replace @Assert macro with throw(ErrorException(...))

Author: jbytecode

CHANGELOG.md

@@ -2,10 +2,8 @@
 
 - More explicit return types, drop `Dict` with `Dict{String, Any}` or `Dict{String, Vector}`
 - Add `Julia v.1.10` to GitHub actions
-- Reduce memory allocations in `lts()` and `lms()`
-- Reduce memory allocations in `hadi92()` and `hadi94()`
-- Reduce memory allocations in `hs93()`
-- Reduce memory allocations in `robcov()`
+- Initial attempt to reduce memory allocations in `lts()`, `lms()`, `hadi92()`, `hadi94()`, `hs93()`, `robcov()`
+- Replace `@assert` macro with `throw(ErrorException())` in whole code
 
 # v0.11.3 
 

src/asm2000.jl

@@ -78,7 +78,9 @@ function asm2000(X::AbstractMatrix{Float64}, y::AbstractVector{Float64})::Dict
     covmatrix = cov(pairs[hsubset, :])
     mahdist = mahalanobisSquaredBetweenPairs(pairs, covmatrix = covmatrix)
 
-    @assert !isnothing(mahdist)
+    if isnothing(mahdist)
+        throw(ErrorException("Mahalanobis distances are not calculated"))
+    end 
 
     outlierset = Array{Int,1}(undef, 0)
 

src/bacon.jl

@@ -31,7 +31,11 @@ function initial_basic_subset_multivariate_data(
     n, _ = size(X)
     if method == "mahalanobis"
         msm = mahalanobisSquaredMatrix(X)
-        @assert !isnothing(msm)
+        
+        if isnothing(msm)
+            throw(ErrorException("Mahalanobis distances are not calculated"))
+        end
+
         distances = sqrt.(diag(msm))
     elseif method == "median"
         median_vector = applyColumns(median, X)
@@ -113,7 +117,9 @@ function bacon_multivariate_outlier_detection(
 
         msm = mahalanobisSquaredMatrix(X, meanvector = mean_basic_subset, covmatrix = cov_basic_subset)
 
-        @assert !isnothing(msm)
+        if isnothing(msm)
+            throw(ErrorException("Mahalanobis distances are not calculated"))
+        end
 
         distances = sqrt.(diag(msm))
         c_hr = (h - r) / (h + r)

src/bch.jl

@@ -105,7 +105,10 @@ function bch(
     A = ((X .- coordmeds')' * (X .- coordmeds')) / (n - 1.0)
 
     msm = mahalanobisSquaredMatrix(X, meanvector = coordmeds, covmatrix = A)
-    @assert !isnothing(msm)
+    
+    if isnothing(msm)
+        throw(ErrorException("Mahalanobis distances are not calculated"))
+    end
 
     dsquared = diag(msm)
     d = sqrt.(dsquared)
@@ -116,7 +119,11 @@ function bch(
     covmatofh = cov(X[bestindicesofd, :])
 
     msm2 = mahalanobisSquaredMatrix(X, meanvector = colmeansofh, covmatrix = covmatofh)
-    @assert !isnothing(msm2)
+
+
+    if isnothing(msm2)
+            throw(ErrorException("Mahalanobis distances are not calculated"))
+        end
 
     newdsquared = diag(msm2)
 
@@ -150,7 +157,11 @@ function bch(
         covmatofbasicsubset = cov(X[basicsubsetindices, :])
 
         msm4 = mahalanobisSquaredMatrix(X, meanvector = colmeanofbasicsubset, covmatrix = covmatofbasicsubset)
-        @assert !isnothing(msm4)
+
+        if isnothing(msm4)
+            throw(ErrorException("Mahalanobis distances are not calculated"))
+        end
+        
         newdsquared = diag(msm4)
         newd = sqrt.(newdsquared)
         sortednewdsquared = sort(newdsquared)

src/dataimage.jl

@@ -49,15 +49,24 @@ function dataimage(
 )::Matrix{RGBX{Float64}}
     d = nothing
     if distance == :mahalanobis
+        
         d = mahalanobisSquaredBetweenPairs(dataMatrix)
-        @assert !isnothing(d)
+
+        if isnothing(d)
+            throw(ErrorException("Mahalanobis distances are not calculated"))
+        end
+
     elseif distance == :euclidean
         d = euclideanDistances(dataMatrix)
     else
         @error "Distance function unknown: " distance
         @error "Using mahalanobis instead"
         d = mahalanobisSquaredBetweenPairs(dataMatrix)
-        @assert !isnothing(d)
+
+        if isnothing(d)
+            throw(ErrorException("Mahalanobis distances are not calculated"))
+        end
+        
     end
     colours = 1.0 .- d / maximum(d)
     n, _ = size(d)

