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helpers do
def embedded_svg image, options={}
doc = Nokogiri::HTML::DocumentFragment.parse image
svg = doc.at_css 'svg'
title = doc.at_css 'title'
if options[:class].present?
svg['class'] = options[:class]
end
if options[:title].present?
title.children.remove
text_node = Nokogiri::XML::Text.new(options[:title], doc)
title.add_child(text_node)
end
doc.to_html.html_safe
end
def prediction_to_csv(m,c,p)
#model = Model::Validation.find(m.to_s)
model = m
model_name = "#{model.endpoint.gsub('_', ' ')} (#{model.species})"
model_unit = model.regression? ? "(#{model.unit})" : ""
converted_model_unit = model.regression? ? "#{model.unit =~ /\b(mmol\/L)\b/ ? "(mg/L)" : "(mg/kg_bw/day)"}" : ""
#predictions = predictions_ids.collect{|prediction_id| Prediction.find prediction_id}
csv = ""
compound = c#Compound.find prediction_object.compound
prediction = p#prediction_object.prediction
#prediction.delete_if{|k,v| k =~ /neighbors|prediction_feature_id/}
output = {}
line = ""
output["model_name"] = model_name
output["model_unit"] = model_unit
output["converted_model_unit"] = converted_model_unit
if prediction[:value]
inApp = (prediction[:warnings].join(" ") =~ /Cannot/ ? "no" : (prediction[:warnings].join(" ") =~ /may|Insufficient/ ? "maybe" : "yes"))
if prediction[:info] =~ /\b(identical)\b/i
prediction[:info] = "This compound was part of the training dataset. All information "\
"from this compound was removed from the training data before the "\
"prediction to obtain unbiased results."
end
note = "\"#{prediction[:warnings].uniq.join(" ")}\""
output["prediction_value"] = model.regression? ? "#{prediction[:value].delog10.signif(3)}" : "#{prediction[:value]}"
output["converted_value"] = model.regression? ? "#{compound.mmol_to_mg(prediction[:value].delog10).signif(3)}" : nil
if prediction[:measurements].is_a?(Array)
output["measurements"] = model.regression? ? prediction[:measurements].collect{|value| "#{value.delog10.signif(3)}"} : prediction[:measurements].collect{|value| "#{value}"}
output["converted_measurements"] = model.regression? ? prediction[:measurements].collect{|value| "#{compound.mmol_to_mg(value.delog10).signif(3)}"} : false
else
output["measurements"] = model.regression? ? "#{prediction[:measurements].delog10.signif(3)}" : "#{prediction[:measurements]}"
output["converted_measurements"] = model.regression? ? "#{compound.mmol_to_mg(prediction[:measurements].delog10).signif(3)}" : false
end #db_hit
if model.regression?
if !prediction[:prediction_interval].blank?
interval = prediction[:prediction_interval]
output['interval'] = []
output['converted_interval'] = []
output['interval'] << interval[1].delog10.signif(3)
output['interval'] << interval[0].delog10.signif(3)
output['converted_interval'] << compound.mmol_to_mg(interval[1].delog10).signif(3)
output['converted_interval'] << compound.mmol_to_mg(interval[0].delog10).signif(3)
end #prediction interval
line += "#{output['model_name']},#{compound.smiles},"\
"\"#{prediction[:info] ? prediction[:info] : "no"}\",\"#{output['measurements'].join("; ") if prediction[:info]}\","\
"#{!output['prediction_value'].blank? ? output['prediction_value'] : ""},"\
"#{!output['converted_value'].blank? ? output['converted_value'] : ""},"\
"#{!prediction[:prediction_interval].blank? ? output['interval'].first : ""},"\
"#{!prediction[:prediction_interval].blank? ? output['interval'].last : ""},"\
"#{!prediction[:prediction_interval].blank? ? output['converted_interval'].first : ""},"\
"#{!prediction[:prediction_interval].blank? ? output['converted_interval'].last : ""},"\
"#{inApp},#{note.nil? ? "" : note.chomp}\n"
else # Classification
if !prediction[:probabilities].blank?
output['probabilities'] = []
prediction[:probabilities].each{|k,v| output['probabilities'] << v.signif(3)}
end
line += "Consensus mutagenicity,#{compound.smiles},"\
"\"#{prediction[:info] ? prediction[:info] : "no"}\",\"#{output['measurements'].join("; ") if prediction[:info]}\","\
"#{prediction['Consensus prediction']},"\
"#{prediction['Consensus confidence']},"\
"#{prediction['Structural alerts for mutagenicity']},"\
"#{output['prediction_value']},"\
"#{!prediction[:probabilities].blank? ? output['probabilities'].first : ""},"\
"#{!prediction[:probabilities].blank? ? output['probabilities'].last : ""},"\
"#{inApp},#{note.nil? ? "" : note}\n"
end
output['warnings'] = prediction[:warnings] if prediction[:warnings]
else #no prediction value
inApp = "no"
if prediction[:info] =~ /\b(identical)\b/i
prediction[:info] = "This compound was part of the training dataset. All information "\
"from this compound was removed from the training data before the "\
"prediction to obtain unbiased results."
end
note = "\"#{prediction[:warnings].join(" ")}\""
output['warnings'] = prediction[:warnings]
output['info'] = prediction[:info] if prediction[:info]
if model.regression?
line += "#{output['model_name']},#{compound.smiles},#{prediction[:info] ? prediction[:info] : "no"},"\
"#{prediction[:measurements].collect{|m| m.delog10.signif(3)}.join("; ") if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
else
line += "Consensus mutagenicity,#{compound.smiles},#{prediction[:info] ? prediction[:info] : "no"},"\
"#{prediction[:measurements].join("; ") if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
end
end
csv += line
# output
csv
end
end
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