matplotlib-users Mailing List for matplotlib (Page 6)

Couldn't see the answers to these questions when looking through the
class reference docs, but they seem like common tasks, so I suspect
there are standard idiomatic way of doing these. Could anyone refer
me to examples showing

1) How to most easily label the x axis for data which is plotted
by date? (More specifically; does matplotlib have any understanding
of date values, and if so, how do I access and use it?) I'm hoping
there's an easier way than explicitly labelling ticks on the x axis.

2) I'll be drawing logy graphs, and I want a certain slope to indicate
a certain rate of growth, which means that, when using matplotlib
via TkAgg, I want it to keep the ratio of the graph display height
and display width constant as it resizes the graph to take into
account changes in the size of the enclosing window. Is there
a standard way to do this?

Thanks,
Ken McDonald

Well, I finally have matplotlib up and running under OS X, and
am amazed at the quality of the graphs. I'm writing up a
summary of what I learned about Python/Tk/OS X, and will
post it to this and other lists in the next day or two.

Now, a real quick question; are there any tutorials or examples
which show the "correct" way of using matplotlibs pythonic (as
opposed to Matlabic) API? I don't know and don't want to learn
Matlab, so figure I might as well start by using the "pure"
python API. However, all of the examples I've looked at use
the Matlab style interface, and the reference docs don't
really give a good idea of _how_ the various Python
classes are intended to be used together.

Thanks,
Ken

On Mon, 19 Apr 2004, John Hunter wrote:

> >>>>> "Srinath" == Srinath Avadhanula <sr...@fa...> writes:
>
>     Srinath> Hello, I seem to have uncovered a bug in setting/updating
>     Srinath> the axis limits.
>
> limits, you get negative display coords which are undefined.  I am not
> sure this case is common enough to warrant the performance hit of
> detecting it and doing the linear interpolation necessary to add

I have no time right now to go into a technical discussion, but IMHO
this is a serious enough bug that it needs to be fixed. One can only
worry about performance after doing the right thing. It doesn't make
sense to give the completely wrong answer in a shorter time.
[Sorry, I do not mean to sound curt or rude. Excuse me if it sounds that
way.]

Besides whether or not its a common enough situation is very application
specific. I was planning to use matplotlib to display a complex layout.
At the original scale, not much can be seen. There necessarily has to be
a lot of scaling to see the details.

> If you have some ideas on what is the best way to handle this case,
> let me know.

Could you let me know which files in matplotlib have the code in
question? I'll take a look then.

Srinath

>>>>> "Steve" == Steve Chaplin <ste...@ya...> writes:

    Steve> John, When panning the viewport through a plot shouldn't
    Steve> the panning stop and ignore your request when you reach the
    Steve> start or end of the plot.  Is there a benefit to being able
    Steve> to pan off the edge of a plot?

I like to see the data scroll past the end so I know I am truly at the
end.  If nothing happens, I might think the mouse click didn't work,
the program froze, or something like that.  Putting the question back
on you, is there a significant cost to doing it the way it is?  Most
users don't continue panning where there is no data, I assume.  It's
kind of in line with the python philosophy: we're all adults here; if
you want to pan through empty space that's your decision.

JDH

>>>>> "Srinath" == Srinath Avadhanula <sr...@fa...> writes:

    Srinath> Hello, I seem to have uncovered a bug in setting/updating
    Srinath> the axis limits.

Hi, I have looked into this and it is indeed a bug.  Here is what is
going on:  The transforms for x and y take your view limits and map
them to display coords, where negative numbers don't make sense.  It
is a standard linear transformation

        scale = displayInterval/viewInterval
        return  scale*(y-viewMin) + displayMin

In your example, if the y axis view limits are [0.516, 0.52] and the
display interval is [44.0, 360.0], then transformation of the y vector
[0, 1].

  scale = (360-44)/0.004
  ytransformed = scale*(y-.516) + 44

which is  [-40720., 38280.]

Ie, when your nearest data point is much smaller than your view
limits, you get negative display coords which are undefined.  I am not
sure this case is common enough to warrant the performance hit of
detecting it and doing the linear interpolation necessary to add
pseudo data points to make your plot well defined.  Simply replacing
the negative data with 0 is incorrect because you have to do linear
interpolation to get the right location in display coords.  Perhaps a
warning if min(xtransformed)<0 or min(ytransformed)<0 would be
appropriate and worth the performance hit.

If you have some ideas on what is the best way to handle this case,
let me know.

JDH

John,
When panning the viewport through a plot shouldn't the panning stop and
ignore your request when you reach the start or end of the plot.
Is there a benefit to being able to pan off the edge of a plot?

Regards,
Steve

Hello,

I seem to have uncovered a bug in setting/updating the axis limits.

