I'm using the bisection method from the scipy.optimize package within a for loop. The idea is to get a value of "sig" with the bisection method for each element (value) in the "eps_komp" vector. I've coded this much:
import numpy as np
import scipy.optimize as optimize
K=300
n = 0.43
E = 210000
Rm = 700
sig_a = []
RO_K = 300
RO_n = 0.43
eps_komp = [0.00012893048999999997,
0.018839115269999998,
0.01230539995,
0.022996934109999999,
-0.0037319012899999999,
0.023293921169999999,
0.0036927752099999997,
0.020621037629999998,
0.0063656587500000002,
0.020324050569999998,
-0.0025439530500000001,
0.018542128209999998,
0.01230539995,
0.019730076449999998,
0.0045837363899999999,
0.015275270549999997,
-0.0040288883499999999,
0.021215011749999999,
-0.0031379271699999997,
0.023590908229999999]
def eps_f(i):
return eps_komp[i]
for j in range(len(eps_komp)):
eps_komp_j = eps_f(j)
if j <= len(eps_komp):
def func(sig):
return eps_komp_j - sig/E - (sig/RO_K)**(1/RO_n)
sig_a.append(optimize.bisect(func, 0, Rm))
else:
break
print(sig_a)
Now if I change the the value of "j" in eps_f(j) to 0:
eps_komp_j = eps_f(0)
it works, and so it does for all other values that I insert by hand, but if I keep it like it is in the for loop, the "j" value doesnt change automatically and I get an error:
f(a) and f(b) must have different signs
Has anyone a clue what is the problem and how could this be solved?
Regards,
L
P.S. I did post another topic on this problem yesterday, but I wasnt very specific with the problem and got negative feedback. However, I do need to solve this today, so I was forced to post it again, however I did manage to get a bit further with the code then I did in the earlier post, so it isn't a repost...