I have a program that creates a solar system, integrates until a close encounter between adjacent planets occur (or until 10e+9 years), then writes two data points to a file. The try and except acts as a flag when planets get too close. This process is repeated 16,000 times. This is all being done by importing the module REBOUND, which is a software package that integrates the motion of particles under the influence of gravity.
for i in range(0,16000):
def P_dist(p1, p2):
x = sim.particles[p1].x - sim.particles[p2].x
y = sim.particles[p1].y - sim.particles[p2].y
z = sim.particles[p1].z - sim.particles[p2].z
dist = np.sqrt(x**2 + y**2 + z**2)
return dist
init_periods = [sim.particles[1].P,sim.particles[2].P,sim.particles[3].P,sim.particles[4].P,sim.particles[5].P]
try:
sim.integrate(10e+9*2*np.pi)
except rebound.Encounter as error:
print(error)
print(sim.t)
for j in range(len(init_periods)-1):
distance = P_dist(j, j+1)
print(j,":",j+1, '=', distance)
if distance <= .01: #returns the period ratio of the two planets that had the close enecounter and the inner orbital period between the two
p_r = init_periods[j+1]/init_periods[j]
with open('good.txt', 'a') as data: #opens a file writing the x & y values for the graph
data.write(str(math.log10(sim.t/init_periods[j])))
data.write('\n')
data.write(str(p_r))
data.write('\n')
Whether or not there is a close encounter depends mostly on a random value I have assigned, and that random value also controls how long a simulation can run. For instance, I chose the random value to be a max of 9.99 and a close encounter happened at approximately 11e+8 years(approximately 14 hours). The random values range from 2-10, and close encounters happen more often on the lower side. Every iteration, if a close encounter occurs, my code will write to the file where I believe may be taking up a lot of simulation time. Since the majority of my simulation time is taken up by trying to locate close encounters, I'd like to shed some time by finding a way to collect the data needed without having to append to the file every iteration.
Since I'm attempting to plot the data collected from this simulation, would creating two arrays and outputting data into those be faster? Or is there a way to only have to write to a file once, when all 16000 iterations are complete?
sim is a variable holding all of the information about the solar system.
This is not the full code, I left out the part where I created the solar system.
count = 0
data = open('good.txt', 'a+')
....
if distance <= .01:
count+=1
while(count<=4570)
data.write(~~~~~~~)
....
data.close()
The problem isn't that you write every time you find a close encounter. It's that, for each encounter, you open the file, write one output record, and close the file. All the opening and appending is slow. Try this, instead: open the file once, and do only one write per record.
# Near the top of the program
data = open('good.txt', 'a')
...
if distance <= .01: #returns the period ratio of the two planets that had the close enecounter and the inner orbital period between the two
# Write one output record
p_r = init_periods[j+1]/init_periods[j]
data.write(str(math.log10(sim.t/init_periods[j])) + '\n' +
str(p_r) + '\n')
...
data.close()
This should work well, as writes will get buffered, and will often run in parallel with the next computation.