local pls regression for nanoparticles

2 files changed, 14 insertions, 36 deletions

diff --git a/test/nanoparticles.rb b/test/nanoparticles.rb
index a2c77b5..b6a2f00 100644
--- a/test/nanoparticles.rb
+++ b/test/nanoparticles.rb
@@ -5,6 +5,7 @@ class NanoparticleTest  < MiniTest::Test
   include OpenTox::Validation
 
   def setup
+    # TODO: multiple runs create duplicates
     #Import::Enanomapper.import File.join(File.dirname(__FILE__),"data","enm")
   end
 
@@ -35,39 +36,13 @@ class NanoparticleTest  < MiniTest::Test
 
   # TODO move to validation-statistics
   def test_inspect_cv
-    skip
     cv = CrossValidation.all.sort_by{|cv| cv.created_at}.last
     cv.correlation_plot_id = nil
     File.open("tmp.pdf","w+"){|f| f.puts cv.correlation_plot}
-    #p cv
-=begin
-    #File.open("tmp.pdf","w+"){|f| f.puts cv.correlation_plot}
-    cv.predictions.sort_by{|sid,p| -(p["value"] - p["measurements"].median).abs}[0,5].each do |sid,p|
-      s = Substance.find(sid)
-      puts
-      p s.name
-      p([p["value"],p["measurements"],(p["value"]-p["measured"].median).abs])
-      neighbors = s.physchem_neighbors dataset_id: cv.model.training_dataset_id, prediction_feature_id: cv.model.prediction_feature_id, type: nil
-      neighbors.each do |n|
-        neighbor = Substance.find(n["_id"])
-        p "=="
-        p neighbor.name, n["similarity"], n["measurements"]
-        p neighbor.core["name"]
-        p neighbor.coating.collect{|c| c["name"]}
-        n["common_descriptors"].each do |id|
-          f = Feature.find(id)
-          print "#{f.name} #{f.conditions["MEDIUM"]}"
-          print ", "
-        end
-        puts
-      end
-
-    end
-=end
+    p cv.statistics
   end
   def test_inspect_worst_prediction
-    skip
-# TODO check/fix single/double neighbor prediction
+  
     cv = CrossValidation.all.sort_by{|cv| cv.created_at}.last
     worst_predictions = cv.worst_predictions(n: 3,show_neigbors: false)
     assert_equal 3, worst_predictions.size
@@ -100,15 +75,18 @@ class NanoparticleTest  < MiniTest::Test
     refute_nil cv.r_squared
     refute_nil cv.rmse
   end
-
   def test_validate_pls_model
-    skip
     training_dataset = Dataset.find_or_create_by(:name => "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles")
-    feature = Feature.find_or_create_by(name: "Net cell association", category: "TOX", unit: "mL/ug(Mg)")
-    model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression", :neighbor_algorithm => "physchem_neighbors"})
-    cv = Validation::RegressionCrossValidation.create model
+    #feature = Feature.find_or_create_by(name: "Net cell association", category: "TOX", unit: "mL/ug(Mg)")
+    feature = Feature.find_or_create_by(name: "Log2 transformed", category: "TOX")
+    
+    model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression", :neighbor_algorithm => "physchem_neighbors", :neighbor_algorithm_parameters => {:min_sim => 0.5}})
+    cv = RegressionCrossValidation.create model
     p cv
-    File.open("tmp.png","w+"){|f| f.puts cv.correlation_plot}
+    #p cv.predictions.sort_by{|sid,p| (p["value"] - p["measurements"].median).abs}
+    p cv.rmse
+    p cv.r_squared
+    File.open("tmp.pdf","w+"){|f| f.puts cv.correlation_plot}
     refute_nil cv.r_squared
     refute_nil cv.rmse
   end
diff --git a/test/setup.rb b/test/setup.rb
index e7c32b4..6c97282 100644
--- a/test/setup.rb
+++ b/test/setup.rb
@@ -5,5 +5,5 @@ require_relative '../lib/lazar.rb'
 include OpenTox
 TEST_DIR ||= File.expand_path(File.dirname(__FILE__))
 DATA_DIR ||= File.join(TEST_DIR,"data")
-$mongo.database.drop
-$gridfs = $mongo.database.fs
+#$mongo.database.drop
+#$gridfs = $mongo.database.fs