diff --git a/NAMESPACE b/NAMESPACE
index e2bcfc5..f1ae3b0 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,6 +1,8 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(modelStudio,dalex._explainer.object.Explainer)
 S3method(modelStudio,explainer)
+S3method(modelStudio,python.builtin.object)
 export(modelStudio)
 export(modelStudioOptions)
 import(progress)
diff --git a/R/modelStudio.R b/R/modelStudio.R
index 592f6b9..168736f 100644
--- a/R/modelStudio.R
+++ b/R/modelStudio.R
@@ -384,6 +384,15 @@ modelStudio.explainer <- function(explainer,
   model_studio
 }
 
+#:# alias for reticulate pickle/dalex Explainer
+#' @noRd
+#' @export
+modelStudio.python.builtin.object <- modelStudio.explainer
+
+#' @noRd
+#' @export
+modelStudio.dalex._explainer.object.Explainer <- modelStudio.explainer
+
 #' @noRd
 #' @title remove_file_paths
 #'
diff --git a/README.md b/README.md
index 6a9a264..b4718e2 100644
--- a/README.md
+++ b/README.md
@@ -16,7 +16,7 @@ The main `modelStudio()` function computes various (instance and dataset level)
 [**explain FIFA20**](https://pbiecek.github.io/explainFIFA20/) &emsp;
 [explain Lung Cancer](https://github.com/hbaniecki/transparent_xai/) &emsp;
 [**R & Python examples**](http://modelstudio.drwhy.ai/articles/vignette_examples.html) &emsp;
-[More Resources](https://modeloriented.github.io/modelStudio/#more) &emsp;
+[More Resources](http://modelstudio.drwhy.ai/#more-resources) &emsp;
 [**FAQ & Troubleshooting**](https://github.com/ModelOriented/modelStudio/issues/54)
 
 ![](man/figures/short.gif)
@@ -73,7 +73,7 @@ install.packages("iBreakDown")
 
 # packages for explainer objects
 install.packages("DALEX")
-devtools::install_github("ModelOriented/DALEXtra")
+install.packages("DALEXtra")
 ```
 
 ### mlr [dashboard](https://modeloriented.github.io/modelStudio/mlr.html)
@@ -94,7 +94,7 @@ test <- data[-index, ]
 # mlr ClassifTask takes target as factor
 train$survived <- as.factor(train$survived)
 
-# prepare the model
+# fit a model
 task <- makeClassifTask(id = "titanic",
                         data = train,
                         target = "survived")
@@ -137,7 +137,7 @@ test <- data[-index, ]
 train_matrix <- model.matrix(survived ~.-1, train)
 test_matrix <- model.matrix(survived ~.-1, test)
 
-# prepare the model
+# fit a model
 xgb_matrix <- xgb.DMatrix(train_matrix, label = train$survived)
 params <- list(eta = 0.01, subsample = 0.6, max_depth = 7, min_child_weight = 3,
                objective = "binary:logistic", eval_metric = "auc")
@@ -161,96 +161,88 @@ modelStudio(explainer,
 
 ### scikit-learn [dashboard](https://modeloriented.github.io/modelStudio/scikit-learn.html)
 
-Use `pickle` Python module and `reticulate` R package to easily produce modelStudio for scikit-learn model.
+Use `pickle` Python module and `reticulate` R package to easily make a studio for a scikit-learn model.
 
-In this example we fit a Pipeline MLPClassifier on the titanic data. First install the `dalex` package.
+In this example we will fit a Pipeline MLPClassifier model on titanic data. 
+
+Install the `dalex` package.
 
 ```bash
 pip3 install dalex --force
 ```
 
-Make an explainer object in Python:
+First, use `dalex` in Python:
 
 ```python
-# import modules
+# load packages and data
 import dalex as dx
-from dalex import datasets
 
-from sklearn.neural_network import MLPClassifier
-from sklearn.preprocessing import StandardScaler, LabelEncoder, OneHotEncoder
-from sklearn.impute import SimpleImputer
+from sklearn.model_selection import train_test_split
 from sklearn.pipeline import Pipeline
-from sklearn.tree import DecisionTreeRegressor
+from sklearn.preprocessing import StandardScaler, OneHotEncoder
+from sklearn.impute import SimpleImputer
 from sklearn.compose import ColumnTransformer
+from sklearn.neural_network import MLPClassifier
 
-# load the data
-data = datasets.load_titanic()
+data = dx.datasets.load_titanic()
 X = data.drop(columns='survived')
 y = data.survived
 
-# make a pipeline model
+# split the data
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=1)
+
+# fit a pipeline model
 numeric_features = ['age', 'fare', 'sibsp', 'parch']
-numeric_transformer = Pipeline(steps=[
+numeric_transformer = Pipeline(
+  steps=[
     ('imputer', SimpleImputer(strategy='median')),
-    ('scaler', StandardScaler())])
-
+    ('scaler', StandardScaler())
+    ]
+)
 categorical_features = ['gender', 'class', 'embarked']
-categorical_transformer = Pipeline(steps=[
+categorical_transformer = Pipeline(
+  steps=[
     ('imputer', SimpleImputer(strategy='constant', fill_value='missing')),
-    ('onehot', OneHotEncoder(handle_unknown='ignore'))])
+    ('onehot', OneHotEncoder(handle_unknown='ignore'))
+    ]
+)
 
 preprocessor = ColumnTransformer(
-    transformers=[
-        ('num', numeric_transformer, numeric_features),
-        ('cat', categorical_transformer, categorical_features)])
-
-
-clf = Pipeline(steps=[('preprocessor', preprocessor),
-                      ('classifier', MLPClassifier(hidden_layer_sizes=(150,100,50),
-                                                   max_iter=500, random_state=0))])
-
-clf.fit(X, y)
+  transformers=[
+    ('num', numeric_transformer, numeric_features),
+    ('cat', categorical_transformer, categorical_features)
+    ]
+)
+
+model = Pipeline(
+  steps=[
+    ('preprocessor', preprocessor),
+    ('classifier', MLPClassifier(hidden_layer_sizes=(150,100,50), max_iter=500, random_state=0))
+    ]
+)
+model.fit(X_train, y_train)
 
-# make an explainer
-explainer = dx.Explainer(clf, X, y)
+# create an explainer for the model
+explainer = dx.Explainer(model, X_test, y_test, label = 'scikit-learn')
 
-# remove these functions before dump
+#! remove residual_function before dump !
 explainer.residual_function = None
-explainer.predict_function = None
 
 # pack the explainer into a pickle file
-import pickle        
-pickle_out = open("explainer_titanic.pickle","wb")
+import pickle
+pickle_out = open("explainer_scikitlearn.pickle","wb")
 pickle.dump(explainer, pickle_out)
-pickle_out.close()     
+pickle_out.close()
 ```
 
-Then use `modelStudio` in R:
+Then, use `modelStudio` in R:
 
 ```r
-# use reticulate to load the explainer from a pickle file
+# load the explainer from the pickle file
 library(reticulate)
-explainer <- py_load_object('explainer_titanic.pickle')
-
-# make a predict_function
-predict_function <- function(model, data) {
-  if ("predict_proba" %in% names(model)) {
-    pred <- model$predict_proba(data)
-    if (ncol(pred) == 2) {
-      pred <- pred[,2]
-    }
-  } else {
-    pred <- model$predict(data)
-  }
-  pred
-}
-
-# adjust the explainer
-explainer$predict_function <- predict_function
-explainer$label <- 'scikit-learn'
-class(explainer) <- c(class(explainer), 'explainer')
-
-# make a modelStudio
+explainer <- py_load_object('explainer_scikitlearn.pickle', pickle = "pickle")
+
+# make a studio for the model
 library(modelStudio)
 modelStudio(explainer)
 ```
diff --git a/inst/WORDLIST b/inst/WORDLIST
index 1f89891..3401999 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -28,6 +28,7 @@ tensorflow
 Shapley
 cran
 CRAN
-MLPCLassifier
+MLPClassifier
 keras
 lightGBM
+customizable
diff --git a/pkgdown/_pkgdown.yml b/pkgdown/_pkgdown.yml
index afdd162..c8e041b 100644
--- a/pkgdown/_pkgdown.yml
+++ b/pkgdown/_pkgdown.yml
@@ -3,4 +3,5 @@ template:
   default_assets: false
   params:
     ganalytics: UA-5650686-14
-    noindex: true
\ No newline at end of file
+    noindex: true
+    
\ No newline at end of file
diff --git a/pkgdown/favicon/h2o.html b/pkgdown/favicon/h2o.html
new file mode 100644
index 0000000..396a5d2
--- /dev/null
+++ b/pkgdown/favicon/h2o.html
@@ -0,0 +1,1795 @@
+<!DOCTYPE html>
+<html>
+<head>
+<meta charset="utf-8" />
+<style>body{background-color:white;}</style>
+<script>(function() {
+  // If window.HTMLWidgets is already defined, then use it; otherwise create a
+  // new object. This allows preceding code to set options that affect the
+  // initialization process (though none currently exist).
+  window.HTMLWidgets = window.HTMLWidgets || {};
+
+  // See if we're running in a viewer pane. If not, we're in a web browser.
+  var viewerMode = window.HTMLWidgets.viewerMode =
+      /\bviewer_pane=1\b/.test(window.location);
+
+  // See if we're running in Shiny mode. If not, it's a static document.
+  // Note that static widgets can appear in both Shiny and static modes, but
+  // obviously, Shiny widgets can only appear in Shiny apps/documents.
+  var shinyMode = window.HTMLWidgets.shinyMode =
+      typeof(window.Shiny) !== "undefined" && !!window.Shiny.outputBindings;
+
+  // We can't count on jQuery being available, so we implement our own
+  // version if necessary.
+  function querySelectorAll(scope, selector) {
+    if (typeof(jQuery) !== "undefined" && scope instanceof jQuery) {
+      return scope.find(selector);
+    }
+    if (scope.querySelectorAll) {
+      return scope.querySelectorAll(selector);
+    }
+  }
+
+  function asArray(value) {
+    if (value === null)
+      return [];
+    if ($.isArray(value))
+      return value;
+    return [value];
+  }
+
+  // Implement jQuery's extend
+  function extend(target /*, ... */) {
+    if (arguments.length == 1) {
+      return target;
+    }
+    for (var i = 1; i < arguments.length; i++) {
+      var source = arguments[i];
+      for (var prop in source) {
+        if (source.hasOwnProperty(prop)) {
+          target[prop] = source[prop];
+        }
+      }
+    }
+    return target;
+  }
+
+  // IE8 doesn't support Array.forEach.
+  function forEach(values, callback, thisArg) {
+    if (values.forEach) {
+      values.forEach(callback, thisArg);
+    } else {
+      for (var i = 0; i < values.length; i++) {
+        callback.call(thisArg, values[i], i, values);
+      }
+    }
+  }
+
+  // Replaces the specified method with the return value of funcSource.
+  //
+  // Note that funcSource should not BE the new method, it should be a function
+  // that RETURNS the new method. funcSource receives a single argument that is
+  // the overridden method, it can be called from the new method. The overridden
+  // method can be called like a regular function, it has the target permanently
+  // bound to it so "this" will work correctly.
+  function overrideMethod(target, methodName, funcSource) {
+    var superFunc = target[methodName] || function() {};
+    var superFuncBound = function() {
+      return superFunc.apply(target, arguments);
+    };
+    target[methodName] = funcSource(superFuncBound);
+  }
+
+  // Add a method to delegator that, when invoked, calls
+  // delegatee.methodName. If there is no such method on
+  // the delegatee, but there was one on delegator before
+  // delegateMethod was called, then the original version
+  // is invoked instead.
+  // For example:
+  //
+  // var a = {
+  //   method1: function() { console.log('a1'); }
+  //   method2: function() { console.log('a2'); }
+  // };
+  // var b = {
+  //   method1: function() { console.log('b1'); }
+  // };
+  // delegateMethod(a, b, "method1");
+  // delegateMethod(a, b, "method2");
+  // a.method1();
+  // a.method2();
+  //
+  // The output would be "b1", "a2".
+  function delegateMethod(delegator, delegatee, methodName) {
+    var inherited = delegator[methodName];
+    delegator[methodName] = function() {
+      var target = delegatee;
+      var method = delegatee[methodName];
+
+      // The method doesn't exist on the delegatee. Instead,
+      // call the method on the delegator, if it exists.
+      if (!method) {
+        target = delegator;
+        method = inherited;
+      }
+
+      if (method) {
+        return method.apply(target, arguments);
+      }
+    };
+  }
+
+  // Implement a vague facsimilie of jQuery's data method
+  function elementData(el, name, value) {
+    if (arguments.length == 2) {
+      return el["htmlwidget_data_" + name];
+    } else if (arguments.length == 3) {
+      el["htmlwidget_data_" + name] = value;
+      return el;
+    } else {
+      throw new Error("Wrong number of arguments for elementData: " +
+        arguments.length);
+    }
+  }
+
+  // http://stackoverflow.com/questions/3446170/escape-string-for-use-in-javascript-regex
+  function escapeRegExp(str) {
+    return str.replace(/[\-\[\]\/\{\}\(\)\*\+\?\.\\\^\$\|]/g, "\\$&");
+  }
+
+  function hasClass(el, className) {
+    var re = new RegExp("\\b" + escapeRegExp(className) + "\\b");
+    return re.test(el.className);
+  }
+
+  // elements - array (or array-like object) of HTML elements
+  // className - class name to test for
+  // include - if true, only return elements with given className;
+  //   if false, only return elements *without* given className
+  function filterByClass(elements, className, include) {
+    var results = [];
+    for (var i = 0; i < elements.length; i++) {
+      if (hasClass(elements[i], className) == include)
+        results.push(elements[i]);
+    }
+    return results;
+  }
+
+  function on(obj, eventName, func) {
+    if (obj.addEventListener) {
+      obj.addEventListener(eventName, func, false);
+    } else if (obj.attachEvent) {
+      obj.attachEvent(eventName, func);
+    }
+  }
+
+  function off(obj, eventName, func) {
+    if (obj.removeEventListener)
+      obj.removeEventListener(eventName, func, false);
+    else if (obj.detachEvent) {
+      obj.detachEvent(eventName, func);
+    }
+  }
+
+  // Translate array of values to top/right/bottom/left, as usual with
+  // the "padding" CSS property
+  // https://developer.mozilla.org/en-US/docs/Web/CSS/padding
+  function unpackPadding(value) {
+    if (typeof(value) === "number")
+      value = [value];
+    if (value.length === 1) {
+      return {top: value[0], right: value[0], bottom: value[0], left: value[0]};
+    }
+    if (value.length === 2) {
+      return {top: value[0], right: value[1], bottom: value[0], left: value[1]};
+    }
+    if (value.length === 3) {
+      return {top: value[0], right: value[1], bottom: value[2], left: value[1]};
+    }
+    if (value.length === 4) {
+      return {top: value[0], right: value[1], bottom: value[2], left: value[3]};
+    }
+  }
+
+  // Convert an unpacked padding object to a CSS value
+  function paddingToCss(paddingObj) {
+    return paddingObj.top + "px " + paddingObj.right + "px " + paddingObj.bottom + "px " + paddingObj.left + "px";
+  }
+
+  // Makes a number suitable for CSS
+  function px(x) {
+    if (typeof(x) === "number")
+      return x + "px";
+    else
+      return x;
+  }
+
+  // Retrieves runtime widget sizing information for an element.
+  // The return value is either null, or an object with fill, padding,
+  // defaultWidth, defaultHeight fields.
+  function sizingPolicy(el) {
+    var sizingEl = document.querySelector("script[data-for='" + el.id + "'][type='application/htmlwidget-sizing']");
+    if (!sizingEl)
+      return null;
+    var sp = JSON.parse(sizingEl.textContent || sizingEl.text || "{}");
+    if (viewerMode) {
+      return sp.viewer;
+    } else {
+      return sp.browser;
+    }
+  }
+
+  // @param tasks Array of strings (or falsy value, in which case no-op).
+  //   Each element must be a valid JavaScript expression that yields a
+  //   function. Or, can be an array of objects with "code" and "data"
+  //   properties; in this case, the "code" property should be a string
+  //   of JS that's an expr that yields a function, and "data" should be
+  //   an object that will be added as an additional argument when that
+  //   function is called.
+  // @param target The object that will be "this" for each function
+  //   execution.
+  // @param args Array of arguments to be passed to the functions. (The
+  //   same arguments will be passed to all functions.)
+  function evalAndRun(tasks, target, args) {
+    if (tasks) {
+      forEach(tasks, function(task) {
+        var theseArgs = args;
+        if (typeof(task) === "object") {
+          theseArgs = theseArgs.concat([task.data]);
+          task = task.code;
+        }
+        var taskFunc = tryEval(task);
+        if (typeof(taskFunc) !== "function") {
+          throw new Error("Task must be a function! Source:\n" + task);
+        }
+        taskFunc.apply(target, theseArgs);
+      });
+    }
+  }
+
+  // Attempt eval() both with and without enclosing in parentheses.
+  // Note that enclosing coerces a function declaration into
+  // an expression that eval() can parse
+  // (otherwise, a SyntaxError is thrown)
+  function tryEval(code) {
+    var result = null;
+    try {
+      result = eval(code);
+    } catch(error) {
+      if (!error instanceof SyntaxError) {
+        throw error;
+      }
+      try {
+        result = eval("(" + code + ")");
+      } catch(e) {
+        if (e instanceof SyntaxError) {
+          throw error;
+        } else {
+          throw e;
+        }
+      }
+    }
+    return result;
+  }
+
+  function initSizing(el) {
+    var sizing = sizingPolicy(el);
+    if (!sizing)
+      return;
+
+    var cel = document.getElementById("htmlwidget_container");
+    if (!cel)
+      return;
+
+    if (typeof(sizing.padding) !== "undefined") {
+      document.body.style.margin = "0";
+      document.body.style.padding = paddingToCss(unpackPadding(sizing.padding));
+    }
+
+    if (sizing.fill) {
+      document.body.style.overflow = "hidden";
+      document.body.style.width = "100%";
+      document.body.style.height = "100%";
+      document.documentElement.style.width = "100%";
+      document.documentElement.style.height = "100%";
+      if (cel) {
+        cel.style.position = "absolute";
+        var pad = unpackPadding(sizing.padding);
+        cel.style.top = pad.top + "px";
+        cel.style.right = pad.right + "px";
+        cel.style.bottom = pad.bottom + "px";
+        cel.style.left = pad.left + "px";
+        el.style.width = "100%";
+        el.style.height = "100%";
+      }
+
+      return {
+        getWidth: function() { return cel.offsetWidth; },
+        getHeight: function() { return cel.offsetHeight; }
+      };
+
+    } else {
+      el.style.width = px(sizing.width);
+      el.style.height = px(sizing.height);
+
+      return {
+        getWidth: function() { return el.offsetWidth; },
+        getHeight: function() { return el.offsetHeight; }
+      };
+    }
+  }
+
+  // Default implementations for methods
+  var defaults = {
+    find: function(scope) {
+      return querySelectorAll(scope, "." + this.name);
+    },
+    renderError: function(el, err) {
+      var $el = $(el);
+
+      this.clearError(el);
+
+      // Add all these error classes, as Shiny does
+      var errClass = "shiny-output-error";
+      if (err.type !== null) {
+        // use the classes of the error condition as CSS class names
+        errClass = errClass + " " + $.map(asArray(err.type), function(type) {
+          return errClass + "-" + type;
+        }).join(" ");
+      }
+      errClass = errClass + " htmlwidgets-error";
+
+      // Is el inline or block? If inline or inline-block, just display:none it
+      // and add an inline error.
+      var display = $el.css("display");
+      $el.data("restore-display-mode", display);
+
+      if (display === "inline" || display === "inline-block") {
+        $el.hide();
+        if (err.message !== "") {
+          var errorSpan = $("<span>").addClass(errClass);
+          errorSpan.text(err.message);
+          $el.after(errorSpan);
+        }
+      } else if (display === "block") {
+        // If block, add an error just after the el, set visibility:none on the
+        // el, and position the error to be on top of the el.
+        // Mark it with a unique ID and CSS class so we can remove it later.
+        $el.css("visibility", "hidden");
+        if (err.message !== "") {
+          var errorDiv = $("<div>").addClass(errClass).css("position", "absolute")
+            .css("top", el.offsetTop)
+            .css("left", el.offsetLeft)
+            // setting width can push out the page size, forcing otherwise
+            // unnecessary scrollbars to appear and making it impossible for
+            // the element to shrink; so use max-width instead
+            .css("maxWidth", el.offsetWidth)
+            .css("height", el.offsetHeight);
+          errorDiv.text(err.message);
+          $el.after(errorDiv);
+
+          // Really dumb way to keep the size/position of the error in sync with
+          // the parent element as the window is resized or whatever.
+          var intId = setInterval(function() {
+            if (!errorDiv[0].parentElement) {
+              clearInterval(intId);
+              return;
+            }
+            errorDiv
+              .css("top", el.offsetTop)
+              .css("left", el.offsetLeft)
+              .css("maxWidth", el.offsetWidth)
+              .css("height", el.offsetHeight);
+          }, 500);
+        }
+      }
+    },
+    clearError: function(el) {
+      var $el = $(el);
+      var display = $el.data("restore-display-mode");
+      $el.data("restore-display-mode", null);
+
+      if (display === "inline" || display === "inline-block") {
+        if (display)
+          $el.css("display", display);
+        $(el.nextSibling).filter(".htmlwidgets-error").remove();
+      } else if (display === "block"){
+        $el.css("visibility", "inherit");
+        $(el.nextSibling).filter(".htmlwidgets-error").remove();
+      }
+    },
+    sizing: {}
+  };
+
+  // Called by widget bindings to register a new type of widget. The definition
+  // object can contain the following properties:
+  // - name (required) - A string indicating the binding name, which will be
+  //   used by default as the CSS classname to look for.
+  // - initialize (optional) - A function(el) that will be called once per
+  //   widget element; if a value is returned, it will be passed as the third
+  //   value to renderValue.
+  // - renderValue (required) - A function(el, data, initValue) that will be
+  //   called with data. Static contexts will cause this to be called once per
+  //   element; Shiny apps will cause this to be called multiple times per
+  //   element, as the data changes.
+  window.HTMLWidgets.widget = function(definition) {
+    if (!definition.name) {
+      throw new Error("Widget must have a name");
+    }
+    if (!definition.type) {
+      throw new Error("Widget must have a type");
+    }
+    // Currently we only support output widgets
+    if (definition.type !== "output") {
+      throw new Error("Unrecognized widget type '" + definition.type + "'");
+    }
+    // TODO: Verify that .name is a valid CSS classname
+
+    // Support new-style instance-bound definitions. Old-style class-bound
+    // definitions have one widget "object" per widget per type/class of
+    // widget; the renderValue and resize methods on such widget objects
+    // take el and instance arguments, because the widget object can't
+    // store them. New-style instance-bound definitions have one widget
+    // object per widget instance; the definition that's passed in doesn't
+    // provide renderValue or resize methods at all, just the single method
+    //   factory(el, width, height)
+    // which returns an object that has renderValue(x) and resize(w, h).
+    // This enables a far more natural programming style for the widget
+    // author, who can store per-instance state using either OO-style
+    // instance fields or functional-style closure variables (I guess this
+    // is in contrast to what can only be called C-style pseudo-OO which is
+    // what we required before).
+    if (definition.factory) {
+      definition = createLegacyDefinitionAdapter(definition);
+    }
+
+    if (!definition.renderValue) {
+      throw new Error("Widget must have a renderValue function");
+    }
+
+    // For static rendering (non-Shiny), use a simple widget registration
+    // scheme. We also use this scheme for Shiny apps/documents that also
+    // contain static widgets.
+    window.HTMLWidgets.widgets = window.HTMLWidgets.widgets || [];
+    // Merge defaults into the definition; don't mutate the original definition.
+    var staticBinding = extend({}, defaults, definition);
+    overrideMethod(staticBinding, "find", function(superfunc) {
+      return function(scope) {
+        var results = superfunc(scope);
+        // Filter out Shiny outputs, we only want the static kind
+        return filterByClass(results, "html-widget-output", false);
+      };
+    });
+    window.HTMLWidgets.widgets.push(staticBinding);
+
+    if (shinyMode) {
+      // Shiny is running. Register the definition with an output binding.
+      // The definition itself will not be the output binding, instead
+      // we will make an output binding object that delegates to the
+      // definition. This is because we foolishly used the same method
+      // name (renderValue) for htmlwidgets definition and Shiny bindings
+      // but they actually have quite different semantics (the Shiny
+      // bindings receive data that includes lots of metadata that it
+      // strips off before calling htmlwidgets renderValue). We can't
+      // just ignore the difference because in some widgets it's helpful
+      // to call this.renderValue() from inside of resize(), and if
+      // we're not delegating, then that call will go to the Shiny
+      // version instead of the htmlwidgets version.
+
+      // Merge defaults with definition, without mutating either.
+      var bindingDef = extend({}, defaults, definition);
+
+      // This object will be our actual Shiny binding.
+      var shinyBinding = new Shiny.OutputBinding();
+
+      // With a few exceptions, we'll want to simply use the bindingDef's
+      // version of methods if they are available, otherwise fall back to
+      // Shiny's defaults. NOTE: If Shiny's output bindings gain additional
+      // methods in the future, and we want them to be overrideable by
+      // HTMLWidget binding definitions, then we'll need to add them to this
+      // list.
+      delegateMethod(shinyBinding, bindingDef, "getId");
+      delegateMethod(shinyBinding, bindingDef, "onValueChange");
+      delegateMethod(shinyBinding, bindingDef, "onValueError");
+      delegateMethod(shinyBinding, bindingDef, "renderError");
+      delegateMethod(shinyBinding, bindingDef, "clearError");
+      delegateMethod(shinyBinding, bindingDef, "showProgress");
+
+      // The find, renderValue, and resize are handled differently, because we
+      // want to actually decorate the behavior of the bindingDef methods.
+
+      shinyBinding.find = function(scope) {
+        var results = bindingDef.find(scope);
+
+        // Only return elements that are Shiny outputs, not static ones
+        var dynamicResults = results.filter(".html-widget-output");
+
+        // It's possible that whatever caused Shiny to think there might be
+        // new dynamic outputs, also caused there to be new static outputs.
+        // Since there might be lots of different htmlwidgets bindings, we
+        // schedule execution for later--no need to staticRender multiple
+        // times.
+        if (results.length !== dynamicResults.length)
+          scheduleStaticRender();
+
+        return dynamicResults;
+      };
+
+      // Wrap renderValue to handle initialization, which unfortunately isn't
+      // supported natively by Shiny at the time of this writing.
+
+      shinyBinding.renderValue = function(el, data) {
+        Shiny.renderDependencies(data.deps);
+        // Resolve strings marked as javascript literals to objects
+        if (!(data.evals instanceof Array)) data.evals = [data.evals];
+        for (var i = 0; data.evals && i < data.evals.length; i++) {
+          window.HTMLWidgets.evaluateStringMember(data.x, data.evals[i]);
+        }
+        if (!bindingDef.renderOnNullValue) {
+          if (data.x === null) {
+            el.style.visibility = "hidden";
+            return;
+          } else {
+            el.style.visibility = "inherit";
+          }
+        }
+        if (!elementData(el, "initialized")) {
+          initSizing(el);
+
+          elementData(el, "initialized", true);
+          if (bindingDef.initialize) {
+            var result = bindingDef.initialize(el, el.offsetWidth,
+              el.offsetHeight);
+            elementData(el, "init_result", result);
+          }
+        }
+        bindingDef.renderValue(el, data.x, elementData(el, "init_result"));
+        evalAndRun(data.jsHooks.render, elementData(el, "init_result"), [el, data.x]);
+      };
+
+      // Only override resize if bindingDef implements it
+      if (bindingDef.resize) {
+        shinyBinding.resize = function(el, width, height) {
+          // Shiny can call resize before initialize/renderValue have been
+          // called, which doesn't make sense for widgets.
+          if (elementData(el, "initialized")) {
+            bindingDef.resize(el, width, height, elementData(el, "init_result"));
+          }
+        };
+      }
+
+      Shiny.outputBindings.register(shinyBinding, bindingDef.name);
+    }
+  };
+
+  var scheduleStaticRenderTimerId = null;
+  function scheduleStaticRender() {
+    if (!scheduleStaticRenderTimerId) {
+      scheduleStaticRenderTimerId = setTimeout(function() {
+        scheduleStaticRenderTimerId = null;
+        window.HTMLWidgets.staticRender();
+      }, 1);
+    }
+  }
+
+  // Render static widgets after the document finishes loading
+  // Statically render all elements that are of this widget's class
+  window.HTMLWidgets.staticRender = function() {
+    var bindings = window.HTMLWidgets.widgets || [];
+    forEach(bindings, function(binding) {
+      var matches = binding.find(document.documentElement);
+      forEach(matches, function(el) {
+        var sizeObj = initSizing(el, binding);
+
+        if (hasClass(el, "html-widget-static-bound"))
+          return;
+        el.className = el.className + " html-widget-static-bound";
+
+        var initResult;
+        if (binding.initialize) {
+          initResult = binding.initialize(el,
+            sizeObj ? sizeObj.getWidth() : el.offsetWidth,
+            sizeObj ? sizeObj.getHeight() : el.offsetHeight
+          );
+          elementData(el, "init_result", initResult);
+        }
+
+        if (binding.resize) {
+          var lastSize = {
+            w: sizeObj ? sizeObj.getWidth() : el.offsetWidth,
+            h: sizeObj ? sizeObj.getHeight() : el.offsetHeight
+          };
+          var resizeHandler = function(e) {
+            var size = {
+              w: sizeObj ? sizeObj.getWidth() : el.offsetWidth,
+              h: sizeObj ? sizeObj.getHeight() : el.offsetHeight
+            };
+            if (size.w === 0 && size.h === 0)
+              return;
+            if (size.w === lastSize.w && size.h === lastSize.h)
+              return;
+            lastSize = size;
+            binding.resize(el, size.w, size.h, initResult);
+          };
+
+          on(window, "resize", resizeHandler);
+
+          // This is needed for cases where we're running in a Shiny
+          // app, but the widget itself is not a Shiny output, but
+          // rather a simple static widget. One example of this is
+          // an rmarkdown document that has runtime:shiny and widget
+          // that isn't in a render function. Shiny only knows to
+          // call resize handlers for Shiny outputs, not for static
+          // widgets, so we do it ourselves.
+          if (window.jQuery) {
+            window.jQuery(document).on(
+              "shown.htmlwidgets shown.bs.tab.htmlwidgets shown.bs.collapse.htmlwidgets",
+              resizeHandler
+            );
+            window.jQuery(document).on(
+              "hidden.htmlwidgets hidden.bs.tab.htmlwidgets hidden.bs.collapse.htmlwidgets",
+              resizeHandler
+            );
+          }
+
+          // This is needed for the specific case of ioslides, which
+          // flips slides between display:none and display:block.
+          // Ideally we would not have to have ioslide-specific code
+          // here, but rather have ioslides raise a generic event,
+          // but the rmarkdown package just went to CRAN so the
+          // window to getting that fixed may be long.
+          if (window.addEventListener) {
+            // It's OK to limit this to window.addEventListener
+            // browsers because ioslides itself only supports
+            // such browsers.
+            on(document, "slideenter", resizeHandler);
+            on(document, "slideleave", resizeHandler);
+          }
+        }
+
+        var scriptData = document.querySelector("script[data-for='" + el.id + "'][type='application/json']");
+        if (scriptData) {
+          var data = JSON.parse(scriptData.textContent || scriptData.text);
+          // Resolve strings marked as javascript literals to objects
+          if (!(data.evals instanceof Array)) data.evals = [data.evals];
+          for (var k = 0; data.evals && k < data.evals.length; k++) {
+            window.HTMLWidgets.evaluateStringMember(data.x, data.evals[k]);
+          }
+          binding.renderValue(el, data.x, initResult);
+          evalAndRun(data.jsHooks.render, initResult, [el, data.x]);
+        }
+      });
+    });
+
+    invokePostRenderHandlers();
+  }
+
+
+  function has_jQuery3() {
+    if (!window.jQuery) {
+      return false;
+    }
+    var $version = window.jQuery.fn.jquery;
+    var $major_version = parseInt($version.split(".")[0]);
+    return $major_version >= 3;
+  }
+
+  /*
+  / Shiny 1.4 bumped jQuery from 1.x to 3.x which means jQuery's
+  / on-ready handler (i.e., $(fn)) is now asyncronous (i.e., it now
+  / really means $(setTimeout(fn)).
+  / https://jquery.com/upgrade-guide/3.0/#breaking-change-document-ready-handlers-are-now-asynchronous
+  /
+  / Since Shiny uses $() to schedule initShiny, shiny>=1.4 calls initShiny
+  / one tick later than it did before, which means staticRender() is
+  / called renderValue() earlier than (advanced) widget authors might be expecting.
+  / https://github.com/rstudio/shiny/issues/2630
+  /
+  / For a concrete example, leaflet has some methods (e.g., updateBounds)
+  / which reference Shiny methods registered in initShiny (e.g., setInputValue).
+  / Since leaflet is privy to this life-cycle, it knows to use setTimeout() to
+  / delay execution of those methods (until Shiny methods are ready)
+  / https://github.com/rstudio/leaflet/blob/18ec981/javascript/src/index.js#L266-L268
+  /
+  / Ideally widget authors wouldn't need to use this setTimeout() hack that
+  / leaflet uses to call Shiny methods on a staticRender(). In the long run,
+  / the logic initShiny should be broken up so that method registration happens
+  / right away, but binding happens later.
+  */
+  function maybeStaticRenderLater() {
+    if (shinyMode && has_jQuery3()) {
+      window.jQuery(window.HTMLWidgets.staticRender);
+    } else {
+      window.HTMLWidgets.staticRender();
+    }
+  }
+
+  if (document.addEventListener) {
+    document.addEventListener("DOMContentLoaded", function() {
+      document.removeEventListener("DOMContentLoaded", arguments.callee, false);
+      maybeStaticRenderLater();
+    }, false);
+  } else if (document.attachEvent) {
+    document.attachEvent("onreadystatechange", function() {
+      if (document.readyState === "complete") {
+        document.detachEvent("onreadystatechange", arguments.callee);
+        maybeStaticRenderLater();
+      }
+    });
+  }
+
+
+  window.HTMLWidgets.getAttachmentUrl = function(depname, key) {
+    // If no key, default to the first item
+    if (typeof(key) === "undefined")
+      key = 1;
+
+    var link = document.getElementById(depname + "-" + key + "-attachment");
+    if (!link) {
+      throw new Error("Attachment " + depname + "/" + key + " not found in document");
+    }
+    return link.getAttribute("href");
+  };
+
+  window.HTMLWidgets.dataframeToD3 = function(df) {
+    var names = [];
+    var length;
+    for (var name in df) {
+        if (df.hasOwnProperty(name))
+            names.push(name);
+        if (typeof(df[name]) !== "object" || typeof(df[name].length) === "undefined") {
+            throw new Error("All fields must be arrays");
+        } else if (typeof(length) !== "undefined" && length !== df[name].length) {
+            throw new Error("All fields must be arrays of the same length");
+        }
+        length = df[name].length;
+    }
+    var results = [];
+    var item;
+    for (var row = 0; row < length; row++) {
+        item = {};
+        for (var col = 0; col < names.length; col++) {
+            item[names[col]] = df[names[col]][row];
+        }
+        results.push(item);
+    }
+    return results;
+  };
+
+  window.HTMLWidgets.transposeArray2D = function(array) {
+      if (array.length === 0) return array;
+      var newArray = array[0].map(function(col, i) {
+          return array.map(function(row) {
+              return row[i]
+          })
+      });
+      return newArray;
+  };
+  // Split value at splitChar, but allow splitChar to be escaped
+  // using escapeChar. Any other characters escaped by escapeChar
+  // will be included as usual (including escapeChar itself).
+  function splitWithEscape(value, splitChar, escapeChar) {
+    var results = [];
+    var escapeMode = false;
+    var currentResult = "";
+    for (var pos = 0; pos < value.length; pos++) {
+      if (!escapeMode) {
+        if (value[pos] === splitChar) {
+          results.push(currentResult);
+          currentResult = "";
+        } else if (value[pos] === escapeChar) {
+          escapeMode = true;
+        } else {
+          currentResult += value[pos];
+        }
+      } else {
+        currentResult += value[pos];
+        escapeMode = false;
+      }
+    }
+    if (currentResult !== "") {
+      results.push(currentResult);
+    }
+    return results;
+  }
+  // Function authored by Yihui/JJ Allaire
+  window.HTMLWidgets.evaluateStringMember = function(o, member) {
+    var parts = splitWithEscape(member, '.', '\\');
+    for (var i = 0, l = parts.length; i < l; i++) {
+      var part = parts[i];
+      // part may be a character or 'numeric' member name
+      if (o !== null && typeof o === "object" && part in o) {
+        if (i == (l - 1)) { // if we are at the end of the line then evalulate
+          if (typeof o[part] === "string")
+            o[part] = tryEval(o[part]);
+        } else { // otherwise continue to next embedded object
+          o = o[part];
+        }
+      }
+    }
+  };
+
+  // Retrieve the HTMLWidget instance (i.e. the return value of an
+  // HTMLWidget binding's initialize() or factory() function)
+  // associated with an element, or null if none.
+  window.HTMLWidgets.getInstance = function(el) {
+    return elementData(el, "init_result");
+  };
+
+  // Finds the first element in the scope that matches the selector,
+  // and returns the HTMLWidget instance (i.e. the return value of
+  // an HTMLWidget binding's initialize() or factory() function)
+  // associated with that element, if any. If no element matches the
+  // selector, or the first matching element has no HTMLWidget
+  // instance associated with it, then null is returned.
+  //
+  // The scope argument is optional, and defaults to window.document.
+  window.HTMLWidgets.find = function(scope, selector) {
+    if (arguments.length == 1) {
+      selector = scope;
+      scope = document;
+    }
+
+    var el = scope.querySelector(selector);
+    if (el === null) {
+      return null;
+    } else {
+      return window.HTMLWidgets.getInstance(el);
+    }
+  };
+
+  // Finds all elements in the scope that match the selector, and
+  // returns the HTMLWidget instances (i.e. the return values of
+  // an HTMLWidget binding's initialize() or factory() function)
+  // associated with the elements, in an array. If elements that
+  // match the selector don't have an associated HTMLWidget
+  // instance, the returned array will contain nulls.
+  //
+  // The scope argument is optional, and defaults to window.document.
+  window.HTMLWidgets.findAll = function(scope, selector) {
+    if (arguments.length == 1) {
+      selector = scope;
+      scope = document;
+    }
+
+    var nodes = scope.querySelectorAll(selector);
+    var results = [];
+    for (var i = 0; i < nodes.length; i++) {
+      results.push(window.HTMLWidgets.getInstance(nodes[i]));
+    }
+    return results;
+  };
+
+  var postRenderHandlers = [];
+  function invokePostRenderHandlers() {
+    while (postRenderHandlers.length) {
+      var handler = postRenderHandlers.shift();
+      if (handler) {
+        handler();
+      }
+    }
+  }
+
+  // Register the given callback function to be invoked after the
+  // next time static widgets are rendered.
+  window.HTMLWidgets.addPostRenderHandler = function(callback) {
+    postRenderHandlers.push(callback);
+  };
+
+  // Takes a new-style instance-bound definition, and returns an
+  // old-style class-bound definition. This saves us from having
+  // to rewrite all the logic in this file to accomodate both
+  // types of definitions.
