path: root/lib/dataset.rb

require 'csv'
require 'tempfile'
require 'digest/md5'

module OpenTox

  # Collection of substances and features
  class Dataset

    field :data_entries, type: Hash, default: {}
    field :md5, type: String

    # Readers

    # Get all compounds
    # @return [Array<OpenTox::Compound>]
    def compounds
      substances.select{|s| s.is_a? Compound}
    end

    # Get all nanoparticles
    # @return [Array<OpenTox::Nanoparticle>]
    def nanoparticles
      substances.select{|s| s.is_a? Nanoparticle}
    end

    # Get all substances
    # @return [Array<OpenTox::Substance>]
    def substances
      @substances ||= data_entries.keys.collect{|id| OpenTox::Substance.find id}.uniq
      @substances
    end

    # Get all features
    # @return [Array<OpenTox::Feature>]
    def features
      @features ||= data_entries.collect{|sid,data| data.keys.collect{|id| OpenTox::Feature.find(id)}}.flatten.uniq
      @features
    end

    # Get all values for a given substance and feature
    # @param [OpenTox::Substance,BSON::ObjectId,String] substance or substance id
    # @param [OpenTox::Feature,BSON::ObjectId,String] feature or feature id
    # @return [TrueClass,FalseClass,Float]
    def values substance,feature
      substance = substance.id if substance.is_a? Substance
      feature = feature.id if feature.is_a? Feature
      if data_entries[substance.to_s] and data_entries[substance.to_s][feature.to_s]
        data_entries[substance.to_s][feature.to_s]
      else
        [nil]
      end
    end

    # Writers

    # Add a value for a given substance and feature
    # @param [OpenTox::Substance,BSON::ObjectId,String] substance or substance id
    # @param [OpenTox::Feature,BSON::ObjectId,String] feature or feature id
    # @param [TrueClass,FalseClass,Float]
    def add(substance,feature,value)
      substance = substance.id if substance.is_a? Substance
      feature = feature.id if feature.is_a? Feature
      data_entries[substance.to_s] ||= {}
      data_entries[substance.to_s][feature.to_s] ||= []
      data_entries[substance.to_s][feature.to_s] << value
      #data_entries[substance.to_s][feature.to_s].uniq! if value.numeric? # assuming that identical values come from the same source
    end

    # Parsers
    
    # Create a dataset from CSV file
    # @param [File] Input file with the following format:
    #   - ID column (optional): header containing "ID" string, arbitrary ID values
    #   - SMILES/InChI column: header indicating "SMILES" or "InChI", Smiles or InChI strings
    #   - one or more properties column(s): header with property name(s), property values
    #     files with a single property column are read as BioActivities (i.e. dependent variable)
    #     files with multiple property columns are read as SubstanceProperties (i.e. independent variables)
    # @return [OpenTox::Dataset]
    def self.from_csv_file file
      md5 = Digest::MD5.hexdigest(File.read(file)) # use hash to identify identical files
      dataset = self.find_by(:md5 => md5)
      if dataset
        $logger.debug "Found #{file} in the database (id: #{dataset.id}, md5: #{dataset.md5}), skipping import."
      else
        $logger.debug "Parsing #{file}."
        table = nil
        sep = ","
        ["\t",";"].each do |s| # guess alternative CSV separator
          if File.readlines(file).first.match(/#{s}/)
            sep = s
            break
          end
        end
        table = CSV.read file, :col_sep => sep, :skip_blanks => true, :encoding => 'windows-1251:utf-8'
        if table
          dataset = self.new(:source => file, :name => File.basename(file,".*"), :md5 => md5)
          dataset.parse_table table
        else
          bad_request_error "#{file} is not a valid CSV/TSV file. Could not find "," ";" or TAB as column separator."
        end
      end
      dataset
    end

    # Create a dataset from SDF file 
    #   files with a single data field are read as BioActivities (i.e. dependent variable)
    #   files with multiple data fields are read as SubstanceProperties (i.e. independent variable)
    # @param [File] 
    # @return [OpenTox::Dataset]
    def self.from_sdf_file file
      md5 = Digest::MD5.hexdigest(File.read(file)) # use hash to identify identical files
      dataset = self.find_by(:md5 => md5)
      if dataset
        $logger.debug "Found #{file} in the database (id: #{dataset.id}, md5: #{dataset.md5}), skipping import."
      else
        $logger.debug "Parsing #{file}."

        dataset = self.new(:source => file, :name => File.basename(file,".*"), :md5 => md5)
        original_id = OriginalId.find_or_create_by(:dataset_id => dataset.id,:name => dataset.name+".ID")

        read_result = false
        sdf = ""
        feature_name = ""
        compound = nil
        features = {}
        table = [["ID","SMILES"]]

