423 lines
26 KiB
Ruby
423 lines
26 KiB
Ruby
class Coloncancerpredictfields1s
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require "pathname"
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require 'json'
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include Mongoid::Document
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include Mongoid::Timestamps
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Field_relations = {"number_field"=>"Fixnum","text_area"=>"String"}
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FIELDINFO = {"variable"=>"String","name"=>"String","is_num"=>"Fixnum","hint"=>"String","comment_text"=>"String","choice_fields"=>"Array","range"=>"Array","right"=>"Fixnum","is_float"=>"Fixnum","revert_value"=>"Fixnum","map_values"=>"Array","coloncancer_predict_mapping_file1"=>"String","lpv_impact"=>"Float","active_choice"=>"number_field","disable_condition"=>"text_area"}
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NonLoclaized = ["variable","is_num","range","right","is_float","revert_value","map_values","coloncancer_predict_mapping_file1","lpv_impact","active_choice","disable_condition"]
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AdvanceFields = ["revert_value","map_values","coloncancer_predict_mapping_file1"]
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TherapyFields = ["variable","name","hint","comment_text","choice_fields","lpv_impact","active_choice","disable_condition"]
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TherapyOnly = ["lpv_impact","active_choice","disable_condition"]
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field :title ,type:String ,default:""
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field :advance_mode, type: Boolean, default: false
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field :form_show , :type=> Hash ,default: {
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"0"=>{"variable"=>"age", "name"=>{"zh_tw"=>"年齡<br/>(Age)", "en"=>"Age"}, "is_num"=>1, "hint"=>{"zh_tw"=>"從 20 歲(含)開始至 80 歲 (含)以下", "en"=>"Age must be between 18 and 93"}, "comment_text"=>{"zh_tw"=>"年齡為該病人於確診罹患大 腸癌時之年齡", "en"=>"Age at diagnosis"}, "choice_fields"=>{"zh_tw"=>[], "en"=>[]}, "range"=>[20, 80], "right"=>0, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
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"1"=>{"variable"=>"size", "name"=>{"zh_tw"=>"腫瘤 大小(單位:mm)<br/>(Tumor size)", "en"=>"Tumor size"}, "is_num"=>1, "hint"=>{"zh_tw"=>"", "en"=>"The unit of tumor size is millimeter (mm)"}, "comment_text"=>{"zh_tw"=>"若有多個原發腫瘤，請輸入最大尺寸之原發腫瘤、上限為 100mm", "en"=>"If there was more than one primary tumor, please enter the size of the largest one."}, "choice_fields"=>{"zh_tw"=>[], "en"=>[]}, "range"=>[1, 100], "right"=>1, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
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"2"=>{"variable"=>"lymph_nodes_examined", "name"=>{"zh_tw"=>"區域淋巴結檢查數目<br/>(Regional lymph nodes examined)", "en"=>"Regional lymph nodes examined"}, "is_num"=>1, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["未知"], "en"=>["unknown"]}, "range"=>[0, 90], "right"=>0, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
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"3"=>{"variable"=>"lymph_nodes_positive", "name"=>{"zh_tw"=>"區域淋巴結侵犯數目<br/>(Regional lymph nodes positive)", "en"=>"Regional lymph nodes positive"}, "is_num"=>1, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"此變項為預測重要變數，若無此資訊預測容易失真。", "en"=>"Regional lymph nodes positive is a key predictive variable. If this information is omitted, the prediction result would be biased."}, "choice_fields"=>{"zh_tw"=>["未知"], "en"=>["unknown"]}, "range"=>[0, 90], "right"=>1, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
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"4"=>{"variable"=>"grade", "name"=>{"zh_tw"=>"腫瘤級數<br/>(Tumor grade)", "en"=>"Tumor grade"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"腫瘤級數代表腫瘤組織與正常組織間的分化程度，若無分 化級數資訊，請選 擇“未知”選項，將以級數 1 進行預測。", "en"=>"The grade refers to how different the cancer cells are from normal cells. Please select “unknown” if there is no information about grade. The prediction model would use “grade 2” as the alternative variable."}, "choice_fields"=>{"zh_tw"=>["1", "2", "3", "未知"], "en"=>["1", "2", "3", "unknown"]}, "range"=>[], "right"=>0, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
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"5"=>{"variable"=>"pstage", "name"=>{"zh_tw"=>"病理分期<br/>(pathologic stage)", "en"=>"Pathologic stage"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"若無分期資訊，請選擇“未知”選項，將以病理分期第 1 期進行預測。", "en"=>"ER status describes the status of estrogen receptor. Please select “unknown” if there is no information about ER status. The prediction model would use “Positive” (the majority class) as the alternative variable."}, "choice_fields"=>{"zh_tw"=>["1", "2", "3", "4", "未知"], "en"=>["positive", "negative", "unknown"]}, "range"=>[], "right"=>1, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]}
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}
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field :form_show_in_result , :type=> Hash ,default: {
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"0"=>{"variable"=>"Chemotherapy", "name"=>{"zh_tw"=>"化學治療", "en"=>"Chemotherapy"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["否", "是"], "en"=>["No", "Yes"]}, "lpv_impact"=>-0.6693, "active_choice"=>2, "disable_condition"=>""}
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}
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field :form_result_is_right , :type=> Integer ,default: 0
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field :text_descibe ,type:Hash ,default: {
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"zh_tw"=>"歡迎使用台灣準備大腸癌預後系統！<br />\r\n本預測系統由台灣癌症登記資料庫2007至2015年間共20,218位大腸癌病 人與經<br />\r\n驗證美國流行病學癌症資料庫22,670位病人所建立 。<br />\r\n若要開始 請在下方選擇相關資訊",
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"en"=>"Welcome to the Taiwan Breast Cancer Prediction System!<br />\r\nThe prediction system is constructed using clinical data from 90,841 breast cancer patients in the Taiwan Cancer Registry database between 2011 to 2015, and validated using clinical data from 49,374 breast cancer patients in the U.S.-based Surveillance, Epidemiology and End Results (SEER) database.<br />\r\nTo start, please select the information below."