If you run the following example, you should see a straight line between
(0,0) and (1,1). Pressing the "Test Zoom" button should reset the axis
limits to the values depicted below. Basically, the X axis is clipped
between [0.1,0.8] and the Y axis limits are either [0.516,0.517] or
[0.5166,0.5167] depending on which of the two lines in the code below is
commented. The following bug(s) are seen:

1. In the first case, where the y axis limit is updated to
   [0.516,0.517], the line should be seen as a sharply vertical line
   passing starting from x=0.516 and continuing sharply upwards till
   x=0.517.  However, the line seems to start significantly _after_
   x=0.52.

2. In the second case, if the ylim variable is changed to
   [0.5166,0.5167], then the line completely dissapears from the axes
   view. It seems to fall off the right edge (is my guess), whereas it
   should be seen as a more or less vertical line passing through
   x=0.5166.

The test code is appended below the signature.

Thanks,
Srinath


import matplotlib
matplotlib.use('GTK')
from matplotlib.backends.backend_gtk import FigureCanvasGTK

from matplotlib.axes import Subplot
from matplotlib.figure import Figure
import gtk

class MyApp:
    def __init__(self):
        self.win = gtk.Window()
        self.win.set_name("Embedding in GTK")
        self.win.connect("destroy", gtk.mainquit)
        self.win.set_border_width(5)

        self.vbox = gtk.VBox(spacing=3)
        self.win.add(self.vbox)
        self.vbox.show()

        self.fig = Figure(figsize=(5,4), dpi=100)
        self.ax = Subplot(self.fig, 111)

        self.ax.plot([0,1], [0,1])
        self.fig.add_axis(self.ax)

        self.canvas = FigureCanvasGTK(self.fig)  # a gtk.DrawingArea
        self.canvas.show()
        self.vbox.pack_start(self.canvas)

        buttonTestZoom = gtk.Button('Test Zoom')
        buttonTestZoom.connect('button_press_event', self.TestZoom)
        buttonTestZoom.show()

        self.vbox.pack_start(buttonTestZoom)

        self.win.show()


    def TestZoom(self, widget, event):
        self.ax.update_viewlim()
        xlim = [0.1, 0.8]
        # this makes the line dissapear from the axes.
        #ylim = [0.5166, 0.5167]
        # this shows the line but in the wrong location!
        ylim = [0.516, 0.517]

        self.ax.set_xlim(xlim)
        self.ax.set_ylim(ylim)

        self.canvas.draw()

if __name__=='__main__':
    app = MyApp()
    gtk.mainloop()

On Fri, 16 Apr 2004, John Hunter wrote:

> Yes, this would be a very nive feature.  When you implement it, please
> send it back to the list. Here is an example that shows you how to
> connect to the events and more importantly for you, convert to user
> coords
>
Here's a very preliminary implementation. Its not really very elegant,
but it seems to work. A couple of questions. Is there a remove_line or
equivalent for axes? As of now, I make the rectangle which shows the
zoom window dissapear by setting its xdata and ydata to [], but it might
be elegant to just remove the line from the axis completely. Also I seem
to trigger a matplotlib bug if I toggle the zoom button and then start
the button press event outside the axes.

I have yet to delve into the matplotlib source itself and maybe I am not
the best person to do it. The best place to add this would be to extend
the axes class with a .zoom() method which would work like the
ZoomButtonPressed() function below (It basically makes the next button
press trigger the ZoomStart() function which in turn calls
ZoomContinue() on the "motion_notify_event"). ZoomStart() will have to
be modified to account for more than one axes belonging to a figure.
We'll have to check whether the user presses the mouse in the axes whos
.zoom() function has been called.

Thanks again for all the help :) I think I am almost ready to get things
working with matplotlib.

-- 
Srinath

from matplotlib.numerix import arange, sin, cos, pi

import matplotlib
matplotlib.use('GTK')
from matplotlib.backends.backend_gtk import FigureCanvasGTK

from matplotlib.axes import Subplot
from matplotlib.figure import Figure
import gtk

class MyApp:
    def __init__(self):
        self.win = gtk.Window()
        self.win.set_name("Embedding in GTK")
        self.win.connect("destroy", gtk.mainquit)
        self.win.set_border_width(5)

        self.vbox = gtk.VBox(spacing=3)
        self.win.add(self.vbox)
        self.vbox.show()

        self.fig = Figure(figsize=(5,4), dpi=100)
        self.ax = Subplot(self.fig, 111)

        self.ax.plot([0,1], [0,1])
        self.fig.add_axis(self.ax)

        self.canvas = FigureCanvasGTK(self.fig)  # a gtk.DrawingArea
        self.canvas.show()
        self.canvas.connect('motion_notify_event', self.setAxisCursorLocation)
        self.vbox.pack_start(self.canvas)

        buttonZoom = gtk.ToggleButton('Toggle Zoom')
        buttonZoom.connect('button_press_event', self.ZoomButtonPressed)
        buttonZoom.show()
        self.vbox.pack_start(buttonZoom)

