sbacchio / pyrsb

PyRSB: a Python interface to the librsb Sparse Matrix library

PyRSB

librsb is a high performance sparse matrix library implementing the Recursive Sparse Blocks format, which is especially well suited for multiplications in iterative methods on huge symmetric sparse matrices.

PyRSB is a Cython-based Python interface to librsb.

So far, PyRSB is only a prototype: prospective users and collaborators feedback are sought; please contact me to feedback and help.

Features

The following functionality is implemented:

• Initialization with rsb.rsb_matrix() styled as scipy.sparse.csr_matrix().
• Conversion from scipy.sparse.csr_matrix().
• Multiplication by vector/multivector.
• Rows/columns through nr=a.shape()[0]/nr=a.shape()[1], or nr()/nc().
• find(), find_block(), tril(), triu(), shape(), nnz().
• print'able.
• PyRSB-Specific: autotune(), do_print().
• load from a Matrix Market file, e.g. rsb.rsb_file_mtx_load(bytes(filename,encoding='utf-8'))

Build and Use

• If you have librsb installed: make shall build and test.
• Make sure you have cython, scipy, numpy. installed.
• If you want to install librsb on Ubuntu or Debian: sudo apt-get install librsb-dev shall suffice. Other operating systems have librsb, too. Please check yours. Or check librsb's web site.
• If you want the Makefile to build librsb (in this directory): make all-local will attempt downloading librsb-1.2.0-rc7 from the web and building it here before building pyrsb. If the file is in place, it won't download it a second time. After that, make local-librsb-pyrsb (or make lp) will build pyrsb using local librsb, then run it.
• make test will test benchmark code using test.py (to compare speed to SciPy)
• make b will also produce graphs (requires gnuplot)

Example Usage

import numpy
import scipy
from scipy.sparse import csr_matrix
from rsb          import rsb_matrix
V=[11.,12.,22.]
I=[  0,  0,  1]
J=[  0,  1,  1]
c=csr_matrix((V,(I,J)))
print(c)
# several constructor forms, as with csr_matrix:
a=rsb_matrix((V,(I,J)))
a=rsb_matrix((V,(I,J)),[3,3])
a=rsb_matrix((V, I,J))
a=rsb_matrix((V, I,J),sym='S') # symmetric example
print(a)
a=rsb_matrix(          (4,4))
a=rsb_matrix(c)
nrhs=1 # set to nrhs>1 to multiply by multiple vectors at once
nr=a.shape()[0]
nc=a.shape()[1]
x=numpy.empty([nc,nrhs],dtype=scipy.double)
y=numpy.empty([nr,nrhs],dtype=scipy.double)
x[:,:]=1.0
y[:,:]=0.0
print(a)
print(x)
print(y)
import rsb # import operators
# a.autotune() # makes only sense for large matrices
# matrix-vector multiply
y=y+a*x; # equivalent to y=y+c*x
print(y)
del a

License

GPLv3+