+  function createLegacyDefinitionAdapter(defn) {
+    var result = {
+      name: defn.name,
+      type: defn.type,
+      initialize: function(el, width, height) {
+        return defn.factory(el, width, height);
+      },
+      renderValue: function(el, x, instance) {
+        return instance.renderValue(x);
+      },
+      resize: function(el, width, height, instance) {
+        return instance.resize(width, height);
+      }
+    };
+
+    if (defn.find)
+      result.find = defn.find;
+    if (defn.renderError)
+      result.renderError = defn.renderError;
+    if (defn.clearError)
+      result.clearError = defn.clearError;
+
+    return result;
+  }
+})();
+
+</script>
+<script>function R2D3(el, width, height) {
+  var self = this;
+  var x = null;
+  var version = null;
+  
+  self.data = null;
+  self.shadow = null;
+  self.root = self.svg = self.canvas = null;
+  self.width = 0;
+  self.height = 0;
+  self.options = null;
+  self.resizer = null;
+  self.renderer = null;
+  self.rendererDefaut = true;
+  self.captureErrors = null;
+  self.theme = {};
+  self.style = null;
+  self.useShadow = true;
+  
+  self.setX = function(newX) {
+    x = newX;
+    self.data = x.data;
+    
+    if (x.type == "data.frame") {
+      self.data = HTMLWidgets.dataframeToD3(self.data);
+    }
+    
+    if (x.theme) {
+      self.theme = themeCapable() ? x.theme.runtime : x.theme.default;
+    }
+    
+    self.options = x.options;
+    
+    if (!x.useShadow) {
+      self.useShadow = false;
+    }
+  };
+  
+  self.setContainer = function(container) {
+    self.container = container;
+  };
+  
+  self.setRoot = function(root) {
+    self.root = self.svg = self.canvas = root;
+  };
+  
+  var createContainer = function() {
+    if (self.container == "svg")
+      return document.createElementNS("http://www.w3.org/2000/svg", "svg");
+    else
+      return document.createElement(self.container);
+  };
+  
+  self.createRoot = function() {
+    if (self.shadow === null) {
+      if (self.useShadow && el.attachShadow) {
+        self.shadow = el.attachShadow({
+          mode: "open"
+        });
+      }
+      else {
+        self.shadow = el;
+      }
+    }
+    
+    if (self.root !== null) {
+      self.d3().select(self.shadow).select(self.container).remove();
+      self.setRoot(null);
+    }
+    
+    var container = createContainer();
+    self.shadow.appendChild(container);
+    var root = self.d3().select(container)
+      .attr("width", self.width)
+      .attr("height", self.height);
+      
+    if (self.theme.background) root.style("background", self.theme.background);
+    if (self.theme.foreground) {
+      root.style("fill", self.theme.foreground);
+      root.style("color", self.theme.foreground);
+    }
+    
+    self.setRoot(root);
+    self.addStyle();
+  };
+  
+  self.setWidth = function(width) {
+    self.width = width;
+  };
+  
+  self.setHeight = function(height) {
+    self.height = height;
+  };
+  
+  self.onRender = function(renderer) {
+    self.renderer = renderer;
+    self.rendererDefaut = false;
+  };
+  
+  self.onResize = function(resizer) {
+    self.resizer = resizer;
+  };
+  
+  self.render = function() {
+    if (self.renderer === null) return;
+    
+    try {
+      self.renderer(self.data, self.root, self.width, self.height, self.options);
+    }
+    catch (err) {
+      self.showError(err, null, null);
+    }
+  };
+  
+  self.resize = function() {
+    if (self.resizer === null) return;
+    try {
+      self.resizer(self.width, self.height);
+    }
+    catch (err) {
+      self.showError(err, null, null);
+    }
+  };
+  
+  var simpleHash = function(data) {
+    var step = Math.max(1, Math.floor(data.length / 1000));
+
+    var hash = 0;
+    for (var idx = 0; idx < data.length; idx += step) {
+		  hash = ((hash << 5) - hash) + data.charCodeAt(idx);
+		  hash = hash & hash;
+    }
+    
+    return Math.abs(hash) % 1000;
+  };
+  
+  self.addScript = function(script) {
+    var el = document.createElement("script");
+    el.type = "text/javascript";
+    
+    var debugHeader = "//# sourceURL=r2d3-script-" + simpleHash(script) + "\n";
+    el.text = debugHeader + script;
+    
+    self.captureErrors = function(msg, url, lineNo, columnNo, error) {
+      self.showError({
+          message: msg,
+          stack: null
+        }, lineNo, columnNo);
+    };
+
+    document.head.appendChild(el);
+    self.captureErrors = null;
+  };
+  
+  self.setStyle = function(style) {
+    self.style = style;
+  };
+  
+  self.addStyle = function() {
+    if (!self.style) return;
+    
+    var el = document.createElement("style");
+            
+    el.type = "text/css";
+    if (el.styleSheet) {
+      el.styleSheet.cssText = self.style;
+    } else {
+      el.appendChild(document.createTextNode(self.style));
+    }
+    
+    self.root.node().appendChild(el);
+  };
+  
+  self.setVersion = function(newVersion) {
+    version = newVersion;
+  };
+  
+  self.d3 = function() {
+    switch(version) {
+      case 3:
+        return window.d3;
+      case 4:
+        return window.d3v4;
+      case 5:
+        return window.d3v5;
+    }
+  };
+  
+  var consoleLog = function(data) {
+    console.log(data);
+
+    var entry = document.createElement("div");
+    lastConsoleEntry = entry;
+    entry.style.bottom = "0";
+    entry.style.left = "0";
+    entry.style.right = "0";
+    entry.style.background = "rgb(244, 248, 249)";
+    entry.style.border = "1px solid #d6dadc";
+    entry.style.padding = "8px 15px 8px 15px";
+    entry.style.position = "absolute";
+    entry.style.fontFamily = "'Lucida Sans', 'DejaVu Sans', 'Lucida Grande', 'Segoe UI', Verdana, Helvetica, sans-serif, serif";
+    entry.style.fontSize = "9pt";
+    self.shadow.appendChild(entry);
+    
+    entry.style.transform = "translateY(40px)";
+    entry.style.opacity = "0";
+    entry.style.transition = "all 0.25s";
+    
+    entry.onmouseenter = function(e) {
+      consoleHovering = true;
+    };
+    
+    entry.onmouseleave = function(e) {
+      if (lastConsoleEntry == e.target) consoleHovering = false;
+    };
+    
+    setTimeout(function() {
+      entry.style.transform = "translateY(0)";
+      entry.style.opacity = "1";
+      entry.style.transition = "all 0.5s";
+    }, 50);
+    
+    entry.innerText = data;
+    
+    (function(entry) {
+      setTimeout(function() {
+        var hideConsole = function() {
+          entry.style.opacity = "0";
+          entry.addEventListener("transitionend", function(event) {
+            event.target.parentNode.removeChild(event.target);
+          });
+        };
+        
+        var retryHide = function() {
+          if (consoleHovering && lastConsoleEntry == entry) {
+            setTimeout(retryHide, 100);
+          }
+          else {
+            hideConsole();
+          }
+        };
+        
+        retryHide();
+      }, 3000);
+    })(entry);
+  };
+  
+  var consoleHovering = false;
+  var lastConsoleEntry = null;
+  var createConsoleOverride = function(type) {
+    return function(data) {
+      consoleLog(type + data);
+    };
+  };
+  
+  self.console = {
+    assert: console.assert,
+    clear: console.clear,
+    count: console.count,
+    error: createConsoleOverride("Error: "),
+    group: console.group,
+    groupCollapsed: console.groupCollapsed,
+    groupEnd: console.groupEnd,
+    info: createConsoleOverride("Info: "),
+    log: createConsoleOverride(""),
+    table: console.table,
+    time: console.time,
+    timeEnd: console.timeEnd,
+    trace: console.trace,
+    warn: console.warn
+  };
+  
+  self.callD3Script = function() {
+    var d3Script = self.d3Script;
+    
+    try {
+      d3Script(self.d3(), self, self.data, self.root, self.width, self.height, self.options, self.theme, self.console);
+    }
+    catch (err) {
+      self.showError(err, null, null);
+    }
+  };
+  
+  self.widgetRender = function(x) {
+    self.setX(x);
+    self.setWidth(width);
+    self.setHeight(height);
+    
+    if (!self.root) {
+      self.setVersion(x.version);
+      self.setStyle(x.style);
+      self.addScript(x.script);
+      self.d3Script = d3Script;
+      self.setContainer(x.container);
+      
+      self.createRoot();
+      
+      self.callD3Script();
+    }
+    
+    self.render();
+    
+    if (self.renderer === null) {
+      self.renderer = function(data, container, width, height, options) {
+        self.callD3Script();
+      };
+    }
+    
+    if (self.resizer === null) {
+      self.resizer = function(width, height) {
+        self.createRoot();
+        self.callD3Script();
+        if (!self.rendererDefaut) self.render();
+      };
+    }
+  };
+  
+  self.debounce = function(f, wait) {
+    var timeout = null;
+    return function() {
+      if (timeout) window.clearTimeout(timeout);
+      timeout = window.setTimeout(f, wait);
+    };
+  };
+  
+  self.resizeDebounce = self.debounce(self.resize, 100);
+  
+  self.widgetResize = function(width, height) {
+    self.root
+      .attr("width", width)
+      .attr("height", height);
+
+    self.setWidth(width);
+    self.setHeight(height);
+    
+    self.resizeDebounce();
+  };
+  
+  var openSource = function(filename, line, column, domain, highlight) {
+    if (window.parent.postMessage) {
+      window.parent.postMessage({
+        message: "openfile",
+        source: "r2d3",
+        file: filename,
+        line: line,
+        column: column,
+        highlight: highlight
+      }, domain);
+    }
+  };
+  
+  var themesLoaded = false;
+  var registerTheme = function(domain) {
+    domain = domain ? domain : window.location.origin;
+    if (window.parent.postMessage) {
+      window.addEventListener('message', function(event) {
+        if (typeof event.data != 'object')
+          return;
+      	if (event.origin !== domain)
+      	  return;
+    	  if (event.data.message !== "ontheme")
+          return;
+          
+        document.body.style.background = event.data.background;
+        
+        self.theme.background = event.data.background;
+        self.theme.foreground = event.data.foreground;
+      	
+      	// resize to give script chance to pick new theme
+      	if (themesLoaded) self.resize();
+      	themesLoaded = true;
+      }, false);
+      
+      window.parent.postMessage({
+        message: "ontheme",
+        source: "r2d3"
+      }, domain);
+    }
+  };
+  
+  var errorObject = null;
+  var errorLine = null;
+  var errorColumn = null;
+  var errorFile = null;
+  var errorHighlightOnce = false;
+  var hostDomain = null;
+  
+  var queryParameter = function(param) {
+    var query = window.location.search.substring(1);
+    var entries = query.split('&');
+    
+    for (var idxEntry = 0; idxEntry < entries.length; idxEntry++) {
+        var params = entries[idxEntry].split('=');
+        if (decodeURIComponent(params[0]) == param) {
+            return decodeURIComponent(params[1]);
+        }
+    }
+    
+    return null;
+  };
+  
+  var themeCapable = function() {
+    return queryParameter("capabilities") === "1";
+  };
+  
+  var registerMessageListeners = function(event) {
+    if (!themeCapable()) {
+      hostDomain = null;
+    } else {
+      hostDomain = queryParameter("host");
+      registerTheme(hostDomain);
+    }
+  };
+  
+  var cleanStackTrace = function(stack) {
+    var cleaned = stack.substr(0, stack.indexOf("at d3Script"));
+    cleaned = cleaned.replace(new RegExp("\\(.*/session/view[^/]*/lib/[^/]+/", "g"), "(");
+    cleaned = cleaned.replace(new RegExp("\\(.*/session/view[^/]*/", "g"), "(");
+    
+    return cleaned;
+  };
+  
+  var parseLineFileRef = function(line) {
+    var lines = x.script.split("\n");
+    line = Math.min(lines.length - 1, line);
+    
+    var header = "/* R2D3 Source File: ";
+    var file = null;
+    for (var maybe = line; line && maybe >= 0; maybe--) {
+      if (lines[maybe].includes(header)) {
+        var data = lines[maybe].split(header)[1];
+        var source = data.split("*/")[0].trim();
+        
+        line = line - (maybe + 2);
+        file = source;
+        
+        break;
+      }
+    }
+      
+    return {
+      file: file,
+      line: line
+    };
+  };
+  
+  var parseCallstackRef = function(callstack) {
+    var reg = new RegExp("at [^\\n]+ \\((<anonymous>|r2d3-script-[0-9]+):([0-9]+):([0-9]+)\\)");
+    var matches = reg.exec(callstack);
+    if (matches && matches.length === 4) {
+      
+      var line = parseInt(matches[2]);
+      var column = parseInt(matches[3]);
+      var file = null;
+      var lineRef = parseLineFileRef(line);
+      if (lineRef) {
+        file = lineRef.file;
+        line = lineRef.line;
+      }
+      
+      return {
+        file: file,
+        line: line,
+        column: column
+      };
+    }
+    else {
+      return null;
+    }
+  };
+  
+  var createSourceLink = function(path, line, column, domain) {
+    var name = baseName(path);
+    var linkEl = document.createElement("a");
+    linkEl.innerText = "(" + name + "#" + line + ":" + column + ")";
+    linkEl.href = "#";
+    linkEl.color = "#4531d6";
+    linkEl.style.display = "inline-block";
+    linkEl.style.textDecoration = "none";
+    linkEl.onclick = function() {
+      openSource(path, line, column, domain, false);
+    };
+    
+    return linkEl;
+  };
+  
+  var baseName = function(path) {
+    var parts = path.split(new RegExp("/|\\\\"));
+    return parts[parts.length - 1];
+  };
+  
+  var showErrorImpl = function() {
+    var message = errorObject, callstack = "";
+    
+    if (errorObject.message) message = errorObject.message;
+    if (errorObject.stack) callstack = errorObject.stack;
+    
+    if (errorLine === null || errorColumn === null) {
+      var parseResult = parseCallstackRef(callstack);
+      if (parseResult) {
+        errorFile = parseResult.file;
+        errorLine = parseResult.line;
+        errorColumn = parseResult.column;
+      }
+    }
+    else {
+      var parseLineResult = parseLineFileRef(errorLine);
+      if (parseLineResult) {
+        errorFile = parseLineResult.file;
+        errorLine = parseLineResult.line;
+      }
+    }
+    
+    if (errorFile) {
+      message = message + " in ";
+    }
+    
+    var container = document.getElementById("r2d3-error-container");
+    if (!container) {
+      container = document.createElement("div");
+      self.shadow.appendChild(container);
+    }
+    else {
+      container.innerHTML = "";
+    }
+    
+    container.id = "r2d3-error-container";
+    container.style.fontFamily = "'Lucida Sans', 'DejaVu Sans', 'Lucida Grande', 'Segoe UI', Verdana, Helvetica, sans-serif, serif";
+    container.style.fontSize = "9pt";
+    container.style.color = "#444";
+    container.style.position = "absolute";
+    container.style.top = "0";
+    container.style.left = "8px";
+    container.style.right = "8px";
+    container.style.overflow = "scroll";
+    container.style.lineHeight = "16px";
+    
+    var header = document.createElement("div");
+    header.innerText = "Error: " + message.replace("\n", "");
+    header.style.marginTop = "8px";
+    header.style.background = "rgb(244, 248, 249)";
+    header.style.border = "1px solid #d6dadc";
+    header.style.padding = "8px 15px 8px 15px";
+    header.style.lineHeight = "24px";
+    container.appendChild(header);
+    
+    if (errorFile) {
+      if (hostDomain) {
+        if (!errorHighlightOnce) {
+          openSource(errorFile, errorLine, errorColumn, hostDomain, true);
+          errorHighlightOnce = true;
+        }
+        
+        var linkEl = createSourceLink(errorFile, errorLine, errorColumn, hostDomain);
+        header.appendChild(linkEl);
+      }
+      else {
+        header.innerText = "Error: " + message.replace("\n", "") + " " + errorFile + "#" + errorLine + ":" + errorColumn;
+      }
+    }
+    
+    if (callstack) {
+      var stack = document.createElement("div");
+      var cleanStack = cleanStackTrace(callstack);
+      stack.style.display = "block";
+      stack.style.border = "1px solid #d6dadc";
+      stack.style.padding = "12px 15px 12px 15px";
+      stack.style.background = "#FFFFFF";
+      stack.style.borderTop = "0";
+      
+      var allEmpty = true;
+      var entries = cleanStack.split("\n");
+      for (var idxEntry in entries) {
+        var entry = entries[idxEntry];
+        var stackEl = document.createElement("div");
+        
+        var stackRes = parseCallstackRef(entry);
+        if (idxEntry === "0") {
+          header.appendChild(document.createElement("br"));
+          header.appendChild(document.createTextNode(entry));
+        } else if (hostDomain && stackRes) {
+          stackEl.innerText = entry.substr(
+            0,
+            Math.max(entry.indexOf("(<anony"), entry.indexOf("(r2d3-script-"))
+          );
+          var stackLinkEl = createSourceLink(stackRes.file, stackRes.line, stackRes.column, hostDomain);
+          stackEl.appendChild(stackLinkEl);
+        }
+        else {
+          stackEl.innerText = entry;
+        }
+        
+        if (stackEl.innerHTML.trim().length > 0)  stack.appendChild(stackEl);
+      }
+      
+      if (stack.childElementCount > 0)
+        container.appendChild(stack);
+    }
+  };
+  
+  self.showError = function(error, line, column) {
+    errorObject = error;
+    errorLine = line;
+    errorColumn = column;
+    
+    showErrorImpl();
+  };
+  
+  window.onerror = function (msg, url, lineNo, columnNo, error) {
+    if (self.captureErrors) {
+      self.captureErrors(msg, url, lineNo, columnNo, error);
+    }
+    
+    return false;
+  };
+  
+  registerMessageListeners();
+}</script>
+<script>// webcomponents.js requires Set api which is not available in all browsers
+if (typeof(Set) !== "undefined") {
+/**
+@license @nocompile
+Copyright (c) 2018 The Polymer Project Authors. All rights reserved.
+This code may only be used under the BSD style license found at http://polymer.github.io/LICENSE.txt
+The complete set of authors may be found at http://polymer.github.io/AUTHORS.txt
+The complete set of contributors may be found at http://polymer.github.io/CONTRIBUTORS.txt
+Code distributed by Google as part of the polymer project is also
+subject to an additional IP rights grant found at http://polymer.github.io/PATENTS.txt
+*/
+(function(){/*
+
+ Copyright (c) 2016 The Polymer Project Authors. All rights reserved.
+ This code may only be used under the BSD style license found at http://polymer.github.io/LICENSE.txt
+ The complete set of authors may be found at http://polymer.github.io/AUTHORS.txt
+ The complete set of contributors may be found at http://polymer.github.io/CONTRIBUTORS.txt
+ Code distributed by Google as part of the polymer project is also
+ subject to an additional IP rights grant found at http://polymer.github.io/PATENTS.txt
+*/
+'use strict';var q,aa="undefined"!=typeof window&&window===this?this:"undefined"!=typeof global&&null!=global?global:this,ba="function"==typeof Object.defineProperties?Object.defineProperty:function(a,b,c){a!=Array.prototype&&a!=Object.prototype&&(a[b]=c.value)};function ca(){ca=function(){};aa.Symbol||(aa.Symbol=da)}var da=function(){var a=0;return function(b){return"jscomp_symbol_"+(b||"")+a++}}();
+function ea(){ca();var a=aa.Symbol.iterator;a||(a=aa.Symbol.iterator=aa.Symbol("iterator"));"function"!=typeof Array.prototype[a]&&ba(Array.prototype,a,{configurable:!0,writable:!0,value:function(){return fa(this)}});ea=function(){}}function fa(a){var b=0;return ha(function(){return b<a.length?{done:!1,value:a[b++]}:{done:!0}})}function ha(a){ea();a={next:a};a[aa.Symbol.iterator]=function(){return this};return a}function ia(a){ea();var b=a[Symbol.iterator];return b?b.call(a):fa(a)}
+function ja(a){for(var b,c=[];!(b=a.next()).done;)c.push(b.value);return c}
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0:this._point=1,this._line?this._context.lineTo(t,n):this._context.moveTo(t,n);break;case 1:this._point=2;default:this._context.lineTo(t,n)}}};var u_=pc(oc);hc.prototype={areaStart:function(){this._curve.areaStart()},areaEnd:function(){this._curve.areaEnd()},lineStart:function(){this._curve.lineStart()},lineEnd:function(){this._curve.lineEnd()},point:function(t,n){this._curve.point(n*Math.sin(t),n*-Math.cos(t))}};var a_=Array.prototype.slice,c_={draw:function(t,n){var e=Math.sqrt(n/r_);t.moveTo(e,0),t.arc(0,0,e,0,o_)}},s_={draw:function(t,n){var e=Math.sqrt(n/5)/2;t.moveTo(-3*e,-e),t.lineTo(-e,-e),t.lineTo(-e,-3*e),t.lineTo(e,-3*e),t.lineTo(e,-e),t.lineTo(3*e,-e),t.lineTo(3*e,e),t.lineTo(e,e),t.lineTo(e,3*e),t.lineTo(-e,3*e),t.lineTo(-e,e),t.lineTo(-3*e,e),t.closePath()}},f_=Math.sqrt(1/3),l_=2*f_,h_={draw:function(t,n){var e=Math.sqrt(n/l_),r=e*f_;t.moveTo(0,-e),t.lineTo(r,0),t.lineTo(0,e),t.lineTo(-r,0),t.closePath()}},p_=Math.sin(r_/10)/Math.sin(7*r_/10),d_=Math.sin(o_/10)*p_,v_=-Math.cos(o_/10)*p_,g_={draw:function(t,n){var e=Math.sqrt(.8908130915292852*n),r=d_*e,i=v_*e;t.moveTo(0,-e),t.lineTo(r,i);for(var o=1;o<5;++o){var u=o_*o/5,a=Math.cos(u),c=Math.sin(u);t.lineTo(c*e,-a*e),t.lineTo(a*r-c*i,c*r+a*i)}t.closePath()}},__={draw:function(t,n){var e=Math.sqrt(n),r=-e/2;t.rect(r,r,e,e)}},y_=Math.sqrt(3),m_={draw:function(t,n){var e=-Math.sqrt(n/(3*y_));t.moveTo(0,2*e),t.lineTo(-y_*e,-e),t.lineTo(y_*e,-e),t.closePath()}},x_=Math.sqrt(3)/2,b_=1/Math.sqrt(12),w_=3*(b_/2+1),M_={draw:function(t,n){var e=Math.sqrt(n/w_),r=e/2,i=e*b_,o=r,u=e*b_+e,a=-o,c=u;t.moveTo(r,i),t.lineTo(o,u),t.lineTo(a,c),t.lineTo(-.5*r-x_*i,x_*r+-.5*i),t.lineTo(-.5*o-x_*u,x_*o+-.5*u),t.lineTo(-.5*a-x_*c,x_*a+-.5*c),t.lineTo(-.5*r+x_*i,-.5*i-x_*r),t.lineTo(-.5*o+x_*u,-.5*u-x_*o),t.lineTo(-.5*a+x_*c,-.5*c-x_*a),t.closePath()}},T_=[c_,s_,h_,__,g_,m_,M_];kc.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._y0=this._y1=NaN,this._point=0},lineEnd:function(){switch(this._point){case 3:Nc(this,this._x1,this._y1);case 2:this._context.lineTo(this._x1,this._y1)}(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,n){switch(t=+t,n=+n,this._point){case 0:this._point=1,this._line?this._context.lineTo(t,n):this._context.moveTo(t,n);break;case 1:this._point=2;break;case 2:this._point=3,this._context.lineTo((5*this._x0+this._x1)/6,(5*this._y0+this._y1)/6);default:Nc(this,t,n)}this._x0=this._x1,this._x1=t,this._y0=this._y1,this._y1=n}},Sc.prototype={areaStart:Tc,areaEnd:Tc,lineStart:function(){this._x0=this._x1=this._x2=this._x3=this._x4=this._y0=this._y1=this._y2=this._y3=this._y4=NaN,this._point=0},lineEnd:function(){switch(this._point){case 1:this._context.moveTo(this._x2,this._y2),this._context.closePath();break;case 2:this._context.moveTo((this._x2+2*this._x3)/3,(this._y2+2*this._y3)/3),this._context.lineTo((this._x3+2*this._x2)/3,(this._y3+2*this._y2)/3),this._context.closePath();break;case 3:this.point(this._x2,this._y2),this.point(this._x3,this._y3),this.point(this._x4,this._y4)}},point:function(t,n){switch(t=+t,n=+n,this._point){case 0:this._point=1,this._x2=t,this._y2=n;break;case 1:this._point=2,this._x3=t,this._y3=n;break;case 2:this._point=3,this._x4=t,this._y4=n,this._context.moveTo((this._x0+4*this._x1+t)/6,(this._y0+4*this._y1+n)/6);break;default:Nc(this,t,n)}this._x0=this._x1,this._x1=t,this._y0=this._y1,this._y1=n}},Ec.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._y0=this._y1=NaN,this._point=0},lineEnd:function(){(this._line||0!==this._line&&3===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,n){switch(t=+t,n=+n,this._point){case 0:this._point=1;break;case 1:this._point=2;break;case 2:this._point=3;var e=(this._x0+4*this._x1+t)/6,r=(this._y0+4*this._y1+n)/6;this._line?this._context.lineTo(e,r):this._context.moveTo(e,r);break;case 3:this._point=4;default:Nc(this,t,n)}this._x0=this._x1,this._x1=t,this._y0=this._y1,this._y1=n}},Ac.prototype={lineStart:function(){this._x=[],this._y=[],this._basis.lineStart()},lineEnd:function(){var t=this._x,n=this._y,e=t.length-1;if(e>0)for(var r,i=t[0],o=n[0],u=t[e]-i,a=n[e]-o,c=-1;++c<=e;)r=c/e,this._basis.point(this._beta*t[c]+(1-this._beta)*(i+r*u),this._beta*n[c]+(1-this._beta)*(o+r*a));this._x=this._y=null,this._basis.lineEnd()},point:function(t,n){this._x.push(+t),this._y.push(+n)}};var N_=function t(n){function e(t){return 1===n?new kc(t):new Ac(t,n)}return e.beta=function(n){return t(+n)},e}(.85);zc.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._point=0},lineEnd:function(){switch(this._point){case 2:this._context.lineTo(this._x2,this._y2);break;case 3:Cc(this,this._x1,this._y1)}(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,n){switch(t=+t,n=+n,this._point){case 0:this._point=1,this._line?this._context.lineTo(t,n):this._context.moveTo(t,n);break;case 1:this._point=2,this._x1=t,this._y1=n;break;case 2:this._point=3;default:Cc(this,t,n)}this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=n}};var k_=function t(n){function e(t){return new zc(t,n)}return e.tension=function(n){return t(+n)},e}(0);Pc.prototype={areaStart:Tc,areaEnd:Tc,lineStart:function(){this._x0=this._x1=this._x2=this._x3=this._x4=this._x5=this._y0=this._y1=this._y2=this._y3=this._y4=this._y5=NaN,this._point=0},lineEnd:function(){switch(this._point){case 1:this._context.moveTo(this._x3,this._y3),this._context.closePath();break;case 2:this._context.lineTo(this._x3,this._y3),this._context.closePath();break;case 3:this.point(this._x3,this._y3),this.point(this._x4,this._y4),this.point(this._x5,this._y5)}},point:function(t,n){switch(t=+t,n=+n,this._point){case 0:this._point=1,this._x3=t,this._y3=n;break;case 1:this._point=2,this._context.moveTo(this._x4=t,this._y4=n);break;case 2:this._point=3,this._x5=t,this._y5=n;break;default:Cc(this,t,n)}this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=n}};var S_=function t(n){function e(t){return new Pc(t,n)}return e.tension=function(n){return t(+n)},e}(0);Rc.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._point=0},lineEnd:function(){(this._line||0!==this._line&&3===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,n){switch(t=+t,n=+n,this._point){case 0:this._point=1;break;case 1:this._point=2;break;case 2:this._point=3,this._line?this._context.lineTo(this._x2,this._y2):this._context.moveTo(this._x2,this._y2);break;case 3:this._point=4;default:Cc(this,t,n)}this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=n}};var E_=function t(n){function e(t){return new Rc(t,n)}return e.tension=function(n){return t(+n)},e}(0);qc.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._l01_a=this._l12_a=this._l23_a=this._l01_2a=this._l12_2a=this._l23_2a=this._point=0},lineEnd:function(){switch(this._point){case 2:this._context.lineTo(this._x2,this._y2);break;case 3:this.point(this._x2,this._y2)}(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,n){if(t=+t,n=+n,this._point){var e=this._x2-t,r=this._y2-n;this._l23_a=Math.sqrt(this._l23_2a=Math.pow(e*e+r*r,this._alpha))}switch(this._point){case 0:this._point=1,this._line?this._context.lineTo(t,n):this._context.moveTo(t,n);break;case 1:this._point=2;break;case 2:this._point=3;default:Lc(this,t,n)}this._l01_a=this._l12_a,this._l12_a=this._l23_a,this._l01_2a=this._l12_2a,this._l12_2a=this._l23_2a,this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=n}};var A_=function t(n){function e(t){return n?new qc(t,n):new zc(t,0)}return e.alpha=function(n){return t(+n)},e}(.5);Dc.prototype={areaStart:Tc,areaEnd:Tc,lineStart:function(){this._x0=this._x1=this._x2=this._x3=this._x4=this._x5=this._y0=this._y1=this._y2=this._y3=this._y4=this._y5=NaN,this._l01_a=this._l12_a=this._l23_a=this._l01_2a=this._l12_2a=this._l23_2a=this._point=0},lineEnd:function(){switch(this._point){case 1:this._context.moveTo(this._x3,this._y3),this._context.closePath();break;case 2:this._context.lineTo(this._x3,this._y3),this._context.closePath();break;case 3:this.point(this._x3,this._y3),this.point(this._x4,this._y4),this.point(this._x5,this._y5)}},point:function(t,n){if(t=+t,n=+n,this._point){var e=this._x2-t,r=this._y2-n;this._l23_a=Math.sqrt(this._l23_2a=Math.pow(e*e+r*r,this._alpha))}switch(this._point){case 0:this._point=1,this._x3=t,this._y3=n;break;case 1:this._point=2,this._context.moveTo(this._x4=t,this._y4=n);break;case 2:this._point=3,this._x5=t,this._y5=n;break;default:Lc(this,t,n)}this._l01_a=this._l12_a,this._l12_a=this._l23_a,this._l01_2a=this._l12_2a,this._l12_2a=this._l23_2a,this._x0=this._x1,this._x1=this._x2,this._x2=t,this._y0=this._y1,this._y1=this._y2,this._y2=n}};var C_=function t(n){function e(t){return n?new Dc(t,n):new Pc(t,0)}return e.alpha=function(n){return 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n?new Uc(t,n):new Rc(t,0)}return e.alpha=function(n){return t(+n)},e}(.5);Oc.prototype={areaStart:Tc,areaEnd:Tc,lineStart:function(){this._point=0},lineEnd:function(){this._point&&this._context.closePath()},point:function(t,n){t=+t,n=+n,this._point?this._context.lineTo(t,n):(this._point=1,this._context.moveTo(t,n))}},Hc.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._y0=this._y1=this._t0=NaN,this._point=0},lineEnd:function(){switch(this._point){case 2:this._context.lineTo(this._x1,this._y1);break;case 3:Bc(this,this._t0,Yc(this,this._t0))}(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line=1-this._line},point:function(t,n){var e=NaN;if(t=+t,n=+n,t!==this._x1||n!==this._y1){switch(this._point){case 0:this._point=1,this._line?this._context.lineTo(t,n):this._context.moveTo(t,n);break;case 1:this._point=2;break;case 2:this._point=3,Bc(this,Yc(this,e=Ic(this,t,n)),e);break;default:Bc(this,this._t0,e=Ic(this,t,n))}this._x0=this._x1,this._x1=t,this._y0=this._y1,this._y1=n,this._t0=e}}},(jc.prototype=Object.create(Hc.prototype)).point=function(t,n){Hc.prototype.point.call(this,n,t)},Xc.prototype={moveTo:function(t,n){this._context.moveTo(n,t)},closePath:function(){this._context.closePath()},lineTo:function(t,n){this._context.lineTo(n,t)},bezierCurveTo:function(t,n,e,r,i,o){this._context.bezierCurveTo(n,t,r,e,o,i)}},Vc.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x=[],this._y=[]},lineEnd:function(){var t=this._x,n=this._y,e=t.length;if(e)if(this._line?this._context.lineTo(t[0],n[0]):this._context.moveTo(t[0],n[0]),2===e)this._context.lineTo(t[1],n[1]);else for(var r=$c(t),i=$c(n),o=0,u=1;u<e;++o,++u)this._context.bezierCurveTo(r[0][o],i[0][o],r[1][o],i[1][o],t[u],n[u]);(this._line||0!==this._line&&1===e)&&this._context.closePath(),this._line=1-this._line,this._x=this._y=null},point:function(t,n){this._x.push(+t),this._y.push(+n)}},Wc.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x=this._y=NaN,this._point=0},lineEnd:function(){0<this._t&&this._t<1&&2===this._point&&this._context.lineTo(this._x,this._y),(this._line||0!==this._line&&1===this._point)&&this._context.closePath(),this._line>=0&&(this._t=1-this._t,this._line=1-this._line)},point:function(t,n){switch(t=+t,n=+n,this._point){case 0:this._point=1,this._line?this._context.lineTo(t,n):this._context.moveTo(t,n);break;case 1:this._point=2;default:if(this._t<=0)this._context.lineTo(this._x,n),this._context.lineTo(t,n);else{var e=this._x*(1-this._t)+t*this._t;this._context.lineTo(e,this._y),this._context.lineTo(e,n)}}this._x=t,this._y=n}},rs.prototype={constructor:rs,insert:function(t,n){var e,r,i;if(t){if(n.P=t,n.N=t.N,t.N&&(t.N.P=n),t.N=n,t.R){for(t=t.R;t.L;)t=t.L;t.L=n}else t.R=n;e=t}else this._?(t=as(this._),n.P=null,n.N=t,t.P=t.L=n,e=t):(n.P=n.N=null,this._=n,e=null);for(n.L=n.R=null,n.U=e,n.C=!0,t=n;e&&e.C;)e===(r=e.U).L?(i=r.R)&&i.C?(e.C=i.C=!1,r.C=!0,t=r):(t===e.R&&(os(this,e),e=(t=e).U),e.C=!1,r.C=!0,us(this,r)):(i=r.L)&&i.C?(e.C=i.C=!1,r.C=!0,t=r):(t===e.L&&(us(this,e),e=(t=e).U),e.C=!1,r.C=!0,os(this,r)),e=t.U;this._.C=!1},remove:function(t){t.N&&(t.N.P=t.P),t.P&&(t.P.N=t.N),t.N=t.P=null;var n,e,r,i=t.U,o=t.L,u=t.R;if(e=o?u?as(u):o:u,i?i.L===t?i.L=e:i.R=e:this._=e,o&&u?(r=e.C,e.C=t.C,e.L=o,o.U=e,e!==u?(i=e.U,e.U=t.U,t=e.R,i.L=t,e.R=u,u.U=e):(e.U=i,i=e,t=e.R)):(r=t.C,t=e),t&&(t.U=i),!r)if(t&&t.C)t.C=!1;else{do{if(t===this._)break;if(t===i.L){if((n=i.R).C&&(n.C=!1,i.C=!0,os(this,i),n=i.R),n.L&&n.L.C||n.R&&n.R.C){n.R&&n.R.C||(n.L.C=!1,n.C=!0,us(this,n),n=i.R),n.C=i.C,i.C=n.R.C=!1,os(this,i),t=this._;break}}else if((n=i.L).C&&(n.C=!1,i.C=!0,us(this,i),n=i.L),n.L&&n.L.C||n.R&&n.R.C){n.L&&n.L.C||(n.R.C=!1,n.C=!0,os(this,n),n=i.L),n.C=i.C,i.C=n.L.C=!1,us(this,i),t=this._;break}n.C=!0,t=i,i=i.U}while(!t.C);t&&(t.C=!1)}}};var P_,R_,L_,q_,D_,U_=[],O_=[],F_=1e-6,I_=1e-12;Ns.prototype={constructor:Ns,polygons:function(){var t=this.edges;return this.cells.map(function(n){var e=n.halfedges.map(function(e){return ds(n,t[e])});return e.data=n.site.data,e})},triangles:function(){var t=[],n=this.edges;return this.cells.forEach(function(e,r){if(o=(i=e.halfedges).length)for(var i,o,u,a=e.site,c=-1,s=n[i[o-1]],f=s.left===a?s.right:s.left;++c<o;)u=f,f=(s=n[i[c]]).left===a?s.right:s.left,u&&f&&r<u.index&&r<f.index&&Ms(a,u,f)<0&&t.push([a.data,u.data,f.data])}),t},links:function(){return this.edges.filter(function(t){return t.right}).map(function(t){return{source:t.left.data,target:t.right.data}})},find:function(t,n,e){for(var r,i,o=this,u=o._found||0,a=o.cells.length;!(i=o.cells[u]);)if(++u>=a)return null;var c=t-i.site[0],s=n-i.site[1],f=c*c+s*s;do{i=o.cells[r=u],u=null,i.halfedges.forEach(function(e){var r=o.edges[e],a=r.left;if(a!==i.site&&a||(a=r.right)){var c=t-a[0],s=n-a[1],l=c*c+s*s;l<f&&(f=l,u=a.index)}})}while(null!==u);return o._found=r,null==e||f<=e*e?i.site:null}},Ss.prototype={constructor:Ss,scale:function(t){return 1===t?this:new Ss(this.k*t,this.x,this.y)},translate:function(t,n){return 0===t&0===n?this:new Ss(this.k,this.x+this.k*t,this.y+this.k*n)},apply:function(t){return[t[0]*this.k+this.x,t[1]*this.k+this.y]},applyX:function(t){return t*this.k+this.x},applyY:function(t){return t*this.k+this.y},invert:function(t){return[(t[0]-this.x)/this.k,(t[1]-this.y)/this.k]},invertX:function(t){return(t-this.x)/this.k},invertY:function(t){return(t-this.y)/this.k},rescaleX:function(t){return t.copy().domain(t.range().map(this.invertX,this).map(t.invert,t))},rescaleY:function(t){return t.copy().domain(t.range().map(this.invertY,this).map(t.invert,t))},toString:function(){return"translate("+this.x+","+this.y+") scale("+this.k+")"}};var Y_=new Ss(1,0,0);Es.prototype=Ss.prototype,t.version="4.13.0",t.bisect=Os,t.bisectRight=Os,t.bisectLeft=Fs,t.ascending=n,t.bisector=e,t.cross=function(t,n,e){var i,o,u,a,c=t.length,s=n.length,f=new Array(c*s);for(null==e&&(e=r),i=u=0;i<c;++i)for(a=t[i],o=0;o<s;++o,++u)f[u]=e(a,n[o]);return f},t.descending=function(t,n){return n<t?-1:n>t?1:n>=t?0:NaN},t.deviation=u,t.extent=a,t.histogram=function(){function t(t){var i,o,u=t.length,a=new Array(u);for(i=0;i<u;++i)a[i]=n(t[i],i,t);var 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predicts that for the selected instance (gender = female), prediction is equal to 0.123<\/br><\/br>The most important change in H2o's prediction would occur for gender = \"male\". It increases the prediction by 0.749. <\/br> <\/br><\/br><\/br>All variables are being displayed."}],"age":[{"type":"desc","text":"H2o predicts that for the selected instance (age = 28), prediction is equal to 0.123<\/br><\/br>The highest prediction occurs for (age = 69), while the lowest for (age = 4.5).<\/br>Breakpoint is identified at (age = 48).<\/br><\/br>Average model responses are *higher* for variable values *higher* than breakpoint (= 48)."}],"class":[{"type":"desc","text":"H2o predicts that for the selected instance (class = 2nd), prediction is equal to 0.123<\/br><\/br>The most important change in H2o's prediction would occur for class = \"3rd\". It increases the prediction by 0.159. <\/br>The second most important change in the prediction would occur for class = \"restaurant staff\". It increases the prediction by 0.124. <\/br>The third most important change in the prediction would occur for class = \"1st\". It decreases the prediction by 0.037.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.035."}],"embarked":[{"type":"desc","text":"H2o predicts that for the selected instance (embarked = Cherbourg), prediction is equal to 0.123<\/br><\/br>The most important change in H2o's prediction would occur for embarked = \"Southampton\". It increases the prediction by 0.12. <\/br>The second most important change in the prediction would occur for embarked = \"Belfast\". It increases the prediction by 0.107. <\/br>The third most important change in the prediction would occur for embarked = \"Queenstown\". It increases the prediction by 0.071.<\/br><\/br>All variables are being displayed."}],"fare":[{"type":"desc","text":"H2o predicts that for the selected instance (fare = 24), prediction is equal to 0.123<\/br><\/br>The highest prediction occurs for (fare = 21), while the lowest for (fare = 512.0607).<\/br>Breakpoint is identified at (fare = 33.1).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 33.1)."}],"sibsp":[{"type":"desc","text":"H2o predicts that for the selected instance (sibsp = 1), prediction is equal to 0.123<\/br><\/br>The highest prediction occurs for (sibsp = 8), while the lowest for (sibsp = 0).<\/br>Breakpoint is identified at (sibsp = 2).<\/br><\/br>Average model responses are *higher* for variable values *higher* than breakpoint (= 2)."}],"parch":[{"type":"desc","text":"H2o predicts that for the selected instance (parch = 0), prediction is equal to 0.123<\/br><\/br>The highest prediction occurs for (parch = 6), while the lowest for (parch = 1).<\/br>Breakpoint is identified at (parch = 2).<\/br><\/br>Average model responses are *higher* for variable values *higher* than breakpoint (= 2)."}]}},{"x":[{"variable_name":"gender","variable":"gender = female","contribution":-0.497,"variable_value":"female","sign":"-1","label":"h2o","barStart":0.1671,"barSupport":0.6639,"tooltipText":"gender = female<br>decreases average response <br>by 0.497","min":0.0944,"q1":0.1071,"q3":0.225,"max":0.2879},{"variable_name":"embarked","variable":"embarked = Cherbourg","contribution":-0.069,"variable_value":"Cherbourg","sign":"-1","label":"h2o","barStart":0.5953,"barSupport":0.6639,"tooltipText":"embarked = Cherbourg<br>decreases average response <br>by 0.069","min":0.5407,"q1":0.5644,"q3":0.6233,"max":0.6343},{"variable_name":"fare","variable":"fare = 24","contribution":0.034,"variable_value":"24","sign":"1","label":"h2o","barStart":0.6639,"barSupport":0.6976,"tooltipText":"fare = 24<br>increases average response <br>by 0.034","min":0.6697,"q1":0.6924,"q3":0.7076,"max":0.7136},{"variable_name":"sibsp","variable":"sibsp = 1","contribution":0.016,"variable_value":"1","sign":"1","label":"h2o","barStart":0.6639,"barSupport":0.6799,"tooltipText":"sibsp = 1<br>increases average response <br>by 0.016","min":0.6669,"q1":0.6701,"q3":0.6812,"max":0.6979},{"variable_name":"age","variable":"age = 28","contribution":-0.016,"variable_value":"28","sign":"-1","label":"h2o","barStart":0.6481,"barSupport":0.6639,"tooltipText":"age = 28<br>decreases average response <br>by 0.016","min":0.6299,"q1":0.6343,"q3":0.6637,"max":0.6776},{"variable_name":"class","variable":"class = 2nd","contribution":-0.012,"variable_value":"2nd","sign":"-1","label":"h2o","barStart":0.6515,"barSupport":0.6639,"tooltipText":"class = 2nd<br>decreases average response <br>by 0.012","min":0.5651,"q1":0.6053,"q3":0.6782,"max":0.7231},{"variable_name":"parch","variable":"parch = 0","contribution":0.003,"variable_value":"0","sign":"1","label":"h2o","barStart":0.6639,"barSupport":0.6667,"tooltipText":"parch = 0<br>increases average response <br>by 0.003","min":0.6632,"q1":0.665,"q3":0.6683,"max":0.6707}],"m":[7],"x_min_max":[0.017,0.7977],"desc":[{"type":"desc","text":"H2o predicts, that the prediction for the selected instance is 0.123 which is lower than the average model prediction 0.664. For the selected instance model's prediction is lower, than for 92% of all observations.<\/br><\/br>The most important variable is gender (= female). It decreases the prediction by 0.497.<\/br>The second most important variable is embarked (= Cherbourg). It decreases the prediction by 0.069.<\/br>The third most important variable is fare (= 24). It increases the prediction by 0.034.<\/br>The average contribution of all the above variables is significant.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is -0.009."}]}],"id2":[{"x":[{"variable":"intercept","contribution":0,"variable_name":"intercept","variable_value":"1","cumulative":0.664,"sign":"X","position":9,"label":"h2o","barStart":0.6639,"barSupport":0.6639,"tooltipText":"Average response: 0.664<br>Prediction: 0.877"},{"variable":"gender = male","contribution":0.114,"variable_name":"gender","variable_value":"male","cumulative":0.778,"sign":"1","position":8,"label":"h2o","barStart":0.6639,"barSupport":0.778,"tooltipText":"gender = male<br>increases average response <br>by 0.114"},{"variable":"class = 3rd","contribution":0.077,"variable_name":"class","variable_value":"3rd","cumulative":0.855,"sign":"1","position":7,"label":"h2o","barStart":0.778,"barSupport":0.8547,"tooltipText":"class = 3rd<br>increases average response <br>by 0.077"},{"variable":"embarked = Cherbourg","contribution":0.003,"variable_name":"embarked","variable_value":"Cherbourg","cumulative":0.858,"sign":"1","position":6,"label":"h2o","barStart":0.8547,"barSupport":0.858,"tooltipText":"embarked = Cherbourg<br>increases average response <br>by 0.003"},{"variable":"age = 27","contribution":-0.018,"variable_name":"age","variable_value":"27","cumulative":0.84,"sign":"-1","position":5,"label":"h2o","barStart":0.8404,"barSupport":0.858,"tooltipText":"age = 27<br>decreases average response <br>by 0.018"},{"variable":"fare = 18.15","contribution":0.024,"variable_name":"fare","variable_value":"18.15","cumulative":0.865,"sign":"1","position":4,"label":"h2o","barStart":0.8404,"barSupport":0.8648,"tooltipText":"fare = 18.15<br>increases average response <br>by 0.024"},{"variable":"sibsp = 0","contribution":-0.009,"variable_name":"sibsp","variable_value":"0","cumulative":0.855,"sign":"-1","position":3,"label":"h2o","barStart":0.8553,"barSupport":0.8648,"tooltipText":"sibsp = 0<br>decreases average response <br>by 0.009"},{"variable":"parch = 0","contribution":0.022,"variable_name":"parch","variable_value":"0","cumulative":0.877,"sign":"1","position":2,"label":"h2o","barStart":0.8553,"barSupport":0.8768,"tooltipText":"parch = 0<br>increases average response <br>by 0.022"},{"variable":"prediction","contribution":0.213,"variable_name":"prediction","variable_value":"","cumulative":0.877,"sign":"X","position":1,"label":"h2o","barStart":0.6639,"barSupport":0.8768,"tooltipText":"Average response: 0.664<br>Prediction: 0.877"}],"m":[9],"x_min_max":[0.6214,0.9196],"desc":[{"type":"desc","text":"H2o predicts, that the prediction for the selected instance is 0.877 which is higher than the average model prediction 0.664.<\/br><\/br>The most important variable is gender (= male). It increases the prediction by 0.114.<\/br>The second most important variable is class (= 3rd). It increases the prediction by 0.077.<\/br>The third most important variable is fare (= 18.15). It increases the prediction by 0.024.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is 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predicts that for the selected instance (gender = male), prediction is equal to 0.877<\/br><\/br>The most important change in H2o's prediction would occur for gender = \"female\". It decreases the prediction by 0.721. <\/br> <\/br><\/br><\/br>All variables are being displayed."}],"age":[{"type":"desc","text":"H2o predicts that for the selected instance (age = 27), prediction is equal to 0.877<\/br><\/br>The highest prediction occurs for (age = 69), while the lowest for (age = 0.3333333333).<\/br>Breakpoint is identified at (age = 4.5).<\/br><\/br>Average model responses are *lower* for variable values *lower* than breakpoint(= 4.5)."}],"class":[{"type":"desc","text":"H2o predicts that for the selected instance (class = 3rd), prediction is equal to 0.877<\/br><\/br>The most important change in H2o's prediction would occur for class = \"deck crew\". It decreases the prediction by 0.606. <\/br>The second most important change in the prediction would occur for class = \"1st\". It decreases the prediction by 0.593. <\/br>The third most important change in the prediction would occur for class = \"engineering crew\". It decreases the prediction by 0.121.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.064."}],"embarked":[{"type":"desc","text":"H2o predicts that for the selected instance (embarked = Cherbourg), prediction is equal to 0.877<\/br><\/br>The most important change in H2o's prediction would occur for embarked = \"Queenstown\". It increases the prediction by 0.028. <\/br>The second most important change in the prediction would occur for embarked = \"Southampton\". It increases the prediction by 0.021. <\/br>The third most important change in the prediction would occur for embarked = \"Belfast\". It increases the prediction by 0.018.<\/br><\/br>All variables are being displayed."}],"fare":[{"type":"desc","text":"H2o predicts that for the selected instance (fare = 18.151), prediction is equal to 0.877<\/br><\/br>The highest prediction occurs for (fare = 21), while the lowest for (fare = 56.1807).<\/br>Breakpoint is identified at (fare = 26).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 26)."}],"sibsp":[{"type":"desc","text":"H2o predicts that for the selected instance (sibsp = 0), prediction is equal to 0.877<\/br><\/br>The highest prediction occurs for (sibsp = 2), while the lowest for (sibsp = 0).<\/br>Breakpoint is identified at (sibsp = 0).<\/br><\/br>Average model responses are *higher* for variable values *higher* than breakpoint (= 0)."}],"parch":[{"type":"desc","text":"H2o predicts that for the selected instance (parch = 0), prediction is equal to 0.877<\/br><\/br>The highest prediction occurs for (parch = 0), while the lowest for (parch = 1).