diff options
Diffstat (limited to 'lib/lazar.rb')
| -rw-r--r-- | lib/lazar.rb | 46 |
1 files changed, 28 insertions, 18 deletions
diff --git a/lib/lazar.rb b/lib/lazar.rb index d6a6f47..2c83f38 100644 --- a/lib/lazar.rb +++ b/lib/lazar.rb @@ -25,13 +25,14 @@ module OpenTox # algorithms field :feature_generation, type: String field :feature_calculation_algorithm, type: String - field :prediction_algorithm, type: Symbol - field :similarity_algorithm, type: Symbol + field :prediction_algorithm, type: String + field :similarity_algorithm, type: String # prediction features field :prediction_feature_id, type: BSON::ObjectId field :predicted_value_id, type: BSON::ObjectId field :predicted_variables, type: Array # parameters + field :nr_hits, type: Boolean field :min_sim, type: Float field :propositionalized, type:Boolean field :min_train_performance, type: Float @@ -46,7 +47,7 @@ module OpenTox # Prepare lazar object (includes graph mining) # @param[Array] lazar parameters as strings # @param[Hash] REST parameters, as input by user - def self.create training_dataset, feature_dataset, prediction_feature=nil, params={} + def self.create training_dataset, feature_dataset, prediction_feature=nil, nr_hits=false, params={} lazar = OpenTox::Model::Lazar.new @@ -79,22 +80,20 @@ module OpenTox lazar.prediction_algorithm =~ /majority_vote/ ? lazar.propositionalized = false : lazar.propositionalized = true lazar.min_sim = params[:min_sim].to_f if params[:min_sim] and params[:min_sim].numeric? - lazar.nr_hits = params[:nr_hits] if params[:nr_hits] - lazar.feature_generation = feature_dataset.creator + lazar.nr_hits = nr_hits + lazar.feature_generation = feature_dataset.training_algorithm #lazar.parameters << {"title" => "feature_generation_uri", "paramValue" => params[:feature_generation_uri]} - # TODO insert algorithm into feature dataset - # TODO store algorithms in mongodb? if lazar.feature_generation =~ /fminer|bbrc|last/ - if (lazar[:nr_hits] == "true") - lazar.feature_calculation_algorithm = "smarts_count" + if lazar[:nr_hits] + lazar.feature_calculation_algorithm = "OpenTox::Algorithm::Descriptor.smarts_count" else - lazar.feature_calculation_algorithm = "smarts_match" + lazar.feature_calculation_algorithm = "OpenTox::Algorithm::Descriptor.smarts_match" end - lazar.similarity_algorithm = "tanimoto" + lazar.similarity_algorithm = "OpenTox::Algorithm::Similarity.tanimoto" lazar.min_sim = 0.3 unless lazar.min_sim elsif lazar.feature_generation =~/descriptor/ or lazar.feature_generation.nil? # cosine similartiy is default (e.g. used when no fetature_generation_uri is given and a feature_dataset_uri is provided instead) - lazar.similarity_algorithm = "cosine" + lazar.similarity_algorithm = "OpenTox::Algorithm::Similarity.cosine" lazar.min_sim = 0.7 unless lazar.min_sim else bad_request_error "unkown feature generation method #{lazar.feature_generation}" @@ -116,7 +115,7 @@ module OpenTox time = Time.now # prepare prediction dataset - prediction_dataset = OpenTox::Dataset.new + prediction_dataset = LazarPrediction.new prediction_feature = OpenTox::Feature.find prediction_feature_id prediction_dataset.title = "Lazar prediction for #{prediction_feature.title}", prediction_dataset.creator = __FILE__, @@ -145,7 +144,11 @@ module OpenTox $logger.debug "Setup: #{Time.now-time}" time = Time.now - @query_fingerprint = OpenTox::Algorithm::Descriptor.send( feature_calculation_algorithm, compounds, @feature_dataset.features.collect{|f| f["title"]} ) + # TODO: remove eval + #p ("#{feature_calculation_algorithm}(#{compounds}, #{@feature_dataset.features.collect{|f| f.smarts}})") + #@query_fingerprint = eval("#{feature_calculation_algorithm}(#{compounds}, #{@feature_dataset.features.collect{|f| f.smarts}})") + @query_fingerprint = Algorithm.run(feature_calculation_algorithm, compounds, @feature_dataset.features.collect{|f| f.smarts} ) + #p @query_fingerprint $logger.debug "Fingerprint calculation: #{Time.now-time}" time = Time.now @@ -173,14 +176,21 @@ module OpenTox # find neighbors neighbors = [] - @feature_dataset.data_entries.each_with_index do |fingerprint, i| - - sim = OpenTox::Algorithm::Similarity.send(similarity_algorithm,fingerprint, @query_fingerprint[c]) + #@feature_dataset.data_entries.each_with_index do |fingerprint, i| + @feature_dataset.compounds.each_with_index do |compound, i| + #p compound + #p @feature_dataset.features.size + fingerprint = @feature_dataset.feature_values(compound) + #fingerprint = @feature_dataset.features(compound) + #p fingerprint + + sim = Algorithm.run(similarity_algorithm,[fingerprint, @query_fingerprint[c]]) # TODO fix for multi feature datasets neighbors << [@feature_dataset.compounds[i],@training_dataset.data_entries[i].first,sim] if sim > self.min_sim end + #p neighbors - prediction = OpenTox::Algorithm::Classification.send(prediction_algorithm, neighbors) + prediction = Algorithm.run(prediction_algorithm, neighbors) $logger.debug "Prediction: #{Time.now-time}" time = Time.now |