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module OpenTox
module Model
include OpenTox
# Run a model with parameters
# @param [Hash] params Parameters for OpenTox model
# @param [optional,OpenTox::Task] waiting_task (can be a OpenTox::Subtask as well), progress is updated accordingly
# @return [text/uri-list] Task or resource URI
def run( params, accept_header=nil, waiting_task=nil )
unless accept_header
if CONFIG[:yaml_hosts].include?(URI.parse(@uri).host)
accept_header = 'application/x-yaml'
else
accept_header = 'application/rdf+xml'
end
end
LOGGER.info "running model "+@uri.to_s+", params: "+params.inspect+", accept: "+accept_header.to_s
RestClientWrapper.post(@uri,params,{:accept => accept_header},waiting_task).to_s
end
# Generic OpenTox model class for all API compliant services
class Generic
include Model
# Find Generic Opentox Model via URI, and loads metadata, could raise NotFound/NotAuthorized error
# @param [String] uri Model URI
# @return [OpenTox::Model::Generic] Model instance
def self.find(uri,subjectid=nil)
return nil unless uri
model = Generic.new(uri)
model.load_metadata(subjectid)
raise "could not load model metadata '"+uri.to_s+"'" if model.metadata==nil or model.metadata.size==0
model
end
# provides feature type, possible types are "regression" or "classification"
# @return [String] feature type, "unknown" if type could not be estimated
def feature_type(subjectid=nil)
# dynamically perform restcalls if necessary
load_metadata(subjectid) if @metadata==nil or @metadata.size==0 or (@metadata.size==1 && @metadata.values[0]==@uri)
@algorithm = OpenTox::Algorithm::Generic.find(@metadata[OT.algorithm], subjectid) unless @algorithm
algorithm_title = @algorithm ? @algorithm.metadata[DC.title] : nil
@dependentVariable = OpenTox::Feature.find( @metadata[OT.dependentVariables],subjectid ) unless @dependentVariable
[@dependentVariable.feature_type, @metadata[OT.isA], @metadata[DC.title], @uri, algorithm_title].each do |type|
case type
when /(?i)classification/
return "classification"
when /(?i)regression/
return "regression"
end
end
raise "unknown model "+[@dependentVariable.feature_type, @metadata[OT.isA],
@metadata[DC.title], @uri, algorithm_title].inspect
end
end
# Lazy Structure Activity Relationship class
class Lazar
include Model
include Algorithm
attr_accessor :compound, :prediction_dataset, :features, :effects, :activities, :p_values, :fingerprints, :feature_calculation_algorithm, :similarity_algorithm, :prediction_algorithm, :min_sim, :subjectid
def initialize(uri=nil)
if uri
super uri
else
super CONFIG[:services]["opentox-model"]
end
@metadata[OT.algorithm] = File.join(CONFIG[:services]["opentox-algorithm"],"lazar")
@features = []
@effects = {}
@activities = {}
@p_values = {}
@fingerprints = {}
@feature_calculation_algorithm = "Substructure.match"
@similarity_algorithm = "Similarity.tanimoto"
@prediction_algorithm = "Neighbors.weighted_majority_vote"
@min_sim = 0.3
end
# Get URIs of all lazar models
# @return [Array] List of lazar model URIs
def self.all(subjectid=nil)
RestClientWrapper.get(CONFIG[:services]["opentox-model"], :subjectid => subjectid).to_s.split("\n")
end
# Find a lazar model
# @param [String] uri Model URI
# @return [OpenTox::Model::Lazar] lazar model
def self.find(uri, subjectid=nil)
YAML.load RestClientWrapper.get(uri,{:accept => 'application/x-yaml', :subjectid => subjectid})
end
# Create a new lazar model
# @param [optional,Hash] params Parameters for the lazar algorithm (OpenTox::Algorithm::Lazar)
# @return [OpenTox::Model::Lazar] lazar model
def self.create(params)
lazar_algorithm = OpenTox::Algorithm::Generic.new File.join( CONFIG[:services]["opentox-algorithm"],"lazar")
model_uri = lazar_algorithm.run(params)
OpenTox::Model::Lazar.find(model_uri, params[:subjectid])
end
# Get a parameter value
# @param [String] param Parameter name
# @return [String] Parameter value
def parameter(param)
@metadata[OT.parameters].collect{|p| p[OT.paramValue] if p[DC.title] == param}.compact.first
end
# Predict a dataset
# @param [String] dataset_uri Dataset URI
# @param [optional,subjectid]
# @param [optional,OpenTox::Task] waiting_task (can be a OpenTox::Subtask as well), progress is updated accordingly
# @return [OpenTox::Dataset] Dataset with predictions
def predict_dataset(dataset_uri, subjectid=nil, waiting_task=nil)
@prediction_dataset = Dataset.create(CONFIG[:services]["opentox-dataset"], subjectid)
@prediction_dataset.add_metadata({
OT.hasSource => @uri,
DC.creator => @uri,
DC.title => URI.decode(File.basename( @metadata[OT.dependentVariables] )),
OT.parameters => [{DC.title => "dataset_uri", OT.paramValue => dataset_uri}]
})
d = Dataset.new(dataset_uri,subjectid)
d.load_compounds(subjectid)
count = 0
d.compounds.each do |compound_uri|
begin
predict(compound_uri,false,subjectid)
count += 1