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}
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field :small ,type:Hash ,default:{'font_size'=>"0.825em",'active'=>0}
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field :medium ,type:Hash ,default:{'font_size'=>"1em",'active'=>1}
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field :large ,type:Hash ,default:{'font_size'=>"1.25em",'active'=>0}
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field :head_images_id ,type:Array , default: []
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field :title_images_id ,type:Array , default: []
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field :title_texts ,type:Hash ,default: {"zh_tw"=>"大腸癌線上預測工具", "en"=>"Asian breast cancer prediction"}
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field :table_above_texts ,type:Hash ,default: {"zh_tw"=>"下表之分析為針對手術後病人，根據選定的術後治療，分別估計在第1年、3 及5年的存活率。", "en"=>"The analysis is for women who had undergone surgery.The table shows the 1-, 3- and 5-year survival rates,based on the treatment you have selected."}
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field :text_above_texts ,type:Hash ,default: {"zh_tw"=>"此研究分析來自已接受根除性手術後之婦女所得之結果，根據您所輸入的資訊以及治療方式，在術後<br/>第{{years}}年，", "en"=>"The analysis is for women who had undergone surgery. Base on the information and the treatment you have selected, the predictions of survival status<br/>{{years}}"}
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field :surgery_only_texts ,type:Hash ,default: {"zh_tw"=>"100 位只接受根除性手術的婦女中，有{{Surgery_only}}位婦女，術後{{surgery_year}}年仍為存活", "en"=>"after surgery are as follows:<br/>{{Surgery_only}} out of 100 women treated with surgery only are alive at {{surgery_year}} years."}
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field :extra_texts ,type:Hash ,default: {"zh_tw"=>"，此外", "en"=>""}
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field :extra_therapy_texts ,type:Hash ,default: {"zh_tw"=>"100 位在術後有接受{{extra_therapy}}的婦女中，有{{survival_num}}位婦女，術後{{surgery_year}}年仍為存活(多了{{Additional_Benefit}}位)", "en"=>"{{survival_num}} out of 100 women treated with {{extra_therapy}} are alive (an extra {{Additional_Benefit}})"}
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field :danger_texts ,type:Hash ,default: {"zh_tw"=>"請注意紅框的輸入資料是否符合要求!", "en"=>"Please check whether input data in red blocks are correct!"}
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field :years ,type:Array ,default:[1,3,5]
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field :texts_between_Result_and_result_block ,type:Hash ,default: {"zh_tw"=>"如果欲將預測結果應用於臨床上，請務必與您的主治醫師討論後再做最後決定。", "en"=>"Please note that the patients need to consult with their medical doctors before making any decision."}
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#field :image_uploader ,type:Object
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field :prediction_formula , type: String ,default: "lpv = ((age - 62.31261) * (0.01385)+ (size - 45.85882)* (0.00786) + (nposit - 0.109264)* (1.83191) +
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grade_2*0.29793+grade_3*0.67389+pstage_2*1.1152+
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pstage_3*2.2501+pstage_4*3.6206+chemo*(-0.6693)
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)"
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field :years_settings , type: Array , default: ["exp(-0.005433642)^exp(lpv)", "exp(-0.02357545)^exp(lpv)", "exp(-0.03637668)^exp(lpv)"]
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field :tmp_years_settings , type: Array , default: []
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field :tmp_years_settings_for_ruby , type: Array , default: []
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field :hidden_variables, type: String, default: "ratio = (lymph_nodes_examined == 0 ? 0 : (1.0 * lymph_nodes_positive / lymph_nodes_examined))
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ratio = (ratio > 1 ? 1 : ratio)
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nposit = ((ratio + 0.1) / 0.1) ^ 0.5
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grade_1 = (grade == 1 || grade == 4) ? 1 : 0
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grade_2 = (grade == 2) ? 1 : 0
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grade_3 = (grade == 3) ? 1 : 0
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pstage_2 = (pstage == 2) ? 1 : 0
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pstage_3 = (pstage == 3) ? 1 : 0
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pstage_4 = (pstage == 4) ? 1 : 0
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chemo = (Chemotherapy == 2) ? 1 : 0
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"
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field :fix_hidden_variables, type: Array, default: []
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field :tmp_hidden_variables_for_ruby, type: String, default: ""
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field :tmp_hidden_variables_for_js, type: String, default: ""
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field :lpv_calc, type: Hash, default: {} #for js code
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field :tmp_lpv_ruby_code, type: String, default: ""
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field :tmp_lpv_variables, type: Array, default: []
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field :mapping_data_from_csv , type: String ,default: ""
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field :all_variables, type: Array, default: []
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field :treatment_method, type: Array, default: ['Surgery_only']
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field :treatment_method_active_indices, type: Array, default: [1]
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field :result_table, type: String, default: "", localize: true
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field :result_text, type: String, default: "", localize: true
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field :therapy_lpv, type: Array, default: [0]
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#before_create :set_expire
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before_save do
