 521 FigureCanvasAgg.draw(self)
> 522 renderer = self.get_renderer()
> 523 original_dpi = renderer.dpi
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/backends/backend_agg.pyc
> in draw(self)
> 467
> 468 try:
> --> 469 self.figure.draw(self.renderer)
> 470 finally:
> 471 RendererAgg.lock.release()
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/artist.pyc in
> draw_wrapper(artist, renderer, *args, **kwargs)
> 57 def draw_wrapper(artist, renderer, *args, **kwargs):
> 58 before(artist, renderer)
> ---> 59 draw(artist, renderer, *args, **kwargs)
> 60 after(artist, renderer)
> 61
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/figure.pyc in
> draw(self, renderer)
> 1083 dsu.sort(key=itemgetter(0))
> 1084 for zorder, a, func, args in dsu:
> -> 1085 func(*args)
> 1086
> 1087 renderer.close_group('figure')
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/artist.pyc in
> draw_wrapper(artist, renderer, *args, **kwargs)
> 57 def draw_wrapper(artist, renderer, *args, **kwargs):
> 58 before(artist, renderer)
> ---> 59 draw(artist, renderer, *args, **kwargs)
> 60 after(artist, renderer)
> 61
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.pyc
> in draw(self, renderer, inframe)
> 2108
> 2109 for zorder, a in dsu:
> -> 2110 a.draw(renderer)
> 2111
> 2112 renderer.close_group('axes')
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/artist.pyc in
> draw_wrapper(artist, renderer, *args, **kwargs)
> 57 def draw_wrapper(artist, renderer, *args, **kwargs):
> 58 before(artist, renderer)
> ---> 59 draw(artist, renderer, *args, **kwargs)
> 60 after(artist, renderer)
> 61
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/axis.pyc in
> draw(self, renderer, *args, **kwargs)
> 1126 self._update_label_position(ticklabelBoxes,
> ticklabelBoxes2)
> 1127
> -> 1128 self.label.draw(renderer)
> 1129
> 1130 self._update_offset_text_position(ticklabelBoxes,
> ticklabelBoxes2)
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/artist.pyc in
> draw_wrapper(artist, renderer, *args, **kwargs)
> 57 def draw_wrapper(artist, renderer, *args, **kwargs):
> 58 before(artist, renderer)
> ---> 59 draw(artist, renderer, *args, **kwargs)
> 60 after(artist, renderer)
> 61
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/text.pyc in
> draw(self, renderer)
> 593 renderer.open_group('text', self.get_gid())
> 594
> --> 595 bbox, info, descent = self._get_layout(renderer)
> 596 trans = self.get_transform()
> 597
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/text.pyc in
> _get_layout(self, renderer)
> 318
> w, h, d =
> renderer.get_text_width_height_descent(clean_line,
>
> 319
> self._fontproperties,
> --> 320
> ismath=ismath)
>
> 321 else:
> 322 w, h, d = 0, 0, 0
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/backends/backend_agg.pyc
> in get_text_width_height_descent(self, s, prop, ismath)
> 226 if ismath:
> 227 ox, oy, width, height, descent, fonts, used_characters
> = \
> --> 228 self.mathtext_parser.parse(s, self.dpi, prop)
> 229 return width, height, descent
> 230
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/mathtext.pyc
> in parse(self, s, dpi, prop)
> 3003 self.__class__._parser = Parser()
> 3004
> -> 3005 box = self._parser.parse(s, font_output, fontsize, dpi)
> 3006 font_output.set_canvas_size(box.width, box.height,
> box.depth)
> 3007 result = font_output.get_results(box)
>
>
>
> /Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/mathtext.pyc
> in parse(self, s, fonts_object, fontsize, dpi)
> 2337 err.line,
> 2338 " " * (err.column - 1) + "^",
> -> 2339
> six.text_type(err)]))
>
> 2340 self._state_stack = None
> 2341 self._em_width_cache = {}
>
>
>
> ValueError
> :
> $ lpha$
> ^
> Expected end of text (at char 0), (line:1, col:1)
>
>
>
>
> ------------------------------------------------------------------------------
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

