You can subscribe to this list here.
2003 |
Jan
|
Feb
|
Mar
|
Apr
|
May
(3) |
Jun
|
Jul
|
Aug
(12) |
Sep
(12) |
Oct
(56) |
Nov
(65) |
Dec
(37) |
---|---|---|---|---|---|---|---|---|---|---|---|---|
2004 |
Jan
(59) |
Feb
(78) |
Mar
(153) |
Apr
(205) |
May
(184) |
Jun
(123) |
Jul
(171) |
Aug
(156) |
Sep
(190) |
Oct
(120) |
Nov
(154) |
Dec
(223) |
2005 |
Jan
(184) |
Feb
(267) |
Mar
(214) |
Apr
(286) |
May
(320) |
Jun
(299) |
Jul
(348) |
Aug
(283) |
Sep
(355) |
Oct
(293) |
Nov
(232) |
Dec
(203) |
2006 |
Jan
(352) |
Feb
(358) |
Mar
(403) |
Apr
(313) |
May
(165) |
Jun
(281) |
Jul
(316) |
Aug
(228) |
Sep
(279) |
Oct
(243) |
Nov
(315) |
Dec
(345) |
2007 |
Jan
(260) |
Feb
(323) |
Mar
(340) |
Apr
(319) |
May
(290) |
Jun
(296) |
Jul
(221) |
Aug
(292) |
Sep
(242) |
Oct
(248) |
Nov
(242) |
Dec
(332) |
2008 |
Jan
(312) |
Feb
(359) |
Mar
(454) |
Apr
(287) |
May
(340) |
Jun
(450) |
Jul
(403) |
Aug
(324) |
Sep
(349) |
Oct
(385) |
Nov
(363) |
Dec
(437) |
2009 |
Jan
(500) |
Feb
(301) |
Mar
(409) |
Apr
(486) |
May
(545) |
Jun
(391) |
Jul
(518) |
Aug
(497) |
Sep
(492) |
Oct
(429) |
Nov
(357) |
Dec
(310) |
2010 |
Jan
(371) |
Feb
(657) |
Mar
(519) |
Apr
(432) |
May
(312) |
Jun
(416) |
Jul
(477) |
Aug
(386) |
Sep
(419) |
Oct
(435) |
Nov
(320) |
Dec
(202) |
2011 |
Jan
(321) |
Feb
(413) |
Mar
(299) |
Apr
(215) |
May
(284) |
Jun
(203) |
Jul
(207) |
Aug
(314) |
Sep
(321) |
Oct
(259) |
Nov
(347) |
Dec
(209) |
2012 |
Jan
(322) |
Feb
(414) |
Mar
(377) |
Apr
(179) |
May
(173) |
Jun
(234) |
Jul
(295) |
Aug
(239) |
Sep
(276) |
Oct
(355) |
Nov
(144) |
Dec
(108) |
2013 |
Jan
(170) |
Feb
(89) |
Mar
(204) |
Apr
(133) |
May
(142) |
Jun
(89) |
Jul
(160) |
Aug
(180) |
Sep
(69) |
Oct
(136) |
Nov
(83) |
Dec
(32) |
2014 |
Jan
(71) |
Feb
(90) |
Mar
(161) |
Apr
(117) |
May
(78) |
Jun
(94) |
Jul
(60) |
Aug
(83) |
Sep
(102) |
Oct
(132) |
Nov
(154) |
Dec
(96) |
2015 |
Jan
(45) |
Feb
(138) |
Mar
(176) |
Apr
(132) |
May
(119) |
Jun
(124) |
Jul
(77) |
Aug
(31) |
Sep
(34) |
Oct
(22) |
Nov
(23) |
Dec
(9) |
2016 |
Jan
(26) |
Feb
(17) |
Mar
(10) |
Apr
(8) |
May
(4) |
Jun
(8) |
Jul
(6) |
Aug
(5) |
Sep
(9) |
Oct
(4) |
Nov
|
Dec
|
2017 |
Jan
(5) |
Feb
(7) |
Mar
(1) |
Apr
(5) |
May
|
Jun
(3) |
Jul
(6) |
Aug
(1) |
Sep
|
Oct
(2) |
Nov
(1) |
Dec
|
2018 |
Jan
|
Feb
|
Mar
|
Apr
(1) |
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
2020 |
Jan
|
Feb
|
Mar
|
Apr
|
May
(1) |
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
2025 |
Jan
(1) |
Feb
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
From: Benjamin R. <ben...@gm...> - 2016-02-24 20:33:54
|
Could you try using faulthandler and post the traceback please? That'll help us isolate the problem better. Ben Root On Wed, Feb 24, 2016 at 3:04 PM, Claude Falbriard <cl...@br...> wrote: > Dear colleagues, > > I've done a build from source of latest *Matplotlib* package and > deployed it at our IBM z13 machine (s390x). It uses the current release > 1.5.1. > During the unit tests I found an issue with a test case from NOAA which > uses a* pcolormesh* draw function with *basemap*. > > Example 2: Plot data from an NWW3 GRiB2 file - [ here: > *http://polar.ncep.noaa.gov/waves/examples/usingpython.shtml* > <http://polar.ncep.noaa.gov/waves/examples/usingpython.shtml>*]* > > The following line is causing a *Segmentation fault* error even when > adding an 8GB swap memory to the process: > > cs = m.pcolormesh(x,y,data,shading='flat',cmap=plt.cm.jet) > > I also tryed to execute other, similar samples that use pcolormesh, but > receiving the same error. Is this a known issue or might it be be related > to the memory environment ? Any hints how to debug this error? > > Regards, > > *Claude Falbriard* > Certified IT Specialist L2 - Middleware > ------------------------------ > *Phone:*55-13-99662-5703 | *Mobile:*55-13-98117-3316 > *E-mail:* *cl...@br...* <cl...@br...> > > > > ------------------------------------------------------------------------------ > Site24x7 APM Insight: Get Deep Visibility into Application Performance > APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month > Monitor end-to-end web transactions and take corrective actions now > Troubleshoot faster and improve end-user experience. Signup Now! > http://pubads.g.doubleclick.net/gampad/clk?id=272487151&iu=/4140 > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > |
From: Claude F. <cl...@br...> - 2016-02-24 20:21:42
|
Dear colleagues, I've done a build from source of latest Matplotlib package and deployed it at our IBM z13 machine (s390x). It uses the current release 1.5.1. During the unit tests I found an issue with a test case from NOAA which uses a pcolormesh draw function with basemap. Example 2: Plot data from an NWW3 GRiB2 file - [ here: http://polar.ncep.noaa.gov/waves/examples/usingpython.shtml ] The following line is causing a Segmentation fault error even when adding an 8GB swap memory to the process: cs = m.pcolormesh(x,y,data,shading='flat',cmap=plt.cm.jet) I also tryed to execute other, similar samples that use pcolormesh, but receiving the same error. Is this a known issue or might it be be related to the memory environment ? Any hints how to debug this error? Regards, Claude Falbriard Certified IT Specialist L2 - Middleware Phone: 55-13-99662-5703 | Mobile: 55-13-98117-3316 E-mail: cl...@br... |
From: Nelle V. <nel...@gm...> - 2016-02-22 09:15:58
|