        File.readlines(file).each do |line|
          if line.match %r{\$\$\$\$}
            sdf << line
            id = sdf.split("\n").first.chomp
            compound = Compound.from_sdf sdf
            row = [id,compound.smiles]
            features.each do |f,v|
              table[0] << f unless table[0].include? f
              row[table[0].index(f)] = v
            end
            table << row
            sdf = ""
            features = {}
          elsif line.match /^>\s+</
            feature_name = line.match(/^>\s+<(.*)>/)[1]
            read_result = true
          else
            if read_result
              value = line.chomp
              features[feature_name] = value
              read_result = false
            else
              sdf << line
            end
          end
        end
        dataset.parse_table table
      end
      dataset.save
      dataset
    end

    # Create a dataset from PubChem Assay
    # @param [Integer] PubChem AssayID (AID)
    # @return [OpenTox::Dataset]
    def self.from_pubchem_aid aid
      url = File.join PUBCHEM_URI, "assay/aid/#{aid}/CSV"
      assay_metadata = JSON.parse(RestClientWrapper.get(File.join PUBCHEM_URI,"assay/aid/#{aid}/description/JSON").to_s)["PC_AssayContainer"][0]["assay"]["descr"]
      name = assay_metadata["name"].gsub(/\s+/,"_")
      csv = CSV.parse(RestClientWrapper.get(url))
      csv.select!{|r| r[0].match /^\d/} # discard header rows
      table = [["SID","SMILES",name]]
      csv.each_slice(100) do |slice| # get SMILES in chunks
        sids = slice.collect{|s| s[1]}
        smiles = RestClientWrapper.get(File.join(PUBCHEM_URI,"compound/cid/#{sids.join(",")}/property/CanonicalSMILES/TXT")).split("\n").collect{|s| s.to_s}
        abort("Could not get SMILES for all SIDs from PubChem") unless sids.size == smiles.size
        smiles.each_with_index do |smi,i|
          table << [slice[i][1].to_s,smi.chomp,slice[i][3].to_s]
        end
      end
      dataset = self.new(:source => url, :name => name) 
      dataset.parse_table table
      dataset
    end

    # Parse data in tabular format (e.g. from csv)
    #   does a lot of guesswork in order to determine feature types
    # @param [Array<Array>] 
    def parse_table table

      # features
      feature_names = table.shift.collect{|f| f.strip}
      warnings << "Duplicated features in table header." unless feature_names.size == feature_names.uniq.size

      original_id = nil 
      if feature_names[0] =~ /ID/i # check ID column
        feature_names.shift 
        original_id = OriginalId.find_or_create_by(:dataset_id => self.id,:name => self.name+".ID")
      end

      compound_format = feature_names.shift
      bad_request_error "#{compound_format} is not a supported compound format. Accepted formats: SMILES, InChI." unless compound_format =~ /SMILES|InChI/i
      numeric = []
      features = []

      # guess feature types
      bioactivity = true if feature_names.size == 1
      feature_names.each_with_index do |f,i|
        original_id ? j = i+2 : j = i+1
        values = table.collect{|row| val=row[j].to_s.strip; val.blank? ? nil : val }.uniq.compact
        types = values.collect{|v| v.numeric? ? true : false}.uniq
        feature = nil
        if values.size == 0 # empty feature
        elsif  values.size > 5 and types.size == 1 and types.first == true # 5 max classes
          numeric[i] = true
          if bioactivity
            feature = NumericBioActivity.find_or_create_by(:name => f)
          else
            feature = NumericSubstanceProperty.find_or_create_by(:name => f)
          end
        else
          numeric[i] = false
          if bioactivity
            feature = NominalBioActivity.find_or_create_by(:name => f, :accept_values => values.sort)
          else
            feature = NominalSubstanceProperty.find_or_create_by(:name => f, :accept_values => values.sort)
          end
        end
        features << feature if feature
      end
      
      # substances and values

      all_substances = []
      table.each_with_index do |vals,i|
        original_id_value = vals.shift.strip if original_id
        identifier = vals.shift.strip
        begin
          case compound_format
          when /SMILES/i
            substance = Compound.from_smiles(identifier)
          when /InChI/i
            substance = Compound.from_inchi(identifier)
          end
        rescue 
          substance = nil
        end
        if substance.nil? # compound parsers may return nil
          warn "Cannot parse #{compound_format} compound '#{identifier}' at line #{i+2} of #{source}, all entries are ignored."
          next
        end
        all_substances << substance
        substance.dataset_ids << self.id
        substance.dataset_ids.uniq!
        substance.save

        add substance, original_id, original_id_value if original_id

        vals.each_with_index do |v,j|
          if v.blank?
            warn "Empty value for compound '#{identifier}' (#{original_id_value}) and feature '#{feature_names[j]}'."
            v = nil
          elsif numeric[j]
            v = v.to_f
          else
            v = v.strip
          end
          add substance, features[j], v
        end
        data_entries[substance.id.to_s] ||= nil #if vals.empty? # no features, eg batch predictions
      end

      all_substances.duplicates.each do |substance|
        positions = []
        all_substances.each_with_index{|c,i| positions << i+1 if !c.blank? and c.inchi and c.inchi == substance.inchi}
        warn "Duplicate compound #{substance.smiles} at rows #{positions.join(', ')}. Entries are accepted, assuming that measurements come from independent experiments." 
      end
      save
    end

