matplotlib-devel Mailing List for matplotlib

Tony S Yu wrote:
> On Sep 26, 2008, at 2:28 PM, John Hunter wrote:
> 
>> On Fri, Sep 26, 2008 at 12:39 PM, Tony S Yu <to...@mi...> wrote:
>>
>>> +                if all(nonzero == False):
>>> +                    raise ValueError('spy cannot plot sparse zeros
>>> matrix')
>> Is raising an exception the right choice here -- why can't we plot an
>> all zeros image?
>>
>> JDH
> 
> I guess you could plot sparse all-zero matrices with image mode.  My  
> only hesitation is that sparse arrays tend to be very large and (I  
> imagine) this would lead to very slow performance. I assumed this was  
> the reason image mode wasn't adapted to use sparse arrays.

Also, if an image cannot be resolved by the output device, info is 
lost--one might not see anything at a location where there actually is a 
value--whereas with markers, a marker will always show up, and the only 
problem is that one can't necessarily distinguish a single point from a 
cluster.

The real problem with all-zero values is that plot can't handle 
"plot([],[])".  One can work around this by putting in bogus values to 
plot a single point, saving the line, and then setting the line data to 
empty; or, better, by not using the high-level plot command, but by 
generating the Line2D object and adding it to the axes.  The Line2D 
initializer is happy with empty x and y sequences. I think if you use 
this approach it will kill two bugs (failure on all-zeros with sparse 
and full arrays) with one very simple stone.

Eric

> 
> Actually, now that I think about it: you could plot a trivially small  
> image and just adjust the coordinates so that they correspond to the  
> original matrix shape. Is this what you were thinking?
> 
> I should note that a dense zero array also fails to plot with spy *if  
> marker mode is used*.
> 
> -T
> 
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On Sep 26, 2008, at 3:38 PM, John Hunter wrote:

> On Fri, Sep 26, 2008 at 2:36 PM, Tony S Yu <to...@mi...> wrote:
>>
>> Actually, now that I think about it: you could plot a trivially  
>> small image
>> and just adjust the coordinates so that they correspond to the  
>> original
>> matrix shape. Is this what you were thinking?
>
> This is something I considered, but I was thinking less about the
> implementation and more about the functionality.  I don't want to
> raise an exception unless the input doesn't make sense.  I would
> rather the user start at a boring image and figure out why it is blank
> that deal with an exception.

Yeah, I agree this is much friendlier.

>> I should note that a dense zero array also fails to plot with spy  
>> *if marker
>> mode is used*.
>
> Can you fix this along with spy2?

I assume you mean spy, not spy2 (I just searched through the  
matplotlib files and saw that spy2 hasn't existed since 2006). I'll  
work on a patch to return a blank plot using the method described  
above (unless someone chimes in with a better suggestion).

-Tony

On Fri, Sep 26, 2008 at 2:36 PM, Tony S Yu <to...@mi...> wrote:

> I guess you could plot sparse all-zero matrices with image mode.  My only
> hesitation is that sparse arrays tend to be very large and (I imagine) this
> would lead to very slow performance. I assumed this was the reason image
> mode wasn't adapted to use sparse arrays.
>
> Actually, now that I think about it: you could plot a trivially small image
> and just adjust the coordinates so that they correspond to the original
> matrix shape. Is this what you were thinking?

This is something I considered, but I was thinking less about the
implementation and more about the functionality.  I don't want to
raise an exception unless the input doesn't make sense.  I would
rather the user start at a boring image and figure out why it is blank
that deal with an exception.

> I should note that a dense zero array also fails to plot with spy *if marker
> mode is used*.

Can you fix this along with spy2?

JDH

On Sep 26, 2008, at 2:28 PM, John Hunter wrote:

> On Fri, Sep 26, 2008 at 12:39 PM, Tony S Yu <to...@mi...> wrote:
>
>> +                if all(nonzero == False):
>> +                    raise ValueError('spy cannot plot sparse zeros
>> matrix')
>
> Is raising an exception the right choice here -- why can't we plot an
> all zeros image?
>
> JDH

I guess you could plot sparse all-zero matrices with image mode.  My  
only hesitation is that sparse arrays tend to be very large and (I  
imagine) this would lead to very slow performance. I assumed this was  
the reason image mode wasn't adapted to use sparse arrays.