I am trying to use LaTeX on the ylabel of a plot using:
plt.ylabel("$\alpha$") 
and I am seeing very inconsistent behaviour. If I use $\alpha$ I get an error (see below), but \gamma is fine. $\tau does not give an error but plots a strange character.
Can you help? thanks
Joao
Using $\alpha$ like above gives a long error message:
---------------------------------------------------------------------------
ValueError
 Traceback (most recent call last)
/Users/joao/anaconda/lib/python2.7/site-packages/IPython/core/formatters.pyc in __call__(self, obj)
 328 pass
 329 else:
--> 330 return printer(obj)
 331 # Finally look for special method names
 332 method = _safe_get_formatter_method(obj, self.print_method)
/Users/joao/anaconda/lib/python2.7/site-packages/IPython/core/pylabtools.pyc in <lambda>(fig)
 205 
 206 if 'png' in formats:
--> 207 png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
 208 if 'retina' in formats or 'png2x' in formats:
 209 png_formatter.for_type(Figure, lambda fig: retina_figure(fig, **kwargs))
/Users/joao/anaconda/lib/python2.7/site-packages/IPython/core/pylabtools.pyc in print_figure(fig, fmt, bbox_inches, **kwargs)
 115 
 116 bytes_io = BytesIO()
--> 117 fig.canvas.print_figure(bytes_io, **kw)
 118 data = bytes_io.getvalue()
 119 if fmt == 'svg':
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/backend_bases.pyc in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, **kwargs)
 2156 orientation=orientation,
 2157 dryrun=True,
-> 2158
 **kwargs)
 2159 renderer = self.figure._cachedRenderer
 2160 bbox_inches = self.figure.get_tightbbox(renderer)
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/backends/backend_agg.pyc in print_png(self, filename_or_obj, *args, **kwargs)
 519 
 520 def print_png(self, filename_or_obj, *args, **kwargs):
--> 521 FigureCanvasAgg.draw(self)
 522 renderer = self.get_renderer()
 523 original_dpi = renderer.dpi
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/backends/backend_agg.pyc in draw(self)
 467 
 468 try:
--> 469 self.figure.draw(self.renderer)
 470 finally:
 471 RendererAgg.lock.release()
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
 57 def draw_wrapper(artist, renderer, *args, **kwargs):
 58 before(artist, renderer)
---> 59 draw(artist, renderer, *args, **kwargs)
 60 after(artist, renderer)
 61 
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/figure.pyc in draw(self, renderer)
 1083 dsu.sort(key=itemgetter(0))
 1084 for zorder, a, func, args in dsu:
-> 1085 func(*args)
 1086 
 1087 renderer.close_group('figure')
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
 57 def draw_wrapper(artist, renderer, *args, **kwargs):
 58 before(artist, renderer)
---> 59 draw(artist, renderer, *args, **kwargs)
 60 after(artist, renderer)
 61 
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.pyc in draw(self, renderer, inframe)
 2108 
 2109 for zorder, a in dsu:
-> 2110 a.draw(renderer)
 2111 
 2112 renderer.close_group('axes')
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
 57 def draw_wrapper(artist, renderer, *args, **kwargs):
 58 before(artist, renderer)
---> 59 draw(artist, renderer, *args, **kwargs)
 60 after(artist, renderer)
 61 
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/axis.pyc in draw(self, renderer, *args, **kwargs)
 1126 self._update_label_position(ticklabelBoxes, ticklabelBoxes2)
 1127 
-> 1128 self.label.draw(renderer)
 1129 
 1130 self._update_offset_text_position(ticklabelBoxes, ticklabelBoxes2)
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
 57 def draw_wrapper(artist, renderer, *args, **kwargs):
 58 before(artist, renderer)
---> 59 draw(artist, renderer, *args, **kwargs)
 60 after(artist, renderer)
 61 
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/text.pyc in draw(self, renderer)
 593 renderer.open_group('text', self.get_gid())
 594 
--> 595 bbox, info, descent = self._get_layout(renderer)
 596 trans = self.get_transform()
 597 
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/text.pyc in _get_layout(self, renderer)
 318
 w, h, d = renderer.get_text_width_height_descent(clean_line,
 319 self._fontproperties,
--> 320
 ismath=ismath)
 321 else:
 322 w, h, d = 0, 0, 0
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/backends/backend_agg.pyc in get_text_width_height_descent(self, s, prop, ismath)
 226 if ismath:
 227 ox, oy, width, height, descent, fonts, used_characters = \
--> 228 self.mathtext_parser.parse(s, self.dpi, prop)
 229 return width, height, descent
 230 
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/mathtext.pyc in parse(self, s, dpi, prop)
 3003 self.__class__._parser = Parser()
 3004 
-> 3005 box = self._parser.parse(s, font_output, fontsize, dpi)
 3006 font_output.set_canvas_size(box.width, box.height, box.depth)
 3007 result = font_output.get_results(box)
/Users/joao/anaconda/lib/python2.7/site-packages/matplotlib/mathtext.pyc in parse(self, s, fonts_object, fontsize, dpi)
 2337 err.line,
 2338 " " * (err.column - 1) + "^",
-> 2339
 six.text_type(err)]))
 2340 self._state_stack = None
 2341 self._em_width_cache = {}
ValueError
: 
$lpha$
^
Expected end of text (at char 0), (line:1, col:1)

 Hi,
In matplotlib, what is the most appropriate way to plot an image with its
native aspect ratio, and optionally its native size, inside existing axes
at a specific data location?
For instance:
from matplotlib.pyplot import plotfrom matplotlib.image import
imreadfrom matplotlib.cbook import get_sample_data
plot([50,60],[1000,2000])
im = imread(get_sample_data("grace_hopper.png", asfileobj=False))
Now I want to plot im for instance centered at coordinates (57,1200) with
some scaling or a max height and without deformation.
Thanks for the help.
-- 
Stephane Raynaud

