stage save for transmission

1 files changed, 106 insertions, 15 deletions

diff --git a/application.rb b/application.rb
index 29c1aca..a702d9a 100644
--- a/application.rb
+++ b/application.rb
@@ -1,9 +1,11 @@
+require 'qsar-report'
 require 'rdiscount'
 $ambit_search = "http://data.enanomapper.net/substance?type=name&search="
 $npo_search = "http://bioportal.bioontology.org/search?q=%s&ontologies=NPO&include_properties=false&include_views=false&includeObsolete=false&require_definition=false&exact_match=false&categories="
 
+
 configure :development do
-  $logger = Logger.new(STDOUT)
+  #$logger = Logger.new(STDOUT)
 end
 
 before do
@@ -13,27 +15,111 @@ end
 get '/?' do
   redirect to('/predict') 
 end
-=begin
-get '/qsar-report/:id' do
+#=begin
+get '/qmrf-report/:id' do
+  prediction_model = OpenTox::Model::NanoPrediction.find(params[:id])
+  if prediction_model
+    model = prediction_model.model
+		model_type = "regression"
+    report = OpenTox::QMRFReport.new
+		if File.directory?("#{File.dirname(__FILE__)}/../../lazar")
+    	lazar_commit = `cd #{File.dirname(__FILE__)}/../../lazar; git rev-parse HEAD`.strip
+    	lazar_commit = "https://github.com/opentox/lazar/tree/#{lazar_commit}"
+  	else
+    	lazar_commit = "https://github.com/opentox/lazar/releases/tag/v#{Gem.loaded_specs["lazar"].version}"
+		end
+    report.value "QSAR_title", "Model for #{prediction_model.species} #{prediction_model.endpoint}"
+    report.change_catalog :software_catalog, :firstsoftware, {:name => "nano-lazar", :description => "nano-lazar toxicity predictions", :number => "1", :url => "https://nano-lazar.in-silico.ch", :contact => "helma@in-silico.ch"}
+    report.ref_catalog :QSAR_software, :software_catalog, :firstsoftware
+    report.value "qmrf_date", "#{Time.now.strftime('%d %B %Y')}"
+    report.change_catalog :authors_catalog, :firstauthor, {:name => "Christoph Helma", :affiliation => "in silico toxicology gmbh", :contact => "Rastatterstrasse 41, CH-4057 Basel, Switzerland", :email => "helma@in-silico.ch", :number => "1", :url => "http://in-silico.ch"}
+    report.ref_catalog :qmrf_authors, :authors_catalog, :firstauthor
+    report.change_catalog :authors_catalog, :modelauthor, {:name => "Christoph Helma", :affiliation => "in silico toxicology gmbh", :contact => "Contact Address", :email => "Contact Email", :number => "1", :url => "Web Page"}
+    report.ref_catalog :model_authors, :authors_catalog, :modelauthor
+    report.value "model_date", "#{Time.parse(model.created_at.to_s).strftime('%Y')}"
+    report.change_catalog :publications_catalog, :publications_catalog_1, {:title => "Rautenberg, Gebele and Helma (2013), Validation of read across predictions for nanoparticle toxicities ", :url => "in preparation"}
+    report.ref_catalog :references, :publications_catalog, :publications_catalog_1
+    report.value "model_species", prediction_model.species
+    report.change_catalog :endpoints_catalog, :endpoints_catalog_1, {:name => prediction_model.endpoint, :group => ""}
+    report.ref_catalog :model_endpoint, :endpoints_catalog, :endpoints_catalog_1
+    report.value "endpoint_units", "#{prediction_model.unit}"
+    report.value "algorithm_type", "#{model.class.to_s.gsub('OpenTox::Model::Lazar','')}"
+    #TODO add more
+		report.change_catalog :algorithms_catalog, :algorithms_catalog_1, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "Neighbor algorithm: #{model.neighbor_algorithm.gsub('_',' ').titleize}#{(model.neighbor_algorithm_parameters[:min_sim] ? ' with similarity > ' + model.neighbor_algorithm_parameters[:min_sim].to_s : '')}"}
+		report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_1
+		report.change_catalog :algorithms_catalog, :algorithms_catalog_3, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "modified k-nearest neighbor #{model_type}"}
+		report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_3
+		if model.prediction_algorithm_parameters
+			pred_algorithm_params = (model.prediction_algorithm_parameters[:method] == "rf" ? "random forest" : model.prediction_algorithm_parameters[:method])
+		end
+		report.change_catalog :algorithms_catalog, :algorithms_catalog_2, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "Prediction algorithm: #{model.prediction_algorithm.gsub('OpenTox::Algorithm::','').gsub('_',' ').gsub('.', ' with ')} #{(pred_algorithm_params ? pred_algorithm_params : '')}"}
+		report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_2
+
+		# Descriptors in the model 4.3
+		if model.neighbor_algorithm_parameters[:type]
+			report.change_catalog :descriptors_catalog, :descriptors_catalog_1, {:description => "", :name => "#{model.neighbor_algorithm_parameters[:type]}", :publication_ref => "", :units => ""}
+			report.ref_catalog :algorithms_descriptors, :descriptors_catalog, :descriptors_catalog_1
+		end
+
+		# Descriptor selection 4.4
+		report.value "descriptors_selection", "#{model.feature_selection_algorithm.gsub('_',' ')} #{model.feature_selection_algorithm_parameters.collect{|k,v| k.to_s + ': ' + v.to_s}.join(', ')}" if model.feature_selection_algorithm  
+    response['Content-Type'] = "application/xml"
+    
+		return report.to_xml
+  else
+    bad_request_error "model with id: #{params[:id]} does not exist."
+  end
 end
-=end
+#=end
 get '/predict/?' do
+  # temporarily outstanding
+  nos = %w(S40.CIT
+    S40.MES
+    S40.MUTA
+    S40.cPEG5K-SH
+    S40.DDT@DOTAP
+    S40.MAA
+    S40.PLL-SH
+    S40.mPEG5K-SH
+    S40.MBA
+    S40.PVA
+    S40.LA
+    S40.AUT
+    S40.HDA
+    S40.SA
+    S40.nPEG5K-SH
+    S40.MHDA
+  )
   @prediction_models = []
   prediction_models = OpenTox::Model::NanoPrediction.all
   prediction_models.each{|m| m.model[:feature_selection_algorithm_parameters]["category"] == "P-CHEM" ? @prediction_models[0] = m : @prediction_models[1] = m}
+  # define type (pc or pcp)
   @prediction_models.each_with_index{|m,idx| idx == 0 ? m[:pc_model] = true : m[:pcp_model] = true}
-  
   # collect nanoparticles by training dataset (Ag + Au)
   dataset = OpenTox::Dataset.find_by(:name=> "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles")
-  nanoparticles = dataset.nanoparticles
-  # select physchem_parameters by relevant_features out of each model
-  @@pc_relevant_features = @prediction_models[0].model.relevant_features.collect{|id, v| OpenTox::Feature.find(id)}
-  @@pcp_relevant_features = @prediction_models[1].model.relevant_features.collect{|id, v| OpenTox::Feature.find(id)}
+  # temporarily delete silver 
+  nanoparticles = dataset.nanoparticles#.delete_if{|n| !nos.include?(n.name)}
+  
+  # select physchem_parameters by relevant_features out of each model; use @@ for global usage (prediction.haml)
+  @pc_relevant_features = @prediction_models[0].model.relevant_features.collect{|id, v| OpenTox::Feature.find(id)}
+  @pcp_relevant_features = @prediction_models[1].model.relevant_features.collect{|id, v| OpenTox::Feature.find(id)}
+  # check for outstanding nanoparticles
   pcp = nanoparticles.sample
-  pcp.physchem_descriptors.delete_if{|id,v| !@@pcp_relevant_features.include?(OpenTox::Feature.find(id))}
+  #while nos.include?(pcp.name)
+  #  pcp = nanoparticles.sample
+  #end
+  # use only relevant features
+  pcp.physchem_descriptors.delete_if{|id,v| !@pcp_relevant_features.include?(OpenTox::Feature.find(id))}
   @example_pcp = pcp
+  
+  # check for outstanding nanoparticles
   pc = nanoparticles.sample
-  pc.physchem_descriptors.delete_if{|id,v| !@@pc_relevant_features.include?(OpenTox::Feature.find(id))}
+  #while nos.include?(pc.name)
+  #  pcp = nanoparticles.sample
+  #end
+  # use only relevant features
+  #pc.physchem_descriptors.delete_if{|id,v| OpenTox::Feature.find(id).category != "P-CHEM"}
+  pc.physchem_descriptors.delete_if{|id,v| !@pc_relevant_features.include?(OpenTox::Feature.find(id))}
   @example_pc = pc
 
