matplotlib-users Mailing List for matplotlib

On 2014年03月03日 11:40 AM, Ying Liu wrote:
> Hi,
>
> I want to know how to set the scientific ticker format in pylab. I know
> that I can set it to the form of 1e21, but what I want is something like
> x10^21, as follows:
>
> Inline image 1 -----> Inline image 2
>
>
> Can anybody tell me how to do this? I searched on this for a long time,
> but still I did not find the answer.
Execute this before plotting:
rcParams['axes.formatter.use_mathtext'] = True
or set it in your matplotlibrc file.
Eric
>
> Sorry to bother those who are not interested.
>
> Best regards
>
>

Hi,
I want to know how to set the scientific ticker format in pylab. I know
that I can set it to the form of 1e21, but what I want is something like
x10^21, as follows:
[image: Inline image 1] -----> [image: Inline image 2]
Can anybody tell me how to do this? I searched on this for a long time, but
still I did not find the answer.
Sorry to bother those who are not interested.
Best regards

Maybe I understand what he means. How can a user override some value in a
colormap? Lets say, in general user wants to inherit some ready made colormap
but in addition wants to force certain colors to some data items.
M.
Eric Firing wrote:
> On 2014年03月02日 1:02 AM, ChaoYue wrote:
>> Dear Eric,
>>
>> This solved part of my problem. thanks a lot.
>> I think I will revisit this issue when I have time (not promised).
>> do you think this could be some feature desirable?
> 
> I don't understand what feature you are referring to; evidently I don't 
> understand what the problem is, so I don't know what part remains unsolved.
> 
> Eric
> 
> 
>>
>> Cheers,
>>
>> Chao
>>
>>
>> On Sat, Mar 1, 2014 at 10:39 PM, Eric Firing [via matplotlib] <[hidden
>> email] </user/SendEmail.jtp?type=node&node=42956&i=0>> wrote:
>>
>> On 2014年03月01日 11:03 AM, ChaoYue wrote:
>> > The most correct way might be to design a new colormap with white
>> color
>> > exactly in the middle, however this is very tedious, especially if I
>> > want to try
>> > different colormaps. so the alternative approach would be to set
>> the values
>> > falling in (-1,1) as being masked, so they will be the same as
>> the axes
>> > background color as you mentioned (in our case it's white). My
>> question is,
>> > how can I put this background color (which shows maksed data) in the
>> > colorbar,
>> > by avoiding design a new colormap?
>>
>> It's not the answer you want to hear, but I think the correct answer is
>> that you should do this via the colormap, and not by masking the low
>> values. It doesn't have to be painful. If, in contourf, you use a
>> diverging colormap with white already in the middle
>> (http://matplotlib.org/examples/color/colormaps_reference.html) and a
>> norm with symmetric limits (vmin and vmax; you can let them be set
>> automatically after you specify your symmetric set of contour
>> boundaries
>> appropriately) then it will be done for you.
>>
>> e.g.,
>>
>> z = 10 * np.random.randn(20, 30)
>> clevs = [-10, -5, -2, -1, 1, 2, 5, 10]
>> cs = plt.contourf(z, levels=clevs, cmap=plt.get_cmap('PRGn'),
>> extend='both')
>> cbar = plt.colorbar(cs, spacing='uniform')
>>
>> Eric
>>
>> ------------------------------------------------------------------------------
> 
> 
> ------------------------------------------------------------------------------
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Thanks. I'd definitely consider this a bug this. Would you mind 
creating an issue or pull request on github.com/matplotlib/matplotlib so 
it doesn't get lost?