<\/br>Breakpoint is identified at (parch = 0).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 0)."}]}},{"x":[{"variable_name":"gender","variable":"gender = male","contribution":0.13,"variable_value":"male","sign":"1","label":"h2o","barStart":0.6639,"barSupport":0.7938,"tooltipText":"gender = male<br>increases average response <br>by 0.13","min":0.7766,"q1":0.778,"q3":0.8039,"max":0.8327},{"variable_name":"class","variable":"class = 3rd","contribution":0.111,"variable_value":"3rd","sign":"1","label":"h2o","barStart":0.6639,"barSupport":0.7749,"tooltipText":"class = 3rd<br>increases average response <br>by 0.111","min":0.7413,"q1":0.7634,"q3":0.7916,"max":0.8112},{"variable_name":"fare","variable":"fare = 18.15","contribution":0.031,"variable_value":"18.15","sign":"1","label":"h2o","barStart":0.6639,"barSupport":0.6951,"tooltipText":"fare = 18.15<br>increases average response <br>by 0.031","min":0.6822,"q1":0.6914,"q3":0.6987,"max":0.7096},{"variable_name":"embarked","variable":"embarked = Cherbourg","contribution":-0.03,"variable_value":"Cherbourg","sign":"-1","label":"h2o","barStart":0.6335,"barSupport":0.6639,"tooltipText":"embarked = Cherbourg<br>decreases average response <br>by 0.03","min":0.6044,"q1":0.6266,"q3":0.6448,"max":0.6568},{"variable_name":"age","variable":"age = 27","contribution":-0.03,"variable_value":"27","sign":"-1","label":"h2o","barStart":0.634,"barSupport":0.6639,"tooltipText":"age = 27<br>decreases average response <br>by 0.03","min":0.6073,"q1":0.6207,"q3":0.6481,"max":0.6634},{"variable_name":"parch","variable":"parch = 0","contribution":0.008,"variable_value":"0","sign":"1","label":"h2o","barStart":0.6639,"barSupport":0.6721,"tooltipText":"parch = 0<br>increases average response <br>by 0.008","min":0.6639,"q1":0.6696,"q3":0.6734,"max":0.6791},{"variable_name":"sibsp","variable":"sibsp = 0","contribution":-0.007,"variable_value":"0","sign":"-1","label":"h2o","barStart":0.6568,"barSupport":0.6639,"tooltipText":"sibsp = 0<br>decreases average response <br>by 0.007","min":0.6531,"q1":0.6549,"q3":0.6587,"max":0.661}],"m":[7],"x_min_max":[0.5932,0.8314],"desc":[{"type":"desc","text":"H2o predicts, that the prediction for the selected instance is 0.877 which is higher than the average model prediction 0.664.For the selected instance model's prediction is higher, than for 72% of all observations.<\/br><\/br>The most important variable is gender (= male). It increases the prediction by 0.13.<\/br>The second most important variable is class (= 3rd). It increases the prediction by 0.111.<\/br>The third most important variable is fare (= 18.15). It increases the prediction by 0.031.<\/br>The average contribution of all the above variables is significant.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is -0.059."}]}]},{"x":[{"variable":"embarked","label":"H2OBinomialModel","dropout_loss":0.757,"full_model":0.754,"min":0.7548,"q1":0.7562,"q3":0.7572,"max":0.7582},{"variable":"parch","label":"H2OBinomialModel","dropout_loss":0.751,"full_model":0.754,"min":0.7505,"q1":0.7512,"q3":0.7517,"max":0.7524},{"variable":"sibsp","label":"H2OBinomialModel","dropout_loss":0.751,"full_model":0.754,"min":0.7493,"q1":0.7498,"q3":0.7515,"max":0.7519},{"variable":"fare","label":"H2OBinomialModel","dropout_loss":0.746,"full_model":0.754,"min":0.7434,"q1":0.745,"q3":0.7465,"max":0.7474},{"variable":"age","label":"H2OBinomialModel","dropout_loss":0.74,"full_model":0.754,"min":0.735,"q1":0.7366,"q3":0.7447,"max":0.746},{"variable":"class","label":"H2OBinomialModel","dropout_loss":0.72,"full_model":0.754,"min":0.7167,"q1":0.7183,"q3":0.7205,"max":0.7238},{"variable":"gender","label":"H2OBinomialModel","dropout_loss":0.676,"full_model":0.754,"min":0.6624,"q1":0.672,"q3":0.679,"max":0.6895}],"m":[7],"x_min_max":[0.6592,0.7699],"desc":[{"type":"desc","text":"The number of important variables for H2OBinomialModel's prediction is 0 out of 7. <\/br> Variables NA have the highest 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mean prediction is equal to 0.66<\/br><\/br>The most important change in H2OBinomialModel's prediction would occur for gender = \"female\". It decreases the prediction by 0.437. <\/br>The second most important change in the prediction would occur for gender = \"male\". It increases the prediction by 0.116. <\/br><\/br><\/br>All variables are being displayed."}],"age":[{"type":"desc","text":"H2OBinomialModel's mean prediction is equal to 0.66<\/br><\/br>The most important change in H2OBinomialModel's prediction would occur for age = \"0.3333333333\". It decreases the prediction by 0.398. <\/br>The second most important change in the prediction would occur for age = \"1\". It decreases the prediction by 0.388. <\/br>The third most important change in the prediction would occur for age = \"2\". It decreases the prediction by 0.377.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.315."}],"class":[{"type":"desc","text":"H2OBinomialModel's mean prediction is equal to 0.66<\/br><\/br>The most important change in H2OBinomialModel's prediction would occur for class = \"deck crew\". It decreases the prediction by 0.302. <\/br>The second most important change in the prediction would occur for class = \"1st\". It decreases the prediction by 0.187. <\/br>The third most important change in the prediction would occur for class = \"3rd\". It increases the prediction by 0.106.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.104."}],"embarked":[{"type":"desc","text":"H2OBinomialModel's mean prediction is equal to 0.66<\/br><\/br>The most important change in H2OBinomialModel's prediction would occur for embarked = \"Queenstown\". It increases the prediction by 0.046. <\/br>The second most important change in the prediction would occur for embarked = \"Belfast\". It increases the prediction by 0.025. <\/br>The third most important change in the prediction would occur for embarked = \"Cherbourg\". It decreases the prediction by 0.025.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.015."}],"fare":[{"type":"desc","text":"H2OBinomialModel's mean prediction is equal to 0.66<\/br><\/br>The most important change in H2OBinomialModel's prediction would occur for fare = \"56.1807\". It decreases the prediction by 0.061. <\/br>The second most important change in the prediction would occur for fare = \"512.0607\". It decreases the prediction by 0.06. <\/br>The third most important change in the prediction would occur for fare = \"21\". It increases the prediction by 0.038.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.038."}],"sibsp":[{"type":"desc","text":"H2OBinomialModel's mean prediction is equal to 0.66<\/br><\/br>The most important change in H2OBinomialModel's prediction would occur for sibsp = \"8\". It increases the prediction by 0.096. <\/br>The second most important change in the prediction would occur for sibsp = \"4\". It increases the prediction by 0.064. <\/br>The third most important change in the prediction would occur for sibsp = \"3\". It increases the prediction by 0.046.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.041."}],"parch":[{"type":"desc","text":"H2OBinomialModel's mean prediction is equal to 0.66<\/br><\/br>The most important change in H2OBinomialModel's prediction would occur for parch = \"1\". It decreases the prediction by 0.026. <\/br>The second most important change in the prediction would occur for parch = \"6\". It increases the prediction by 0.01. <\/br>The third most important change in the prediction would occur for parch = \"2\". It decreases the prediction by 0.007.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 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single text\n\n  var canvas = document.createElement('canvas');\n  var context = canvas.getContext('2d');\n  context.font = fontSize + 'px ' + fontFace;\n  return context.measureText(text).width;\n}\n\nfunction wrapText(text, width) {\n  // this function wraps text\n  text.each(function () {\n      var text = d3.select(this).style('font-family', 'Fira Sans, sans-serif'),\n          words = text.text().split(/\\s+/).reverse(),\n          word,\n          line = [],\n          lineNumber = 0,\n          lineHeight = 1.05, // ems\n          x = text.attr(\"x\"),\n          y = text.attr(\"y\"),\n          dy = 0, //parseFloat(text.attr(\"dy\")),\n          tspan = text.text(null)\n                      .append(\"tspan\")\n                      .attr(\"x\", x)\n                      .attr(\"y\", y)\n                      .attr(\"dy\", dy + \"em\");\n      while (word = words.pop()) {\n          line.push(word);\n          tspan.text(line.join(\" \"));\n          if (tspan.node().getComputedTextLength() > width) {\n              line.pop();\n              tspan.text(line.join(\" \"));\n              line = [word];\n              tspan = text.append(\"tspan\")\n                          .attr(\"x\", x)\n                          .attr(\"y\", y)\n                          .attr(\"dy\", ++lineNumber * lineHeight + dy + \"em\")\n                          .text(word);\n          }\n      }\n  });\n}\n\nfunction wrapHtmlOutput(text) {\n  var output = \"\";\n  text.replace(/\\(?[A-Z][^\\.]+[\\.!\\?]\\)?/g, function (sentence) {\n      output += (sentence + '<br>');\n  });\n  return output;\n}\n\n/* R2D3 Source File:   */\n/* d3.tip Copyright (c) 2013 Justin Palmer Tooltips for d3.js SVG visualizations */\n/// MADE SOME CHANGES\n\nd3.functor = function functor(v) {\n  return typeof v === \"function\" ? v : function() {\n    return v;\n  };\n};\n\nd3.tip = function(widget_id) {\n\n  var direction = d3_tip_direction,\n      offset    = d3_tip_offset,\n      html      = d3_tip_html,\n      node      = initNode(),\n      svg       = null,\n      point     = null,\n      target    = null,\n      widget_id = widget_id;\n\n  function tip(vis) {\n    svg = getSVGNode(vis)\n    point = svg.createSVGPoint()\n    document.getElementById(widget_id).appendChild(node)\n  }\n\n  // Public - show the tooltip on the screen\n  //\n  // Returns a tip\n  tip.show = function() {\n    var args = Array.prototype.slice.call(arguments)\n    if(args[args.length - 1] instanceof SVGElement) target = args.pop()\n\n    var content = html.apply(this, args),\n        poffset = offset.apply(this, args),\n        dir     = direction.apply(this, args),\n        nodel   = getNodeEl(),\n        i       = directions.length,\n        coords,\n        scrollTop  = document.documentElement.scrollTop || document.body.scrollTop,\n        scrollLeft = document.documentElement.scrollLeft || document.body.scrollLeft\n\n    /// unclass all directions\n    while(i--) nodel.classed(directions[i], false)\n\n    ////////////////////////////////:::::::::////////////////////////////////\n    // make sure that tip is pointing right direction (not outside of svg) \\\\\n    // 'n' means that tooltip will go north from pointer\n\n    // do not move this code V\n    nodel.html(content)\n          .style('position', 'fixed')\n          .style('opacity', .8)\n          .style('pointer-events', 'all')\n    // do not move this code ^\n\n    var tdir = dir;\n\n    var divDim = node.getBoundingClientRect(),\n        svgDim = svg.getBBox();\n\n    // 20 is for 2x r2d3 margin and 7 was added empiricaly\n    var sh = 20 + svgDim.height;// + 7; // this is modelStudio plotHeight\n    var sw = 20 + svgDim.width;\n    var dh = divDim.height;\n    var dw = divDim.width;\n    var py = d3.event.pageY;\n    var px = d3.event.pageX;\n\n    // by default put tooltip 'n'\n    var ttop = py - dh - 5;\n    var tleft = px - dw/2;\n    var tdir = \"n\";\n    var tpdd = '6px 6px 13px 6px';\n\n    if (px - dw/2 < 10) {\n      tleft = px + 5;\n      tdir = \"ne\";\n      tpdd = '6px 6px 11px 11px';\n      if (py - dh/2 < 10) {\n        ttop = py - dh/2;\n        tdir = \"e\";\n        tpdd = '6px 6px 6px 13px';\n      } else if (py - dh < 10) {\n        ttop = py + 5;\n        tdir = \"se\";\n        tpdd = '11px 6px 6px 11px';\n      }\n    } else if (px + dw/2 > sw - 10) {\n      tleft = px - dw - 5;\n      ttop = py - dh - 5;\n      tdir = \"nw\";\n      tpdd = '6px 11px 11px 6px';\n      if (py - dh/2 < 10) {\n        ttop = py - dh/2;\n        tdir = \"w\"\n        tpdd = '6px 13px 6px 6px';\n      } else if (py - dh < 10) {\n        ttop = py + 5;\n        tdir = \"sw\";\n        tpdd = '11px 11px 6px 6px';\n      }\n      // because description is to long FIXME/TODO: more cases\n      if (tleft < 5) {\n        ttop = py + 5;\n        tleft = px - dw/2;\n        tdir = \"s\";\n        tpdd = '13px 6px 6px 6px';\n      }\n    } else if (py - dh < 10) {\n      ttop = py + 5;\n      tleft = px - dw/2;\n      tdir = \"s\";\n      tpdd = '13px 6px 6px 6px';\n    }\n\n    nodel.classed(tdir, true)\n          .style('top', (ttop - scrollTop) + 'px')\n          .style('left', (tleft - scrollLeft) + 'px')\n          .style('padding', tpdd);\n\n    ////////////////////////////////::::::::://///////////////////////////////\n\n    //safeguard\n    if (dw == 0) {\n      return tip.hide()\n    } else {\n      return tip\n    }\n  }\n\n  // Public - hide the tooltip\n  //\n  // Returns a tip\n  tip.hide = function() {\n    var nodel = getNodeEl()\n    nodel\n      .style('opacity', 0)\n      .style('pointer-events', 'none')\n    return tip\n  }\n\n  // Public: Proxy attr calls to the d3 tip container.  Sets or gets attribute value.\n  //\n  // n - name of the attribute\n  // v - value of the attribute\n  //\n  // Returns tip or attribute value\n  tip.attr = function(n, v) {\n    if (arguments.length < 2 && typeof n === 'string') {\n      return getNodeEl().attr(n)\n    } else {\n      var args =  Array.prototype.slice.call(arguments)\n      d3.selection.prototype.attr.apply(getNodeEl(), args)\n    }\n\n    return tip\n  }\n\n  // Public: Proxy style calls to the d3 tip container.  Sets or gets a style value.\n  //\n  // n - name of the property\n  // v - value of the property\n  //\n  // Returns tip or style property value\n  tip.style = function(n, v) {\n    // debugger;\n    if (arguments.length < 2 && typeof n === 'string') {\n      return getNodeEl().style(n)\n    } else {\n      var args = Array.prototype.slice.call(arguments);\n      if (args.length === 1) {\n        var styles = args[0];\n        Object.keys(styles).forEach(function(key) {\n          return d3.selection.prototype.style.apply(getNodeEl(), [key, styles[key]]);\n        });\n      }\n    }\n\n    return tip\n  }\n\n  // Public: Set or get the direction of the tooltip\n  //\n  // v - One of n(north), s(south), e(east), or w(west), nw(northwest),\n  //     sw(southwest), ne(northeast) or se(southeast)\n  //\n  // Returns tip or direction\n  tip.direction = function(v) {\n    if (!arguments.length) return direction\n    direction = v == null ? v : d3.functor(v)\n\n    return tip\n  }\n\n  // Public: Sets or gets the offset of the tip\n  //\n  // v - Array of [x, y] offset\n  //\n  // Returns offset or\n  tip.offset = function(v) {\n    if (!arguments.length) return offset\n    offset = v == null ? v : d3.functor(v)\n\n    return tip\n  }\n\n  // Public: sets or gets the html value of the tooltip\n  //\n  // v - String value of the tip\n  //\n  // Returns html value or tip\n  tip.html = function(v) {\n    if (!arguments.length) return html\n    html = v == null ? v : d3.functor(v)\n\n    return tip\n  }\n\n  // Public: destroys the tooltip and removes it from the DOM\n  //\n  // Returns a tip\n  tip.destroy = function() {\n    if(node) {\n      getNodeEl().remove();\n      node = null;\n    }\n    return tip;\n  }\n\n  function d3_tip_direction() { return 'n' }\n  function d3_tip_offset() { return [0, 0] }\n  function d3_tip_html() { return ' ' }\n\n  var direction_callbacks = {\n    n:  direction_n,\n    s:  direction_s,\n    e:  direction_e,\n    w:  direction_w,\n    nw: direction_nw,\n    ne: direction_ne,\n    sw: direction_sw,\n    se: direction_se\n  };\n\n  var directions = Object.keys(direction_callbacks);\n\n  function direction_n() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.n.y - node.offsetHeight,\n      left: bbox.n.x - node.offsetWidth / 2\n    }\n  }\n\n  function direction_s() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.s.y,\n      left: bbox.s.x - node.offsetWidth / 2\n    }\n  }\n\n  function direction_e() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.e.y - node.offsetHeight / 2,\n      left: bbox.e.x\n    }\n  }\n\n  function direction_w() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.w.y - node.offsetHeight / 2,\n      left: bbox.w.x - node.offsetWidth\n    }\n  }\n\n  function direction_nw() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.nw.y - node.offsetHeight,\n      left: bbox.nw.x - node.offsetWidth\n    }\n  }\n\n  function direction_ne() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.ne.y - node.offsetHeight,\n      left: bbox.ne.x\n    }\n  }\n\n  function direction_sw() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.sw.y,\n      left: bbox.sw.x - node.offsetWidth\n    }\n  }\n\n  function direction_se() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.se.y,\n      left: bbox.e.x\n    }\n  }\n\n  function initNode() {\n    var node = d3.select(document.createElement('div'))\n    node\n      .style('position', 'fixed')\n      .style('top', 0)\n      .style('opacity', 0)\n      .style('pointer-events', 'none')\n      .style('box-sizing', 'border-box')\n      .style('line-height', 1.1)\n      .style('background', \"#000000\")\n      .style('color', '#fff')\n      .style('font-size', '14px')\n      .style('font-family', \"'Roboto Condensed', sans-serif\");\n\n    return node.node()\n  }\n\n\n  function getSVGNode(el) {\n    el = el.node()\n    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svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"AD\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  AD = svg.select(\"#AD\");\n}\nmapIdPlotFunction.AD = accumulatedDependence;\n\nif (svg.select(\"#FD\").empty()) {\n  FD = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"FD\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  FD = svg.select(\"#FD\");\n}\nmapIdPlotFunction.FD = featureDistribution;\n\nif (svg.select(\"#TV\").empty()) {\n  TV = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"TV\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  TV = svg.select(\"#TV\");\n}\nmapIdPlotFunction.TV = targetVs;\n\nif (svg.select(\"#AT\").empty()) {\n  AT = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"AT\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  AT = svg.select(\"#AT\");\n}\nmapIdPlotFunction.AT = averageTarget;\n\n/// general plot functions\n\nfunction breakDown() {\n\n  let tObservationId = CLICKED_OBSERVATION_ID,\n      tData = obsData[tObservationId];\n\n  if (tData[0].x === undefined) return null;\n\n  var bdData = tData[0],\n      bData = bdData.x;\n      bdBarCount = bdData.m[0],\n      xMinMax = bdData.x_min_max,\n      desc = bdData.desc;\n\n  var bdPlotHeight = SCALE_PLOT ? h : bdBarCount*bdBarWidth + (bdBarCount+1)*bdBarWidth/2,\n      bdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + bdPlotWidth])\n            .domain([xMinMax[0], xMinMax[1]]);\n\n  BD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + bdPlotWidth/2) + \" ,\" +\n                         (margin.top + bdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"contribution\");\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = BD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + bdPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + bdPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.variable));\n\n  var xGrid = BD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + bdPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-bdPlotHeight-additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = BD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-bdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = BD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.select(\".tick:last-child\").select(\"text\").attr('font-weight', 600);\n\n  // wrap y label text\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  BD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(bdSubtitle);\n\n  BD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(bdTitle);\n\n  // add tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipBD\")\n                  .html(d => d.type === \"desc\"\n                             ? descTooltipHtml(d) : bdTooltipHtml(d));\n\n  BD.call(tooltip);\n\n  // find boundaries\n  let intercept = bData[0].contribution > 0\n                  ? bData[0].barStart\n                  : bData[0].barSupport;\n\n  // make dotted line from intercept to prediction\n  var dotLineData = [{\"x\": x(intercept), \"y\": y(\"intercept\")},\n                     {\"x\": x(intercept), \"y\": y(\"prediction\") + y.bandwidth()}];\n\n  var lineFunction = d3.line()\n                       .x(d => d.x)\n                       .y(d => d.y);\n\n  BD.append(\"path\")\n    .data([dotLineData])\n    .attr(\"class\", \"dotLine\")\n    .attr(\"d\", lineFunction)\n    .style(\"stroke-dasharray\", (\"1, 2\"));\n\n  // add bars\n  var bars = BD.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"BD-bars\")\n      .attr(\"id\", d => d.variable_name)\n      .attr(\"fill\", d => {\n        switch (d.sign) {\n          case \"-1\":\n            return bdNegativeColor;\n          case \"1\":\n            return bdPositiveColor;\n          default:\n            return defaultColor;\n        }\n      })\n      .attr(\"fill-opacity\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                                 ? 0 : 1) //invisible bar for clicking purpose\n      .attr(\"y\", d => y(d.variable))\n      .attr(\"height\", y.bandwidth())\n      .attr(\"x\", d => d.contribution > 0 ? x(d.barStart) : x(d.barSupport))\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .on(\"click\", function() {\n        updatePlots(event = \"variableChange\",\n                    variableName = this.id,\n                    observationId = null,\n                    plotId = null);\n      })\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.barStart))\n      .attr(\"width\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                          ? 5 : x(d.barSupport) - x(d.barStart));\n\n  // add labels to bars\n  var ctbLabel = BD.selectAll()\n                   .data(bData)\n                   .enter()\n                   .append(\"g\");\n\n  ctbLabel.append(\"text\")\n          .attr(\"class\", \"axisLabel\")\n          .attr(\"x\", d => {\n            switch (d.sign) {\n              case \"X\":\n                return d.contribution < 0\n                       ? x(d.barStart) - 5 : x(d.barSupport) + 5;\n              default:\n                return x(d.barSupport) + 5;\n            }\n          })\n          .attr(\"y\", d => y(d.variable) + y.bandwidth()/2)\n          .attr(\"dy\", \"0.4em\")\n          .attr(\"text-anchor\", d => d.sign == \"X\" && d.contribution < 0\n                               ? \"end\" : null)\n          .transition()\n          .duration(TIME)\n          .delay((d,i) => (i+1) * TIME)\n          .text(d => {\n            switch (d.variable) {\n              case \"intercept\":\n              case \"prediction\":\n                return d.cumulative;\n              default:\n                return d.sign === \"-1\" ? d.contribution : \"+\"+d.contribution;\n            }\n          });\n\n  // add lines to bars\n  var lines = BD.selectAll()\n                .data(bData)\n                .enter()\n                .append(\"g\");\n\n  lines.append(\"line\")\n       .attr(\"class\", \"interceptLine\")\n       .attr(\"x1\", d => d.contribution < 0 ? x(d.barStart) : x(d.barSupport))\n       .attr(\"y1\", d => y(d.variable))\n       .attr(\"x2\", d => d.contribution < 0 ? x(d.barStart) : x(d.barSupport))\n       .attr(\"y2\", d => y(d.variable))\n       .transition()\n       .duration(TIME)\n       .delay((d,i) => (i+1) * TIME)\n       .attr(\"y2\", d => d.variable == \"prediction\"\n                        ? y(d.variable) : y(d.variable) + y.bandwidth()*2.5);\n\n  var description = BD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + bdPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction shapleyValues() {\n\n  let tObservationId = CLICKED_OBSERVATION_ID,\n      tData = obsData[tObservationId];\n\n  if (tData[2].x === undefined) return null;\n\n  var svData = tData[2],\n      bData = svData.x,\n      svBarCount = svData.m[0],\n      xMinMax = svData.x_min_max,\n      desc = svData.desc;\n\n  var svPlotHeight = SCALE_PLOT ? h : svBarCount*svBarWidth + (svBarCount+1)*svBarWidth/2,\n      svPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + svPlotWidth])\n            .domain([xMinMax[0], xMinMax[1]]);\n\n  SV.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + svPlotWidth/2) + \" ,\" +\n                         (margin.top + svPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"contribution\");\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = SV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + svPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + svPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.variable));\n\n  var xGrid = SV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + svPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-svPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = SV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-svPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = SV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // wrap y label text\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  SV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(svSubtitle);\n\n  SV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(svTitle);\n\n  // add tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipSV\")\n                  .html(d => d.type === \"desc\"\n                             ? descTooltipHtml(d) : bdTooltipHtml(d));\n\n  SV.call(tooltip);\n\n  // add bars\n  var bars = SV.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"SV-bars\")\n      .attr(\"id\", (d) => d.variable_name)\n      .attr(\"fill\", function(d) {\n        switch (d.sign) {\n          case \"-1\":\n            return svNegativeColor;\n          case \"1\":\n            return svPositiveColor;\n          default:\n            return defaultColor;\n        }\n      })\n      .attr(\"fill-opacity\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                                 ? 0 : 1) //invisible bar for clicking purpose\n      .attr(\"x\", d => d.contribution > 0 ? x(d.barStart) : x(d.barSupport))\n      .attr(\"y\", d => y(d.variable))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .on(\"click\", function() {\n        updatePlots(event = \"variableChange\",\n                    variableName = this.id,\n                    observationId = null,\n                    plotId = null);\n      })\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.barStart))\n      .attr(\"width\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                          ? 5 : x(d.barSupport) - x(d.barStart));\n\n  // add labels to bars\n  var ctbLabel = SV.selectAll()\n                   .data(bData)\n                   .enter()\n                   .append(\"g\");\n\n  ctbLabel.append(\"text\")\n          .attr(\"class\", \"axisLabel\")\n          .attr(\"x\", d => d.contribution > 0\n                          ? x(d.barStart) - 5 : x(d.barSupport) + 5)\n          .attr(\"y\", d => y(d.variable) + y.bandwidth()/2)\n          .attr(\"dy\", \"0.4em\")\n          .attr(\"text-anchor\", d => d.sign == \"1\" ? \"end\" : \"start\")\n          .transition()\n          .duration(TIME)\n          .delay((d,i) => (i+1) * TIME)\n          .text(d => d.sign == \"-1\" ? d.contribution : \"+\"+d.contribution);\n\n  // add lines to bars\n  var lines = SV.selectAll()\n                .data(bData)\n                .enter()\n                .append(\"g\");\n\n  lines.append(\"line\")\n        .attr(\"class\", \"interceptLine\")\n        .attr(\"x1\", d => d.contribution < 0 ? x(d.barSupport) : x(d.barStart))\n        .attr(\"y1\", d => y(d.variable))\n        .attr(\"x2\", d => d.contribution < 0 ? x(d.barSupport) : x(d.barStart))\n        .attr(\"y2\", d => y(d.variable))\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => (i+1) * TIME)\n        .attr(\"y2\", (d,i) => i == svBarCount - 1\n                             ? y(d.variable) + y.bandwidth()\n                             : y(d.variable) + y.bandwidth()*2.5);\n\n\n  // boxplots\n  if (SHOW_BOXPLOT) {\n    // main horizontal line\n    bars.append(\"line\")\n        .attr(\"class\", \"interceptLine\")\n        .attr(\"x1\", d => d.contribution < 0 ? x(d.max) : x(d.min))\n        .attr(\"x2\", d => d.contribution < 0 ? x(d.max) : x(d.min))\n        .attr(\"y1\", d => y(d.variable) + y.bandwidth()/2)\n        .attr(\"y2\", d => y(d.variable) + y.bandwidth()/2)\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x1\", d => x(d.min))\n        .attr(\"x2\", d => x(d.max));\n\n    // rectangle for the main box\n    bars.append(\"rect\")\n        .attr(\"x\", d => d.contribution < 0 ? x(d.q3) : x(d.q1))\n        .attr(\"y\", d => y(d.variable) + y.bandwidth()/3)\n        .attr(\"height\", y.bandwidth()/3)\n        .style(\"fill\", \"#371ea3\")\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x\", d => x(d.q1))\n        .attr(\"width\", d => Math.abs(x(d.q3) - x(d.q1)));\n  }\n\n  // description\n  var description = SV.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + svPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction ceterisParibus() {\n\n  let tObservationId = CLICKED_OBSERVATION_ID,\n      tData = obsData[tObservationId];\n\n  if (tData[1].x === undefined) return null;\n\n  let cpData = tData[1],\n      profData = cpData.x,\n      xMinMax = cpData.x_min_max_list,\n      yMinMax = cpData.y_min_max,\n      pData = cpData.observation,\n      isNumeric = cpData.is_numeric\n      desc = cpData.desc;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // lines or bars?\n  if (isNumeric[tVariableName][0]) {\n    cpNumericalPlot(tVariableName, profData[tVariableName],\n                    xMinMax[tVariableName], yMinMax, pData,\n                    desc[tVariableName]);\n  } else {\n    cpCategoricalPlot(tVariableName, profData[tVariableName],\n                      yMinMax, pData, desc[tVariableName]);\n  }\n}\n\nfunction featureImportance() {\n\n  if (fiData.x === undefined) return null;\n\n  var fiBarCount = fiData.m[0],\n      bData = fiData.x,\n      xMinMax = fiData.x_min_max,\n      desc = fiData.desc;\n\n  var fiPlotHeight = SCALE_PLOT ? h : fiBarCount*fiBarWidth + (fiBarCount+1)*fiBarWidth/2,\n      fiPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + fiPlotWidth])\n            .domain([xMinMax[0], xMinMax[1]]);\n\n  FI.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + fiPlotWidth/2) + \" ,\" +\n                         (margin.top + fiPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"drop-out loss\");\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = FI.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + fiPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + fiPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.variable));\n\n  var xGrid = FI.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + fiPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-fiPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = FI.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-fiPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = FI.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  FI.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(fiSubtitle);\n\n  FI.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(fiTitle);\n\n  // tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipFI\")\n                  .html(d => d.type === \"desc\"\n                             ? descTooltipHtml(d)\n                             : fiStaticTooltipHtml(d));\n  FI.call(tooltip);\n\n  // bars\n  var bars = FI.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  // find full model dropout_loss value\n  var fullModel = bData[0].full_model;\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"FI-bars\")\n      .attr(\"fill\", fiBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.variable))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .attr(\"id\", (d) => d.variable)\n      .on(\"click\", function(){\n        updatePlots(event = \"variableChange\",\n                    variableName = this.id,\n                    observationId = null,\n                    plotId = null);\n      })\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.dropout_loss) < x(fullModel)\n                      ? x(d.dropout_loss) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.dropout_loss) - x(fullModel)));\n\n  // make the interceptLine\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n  bars.selectAll(\".FI-bars\").each(function() {\n    if (+this.getAttribute('y') < minimumY) {\n      minimumY = +this.getAttribute('y');\n    }\n    if (+this.getAttribute('y') > maximumY) {\n      maximumY = +this.getAttribute('y');\n    }\n  });\n\n  FI.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  // boxplots\n  if (SHOW_BOXPLOT) {\n\n    // main horizontal line\n    bars.append(\"line\")\n        .attr(\"class\", \"interceptLine\")\n        .attr(\"x1\", d => x(d.dropout_loss) < x(fullModel) ? x(d.max) : x(d.min))\n        .attr(\"x2\", d => x(d.dropout_loss) < x(fullModel) ? x(d.max) : x(d.min))\n        .attr(\"y1\", d => y(d.variable) + y.bandwidth()/2)\n        .attr(\"y2\", d => y(d.variable) + y.bandwidth()/2)\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x1\", d => x(d.min))\n        .attr(\"x2\", d => x(d.max));\n\n    // rectangle for the main box\n    bars.append(\"rect\")\n        .attr(\"x\", d => x(d.dropout_loss) < x(fullModel) ? x(d.q3) : x(d.q1))\n        .attr(\"y\", d => y(d.variable) + y.bandwidth()/3)\n        .attr(\"height\", y.bandwidth()/3)\n        .style(\"fill\", \"#371ea3\")\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x\", d => x(d.q1))\n        .attr(\"width\", d => Math.abs(x(d.q3) - x(d.q1)));\n  }\n\n  // description\n  var description = FI.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + fiPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction partialDependence() {\n\n  if (pdData.x === undefined) return null;\n\n  let profData = pdData.x,\n      xMinMax = pdData.x_min_max_list,\n      yMinMax = pdData.y_min_max,\n      yMean = pdData.y_mean,\n      isNumeric = pdData.is_numeric,\n      desc = pdData.desc;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // lines or bars?\n  if (isNumeric[tVariableName][0]) {\n    pdNumericalPlot(tVariableName, profData[tVariableName],\n                    xMinMax[tVariableName], yMinMax, yMean,\n                    desc[tVariableName]);\n  } else {\n    pdCategoricalPlot(tVariableName, profData[tVariableName],\n                      yMinMax, yMean, desc[tVariableName]);\n  }\n}\n\nfunction accumulatedDependence() {\n\n  if (adData.x === undefined) return null;\n\n  let profData = adData.x,\n      xMinMax = adData.x_min_max_list,\n      yMinMax = adData.y_min_max,\n      yMean = adData.y_mean,\n      isNumeric = adData.is_numeric,\n      desc = adData.desc;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // lines or bars?\n  if (isNumeric[tVariableName][0]) {\n    adNumericalPlot(tVariableName, profData[tVariableName],\n                    xMinMax[tVariableName], yMinMax, yMean,\n                    desc[tVariableName]);\n  } else {\n    adCategoricalPlot(tVariableName, profData[tVariableName],\n                      yMinMax, yMean, desc[tVariableName]);\n  }\n}\n\nfunction featureDistribution() {\n\n  if (fdData.x === undefined) return null;\n\n  let dData = fdData.x,\n      xMinMax = fdData.x_min_max_list,\n      xMax = fdData.x_max_list,\n      nBin = fdData.nbin,\n      isNumeric = fdData.is_numeric;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // histogram or bars?\n  if (isNumeric[tVariableName][0]) {\n    fdNumericalPlot(tVariableName, dData, xMinMax[tVariableName],\n                    nBin[tVariableName]);\n  } else {\n    fdCategoricalPlot(tVariableName, dData, xMinMax[tVariableName],\n                      xMax[tVariableName]);\n  }\n}\n\nfunction targetVs() {\n\n  if (tvData.x === undefined) return null;\n\n  let xData = tvData.x,\n      xMinMax = tvData.x_min_max_list,\n      yMinMax = tvData.y_min_max,\n      isNumeric = tvData.is_numeric;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // scatterplot or violin?\n  if (isNumeric[tVariableName][0]) {\n    tvNumericalPlot(tVariableName, xData, xMinMax[tVariableName], yMinMax);\n  } else {\n    tvCategoricalPlot(tVariableName, xData, xMinMax[tVariableName], yMinMax);\n  }\n}\n\nfunction averageTarget() {\n\n  if (atData.x === undefined) return null;\n\n  let xData = atData.x,\n      xMinMax = atData.x_min_max_list,\n      yMinMax = atData.y_min_max_list,\n      yMean = atData.y_mean,\n      isNumeric = atData.is_numeric;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // scatterplot or violin?\n  if (isNumeric[tVariableName][0]) {\n    atNumericalPlot(tVariableName, xData[tVariableName],\n                    xMinMax[tVariableName], yMinMax[tVariableName], yMean);\n  } else {\n    atCategoricalPlot(tVariableName, xData[tVariableName],\n                      xMinMax[tVariableName], yMinMax[tVariableName], yMean);\n  }\n}\n\n/// small plot functions\n\nfunction cpNumericalPlot(variableName, lData, mData, yMinMax, pData, desc) {\n\n  var cpPlotHeight = h,\n      cpPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + cpPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  CP.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + cpPlotWidth/2) + \" ,\" +\n                         (margin.top + cpPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName + \" = \" + pData[0][variableName]);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + cpPlotHeight, margin.top - additionalHeight])\n            .domain([yMinMax[0], yMinMax[1]]);\n\n  var line = d3.line()\n               .x(d => x(d.xhat))\n               .y(d => y(d.yhat))\n               .curve(d3.curveMonotoneX);\n\n   CP.append(\"text\")\n     .attr(\"class\",\"smallTitle\")\n     .attr(\"x\", margin.left)\n     .attr(\"y\", margin.top - 15)\n     .text(cpSubtitle); //variableName + \" = \" + pData[0][variableName]\n\n  CP.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(cpTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + cpPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = CP.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-cpPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipCP\")\n                  .html((d, addData) => {\n\n                    if (d.type === \"desc\") {\n                      return descTooltipHtml(d)\n                    } else if (addData !== undefined) {\n                      return cpChangedTooltipHtml(d, addData);\n                    } else {\n                        return cpStaticTooltipHtml(d);\n                    }\n                   });\n  CP.call(tooltip);\n\n  // function to find nearest point on the line\n  var bisectXhat = d3.bisector(d => d.xhat).right;\n\n  // show tooltip with info nearest to mouseover\n  function showTooltip(hover) {\n    var x0 = x.invert(d3.mouse(d3.event.currentTarget)[0]),\n        i = bisectXhat(hover, x0),\n        d0 = hover[i - 1],\n        d1 = hover[i],\n        d = x0 - d0.xhat > d1.xhat - x0 ? d1 : d0;\n    let temp = pData.find(el => el[\"observation.id\"] === d.id);\n    tooltip.show(d, temp);\n  }\n\n  // add path\n  var p = CP.append(\"path\")\n            .attr(\"class\", \"CP-lines\")\n            .style(\"fill\", \"none\")\n            .style(\"stroke\", cpLineColor)\n            .style(\"stroke-width\", cpLineSize)\n            .on('mouseover', function(d) {\n\n              // make mouseover line more visible\n              d3.select(this)\n                .style(\"stroke\", defaultColor)\n                .style(\"stroke-width\", cpLineSize*1.5);\n\n              // make line and points appear on top\n              this.parentNode.appendChild(this);\n              d3.select(this.parentNode).selectAll(\".point\").each(function() {\n                               this.parentNode.appendChild(this);\n                          });\n\n              // show changed tooltip\n              showTooltip(d);\n            })\n            .on('mouseout', function(d) {\n\n              d3.select(this)\n                .style(\"stroke\", cpLineColor)\n                .style(\"stroke-width\", cpLineSize);\n\n              // hide changed tooltip\n              tooltip.hide(d);\n            });\n\n  // animate path\n  p.data([{\"xhat\":0, \"yhat\": 0}])\n   .attr(\"d\", line)\n   .transition()\n   .duration(TIME)\n   .attrTween(\"d\", function() {\n     var previous = d3.select(this).attr('d');\n     var current = line(lData);\n     return d3.interpolatePath(previous, current);\n   });\n\n  // add data for tooltip\n  p.data([lData]);\n\n  // add points\n  CP.selectAll()\n    .data(pData)\n    .enter()\n    .append(\"circle\")\n    .attr(\"class\", \"point\")\n    .attr(\"id\", d => d[\"observation.id\"])\n    .attr(\"cx\", d => x(d[variableName]))\n    .attr(\"cy\", d => y(d.yhat))\n    .attr(\"r\", 0)\n    .style(\"stroke-width\", 15)\n    .style(\"stroke\", \"red\")\n    .style(\"stroke-opacity\", 0)\n    .style(\"fill\", cpPointColor)\n    .on('mouseover', function(d) {\n      tooltip.show(d);\n  \t\td3.select(this)\n  \t\t\t.attr(\"r\", 2*cpPointSize);\n  \t})\n    .on('mouseout', function(d) {\n      tooltip.hide(d);\n  \t\td3.select(this)\n  \t\t\t.attr(\"r\", cpPointSize);\n  \t})\n    .transition()\n    .duration(TIME)\n    .delay(TIME)\n    .attr(\"r\", cpPointSize);\n\n  // add rugs\n  CP.selectAll()\n    .data(pData)\n    .enter()\n    .append(\"line\")\n    .attr(\"class\", \"rugLine\")\n    .style(\"stroke\", \"red\")\n    .style(\"stroke-width\", 2)\n    .attr(\"x1\", d => x(d[variableName]))\n    .attr(\"y1\", margin.top + cpPlotHeight)\n    .attr(\"x2\", d => x(d[variableName]))\n    .attr(\"y2\", margin.top + cpPlotHeight - 10);\n\n  CP.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + cpPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"prediction\");\n\n  var description = CP.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + cpPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction cpCategoricalPlot(variableName, bData, yMinMax, lData, desc) {\n\n  var cpBarCount = bData.map(d => d.xhat).length;\n\n  var cpPlotHeight = SCALE_PLOT ? h : cpBarCount*cpBarWidth + (cpBarCount+1)*cpBarWidth/2,\n      cpPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + cpPlotWidth])\n            .domain([yMinMax[0], yMinMax[1]]); // because it is flipped\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + cpPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + cpPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.xhat));\n\n  var xGrid = CP.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + cpPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-cpPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = CP.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-cpPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  CP.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(cpSubtitle); //variableName + \" = \" + lData[0][variableName]\n\n  CP.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(cpTitle);\n\n  var bars = CP.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  var fullModel = lData[0].yhat;\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipCP\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : cpChangedTooltipHtml(d, lData[0]));\n  CP.call(tooltip);\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"CP-bars\")\n      .attr(\"fill\", cpBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.xhat))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.yhat) < x(fullModel) ? x(d.yhat) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.yhat) - x(fullModel)));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".CP-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  CP.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  CP.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + cpPlotWidth/2) + \" ,\" +\n                         (margin.top + cpPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"prediction\");\n\n  var description = CP.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + cpPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction pdNumericalPlot(variableName, lData, mData, yMinMax, yMean, desc) {\n\n  var pdPlotHeight = h,\n      pdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + pdPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  PD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + pdPlotWidth/2) + \" ,\" +\n                         (margin.top + pdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + pdPlotHeight, margin.top - additionalHeight])\n            .domain([yMinMax[0], yMinMax[1]]);\n\n  var line = d3.line()\n               .x(d => x(d.xhat))\n               .y(d => y(d.yhat))\n               .curve(d3.curveMonotoneX);\n\n   PD.append(\"text\")\n     .attr(\"class\",\"smallTitle\")\n     .attr(\"x\", margin.left)\n     .attr(\"y\", margin.top - 15)\n     .text(pdSubtitle); // variableName\n\n  PD.