X-Git-Url: https://svn.cri.ensmp.fr/git/linpy.git/blobdiff_plain/a4a564b4061ca0a495f2f2dba784d28b685b6f1d..9a4172e83557d605fbcb6b6b8fb41f8debab2e13:/linpy/linexprs.py?ds=sidebyside

diff --git a/linpy/linexprs.py b/linpy/linexprs.py
index d62c671..a0be583 100644
--- a/linpy/linexprs.py
+++ b/linpy/linexprs.py
@@ -247,26 +247,28 @@ class LinExpr:
         """
         Test whether two linear expressions are equal.
         """
-        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):
         """
@@ -339,7 +341,7 @@ class LinExpr:
         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)
@@ -405,7 +407,7 @@ class LinExpr:
     @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
@@ -416,7 +418,8 @@ class LinExpr:
             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)
@@ -430,7 +433,7 @@ class LinExpr:
 
     def tosympy(self):
         """
-        Convert the linear expression to a sympy expression.
+        Convert the linear expression to a SymPy expression.
         """
         import sympy
         expr = 0
@@ -450,6 +453,13 @@ class Symbol(LinExpr):
     Two instances of Symbol are equal if they have the same name.
     """
 
+    __slots__ = (
+        '_name',
+        '_constant',
+        '_symbols',
+        '_dimension',
+    )
+
     def __new__(cls, name):
         """
         Return a symbol with the name string given in argument.
@@ -470,6 +480,8 @@ class Symbol(LinExpr):
 
     @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
@@ -582,6 +594,13 @@ class Rational(LinExpr, Fraction):
     fractions.Fraction classes.
     """
 
+    __slots__ = (
+        '_coefficients',
+        '_constant',
+        '_symbols',
+        '_dimension',
+    ) + Fraction.__slots__
+
     def __new__(cls, numerator=0, denominator=None):
         self = object().__new__(cls)
         self._coefficients = {}