Reputation: 2283
Why doesn't the following function take the inner h
value that is defined in the function body and gives weird results (arbitrary h
value)?
def diff(f): # def not define
h = 0.001
return (lambda x: (f(x+h) - f(x)) / h)
def sin_by_million (x):
return math.sin( 10 ** 6 *x)
>>> diff(sin_by_million) (0)
826.8795405320026
Instead of 1000000
?
Upvotes: 0
Views: 48
Reputation: 26211
As per @ThierryLathuille comment, your step h
is too big. In real life, you should adapt it based on the function and value at which you want the derivative.
Check out jax
instead:
import jax
import jax.numpy as np
def sin_by_million(x):
return np.sin(1e6 * x)
Then:
>>> g = jax.grad(sin_by_million)
... g(0.0)
DeviceArray(1000000., dtype=float32)
The beauty of jax
is that it actually compiles your call tree using chain rule, and produces some code (the calls after the first one are much, much faster). It also works on multivariate functions and complex code (with some rules though). And it works wonderfully well & fast on GPUs.
Upvotes: 1