Huh,
My definition of kill is just like you said.
Inside Ipython print statements output x_new, and y_new values, but no
context saving :(
Worse thing is python rect.py does not nothing, not even with -d switch :(
:(
I will try with Ipython 0.9.1.
Gökhan
On Wed, Apr 22, 2009 at 4:40 AM, Matthias Michler
<matthiasmich...@gmx.net>wrote:
> Hi Gökhan,
> Hi list,
>
> On Tuesday 21 April 2009 19:44:18 Gökhan SEVER wrote:
> > Hi Matthias,
> >
> > Thanks for your reply again. Unfortunately I can't read x_new or y_new
> > after I kill the figures (nor when they are active). I don't know what
> > exactly wrong in my configuration or IPython. I use IPython
> 0.10.bzr.r1163
> > on Fedora 10.
> With "kill" you mean just closing the figures with button "X", isn't it?
>
> What about adding the line
> print x_new, y_new
> after the show() in your rect.py-script? Does this give some output in
> ipython
> or if you run the script using "python rect.py" ?
>
> best regards
> Matthias
>
> > Hopefully, I will solve the masked array riddle by reading more (although
> > haven't seen a specific example similar to my question on the numpy
> > reference pages), if not getting some insight from a numpy expert or like
> > you said from an expert on masked arrays :)
> >
> > Have a good Tuesday to all.
> >
> > Gökhan
> >
> >
> > On Tue, Apr 21, 2009 at 3:21 AM, Matthias Michler
> >
> > <matthiasmich...@gmx.net>wrote:
> > > Hi Gökhan,
> > > Hi list,
> > > Hi experts on masked arrays,
> > >
> > > I run the attached script (copied from your last two emails) and I can
> > > use x_new, y_new after closing the figures (where x_new and y_new are
> the
> > > values
> > > selected in the last selection).
> > >
> > > I don't know, what is going wrong with your script on your system.
> > >
> > > ### my output ##########################
> > > In [1]: run rect.py
> > > startposition : (0.276210, 0.592969)
> > > endposition : (0.542339, 0.309375)
> > > used button : 1
> > > startposition : (0.745968, 0.747656)
> > > endposition : (0.745968, 0.747656)
> > > used button : 1
> > > startposition : (0.645161, 0.761719)
> > > endposition : (0.806452, 0.609375)
> > > used button : 3
> > > startposition : (0.808468, 0.607031)
> > > endposition : (0.808468, 0.604688)
> > > used button : 3
> > > startposition : (0.086694, 0.166406)
> > > endposition : (0.137097, 0.070313)
> > > used button : 1
> > > startposition : (0.921371, 0.850781)
> > > endposition : (0.987903, 0.728906)
> > > used button : 1
> > >
> > > In [2]: x_new
> > > Out[2]:
> > > array([ 0.92929293, 0.93939394, 0.94949495, 0.95959596, 0.96969697,
> > > 0.97979798])
> > >
> > > In [3]: y_new
> > > Out[3]:
> > > array([ 0.80119703, 0.8072005 , 0.81312162, 0.81895978, 0.82471437,
> > > 0.83038482])
> > >
> > > In [4]:
> > > #############
> > >
> > > Please see my comments below.
> > >
> > > On Monday 20 April 2009 23:16:37 Gökhan SEVER wrote:
> > > > Thanks for elegant trick Matthias.
> > > >
> > > > I have modified onselect function following your suggestions, and it
> is
> > > > working as I wanted it to be. Select a portion and get a zoomed view
> in
> > > > a new figure.
> > > >
> > > > def onselect(eclick, erelease):
> > > > # eclick and erelease are matplotlib events at press and release
> > > > global x_new
> > > > global y_new
> > > > print ' startposition : (%f, %f)' % (eclick.xdata, eclick.ydata)
> > > > print ' endposition : (%f, %f)' % (erelease.xdata,
> > > > erelease.ydata) print ' used button : ', eclick.button
> > > > xmin = min(eclick.xdata, erelease.xdata)
> > > > xmax = max(eclick.xdata, erelease.xdata)
> > > > ymin = min(eclick.ydata, erelease.ydata)
> > > > ymax = max(eclick.ydata, erelease.ydata)
> > > > indices = (x >= xmin) & (x <= xmax) & (y >= ymin) & (y <= ymax)
> > > > x_new = x[indices]
> > > > y_new = y[indices]
> > > > fig_new = figure()
> > > > plot(x_new, y_new)
> > > > fig_new.show()
> > > >
> > > > There is still a minute point, that I would like mention again. Even
> > >
> > > though
> > >
> > > > I used global style variables I can't still see them when I quit the
> > > > program.
