Various useful tools in simulating discrete system events based on outcome and probabilities
Project description
Description
eventsim makes discrete event easy to simulate
Currently, it consists of three modules: models, randgen and simevent
MODULES
Models
contains methods for simplifying and calculating:
probability,
estimated variance,
estimated mean,
estimated standard deviation,
expectation value,
discreteEmp
most of its methods takes in two arguments, outcome and cummulative probability and a third optional argument which is how many times an item should be generated or times to be calculated.
Randgen
contains methods for simplifying and generating a:
random outcome,
a unique outcome
times of occurrence of outcome
probability of occurrence
cummulative probability of occurrence
Simevent
contains methods for generating and estimating events that happens in a workplace scenario. Simulating events like:
Interarrival time
Service time
Arrival time
Time when service begins
Time when service ends
Wait time in queue
Time customer spends in system
Idle time of server
help on using this package is included in the installation file or alternatively call. manual(modulename) after importing the package to view how to use it
For more help information please read the help notes provided in the package
Requirements
Any version of python
Acknowledgements
I was inspired to write this package after my university coursework demanded using python to simulate events. I hope Modelling and Simulation students find it useful
All glory belongs to God for helping me in completing my first module.
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