Cleanups and minor fixes:

Raising exception from ??? in ipm exec.
Remove unused mm_exec function.
Remove namespace function that was moved to code.py.
Fix devlog import for dtypes refactor.

epymorph/engine/ipm_exec.py

@@ -189,7 +189,7 @@ def _events(self, node: int, tick: Tick, effective_pop: NDArray[SimDType]) -> ND
                         raise IpmSimNaNException(
                             self._get_zero_division_args(
                                 rate_args, node, tick, t)
-                        )
+                        ) from None
                     # check for < 0 rate, throw error in this case
                     if rate < 0:
                         raise IpmSimLessThanZeroException(
@@ -204,7 +204,7 @@ def _events(self, node: int, tick: Tick, effective_pop: NDArray[SimDType]) -> ND
                         raise IpmSimNaNException(
                             self._get_zero_division_args(
                                 rate_args, node, tick, t)
-                        )
+                        ) from None
                     # check for < 0 base, throw error in this case
                     if rate < 0:
                         raise IpmSimLessThanZeroException(

epymorph/engine/mm_exec.py

@@ -197,72 +197,3 @@ def apply(self, world: World, tick: Tick) -> None:
 
         self.on_movement_finish.publish(
             OnMovementFinish(tick.index, tick.day, tick.step, total))
-
-    def _travelers(self, clause: TravelClause, tick: Tick, local_cohorts: NDArray[SimDType]) -> NDArray[SimDType]:
-        """
-        Calculate the number of travelers resulting from this movement clause for this tick.
-        This evaluates the requested number movers, modulates that based on the available movers,
-        then selects exactly which individuals (by compartment) should move.
-        Returns an (N,N,C) array; from-source-to-destination-by-compartment.
-        """
-        _, N, C, _ = self._ctx.dim.TNCE
-
-        clause_movers = clause.requested(self._ctx, self._predef, tick)
-        np.fill_diagonal(clause_movers, 0)
-        clause_sum = clause_movers.sum(axis=1, dtype=SimDType)
-
-        available_movers = local_cohorts * self._clause_masks[clause]
-        available_sum = available_movers.sum(axis=1, dtype=SimDType)
-
-        # If clause requested total is greater than the total available,
-        # use mvhg to select as many as possible.
-        if not np.any(clause_sum > available_sum):
-            throttled = False
-            requested_movers = clause_movers
-            requested_sum = clause_sum
-        else:
-            throttled = True
-            requested_movers = clause_movers.copy()
-            for src in range(N):
-                if clause_sum[src] > available_sum[src]:
-                    requested_movers[src, :] = self._ctx.rng.multivariate_hypergeometric(
-                        colors=requested_movers[src, :],
-                        nsample=available_sum[src]
-                    )
-            requested_sum = requested_movers.sum(axis=1, dtype=SimDType)
-
-        # The probability a mover from a src will go to a dst.
-        requested_prb = row_normalize(requested_movers, requested_sum, dtype=SimDType)
-
-        travelers_cs = np.zeros((N, N, C), dtype=SimDType)
-        for src in range(N):
-            if requested_sum[src] == 0:
-                continue
-
-            # Select which individuals will be leaving this node.
-            mover_cs = self._ctx.rng.multivariate_hypergeometric(
-                available_movers[src, :],
-                requested_sum[src]
-            ).astype(SimDType)
-
-            # Select which location they are each going to.
-            # (Each row contains the compartments for a destination.)
-            travelers_cs[src, :, :] = self._ctx.rng.multinomial(
-                mover_cs,
-                requested_prb[src, :]
-            ).T.astype(SimDType)
-
-        self.on_movement_clause.publish(
-            OnMovementClause(
-                tick.index,
-                tick.day,
-                tick.step,
-                clause.name,
-                clause_movers,
-                travelers_cs,
-                requested_sum.sum(),
-                throttled,
-            )
-        )
-
-        return travelers_cs

epymorph/simulation.py

@@ -238,55 +238,3 @@ def enable_logging(filename: str = 'debug.log', movement: bool = True) -> None:
     logging.basicConfig(filename=filename, filemode='w')
     if movement:
         logging.getLogger('movement').setLevel(logging.DEBUG)
-
-
-def epymorph_namespace() -> dict[str, Any]:
-    """
-    Make a safe namespace for user-defined functions,
-    including utilities that functions might need in epymorph.
-    """
-    return {
-        'SimDType': SimDType,
-        # our utility functions
-        'pairwise_haversine': pairwise_haversine,
-        'row_normalize': row_normalize,
-        # numpy namespace
-        'np': ImmutableNamespace({
-            # numpy utility functions
-            'array': partial(np.array, dtype=SimDType),
-            'zeros': partial(np.zeros, dtype=SimDType),
-            'zeros_like': partial(np.zeros_like, dtype=SimDType),
-            'ones': partial(np.ones, dtype=SimDType),
-            'ones_like': partial(np.ones_like, dtype=SimDType),
-            'full': partial(np.full, dtype=SimDType),
-            'arange': partial(np.arange, dtype=SimDType),
-            'concatenate': partial(np.concatenate, dtype=SimDType),
-            'sum': partial(np.sum, dtype=SimDType),
-            'newaxis': np.newaxis,
-            'fill_diagonal': np.fill_diagonal,
-            # numpy math functions
-            'radians': np.radians,
-            'degrees': np.degrees,
-            'exp': np.exp,
-            'log': np.log,
-            'sin': np.sin,
-            'cos': np.cos,
-            'tan': np.tan,
-            'arcsin': np.arcsin,
-            'arccos': np.arccos,
-            'arctan': np.arctan,
-            'arctan2': np.arctan2,
-            'sqrt': np.sqrt,
-            'add': np.add,
-            'subtract': np.subtract,
-            'multiply': np.multiply,
-            'divide': np.divide,
-            'maximum': np.maximum,
-            'minimum': np.minimum,
-            'absolute': np.absolute,
-            'floor': np.floor,
-            'ceil': np.ceil,
-            'pi': np.pi,
-        }),
-        **base_namespace(),
-    }