> > > >
> > > > What I do is run the file within IPython by run command. In my case
> the
> > > > file is 'rect.py.' and I do run rect.py. When I quit and do whos
> > > > querry,
> > >
> > > I
> > >
> > > > can't see global x_new nor y_new at the resulting lines:
> > > >
> > > > In [13]: whos
> > > > Variable Type Data/Info
> > > > --------------------------------------------
> > > > RectangleSelector classobj
> matplotlib.widgets.RectangleSelector
> > > > ax AxesSubplot Axes(0.125,0.1;0.775x0.8)
> > > > fig function <function figure at 0xa752c6c>
> > > > onselect function <function onselect at 0xac0ec34>
> > > > toggle_selector function <function toggle_selector at
> > >
> > > 0xac0ef0c>
> > >
> > > > x ndarray 100: 100 elems, type `float64`,
> 800
> > > > bytes y ndarray 100: 100 elems, type
> > > > `float64`, 800 bytes
> > > >
> > > >
> > > > For the masking, I was planning to use a masking scheme as given
> below.
> > >
> > > Let
> > >
> > > > say I have an array which "a"
> > > >
> > > > In [14]: a = arange(5)
> > > >
> > > > In [15]: a
> > > > Out[15]: array([0, 1, 2, 3, 4])
> > > >
> > > > and my secondary array is "b"
> > > >
> > > > In [16]: b = array([2,3])
> > > >
> > > > What I want to do is to mask a with b values and get an array of:
> > > >
> > > > [array([False, False, True, True, False], dtype=bool)]
> > > >
> > > > That is just an manually created array. I still don't know how to do
> > > > this programmatically in Pythonic fashion.
> > >
> > > As I mentioned before I'm not familiar with numpys masked arrays. In
> this
> > > list
> > > I read several comments on them, but I never used them. But I think
> they
> > > are
> > > what you are after. Maybe someone else can give you a hint or you try
> > > numpys
> > > online documentation.
> > > All I could provide is again a little manually work using a for-loop.
> So
> > > something like
> > >
> > > mask = zeros(len(a), dtype=bool)
> > > for index in xrange(len(a)): # run through array a
> > > if a[index] in b:
> > > mask[index] = True
> > > print mask # gives array([False, False, True, True, False],
> > > dtype=bool)
> > >
> > > Furthermore I'm not a Python expert and therefore I'm not the guy to
> ask
> > > for
> > > programing in "Pythonic fashion". Maybe some else can give a comment?
> > >
> > > best regards Matthias
> > >
> > > > Again thanks for your help.
> > > >
> > > > Gökhan
> > > >
> > > >
> > > > On Mon, Apr 20, 2009 at 4:09 AM, Matthias Michler
> > > >
> > > > <matthiasmich...@gmx.net>wrote:
> > > > > Hi Gökhan,
> > > > >
> > > > > On Friday 17 April 2009 20:21:00 Gökhan SEVER wrote:
> > > > > > Thanks for the pointer Matthias,
> > > > > >
> > > > > > That is exactly what I have been looking for.
> > > > > >
> > > > > > I use the code from the RectangleSelector class help with your
> > > > > > suggested code. I know that I have to update y-axis accordingly
> to
> > > > > > x values such
> > > > >
> > > > > that
> > > > >
> > > > > > their positions and sizes must much so that I can plot them in a
> > > > > > new
> > > > >
> > > > > plot.
> > > > >
> > > > > > And I know that the answer lies in a mask; I have to create a
> mask
> > >
> > > from
> > >
> > > > > > x_new and apply it to y. Do you have any hint on this?