​I second that motion and would especially like it if the default color
cycle were longer than the current one (7 colors).
Jon​
On Wed, Jul 22, 2015 at 4:30 AM, <
mat...@li...> wrote:
> From: Thomas Robitaille <tho...@gm...>
> To: Thomas Caswell <tca...@gm...>
> Cc: Matplotlib Users <mat...@li...>
> Date: 2015年7月20日 08:33:50 +0200
> Subject: Re: [Matplotlib-users] Call for new style defaults
> Hi Thomas,
>
> Are there also already plans to change the default color cycle?
> Changing to one of the qualitative color sequences from colorbrewer2
> would be a very nice change in defaults, but I am presuming that this
> has already been suggested?
>
> Cheers,
> Tom
>
-- 
________________________________________________________
Jonathan D. Slavin Harvard-Smithsonian CfA
js...@cf... 60 Garden Street, MS 83
phone: (617) 496-7981 Cambridge, MA 02138-1516
cell: (781) 363-0035 USA
________________________________________________________

Hi Thomas,
Are there also already plans to change the default color cycle?
Changing to one of the qualitative color sequences from colorbrewer2
would be a very nice change in defaults, but I am presuming that this
has already been suggested?
Cheers,
Tom
On 12 July 2015 at 18:11, Thomas Caswell <tca...@gm...> wrote:
> Hello all,
>
> Following much discussion, we are changing the default color map and styles
> in the upcoming 2.0 release!
>
> The new default color map will be 'viridis' (aka option D). I recommend
> everyone watch Nathaniel Smith and Stéfan van der Walt's talk from
> SciPy2015 introducing the new color map and providing an introduction to the
> math of color perception: https://www.youtube.com/watch?v=xAoljeRJ3lU
>
> We are soliciting proposals to change any and all other visual defaults
> (including adding new rcParams as needed).
>
> If you have a proposal please create a PR or issue with the changes to
> `rcsetup.py` and `matplotlibrc.template` implementing the changes by August
> 9, 2015 (1 month from now). Do not worry about updating any failing tests.
>
> At the end, Micheal Droettboom and I will decide on the new defaults.
>
> A 'classic' style will be provided so reverting to the current default
> values will be a single line of python (`mpl.style.use('classic')`).
>
> Please distribute this as widely as possible. We only want to do this once
> and want to get feedback from as many users as possible.
>
> Thomas Caswell
>
> PS jet is harmful to you and those around you
>
> See https://github.com/matplotlib/matplotlib/pull/4622 for an example
> proposal PR.
>
> ------------------------------------------------------------------------------
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On 2015年7月15日 07:19:53 -1000
Eric Firing <ef...@ha...> wrote:
> John, if you haven't already done so, please escalate this to a github 
> issue.
Will do...
Cheers,
John

It is not clear to me that 4202 would fix it, and I think 4202 has a 
basic problem of its own.
John, if you haven't already done so, please escalate this to a github 
issue.
Eric
On 2015年07月15日 4:58 AM, Thomas Caswell wrote:
> The PR to fix this is still open
> (https://github.com/matplotlib/matplotlib/pull/4202).
>
> Tom
>
> On Wed, Jul 15, 2015 at 10:29 AM John Coppens <jo...@jc...
> <mailto:jo...@jc...>> wrote:
>
> Hello again,
>
> I've posted these two issues in separate mails, as I suspect they're
> actually different problems.
>
> This error is particular to the default version of MacOSX's matplotlib
> version 1.4.3:
>
> When doing a simple plot:
>
> import matplotlib.pyplot as plt
>
> def test_plot():
> x = range(11)
> y = [x0**2 for x0 in x]
>
> plt.plot(x, y, 'o:', fillstyle='none', label = "1", ms = 10)
> plt.legend()
> plt.show()
>
> def main(args):
> test_plot()
> return 0
>
> if __name__ == '__main__':
> import sys
> sys.exit(main(sys.argv))
>
> Much of the data is available on this thread on stackoverflow:
>
> http://stackoverflow.com/questions/31408928/how-can-i-plot-hollowed-symbols-connected-with-dotted-lines-in-one-go/31410105?noredirect=1#comment50794519_31410105
>
> The gist is that a dotted line ('o:') works correctly
> on my system (Linux Slackware/matplotlib 1.3.1 and 1.4.3), on C.C.Yang's
> Linux Mint, but not on his MacOSX (on which the _circle symbols_ are
> also
> dotted).
>
> It does work if he defines TkAgg or GtkAgg (even though he does not have
> Gtk installed on his Mac)
>
> Any suggestions to solve this?
>
> Is there a problem in the MacOSXAgg backend?
>
> John
>
> ------------------------------------------------------------------------------
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>
>
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