    # Serialisation
    
    # Convert dataset to csv format including compound smiles as first column, other column headers are feature names
    # @return [String]
    def to_csv(inchi=false)
      CSV.generate() do |csv| 
        compound = substances.first.is_a? Compound
        if compound
          csv << [inchi ? "InChI" : "SMILES"] + features.collect{|f| f.name}
        else
          csv << ["Name"] + features.collect{|f| f.name}
        end
        substances.each do |substance|
          if compound
            name = (inchi ? substance.inchi : substance.smiles)
          else
            name = substance.name
          end
          nr_measurements = features.collect{|f| data_entries[substance.id.to_s][f.id.to_s].size if data_entries[substance.id.to_s][f.id.to_s]}.compact.uniq

          if nr_measurements.size > 1
            warn "Unequal number of measurements (#{nr_measurements}) for '#{name}'. Skipping entries."
          else
            (0..nr_measurements.first-1).each do |i|
              row = [name]
              features.each do |f|
                values(substance,f) ? row << values(substance,f)[i] : row << ""
              end
              csv << row
            end
          end
        end
      end
    end

    # Convert dataset to SDF format
    # @return [String] SDF string
    def to_sdf
      sdf = ""
      substances.each do |substance|
        sdf_lines = substance.sdf.sub(/\$\$\$\$\n/,"").split("\n")
        sdf_lines[0] = substance.smiles
        sdf += sdf_lines.join("\n")
        features.each do |f|
          sdf += "\n> <#{f.name}>\n"
          sdf += values(substance,f).uniq.join ","
        end
        sdf += "\n$$$$\n"
      end
      sdf
    end

    # Dataset operations

    # Merge an array of datasets 
    # @param [Array] OpenTox::Dataset Array to be merged
    # @param [Hash] feature modifications
    # @param [Hash] value modifications
    # @return [OpenTox::Dataset] merged dataset
    def self.merge datasets, feature_map=nil, value_map=nil
      dataset = self.new(:source => datasets.collect{|d| d.source}.join(", "), :name => datasets.collect{|d| d.name}.uniq.join(", "))
      datasets.each do |d|
        d.substances.each do |s|
          d.features.each do |f|
            d.values(s,f).each do |v|
              f = feature_map[f] if feature_map and feature_map[f]
              v = value_map[v] if value_map and value_map[v]
              dataset.add s,f,v #unless dataset.values(s,f).include? v
            end
          end
        end
      end
      dataset.save
      dataset
    end

    # Split a dataset into n folds
    # @param [Integer] number of folds
    # @return [Array] Array with folds [training_dataset,test_dataset]
    def folds n
      len = self.substances.size
      indices = (0..len-1).to_a.shuffle
      mid = (len/n)
      chunks = []
      start = 0
      1.upto(n) do |i|
        last = start+mid
        last = last-1 unless len%n >= i
        test_idxs = indices[start..last] || []
        test_substances = test_idxs.collect{|i| substances[i]}
        training_idxs = indices-test_idxs
        training_substances = training_idxs.collect{|i| substances[i]}
        chunk = [training_substances,test_substances].collect do |substances|
          dataset = self.class.create(:name => "#{self.name} (Fold #{i-1})",:source => self.id )
          substances.each do |substance|
            substance.dataset_ids << dataset.id
            substance.dataset_ids.uniq!
            substance.save
            dataset.data_entries[substance.id.to_s] = data_entries[substance.id.to_s] ||= {}
          end
          dataset.save
          dataset
        end
        start = last+1
        chunks << chunk
      end
      chunks
    end
    
    def transform # TODO
    end

    # Delete dataset
    def delete
      compounds.each{|c| c.dataset_ids.delete id.to_s}
      super
    end

  end

  # Dataset for lazar predictions
  class LazarPrediction #< Dataset
    field :creator, type: String
    field :prediction_feature_id, type: BSON::ObjectId
    field :predictions, type: Hash, default: {}

    # Get prediction feature
    # @return [OpenTox::Feature]
    def prediction_feature
      Feature.find prediction_feature_id
    end

    # Get all compounds
    # @return [Array<OpenTox::Compound>]
    def compounds
      substances.select{|s| s.is_a? Compound}
    end

    # Get all substances
    # @return [Array<OpenTox::Substance>]
    def substances
      predictions.keys.collect{|id| Substance.find id}
    end

  end

end