Dear all, SciPy 2016, the Fifteenth Annual Conference on Python in Science, takes place in Austin, TX on July, 11th to 17th. The conference features two days of tutorials by followed by three days of presentations, and concludes with two days of developer sprints on projects of interest to attendees. . The topics presented at SciPy are very diverse, with a focus on advanced software engineering and original uses of Python and its scientific libraries, either in theoretical or experimental research, from both academia and the industry. This year we are happy to announce two specialized tracks that run in parallel to the general conference (Data Science , High Performance Computing) and 8 mini-symposia (Earth and Space Science, Biology and Medicine, Engineering, Social Sciences, Special Purpose Databases, Case Studies in Industry, Education, Reproducibility) Submissions for talks and posters are welcome on our website ( http://scipy2016.scipy.org). In your abstract, please provide details on what Python tools are being employed, and how. The talk and poster submission deadline is March 25th, 2016, while the tutorial submission deadline is March, 21st, 2016. Important dates: Mar 21: Tutorial Proposals Due Mar 25: Talk and Poster Proposals Due May 11: Plotting Contest Submissions Due Apr 22: Tutorials Announced Apr 22: Financial Aid Submissions Due May 4: Talk and Posters Announced May 11: Financial Aid Recipients Notified May 22: Early Bird Registration Deadline Jul 11-12: SciPy 2016 Tutorials Jul 13-15: SciPy 2016 General Conference Jul 16-17: SciPy 2016 Sprints We look forward to an exciting conference and hope to see you in Austin in July! The Scipy 2016 http://scipy2016.scipy.org/ Conference Chairs: Aric Hagberg, Prabhu Ramachandran Tutorial Chairs: Justin Vincent, Ben Root Program Chair: Serge Rey, Nelle Varoquaux Proceeding Chairs: Sebastian Benthall |
From: Jesper L. <jes...@gm...> - 2016-02-15 08:19:04
|
Hi Matplotlib users, We are using Matplotlib for a web service which makes PNG images on the fly for presentation on a map (web site using the web service is here: https://ifm-beta.fcoo.dk) Performance and image size are two major concerns for us. We therefore save the resulting RGBA PNG to a buffer and afterwards use Pillow (PIL) to convert it to a P PNG (paletted PNG) to reduce the image size dramatically. This procedure does however use a significant amount of our total processing time per image. I would therefore be interested in extending e.g. the AGG backend to produce paletted PNGs directly. I am of course aware that this might not be useful for many others since one would have to provide some extra information when rendering with this backend (possibly output palette and quantizing method). But on the other hand it might be useful for others doing web services using matplotlib. My questions are: 1) Is it possible to extend the AGG backend for this and how? 2) Is it better to make a separate Pillow based backend for this (Pillow is probably not as fast as AGG)? Best regards, Jesper |
From: Sourish B. <sou...@gm...> - 2016-02-02 20:30:04
|
<html> <head> <meta http-equiv="content-type" content="text/html; charset=utf-8"> </head> <body text="#000000" bgcolor="#FFFFFF"> Hello all,<br> <br> I'm trying to use the shadedrelief() method to paint the background of a scatter plot, but it fails. The lines below are a minimal working example:<br> <br> <tt>In [1]: from mpl_toolkits.basemap import Basemap</tt><tt><br> </tt><tt>In [2]: world_map = Basemap(projection='cyl', llcrnrlat=-70., urcrnrlat=85., llcrnrlon=-180., urcrnrlon=180., resolution='l')</tt><tt><br> </tt><tt>In [3]: world_map.shadedrelief()</tt><tt><br> </tt><tt>---------------------------------------------------------------------------</tt><tt><br> </tt><tt>IndexError Traceback (most recent call last)</tt><tt><br> </tt><tt><ipython-input-3-2f6045a33141> in <module>()</tt><tt><br> </tt><tt>----> 1 world_map.shadedrelief()</tt><tt><br> </tt><tt><br> </tt><tt>/usr/local/lib/python2.7/dist-packages/mpl_toolkits/basemap/__init__.pyc in shadedrelief(self, ax, scale, **kwargs)</tt><tt><br> </tt><tt> 3997 return self.warpimage(image='shadedrelief',ax=ax,scale=scale,**kwargs)</tt><tt><br> </tt><tt> 3998 else:</tt><tt><br> </tt><tt>-> 3999 return self.warpimage(image='shadedrelief',scale=scale,**kwargs)</tt><tt><br> </tt><tt> 4000 </tt><tt><br> </tt><tt> 4001 def etopo(self,ax=None,scale=None,**kwargs):</tt><tt><br> </tt><tt><br> </tt><tt>/usr/local/lib/python2.7/dist-packages/mpl_toolkits/basemap/__init__.pyc in warpimage(self, image, scale, **kwargs)</tt><tt><br> </tt><tt> 4115 # any range of longitudes may be plotted on a world map.</tt><tt><br> </tt><tt> 4116 self._bm_lons = \</tt><tt><br> </tt><tt>-> 4117 np.concatenate((self._bm_lons,self._bm_lons+360),1)</tt><tt><br> </tt><tt> 4118 self._bm_rgba = \</tt><tt><br> </tt><tt> 4119 np.concatenate((self._bm_rgba,self._bm_rgba),1)</tt><tt><br> </tt><tt><br> </tt><tt>IndexError: axis 1 out of bounds [0, 1)</tt><br> <br> Anyone seen this error before? I'm using python 2.7.6, numpy 1.10.4, matplotlib 1.5.1 and basemap 1.0.7. The latter three were downloaded as source archives and installed using 'python setup.py install'.<br> <br> Thanks,<br> Sourish<br> <br> <div class="moz-signature">-- <br> <b>Q:</b> What if you strapped C4 to a boomerang? Could this be an effective weapon, or would it be as stupid as it sounds?<br> <b>A:</b> Aerodynamics aside, I’m curious what tactical advantage you’re expecting to gain by having the high explosive fly back at you if it misses the target.<br> </div> </body> </html> |
From: Julian I. <jul...@gm...> - 2016-01-31 19:53:30
|
Thanks for your suggestion Oscar. I tried editing the ticks like this, but this method removes both the tick marks and the labels. I think I have found a decent solution. Unfortunately my solution required a very particular order of operations. It is much less convenient than the functions provided in the API like tick_params(), which don't care if you have run plt.draw() ahead of time... 1) Run all of the setup for the plot and also the plotting commands (ax.plot(), ax.hist()...whatever) 2) Run `plt.draw()` because this updates the tick objects contained in your axes. 3) Grab your Tick objects: `ticks = ax.[x/y]axis.[major/minor]Ticks` 4) For each tick you want to hide do: `tick.tick1On = False` `tick.tick2On = False` The `1` and `2` refer to the bottom, top (left, right) for the x (y) axis respectively. 5) Run plt.show(), fig.show() or fig.savefig or whatever else you are using. Ahhhhh, no messy ticks in the corner! Julian On Fri, Jan 29, 2016 at 10:49 AM, Oscar Benjamin <osc...@gm... > wrote: > On 28 January 2016 at 19:49, Julian Irwin <jul...@gm...> wrote: > > > > > > I am looking for a way to hide tick marks (not the labels!) that > coincide with axis lines. I think this is a problem for me because of the > relative line thicknesses of my axis lines and tick marks, but I want to > leave those thicknesses unchanged (I like the look of the thickness > settings I am using now). > > Try this: > > from matplotlib import pyplot as plt > fig = plt.figure() > ax = fig.add_subplot(1, 1, 1) > ax.plot([0, 1], [0, 1]) > print(ax.get_xticks()) > ax.set_xticks(ax.get_xticks()[1:-1]) # Remove first and last ticks > print(ax.get_xticks()) > > -- > Oscar > |
