[SciPy-user] sparse matrices - list assignment to rows and columns
Thu Apr 9 04:05:29 CDT 2009
On Thu, Apr 9, 2009 at 4:51 AM, <email@example.com> wrote:
> On Wed, Apr 8, 2009 at 11:51 PM, Gergely Imreh <firstname.lastname@example.org> wrote:
>> I was trying figure out the scipy sparse matrix handling, but run
>> into some difficulties assigning a list of values to rows and columns.
>> The scipy tutorial has the following example :
>> from scipy import sparse
>> Asp = sparse.lil_matrix((50000,50000))
>> Asp[20,100:250] = 10*random.rand(150)
>> Asp[200:250,30] = 10*random.rand(50)
>> That looks straightforward enough, make a large, diagonal sparse
>> matrix, and set some additional elements to non-zero. What I get,
>> however, is different:
>> Asp[20,100:250] = 10*random.rand(150) sets the matrix elements at row
>> 20, column 100-249 to random values.
>> Asp[200:250,30] = 10*random.rand(50) sets the matrix element at row
>> 200, column 30 to a 50 element row vector with random values....
>> (elements at row 201-249, column 30 are still 0)
>> If I reshape the results of random.rand(50) to be in a column
>> instead of row, the assignment will results in the elements of row
>> 200-249, column 30 to be set to a single element array values (So, for
>> exaple Asp[200,30] will be an array, which will have a single random
>> value at [0,0])
>> I'm using Python 2.6 (that comes with my distro, or 2.4 for which
>> I'd have to recompile scipy) and scipy 0.7.0. Is this kind of
>> behaviour due to the changes (and incompatibilites) of 2.6 (since I
>> know scipy is writtend to be compatible up to 2.5) or something else?
>> The other sparse matrix types would handle this differently?
>> A workaround is to do single element assignments but I'd think
>> that's probably slower in general.
>>  http://www.scipy.org/SciPy_Tutorial
> There is an assignment error:
> Asp[200:250,30] seems to assign all 50 elements to to the position Asp[200,30]
> <1x50 sparse matrix of type '<type 'numpy.float64'>'
> with 50 stored elements in LInked List format>
>>>> Aspc = Asp.tocrc()
> Traceback (most recent call last):
> File "<pyshell#4>", line 1, in <module>
> Aspc = Asp.tocrc()
> File "c:\josef\_progs_scipy\scipy\sparse\base.py", line 429, in __getattr__
> raise AttributeError, attr + " not found"
> AttributeError: tocrc not found
sorry, I copied the wrong traceback, it should be:
>>> Aspc = Asp.tocsr()
Traceback (most recent call last):
File "<pyshell#7>", line 1, in <module>
Aspc = Asp.tocsr()
File "c:\josef\_progs_scipy\scipy\sparse\lil.py", line 427, in tocsr
data = np.asarray(data, dtype=self.dtype)
line 230, in asarray
return array(a, dtype, copy=False, order=order)
ValueError: setting an array element with a sequence.
> this is with
> there is a related assignment error that got fixed in trunk,
> I don't know if it also handles this case, a bug report might be
> useful to make sure this case is handled correctly
> I think, for this example dok format would be better to build the
> matrix, since column slices need to access many lists
> Asp = sparse.dok_matrix((50000,50000))
> Aspr = Asp.tocsr()
> works without problems
> I checked the history of the scipy tutorial that you linked to, the
> main editing has been done in 2006, and maybe it isn't up to date.
> The current docs are being written and are available at
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