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- CumulRandomStream
class CumulRandomStream() |
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CLASS FOR INITIATING STREAMS OF RANDOM NUMBERS REPRESENTING CUMULATIVE TIME
FOR EVENTS ASSOCIATED WITH HOMOGENEOUS AND INHOMOGENEOUS POISSON PROCESSES.
CUMULATIVE TIME IS RECORDED INTERNALLY AND MUST NOT BE KEPT IN RECORD BY
THE CALLER.
NB. All methods return a single random number on each call.
CumulRandomStream uses the built-in basic rng from Python's built-in
Random class, the so called "Mersenne Twister".
The class is normally used something like this:
rstream1 = CumulRandomStream()
lam1 = 2.5
tstop = 24.0
nrealiz = 1000
for k in range(0, nrealiz)
while True:
tevent = rstream1.rexpo_cum(lam1)
....
if tevent > tstop: break
rstream1.reset()
If another seed than the default is desired just type
rstream1 = CumulRandomStream(|some positive integer|)
In order to continue with a restart from and time zero in the
same simulation the instance must have its methods reset:
rstream1.reset()
A SEPARATE STREAM MUST BE INSTANTIATED FOR EACH ONE OF THE VARIATES
THAT ARE GENERATED USING THIS CLASS, AND IT MAY BE WISE TO START
EACH ONE WITH A SEPARATE SEED!
NB. Methods may return float('inf') or float('-inf') !!!!!
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Methods defined here:
- __init__(self, nseed=2147483647)
- Initiates the instance object and sets cumulative quantities to zero.
- rconst_cum(self, lamc)
- Generates - cumulatively - constantly spaced interarrival times with
arrival rate (arrival frequency) lamc from clock time = 0.0.
NB A dummy random number is picked each time the method is called
for reasons of synchronization.
NB. A SEPARATE STREAM MUST BE INSTANTIATED FOR EACH ONE OF THE VARIATES
THAT ARE GENERATED USING THIS METHOD, EACH WITH A SEPARATE SEED!!
- reset(self)
- Used to reset all cumulative parameters/attributes to zero.
- rexpo_cum(self, lam)
- Generates - cumulatively - exponentially distributed interarrival times
with arrival rate (arrivale frequency) 'lam' from clock time = 0.0.
NB. A SEPARATE STREAM MUST BE INSTANTIATED FOR EACH ONE OF THE VARIATES
THAT ARE GENERATED USING THIS METHOD, EACH WITH A SEPARATE SEED!!
- rinhomexpo_cum(self, lamt, suplamt)
- Generates - cumulatively - inhomogeneously exponentially distributed
interarrival times (due to an inhomogeneous Poisson process) from
clock time = 0.0 (the algorithm is taken from Bratley, Fox & Schrage).
'lamt' is an externally defined function of clock time that returns
the present arrival rate (arrival frequency). 'suplamt' is another
externally defined function that returns the supremum of the arrival
rate over the REMAINING time from the present clock time.
NB. A SEPARATE STREAM MUST BE INSTANTIATED FOR EACH ONE OF THE VARIATES
THAT ARE GENERATED USING THIS METHOD, EACH WITH A SEPARATE SEED!!
- rpiecexpo_cum(self, times, lamt)
- Generates - cumulatively - piecewise exponentially distributed
interarrival times from clock time = 0.0 (the algorithm is taken
from Bratley, Fox & Schrage).
'times' is a list or tuple containing the points at which the arrival
rate (= arrival frequency) changes (the first break time point must
be 0.0). 'lamt' is a list or tuple containing the arrival rates between
break points. The number of elements in 'times' must be one more than
the number of elements in 'lamt'!
The algorithm cranking out the numbers is cyclic - the procedure
starts over from time zero when the last break point is reached.
THE PREVENT THE RESTART FROM TAKING PLACE, A (VERY) LARGE NUMBER
MUST BE GIVEN AS THE LAST BREAK POINT (the cyclicity is rarely
needed or desired in practice).
NB. A SEPARATE STREAM MUST BE INSTANTIATED FOR EACH ONE OF THE VARIATES
THAT ARE GENERATED USING THIS METHOD, EACH WITH A SEPARATE SEED!!
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
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