Mailman 3 January 2016 - Matplotlib-users

em-dash not correctly displayed in saved pdf when using tex
by Chao-Chin Yang March 15, 2016

March 15, 2016

Hi, I am having issues with producing an em-dash in pdf when using tex. A sample script is as below: #!/usr/bin/env python3 import matplotlib.pyplot as plt import math import numpy as np x = np.linspace(0, 2 * math.pi) y = np.cos(x) plt.plot(x, y) plt.suptitle(r"abc --- def") plt.savefig("test.pdf") plt.show() I have customized rc parameters: backend = “TkAgg” font.family = “serif” text.usetex = True image.cmap = “CMRmap" The plot rendered on screen looks fine. However, there are some weird characters showing up right before the em-dash in the saved pdf, as attached here. I am using Linux Mint 17.3, and uname -a gives Linux Eridanus 3.19.0-32-generic #37~14.04.1-Ubuntu SMP Thu Oct 22 09:41:40 UTC 2015 x86_64 x86_64 x86_64 GNU/Linux I am using python 3.4.3 + matplotlib 1.3.1, the latter of which is kind of old, but still remains the latest in the Ubuntu LTS repository. On the other had, I have installed the texlive-full package, which should include all the tex related packages. My dvipng is 1.14, and my ghostscript is 9.10. I have also tried different backends like Agg or PDF, but it makes no difference. I have tried googling around for similar issues, but had no luck. It would be very much appreciated If anyone had some idea how this comes about. Sincerely, Chao-Chin

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Editing legend labels
by Lorenzo De Leo Feb. 6, 2016

Feb. 6, 2016

Hello, I have a problem with the way the legend labels are handled, certainly due to my poor knowledge of matplotlib internals. Here an example (matplotlib-1.4.3, py-2.7): In [1]: import matplotlib.pyplot as plt In [2]: plt.plot([1,2,3], label='A') Out[2]: [<matplotlib.lines.Line2D at 0x7f60749be310>] In [3]: plt.plot([2,3,4], label='B') Out[3]: [<matplotlib.lines.Line2D at 0x7f60749f1850>] In [4]: ax = plt.gca() In [5]: l = ax.get_legend_handles_labels() In [6]: l Out[6]: ([<matplotlib.lines.Line2D at 0x7f60749be310>, <matplotlib.lines.Line2D at 0x7f60749f1850>], [u'A', u'B']) In [7]: plt.legend(['C', 'D']) ### This correctly modifies the legend to show 'C' and 'D', but then ... Out[7]: <matplotlib.legend.Legend at 0x7f6081dce190> In [10]: l = ax.get_legend_handles_labels() In [11]: l Out[11]: ([<matplotlib.lines.Line2D at 0x7f60749be310>, <matplotlib.lines.Line2D at 0x7f60749f1850>], [u'A', u'B']) At this point I have no idea how to retrieve the list of shown labels, i.e. ['C', 'D']. What am I missing? What other method should I use? Thanks in advance

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Totaly new to matplotlib
by Stevo Jan. 29, 2016

Jan. 29, 2016

Hi guys, Im new to Python and matplotlib, I have a need to try and make a chart of some kind so was just searching around and looking at Plotly but it looks so complicated then I found the matplotlib site and was quite amazed how simple the code was to create some really incredible looking plots. Unfortunately none of the examples are quite what Im needing but Im guessing that is possible to create what i need as by the look of the gallery it would be a breeze for you experienced guys. The data I want to plot is durations during days (its a sort of working time/clock machine plot).... I imagine it to be a cross between the histogram_path_demo and one of those candle stick type ones, x being the day's time range centre of range being say lunchtime and each bar showing the shift start and end (centred on 12 lunchtime) but allowing for the bar to be broken when ever clocked in or out within that day.. if that makes sense ? Im very unsure even where to start so any pointers and advise would be greatly appreciated. Cheers Stevo -- View this message in context: http://matplotlib.1069221.n5.nabble.com/Totaly-new-to-matplotlib-tp46682.ht… Sent from the matplotlib - users mailing list archive at Nabble.com.

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matploltib use gpu ?
by nice Jan. 29, 2016

Jan. 29, 2016

Hello, i have a question. I'm in Python 3.5, and can i use matploltib with GPU ?, can i use OpenGL or PyOpenCL implemnetation for matploltib ? Thanks for advance. -- View this message in context: http://matplotlib.1069221.n5.nabble.com/matploltib-use-gpu-tp46633.html Sent from the matplotlib - users mailing list archive at Nabble.com.

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Re: [Matplotlib-users] matploltib use gpu ?
by Jon Roadley-Battin Jan. 29, 2016

