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From: Benjamin R. <ben...@ou...> - 2015-07-31 18:22:47
|
nabble is also another fairly commonly used resource for viewing archived discussions. 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 > > > > ------------------------------------------------------------------------------ > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > |
From: Michael D. <md...@st...> - 2015-07-31 17:07:13
|
Due to recent technical problems and changes in policy on SourceForge, we have decided to move the matplotlib mailing lists to python.org. To subscribe to the new mailing lists, please visit: * For user questions and support: https://mail.python.org/mailman/listinfo/matplotlib-users mat...@py... * For low-volume announcements about matplotlib releases and related events and software: https://mail.python.org/mailman/listinfo/matplotlib-announce mat...@py... * For developer discussion: https://mail.python.org/mailman/listinfo/matplotlib-devel mat...@py... The old list will remain active in the meantime, but all new posts will auto-reply with the location of the new mailing lists. The old mailing list archives will remain available. Thanks to Ralf Hildebrandt at python.org for making this possible. Cheers, Michael Droettboom |
From: Eric F. <ef...@ha...> - 2015-07-31 07:29:36
|
Thank you! We are always happy to have new contributors! |
From: Fabien <fab...@gm...> - 2015-07-30 14:40:42
|
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 > > > ------------------------------------------------------------------------------ > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > <mailto:Mat...@li...> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > ------------------------------------------------------------------------------ > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > <mailto:Mat...@li...> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > > > > ------------------------------------------------------------------------------ > > > > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |
From: Paul H. <pmh...@gm...> - 2015-07-30 14:29:39
|
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 >> > |
From: vijai <vi...@vi...> - 2015-07-30 14:02:22
|
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. |
From: Jens N. <jen...@gm...> - 2015-07-30 13:47:28
|
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 > |
From: Thomas C. <tca...@gm...> - 2015-07-30 13:42:32
|
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 > |
From: Fabien <fab...@gm...> - 2015-07-30 13:27:59
|
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 |
From: Fabien <fab...@gm...> - 2015-07-30 11:31:59
|
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 |
From: Eric F. <ef...@ha...> - 2015-07-30 08:35:42
|
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? |
From: Fabien <fab...@gm...> - 2015-07-30 07:38:20
|
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 |
From: Paul H. <pmh...@gm...> - 2015-07-29 20:34:30
|
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 |
From: Fabien <fab...@gm...> - 2015-07-29 10:19:12
|
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 |
From: Brendan B. <bre...@br...> - 2015-07-28 17:54:20
|
On 2015-07-28 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 |
From: <c....@po...> - 2015-07-28 17:49:01
|
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] |
From: Joao Q. da F. <Joa...@ma...> - 2015-07-28 15:12:15
|
That makes sense. Thank you. João > On 28 Jul 2015, at 16:08, Oscar Benjamin <osc...@gm...> wrote: > > > > On Tue, 28 Jul 2015 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 |
From: Oscar B. <osc...@gm...> - 2015-07-28 15:08:23
|
On Tue, 28 Jul 2015 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 |
From: Jens N. <jen...@gm...> - 2015-07-28 15:05:18
|
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 > |
From: Joao Q. da F. <Joa...@ma...> - 2015-07-28 14:59:50
|
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) |
From: Stephane R. <ste...@gm...> - 2015-07-27 15:32:48
|
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 |
From: Slavin, J. <js...@cf...> - 2015-07-22 14:36:27
|
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: Mon, 20 Jul 2015 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 ________________________________________________________ |
From: Thomas R. <tho...@gm...> - 2015-07-22 08:30:53
|
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. > > ------------------------------------------------------------------------------ > Don't Limit Your Business. Reach for the Cloud. > GigeNET's Cloud Solutions provide you with the tools and support that > you need to offload your IT needs and focus on growing your business. > Configured For All Businesses. Start Your Cloud Today. > https://www.gigenetcloud.com/ > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |
From: John C. <jo...@jc...> - 2015-07-15 20:12:25
|
On Wed, 15 Jul 2015 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 |
From: Eric F. <ef...@ha...> - 2015-07-15 17:20:02
|
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 2015/07/15 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 > > ------------------------------------------------------------------------------ > Don't Limit Your Business. Reach for the Cloud. > GigeNET's Cloud Solutions provide you with the tools and support that > you need to offload your IT needs and focus on growing your business. > Configured For All Businesses. Start Your Cloud Today. > https://www.gigenetcloud.com/ > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > <mailto:Mat...@li...> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > > > ------------------------------------------------------------------------------ > Don't Limit Your Business. Reach for the Cloud. > GigeNET's Cloud Solutions provide you with the tools and support that > you need to offload your IT needs and focus on growing your business. > Configured For All Businesses. Start Your Cloud Today. > https://www.gigenetcloud.com/ > > > > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |