本文整理匯總了Python中sage.modules.free_module.VectorSpace.base_ring方法的典型用法代碼示例。如果您正苦於以下問題：Python VectorSpace.base_ring方法的具體用法？Python VectorSpace.base_ring怎麽用？Python VectorSpace.base_ring使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類sage.modules.free_module.VectorSpace的用法示例。
在下文中一共展示了VectorSpace.base_ring方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: linear_transformation
# 需要導入模塊: from sage.modules.free_module import VectorSpace [as 別名]
# 或者: from sage.modules.free_module.VectorSpace import base_ring [as 別名]
#.........這裏部分代碼省略.........
...
ValueError: symbolic function has the wrong number of outputs for codomain
sage: x, y = var('x y')
sage: f(x, y) = [y, x*y]
sage: linear_transformation(QQ^2, QQ^2, f)
Traceback (most recent call last):
...
ValueError: symbolic function must be linear in all the inputs:
unable to convert y to a rational
sage: x, y = var('x y')
sage: f(x, y) = [x, 2*y]
sage: C = (QQ^2).span([vector(QQ, [1, 1])])
sage: linear_transformation(QQ^2, C, f)
Traceback (most recent call last):
...
ArithmeticError: some image of the function is not in the codomain, because
element [1, 0] is not in free module
"""
from sage.matrix.constructor import matrix
from sage.modules.module import is_VectorSpace
from sage.modules.free_module import VectorSpace
from sage.categories.homset import Hom
from sage.symbolic.ring import SymbolicRing
from sage.modules.vector_callable_symbolic_dense import Vector_callable_symbolic_dense
from inspect import isfunction
if not side in ['left', 'right']:
raise ValueError("side must be 'left' or 'right', not {0}".format(side))
if not (is_Matrix(arg0) or is_VectorSpace(arg0)):
raise TypeError('first argument must be a matrix or a vector space, not {0}'.format(arg0))
if is_Matrix(arg0):
R = arg0.base_ring()
if not R.is_field():
try:
R = R.fraction_field()
except (NotImplementedError, TypeError):
msg = 'matrix must have entries from a field, or a ring with a fraction field, not {0}'
raise TypeError(msg.format(R))
if side == 'right':
arg0 = arg0.transpose()
side = 'left'
arg2 = arg0
arg0 = VectorSpace(R, arg2.nrows())
arg1 = VectorSpace(R, arg2.ncols())
elif is_VectorSpace(arg0):
if not is_VectorSpace(arg1):
msg = 'if first argument is a vector space, then second argument must be a vector space, not {0}'
raise TypeError(msg.format(arg1))
if arg0.base_ring() != arg1.base_ring():
msg = 'vector spaces must have the same field of scalars, not {0} and {1}'
raise TypeError(msg.format(arg0.base_ring(), arg1.base_ring()))
# Now arg0 = domain D, arg1 = codomain C, and
# both are vector spaces with common field of scalars
# use these to make a VectorSpaceHomSpace
# arg2 might be a matrix that began in arg0
D = arg0
C = arg1
H = Hom(D, C, category=None)
# Examine arg2 as the "rule" for the linear transformation
# Pass on matrices, Python functions and lists to homspace call
# Convert symbolic function here, to a matrix
if is_Matrix(arg2):