MNT: remove legacy product_ids and agent_ids code

pyblp/economies/economy.py

@@ -244,55 +244,6 @@ def _validate_name(self, name: Optional[str], none_valid: bool = True) -> None:
         if name not in names:
             raise NameError(f"'{name}' is not None or one of the underlying variables, {list(sorted(names))}.")
 
-    def _validate_product_ids(self, product_ids: Sequence[Any], market_ids: Optional[Array] = None) -> None:
-        """Validate that product IDs either contain None (denoting the outside option) or contain at least one product
-        ID for each market in the data (or in specific markets if specified). Also verify that each product ID appears
-        only once in each relevant market.
-        """
-        if self.unique_product_ids.size == 0 and any(i is not None for i in product_ids):
-            raise ValueError("Product IDs must have been specified.")
-
-        if market_ids is None:
-            market_ids = self.unique_market_ids
-
-        for t in market_ids:
-            counts = []
-            for product_id in product_ids:
-                count = 1
-                if product_id is not None:
-                    count = (self.products.product_ids[self._product_market_indices[t]] == product_id).sum()
-                    if count > 1:
-                        raise ValueError(
-                            f"Product IDs should be unique within markets, but ID '{product_id}' shows up {count} "
-                            f"times in market '{t}'."
-                        )
-
-                counts.append(count)
-
-            if all(c == 0 for c in counts):
-                raise ValueError(
-                    f"None of the product_ids {sorted(list(product_ids))} show up in market '{t}' with IDs: "
-                    f"{list(sorted(self.products.product_ids[self._product_market_indices[t]]))}."
-                )
-
-    def _validate_agent_ids(self, agent_ids: Sequence[Any], market_ids: Optional[Array] = None) -> None:
-        """Validate that agent IDs have at least one agent ID for each market in the data (or in specific markets if
-        specified).
-        """
-        if self.unique_agent_ids.size == 0:
-            raise ValueError("Agent IDs must have been specified.")
-
-        if market_ids is None:
-            market_ids = self.unique_market_ids
-
-        for t in market_ids:
-            counts = [(self.agents.agent_ids[self._agent_market_indices[t]] == i).sum() for i in agent_ids]
-            if all(c == 0 for c in counts):
-                raise ValueError(
-                    f"None of the agent_ids {sorted(list(agent_ids))} show up in market '{t}' with IDs: "
-                    f"{list(sorted(self.agents.agent_ids[self._agent_market_indices[t]]))}."
-                )
-
     def _coerce_optional_firm_ids(self, firm_ids: Optional[Any], market_ids: Optional[Array] = None) -> Array:
         """Coerce optional array-like firm IDs into a column vector and validate it. By default, assume that firm IDs
         are for all markets.

pyblp/economies/problem.py

@@ -1218,7 +1218,7 @@ class Problem(ProblemEconomy):
 
         It may be convenient to define IDs for different products:
 
-            - **product_ids** (`object, optional`) - IDs that identify individual products within markets.
+            - **product_ids** (`object, optional`) - IDs that identify products within markets.
 
         Finally, clustering groups can be specified to account for within-group correlation while updating the weighting
         matrix and estimating standard errors:
@@ -1268,8 +1268,8 @@ class Problem(ProblemEconomy):
 
         It may be convenient to define IDs for different agents:
 
-            - **agent_ids** (`object, optional`) - IDs that identify individual agents within markets. There can be
-              multiple of the same ID within a market.
+            - **agent_ids** (`object, optional`) - IDs that identify agents within markets. There can be multiple of the
+              same ID within a market.
 
         Along with ``market_ids`` and ``agent_ids``, the names of any additional fields can be typically be used as
         variables in ``agent_formulation``. The exception is the name ``'demographics'``, which is reserved for use by

pyblp/economies/simulation.py

@@ -106,7 +106,7 @@ class Simulation(Economy):
 
         It may be convenient to define IDs for different products:
 
-            - **product_ids** (`object, optional`) - IDs that identify individual products within markets.
+            - **product_ids** (`object, optional`) - IDs that identify products within markets.
 