From: Benjamin R. <ben...@gm...> - 2016-01-31 02:04:09
|
You've already done it. But we encourage you to take a crack at it. I would suggest just first factoring it out into a new file lib/matplotlib/hexbin.py and have the current function utilize it. When that is done, we can look to getting it into numpy as well. We will need a copy of it ourselves for compatibility with older releases of numpy. Let us know if you have questions! Ben Root On Jan 30, 2016 8:45 PM, "Sebastian" <se...@gm...> wrote: > Ahhhh thats too bad (that we can't recover the original ids.) > What could one (as user) do to officially request it be fixed/factored out > to numpy? > > > > On Fri, Jan 29, 2016 at 7:30 PM, Thomas Caswell <tca...@gm...> > wrote: > >> Factor it out and give it to numpy! >> >> On Fri, Jan 29, 2016, 17:27 Benjamin Root <ben...@gm...> wrote: >> >>> Hmm, you are right, there is no way to get back the information that >>> hexbin computed. The hexbin function is massive (in >>> lib/matplotlib/axes/_axes.py) and is a bit tangled up with the >>> artist-handling code, too. I think it would make sense to factor out the >>> hexbinning component into its own hexbin.py that others might be able to >>> use separately. >>> >>> Ben Root >>> >>> >>> On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote: >>> >>>> Is there a simple way to hexbin using "pyplot.hexbin" and to return >>>> the ids of the set of >>>> points in each hexbin? That is to output an array of n elements >>>> (one for each hexbin), and each element itself an array with the point >>>> ids? The sum >>>> of the number of inner elements would be equal the sum of all points >>>> (x,y). >>>> >>>> Is hexbin missing this simple feature? >>>> >>>> Or perhaps specifying C=N.arange(len(x)) then some specific >>>> "reduced_C_function" >>>> to return those elements. But I don't know if there is a >>>> "reduced_C_function" available, >>>> or perhaps one could be added? >>>> >>>> many thanks in advance... >>>> >>>> link: >>>> http://stackoverflow >>>> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the- >>>> hexbin-reduce-c-function/35088073#35088073 >>>> >>>> >>>> >>>> >>>> ------------------------------------------------------------------------------ >>>> Site24x7 APM Insight: Get Deep Visibility into Application Performance >>>> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month >>>> Monitor end-to-end web transactions and take corrective actions now >>>> Troubleshoot faster and improve end-user experience. Signup Now! >>>> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 >>>> _______________________________________________ >>>> Matplotlib-users mailing list >>>> Mat...@li... >>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >>>> >>>> >>> >>> ------------------------------------------------------------------------------ >>> Site24x7 APM Insight: Get Deep Visibility into Application Performance >>> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month >>> Monitor end-to-end web transactions and take corrective actions now >>> Troubleshoot faster and improve end-user experience. Signup Now! >>> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 >>> _______________________________________________ >>> Matplotlib-users mailing list >>> Mat...@li... >>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >>> >> > |
From: Sebastian <se...@gm...> - 2016-01-31 01:46:05
|
Ahhhh thats too bad (that we can't recover the original ids.) What could one (as user) do to officially request it be fixed/factored out to numpy? On Fri, Jan 29, 2016 at 7:30 PM, Thomas Caswell <tca...@gm...> wrote: > Factor it out and give it to numpy! > > On Fri, Jan 29, 2016, 17:27 Benjamin Root <ben...@gm...> wrote: > >> Hmm, you are right, there is no way to get back the information that >> hexbin computed. The hexbin function is massive (in >> lib/matplotlib/axes/_axes.py) and is a bit tangled up with the >> artist-handling code, too. I think it would make sense to factor out the >> hexbinning component into its own hexbin.py that others might be able to >> use separately. >> >> Ben Root >> >> >> On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote: >> >>> Is there a simple way to hexbin using "pyplot.hexbin" and to return the >>> ids of the set of >>> points in each hexbin? That is to output an array of n elements >>> (one for each hexbin), and each element itself an array with the point >>> ids? The sum >>> of the number of inner elements would be equal the sum of all points >>> (x,y). >>> >>> Is hexbin missing this simple feature? >>> >>> Or perhaps specifying C=N.arange(len(x)) then some specific >>> "reduced_C_function" >>> to return those elements. But I don't know if there is a >>> "reduced_C_function" available, >>> or perhaps one could be added? >>> >>> many thanks in advance... >>> >>> link: >>> http://stackoverflow >>> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the- >>> hexbin-reduce-c-function/35088073#35088073 >>> >>> >>> >>> >>> ------------------------------------------------------------------------------ >>> Site24x7 APM Insight: Get Deep Visibility into Application Performance >>> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month >>> Monitor end-to-end web transactions and take corrective actions now >>> Troubleshoot faster and improve end-user experience. Signup Now! >>> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 >>> _______________________________________________ >>> Matplotlib-users mailing list >>> Mat...@li... >>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >>> >>> >> >> ------------------------------------------------------------------------------ >> Site24x7 APM Insight: Get Deep Visibility into Application Performance >> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month >> Monitor end-to-end web transactions and take corrective actions now >> Troubleshoot faster and improve end-user experience. Signup Now! >> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 >> _______________________________________________ >> Matplotlib-users mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >> > |
