Minor fix in Quantile transform

JuliaML · Sep 16, 2024 · 5b387cf · 5b387cf
1 parent 56917f6
commit 5b387cf
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Showing 2 changed files with 5 additions and 6 deletions.
diff --git a/src/distributions.jl b/src/distributions.jl
@@ -20,7 +20,7 @@ EmpiricalDistribution(values) = EmpiricalDistribution{eltype(values)}(values)
 
 quantile(d::EmpiricalDistribution, p::Real) = quantile(d.values, p, sorted=true)
 
-function cdf(d::EmpiricalDistribution{T}, x::T) where {T}
+function cdf(d::EmpiricalDistribution, x)
   v = d.values
   n = length(v)
 
@@ -37,9 +37,9 @@ function cdf(d::EmpiricalDistribution{T}, x::T) where {T}
   l, u = v[head], v[tail]
 
   if x < l
-    return T(0)
+    return 0.0
   elseif x > u
-    return T(1)
+    return 1.0
   else
     if l == u
       return tail / n

diff --git a/src/transforms/quantile.jl b/src/transforms/quantile.jl
@@ -66,9 +66,8 @@ end
 # transform samples from original to target distribution
 function qtransform(samples, origin, target)
   # avoid evaluating the quantile at 0 or 1
-  T = eltype(samples)
-  pmin = T(0) + T(1e-3)
-  pmax = T(1) - T(1e-3)
+  pmin = 0.0 + 1e-3
+  pmax = 1.0 - 1e-3
   map(samples) do sample
     prob = cdf(origin, sample)
     quantile(target, clamp(prob, pmin, pmax))