I have written a method that approximates a definite integral by the composite Simpson's rule.
#=
f integrand
a lower integration bound
b upper integration bound
n number of iterations or panels
h step size
=#
function simpson(f::Function, a::Number, b::Number, n::Number)
n % 2 == 0 || error("`n` must be even")
h = (b - a) / n
s = f(a) + f(b)
s += 4*sum(f(a .+ collect(1:2:n) .* h))
s += 2*sum(f(a .+ collect(2:2:n-1) .* h))
return h/3 * s
end
For "simple" functions, like e^(-x^2)
, the simpson
function works.
Input: simpson(x -> simpson(x -> exp.(-x.^2), 0, 5, 100)
Output: 0.8862269254513949
However, for the more complicated function f(x)
gArgs(x) = (30 .+ x, 0)
f(x) = exp.(-x.^2) .* maximum(generator.(gArgs.(x)...)[1])
where generator(θ, plotsol)
is a function that takes in a defect θ in percent and a boolean value plotsol
(either 0 or 1) that determines whether the generator should be plotted, and returns a vector with the magnetization in certain points in the generator.
When I try to compute the integral by running the below code
gArgs(x) = (30 .+ x, 0)
f(x) = exp.(-x.^2) .* maximum(generator.(gArgs.(x)...)[1])
println(simpson(x -> f(x), 0, 5, 10))
I encounter the error MethodError: no method matching generator(::Float64)
. With slight variants of the expression for f(x)
I run into different errors like DimensionMismatch("array could not be broadcast to match destination")
and InexactError: Bool(33.75)
. In the end, I think the cause of the error boils down to that I cannot figure out how to properly enter an expression for the integrand f(x)
. Could someone help me figure out how to enter f(x)
correctly? Let me know if anything is unclear in my question.
Given an array x
, gArgs.(x)
returns an array of Tuple
s and you are trying to broadcast over an array of tuples. But the behavior of broadcasting with tuples is a bit different. Tuples are not treated as a single element and they themselves broadcast.
julia> println.(gArgs.([0.5, 1.5, 2.5, 3.5, 4.5])...)
30.531.532.533.534.5
00000
This is not what you expected, is it?
You can also see the problem with the following example;
julia> (2, 5) .!= [(2, 5)]
2-element BitArray{1}:
true
true
I believe f
is a function that actually takes a scalar and returns a scalar. Instead of making f
work on arrays, you should leave the broadcasting to the caller. You are very likely to be better of implementing f
element-wise. This is the more Julia way of doing things and will make your job much easier.
That said, I believe your implementation should work with the following modifications, if you do not have an error in generator
.
function simpson(f::Function, a::Number, b::Number, n::Number)
n % 2 == 0 || error("`n` must be even")
h = (b - a) / n
s = f(a) + f(b)
s += 4*sum(f.(a .+ collect(1:2:n) .* h)) # broadcast `f`
s += 2*sum(f.(a .+ collect(2:2:n-1) .* h)) # broadcast `f`
return h/3 * s
end
# define `gArg` and `f` element-wise and `generator`, too.
gArgs(x) = (30 + x, 0) # get rid of broadcasting dot. Shouldn't `0` be `false`?
f(x) = exp(-x^2) * maximum(generator(gArgs(x)...)[1]) # get rid of broadcasting dots
println(simpson(f, 0, 5, 10)) # you can just write `f`
You should also define the generator
function element-wise.