scipys quadrature function complains about perfectly sane lambda?
Question:
I have 2 versions of a snippet one works one doesn’t, this works:
f = lambda x : x * 2.0 * pi
print(scipy.integrate.quadrature(f, 0.0, 1.0))
This fails:
f = lambda x : math.exp(x * 2.0 * pi)`
print(scipy.integrate.quadrature(f, 0.0, 1.0))
With error:
TypeError: only size-1 arrays can be converted to Python scalars
I don;t understand both are scalar functions, why is one accepted but the other is not?
Answers:
You may have intended your functions to operate on scalars, but unless you pass vec_func=False, scipy.integrate.quadrature will assume your functions can safely take and operate elementwise over arrays.
As it happens, your first f can indeed handle arrays, even though you didn’t intend it to. Your second f uses math.exp, which only handles scalars.
I have 2 versions of a snippet one works one doesn’t, this works:
f = lambda x : x * 2.0 * pi
print(scipy.integrate.quadrature(f, 0.0, 1.0))
This fails:
f = lambda x : math.exp(x * 2.0 * pi)`
print(scipy.integrate.quadrature(f, 0.0, 1.0))
With error:
TypeError: only size-1 arrays can be converted to Python scalars
I don;t understand both are scalar functions, why is one accepted but the other is not?
You may have intended your functions to operate on scalars, but unless you pass vec_func=False, scipy.integrate.quadrature will assume your functions can safely take and operate elementwise over arrays.
As it happens, your first f can indeed handle arrays, even though you didn’t intend it to. Your second f uses math.exp, which only handles scalars.