src/hadi1992.jl

@@ -87,7 +87,10 @@ function hadi1992(multivariateData::AbstractMatrix{Float64}; alpha = 0.05)
     Sm = (1.0 / (n - 1.0)) * (multivariateData .- meds')' * (multivariateData .- meds')
 
     msm1 = mahalanobisSquaredMatrix(multivariateData, meanvector = meds, covmatrix = Sm)
-    @assert !isnothing(msm1)
+
+    if isnothing(msm1)
+            throw(ErrorException("Mahalanobis distances are not calculated"))
+        end
 
     mah0 = diag(msm1)
 
@@ -99,7 +102,10 @@ function hadi1992(multivariateData::AbstractMatrix{Float64}; alpha = 0.05)
     Sv = (1.0 / (h - 1.0)) * (starting_data .- Cv')' * (starting_data .- Cv')
 
     msm2 = mahalanobisSquaredMatrix(multivariateData, meanvector = Cv, covmatrix = Sv)
-    @assert !isnothing(msm2)
+    
+    if isnothing(msm2)
+        throw(ErrorException("Mahalanobis distances are not calculated"))
+    end
 
     mah1 = diag(msm2)
     ordering_indices_mah1 = sortperm(mah1)
@@ -130,15 +136,22 @@ function hadi1992(multivariateData::AbstractMatrix{Float64}; alpha = 0.05)
             newSb .= hadi1992_handle_singularity(cfactor * Sb)
 
             msm3 .= mahalanobisSquaredMatrix(multivariateData, meanvector = Cb, covmatrix = newSb,)
-            @assert !isnothing(msm3)
+
+            if isnothing(msm3)
+                throw(ErrorException("Mahalanobis distances are not calculated"))
+            end
 
             mah1 .= diag(msm3)
 
             ordering_indices_mah1 = sortperm(mah1)
             basic_subset_indices = ordering_indices_mah1[1:r]
         else
             msm4 .= mahalanobisSquaredMatrix(multivariateData, meanvector = Cb, covmatrix = (cfactor * Sb))
-            @assert !isnothing(msm4)
+
+            if isnothing(msm4)
+                throw(ErrorException("Mahalanobis distances are not calculated"))
+            end
+            
             mah1 .= diag(msm4)
             ordering_indices_mah1 = sortperm(mah1)
             basic_subset_indices = ordering_indices_mah1[1:r]

src/hadi1994.jl

@@ -60,7 +60,10 @@ function hadi1994(multivariateData::AbstractMatrix{Float64}; alpha = 0.05)
     Sm = (1.0 / (n - 1.0)) * (multivariateData .- meds')' * (multivariateData .- meds')
 
     msm1 = mahalanobisSquaredMatrix(multivariateData, meanvector = meds, covmatrix = Sm)
-    @assert !isnothing(msm1)
+
+    if isnothing(msm1)
+            throw(ErrorException("Mahalanobis distances are not calculated"))
+        end
 
     mah0 = diag(msm1)
 
@@ -71,7 +74,11 @@ function hadi1994(multivariateData::AbstractMatrix{Float64}; alpha = 0.05)
     Cv = coordinatwisemedians(starting_data)
     Sv = (1.0 / (h - 1.0)) * (starting_data .- Cv')' * (starting_data .- Cv')
     msm2 = mahalanobisSquaredMatrix(multivariateData, meanvector = Cv, covmatrix = Sv)
-    @assert !isnothing(msm2)
+
+    if isnothing(msm2)
+        throw(ErrorException("Mahalanobis distances are not calculated"))
+    end
+    
     mah1 = diag(msm2)
     ordering_indices_mah1 = sortperm(mah1)
 
@@ -116,7 +123,9 @@ function hadi1994(multivariateData::AbstractMatrix{Float64}; alpha = 0.05)
             covmatrix = (cfactor * Sb),
         )
 
-        @assert !isnothing(msm3)
+        if isnothing(msm3)
+            throw(ErrorException("Mahalanobis distances are not calculated"))
+        end
 
         mah1 = diag(msm3)