diff --git a/src/SOM.jl b/src/SOM.jl
index 2b738b6..20029a3 100644
--- a/src/SOM.jl
+++ b/src/SOM.jl
@@ -15,6 +15,7 @@ using Distances
 using ProgressMeter
 using StatsBase
 using Distributions
+using NearestNeighbors
 #using TensorToolbox
 using LinearAlgebra
 # if VERSION < v"0.7.0-DEV.5183"
diff --git a/src/helpers.jl b/src/helpers.jl
index 8e365eb..c954950 100644
--- a/src/helpers.jl
+++ b/src/helpers.jl
@@ -90,6 +90,14 @@ function findWinner(cod, sampl)
     return winner
 end
 
+function findWinner(kd_tree::KDTree, sampl)
+    idxs, _ = knn(kd_tree, sampl, 1)
+    idxs[1]
+end
+
+function buildKDTree(codes)
+    permutedims(codes,(2,1)) |> KDTree
+end
 
 """
     normTrainData(x, normParams)
diff --git a/src/soms.jl b/src/soms.jl
index 24acd65..fd4bb0b 100644
--- a/src/soms.jl
+++ b/src/soms.jl
@@ -76,16 +76,21 @@ end
 Return the index of the winner neuron for each training pattern
 in x (row-wise).
 """
-function visual(codes, x)
+
+function visualGeneric(codes, x)
 
     vis = zeros(Int, nrow(x))
-    for i in 1:nrow(x)
+    @time for i in 1:nrow(x)
         vis[i] = findWinner(codes, [x[i, col] for col in 1:size(x, 2)])
     end
 
     return(vis)
 end
 
+function visual(codes, x)
+    kd_tree = buildKDTree(codes)
+    visualGeneric(kd_tree, x)
+end
 
 """
     makePopulation(nCodes, vis)
diff --git a/test/testFuns.jl b/test/testFuns.jl
index be94ed1..5741784 100644
--- a/test/testFuns.jl
+++ b/test/testFuns.jl
@@ -16,7 +16,6 @@ end
 
 
 
-
 function testVisual(train, topol)
 
     xdim = 8
@@ -38,6 +37,49 @@ function testVisual(train, topol)
 end
 
 
+function testVisualGeneric()
+
+    nonce = (function()
+        count = 0.0
+        function()
+            count += 1
+        end
+    end)()
+
+    for i in 1:10
+
+        # tests on random data
+        dimensions = rand(1:10)
+        ncodes = rand(1:10)
+        nrows = rand(1:10)
+        codes = rand(ncodes,dimensions)
+        samples = rand(nrows,dimensions)
+
+        if visual(codes,samples) != visualGeneric(codes,samples)
+            return false
+        end
+
+        # tests on sequenced data
+        dimensions = i
+        ncodes = i
+        nrows = i
+        codes = zeros(ncodes,dimensions)
+        codes = map(_->(nonce()),codes)
+        samples = zeros(nrows,dimensions)
+        samples = map(_->(nonce()),samples)
+
+        if visual(codes,samples) != visualGeneric(codes,samples)
+            return false
+        end
+
+    end
+
+    return true
+
+end
+
+
+
 function testFreqs(train, wClasses, classes)
 
     xdim = 8