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(pdTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + pdPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = PD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-pdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipPD\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : pdStaticTooltipHtml(d, variableName, yMean));\n  PD.call(tooltip);\n\n  // function to find nearest point on the line\n  var bisectXhat = d3.bisector(d => d.xhat).right;\n\n  // show tooltip with info nearest to mouseover\n  function showTooltip(hover) {\n    var x0 = x.invert(d3.mouse(d3.event.currentTarget)[0]),\n        i = bisectXhat(hover, x0),\n        d0 = hover[i - 1],\n        d1 = hover[i],\n        d = x0 - d0.xhat > d1.xhat - x0 ? d1 : d0;\n\n    tooltip.show(d);\n  }\n\n  // add lines\n  var p = PD.append(\"path\")\n            .attr(\"class\", \"PD-lines\")\n            .style(\"fill\", \"none\")\n            .style(\"stroke\", pdLineColor)\n            .style(\"stroke-width\", pdLineSize)\n            .on('mouseover', function(d) {\n\n              // make mouseover line more visible\n              d3.select(this)\n                .style(\"stroke\", defaultColor)\n                .style(\"stroke-width\", pdLineSize*1.5);\n\n              // make line appear on top\n              this.parentNode.appendChild(this);\n\n              // show changed tooltip\n              showTooltip(d);\n            })\n            .on('mouseout', function(d) {\n\n              d3.select(this)\n                .style(\"stroke\", pdLineColor)\n                .style(\"stroke-width\", pdLineSize);\n\n              // hide changed tooltip\n              tooltip.hide(d);\n            });\n\n  // animate path\n  p.data([{\"xhat\":0, \"yhat\": 0}])\n   .attr(\"d\", line)\n   .transition()\n   .duration(TIME)\n   .attrTween(\"d\", function() {\n     var previous = d3.select(this).attr('d');\n     var current = line(lData);\n     return d3.interpolatePath(previous, current);\n   });\n\n  // add data for tooltip\n  p.data([lData]);\n\n  PD.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + pdPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average prediction\");\n\n  var description = PD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + pdPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction pdCategoricalPlot(variableName, bData, yMinMax, yMean, desc) {\n\n  var pdBarCount = bData.map(d => d.xhat).length;\n\n  var pdPlotHeight = SCALE_PLOT ? h : pdBarCount*pdBarWidth + (pdBarCount+1)*pdBarWidth/2,\n      pdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + pdPlotWidth])\n            .domain([yMinMax[0], yMinMax[1]]); // because it is flipped\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + pdPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + pdPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.xhat));\n\n  var xGrid = PD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + pdPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-pdPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = PD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-pdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 8) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  PD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(pdSubtitle); // variableName\n\n  PD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(pdTitle);\n\n  var bars = PD.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  var fullModel = yMean;\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipPD\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : pdStaticTooltipHtml(d, variableName, yMean));\n  PD.call(tooltip);\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"PD-bars\")\n      .attr(\"fill\", pdBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.xhat))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.yhat) < x(fullModel) ? x(d.yhat) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.yhat) - x(fullModel)));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".PD-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  PD.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  PD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + pdPlotWidth/2) + \",\" +\n                         (margin.top + pdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average prediction\");\n\n  var description = PD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + pdPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction adNumericalPlot(variableName, lData, mData, yMinMax, yMean, desc) {\n\n  var adPlotHeight = h,\n      adPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + adPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  AD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + adPlotWidth/2) + \" ,\" +\n                         (margin.top + adPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + adPlotHeight, margin.top - additionalHeight])\n            .domain([yMinMax[0], yMinMax[1]]);\n\n  var line = d3.line()\n               .x(d => x(d.xhat))\n               .y(d => y(d.yhat))\n               .curve(d3.curveMonotoneX);\n\n  AD.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(adSubtitle); // variableName\n\n  AD.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(adTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + adPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = AD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-adPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipPD\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : adStaticTooltipHtml(d, variableName, yMean));\n  AD.call(tooltip);\n\n  // function to find nearest point on the line\n  var bisectXhat = d3.bisector(d => d.xhat).right;\n\n  // show tooltip with info nearest to mouseover\n  function showTooltip(hover) {\n    var x0 = x.invert(d3.mouse(d3.event.currentTarget)[0]),\n        i = bisectXhat(hover, x0),\n        d0 = hover[i - 1],\n        d1 = hover[i],\n        d = x0 - d0.xhat > d1.xhat - x0 ? d1 : d0;\n\n    tooltip.show(d);\n  }\n\n  // add lines\n  var p = AD.append(\"path\")\n            .attr(\"class\", \"AD-lines\")\n            .style(\"fill\", \"none\")\n            .style(\"stroke\", adLineColor)\n            .style(\"stroke-width\", adLineSize)\n            .on('mouseover', function(d) {\n\n              // make mouseover line more visible\n              d3.select(this)\n                .style(\"stroke\", defaultColor)\n                .style(\"stroke-width\", adLineSize*1.5);\n\n              // make line appear on top\n              this.parentNode.appendChild(this);\n\n              // show changed tooltip\n              showTooltip(d);\n            })\n            .on('mouseout', function(d) {\n\n              d3.select(this)\n                .style(\"stroke\", adLineColor)\n                .style(\"stroke-width\", adLineSize);\n\n              // hide changed tooltip\n              tooltip.hide(d);\n            });\n\n  // animate path\n  p.data([{\"xhat\":0, \"yhat\": 0}])\n   .attr(\"d\", line)\n   .transition()\n   .duration(TIME)\n   .attrTween(\"d\", function() {\n     var previous = d3.select(this).attr('d');\n     var current = line(lData);\n     return d3.interpolatePath(previous, current);\n   });\n\n  // add data for tooltip\n  p.data([lData]);\n\n  AD.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + adPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"accumulated prediction\");\n\n  var description = AD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + adPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction adCategoricalPlot(variableName, bData, yMinMax, yMean, desc) {\n\n  var adBarCount = bData.map(d => d.xhat).length;\n\n  var adPlotHeight = SCALE_PLOT ? h : adBarCount*adBarWidth + (adBarCount+1)*adBarWidth/2,\n      adPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + adPlotWidth])\n            .domain([yMinMax[0], yMinMax[1]]); // because it is flipped\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + adPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + adPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.xhat));\n\n  var xGrid = AD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + adPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-adPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = AD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-adPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  AD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(adSubtitle); // variableName\n\n  AD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(adTitle);\n\n  var bars = AD.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  var fullModel = 0; //yMean;\n    // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : adStaticTooltipHtml(d, variableName, yMean));\n  AD.call(tooltip);\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"AD-bars\")\n      .attr(\"fill\", adBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.xhat))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.yhat) < x(fullModel) ? x(d.yhat) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.yhat) - x(fullModel)));;\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".AD-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  AD.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  AD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + adPlotWidth/2) + \",\" +\n                         (margin.top + adPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"accumulated prediction\");\n\n  var description = AD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + adPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction fdNumericalPlot(variableName, dData, mData, nBin) {\n\n  var fdPlotHeight = h,\n      fdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + fdPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  FD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + fdPlotWidth/2) + \" ,\" +\n                         (margin.top + fdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  FD.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + fdPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"count\");\n\n  var y = d3.scaleLinear()\n        .range([margin.top + fdPlotHeight - 5, margin.top]);\n\n  FD.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(fdSubtitle);\n\n  FD.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(fdTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = FD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + fdPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yAxis = FD.append(\"g\")\n                .attr(\"class\", \"axisLabel\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\");\n\n  var yGrid = FD.append(\"g\")\n                  .attr(\"class\", \"grid\")\n                  .attr(\"transform\", \"translate(\" + margin.left + \",0)\");\n\n  var slider = d3.sliderBottom()\n                 .min(d3.max([+nBin-10,2]))\n                 .max(d3.max([+nBin+10,12]))\n                 .width(fdPlotWidth/2 - 40) // fit exit button\n                 .ticks(8)\n                 .step(1)\n                 .default(nBin)\n                 .fill(fdBarColor)\n                 .on('onchange', val => updateHist(val));\n\n  var sliderg = FD.append(\"g\").call(slider);\n\n  sliderg.attr(\"transform\", \"translate(\" + (margin.left + fdPlotWidth/2 - margin.small)\n                            + \",\" + margin.small + \")\");\n\n  updateHist(+nBin);\n\n  function updateHist(nbin) {\n\n    var histogram = d3.histogram()\n                      .value(d => d[variableName])\n                      .domain(x.domain())\n                      .thresholds(nbin);\n\n    var bins = histogram(dData);\n\n    y.domain([0, d3.max(bins, d => d.length)]);\n\n    let yaF = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n    yAxis.call(yaF)\n         .call(g => g.select(\".domain\").remove());\n\n    yGrid.call(d3.axisLeft(y)\n                 .ticks(10)\n                 .tickSize(-fdPlotWidth)\n                 .tickFormat(\"\")\n               ).call(g => g.select(\".domain\").remove());\n\n    var bars = FD.selectAll(\"rect\")\n                 .data(bins);\n\n    bars.enter()\n        .append(\"rect\")\n        .attr(\"fill\", fdBarColor)\n        .merge(bars)\n        .attr(\"x\", d => x(d.x0))\n        .attr(\"y\", d => y(0))\n        .attr(\"height\", d => 0)\n        .attr(\"width\", d => x(d.x1) - x(d.x0))\n        .transition()\n        .duration(TIME)\n          .attr(\"y\", d => y(d.length))\n          .attr(\"height\", d => y(0) - y(d.length));\n\n    bars.exit()\n        .remove()\n  }\n}\n\nfunction fdCategoricalPlot(variableName, dData, xMinMax, mData) {\n\n  // equivalent of R table function\n  var tableData = d3.nest()\n                    .key(d => d[variableName])\n                    .rollup(v => v.length)\n                    .entries(dData);\n  // sort tableData\n  var tableDataSorted = [];\n  tableData.forEach(e => {\n    tableDataSorted[xMinMax.indexOf(e.key)] = e;\n  });\n\n  var fdBarCount = tableData.map(d => d.key).length;\n\n  var fdPlotHeight = SCALE_PLOT ? h : fdBarCount*fdBarWidth + (fdBarCount+1)*fdBarWidth/2,\n      fdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + fdPlotWidth])\n            .domain([0, mData]);\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = FD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + fdPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + fdPlotHeight])\n            .padding(0.33)\n            .domain(xMinMax);\n\n  var xGrid = FD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + fdPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-fdPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = FD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-fdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = FD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  FD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(fdSubtitle);\n\n  FD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(fdTitle);\n\n  var bars = FD.selectAll()\n               .data(tableDataSorted)\n               .enter()\n               .append(\"g\");\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"FD-bars\")\n      .attr(\"fill\", fdBarColor)\n      .attr(\"x\", d => x(0))\n      .attr(\"y\", d => y(d.key))\n      .attr(\"height\", y.bandwidth())\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"width\", d => x(d.value)-x(0));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".FD-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  FD.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(0))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(0))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  FD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + fdPlotWidth/2) + \",\" +\n                         (margin.top + fdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"count\");\n}\n\nfunction tvNumericalPlot(variableName, xData, xMinMax, yMinMax) {\n\n  var tvPlotHeight = h,\n      tvPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + tvPlotWidth - 10])\n            .domain(xMinMax);\n\n  TV.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + tvPlotWidth/2) + \" ,\" +\n                         (margin.top + tvPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + tvPlotHeight, margin.top - additionalHeight])\n            .domain(yMinMax);\n\n  TV.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(tvSubtitle);\n\n  TV.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(tvTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + tvPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = TV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-tvPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  TV.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + tvPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"target\");\n\n  TV.selectAll()\n    .data(xData)\n    .enter()\n    .append(\"circle\")\n    .attr(\"class\", \"point\")\n    .attr(\"cx\", d => x(d[variableName]))\n    .attr(\"cy\", d => y(d[\"_target_\"]))\n    .attr(\"r\", 0)\n    .style(\"fill\", tvPointColor)\n    .transition()\n    .duration(TIME)\n    .attr(\"r\", tvPointSize);\n}\n\nfunction tvCategoricalPlot(variableName, xData, xMinMax, yMinMax) {\n\n  var tvPlotHeight = h,\n      tvPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + tvPlotWidth])\n            .domain(yMinMax);\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + tvPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + tvPlotHeight])\n            .padding(0.33)\n            .domain(xMinMax);\n\n  var xGrid = TV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + tvPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-tvPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = TV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-tvPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  TV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(tvSubtitle);\n\n  TV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(tvTitle);\n\n  TV.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + tvPlotWidth/2) + \" ,\" +\n                         (margin.top + tvPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"target\");\n\n  TV.selectAll()\n    .data(xData)\n    .enter()\n    .append(\"circle\")\n    .attr(\"class\", \"point\")\n    .attr(\"cx\", d => x(d[\"_target_\"]))\n    .attr(\"cy\", d => y(d[variableName]) + y.bandwidth()\n    - (0.1 + 0.8*Math.random()) * y.bandwidth())\n    .attr(\"r\", 0)\n    .style(\"fill\", tvPointColor)\n    .transition()\n    .duration(TIME)\n    .attr(\"r\", tvPointSize);\n}\n\nfunction atNumericalPlot(variableName, xData, xMinMax, yMinMax, yMean) {\n\n  var atPlotHeight = h,\n      atPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + atPlotWidth - 10])\n            .domain(xMinMax);\n\n  AT.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + atPlotWidth/2) + \" ,\" +\n                         (margin.top + atPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + atPlotHeight, margin.top - additionalHeight])\n            .domain(yMinMax);\n\n  AT.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(atSubtitle);\n\n  AT.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(atTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + atPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = AT.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-atPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  AT.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + atPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average target\");\n\n  AT.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(x.domain()[0]))\n    .attr(\"y1\", y(yMean))\n    .attr(\"x2\", x(x.domain()[1]))\n    .attr(\"y2\", y(yMean));\n\n  var lines = AT.selectAll()\n                .data(xData)\n                .enter()\n                .append(\"g\");\n\n  lines.append(\"line\")\n       .style(\"stroke\", atLineColor)\n       .style(\"stroke-width\", atLineSize)\n       .attr(\"x1\", d => x(d.x0))\n       .attr(\"x2\", d => x(d.x0))\n       .attr(\"y1\", d => y(d.y0))\n       .attr(\"y2\", d => y(d.y0))\n       .transition()\n       .duration(TIME/2)\n       .delay((d,i) => (i+1) * TIME/2)\n       .attr(\"x2\", d => x(d.x1))\n       .attr(\"y2\", d => y(d.y1))\n\n  lines.append(\"circle\")\n       .attr(\"cx\", d => x(d.x0))\n       .attr(\"cy\", d => y(d.y0))\n       .attr(\"r\", 0)\n       .style(\"fill\", atPointColor)\n       .transition()\n       .duration(TIME/2)\n       .delay((d,i) => i * TIME/2)\n       .attr(\"r\", atPointSize);\n\n  let lastPoint = xData.slice(-1)[0]\n\n  AT.append(\"circle\")\n    .attr(\"cx\", x(lastPoint.x1))\n    .attr(\"cy\", y(lastPoint.y1))\n    .attr(\"r\", 0)\n    .style(\"fill\", atPointColor)\n    .transition()\n    .duration(TIME/2)\n    .delay(xData.length * TIME/2)\n    .attr(\"r\", atPointSize);\n}\n\nfunction atCategoricalPlot(variableName, xData, xMinMax, yMinMax, yMean) {\n\n  var atBarCount = xData.length;\n\n  var atPlotHeight = SCALE_PLOT ? h : atBarCount*atBarWidth + (atBarCount+1)*atBarWidth/2,\n      atPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + atPlotWidth])\n            .domain(yMinMax);\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + atPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + atPlotHeight])\n            .padding(0.33)\n            .domain(xMinMax);\n\n  var xGrid = AT.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + atPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-atPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = AT.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-atPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  AT.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(atSubtitle);\n\n  AT.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(atTitle);\n\n  AT.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + atPlotWidth/2) + \" ,\" +\n                         (margin.top + atPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average target\");\n\n  var bars = AT.selectAll()\n               .data(xData)\n               .enter()\n               .append(\"g\");\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"AT-bars\")\n      .attr(\"fill\", atBarColor)\n      .attr(\"x\", d => x(yMean))\n      .attr(\"y\", d => y(d.y))\n      .attr(\"height\", y.bandwidth())\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => d.sign == 1 ? x(yMean) : x(d.x0))\n      .attr(\"width\", d => Math.abs(x(d.x0) - x(yMean)));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".AT-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  AT.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(yMean))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(yMean))\n    .attr(\"y2\", maximumY + y.bandwidth());\n}\n\n/// event plot functions\n\nfunction updatePlots(event, variableName, observationId, plotId) {\n  /// main plot controller, not used arguments are passed as null\n\n  switch (event) {\n    case \"observationChange\":\n      CLICKED_OBSERVATION_ID = observationId;\n      removePlots([\"BD\", \"SV\", \"CP\"]);\n      generatePlots([\"BD\", \"SV\", \"CP\"]);\n      break;\n\n    case \"variableChange\":\n      // safeguard\n      if (variableName == \"prediction\" || variableName == \"intercept\" ||\n          variableName == \"other\") { return; }\n      CLICKED_VARIABLE_NAME = variableName;\n      removePlots([\"CP\", \"PD\", \"AD\", \"FD\", \"TV\", \"AT\"]);\n      generatePlots([\"CP\", \"PD\", \"AD\", \"FD\", \"TV\", \"AT\"]);\n      break;\n\n    case \"chosePlot\":\n      removePlots([plotId]);\n      generatePlots([plotId]);\n      break;\n\n    default:\n      console.log(\"Unknown event in updatePlots \" +\n                  [event,variableName, observationId, plotId]);\n      break;\n  }\n}\n\nfunction removePlots(arrPlotId) {\n  /// check if there is something to delete and get rid of it (with tooltip)\n  arrPlotId.forEach((id) => {\n    if (!svg.select(\"#\"+id).selectAll(\"*\").empty()) {\n      svg.select(\"#\"+id).selectAll(\"*\").remove();\n      d3.select(\"body\").select(\"#tooltip\"+id).remove();\n    }\n  });\n}\n\nfunction generatePlots(arrPlotId) {\n  /// check if the plot got removed and make new one\n  arrPlotId.forEach((id) => {\n    if (svg.select(\"#\"+id).selectAll(\"*\").empty()) {\n      // execute plot function\n      mapIdPlotFunction[id]();\n    }\n  });\n}\n\n/* R2D3 Source File:   */\n//:\\\\\\ here are functions for tooltips HTML //:\\\\\\\n\nfunction bdTooltipHtml(d) {\n  var temp = \"<center>\";\n  temp += d.tooltipText;\n  temp += \"<\/center>\";\n  return temp;\n}\n\nfunction cpStaticTooltipHtml(d) {\n  // function formats tooltip text\n  var temp = \"\";\n  for (var [k, v] of Object.entries(d)) {\n    if (k === \"yhat\") {\n      k = \"prediction\";\n      temp += \"<center>\" +  k + \": \" + v + \"<\/br>\";\n      temp += \"<\/br>\";\n    } else {\n      temp += \"<center>\" +  k + \": \" + v + \"<\/br>\";\n    }\n  }\n  return temp;\n}\n\nfunction cpChangedTooltipHtml(d, addData) {\n  // function formats tooltip text with update in red\n  var temp = \"<center>\";\n  for (var [k, v] of Object.entries(addData)) {\n    if (k === \"yhat\") {\n      temp += \"prediction:<\/br>\";\n      temp += \"- before\" + \": \" + v + \"<\/br>\";\n      temp += \"- after\" + \": \" + \"<font color = \\\"red\\\">\" + d.yhat + \"<\/br><\/font>\";\n      temp += \"<\/br>\";\n    } else if (k === d.vname) {\n      temp +=  k + \": \" + \"<font color = \\\"red\\\">\"  +  d.xhat + \"<\/br><\/font>\";\n    } else {\n      temp += k + \": \" + v + \"<\/br>\";\n    }\n  }\n  temp += \"<\/center>\";\n  return temp;\n}\n\nfunction fiStaticTooltipHtml(d) {\n    let sign;\n    if (d.dropout_loss > d.full_model) sign = \"+\"; else sign = \"\";\n    var temp =  \"<center>\" + \"model loss after feature \" + d.variable\n      + \"<\/br>\" + \"<center>\" +\n      \" is permuted: \" +  Math.round(d.dropout_loss * 1000)/1000\n      + \"<\/br>\" + \"<center>\" + \"drop-out loss change: \" +\n      sign + Math.round((d.dropout_loss-d.full_model)*1000)/1000;\n    return temp;\n}\n\nfunction pdStaticTooltipHtml(d, variableName, yMean) {\n  // function formats tooltip text\n  var temp = \"\";\n  for (var [k, v] of Object.entries(d)) {\n    switch(k){\n      case \"xhat\":\n        temp += \"<center>\" +  variableName  + \": \" + v + \"<\/br>\";\n        break;\n      case \"yhat\":\n        temp += \"<center>\" +  \"average prediction\"  + \": \" + v + \"<\/br>\";\n        break;\n      case \"vname\":\n        break;\n      default:\n        temp += \"<center>\" +  k  + \": \" + v + \"<\/br>\";\n        break;\n    }\n  }\n\n  temp += \"<\/br><center>\" +\n          \"mean observation prediction:\" +\n          \"<\/br>\" + yMean + \"<\/br>\";\n  return temp;\n}\n\nfunction adStaticTooltipHtml(d, variableName, yMean) {\n  // function formats tooltip text\n  var temp = \"\";\n  for (var [k, v] of Object.entries(d)) {\n    switch(k){\n      case \"xhat\":\n        temp += \"<center>\" +  variableName  + \": \" + v + \"<\/br>\";\n        break;\n      case \"yhat\":\n        temp += \"<center>\" +  \"accumulated prediction\"  + \": \" + v + \"<\/br>\";\n        break;\n      case \"vname\":\n        break;\n      default:\n        temp += \"<center>\" +  k  + \": \" + v + \"<\/br>\";\n        break;\n    }\n  }\n\n  temp += \"<\/br><center>\" +\n          \"mean observation prediction:\" +\n          \"<\/br>\" + yMean + \"<\/br>\";\n  return temp;\n}\n\nfunction descTooltipHtml(d) {\n  var temp = \"<center>\";\n  temp += d.text;\n  temp += \"<\/center>\";\n  return temp;\n}\nsvg = d3.select(svg.node());\n/* R2D3 Source File:   */\n///:\\\\\\ --------- main modelStudio file --------- ///:\\\\\\\n///:\\\\\\ (for myself to remember):                 ///:\\\\\\\n///:\\\\\\ use CAPITAL for global variables and 'g'  ///:\\\\\\\n///:\\\\\\ use let where possible                    ///:\\\\\\\n///:\\\\\\ use class for css and id for select       ///:\\\\\\\n///:\\\\\\ use lambdas and ifelse where possible     ///:\\\\\\\n///:\\\\\\ ----------------------------------------- ///:\\\\\\\n\n/// prevent modelStudio from reloading onResize\nr2d3.onResize(function() {\n  return;\n});\n\n/// load all data\nvar obsData = data[0],\n    fiData = data[1], pdData = data[2],\n    adData = data[3], fdData = data[4],\n    tvData = data[4], atData = data[5];\n\n/// load options\nvar TIME = options.time,\n    modelName = options.model_name,\n    variableNames = options.variable_names,\n    dim = options.facet_dim,\n    footerText = options.footer_text,\n    dropDownData = options.drop_down_data,\n    EDA = options.eda,\n    WIDGET_ID = options.widget_id,\n    SCALE_PLOT = options.scale_plot,\n    SHOW_BOXPLOT = options.show_boxplot,\n    SHOW_SUBTITLE = options.show_subtitle,\n    subTitle = options.subtitle || modelName,\n    msTitle = options.ms_title,\n    barWidth = options.bar_width,\n    lineSize = options.line_size,\n    pointSize = options.point_size,\n    barColor = options.bar_color,\n    lineColor = options.line_color,\n    pointColor = options.point_color,\n    positiveColor = options.positive_color,\n    negativeColor = options.negative_color,\n    defaultColor = options.default_color,\n    bdTitle = options.bd_title,\n    bdSubtitle = options.bd_subtitle || subTitle,\n    bdBarWidth = options.bd_bar_width || barWidth,\n    bdPositiveColor = options.bd_positive_color || positiveColor,\n    bdNegativeColor = options.bd_negative_color || negativeColor,\n    bdDefaultColor = options.bd_default_color || defaultColor,\n    svTitle = options.sv_title,\n    svSubtitle = options.sv_subtitle || subTitle,\n    svBarWidth = options.sv_bar_width || barWidth,\n    svPositiveColor = options.sv_positive_color || positiveColor,\n    svNegativeColor = options.sv_negative_color || negativeColor,\n    cpTitle = options.cp_title,\n    cpSubtitle = options.cp_subtitle || subTitle,\n    cpBarWidth = options.cp_bar_width || barWidth,\n    cpLineSize = options.cp_line_size || lineSize,\n    cpPointSize = options.cp_point_size || pointSize,\n    cpBarColor = options.cp_bar_color || barColor,\n    cpLineColor = options.cp_line_color || lineColor,\n    cpPointColor = options.cp_point_color || pointColor,\n    fiTitle = options.fi_title,\n    fiSubtitle = options.fi_subtitle || subTitle,\n    fiBarWidth = options.fi_bar_width || barWidth,\n    fiBarColor = options.fi_bar_color || barColor,\n    pdTitle = options.pd_title,\n    pdSubtitle = options.pd_subtitle || subTitle,\n    pdBarWidth = options.pd_bar_width || barWidth,\n    pdLineSize = options.pd_line_size || lineSize,\n    pdBarColor = options.pd_bar_color || barColor,\n    pdLineColor = options.pd_line_color || lineColor,\n    adTitle = options.ad_title,\n    adSubtitle = options.ad_subtitle || subTitle,\n    adBarWidth = options.ad_bar_width || barWidth,\n    adLineSize = options.ad_line_size || lineSize,\n    adBarColor = options.ad_bar_color || barColor,\n    adLineColor = options.ad_line_color || lineColor,\n    fdTitle = options.fd_title,\n    fdSubtitle = options.fd_subtitle || subTitle,\n    fdBarWidth = options.fd_bar_width || barWidth,\n    fdBarColor = options.fd_bar_color || barColor,\n    tvTitle = options.tv_title,\n    tvSubtitle = options.tv_subtitle || subTitle,\n    tvPointSize = options.tv_point_size || pointSize,\n    tvPointColor = options.tv_point_color || pointColor,\n    atTitle = options.at_title,\n    atSubtitle = options.at_subtitle || subTitle,\n    atBarWidth = options.at_bar_width || barWidth,\n    atLineSize = options.at_line_size || lineSize,\n    atPointSize = options.at_point_size || pointSize,\n    atBarColor = options.at_bar_color || barColor,\n    atLineColor = options.at_line_color || lineColor,\n    atPointColor = options.at_point_color || pointColor;\n\n/// for observation choice\nvar observationIds = Object.keys(obsData);\n\n/// set global variables\nvar CLICKED_VARIABLE_NAME = variableNames[0],\n    CLICKED_OBSERVATION_ID = observationIds[0],\n    IS_BUTTON_CLICKED = false;\n\n/// set dimensions\nvar margin = {top: options.margin_top, right: options.margin_right,\n              bottom: options.margin_bottom, left: options.margin_left,\n              inner: options.margin_inner,\n              small: options.margin_small, big: options.margin_big,\n              ytitle: options.margin_ytitle};\n\nvar w = options.w, h = options.h;\n\nvar plotWidth = w + margin.left + margin.right,\n    plotHeight = h + margin.top + margin.bottom;\n\nvar studioMargin = {top: 50, bottom: 50},\n    studioWidth = dim[1]*plotWidth,\n    studioHeight = studioMargin.top + dim[0]*plotHeight + studioMargin.bottom;\n\n/// should subtitle be displayed and plot height be extended\nvar additionalHeight = 0;\nif (!SHOW_SUBTITLE) {\n  additionalHeight = 25;\n  bdSubtitle = null;\n  svSubtitle = null;\n  cpSubtitle = null;\n  fiSubtitle = null;\n  pdSubtitle = null;\n  adSubtitle = null;\n  fdSubtitle = null;\n  tvSubtitle = null;\n  atSubtitle = null;\n}\n\n/// for plot chosing\nvar notVisiblePlots = EDA ?\n                       [{id:\"BD\", text: bdTitle + \" [Local]\"},\n                       {id:\"SV\", text: svTitle + \" [Local]\"},\n                       {id:\"CP\", text: cpTitle + \" [Local]\"},\n                       {id:\"FI\", text: fiTitle + \" [Global]\"},\n                       {id:\"PD\", text: pdTitle + \" [Global]\"},\n                       {id:\"AD\", text: adTitle + \" [Global]\"},\n                       {id:\"FD\", text: fdTitle + \" [EDA]\"},\n                       {id:\"TV\", text: tvTitle + \" [EDA]\"},\n                       {id:\"AT\", text: atTitle + \" [EDA]\"}] :\n                       [{id:\"BD\", text: bdTitle + \" [Local]\"},\n                       {id:\"SV\", text: svTitle + \" [Local]\"},\n                       {id:\"CP\", text: cpTitle + \" [Local]\"},\n                       {id:\"FI\", text: fiTitle + \" [Global]\"},\n                       {id:\"PD\", text: pdTitle + \" [Global]\"},\n                       {id:\"AD\", text: adTitle + \" [Global]\"}];\n\nvar visiblePlots = [];\n\n/// generate facet x,y coordinates with grid index\nvar facetData = [], id = 0;\nfor (let i = 0; i < dim[0]; i++) {\n  for (let j = 0; j < dim[1]; j++) {\n    facetData.push({x: 0 + j*plotWidth,\n                    y: studioMargin.top + i*plotHeight,\n                    index: id});\n    id++;\n  }\n}\n\n///:\\\\\\\ninitializeStudio();\n///:\\\\\\\n\nfunction initializeStudio() {\n  /// this function initializes modelStudio (used only once, at start)\n\n  // top decorations\n  var TOP_G = svg.append(\"g\")\n                 .attr(\"class\", \"TOP_G\");\n\n  TOP_G.append(\"text\")\n       .attr(\"class\", \"mainTitle\")\n       .attr(\"x\", 15)\n       .attr(\"y\", 30)\n       .text(msTitle);\n\n  TOP_G.append(\"line\")\n       .attr(\"class\", \"mainLine\")\n       .attr(\"x1\", 10)\n       .attr(\"x2\", studioWidth - 10)\n       .attr(\"y1\", studioMargin.top - margin.big)\n       .attr(\"y2\", studioMargin.top - margin.big);\n\n  ///:\\\\\\ add select observation input\n  let tempW = calculateTextWidth(dropDownData.map(e => e.text))*1.6 + 18; // 15px bold 600\n\n  // center the ms\n  d3.select(\"#\" + WIDGET_ID)\n    .style('position', 'absolute')\n    .style('left', 0)\n    .style('right', 0)\n    .style('margin', 'auto');\n\n  var input = d3.select(\"#\" + WIDGET_ID)\n                .append(\"select\")\n                .attr(\"id\",\"input\")\n                .style(\"position\", \"absolute\") // to make input appear on top\n                .style(\"left\", (studioWidth - margin.big - tempW)+\"px\")\n                .style(\"top\", -studioHeight + 180)\n                .style(\"font-size\", \"15px\")\n                .style(\"font-weight\", 600)\n                .style(\"color\", \"#371ea3\");\n\n  input.selectAll()\n       .data(dropDownData)\n       .enter()\n       .append(\"option\")\n       .attr(\"value\", d => d.id)\n       .text(d => d.text)\n       .style(\"font-size\", \"15px\")\n       .style(\"font-weight\", 600)\n       .style(\"color\", \"#371ea3\");\n\n  input.on(\"change\", function() {\n\n    // update observation specific plots\n    updatePlots(event = \"observationChange\",\n                variableName = null,\n                observationId = this.value,\n                plotId = null);\n  });\n  ///:\\\\\\\n\n  // bottom decorations\n  var BOTTOM_G = svg.append(\"g\")\n                    .attr(\"class\", \"BOTTOM_G\");\n\n  BOTTOM_G.append(\"text\")\n          .attr(\"class\", \"footerTitle\")\n          .attr(\"x\", studioWidth - 15 - getTextWidth(footerText, 12, 'Fira Sans, sans-serif'))\n          .attr(\"y\", studioHeight - studioMargin.bottom + 25)\n          .text(footerText);\n\n  BOTTOM_G.append(\"line\")\n          .attr(\"class\", \"footerLine\")\n          .attr(\"x1\", 10)\n          .attr(\"x2\", studioWidth - 10)\n          .attr(\"y1\", studioHeight - studioMargin.bottom + margin.big)\n          .attr(\"y2\", studioHeight - 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diff --git a/pkgdown/favicon/scikit-learn.html b/pkgdown/favicon/scikit-learn.html
index c87d20a..6873080 100644
--- a/pkgdown/favicon/scikit-learn.html
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-<script type="application/json" data-for="widget-38034f76bcee9eb3105d6d32a6cdd075">{"x":{"data":[{"515":[{"x":[{"variable":"intercept","contribution":0,"variable_name":"intercept","variable_value":"1","cumulative":0.337,"sign":"X","position":9,"label":"scikit-learn","barStart":0.3367,"barSupport":0.3367,"tooltipText":"Average response: 0.337<br>Prediction: 0.074"},{"variable":"gender = male","contribution":-0.116,"variable_name":"gender","variable_value":"male","cumulative":0.221,"sign":"-1","position":8,"label":"scikit-learn","barStart":0.2208,"barSupport":0.3367,"tooltipText":"gender = male<br>decreases average response <br>by 0.116"},{"variable":"age = 45","contribution":-0.083,"variable_name":"age","variable_value":"45","cumulative":0.138,"sign":"-1","position":7,"label":"scikit-learn","barStart":0.1378,"barSupport":0.2208,"tooltipText":"age = 45<br>decreases average response <br>by 0.083"},{"variable":"class = 2nd","contribution":-0.081,"variable_name":"class","variable_value":"2nd","cumulative":0.057,"sign":"-1","position":6,"label":"scikit-learn","barStart":0.0568,"barSupport":0.1378,"tooltipText":"class = 2nd<br>decreases average response <br>by 0.081"},{"variable":"fare = 10.1","contribution":0.003,"variable_name":"fare","variable_value":"10.1","cumulative":0.06,"sign":"1","position":5,"label":"scikit-learn","barStart":0.0568,"barSupport":0.0595,"tooltipText":"fare = 10.1<br>increases average response <br>by 0.003"},{"variable":"sibsp = 0","contribution":0.006,"variable_name":"sibsp","variable_value":"0","cumulative":0.066,"sign":"1","position":4,"label":"scikit-learn","barStart":0.0595,"barSupport":0.0657,"tooltipText":"sibsp = 0<br>increases average response <br>by 0.006"},{"variable":"embarked = Southampton","contribution":0.001,"variable_name":"embarked","variable_value":"Southampton","cumulative":0.067,"sign":"1","position":3,"label":"scikit-learn","barStart":0.0657,"barSupport":0.0671,"tooltipText":"embarked = Southampton<br>increases average response <br>by 0.001"},{"variable":"parch = 0","contribution":0.007,"variable_name":"parch","variable_value":"0","cumulative":0.074,"sign":"1","position":2,"label":"scikit-learn","barStart":0.0671,"barSupport":0.0736,"tooltipText":"parch = 0<br>increases average response <br>by 0.007"},{"variable":"prediction","contribution":-0.263,"variable_name":"prediction","variable_value":"","cumulative":0.074,"sign":"X","position":1,"label":"scikit-learn","barStart":0.0736,"barSupport":0.3367,"tooltipText":"Average response: 0.337<br>Prediction: 0.074"}],"m":[9],"x_min_max":[0.001,0.393],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 0.074 which is lower than the average model prediction 0.337.<\/br><\/br>The most important variable is gender (= male). It decreases the prediction by 0.116.<\/br>The second most important variable is age (= 45). It decreases the prediction by 0.083.<\/br>The third most important variable is class (= 2nd). It decreases the prediction by 0.081.<\/br><\/br>Other variables are with less importance. 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predicts that for the selected instance (gender = male), prediction is equal to 0.074<\/br><\/br>The most important change in Scikit-learn's prediction would occur for gender = \"female\". It increases the prediction by 0.855. <\/br> <\/br><\/br><\/br>All variables are being displayed."}],"age":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (age = 45), prediction is equal to 0.074<\/br><\/br>The highest prediction occurs for (age = 0.1666666667), while the lowest for (age = 74).<\/br>Breakpoint is identified at (age = 4).<\/br><\/br>Average model responses are *higher* for variable values *lower* than breakpoint (= 4)."}],"class":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (class = 2nd), prediction is equal to 0.074<\/br><\/br>The most important change in Scikit-learn's prediction would occur for class = \"deck crew\". It increases the prediction by 0.683. <\/br>The second most important change in the prediction would occur for class = \"1st\". It increases the prediction by 0.442. <\/br>The third most important change in the prediction would occur for class = \"engineering crew\". It increases the prediction by 0.086.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.072."}],"embarked":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (embarked = Southampton), prediction is equal to 0.074<\/br><\/br>The most important change in Scikit-learn's prediction would occur for embarked = \"Cherbourg\". It increases the prediction by 0.072. <\/br>The second most important change in the prediction would occur for embarked = \"Queenstown\". It decreases the prediction by 0.065. <\/br>The third most important change in the prediction would occur for embarked = \"Belfast\". It decreases the prediction by 0.053.<\/br><\/br>All variables are being displayed."}],"fare":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (fare = 10.1), prediction is equal to 0.074<\/br><\/br>The highest prediction occurs for (fare = 512.0607), while the lowest for (fare = 247.1005).<\/br>Breakpoints are identified at (fare = 65.582 and fare = 0).<\/br><\/br>Average model responses are *lower* for variable values *lower* than breakpoint(= 0)."}],"sibsp":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (sibsp = 0), prediction is equal to 0.074<\/br><\/br>The highest prediction occurs for (sibsp = 0), while the lowest for (sibsp = 8).<\/br>Breakpoint is identified at (sibsp = 0).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 0)."}],"parch":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (parch = 0), prediction is equal to 0.074<\/br><\/br>The highest prediction occurs for (parch = 0), while the lowest for (parch = 9).<\/br>Breakpoint is identified at (parch = 0).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 0)."}]}},{"x":[{"variable_name":"gender","variable":"gender = male","contribution":-0.148,"variable_value":"male","sign":"-1","label":"scikit-learn","barStart":0.1888,"barSupport":0.3367,"tooltipText":"gender = male<br>decreases average response <br>by 0.148","min":0.139,"q1":0.159,"q3":0.2105,"max":0.2259},{"variable_name":"age","variable":"age = 45","contribution":-0.078,"variable_value":"45","sign":"-1","label":"scikit-learn","barStart":0.2588,"barSupport":0.3367,"tooltipText":"age = 45<br>decreases average response <br>by 0.078","min":0.2293,"q1":0.2464,"q3":0.2777,"max":0.2823},{"variable_name":"class","variable":"class = 2nd","contribution":-0.061,"variable_value":"2nd","sign":"-1","label":"scikit-learn","barStart":0.2761,"barSupport":0.3367,"tooltipText":"class = 2nd<br>decreases average response <br>by 0.061","min":0.2267,"q1":0.2469,"q3":0.3004,"max":0.3424},{"variable_name":"fare","variable":"fare = 10.1","contribution":0.017,"variable_value":"10.1","sign":"1","label":"scikit-learn","barStart":0.3367,"barSupport":0.3539,"tooltipText":"fare = 10.1<br>increases average response <br>by 0.017","min":0.3384,"q1":0.3451,"q3":0.3569,"max":0.3746},{"variable_name":"sibsp","variable":"sibsp = 0","contribution":0.01,"variable_value":"0","sign":"1","label":"scikit-learn","barStart":0.3367,"barSupport":0.3462,"tooltipText":"sibsp = 0<br>increases average response <br>by 0.01","min":0.3332,"q1":0.3444,"q3":0.3519,"max":0.3628},{"variable_name":"embarked","variable":"embarked = Southampton","contribution":-0.006,"variable_value":"Southampton","sign":"-1","label":"scikit-learn","barStart":0.3306,"barSupport":0.3367,"tooltipText":"embarked = Southampton<br>decreases average response <br>by 0.006","min":0.3184,"q1":0.3262,"q3":0.3345,"max":0.3424},{"variable_name":"parch","variable":"parch = 0","contribution":0.003,"variable_value":"0","sign":"1","label":"scikit-learn","barStart":0.3367,"barSupport":0.3395,"tooltipText":"parch = 0<br>increases average response <br>by 0.003","min":0.3219,"q1":0.335,"q3":0.3438,"max":0.3569}],"m":[7],"x_min_max":[0.1293,0.3866],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 0.074 which is lower than the average model prediction 0.337. For the selected instance model's prediction is lower, than for 85% of all observations.<\/br><\/br>The most important variable is gender (= male). It decreases the prediction by 0.148.<\/br>The second most important variable is age (= 45). It decreases the prediction by 0.078.<\/br>The third most important variable is class (= 2nd). It decreases the prediction by 0.061.<\/br>The average contribution of all the above variables is significant.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is 0.023."