Bill Baxter wrote: > On 3/24/07, Anne Archibald <[EMAIL PROTECTED]> wrote: >> On 24/03/07, Bill Baxter <[EMAIL PROTECTED]> wrote: >>> I mentioned in another thread Travis started on the scipy list that I >>> would find it useful if there were a function like dot() that could >>> multiply more than just two things. >>> >>> Here's a sample implementation called 'mdot'. >>> >>> mdot(a,b,c,d) ==> dot(dot(dot(a,b),c),d) >>> mdot(a,(b,c),d) ==> dot(dot(a,dot(b,c),d) >>> mdot(a,(b,(c,d))) ==> dot(a,dot(b,dot(c,d)) >>> >>> --- >>> def mdot(*args): >>> """Multiply all the arguments using matrix product rules. >>> The output is equivalent to multiplying the arguments one by one >>> from left to right using dot(). >>> Precedence can be controlled by creating tuples of arguments, >>> for instance mdot(a,((b,c),d)) multiplies a (a*((b*c)*d)). >>> Note that this means the output of dot(a,b) and mdot(a,b) will differ if >>> a or b is a pure tuple of numbers. >>> """ >>> if len(args)==1: >>> return args[0] >>> elif len(args)==2: >>> return _mdot_r(args[0],args[1]) >>> else: >>> return _mdot_r(args[:-1],args[-1]) >>> >>> def _mdot_r(a,b): >>> """Recursive helper for mdot""" >>> if type(a)==types.TupleType: >>> if len(a)>1: >>> a = mdot(*a) >>> else: >>> a = a[0] >>> if type(b)==types.TupleType: >>> if len(b)>1: >>> b = mdot(*b) >>> else: >>> b = b[0] >>> return numpy.dot(a,b) >> You can do better: >> In [1]: from numpy import * >> >> In [2]: a = array([[0,-1],[1,0]]) >> >> In [3]: reduce(dot,(a,a,a,a)) >> Out[3]: >> array([[1, 0], >> [0, 1]]) >> >> In [4]: def mdot(*args): >> ...: return reduce(dot,args) >> ...: >> >> In [5]: mdot(a,a,a,a) >> Out[5]: >> array([[1, 0], >> [0, 1]]) >> > > Nice, but how does that fare on things like mdot(a,(b,c),d) ? I'm > pretty sure it doesn't handle it. > I think an mdot that can only multiply things left to right comes up > short compared to an infix operator that can easily use parentheses to > control order. +1 for infix
Colin W. > > --bb _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
