Source code for pypdevs.randomGenerator
# 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.
"""
Module to offer 'really deterministic' (pseudo-)random number generation in a Distributed Time Warp implementation.
For local simulation, using the random library from Python as usual is perfectly ok.
"""
import random
[docs]class RandomGenerator(object):
"""
Base class, which implements a random number interface for the 'uniform' and 'random' Python standard library functions.
.. note:: The generated random numbers are **not** equal to those generated by direct calls to the library functions, as we also use a random number to initialize the seed in the next iteration.
"""
[docs] def __init__(self, seed):
"""
Constructor
:param seed: the seed to start with, this will simply be passed to the *random* library at every function call
"""
#NOTE: This is implemented using only a seed (and actually, only a number), instead of using the 'getState()' en 'setState(state)'
# functions provided by the library. This was done to allow far more simple comparison (for memoization), hashing (as we
# have overwritten the comparison) and copying (for custom state saving).
self.seed = seed
[docs] def __eq__(self, other):
"""
Compare two instances of random number generators.
Needed for memoization.
:param other: the instance to compare with
:returns: bool -- do these random number generators return the same sequence?
"""
return type(self) == type(other) and self.seed == other.seed
[docs] def __hash__(self):
"""
Hash this random number generator.
Needed as the comparison method was changed!
:returns: hash
"""
return self.seed
[docs] def copy(self):
"""
A copy method to be used when defining custom state saving methods. It will return a complete copy of this random number
generator, which will generate exactly the same sequence of numbers.
"""
return RandomGenerator(self.seed)
def __wrapFunction(self, func, args):
"""
Internal wrapper for most functions, allows easy addition of new functions should the need arise. It updates the internal state and
guarantees determinism even when revertions happen.
:param func: the function to call on the *random* module (a string)
:param args: the arguments to pass (a list)
:returns: random -- the generated value
"""
random.seed(self.seed)
val = getattr(random, func)(*args)
self.seed = random.random()
return val
[docs] def random(self):
"""
Call the random function of the *random* library.
:returns: float -- a random value between 0 and 1
"""
return self.__wrapFunction("random", [])