        self.win.show()

    def setAxisCursorLocation(self, widget, event):
        height = self.canvas.figure.bbox.y.interval()
        x, y = event.x, height-event.y

        t = self.ax.xaxis.transData.inverse_positions(x)
        val = self.ax.yaxis.transData.inverse_positions(y)

        self.cursorLocation = (t, val)

    def getAxisCursorLocation(self):
        if not hasattr(self, 'cursorLocation'):
            return None

        return self.cursorLocation

    def ZoomButtonPressed(self, widget, event):
        if not widget.get_active():
            self.zoomStartEventHandle = self.canvas.connect('button_press_event', self.ZoomStart)
        else:
            if hasattr(self, 'zoomStartEventHandle'):
                self.canvas.disconnect(self.zoomStartEventHandle)

    def ZoomStart(self, widget, event):
        self.zoomStartPosition = self.getAxisCursorLocation()
        x, y = self.zoomStartPosition
        if hasattr(self, 'zoomRectangle'):
            self.zoomRectangle.set_xdata([x,x,x,x,x])
            self.zoomRectangle.set_ydata([y,y,y,y,y])
        else:
            self.zoomRectangle = self.ax.plot([x,x,x,x,x], [y,y,y,y,y], 'k:')[0]

        self.zoomContinueEventHandle = self.canvas.connect_after('motion_notify_event', self.ZoomContinue)
        self.zoomStopEventHandle = self.canvas.connect('button_release_event', self.ZoomStop)

    def ZoomContinue(self, widget, event):
        xs, ys = self.zoomStartPosition
        x, y = self.getAxisCursorLocation()
        self.zoomRectangle.set_xdata([xs, x, x, xs, xs])
        self.zoomRectangle.set_ydata([ys, ys, y, y, ys])

        self.canvas.draw()

    def ZoomStop(self, widget, event):
        self.canvas.disconnect(self.zoomContinueEventHandle)
        self.canvas.disconnect(self.zoomStopEventHandle)

        self.zoomRectangle.set_xdata([])
        self.zoomRectangle.set_ydata([])

        xs, ys = self.zoomStartPosition
        x, y = self.getAxisCursorLocation()

        self.ax.set_xlim([min([xs,x]), max([xs,x])])
        self.ax.set_ylim([min([ys,y]), max([ys,y])])
        self.canvas.draw()

if __name__=='__main__':
    app = MyApp()
    gtk.mainloop()

>>>>> "Jim" == Jim Benson <jb...@se...> writes:

    Jim> Hi,

    Jim>   I seem to be seeing some extra debug output. I have been
    Jim> using the wx background and the embedding_in_wx.py example as
    Jim> a template for how to make matplotlib plots in an app i'm
    Jim> writing.  This part works great!!  I am however seeing what
    Jim> appears to be a debug flag left on somewhere?

No, this is in the wx code.  I traced it to the line

  wxInitAllImageHandlers()

Miraculously, I commented this out, got rid of the annoying messages,
and fixed the wx exception swallowing bug!  Jeremy and I have been
killing ourselves for about 6 months trying to figure out why backend
wx was swallowing our exceptions, and I can't really convey how happy
I am to have found this.  We have tried all manner of hacks, google
searches and plantive pleas to get our exceptions back to no avail.
It made debugging wx virtually impossible.

Please test this change on your system.  win32 users, I would also be
much obliged if you could try commenting this out on your system to
see if you lose functionality.  On my linux box, the figures came up
as expected, I was able to print to jpg and png, so all looks well.

Note, wxagg is in CVS if you need some of the agg features that native
wx drawing does not provide.  But it looks like all systems are go for
a release next week so you may as well wait.

JDH

>>>>> "Srinath" == Srinath Avadhanula <sr...@fa...> writes:

    Srinath> Hello all!  I just recently downloaded Matplotlib and
    Srinath> love it so far :)

Thanks!

    Srinath> A hopefully quick question. In all the demo examples, the
    Srinath> navigation bar has buttons for incremental +/- zoom in
    Srinath> the X/Y directions, but no way to directly choose a
    Srinath> rectange within the figure window to zoom to like in
    Srinath> matlab. It gets very tedious the way it is if a lot of
    Srinath> zooming and panning is involved.

    Srinath> I found that I could draw a rectange in the axes and
    Srinath> update its coordinates on an motion_notify_event. The
    Srinath> problem is I do not know how to link the
    Srinath> event.get_pointer() coordinates to the coordinates within
    Srinath> the axes. Therefore I cannot set the coordinates of the
    Srinath> rectangle correctly. The following code which is slightly
    Srinath> modified from embed_gtk2.py demonstrates what I am trying
    Srinath> to do...


