Fix skipped version, clean up tests

AP6YC · Aug 12, 2021 · 692d59f · 692d59f · AP6YC · Aug 12, 2021
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commit 692d59f
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Showing 6 changed files with 18 additions and 25 deletions.
diff --git a/Project.toml b/Project.toml
@@ -2,7 +2,7 @@ name = "AdaptiveResonance"
 uuid = "3d72adc0-63d3-4141-bf9b-84450dd0395b"
 authors = ["Sasha Petrenko"]
 description = "A Julia package for Adaptive Resonance Theory (ART) algorithms."
-version = "0.3.5"
+version = "0.3.4"
 
 [deps]
 Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"

diff --git a/test/modules.jl b/test/modules.jl
@@ -3,13 +3,13 @@
     fam = FAM()
     dam = DAM()
     sfam = SFAM()
+    dvfa = DVFA()
     ddvfa = DDVFA()
 
     # Specify constructors
-    fam_opts = opts_FAM()
-    dam_opts = opts_DAM()
-    sfam_opts = opts_SFAM()
-    fam_2 = FAM(fam_opts)
-    dam_2 = DAM(dam_opts)
-    sfam_2 = SFAM(sfam_opts)
-end # @testset "Modules"
+    fam_2 = FAM(opts_FAM())
+    dam_2 = DAM(opts_DAM())
+    sfam_2 = SFAM(opts_SFAM())
+    dvfa_2 = DVFA(opts_DVFA())
+    ddvfa_2 = DDVFA(opts_DDVFA())
+end # @testset "Modules"
diff --git a/test/test_artscene.jl b/test/test_artscene.jl
@@ -23,6 +23,9 @@ Runs the artscene user-level functions on a random image.
 
     # Process the image through the filters
     O, C = artscene_filter(raw_image)
+
+    # Set the logging level back to Info
+    LogLevel(Logging.Info)
 end # @testset "ARTSCENE Filter Porcelain"
 
 # Close the workers after testing

diff --git a/test/test_ddvfa.jl b/test/test_ddvfa.jl
@@ -22,9 +22,6 @@ end # tt_ddvfa(opts::opts_DDVFA, train_x::Array)
 @testset "DDVFA Sequential" begin
     @info "------- DDVFA Sequential -------"
 
-    # Load the data and test across all supervised modules
-    # data = load_iris("../data/Iris.csv")
-
     # Initialize the ART module
     art = DDVFA()
     # Turn off display for sequential training/testing
@@ -69,9 +66,6 @@ end
 @testset "DDVFA Supervised" begin
     @info "------- DDVFA Supervised -------"
 
-    # Load the data and test across all supervised modules
-    # data = load_iris("../data/Iris.csv")
-
     # Train and classify
     art = DDVFA()
     y_hat_train = train!(art, data.train_x, y=data.train_y)
@@ -114,18 +108,15 @@ end
     no_disp_art = tt_ddvfa(no_disp_opts, train_x)
     @info "DDVFA Testing: No Display Complete"
 
+    # Test that the resulting weights are equivalent
     @test default_art.W == no_disp_art.W
-    # # View the profile as a flamegraph
-    # ProfileVega.view()
 end # @testset "DDVFA"
 
 @testset "GNFA" begin
     @info "------- GNFA Testing -------"
 
     # GNFA train and test
     my_gnfa = GNFA()
-    # data = load_am_data(200, 50)
-    # data = load_iris("../data/Iris.csv")
     local_complement_code = AdaptiveResonance.complement_code(data.train_x)
     train!(my_gnfa, local_complement_code)
 

diff --git a/test/test_sets.jl b/test/test_sets.jl
@@ -2,7 +2,6 @@ using AdaptiveResonance
 using Test
 using Logging
 using DelimitedFiles
-# using Random
 
 # Set the log level
 LogLevel(Logging.Info)
@@ -47,6 +46,12 @@ end # @testset "common.jl"
     @test AdaptiveResonance.DDVFA_METHODS == ddvfa_methods
 end # @testset "constants.jl"
 
+@testset "AdaptiveResonance.jl" begin
+    # Module loading
+    include("modules.jl")
+end # @testset "AdaptiveResonance.jl"
+
+
 @testset "DVFA.jl" begin
     @info "------- DVFA Unsupervised -------"
 
@@ -84,11 +89,6 @@ end
     include("test_ddvfa.jl")
 end # @testset "DDVFA.jl"
 
-@testset "AdaptiveResonance.jl" begin
-    # Module loading
-    include("modules.jl")
-end # @testset "AdaptiveResonance.jl"
-
 @testset "ARTMAP.jl" begin
     # Declare the baseline performance for all modules
     perf_baseline = 0.7

diff --git a/test/test_utils.jl b/test/test_utils.jl
@@ -1,4 +1,3 @@
-# using Random
 using DelimitedFiles
 
 """