[Matrix-SIG] Question for the NumPy gurus

[Konrad Hinsen]

   I have two arrays with in1.shape = (N,M,P) and in2.shape = (N,P)

   Is there a fast way (no Python for loop) to perform
   an innerproduct element-wise along the first dimension to 
   return an array of shape (N,M)?  I was hoping for the equivalent of

Not with dot(), but it's easy enough to do it in two steps:

   out = add.reduce(in1*in2[:,Numeric.NewAxis,:], 1)

(not tested, of course, after all I am on vacation!)
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