Need to import from submodules before doing top-level convenience export, also other minor fixes

Project.toml

@@ -1,7 +1,7 @@
 name = "ChemistryFeaturization"
 uuid = "6c925690-434a-421d-aea7-51398c5b007a"
 authors = ["Rachel Kurchin <[email protected]>", "Sean Sun"]
-version = "0.3.0"
+version = "0.3.1"
 
 [deps]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"

src/ChemistryFeaturization.jl

@@ -2,6 +2,9 @@ module ChemistryFeaturization
 
 using SimpleWeightedGraphs
 
+encodable_elements(a::Any) = throw(MethodError(encodable_elements, a))
+decode(a::Any, encoded_features) = throw(MethodError(decode, a))
+
 include("utils/Utils.jl")
 export Utils
 
@@ -11,20 +14,20 @@ export AbstractType
 include("codecs/codecs.jl")
 export Codec
 
-encodable_elements(a::Any) = throw(MethodError(encodable_elements, a))
-decode(a::Any, encoded_features) = throw(MethodError(decode, a))
-
 include("features/features.jl")
 export FeatureDescriptor
+using .FeatureDescriptor: ElementFeatureDescriptor
 export ElementFeatureDescriptor
 
 include("atoms/atoms.jl")
 export Atoms
+using .Atoms: AtomGraph
 export AtomGraph
 
 include("featurizations/featurizations.jl")
 export Featurization
-export GraphNodeFeaturization
+using .Featurization: GraphNodeFeaturization, featurize!
+export GraphNodeFeaturization, featurize!
 
 export encodable_elements, decode
 

src/atoms/atomgraph.jl

@@ -62,16 +62,18 @@ function AtomGraph(
     num_atoms = size(graph)[1]
     @assert length(elements) == num_atoms "Element list length doesn't match graph size!"
 
-    # check that features is the right dimensions (# features x # nodes)
-    expected_feature_length = sum(f.num_bins for f in featurization)
-    @assert size(features) == (expected_feature_length, num_atoms) "Feature matrix is of wrong dimension! It should be of size (# features, # nodes)"
+    # TO CONSIDER: add `validate_features` function or something like that for when this constructor is used
+    # that we can then dispatch on different featurization types. Alternatively, remove this constructor?
+
+    # check that features is the right dimensions (# features x # nodes) -> commented out because doesn't work with generic fzn
+    # expected_feature_length = sum(f.num_bins for f in featurization)
+    # @assert size(features) == (expected_feature_length, num_atoms) "Feature matrix is of wrong dimension! It should be of size (# features, # nodes)"
 
     # if all these are good, calculate laplacian and build the thing
     laplacian = normalized_laplacian(graph)
     AtomGraph(graph, elements, laplacian, features, featurization, id)
 end
 
-
 # one without features or featurization initialized yet
 function AtomGraph(
     graph::SimpleWeightedGraph{A,B},

src/featurizations/graphnodefeaturization.jl

@@ -34,7 +34,7 @@ end
 function GraphNodeFeaturization(
     feature_names::Vector{String},
     lookup_table::Union{DataFrame,Nothing} = nothing;
-    nbins::Union{Vector{Integer},Integer,Nothing} = nothing,
+    nbins::Union{Vector{<:Integer},Integer,Nothing} = nothing,
     logspaced::Union{Vector{Bool},Bool,Nothing} = nothing,
     categorical::Union{Vector{Bool},Bool,Nothing} = nothing,
 )

test/featurizations/GraphNodeFeaturization_tests.jl

@@ -28,9 +28,15 @@ using ChemistryFeaturization.Featurization
         featurize!(F2, fzn3)
         decoded_matrix = decode(fzn3, F2.encoded_features)
         decoded_ag = decode(F2)
+        enc1 = F2.encoded_features
         @test all(
             map(d -> d[1]["Block"] == d[2]["Block"] == "p", [decoded_matrix, decoded_ag]),
         )
+
+        fzn4 = GraphNodeFeaturization(fnames, nbins = [2, 4, 2])
+        F2 = AtomGraph(Float32.([0 1; 1 0]), ["F", "F"])
+        featurize!(F2, fzn4)
+        @test all(F2.encoded_features .== enc1)
     end
 
     # encodable_elements

test/utils/ElementFeatureUtils_tests.jl

@@ -11,12 +11,6 @@ using ChemistryFeaturization.Utils.ElementFeatureUtils
     @test fea_minmax("Group") == [1, 18]
     @test fea_minmax("MeaningOfLife", df) == [-1, 42]
 
-    # default_log
-    @test default_log("Block") == false # not numbers
-    @test default_log("MeaningOfLife", df) == false # values span 0
-    @test default_log("Valence") == false # extremal value 0
-    @test default_log("Atomic mass") == true
-    @test default_log("Atomic mass", threshold = 3) == false
     # default_log
     @test default_log("Block") == false # not numbers
     @test default_log("MeaningOfLife", df) == false # values span 0