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require 'csv'
require 'tempfile'
module OpenTox
# Collection of substances and features
class Dataset
field :data_entries, type: Hash, default: {}
# 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
# Dataset operations
# 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
# 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
# Parsers
# Create a dataset from file (csv,sdf,...)
# @param filename [String]
# @return [String] dataset uri
# TODO
#def self.from_sdf_file
#end
# Create a dataset from CSV file
# @param [File]
# @param [TrueClass,FalseClass] accept or reject empty values
# @return [OpenTox::Dataset]
def self.from_csv_file file, accept_empty_values=false
source = file
name = File.basename(file,".*")
dataset = self.find_by(:source => source, :name => name)
if dataset
$logger.debug "Skipping import of #{file}, it is already in the database (id: #{dataset.id})."
else
$logger.debug "Parsing #{file}."
table = CSV.read file, :skip_blanks => true, :encoding => 'windows-1251:utf-8'
dataset = self.new(:source => source, :name => name)
dataset.parse_table table, accept_empty_values
end
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>]
# @param [TrueClass,FalseClass] accept or reject empty values
def parse_table table, accept_empty_values
# features
feature_names = table.shift.collect{|f| f.strip}
warnings << "Duplicated features in table header." unless feature_names.size == feature_names.uniq.size
compound_format = feature_names.shift.strip
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
feature_names.each_with_index do |f,i|
metadata = {:name => f}
values = table.collect{|row| val=row[i+1].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
feature = NumericFeature.find_or_create_by(metadata)
else
metadata["accept_values"] = values
numeric[i] = false
feature = NominalFeature.find_or_create_by(metadata)
end
features << feature if feature
end
# substances and values
all_substances = []
table.each_with_index do |vals,i|
identifier = vals.shift.strip
warn "No feature values for compound at line #{i+2} of #{source}." if vals.compact.empty? and !accept_empty_values
begin
case compound_format
when /SMILES/i
substance = OpenTox::Compound.from_smiles(identifier)
when /InChI/i
substance = OpenTox::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
unless vals.size == features.size
warn "Number of values at position #{i+2} is different than header size (#{vals.size} vs. #{features.size}), all entries are ignored."
next
end
vals.each_with_index do |v,j|
if v.blank?
warn "Empty value for compound '#{identifier}' and feature '#{feature_names[i]}'."
next
elsif numeric[j]
v = v.to_f
else
v = v.strip
end
add substance, features[j], v
end
data_entries[substance.id.to_s] = {} if vals.empty? and accept_empty_values
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
# 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
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