Yes, this would be a very nive feature.  When you implement it, please
send it back to the list. Here is an example that shows you how to
connect to the events and more importantly for you, convert to user
coords

"""
An example of how to interact with the plotting canvas by connecting
to move and click events
"""
from matplotlib.matlab import *

t = arange(0.0, 1.0, 0.01)
s = sin(2*pi*t)
ax = subplot(111)
ax.plot(t,s)

canvas = get_current_fig_manager().canvas

def on_move(widget, event):
    # get the x and y coords, flip y from top to bottom
    height = canvas.figure.bbox.y.interval()
    x, y = event.x, height-event.y

    if ax.in_axes(x, y):
        # transData transforms data coords to display coords.  Use the
        # inverse method to transform back
        t = ax.xaxis.transData.inverse_positions(x)
        val = ax.yaxis.transData.inverse_positions(y)
        print t, val

def on_click(widget, event):
    # get the x and y coords, flip y from top to bottom
    height = canvas.figure.bbox.y.interval()
    x, y = event.x, height-event.y
    if event.button==1:
        if ax.in_axes(x, y):
            # transData transforms data coords to display coords.  Use the
            # inverse method to transform back
            t = ax.xaxis.transData.inverse_positions(x)
            val = ax.yaxis.transData.inverse_positions(y)
        
            print t, val


#canvas.connect('motion_notify_event', on_move)
canvas.connect('button_press_event', on_click)

show()

Hello all!

I just recently downloaded Matplotlib and love it so far :)

A hopefully quick question. In all the demo examples, the navigation bar
has buttons for incremental +/- zoom in the X/Y directions, but no way
to directly choose a rectange within the figure window to zoom to like
in matlab. It gets very tedious the way it is if a lot of zooming and
panning is involved.

I found that I could draw a rectange in the axes and update its
coordinates on an motion_notify_event. The problem is I do not know how
to link the event.get_pointer() coordinates to the coordinates within
the axes. Therefore I cannot set the coordinates of the rectangle
correctly. The following code which is slightly modified from
embed_gtk2.py demonstrates what I am trying to do...

Thanks,

-- 
Srinath

from matplotlib.numerix import arange, sin, cos, pi

import matplotlib
matplotlib.use('GTK')
from matplotlib.backends.backend_gtk import FigureCanvasGTK

from matplotlib.axes import Subplot
from matplotlib.figure import Figure
import gtk

class MyApp:
    def __init__(self):
        self.win = gtk.Window()
        self.win.set_name("Embedding in GTK")
        self.win.connect("destroy", gtk.mainquit)
        self.win.set_border_width(5)

        self.vbox = gtk.VBox(spacing=3)
        self.win.add(self.vbox)
        self.vbox.show()

        self.fig = Figure(figsize=(5,4), dpi=100)
        self.ax = Subplot(self.fig, 111)

        self.recth = 0.2
        self.ylast = 0

        x = [0,0.5,0.5,0,0]
        y = [0,0,self.recth,self.recth,0]
        t = [0,1]
        r = [0,1]

        self.h = self.ax.plot(x,y,t,r)
        self.fig.add_axis(self.ax)

        self.canvas = FigureCanvasGTK(self.fig)  # a gtk.DrawingArea
        self.canvas.show()
        self.canvas.connect('motion_notify_event', self.findClick)
        self.vbox.pack_start(self.canvas)

        self.win.show()

    def findClick(self, widget, event):
        ynow = event.get_coords()[1]
        if ynow < self.ylast:
            self.recth += 0.01
        elif ynow > self.ylast:
            self.recth -= 0.01

        self.h[0].set_ydata([0,0,self.recth,self.recth,0])
        self.ylast = ynow
        self.canvas.draw()

if __name__=='__main__':
    app = MyApp()
    gtk.mainloop()

Hi,

  I seem to be seeing some extra debug output. I have been using
the wx background and the embedding_in_wx.py example as a template
for how to make matplotlib plots in an app i'm writing.
This part works great!!  I am however seeing what appears to be
a debug flag left on somewhere?

Here is my test script:
 
(test.py)

import matplotlib
matplotlib.use('WX')

from matplotlib.backends.backend_wx import Toolbar, FigureCanvasWx,\
     FigureManager

#from matplotlib.figure import Figure
#from matplotlib.axes import Subplot
#import matplotlib.numerix as numpy
#from wxPython.wx import *

if __name__ == '__main__':

    print 'Hi There'

This works:

>>> import test
>>>

This gives me:

clavius:/home/jbenson/python>python test.py
[Debug] 10:07:56 AM: Adding duplicate image handler for 'PNG file'
[Debug] 10:07:56 AM: Adding duplicate image handler for 'JPEG file'
[Debug] 10:07:56 AM: Adding duplicate image handler for 'TIFF file'
[Debug] 10:07:56 AM: Adding duplicate image handler for 'GIF file'
[Debug] 10:07:56 AM: Adding duplicate image handler for 'PNM file'
[Debug] 10:07:56 AM: Adding duplicate image handler for 'PCX file'
[Debug] 10:07:56 AM: Adding duplicate image handler for 'XPM file'
[Debug] 10:07:56 AM: Adding duplicate image handler for 'Windows icon 
file'
[Debug] 10:07:56 AM: Adding duplicate image handler for 'Windows cursor 
file'
[Debug] 10:07:56 AM: Adding duplicate image handler for 'Windows animated 
cursor file'
Hi There
clavius:/home/jbenson/python>

I'm using matplotlib-0.52

Is this comming from matplotlib? Is there a flag i should turn off?

