Source code for pypdevs.schedulers.schedulerDH
# Copyright 2014 Modelling, Simulation and Design Lab (MSDL) at
# McGill University and the University of Antwerp (http://msdl.cs.mcgill.ca/)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
The Dirty Heap is based on a heap, though allows for reschedules.
To allow reschedules to happen, a model is accompagnied by a flag to indicate
whether or not it is still valid. As soon as a model is rescheduled,
the flag of the previously scheduled time is set and another entry is added.
This causes the heap to become *dirty*, requiring a check for the flag
as soon as the first element is requested.
Another problem is that it might consume more memory than other schedulers,
due to invalid elements being kept in memory. However, the actual model and
states are not duplicated as they are references.
The additional memory requirement should not be a problem in most situations.
The 'activity' part from the name stems from the fact that only models where
the *time_next* attribute is smaller than infinity will be scheduled.
Since these elements are not added to the heap, they aren't taken into account
in the complexity. This allows for severe optimisations in situations where
a lot of models can be scheduled for infinity.
Of all provided schedulers, this one is the most mature due to it being the
oldest and also the default scheduler. It is also applicable in every situation
and it offers sufficient performance in most cases.
This scheduler is ideal in situations where (nearly) no reschedules happen and
where most models transition at a different time.
It results in slow behaviour in situations requiring lots of rescheduling,
and thus lots of dirty elements.
This method is also applied in the VLE simulator and is the common approach to
heap schedulers that require invalidation. It varies from the scheduler in ADEVS
due to the heap from the heapq library being used, which doesn't offer functions
to restructure the heap.
Reimplementing these methods in pure Python would be unnecessarily slow.
"""
from heapq import heappush, heappop
from pypdevs.logger import debug
[docs]class SchedulerDH(object):
"""
Scheduler class itself
"""
[docs] def __init__(self, models, epsilon, total_models):
"""
Constructor
:param models: all models in the simulation
"""
self.heap = []
self.id_fetch = [None] * total_models
for model in models:
self.id_fetch[model.model_id] = [model.time_next,
model.model_id,
False,
model]
self.schedule(model)
self.epsilon = epsilon
[docs] def schedule(self, model):
"""
Schedule a model
:param model: the model to schedule
"""
#assert debug("Scheduling " + str(model))
# Create the entry, as we have accepted the model
elem = [model.time_next, model.model_id, False, model]
try:
self.id_fetch[model.model_id] = elem
except IndexError:
# A completely new model
self.id_fetch.append(elem)
# Check if it requires to be scheduled
if model.time_next[0] != float('inf'):
self.id_fetch[model.model_id][2] = True
heappush(self.heap, self.id_fetch[model.model_id])
[docs] def unschedule(self, model):
"""
Unschedule a model
:param model: model to unschedule
"""
#assert debug("Unscheduling " + str(model))
# Update the referece still in the heap
self.id_fetch[model.model_id][2] = False
# Remove the reference in our id_fetch
self.id_fetch[model.model_id] = None
[docs] def massReschedule(self, reschedule_set):
"""
Reschedule all models provided.
Equivalent to calling unschedule(model); schedule(model) on every element in the iterable.
:param reschedule_set: iterable containing all models to reschedule
"""
#NOTE rather dirty, though a lot faster for huge models
#assert debug("Mass rescheduling")
inf = float('inf')
for model in reschedule_set:
event = self.id_fetch[model.model_id]
if event[2]:
if model.time_next == event[0]:
continue
event[2] = False
if model.time_next[0] != inf:
self.id_fetch[model.model_id] = [model.time_next,
model.model_id,
True,
model]
heappush(self.heap, self.id_fetch[model.model_id])
[docs] def readFirst(self):
"""
Returns the time of the first model that has to transition
:returns: timestamp of the first model
"""
#assert debug("Reading first element from heap")
self.cleanFirst()
return self.heap[0][0]
[docs] def cleanFirst(self):
"""
Clean up the invalid elements in front of the list
"""
#assert debug("Cleaning list")
try:
while not self.heap[0][2]:
heappop(self.heap)
except IndexError:
# Nothing left, so it as clean as can be
#assert debug("None in list")
pass
[docs] def getImminent(self, time):
"""
Returns a list of all models that transition at the provided time, with a specified epsilon deviation allowed.
:param time: timestamp to check for models
.. warning:: For efficiency, this method only checks the **first** elements, so trying to invoke this function with a timestamp higher than the value provided with the *readFirst* method, will **always** return an empty set.
"""
#assert debug("Asking all imminent models")
imm_children = []
t, age = time
try:
# Age must be exactly the same
first = self.heap[0]
while (abs(first[0][0] - t) < self.epsilon) and (first[0][1] == age):
# Check if the found event is actually still active
if(first[2]):
# Active, so event is imminent
imm_children.append(first[3])
first[2] = False
# Advance the while loop
heappop(self.heap)
first = self.heap[0]
except IndexError:
pass
return imm_children