Hi
I am attempting to translate some of the models that Donella Meadows
wrote about in her book "Thinking in systems" into code. Originally, I
had wanted to do this in Python, but thought that it would be fun to see
if it is feasible to do so in R, especially given the plotting capacity
of R.
Meadows describes a very simple example of a stock and flow: 50 gallons
of water in a bath tub - drain out at a rate of 5 gal/ minute and then
turn on the faucet after five minutes which flows at 5 gal/ min. The
outcome is obviously that after 5 minutes, the bath tub will maintain a
steady stock of 25 gal thereafter.
My basic code in Python looks like this:
====Python code=====
stock = 50
time = 1
inflow_a = 0
inflow_b = 5
outflow = 5
x = [stock]
y = [time]
print "Model of inflow and outflow rates of water"
print "version 3"
print
print stock
while time <= 5:
stock = (stock - outflow) + inflow_a
time += 1
y += [time]
x += [stock]
print stock
if stock == 30:
print "Faucet turned on"
while time >= 6 and time <= 9:
stock = (stock - outflow) + inflow_b
time += 1
y += [time]
x += [stock]
print stock
print "Volume in tub stabilises at %d gallons over %d minutes" % (stock,
time)
print x
print y
==== end code====
I want to translate this into an equivalent script in R.
After some searching around, I found how to set up a while loop, and
constructed the first section, like this:
======R code======
while(time <= 10) {
if time <= 5
stock <
time <- time + 1
print(time)
}
===== end code =====
However, what I would like to learn how to do is to nest the if
conditions in a way similar to that given in the Python code.
I'm sure that there must be some very elegant way to do this, but I
cannot find out how to do so in any of the books I have, nor do my web
searches throw back anything useful (I suspect that I'm not phrasing the
question properly).
Can someone please offer a few suggestions about ways that I could
translate the Python script into R so that I can then run a plot as well?
Many thanks in anticipation.
Sun
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