From: Fernando P. <fpe...@gm...> - 2016-01-30 01:20:19
|
On Fri, Jan 29, 2016 at 8:25 AM, Andreas Mueller <t3...@gm...> wrote: > Thanks for your input Fernando. > I thought about cross-posting to Jupyter, but I'm glad you also saw it > here :) > That would help, but not solve all problems. > I guess the Figure could hold a tag for referencing, too. It would be nice > to get a tag and caption from matplotlib. > Maybe Benjamin's reply would help with that. But it sounds like the figure > has a single string attached (which is more the tag). > I guess I can do > IPython.display.Figure(matplotlib_figure, caption="stuff", tag="tag") > That would be acceptable, I think. > Yes, I'd forgotten about the label ("label" is the LaTeX name for what you're calling "tag" here). > But how do I reference that in a markup cell? [maybe I should move that > question to the jupyter list, though] > Yup, this is the slightly trickier part. A sketch of the solution, we need to: - generate a local anchor element for the labeled output. That's the easier part, it would be the job of the displayed output from this hypothetical Figure() object. It needs to wrap the output in `<a name=label>... </a>`. - For markdown referencing, you simply do [link text](#label). - The problem would be latex conversion: by default, the above is converted to \protect\hyperlink{label}{link text} where as you want a \ref{label} call instead. - You also want this to generate the Internal cross-referencing is one of Markdown's main weaknesses for complex more document-oriented workflows that aren't purely HTML oriented. Markdown is really a thin wrapper around HTML, so it doesn't expose the rich labeling/referencing semantics of rST or LaTeX. I didn't say this was a done deal, and there might be some tricky edges to it :) Cheers f -- Fernando Perez (@fperez_org; http://fperez.org) fperez.net-at-gmail: mailing lists only (I ignore this when swamped!) fernando.perez-at-berkeley: contact me here for any direct mail |
From: Thomas C. <tca...@gm...> - 2016-01-29 22:31:06
|
Factor it out and give it to numpy! On Fri, Jan 29, 2016, 17:27 Benjamin Root <ben...@gm...> wrote: > Hmm, you are right, there is no way to get back the information that > hexbin computed. The hexbin function is massive (in > lib/matplotlib/axes/_axes.py) and is a bit tangled up with the > artist-handling code, too. I think it would make sense to factor out the > hexbinning component into its own hexbin.py that others might be able to > use separately. > > Ben Root > > > On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote: > >> Is there a simple way to hexbin using "pyplot.hexbin" and to return the >> ids of the set of >> points in each hexbin? That is to output an array of n elements >> (one for each hexbin), and each element itself an array with the point >> ids? The sum >> of the number of inner elements would be equal the sum of all points >> (x,y). >> >> Is hexbin missing this simple feature? >> >> Or perhaps specifying C=N.arange(len(x)) then some specific >> "reduced_C_function" >> to return those elements. But I don't know if there is a >> "reduced_C_function" available, >> or perhaps one could be added? >> >> many thanks in advance... >> >> link: >> http://stackoverflow >> .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the- >> hexbin-reduce-c-function/35088073#35088073 >> >> >> >> >> ------------------------------------------------------------------------------ >> Site24x7 APM Insight: Get Deep Visibility into Application Performance >> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month >> Monitor end-to-end web transactions and take corrective actions now >> Troubleshoot faster and improve end-user experience. Signup Now! >> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 >> _______________________________________________ >> Matplotlib-users mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >> >> > > ------------------------------------------------------------------------------ > Site24x7 APM Insight: Get Deep Visibility into Application Performance > APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month > Monitor end-to-end web transactions and take corrective actions now > Troubleshoot faster and improve end-user experience. Signup Now! > http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |
From: Benjamin R. <ben...@gm...> - 2016-01-29 22:27:13
|
Hmm, you are right, there is no way to get back the information that hexbin computed. The hexbin function is massive (in lib/matplotlib/axes/_axes.py) and is a bit tangled up with the artist-handling code, too. I think it would make sense to factor out the hexbinning component into its own hexbin.py that others might be able to use separately. Ben Root On Fri, Jan 29, 2016 at 5:15 PM, Sebastian <se...@gm...> wrote: > Is there a simple way to hexbin using "pyplot.hexbin" and to return the > ids of the set of > points in each hexbin? That is to output an array of n elements > (one for each hexbin), and each element itself an array with the point > ids? The sum > of the number of inner elements would be equal the sum of all points (x,y). > > Is hexbin missing this simple feature? > > Or perhaps specifying C=N.arange(len(x)) then some specific > "reduced_C_function" > to return those elements. But I don't know if there is a > "reduced_C_function" available, > or perhaps one could be added? > > many thanks in advance... > > link: > http://stackoverflow > .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the- > hexbin-reduce-c-function/35088073#35088073 > > > > > ------------------------------------------------------------------------------ > Site24x7 APM Insight: Get Deep Visibility into Application Performance > APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month > Monitor end-to-end web transactions and take corrective actions now > Troubleshoot faster and improve end-user experience. Signup Now! > http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > |
From: Sebastian <se...@gm...> - 2016-01-29 22:16:02
|