waiting_task.progress( count/d.compounds.size.to_f*100.0 ) if waiting_task
rescue => ex
LOGGER.warn "prediction for compound "+compound_uri.to_s+" failed: "+ex.message
end
end
@prediction_dataset.save(subjectid)
@prediction_dataset
end
# Predict a compound
# @param [String] compound_uri Compound URI
# @param [optinal,Boolean] verbose Verbose prediction (output includes neighbors and features)
# @return [OpenTox::Dataset] Dataset with prediction
def predict(compound_uri,verbose=false,subjectid=nil)
@compound = Compound.new compound_uri
features = {}
unless @prediction_dataset
#@prediction_dataset = cached_prediction
#return @prediction_dataset if cached_prediction
@prediction_dataset = Dataset.create(CONFIG[:services]["opentox-dataset"], subjectid)
@prediction_dataset.add_metadata( {
OT.hasSource => @uri,
DC.creator => @uri,
# TODO: fix dependentVariable
DC.title => URI.decode(File.basename( @metadata[OT.dependentVariables] )),
OT.parameters => [{DC.title => "compound_uri", OT.paramValue => compound_uri}]
} )
end
return @prediction_dataset if database_activity(subjectid)
neighbors
prediction = eval("#{@prediction_algorithm}(@neighbors,{:similarity_algorithm => @similarity_algorithm, :p_values => @p_values})")
prediction_feature_uri = File.join( @prediction_dataset.uri, "feature", "prediction", File.basename(@metadata[OT.dependentVariables]),@prediction_dataset.compounds.size.to_s)
# TODO: fix dependentVariable
@prediction_dataset.metadata[OT.dependentVariables] = prediction_feature_uri
if @neighbors.size == 0
@prediction_dataset.add_feature(prediction_feature_uri, {
OT.isA => OT.MeasuredFeature,
OT.hasSource => @uri,
DC.creator => @uri,
DC.title => URI.decode(File.basename( @metadata[OT.dependentVariables] )),
OT.error => "No similar compounds in training dataset.",
OT.parameters => [{DC.title => "compound_uri", OT.paramValue => compound_uri}]
})
@prediction_dataset.add @compound.uri, prediction_feature_uri, prediction[:prediction]
else
@prediction_dataset.add_feature(prediction_feature_uri, {
OT.isA => OT.ModelPrediction,
OT.hasSource => @uri,
DC.creator => @uri,
DC.title => URI.decode(File.basename( @metadata[OT.dependentVariables] )),
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, prediction[:prediction]
if verbose
if @feature_calculation_algorithm == "Substructure.match"
f = 0
@compound_features.each do |feature|
feature_uri = File.join( @prediction_dataset.uri, "feature", "descriptor", f.to_s)
features[feature] = feature_uri
@prediction_dataset.add_feature(feature_uri, {
OT.isA => OT.Substructure,
OT.smarts => feature,
OT.pValue => @p_values[feature],
OT.effect => @effects[feature]
})
@prediction_dataset.add @compound.uri, feature_uri, true
f+=1
end
else
@compound_features.each do |feature|
features[feature] = feature
@prediction_dataset.add @compound.uri, feature, true
end
end
n = 0
@neighbors.each do |neighbor|
neighbor_uri = File.join( @prediction_dataset.uri, "feature", "neighbor", n.to_s )
@prediction_dataset.add_feature(neighbor_uri, {
OT.compound => neighbor[:compound],
OT.similarity => neighbor[:similarity],
OT.measuredActivity => neighbor[:activity],
OT.isA => OT.Neighbor
})
@prediction_dataset.add @compound.uri, neighbor_uri, true
f = 0 unless f
neighbor[:features].each do |feature|
if @feature_calculation_algorithm == "Substructure.match"
feature_uri = File.join( @prediction_dataset.uri, "feature", "descriptor", f.to_s) unless feature_uri = features[feature]
else
feature_uri = feature
end
@prediction_dataset.add neighbor[:compound], feature_uri, true
unless features.has_key? feature
features[feature] = feature_uri
@prediction_dataset.add_feature(feature_uri, {
OT.isA => OT.Substructure,
OT.smarts => feature,
OT.pValue => @p_values[feature],
OT.effect => @effects[feature]
})
f+=1
end
end
n+=1
end
# what happens with dataset predictions?
end
end
@prediction_dataset.save(subjectid)
@prediction_dataset
end
# Find neighbors and store them as object variable
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
end
end
end
# Find database activities and store them in @prediction_dataset
# @return [Boolean] true if compound has databasse activities, false if not
def database_activity(subjectid)
if @activities[@compound.uri]
@activities[@compound.uri].each { |act| @prediction_dataset.add @compound.uri, @metadata[OT.dependentVariables], act }
@prediction_dataset.add_metadata(OT.hasSource => @metadata[OT.trainingDataset])
@prediction_dataset.save(subjectid)
true
else
false
end
end
# Save model at model service
def save(subjectid)
self.uri = RestClientWrapper.post(@uri,self.to_yaml,{:content_type => "application/x-yaml", :subjectid => subjectid})
end
# Delete model at model service
def delete(subjectid)
RestClientWrapper.delete(@uri, :subjectid => subjectid) unless @uri == CONFIG[:services]["opentox-model"]
end
end
end
end
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