diff options
Diffstat (limited to 'application.rb')
| -rw-r--r-- | application.rb | 235 |
1 files changed, 35 insertions, 200 deletions
diff --git a/application.rb b/application.rb index 5f64b84..eefd833 100644 --- a/application.rb +++ b/application.rb @@ -1,11 +1,6 @@ #require_relative 'helper.rb' require 'rdiscount' include OpenTox -#require File.join(ENV["HOME"],".opentox","config","lazar-gui.rb") # until added to ot-tools - -# DG: workaround for https://github.com/sinatra/sinatra/issues/808 -# Date: 18/11/2013 -#set :protection, :except => :path_traversal configure :development do $logger = Logger.new(STDOUT) @@ -38,16 +33,6 @@ end get '/predict/modeldetails/:model' do model = OpenTox::Model::Prediction.find params[:model] crossvalidations = OpenTox::Validation::RepeatedCrossValidation.find(model.repeated_crossvalidation_id).crossvalidations - #confidence_plots = crossvalidations.collect{|cv| [cv.id, cv.confidence_plot]} - #confidence_plots.each do |confp| - # File.open(File.join('public', "confp#{confp[0]}.svg"), 'w'){|file| file.write(confp[1])} unless File.exists? File.join('public', "confp#{confp[0]}.svg") - #end - #if model.regression? - # correlation_plots = crossvalidations.collect{|cv| [cv.id, cv.correlation_plot]} - # correlation_plots.each do |corrp| - # File.open(File.join('public', "corrp#{corrp[0]}.svg"), 'w'){|file| file.write(corrp[1])} unless File.exists? File.join('public', "corrp#{corrp[0]}.svg") - # end - #end return haml :model_details, :layout=> false, :locals => {:model => model, :crossvalidations => crossvalidations} end @@ -56,198 +41,47 @@ get '/jme_help/?' do File.read(File.join('views','jme_help.html')) end -# get individual compound details -get '/prediction/:neighbor/details/?' do - @compound = OpenTox::Compound.new params[:neighbor] - @smiles = @compound.smiles - task = OpenTox::Task.run("Get names for '#{@smiles}'.") do - names = @compound.names - end - task.wait - - case task[RDF::OT.hasStatus] - when "Error" - @names = "No names for this compound available." - when "Completed" - @names = @compound.names - else - @names = "No names for this compound available." - end - @inchi = @compound.inchi.gsub("InChI=", "") - - haml :details, :layout => false -end -=begin -# sdf representation for datasets -#TODO fix 502 errors from compound service -get '/predict/:dataset_uri/sdf/?' do - uri = CGI.unescape(params[:dataset_uri]) - $logger.debug uri - bad_request_error "Not a dataset uri." unless URI.dataset? uri - dataset = OpenTox::Dataset.find uri - @compounds = dataset.compounds - @data_entries = dataset.data_entries - sum="" - @compounds.each_with_index{ |c, idx| - sum << c.inchi - sum << c.sdf.sub(/\n\$\$\$\$/,'') - @data_entries[idx].each{ |f,v| - sum << "> <\"#{f}\">\n" - sum << v.join(", ") - sum << "\n\n" - } - sum << "$$$$\n" - } - send_file sum, :filename => "#{dataset.title}.sdf" -end -=end -# fingerprints for compound in predictions -get '/prediction/:model_uri/:type/:compound_uri/fingerprints/?' do - @type = params[:type] - model = OpenTox::Model::Lazar.find params[:model_uri] - feature_dataset = OpenTox::Dataset.find model[RDF::OT.featureDataset] - @compound = OpenTox::Compound.new params[:compound_uri] - @significant_fragments = [] - if @type =~ /classification/i - # collect all feature values with fingerprint - fingerprints = OpenTox::Algorithm::Descriptor.send("smarts_match", [@compound], feature_dataset.features.collect{ |f| f[RDF::DC.title]})[@compound.uri] - #$logger.debug "fingerprints:\t#{fingerprints}\n" - - # collect fingerprints with value 1 - @fingerprint_values = fingerprints.collect{|smarts, value| [smarts, value] if value > 0} - - # collect all features from feature_dataset - @features = feature_dataset.features.collect{|f| f } - - # search for each fingerprint in all features and collect feature values( effect, smarts, pValue ) - @fingerprint_values.each{ |fi, v| @features.each{ |f| @significant_fragments << [f[RDF::OT.effect].to_i, f[RDF::OT.smarts], f[RDF::OT.pValue]] if fi == f[RDF::OT.smarts] } } - - # pass