Is there a simple way to hexbin using "pyplot.hexbin" and to return the ids of the set of points in each hexbin? That is to output an array of n elements (one for each hexbin), and each element itself an array with the point ids? The sum of the number of inner elements would be equal the sum of all points (x,y). Is hexbin missing this simple feature? Or perhaps specifying C=N.arange(len(x)) then some specific "reduced_C_function" to return those elements. But I don't know if there is a "reduced_C_function" available, or perhaps one could be added? many thanks in advance... link: http://stackoverflow .com/questions/18886461/how-can-i-print-a-list-of-the-outputs-from-the- hexbin-reduce-c-function/35088073#35088073 |
From: Oscar B. <osc...@gm...> - 2016-01-29 16:50:10
|
On 28 January 2016 at 19:49, Julian Irwin <jul...@gm...> wrote: > > > I am looking for a way to hide tick marks (not the labels!) that coincide with axis lines. I think this is a problem for me because of the relative line thicknesses of my axis lines and tick marks, but I want to leave those thicknesses unchanged (I like the look of the thickness settings I am using now). Try this: from matplotlib import pyplot as plt fig = plt.figure() ax = fig.add_subplot(1, 1, 1) ax.plot([0, 1], [0, 1]) print(ax.get_xticks()) ax.set_xticks(ax.get_xticks()[1:-1]) # Remove first and last ticks print(ax.get_xticks()) -- Oscar |
From: Andreas M. <t3...@gm...> - 2016-01-29 16:25:50
|
Thanks for your input Fernando. I thought about cross-posting to Jupyter, but I'm glad you also saw it here :) That would help, but not solve all problems. I guess the Figure could hold a tag for referencing, too. It would be nice to get a tag and caption from matplotlib. Maybe Benjamin's reply would help with that. But it sounds like the figure has a single string attached (which is more the tag). I guess I can do IPython.display.Figure(matplotlib_figure, caption="stuff", tag="tag") That would be acceptable, I think. But how do I reference that in a markup cell? [maybe I should move that question to the jupyter list, though] On 01/28/2016 10:17 PM, Fernando Perez wrote: > On Thu, Jan 28, 2016 at 3:23 PM, Andreas Mueller <t3...@gm... > <mailto:t3...@gm...>> wrote: > > Hi all. > > This is about a joint jupyter-notebook / matplotlib problem I've been > thinking about. > So I'm writing a book using jupyter-notebook, and all my figures are > generated using matplotlib. > > In books, there is usually a figure caption with a running number and > some description. > From what I read, the best way to add captions is just using > plt.text. > However, the caption should probably be in the markup, > not in a rendered PNG. I'm not sure if changing the backend might > help, > but that probably doesn't make the notebook happy? > > The other problem is that I want to have running numbers that I can > refer to by a tag (as you would in latex). > That is more of a notebook problem, though. > > Any feedback would be very welcome > > > I've been wanting to do something about this problem for a while, but > haven't had the cycles to work on it... Here's my current idea, > perhaps I can goad you into implementing it :) > > I think that IPython.display should provide a Figure object, capable > of wrapping any input image (with nice code to automatically swallow a > matplotlib figure without asking the user to convert it to an image > first), and taking an optional caption. > > Figure() would then produce as output the displayed image but with a > bit of nice CSS to center it on the page, along with the caption. > > The trick is to send the entire data bundle correctly structured so > that, at the other end, nbconvert could recognize these figures as > such, and not only produce nice HTML, but more importantly, push them > into the LaTeX output with the correct call to \figure, including > \caption as well as size and placement specifiers. > > The signature of Figure() might be something like > > def Figure(fig, caption=None, width=None, height=None, > latex_placement=None): > > > I would try implementing this first as a standalone tool, and once > it's been tested enough in real-world usage with both HTML and LaTeX > output from nbconvert, it could be merged in. I suspect it's going to > take a few iterations to get it right. > > But it's not particularly hard, and someone working on a book would be > the perfect candidate to have enough test cases to be able to iterate > until happy ;) > > If you think you want to take a stab at this, don't hesitate to ping > us on the jupyter list. We can help with some of the more obscure > parts of getting this to work on nbconvert (and there may be things > I've overlooked in the sketch above). > > Cheers, > > f > > -- > Fernando Perez (@fperez_org; http://fperez.org) > fperez.net-at-gmail: mailing lists only (I ignore this when swamped!) > fernando.perez-at-berkeley: contact me here for any direct mail |
From: Benjamin R. <ben...@gm...> - 2016-01-29 04:03:21
|
In mpl, our figure objects get numbers assigned to them by default, but they can also be strings. These labels are used in the figure window title bar. Perhaps that existing data could be hijacked? Admittedly, most people use the string name to give nice short names to their figures, so maybe those names could be the "tag" name in latex? So, all we would need is some way to supply the actual caption string. Ben Root On Thu, Jan 28, 2016 at 10:17 PM, Fernando Perez <fpe...@gm...> wrote: > On Thu, Jan 28, 2016 at 3:23 PM, Andreas Mueller <t3...@gm...