   haml :predict
@@ -45,7 +131,6 @@ get '/license' do
 end
 
 post '/predict/?' do
-  
   # choose the right prediction model
   prediction_model = OpenTox::Model::NanoPrediction.find(params[:prediction_model])
   size = params[:size].to_i
@@ -64,7 +149,13 @@ post '/predict/?' do
   input_coating = in_coating
 
   input_pc = {}
-  (1..size).each{|i| input_pc["#{params["input_key_#{i}"]}"] = [params["input_value_#{i}"].to_f]}
+  (1..size).each{|i| input_pc["#{params["input_key_#{i}"]}"] = [params["input_value_#{i}"].to_f] unless params["input_value_#{i}"] == "-"}
+
+  
+  # define relevant_features by input
+  @type = "pc" ? (@pc_relevant_features = input_pc.collect{|id,v| OpenTox::Feature.find(id)}) : (@pc_relevant_features = [])
+  @type = "pcp" ? (@pcp_relevant_features = input_pc.collect{|id,v| OpenTox::Feature.find(id)}) : (@pcp_relevant_features = [])
+
   if input_pc == example_pc && input_core == example_core && input_coating == example_coating
     # unchanged input = database hit
     nanoparticle = OpenTox::Nanoparticle.find_by(:id => params[:example_id])
@@ -81,9 +172,9 @@ post '/predict/?' do
     @match = false
     @nanoparticle = nanoparticle
   end
-  # output
+  # prediction output
   @input = input_pc
   @prediction = prediction_model.model.predict_substance nanoparticle
-
+  
   haml :prediction
 end