Thanks,

Jim

>>>>> "Flavio" == Flavio Codeco Coelho <fcc...@fi...> writes:

    Flavio> Jeremy, how can I set axes limits on a figure embedded in
    Flavio> WX?  I am plotting with

    Flavio> a = self.figmgr.add_subplot(111) a.plot(x,y)

    Flavio> just like in your example.

    Flavio> I would like to do someting like:

    Flavio> axis([0,10,0,10])

There is no axis command in the OO interface (though is would be easy
to add..).  You can always go to matlab.py and see how it is
interacting with the gca instance.  If you use your 'a' instance
everywhere it uses gca(), you can duplicate it's functionality.

    Flavio> set(gca(),'xticklabels',[]) set(gca(),'yticklabels',[])
    Flavio> set(gca(),'xticks',[]) set(gca(),'yticks',[])

the syntax of set is

  set(object or sequence, somestring, attribute)

if called with an object, set calls

  object.set_somestring(attribute)

if called with a sequence, set does

  for object in sequence:
       object.set_somestring(attribute)

So for your example, gca() is an object, so 

  a.set_xticklabels([])
  a.set_yticklabels([])
  a.set_xticks([])
  a.set_yticks([])

You may want to take another look at the tutorial section "Controlling
axes properties" which gives examples of both the matlab and OO
methods

To replicate axis, do

  a.set_xlim((xmin, xmax))
  a.set_ylim((ymin, ymax))

Should help!
JDH

waouw thanks, that's an amazing support!

----- Original Message ----- 
From: "John Hunter" <jdh...@ac...>
To: "Philippe Strauss" <phi...@pr...>
Cc: <Mat...@li...>
Sent: Friday, April 16, 2004 3:49 AM
Subject: Re: [Matplotlib-users] setting grid density


> >>>>> "Philippe" == Philippe Strauss <phi...@pr...> writes:
>
>     Philippe> This one is 1h per minor grid and tick, 6h per majors.
>
> Hi Phillipe,
>
> I just wanted to let you know that I've finished adding the major and
> minor tick support for the next release of matplotlib.  There is
> additional support for plotting dates and formatting dates with major
> and minor ticks.  There are specialized tick locators for marking
> ticks by minute, hour, day, weekday, month, year, every 4 hours, every
> 3 months, and so on.  There is a new command plot_date function and a
> series of date converters to let you plot dates with, for example,
> epochs, python datetimes or mx.Datetimes.  You can work with custom
> date instances by supplying a custom converter.  You can format the
> date ticks with strftime strings of your choice.
>
> The major and minor tick support is generic and fully customizable and
> should be useful for many other applications.
>
> Look for the release next week.
>
> JDH

>>>>> "Philippe" == Philippe Strauss <phi...@pr...> writes:

    Philippe> This one is 1h per minor grid and tick, 6h per majors.

Hi Phillipe,

I just wanted to let you know that I've finished adding the major and
minor tick support for the next release of matplotlib.  There is
additional support for plotting dates and formatting dates with major
and minor ticks.  There are specialized tick locators for marking
ticks by minute, hour, day, weekday, month, year, every 4 hours, every
3 months, and so on.  There is a new command plot_date function and a
series of date converters to let you plot dates with, for example,
epochs, python datetimes or mx.Datetimes.  You can work with custom
date instances by supplying a custom converter.  You can format the
date ticks with strftime strings of your choice.

The major and minor tick support is generic and fully customizable and
should be useful for many other applications.

Look for the release next week.

