# Get a list of all possible reports to prediction models
# @param [Header] Accept one of text/uri-list,
# @return [text/uri-list] list of all prediction models
get "/report/?" do
  models = Model::Validation.all
  case @accept
  when "text/uri-list"
    uri_list = models.collect{|model| uri("/report/#{model.model_id}")}
    return uri_list.join("\n") + "\n"
  when "application/json"
    models = JSON.parse models.to_json
    list = []
    models.each{|m| list << uri("/report/#{m["model_id"]["$oid"]}")}
    return list.to_json
  else
    bad_request_error "Mime type #{@accept} is not supported."
  end
end

get "/report/:id/?" do
  case @accept
  when "application/xml"
    model = Model::Lazar.find params[:id]
    not_found_error "Model with id: #{params[:id]} not found." unless model
    prediction_model = Model::Validation.find_by :model_id => params[:id]
    validation_template = File.join(File.dirname(__FILE__),"../views/model_details.haml")

    if File.directory?("#{File.dirname(__FILE__)}/../../lazar")
      lazar_commit = `cd #{File.dirname(__FILE__)}/../../lazar; git rev-parse HEAD`.strip
      lazar_commit = "https://github.com/opentox/lazar/tree/#{lazar_commit}"
    else
      lazar_commit = "https://github.com/opentox/lazar/releases/tag/v#{Gem.loaded_specs["lazar"].version}"
    end

    report = OpenTox::QMRFReport.new

    # QSAR Identifier Title 1.1
    report.value "QSAR_title", "Lazar model for #{prediction_model.species} #{prediction_model.endpoint}"

    # Software coding the model 1.3
    report.change_catalog :software_catalog, :firstsoftware, {:name => "lazar", :description => "lazar Lazy Structure- Activity Relationships", :number => "1", :url => "https://lazar.in-silico.ch", :contact => "info@in-silico.ch"}
    report.ref_catalog :QSAR_software, :software_catalog, :firstsoftware

    # Date of QMRF 2.1
    report.value "qmrf_date", "#{Time.now.strftime('%d %B %Y')}"

    # QMRF author(s) and contact details 2.1
    report.change_catalog :authors_catalog, :firstauthor, {:name => "Christoph Helma", :affiliation => "in silico toxicology gmbh", :contact => "Rastatterstr. 41, CH-4057 Basel", :email => "info@in-silico.ch", :number => "1", :url => "www.in-silico.ch"}
    report.ref_catalog :qmrf_authors, :authors_catalog, :firstauthor

    # Model developer(s) and contact details 2.5
    report.change_catalog :authors_catalog, :modelauthor, {:name => "Christoph Helma", :affiliation => "in silico toxicology gmbh", :contact => "Rastatterstr. 41, CH-4057 Basel", :email => "info@in-silico.ch", :number => "1", :url => "www.in-silico.ch"}
    report.ref_catalog :model_authors, :authors_catalog, :modelauthor

    # Date of model development and/or publication 2.6
    report.value "model_date", "#{Time.parse(model.created_at.to_s).strftime('%Y')}"

    # Reference(s) to main scientific papers and/or software package 2.7
    report.change_catalog :publications_catalog, :publications_catalog_1, {:title => "Maunz, Guetlein, Rautenberg, Vorgrimmler, Gebele and Helma (2013), lazar: a modular predictive toxicology framework  ", :url => "http://dx.doi.org/10.3389/fphar.2013.00038"}
    report.ref_catalog :references, :publications_catalog, :publications_catalog_1

    # Reference(s) to main scientific papers and/or software package 2.7
    report.change_catalog :publications_catalog, :publications_catalog_2, {:title => "Maunz A and Helma C (2008) Prediction of chemical toxicity with local support vector regression and activity-specific kernels. SAR & QSAR in Environmental Research 19 (5-6), 413-431", :url => "http://dx.doi.org/10.1080/10629360802358430"}
    report.ref_catalog :references, :publications_catalog, :publications_catalog_2

