diff options
Diffstat (limited to 'lib/compound.rb')
| -rw-r--r-- | lib/compound.rb | 52 |
1 files changed, 31 insertions, 21 deletions
diff --git a/lib/compound.rb b/lib/compound.rb index 4e62637..ad0eaba 100644 --- a/lib/compound.rb +++ b/lib/compound.rb @@ -24,13 +24,16 @@ module OpenTox field :molecular_weight, type: Float field :fingerprints, type: Hash, default: {} field :default_fingerprint_size, type: Integer + field :dataset_ids, type: Array, default: [] + field :features, type: Hash, default: {} index({smiles: 1}, {unique: true}) + #index({default_fingerprint: 1}, {unique: false}) # Overwrites standard Mongoid method to create fingerprints before database insertion def self.find_or_create_by params compound = self.find_or_initialize_by params - compound.default_fingerprint_size = compound.fingerprint(DEFAULT_FINGERPRINT) + compound.default_fingerprint_size = compound.fingerprint(DEFAULT_FINGERPRINT).size compound.save compound end @@ -42,7 +45,7 @@ module OpenTox if type == "MP2D" fp = obconversion(smiles,"smi","mpd").strip.split("\t") name = fp.shift # remove Title - fingerprints[type] = fp + fingerprints[type] = fp.uniq # no fingerprint counts #http://openbabel.org/docs/dev/FileFormats/Multilevel_Neighborhoods_of_Atoms_(MNA).html elsif type== "MNA" level = 2 # TODO: level as parameter, evaluate level 1, see paper @@ -245,20 +248,23 @@ module OpenTox def fingerprint_neighbors params bad_request_error "Incorrect parameters '#{params}' for Compound#fingerprint_neighbors. Please provide :type, :training_dataset_id, :min_sim." unless params[:type] and params[:training_dataset_id] and params[:min_sim] neighbors = [] - #if params[:type] == DEFAULT_FINGERPRINT - #neighbors = db_neighbors params - #p neighbors - #else + if params[:type] == DEFAULT_FINGERPRINT + neighbors = db_neighbors params + else query_fingerprint = self.fingerprint params[:type] - training_dataset = Dataset.find(params[:training_dataset_id]).compounds.each do |compound| - unless self == compound + training_dataset = Dataset.find(params[:training_dataset_id]) + prediction_feature = training_dataset.features.first + training_dataset.compounds.each do |compound| + #unless self == compound candidate_fingerprint = compound.fingerprint params[:type] sim = (query_fingerprint & candidate_fingerprint).size/(query_fingerprint | candidate_fingerprint).size.to_f - neighbors << [compound.id, sim] if sim >= params[:min_sim] - end + feature_values = training_dataset.values(compound,prediction_feature) + neighbors << {"_id" => compound.id, "features" => {prediction_feature.id.to_s => feature_values}, "tanimoto" => sim} if sim >= params[:min_sim] + #end end - #end - neighbors.sort{|a,b| b.last <=> a.last} + neighbors.sort!{|a,b| b["tanimoto"] <=> a["tanimoto"]} + end + neighbors end def fminer_neighbors params @@ -300,30 +306,34 @@ module OpenTox end def db_neighbors params - p "DB NEIGHBORS" - p params - # TODO restrict to dataset # from http://blog.matt-swain.com/post/87093745652/chemical-similarity-search-in-mongodb - qn = fingerprint(params[:type]).size + + #qn = default_fingerprint_size #qmin = qn * threshold #qmax = qn / threshold #not sure if it is worth the effort of keeping feature counts up to date (compound deletions, additions, ...) #reqbits = [count['_id'] for count in db.mfp_counts.find({'_id': {'$in': qfp}}).sort('count', 1).limit(qn - qmin + 1)] aggregate = [ #{'$match': {'mfp.count': {'$gte': qmin, '$lte': qmax}, 'mfp.bits': {'$in': reqbits}}}, - {'$match' => {'_id' => {'$ne' => self.id}}}, # remove self + #{'$match' => {'_id' => {'$ne' => self.id}}}, # remove self {'$project' => { 'tanimoto' => {'$let' => { - 'vars' => {'common' => {'$size' => {'$setIntersection' => ["'$#{DEFAULT_FINGERPRINT}'", DEFAULT_FINGERPRINT]}}}, - 'in' => {'$divide' => ['$$common', {'$subtract' => [{'$add' => [qn, '$default_fingerprint_size']}, '$$common']}]} + 'vars' => {'common' => {'$size' => {'$setIntersection' => ["$fingerprints.#{DEFAULT_FINGERPRINT}", fingerprints[DEFAULT_FINGERPRINT]]}}}, + #'vars' => {'common' => {'$size' => {'$setIntersection' => ["$default_fingerprint", default_fingerprint]}}}, + 'in' => {'$divide' => ['$$common', {'$subtract' => [{'$add' => [default_fingerprint_size, '$default_fingerprint_size']}, '$$common']}]} }}, - '_id' => 1 + '_id' => 1, + 'features' => 1, + 'dataset_ids' => 1 }}, {'$match' => {'tanimoto' => {'$gte' => params[:min_sim]}}}, {'$sort' => {'tanimoto' => -1}} ] - $mongo["compounds"].aggregate(aggregate).collect{ |r| [r["_id"], r["tanimoto"]] } + $mongo["compounds"].aggregate(aggregate).select{|r| r["dataset_ids"].include? params[:training_dataset_id]} + + + #$mongo["compounds"].aggregate(aggregate).collect{ |r| [r["_id"], r["tanimoto"]] } end |