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Set max distance to one when it's zero #65

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Merged
andreasnoack merged 1 commit into from
Apr 19, 2023
Merged

Set max distance to one when it's zero #65

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4 changes: 1 addition & 3 deletions src/Loess.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -50,9 +50,6 @@ function loess(

n, m = size(xs)
q = floor(Int, span * n)
if q < degree + 1
throw(ArgumentError("neighborhood size must be larger than degree+1=$(degree + 1) but was $q. Try increasing the value of span."))
end

# TODO: We need to keep track of how we are normalizing so we can
# correctly apply predict to unnormalized data. We should have a normalize
Expand Down Expand Up @@ -90,6 +87,7 @@ function loess(
# find the q closest points
partialsort!(perm, 1:q, by=i -> ds[i])
dmax = maximum([ds[perm[i]] for i = 1:q])
dmax = iszero(dmax) ? one(dmax) : dmax

for i in 1:q
pᵢ = perm[i]
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14 changes: 7 additions & 7 deletions test/runtests.jl
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Expand Up @@ -44,18 +44,18 @@ end
@testset "Example 1" begin
x = [1.0, 2.0, 3.0, 4.0]
y = [1.0, 2.0, 3.0, 4.0]
@test_throws ArgumentError("neighborhood size must be larger than degree+1=3 but was 1. Try increasing the value of span.") loess(x, y, span = 0.25)
@test_throws ArgumentError("neighborhood size must be larger than degree+1=3 but was 1. Try increasing the value of span.") loess(x, y, span = 0.33)
@test predict(loess(x, y), x) ≈ x
@test predict(loess(x, y, span = 0.25), x) ≈ y
@test predict(loess(x, y, span = 0.33), x) ≈ y
@test predict(loess(x, y), x) ≈ y
end

@testset "Example 2" begin
x = [1.0, 1.0, 2.0, 3.0, 4.0, 4.0]
y = [1.0, 1.0, 2.0, 3.0, 4.0, 4.0]
@test_throws ArgumentError("neighborhood size must be larger than degree+1=3 but was 1. Try increasing the value of span.") loess(x, y, span = 0.33)
@test_throws ArgumentError("neighborhood size must be larger than degree+1=3 but was 2. Try increasing the value of span.") predict(loess(x, y, span = 0.4), x) ≈ x
@test predict(loess(x, y, span = 0.5), x) ≈ x
@test predict(loess(x, y, span = 0.6), x) ≈ x
@test predict(loess(x, y, span = 0.33), x) ≈ y
@test predict(loess(x, y, span = 0.4), x) ≈ y
@test predict(loess(x, y, span = 0.5), x) ≈ y
@test predict(loess(x, y, span = 0.6), x) ≈ y
end
end

Expand Down