I have the following for loop that is part of a larger code. So far it has been running over night. The input data is a file of three columns and roughly 5 million rows. The code is not carrying out any complex computations so I am at a loss as to why this is taking so long to complete. I am running cProfile at the moment to see if I can find any bottle necks , but wanted to ask if there was anything simple that I have missed?
TID = []
M = []
R = []
ID = np.array(TID,dtype=float)
MASS = np.array(M, dtype=float) #Converts lists to NumPy arrays
RED = np.array(R, dtype=float)
def formation_def():
count = 100000000
l =len(TID)
for i in range(l):
if ID[i] == count:
for j in range(i,l):
if MASS[j] > (0.02)*MASS[i]/2:
continue
else:
filesave(MASS[j-1],RED[j-1])
count += 100000000
break
else:
count +=100000000
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