turn an array of (scalar) functions into a function returning an array

Question

I have an array farr of functions, say

import numpy as np
farr=np.array([(lambda x, y: x+y) for n in range(5)])

(in reality, the functions are all different splines) Now, I would like one function f that returns the result of all the functions in farr as an array. Basically this:

def f(x, y):
    return np.array([f(x, y) for f in farr])

Can this be done in a more efficient way?

and what did you get with this code ? What result did you expect? Use some example data to show expected result. — furas
– furas, Commented Nov 20, 2019 at 16:21
@furas my code works, but I wonder if this is the most efficient way — riddleculous
– riddleculous, Commented Nov 20, 2019 at 16:32
If farr is a list instead of an array it should iterate a bit faster. — hpaulj
– hpaulj, Commented Nov 20, 2019 at 16:45
frompyfunc often provides a modest improvement over iteration (up to 2x). A possible use: fn=np.frompyfunc(lambda f,x,y:f(x,y),3,1), and fn(farr[:,None],x,y). — hpaulj
– hpaulj, Commented Nov 20, 2019 at 16:54

J. Jaccard · Accepted Answer · 2019-11-20 17:06:56Z

2

Another way is to use map:

x = 3
y = 3
value = list(map(lambda f: f(x,y), farr))

For more details see map doc. On my machine this is a tiny bit more efficient (~20% faster)

answered Nov 20, 2019 at 17:06

J. Jaccard

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1 Comment

riddleculous Over a year ago

I like this. Typically, I think of mapping a function over some value, but here I "map the values" over some functions.

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