CODEWITHSUNDEEP
pythonscipynumerical-integrationquad
user7248647
user7248647

Reputation: 67

Python: Evaluating Integral for array

import numpy

import matplotlib.pyplot as plt

from scipy import integrate

def f(x,y):
    return x*y + x**2 

def integral(x,y):
    I = integrate.quad(f, 0, x, args=(y,))[0]
    return I

def gau(x,y):
    return (1+x)*integral(x,y)


xlist = numpy.linspace(-3.0, 3.0, 100)
ylist = numpy.linspace(-3.0, 3.0, 100)
X, Y = numpy.meshgrid(xlist, ylist)
Z = gau(2, Y)

print(Z)

I keep on getting the error message "Supplied function does not return a valid float." , I think the problem is that I try to pass an array to the quad function. I thought about evaluating the integral for every entry of the array with something like that: 

yi=numpy.linspace(-3.0,3.0,100)
for i, item in enumerate(yi):
    return integral[i]=integrate.quad(f,0,x,args=(yi,))[0]

It doesn't work but is it the right way? Any other/better suggestions?

Upvotes: 0

Views: 652

Answers (3)

Nico Schlömer
Nico Schlömer

Reputation: 58721

You can use quadpy (one of my projects). quadpy is fully vectorized with respect to the dimensionality of the function range and the domains, so you can plug in a function that returns a vector and integrate that function over many intervals at once. You just have to make sure that the input function deals with vectorized input correctly. In your case, that would be

import numpy
import quadpy


def f(x, y):
    return numpy.multiply.outer(y, x) + numpy.multiply.outer(numpy.ones_like(y), x ** 2)


def integral(x, y):
    scheme = quadpy.line_segment.gauss_legendre(5)
    intervals = numpy.array([numpy.zeros_like(x), x])
    out = scheme.integrate(lambda t: f(t, y), intervals)
    return out


def gau(x, y):
    return (1 + x) * integral(x, y)


xlist = numpy.linspace(-3.0, 3.0, 100)
ylist = numpy.linspace(-3.0, 3.0, 100)
Z = gau(2, ylist)

print(Z)

You also insert xlist instead of 2 here to compute it all at once.

Upvotes: 0

mzzx
mzzx

Reputation: 2164

You could use a universal function (see https://docs.scipy.org/doc/numpy/reference/ufuncs.html) which operates on arrays element-by-element. You can create these universal functions from any function using the frompyfunc function (https://docs.scipy.org/doc/numpy/reference/generated/numpy.frompyfunc.html):

ugau = numpy.frompyfunc(gau,2,1)
Z=ugau(X,Y)

Upvotes: 2

Marek Ososinski
Marek Ososinski

Reputation: 21

It if your f() that does not provide a valid float when passed an array, not the scipy.integral itself;

why do you pass an array to your f() ?

Upvotes: 0

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