mjo/matrix_vector: rename basis_representation() to basis_repr().

diff --git a/mjo/cone/doubly_nonnegative.py b/mjo/cone/doubly_nonnegative.py
index 373557c6c72dde4974dfdce30efe435d0d526cc2..3970c32ca85f8cdfc2e44c86f54c01c7d8c4956a 100644 (file)
--- a/mjo/cone/doubly_nonnegative.py
+++ b/mjo/cone/doubly_nonnegative.py
@@ -16,7 +16,7 @@ from sage.all import *
 from mjo.cone.symmetric_psd import (factor_psd,
                                     is_symmetric_psd,
                                     random_symmetric_psd)
-from mjo.matrix_vector import basis_representation
+from mjo.matrix_vector import basis_repr
 
 
 def is_doubly_nonnegative(A):
@@ -383,7 +383,7 @@ def is_extreme_doubly_nonnegative(A):
     # can't compute the dimension of a set of matrices anyway, so we
     # convert them all to vectors and just ask for the dimension of the
     # resulting vector space.
-    (phi, phi_inverse) = basis_representation(A.matrix_space())
+    (phi, phi_inverse) = basis_repr(A.matrix_space())
     vectors = map(phi,spanning_set)
 
     V = span(vectors, A.base_ring())

diff --git a/mjo/matrix_vector.py b/mjo/matrix_vector.py
index 83bf313a82cde7c689d10337efff8054301acad7..08743d5c5ecf000dbcc5ca6f4b475cd67af6a593 100644 (file)
--- a/mjo/matrix_vector.py
+++ b/mjo/matrix_vector.py
@@ -12,7 +12,7 @@ from sage.matrix.matrix_space import is_MatrixSpace
 def _mat2vec(m):
     return vector(m.base_ring(), m.list())
 
-def basis_representation(M):
+def basis_repr(M):
     """
     Return the forward (``MatrixSpace`` -> ``VectorSpace``) and
     inverse isometries, as a pair, that take elements of the given
@@ -46,7 +46,7 @@ def basis_representation(M):
 
     SETUP::
 
-        sage: from mjo.matrix_vector import basis_representation
+        sage: from mjo.matrix_vector import basis_repr
 
     EXAMPLES:
 
@@ -61,7 +61,7 @@ def basis_representation(M):
         sage: E22 = matrix(QQbar,[ [0,0],
         ....:                      [0,1] ])
         sage: basis = [E11, E12, E22]
-        sage: phi, phi_inv = basis_representation(basis)
+        sage: phi, phi_inv = basis_repr(basis)
         sage: phi(E11); phi(E12); phi(E22)
         (1, 0, 0)
         (0, 1, 0)
@@ -76,7 +76,7 @@ def basis_representation(M):
     MatrixSpace arguments work too::
 
         sage: M = MatrixSpace(QQ,2)
-        sage: phi, phi_inv = basis_representation(M)
+        sage: phi, phi_inv = basis_repr(M)
         sage: X = matrix(QQ, [ [1,2],
         ....:                  [3,4] ])
         sage: phi(X)
@@ -92,7 +92,7 @@ def basis_representation(M):
         sage: n = ZZ.random_element(10)
         sage: M = MatrixSpace(QQ,n)
         sage: X = M.random_element()
-        sage: (phi, phi_inv) = basis_representation(M)
+        sage: (phi, phi_inv) = basis_repr(M)
         sage: phi_inv(phi(X)) == X
         True
 
@@ -153,7 +153,7 @@ def basis_repr_of_operator(M, L):
 
     SETUP::
 
-        sage: from mjo.matrix_vector import (basis_representation,
+        sage: from mjo.matrix_vector import (basis_repr,
         ....:                                basis_repr_of_operator)
 
     EXAMPLES:
@@ -200,7 +200,7 @@ def basis_repr_of_operator(M, L):
         [0 0 0 0 0 0 0 1 0]
         [0 0 0 0 0 0 1 0 0]
         [0 0 0 0 0 0 0 0 1]
-        sage: phi, phi_inv = basis_representation(M)
+        sage: phi, phi_inv = basis_repr(M)
         sage: X = M([[1,2,3],[4,5,6],[7,8,9]])
         sage: F*phi(X) == phi(f(X))
         True
@@ -213,7 +213,7 @@ def basis_repr_of_operator(M, L):
         basis_space = M[0].matrix_space()
         basis = M
 
-    (phi, phi_inv) = basis_representation(M)
+    (phi, phi_inv) = basis_repr(M)
 
     # Get a basis for the image space. Since phi is an isometry,
     # it takes one basis to another.