value_map, important to interprete effect value - prediction_feature_uri = "" - model.parameters.each {|p| - if p[RDF::DC.title].to_s == "prediction_feature_uri" - prediction_feature_uri = p[RDF::OT.paramValue].object - end - } - prediction_feature = OpenTox::Feature.find prediction_feature_uri - @value_map = prediction_feature.value_map - - else #regression - feature_calc_algo = "" - model.parameters.each {|p| - if p[RDF::DC.title].to_s == "feature_calculation_algorithm" - feature_calc_algo = p[RDF::OT.paramValue].object - end - } - - @desc = [] - fingerprints = OpenTox::Algorithm::Descriptor.send( feature_calc_algo, [ @compound ], feature_dataset.features.collect{ |f| f[RDF::DC.title] } ) - fingerprints.each{|x, h| h.each{|descriptor, value| @desc << [descriptor, [value]]}} - - pc_descriptor_titles_descriptions = {} - feature_dataset.features.collect{ |f| - pc_descriptor_titles_descriptions[f[RDF::DC.title]]= f[RDF::DC.description] - } - - @desc.each{|d, v| @significant_fragments << [pc_descriptor_titles_descriptions[d], v] } - end - - haml :significant_fragments, :layout => false -end - -get '/prediction/:model_uri/:type/:neighbor/significant_fragments/?' do - @type = params[:type] - @compound = OpenTox::Compound.new params[:neighbor] - model = OpenTox::Model::Lazar.find params[:model_uri] - #$logger.debug "model for significant fragments:\t#{model.uri}" - - feature_dataset = OpenTox::Dataset.find model[RDF::OT.featureDataset] - $logger.debug "feature_dataset_uri:\t#{feature_dataset.uri}\n" - - # load all compounds - feature_dataset.compounds - - # load all features - @features = feature_dataset.features.collect{|f| f} - - # find all features and values for a neighbor compound - @significant_fragments = [] - # check type first - if @type =~ /classification/i - # get compound index in feature dataset - c_idx = feature_dataset.compound_indices @compound.uri - - # collect feature uris with value - @feat = @features.collect{|f| [feature_dataset.data_entry_value(c_idx[0], f.uri), f.uri]} - #$logger.debug "@feat:\t#{@feat}\n" - - # pass feature uris if value > 0 - @feat.each do |f| - # search relevant features - if f[0] > 0 - f = OpenTox::Feature.find f[1] - # pass relevant features with [ effect, smarts, pValue ] - @significant_fragments << [f[RDF::OT.effect].to_i, f[RDF::OT.smarts], f[RDF::OT.pValue].to_f.round(3)] - end - end - # pass value_map, important to interprete effect value - prediction_feature_uri = "" - model.parameters.each {|p| - if p[RDF::DC.title].to_s == "prediction_feature_uri" - prediction_feature_uri = p[RDF::OT.paramValue].object - end - } - prediction_feature = OpenTox::Feature.find prediction_feature_uri - @value_map = prediction_feature.value_map - - else # regression - # find a value in feature dataset by compound and feature - @values = @features.collect{|f| feature_dataset.values(@compound, f)} - #$logger.debug "values in fd:\t#{@values}" - - @features.each_with_index{|f, i| @significant_fragments << [f.description, @values[i]]} - end - #$logger.debug "significant fragments:\t#{@significant_fragments}\n" - - haml :significant_fragments, :layout => false +get '/predict/dataset/:name' do + response['Content-Type'] = "text/csv" + dataset = Dataset.find_by(:name=>params[:name]) + csv = dataset.to_csv + csv end get '/predict/?:csv?' do response['Content-Type'] = "text/csv" - @csv = "\"Compound\",\"Endpoint\",\"Type\",\"Prediction\",\"Confidence\"\n" + @csv = "\"Compound\",\"Endpoint\",\"Type\",\"Prediction\",\"95% Prediction interval\"\n" @@batch.each do |key, values| + compound = key + smiles = compound.smiles values.each do |array| model = array[0] + type = model.model.class.to_s.match("Classification") ? "Classification" : "Regression" prediction = array[1] - compound = key.smiles - mw = key.molecular_weight endpoint = "#{model.endpoint.gsub('_', ' ')} (#{model.species})" if prediction[:confidence] == "measured" if prediction[:value].is_a?