symbols to their coefficients, and a constant term. The coefficients and
the constant term must be rational numbers.
- For example, the linear expression x + 2y + 1 can be constructed using
+ For example, the linear expression x + 2*y + 1 can be constructed using
one of the following instructions:
>>> x, y = symbols('x y')
Alternatively, linear expressions can be constructed from a string:
- >>> LinExpr('x + 2*y + 1')
+ >>> LinExpr('x + 2y + 1')
A linear expression with a single symbol of coefficient 1 and no
constant term is automatically subclassed as a Symbol instance. A linear
@_polymorphic
def __eq__(self, other):
"""
- Test whether two linear expressions are equal.
+ Test whether two linear expressions are equal. Unlike methods
+ LinExpr.__lt__(), LinExpr.__le__(), LinExpr.__ge__(), LinExpr.__gt__(),
+ the result is a boolean value, not a polyhedron. To express that two
+ linear expressions are equal or not equal, use functions Eq() and Ne()
+ instead.
"""
- if isinstance(other, LinExpr):
- return self._coefficients == other._coefficients and \
- self._constant == other._constant
- return NotImplemented
-
- def __le__(self, other):
- from .polyhedra import Le
- return Le(self, other)
+ return self._coefficients == other._coefficients and \
+ self._constant == other._constant
+ @_polymorphic
def __lt__(self, other):
- from .polyhedra import Lt
- return Lt(self, other)
+ from .polyhedra import Polyhedron
+ return Polyhedron([], [other - self - 1])
+ @_polymorphic
+ def __le__(self, other):
+ from .polyhedra import Polyhedron
+ return Polyhedron([], [other - self])
+
+ @_polymorphic
def __ge__(self, other):
- from .polyhedra import Ge
- return Ge(self, other)
+ from .polyhedra import Polyhedron
+ return Polyhedron([], [self - other])
+ @_polymorphic
def __gt__(self, other):
- from .polyhedra import Gt
- return Gt(self, other)
+ from .polyhedra import Polyhedron
+ return Polyhedron([], [self - other - 1])
def scaleint(self):
"""
Create an expression from a string. Raise SyntaxError if the string is
not properly formatted.
"""
- # add implicit multiplication operators, e.g. '5x' -> '5*x'
+ # Add implicit multiplication operators, e.g. '5x' -> '5*x'.
string = LinExpr._RE_NUM_VAR.sub(r'\1*\2', string)
tree = ast.parse(string, 'eval')
expr = cls._fromast(tree)
@classmethod
def fromsympy(cls, expr):
"""
- Create a linear expression from a sympy expression. Raise TypeError is
+ Create a linear expression from a SymPy expression. Raise TypeError is
the sympy expression is not linear.
"""
import sympy
if symbol == sympy.S.One:
constant = coefficient
elif isinstance(symbol, sympy.Dummy):
- # we cannot properly convert dummy symbols
+ # We cannot properly convert dummy symbols with respect to
+ # symbol equalities.
raise TypeError('cannot convert dummy symbols')
elif isinstance(symbol, sympy.Symbol):
symbol = Symbol(symbol.name)
def tosympy(self):
"""
- Convert the linear expression to a sympy expression.
+ Convert the linear expression to a SymPy expression.
"""
import sympy
expr = 0
@property
def _coefficients(self):
+ # This is not implemented as an attribute, because __hash__ is not
+ # callable in __new__ in class Dummy.
return {self: Fraction(1)}
@property