path: root/views/predict.haml

%link{ :href=>"/jsme/jsa.css", :rel=>"stylesheet"}
%script{:src=>"/jsme/jsme.nocache.js"}
:javascript
  $(function() { 
    $('a[data-toggle="tab"]').on('click', function (e) {
      localStorage.setItem('lastTab', $(e.target).attr('href'));
    });
    var lastTab = localStorage.getItem('lastTab');
    if (lastTab) {
      $('a[href="'+lastTab+'"]').click();
    }
  });  
  
  function getInput(){
    identifier = document.getElementById("identifier").value;
    fileselect = document.getElementById("fileselect").value;
    if (fileselect != ""){
      return 1;
    };
    if (identifier != ""){
      return 2;
    };
    return 0;
  };
  function showcircle() {
    switch (getInput()){
      case 0:
        alert("Please draw or insert a chemical structure.");
        return false;
        break;
      case 1:
        if (checkfile() && checkboxes()){
          button = document.getElementById("submit");
          image = document.getElementById("circle");
          button.parentNode.replaceChild(image, button);
          $("img.circle").show();
          return true;
        };
        return false;
        break;
      case 2:
        if (checksmiles() && checkboxes()){
          button = document.getElementById("submit");
          image = document.getElementById("circle");
          button.parentNode.replaceChild(image, button);
          $("img.circle").show();
          return true;
        };
        return false;
        break;
      default: false;
    };
    return false;
  };
  function checkfile() {
    var fileinput = document.getElementById("fileselect");
    if(fileinput.value != "") {
      //TODO check file type is csv
      return true;
    };
    alert("Please select a file (csv).");
    return false;
  };
  function checksmiles () {
    getsmiles();
    if (document.form.identifier.value == "") {
      alert("Please draw or insert a chemical structure.");
      document.form.identifier.focus();
      $("img.circle").hide();
      return false;
    };
    return true;
  };
  function checkboxes () {
    var checked = false;
    $('input[type="checkbox"]').each(function() {
      if ($(this).is(":checked")) {
        checked = true;
      };
    });
    if (checked == false){
      alert("Please select an endpoint.");
      $("img.circle").hide();
      return false;
    };
    return true;
  };
  function jsmeOnLoad() {
    jsmeApplet = new JSApplet.JSME("appletContainer", "380px", "340px", {
      //optional parameters
      "options" : "polarnitro"
    });
  document.JME = jsmeApplet;
  };
  function getsmiles() {
    if (document.JME.smiles() != '') {
      document.form.identifier.value = document.JME.smiles() ;
    };
  };

// whole site content needs to be in one form. Input and checkboxes are proofed by js functions. 
%form{:name => "form", :action => to('/predict'), :method => "post", :enctype => "multipart/form-data", :onsubmit => "return  !!(showcircle())" }
  %fieldset#top.well
    %h2 1. Draw a chemical structure
    #insert
      %label  
      #appletContainer
      %br
      %label{:for => 'identifier'}
        or enter the
        %a{:href => "http://en.wikipedia.org/wiki/Simplified_molecular_input_line_entry_specification", :rel => "external"} SMILES
        string:
      %br
      %input{:type => 'text', :name => 'identifier', :id => 'identifier', :size => '60'}
      %p
      %label{:for=>"fileselect"}
        or upload a CSV file for batch predictions
      %br
      %span.btn.btn-default.btn-file
        -#%input{:type=>"file", :name=> "fileselect", :id=>"fileselect", :accept=>".csv", :disabled=>"disabled"}
        %input{:type=>"file", :name=> "fileselect", :id=>"fileselect", :accept=>"text/csv"}

  %fieldset#middle.well
    %h2 2. Select one or more endpoints
    #models
      - @endpoints.each do |endpoint|
        %div{:id=>endpoint}
          %h4.head-back=endpoint
          - @models.select{|m| m.endpoint == endpoint}.each do |model|
            %div.row{:id => model.id}
              %span.col-sm-4
                %input{:type => "checkbox", :name => "selection[#{model.id}]", :id => "selection[#{model.species}]", :value => true, :disabled => false}
                %label{:for => "selection[#{model.species}]"}
                  = model.species
              %span.col-sm-8
                %a.btn.btn-default.btn-xs{:data=>{:toggle=>"collapse"}, :href=>"#details#{model.id}", :id => "link#{model.id}", :style=>"font-size:small;"}
                  Details | Validation
            %div.panel-collapse.collapse{:id=>"details#{model.id}", :style=>"margin-left:1em;"}
              %b Model:
              %br
              Source:
              %a{:href=>model.source, :rel=>"external"}
                = model.source
              %br
              = "Algorithm:\tLAZAR"
              %br
              - model.classification? ? type = "Classification" : type = "Regression"
              = "Type:\t"
              = type
              %br
              - training_dataset = OpenTox::Dataset.find model.training_dataset.id
              = "Training dataset:\t"
              = training_dataset.source.split("/").last
              %br
              = "Training compounds:\t"
              = training_dataset.compounds.size