}]}],"604":[{"x":[{"variable":"intercept","contribution":0,"variable_name":"intercept","variable_value":"1","cumulative":0.337,"sign":"X","position":9,"label":"scikit-learn","barStart":0.3367,"barSupport":0.3367,"tooltipText":"Average response: 0.337<br>Prediction: 0.07"},{"variable":"gender = male","contribution":-0.116,"variable_name":"gender","variable_value":"male","cumulative":0.221,"sign":"-1","position":8,"label":"scikit-learn","barStart":0.2208,"barSupport":0.3367,"tooltipText":"gender = male<br>decreases average response <br>by 0.116"},{"variable":"class = 3rd","contribution":-0.067,"variable_name":"class","variable_value":"3rd","cumulative":0.154,"sign":"-1","position":7,"label":"scikit-learn","barStart":0.1543,"barSupport":0.2208,"tooltipText":"class = 3rd<br>decreases average response <br>by 0.067"},{"variable":"age = 17","contribution":-0.01,"variable_name":"age","variable_value":"17","cumulative":0.144,"sign":"-1","position":6,"label":"scikit-learn","barStart":0.1445,"barSupport":0.1543,"tooltipText":"age = 17<br>decreases average response <br>by 0.01"},{"variable":"sibsp = 1","contribution":-0.046,"variable_name":"sibsp","variable_value":"1","cumulative":0.099,"sign":"-1","position":5,"label":"scikit-learn","barStart":0.0987,"barSupport":0.1445,"tooltipText":"sibsp = 1<br>decreases average response <br>by 0.046"},{"variable":"embarked = Southampton","contribution":-0.012,"variable_name":"embarked","variable_value":"Southampton","cumulative":0.086,"sign":"-1","position":4,"label":"scikit-learn","barStart":0.0863,"barSupport":0.0987,"tooltipText":"embarked = Southampton<br>decreases average response <br>by 0.012"},{"variable":"fare = 7.17","contribution":-0.016,"variable_name":"fare","variable_value":"7.17","cumulative":0.07,"sign":"-1","position":3,"label":"scikit-learn","barStart":0.0698,"barSupport":0.0863,"tooltipText":"fare = 7.17<br>decreases average response <br>by 0.016"},{"variable":"parch = 0","contribution":-0,"variable_name":"parch","variable_value":"0","cumulative":0.07,"sign":"-1","position":2,"label":"scikit-learn","barStart":0.0697,"barSupport":0.0698,"tooltipText":"parch = 0<br>decreases average response <br>by 0"},{"variable":"prediction","contribution":-0.267,"variable_name":"prediction","variable_value":"","cumulative":0.07,"sign":"X","position":1,"label":"scikit-learn","barStart":0.0697,"barSupport":0.3367,"tooltipText":"Average response: 0.337<br>Prediction: 0.07"}],"m":[9],"x_min_max":[0.0166,0.3904],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 0.07 which is lower than the average model prediction 0.337.<\/br><\/br>The most important variable is gender (= male). It decreases the prediction by 0.116.<\/br>The second most important variable is class (= 3rd). It decreases the prediction by 0.067.<\/br>The third most important variable is sibsp (= 1). It decreases the prediction by 0.046.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is 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predicts that for the selected instance (gender = male), prediction is equal to 0.07<\/br><\/br>The most important change in Scikit-learn's prediction would occur for gender = \"female\". It increases the prediction by 0.236. <\/br> <\/br><\/br><\/br>All variables are being displayed."}],"age":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (age = 17), prediction is equal to 0.07<\/br><\/br>The highest prediction occurs for (age = 0.1666666667), while the lowest for (age = 74).<\/br>Breakpoint is identified at (age = 2).<\/br><\/br>Average model responses are *higher* for variable values *lower* than breakpoint (= 2)."}],"class":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (class = 3rd), prediction is equal to 0.07<\/br><\/br>The most important change in Scikit-learn's prediction would occur for class = \"1st\". It increases the prediction by 0.518. <\/br>The second most important change in the prediction would occur for class = \"deck crew\". It increases the prediction by 0.497. <\/br>The third most important change in the prediction would occur for class = \"engineering crew\". It increases the prediction by 0.288.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.071."}],"embarked":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (embarked = Southampton), prediction is equal to 0.07<\/br><\/br>The most important change in Scikit-learn's prediction would occur for embarked = \"Cherbourg\". It increases the prediction by 0.112. <\/br>The second most important change in the prediction would occur for embarked = \"Queenstown\". It increases the prediction by 0.028. <\/br>The third most important change in the prediction would occur for embarked = \"Belfast\". It decreases the prediction by 0.022.<\/br><\/br>All variables are being displayed."}],"fare":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (fare = 7.17), prediction is equal to 0.07<\/br><\/br>The highest prediction occurs for (fare = 512.0607), while the lowest for (fare = 0).<\/br>Breakpoint is identified at (fare = 152.859).<\/br><\/br>Average model responses are *higher* for variable values *higher* than breakpoint (= 152.859)."}],"sibsp":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (sibsp = 1), prediction is equal to 0.07<\/br><\/br>The highest prediction occurs for (sibsp = 0), while the lowest for (sibsp = 8).<\/br>Breakpoint is identified at (sibsp = 0).<\/br><\/br>Average model responses are *higher* for variable values *lower* than breakpoint (= 0)."}],"parch":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (parch = 0), prediction is equal to 0.07<\/br><\/br>The highest prediction occurs for (parch = 1), while the lowest for (parch = 9).<\/br>Breakpoint is identified at (parch = 1).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 1)."}]}},{"x":[{"variable_name":"class","variable":"class = 3rd","contribution":-0.135,"variable_value":"3rd","sign":"-1","label":"scikit-learn","barStart":0.2018,"barSupport":0.3367,"tooltipText":"class = 3rd<br>decreases average response <br>by 0.135","min":0.1468,"q1":0.1871,"q3":0.214,"max":0.2465},{"variable_name":"gender","variable":"gender = male","contribution":-0.086,"variable_value":"male","sign":"-1","label":"scikit-learn","barStart":0.2503,"barSupport":0.3367,"tooltipText":"gender = male<br>decreases average response <br>by 0.086","min":0.2132,"q1":0.2256,"q3":0.2757,"max":0.2844},{"variable_name":"sibsp","variable":"sibsp = 1","contribution":-0.05,"variable_value":"1","sign":"-1","label":"scikit-learn","barStart":0.287,"barSupport":0.3367,"tooltipText":"sibsp = 1<br>decreases average response <br>by 0.05","min":0.2346,"q1":0.2772,"q3":0.3081,"max":0.3336},{"variable_name":"age","variable":"age = 17","contribution":0.012,"variable_value":"17","sign":"1","label":"scikit-learn","barStart":0.3367,"barSupport":0.3484,"tooltipText":"age = 17<br>increases average response <br>by 0.012","min":0.2833,"q1":0.3295,"q3":0.3777,"max":0.3801},{"variable_name":"embarked","variable":"embarked = Southampton","contribution":-0.01,"variable_value":"Southampton","sign":"-1","label":"scikit-learn","barStart":0.3272,"barSupport":0.3367,"tooltipText":"embarked = Southampton<br>decreases average response <br>by 0.01","min":0.3162,"q1":0.3216,"q3":0.3303,"max":0.3434},{"variable_name":"fare","variable":"fare = 7.17","contribution":0.008,"variable_value":"7.17","sign":"1","label":"scikit-learn","barStart":0.3367,"barSupport":0.3444,"tooltipText":"fare = 7.17<br>increases average response <br>by 0.008","min":0.306,"q1":0.326,"q3":0.3577,"max":0.3789},{"variable_name":"parch","variable":"parch = 0","contribution":-0.006,"variable_value":"0","sign":"-1","label":"scikit-learn","barStart":0.3309,"barSupport":0.3367,"tooltipText":"parch = 0<br>decreases average response <br>by 0.006","min":0.3103,"q1":0.3261,"q3":0.3366,"max":0.3433}],"m":[7],"x_min_max":[0.1585,0.4063],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 0.07 which is lower than the average model prediction 0.337. For the selected instance model's prediction is lower, than for 86% of all observations.<\/br><\/br>The most important variable is class (= 3rd). It decreases the prediction by 0.135.<\/br>The second most important variable is gender (= male). It decreases the prediction by 0.086.<\/br>The third most important variable is sibsp (= 1). It decreases the prediction by 0.05.<\/br>The average contribution of all the above variables is significant.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is 0.004."}]}],"1430":[{"x":[{"variable":"intercept","contribution":0,"variable_name":"intercept","variable_value":"1","cumulative":0.337,"sign":"X","position":9,"label":"scikit-learn","barStart":0.3367,"barSupport":0.3367,"tooltipText":"Average response: 0.337<br>Prediction: 0.308"},{"variable":"gender = male","contribution":-0.116,"variable_name":"gender","variable_value":"male","cumulative":0.221,"sign":"-1","position":8,"label":"scikit-learn","barStart":0.2208,"barSupport":0.3367,"tooltipText":"gender = male<br>decreases average response <br>by 0.116"},{"variable":"class = engineering crew","contribution":0.053,"variable_name":"class","variable_value":"engineering crew","cumulative":0.274,"sign":"1","position":7,"label":"scikit-learn","barStart":0.2208,"barSupport":0.2743,"tooltipText":"class = engineering crew<br>increases average response <br>by 0.053"},{"variable":"age = 25","contribution":0.003,"variable_name":"age","variable_value":"25","cumulative":0.277,"sign":"1","position":6,"label":"scikit-learn","barStart":0.2743,"barSupport":0.2771,"tooltipText":"age = 25<br>increases average response <br>by 0.003"},{"variable":"sibsp = 0","contribution":-0.023,"variable_name":"sibsp","variable_value":"0","cumulative":0.254,"sign":"-1","position":5,"label":"scikit-learn","barStart":0.2539,"barSupport":0.2771,"tooltipText":"sibsp = 0<br>decreases average response <br>by 0.023"},{"variable":"embarked = Southampton","contribution":0.035,"variable_name":"embarked","variable_value":"Southampton","cumulative":0.288,"sign":"1","position":4,"label":"scikit-learn","barStart":0.2539,"barSupport":0.2885,"tooltipText":"embarked = Southampton<br>increases average response <br>by 0.035"},{"variable":"fare = 0","contribution":0.028,"variable_name":"fare","variable_value":"0","cumulative":0.317,"sign":"1","position":3,"label":"scikit-learn","barStart":0.2885,"barSupport":0.3165,"tooltipText":"fare = 0<br>increases average response <br>by 0.028"},{"variable":"parch = 0","contribution":-0.009,"variable_name":"parch","variable_value":"0","cumulative":0.308,"sign":"-1","position":2,"label":"scikit-learn","barStart":0.3077,"barSupport":0.3165,"tooltipText":"parch = 0<br>decreases average response <br>by 0.009"},{"variable":"prediction","contribution":-0.029,"variable_name":"prediction","variable_value":"","cumulative":0.308,"sign":"X","position":1,"label":"scikit-learn","barStart":0.3077,"barSupport":0.3367,"tooltipText":"Average response: 0.337<br>Prediction: 0.308"}],"m":[9],"x_min_max":[0.1978,0.3602],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 0.308 which is close to the average model prediction 0.337.<\/br><\/br>The most important variable is gender (= male). It decreases the prediction by 0.116.<\/br>The second most important variable is class (= engineering crew). It increases the prediction by 0.053.<\/br>The third most important variable is embarked (= Southampton). It increases the prediction by 0.035.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is -0.001."}]},{"observation":[{"observation.id":"1430","model":"scikit-learn","yhat":0.3077,"gender":"male","age":25,"class":"engineering 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predicts that for the selected instance (gender = male), prediction is equal to 0.308<\/br><\/br>The most important change in Scikit-learn's prediction would occur for gender = \"female\". It increases the prediction by 0.582. <\/br> <\/br><\/br><\/br>All variables are being displayed."}],"age":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (age = 25), prediction is equal to 0.308<\/br><\/br>The highest prediction occurs for (age = 0.1666666667), while the lowest for (age = 74).<\/br>Breakpoint is identified at (age = 7).<\/br><\/br>Average model responses are *higher* for variable values *lower* than breakpoint (= 7)."}],"class":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (class = engineering crew), prediction is equal to 0.308<\/br><\/br>The most important change in Scikit-learn's prediction would occur for class = \"deck crew\". It increases the prediction by 0.3. <\/br>The second most important change in the prediction would occur for class = \"restaurant staff\". It decreases the prediction by 0.283. <\/br>The third most important change in the prediction would occur for class = \"1st\". It increases the prediction by 0.182.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.173."}],"embarked":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (embarked = Southampton), prediction is equal to 0.308<\/br><\/br>The most important change in Scikit-learn's prediction would occur for embarked = \"Belfast\". It decreases the prediction by 0.259. <\/br>The second most important change in the prediction would occur for embarked = \"Queenstown\". It decreases the prediction by 0.229. <\/br>The third most important change in the prediction would occur for embarked = \"Cherbourg\". It increases the prediction by 0.005.<\/br><\/br>All variables are being displayed."}],"fare":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (fare = 0), prediction is equal to 0.308<\/br><\/br>The highest prediction occurs for (fare = 512.0607), while the lowest for (fare = 152.858664).<\/br>Breakpoint is identified at (fare = 152.859).<\/br><\/br>Average model responses are *higher* for variable values *higher* than breakpoint (= 152.859)."}],"sibsp":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (sibsp = 0), prediction is equal to 0.308<\/br><\/br>The highest prediction occurs for (sibsp = 4), while the lowest for (sibsp = 8).<\/br>Breakpoints are identified at (sibsp = 2 and sibsp = 0).<\/br><\/br>Average model responses are *higher* for variable values *higher* than breakpoint (= 0)."}],"parch":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (parch = 0), prediction is equal to 0.308<\/br><\/br>The highest prediction occurs for (parch = 3), while the lowest for (parch = 9).<\/br>Breakpoints are identified at (parch = 0 and parch = 0).<\/br><\/br>Average model responses are *higher* for variable values *higher* than breakpoint (= 0)."}]}},{"x":[{"variable_name":"gender","variable":"gender = male","contribution":-0.124,"variable_value":"male","sign":"-1","label":"scikit-learn","barStart":0.213,"barSupport":0.3367,"tooltipText":"gender = male<br>decreases average response <br>by 0.124","min":0.1951,"q1":0.2032,"q3":0.2208,"max":0.2275},{"variable_name":"class","variable":"class = engineering crew","contribution":0.065,"variable_value":"engineering crew","sign":"1","label":"scikit-learn","barStart":0.3367,"barSupport":0.4013,"tooltipText":"class = engineering crew<br>increases average response <br>by 0.065","min":0.3811,"q1":0.401,"q3":0.4143,"max":0.424},{"variable_name":"fare","variable":"fare = 0","contribution":0.021,"variable_value":"0","sign":"1","label":"scikit-learn","barStart":0.3367,"barSupport":0.3579,"tooltipText":"fare = 0<br>increases average response <br>by 0.021","min":0.3455,"q1":0.3472,"q3":0.3673,"max":0.3868},{"variable_name":"age","variable":"age = 25","contribution":0.012,"variable_value":"25","sign":"1","label":"scikit-learn","barStart":0.3367,"barSupport":0.3488,"tooltipText":"age = 25<br>increases average response <br>by 0.012","min":0.3341,"q1":0.3466,"q3":0.355,"max":0.3591},{"variable_name":"parch","variable":"parch = 0","contribution":-0.006,"variable_value":"0","sign":"-1","label":"scikit-learn","barStart":0.3307,"barSupport":0.3367,"tooltipText":"parch = 0<br>decreases average response <br>by 0.006","min":0.3172,"q1":0.3275,"q3":0.3344,"max":0.3418},{"variable_name":"sibsp","variable":"sibsp = 0","contribution":0.005,"variable_value":"0","sign":"1","label":"scikit-learn","barStart":0.3367,"barSupport":0.3422,"tooltipText":"sibsp = 0<br>increases average response <br>by 0.005","min":0.3135,"q1":0.3339,"q3":0.3489,"max":0.3604},{"variable_name":"embarked","variable":"embarked = Southampton","contribution":-0.002,"variable_value":"Southampton","sign":"-1","label":"scikit-learn","barStart":0.3343,"barSupport":0.3367,"tooltipText":"embarked = Southampton<br>decreases average response <br>by 0.002","min":0.3145,"q1":0.3227,"q3":0.3386,"max":0.3625}],"m":[7],"x_min_max":[0.1716,0.446],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 0.308 which is close to the average model prediction 0.337.For the selected instance model's prediction is higher, than for 67% of all observations.<\/br><\/br>The most important variable is gender (= male). It decreases the prediction by 0.124.<\/br>The second most important variable is class (= engineering crew). It increases the prediction by 0.065.<\/br>The third most important variable is fare (= 0). It increases the prediction by 0.021.<\/br>The average contribution of all the above variables is significant.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is 0.009."}]}]},{"x":[{"variable":"gender","label":"sklearn.pipeline.Pipeline","dropout_loss":0.505,"full_model":0.346,"min":0.4972,"q1":0.5033,"q3":0.5073,"max":0.5133},{"variable":"class","label":"sklearn.pipeline.Pipeline","dropout_loss":0.432,"full_model":0.346,"min":0.4257,"q1":0.4301,"q3":0.4346,"max":0.436},{"variable":"age","label":"sklearn.pipeline.Pipeline","dropout_loss":0.398,"full_model":0.346,"min":0.3931,"q1":0.3958,"q3":0.3988,"max":0.4026},{"variable":"sibsp","label":"sklearn.pipeline.Pipeline","dropout_loss":0.374,"full_model":0.346,"min":0.3705,"q1":0.3727,"q3":0.3757,"max":0.378},{"variable":"fare","label":"sklearn.pipeline.Pipeline","dropout_loss":0.369,"full_model":0.346,"min":0.3645,"q1":0.3682,"q3":0.3708,"max":0.3731},{"variable":"parch","label":"sklearn.pipeline.Pipeline","dropout_loss":0.369,"full_model":0.346,"min":0.3648,"q1":0.3669,"q3":0.37,"max":0.3723},{"variable":"embarked","label":"sklearn.pipeline.Pipeline","dropout_loss":0.367,"full_model":0.346,"min":0.3619,"q1":0.3659,"q3":0.3691,"max":0.3696}],"m":[7],"x_min_max":[0.3218,0.5315],"desc":[{"type":"desc","text":"The number of important variables for sklearn.pipeline.Pipeline's prediction is 3 out of 7. <\/br> Variables gender, class, age have the highest 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SemiBold'),local('FiraSans-SemiBold'),url(https://fonts.gstatic.com/s/firasans/v10/va9B4kDNxMZdWfMOD5VnSKzeRhf6.woff2) format('woff2');unicode-range:U+0000-00FF,U+0131,U+0152-0153,U+02BB-02BC,U+02C6,U+02DA,U+02DC,U+2000-206F,U+2074,U+20AC,U+2122,U+2191,U+2193,U+2212,U+2215,U+FEFF,U+FFFD}@font-face{font-family:'Fira Sans';font-style:normal;font-weight:700;font-display:swap;src:local('Fira Sans Bold'),local('FiraSans-Bold'),url(https://fonts.gstatic.com/s/firasans/v10/va9B4kDNxMZdWfMOD5VnLK3eSBf6TF0.woff2) format('woff2');unicode-range:U+0100-024F,U+0259,U+1E00-1EFF,U+2020,U+20A0-20AB,U+20AD-20CF,U+2113,U+2C60-2C7F,U+A720-A7FF}@font-face{font-family:'Fira Sans';font-style:normal;font-weight:700;font-display:swap;src:local('Fira Sans Bold'),local('FiraSans-Bold'),url(https://fonts.gstatic.com/s/firasans/v10/va9B4kDNxMZdWfMOD5VnLK3eRhf6.woff2) format('woff2');unicode-range:U+0000-00FF,U+0131,U+0152-0153,U+02BB-02BC,U+02C6,U+02DA,U+02DC,U+2000-206F,U+2074,U+20AC,U+2122,U+2191,U+2193,U+2212,U+2215,U+FEFF,U+FFFD}\");\n\n/*function ga() {\n  var script = document.createElement('script');\n  script.setAttribute('src', 'https://www.googletagmanager.com/gtag/js?id=UA-160640242-1');\n  script.setAttribute('async', '');\n  document.head.appendChild(script);\n\n  var script2 = document.createElement('script');\n  script2.innerText =   \"window.dataLayer = window.dataLayer || [];\" +\n  \"function gtag(){dataLayer.push(arguments);}\" +\n  \"gtag('js', new Date()); gtag('config', 'UA-160640242-1');\";\n  document.head.appendChild(script2);\n}*/\n\n\n/* R2D3 Source File:   */\n//:\\\\\\ usefull functions //:\\\\\\\n\nfunction getColors(n, type) {\n  // get drWhy palette\n\n  var temp = [\"#8bdcbe\", \"#f05a71\", \"#371ea3\", \"#46bac2\", \"#ae2c87\", \"#ffa58c\", \"#4378bf\"];\n  var ret = [];\n\n  if (type == \"bar\") {\n    switch (n) {\n      case 1:\n        return [\"#46bac2\"];\n      case 2:\n        return [\"#46bac2\", \"#4378bf\"];\n      case 3:\n        return [\"#8bdcbe\", \"#4378bf\", \"#46bac2\"];\n      case 4:\n        return [\"#46bac2\", \"#371ea3\", \"#8bdcbe\", \"#4378bf\"];\n      case 5:\n        return [\"#8bdcbe\", \"#f05a71\", \"#371ea3\", \"#46bac2\", \"#ffa58c\"];\n      case 6:\n        return [\"#8bdcbe\", \"#f05a71\", \"#371ea3\", \"#46bac2\", \"#ae2c87\", \"#ffa58c\"];\n      case 7:\n        return temp;\n      default:\n        for (var i = 0; i <= n%7; i++) {\n          ret = ret.concat(temp);\n        }\n        return ret;\n    }\n  } else if (type == \"line\") {\n    switch (n) {\n      case 1:\n        return [\"#46bac2\"];\n      case 2:\n        return [\"#8bdcbe\", \"#4378bf\"];\n      case 3:\n        return [\"#8bdcbe\", \"#f05a71\", \"#4378bf\"];\n      case 4:\n        return [\"#8bdcbe\", \"#f05a71\", \"#4378bf\", \"#ffa58c\"];\n      case 5:\n        return [\"#8bdcbe\", \"#f05a71\", \"#4378bf\", \"#ae2c87\", \"#ffa58c\"];\n      case 6:\n        return [\"#8bdcbe\", \"#f05a71\", \"#46bac2\", \"#ae2c87\", \"#ffa58c\", \"#4378bf\"];\n      case 7:\n        return temp;\n      default:\n        for (var j = 0; j <= n%7; j++) {\n          ret = ret.concat(temp);\n        }\n        return ret;\n    }\n  } else if (type == \"point\") {\n    switch (n) {\n      default:\n        return [\"#371ea3\", \"#46bac2\", \"#ceced9\"];\n    }\n  } else if (type == \"breakDown\") {\n    switch (n) {\n      default:\n        return [\"#8bdcbe\", \"#f05a71\", \"#371ea3\"];\n    }\n  }\n}\n\nfunction getTickValues(domain) {\n  // find 5 nice ticks with max and min - do better than d3\n\n  var tickValues = d3.ticks(domain[0], domain[1],5);\n\n  switch (tickValues.length) {\n    case 3:\n      tickValues.unshift(domain[0]);\n      tickValues.push(domain[1]);\n      break;\n\n    case 4:\n      if(Math.abs(domain[0] - tickValues[0]) < Math.abs(domain[1] - tickValues[3])){\n        tickValues.shift();\n        tickValues.unshift(domain[0]);\n        tickValues.push(domain[1]);\n      } else {\n        tickValues.pop();\n        tickValues.push(domain[1]);\n        tickValues.unshift(domain[0]);\n      }\n      break;\n\n    case 5:\n      tickValues.pop();\n      tickValues.shift();\n      tickValues.push(domain[1]);\n      tickValues.unshift(domain[0]);\n      break;\n\n    case 6:\n      if(Math.abs(domain[0] - tickValues[0]) < Math.abs(domain[1] - tickValues[5])){\n        tickValues.pop();\n        tickValues.shift();\n        tickValues.shift();\n        tickValues.push(domain[1]);\n        tickValues.unshift(domain[0]);\n      } else {\n        tickValues.pop();\n        tickValues.pop();\n        tickValues.shift();\n        tickValues.push(domain[1]);\n        tickValues.unshift(domain[0]);\n      }\n      break;\n\n    case 7:\n      tickValues.pop();\n      tickValues.pop();\n      tickValues.shift();\n      tickValues.shift();\n      tickValues.push(domain[1]);\n      tickValues.unshift(domain[0]);\n      break;\n\n    case 8:\n      if(Math.abs(domain[0] - tickValues[0]) < Math.abs(domain[1] - tickValues[7])){\n        tickValues.pop();\n        tickValues.pop();\n        tickValues.shift();\n        tickValues.shift();\n        tickValues.shift();\n        tickValues.push(domain[1]);\n        tickValues.unshift(domain[0]);\n      } else {\n        tickValues.pop();\n        tickValues.pop();\n        tickValues.pop();\n        tickValues.shift();\n        tickValues.shift();\n        tickValues.push(domain[1]);\n        tickValues.unshift(domain[0]);\n      }\n      break;\n    }\n\n  return tickValues;\n}\n\nfunction calculateTextWidth(text) {\n  // calculate max width of 11px text array\n\n  var temp = svg.selectAll()\n                .data(text)\n                .enter();\n\n  var textWidth = [];\n\n  temp.append(\"text\")\n      .attr(\"class\", \"toRemove\")\n      .text(function(d) { return d;})\n      .style(\"font-size\", \"11px\")\n      .style('font-family', 'Fira Sans, sans-serif')\n      .each(function(d,i) {\n          var thisWidth = this.getComputedTextLength();\n          textWidth.push(thisWidth);\n      });\n\n  svg.selectAll('.toRemove').remove();\n  temp.remove();\n\n  var maxLength = d3.max(textWidth);\n\n  return maxLength;\n}\n\nfunction getTextWidth(text, fontSize, fontFace) {\n  // calculate width of single text\n\n  var canvas = document.createElement('canvas');\n  var context = canvas.getContext('2d');\n  context.font = fontSize + 'px ' + fontFace;\n  return context.measureText(text).width;\n}\n\nfunction wrapText(text, width) {\n  // this function wraps text\n  text.each(function () {\n      var text = d3.select(this).style('font-family', 'Fira Sans, sans-serif'),\n          words = text.text().split(/\\s+/).reverse(),\n          word,\n          line = [],\n          lineNumber = 0,\n          lineHeight = 1.05, // ems\n          x = text.attr(\"x\"),\n          y = text.attr(\"y\"),\n          dy = 0, //parseFloat(text.attr(\"dy\")),\n          tspan = text.text(null)\n                      .append(\"tspan\")\n                      .attr(\"x\", x)\n                      .attr(\"y\", y)\n                      .attr(\"dy\", dy + \"em\");\n      while (word = words.pop()) {\n          line.push(word);\n          tspan.text(line.join(\" \"));\n          if (tspan.node().getComputedTextLength() > width) {\n              line.pop();\n              tspan.text(line.join(\" \"));\n              line = [word];\n              tspan = text.append(\"tspan\")\n                          .attr(\"x\", x)\n                          .attr(\"y\", y)\n                          .attr(\"dy\", ++lineNumber * lineHeight + dy + \"em\")\n                          .text(word);\n          }\n      }\n  });\n}\n\nfunction wrapHtmlOutput(text) {\n  var output = \"\";\n  text.replace(/\\(?[A-Z][^\\.]+[\\.!\\?]\\)?/g, function (sentence) {\n      output += (sentence + '<br>');\n  });\n  return output;\n}\n\n/* R2D3 Source File:   */\n/* d3.tip Copyright (c) 2013 Justin Palmer Tooltips for d3.js SVG visualizations */\n/// MADE SOME CHANGES\n\nd3.functor = function functor(v) {\n  return typeof v === \"function\" ? v : function() {\n    return v;\n  };\n};\n\nd3.tip = function(widget_id) {\n\n  var direction = d3_tip_direction,\n      offset    = d3_tip_offset,\n      html      = d3_tip_html,\n      node      = initNode(),\n      svg       = null,\n      point     = null,\n      target    = null,\n      widget_id = widget_id;\n\n  function tip(vis) {\n    svg = getSVGNode(vis)\n    point = svg.createSVGPoint()\n    document.getElementById(widget_id).appendChild(node)\n  }\n\n  // Public - show the tooltip on the screen\n  //\n  // Returns a tip\n  tip.show = function() {\n    var args = Array.prototype.slice.call(arguments)\n    if(args[args.length - 1] instanceof SVGElement) target = args.pop()\n\n    var content = html.apply(this, args),\n        poffset = offset.apply(this, args),\n        dir     = direction.apply(this, args),\n        nodel   = getNodeEl(),\n        i       = directions.length,\n        coords,\n        scrollTop  = document.documentElement.scrollTop || document.body.scrollTop,\n        scrollLeft = document.documentElement.scrollLeft || document.body.scrollLeft\n\n    /// unclass all directions\n    while(i--) nodel.classed(directions[i], false)\n\n    ////////////////////////////////:::::::::////////////////////////////////\n    // make sure that tip is pointing right direction (not outside of svg) \\\\\n    // 'n' means that tooltip will go north from pointer\n\n    // do not move this code V\n    nodel.html(content)\n          .style('position', 'fixed')\n          .style('opacity', .8)\n          .style('pointer-events', 'all')\n    // do not move this code ^\n\n    var tdir = dir;\n\n    var divDim = node.getBoundingClientRect(),\n        svgDim = svg.getBBox();\n\n    // 20 is for 2x r2d3 margin and 7 was added empiricaly\n    var sh = 20 + svgDim.height;// + 7; // this is modelStudio plotHeight\n    var sw = 20 + svgDim.width;\n    var dh = divDim.height;\n    var dw = divDim.width;\n    var py = d3.event.pageY;\n    var px = d3.event.pageX;\n\n    // by default put tooltip 'n'\n    var ttop = py - dh - 5;\n    var tleft = px - dw/2;\n    var tdir = \"n\";\n    var tpdd = '6px 6px 13px 6px';\n\n    if (px - dw/2 < 10) {\n      tleft = px + 5;\n      tdir = \"ne\";\n      tpdd = '6px 6px 11px 11px';\n      if (py - dh/2 < 10) {\n        ttop = py - dh/2;\n        tdir = \"e\";\n        tpdd = '6px 6px 6px 13px';\n      } else if (py - dh < 10) {\n        ttop = py + 5;\n        tdir = \"se\";\n        tpdd = '11px 6px 6px 11px';\n      }\n    } else if (px + dw/2 > sw - 10) {\n      tleft = px - dw - 5;\n      ttop = py - dh - 5;\n      tdir = \"nw\";\n      tpdd = '6px 11px 11px 6px';\n      if (py - dh/2 < 10) {\n        ttop = py - dh/2;\n        tdir = \"w\"\n        tpdd = '6px 13px 6px 6px';\n      } else if (py - dh < 10) {\n        ttop = py + 5;\n        tdir = \"sw\";\n        tpdd = '11px 11px 6px 6px';\n      }\n      // because description is to long FIXME/TODO: more cases\n      if (tleft < 5) {\n        ttop = py + 5;\n        tleft = px - dw/2;\n        tdir = \"s\";\n        tpdd = '13px 6px 6px 6px';\n      }\n    } else if (py - dh < 10) {\n      ttop = py + 5;\n      tleft = px - dw/2;\n      tdir = \"s\";\n      tpdd = '13px 6px 6px 6px';\n    }\n\n    nodel.classed(tdir, true)\n          .style('top', (ttop - scrollTop) + 'px')\n          .style('left', (tleft - scrollLeft) + 'px')\n          .style('padding', tpdd);\n\n    ////////////////////////////////::::::::://///////////////////////////////\n\n    //safeguard\n    if (dw == 0) {\n      return tip.hide()\n    } else {\n      return tip\n    }\n  }\n\n  // Public - hide the tooltip\n  //\n  // Returns a tip\n  tip.hide = function() {\n    var nodel = getNodeEl()\n    nodel\n      .style('opacity', 0)\n      .style('pointer-events', 'none')\n    return tip\n  }\n\n  // Public: Proxy attr calls to the d3 tip container.  Sets or gets attribute value.\n  //\n  // n - name of the attribute\n  // v - value of the attribute\n  //\n  // Returns tip or attribute value\n  tip.attr = function(n, v) {\n    if (arguments.length < 2 && typeof n === 'string') {\n      return getNodeEl().attr(n)\n    } else {\n      var args =  Array.prototype.slice.call(arguments)\n      d3.selection.prototype.attr.apply(getNodeEl(), args)\n    }\n\n    return tip\n  }\n\n  // Public: Proxy style calls to the d3 tip container.  Sets or gets a style value.\n  //\n  // n - name of the property\n  // v - value of the property\n  //\n  // Returns tip or style property value\n  tip.style = function(n, v) {\n    // debugger;\n    if (arguments.length < 2 && typeof n === 'string') {\n      return getNodeEl().style(n)\n    } else {\n      var args = Array.prototype.slice.call(arguments);\n      if (args.length === 1) {\n        var styles = args[0];\n        Object.keys(styles).forEach(function(key) {\n          return d3.selection.prototype.style.apply(getNodeEl(), [key, styles[key]]);\n        });\n      }\n    }\n\n    return tip\n  }\n\n  // Public: Set or get the direction of the tooltip\n  //\n  // v - One of n(north), s(south), e(east), or w(west), nw(northwest),\n  //     sw(southwest), ne(northeast) or se(southeast)\n  //\n  // Returns tip or direction\n  tip.direction = function(v) {\n    if (!arguments.length) return direction\n    direction = v == null ? v : d3.functor(v)\n\n    return tip\n  }\n\n  // Public: Sets or gets the offset of the tip\n  //\n  // v - Array of [x, y] offset\n  //\n  // Returns offset or\n  tip.offset = function(v) {\n    if (!arguments.length) return offset\n    offset = v == null ? v : d3.functor(v)\n\n    return tip\n  }\n\n  // Public: sets or gets the html value of the tooltip\n  //\n  // v - String value of the tip\n  //\n  // Returns html value or tip\n  tip.html = function(v) {\n    if (!arguments.length) return html\n    html = v == null ? v : d3.functor(v)\n\n    return tip\n  }\n\n  // Public: destroys the tooltip and removes it from the DOM\n  //\n  // Returns a tip\n  tip.destroy = function() {\n    if(node) {\n      getNodeEl().remove();\n      node = null;\n    }\n    return tip;\n  }\n\n  function d3_tip_direction() { return 'n' }\n  function d3_tip_offset() { return [0, 0] }\n  function d3_tip_html() { return ' ' }\n\n  var direction_callbacks = {\n    n:  direction_n,\n    s:  direction_s,\n    e:  direction_e,\n    w:  direction_w,\n    nw: direction_nw,\n    ne: direction_ne,\n    sw: direction_sw,\n    se: direction_se\n  };\n\n  var directions = Object.keys(direction_callbacks);\n\n  function direction_n() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.n.y - node.offsetHeight,\n      left: bbox.n.x - node.offsetWidth / 2\n    }\n  }\n\n  function direction_s() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.s.y,\n      left: bbox.s.x - node.offsetWidth / 2\n    }\n  }\n\n  function direction_e() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.e.y - node.offsetHeight / 2,\n      left: bbox.e.x\n    }\n  }\n\n  function direction_w() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.w.y - node.offsetHeight / 2,\n      left: bbox.w.x - node.offsetWidth\n    }\n  }\n\n  function direction_nw() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.nw.y - node.offsetHeight,\n      left: bbox.nw.x - node.offsetWidth\n    }\n  }\n\n  function direction_ne() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.ne.y - node.offsetHeight,\n      left: bbox.ne.x\n    }\n  }\n\n  function direction_sw() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.sw.y,\n      left: bbox.sw.x - node.offsetWidth\n    }\n  }\n\n  function direction_se() {\n    var bbox = getScreenBBox()\n    return {\n      top:  bbox.se.y,\n      left: bbox.e.x\n    }\n  }\n\n  function initNode() {\n    var node = d3.select(document.createElement('div'))\n    node\n      .style('position', 'fixed')\n      .style('top', 0)\n      .style('opacity', 0)\n      .style('pointer-events', 'none')\n      .style('box-sizing', 'border-box')\n      .style('line-height', 1.1)\n      .style('background', \"#000000\")\n      .style('color', '#fff')\n      .style('font-size', '14px')\n      .style('font-family', \"'Roboto Condensed', sans-serif\");\n\n    return node.node()\n  }\n\n\n  function getSVGNode(el) {\n    el = el.node()\n    if(el.tagName.toLowerCase() === 'svg')\n      return el\n\n    return el.ownerSVGElement\n  }\n\n  function getNodeEl() {\n    if(node === null) {\n      node = initNode();\n      // re-add node to DOM\n      document.getElementById(widget_id).appendChild(node);\n    };\n    return d3.select(node);\n  }\n\n  // Returns an Object {n, s, e, w, nw, sw, ne, se}\n  function getScreenBBox() {\n    var targetel   = target || d3.event.target;\n\n    while ('undefined' === typeof targetel.getScreenCTM && 'undefined' === targetel.parentNode) {\n        targetel = targetel.parentNode;\n    }\n\n    var bbox       = {},\n        matrix     = targetel.getScreenCTM(),\n        tbbox      = targetel.getBBox(),\n        width      = tbbox.width,\n        height     = tbbox.height,\n        x          = tbbox.x,\n        y          = tbbox.y\n\n    point.x = x\n    point.y = y\n    bbox.nw = point.matrixTransform(matrix)\n    point.x += width\n    bbox.ne = point.matrixTransform(matrix)\n    point.y += 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averageTarget;\n\n/// general plot functions\n\nfunction breakDown() {\n\n  let tObservationId = CLICKED_OBSERVATION_ID,\n      tData = obsData[tObservationId];\n\n  if (tData[0].x === undefined) return null;\n\n  var bdData = tData[0],\n      bData = bdData.x;\n      bdBarCount = bdData.m[0],\n      xMinMax = bdData.x_min_max,\n      desc = bdData.desc;\n\n  var bdPlotHeight = SCALE_PLOT ? h : bdBarCount*bdBarWidth + (bdBarCount+1)*bdBarWidth/2,\n      bdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + bdPlotWidth])\n            .domain([xMinMax[0], xMinMax[1]]);\n\n  BD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + bdPlotWidth/2) + \" ,\" +\n                         (margin.top + bdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"contribution\");\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = BD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + bdPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + bdPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.variable));\n\n  var xGrid = BD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + bdPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-bdPlotHeight-additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = BD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-bdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = BD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.select(\".tick:last-child\").select(\"text\").attr('font-weight', 600);\n\n  // wrap y label text\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  BD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(bdSubtitle);\n\n  BD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(bdTitle);\n\n  // add tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipBD\")\n                  .html(d => d.type === \"desc\"\n                             ? descTooltipHtml(d) : bdTooltipHtml(d));\n\n  BD.call(tooltip);\n\n  // find boundaries\n  let intercept = bData[0].contribution > 0\n                  ? bData[0].barStart\n                  : bData[0].barSupport;\n\n  // make dotted line from intercept to prediction\n  var dotLineData = [{\"x\": x(intercept), \"y\": y(\"intercept\")},\n                     {\"x\": x(intercept), \"y\": y(\"prediction\") + y.bandwidth()}];\n\n  var lineFunction = d3.line()\n                       .x(d => d.x)\n                       .y(d => d.y);\n\n  BD.append(\"path\")\n    .data([dotLineData])\n    .attr(\"class\", \"dotLine\")\n    .attr(\"d\", lineFunction)\n    .style(\"stroke-dasharray\", (\"1, 2\"));\n\n  // add bars\n  var bars = BD.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"BD-bars\")\n      .attr(\"id\", d => d.variable_name)\n      .attr(\"fill\", d => {\n        switch (d.sign) {\n          case \"-1\":\n            return bdNegativeColor;\n          case \"1\":\n            return bdPositiveColor;\n          default:\n            return defaultColor;\n        }\n      })\n      .attr(\"fill-opacity\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                                 ? 0 : 1) //invisible bar for clicking purpose\n      .attr(\"y\", d => y(d.variable))\n      .attr(\"height\", y.bandwidth())\n      .attr(\"x\", d => d.contribution > 0 ? x(d.barStart) : x(d.barSupport))\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .on(\"click\", function() {\n        updatePlots(event = \"variableChange\",\n                    variableName = this.id,\n                    observationId = null,\n                    plotId = null);\n      })\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.barStart))\n      .attr(\"width\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                          ? 5 : x(d.barSupport) - x(d.barStart));\n\n  // add labels to bars\n  var ctbLabel = BD.selectAll()\n                   .data(bData)\n                   .enter()\n                   .append(\"g\");\n\n  ctbLabel.append(\"text\")\n          .attr(\"class\", \"axisLabel\")\n          .attr(\"x\", d => {\n            switch (d.sign) {\n              case \"X\":\n                return d.contribution < 0\n                       ? x(d.barStart) - 5 : x(d.barSupport) + 5;\n              default:\n                return x(d.barSupport) + 5;\n            }\n          })\n          .attr(\"y\", d => y(d.variable) + y.bandwidth()/2)\n          .attr(\"dy\", \"0.4em\")\n          .attr(\"text-anchor\", d => d.sign == \"X\" && d.contribution < 0\n                               ? \"end\" : null)\n          .transition()\n          .duration(TIME)\n          .delay((d,i) => (i+1) * TIME)\n          .text(d => {\n            switch (d.variable) {\n              case \"intercept\":\n              case \"prediction\":\n                return d.cumulative;\n              default:\n                return d.sign === \"-1\" ? d.contribution : \"+\"+d.contribution;\n            }\n          });\n\n  // add lines to bars\n  var lines = BD.selectAll()\n                .data(bData)\n                .enter()\n                .append(\"g\");\n\n  lines.append(\"line\")\n       .attr(\"class\", \"interceptLine\")\n       .attr(\"x1\", d => d.contribution < 0 ? x(d.barStart) : x(d.barSupport))\n       .attr(\"y1\", d => y(d.variable))\n       .attr(\"x2\", d => d.contribution < 0 ? x(d.barStart) : x(d.barSupport))\n       .attr(\"y2\", d => y(d.variable))\n       .transition()\n       .duration(TIME)\n       .delay((d,i) => (i+1) * TIME)\n       .attr(\"y2\", d => d.variable == \"prediction\"\n                        ? y(d.variable) : y(d.variable) + y.bandwidth()*2.5);\n\n  var description = BD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + bdPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction shapleyValues() {\n\n  let tObservationId = CLICKED_OBSERVATION_ID,\n      tData = obsData[tObservationId];\n\n  if (tData[2].x === undefined) return null;\n\n  var svData = tData[2],\n      bData = svData.x,\n      svBarCount = svData.m[0],\n      xMinMax = svData.x_min_max,\n      desc = svData.desc;\n\n  var svPlotHeight = SCALE_PLOT ? h : svBarCount*svBarWidth + (svBarCount+1)*svBarWidth/2,\n      svPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + svPlotWidth])\n            .domain([xMinMax[0], xMinMax[1]]);\n\n  SV.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + svPlotWidth/2) + \" ,\" +\n                         (margin.top + svPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"contribution\");\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = SV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + svPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + svPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.variable));\n\n  var xGrid = SV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + svPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-svPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = SV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-svPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = SV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // wrap y label text\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  SV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(svSubtitle);\n\n  SV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(svTitle);\n\n  // add tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipSV\")\n                  .html(d => d.type === \"desc\"\n                             ? descTooltipHtml(d) : bdTooltipHtml(d));\n\n  SV.call(tooltip);\n\n  // add bars\n  var bars = SV.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"SV-bars\")\n      .attr(\"id\", (d) => d.variable_name)\n      .attr(\"fill\", function(d) {\n        switch (d.sign) {\n          case \"-1\":\n            return svNegativeColor;\n          case \"1\":\n            return svPositiveColor;\n          default:\n            return defaultColor;\n        }\n      })\n      .attr(\"fill-opacity\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                                 ? 0 : 1) //invisible bar for clicking purpose\n      .attr(\"x\", d => d.contribution > 0 ? x(d.barStart) : x(d.barSupport))\n      .attr(\"y\", d => y(d.variable))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .on(\"click\", function() {\n        updatePlots(event = \"variableChange\",\n                    variableName = this.id,\n                    observationId = null,\n                    plotId = null);\n      })\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.barStart))\n      .attr(\"width\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                          ? 5 : x(d.barSupport) - x(d.barStart));\n\n  // add labels to bars\n  var ctbLabel = SV.selectAll()\n                   .data(bData)\n                   .enter()\n                   .append(\"g\");\n\n  ctbLabel.append(\"text\")\n          .attr(\"class\", \"axisLabel\")\n          .attr(\"x\", d => d.contribution > 0\n                          ? x(d.barStart) - 5 : x(d.barSupport) + 5)\n          .attr(\"y\", d => y(d.variable) + y.bandwidth()/2)\n          .attr(\"dy\", \"0.4em\")\n          .attr(\"text-anchor\", d => d.sign == \"1\" ? \"end\" : \"start\")\n          .transition()\n          .duration(TIME)\n          .delay((d,i) => (i+1) * TIME)\n          .text(d => d.sign == \"-1\" ? d.contribution : \"+\"+d.contribution);\n\n  // add lines to bars\n  var lines = SV.selectAll()\n                .data(bData)\n                .enter()\n                .append(\"g\");\n\n  lines.append(\"line\")\n        .attr(\"class\", \"interceptLine\")\n        .attr(\"x1\", d => d.contribution < 0 ? x(d.barSupport) : x(d.barStart))\n        .attr(\"y1\", d => y(d.variable))\n        .attr(\"x2\", d => d.contribution < 0 ? x(d.barSupport) : x(d.barStart))\n        .attr(\"y2\", d => y(d.variable))\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => (i+1) * TIME)\n        .attr(\"y2\", (d,i) => i == svBarCount - 1\n                             ? y(d.variable) + y.bandwidth()\n                             : y(d.variable) + y.bandwidth()*2.5);\n\n\n  // boxplots\n  if (SHOW_BOXPLOT) {\n    // main horizontal line\n    bars.append(\"line\")\n        .attr(\"class\", \"interceptLine\")\n        .attr(\"x1\", d => d.contribution < 0 ? x(d.max) : x(d.min))\n        .attr(\"x2\", d => d.contribution < 0 ? x(d.max) : x(d.min))\n        .attr(\"y1\", d => y(d.variable) + y.bandwidth()/2)\n        .attr(\"y2\", d => y(d.variable) + y.bandwidth()/2)\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x1\", d => x(d.min))\n        .attr(\"x2\", d => x(d.max));\n\n    // rectangle for the main box\n    bars.append(\"rect\")\n        .attr(\"x\", d => d.contribution < 0 ? x(d.q3) : x(d.q1))\n        .attr(\"y\", d => y(d.variable) + y.bandwidth()/3)\n        .attr(\"height\", y.bandwidth()/3)\n        .style(\"fill\", \"#371ea3\")\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x\", d => x(d.q1))\n        .attr(\"width\", d => Math.abs(x(d.q3) - x(d.q1)));\n  }\n\n  // description\n  var description = SV.