Hi, On Mon, Jun 18, 2012 at 6:55 PM, bob tnur <bobtnu...@gmail.com> wrote:
> Hi, > how I can convert (by adding zero) of any non-square numpy matrix in to > square matrix using numpy? then how to find the minimum number in each row > except the zeros added(for making square matrix)? ;) > Perhaps something like this: In []: def make_square(A): ..: s= A.shape ..: if s[0]< s[1]: ....: return r_[A, zeros((s[1]- s[0], s[1]), dtype= A.dtype)] ..: return c_[A, zeros((s[0], s[0]- s[1]), dtype= A.dtype)] ..: In []: A= rand(4, 2) In []: make_square(A) Out[]: array([[ 0.76109774, 0.42980812, 0. , 0. ], [ 0.11810978, 0.59622975, 0. , 0. ], [ 0.54991376, 0.29315485, 0. , 0. ], [ 0.78182313, 0.3828001 , 0. , 0. ]]) In []: make_square(A.T) Out[]: array([[ 0.76109774, 0.11810978, 0.54991376, 0.78182313], [ 0.42980812, 0.59622975, 0.29315485, 0.3828001 ], [ 0. , 0. , 0. , 0. ], [ 0. , 0. , 0. , 0. ]]) will help you. My 2 cents, -eat > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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