> > > > >
> > > > > Unfortunately I'm not familiar with numpy masks, but what I would
> do
> > >
> > > is:
> > > > > xmin = min(eclick.xdata, erelease.xdata)
> > > > > xmax = max(eclick.xdata, erelease.xdata)
> > > > > ymin = min(eclick.ydata, erelease.ydata)
> > > > > ymax = max(eclick.ydata, erelease.ydata)
> > > > > # indices inside x-range
> > > > > indices = (x>= xmin) & (x <= xmax)
> > > > > # OR: indices for data inside the selected rectangle
> > > > > #indices = (x>= xmin) & (x <= xmax) & (y>=ymin) & (y<=ymax)
> > > > > xnew = x[indices]
> > > > > ynew = y[indices]
> > > > >
> > > > > > Another point is do you have any idea how to save values from
> > > > > > inside onselect action?
> > > > >
> > > > > What do you mean by saving?
> > > > > Saving to disk?
> > > > > # for ascii format I use:
> > > > > from scipy.io import write_array
> > > > >
> > > > > # for numpy arrays you can use
> > > > > import numpy as np
> > > > > a = np.arange(10)
> > > > > a.tofile # Write array to a file as text or binary.
> > > > >
> > > > > and I think there is also some Matplotlib function for this. In the
> > > > > module matplotlib.mlab, which also allows reading different types
> of
> > > > > formatted data.
> > > > >
> > > > > If you think of saving inside the program. You need a global
> variable
> > > > > (statement "global x" at the beginning of onselect) otherwise all
> > > > > variables are deleted at the end of each onselect call.
> > > > >
> > > > > > For some reason my ipython session doesn't remember values after
> I
> > >
> > > run
> > >
> > > > > the
> > > > >
> > > > > > given script:
> > > > >
> > > > > see three lines above, please.
> > > > >
> > > > > best regards Matthias
> > > > >
> > > > > > from matplotlib.widgets import RectangleSelector
> > > > > > from pylab import *
> > > > > >
> > > > > > def onselect(eclick, erelease):
> > > > > > # eclick and erelease are matplotlib events at press and release
> > > > > > print ' startposition : (%f, %f)' % (eclick.xdata,
> > > > > > eclick.ydata) print ' endposition : (%f, %f)' %
> (erelease.xdata,
> > > > > > erelease.ydata) print ' used button : ', eclick.button
> > > > > > xmin = min(eclick.xdata, erelease.xdata)
> > > > > > xmax = max(eclick.xdata, erelease.xdata)
> > > > > > ymin = min(eclick.ydata, erelease.ydata)
> > > > > > ymax = max(eclick.ydata, erelease.ydata)
> > > > > > x_new = x[(x>= xmin) & (x <= xmax)]
> > > > > > #mask = [x == x_new[i] for i in range(len(x_new))]
> > > > > > #print mask
> > > > > > #print len(x_new)
> > > > > > #print len(y_new)
> > > > > > #fig_new = figure()
> > > > > > #plot(x_new, y_new)
> > > > > > #fig_new.show()
> > > > > >
> > > > > > def toggle_selector(event):
> > > > > > print ' Key pressed.'
> > > > > > if event.key in ['Q', 'q'] and toggle_selector.RS.active:
> > > > > > print ' RectangleSelector deactivated.'
> > > > > > toggle_selector.RS.set_active(False)
> > > > > > if event.key in ['A', 'a'] and not toggle_selector.RS.active:
> > > > > > print ' RectangleSelector activated.'
> > > > > > toggle_selector.RS.set_active(True)
> > > > > >
> > > > > > x = arange(100)/(99.0)
> > > > > > y = sin(x)
> > > > > > fig = figure
> > > > > > ax = subplot(111)
> > > > > > ax.plot(x,y)
> > > > > >
> > > > > > toggle_selector.RS = RectangleSelector(ax, onselect,
> > > > > > drawtype='box') connect('key_press_event', toggle_selector)
> > > > > > show()
> > > > > >
> > > > > > Gökhan
> > > > > >
> > > > > >
> > > > > > On Fri, Apr 17, 2009 at 2:31 AM, Matthias Michler
> > > > > >
> > > > > > <matthiasmich...@gmx.net>wrote:
> > > > > > > Hi Gökhan,
> > > > > > >
> > > > > > > I recommend you to use matplotlib.widgets.RectangleSelector
> > > > > > > instead of the zoom functionality to select the data (An
> example
> > > > > > > can be
> > >
> > > found
> > >
> > > > > > > at
> > >
> > >
> http://matplotlib.sourceforge.net/examples/widgets/rectangle_selector.htm
> > >
> > > > > > >l). This will return you the x and y-coordinate of button press
> > > > > > > and
> > > > >
> > > > > button
> > > > >
> > > > > > > release
> > > > > > > event and with that you can take a portion of your data.
