matplotlib-users Mailing List for matplotlib

On Thu, Nov 24, 2011 at 7:57 AM, Marianne C. <mar...@gm...> wrote:
>
> My name is Marianne, I am a beginner user of matplotlib.
>> I am using imshow in pyplot. I am desperate to get rid of
>> the ticks on both x and y axes (see attached picture). I
>> do not need the black box around the data either. Should
>> I use imshow in axes.Axes instead, to be able to call
>
>
plt.axis('off')
or
ax = plt.gca()
ax.set_axis_off()
should clear the axis bounds and remove ticks as well.
-- 
Gökhan

Hi Friedrich and everybody else,
Thank you for your reply.
I think I am not getting everything, but in my understanding,
the object which I create is not a Figure or an Axis, it is an
AxesImage. gca() or gcf() return errors indeed.
Therefore, I cannot use attributes which are specific to Figures
and Axes.
Would there be a reason for the class AxesImage to handle
very few attributes? Is this class not so popular? :p
Best,
Marianne
On Thu, Nov 24, 2011 at 8:09 PM, Friedrich Romstedt <
fri...@gm...> wrote:
> 2011年11月24日 Marianne C. <mar...@gm...>:
> > On Thu, Nov 24, 2011 at 3:48 PM, Marianne C. <mar...@gm...>
> wrote:
> >> Hi all,
> >>
> >> My name is Marianne, I am a beginner user of matplotlib.
> >> I am using imshow in pyplot. I am desperate to get rid of
> >> the ticks on both x and y axes (see attached picture). I
> >> do not need the black box around the data either. Should
>
> The cleanes solution, is to use the NullLocator. I'm not a user of
> pylab Matlabish interface, but from what I know::
>
> gca().xaxis.set_major_locator(matplotlib.ticker.NullLocator())
> gca().yaxis.set_major_locator(matplotlib.ticker.NullLocator())
>
> after importing matplotlib.ticker of course. Should work, but didn't try.
>
> http://matplotlib.sourceforge.net/api/ticker_api.html
>
> http://matplotlib.sourceforge.net/api/axis_api.html#matplotlib.axis.Axis.set_major_locator
> http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.gca
>
> You are free to use the OO interface which yields the same.
>
> Notice that upon clear() the locators are most probably lost.
>
> gca() get the current Axes object. xaxis and yaxis are its Axis
> attributes. The locator defines where to set ticks. If it's the
> NoneLocator this is rather a stub to saying "don't place ticks ever".
> But it's more clean than to force them directly to the empty list
> because it'll survive at least limit changes. I don't know if the
> manual method survives that. Otherwise it's also a matter of taste.
>
> From the docs I do not see that you could hand over the locators
> directly to the imshow call
>
> http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.imshow
> .
>
> For the frame, if it really matters, you can set the ``edgecolor``
> probably to 'none', literally with the quotes. There's a Figure
> object created when you create the plot, you can get it via gcf().
> Try to figure out how to set its egdecolor either on construction or
> later. If you are stuck tell.
>
> Make sure to "reply to all".
>
> cu,
> Friedrich
>

On Friday, November 25, 2011, Keith Hughitt <kei...@gm...> wrote:
> Hi,
> I would like to draw a contour plot on top of an image and such that any
values of the countour plot < x are made transparent.
> Here is what I am doing at the moment to handle the overplotting:
>
> from matplotlib import pyplot as plt
> fig = plt.figure()
> axes = fig.add_subplot(111)
> contour = plt.imshow(contour_data,
extent=contour_extent,cmap=contour_cmap, origin='lower', zorder=10)
> im = plt.imshow(im_data, extent=im_extent, cmap=im_cmap, origin='lower',
zorder=1)
> plt.show()
>
> Any suggestions? One thing I thought about doing is converting im_data
and contour_data from grayscale to RGBA, and setting the alpha channel to 0
for all data with value less than x, but I was hoping there might be a more
straight-forward way to handle this.
> Thanks,
> Keith
>
>
Just use a numpy masked array and it will do exactly what you want.
contour_data = np.ma.masked_array(contour_data, mask=(contour_data < 0))
Cheers!
Ben Root