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self.form_show.each do |num,property|
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property[:need_map_values] = (property[:map_values].class == Array && property[:choice_fields].class == Array && property[:map_values].length == property[:choice_fields].length) ? 1 : 0
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end
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result_keys = []
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self.form_show.each do |num,property|
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variable_name = property[:variable]
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if variable_name.present?
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result_keys << variable_name
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end
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end
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self.form_show_in_result.each do |num,property|
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variable_name = property[:variable]
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if variable_name.present?
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result_keys << variable_name
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end
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end
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mapping_data = JSON.parse(self.mapping_data_from_csv) rescue {}
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if self.advance_mode && mapping_data.present?
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mapping_data.each do |k,v|
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result_keys += (v.keys rescue [])
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end
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end
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result_keys = result_keys.uniq
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self.all_variables = result_keys
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formula = text_to_math(self.prediction_formula)
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tmp_hidden_variables = text_to_math(self.hidden_variables)
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result_keys.each do |k|
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formula = formula.gsub(/(\A|[^\w])#{k}($|[^\w])/){|f| "#{$1}result[\"#{k.strip}\"]#{$2}" }
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tmp_hidden_variables = tmp_hidden_variables.gsub(/(\A|[^\w])#{k}($|[^\w])/){|f| "#{$1}result[\"#{k.strip}\"]#{$2}" }
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end
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self.tmp_hidden_variables_for_js = tmp_hidden_variables.rstrip.gsub(/\n\s+/,"\n ").gsub("\n",";\n") + ";"
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self.fix_hidden_variables = []
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self.tmp_hidden_variables_for_ruby = tmp_hidden_variables.split(/^([^=!]+)=([^=!])/).select{|s| s.present?}.each_slice(2).map do |a,b|
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a = a.strip
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self.fix_hidden_variables << a
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if b
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("result[\"#{a}\"]=" + b.gsub("\n",""))
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else
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a
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end
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end.join("\n")
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self.fix_hidden_variables = self.fix_hidden_variables.uniq
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formula = formula.split(/^([^=!]+)=([^=!])/).select{|s| s.present?}.each_slice(2).map do |a,b|
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a = a.strip
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if b
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("result[\"#{a}\"]=" + b.gsub("\n",""))
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else
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a
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end
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end.join("\n")
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self.fix_hidden_variables.each do |v|
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formula = formula.gsub(/(\A|[^\w\"])#{v}($|[^\w])/){|f| "#{$1}result[\"#{v.strip}\"]#{$2}"}
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self.tmp_hidden_variables_for_ruby = self.tmp_hidden_variables_for_ruby.gsub(/(\A|[^\w\"])#{v}($|[^\w])/){|f| "#{$1}result[\"#{v.strip}\"]#{$2}"}
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end
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self.tmp_lpv_ruby_code = formula
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formula_variables = formula.enum_for(:scan,/([^\=\(\)]+)?=[^=]/).map {|x| x[-1] }.compact.map{|s| s.strip[8..-3]}
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self.tmp_lpv_variables = formula_variables
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self.tmp_years_settings = self.years_settings.map do |s|
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text_to_math(s)
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end
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self.tmp_years_settings_for_ruby = self.tmp_years_settings.clone
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formula_variables.each do |variable_name|
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self.tmp_years_settings_for_ruby = self.tmp_years_settings_for_ruby.map do |y|
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y.gsub(variable_name,"result[\"#{variable_name}\"]")
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end
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end
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self.treatment_method = ['Surgery_only']
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self.form_show_in_result.values.each do |choice|
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variable = choice["variable"]
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if variable.present?