> > > > > > > Something like the following could be a starting point:
> > > > > > > x_min = min(eclick.xdata, erelease.xdata)
> > > > > > > x_max = max(eclick.xdata, erelease.xdata)
> > > > > > > x_new = x[(x>= x_min) & (x <= x_max)]
> > > > > > >
> > > > > > > where eclick and erelease correspond to the click and release
> > > > > > > event of the rectangle selection (see the example below).
> > > > > > >
> > > > > > > Opening a new figure after show can be achieved by:
> > > > > > >
> > > > > > > fig_new = plt.figure()
> > > > > > > # some plotting
> > > > > > > fig_new.show() # show up the new figure
> > > > > > >
> > > > > > >
> > > > > > > best regards Matthias
> > > > > > >
> > > > > > >
> > > > > > > yet another example for the usage of the RectangleSelector
> copied
> > > > > > > from its class documentation:
> > > > > > >
> > > > > > > """
> > > > > > > Select a min/max range of the x axes for a matplotlib Axes
> > > > > > >
> > > > > > > Example usage::
> > > > > > >
> > > > > > > from matplotlib.widgets import RectangleSelector
> > > > > > > from pylab import *
> > > > > > >
> > > > > > > def onselect(eclick, erelease):
> > > > > > > 'eclick and erelease are matplotlib events at press
> and
> > > > >
> > > > > release'
> > > > >
> > > > > > > print ' startposition : (%f, %f)' % (eclick.xdata,
> > > > >
> > > > > eclick.ydata)
> > > > >
> > > > > > > print ' endposition : (%f, %f)' % (erelease.xdata,
> > > > > > > erelease.ydata)
> > > > > > > print ' used button : ', eclick.button
> > > > > > >
> > > > > > > def toggle_selector(event):
> > > > > > > print ' Key pressed.'
> > > > > > > if event.key in ['Q', 'q'] and
> > >
> > > toggle_selector.RS.active:
> > > > > > > print ' RectangleSelector deactivated.'
> > > > > > > toggle_selector.RS.set_active(False)
> > > > > > > if event.key in ['A', 'a'] and not
> > > > >
> > > > > toggle_selector.RS.active:
> > > > > > > print ' RectangleSelector activated.'
> > > > > > > toggle_selector.RS.set_active(True)
> > > > > > >
> > > > > > > x = arange(100)/(99.0)
> > > > > > > y = sin(x)
> > > > > > > fig = figure
> > > > > > > ax = subplot(111)
> > > > > > > ax.plot(x,y)
> > > > > > >
> > > > > > > toggle_selector.RS = RectangleSelector(ax, onselect,
> > > > > > > drawtype='line')
> > > > > > > connect('key_press_event', toggle_selector)
> > > > > > > show()
> > > > > > > """
> > > > > > >
> > > > > > > On Friday 17 April 2009 02:26:51 Gökhan SEVER wrote:
> > > > > > > > Hello,
> > > > > > > >
> > > > > > > > A quick question:
> > > > > > > >
> > > > > > > > I am using two numpy arrays to plot the figure shown in
> > >
> > > attachment.
> > >
> > > > > Is
> > > > >
> > > > > > > > it possible to get array indices of selected X-axes while
> using
> > >
> > > the
> > >
> > > > > > > > zoom function? Later I can create a new figure from this
> > > > > > > > selected portion instead of the same figure and/or apply an
> > > > > > > > analysis.
> > > > > > > >
> > > > > > > > Thank you.
>
>
>
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