removed Plots and UMAP, removed Manifest (#11)

mkarikom · web-flow · commit a8935417d36d · 2020-05-30T18:53:23.000-07:00
diff --git a/.gitignore b/.gitignore
@@ -1 +1,3 @@
 .DS_Store
+*.jld
+Manifest.toml
diff --git a/Manifest.toml b/Manifest.toml
diff --git a/Project.toml b/Project.toml
@@ -6,10 +6,8 @@ version = "0.1.0"
 [deps]
 Clustering = "aaaa29a8-35af-508c-8bc3-b662a17a0fe5"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
-UMAP = "c4f8c510-2410-5be4-91d7-4fbaeb39457e"
 
 [compat]
 julia = "1.3"
diff --git a/examples/LDA.jl b/examples/LDA.jl
@@ -1,4 +1,4 @@
-using TopicModels, Plots, UMAP
+using TopicModels
 
 ##################################################################################################################################
 # Fit and Visualize Real-World Text Data
@@ -17,9 +17,10 @@ state = State(model,corpus)
 topWords = topTopicWords(model, state, 10)
 
 # visualize the fit
-@time embedding = umap(state.topics, 2, n_neighbors=10)
-maxlabels = vec(map(i->i[1], findmax(state.topics,dims=1)[2]))
-scatter(embedding[1,:], embedding[2,:], zcolor=maxlabels, title="UMAP: Max-Likelihood Doc Topics on Learned", marker=(2, 2, :auto, stroke(0)))
+# using Plots, UMAP
+# @time embedding = umap(state.topics, 2, n_neighbors=10)
+# maxlabels = vec(map(i->i[1], findmax(state.topics,dims=1)[2]))
+# scatter(embedding[1,:], embedding[2,:], zcolor=maxlabels, title="UMAP: Max-Likelihood Doc Topics on Learned", marker=(2, 2, :auto, stroke(0)))
 
 ##################################################################################################################################
 # Fit, Validate, and Visualize Synthetic Data Derived from a Fully-Generative Simulation (Poisson-distributed document-length)
@@ -34,13 +35,8 @@ testCorpus = LdaCorpus(k, lexLength, corpLambda, corpLength, scaleK, scaleL)
 
 testModel = Model(testCorpus.alpha, testCorpus.beta, testCorpus)
 testState = State(testModel, testCorpus)
-@time trainModel(testModel, testState, 100)
+    @time trainModel(testModel, testState, 100)
 
 # compute validation metrics on a single fit
 CorpusARI(testState,testModel,testCorpus) # ARI for max. likelihood. document topics
 DocsARI(testState,testCorpus) # ARI for actual word topics
-
-# visualize the fit
-@time embedding = umap(testState.topics, 2;n_neighbors=10)
-maxlabels = vec(map(i->i[1], findmax(CorpusTopics(testCorpus),dims=1)[2]))
-scatter(embedding[1,:], embedding[2,:], zcolor=maxlabels, title="UMAP: True on Learned", marker=(2, 2, :auto, stroke(0)))
diff --git a/src/TopicModels.jl b/src/TopicModels.jl
@@ -3,7 +3,7 @@ module TopicModels
 #Imports
 import Base.length
 
-using Random, Distributions, Plots, UMAP
+using Random, Distributions
 using SpecialFunctions: loggamma
 using Clustering: randindex
 
@@ -29,4 +29,4 @@ include("Computation.jl")
 
 #Stuff like perplexity and ARI:
 include("Validation.jl")
-end #module
+end #module
diff --git a/test/runtests.jl b/test/runtests.jl
@@ -0,0 +1,5 @@
+using Test
+
+@testset "Inference" begin
+    include("Gibbs_unit_tests.jl")
+end

Original file line number	Diff line number	Diff line change
`@@ -1 +1,3 @@`
`1`	`1`	`.DS_Store`
	`2`	`+*.jld`
	`3`	`+Manifest.toml`