[SciPy-user] unsupported operand type(s) for +: 'slice' and 'int'

[Nils Wagner]

Ed Schofield wrote:
> Nils Wagner wrote:
>   
>> Traceback (most recent call last):
>>   File "aispd.py", line 33, in ?
>>     M[:,j] = m_j
>>   File "/usr/lib64/python2.4/site-packages/scipy/sparse/sparse.py", line 
>> 1308, in __setitem__
>>     self.indptr = resize1d(self.indptr, row+2)
>> TypeError: unsupported operand type(s) for +: 'slice' and 'int'
>>  >>> M
>> <420x420 sparse matrix of type '<type 'float64scalar'>'
>>         with 0 stored elements (space for 100)
>>         in Compressed Sparse Row format>
>>  >>> m_j
>> <420x1 sparse matrix of type '<type 'float64scalar'>'
>>         with 10 stored elements (space for 1002)
>>         in Compressed Sparse Row format>
>>
>> How can I resolve this problem ?
>>
>>  
>>
>> for i in arange(0,420):
>>      M[i,j] = m_j[i]
>>
>> seems to be not very efficient.
>>   
>>     
> There's only support for slicing lil_matrix and dok_matrix objects.  All
> sparse matrix manipulations like your for loop are much more efficient
> with these objects.  You're trying to do column-wise slicing and
> lil_matrix is a row-wise format, so I suggest you use dok_matrix.  Only
> convert to CSR or CSC after you've finished modifying its elements, for
> multiplication, solvers, etc.
>
> -- Ed
>
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>   
I followed your advice.
M = dok_matrix((n,n))

Traceback (most recent call last):
  File "aispd.py", line 40, in ?
    M[:,j] = m_j
  File "/usr/lib64/python2.4/site-packages/scipy/sparse/sparse.py", line 
1644, in __setitem__
    if len(seq) != len(value):
TypeError: __len__() should return an int
 >>> M
<420x420 sparse matrix with 0 stored elements in Dictionary Of Keys format>
 >>> m_j
<420x1 sparse matrix of type '<type 'float64scalar'>'
        with 3 stored elements (space for 2002)
        in Compressed Sparse Row format>

Am I missing something ?

Nils