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76 lines
1.7 KiB
76 lines
1.7 KiB
# $Id: __init__.py,v 1.2 2011-10-06 19:14:49 wirawan Exp $
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#
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# wpylib.math.linalg main module
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# Created: 20110714
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# Wirawan Purwanto
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#
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"""
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wpylib.math.linalg
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Provides convenience functions for linear algebra things beyond what's
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already provided by numpy.
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"""
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import numpy
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import numpy.linalg
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# My favorites:
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from numpy import dot, trace
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from numpy.linalg import det, inv
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MATMUL_USE_BLAS = False
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def matmul(*Mats, **opts):
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"""Do successive matrix product. For example,
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matmul(A,B,C,D)
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will evaluate a matrix multiplication ((A*B)*C)*D .
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The matrices must be of matching sizes."""
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from numpy import asarray, dot, iscomplexobj
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use_blas = opts.get('use_blas', MATMUL_USE_BLAS)
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debug = opts.get('debug', True)
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if debug:
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def dbg(msg):
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print msg,
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else:
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def dbg(msg):
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pass
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if use_blas:
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try:
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from scipy.linalg.blas import zgemm, dgemm
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except:
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# Older scipy (<= 0.10?)
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from scipy.linalg.blas import fblas
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zgemm = fblas.zgemm
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dgemm = fblas.dgemm
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if not use_blas:
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p = dot(Mats[0], Mats[1])
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for M in Mats[2:]:
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p = dot(p, M)
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else:
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dbg("Using BLAS\n")
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# FIXME: Right now only supporting double precision arithmetic.
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M0 = asarray(Mats[0])
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M1 = asarray(Mats[1])
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if iscomplexobj(M0) or iscomplexobj(M1):
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p = zgemm(alpha=1.0, a=M0, b=M1)
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Cplx = True
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dbg("- zgemm ")
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else:
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p = dgemm(alpha=1.0, a=M0, b=M1)
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Cplx = False
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dbg("- dgemm ")
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for M in Mats[2:]:
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M2 = asarray(M)
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if Cplx or iscomplexobj(M2):
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p = zgemm(alpha=1.0, a=p, b=M2)
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Cplx = True
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dbg(" zgemm")
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else:
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p = dgemm(alpha=1.0, a=p, b=M2)
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dbg(" dgemm")
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dbg("\n")
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return p
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