         To simulate a nested logit or random coefficients nested logit (RCNL) model, nesting groups must be specified:
 
@@ -170,8 +170,8 @@ class Simulation(Economy):
 
         It may be convenient to define IDs for different agents:
 
-            - **agent_ids** (`object, optional`) - IDs that identify individual agents within markets. There can be
-              multiple of the same ID within a market.
+            - **agent_ids** (`object, optional`) - IDs that identify agents within markets. There can be multiple of the
+              same ID within a market.
 
         Along with ``market_ids`` and ``agent_ids``, the names of any additional fields can typically be used as
         variables in ``agent_formulation``. The exception is the name ``'demographics'``, which is reserved for use by

pyblp/markets/market.py

@@ -1,7 +1,7 @@
 """Market underlying the BLP model."""
 
 import functools
-from typing import Any, Dict, List, Optional, Sequence, Tuple
+from typing import Any, Dict, List, Optional, Tuple
 
 import numpy as np
 
@@ -130,16 +130,6 @@ def __init__(
         with np.errstate(all='ignore'):
             self.mu = self.compute_mu()
 
-    def get_product(self, product_id: Any) -> int:
-        """Get the product index associated with a product ID. This assumes that the market has already been validated
-        to make sure that the product ID appears exactly once.
-        """
-        return int(np.argmax(self.products.product_ids == product_id))
-
-    def get_agents_index(self, agent_ids: Sequence[Any]) -> Array:
-        """Get an index of agents associated with agent IDs."""
-        return np.array([i in agent_ids for i in self.agents.agent_ids])
-
     def get_membership_matrix(self) -> Array:
         """Build a membership matrix from nesting IDs."""
         if self.membership_matrix is None:

pyblp/markets/results_market.py

@@ -378,9 +378,8 @@ def safely_compute_consumer_surplus(
 
         # eliminate any products from the choice set
         if eliminate_product_ids is not None:
-            for product_id in eliminate_product_ids:
-                if product_id in self.products.product_ids:
-                    j = self.get_product(product_id)
+            for j, product_id in enumerate(self.products.product_ids):
+                if product_id in eliminate_product_ids:
                     exp_utilities[j] = 0
 
         # handle nesting

pyblp/primitives.py

@@ -30,7 +30,7 @@ class Products(object):
     nesting_ids : `ndarray`
         IDs that associate products with nesting groups.
     product_ids : `ndarray`
-        IDs that identify individual products within markets.
+        IDs that identify products within markets.
     clustering_ids : `ndarray`
         IDs used to compute clustered standard errors.
     ownership : `ndarray`
@@ -157,13 +157,8 @@ def __new__(
             raise ValueError("The firm_ids field of product_data must be one-dimensional.")
         if nesting_ids is not None and nesting_ids.shape[1] > 1:
             raise ValueError("The nesting_ids field of product_data must be one-dimensional.")
-        if product_ids is not None:
-            if product_ids.shape[1] > 1:
-                raise ValueError("The product_ids field of product_data must be one-dimensional.")
-            if any(i is None for i in product_ids):
-                raise ValueError(
-                    "The product_ids field of product_data must not contain None, which denotes the outside option."
-                )
+        if product_ids is not None and product_ids.shape[1] > 1:
+            raise ValueError("The product_ids field of product_data must be one-dimensional.")
         if clustering_ids is not None:
             if clustering_ids.shape[1] > 1:
                 raise ValueError("The clustering_ids field of product_data must be one-dimensional.")
@@ -237,7 +232,7 @@ class Agents(object):
     market_ids : `ndarray`
         IDs that associate agents with markets.
     agent_ids : `ndarray`
-        IDs that identify individual agents within markets.
+        IDs that identify agents within markets.
     weights : `ndarray`
         Integration weights, :math:`w`.
     nodes : `ndarray`