@@ -209,7 +209,7 @@ Here, we make a new ``Module`` and we give it two inner ``Modules`` like
the one defined in the basic example. Each inner module has methods inc
and dec as well as a state c and their state is directly accessible from
the outer module, which means that it can define methods using them. The
instance(inst) we make from the ``Module``(m) reflects the hierarchy
instance (inst) we make from the ``Module`` (m) reflects the hierarchy
that we created. Unlike the method using function, there is no need to
manipulate any containers directly.
...
...
@@ -219,7 +219,7 @@ Advanced example
Complex models can be implemented by subclassing ``Module`` (though that is not mandatory). Here is a complete, extensible (and working) regression model implemented using this system:
@@ -34,9 +34,9 @@ Their seam new format planed for scipy 0.7.x:
``bsr_matrix``
Block Compressed Row (BSR). From their doc: The Block Compressed Row (BSR) format is very similar to the Compressed Sparse Row (CSR) format. BSR is appropriate for sparse matrices with dense sub matrices like the last example below. Block matrices often arise in vector-valued finite element discretizations. In such cases, BSR is considerably more efficient than CSR and CSC for many sparse arithmetic operations.
``dia_matrix``
Sparse matrix with DIAgonal storage
Sparse matrix with DIAgonal storage
There are four member variables that comprise a compressed matrix ``sp``(for at least csc, csr and bsr):
There are four member variables that comprise a compressed matrix ``sp``(for at least csc, csr and bsr):