    # Species 3.1
    report.value "model_species", prediction_model.species 

    # Endpoint 3.2 
    report.change_catalog :endpoints_catalog, :endpoints_catalog_1, {:name => prediction_model.endpoint, :group => ""}
    report.ref_catalog :model_endpoint, :endpoints_catalog, :endpoints_catalog_1

    # Endpoint Units 3.4
    report.value "endpoint_units", "#{prediction_model.unit}"

    model_type = model.class.to_s.gsub('OpenTox::Model::Lazar','')

    # Type of model 4.1
    report.value "algorithm_type", "#{model_type}"

    # Explicit algorithm 4.2
    report.change_catalog :algorithms_catalog, :algorithms_catalog_1, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "Neighbor algorithm: #{model.algorithms["similarity"]["method"].gsub('_',' ').titleize}#{(model.algorithms["similarity"][:min] ? ' with similarity > ' + model.algorithms["similarity"][:min].to_s : '')}"}
    report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_1
    report.change_catalog :algorithms_catalog, :algorithms_catalog_3, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "modified k-nearest neighbor #{model_type}"}
    report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_3
    if model.algorithms["prediction"]
      pred_algorithm_params = (model.algorithms["prediction"][:method] == "rf" ? "random forest" : model.algorithms["prediction"][:method])
    end
    report.change_catalog :algorithms_catalog, :algorithms_catalog_2, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "Prediction algorithm: #{model.algorithms["prediction"].to_s.gsub('OpenTox::Algorithm::','').gsub('_',' ').gsub('.', ' with ')} #{(pred_algorithm_params ? pred_algorithm_params : '')}"}
    report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_2

    # Descriptors in the model 4.3
    if model.algorithms["descriptors"][:type]
      report.change_catalog :descriptors_catalog, :descriptors_catalog_1, {:description => "", :name => "#{model.algorithms["descriptors"][:type]}", :publication_ref => "", :units => ""}
      report.ref_catalog :algorithms_descriptors, :descriptors_catalog, :descriptors_catalog_1
    end

    # Descriptor selection 4.4
    report.value "descriptors_selection", "#{model.algorithms["feature_selection"].gsub('_',' ')} #{model.algorithms["feature_selection"].collect{|k,v| k.to_s + ': ' + v.to_s}.join(', ')}" if model.algorithms["feature_selection"]
    
    # Algorithm and descriptor generation 4.5
    report.value "descriptors_generation", "exhaustive breadth first search for paths in chemical graphs (simplified MolFea algorithm)"
    
    # Software name and version for descriptor generation 4.6
    report.change_catalog :software_catalog, :software_catalog_2, {:name => "lazar, submitted version: #{lazar_commit}", :description => "simplified MolFea algorithm", :number => "2", :url => "https://lazar.in-silico.ch", :contact => "info@in-silico.ch"}
    report.ref_catalog :descriptors_generation_software, :software_catalog, :software_catalog_2

    # Chemicals/Descriptors ratio 4.7
    report.value "descriptors_chemicals_ratio", "not applicable (classification based on activities of neighbors, descriptors are used for similarity calculation)"

    # Description of the applicability domain of the model 5.1
    report.value "app_domain_description", "<html><head></head><body>
        <p>
          The applicability domain (AD) of the training set is characterized by 
          the confidence index of a prediction (high confidence index: close to 
          the applicability domain of the training set/reliable prediction, low 
          confidence: far from the applicability domain of the 
          trainingset/unreliable prediction). The confidence index considers (i) 
          the similarity and number of neighbors and (ii) contradictory examples 
          within the neighbors. A formal definition can be found in Helma 2006.
        </p>
        <p>
          The reliability of predictions decreases gradually with increasing 
          distance from the applicability domain (i.e. decreasing confidence index)
        </p>
      </body>
    </html>"

    # Method used to assess the applicability domain 5.2
    report.value "app_domain_method", "see Helma 2006 and Maunz 2008"
    