              %p
              %b Validation (repeated):
              %div.row{:style=>"background-color:#f5f5f5;"}
                - model.crossvalidations.each do |crossvalidation|
                  %span.col-xs-4.col-sm-4.col-md-4.col-lg-4
                    - cv = OpenTox::CrossValidation.find crossvalidation.id
                    = "Num folds:\t"
                    = cv.folds
                    %br
                    = "Num instances:\t"
                    = cv.nr_instances
                    %br
                    = "Num unpredicted"
                    = cv.nr_unpredicted
                    - if model.classification? 
                      %br
                      = "Accuracy:\t"
                      = cv.accuracy.round(3) if cv.accuracy
                      %br
                      = "Weighted Accuracy:\t"
                      = cv.weighted_accuracy.round(3) if cv.weighted_accuracy
                      %br
                      = "True positive rate:\t"
                      = cv.true_rate["active"].round(3) if cv.true_rate["active"]
                      %br
                      = "True negative rate:\t"
                      = cv.true_rate["inactive"].round(3) if cv.true_rate["inactive"]
                      %br 
                      = "Positive predictive value:\t"
                      = cv.predictivity["active"].round(3) if cv.predictivity["active"]
                      %br
                      = "Negative predictive value:\t"
                      = cv.predictivity["inactive"].round(3) if cv.predictivity["inactive"]
                      %p
                      %b Confusion Matrix:
                      %table.table.table-condensed.table-borderless{:style=>"width:20%;"}
                        %tbody
                          %tr
                            %td
                            %td
                            %td 
                              %b actual
                            %td
                            %td
                          %tr
                            %td
                            %td
                            %td active
                            %td inactive
                            -#%td total
                          %tr
                            %td 
                              %b predicted
                            %td active
                            %td 
                              =cv.confusion_matrix[0][0]
                            %td 
                              =cv.confusion_matrix[0][1]
                            -#%td 
                              =cv.confusion_matrix[0][0]+cv.confusion_matrix[0][1]
                          %tr
                            %td
                            %td inactive
                            %td 
                              =cv.confusion_matrix[1][0]
                            %td 
                              =cv.confusion_matrix[1][1]
                            -#%td 
                              =cv.confusion_matrix[1][0]+cv.confusion_matrix[1][1]
                          -#%tr
                            %td
                            %td total
                            %td
                              =cv.confusion_matrix[0][0]+cv.confusion_matrix[1][0]
                            %td
                              =cv.confusion_matrix[0][1]+cv.confusion_matrix[1][1]
                            %td
                              -#= "Confusion Matrix:\t"
                              -#= cv.confusion_matrix
                    - if model.regression?
                      %br
                      = "Root mean squared error:\t"
                      = cv.rmse.round(3) if cv.rmse
                      %br
                      = "Weighted root mean squared error:\t"
                      = cv.weighted_rmse.round(3) if cv.weighted_rmse
                      %br
                      = "Mean absolute error:\t"
                      = cv.mae.round(3) if cv.mae
                      %br
                      = "Weighted mean absolute error:\t"
                      = cv.weighted_mae.round(3) if cv.weighted_mae
                      %br 
                      = "R square:\t"
                      = cv.r_squared.round(3) if cv.r_squared
                      /%br
                      /= "Correlation plot"
                      /= cv.correlation_plot
                      /%br
                      /= "Confidence plot:"
                      /= cv.confidence_plot

  
  %fieldset#bottom.well
    %div.row
      %div.col-md-2
        %h2
          3. Predict
      %div.col-md-10
        %input.btn.btn-warning.h2{ :type => "submit", :id => "submit", :value=>">>", :onclick => "getsmiles()"}
        %img.h2{:src=>"/images/wait30trans.gif", :id=>"circle", :class=>"circle", :style=>"display:none;"}