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module OpenTox
class Validation
include OpenTox
attr_accessor :report_uri, :qmrf_report_uri
def self.create_crossvalidation(params)
params[:uri] = File.join(CONFIG[:services]['opentox-validation'], "crossvalidation")
params[:num_folds] = 10 unless params[:num_folds]
params[:random_seed] = 2 unless params[:random_seed]
params[:stratified] = false unless params[:stratified]
uri = OpenTox::RestClientWrapper.post(File.join(CONFIG[:services]["opentox-validation"],"/crossvalidation"),params,nil,false)
OpenTox::Validation.new(uri)
end
def create_report(subjectid=nil)
@report_uri = OpenTox::RestClientWrapper.post(File.join(CONFIG[:services]["opentox-validation"],"/report/crossvalidation"), {:validation_uris => @uri, :subjectid => subjectid}).to_s
@report_uri
end
def create_qmrf_report(subjectid=nil)
@qmrf_report_uri = OpenTox::RestClientWrapper.post(File.join(CONFIG[:services]["opentox-validation"],"/reach_report/qmrf"), {:model_uri => @uri, :subjectid => subjectid}).to_s
@qmrf_report_uri
end
def summary(type, subjectid=nil)
v = YAML.load OpenTox::RestClientWrapper.get(File.join(@uri, 'statistics'),{:accept => "application/x-yaml", :subjectid => subjectid}).to_s
case type
when "classification"
tp=0; tn=0; fp=0; fn=0; n=0
v[:classification_statistics][:confusion_matrix][:confusion_matrix_cell].each do |cell|
if cell[:confusion_matrix_predicted] == "true" and cell[:confusion_matrix_actual] == "true"
tp = cell[:confusion_matrix_value]
n += tp
elsif cell[:confusion_matrix_predicted] == "false" and cell[:confusion_matrix_actual] == "false"
tn = cell[:confusion_matrix_value]
n += tn
elsif cell[:confusion_matrix_predicted] == "false" and cell[:confusion_matrix_actual] == "true"
fn = cell[:confusion_matrix_value]
n += fn
elsif cell[:confusion_matrix_predicted] == "true" and cell[:confusion_matrix_actual] == "false"
fp = cell[:confusion_matrix_value]
n += fp
end
end
{
:nr_predictions => n,
:true_positives => tp,
:false_positives => fp,
:true_negatives => tn,
:false_negatives => fn,
:correct_predictions => 100*(tp+tn).to_f/n,
:weighted_area_under_roc => v[:classification_statistics][:weighted_area_under_roc].to_f,
:sensitivity => tp.to_f/(tp+fn),
:specificity => tn.to_f/(tn+fp),
}
when "regression"
{
:nr_predictions => v[:num_instances] - v[:num_unpredicted],
:r_square => v[:regression_statistics][:r_square],
:root_mean_squared_error => v[:regression_statistics][:root_mean_squared_error],
:mean_absolute_error => v[:regression_statistics][:mean_absolute_error],
}
end
end
end
end
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