> wrote: > >> Hi all. >> >> This is about a joint jupyter-notebook / matplotlib problem I've been >> thinking about. >> So I'm writing a book using jupyter-notebook, and all my figures are >> generated using matplotlib. >> >> In books, there is usually a figure caption with a running number and >> some description. >> From what I read, the best way to add captions is just using plt.text. >> However, the caption should probably be in the markup, >> not in a rendered PNG. I'm not sure if changing the backend might help, >> but that probably doesn't make the notebook happy? >> >> The other problem is that I want to have running numbers that I can >> refer to by a tag (as you would in latex). >> That is more of a notebook problem, though. >> >> Any feedback would be very welcome >> > > I've been wanting to do something about this problem for a while, but > haven't had the cycles to work on it... Here's my current idea, perhaps I > can goad you into implementing it :) > > I think that IPython.display should provide a Figure object, capable of > wrapping any input image (with nice code to automatically swallow a > matplotlib figure without asking the user to convert it to an image first), > and taking an optional caption. > > Figure() would then produce as output the displayed image but with a bit > of nice CSS to center it on the page, along with the caption. > > The trick is to send the entire data bundle correctly structured so that, > at the other end, nbconvert could recognize these figures as such, and not > only produce nice HTML, but more importantly, push them into the LaTeX > output with the correct call to \figure, including \caption as well as size > and placement specifiers. > > The signature of Figure() might be something like > > def Figure(fig, caption=None, width=None, height=None, > latex_placement=None): > > > I would try implementing this first as a standalone tool, and once it's > been tested enough in real-world usage with both HTML and LaTeX output from > nbconvert, it could be merged in. I suspect it's going to take a few > iterations to get it right. > > But it's not particularly hard, and someone working on a book would be the > perfect candidate to have enough test cases to be able to iterate until > happy ;) > > If you think you want to take a stab at this, don't hesitate to ping us on > the jupyter list. We can help with some of the more obscure parts of > getting this to work on nbconvert (and there may be things I've overlooked > in the sketch above). > > Cheers, > > f > > -- > Fernando Perez (@fperez_org; http://fperez.org) > fperez.net-at-gmail: mailing lists only (I ignore this when swamped!) > fernando.perez-at-berkeley: contact me here for any direct mail > > > ------------------------------------------------------------------------------ > Site24x7 APM Insight: Get Deep Visibility into Application Performance > APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month > Monitor end-to-end web transactions and take corrective actions now > Troubleshoot faster and improve end-user experience. Signup Now! > http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > |
From: Fernando P. <fpe...@gm...> - 2016-01-29 03:18:10
|
On Thu, Jan 28, 2016 at 3:23 PM, Andreas Mueller <t3...@gm...> wrote: > Hi all. > > This is about a joint jupyter-notebook / matplotlib problem I've been > thinking about. > So I'm writing a book using jupyter-notebook, and all my figures are > generated using matplotlib. > > In books, there is usually a figure caption with a running number and > some description. > From what I read, the best way to add captions is just using plt.text. > However, the caption should probably be in the markup, > not in a rendered PNG. I'm not sure if changing the backend might help, > but that probably doesn't make the notebook happy? > > The other problem is that I want to have running numbers that I can > refer to by a tag (as you would in latex). > That is more of a notebook problem, though. > > Any feedback would be very welcome > I've been wanting to do something about this problem for a while, but haven't had the cycles to work on it... Here's my current idea, perhaps I can goad you into implementing it :) I think that IPython.display should provide a Figure object, capable of wrapping any input image (with nice code to automatically swallow a matplotlib figure without asking the user to convert it to an image first), and taking an optional caption. Figure() would then produce as output the displayed image but with a bit of nice CSS to center it on the page, along with the caption. The trick is to send the entire data bundle correctly structured so that, at the other end, nbconvert could recognize these figures as such, and not only produce nice HTML, but more importantly, push them into the LaTeX output with the correct call to \figure, including \caption as well as size and placement specifiers. The signature of Figure() might be something like def Figure(fig, caption=None, width=None, height=None, latex_placement=None): I would try implementing this first as a standalone tool, and once it's been tested enough in real-world usage with both HTML and LaTeX output from nbconvert, it could be merged in. I suspect it's going to take a few iterations to get it right. But it's not particularly hard, and someone working on a book would be the perfect candidate to have enough test cases to be able to iterate until happy ;) If you think you want to take a stab at this, don't hesitate to ping us on the jupyter list. We can help with some of the more obscure parts of getting this to work on nbconvert (and there may be things I've overlooked in the sketch above). Cheers, f -- Fernando Perez (@fperez_org; http://fperez.org) fperez.net-at-gmail: mailing lists only (I ignore this when swamped!) fernando.perez-at-berkeley: contact me here for any direct mail |
From: Andreas M. <t3...@gm...> - 2016-01-28 23:23:54
|
Hi all. This is about a joint jupyter-notebook / matplotlib problem I've been thinking about. So I'm writing a book using jupyter-notebook, and all my figures are generated using matplotlib. In books, there is usually a figure caption with a running number and some description. From what I read, the best way to add captions is just using plt.text. However, the caption should probably be in the markup, not in a rendered PNG. I'm not sure if changing the backend might help, but that probably doesn't make the notebook happy? The other problem is that I want to have running numbers that I can refer to by a tag (as you would in latex). That is more of a notebook problem, though. Any feedback would be very welcome. Cheers, Andy |
From: Julian I. <jul...@gm...> - 2016-01-28 19:49:59
|