JDH

>
> VTK, including the Python API, does Delaunay triangulation, and I've  
> used it to do what you're talking about.  IIRC, there are other  
> Delaunay triangulation codes with Python bindings around. However, 
> the  Matlab function is a little more complicated;  they use 
> interpolation  in addition to a straight Delaunay triangulation, and 
> it often produces  nice-looking results.  They cite a reference in 
> either the help file or  the .m file; one can presumably read the 
> reference and re-implement it  for use in Python.
>
> FYI, here's some relevant Python VTK code:
>
>         profile = vtkPolyData()
>         profile.SetPoints(points)
>
>         delny = vtk.vtkDelaunay2D()
>         delny.SetInput(profile)
>         delny.SetTolerance(0.01)
>         delny.BoundingTriangulationOff()
>
>         normals = vtk.vtkPolyDataNormals()
>         normals.SetInput(delny.GetOutput())
>
>         lo,hi = zrange
>         elevation = vtk.vtkElevationFilter()
>         elevation.SetInput(delny.GetOutput())
>         elevation.SetLowPoint(0, 0, lo)
>         elevation.SetHighPoint(0, 0, hi)
>         elevation.SetScalarRange(lo, hi)
>         elevation.ReleaseDataFlagOn()
>
>         delMesh = vtk.vtkPolyDataMapper()
>         delMesh.SetInput(elevation.GetOutput())
>         delMesh.SetLookupTable(lutLand) # doesn't work
>         delActor = vtk.vtkActor()
>         delActor.SetMapper(delMesh)
>         ren1.AddActor( delActor ) 


Thanks Andrew.

I have tried octave with the octive-forge extensions. In fact I have 
tried two different versions with three different versions of 
octave-forge. All seem to be broken in one way or another. I get random 
segmentation faults here and there on data that other times gets 
processed properly. Their implementation of griddata gives me some areas 
(triangles) which are empty even though MATLAB produces nice plots  - 
perhaps some convergence issue.

In any case I tried using octave's griddata and plot the result using 
matplotlib's pcolor. If not for the empty triangles (due to griddata) 
the plots are precisely what I need. I will look into VTK and see what 
it can do.

Peter

On Apr 14, 2004, at 11:37 AM, Peter Groszkowski wrote:

> Hello Everyone:
>
> Before I reinvent the wheel, I'd thought I'd ask:
>
> I have a set of x,y points in a plane, and to each a corresponding z.  
> They are spread out in circular concentric orbits.
> I need to do a flat surface plot (via pcolor) of these z values. A  
> simple algorithm would be:
>
> #get data for x, y, z.. this would be some fixed points x,y inside
> #a box -4<=x<=4 and -4<=y<=4 with a z value for each.
>
> #Create a grid
> xi=linspace(-4,4,200)
> yi=linspace(-4,4,200)
> [Xi,Yi]=meshgrid(xi,yi)
>
> # This is the key step; find a z value for each grid point.
> Zi=griddata(x,y,z,Xi,Yi)
>
> pcolor(Xi, Yi, Zi, shading='flat')
>
> show()
>
> The key here is this griddata function. It interpolates the surface at  
> the grid points based on the few data points I provide it with  
> (x,y,z). It uses Delaunay triangulation, and is part of the standard  
> MATLAB distribution (more about it here:  
> http://www.mathworks.com/access/helpdesk/help/techdoc/ref/ 
> griddata.html#1007265). My question is whether anyone has come across  
> its implementation in python. I could not find any information in any  
> of the "standard" math packages. How do people do this?

VTK, including the Python API, does Delaunay triangulation, and I've  
used it to do what you're talking about.  IIRC, there are other  
Delaunay triangulation codes with Python bindings around. However, the  
Matlab function is a little more complicated;  they use interpolation  
in addition to a straight Delaunay triangulation, and it often produces  
nice-looking results.  They cite a reference in either the help file or  
the .m file; one can presumably read the reference and re-implement it  
for use in Python.

FYI, here's some relevant Python VTK code:

         profile = vtkPolyData()
         profile.SetPoints(points)

         delny = vtk.vtkDelaunay2D()
         delny.SetInput(profile)
         delny.SetTolerance(0.01)
         delny.BoundingTriangulationOff()

         normals = vtk.vtkPolyDataNormals()
         normals.SetInput(delny.GetOutput())

         lo,hi = zrange
         elevation = vtk.vtkElevationFilter()
         elevation.SetInput(delny.GetOutput())
         elevation.SetLowPoint(0, 0, lo)
         elevation.SetHighPoint(0, 0, hi)
         elevation.SetScalarRange(lo, hi)
         elevation.ReleaseDataFlagOn()

         delMesh = vtk.vtkPolyDataMapper()
         delMesh.SetInput(elevation.GetOutput())
         delMesh.SetLookupTable(lutLand) # doesn't work
         delActor = vtk.vtkActor()
         delActor.SetMapper(delMesh)
         ren1.AddActor( delActor )

Cheers!
Andrew

Eugeni Doljenko writes:
> > John Hunter wrote:
> > > Best is to use the binary string operations tostring and fromstring
> > >
> > >     from Numeric import fromstring, Float
> > >     # write
> > >     file('fname.out', 'wb').write(x.tostring())
> > >
> > >     # read
> > >     x = fromstring(file('fname.out', 'rb').read(), Float)
> > >
> > >     #If data is MxN you'll need to reshape
> > >     x.shape = M,N
> > >
> > > Hope this help,
> > > JDH
> > >
> >
> > Note that numarray has a tofile method and a fromfile function
> > to do this without going through the copying required by tostring
> > and fromstring. Like those, it also doesn't save any shape or
> Moreover tostring() and fromstring() are deprecated iirc, because you can
> convert arrays from and to strings by StringIO.
>
I just noticed this recently. It isn't the case that tostring and
fromstring are deprecated for numarray. I just wanted to clarify.