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self.treatment_method << variable
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end
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end
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tmp_table_translations = {}
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tmp_text_translations = {}
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@years = self.years
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@head_name = ['Treatment','Additional_Benefit','Overall_Survival']
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# @head_name = ['Treatment','Overall_Survival']
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@therapy_names = self.treatment_method
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I18n.available_locales.each do |locale|
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I18n.with_locale(locale) do
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@table_head = @head_name.map{|name| I18n.t('coloncancerpredict1.table.'+name)}
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@therapy_choices = [I18n.t('coloncancerpredict1.table.Surgeryonly')]
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self.form_show_in_result.values.each{|choice| @therapy_choices.push choice["name"][locale].to_s}
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tmp_table = "<span class=\"result_title print_only\">#{I18n.t("coloncancerpredict1.table.table")}</span><div style=\"clear: both\"></div>"
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tmp_table += '<input id="current_year" type="hidden" value="'+@years[-1].to_s+'" index="0"/><p id="cancer_table_texts">'+self.table_above_texts[locale].to_s+'</p>'
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tmp_table += ('<a style="display: inline-block;">'+(locale.to_s == 'zh_tw' ? '第' : '')+'</a><a style="display: inline-block;">')
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@years.each{|year| tmp_table += ('<button class="cancer_years cancer_table_btn btn btn-default btn-sm">'+year.to_s+'</button>')}
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tmp_table += ('</a><a style="display: inline-block;">'+(locale == 'zh_tw' ? '年' : '')+'</a>')
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tmp_table += '<table><thead><tr>'
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@table_head.each_with_index{|head,index| tmp_table += ('<th class="cancer_th '+@head_name[index]+'">' + head + '</th>')}
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tmp_table += '</tr></thead><tbody>'
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@therapy_choices.each_with_index do |choice,i|
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tmp_table += '<tr class="'+@therapy_names[i].to_s+'">'
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@table_head.each_with_index do |head,index|
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tmp_table += ('<td class="cancer_td '+ @head_name[index]+'">' + ((index == 0) ? (((i==0)? '' : '+') + choice) : '-') + '</td>')
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end
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tmp_table += '</tr>'
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end
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tmp_table_translations[locale] = tmp_table
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@texts = self.text_above_texts[locale].to_s.gsub('<br/>','</span><br/><span>').gsub('{{Surgery_only}}','<span class="'+@therapy_names[0]+' Overall_Survival"></span>')
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@texts = @texts.split('{{years}}')
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@texts.delete('')
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tmp_text = "<span class=\"result_title print_only\">#{I18n.t("coloncancerpredict1.table.text")}</span><div style=\"clear: both\"></div>"
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tmp_text += ('<span>'+@texts[0].to_s)
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@years.each{|year| tmp_text += ('<button class="cancer_years cancer_table_btn btn btn-default btn-sm" style="float:none;">'+year.to_s+'</button>')}
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if @texts.count > 1
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tmp_text += (@texts[1]+'</span>') if @texts.count > 1
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else
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tmp_text += '</span>'
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end
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if !self.surgery_only_texts[locale].blank?
