# Google Summer of Code Proposal Preperation

## 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 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.

```
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
, 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.

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