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + svPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction ceterisParibus() {\n\n  let tObservationId = CLICKED_OBSERVATION_ID,\n      tData = obsData[tObservationId];\n\n  if (tData[1].x === undefined) return null;\n\n  let cpData = tData[1],\n      profData = cpData.x,\n      xMinMax = cpData.x_min_max_list,\n      yMinMax = cpData.y_min_max,\n      pData = cpData.observation,\n      isNumeric = cpData.is_numeric\n      desc = cpData.desc;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // lines or bars?\n  if (isNumeric[tVariableName][0]) {\n    cpNumericalPlot(tVariableName, profData[tVariableName],\n                    xMinMax[tVariableName], yMinMax, pData,\n                    desc[tVariableName]);\n  } else {\n    cpCategoricalPlot(tVariableName, profData[tVariableName],\n                      yMinMax, pData, desc[tVariableName]);\n  }\n}\n\nfunction featureImportance() {\n\n  if (fiData.x === undefined) return null;\n\n  var fiBarCount = fiData.m[0],\n      bData = fiData.x,\n      xMinMax = fiData.x_min_max,\n      desc = fiData.desc;\n\n  var fiPlotHeight = SCALE_PLOT ? h : fiBarCount*fiBarWidth + (fiBarCount+1)*fiBarWidth/2,\n      fiPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + fiPlotWidth])\n            .domain([xMinMax[0], xMinMax[1]]);\n\n  FI.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + fiPlotWidth/2) + \" ,\" +\n                         (margin.top + fiPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"drop-out loss\");\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = FI.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + fiPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + fiPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.variable));\n\n  var xGrid = FI.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + fiPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-fiPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = FI.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-fiPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = FI.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  FI.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(fiSubtitle);\n\n  FI.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(fiTitle);\n\n  // tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipFI\")\n                  .html(d => d.type === \"desc\"\n                             ? descTooltipHtml(d)\n                             : fiStaticTooltipHtml(d));\n  FI.call(tooltip);\n\n  // bars\n  var bars = FI.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  // find full model dropout_loss value\n  var fullModel = bData[0].full_model;\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"FI-bars\")\n      .attr(\"fill\", fiBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.variable))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .attr(\"id\", (d) => d.variable)\n      .on(\"click\", function(){\n        updatePlots(event = \"variableChange\",\n                    variableName = this.id,\n                    observationId = null,\n                    plotId = null);\n      })\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.dropout_loss) < x(fullModel)\n                      ? x(d.dropout_loss) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.dropout_loss) - x(fullModel)));\n\n  // make the interceptLine\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n  bars.selectAll(\".FI-bars\").each(function() {\n    if (+this.getAttribute('y') < minimumY) {\n      minimumY = +this.getAttribute('y');\n    }\n    if (+this.getAttribute('y') > maximumY) {\n      maximumY = +this.getAttribute('y');\n    }\n  });\n\n  FI.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  // boxplots\n  if (SHOW_BOXPLOT) {\n\n    // main horizontal line\n    bars.append(\"line\")\n        .attr(\"class\", \"interceptLine\")\n        .attr(\"x1\", d => x(d.dropout_loss) < x(fullModel) ? x(d.max) : x(d.min))\n        .attr(\"x2\", d => x(d.dropout_loss) < x(fullModel) ? x(d.max) : x(d.min))\n        .attr(\"y1\", d => y(d.variable) + y.bandwidth()/2)\n        .attr(\"y2\", d => y(d.variable) + y.bandwidth()/2)\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x1\", d => x(d.min))\n        .attr(\"x2\", d => x(d.max));\n\n    // rectangle for the main box\n    bars.append(\"rect\")\n        .attr(\"x\", d => x(d.dropout_loss) < x(fullModel) ? x(d.q3) : x(d.q1))\n        .attr(\"y\", d => y(d.variable) + y.bandwidth()/3)\n        .attr(\"height\", y.bandwidth()/3)\n        .style(\"fill\", \"#371ea3\")\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x\", d => x(d.q1))\n        .attr(\"width\", d => Math.abs(x(d.q3) - x(d.q1)));\n  }\n\n  // description\n  var description = FI.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + fiPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction partialDependence() {\n\n  if (pdData.x === undefined) return null;\n\n  let profData = pdData.x,\n      xMinMax = pdData.x_min_max_list,\n      yMinMax = pdData.y_min_max,\n      yMean = pdData.y_mean,\n      isNumeric = pdData.is_numeric,\n      desc = pdData.desc;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // lines or bars?\n  if (isNumeric[tVariableName][0]) {\n    pdNumericalPlot(tVariableName, profData[tVariableName],\n                    xMinMax[tVariableName], yMinMax, yMean,\n                    desc[tVariableName]);\n  } else {\n    pdCategoricalPlot(tVariableName, profData[tVariableName],\n                      yMinMax, yMean, desc[tVariableName]);\n  }\n}\n\nfunction accumulatedDependence() {\n\n  if (adData.x === undefined) return null;\n\n  let profData = adData.x,\n      xMinMax = adData.x_min_max_list,\n      yMinMax = adData.y_min_max,\n      yMean = adData.y_mean,\n      isNumeric = adData.is_numeric,\n      desc = adData.desc;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // lines or bars?\n  if (isNumeric[tVariableName][0]) {\n    adNumericalPlot(tVariableName, profData[tVariableName],\n                    xMinMax[tVariableName], yMinMax, yMean,\n                    desc[tVariableName]);\n  } else {\n    adCategoricalPlot(tVariableName, profData[tVariableName],\n                      yMinMax, yMean, desc[tVariableName]);\n  }\n}\n\nfunction featureDistribution() {\n\n  if (fdData.x === undefined) return null;\n\n  let dData = fdData.x,\n      xMinMax = fdData.x_min_max_list,\n      xMax = fdData.x_max_list,\n      nBin = fdData.nbin,\n      isNumeric = fdData.is_numeric;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // histogram or bars?\n  if (isNumeric[tVariableName][0]) {\n    fdNumericalPlot(tVariableName, dData, xMinMax[tVariableName],\n                    nBin[tVariableName]);\n  } else {\n    fdCategoricalPlot(tVariableName, dData, xMinMax[tVariableName],\n                      xMax[tVariableName]);\n  }\n}\n\nfunction targetVs() {\n\n  if (tvData.x === undefined) return null;\n\n  let xData = tvData.x,\n      xMinMax = tvData.x_min_max_list,\n      yMinMax = tvData.y_min_max,\n      isNumeric = tvData.is_numeric;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // scatterplot or violin?\n  if (isNumeric[tVariableName][0]) {\n    tvNumericalPlot(tVariableName, xData, xMinMax[tVariableName], yMinMax);\n  } else {\n    tvCategoricalPlot(tVariableName, xData, xMinMax[tVariableName], yMinMax);\n  }\n}\n\nfunction averageTarget() {\n\n  if (atData.x === undefined) return null;\n\n  let xData = atData.x,\n      xMinMax = atData.x_min_max_list,\n      yMinMax = atData.y_min_max_list,\n      yMean = atData.y_mean,\n      isNumeric = atData.is_numeric;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // scatterplot or violin?\n  if (isNumeric[tVariableName][0]) {\n    atNumericalPlot(tVariableName, xData[tVariableName],\n                    xMinMax[tVariableName], yMinMax[tVariableName], yMean);\n  } else {\n    atCategoricalPlot(tVariableName, xData[tVariableName],\n                      xMinMax[tVariableName], yMinMax[tVariableName], yMean);\n  }\n}\n\n/// small plot functions\n\nfunction cpNumericalPlot(variableName, lData, mData, yMinMax, pData, desc) {\n\n  var cpPlotHeight = h,\n      cpPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + cpPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  CP.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + cpPlotWidth/2) + \" ,\" +\n                         (margin.top + cpPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName + \" = \" + pData[0][variableName]);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + cpPlotHeight, margin.top - additionalHeight])\n            .domain([yMinMax[0], yMinMax[1]]);\n\n  var line = d3.line()\n               .x(d => x(d.xhat))\n               .y(d => y(d.yhat))\n               .curve(d3.curveMonotoneX);\n\n   CP.append(\"text\")\n     .attr(\"class\",\"smallTitle\")\n     .attr(\"x\", margin.left)\n     .attr(\"y\", margin.top - 15)\n     .text(cpSubtitle); //variableName + \" = \" + pData[0][variableName]\n\n  CP.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(cpTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + cpPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = CP.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-cpPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipCP\")\n                  .html((d, addData) => {\n\n                    if (d.type === \"desc\") {\n                      return descTooltipHtml(d)\n                    } else if (addData !== undefined) {\n                      return cpChangedTooltipHtml(d, addData);\n                    } else {\n                        return cpStaticTooltipHtml(d);\n                    }\n                   });\n  CP.call(tooltip);\n\n  // function to find nearest point on the line\n  var bisectXhat = d3.bisector(d => d.xhat).right;\n\n  // show tooltip with info nearest to mouseover\n  function showTooltip(hover) {\n    var x0 = x.invert(d3.mouse(d3.event.currentTarget)[0]),\n        i = bisectXhat(hover, x0),\n        d0 = hover[i - 1],\n        d1 = hover[i],\n        d = x0 - d0.xhat > d1.xhat - x0 ? d1 : d0;\n    let temp = pData.find(el => el[\"observation.id\"] === d.id);\n    tooltip.show(d, temp);\n  }\n\n  // add path\n  var p = CP.append(\"path\")\n            .attr(\"class\", \"CP-lines\")\n            .style(\"fill\", \"none\")\n            .style(\"stroke\", cpLineColor)\n            .style(\"stroke-width\", cpLineSize)\n            .on('mouseover', function(d) {\n\n              // make mouseover line more visible\n              d3.select(this)\n                .style(\"stroke\", defaultColor)\n                .style(\"stroke-width\", cpLineSize*1.5);\n\n              // make line and points appear on top\n              this.parentNode.appendChild(this);\n              d3.select(this.parentNode).selectAll(\".point\").each(function() {\n                               this.parentNode.appendChild(this);\n                          });\n\n              // show changed tooltip\n              showTooltip(d);\n            })\n            .on('mouseout', function(d) {\n\n              d3.select(this)\n                .style(\"stroke\", cpLineColor)\n                .style(\"stroke-width\", cpLineSize);\n\n              // hide changed tooltip\n              tooltip.hide(d);\n            });\n\n  // animate path\n  p.data([{\"xhat\":0, \"yhat\": 0}])\n   .attr(\"d\", line)\n   .transition()\n   .duration(TIME)\n   .attrTween(\"d\", function() {\n     var previous = d3.select(this).attr('d');\n     var current = line(lData);\n     return d3.interpolatePath(previous, current);\n   });\n\n  // add data for tooltip\n  p.data([lData]);\n\n  // add points\n  CP.selectAll()\n    .data(pData)\n    .enter()\n    .append(\"circle\")\n    .attr(\"class\", \"point\")\n    .attr(\"id\", d => d[\"observation.id\"])\n    .attr(\"cx\", d => x(d[variableName]))\n    .attr(\"cy\", d => y(d.yhat))\n    .attr(\"r\", 0)\n    .style(\"stroke-width\", 15)\n    .style(\"stroke\", \"red\")\n    .style(\"stroke-opacity\", 0)\n    .style(\"fill\", cpPointColor)\n    .on('mouseover', function(d) {\n      tooltip.show(d);\n  \t\td3.select(this)\n  \t\t\t.attr(\"r\", 2*cpPointSize);\n  \t})\n    .on('mouseout', function(d) {\n      tooltip.hide(d);\n  \t\td3.select(this)\n  \t\t\t.attr(\"r\", cpPointSize);\n  \t})\n    .transition()\n    .duration(TIME)\n    .delay(TIME)\n    .attr(\"r\", cpPointSize);\n\n  // add rugs\n  CP.selectAll()\n    .data(pData)\n    .enter()\n    .append(\"line\")\n    .attr(\"class\", \"rugLine\")\n    .style(\"stroke\", \"red\")\n    .style(\"stroke-width\", 2)\n    .attr(\"x1\", d => x(d[variableName]))\n    .attr(\"y1\", margin.top + cpPlotHeight)\n    .attr(\"x2\", d => x(d[variableName]))\n    .attr(\"y2\", margin.top + cpPlotHeight - 10);\n\n  CP.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + cpPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"prediction\");\n\n  var description = CP.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + cpPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction cpCategoricalPlot(variableName, bData, yMinMax, lData, desc) {\n\n  var cpBarCount = bData.map(d => d.xhat).length;\n\n  var cpPlotHeight = SCALE_PLOT ? h : cpBarCount*cpBarWidth + (cpBarCount+1)*cpBarWidth/2,\n      cpPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + cpPlotWidth])\n            .domain([yMinMax[0], yMinMax[1]]); // because it is flipped\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + cpPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + cpPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.xhat));\n\n  var xGrid = CP.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + cpPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-cpPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = CP.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-cpPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  CP.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(cpSubtitle); //variableName + \" = \" + lData[0][variableName]\n\n  CP.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(cpTitle);\n\n  var bars = CP.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  var fullModel = lData[0].yhat;\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipCP\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : cpChangedTooltipHtml(d, lData[0]));\n  CP.call(tooltip);\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"CP-bars\")\n      .attr(\"fill\", cpBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.xhat))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.yhat) < x(fullModel) ? x(d.yhat) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.yhat) - x(fullModel)));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".CP-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  CP.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  CP.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + cpPlotWidth/2) + \" ,\" +\n                         (margin.top + cpPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"prediction\");\n\n  var description = CP.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + cpPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction pdNumericalPlot(variableName, lData, mData, yMinMax, yMean, desc) {\n\n  var pdPlotHeight = h,\n      pdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + pdPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  PD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + pdPlotWidth/2) + \" ,\" +\n                         (margin.top + pdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + pdPlotHeight, margin.top - additionalHeight])\n            .domain([yMinMax[0], yMinMax[1]]);\n\n  var line = d3.line()\n               .x(d => x(d.xhat))\n               .y(d => y(d.yhat))\n               .curve(d3.curveMonotoneX);\n\n   PD.append(\"text\")\n     .attr(\"class\",\"smallTitle\")\n     .attr(\"x\", margin.left)\n     .attr(\"y\", margin.top - 15)\n     .text(pdSubtitle); // variableName\n\n  PD.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(pdTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + pdPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = PD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-pdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipPD\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : pdStaticTooltipHtml(d, variableName, yMean));\n  PD.call(tooltip);\n\n  // function to find nearest point on the line\n  var bisectXhat = d3.bisector(d => d.xhat).right;\n\n  // show tooltip with info nearest to mouseover\n  function showTooltip(hover) {\n    var x0 = x.invert(d3.mouse(d3.event.currentTarget)[0]),\n        i = bisectXhat(hover, x0),\n        d0 = hover[i - 1],\n        d1 = hover[i],\n        d = x0 - d0.xhat > d1.xhat - x0 ? d1 : d0;\n\n    tooltip.show(d);\n  }\n\n  // add lines\n  var p = PD.append(\"path\")\n            .attr(\"class\", \"PD-lines\")\n            .style(\"fill\", \"none\")\n            .style(\"stroke\", pdLineColor)\n            .style(\"stroke-width\", pdLineSize)\n            .on('mouseover', function(d) {\n\n              // make mouseover line more visible\n              d3.select(this)\n                .style(\"stroke\", defaultColor)\n                .style(\"stroke-width\", pdLineSize*1.5);\n\n              // make line appear on top\n              this.parentNode.appendChild(this);\n\n              // show changed tooltip\n              showTooltip(d);\n            })\n            .on('mouseout', function(d) {\n\n              d3.select(this)\n                .style(\"stroke\", pdLineColor)\n                .style(\"stroke-width\", pdLineSize);\n\n              // hide changed tooltip\n              tooltip.hide(d);\n            });\n\n  // animate path\n  p.data([{\"xhat\":0, \"yhat\": 0}])\n   .attr(\"d\", line)\n   .transition()\n   .duration(TIME)\n   .attrTween(\"d\", function() {\n     var previous = d3.select(this).attr('d');\n     var current = line(lData);\n     return d3.interpolatePath(previous, current);\n   });\n\n  // add data for tooltip\n  p.data([lData]);\n\n  PD.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + pdPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average prediction\");\n\n  var description = PD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + pdPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction pdCategoricalPlot(variableName, bData, yMinMax, yMean, desc) {\n\n  var pdBarCount = bData.map(d => d.xhat).length;\n\n  var pdPlotHeight = SCALE_PLOT ? h : pdBarCount*pdBarWidth + (pdBarCount+1)*pdBarWidth/2,\n      pdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + pdPlotWidth])\n            .domain([yMinMax[0], yMinMax[1]]); // because it is flipped\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + pdPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + pdPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.xhat));\n\n  var xGrid = PD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + pdPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-pdPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = PD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-pdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 8) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  PD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(pdSubtitle); // variableName\n\n  PD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(pdTitle);\n\n  var bars = PD.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  var fullModel = yMean;\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipPD\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : pdStaticTooltipHtml(d, variableName, yMean));\n  PD.call(tooltip);\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"PD-bars\")\n      .attr(\"fill\", pdBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.xhat))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.yhat) < x(fullModel) ? x(d.yhat) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.yhat) - x(fullModel)));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".PD-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  PD.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  PD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + pdPlotWidth/2) + \",\" +\n                         (margin.top + pdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average prediction\");\n\n  var description = PD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + pdPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction adNumericalPlot(variableName, lData, mData, yMinMax, yMean, desc) {\n\n  var adPlotHeight = h,\n      adPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + adPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  AD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + adPlotWidth/2) + \" ,\" +\n                         (margin.top + adPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + adPlotHeight, margin.top - additionalHeight])\n            .domain([yMinMax[0], yMinMax[1]]);\n\n  var line = d3.line()\n               .x(d => x(d.xhat))\n               .y(d => y(d.yhat))\n               .curve(d3.curveMonotoneX);\n\n  AD.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(adSubtitle); // variableName\n\n  AD.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(adTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + adPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = AD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-adPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipPD\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : adStaticTooltipHtml(d, variableName, yMean));\n  AD.call(tooltip);\n\n  // function to find nearest point on the line\n  var bisectXhat = d3.bisector(d => d.xhat).right;\n\n  // show tooltip with info nearest to mouseover\n  function showTooltip(hover) {\n    var x0 = x.invert(d3.mouse(d3.event.currentTarget)[0]),\n        i = bisectXhat(hover, x0),\n        d0 = hover[i - 1],\n        d1 = hover[i],\n        d = x0 - d0.xhat > d1.xhat - x0 ? d1 : d0;\n\n    tooltip.show(d);\n  }\n\n  // add lines\n  var p = AD.append(\"path\")\n            .attr(\"class\", \"AD-lines\")\n            .style(\"fill\", \"none\")\n            .style(\"stroke\", adLineColor)\n            .style(\"stroke-width\", adLineSize)\n            .on('mouseover', function(d) {\n\n              // make mouseover line more visible\n              d3.select(this)\n                .style(\"stroke\", defaultColor)\n                .style(\"stroke-width\", adLineSize*1.5);\n\n              // make line appear on top\n              this.parentNode.appendChild(this);\n\n              // show changed tooltip\n              showTooltip(d);\n            })\n            .on('mouseout', function(d) {\n\n              d3.select(this)\n                .style(\"stroke\", adLineColor)\n                .style(\"stroke-width\", adLineSize);\n\n              // hide changed tooltip\n              tooltip.hide(d);\n            });\n\n  // animate path\n  p.data([{\"xhat\":0, \"yhat\": 0}])\n   .attr(\"d\", line)\n   .transition()\n   .duration(TIME)\n   .attrTween(\"d\", function() {\n     var previous = d3.select(this).attr('d');\n     var current = line(lData);\n     return d3.interpolatePath(previous, current);\n   });\n\n  // add data for tooltip\n  p.data([lData]);\n\n  AD.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + adPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"accumulated prediction\");\n\n  var description = AD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + adPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction adCategoricalPlot(variableName, bData, yMinMax, yMean, desc) {\n\n  var adBarCount = bData.map(d => d.xhat).length;\n\n  var adPlotHeight = SCALE_PLOT ? h : adBarCount*adBarWidth + (adBarCount+1)*adBarWidth/2,\n      adPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + adPlotWidth])\n            .domain([yMinMax[0], yMinMax[1]]); // because it is flipped\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + adPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + adPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.xhat));\n\n  var xGrid = AD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + adPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-adPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = AD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-adPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  AD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(adSubtitle); // variableName\n\n  AD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(adTitle);\n\n  var bars = AD.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  var fullModel = 0; //yMean;\n    // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : adStaticTooltipHtml(d, variableName, yMean));\n  AD.call(tooltip);\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"AD-bars\")\n      .attr(\"fill\", adBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.xhat))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.yhat) < x(fullModel) ? x(d.yhat) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.yhat) - x(fullModel)));;\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".AD-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  AD.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  AD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + adPlotWidth/2) + \",\" +\n                         (margin.top + adPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"accumulated prediction\");\n\n  var description = AD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + adPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction fdNumericalPlot(variableName, dData, mData, nBin) {\n\n  var fdPlotHeight = h,\n      fdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + fdPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  FD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + fdPlotWidth/2) + \" ,\" +\n                         (margin.top + fdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  FD.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + fdPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"count\");\n\n  var y = d3.scaleLinear()\n        .range([margin.top + fdPlotHeight - 5, margin.top]);\n\n  FD.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(fdSubtitle);\n\n  FD.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(fdTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = FD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + fdPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yAxis = FD.append(\"g\")\n                .attr(\"class\", \"axisLabel\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\");\n\n  var yGrid = FD.append(\"g\")\n                  .attr(\"class\", \"grid\")\n                  .attr(\"transform\", \"translate(\" + margin.left + \",0)\");\n\n  var slider = d3.sliderBottom()\n                 .min(d3.max([+nBin-10,2]))\n                 .max(d3.max([+nBin+10,12]))\n                 .width(fdPlotWidth/2 - 40) // fit exit button\n                 .ticks(8)\n                 .step(1)\n                 .default(nBin)\n                 .fill(fdBarColor)\n                 .on('onchange', val => updateHist(val));\n\n  var sliderg = FD.append(\"g\").call(slider);\n\n  sliderg.attr(\"transform\", \"translate(\" + (margin.left + fdPlotWidth/2 - margin.small)\n                            + \",\" + margin.small + \")\");\n\n  updateHist(+nBin);\n\n  function updateHist(nbin) {\n\n    var histogram = d3.histogram()\n                      .value(d => d[variableName])\n                      .domain(x.domain())\n                      .thresholds(nbin);\n\n    var bins = histogram(dData);\n\n    y.domain([0, d3.max(bins, d => d.length)]);\n\n    let yaF = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n    yAxis.call(yaF)\n         .call(g => g.select(\".domain\").remove());\n\n    yGrid.call(d3.axisLeft(y)\n                 .ticks(10)\n                 .tickSize(-fdPlotWidth)\n                 .tickFormat(\"\")\n               ).call(g => g.select(\".domain\").remove());\n\n    var bars = FD.selectAll(\"rect\")\n                 .data(bins);\n\n    bars.enter()\n        .append(\"rect\")\n        .attr(\"fill\", fdBarColor)\n        .merge(bars)\n        .attr(\"x\", d => x(d.x0))\n        .attr(\"y\", d => y(0))\n        .attr(\"height\", d => 0)\n        .attr(\"width\", d => x(d.x1) - x(d.x0))\n        .transition()\n        .duration(TIME)\n          .attr(\"y\", d => y(d.length))\n          .attr(\"height\", d => y(0) - y(d.length));\n\n    bars.exit()\n        .remove()\n  }\n}\n\nfunction fdCategoricalPlot(variableName, dData, xMinMax, mData) {\n\n  // equivalent of R table function\n  var tableData = d3.nest()\n                    .key(d => d[variableName])\n                    .rollup(v => v.length)\n                    .entries(dData);\n  // sort tableData\n  var tableDataSorted = [];\n  tableData.forEach(e => {\n    tableDataSorted[xMinMax.indexOf(e.key)] = e;\n  });\n\n  var fdBarCount = tableData.map(d => d.key).length;\n\n  var fdPlotHeight = SCALE_PLOT ? h : fdBarCount*fdBarWidth + (fdBarCount+1)*fdBarWidth/2,\n      fdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + fdPlotWidth])\n            .domain([0, mData]);\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = FD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + fdPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + fdPlotHeight])\n            .padding(0.33)\n            .domain(xMinMax);\n\n  var xGrid = FD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + fdPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-fdPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = FD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-fdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = FD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  FD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(fdSubtitle);\n\n  FD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(fdTitle);\n\n  var bars = FD.selectAll()\n               .data(tableDataSorted)\n               .enter()\n               .append(\"g\");\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"FD-bars\")\n      .attr(\"fill\", fdBarColor)\n      .attr(\"x\", d => x(0))\n      .attr(\"y\", d => y(d.key))\n      .attr(\"height\", y.bandwidth())\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"width\", d => x(d.value)-x(0));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".FD-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  FD.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(0))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(0))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  FD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + fdPlotWidth/2) + \",\" +\n                         (margin.top + fdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"count\");\n}\n\nfunction tvNumericalPlot(variableName, xData, xMinMax, yMinMax) {\n\n  var tvPlotHeight = h,\n      tvPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + tvPlotWidth - 10])\n            .domain(xMinMax);\n\n  TV.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + tvPlotWidth/2) + \" ,\" +\n                         (margin.top + tvPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + tvPlotHeight, margin.top - additionalHeight])\n            .domain(yMinMax);\n\n  TV.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(tvSubtitle);\n\n  TV.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(tvTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + tvPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = TV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-tvPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  TV.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + tvPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"target\");\n\n  TV.selectAll()\n    .data(xData)\n    .enter()\n    .append(\"circle\")\n    .attr(\"class\", \"point\")\n    .attr(\"cx\", d => x(d[variableName]))\n    .attr(\"cy\", d => y(d[\"_target_\"]))\n    .attr(\"r\", 0)\n    .style(\"fill\", tvPointColor)\n    .transition()\n    .duration(TIME)\n    .attr(\"r\", tvPointSize);\n}\n\nfunction tvCategoricalPlot(variableName, xData, xMinMax, yMinMax) {\n\n  var tvPlotHeight = h,\n      tvPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + tvPlotWidth])\n            .domain(yMinMax);\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + tvPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + tvPlotHeight])\n            .padding(0.33)\n            .domain(xMinMax);\n\n  var xGrid = TV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + tvPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-tvPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = TV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-tvPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  TV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(tvSubtitle);\n\n  TV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(tvTitle);\n\n  TV.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + tvPlotWidth/2) + \" ,\" +\n                         (margin.top + tvPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"target\");\n\n  TV.selectAll()\n    .data(xData)\n    .enter()\n    .append(\"circle\")\n    .attr(\"class\", \"point\")\n    .attr(\"cx\", d => x(d[\"_target_\"]))\n    .attr(\"cy\", d => y(d[variableName]) + y.bandwidth()\n    - (0.1 + 0.8*Math.random()) * y.bandwidth())\n    .attr(\"r\", 0)\n    .style(\"fill\", tvPointColor)\n    .transition()\n    .duration(TIME)\n    .attr(\"r\", tvPointSize);\n}\n\nfunction atNumericalPlot(variableName, xData, xMinMax, yMinMax, yMean) {\n\n  var atPlotHeight = h,\n      atPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + atPlotWidth - 10])\n            .domain(xMinMax);\n\n  AT.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + atPlotWidth/2) + \" ,\" +\n                         (margin.top + atPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + atPlotHeight, margin.top - additionalHeight])\n            .domain(yMinMax);\n\n  AT.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(atSubtitle);\n\n  AT.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(atTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + atPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = AT.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-atPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  AT.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + atPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average target\");\n\n  AT.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(x.domain()[0]))\n    .attr(\"y1\", y(yMean))\n    .attr(\"x2\", x(x.domain()[1]))\n    .attr(\"y2\", y(yMean));\n\n  var lines = AT.selectAll()\n                .data(xData)\n                .enter()\n                .append(\"g\");\n\n  lines.append(\"line\")\n       .style(\"stroke\", atLineColor)\n       .style(\"stroke-width\", atLineSize)\n       .attr(\"x1\", d => x(d.x0))\n       .attr(\"x2\", d => x(d.x0))\n       .attr(\"y1\", d => y(d.y0))\n       .attr(\"y2\", d => y(d.y0))\n       .transition()\n       .duration(TIME/2)\n       .delay((d,i) => (i+1) * TIME/2)\n       .attr(\"x2\", d => x(d.x1))\n       .attr(\"y2\", d => y(d.y1))\n\n  lines.append(\"circle\")\n       .attr(\"cx\", d => x(d.x0))\n       .attr(\"cy\", d => y(d.y0))\n       .attr(\"r\", 0)\n       .style(\"fill\", atPointColor)\n       .transition()\n       .duration(TIME/2)\n       .delay((d,i) => i * TIME/2)\n       .attr(\"r\", atPointSize);\n\n  let lastPoint = xData.slice(-1)[0]\n\n  AT.append(\"circle\")\n    .attr(\"cx\", x(lastPoint.x1))\n    .attr(\"cy\", y(lastPoint.y1))\n    .attr(\"r\", 0)\n    .style(\"fill\", atPointColor)\n    .transition()\n    .duration(TIME/2)\n    .delay(xData.length * TIME/2)\n    .attr(\"r\", atPointSize);\n}\n\nfunction atCategoricalPlot(variableName, xData, xMinMax, yMinMax, yMean) {\n\n  var atBarCount = xData.length;\n\n  var atPlotHeight = SCALE_PLOT ? h : atBarCount*atBarWidth + (atBarCount+1)*atBarWidth/2,\n      atPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + atPlotWidth])\n            .domain(yMinMax);\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + atPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + atPlotHeight])\n            .padding(0.33)\n            .domain(xMinMax);\n\n  var xGrid = AT.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + atPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-atPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = AT.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-atPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  AT.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(atSubtitle);\n\n  AT.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(atTitle);\n\n  AT.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + atPlotWidth/2) + \" ,\" +\n                         (margin.top + atPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average target\");\n\n  var bars = AT.selectAll()\n               .data(xData)\n               .enter()\n               .append(\"g\");\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"AT-bars\")\n      .attr(\"fill\", atBarColor)\n      .attr(\"x\", d => x(yMean))\n      .attr(\"y\", d => y(d.y))\n      .attr(\"height\", y.bandwidth())\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => d.sign == 1 ? x(yMean) : x(d.x0))\n      .attr(\"width\", d => Math.abs(x(d.x0) - x(yMean)));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".AT-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  AT.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(yMean))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(yMean))\n    .attr(\"y2\", maximumY + y.bandwidth());\n}\n\n/// event plot functions\n\nfunction updatePlots(event, variableName, observationId, plotId) {\n  /// main plot controller, not used arguments are passed as null\n\n  switch (event) {\n    case \"observationChange\":\n      CLICKED_OBSERVATION_ID = observationId;\n      removePlots([\"BD\", \"SV\", \"CP\"]);\n      generatePlots([\"BD\", \"SV\", \"CP\"]);\n      break;\n\n    case \"variableChange\":\n      // safeguard\n      if (variableName == \"prediction\" || variableName == \"intercept\" ||\n          variableName == \"other\") { return; }\n      CLICKED_VARIABLE_NAME = variableName;\n      removePlots([\"CP\", \"PD\", \"AD\", \"FD\", \"TV\", \"AT\"]);\n      generatePlots([\"CP\", \"PD\", \"AD\", \"FD\", \"TV\", \"AT\"]);\n      break;\n\n    case \"chosePlot\":\n      removePlots([plotId]);\n      generatePlots([plotId]);\n      break;\n\n    default:\n      console.log(\"Unknown event in updatePlots \" +\n                  [event,variableName, observationId, plotId]);\n      break;\n  }\n}\n\nfunction removePlots(arrPlotId) {\n  /// check if there is something to delete and get rid of it (with tooltip)\n  arrPlotId.forEach((id) => {\n    if (!svg.select(\"#\"+id).selectAll(\"*\").empty()) {\n      svg.select(\"#\"+id).selectAll(\"*\").remove();\n      d3.select(\"body\").select(\"#tooltip\"+id).remove();\n    }\n  });\n}\n\nfunction generatePlots(arrPlotId) {\n  /// check if the plot got removed and make new one\n  arrPlotId.forEach((id) => {\n    if (svg.select(\"#\"+id).selectAll(\"*\").empty()) {\n      // execute plot function\n      mapIdPlotFunction[id]();\n    }\n  });\n}\n\n/* R2D3 Source File:   */\n//:\\\\\\ here are functions for tooltips HTML //:\\\\\\\n\nfunction bdTooltipHtml(d) {\n  var temp = \"<center>\";\n  temp += d.tooltipText;\n  temp += \"<\/center>\";\n  return temp;\n}\n\nfunction cpStaticTooltipHtml(d) {\n  // function formats tooltip text\n  var temp = \"\";\n  for (var [k, v] of Object.entries(d)) {\n    if (k === \"yhat\") {\n      k = \"prediction\";\n      temp += \"<center>\" +  k + \": \" + v + \"<\/br>\";\n      temp += \"<\/br>\";\n    } else {\n      temp += \"<center>\" +  k + \": \" + v + \"<\/br>\";\n    }\n  }\n  return temp;\n}\n\nfunction cpChangedTooltipHtml(d, addData) {\n  // function formats tooltip text with update in red\n  var temp = \"<center>\";\n  for (var [k, v] of Object.entries(addData)) {\n    if (k === \"yhat\") {\n      temp += \"prediction:<\/br>\";\n      temp += \"- before\" + \": \" + v + \"<\/br>\";\n      temp += \"- after\" + \": \" + \"<font color = \\\"red\\\">\" + d.yhat + \"<\/br><\/font>\";\n      temp += \"<\/br>\";\n    } else if (k === d.vname) {\n      temp +=  k + \": \" + \"<font color = \\\"red\\\">\"  +  d.xhat + \"<\/br><\/font>\";\n    } else {\n      temp += k + \": \" + v + \"<\/br>\";\n    }\n  }\n  temp += \"<\/center>\";\n  return temp;\n}\n\nfunction fiStaticTooltipHtml(d) {\n    let sign;\n    if (d.dropout_loss > d.full_model) sign = \"+\"; else sign = \"\";\n    var temp =  \"<center>\" + \"model loss after feature \" + d.variable\n      + \"<\/br>\" + \"<center>\" +\n      \" is permuted: \" +  Math.round(d.dropout_loss * 1000)/1000\n      + \"<\/br>\" + \"<center>\" + \"drop-out loss change: \" +\n      sign + Math.round((d.dropout_loss-d.full_model)*1000)/1000;\n    return temp;\n}\n\nfunction pdStaticTooltipHtml(d, variableName, yMean) {\n  // function formats tooltip text\n  var temp = \"\";\n  for (var [k, v] of Object.entries(d)) {\n    switch(k){\n      case \"xhat\":\n        temp += \"<center>\" +  variableName  + \": \" + v + \"<\/br>\";\n        break;\n      case \"yhat\":\n        temp += \"<center>\" +  \"average prediction\"  + \": \" + v + \"<\/br>\";\n        break;\n      case \"vname\":\n        break;\n      default:\n        temp += \"<center>\" +  k  + \": \" + v + \"<\/br>\";\n        break;\n    }\n  }\n\n  temp += \"<\/br><center>\" +\n          \"mean observation prediction:\" +\n          \"<\/br>\" + yMean + \"<\/br>\";\n  return temp;\n}\n\nfunction adStaticTooltipHtml(d, variableName, yMean) {\n  // function formats tooltip text\n  var temp = \"\";\n  for (var [k, v] of Object.entries(d)) {\n    switch(k){\n      case \"xhat\":\n        temp += \"<center>\" +  variableName  + \": \" + v + \"<\/br>\";\n        break;\n      case \"yhat\":\n        temp += \"<center>\" +  \"accumulated prediction\"  + \": \" + v + \"<\/br>\";\n        break;\n      case \"vname\":\n        break;\n      default:\n        temp += \"<center>\" +  k  + \": \" + v + \"<\/br>\";\n        break;\n    }\n  }\n\n  temp += \"<\/br><center>\" +\n          \"mean observation prediction:\" +\n          \"<\/br>\" + yMean + \"<\/br>\";\n  return temp;\n}\n\nfunction descTooltipHtml(d) {\n  var temp = \"<center>\";\n  temp += d.text;\n  temp += \"<\/center>\";\n  return temp;\n}\nsvg = d3.select(svg.node());\n/* R2D3 Source File:   */\n///:\\\\\\ --------- main modelStudio file --------- ///:\\\\\\\n///:\\\\\\ (for myself to remember):                 ///:\\\\\\\n///:\\\\\\ use CAPITAL for global variables and 'g'  ///:\\\\\\\n///:\\\\\\ use let where possible                    ///:\\\\\\\n///:\\\\\\ use class for css and id for select       ///:\\\\\\\n///:\\\\\\ use lambdas and ifelse where possible     ///:\\\\\\\n///:\\\\\\ ----------------------------------------- ///:\\\\\\\n\n/// prevent modelStudio from reloading onResize\nr2d3.onResize(function() {\n  return;\n});\n\n/// load all data\nvar obsData = data[0],\n    fiData = data[1], pdData = data[2],\n    adData = data[3], fdData = data[4],\n    tvData = data[4], atData = data[5];\n\n/// load options\nvar TIME = options.time,\n    modelName = options.model_name,\n    variableNames = options.variable_names,\n    dim = options.facet_dim,\n    footerText = options.footer_text,\n    dropDownData = options.drop_down_data,\n    EDA = options.eda,\n    WIDGET_ID = options.widget_id,\n    SCALE_PLOT = options.scale_plot,\n    SHOW_BOXPLOT = options.show_boxplot,\n    SHOW_SUBTITLE = options.show_subtitle,\n    subTitle = options.subtitle || modelName,\n    msTitle = options.ms_title,\n    barWidth = options.bar_width,\n    lineSize = options.line_size,\n    pointSize = options.point_size,\n    barColor = options.bar_color,\n    lineColor = options.line_color,\n    pointColor = options.point_color,\n    positiveColor = options.positive_color,\n    negativeColor = options.negative_color,\n    defaultColor = options.default_color,\n    bdTitle = options.bd_title,\n    bdSubtitle = options.bd_subtitle || subTitle,\n    bdBarWidth = options.bd_bar_width || barWidth,\n    bdPositiveColor = options.bd_positive_color || positiveColor,\n    bdNegativeColor = options.bd_negative_color || negativeColor,\n    bdDefaultColor = options.bd_default_color || defaultColor,\n    svTitle = options.sv_title,\n    svSubtitle = options.sv_subtitle || subTitle,\n    svBarWidth = options.sv_bar_width || barWidth,\n    svPositiveColor = options.sv_positive_color || positiveColor,\n    svNegativeColor = options.sv_negative_color || negativeColor,\n    cpTitle = options.cp_title,\n    cpSubtitle = options.cp_subtitle || subTitle,\n    cpBarWidth = options.cp_bar_width || barWidth,\n    cpLineSize = options.cp_line_size || lineSize,\n    cpPointSize = options.cp_point_size || pointSize,\n    cpBarColor = options.cp_bar_color || barColor,\n    cpLineColor = options.cp_line_color || lineColor,\n    cpPointColor = options.cp_point_color || pointColor,\n    fiTitle = options.fi_title,\n    fiSubtitle = options.fi_subtitle || subTitle,\n    fiBarWidth = options.fi_bar_width || barWidth,\n    fiBarColor = options.fi_bar_color || barColor,\n    pdTitle = options.pd_title,\n    pdSubtitle = options.pd_subtitle || subTitle,\n    pdBarWidth = options.pd_bar_width || barWidth,\n    pdLineSize = options.pd_line_size || lineSize,\n    pdBarColor = options.pd_bar_color || barColor,\n    pdLineColor = options.pd_line_color || lineColor,\n    adTitle = options.ad_title,\n    adSubtitle = options.ad_subtitle || subTitle,\n    adBarWidth = options.ad_bar_width || barWidth,\n    adLineSize = options.ad_line_size || lineSize,\n    adBarColor = options.ad_bar_color || barColor,\n    adLineColor = options.ad_line_color || lineColor,\n    fdTitle = options.fd_title,\n    fdSubtitle = options.fd_subtitle || subTitle,\n    fdBarWidth = options.fd_bar_width || barWidth,\n    fdBarColor = options.fd_bar_color || barColor,\n    tvTitle = options.tv_title,\n    tvSubtitle = options.tv_subtitle || subTitle,\n    tvPointSize = options.tv_point_size || pointSize,\n    tvPointColor = options.tv_point_color || pointColor,\n    atTitle = options.at_title,\n    atSubtitle = options.at_subtitle || subTitle,\n    atBarWidth = options.at_bar_width || barWidth,\n    atLineSize = options.at_line_size || lineSize,\n    atPointSize = options.at_point_size || pointSize,\n    atBarColor = options.at_bar_color || barColor,\n    atLineColor = options.at_line_color || lineColor,\n    atPointColor = options.at_point_color || pointColor;\n\n/// for observation choice\nvar observationIds = Object.keys(obsData);\n\n/// set global variables\nvar CLICKED_VARIABLE_NAME = variableNames[0],\n    CLICKED_OBSERVATION_ID = observationIds[0],\n    IS_BUTTON_CLICKED = false;\n\n/// set dimensions\nvar margin = {top: options.margin_top, right: options.margin_right,\n              bottom: options.margin_bottom, left: options.margin_left,\n              inner: options.margin_inner,\n              small: options.margin_small, big: options.margin_big,\n              ytitle: options.margin_ytitle};\n\nvar w = options.w, h = options.h;\n\nvar plotWidth = w + margin.left + margin.right,\n    plotHeight = h + margin.top + margin.bottom;\n\nvar studioMargin = {top: 50, bottom: 50},\n    studioWidth = dim[1]*plotWidth,\n    studioHeight = studioMargin.top + dim[0]*plotHeight + studioMargin.bottom;\n\n/// should subtitle be displayed and plot height be extended\nvar additionalHeight = 0;\nif (!SHOW_SUBTITLE) {\n  additionalHeight = 25;\n  bdSubtitle = null;\n  svSubtitle = null;\n  cpSubtitle = null;\n  fiSubtitle = null;\n  pdSubtitle = null;\n  adSubtitle = null;\n  fdSubtitle = null;\n  tvSubtitle = null;\n  atSubtitle = null;\n}\n\n/// for plot chosing\nvar notVisiblePlots = EDA ?