Revision history [back]
 | 1 | initial version |
r is correctly defined. For s, i would just do:
sage: s = matrix(QQ,[2,-3,-4]).right_kernel()
sage: s
Vector space of degree 3 and dimension 2 over Rational Field
Basis matrix:
[ 1 0 1/2]
[ 0 1 -3/4]
Then you can do:
sage: s.intersection(r)
Vector space of degree 3 and dimension 1 over Rational Field
Basis matrix:
[ 1 15 -43/4]
And check
sage: r.intersection(s)
Vector space of degree 3 and dimension 1 over Rational Field
Basis matrix:
[ 1 15 -43/4]
sage: b = r.intersection(s).basis()[0] ; b
(1, 15, -43/4)
sage: b in r
True
sage: b in s
True
| | 2 | No.2 Revision |
r is correctly defined. For s, i would just do:
sage: s = matrix(QQ,[2,-3,-4]).right_kernel()
sage: s
Vector space of degree 3 and dimension 2 over Rational Field
Basis matrix:
[ 1 0 1/2]
[ 0 1 -3/4]
Then you can do:
sage: s.intersection(r)
Vector space of degree 3 and dimension 1 over Rational Field
Basis matrix:
[ 1 15 -43/4]
And check
sage: r.intersection(s)
Vector space of degree 3 and dimension 1 over Rational Field
Basis matrix:
[ 1 15 -43/4]
sage: b = r.intersection(s).basis()[0] ; b
(1, 15, -43/4)
sage: b in r
True
sage: b in s
True
As a general rule, unlike say complex analysis, Sage already offers precise objects to work with linear spaces, polynomials, combinatorics, so that you should avoid the use of fuzzy symbolic things.