Perry 

Hello Everyone:

Before I reinvent the wheel, I'd thought I'd ask:

I have a set of x,y points in a plane, and to each a corresponding z. 
They are spread out in circular concentric orbits.
I need to do a flat surface plot (via pcolor) of these z values. A 
simple algorithm would be:

#get data for x, y, z.. this would be some fixed points x,y inside
#a box -4<=x<=4 and -4<=y<=4 with a z value for each.

#Create a grid
xi=linspace(-4,4,200)
yi=linspace(-4,4,200)
[Xi,Yi]=meshgrid(xi,yi)

# This is the key step; find a z value for each grid point.
Zi=griddata(x,y,z,Xi,Yi)

pcolor(Xi, Yi, Zi, shading='flat')

show()

The key here is this griddata function. It interpolates the surface at 
the grid points based on the few data points I provide it with (x,y,z). 
It uses Delaunay triangulation, and is part of the standard MATLAB 
distribution (more about it here: 
http://www.mathworks.com/access/helpdesk/help/techdoc/ref/griddata.html#1007265). 
My question is whether anyone has come across its implementation in 
python. I could not find any information in any of the "standard" math 
packages. How do people do this?

Thanks,
Peter

>>>>> "David" == David Brown <db...@ya...> writes:

    David> Also, not sure if it's relevant but if I try to continue in
    David> IDLE I sometimes get "too many files open" errors as well
    David> as mostly non-working windows.  Any suggestions?

I have seen problems on win32 with repeatedly loading the same
freetype2 font in backend agg.  I've implemented several changes in
the next release to fix this.  Hopefully they will solve your problem.

Stay tuned...

JDH

I'm using Tkinter as the backend display for
matplotlib and also using IDLE -n.  It works fine the
first several times I run it but ends up crashing and
taking down IDLE and pythonw.exe with it after ~10
runs of the script.  I know this is not the best way
to use matplotlib right now. Anyway, here's the
plotting part of the script (.matplotlib set to
interactive mode)

if useMatplotlib:
    yrange = 1.5
    wfList = [p1, p2, p3]
    close() # close last plot window if still open
    nplots = len(waveformList)
    i = 0
    for p in wfList:
        i +=1
        subplot(nplots,1,i)
        plot(p, color='#7070a0')
        axis([0, totalPoints, -yrange, yrange])
        ylabel('Volts')
        grid(True)


Here's the eventual error message:

Traceback (most recent call last):
Exception in Tkinter callback
Traceback (most recent call last):
  File "C:\Python23\lib\lib-tk\Tkinter.py", line 1345,
in __call__
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_tkagg.py",
line 120, in resize
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_tkagg.py",
line 127, in show
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_agg.py",
line 342, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\artist.py",
line 88, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\figure.py",
line 83, in _draw
  File
"C:\Python23\lib\site-packages\matplotlib\artist.py",
line 88, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\axes.py",
line 527, in _draw
  File
"C:\Python23\lib\site-packages\matplotlib\artist.py",
line 88, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\axis.py",
line 395, in _draw
  File
"C:\Python23\lib\site-packages\matplotlib\artist.py",
line 88, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\axis.py",
line 93, in _draw
  File
"C:\Python23\lib\site-packages\matplotlib\artist.py",
line 88, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\text.py",
line 87, in _draw
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_agg.py",
line 199, in draw_text
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_agg.py",
line 227, in compute_text_offsets
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_agg.py",
line 257, in _get_agg_font
RuntimeError: Could not load the facefile
  File "C:\Documents and Settings\dlbrown\My
Documents\Python Scripts\gen_nonlinear_error.py", line
114, in ?
  File
"C:\Python23\lib\site-packages\matplotlib\matlab.py",
line 942, in plot
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_tkagg.py",
line 46, in draw_if_interactive
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_tkagg.py",
line 127, in show
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_agg.py",
line 342, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\artist.py",
line 88, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\figure.py",
line 83, in _draw
  File
"C:\Python23\lib\site-packages\matplotlib\artist.py",
line 88, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\axes.py",
line 527, in _draw
  File
"C:\Python23\lib\site-packages\matplotlib\artist.py",
line 88, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\axis.py",
line 395, in _draw
  File
"C:\Python23\lib\site-packages\matplotlib\artist.py",
line 88, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\axis.py",
line 93, in _draw
  File
"C:\Python23\lib\site-packages\matplotlib\artist.py",
line 88, in draw
  File
"C:\Python23\lib\site-packages\matplotlib\text.py",
line 87, in _draw
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_agg.py",
line 199, in draw_text
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_agg.py",
line 227, in compute_text_offsets
  File
"C:\Python23\lib\site-packages\matplotlib\backends\backend_agg.py",
line 257, in _get_agg_font
RuntimeError: Could not load the facefile


Also, not sure if it's relevant but if I try to
continue in IDLE I sometimes get "too many files open"
errors as well as mostly non-working windows.  Any
suggestions?