Hello.
I'm searching for a method to show a stream of data on a graph. So far
I've only managed to get the stream on a regular graph but the data
bandwidth is very high (100 samples/sec) and the usual graph doesn't
handle redrawing so good.
I was searching for a way to utilize the animation functionality of
matplotlib but found only some Tk examples (with very smooth refresh
rate).
But I couldn't modify the source to create the same effect using the Gtk
+ front-end. The problem is that I don't know how to integrate the graph
into the Glib main loop. 
Please help.
This is an example I found o the net:
----------------------------------------------------------
import matplotlib
matplotlib.use('TkAgg') # do this before importing pylab
import matplotlib.pyplot as plt
import random
fig = plt.figure()
ax = fig.add_subplot(111)
x = range(30)
y = [random.random() for i in x]
line, = ax.plot(x,y)
def animate(*args):
 n = len(y)
 while True:
 data = random.random()
 y.append(data)
 n += 1
 line.set_data(range(n-30, n), y[-30:])
 ax.set_xlim(n-31, n-1)
 fig.canvas.draw()
fig.canvas.manager.window.after(100, animate)
plt.show()
----------------------------------------------------------

Hi,
I would like to draw a contour plot on top of an image and such that any
values of the countour plot < x are made transparent.
Here is what I am doing at the moment to handle the overplotting:
from matplotlib import pyplot as plt
fig = plt.figure()
axes = fig.add_subplot(111)
contour = plt.imshow(contour_data, extent=contour_extent,cmap=contour_cmap,
origin='lower', zorder=10)
im = plt.imshow(im_data, extent=im_extent, cmap=im_cmap, origin='lower',
zorder=1)
plt.show()
Any suggestions? One thing I thought about doing is converting im_data and
contour_data from grayscale to RGBA, and setting the alpha channel to 0 for
all data with value less than x, but I was hoping there might be a more
straight-forward way to handle this.
Thanks,
Keith

Hi all,
On 24/11/11 23:02, Friedrich Romstedt wrote:
> How does the ebuild work? Does it invoke setup.py? If yes, maybe
> matplotlib installs the CXX dir s.t. it does not work for py3k?
Sorry for making the noise, I found the problem, actually it was my
ebuild which removed the CXX folder after the 2.7 python succeeded to
build. I do not know the reasons behind this though.
No I do not have the error there, but I have elsewhere. :) Here it is:
------------------
x86_64-pc-linux-gnu-g++ -pthread -march=native -O2 -fno-strict-aliasing
-fPIC -DPY_ARRAY_UNIQUE_SYMBOL=MPL_ARRAY_API -DPYCXX_ISO_CPP_LIB=1
-DPYCXX_PYTHON_2TO3=1 -I/usr/local/include -I/usr/include -I/usr/include
-I. -I/usr/lib64/python3.2/site-packages/numpy/core/include -Isrc
-Iagg24/include -I.
-I/usr/lib64/python3.2/site-packages/numpy/core/include
-I/usr/include/freetype2 -I/usr/include -I. -I/usr/include -I.
-I/usr/include/pygtk-2.0 -I/usr/include/gtk-2.0 -I/usr/include/glib-2.0
-I/usr/lib64/glib-2.0/include -I/usr/lib64/gtk-2.0/include
-I/usr/include/atk-1.0 -I/usr/include/cairo
-I/usr/include/gdk-pixbuf-2.0 -I/usr/include/pango-1.0
-I/usr/include/pixman-1 -I/usr/include/libpng15 -I/usr/include/libdrm
-I/usr/lib64/python3.2/site-packages/numpy/core/include
-I/usr/include/python3.2 -c src/_gtkagg.cpp -o
build-3.2/temp.linux-x86_64-3.2/src/_gtkagg.o
src/_gtkagg.cpp: In function ‘PyObject* init_gtkagg()’:
src/_gtkagg.cpp:137:5: error: return-statement with no value, in
function returning ‘PyObject*’
src/_gtkagg.cpp:138:5: error: ‘PyCObject_Check’ was not declared in this
scope
src/_gtkagg.cpp:138:5: error: ‘PyCObject_AsVoidPtr’ was not declared in
this scope
src/_gtkagg.cpp:138:5: error: return-statement with no value, in
function returning ‘PyObject*’
src/_gtkagg.cpp:138:5: error: return-statement with no value, in
function returning ‘PyObject*’
------------------
If anybody could explain why I am getting the above. Is it because of
a wrong version of PyGobject (2.28.6) or PyGtk (2.24.0) ? Or is it
because the GTK Backend is not yet ported to Python 3?
Also, could anybody tell me what differences are there in dependencies
between Py2 and Py3 versions of MPL?
Cheers,
Ignas A.
-- 
Q: Because it reverses the logical flow of conversation.
A: Why is putting a reply at the top of the message frowned upon?