Mike
On 03/01/2014 05:42 PM, Jon Roadley-Battin wrote:
> >On 02/27/2014 06:58 PM, Jon Roadley-Battin wrote:
> >> Good evening,
> >>
> >> I am at present migrating an application of mine from py27+pygtk (with
> >> mpl) to py33+pygobject (gtk3)
> >>
> >> Unfortunately I am unable to use
> >>
> >> from matplotlib.backends.backend_gtk3agg import 
> FigureCanvasGTK3Agg as FigureCanvas
> >> from matplotlib.backends.backend_gtk3 import 
> NavigationToolbar2GTK3 as NavigationToolbar
> >>
> >> Which is is on the examples (
> >> 
> http://matplotlib.org/examples/user_interfaces/embedding_in_gtk3_panzoom.html
> >> ) but is also the logical translation from what I presently have.
> >> This falls fowl of the cairo issue
> >>
> >> What I am having to use is backend_gtk3cairo. However this is being
> >> triggered
> >>
> >> raise ValueError("The Cairo backend can not draw paths longer than
> >> 18980 points.")
> >>
> >> I am generally plotting 7 x-y plots with upto 30,000 points.
> >> Now for now I have commented this out from my local install, is there
> >> a better/preferred/recommended alternative?
> >
> >This was put in there because cairo had (at least at the time) a hard
> >coded limit on path size, and getting a Python exception was IMHO
> >preferable to segfaulting and having the process go away. Are you
> >saying that when you comment it out, it's currently working? It may be
> >that cairo has fixed this limit in the intervening years. Can you
> >provide a simple, standalone example that reproduces the error?
>
>
> Using python33 & pygi-aio-3.10.2-win32_rev18 (to provide pygobject for 
> windows:)
> Using: 
> http://matplotlib.org/examples/user_interfaces/embedding_in_gtk3_panzoom.html 
> as the baseline provides the following error:
>
> < File 
> "c:\Python33\lib\site-packages\matplotlib\backends\backend_gtk3agg.py", line 
> 52, in on_draw_event
> buf, cairo.FORMAT_ARGB32, width, height)
> NotImplementedError: Surface.create_for_data: Not Implemented yet.
>
>
> This has been mentioned a few times across the ml
>
> Modifying the example to use backend_gtk3cairo
>
> from matplotlib.backends.backend_gtk3cairo import 
> FigureCanvasGTK3Cairo as FigureCanvas
> from matplotlib.backends.backend_gtk3 import NavigationToolbar2GTK3 as 
> NavigationToolbar
>
>
> Now the example runs and plots a nice sinewave (as expected). Modify 
> the script to plot 7 waveforms, 100pts
>
> ##############################################################################################################
> #!/usr/bin/env python3
> """
> demonstrate NavigationToolbar with GTK3 accessed via pygobject
> """
>
> from gi.repository import Gtk
>
> from matplotlib.figure import Figure
> import numpy as np
> from matplotlib.backends.backend_gtk3cairo import 
> FigureCanvasGTK3Cairo as FigureCanvas
> from matplotlib.backends.backend_gtk3 import NavigationToolbar2GTK3 as 
> NavigationToolbar
>
>
> win = Gtk.Window()
> win.connect("delete-event", Gtk.main_quit )
> win.set_default_size(400,300)
> win.set_title("Embedding in GTK")
>
> fig = Figure(figsize=(5,4), dpi=100)
> plt = fig.add_subplot(1,1,1)
>
> t = np.arange(0,2*np.pi,2*np.pi/100)
> a = np.sin(t + 0*(2*np.pi/7))
> b = np.sin(t + 1*(2*np.pi/7))
> c = np.sin(t + 2*(2*np.pi/7))
> d = np.sin(t + 3*(2*np.pi/7))
> e = np.sin(t + 4*(2*np.pi/7))
> f = np.sin(t + 5*(2*np.pi/7))
> g = np.sin(t + 6*(2*np.pi/7))
> plt.plot(t,a)
> plt.plot(t,b)
> plt.plot(t,c)
> plt.plot(t,d)
> plt.plot(t,e)
> plt.plot(t,f)
> plt.plot(t,g)
>
> vbox = Gtk.VBox()
> win.add(vbox)
>
> # Add canvas to vbox
> canvas = FigureCanvas(fig) # a Gtk.DrawingArea
> vbox.pack_start(canvas, True, True, 0)
>
> # Create toolbar
> toolbar = NavigationToolbar(canvas, win)
> vbox.pack_start(toolbar, False, False, 0)
>
> win.show_all()
> Gtk.main()
> ####################################################################################################################
>
> This works, its only 100pts for 7 scatters so nothing unexpected.
