Python/Biophysics- Trying to code a simple stochastic simulation!
- by user359597
Hey guys- I'm trying to figure out what to make of the following code- this is not the clear, intuitive python I've been learning. Was it written in C or something then wrapped in a python fxn? The code I wrote (not shown) is using the same math, but I couldn't figure out how to write a conditional loop. If anyone could explain/decipher/clean this up, I'd be really appreciative. I mean- is this 'good' python- or does it look funky? I'm brand new to this- but it's like the order of the fxns is messed up? I understand Gillespie's- I've successfully coded several simpler simulations. So in a nutshell- good code-(pythonic)? order? c? improvements? am i being an idiot? The code shown is the 'answer,' to the following question from a biophysics text (petri-net not shown and honestly not necessary to understand problem):
"In a programming language of your choice, implement Gillespie’s First Reaction Algorithm to study the temporal behaviour of the reaction A---B in which the transition from A to B can only take place if another compound, C, is present, and where C dynamically interconverts with D, as modelled in the Petri-net below. Assume that there are 100 molecules of A, 1 of C, and no B or D present at the start of the reaction. Set kAB to 0.1 s-1 and both kCD and kDC to 1.0 s-1. Simulate the behaviour of the system over 100 s."
def sim():
# Set the rate constants for all transitions
kAB = 0.1
kCD = 1.0
kDC = 1.0
# Set up the initial state
A = 100
B = 0
C = 1
D = 0
# Set the start and end times
t = 0.0
tEnd = 100.0
print "Time\t", "Transition\t", "A\t", "B\t", "C\t", "D"
# Compute the first interval
transition, interval = transitionData(A, B, C, D, kAB, kCD, kDC)
# Loop until the end time is exceded or no transition can fire any more
while t <= tEnd and transition >= 0:
print t, '\t', transition, '\t', A, '\t', B, '\t', C, '\t', D
t += interval
if transition == 0:
A -= 1
B += 1
if transition == 1:
C -= 1
D += 1
if transition == 2:
C += 1
D -= 1
transition, interval = transitionData(A, B, C, D, kAB, kCD, kDC)
def transitionData(A, B, C, D, kAB, kCD, kDC):
""" Returns nTransition, the number of the firing transition (0: A->B,
1: C->D, 2: D->C), and interval, the interval between the time of
the previous transition and that of the current one. """
RAB = kAB * A * C
RCD = kCD * C
RDC = kDC * D
dt = [-1.0, -1.0, -1.0]
if RAB > 0.0:
dt[0] = -math.log(1.0 - random.random())/RAB
if RCD > 0.0:
dt[1] = -math.log(1.0 - random.random())/RCD
if RDC > 0.0:
dt[2] = -math.log(1.0 - random.random())/RDC
interval = 1e36
transition = -1
for n in range(len(dt)):
if dt[n] > 0.0 and dt[n] < interval:
interval = dt[n]
transition = n
return transition, interval
if __name__ == '__main__':
sim()
