Re: [Matplotlib-users] How can I put a white area in the middle of colorbar showing the masked data?
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?
Cheers,
Chao
On Sat, Mar 1, 2014 at 10:39 PM, Eric Firing [via matplotlib]
ml-node+s1069221n42952...@n5.nabble.com wrote:
On 2014/03/01 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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Re: [Matplotlib-users] How can I put a white area in the middle of colorbar showing the masked data?
On 2014/03/02 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=nodenode=42956i=0 wrote:
On 2014/03/01 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
--
--
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.
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Re: [Matplotlib-users] Matplotlib + py3 + gtk3
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/3) 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
