# Improving the sparse matrix package in Scipy
Among otherthings, I'm preparing a proposal to improve the handling of the
`bool` datatype in Scipy's sparse matrix package. Once these types are
consistently codified, improving interactions between `spmatrix` objects and
other Numpy/Scipy types should be easier. So fixing things like [trac ticket#1598](http://projects.scipy.org/scipy/ticket/1598) would come next.
So first I would need to write a specification for handling bools with other
spmatrix objects and other kinds of objects like ndarrays. But what is
wrong now? Here is one thing.
## Bool problems: Making sparse bool matricies
Not every sparse matrix format supports bool dtypes. Try instantiating any class
which inherits from `_cs_matrix` with a ndarray of bool dtype, and it will upcast
it to int8. See my comments on the [trac ticket #1533.](http://projects.scipy.org/scipy/ticket/1533)
In [3]: A = np.array([[True, False],[False, True]], dtype=bool)
In [4]: B = sp.csr_matrix(A)
In [5]: B.data
Out[5]: array([1, 1], dtype=int8)
But we can get a spmatrix with a bool dtype if we pass the kwarg `dtype=bool`
In [6]: C = sp.csr_matrix(A, dtype=bool)
In [7]: C.data
Out[7]: array([ True, True], dtype=bool)
This seems inconsisent; but now we have other problems.
In [8]: C.toarray()
...
171 """
--> 172 return _coo.coo_todense(*args)
173
174 def coo_matvec(*args):
TypeError: Array of type 'byte' required. Array of type 'bool' given
I think the type is upcast here because there is no support for bool
types in the `coo_todense` function. This is defined in [coo.h](https://github.com/scipy/scipy/blob/master/scipy/sparse/sparsetools/coo.h)
, where the type is required by the class T. To apparently not be bool.
So to add support for bool, this class T needs to have support for it
added. Once that is done the `toarray()` method should work with
`dtype==bool`.
I don't yet understand how this SWIG wrapper works. I'm not sure where this class T
is coming from. Any comments would be helpful.