    # Software name and version for applicability domain assessment 5.3  
    report.change_catalog :software_catalog, :software_catalog_3, {:name => "lazar, submitted version: #{lazar_commit}", :description => "integrated into main lazar algorithm", :number => "3", :url => "https://lazar.in-silico.ch", :contact => "info@in-silico.ch"}
    report.ref_catalog :app_domain_software, :software_catalog, :software_catalog_3

    # Limits of applicability 5.4
    report.value "applicability_limits", "Predictions with low confidence index, unknown substructures and neighbors that might act by different mechanisms"

    # Availability of the training set 6.1
    report.change_attributes "training_set_availability", {:answer => "Yes"}

    # Available information for the training set 6.2
    report.change_attributes "training_set_data", {:cas => "Yes", :chemname => "Yes", :formula => "Yes", :inchi => "Yes", :mol => "Yes", :smiles => "Yes"}

    # Data for each descriptor variable for the training set 6.3
    report.change_attributes "training_set_descriptors", {:answer => "No"}

    # Data for the dependent variable for the training set 6.4
    report.change_attributes "dependent_var_availability", {:answer => "All"}

    # Other information about the training set 6.5
    report.value "other_info", "#{prediction_model.source}"

    # Pre-processing of data before modelling 6.6
    report.value "preprocessing", (model.class == OpenTox::Model::LazarRegression ? "-log10 transformation" : "none")

    # Robustness - Statistics obtained by leave-many-out cross-validation 6.9
    if prediction_model.repeated_crossvalidation
      crossvalidations = prediction_model.crossvalidations
      out = haml File.read(validation_template), :layout=> false, :locals => {:model => prediction_model}
      report.value "lmo",  out
    end

    # Mechanistic basis of the model 8.1
    report.value "mechanistic_basis","<html><head></head><body>
      <p>
        Compounds with similar structures (neighbors) are assumed to have 
        similar activities as the query compound. For the determination of 
        activity specific similarities only statistically relevant subtructures 
        (paths) are used. For this reason there is a priori no bias towards 
        specific mechanistic hypothesis.
      </p>
    </body>
  </html>"

    # A priori or a posteriori mechanistic interpretation 8.2
    report.value "mechanistic_basis_comments","a posteriori for individual predictions"

    # Other information about the mechanistic interpretation 8.3
    report.value "mechanistic_basis_info","<html><head></head><body><p>Hypothesis about biochemical mechanisms can be derived from individual 
        predictions by inspecting neighbors and relevant fragments.</p>
        <p>Neighbors are compounds that are similar in respect to a certain 
        endpoint and it is likely that compounds with high similarity act by 
        similar mechanisms as the query compound. Links at the webinterface 
        prove an easy access to additional experimental data and literature 
        citations for the neighbors and the query structure.</p>
        <p>Activating and deactivating parts of the query compound are highlighted 
        in red and green on the webinterface. Fragments that are unknown (or too 
        infrequent for statistical evaluation are marked in yellow and 
        additional statistical information about the individual fragments can be 
        retrieved. Please note that lazar predictions are based on neighbors and 
        not on fragments. Fragments and their statistical significance are used 
        for the calculation of activity specific similarities.</p>"

    # Bibliography 9.2
    report.ref_catalog :bibliography, :publications_catalog, :publications_catalog_1
    report.ref_catalog :bibliography, :publications_catalog, :publications_catalog_2
    report.change_catalog :publications_catalog, :publications_catalog_3, {:title => "Helma (2006), Lazy structure-activity relationships (lazar) for the prediction of rodent carcinogenicity and Salmonella mutagenicity.", :url => "http://dx.doi.org/10.1007/s11030-005-9001-5"}
    report.ref_catalog :bibliography, :publications_catalog, :publications_catalog_3

    # output
    response['Content-Type'] = "application/xml"
    return report.to_xml
  else
    bad_request_error "Mime type #{@accept} is not supported."
  end

end