diff options
Diffstat (limited to 'lib')
| -rw-r--r-- | lib/model.rb | 126 |
1 files changed, 70 insertions, 56 deletions
diff --git a/lib/model.rb b/lib/model.rb index 139aed8..f4df8ea 100644 --- a/lib/model.rb +++ b/lib/model.rb @@ -177,7 +177,7 @@ module OpenTox return @prediction_dataset if database_activity(subjectid) - if metadata[RDF.type] == [OTA.ClassificationLazySingleTarget] + if metadata[RDF.type] == [OTA.ClassificationLazySingleTarget] # AM: Balancing, see http://www.maunz.de/wordpress/opentox/2011/balanced-lazar l = Array.new # larger s = Array.new # smaller fraction @@ -211,17 +211,18 @@ module OpenTox neighbors_best=nil begin - for i in 1..modulo[0] do - (i == modulo[0]) && (slack>0) ? lr_size = s.size + slack : lr_size = s.size + addon # determine fraction - LOGGER.info "BLAZAR: Neighbors round #{i}: #{position} + #{lr_size}." - neighbors_balanced(s, l, position, lr_size) # get ratio fraction of larger part - prediction = eval("#{@prediction_algorithm}(@neighbors,{:similarity_algorithm => @similarity_algorithm, :p_values => @p_values})") - if prediction_best.nil? || prediction[:confidence].abs > prediction_best[:confidence].abs - prediction_best=prediction - neighbors_best=@neighbors + for i in 1..modulo[0] do + (i == modulo[0]) && (slack>0) ? lr_size = s.size + slack : lr_size = s.size + addon # determine fraction + LOGGER.info "BLAZAR: Neighbors round #{i}: #{position} + #{lr_size}." + neighbors_balanced(s, l, position, lr_size) # get ratio fraction of larger part + props = get_props + prediction = eval("#{@prediction_algorithm}(@neighbors,{:similarity_algorithm => @similarity_algorithm, :p_values => @p_values})") + if prediction_best.nil? || prediction[:confidence].abs > prediction_best[:confidence].abs + prediction_best=prediction + neighbors_best=@neighbors + end + position = position + lr_size end - position = position + lr_size - end rescue Exception => e LOGGER.error "BLAZAR failed in prediction: "+e.class.to_s+": "+e.message end @@ -232,10 +233,11 @@ module OpenTox else # regression case: no balancing neighbors + props = get_props prediction = eval("#{@prediction_algorithm}(@neighbors,{:similarity_algorithm => @similarity_algorithm, :p_values => @p_values})") end - - # TODO: reasonable feature name + + # TODO: reasonable feature name #prediction_feature_uri = File.join( @prediction_dataset.uri, "feature", "prediction", File.basename(@metadata[OT.dependentVariables]),@prediction_dataset.compounds.size.to_s) value_feature_uri = File.join( @prediction_dataset.uri, "feature", "prediction", File.basename(@metadata[OT.dependentVariables]),"value") confidence_feature_uri = File.join( @prediction_dataset.uri, "feature", "prediction", File.basename(@metadata[OT.dependentVariables]),"confidence") @@ -243,7 +245,7 @@ module OpenTox prediction_feature_uris = {value_feature_uri => prediction[:prediction], confidence_feature_uri => prediction[:confidence]} #prediction_feature_uris[value_feature_uri] = "No similar compounds in training dataset." if @neighbors.size == 0 or prediction[:prediction].nil? prediction_feature_uris[value_feature_uri] = nil if @neighbors.size == 0 or prediction[:prediction].nil? - + #@prediction_dataset.metadata[OT.dependentVariables] = prediction_feature_uri @prediction_dataset.metadata[OT.dependentVariables] = @metadata[OT.dependentVariables] @@ -273,10 +275,10 @@ module OpenTox DC.title => URI.decode(File.basename( @metadata[OT.dependentVariables] )), # TODO: factor information to value }) - #OT.prediction => prediction[:prediction], - #OT.confidence => prediction[:confidence], - #OT.parameters => [{DC.title => "compound_uri", OT.paramValue => compound_uri}] - @prediction_dataset.add @compound.uri, prediction_feature_uri, value + #OT.prediction => prediction[:prediction], + #OT.confidence => prediction[:confidence], + #OT.parameters => [{DC.title => "compound_uri", OT.paramValue => compound_uri}] + @prediction_dataset.add @compound.uri, prediction_feature_uri, value end if verbose @@ -338,54 +340,66 @@ module OpenTox @prediction_dataset end - # Find neighbors and store them as object variable - def neighbors_balanced(s, l, start, offset) - @compound_features = eval("#{@feature_calculation_algorithm}(@compound,@features)") if @feature_calculation_algorithm - - @neighbors = [] - begin - #@fingerprints.each do |training_compound,training_features| # AM: this is original by CH - [ l[start, offset ] , s ].flatten.each do |training_compound| # AM: access only a balanced subset - training_features = @fingerprints[training_compound] - sim = eval("#{@similarity_algorithm}(@compound_features,training_features,@p_values)") - if sim > @min_sim - @activities[training_compound].each do |act| - this_neighbor = { - :compound => training_compound, - :similarity => sim, - :features => training_features, - :activity => act - } - @neighbors << this_neighbor + # Calculate the propositionalization matrix aka instantiation matrix (0/1 entries for features) + # Same for the vector describing the query compound + def get_props + matrix = Array.new + begin + @neighbors.each do |n| + n = n[:compound] + row = [] + @features.each do |f| + if ! @fingerprints[n].nil? + row << (@fingerprints[n].include?(f) ? 0.0 : @p_values[f]) + else + row << 0.0 end end + matrix << row + end + row = [] + @features.each do |f| + row << (@compound.match([f]).size == 0 ? 0.0 : @p_values[f]) end rescue Exception => e - LOGGER.error "BLAZAR failed in neighbors: "+e.class.to_s+": "+e.message + LOGGER.debug "get_props failed with '" + $! + "'" end - + [ matrix, row ] end + # Find neighbors and store them as object variable, access only a subset of compounds for that. + def neighbors_balanced(s, l, start, offset) + @compound_features = eval("#{@feature_calculation_algorithm}(@compound,@features)") if @feature_calculation_algorithm + @neighbors = [] + [ l[start, offset ] , s ].flatten.each do |training_compound| # AM: access only a balanced subset + training_features = @fingerprints[training_compound] + add_neighbor training_features, training_compound + end - # Find neighbors and store them as object variable + end + + # Find neighbors and store them as object variable, access all compounds for that. def neighbors - - @compound_features = eval("#{@feature_calculation_algorithm}(@compound,@features)") if @feature_calculation_algorithm - - @neighbors = [] - @fingerprints.each do |training_compound,training_features| - sim = eval("#{@similarity_algorithm}(@compound_features,training_features,@p_values)") - if sim > @min_sim - @activities[training_compound].each do |act| - @neighbors << { - :compound => training_compound, - :similarity => sim, - :features => training_features, - :activity => act - } - end + @compound_features = eval("#{@feature_calculation_algorithm}(@compound,@features)") if @feature_calculation_algorithm + @neighbors = [] + @fingerprints.each do |training_compound,training_features| # AM: access all compounds + add_neighbor training_features, training_compound + end + end + + # Adds a neighbor to @neighbors if it passes the similarity threshold. + def add_neighbor(training_features, training_compound) + sim = eval("#{@similarity_algorithm}(@compound_features,training_features,@p_values)") + if sim > @min_sim + @activities[training_compound].each do |act| + @neighbors << { + :compound => training_compound, + :similarity => sim, + :features => training_features, + :activity => act + } end - end + end end # Find database activities and store them in @prediction_dataset |