"""
======================
Partitioning Processes
======================
This bundle of processes includes Requester, Evolver, and PartitionedProcess.
PartitionedProcess is the inherited base class for all Processes that can be
partitioned; these processes provide calculate_request or evolve_state methods,
rather than the usual Process next_update.
A PartitionedProcess can be passed into a Requester and Evolver, which call its
calculate_request and evolve_state methods in coordination with an Allocator process,
which reads the requests and allocates molecular counts for the evolve_state.
"""
import abc
import warnings
from vivarium.core.process import Step, Process
from vivarium.library.dict_utils import deep_merge
from ecoli.processes.registries import topology_registry
[docs]
class Requester(Step):
"""Requester Step
Accepts a PartitionedProcess as an input, and runs in coordination with an
Evolver that uses the same PartitionedProcess.
"""
defaults = {"process": None}
def __init__(self, parameters=None):
assert isinstance(parameters["process"], PartitionedProcess)
if parameters["process"].parallel:
raise RuntimeError("PartitionedProcess objects cannot be parallelized.")
parameters["name"] = f'{parameters["process"].name}_requester'
super().__init__(parameters)
[docs]
def update_condition(self, timestep, states):
"""
Implements variable timestepping for partitioned processes
Vivarium cycles through all :py:class:~vivarium.core.process.Step`
instances every time a :py:class:`~vivarium.core.process.Process`
instance updates the simulation state. When that happens, Vivarium
will only call the :py:meth:`~.Requester.next_update` method of this
Requester if ``update_condition`` returns True.
Each process has access to a process-specific ``next_update_time``
store and the ``global_time`` store. If the next update time is
less than or equal to the global time, the process runs. If the
next update time is ever earlier than the global time, this usually
indicates that the global clock process is running with too large
a timestep, preventing accurate timekeeping.
"""
if states["next_update_time"] <= states["global_time"]:
if states["next_update_time"] < states["global_time"]:
warnings.warn(
f"{self.name} updated at t="
f"{states['global_time']} instead of t="
f"{states['next_update_time']}. Decrease the "
"timestep of the global_clock process for more "
"accurate timekeeping."
)
return True
return False
[docs]
def ports_schema(self):
process = self.parameters.get("process")
ports = process.get_schema()
ports["request"] = {
"bulk": {
"_updater": "set",
"_divider": "null",
"_emit": False,
}
}
ports["process"] = {
"_default": tuple(),
"_updater": "set",
"_divider": "null",
"_emit": False,
}
ports["global_time"] = {"_default": 0.0}
ports["timestep"] = {"_default": process.parameters["time_step"]}
ports["next_update_time"] = {
"_default": process.parameters["timestep"],
"_updater": "set",
"_divider": "set",
}
self.cached_bulk_ports = list(ports["request"].keys())
return ports
[docs]
def next_update(self, timestep, states):
process = states["process"][0]
request = process.calculate_request(self.parameters["time_step"], states)
process.request_set = True
request["request"] = {}
# Send bulk requests through request port
for bulk_port in self.cached_bulk_ports:
bulk_request = request.pop(bulk_port, None)
if bulk_request is not None:
request["request"][bulk_port] = bulk_request
# Ensure listeners are updated if present
listeners = request.pop("listeners", None)
if listeners is not None:
request["listeners"] = listeners
# Update shared process instance
request["process"] = (process,)
return request
[docs]
class Evolver(Step):
"""Evolver Step
Accepts a PartitionedProcess as an input, and runs in coordination with an
Requester that uses the same PartitionedProcess.
"""
defaults = {"process": None}
def __init__(self, parameters=None):
assert isinstance(parameters["process"], PartitionedProcess)
parameters["name"] = f'{parameters["process"].name}_evolver'
super().__init__(parameters)
[docs]
def update_condition(self, timestep, states):
"""
See :py:meth:`~.Requester.update_condition`.
"""
if states["next_update_time"] <= states["global_time"]:
if states["next_update_time"] < states["global_time"]:
warnings.warn(
f"{self.name} updated at t="
f"{states['global_time']} instead of t="
f"{states['next_update_time']}. Decrease the "
"timestep for the global clock process for more "
"accurate timekeeping."
)
return True
return False
[docs]
def ports_schema(self):
process = self.parameters.get("process")
ports = process.get_schema()
ports["allocate"] = {
"bulk": {
"_updater": "set",
"_divider": "null",
"_emit": False,
}
}
ports["process"] = {
"_default": tuple(),
"_updater": "set",
"_divider": "null",
"_emit": False,
}
ports["global_time"] = {"_default": 0.0}
ports["timestep"] = {"_default": process.parameters["timestep"]}
ports["next_update_time"] = {
"_default": process.parameters["timestep"],
"_updater": "set",
"_divider": "set",
}
return ports
[docs]
def next_update(self, timestep, states):
allocations = states.pop("allocate")
states = deep_merge(states, allocations)
process = states["process"][0]
# If the Requester has not run yet, skip the Evolver's update to
# let the Requester run in the next time step. This problem
# often arises after division because after the step divider
# runs, Vivarium wants to run the Evolvers instead of re-running
# the Requesters. Skipping the Evolvers in this case means our
# timesteps are slightly off. However, the alternative is to run
# self.process.calculate_request and discard the result before
# running the Evolver this timestep, which means we skip the
# Allocator. Skipping the Allocator can cause the simulation to
# crash, so having a slightly off timestep is preferable.
if not process.request_set:
return {}
update = process.evolve_state(timestep, states)
update["process"] = (process,)
update["next_update_time"] = states["global_time"] + states["timestep"]
return update
[docs]
class PartitionedProcess(Process):
"""Partitioned Process Base Class
This is the base class for all processes whose updates can be partitioned.
"""
def __init__(self, parameters=None):
super().__init__(parameters)
# set partition mode
self.evolve_only = self.parameters.get("evolve_only", False)
self.request_only = self.parameters.get("request_only", False)
self.request_set = False
# register topology
assert self.name
assert self.topology
topology_registry.register(self.name, self.topology)
[docs]
@abc.abstractmethod
def ports_schema(self):
return {}
[docs]
@abc.abstractmethod
def calculate_request(self, timestep, states):
return {}
[docs]
@abc.abstractmethod
def evolve_state(self, timestep, states):
return {}
[docs]
def next_update(self, timestep, states):
if self.request_only:
return self.calculate_request(timestep, states)
if self.evolve_only:
return self.evolve_state(timestep, states)
requests = self.calculate_request(timestep, states)
bulk_requests = requests.pop("bulk", [])
if bulk_requests:
bulk_copy = states["bulk"].copy()
for bulk_idx, request in bulk_requests:
bulk_copy[bulk_idx] = request
states["bulk"] = bulk_copy
states = deep_merge(states, requests)
update = self.evolve_state(timestep, states)
if "listeners" in requests:
update["listeners"] = deep_merge(update["listeners"], requests["listeners"])
return update