[SciPy-dev] Checking matrix dtype in umfpack.py

[Pietro Berkes]

Dear all,

on a Mac OS X 10.5, with the latest scipy SVN version I get a few
errors from the sparse package when running scipy.test() . They all
look more or less like this:

======================================================================
ERROR: Prefactorize (with UMFPACK) matrix for solving with multiple rhs
----------------------------------------------------------------------
Traceback (most recent call last):
 File "numpy/testing/decorators.py", line 82, in skipper
 File "/Users/berkes/local/python_libs/lib/python2.5/site-packages/scipy/sparse/linalg/dsolve/umfpack/tests/test_umfpack.py",
line 90, in test_factorized_umfpack
   solve = linsolve.factorized( a )
 File "/Users/berkes/local/python_libs//lib/python2.5/site-packages/scipy/sparse/linalg/dsolve/linsolve.py",
line 160, in factorized
   umf.numeric( A )
 File "umfpack/umfpack.py", line 395, in numeric
 File "umfpack/umfpack.py", line 356, in symbolic
 File "umfpack/umfpack.py", line 341, in _getIndx
ValueError: matrix must have float64 values

This is due to a non-robust type checking in umfpack.py in the
function _getIndx. I suggest to replace this code

       if self.isReal:
           if mtx.data.dtype != nm.dtype('<f8'):
               raise ValueError, 'matrix must have float64 values'
       else:
           if mtx.data.dtype != nm.dtype('<c16'):
               raise ValueError, 'matrix must have complex128 values'

with the more robust

       if self.isReal:
           if mtx.data.dtype.type != nm.float64:
               raise ValueError, 'matrix must have float64 values'
       else:
           if mtx.data.dtype.type != nm.complex128:
               raise ValueError, 'matrix must have complex128 values'

At least, this solved the problem for me...

Cheers,
Pietro