-- David



	
		
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On Tue, 2004-04-13 at 10:12, John Hunter wrote:
> >>>>> "Philippe" == Philippe Strauss <phi...@pr...> writes:
> 
>     Philippe> Hello, I'm new to matplotlib and this list.
>     Philippe> Congratulation to the developers of this great package,
>     Philippe> I've been looking for a long while for a good quality
>     Philippe> plotting package.
> 
>     Philippe> I would like to plot time in hours on the x axis, with
>     Philippe> one minor grid per 15 minutes and one major grid per
>     Philippe> hour, but I can only see 10 fixed grids on all tutorial
>     Philippe> and documentation.
> 
>     Philippe> How can I configure that?
> 
> No support for minor and major ticks yet, but I can add it pretty
> quickly, probably for the next release due out soon.  I just need a
> little information.  How do grids interact with major and minor ticks?
> I know major ticks are generally bigger and are labeled, and minor
> ticks are smaller and not labeled, but I don't know how grid lines are
> usually handled with respect to major and minor ticks.  If you have a
> link to a canonical figure which uses major and minor ticks, I can
> follow that example.
> 
> JDH
> 

I've also been playing around with plots versus time (in my case
calendar time) and experimenting with tick style and ticklabel placement
computed as a function of the time span.

I attached a plot of one of my experiments. (This is where the need for
multi-line ticklabels comes from.)

The ticks and ticklabels that one wants differ according to the span of
time plotted. For instance, for multi-year plots, the ticks are no finer
than quarterly, but adjust to monthly, weekly, or daily if the span is
sub-year. The tick placement is, of course, not uniform, because of the
irregularities in the calendar.

I have not experimented with sub-day time-spans of the kind shown by
Philippe.

	-Al Schapira

From: "John Hunter" <jdh...@ac...
> >>>>> "Philippe" == Philippe Strauss <phi...@pr...> writes:
>
>     Philippe> Hello, I'm new to matplotlib and this list.
>     Philippe> Congratulation to the developers of this great package,
>     Philippe> I've been looking for a long while for a good quality
>     Philippe> plotting package.
>
>     Philippe> I would like to plot time in hours on the x axis, with
>     Philippe> one minor grid per 15 minutes and one major grid per
>     Philippe> hour, but I can only see 10 fixed grids on all tutorial
>     Philippe> and documentation.
>
>     Philippe> How can I configure that?
>
> No support for minor and major ticks yet, but I can add it pretty
> quickly, probably for the next release due out soon.  I just need a
> little information.  How do grids interact with major and minor ticks?
> I know major ticks are generally bigger and are labeled, and minor
> ticks are smaller and not labeled, but I don't know how grid lines are
> usually handled with respect to major and minor ticks.  If you have a
> link to a canonical figure which uses major and minor ticks, I can
> follow that example.
>
> JDH

for my application, I need something that looks like Tobias Oetiker
RRD tool graph:




This one is 1h per minor grid and tick, 6h per majors.

Thanks!!

>>>>> "Philippe" == Philippe Strauss <phi...@pr...> writes:

    Philippe> Hello, I'm new to matplotlib and this list.
    Philippe> Congratulation to the developers of this great package,
    Philippe> I've been looking for a long while for a good quality
    Philippe> plotting package.

    Philippe> I would like to plot time in hours on the x axis, with
    Philippe> one minor grid per 15 minutes and one major grid per
    Philippe> hour, but I can only see 10 fixed grids on all tutorial
    Philippe> and documentation.

    Philippe> How can I configure that?

No support for minor and major ticks yet, but I can add it pretty
quickly, probably for the next release due out soon.  I just need a
little information.  How do grids interact with major and minor ticks?
I know major ticks are generally bigger and are labeled, and minor
ticks are smaller and not labeled, but I don't know how grid lines are
usually handled with respect to major and minor ticks.  If you have a
link to a canonical figure which uses major and minor ticks, I can
follow that example.

JDH

Hello, I'm new to matplotlib and this list.
Congratulation to the developers of this great package, I've been looking
for
a long while for a good quality plotting package.

I would like to plot time in hours on the x axis, with one minor
grid per 15 minutes and one major grid per hour, but I can only see
10 fixed grids on all tutorial and documentation.

How can I configure that?

--
Philippe Strauss