X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Fcone%2Fsymmetric_psd.py;h=c6b9f69dd179a9f9950cbcd3b96a0c6bfd4e8436;hb=1e8a8f3916b47dbd059928d0e7d684364fb817dd;hp=fae0ae2307bb4e8b0583cf5b2200951f66a7e256;hpb=bc32004c617931e80f5c87775086e3f0e05f502e;p=sage.d.git diff --git a/mjo/cone/symmetric_psd.py b/mjo/cone/symmetric_psd.py index fae0ae2..c6b9f69 100644 --- a/mjo/cone/symmetric_psd.py +++ b/mjo/cone/symmetric_psd.py @@ -15,13 +15,66 @@ addsitedir(abspath('../../')) from mjo.symbolic import matrix_simplify_full +def is_symmetric_psd(A): + """ + Determine whether or not the matrix ``A`` is symmetric + positive-semidefinite. + + INPUT: + + - ``A`` - The matrix in question + + OUTPUT: + + Either ``True`` if ``A`` is symmetric positive-semidefinite, or + ``False`` otherwise. + + EXAMPLES: + + Every completely positive matrix is symmetric + positive-semidefinite:: + + sage: v = vector(map(abs, random_vector(ZZ, 10))) + sage: A = v.column() * v.row() + sage: is_symmetric_psd(A) + True + + The following matrix is symmetric but not positive semidefinite:: + + sage: A = matrix(ZZ, [[1, 2], [2, 1]]) + sage: is_symmetric_psd(A) + False + + This matrix isn't even symmetric:: + + sage: A = matrix(ZZ, [[1, 2], [3, 4]]) + sage: is_symmetric_psd(A) + False + + """ + + if A.base_ring() == SR: + msg = 'The matrix ``A`` cannot be symbolic.' + raise ValueError.new(msg) + + # First make sure that ``A`` is symmetric. + if not A.is_symmetric(): + return False + + # If ``A`` is symmetric, we only need to check that it is positive + # semidefinite. For that we can consult its minimum eigenvalue, + # which should be zero or greater. Since ``A`` is symmetric, its + # eigenvalues are guaranteed to be real. + return min(A.eigenvalues()) >= 0 + + def unit_eigenvectors(A): """ Return the unit eigenvectors of a symmetric positive-definite matrix. INPUT: - - ``A`` - The matrix whose eigenvectors we want to compute. + - ``A`` - The matrix whose eigenvectors we want to compute. OUTPUT: @@ -61,11 +114,15 @@ def factor_psd(A): INPUT: - - ``A`` - The matrix to factor. + - ``A`` - The matrix to factor. The base ring of ``A`` must be either + exact or the symbolic ring (to compute eigenvalues), and it + must be a field so that we can take its algebraic closure + (necessary to e.g. take square roots). OUTPUT: - A matrix ``X`` such that `A = XX^{T}`. + A matrix ``X`` such that `A = XX^{T}`. The base field of ``X`` will + be the algebraic closure of the base field of ``A``. ALGORITHM: @@ -89,7 +146,10 @@ def factor_psd(A): `$D$` will have dimension `$k \times k$`. In the end everything works out the same. - EXAMPLES:: + EXAMPLES: + + Create a symmetric positive-semidefinite matrix over the symbolic + ring and factor it:: sage: A = matrix(SR, [[0, 2, 3], [2, 0, 0], [3, 0, 0]]) sage: X = factor_psd(A) @@ -97,8 +157,38 @@ def factor_psd(A): sage: A == A2 True + Attempt to factor the same matrix over ``RR`` which won't work + because ``RR`` isn't exact:: + + sage: A = matrix(RR, [[0, 2, 3], [2, 0, 0], [3, 0, 0]]) + sage: factor_psd(A) + Traceback (most recent call last): + ... + ValueError: The base ring of ``A`` must be either exact or symbolic. + + Attempt to factor the same matrix over ``ZZ`` which won't work + because ``ZZ`` isn't a field:: + + sage: A = matrix(ZZ, [[0, 2, 3], [2, 0, 0], [3, 0, 0]]) + sage: factor_psd(A) + Traceback (most recent call last): + ... + ValueError: The base ring of ``A`` must be a field. + """ + if not A.base_ring().is_exact() and not A.base_ring() is SR: + raise ValueError('The base ring of ``A`` must be either exact or symbolic.') + + if not A.base_ring().is_field(): + raise ValueError('The base ring of ``A`` must be a field.') + + if not A.base_ring() is SR: + # Change the base field of ``A`` so that we are sure we can take + # roots. The symbolic ring has no algebraic closure. + A = A.change_ring(A.base_ring().algebraic_closure()) + + # Get the eigenvectors, and filter out the ones that correspond to # the eigenvalue zero. all_evs = unit_eigenvectors(A)