'
@therapy_choices.each_with_index do |choice,i|
tmp_table += ''
@table_head.each_with_index do |head,index|
tmp_table += ('| ' + ((index == 0) ? (((i==0)? '' : '+') + choice) : '-') + ' | ')
end
tmp_table += '
'
end
tmp_table_translations[locale] = tmp_table
@texts = self.text_above_texts[locale].to_s.gsub('
','
').gsub('{{Surgery_only}}','')
@texts = @texts.split('{{years}}')
@texts.delete('')
tmp_text = "#{I18n.t("cancerpredict.table.text")}"
tmp_text += (''+@texts[0].to_s)
@years.each{|year| tmp_text += ('')}
if @texts.count > 1
tmp_text += (@texts[1]+'') if @texts.count > 1
else
tmp_text += ''
end
if !self.surgery_only_texts[locale].blank?
@surgery_only_texts = self.surgery_only_texts[locale]
@surgery_only_texts.insert(0,'')
@surgery_only_texts = @surgery_only_texts.gsub('{{Surgery_only}}','')
@surgery_only_texts = @surgery_only_texts.gsub('{{surgery_year}}',''+@years[-1].to_s+'')
@surgery_only_texts += ''
else
@surgery_only_texts = ''
end
tmp_text += @surgery_only_texts
tmp_text += ''+(self.extra_texts[locale].to_s rescue '')+'
'
tmp_text_translations[locale] = tmp_text
end
end
self.result_table_translations = tmp_table_translations
self.result_text_translations = tmp_text_translations
self.treatment_method_active_indices = [1]
self.form_show_in_result.each do |num, property|
v = property[:active_choice]
if v.present?
self.treatment_method_active_indices << (v - 1)
else
self.treatment_method_active_indices << 1
end
end
self.lpv_calc = get_years_settings_dict
self.generate_eval_formula
end
def reload_any_asset(path, type=nil, force_reload=false)
env = Rails.application.assets
new_env = Sprockets::Environment.new(Rails.root.to_s) do |env|
env.version = ::Rails.env
tmp_path = "#{Rails.application.config.root}/tmp/cache/assets/#{::Rails.env}"
env.cache = ::Sprockets::Cache::FileStore.new(tmp_path)
env.context_class.class_eval do
include ::Sprockets::Rails::Helper
end
end
new_env.config = env.config
stats = env.cached.instance_variable_get(:@stats)
new_path = path.sub(/\.erb$/,'')
if force_reload || (stats && stats[path]) #Need reload asset
if type.nil?
ext = File.extname(new_path)
env.mime_types.each do |t, h|
if h[:extensions].include?(ext)
type = t
break
end
end
end
if type
full_path = 'file://'+path+'?type='+type
uris = env.cached.instance_variable_get(:@uris)
keys = uris.keys.select{|k| k.include?(full_path)}
asset = new_env.load(full_path)
if keys.count != 0
keys.each do |k|
uris[k] = asset
end
end
new_path = new_path.sub(/\.[^.]+$/){|ext| '-' + asset.digest + ext}
File.binwrite(new_path, asset.to_s)
yield new_path if block_given?
end
end
end
def reload_js_asset(path, force_reload=false)
reload_any_asset(path, 'application/javascript', force_reload) do |new_path|
File.open("#{Rails.root}/public/cancer_tool_js_filename.txt",'w+'){|f| f.write(new_path)}
end
end
def generate_eval_formula
eval_hidden_variables = "def eval_hidden_variables(result); #{self.tmp_hidden_variables_for_ruby}; end"
CancerpredictsController.module_eval(eval_hidden_variables)
eval_formula = "def eval_formula(result); #{self.tmp_lpv_ruby_code}; end"
CancerpredictsController.module_eval(eval_formula)
end
def generate_jscode
js_code = "var map_values , mapping_hash , temp_index ,temp_value , index , closest_value;\r\n"
mapping_data_from_csv = JSON.parse(self.mapping_data_from_csv) rescue {}
tmp_hash = self.form_show.values + self.form_show_in_result.values
tmp_hash.each do |property|
@variable = property[:variable]
if @variable.present?
if property[:is_num] == 1
js_code += " result['#{@variable}'] = Number(result_json['#{@variable}']);\r\n"
elsif property[:choice_fields].present?
if !(self.advance_mode)
js_code += " result['#{@variable}'] = Number(result_json['#{@variable}']);\r\n"
else
if property[:need_map_values] == 1
js_code += " map_values = #{property[:map_values]};\r\n"
js_code += " result['#{@variable}'] = map_values[Number(result_json['#{@variable}'']) - 1];\r\n"
else
if property[:revert_value] != 1
js_code += " result['#{@variable}'] = Number(result_json['#{@variable}']) - 1;\r\n"
else
js_code += " result['#{@variable}'] = (#{property[:choice_fields].length} - Number(result_json['#{@variable}']));\r\n"
end
end
end
end
if self.advance_mode && property[:cancer_predict_mapping_file].present?
if (mapping_data_from_csv != {} && !mapping_data_from_csv[@variable].blank?)
js_code += " mapping_hash = mapping_data_from_csv['#{@variable}'];\r\n"
js_code += " temp_index = 0;\r\n"
js_code += " temp_value = result['#{@variable}'];\r\n"
js_code += " index = 0;
$.each(mapping_hash,function(k,v){
if( index == 0 ){
var index_val = v.indexOf(temp_value);
if( index_val != -1 ){
temp_index = index_val;
}else{
closest_value = v.get_nearest_value(temp_value);
temp_index = v.indexOf(closest_value)
}
}
result[k] = v[temp_index];
index++;
});\r\n"
end
end
end
end
js_code += "\n Object.keys(result).forEach(function(k){
if(Number.isNaN(result[k])){
result[k] = 0;
}
})"
js_code += "\n #{self.tmp_hidden_variables_for_js}"
formula = text_to_math(self.prediction_formula)
self.all_variables.each do |k|
formula = formula.gsub(/(\A|[^\w])#{k}($|[^\w])/){|f| "#{$1}result[\"#{k.strip}\"]#{$2}" }
end
formula_variables = self.tmp_lpv_variables.map{|v| v}
js_code = "\n function calculate_first_lpv(result_json){
result = {};
#{js_code}
try{
#{formula.gsub(/\s{2,10}/," ").gsub("\n","\n ")}
}catch(e){console.log(e)};
result['lpv_variable'] = {};
#{formula_variables.map{|v| "result['lpv_variable']['#{v}'] = #{v};"}.join("\n ") }
result['lpv'] = #{formula_variables.count == 0 ? 0 : formula_variables.last};
result['lpv_variable']['lpv'] = result['lpv'];
return result;
};
function calculate_and_change_result_value(obj){
obj.servive_ratio_arr = [];
for(var i = 0;i