Add histvar, fix histstd

Project.toml

@@ -1,7 +1,7 @@
 name = "NaNStatistics"
 uuid = "b946abbf-3ea7-4610-9019-9858bfdeaf2d"
 authors = ["C. Brenhin Keller"]
-version = "0.6.37"
+version = "0.6.38"
 
 [deps]
 PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"

src/Histograms.jl

@@ -35,6 +35,7 @@ function histcounts(x, xedges::AbstractRange; T=Int64)
 end
 histcounts(x, xmin::Number, xmax::Number, nbins::Integer; T=Int64) = histcounts(x, range(xmin, xmax, length=nbins+1); T=T)
 
+
 """
 ```julia
 histmean(counts, bincenters)
@@ -67,9 +68,10 @@ function histmean(counts, bincenters)
 end
 export histmean
 
+
 """
 ```julia
-histstd(counts, bincenters; corrected::Bool=true)
+histvar(counts, bincenters; corrected::Bool=true)
 ```
 Estimate the standard deviation of the data represented by a histogram, 
 specified as `counts` in equally spaced bins centered at `bincenters`.
@@ -88,11 +90,11 @@ julia> counts = histcounts(randn(10000), binedges);
 julia> bincenters = (binedges[1:end-1] + binedges[2:end])/2
 -9.995:0.01:9.995
 t
-julia> histstd(counts, bincenters)
+julia> histvar(counts, bincenters)
 0.9991854064196424
 ```
 """
-function histstd(counts, bincenters; corrected::Bool=true)
+function histvar(counts, bincenters; corrected::Bool=true)
     N = ∅ₙ = zero(eltype(counts))
     Σ = ∅ = zero(Base.promote_op(*, eltype(counts), eltype(bincenters)))
     @inbounds @simd ivdep for i in eachindex(counts, bincenters)
@@ -109,6 +111,35 @@ function histstd(counts, bincenters; corrected::Bool=true)
     end
     return Σ / max(N-corrected, ∅ₙ)
 end
+export histvar
+
+
+"""
+```julia
+histstd(counts, bincenters; corrected::Bool=true)
+```
+Estimate the standard deviation of the data represented by a histogram, 
+specified as `counts` in equally spaced bins centered at `bincenters`.
+
+If `counts` have been normalized, or represent an analytical estimate of a PDF 
+rather than a histogram representing counts of a dataset, Bessel's correction 
+to the standard deviation should likely not be performed - i.e., set the 
+`corrected` keyword argument to `false`. 
+
+## Examples
+```julia
+julia> binedges = -10:0.01:10;
+
+julia> counts = histcounts(randn(10000), binedges);
+
+julia> bincenters = (binedges[1:end-1] + binedges[2:end])/2
+-9.995:0.01:9.995
+t
+julia> histstd(counts, bincenters)
+0.999592620230683
+```
+"""
+histstd(counts, bincenters; corrected::Bool=true) = sqrt(histvar(counts, bincenters; corrected))
 export histstd
 
 

test/testHistograms.jl

@@ -36,15 +36,23 @@
 
 ## --- Statistics on histograms
 
-    a = randn(10000)
+    a = randn(10000) * 1.2
     binedges = -10:0.1:10
     bincenters = (binedges[1:end-1] + binedges[2:end])/2
     h = histcounts(a, binedges)
-    @test histmean(h, bincenters) ≈ nanmean(a) atol = 0.1
-    @test histstd(h, bincenters) ≈ nanstd(a) atol = 0.1
+    @test histmean(h, bincenters) ≈ nanmean(a) atol = 0.02
+    @test histvar(h, bincenters) ≈ nanvar(a) atol = 0.02
+    @test histstd(h, bincenters) ≈ nanstd(a) atol = 0.02
 
     n = pdf.(Normal(0,1), bincenters)
     @test histmean(n, bincenters) ≈ 0 atol = 1e-6
     @test histstd(n, bincenters, corrected=false) ≈ 1 atol = 1e-6
 
+    binedges = -20:0.1:20
+    bincenters = (binedges[1:end-1] + binedges[2:end])/2
+    n = pdf.(Normal(1,2), bincenters)
+    @test histmean(n, bincenters) ≈ 1 atol = 1e-6
+    @test histvar(n, bincenters, corrected=false) ≈ 4 atol = 1e-3
+    @test histstd(n, bincenters, corrected=false) ≈ 2 atol = 2e-6
+
 ## --- End of File