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@surgery_only_texts = self.surgery_only_texts[locale]
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@surgery_only_texts.insert(0,'<p class="show"><span>')
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@surgery_only_texts = @surgery_only_texts.gsub('{{Surgery_only}}','<span class="'+@therapy_names[0]+' Overall_Survival"></span><span>')
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@surgery_only_texts = @surgery_only_texts.gsub('{{surgery_year}}','</span><span class="surgery_year">'+@years[-1].to_s+'</span><span>')
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@surgery_only_texts += '</span>'
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else
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@surgery_only_texts = ''
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end
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tmp_text += @surgery_only_texts
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tmp_text += '<span class="addition">'+(self.extra_texts[locale].to_s rescue '')+'</span><div class="extra-text" style="display:none;"><div class="texts_show" style="clear:both;"></div></div></p>'
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tmp_text_translations[locale] = tmp_text
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end
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end
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self.result_table_translations = tmp_table_translations
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self.result_text_translations = tmp_text_translations
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self.treatment_method_active_indices = [1]
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self.form_show_in_result.each do |num, property|
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v = property[:active_choice]
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if v.present?
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self.treatment_method_active_indices << (v - 1)
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else
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self.treatment_method_active_indices << 1
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end
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end
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self.lpv_calc = get_years_settings_dict
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self.generate_eval_formula
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end
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def generate_eval_formula
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eval_hidden_variables = "def eval_hidden_variables(result); #{self.tmp_hidden_variables_for_ruby}; end"
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Coloncancerpredict1sController.module_eval(eval_hidden_variables)
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eval_formula = "def eval_formula(result); #{self.tmp_lpv_ruby_code}; end"
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Coloncancerpredict1sController.module_eval(eval_formula)
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end
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def generate_jscode
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js_code = "var map_values , mapping_hash , temp_index ,temp_value , index , closest_value;\r\n"
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mapping_data_from_csv = JSON.parse(self.mapping_data_from_csv) rescue {}
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tmp_hash = self.form_show.values + self.form_show_in_result.values
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tmp_hash.each do |property|
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@variable = property[:variable]
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if @variable.present?
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if property[:is_num] == 1
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js_code += " result['#{@variable}'] = Number(result_json['#{@variable}']);\r\n"
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elsif property[:choice_fields].present?
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if !(self.advance_mode)
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js_code += " result['#{@variable}'] = Number(result_json['#{@variable}']);\r\n"
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||
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[:coloncancer_predict_mapping_file1].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<obj.active_treatment.length;i++){
|
||
var servive_ratio = round(calculate_servive_ratio(obj.year,obj.lpv_real[i])*100,2);
|
||
var benefit = servive_ratio - obj.servive_ratio_arr[obj.servive_ratio_arr.length-1];
|
||
obj.servive_ratio_arr.push(servive_ratio);
|
||
$('tr.'+obj.active_treatment[i]+' td.Overall_Survival').html(servive_ratio+'%');
|
||
$('.'+obj.active_treatment[i]+'.Overall_Survival').html(Math.round(servive_ratio));
|
||
if(i != 0){
|
||
$('tr.'+obj.active_treatment[i]+' td.Additional_Benefit').html(round(benefit,2)+'%');
|
||
$('.'+obj.active_treatment[i]+'.Additional_Benefit').html(Math.round(benefit));
|
||
}
|
||
}
|
||
//$('.'+obj.active_treatment[0]+'.Overall_Survival').html(Math.round(obj.servive_ratio_arr[0]));
|
||
};"
|
||
@years = self.years
|
||
switch_texts = "
|
||
#{formula_variables.map{|v| "var #{v} = obj['#{v}'];"}.join("\n ")}
|
||
switch(year) {"
|
||
@years.each do |year|
|
||
year_index = @years.index(year)
|
||
switch_texts +=
|
||
"
|
||
case '#{year}':
|
||
servive_ratio = #{text_to_math(self.years_settings[year_index])};
|
||
break;"
|
||
end
|
||
switch_texts += "
|
||
default:
|
||
console.log('not found year.');
|
||
}"
|
||
js_code = js_code +"
|
||
|
||
function calculate_servive_ratio(year,obj){
|
||
var servive_ratio;#{switch_texts}
|
||
return servive_ratio;
|
||
}
|
||
"
|
||
return js_code
|
||
end
|
||
def text_to_math(text)
|
||
text.gsub("\r\n","\n").gsub('^','**').gsub('exp','Math.exp').gsub('log','Math.log')
|
||
end
|
||
def replace_str_with_idx(org_str,st, ed, replace_str)
|
||
org_str.slice!(st, ed - st + 1)
|
||
org_str.insert(st, replace_str)
|
||
org_str
|
||
end
|
||
def auto_write_predict_js
|
||
js_codes = generate_jscode
|
||
module_app_path = Pathname.new(File.expand_path(__dir__)).dirname.dirname.to_s
|
||
save_path = module_app_path + '/app/assets/javascripts/colon_cancer_predict1.js'
|
||
file_texts = File.read(save_path)
|
||
need_write = false
|
||
str1 = "/* auto add start */"
|
||
index1 = file_texts.index(str1)
|
||
str2 = "/* auto add end */"
|
||
index2 = file_texts.index(str2)
|
||
if (!index1.nil? && !index2.nil?)