> Modify the arange to create a time array of 30,000 pts.
>
> t = np.arange(0,2*np.pi,2*np.pi/30000)
>
>
> File 
> "c:\Python33\lib\site-packages\matplotlib\backends\backend_cairo.py", 
> line 143, in draw_path
> raise ValueError("The Cairo backend can not draw paths longer than 
> 18980 points.")
> ValueError: The Cairo backend can not draw paths longer than 18980 points.
>
>
> The already mentioned raise to protect against a segfault.
> Edit backend_cairo to comment out the check:
>
>
> def draw_path(self, gc, path, transform, rgbFace=None):
> #if len(path.vertices) > 18980:
> # raise ValueError("The Cairo backend can not draw paths 
> longer than 18980 points.")
>
> ctx = gc.ctx
>
>
>
> 7channel, 30,000 pts each is plotted just fine. Zoom rectangle is slow 
> to render, but this is true for 100pts (so more a gtk3 thing than a 
> cairo and multiple points thing)
>
> Final script:
>
>
>
> #######################################################################################################################
> #!/usr/bin/env python3
> """
> demonstrate NavigationToolbar with GTK3 accessed via pygobject
> """
>
> from gi.repository import Gtk
>
> from matplotlib.figure import Figure
> import numpy as np
> from matplotlib.backends.backend_gtk3cairo import 
> FigureCanvasGTK3Cairo as FigureCanvas #changed to use gtk3cairo
> from matplotlib.backends.backend_gtk3 import NavigationToolbar2GTK3 as 
> NavigationToolbar
>
>
> win = Gtk.Window()
> win.connect("delete-event", Gtk.main_quit )
> win.set_default_size(400,300)
> win.set_title("Embedding in GTK")
>
> fig = Figure(figsize=(5,4), dpi=100)
> plt = fig.add_subplot(1,1,1)
>
> t = np.arange(0,2*np.pi,2*np.pi/30000) # 30,000 pt time 
> array for 7 signals
> a = np.sin(t + 0*(2*np.pi/7))
> b = np.sin(t + 1*(2*np.pi/7))
> c = np.sin(t + 2*(2*np.pi/7))
> d = np.sin(t + 3*(2*np.pi/7))
> e = np.sin(t + 4*(2*np.pi/7))
> f = np.sin(t + 5*(2*np.pi/7))
> g = np.sin(t + 6*(2*np.pi/7))
> plt.plot(t,a)
> plt.plot(t,b)
> plt.plot(t,c)
> plt.plot(t,d)
> plt.plot(t,e)
> plt.plot(t,f)
> plt.plot(t,g)
>
> vbox = Gtk.VBox()
> win.add(vbox)
>
> # Add canvas to vbox
> canvas = FigureCanvas(fig) # a Gtk.DrawingArea
> vbox.pack_start(canvas, True, True, 0)
>
> # Create toolbar
> toolbar = NavigationToolbar(canvas, win)
> vbox.pack_start(toolbar, False, False, 0)
>
> win.show_all()
> Gtk.main()
> ######################################################################################################################
>
>
>
> Hope this helps. or is useful
>
> JonRB
>
>
>
> ------------------------------------------------------------------------------
> Flow-based real-time traffic analytics software. Cisco certified tool.
> Monitor traffic, SLAs, QoS, Medianet, WAAS etc. with NetFlow Analyzer
> Customize your own dashboards, set traffic alerts and generate reports.
> Network behavioral analysis & security monitoring. All-in-one tool.
> http://pubads.g.doubleclick.net/gampad/clk?id=126839071&iu=/4140/ostg.clktrk
>
>
> _______________________________________________
> Matplotlib-users mailing list
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