Figure out the base field automatically in condition_number().

[dunshire.git] / dunshire / matrices.py

diff --git a/dunshire/matrices.py b/dunshire/matrices.py
index 13e8150f5c807914782dbcb49733f36be513912c..123085c6c02f69574dc614fcff49d46207b7981c 100644 (file)
--- a/dunshire/matrices.py
+++ b/dunshire/matrices.py
@@ -3,6 +3,7 @@ Utility functions for working with CVXOPT matrices (instances of the
 class:`cvxopt.base.matrix` class).
 """
 
 class:`cvxopt.base.matrix` class).
 """
 

+from copy import copy

 from math import sqrt
 from cvxopt import matrix
 from cvxopt.lapack import gees, gesdd, syevr
 from math import sqrt
 from cvxopt import matrix
 from cvxopt.lapack import gees, gesdd, syevr


@@ -140,7 +141,10 @@ def eigenvalues(symmat):
 
     domain_dim = symmat.size[0]
     eigs = matrix(0, (domain_dim, 1), tc='d')
 
     domain_dim = symmat.size[0]
     eigs = matrix(0, (domain_dim, 1), tc='d')

-    syevr(symmat, eigs)
+
+    # Create a copy of ``symmat`` here because ``syevr`` clobbers it.
+    dummy = copy(symmat)
+    syevr(dummy, eigs)

     return list(eigs)
 
 
     return list(eigs)
 
 


@@ -326,12 +330,12 @@ def norm(matrix_or_vector):
     --------
 
         >>> v = matrix([1,1])
     --------
 
         >>> v = matrix([1,1])

-        >>> print('{:.5f}'.format(norm(v)))
-        1.41421
+        >>> norm(v)
+        1.414...

 
         >>> A = matrix([1,1,1,1], (2,2))
         >>> norm(A)
 
         >>> A = matrix([1,1,1,1], (2,2))
         >>> norm(A)

-        2.0
+        2.0...

 
     """
     return sqrt(inner_product(matrix_or_vector, matrix_or_vector))
 
     """
     return sqrt(inner_product(matrix_or_vector, matrix_or_vector))


@@ -418,25 +422,25 @@ def condition_number(mat):
     Examples
     --------
 
     Examples
     --------
 

-    >>> condition_number(identity(1, typecode='d'))
-    1.0
-    >>> condition_number(identity(2, typecode='d'))
-    1.0
-    >>> condition_number(identity(3, typecode='d'))
+    >>> condition_number(identity(3))

     1.0
 
     1.0
 

-    >>> A = matrix([[2,1],[1,2]], tc='d')
+    >>> A = matrix([[2,1],[1,2]])

     >>> abs(condition_number(A) - 3.0) < options.ABS_TOL
     True
 
     >>> abs(condition_number(A) - 3.0) < options.ABS_TOL
     True
 

-    >>> A = matrix([[2,1j],[-1j,2]], tc='z')
+    >>> A = matrix([[2,1j],[-1j,2]])

     >>> abs(condition_number(A) - 3.0) < options.ABS_TOL
     True
 
     """
     num_eigs = min(mat.size)
     eigs = matrix(0, (num_eigs, 1), tc='d')
     >>> abs(condition_number(A) - 3.0) < options.ABS_TOL
     True
 
     """
     num_eigs = min(mat.size)
     eigs = matrix(0, (num_eigs, 1), tc='d')

-    gesdd(mat, eigs)
+    typecode = 'd'
+    if any([isinstance(entry, complex) for entry in mat]):
+        typecode = 'z'
+    dummy = matrix(mat, mat.size, tc=typecode)
+    gesdd(dummy, eigs)

 
     if len(eigs) > 0:
         return eigs[0]/eigs[-1]
 
     if len(eigs) > 0:
         return eigs[0]/eigs[-1]