Add tensor total convenience method (#101)

opvious/modeling/definitions.py

@@ -41,6 +41,7 @@
     literal,
     render_identifier,
     to_expression,
+    total,
     within_domain,
 )
 from .identifiers import (
@@ -325,6 +326,17 @@ def __call__(self, *subscripts: ExpressionLike) -> Expression:
             self._identifier, tuple(to_expression(s) for s in subscripts)
         )
 
+    def total(self, absolute=False) -> Expression:
+        """The tensor's total summed value
+
+        Args:
+            absolute: Sum the absolute value of the tensor's terms instead of
+                its raw values
+        """
+        return total(
+            abs(self(*q)) if absolute else self(*q) for q in self.space()
+        )
+
     def render_statement(self, label: Label) -> Optional[str]:
         _logger.debug("Rendering tensor %s...", label)
         c = self.category[0].lower()

opvious/modeling/fragments.py

@@ -159,8 +159,8 @@ def __new__(
         cls,
         tensor: TensorLike,
         *quantifiables: Quantifiable,
-        upper_bound: Union[ExpressionLike, bool] = True,
-        lower_bound: Union[ExpressionLike, bool] = False,
+        upper_bound: Union[ExpressionLike, TensorLike, bool] = True,
+        lower_bound: Union[ExpressionLike, TensorLike, bool] = False,
         name: Optional[Name] = None,
         projection: Projection = -1,
     ) -> ActivationVariable:
@@ -190,16 +190,16 @@ def __call__(self, *subs: ExpressionLike) -> Expression:
             @constraint(disabled=upper_bound is False)
             def activates(self):
                 bound = upper_bound
-                if bound is True:
-                    bound = tensor_image().upper_bound
                 for cp in quantification(lift=True):
+                    if callable(bound):
+                        bound = bound(*cp.lifted)
+                    elif bound is True:
+                        bound = tensor_image().upper_bound
                     yield bound * self.value(*cp) >= tensor(*cp.lifted)
 
             @constraint(disabled=lower_bound is False)
             def deactivates(self):
                 bound = lower_bound
-                if bound is True:
-                    bound = tensor_image().lower_bound
                 for cp in quantification():
                     if projection >= 0:
                         term = total(
@@ -208,6 +208,10 @@ def deactivates(self):
                         )
                     else:
                         term = tensor(*cp)
+                    if callable(bound):
+                        bound = bound(*cp)
+                    elif bound is True:
+                        bound = tensor_image().lower_bound
                     yield bound * self.value(*cp) <= term
 
         return _Fragment()

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "opvious"
-version = "0.16.6rc1"
+version = "0.16.7rc1"
 description = "Opvious Python SDK"
 authors = ["Opvious Engineering <[email protected]>"]
 readme = "README.md"

tests/test_modeling.py

@@ -34,10 +34,11 @@ def __init__(self) -> None:
         self.setup_cost = om.Parameter.non_negative(self.steps)
         self.demand = om.Parameter.non_negative(self.steps)
 
-        self.production = om.Variable.non_negative(self.steps)
+        self.production = om.Variable.non_negative(
+            self.steps, upper_bound=self.demand.total(absolute=True)
+        )
         self.production_indicator = om.fragments.ActivationIndicator(
             tensor=self.production,
-            upper_bound=om.total(self.demand(t) for t in self.steps),
         )
         self.inventory = om.Variable.non_negative(self.steps)