How to integrate using scipy with an array as part of the function

Question

I would like to use the integral command in scipy and have a function that gets multiplied by each element in the array once.

import math 
import matplotlib.pyplot as plt
import numpy as np
import scipy.integrate as integrate
from scipy.integrate import quad, romberg
import scipy.special as special
from numpy import sqrt

yes = np.array([0,1])

def integrate(x,yes):
    return x+yes

result = quad(integrate,0,1,args=(yes))

print(result)

when I do this I get the error only size-1 arrays can be converted to Python scalars

But if I do this

import math 
import matplotlib.pyplot as plt
import numpy as np
import scipy.integrate as integrate
from scipy.integrate import quad, romberg
import scipy.special as special
from numpy import sqrt

yes = np.array([0])

def integrate(x,yes):
    return x+yes

result = quad(integrate,0,1,args=(yes))

print(result)

it gives me this (0.5, 5.551115123125783e-15) Which is exactly what I want, but I would like it for each element in the array.

Is there a way to write a for loop? I've also heard of scipy.integrate.quad_vec, but that was not working. Thank you in advance

args is supposed to get a tuple. (yes) is not a tuple, it is just yes. args=(yes,) is the correct way of passing variable yes to your function. That said, quad can only integrate one value; your function needs to return a scalar. — hpaulj
– hpaulj, Commented Feb 2, 2020 at 21:03

Nico Schlömer · Accepted Answer · 2020-02-02 23:14:36Z

2

You can use quadpy, it's fully vectorized. Just make sure that your function f, if given an input x of a particular length/shape, returns an object of shape range_shape + x.shape. The result will be of shape range_shape.

import numpy as np
from quadpy import quad


def f(x):
    return np.add.outer(np.array([0, 1]), x)


val, err = quad(f, 0, 1)
print(val)

[0.5 1.5]

answered Feb 2, 2020 at 23:14

Nico Schlömer

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