f_tu(t) is given as numpy.array
. The graph looks like this:
How can I implement this? Everything I could find looks something like this
from scipy.integrate import quad
def f(x):
return 1/sin(x)
I = quad(f, 0, 1)
but I have an array there, not a specific function like sin
.
How about auc from sklearn.metrics?
import numpy as np
import numpy as np
from scipy.integrate import quad
from sklearn.metrics import auc
x = np.arange(0, 100, 0.001)
y = np.sin(x)
print('auc:', auc(x,y))
print('quad:', quad(np.sin, 0, 100))
auc: 0.13818791291277366
quad: (0.1376811277123232, 9.459751315610276e-09)