Jan. 29, 2016

> > On Mon, Jan 25, 2016 at 12:35 PM, nice <sazearte(a)live.fr> wrote: > > > My problem: I have about 10 million point to plot. > > > > with this example, moving in the graph is very slow. > > Is there a way to have an intelligent zoom which removes invisible items > on > > the eye? > > > > > > > > import matplotlib > > matplotlib.use('TkAgg') > > import numpy > > from numpy import arange, sin, pi > > from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, > > NavigationToolbar2TkAgg > > from matplotlib.figure import Figure > > import tkinter as Tk > > > > root = Tk.Tk() > > root.wm_title("Embedding in TK") > > > > > > f = Figure(figsize=(5, 4), dpi=100) > > a = f.add_subplot(111) > > > > > > t = arange(0.0, 10000000, 1) > > s = arange(0.0, 10000000, 1) > > a.plot(t, s) > > > > > > canvas = FigureCanvasTkAgg(f, master=root) > > canvas.show() > > canvas.get_tk_widget().pack(side=Tk.TOP, fill=Tk.BOTH, expand=1) > > > > toolbar = NavigationToolbar2TkAgg(canvas, root) > > toolbar.update() > > canvas._tkcanvas.pack(side=Tk.TOP, fill=Tk.BOTH, expand=1) > > > > > > def _quit(): > > root.quit() > > root.destroy() > > > > button = Tk.Button(master=root, text='Exit', command=_quit) > > button.pack(side=Tk.BOTTOM) > > > > Tk.mainloop() > Afternoon, Have you considered enabling Rasterization? a.plot(t, s, rasterized=True)

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Automatic adjustment of labels - adjustText
by Phlya Jan. 15, 2016

Jan. 15, 2016

Hi all, I would like to share my mini-library to automatically adjust text labels on matplotlib plots to minimize overlaps between them and with data points - adjustText: https://github.com/Phlya/adjustText It was inspired by ggrepel - a similar package for R/ggplot2, and performs almost as well as that one. Would love to hear your feedback! (Not yet on pypi, but hopefully should be installable by pip directly from github) -- View this message in context: http://matplotlib.1069221.n5.nabble.com/Automatic-adjustment-of-labels-adju… Sent from the matplotlib - users mailing list archive at Nabble.com.

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Re: [Matplotlib-users] Problem with "set_array" function
by eadsjr Jan. 15, 2016

Jan. 15, 2016

Try adding a matplotlib.pyplot.pause(0) immediately after your 'self.im.set_array(welldata)'. The pause forces it to display the changed data. For anyone who finds this. -- View this message in context: http://matplotlib.1069221.n5.nabble.com/Problem-with-set-array-function-tp3… Sent from the matplotlib - users mailing list archive at Nabble.com.

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Automatic adjustment of text labels - adjustText
by Phlya Jan. 14, 2016

Jan. 14, 2016

Hi all, I would like to share my mini-library to automatically adjust text labels on matplotlib plots to minimize overlaps between them and with data points - adjustText: https://github.com/Phlya/adjustText It's very easy to use and quite configurable for adjusting to particular use cases. Would love to hear your feedback! Best wishes, Ilya -- View this message in context: http://matplotlib.1069221.n5.nabble.com/Automatic-adjustment-of-text-labels… Sent from the matplotlib - users mailing list archive at Nabble.com.

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plot with 2 scales (not 2 plots)
by Neal Becker Jan. 14, 2016

Jan. 14, 2016

I'm trying to make a plot which has 2 scales (linearly related), but just 1 set of data. I've seen many examples with 2 plots and 2 scales, but that's not what I need here. I blindly followed some examples and was able to make a pretty good plot with one scale on bottom and one on top. I'd like to see how it looks with 2 scales on the bottom, with an offset between them, but I don't know how to do it. Attached is the current version.

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(no subject)
by David Bourgeois Jan. 13, 2016

Jan. 13, 2016

Indeed, it works with Qt. I'm going to report this as a bug then. Thank you, David On Wed, Jan 13, 2016 at 12:29 PM, Jens Nielsen <jenshnielsen(a)gmail.com> wrote: > It looks like a bug in the OSX backend. I can reproduce with the OSX > backend but it looks correct with any other backend that also explains why > the saved images looks correct. > If you have other GUI toolkits installed you can switch by adding > > import matplotlib > matplotlib.use('Qt4Agg') #Or any other backend > > before importing pyplot the first time > > best > Jens > > On Wed, 13 Jan 2016 at 11:08 David Bourgeois <david(a)jaguarondi.com> wrote: > >> In Matplotlib, images and patches are shown on screen with different >> color rendering, at least with my setup. The following script displays an >> image of a grayscale (np.array) overlaid at the center with the same >> grayscale generated from matplotlib.patches. >> >> There is a difference of gamma between the image and the patches on >> what's displayed on screen but if I save this figure, then the resulting >> file is correct. Checking with some graphic software, the patches are >> displaying the correct color, not the image. >> >> Snapshot: >> http://i.stack.imgur.com/mv8aU.jpg >> >> Saving the figure from the figure window 'save' button gives this: >> http://i.stack.imgur.com/fVNnh.png >> >> Is there anything I'm missing in this code? >> >> import numpy as np >> import matplotlib.pyplot as plt >> from matplotlib.patches import Rectangle >> >> color = np.zeros(3) >> >> f, ax = plt.subplots() >> im = np.zeros((1000, 1100,3)) >> for i in range(11): >> im[:,i*100:(i+1)*100,:] = np.tile(np.array([[color]]), (1000, >> 100, 1)) >> ax.add_patch(Rectangle((i*100,300), 100, 400, linewidth=0, >> facecolor=color)) >> color = color + 0.1 >> plt.imshow(im) >> plt.show() >> >> I'm on OSX, so I also checked the color management and by changing the >> color profile of my display, both image and patches are affected so I guess >> color management is not where the problem lies. >> >> Thank you, >> David >> _______________________________________________ >> Matplotlib-users mailing list >> Matplotlib-users(a)python.org >> https://mail.python.org/mailman/listinfo/matplotlib-users >> >

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