\n                       [{id:\"BD\", text: bdTitle + \" [Local]\"},\n                       {id:\"SV\", text: svTitle + \" [Local]\"},\n                       {id:\"CP\", text: cpTitle + \" [Local]\"},\n                       {id:\"FI\", text: fiTitle + \" [Global]\"},\n                       {id:\"PD\", text: pdTitle + \" [Global]\"},\n                       {id:\"AD\", text: adTitle + \" [Global]\"},\n                       {id:\"FD\", text: fdTitle + \" [EDA]\"},\n                       {id:\"TV\", text: tvTitle + \" [EDA]\"},\n                       {id:\"AT\", text: atTitle + \" [EDA]\"}] :\n                       [{id:\"BD\", text: bdTitle + \" [Local]\"},\n                       {id:\"SV\", text: svTitle + \" [Local]\"},\n                       {id:\"CP\", text: cpTitle + \" [Local]\"},\n                       {id:\"FI\", text: fiTitle + \" [Global]\"},\n                       {id:\"PD\", text: pdTitle + \" [Global]\"},\n                       {id:\"AD\", text: adTitle + \" [Global]\"}];\n\nvar visiblePlots = [];\n\n/// generate facet x,y coordinates with grid index\nvar facetData = [], id = 0;\nfor (let i = 0; i < dim[0]; i++) {\n  for (let j = 0; j < dim[1]; j++) {\n    facetData.push({x: 0 + j*plotWidth,\n                    y: studioMargin.top + i*plotHeight,\n                    index: id});\n    id++;\n  }\n}\n\n///:\\\\\\\ninitializeStudio();\n///:\\\\\\\n\nfunction initializeStudio() {\n  /// this function initializes modelStudio (used only once, at start)\n\n  // top decorations\n  var TOP_G = svg.append(\"g\")\n                 .attr(\"class\", \"TOP_G\");\n\n  TOP_G.append(\"text\")\n       .attr(\"class\", \"mainTitle\")\n       .attr(\"x\", 15)\n       .attr(\"y\", 30)\n       .text(msTitle);\n\n  TOP_G.append(\"line\")\n       .attr(\"class\", \"mainLine\")\n       .attr(\"x1\", 10)\n       .attr(\"x2\", studioWidth - 10)\n       .attr(\"y1\", studioMargin.top - margin.big)\n       .attr(\"y2\", studioMargin.top - margin.big);\n\n  ///:\\\\\\ add select observation input\n  let tempW = calculateTextWidth(dropDownData.map(e => e.text))*1.6 + 18; // 15px bold 600\n\n  // center the ms\n  d3.select(\"#\" + WIDGET_ID)\n    .style('position', 'absolute')\n    .style('left', 0)\n    .style('right', 0)\n    .style('margin', 'auto');\n\n  var input = d3.select(\"#\" + WIDGET_ID)\n                .append(\"select\")\n                .attr(\"id\",\"input\")\n                .style(\"position\", \"absolute\") // to make input appear on top\n                .style(\"left\", (studioWidth - margin.big - tempW)+\"px\")\n                .style(\"top\", -studioHeight + 180)\n                .style(\"font-size\", \"15px\")\n                .style(\"font-weight\", 600)\n                .style(\"color\", \"#371ea3\");\n\n  input.selectAll()\n       .data(dropDownData)\n       .enter()\n       .append(\"option\")\n       .attr(\"value\", d => d.id)\n       .text(d => d.text)\n       .style(\"font-size\", \"15px\")\n       .style(\"font-weight\", 600)\n       .style(\"color\", \"#371ea3\");\n\n  input.on(\"change\", function() {\n\n    // update observation specific plots\n    updatePlots(event = \"observationChange\",\n                variableName = null,\n                observationId = this.value,\n                plotId = null);\n  });\n  ///:\\\\\\\n\n  // bottom decorations\n  var BOTTOM_G = svg.append(\"g\")\n                    .attr(\"class\", \"BOTTOM_G\");\n\n  BOTTOM_G.append(\"text\")\n          .attr(\"class\", \"footerTitle\")\n          .attr(\"x\", studioWidth - 15 - getTextWidth(footerText, 12, 'Fira Sans, sans-serif'))\n          .attr(\"y\", studioHeight - studioMargin.bottom + 25)\n          .text(footerText);\n\n  BOTTOM_G.append(\"line\")\n          .attr(\"class\", \"footerLine\")\n          .attr(\"x1\", 10)\n          .attr(\"x2\", studioWidth - 10)\n          .attr(\"y1\", studioHeight - studioMargin.bottom + margin.big)\n          .attr(\"y2\", studioHeight - studioMargin.bottom + margin.big);\n\n  // middle buttons\n  var MIDDLE_G = svg.append(\"g\")\n                    .attr(\"class\", \"MIDDLE_G\");\n\n  var enterChoiceButtons = MIDDLE_G.selectAll()\n                                   .data(facetData)\n                                   .enter()\n                                   .append(\"rect\")\n                                   .attr(\"class\", \"enterChoiceButton\")\n                                   .attr(\"id\", (d,i) => \"enterChoiceButton\"+i)\n                                   .attr(\"width\", plotWidth)\n                                   .attr(\"height\", plotHeight)\n                                   .attr(\"x\", d => d.x)\n                                   .attr(\"y\", d => d.y);\n\n  // add `+` to buttons\n  MIDDLE_G.selectAll()\n          .data(facetData)\n          .enter()\n          .append(\"line\")\n          .attr(\"class\", \"mainLine\")\n          .attr(\"id\", (d,i) => \"enterChoiceButton\"+i)\n          .attr(\"x1\", d => d.x + plotWidth/2)\n          .attr(\"x2\", d => d.x + plotWidth/2)\n          .attr(\"y1\", d => d.y + plotHeight/2 - margin.big)\n          .attr(\"y2\", d => d.y + plotHeight/2 + margin.big);\n\n  MIDDLE_G.selectAll()\n          .data(facetData)\n          .enter()\n          .append(\"line\")\n          .attr(\"class\", \"mainLine\")\n          .attr(\"id\", (d,i) => \"enterChoiceButton\"+i)\n          .attr(\"x1\", d => d.x + plotWidth/2 - margin.big)\n          .attr(\"x2\", d => d.x + plotWidth/2 + margin.big)\n          .attr(\"y1\", d => d.y + plotHeight/2)\n          .attr(\"y2\", d => d.y + plotHeight/2);\n\n  // events\n  enterChoiceButtons.on('mouseover', function() { d3.select(this).style(\"opacity\", 1);})\n                    .on('mouseout', function() { d3.select(this).style(\"opacity\", 0.5);})\n                    .on(\"click\", function(d,i) {\n\n                      // block other buttons\n                      if (!IS_BUTTON_CLICKED) {\n                        IS_BUTTON_CLICKED = true;\n                        // allow for plot choice or exit choice\n                        showChoiceButtons(this, i);\n                      }\n                    });\n\n  var exitChoiceButtons = MIDDLE_G.selectAll()\n                                  .data(facetData)\n                                  .enter()\n                                  .append(\"rect\")\n                                  .attr(\"class\", \"exitChoiceButton\")\n                                  .attr(\"id\", (d,i) => \"exitChoiceButton\"+i)\n                                  .attr(\"width\", plotWidth - margin.big)\n                                  .attr(\"height\", plotHeight - margin.big)\n                                  .attr(\"x\", d => d.x + margin.small)\n                                  .attr(\"y\", d => d.y + margin.small)\n                                  .style(\"visibility\", \"hidden\");\n\n  // events\n  exitChoiceButtons.on(\"click\", function(d,i) {\n\n                     // delete chosePlotButtons\n                     svg.select(\"#chosePlotButton\"+i).remove();\n                     // hide this button\n                     svg.select(\"#exitChoiceButton\"+i).style(\"visibility\", \"hidden\");\n                     // show enterChoiceButton\n                     svg.selectAll(\"#enterChoiceButton\"+i).style(\"visibility\", \"visible\");\n                     // let the user click other buttons\n                     IS_BUTTON_CLICKED = false;\n                   });\n\n  var exitPlotButtons = MIDDLE_G.selectAll()\n                                .data(facetData)\n                                .enter()\n                                .append(\"g\")\n                                .attr(\"id\", (d,i) => \"exitPlotButton\"+i)\n                                .attr(\"transform\", d => \"translate(\" +\n                                (d.x + margin.left + w - 2*margin.big) + \",\" +\n                                (d.y + margin.small) + \")\")\n                                .style(\"visibility\", \"hidden\");\n\n  exitPlotButtons.append(\"rect\")\n                 .attr(\"class\", \"descriptionBox\")\n                 .attr(\"width\", 2*margin.big)\n                 .attr(\"height\", 2*margin.big)\n                 .attr(\"rx\", 2*margin.big)\n                 .attr(\"ry\", 2*margin.big);\n\n  exitPlotButtons.append(\"text\")\n                 .attr(\"class\", \"descriptionLabel\")\n                 .attr(\"dy\", \"1.05em\")\n                 .attr(\"x\", 6)\n                 .text(\"X\");\n\n  // events\n  exitPlotButtons.selectAll(\"*\")\n                 .on(\"mouseover\", function() { d3.select(this).style(\"cursor\", \"pointer\");})\n                 .on(\"mouseout\", function() { d3.select(this).style(\"cursor\", \"auto\");})\n                 .on(\"click\", function(d) {\n\n                   let j = d.index;\n                   // available only when no enterPlotButton clicked\n                   if (!IS_BUTTON_CLICKED) {\n                     // which plot is in this place?\n                     let temp = visiblePlots.filter(el => el.index == j)[0];\n                     // add this plot to not visible\n                     notVisiblePlots.push({text: temp.text, id: temp.id});\n                     // delete this plot from visible\n                     visiblePlots = visiblePlots.filter(el => el.id !== temp.id);\n                     // hide this button\n                     svg.select(\"#exitPlotButton\"+j).style(\"visibility\", \"hidden\");\n                     // hide plot\n                     svg.select(\"#\"+temp.id)\n                        .style(\"visibility\", \"hidden\");\n                     // show enterChoiceButton\n                     svg.selectAll(\"#enterChoiceButton\"+j).style(\"visibility\", \"visible\");\n                   }\n                 });\n\n  function showChoiceButtons(object, j) {\n    /// chosePlotButtons controller\n\n    // hide this button\n    svg.selectAll(\"#enterChoiceButton\"+j).style(\"visibility\", \"hidden\");\n    // show exitChoiceButton\n    svg.select(\"#exitChoiceButton\"+j).style(\"visibility\", \"visible\");\n\n    // where to place text?\n    let plotWidth = parseFloat(d3.select(object).attr(\"width\")),\n        plotHeight = parseFloat(d3.select(object).attr(\"height\")),\n        x = parseFloat(d3.select(object).attr(\"x\")),\n        y = parseFloat(d3.select(object).attr(\"y\"));\n\n    let chosePlotButtons = MIDDLE_G.append(\"g\")\n                                   .attr(\"id\",\"chosePlotButton\"+j);\n\n    chosePlotButtons.selectAll()\n             .data(notVisiblePlots)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"bigTitle\")\n             .attr(\"id\", d => d.id)\n             .attr(\"x\", x + plotWidth/2)\n             .attr(\"y\", (d,i) => y + plotHeight/2 + 25*i - (notVisiblePlots.length/2)*25)\n             .attr(\"text-anchor\", \"middle\")\n             .text(d => d.text)\n             .on(\"mouseover\", function() { d3.select(this).style(\"cursor\", \"pointer\");})\n             .on(\"mouseout\", function() { d3.select(this).style(\"cursor\", \"auto\");})\n             .on(\"click\", function(d) {\n\n               // when clicking on text, hide exitChoiceButton\n               svg.selectAll(\"#exitChoiceButton\"+j).style(\"visibility\", \"hidden\");\n               // delete chosePlotButtons\n               svg.select(\"#chosePlotButton\"+j).remove();\n               // add this plot to visible\n               visiblePlots.push({text: d.text, id: this.id, index: j });\n               // delete this plot from not visible\n               notVisiblePlots = notVisiblePlots.filter(el => el.id !== this.id);\n\n               updatePlots(event = \"chosePlot\",\n                           variableName = null,\n                           observationId = null,\n                           plotId = this.id);\n\n               // 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+<script type="application/json" data-for="widget-885d187ac1050eef43a1e9da6779043f">{"x":{"data":[{"98":[{"x":[{"variable":"intercept","contribution":0,"variable_name":"intercept","variable_value":"1","cumulative":0.314,"sign":"X","position":9,"label":"scikit-learn","barStart":0.3144,"barSupport":0.3144,"tooltipText":"Average response: 0.314<br>Prediction: 1"},{"variable":"gender = female","contribution":0.433,"variable_name":"gender","variable_value":"female","cumulative":0.748,"sign":"1","position":8,"label":"scikit-learn","barStart":0.3144,"barSupport":0.7477,"tooltipText":"gender = female<br>increases average response <br>by 0.433"},{"variable":"class = 1st","contribution":0.233,"variable_name":"class","variable_value":"1st","cumulative":0.981,"sign":"1","position":7,"label":"scikit-learn","barStart":0.7477,"barSupport":0.9812,"tooltipText":"class = 1st<br>increases average response <br>by 0.233"},{"variable":"age = 50","contribution":-0.033,"variable_name":"age","variable_value":"50","cumulative":0.949,"sign":"-1","position":6,"label":"scikit-learn","barStart":0.9486,"barSupport":0.9812,"tooltipText":"age = 50<br>decreases average response <br>by 0.033"},{"variable":"embarked = Cherbourg","contribution":0.05,"variable_name":"embarked","variable_value":"Cherbourg","cumulative":0.999,"sign":"1","position":5,"label":"scikit-learn","barStart":0.9486,"barSupport":0.999,"tooltipText":"embarked = Cherbourg<br>increases average response <br>by 0.05"},{"variable":"parch = 1","contribution":0.001,"variable_name":"parch","variable_value":"1","cumulative":1,"sign":"1","position":4,"label":"scikit-learn","barStart":0.999,"barSupport":0.9999,"tooltipText":"parch = 1<br>increases average response <br>by 0.001"},{"variable":"fare = 247.1","contribution":0,"variable_name":"fare","variable_value":"247.1","cumulative":1,"sign":"1","position":3,"label":"scikit-learn","barStart":0.9999,"barSupport":1,"tooltipText":"fare = 247.1<br>decreases average response <br>by 0"},{"variable":"sibsp = 0","contribution":0,"variable_name":"sibsp","variable_value":"0","cumulative":1,"sign":"1","position":2,"label":"scikit-learn","barStart":1,"barSupport":1,"tooltipText":"sibsp = 0<br>decreases average response <br>by 0"},{"variable":"prediction","contribution":0.686,"variable_name":"prediction","variable_value":"","cumulative":1,"sign":"X","position":1,"label":"scikit-learn","barStart":0.3144,"barSupport":1,"tooltipText":"Average response: 0.314<br>Prediction: 1"}],"m":[9],"x_min_max":[0.1768,1.1372],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 1 which is higher than the average model prediction 0.314.<\/br><\/br>The most important variable is gender (= female). It increases the prediction by 0.433.<\/br>The second most important variable is class (= 1st). It increases the prediction by 0.233.<\/br>The third most important variable is embarked (= Cherbourg). It increases the prediction by 0.05.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is 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predicts that for the selected instance (gender = female), prediction is equal to 1<\/br><\/br>The most important change in Scikit-learn's prediction would occur for gender = \"male\". It decreases the prediction by 0.543. <\/br> <\/br><\/br><\/br>All variables are being displayed."}],"age":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (age = 50), prediction is equal to 1<\/br><\/br>The highest prediction occurs for (age = 48), while the lowest for (age = 72).<\/br>Breakpoints are identified at (age = 1.28 and age = 17).<\/br><\/br>Average model responses are *lower* for variable values *lower* than breakpoint(= 17)."}],"class":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (class = 1st), prediction is equal to 1<\/br><\/br>The most important change in Scikit-learn's prediction would occur for class = \"2nd\". It decreases the prediction by 0. <\/br>The second most important change in the prediction would occur for class = \"3rd\". It decreases the prediction by 0. <\/br>The third most important change in the prediction would occur for class = \"deck crew\". It increases the prediction by 0.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0."}],"embarked":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (embarked = Cherbourg), prediction is equal to 1<\/br><\/br>The most important change in Scikit-learn's prediction would occur for embarked = \"Queenstown\". It decreases the prediction by 0.943. <\/br>The second most important change in the prediction would occur for embarked = \"Belfast\". It decreases the prediction by 0.002. <\/br>The third most important change in the prediction would occur for embarked = \"Southampton\". It decreases the prediction by 0.001.<\/br><\/br>All variables are being displayed."}],"fare":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (fare = 247.101), prediction is equal to 1<\/br><\/br>The highest prediction occurs for (fare = 263), while the lowest for (fare = 15.0008).<\/br>Breakpoint is identified at (fare = 35.184).<\/br><\/br>Average model responses are *lower* for variable values *lower* than breakpoint(= 35.184)."}],"sibsp":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (sibsp = 0), prediction is equal to 1<\/br><\/br>The highest prediction occurs for (sibsp = 8), while the lowest for (sibsp = 2).<\/br>Breakpoints are identified at (sibsp = 1 and sibsp = 0).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 0)."}],"parch":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (parch = 1), prediction is equal to 1<\/br><\/br>The highest prediction occurs for (parch = 1), while the lowest for (parch = 6).<\/br>Breakpoints are identified at (parch = 0 and parch = 0).<\/br><\/br>Average model responses are *higher* for variable values *lower* than breakpoint (= 0)."}]}},{"x":[{"variable_name":"gender","variable":"gender = female","contribution":0.466,"variable_value":"female","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.7808,"tooltipText":"gender = female<br>increases average response <br>by 0.466","min":0.5153,"q1":0.7305,"q3":0.8739,"max":0.9773},{"variable_name":"fare","variable":"fare = 247.1","contribution":0.146,"variable_value":"247.1","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.4605,"tooltipText":"fare = 247.1<br>increases average response <br>by 0.146","min":0.2856,"q1":0.3642,"q3":0.5594,"max":0.6641},{"variable_name":"embarked","variable":"embarked = Cherbourg","contribution":0.093,"variable_value":"Cherbourg","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.407,"tooltipText":"embarked = Cherbourg<br>increases average response <br>by 0.093","min":0.2978,"q1":0.3673,"q3":0.4136,"max":0.483},{"variable_name":"class","variable":"class = 1st","contribution":0.063,"variable_value":"1st","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.3777,"tooltipText":"class = 1st<br>increases average response <br>by 0.063","min":0.2819,"q1":0.3144,"q3":0.3782,"max":0.474},{"variable_name":"age","variable":"age = 50","contribution":-0.051,"variable_value":"50","sign":"-1","label":"scikit-learn","barStart":0.263,"barSupport":0.3144,"tooltipText":"age = 50<br>decreases average response <br>by 0.051","min":0.1491,"q1":0.2044,"q3":0.3145,"max":0.4797},{"variable_name":"parch","variable":"parch = 1","contribution":-0.044,"variable_value":"1","sign":"-1","label":"scikit-learn","barStart":0.2701,"barSupport":0.3144,"tooltipText":"parch = 1<br>decreases average response <br>by 0.044","min":0.1552,"q1":0.2529,"q3":0.3181,"max":0.4159},{"variable_name":"sibsp","variable":"sibsp = 0","contribution":0.013,"variable_value":"0","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.327,"tooltipText":"sibsp = 0<br>increases average response <br>by 0.013","min":0.2852,"q1":0.3111,"q3":0.3421,"max":0.3746}],"m":[7],"x_min_max":[0.104,0.9743],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 1 which is higher than the average model prediction 0.314.For the selected instance model's prediction is higher, than for 100% of all observations.<\/br><\/br>The most important variable is gender (= female). It increases the prediction by 0.466.<\/br>The second most important variable is fare (= 247.1). It increases the prediction by 0.146.<\/br>The third most important variable is embarked (= Cherbourg). It increases the prediction by 0.093.<\/br>The average contribution of all the above variables is significant.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is -0.02."}]}],"2028":[{"x":[{"variable":"intercept","contribution":0,"variable_name":"intercept","variable_value":"1","cumulative":0.314,"sign":"X","position":9,"label":"scikit-learn","barStart":0.3144,"barSupport":0.3144,"tooltipText":"Average response: 0.314<br>Prediction: 0.148"},{"variable":"age = 55","contribution":-0.131,"variable_name":"age","variable_value":"55","cumulative":0.184,"sign":"-1","position":8,"label":"scikit-learn","barStart":0.1836,"barSupport":0.3144,"tooltipText":"age = 55<br>decreases average response <br>by 0.131"},{"variable":"gender = male","contribution":-0.109,"variable_name":"gender","variable_value":"male","cumulative":0.074,"sign":"-1","position":7,"label":"scikit-learn","barStart":0.0742,"barSupport":0.1836,"tooltipText":"gender = male<br>decreases average response <br>by 0.109"},{"variable":"class = victualling crew","contribution":0.04,"variable_name":"class","variable_value":"victualling crew","cumulative":0.115,"sign":"1","position":6,"label":"scikit-learn","barStart":0.0742,"barSupport":0.1146,"tooltipText":"class = victualling crew<br>increases average response <br>by 0.04"},{"variable":"fare = 0","contribution":0.004,"variable_name":"fare","variable_value":"0","cumulative":0.118,"sign":"1","position":5,"label":"scikit-learn","barStart":0.1146,"barSupport":0.1185,"tooltipText":"fare = 0<br>increases average response <br>by 0.004"},{"variable":"sibsp = 0","contribution":-0.008,"variable_name":"sibsp","variable_value":"0","cumulative":0.111,"sign":"-1","position":4,"label":"scikit-learn","barStart":0.111,"barSupport":0.1185,"tooltipText":"sibsp = 0<br>decreases average response <br>by 0.008"},{"variable":"parch = 0","contribution":0.015,"variable_name":"parch","variable_value":"0","cumulative":0.126,"sign":"1","position":3,"label":"scikit-learn","barStart":0.111,"barSupport":0.1257,"tooltipText":"parch = 0<br>increases average response <br>by 0.015"},{"variable":"embarked = Southampton","contribution":0.022,"variable_name":"embarked","variable_value":"Southampton","cumulative":0.148,"sign":"1","position":2,"label":"scikit-learn","barStart":0.1257,"barSupport":0.148,"tooltipText":"embarked = Southampton<br>increases average response <br>by 0.022"},{"variable":"prediction","contribution":-0.166,"variable_name":"prediction","variable_value":"","cumulative":0.148,"sign":"X","position":1,"label":"scikit-learn","barStart":0.148,"barSupport":0.3144,"tooltipText":"Average response: 0.314<br>Prediction: 0.148"}],"m":[9],"x_min_max":[0.026,0.362],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 0.148 which is lower than the average model prediction 0.314.<\/br><\/br>The most important variable is age (= 55). It decreases the prediction by 0.131.<\/br>The second most important variable is gender (= male). It decreases the prediction by 0.109.<\/br>The third most important variable is class (= victualling crew). It increases the prediction by 0.04.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is 0.033."}]},{"observation":[{"observation.id":"2028","model":"scikit-learn","yhat":[0.148],"gender":"male","age":55,"class":"victualling 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crew","yhat":0.148,"vname":"class"}],"embarked":[{"xhat":"Belfast","yhat":0.2086,"vname":"embarked"},{"xhat":"Cherbourg","yhat":0.0091,"vname":"embarked"},{"xhat":"Queenstown","yhat":0.0003,"vname":"embarked"},{"xhat":"Southampton","yhat":0.148,"vname":"embarked"}],"fare":[{"xhat":0,"yhat":0.148,"id":"2028","vname":"fare"},{"xhat":5.9576,"yhat":0.1279,"id":"2028","vname":"fare"},{"xhat":6.3523,"yhat":0.1265,"id":"2028","vname":"fare"},{"xhat":7.0406,"yhat":0.124,"id":"2028","vname":"fare"},{"xhat":7.0407,"yhat":0.124,"id":"2028","vname":"fare"},{"xhat":7.0411,"yhat":0.124,"id":"2028","vname":"fare"},{"xhat":7.1139,"yhat":0.1237,"id":"2028","vname":"fare"},{"xhat":7.15,"yhat":0.1236,"id":"2028","vname":"fare"},{"xhat":7.1506,"yhat":0.1236,"id":"2028","vname":"fare"},{"xhat":7.1701,"yhat":0.1235,"id":"2028","vname":"fare"},{"xhat":7.1707,"yhat":0.1235,"id":"2028","vname":"fare"},{"xhat":7.1711,"yhat":0.1235,"id":"2028","vname":"fare"},{"xhat":7.1806,"yhat":0.1235,"id":"2028","vname":"fare"},{"xhat":8.01,"yhat":0.1207,"id":"2028","vname":"fare"},{"xhat":8.1303,"yhat":0.1203,"id":"2028","vname":"fare"},{"xhat":9,"yhat":0.1177,"id":"2028","vname":"fare"},{"xhat":9.1,"yhat":0.1174,"id":"2028","vname":"fare"},{"xhat":10.0783,"yhat":0.1146,"id":"2028","vname":"fare"},{"xhat":10.1,"yhat":0.1145,"id":"2028","vname":"fare"},{"xhat":11.0208,"yhat":0.1126,"id":"2028","vname":"fare"},{"xhat":12.1418,"yhat":0.1119,"id":"2028","vname":"fare"},{"xhat":13,"yhat":0.1114,"id":"2028","vname":"fare"},{"xhat":13.1,"yhat":0.1114,"id":"2028","vname":"fare"},{"xhat":14.0877,"yhat":0.1108,"id":"2028","vname":"fare"},{"xhat":15.0008,"yhat":0.1102,"id":"2028","vname":"fare"},{"xhat":15.1,"yhat":0.1102,"id":"2028","vname":"fare"},{"xhat":16.02,"yhat":0.1096,"id":"2028","vname":"fare"},{"xhat":18,"yhat":0.1095,"id":"2028","vname":"fare"},{"xhat":20.202,"yhat":0.1091,"id":"2028","vname":"fare"},{"xhat":21.4459,"yhat":0.1086,"id":"2028","vname":"fare"},{"xhat":23,"yhat":0.108,"id":"2028","vname":"fare"},{"xhat":24.03,"yhat":0.1077,"id":"2028","vname":"fare"},{"xhat":25.4101,"yhat":0.1073,"id":"2028","vname":"fare"},{"xhat":26,"yhat":0.107,"id":"2028","vname":"fare"},{"xhat":26.0509,"yhat":0.1069,"id":"2028","vname":"fare"},{"xhat":26.11,"yhat":0.1069,"id":"2028","vname":"fare"},{"xhat":27.0551,"yhat":0.1064,"id":"2028","vname":"fare"},{"xhat":27.15,"yhat":0.1064,"id":"2028","vname":"fare"},{"xhat":29.0493,"yhat":0.105,"id":"2028","vname":"fare"},{"xhat":31.0263,"yhat":0.1031,"id":"2028","vname":"fare"},{"xhat":31.1,"yhat":0.103,"id":"2028","vname":"fare"},{"xhat":35.184,"yhat":0.0993,"id":"2028","vname":"fare"},{"xhat":39.8367,"yhat":0.095,"id":"2028","vname":"fare"},{"xhat":49.1001,"yhat":0.0892,"id":"2028","vname":"fare"},{"xhat":52,"yhat":0.0901,"id":"2028","vname":"fare"},{"xhat":55.283,"yhat":0.0969,"id":"2028","vname":"fare"},{"xhat":60.5139,"yhat":0.1121,"id":"2028","vname":"fare"},{"xhat":69.11,"yhat":0.1306,"id":"2028","vname":"fare"},{"xhat":76.1407,"yhat":0.1355,"id":"2028","vname":"fare"},{"xhat":79.3472,"yhat":0.1367,"id":"2028","vname":"fare"},{"xhat":83.0664,"yhat":0.1396,"id":"2028","vname":"fare"},{"xhat":92.728,"yhat":0.1509,"id":"2028","vname":"fare"},{"xhat":122.256,"yhat":0.2098,"id":"2028","vname":"fare"},{"xhat":152.0093,"yhat":0.2909,"id":"2028","vname":"fare"},{"xhat":218.3365,"yhat":0.2975,"id":"2028","vname":"fare"},{"xhat":263,"yhat":0.3867,"id":"2028","vname":"fare"}],"sibsp":[{"xhat":0,"yhat":0.148,"id":"2028","vname":"sibsp"},{"xhat":1,"yhat":0.096,"id":"2028","vname":"sibsp"},{"xhat":2,"yhat":0.4131,"id":"2028","vname":"sibsp"},{"xhat":3,"yhat":0.5754,"id":"2028","vname":"sibsp"},{"xhat":4,"yhat":0.7449,"id":"2028","vname":"sibsp"},{"xhat":8,"yhat":0.9852,"id":"2028","vname":"sibsp"}],"parch":[{"xhat":0,"yhat":0.148,"id":"2028","vname":"parch"},{"xhat":1,"yhat":0.0124,"id":"2028","vname":"parch"},{"xhat":2,"yhat":0.0003,"id":"2028","vname":"parch"},{"xhat":6,"yhat":5.3495e-008,"id":"2028","vname":"parch"}]},"y_min_max":[-0.0999,1.0988],"x_min_max_list":{"age":[[0.5833],[72]],"fare":[[0],[263]],"sibsp":[[0],[8]],"parch":[[0],[6]]},"is_numeric":{"gender":[false],"age":[true],"class":[false],"embarked":[false],"fare":[true],"sibsp":[true],"parch":[true]},"desc":{"gender":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (gender = male), prediction is equal to 0.148<\/br><\/br>The most important change in Scikit-learn's prediction would occur for gender = \"female\". It increases the prediction by 0.851. <\/br> <\/br><\/br><\/br>All variables are being displayed."}],"age":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (age = 55), prediction is equal to 0.148<\/br><\/br>The highest prediction occurs for (age = 0.5833333333), while the lowest for (age = 72).<\/br>Breakpoint is identified at (age = 1.28).<\/br><\/br>Average model responses are *higher* for variable values *lower* than breakpoint (= 1.28)."}],"class":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (class = victualling crew), prediction is equal to 0.148<\/br><\/br>The most important change in Scikit-learn's prediction would occur for class = \"deck crew\". It increases the prediction by 0.543. <\/br>The second most important change in the prediction would occur for class = \"1st\". It increases the prediction by 0.516. <\/br>The third most important change in the prediction would occur for class = \"3rd\". It decreases the prediction by 0.148.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.148."}],"embarked":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (embarked = Southampton), prediction is equal to 0.148<\/br><\/br>The most important change in Scikit-learn's prediction would occur for embarked = \"Queenstown\". It decreases the prediction by 0.148. <\/br>The second most important change in the prediction would occur for embarked = \"Cherbourg\". It decreases the prediction by 0.139. <\/br>The third most important change in the prediction would occur for embarked = \"Belfast\". It increases the prediction by 0.061.<\/br><\/br>All variables are being displayed."}],"fare":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (fare = 0), prediction is equal to 0.148<\/br><\/br>The highest prediction occurs for (fare = 263), while the lowest for (fare = 49.1001).<\/br>Breakpoint is identified at (fare = 122.256).<\/br><\/br>Average model responses are *higher* for variable values *higher* than breakpoint (= 122.256)."}],"sibsp":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (sibsp = 0), prediction is equal to 0.148<\/br><\/br>The highest prediction occurs for (sibsp = 8), while the lowest for (sibsp = 1).<\/br>Breakpoint is identified at (sibsp = 2).<\/br><\/br>Average model responses are *higher* for variable values *higher* than breakpoint (= 2)."}],"parch":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (parch = 0), prediction is equal to 0.148<\/br><\/br>The highest prediction occurs for (parch = 0), while the lowest for (parch = 6).<\/br>Breakpoint is identified at (parch = 0).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 0)."}]}},{"x":[{"variable_name":"gender","variable":"gender = male","contribution":-0.155,"variable_value":"male","sign":"-1","label":"scikit-learn","barStart":0.1597,"barSupport":0.3144,"tooltipText":"gender = male<br>decreases average response <br>by 0.155","min":0.1159,"q1":0.1236,"q3":0.1753,"max":0.2506},{"variable_name":"age","variable":"age = 55","contribution":-0.048,"variable_value":"55","sign":"-1","label":"scikit-learn","barStart":0.2663,"barSupport":0.3144,"tooltipText":"age = 55<br>decreases average response <br>by 0.048","min":0.1673,"q1":0.2219,"q3":0.3009,"max":0.3622},{"variable_name":"fare","variable":"fare = 0","contribution":0.024,"variable_value":"0","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.3382,"tooltipText":"fare = 0<br>increases average response <br>by 0.024","min":0.3248,"q1":0.3287,"q3":0.3428,"max":0.364},{"variable_name":"class","variable":"class = victualling crew","contribution":0.017,"variable_value":"victualling crew","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.3318,"tooltipText":"class = victualling crew<br>increases average response <br>by 0.017","min":0.2816,"q1":0.3188,"q3":0.3436,"max":0.3807},{"variable_name":"parch","variable":"parch = 0","contribution":-0.004,"variable_value":"0","sign":"-1","label":"scikit-learn","barStart":0.3107,"barSupport":0.3144,"tooltipText":"parch = 0<br>decreases average response <br>by 0.004","min":0.2787,"q1":0.2958,"q3":0.3251,"max":0.3434},{"variable_name":"embarked","variable":"embarked = Southampton","contribution":-0.003,"variable_value":"Southampton","sign":"-1","label":"scikit-learn","barStart":0.3111,"barSupport":0.3144,"tooltipText":"embarked = Southampton<br>decreases average response <br>by 0.003","min":0.2776,"q1":0.2882,"q3":0.3294,"max":0.3431},{"variable_name":"sibsp","variable":"sibsp = 0","contribution":0.002,"variable_value":"0","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.3163,"tooltipText":"sibsp = 0<br>increases average response <br>by 0.002","min":0.3002,"q1":0.3058,"q3":0.3302,"max":0.3344}],"m":[7],"x_min_max":[0.0906,0.3765],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 0.148 which is lower than the average model prediction 0.314. For the selected instance model's prediction is lower, than for 61% of all observations.<\/br><\/br>The most important variable is gender (= male). It decreases the prediction by 0.155.<\/br>The second most important variable is age (= 55). It decreases the prediction by 0.048.<\/br>The third most important variable is fare (= 0). It increases the prediction by 0.024.<\/br>The average contribution of all the above variables is significant.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is 0.013."}]}],"1047":[{"x":[{"variable":"intercept","contribution":0,"variable_name":"intercept","variable_value":"1","cumulative":0.314,"sign":"X","position":9,"label":"scikit-learn","barStart":0.3144,"barSupport":0.3144,"tooltipText":"Average response: 0.314<br>Prediction: 0.216"},{"variable":"embarked = Queenstown","contribution":-0.144,"variable_name":"embarked","variable_value":"Queenstown","cumulative":0.17,"sign":"-1","position":8,"label":"scikit-learn","barStart":0.1701,"barSupport":0.3144,"tooltipText":"embarked = Queenstown<br>decreases average response <br>by 0.144"},{"variable":"gender = male","contribution":-0.12,"variable_name":"gender","variable_value":"male","cumulative":0.05,"sign":"-1","position":7,"label":"scikit-learn","barStart":0.0502,"barSupport":0.1701,"tooltipText":"gender = male<br>decreases average response <br>by 0.12"},{"variable":"class = 3rd","contribution":0.012,"variable_name":"class","variable_value":"3rd","cumulative":0.062,"sign":"1","position":6,"label":"scikit-learn","barStart":0.0502,"barSupport":0.0624,"tooltipText":"class = 3rd<br>increases average response <br>by 0.012"},{"variable":"age = 24","contribution":0.08,"variable_name":"age","variable_value":"24","cumulative":0.143,"sign":"1","position":5,"label":"scikit-learn","barStart":0.0624,"barSupport":0.1428,"tooltipText":"age = 24<br>increases average response <br>by 0.08"},{"variable":"sibsp = 0","contribution":0.012,"variable_name":"sibsp","variable_value":"0","cumulative":0.154,"sign":"1","position":4,"label":"scikit-learn","barStart":0.1428,"barSupport":0.1545,"tooltipText":"sibsp = 0<br>increases average response <br>by 0.012"},{"variable":"fare = 7.15","contribution":0.03,"variable_name":"fare","variable_value":"7.15","cumulative":0.184,"sign":"1","position":3,"label":"scikit-learn","barStart":0.1545,"barSupport":0.1841,"tooltipText":"fare = 7.15<br>increases average response <br>by 0.03"},{"variable":"parch = 0","contribution":0.032,"variable_name":"parch","variable_value":"0","cumulative":0.216,"sign":"1","position":2,"label":"scikit-learn","barStart":0.1841,"barSupport":0.216,"tooltipText":"parch = 0<br>increases average response <br>by 0.032"},{"variable":"prediction","contribution":-0.098,"variable_name":"prediction","variable_value":"","cumulative":0.216,"sign":"X","position":1,"label":"scikit-learn","barStart":0.216,"barSupport":0.3144,"tooltipText":"Average response: 0.314<br>Prediction: 0.216"}],"m":[9],"x_min_max":[-0.0028,0.3668],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 0.216 which is lower than the average model prediction 0.314.<\/br><\/br>The most important variable is embarked (= Queenstown). It decreases the prediction by 0.144.<\/br>The second most important variable is gender (= male). It decreases the prediction by 0.12.<\/br>The third most important variable is age (= 24). It increases the prediction by 0.08.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is 0.085."}]},{"observation":[{"observation.id":"1047","model":"scikit-learn","yhat":[0.216],"gender":"male","age":24,"class":"3rd","embarked":"Queenstown","fare":7.15,"sibsp":0,"parch":0}],"x":{"gender":[{"xhat":"female","yhat":0.6736,"vname":"gender"},{"xhat":"male","yhat":0.216,"vname":"gender"}],"age":[{"xhat":0.5833,"yhat":0.1705,"id":"1047","vname":"age"},{"xhat":1.28,"yhat":0.1595,"id":"1047","vname":"age"},{"xhat":4,"yhat":0.1123,"id":"1047","vname":"age"},{"xhat":7,"yhat":0.0802,"id":"1047","vname":"age"},{"xhat":8.12,"yhat":0.0699,"id":"1047","vname":"age"},{"xhat":11,"yhat":0.0547,"id":"1047","vname":"age"},{"xhat":15,"yhat":0.0713,"id":"1047","vname":"age"},{"xhat":17,"yhat":0.0932,"id":"1047","vname":"age"},{"xhat":18,"yhat":0.1104,"id":"1047","vname":"age"},{"xhat":19,"yhat":0.1317,"id":"1047","vname":"age"},{"xhat":20,"yhat":0.1561,"id":"1047","vname":"age"},{"xhat":21,"yhat":0.1804,"id":"1047","vname":"age"},{"xhat":22,"yhat":0.1916,"id":"1047","vname":"age"},{"xhat":23,"yhat":0.2033,"id":"1047","vname":"age"},{"xhat":24,"yhat":0.216,"id":"1047","vname":"age"},{"xhat":25,"yhat":0.2001,"id":"1047","vname":"age"},{"xhat":25.24,"yhat":0.194,"id":"1047","vname":"age"},{"xhat":26,"yhat":0.1721,"id":"1047","vname":"age"},{"xhat":27,"yhat":0.1454,"id":"1047","vname":"age"},{"xhat":27.2,"yhat":0.1408,"id":"1047","vname":"age"},{"xhat":28,"yhat":0.1255,"id":"1047","vname":"age"},{"xhat":29,"yhat":0.1098,"id":"1047","vname":"age"},{"xhat":29.44,"yhat":0.0938,"id":"1047","vname":"age"},{"xhat":30,"yhat":0.0663,"id":"1047","vname":"age"},{"xhat":31,"yhat":0.0326,"id":"1047","vname":"age"},{"xhat":32,"yhat":0.0159,"id":"1047","vname":"age"},{"xhat":33,"yhat":0.0075,"id":"1047","vname":"age"},{"xhat":34,"yhat":0.0038,"id":"1047","vname":"age"},{"xhat":35,"yhat":0.0019,"id":"1047","vname":"age"},{"xhat":35.04,"yhat":0.0019,"id":"1047","vname":"age"},{"xhat":36,"yhat":0.001,"id":"1047","vname":"age"},{"xhat":36.88,"yhat":0.0006,"id":"1047","vname":"age"},{"xhat":37,"yhat":0.0005,"id":"1047","vname":"age"},{"xhat":38,"yhat":0.0003,"id":"1047","vname":"age"},{"xhat":39,"yhat":0.0001,"id":"1047","vname":"age"},{"xhat":40,"yhat":0.0001,"id":"1047","vname":"age"},{"xhat":41,"yhat":0,"id":"1047","vname":"age"},{"xhat":42,"yhat":0,"id":"1047","vname":"age"},{"xhat":43,"yhat":8.1131e-006,"id":"1047","vname":"age"},{"xhat":44,"yhat":3.8981e-006,"id":"1047","vname":"age"},{"xhat":45,"yhat":1.8865e-006,"id":"1047","vname":"age"},{"xhat":45.64,"yhat":1.1914e-006,"id":"1047","vname":"age"},{"xhat":46,"yhat":9.1962e-007,"id":"1047","vname":"age"},{"xhat":46.2,"yhat":7.9618e-007,"id":"1047","vname":"age"},{"xhat":48,"yhat":2.3186e-007,"id":"1047","vname":"age"},{"xhat":49,"yhat":1.2158e-007,"id":"1047","vname":"age"},{"xhat":50,"yhat":6.5324e-008,"id":"1047","vname":"age"},{"xhat":51,"yhat":3.7709e-008,"id":"1047","vname":"age"},{"xhat":53.6,"yhat":9.7063e-009,"id":"1047","vname":"age"},{"xhat":55,"yhat":4.7187e-009,"id":"1047","vname":"age"},{"xhat":56,"yhat":2.7814e-009,"id":"1047","vname":"age"},{"xhat":60,"yhat":3.4816e-010,"id":"1047","vname":"age"},{"xhat":63,"yhat":7.6451e-011,"id":"1047","vname":"age"},{"xhat":72,"yhat":9.0163e-013,"id":"1047","vname":"age"}],"class":[{"xhat":"1st","yhat":0.1037,"vname":"class"},{"xhat":"2nd","yhat":0.023,"vname":"class"},{"xhat":"3rd","yhat":0.216,"vname":"class"},{"xhat":"deck 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predicts that for the selected instance (gender = male), prediction is equal to 0.216<\/br><\/br>The most important change in Scikit-learn's prediction would occur for gender = \"female\". It increases the prediction by 0.458. <\/br> <\/br><\/br><\/br>All variables are being displayed."}],"age":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (age = 24), prediction is equal to 0.216<\/br><\/br>The highest prediction occurs for (age = 24), while the lowest for (age = 72).<\/br>Breakpoint is identified at (age = 30).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 30)."}],"class":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (class = 3rd), prediction is equal to 0.216<\/br><\/br>The most important change in Scikit-learn's prediction would occur for class = \"restaurant staff\". It decreases the prediction by 0.215. <\/br>The second most important change in the prediction would occur for class = \"2nd\". It decreases the prediction by 0.193. <\/br>The third most important change in the prediction would occur for class = \"victualling crew\". It decreases the prediction by 0.173.<\/br><\/br>Other variable values are with less importance. They do not change the prediction by more than 0.162."}],"embarked":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (embarked = Queenstown), prediction is equal to 0.216<\/br><\/br>The most important change in Scikit-learn's prediction would occur for embarked = \"Belfast\". It decreases the prediction by 0.155. <\/br>The second most important change in the prediction would occur for embarked = \"Southampton\". It decreases the prediction by 0.116. <\/br>The third most important change in the prediction would occur for embarked = \"Cherbourg\". It decreases the prediction by 0.072.<\/br><\/br>All variables are being displayed."}],"fare":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (fare = 7.15), prediction is equal to 0.216<\/br><\/br>The highest prediction occurs for (fare = 7.1806), while the lowest for (fare = 218.336504).<\/br>Breakpoint is identified at (fare = 39.837).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 39.837)."}],"sibsp":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (sibsp = 0), prediction is equal to 0.216<\/br><\/br>The highest prediction occurs for (sibsp = 0), while the lowest for (sibsp = 8).<\/br>Breakpoint is identified at (sibsp = 0).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 0)."}],"parch":[{"type":"desc","text":"Scikit-learn predicts that for the selected instance (parch = 0), prediction is equal to 0.216<\/br><\/br>The highest prediction occurs for (parch = 0), while the lowest for (parch = 6).<\/br>Breakpoint is identified at (parch = 0).<\/br><\/br>Average model responses are *lower* for variable values *higher* than breakpoint (= 0)."