Difference between revisions of "Modeling"
Jump to navigation
Jump to search
Line 1: | Line 1: | ||
− | Mostly based on [http://greenteapress.com/ModSimPy/ModSimPy.pdf this paper] | + | Mostly based on [http://greenteapress.com/ModSimPy/ModSimPy.pdf this paper] that comes with its own modsim library. |
=Eyeopeners= | =Eyeopeners= | ||
Line 20: | Line 20: | ||
results[a] = functioncall(bla,bla) | results[a] = functioncall(bla,bla) | ||
</syntaxhighlight> | </syntaxhighlight> | ||
− | TimeSeries is a modified version (subclass) of the pandas.Series class. | + | TimeSeries is a modsim modified version (subclass) of the pandas.Series class. |
Revision as of 15:41, 15 December 2018
Mostly based on this paper that comes with its own modsim library.
Eyeopeners
Store results in a list.
for a in range(100):
funcAresults[a] = functionAcall(bla,bla)
funcBresults[a] = functionBcall(bla,bla)
ModSimPy is using Series from Pandas to store results. This adds handy functions.
- results.mean()
- Return the mean (average) for the items in results
I have not studied the pandas Series yet but this works:
from modsim import *
results = TimeSeries()
for a in range(100):
results[a] = functioncall(bla,bla)
TimeSeries is a modsim modified version (subclass) of the pandas.Series class.