Hello, I am looking for a way to hide tick marks (not the labels!) that coincide with axis lines. I think this is a problem for me because of the relative line thicknesses of my axis lines and tick marks, but I want to leave those thicknesses unchanged (I like the look of the thickness settings I am using now). Here is a screenshot of what I'm talking about: [image: Inline image 1] I know this looks minor, but it is quite obvious on some plots and I'd really like to get rid of it. Thanks, Julian Irwin |
From: Fabrice S. <si...@lm...> - 2016-01-28 17:03:39
|
Le mercredi 27 janvier 2016, Matteo Niccoli a écrit : > Can something like this (which by the way I can't get to work): > http://stackoverflow.com/questions/3114925/pil-convert-rgb-image-to-a > -specific-8-bit-palette > > What I would like to do is this: > 1) Import an RGB image, which would have its own colormap - say this > one for example: > https://upload.wikimedia.org/wikipedia/commons/b/b3/Jupiter_new_hubble_view_above_pole.png > 2) convert it to intensity, display the intensity color-mapped to the > same colours the original RGB had. According to the PNG header, this image does not have a palette (i.e. a list of colors). The data chunks define the image as an array of NxMx3 values (N rows, M cols, 3 channels=no alpha), each value being defined using 8 bits. I may however badly understand what you call the "own colormap"... You still can convert it to a grayscale img representing the intensity (NxM values), but you then lose some information and you cannot display it back with the same colors as originally. Because some different RGB tuple are converted into the same intensity level, you can then not discriminate them using the intensity image only. Maybe there is some trick to convert to a grayscale image where those RGB values are converted to almost-equal-but-different intensity levels that would enable the later reconstruction, but I am not aware of... Fabrice |
From: Benjamin R. <ben...@gm...> - 2016-01-28 15:39:52
|
You might have better luck asking the scikit-image people, or the Pillow people. ImageMagick might also have what you are looking for. Cheers! Ben Root On Wed, Jan 27, 2016 at 11:23 PM, Matteo Niccoli <ma...@my...> wrote: > Can something like this (which by the way I can't get to work): > > http://stackoverflow.com/questions/3114925/pil-convert-rgb-image-to-a-specific-8-bit-palette > > What I would like to do is this: > 1) Import an RGB image, which would have its own colormap - say this one > for example: > > https://upload.wikimedia.org/wikipedia/commons/b/b3/Jupiter_new_hubble_view_above_pole.png > > 2) convert it to intensity, display the intensity color-mapped to the same > colours the original RGB had. > > Any tips, or even better code or pseudocode would be greatly appreciated. > > Thanks > Matteo > > > > ------------------------------------------------------------------------------ > Site24x7 APM Insight: Get Deep Visibility into Application Performance > APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month > Monitor end-to-end web transactions and take corrective actions now > Troubleshoot faster and improve end-user experience. Signup Now! > http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |
From: Matteo N. <ma...@my...> - 2016-01-28 04:59:58
|
Can something like this (which by the way I can't get to work): http://stackoverflow.com/questions/3114925/pil-convert-rgb-image-to-a-specific-8-bit-palette What I would like to do is this: 1) Import an RGB image, which would have its own colormap - say this one for example: https://upload.wikimedia.org/wikipedia/commons/b/b3/Jupiter_new_hubble_view_above_pole.png 2) convert it to intensity, display the intensity color-mapped to the same colours the original RGB had. Any tips, or even better code or pseudocode would be greatly appreciated. Thanks Matteo |
From: Benjamin R. <ben...@gm...> - 2016-01-20 20:00:13
|
Add "blit=False" in the instantiation for multicursor to get around the copy_from_bbox issue. I wonder if the use of fig.axes might be a problem? On Jan 20, 2016 2:27 PM, "Bilheux, Jean-Christophe" <bil...@or...> wrote: > HI all, > > I wanted to help (for a change) but running the script on mac (with the > multi cursor code commented out), I got the following error. If anyone can > figure out why ! > > File > "/Users/j35/anaconda/lib/python3.4/site-packages/matplotlib/widgets.py", > line 1046, in clear > self.canvas.copy_from_bbox(self.canvas.figure.bbox)) > AttributeError: 'FigureCanvasMac' object has no attribute ‘copy_from_bbox' > > I’m using python 3.4 and matplotlib 1.4.3 > > Thanks > > Jean > > > > > On Jan 20, 2016, at 1:26 PM, Michael Kaufman <kau...@or...> wrote: > > > > Hi Gurus: > > > > I'm having a serious problem with MultiCursor and autoscaling... > > > > If I do the code below with both MultiCursor instantiations commented > out, then all plots are xscaled to [50,55] and yscaled to each plot's > appropriate ylimits. > > > > If I uncomment the top MultiCursor instantiation, then both the xlimits > and ylimits are screwed up: xlim=[0,60] and ylim is all over the place, > certainly not autoscaled tight. > > > > If I uncomment the bottom MultiCursor instantiation, then the xlimit > appears to be scaled correctly, [50,55], but two of the four plots (lower > left and upper right) are not autoscaled in y. > > > > How to I instantiate MultiCursor to get the normal and expected > autoscaling behavior? > > > > Not that it should matter, but I'm using here Tk and Python3 with MPL > 1.5dev1 (91ca2a3724ae91d28d97) > > > > Thanks for any help, > > > > M > > > > ============= > > > > from matplotlib import pyplot as pl > > from matplotlib.widgets import MultiCursor > > from matplotlib import gridspec > > import numpy as np > > > > if __name__ == "__main__": > > > > fig = pl.gcf() > > gs = gridspec.GridSpec(2,2) > > > > ax = None > > for g in gs: > > ax = pl.subplot(g, sharex=ax) > > > > #multi = MultiCursor(fig.canvas, tuple(fig.axes), > > # useblit=True, horizOn=True, color='k', lw=1) > > > > x = np.arange(50,55,0.01) > > y1 = np.sin(x) > > y2 = np.cos(x) + 4 > > y3 = 0.2*np.cos(x) - 4 > > y4 = np.cos(2*x) - 1 > > > > for ax,y in zip(fig.axes, [y1,y2,y3,y4]): > > ax.plot(x,y) > > > > for ax in fig.axes: > > ax.grid() > > > > #multi = MultiCursor(fig.canvas, tuple(fig.axes), > > # useblit=True, horizOn=True, color='k', lw=1) > > > > pl.draw() > > pl.show() > > > <multicursor_limtest.py>------------------------------------------------------------------------------ > > Site24x7 APM Insight: Get Deep Visibility into Application Performance > > APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month > > Monitor end-to-end web transactions and take corrective actions now > > Troubleshoot faster and improve end-user experience. Signup Now! > > > http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140_______________________________________________ > > Matplotlib-users mailing list > > Mat...