|
||
file_texts = replace_str_with_idx(file_texts, index1 + str1.length, index2 - 1, js_codes)
|
||
need_write = true
|
||
end
|
||
str3 = "/*lpv_calc_formula_start*/"
|
||
index3 = file_texts.index(str3)
|
||
str4 = "/*lpv_calc_formula_end*/"
|
||
index4 = file_texts.index(str4)
|
||
if (!index3.nil? && !index4.nil?)
|
||
file_texts = replace_str_with_idx(file_texts, index3 + str3.length, index4 - 1, self.lpv_calc.to_json.gsub("@",".") + ';')
|
||
need_write = true
|
||
end
|
||
tmp_disable_jscodes = ""
|
||
str5 = "/*disable_condition start*/"
|
||
index5 = file_texts.index(str5)
|
||
str6 = "/*disable_condition end*/"
|
||
index6 = file_texts.index(str6)
|
||
self.form_show_in_result.each do |num,property|
|
||
if property[:disable_condition].present?
|
||
tmp = property[:disable_condition].clone
|
||
self.all_variables.each do |k|
|
||
tmp = tmp.gsub(/(\A|[^\w])#{k}($|[^\w])/){|f| "#{$1}post_json[\"#{k}\"]#{$2}" }
|
||
end
|
||
variable = property[:variable]
|
||
tmp_disable_jscodes += "\n if(#{tmp}){
|
||
$('##{variable} .cancer_table_btn').attr('disabled','disabled');
|
||
$('[for=\"#{variable}\"]').css('color','rgb(204, 204, 204)');
|
||
}else{
|
||
$('##{variable} .cancer_table_btn').removeAttr('disabled');
|
||
$('[for=\"#{variable}\"]').css('color','');
|
||
}"
|
||
end
|
||
end
|
||
if (!index5.nil? && !index6.nil?)
|
||
tmp_disable_jscodes += "\n\t\t\t"
|
||
file_texts = replace_str_with_idx(file_texts, index5 + str5.length, index6 - 1, tmp_disable_jscodes)
|
||
need_write = true
|
||
end
|
||
str7 = "/*therapy_lpv start*/"
|
||
index7 = file_texts.index(str7)
|
||
str8 = "/*therapy_lpv end*/"
|
||
index8 = file_texts.index(str8)
|
||
self.therapy_lpv = [0]
|
||
self.form_show_in_result.each do |num,property|
|
||
if property[:lpv_impact].present?
|
||
self.therapy_lpv << property[:lpv_impact]
|
||
else
|
||
self.therapy_lpv << 0
|
||
end
|
||
end
|
||
if (!index7.nil? && !index8.nil?)
|
||
file_texts = replace_str_with_idx(file_texts, index7 + str7.length, index8 - 1, self.therapy_lpv.to_s + ';')
|
||
need_write = true
|
||
end
|
||
if need_write
|
||
File.write(save_path,file_texts)
|
||
end
|
||
end
|
||
def get_years_settings_dict
|
||
lpv_variable_name = (prediction_formula.include?("=") ? prediction_formula.split("=")[0].strip : "" rescue "")
|
||
res = self.years.map.with_index do |y, i|
|
||
tmp_formula = self.tmp_years_settings[i]
|
||
if lpv_variable_name.present?
|
||
tmp_formula = tmp_formula.gsub(lpv_variable_name, "lpv_current")
|
||
else
|
||
tmp_formula = tmp_formula.gsub("lpv", "lpv_current")
|
||
end
|
||
[y.to_s.sub(".","@"), tmp_formula]
|
||
end
|
||
res.to_h
|
||
end
|
||
end |