[Numpy-discussion] Familiar w/ reduce ?
Tue Jun 26 03:52:24 CDT 2007
Pierre GM schrieb:
> I have a (m_1+1,m_2+1) matrix of 0 and 1, and I need to compute a second
> matrix U by recurrence.
> A double-loop as such
> U = empty((m_1+1, m_2+1))
> U[:,0] = C[:,0]
> U[0,:] = C[0,:]
> for i in range(1,m_1+1):
> for j in range(1,m_2+1):
> U[i,j] = C[i,j] * (U[i,j-1] + U[i-1,j])
> does the trick, but I suspect there is not a simpler, more elegant solution.
> Would anybody have any idea ?
> Thanks a lot in advance, and all my apologies for being a tad lazy...
Going from two to one loop at least seems relatively easy; what about
something like (untested, especially all the parentheses...):
for i in range (1,m_1+1):
U[i,1:] = dot(C[i,1:], vstack((U[i,:-1],U[i-1,1:])).sum(axis=0))
Actually, now that I see the structure more clearly, what about
tempU1 = U[:-1,1:] # upper right block (w/o last row and first col)
tempU2 = U[1:,:-1] # lower left (w/9 first row and last col)
U[1:,1:] = dot(C[1:,1:], tempU1+tempU2) # hopefully does it elementwise?
> (PS: FYI, it's for a reimplementation of the Kolmogorov-Smirnov test
> statistic, where ties occur)
Glad that there are other applied statisticians (maybe even
econometrician?) around working with plain old 2d matrices... Would you
mind posting the resulting code?
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