@li... > > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > > ------------------------------------------------------------------------------ > Site24x7 APM Insight: Get Deep Visibility into Application Performance > APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month > Monitor end-to-end web transactions and take corrective actions now > Troubleshoot faster and improve end-user experience. Signup Now! > http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |
From: Bilheux, Jean-C. <bil...@or...> - 2016-01-20 19:24:14
|
HI all, I wanted to help (for a change) but running the script on mac (with the multi cursor code commented out), I got the following error. If anyone can figure out why ! File "/Users/j35/anaconda/lib/python3.4/site-packages/matplotlib/widgets.py", line 1046, in clear self.canvas.copy_from_bbox(self.canvas.figure.bbox)) AttributeError: 'FigureCanvasMac' object has no attribute ‘copy_from_bbox' I’m using python 3.4 and matplotlib 1.4.3 Thanks Jean > On Jan 20, 2016, at 1:26 PM, Michael Kaufman <kau...@or...> wrote: > > Hi Gurus: > > I'm having a serious problem with MultiCursor and autoscaling... > > If I do the code below with both MultiCursor instantiations commented out, then all plots are xscaled to [50,55] and yscaled to each plot's appropriate ylimits. > > If I uncomment the top MultiCursor instantiation, then both the xlimits and ylimits are screwed up: xlim=[0,60] and ylim is all over the place, certainly not autoscaled tight. > > If I uncomment the bottom MultiCursor instantiation, then the xlimit appears to be scaled correctly, [50,55], but two of the four plots (lower left and upper right) are not autoscaled in y. > > How to I instantiate MultiCursor to get the normal and expected autoscaling behavior? > > Not that it should matter, but I'm using here Tk and Python3 with MPL 1.5dev1 (91ca2a3724ae91d28d97) > > Thanks for any help, > > M > > ============= > > from matplotlib import pyplot as pl > from matplotlib.widgets import MultiCursor > from matplotlib import gridspec > import numpy as np > > if __name__ == "__main__": > > fig = pl.gcf() > gs = gridspec.GridSpec(2,2) > > ax = None > for g in gs: > ax = pl.subplot(g, sharex=ax) > > #multi = MultiCursor(fig.canvas, tuple(fig.axes), > # useblit=True, horizOn=True, color='k', lw=1) > > x = np.arange(50,55,0.01) > y1 = np.sin(x) > y2 = np.cos(x) + 4 > y3 = 0.2*np.cos(x) - 4 > y4 = np.cos(2*x) - 1 > > for ax,y in zip(fig.axes, [y1,y2,y3,y4]): > ax.plot(x,y) > > for ax in fig.axes: > ax.grid() > > #multi = MultiCursor(fig.canvas, tuple(fig.axes), > # useblit=True, horizOn=True, color='k', lw=1) > > pl.draw() > pl.show() > <multicursor_limtest.py>------------------------------------------------------------------------------ > Site24x7 APM Insight: Get Deep Visibility into Application Performance > APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month > Monitor end-to-end web transactions and take corrective actions now > Troubleshoot faster and improve end-user experience. Signup Now! > http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140_______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users |
From: Michael K. <kau...@or...> - 2016-01-20 18:26:13
|
Hi Gurus: I'm having a serious problem with MultiCursor and autoscaling... If I do the code below with both MultiCursor instantiations commented out, then all plots are xscaled to [50,55] and yscaled to each plot's appropriate ylimits. If I uncomment the top MultiCursor instantiation, then both the xlimits and ylimits are screwed up: xlim=[0,60] and ylim is all over the place, certainly not autoscaled tight. If I uncomment the bottom MultiCursor instantiation, then the xlimit appears to be scaled correctly, [50,55], but two of the four plots (lower left and upper right) are not autoscaled in y. How to I instantiate MultiCursor to get the normal and expected autoscaling behavior? Not that it should matter, but I'm using here Tk and Python3 with MPL 1.5dev1 (91ca2a3724ae91d28d97) Thanks for any help, M ============= from matplotlib import pyplot as pl from matplotlib.widgets import MultiCursor from matplotlib import gridspec import numpy as np if __name__ == "__main__": fig = pl.gcf() gs = gridspec.GridSpec(2,2) ax = None for g in gs: ax = pl.subplot(g, sharex=ax) #multi = MultiCursor(fig.canvas, tuple(fig.axes), # useblit=True, horizOn=True, color='k', lw=1) x = np.arange(50,55,0.01) y1 = np.sin(x) y2 = np.cos(x) + 4 y3 = 0.2*np.cos(x) - 4 y4 = np.cos(2*x) - 1 for ax,y in zip(fig.axes, [y1,y2,y3,y4]): ax.plot(x,y) for ax in fig.axes: ax.grid() #multi = MultiCursor(fig.canvas, tuple(fig.axes), # useblit=True, horizOn=True, color='k', lw=1) pl.draw() pl.show() |
From: Sudheer J. <sud...@ya...> - 2016-01-07 09:37:44
|
Dear experts, I tried to use the matplotlib function plt.xcorr for calculating cross correlation between to check its functionality using the data from a standard example given in R web site example. https://onlinecourses.science.psu.edu/stat510/node/74 However when the example given above is replicated using python I get a totally different graph. Any idea why this happens? I tried normed=True but do not appears to have any effect. Any advice on this will be of extreme help import urllib as web from matplotlib import pylab as plt f=web.urlopen('http://anson.ucdavis.edu/~shumway/soi.dat') soi=[] for line in f: soi.append(float(line.strip())) f.close() rec=[] f=web.urlopen('http://anson.ucdavis.edu/~shumway/recruit.dat') for line in f: rec.append(float(line.strip())) ax=plt.figure() anl_ccf=plt.xcorr(soi,rec,maxlags=30) plt.show() With best regards, Sudheer |