(Array) prediction[:value].each do |value| - type = "" - weight = Compound.from_smiles(compound).mmol_to_mg(value, mw) - pred = value.numeric? ? "#{'%.2e' % value} (#{model.unit}) | #{'%.2e' % weight} (mg/kg_bw/day)" : value - confidence = "measured activity" - @csv += "\"#{compound}\",\"#{endpoint}\",\"#{type}\",\"#{pred}\",\"#{confidence}\"\n" + pred = value.numeric? ? "#{value} (#{model.unit}), #{compound.mmol_to_mg(value.delog10)} #{(model.unit =~ /\b(mol\/L)\b/) ? "(mg/L)" : "(mg/kg_bw/day)"}" : value + int = (prediction[:prediction_interval].nil? ? nil : prediction[:prediction_interval]) + interval = (int.nil? ? "--" : "#{int[1].delog10} - #{int[0].delog10} (#{model.unit})") + @csv += "\"#{smiles}\",\"#{endpoint}\",\"#{type}\",\"#{pred}\",\"#{interval}\"\n" end else - type = "" - weight = Compound.from_smiles(compound).mmol_to_mg(prediction[:value], mw) - pred = prediction[:value].numeric? ? "#{'%.2e' % prediction[:value]} (#{model.unit}) | #{'%.2e' % weight} (mg/kg_bw/day)" : prediction[:value] + pred = prediction[:value].numeric? ? "#{prediction[:value]} (#{model.unit}), #{compound.mmol_to_mg(prediction[:value].delog10)} #{(model.unit =~ /\b(mol\/L)\b/) ? "(mg/L)" : "(mg/kg_bw/day)"}" : prediction[:value] confidence = "measured activity" end elsif prediction[:neighbors].size > 0 - weight = Compound.from_smiles(compound).mmol_to_mg(prediction[:value], mw) type = model.model.class.to_s.match("Classification") ? "Classification" : "Regression" - pred = prediction[:value].numeric? ? "#{'%.2e' % prediction[:value]} (#{model.unit}) | #{'%.2e' % weight} (mg/kg_bw/day)" : prediction[:value] - confidence = prediction[:confidence] + pred = prediction[:value].numeric? ? "#{prediction[:value].delog10} (#{model.unit}), #{compound.mmol_to_mg(prediction[:value].delog10)} #{(model.unit =~ /\b(mol\/L)\b/) ? "(mg/L)" : "(mg/kg_bw/day)"}" : prediction[:value] + int = (prediction[:prediction_interval].nil? ? nil : prediction[:prediction_interval]) + interval = (int.nil? ? "--" : "#{int[1].delog10} - #{int[0].delog10} (#{model.unit})") else type = "" pred = "Not enough similar compounds in training dataset." - confidence = "" + interval = "" end - @csv += "\"#{compound}\",\"#{endpoint}\",\"#{type}\",\"#{pred}\",\"#{confidence}\"\n" unless prediction[:value].is_a?(Array) + @csv += "\"#{smiles}\",\"#{endpoint}\",\"#{type}\",\"#{pred}\",\"#{interval}\"\n" unless prediction[:value].is_a?(Array) end end @csv @@ -265,11 +99,21 @@ post '/predict/?' do f.write(params[:fileselect][:tempfile].read) end @filename = params[:fileselect][:filename] - input = OpenTox::Dataset.from_csv_file File.join "tmp", params[:fileselect][:filename] - dataset = OpenTox::Dataset.find input.id + begin + input = OpenTox::Dataset.from_csv_file File.join("tmp", params[:fileselect][:filename]), true + if input.class == OpenTox::Dataset + dataset = OpenTox::Dataset.find input + else + @error_report = "Could not serialize file '#{@filename}' ." + return haml :error + end + rescue + @error_report = "Could not serialize file '#{@filename}' ." + return haml :error + end @compounds = dataset.compounds if @compounds.size == 0 - @error_report = "No valid SMILES submitted." + @error_report = dataset[:warnings] dataset.delete return haml :error end @@ -283,7 +127,9 @@ post '/predict/?' do end end @@batch = @batch + @warnings = dataset[:warnings] dataset.delete + File.delete File.join("tmp", params[:fileselect][:filename]) return haml :batch end @@ -295,7 +141,7 @@ post '/predict/?' do # get compound from SMILES @compound = Compound.from_smiles @identifier if @compound.blank? - @error_report = "Attention, '#{@identifier}' is not a valid SMILES string." + @error_report = "'#{@identifier}' is not a valid SMILES string." return haml :error end @@ -310,17 +156,6 @@ post '/predict/?' do end end -get '/license' do - @license = RDiscount.new(File.read("LICENSE.md")).to_html - haml :license, :layout => false -end - -=begin -get '/faq' do - @faq = RDiscount.new(File.read("FAQ.md")).to_html - haml :faq, :layout => :faq_layout -end -=end get '/style.css' do headers 'Content-Type' => 'text/css; charset=utf-8' scss :style |