Actually, now that I think about it: you could plot a trivially small  
image and just adjust the coordinates so that they correspond to the  
original matrix shape. Is this what you were thinking?

I should note that a dense zero array also fails to plot with spy *if  
marker mode is used*.

-T

On Fri, Sep 26, 2008 at 12:39 PM, Tony S Yu <to...@mi...> wrote:

> +                if all(nonzero == False):
> +                    raise ValueError('spy cannot plot sparse zeros
> matrix')

Is raising an exception the right choice here -- why can't we plot an
all zeros image?

JDH

When sparse matrices have explicit zero values, `axes.spy` plots those  
zero values. This behavior seems unintentional. For example, the  
following code should have a main diagonal with markers missing in the  
middle, but `spy` currently plots a full main diagonal.

#~~~~~~~~~~~
import scipy.sparse as sparse
import matplotlib.pyplot as plt

sp = sparse.spdiags([[1,1,1,0,0,0,1,1,1]], [0], 9, 9)
plt.spy(sp, marker='.')
#~~~~~~~~~~~

Below is a patch which only plots the nonzero entries in a sparse  
matrix. Note, sparse matrices with all zero entries raises an error;  
this behavior differs from dense matrices. I could change this  
behavior, but I wanted to minimize the code changed.

Cheers,

-Tony

PS: this patch also includes two trivial changes to some examples.

Index: lib/matplotlib/axes.py
===================================================================
--- lib/matplotlib/axes.py	(revision 6122)
+++ lib/matplotlib/axes.py	(working copy)
@@ -6723,9 +6723,11 @@
          else:
              if hasattr(Z, 'tocoo'):
                  c = Z.tocoo()
-                y = c.row
-                x = c.col
-                z = c.data
+                nonzero = c.data != 0.
+                if all(nonzero == False):
+                    raise ValueError('spy cannot plot sparse zeros  
matrix')
+                y = c.row[nonzero]
+                x = c.col[nonzero]
              else:
                  Z = np.asarray(Z)
                  if precision is None: mask = Z!=0.
Index: examples/pylab_examples/masked_demo.py
===================================================================
--- examples/pylab_examples/masked_demo.py	(revision 6122)
+++ examples/pylab_examples/masked_demo.py	(working copy)
@@ -1,4 +1,4 @@
-#!/bin/env python
+#!/usr/bin/env python
  '''
  Plot lines with points masked out.

Index: examples/misc/rec_groupby_demo.py
===================================================================
--- examples/misc/rec_groupby_demo.py	(revision 6122)
+++ examples/misc/rec_groupby_demo.py	(working copy)
@@ -2,7 +2,7 @@
  import matplotlib.mlab as mlab


-r = mlab.csv2rec('data/aapl.csv')
+r = mlab.csv2rec('../data/aapl.csv')
  r.sort()

  def daily_return(prices):

Robert Kern <rob...@gm...>
writes:

 > L*u*v* or its cylindrical-coordinate cousin L*t*theta* (or
 > LCH_uv). "Choosing Color Palettes for Statistical Graphics" is a
 > nice paper talking about an implementation in R (although they do
 > seem to misname L*t*theta* as HCL, which officially is different):
 >
 >    http://eeyore.ucdavis.edu/stat250/epub-wu-01_abd.pdf

That link did not work for me, this looks to be an alternative:

http://epub.wu-wien.ac.at/dyn/virlib/wp/eng/mediate/epub-wu-01_abd.pdf?ID=epub-wu-01_abd

-- 
Pete Forman                -./\.-  Disclaimer: This post is originated
WesternGeco                  -./\.-   by myself and does not represent
pet...@we...    -./\.-   the opinion of Schlumberger or
http://petef.22web.net           -./\.-   WesternGeco.