matplotlib-users Mailing List for matplotlib

Additional functionality for segplot could be; instead of providing maxdelta, be able to supply start and stop indices, or perhaps a list of start and stop indices. Another alternative would be to supply x and y ranges which specify to only join the dots when both points are within the range. It might also be worth thinking about factoring out the segment breaking code. Then you could do things like apply regression fit lines to individual segments etc.

Gary

----- Original Message -----

> Any suggestions for a name, or additional functionality?
> 
> JDH

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>>>>> "Peter" == Peter Groszkowski <pgr...@ge...> writes:

    Peter> Hi everyone: I was wondering whether it is possible to tell
    Peter> matplotlib how/when to connect data points. Consider this
    Peter> simple script:

    Peter> from matplotlib.matlab import * figure(1) t =
    Peter> [0,1,2,3,4,5,105,106,107] s = [1,4,5,3,9,11,-5,-8,3]
    Peter> plot(t, s, antialiased=False) grid(True) show()


    Peter> There are no data points between t=5 and t=105. By default
    Peter> the points (5,11) and (105,-5) are connected, but I would
    Peter> like to tell matplotlib NOT to do so. In my case I would
    Peter> like to pass the plot function a variable telling it what
    Peter> to do. So for example would have:

    Peter> plot(t, s, max_delta=40)

    Peter> This would mean that the points are only to be connected if
    Peter> the difference between the adjacent t values is less than
    Peter> 40.  In my case this is relevant because sometimes there
    Peter> are "holes" in my data, and connecting the points makes the
    Peter> plots look very messy.

    Peter> Would anyone find something like this useful? Would it be
    Peter> difficult to implement?

Certainly not difficult, and probably useful enough to put in the
standard distro.  Eg, in a stock market trading example, you would
have lots of quotes, minute by minute, punctuated by long intervals
overnight where the market is closed.  If you set maxdelta
appropriately, you could draw connected lines only within trading
days.

Here is a sample implementation

from matplotlib.matlab import *
def segplot(x, y, fmt, maxdelta, **kwargs):
    """
    Plot x versus y, breaking the plot at any point where x[i] -
    x[i-1] > maxdelta. kwargs are passed on to plot
    """
    x = asarray(x)
    y = asarray(y)
    d = diff(x)
    lines = []
    ind = nonzero(greater(d, maxdelta))
    ind = ind+1
    if not len(ind):
        lines.extend( plot(x,y,fmt,**kwargs) ) 
    else:
        allind = [0]
        allind.extend(ind)
        allind.append(len(x))
        for i1,i2 in zip(allind[:-1], allind[1:]):
            lines.extend( plot(x[i1:i2], y[i1:i2], fmt, **kwargs) )
    return lines

t = [0,1,2,3,4,5,105,106,107,187, 200, 212, 300, 320]
s = [1,4,5,3,9,11,-5,-8,3,12, 15, 12, -1, 3]
segplot(t, s, 'b-o', 40, antialiased=False)
grid(True)
show()

I'm inclined not to make this part of plot, since plot processes a
variable number of arguments it makes it a little difficult.
Certainly doable, but I'm hesitant to put too much on plot because it
might become unwieldy.  But a new function, like segment plot, would
be easy enough to include.

Any suggestions for a name, or additional functionality?

JDH

>>>>> "Dominique" == Dominique Orban <Dom...@po...> writes:

    Dominique> Many thanks for your reply and suggestions. I see what
    Dominique> is happening. Nearest neighbor interpolation has the
    Dominique> colors right, but i was trying to get "more
    Dominique> interpolation". I guess looking at the great pictures
    Dominique> that imshow() produces i was hoping for a result such
    Dominique> as that of

    Dominique> X = rand(10) pcolor( X ) shading 'interp'

As far as I recall, matlab's pcolor also loses an edge due to
interpolation.  Perhaps the main difference is that in matlab, the
axes limits are set by default so that you don't see it.  I remember
being surprised by this many moons ago the first time I used pcolor in
matlab.

    Dominique> in Matlab. The Matplotlib picture is just as good
    Dominique> really, except for the border. Why are the other
    Dominique> borders not white as well? Is the interpolation
    Dominique> "directional"? Why aren't pixels on the border only
    Dominique> interpolated with their neighbors inside the image, and
    Dominique> not those outside (these have less neighbors than
    Dominique> pixels in the middle)?

I'll have to think about this some more.  

There is also something funny about how the tick labeling currently
works for images, because the X[0,0] coord is upper left but is
labeled as 0,10.  Perhaps ticks should be off be default, or labeled
with the y axis descending.  Those who have opinions please weigh in.

BTW, the developer of agg, Maxim, is fairly responsive, so if you want
to pursue this issue after reading some of the code I point to below
on the agg mailing list

  http://lists.sourceforge.net/lists/listinfo/vector-agg-general

Maxim can probably provide some additional guidance.


    Dominique> Perhaps you can point me to the part of the code (c++ i
    Dominique> assume) which does the interpolation? Should i grab the
    Dominique> CVS repository for that?  Then maybe i can play around
    Dominique> and see if i can achieve the effect i am looking for.

