diagonal_matrix() does not seem smart enough to deal with 1-dimensional numpy arrays:
sage: s array([ 7.10977223, 2.10977223]) Both values are numpy floats: sage: [parent(_) for _ in s] [<type 'numpy.float64'>, <type 'numpy.float64'>] But diagonal_matrix() can't make sense of s: sage: diagonal_matrix(s) Traceback (most recent call last): [...] UnboundLocalError: local variable 'v' referenced before assignment I tried specifying the ring: sage: diagonal_matrix(RDF, s) Traceback (most recent call last): [...] ValueError: Invalid matrix constructor. Type matrix? for help I also tried making a list out of s: sage: diagonal_matrix(RDF, list(s)) Traceback (most recent call last): [...] TypeError: unable to find a common ring for all elements (That's an unusual error, since both elements coerce into Sage float types with no problem.) Finally I got it to work, by doing everything myself: sage: diagonal_matrix([RDF(_) for _ in s]) [7.10977222865 0.0] [ 0.0 2.10977222865] The usual matrix() function deals with numpy arrays with no problem, so I expected diagonal_matrix() to do so as well. Should diagonal_matrix() "Just Work" when given numpy arrays? Dan -- --- Dan Drake ----- http://mathsci.kaist.ac.kr/~drake -------
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