Here an array of functions is generated. Is there some vectorized way (ie. not an explicit loop) of calling them?
Example:
funcs = np.array(lambda x: 2*x, lambda x: 2.5*x)#in principle more funcs
args = np.array([3.0,4.0])
# numpy array of func[0](arg[0]), func[1](arg[1])
#output : array([6.0,10.0])
The functions are assumed to have the same signature, but are assumed to be non-trivial (eg. spline functions of a set of curves), and completely independent of eachother.
You could use itertools.imap as follows:
from itertools import imap
import numpy as np
funcs = np.array([lambda x: 2*x, lambda x: 2.5*x])
args = np.array([3.0,4.0])
answer = np.fromiter(imap(lambda func, arg: func(arg), funcs, args),float)
print(answer)
Output
[6.0, 10.0]
list.without import anything, try this:
import numpy as np
funcs = np.array(lambda x: 2*x, lambda x: 2.5*x)#in principle more funcs
args = np.array([3.0,4.0])
output = map(lambda x,y:x(y), funcs, args)
it works also on list and tuple.