The code is available in the matplotlib src distribution.  The module
is src/_image.cpp, which uses agg for image manipulation; see the
function Image_resize.  All the agg code is also in the matplotlib src
distro, eg, agg2/include.  agg2 doesn't have a lot of documentation -
hence I spend a lot of time reading src files, eg

    agg_conv_transform.h
    agg_span_image_filter_rgb24.h
    agg_span_image_filter_rgba32.h
    agg_span_interpolator_linear.h

The latest agg snapshot it http://www.antigrain.com/agg2.tar.gz which
has lots of examples in the examples dir.  Agg can do a lot with
images, some of which would be nice to add to the matplotlib
interface....

JDH

John Hunter wrote:

>>>>>>"Dominique" == Dominique Orban <Dom...@po...> writes:
> 
> 
>     Dominique> When using imshow(), why does there always seem to be a
>     Dominique> blank zone along the southern and eastern edges of the
>     Dominique> figure? For instance:
> 
>     Dominique> X = rand(10,10) imshow(X)
> 
>     Dominique> plots a luminance image of X, which seems fine, except
>     Dominique> for the lower and rightmost edges, which are blank. I
>     Dominique> may be misunderstanding the purpose of imshow, but
>     Dominique> skimming through the code didn't give me an answer. I
>     Dominique> am using matplotlib 0.52 on WinXP with either GTKAgg or
>     Dominique> TkAgg.
> 
> Hi Dominique,
> 
> Your example did point me to a small bug in the image module, but it
> is mostly unrelated to what you are observing.  In the axes.py
> function imshow, replace
> 
>             self.set_image_extent(0, numcols-1, 0, numrows-1) 
> with 
>             self.set_image_extent(0, numcols, 0, numrows) 
> 
> 
> This only affects the tick labeling (not the actual image display)
> but it was wrong before and should be changed.
> 
> Now run this script
> 
>     from matplotlib.matlab import *
>     X = rand(10,10)
> 
>     subplot(211)
>     im = imshow(X)
>     im.set_interpolation('nearest')
> 
>     subplot(212)
>     im = imshow(X)
>     show()
> 
> The key thing is that the white border you are seeing arises from
> interpolation.  The points on the bottom and right have no neighbors
> in those directions, and so they interpolate to the background color,
> which is white.
> 
> You can set the axis limits so that these regions don't appear, or use
> nearest neighbor interpolation.
> 
> Let me know if these suggestions don't work for you.
> 
> JDH

John,

Many thanks for your reply and suggestions. I see what is happening. 
Nearest neighbor interpolation has the colors right, but i was trying to 
get "more interpolation". I guess looking at the great pictures that 
imshow() produces i was hoping for a result such as that of

X = rand(10)
pcolor( X )
shading 'interp'

in Matlab. The Matplotlib picture is just as good really, except for the 
border. Why are the other borders not white as well? Is the 
interpolation "directional"? Why aren't pixels on the border only 
interpolated with their neighbors inside the image, and not those 
outside (these have less neighbors than pixels in the middle)?

Perhaps you can point me to the part of the code (c++ i assume) which 
does the interpolation? Should i grab the CVS repository for that? Then 
maybe i can play around and see if i can achieve the effect i am looking 
for.

Thanks again !
Dominique

>>>>> "Dominique" == Dominique Orban <Dom...@po...> writes:

    Dominique> When using imshow(), why does there always seem to be a
    Dominique> blank zone along the southern and eastern edges of the
    Dominique> figure? For instance:

    Dominique> X = rand(10,10) imshow(X)

    Dominique> plots a luminance image of X, which seems fine, except
    Dominique> for the lower and rightmost edges, which are blank. I
    Dominique> may be misunderstanding the purpose of imshow, but
    Dominique> skimming through the code didn't give me an answer. I
    Dominique> am using matplotlib 0.52 on WinXP with either GTKAgg or
    Dominique> TkAgg.

Hi Dominique,

Your example did point me to a small bug in the image module, but it
is mostly unrelated to what you are observing.  In the axes.py
function imshow, replace

            self.set_image_extent(0, numcols-1, 0, numrows-1) 
with 
            self.set_image_extent(0, numcols, 0, numrows) 


This only affects the tick labeling (not the actual image display)
but it was wrong before and should be changed.

Now run this script

    from matplotlib.matlab import *
    X = rand(10,10)

    subplot(211)
    im = imshow(X)
    im.set_interpolation('nearest')

    subplot(212)
    im = imshow(X)
    show()

The key thing is that the white border you are seeing arises from
interpolation.  The points on the bottom and right have no neighbors
in those directions, and so they interpolate to the background color,
which is white.

You can set the axis limits so that these regions don't appear, or use
nearest neighbor interpolation.

Let me know if these suggestions don't work for you.

JDH

Hi john ,

I was doing a pure TeX plot (a bunch of equations inside a box)  and I 
noticed that the \sqrt{}command does not work even though it listed in 
the help page for mathtext.

\frac and \dfrac would be a nice addition too...

feel free to used this little script as an example of another use of 
mathtext...

Flavio