"""
=========================
Randomness System Manager
=========================
"""
import pandas as pd
from vivarium.framework.randomness.exceptions import RandomnessError
from vivarium.framework.randomness.index_map import IndexMap
from vivarium.framework.randomness.stream import RandomnessStream, get_hash
[docs]class RandomnessManager:
"""Access point for common random number generation."""
configuration_defaults = {
"randomness": {
"map_size": 1_000_000,
"key_columns": [],
"random_seed": 0,
"additional_seed": None,
}
}
def __init__(self):
self._seed = None
self._clock = None
self._key_columns = None
self._key_mapping = None
self._decision_points = dict()
@property
def name(self):
return "randomness_manager"
[docs] def setup(self, builder):
self._seed = str(builder.configuration.randomness.random_seed)
if builder.configuration.randomness.additional_seed is not None:
self._seed += str(builder.configuration.randomness.additional_seed)
self._clock = builder.time.clock()
self._key_columns = builder.configuration.randomness.key_columns
map_size = builder.configuration.randomness.map_size
pop_size = builder.configuration.population.population_size
map_size = max(map_size, 10 * pop_size)
self._key_mapping = IndexMap(self._key_columns, map_size)
self.resources = builder.resources
self._add_constraint = builder.lifecycle.add_constraint
self._add_constraint(self.get_seed, restrict_during=["initialization"])
self._add_constraint(self.get_randomness_stream, allow_during=["setup"])
self._add_constraint(
self.register_simulants,
restrict_during=[
"initialization",
"setup",
"post_setup",
"simulation_end",
"report",
],
)
[docs] def get_randomness_stream(
self, decision_point: str, initializes_crn_attributes: bool = False
) -> RandomnessStream:
"""Provides a new source of random numbers for the given decision point.
Parameters
----------
decision_point
A unique identifier for a stream of random numbers. Typically
represents a decision that needs to be made each time step like
'moves_left' or 'gets_disease'.
initializes_crn_attributes
A flag indicating whether this stream is used to generate key
initialization information that will be used to identify simulants
in the Common Random Number framework. These streams cannot be
copied and should only be used to generate the state table columns
specified in ``builder.configuration.randomness.key_columns``.
Raises
------
RandomnessError
If another location in the simulation has already created a randomness stream
with the same identifier.
"""
stream = self._get_randomness_stream(decision_point, initializes_crn_attributes)
if not initializes_crn_attributes:
# We need the key columns to be created before this stream can be called.
self.resources.add_resources(
"stream",
[decision_point],
stream,
[f"column.{name}" for name in self._key_columns],
)
self._add_constraint(
stream.get_draw, restrict_during=["initialization", "setup", "post_setup"]
)
self._add_constraint(
stream.filter_for_probability,
restrict_during=["initialization", "setup", "post_setup"],
)
self._add_constraint(
stream.filter_for_rate, restrict_during=["initialization", "setup", "post_setup"]
)
self._add_constraint(
stream.choice, restrict_during=["initialization", "setup", "post_setup"]
)
return stream
def _get_randomness_stream(
self, decision_point: str, initializes_crn_attributes: bool = False
) -> RandomnessStream:
if decision_point in self._decision_points:
raise RandomnessError(
f"Two separate places are attempting to create "
f"the same randomness stream for {decision_point}"
)
stream = RandomnessStream(
key=decision_point,
clock=self._clock,
seed=self._seed,
index_map=self._key_mapping,
initializes_crn_attributes=initializes_crn_attributes,
)
self._decision_points[decision_point] = stream
return stream
[docs] def get_seed(self, decision_point: str) -> int:
"""Get a randomly generated seed for use with external randomness tools.
Parameters
----------
decision_point
A unique identifier for a stream of random numbers. Typically
represents a decision that needs to be made each time step like
'moves_left' or 'gets_disease'.
Returns
-------
int
A seed for a random number generation that is linked to Vivarium's
common random number framework.
"""
return get_hash("_".join([decision_point, str(self._clock()), str(self._seed)]))
[docs] def register_simulants(self, simulants: pd.DataFrame):
"""Adds new simulants to the randomness mapping.
Parameters
----------
simulants
A table with state data representing the new simulants. Each
simulant should pass through this function exactly once.
Raises
------
RandomnessError
If the provided table does not contain all key columns specified
in the configuration.
"""
if not all(k in simulants.columns for k in self._key_columns):
raise RandomnessError(
"The simulants dataframe does not have all specified key_columns."
)
self._key_mapping.update(simulants.loc[:, self._key_columns], self._clock())
def __str__(self):
return "RandomnessManager()"
def __repr__(self) -> str:
return f"RandomnessManager(seed={self._seed}, key_columns={self._key_columns})"
[docs]class RandomnessInterface:
def __init__(self, manager: RandomnessManager):
self._manager = manager
[docs] def get_stream(
self, decision_point: str, initializes_crn_attributes: bool = False
) -> RandomnessStream:
"""Provides a new source of random numbers for the given decision point.
``vivarium`` provides a framework for Common Random Numbers which
allows for variance reduction when modeling counter-factual scenarios.
Users interested in causal analysis and comparisons between simulation
scenarios should be careful to use randomness streams provided by the
framework wherever randomness is employed.
Parameters
----------
decision_point
A unique identifier for a stream of random numbers. Typically
represents a decision that needs to be made each time step like
'moves_left' or 'gets_disease'.
initializes_crn_attributes
A flag indicating whether this stream is used to generate key
initialization information that will be used to identify simulants
in the Common Random Number framework. These streams cannot be
copied and should only be used to generate the state table columns
specified in ``builder.configuration.randomness.key_columns``.
Returns
-------
RandomnessStream
An entry point into the Common Random Number generation framework.
The stream provides vectorized access to random numbers and a few
other utilities.
"""
return self._manager.get_randomness_stream(decision_point, initializes_crn_attributes)
[docs] def get_seed(self, decision_point: str) -> int:
"""Get a randomly generated seed for use with external randomness tools.
Parameters
----------
decision_point :
A unique identifier for a stream of random numbers. Typically
represents a decision that needs to be made each time step like
'moves_left' or 'gets_disease'.
Returns
-------
int
A seed for a random number generation that is linked to Vivarium's
common random number framework.
"""
return self._manager.get_seed(decision_point)
[docs] def register_simulants(self, simulants: pd.DataFrame):
"""Registers simulants with the Common Random Number Framework.
Parameters
----------
simulants
A section of the state table with new simulants and at least the
columns specified in
``builder.configuration.randomness.key_columns``. This function
should be called as soon as the key columns are generated.
"""
self._manager.register_simulants(simulants)