}]}},{"x":[{"variable_name":"gender","variable":"gender = male","contribution":-0.123,"variable_value":"male","sign":"-1","label":"scikit-learn","barStart":0.1912,"barSupport":0.3144,"tooltipText":"gender = male<br>decreases average response <br>by 0.123","min":0.1444,"q1":0.1752,"q3":0.2074,"max":0.2401},{"variable_name":"embarked","variable":"embarked = Queenstown","contribution":-0.068,"variable_value":"Queenstown","sign":"-1","label":"scikit-learn","barStart":0.2463,"barSupport":0.3144,"tooltipText":"embarked = Queenstown<br>decreases average response <br>by 0.068","min":0.1545,"q1":0.1739,"q3":0.2832,"max":0.4212},{"variable_name":"age","variable":"age = 24","contribution":0.061,"variable_value":"24","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.3753,"tooltipText":"age = 24<br>increases average response <br>by 0.061","min":0.3229,"q1":0.3429,"q3":0.4073,"max":0.454},{"variable_name":"fare","variable":"fare = 7.15","contribution":0.022,"variable_value":"7.15","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.3367,"tooltipText":"fare = 7.15<br>increases average response <br>by 0.022","min":0.3033,"q1":0.3293,"q3":0.3465,"max":0.3576},{"variable_name":"sibsp","variable":"sibsp = 0","contribution":0.018,"variable_value":"0","sign":"1","label":"scikit-learn","barStart":0.3144,"barSupport":0.332,"tooltipText":"sibsp = 0<br>increases average response <br>by 0.018","min":0.3159,"q1":0.3219,"q3":0.3339,"max":0.352},{"variable_name":"class","variable":"class = 3rd","contribution":-0.007,"variable_value":"3rd","sign":"-1","label":"scikit-learn","barStart":0.3078,"barSupport":0.3144,"tooltipText":"class = 3rd<br>decreases average response <br>by 0.007","min":0.1475,"q1":0.2153,"q3":0.4191,"max":0.4191},{"variable_name":"parch","variable":"parch = 0","contribution":-0.002,"variable_value":"0","sign":"-1","label":"scikit-learn","barStart":0.3128,"barSupport":0.3144,"tooltipText":"parch = 0<br>decreases average response <br>by 0.002","min":0.3021,"q1":0.3026,"q3":0.3158,"max":0.3357}],"m":[7],"x_min_max":[0.1371,0.4559],"desc":[{"type":"desc","text":"Scikit-learn predicts, that the prediction for the selected instance is 0.216 which is lower than the average model prediction 0.314.For the selected instance model's prediction is higher, than for 62% of all observations.<\/br><\/br>The most important variable is gender (= male). It decreases the prediction by 0.123.<\/br>The second most important variable is embarked (= Queenstown). It decreases the prediction by 0.068.<\/br>The third most important variable is age (= 24). It increases the prediction by 0.061.<\/br>The average contribution of all the above variables is significant.<\/br><\/br>Other variables are with less importance. The contribution of all other variables is 0.032."}]}]},{"x":[{"variable":"gender","label":"sklearn.pipeline.Pipeline","dropout_loss":0.531,"full_model":0.39,"min":0.5098,"q1":0.5248,"q3":0.5355,"max":0.5469},{"variable":"class","label":"sklearn.pipeline.Pipeline","dropout_loss":0.458,"full_model":0.39,"min":0.4486,"q1":0.4557,"q3":0.4605,"max":0.4676},{"variable":"age","label":"sklearn.pipeline.Pipeline","dropout_loss":0.415,"full_model":0.39,"min":0.4083,"q1":0.4119,"q3":0.4177,"max":0.4258},{"variable":"parch","label":"sklearn.pipeline.Pipeline","dropout_loss":0.407,"full_model":0.39,"min":0.4006,"q1":0.4054,"q3":0.4086,"max":0.4134},{"variable":"embarked","label":"sklearn.pipeline.Pipeline","dropout_loss":0.403,"full_model":0.39,"min":0.3973,"q1":0.4012,"q3":0.4038,"max":0.4078},{"variable":"fare","label":"sklearn.pipeline.Pipeline","dropout_loss":0.4,"full_model":0.39,"min":0.3929,"q1":0.3967,"q3":0.4035,"max":0.4077},{"variable":"sibsp","label":"sklearn.pipeline.Pipeline","dropout_loss":0.4,"full_model":0.39,"min":0.391,"q1":0.3984,"q3":0.4034,"max":0.405}],"m":[7],"x_min_max":[0.3682,0.5574],"desc":[{"type":"desc","text":"The 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s,v=m[Symbol.iterator]();!(h=(s=v.next()).done);h=!0){y+=w(s.value)}}catch(t){p=!0,g=t}finally{try{h||null==v.return||v.return()}finally{if(p)throw g}}return O&&(y+=\"Z\"),y}},Object.defineProperty(t,\"__esModule\",{value:!0})});\n\n/* R2D3 Source File:   */\n//:\\\\\\ here are functions for modelStudio plots //:\\\\\\\n\n// model specific data and other variables come from modelStudio.js file\n// descriptions need to be IN plot functions because of tooltips\n\n/// initialize plots, select them if already there\nvar BD, SV, CP, FI, PD, AD, FD, TV, AT;\n\n/// later plot specific plotIds\nvar mapIdPlotFunction = {};\n\nif (svg.select(\"#BD\").empty()) {\n  BD = svg.append(\"g\")\n              .attr(\"class\",\"plot\")\n              .attr(\"id\", \"BD\")\n              .style(\"visibility\", \"hidden\");\n} else {\n  BD = svg.select(\"#BD\");\n}\nmapIdPlotFunction.BD = breakDown;\n\nif (svg.select(\"#SV\").empty()) {\n  SV = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"SV\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  SV = svg.select(\"#SV\");\n}\nmapIdPlotFunction.SV = shapleyValues;\n\nif (svg.select(\"#CP\").empty()) {\n  CP = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\", \"CP\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  CP = svg.select(\"#CP\");\n}\nmapIdPlotFunction.CP = ceterisParibus;\n\nif (svg.select(\"#FI\").empty()) {\n  FI = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"FI\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  FI = svg.select(\"#FI\");\n}\nmapIdPlotFunction.FI = featureImportance;\n\nif (svg.select(\"#PD\").empty()) {\n  PD = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"PD\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  PD = svg.select(\"#PD\");\n}\nmapIdPlotFunction.PD = partialDependence;\n\nif (svg.select(\"#AD\").empty()) {\n  AD = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"AD\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  AD = svg.select(\"#AD\");\n}\nmapIdPlotFunction.AD = accumulatedDependence;\n\nif (svg.select(\"#FD\").empty()) {\n  FD = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"FD\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  FD = svg.select(\"#FD\");\n}\nmapIdPlotFunction.FD = featureDistribution;\n\nif (svg.select(\"#TV\").empty()) {\n  TV = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"TV\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  TV = svg.select(\"#TV\");\n}\nmapIdPlotFunction.TV = targetVs;\n\nif (svg.select(\"#AT\").empty()) {\n  AT = svg.append(\"g\")\n          .attr(\"class\",\"plot\")\n          .attr(\"id\",\"AT\")\n          .style(\"visibility\", \"hidden\");\n} else {\n  AT = svg.select(\"#AT\");\n}\nmapIdPlotFunction.AT = averageTarget;\n\n/// general plot functions\n\nfunction breakDown() {\n\n  let tObservationId = CLICKED_OBSERVATION_ID,\n      tData = obsData[tObservationId];\n\n  if (tData[0].x === undefined) return null;\n\n  var bdData = tData[0],\n      bData = bdData.x;\n      bdBarCount = bdData.m[0],\n      xMinMax = bdData.x_min_max,\n      desc = bdData.desc;\n\n  var bdPlotHeight = SCALE_PLOT ? h : bdBarCount*bdBarWidth + (bdBarCount+1)*bdBarWidth/2,\n      bdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + bdPlotWidth])\n            .domain([xMinMax[0], xMinMax[1]]);\n\n  BD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + bdPlotWidth/2) + \" ,\" +\n                         (margin.top + bdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"contribution\");\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = BD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + bdPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + bdPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.variable));\n\n  var xGrid = BD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + bdPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-bdPlotHeight-additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = BD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-bdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = BD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.select(\".tick:last-child\").select(\"text\").attr('font-weight', 600);\n\n  // wrap y label text\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  BD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(bdSubtitle);\n\n  BD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(bdTitle);\n\n  // add tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipBD\")\n                  .html(d => d.type === \"desc\"\n                             ? descTooltipHtml(d) : bdTooltipHtml(d));\n\n  BD.call(tooltip);\n\n  // find boundaries\n  let intercept = bData[0].contribution > 0\n                  ? bData[0].barStart\n                  : bData[0].barSupport;\n\n  // make dotted line from intercept to prediction\n  var dotLineData = [{\"x\": x(intercept), \"y\": y(\"intercept\")},\n                     {\"x\": x(intercept), \"y\": y(\"prediction\") + y.bandwidth()}];\n\n  var lineFunction = d3.line()\n                       .x(d => d.x)\n                       .y(d => d.y);\n\n  BD.append(\"path\")\n    .data([dotLineData])\n    .attr(\"class\", \"dotLine\")\n    .attr(\"d\", lineFunction)\n    .style(\"stroke-dasharray\", (\"1, 2\"));\n\n  // add bars\n  var bars = BD.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"BD-bars\")\n      .attr(\"id\", d => d.variable_name)\n      .attr(\"fill\", d => {\n        switch (d.sign) {\n          case \"-1\":\n            return bdNegativeColor;\n          case \"1\":\n            return bdPositiveColor;\n          default:\n            return defaultColor;\n        }\n      })\n      .attr(\"fill-opacity\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                                 ? 0 : 1) //invisible bar for clicking purpose\n      .attr(\"y\", d => y(d.variable))\n      .attr(\"height\", y.bandwidth())\n      .attr(\"x\", d => d.contribution > 0 ? x(d.barStart) : x(d.barSupport))\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .on(\"click\", function() {\n        updatePlots(event = \"variableChange\",\n                    variableName = this.id,\n                    observationId = null,\n                    plotId = null);\n      })\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.barStart))\n      .attr(\"width\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                          ? 5 : x(d.barSupport) - x(d.barStart));\n\n  // add labels to bars\n  var ctbLabel = BD.selectAll()\n                   .data(bData)\n                   .enter()\n                   .append(\"g\");\n\n  ctbLabel.append(\"text\")\n          .attr(\"class\", \"axisLabel\")\n          .attr(\"x\", d => {\n            switch (d.sign) {\n              case \"X\":\n                return d.contribution < 0\n                       ? x(d.barStart) - 5 : x(d.barSupport) + 5;\n              default:\n                return x(d.barSupport) + 5;\n            }\n          })\n          .attr(\"y\", d => y(d.variable) + y.bandwidth()/2)\n          .attr(\"dy\", \"0.4em\")\n          .attr(\"text-anchor\", d => d.sign == \"X\" && d.contribution < 0\n                               ? \"end\" : null)\n          .transition()\n          .duration(TIME)\n          .delay((d,i) => (i+1) * TIME)\n          .text(d => {\n            switch (d.variable) {\n              case \"intercept\":\n              case \"prediction\":\n                return d.cumulative;\n              default:\n                return d.sign === \"-1\" ? d.contribution : \"+\"+d.contribution;\n            }\n          });\n\n  // add lines to bars\n  var lines = BD.selectAll()\n                .data(bData)\n                .enter()\n                .append(\"g\");\n\n  lines.append(\"line\")\n       .attr(\"class\", \"interceptLine\")\n       .attr(\"x1\", d => d.contribution < 0 ? x(d.barStart) : x(d.barSupport))\n       .attr(\"y1\", d => y(d.variable))\n       .attr(\"x2\", d => d.contribution < 0 ? x(d.barStart) : x(d.barSupport))\n       .attr(\"y2\", d => y(d.variable))\n       .transition()\n       .duration(TIME)\n       .delay((d,i) => (i+1) * TIME)\n       .attr(\"y2\", d => d.variable == \"prediction\"\n                        ? y(d.variable) : y(d.variable) + y.bandwidth()*2.5);\n\n  var description = BD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + bdPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction shapleyValues() {\n\n  let tObservationId = CLICKED_OBSERVATION_ID,\n      tData = obsData[tObservationId];\n\n  if (tData[2].x === undefined) return null;\n\n  var svData = tData[2],\n      bData = svData.x,\n      svBarCount = svData.m[0],\n      xMinMax = svData.x_min_max,\n      desc = svData.desc;\n\n  var svPlotHeight = SCALE_PLOT ? h : svBarCount*svBarWidth + (svBarCount+1)*svBarWidth/2,\n      svPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + svPlotWidth])\n            .domain([xMinMax[0], xMinMax[1]]);\n\n  SV.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + svPlotWidth/2) + \" ,\" +\n                         (margin.top + svPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"contribution\");\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = SV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + svPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + svPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.variable));\n\n  var xGrid = SV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + svPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-svPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = SV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-svPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = SV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // wrap y label text\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  SV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(svSubtitle);\n\n  SV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(svTitle);\n\n  // add tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipSV\")\n                  .html(d => d.type === \"desc\"\n                             ? descTooltipHtml(d) : bdTooltipHtml(d));\n\n  SV.call(tooltip);\n\n  // add bars\n  var bars = SV.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"SV-bars\")\n      .attr(\"id\", (d) => d.variable_name)\n      .attr(\"fill\", function(d) {\n        switch (d.sign) {\n          case \"-1\":\n            return svNegativeColor;\n          case \"1\":\n            return svPositiveColor;\n          default:\n            return defaultColor;\n        }\n      })\n      .attr(\"fill-opacity\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                                 ? 0 : 1) //invisible bar for clicking purpose\n      .attr(\"x\", d => d.contribution > 0 ? x(d.barStart) : x(d.barSupport))\n      .attr(\"y\", d => y(d.variable))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .on(\"click\", function() {\n        updatePlots(event = \"variableChange\",\n                    variableName = this.id,\n                    observationId = null,\n                    plotId = null);\n      })\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.barStart))\n      .attr(\"width\", d => x(d.barSupport) - x(d.barStart) < 1.5\n                          ? 5 : x(d.barSupport) - x(d.barStart));\n\n  // add labels to bars\n  var ctbLabel = SV.selectAll()\n                   .data(bData)\n                   .enter()\n                   .append(\"g\");\n\n  ctbLabel.append(\"text\")\n          .attr(\"class\", \"axisLabel\")\n          .attr(\"x\", d => d.contribution > 0\n                          ? x(d.barStart) - 5 : x(d.barSupport) + 5)\n          .attr(\"y\", d => y(d.variable) + y.bandwidth()/2)\n          .attr(\"dy\", \"0.4em\")\n          .attr(\"text-anchor\", d => d.sign == \"1\" ? \"end\" : \"start\")\n          .transition()\n          .duration(TIME)\n          .delay((d,i) => (i+1) * TIME)\n          .text(d => d.sign == \"-1\" ? d.contribution : \"+\"+d.contribution);\n\n  // add lines to bars\n  var lines = SV.selectAll()\n                .data(bData)\n                .enter()\n                .append(\"g\");\n\n  lines.append(\"line\")\n        .attr(\"class\", \"interceptLine\")\n        .attr(\"x1\", d => d.contribution < 0 ? x(d.barSupport) : x(d.barStart))\n        .attr(\"y1\", d => y(d.variable))\n        .attr(\"x2\", d => d.contribution < 0 ? x(d.barSupport) : x(d.barStart))\n        .attr(\"y2\", d => y(d.variable))\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => (i+1) * TIME)\n        .attr(\"y2\", (d,i) => i == svBarCount - 1\n                             ? y(d.variable) + y.bandwidth()\n                             : y(d.variable) + y.bandwidth()*2.5);\n\n\n  // boxplots\n  if (SHOW_BOXPLOT) {\n    // main horizontal line\n    bars.append(\"line\")\n        .attr(\"class\", \"interceptLine\")\n        .attr(\"x1\", d => d.contribution < 0 ? x(d.max) : x(d.min))\n        .attr(\"x2\", d => d.contribution < 0 ? x(d.max) : x(d.min))\n        .attr(\"y1\", d => y(d.variable) + y.bandwidth()/2)\n        .attr(\"y2\", d => y(d.variable) + y.bandwidth()/2)\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x1\", d => x(d.min))\n        .attr(\"x2\", d => x(d.max));\n\n    // rectangle for the main box\n    bars.append(\"rect\")\n        .attr(\"x\", d => d.contribution < 0 ? x(d.q3) : x(d.q1))\n        .attr(\"y\", d => y(d.variable) + y.bandwidth()/3)\n        .attr(\"height\", y.bandwidth()/3)\n        .style(\"fill\", \"#371ea3\")\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x\", d => x(d.q1))\n        .attr(\"width\", d => Math.abs(x(d.q3) - x(d.q1)));\n  }\n\n  // description\n  var description = SV.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + svPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction ceterisParibus() {\n\n  let tObservationId = CLICKED_OBSERVATION_ID,\n      tData = obsData[tObservationId];\n\n  if (tData[1].x === undefined) return null;\n\n  let cpData = tData[1],\n      profData = cpData.x,\n      xMinMax = cpData.x_min_max_list,\n      yMinMax = cpData.y_min_max,\n      pData = cpData.observation,\n      isNumeric = cpData.is_numeric\n      desc = cpData.desc;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // lines or bars?\n  if (isNumeric[tVariableName][0]) {\n    cpNumericalPlot(tVariableName, profData[tVariableName],\n                    xMinMax[tVariableName], yMinMax, pData,\n                    desc[tVariableName]);\n  } else {\n    cpCategoricalPlot(tVariableName, profData[tVariableName],\n                      yMinMax, pData, desc[tVariableName]);\n  }\n}\n\nfunction featureImportance() {\n\n  if (fiData.x === undefined) return null;\n\n  var fiBarCount = fiData.m[0],\n      bData = fiData.x,\n      xMinMax = fiData.x_min_max,\n      desc = fiData.desc;\n\n  var fiPlotHeight = SCALE_PLOT ? h : fiBarCount*fiBarWidth + (fiBarCount+1)*fiBarWidth/2,\n      fiPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + fiPlotWidth])\n            .domain([xMinMax[0], xMinMax[1]]);\n\n  FI.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + fiPlotWidth/2) + \" ,\" +\n                         (margin.top + fiPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"drop-out loss\");\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = FI.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + fiPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + fiPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.variable));\n\n  var xGrid = FI.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + fiPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-fiPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = FI.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-fiPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = FI.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  FI.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(fiSubtitle);\n\n  FI.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(fiTitle);\n\n  // tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipFI\")\n                  .html(d => d.type === \"desc\"\n                             ? descTooltipHtml(d)\n                             : fiStaticTooltipHtml(d));\n  FI.call(tooltip);\n\n  // bars\n  var bars = FI.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  // find full model dropout_loss value\n  var fullModel = bData[0].full_model;\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"FI-bars\")\n      .attr(\"fill\", fiBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.variable))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .attr(\"id\", (d) => d.variable)\n      .on(\"click\", function(){\n        updatePlots(event = \"variableChange\",\n                    variableName = this.id,\n                    observationId = null,\n                    plotId = null);\n      })\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.dropout_loss) < x(fullModel)\n                      ? x(d.dropout_loss) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.dropout_loss) - x(fullModel)));\n\n  // make the interceptLine\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n  bars.selectAll(\".FI-bars\").each(function() {\n    if (+this.getAttribute('y') < minimumY) {\n      minimumY = +this.getAttribute('y');\n    }\n    if (+this.getAttribute('y') > maximumY) {\n      maximumY = +this.getAttribute('y');\n    }\n  });\n\n  FI.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  // boxplots\n  if (SHOW_BOXPLOT) {\n\n    // main horizontal line\n    bars.append(\"line\")\n        .attr(\"class\", \"interceptLine\")\n        .attr(\"x1\", d => x(d.dropout_loss) < x(fullModel) ? x(d.max) : x(d.min))\n        .attr(\"x2\", d => x(d.dropout_loss) < x(fullModel) ? x(d.max) : x(d.min))\n        .attr(\"y1\", d => y(d.variable) + y.bandwidth()/2)\n        .attr(\"y2\", d => y(d.variable) + y.bandwidth()/2)\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x1\", d => x(d.min))\n        .attr(\"x2\", d => x(d.max));\n\n    // rectangle for the main box\n    bars.append(\"rect\")\n        .attr(\"x\", d => x(d.dropout_loss) < x(fullModel) ? x(d.q3) : x(d.q1))\n        .attr(\"y\", d => y(d.variable) + y.bandwidth()/3)\n        .attr(\"height\", y.bandwidth()/3)\n        .style(\"fill\", \"#371ea3\")\n        .transition()\n        .duration(TIME)\n        .delay((d,i) => i * TIME)\n        .attr(\"x\", d => x(d.q1))\n        .attr(\"width\", d => Math.abs(x(d.q3) - x(d.q1)));\n  }\n\n  // description\n  var description = FI.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + fiPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction partialDependence() {\n\n  if (pdData.x === undefined) return null;\n\n  let profData = pdData.x,\n      xMinMax = pdData.x_min_max_list,\n      yMinMax = pdData.y_min_max,\n      yMean = pdData.y_mean,\n      isNumeric = pdData.is_numeric,\n      desc = pdData.desc;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // lines or bars?\n  if (isNumeric[tVariableName][0]) {\n    pdNumericalPlot(tVariableName, profData[tVariableName],\n                    xMinMax[tVariableName], yMinMax, yMean,\n                    desc[tVariableName]);\n  } else {\n    pdCategoricalPlot(tVariableName, profData[tVariableName],\n                      yMinMax, yMean, desc[tVariableName]);\n  }\n}\n\nfunction accumulatedDependence() {\n\n  if (adData.x === undefined) return null;\n\n  let profData = adData.x,\n      xMinMax = adData.x_min_max_list,\n      yMinMax = adData.y_min_max,\n      yMean = adData.y_mean,\n      isNumeric = adData.is_numeric,\n      desc = adData.desc;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // lines or bars?\n  if (isNumeric[tVariableName][0]) {\n    adNumericalPlot(tVariableName, profData[tVariableName],\n                    xMinMax[tVariableName], yMinMax, yMean,\n                    desc[tVariableName]);\n  } else {\n    adCategoricalPlot(tVariableName, profData[tVariableName],\n                      yMinMax, yMean, desc[tVariableName]);\n  }\n}\n\nfunction featureDistribution() {\n\n  if (fdData.x === undefined) return null;\n\n  let dData = fdData.x,\n      xMinMax = fdData.x_min_max_list,\n      xMax = fdData.x_max_list,\n      nBin = fdData.nbin,\n      isNumeric = fdData.is_numeric;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // histogram or bars?\n  if (isNumeric[tVariableName][0]) {\n    fdNumericalPlot(tVariableName, dData, xMinMax[tVariableName],\n                    nBin[tVariableName]);\n  } else {\n    fdCategoricalPlot(tVariableName, dData, xMinMax[tVariableName],\n                      xMax[tVariableName]);\n  }\n}\n\nfunction targetVs() {\n\n  if (tvData.x === undefined) return null;\n\n  let xData = tvData.x,\n      xMinMax = tvData.x_min_max_list,\n      yMinMax = tvData.y_min_max,\n      isNumeric = tvData.is_numeric;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // scatterplot or violin?\n  if (isNumeric[tVariableName][0]) {\n    tvNumericalPlot(tVariableName, xData, xMinMax[tVariableName], yMinMax);\n  } else {\n    tvCategoricalPlot(tVariableName, xData, xMinMax[tVariableName], yMinMax);\n  }\n}\n\nfunction averageTarget() {\n\n  if (atData.x === undefined) return null;\n\n  let xData = atData.x,\n      xMinMax = atData.x_min_max_list,\n      yMinMax = atData.y_min_max_list,\n      yMean = atData.y_mean,\n      isNumeric = atData.is_numeric;\n\n  let tVariableName = CLICKED_VARIABLE_NAME;\n\n  // scatterplot or violin?\n  if (isNumeric[tVariableName][0]) {\n    atNumericalPlot(tVariableName, xData[tVariableName],\n                    xMinMax[tVariableName], yMinMax[tVariableName], yMean);\n  } else {\n    atCategoricalPlot(tVariableName, xData[tVariableName],\n                      xMinMax[tVariableName], yMinMax[tVariableName], yMean);\n  }\n}\n\n/// small plot functions\n\nfunction cpNumericalPlot(variableName, lData, mData, yMinMax, pData, desc) {\n\n  var cpPlotHeight = h,\n      cpPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + cpPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  CP.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + cpPlotWidth/2) + \" ,\" +\n                         (margin.top + cpPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName + \" = \" + pData[0][variableName]);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + cpPlotHeight, margin.top - additionalHeight])\n            .domain([yMinMax[0], yMinMax[1]]);\n\n  var line = d3.line()\n               .x(d => x(d.xhat))\n               .y(d => y(d.yhat))\n               .curve(d3.curveMonotoneX);\n\n   CP.append(\"text\")\n     .attr(\"class\",\"smallTitle\")\n     .attr(\"x\", margin.left)\n     .attr(\"y\", margin.top - 15)\n     .text(cpSubtitle); //variableName + \" = \" + pData[0][variableName]\n\n  CP.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(cpTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + cpPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = CP.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-cpPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipCP\")\n                  .html((d, addData) => {\n\n                    if (d.type === \"desc\") {\n                      return descTooltipHtml(d)\n                    } else if (addData !== undefined) {\n                      return cpChangedTooltipHtml(d, addData);\n                    } else {\n                        return cpStaticTooltipHtml(d);\n                    }\n                   });\n  CP.call(tooltip);\n\n  // function to find nearest point on the line\n  var bisectXhat = d3.bisector(d => d.xhat).right;\n\n  // show tooltip with info nearest to mouseover\n  function showTooltip(hover) {\n    var x0 = x.invert(d3.mouse(d3.event.currentTarget)[0]),\n        i = bisectXhat(hover, x0),\n        d0 = hover[i - 1],\n        d1 = hover[i],\n        d = x0 - d0.xhat > d1.xhat - x0 ? d1 : d0;\n    let temp = pData.find(el => el[\"observation.id\"] === d.id);\n    tooltip.show(d, temp);\n  }\n\n  // add path\n  var p = CP.append(\"path\")\n            .attr(\"class\", \"CP-lines\")\n            .style(\"fill\", \"none\")\n            .style(\"stroke\", cpLineColor)\n            .style(\"stroke-width\", cpLineSize)\n            .on('mouseover', function(d) {\n\n              // make mouseover line more visible\n              d3.select(this)\n                .style(\"stroke\", defaultColor)\n                .style(\"stroke-width\", cpLineSize*1.5);\n\n              // make line and points appear on top\n              this.parentNode.appendChild(this);\n              d3.select(this.parentNode).selectAll(\".point\").each(function() {\n                               this.parentNode.appendChild(this);\n                          });\n\n              // show changed tooltip\n              showTooltip(d);\n            })\n            .on('mouseout', function(d) {\n\n              d3.select(this)\n                .style(\"stroke\", cpLineColor)\n                .style(\"stroke-width\", cpLineSize);\n\n              // hide changed tooltip\n              tooltip.hide(d);\n            });\n\n  // animate path\n  p.data([{\"xhat\":0, \"yhat\": 0}])\n   .attr(\"d\", line)\n   .transition()\n   .duration(TIME)\n   .attrTween(\"d\", function() {\n     var previous = d3.select(this).attr('d');\n     var current = line(lData);\n     return d3.interpolatePath(previous, current);\n   });\n\n  // add data for tooltip\n  p.data([lData]);\n\n  // add points\n  CP.selectAll()\n    .data(pData)\n    .enter()\n    .append(\"circle\")\n    .attr(\"class\", \"point\")\n    .attr(\"id\", d => d[\"observation.id\"])\n    .attr(\"cx\", d => x(d[variableName]))\n    .attr(\"cy\", d => y(d.yhat))\n    .attr(\"r\", 0)\n    .style(\"stroke-width\", 15)\n    .style(\"stroke\", \"red\")\n    .style(\"stroke-opacity\", 0)\n    .style(\"fill\", cpPointColor)\n    .on('mouseover', function(d) {\n      tooltip.show(d);\n  \t\td3.select(this)\n  \t\t\t.attr(\"r\", 2*cpPointSize);\n  \t})\n    .on('mouseout', function(d) {\n      tooltip.hide(d);\n  \t\td3.select(this)\n  \t\t\t.attr(\"r\", cpPointSize);\n  \t})\n    .transition()\n    .duration(TIME)\n    .delay(TIME)\n    .attr(\"r\", cpPointSize);\n\n  // add rugs\n  CP.selectAll()\n    .data(pData)\n    .enter()\n    .append(\"line\")\n    .attr(\"class\", \"rugLine\")\n    .style(\"stroke\", \"red\")\n    .style(\"stroke-width\", 2)\n    .attr(\"x1\", d => x(d[variableName]))\n    .attr(\"y1\", margin.top + cpPlotHeight)\n    .attr(\"x2\", d => x(d[variableName]))\n    .attr(\"y2\", margin.top + cpPlotHeight - 10);\n\n  CP.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + cpPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"prediction\");\n\n  var description = CP.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + cpPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction cpCategoricalPlot(variableName, bData, yMinMax, lData, desc) {\n\n  var cpBarCount = bData.map(d => d.xhat).length;\n\n  var cpPlotHeight = SCALE_PLOT ? h : cpBarCount*cpBarWidth + (cpBarCount+1)*cpBarWidth/2,\n      cpPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + cpPlotWidth])\n            .domain([yMinMax[0], yMinMax[1]]); // because it is flipped\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + cpPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + cpPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.xhat));\n\n  var xGrid = CP.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + cpPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-cpPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = CP.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-cpPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = CP.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  CP.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(cpSubtitle); //variableName + \" = \" + lData[0][variableName]\n\n  CP.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(cpTitle);\n\n  var bars = CP.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  var fullModel = lData[0].yhat;\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipCP\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : cpChangedTooltipHtml(d, lData[0]));\n  CP.call(tooltip);\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"CP-bars\")\n      .attr(\"fill\", cpBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.xhat))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.yhat) < x(fullModel) ? x(d.yhat) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.yhat) - x(fullModel)));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".CP-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  CP.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  CP.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + cpPlotWidth/2) + \" ,\" +\n                         (margin.top + cpPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"prediction\");\n\n  var description = CP.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + cpPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction pdNumericalPlot(variableName, lData, mData, yMinMax, yMean, desc) {\n\n  var pdPlotHeight = h,\n      pdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + pdPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  PD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + pdPlotWidth/2) + \" ,\" +\n                         (margin.top + pdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + pdPlotHeight, margin.top - additionalHeight])\n            .domain([yMinMax[0], yMinMax[1]]);\n\n  var line = d3.line()\n               .x(d => x(d.xhat))\n               .y(d => y(d.yhat))\n               .curve(d3.curveMonotoneX);\n\n   PD.append(\"text\")\n     .attr(\"class\",\"smallTitle\")\n     .attr(\"x\", margin.left)\n     .attr(\"y\", margin.top - 15)\n     .text(pdSubtitle); // variableName\n\n  PD.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(pdTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + pdPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = PD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-pdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipPD\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : pdStaticTooltipHtml(d, variableName, yMean));\n  PD.call(tooltip);\n\n  // function to find nearest point on the line\n  var bisectXhat = d3.bisector(d => d.xhat).right;\n\n  // show tooltip with info nearest to mouseover\n  function showTooltip(hover) {\n    var x0 = x.invert(d3.mouse(d3.event.currentTarget)[0]),\n        i = bisectXhat(hover, x0),\n        d0 = hover[i - 1],\n        d1 = hover[i],\n        d = x0 - d0.xhat > d1.xhat - x0 ? d1 : d0;\n\n    tooltip.show(d);\n  }\n\n  // add lines\n  var p = PD.append(\"path\")\n            .attr(\"class\", \"PD-lines\")\n            .style(\"fill\", \"none\")\n            .style(\"stroke\", pdLineColor)\n            .style(\"stroke-width\", pdLineSize)\n            .on('mouseover', function(d) {\n\n              // make mouseover line more visible\n              d3.select(this)\n                .style(\"stroke\", defaultColor)\n                .style(\"stroke-width\", pdLineSize*1.5);\n\n              // make line appear on top\n              this.parentNode.appendChild(this);\n\n              // show changed tooltip\n              showTooltip(d);\n            })\n            .on('mouseout', function(d) {\n\n              d3.select(this)\n                .style(\"stroke\", pdLineColor)\n                .style(\"stroke-width\", pdLineSize);\n\n              // hide changed tooltip\n              tooltip.hide(d);\n            });\n\n  // animate path\n  p.data([{\"xhat\":0, \"yhat\": 0}])\n   .attr(\"d\", line)\n   .transition()\n   .duration(TIME)\n   .attrTween(\"d\", function() {\n     var previous = d3.select(this).attr('d');\n     var current = line(lData);\n     return d3.interpolatePath(previous, current);\n   });\n\n  // add data for tooltip\n  p.data([lData]);\n\n  PD.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + pdPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average prediction\");\n\n  var description = PD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + pdPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction pdCategoricalPlot(variableName, bData, yMinMax, yMean, desc) {\n\n  var pdBarCount = bData.map(d => d.xhat).length;\n\n  var pdPlotHeight = SCALE_PLOT ? h : pdBarCount*pdBarWidth + (pdBarCount+1)*pdBarWidth/2,\n      pdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + pdPlotWidth])\n            .domain([yMinMax[0], yMinMax[1]]); // because it is flipped\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + pdPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + pdPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.xhat));\n\n  var xGrid = PD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + pdPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-pdPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = PD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-pdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = PD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 8) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  PD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(pdSubtitle); // variableName\n\n  PD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(pdTitle);\n\n  var bars = PD.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  var fullModel = yMean;\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipPD\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : pdStaticTooltipHtml(d, variableName, yMean));\n  PD.call(tooltip);\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"PD-bars\")\n      .attr(\"fill\", pdBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.xhat))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.yhat) < x(fullModel) ? x(d.yhat) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.yhat) - x(fullModel)));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".PD-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  PD.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  PD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + pdPlotWidth/2) + \",\" +\n                         (margin.top + pdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average prediction\");\n\n  var description = PD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + pdPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction adNumericalPlot(variableName, lData, mData, yMinMax, yMean, desc) {\n\n  var adPlotHeight = h,\n      adPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + adPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  AD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + adPlotWidth/2) + \" ,\" +\n                         (margin.top + adPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + adPlotHeight, margin.top - additionalHeight])\n            .domain([yMinMax[0], yMinMax[1]]);\n\n  var line = d3.line()\n               .x(d => x(d.xhat))\n               .y(d => y(d.yhat))\n               .curve(d3.curveMonotoneX);\n\n  AD.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(adSubtitle); // variableName\n\n  AD.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(adTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + adPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = AD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-adPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .attr(\"id\", \"tooltipPD\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : adStaticTooltipHtml(d, variableName, yMean));\n  AD.call(tooltip);\n\n  // function to find nearest point on the line\n  var bisectXhat = d3.bisector(d => d.xhat).right;\n\n  // show tooltip with info nearest to mouseover\n  function showTooltip(hover) {\n    var x0 = x.invert(d3.mouse(d3.event.currentTarget)[0]),\n        i = bisectXhat(hover, x0),\n        d0 = hover[i - 1],\n        d1 = hover[i],\n        d = x0 - d0.xhat > d1.xhat - x0 ? d1 : d0;\n\n    tooltip.show(d);\n  }\n\n  // add lines\n  var p = AD.append(\"path\")\n            .attr(\"class\", \"AD-lines\")\n            .style(\"fill\", \"none\")\n            .style(\"stroke\", adLineColor)\n            .style(\"stroke-width\", adLineSize)\n            .on('mouseover', function(d) {\n\n              // make mouseover line more visible\n              d3.select(this)\n                .style(\"stroke\", defaultColor)\n                .style(\"stroke-width\", adLineSize*1.5);\n\n              // make line appear on top\n              this.parentNode.appendChild(this);\n\n              // show changed tooltip\n              showTooltip(d);\n            })\n            .on('mouseout', function(d) {\n\n              d3.select(this)\n                .style(\"stroke\", adLineColor)\n                .style(\"stroke-width\", adLineSize);\n\n              // hide changed tooltip\n              tooltip.hide(d);\n            });\n\n  // animate path\n  p.data([{\"xhat\":0, \"yhat\": 0}])\n   .attr(\"d\", line)\n   .transition()\n   .duration(TIME)\n   .attrTween(\"d\", function() {\n     var previous = d3.select(this).attr('d');\n     var current = line(lData);\n     return d3.interpolatePath(previous, current);\n   });\n\n  // add data for tooltip\n  p.data([lData]);\n\n  AD.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + adPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"accumulated prediction\");\n\n  var description = AD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + adPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction adCategoricalPlot(variableName, bData, yMinMax, yMean, desc) {\n\n  var adBarCount = bData.map(d => d.xhat).length;\n\n  var adPlotHeight = SCALE_PLOT ? h : adBarCount*adBarWidth + (adBarCount+1)*adBarWidth/2,\n      adPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left,  margin.left + adPlotWidth])\n            .domain([yMinMax[0], yMinMax[1]]); // because it is flipped\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + adPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + adPlotHeight])\n            .padding(0.33)\n            .domain(bData.map(d => d.xhat));\n\n  var xGrid = AD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + adPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-adPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = AD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-adPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = AD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  AD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(adSubtitle); // variableName\n\n  AD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(adTitle);\n\n  var bars = AD.selectAll()\n               .data(bData)\n               .enter()\n               .append(\"g\");\n\n  var fullModel = 0; //yMean;\n    // make tooltip\n  var tooltip = d3.tip(WIDGET_ID)\n                  .attr(\"class\", \"d3-tip\")\n                  .html(d => d.type === \"desc\" ?\n                   descTooltipHtml(d) : adStaticTooltipHtml(d, variableName, yMean));\n  AD.call(tooltip);\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"AD-bars\")\n      .attr(\"fill\", adBarColor)\n      .attr(\"x\", d => x(fullModel))\n      .attr(\"y\", d => y(d.xhat))\n      .attr(\"height\", y.bandwidth())\n      .on('mouseover', tooltip.show)\n      .on('mouseout', tooltip.hide)\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => x(d.yhat) < x(fullModel) ? x(d.yhat) : x(fullModel))\n      .attr(\"width\", d => Math.abs(x(d.yhat) - x(fullModel)));;\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".AD-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  AD.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(fullModel))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(fullModel))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  AD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + adPlotWidth/2) + \",\" +\n                         (margin.top + adPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"accumulated prediction\");\n\n  var description = AD.append(\"g\")\n                      .attr(\"transform\", \"translate(\" +\n                            (margin.left + adPlotWidth - 4*margin.big - margin.small)\n                            + \",\" + (-margin.big) + \")\");\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"rect\")\n             .attr(\"class\", \"descriptionBox\")\n             .attr(\"width\", 2*margin.big)\n             .attr(\"height\", 2*margin.big)\n             .attr(\"rx\", 2*margin.big)\n             .attr(\"ry\", 2*margin.big)\n             .on('mouseover', tooltip.show)\n             .on('mouseout', tooltip.hide);\n\n  description.selectAll()\n             .data(desc)\n             .enter()\n             .append(\"text\")\n             .attr(\"class\", \"descriptionLabel\")\n             .attr(\"x\", 6)\n             .attr(\"dy\", \"1.05em\")\n             .text(\"D\")\n             .on('mouseover', function(d) {\n               tooltip.show(d);\n               d3.select(this).style(\"cursor\", \"default\");\n             })\n             .on('mouseout', tooltip.hide);\n}\n\nfunction fdNumericalPlot(variableName, dData, mData, nBin) {\n\n  var fdPlotHeight = h,\n      fdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + fdPlotWidth - 10])\n            .domain([mData[0], mData[1]]);\n\n  FD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + fdPlotWidth/2) + \" ,\" +\n                         (margin.top + fdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  FD.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + fdPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"count\");\n\n  var y = d3.scaleLinear()\n        .range([margin.top + fdPlotHeight - 5, margin.top]);\n\n  FD.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(fdSubtitle);\n\n  FD.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(fdTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = FD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + fdPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yAxis = FD.append(\"g\")\n                .attr(\"class\", \"axisLabel\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\");\n\n  var yGrid = FD.append(\"g\")\n                  .attr(\"class\", \"grid\")\n                  .attr(\"transform\", \"translate(\" + margin.left + \",0)\");\n\n  var slider = d3.sliderBottom()\n                 .min(d3.max([+nBin-10,2]))\n                 .max(d3.max([+nBin+10,12]))\n                 .width(fdPlotWidth/2 - 40) // fit exit button\n                 .ticks(8)\n                 .step(1)\n                 .default(nBin)\n                 .fill(fdBarColor)\n                 .on('onchange', val => updateHist(val));\n\n  var sliderg = FD.append(\"g\").call(slider);\n\n  sliderg.attr(\"transform\", \"translate(\" + (margin.left + fdPlotWidth/2 - margin.small)\n                            + \",\" + margin.small + \")\");\n\n  updateHist(+nBin);\n\n  function updateHist(nbin) {\n\n    var histogram = d3.histogram()\n                      .value(d => d[variableName])\n                      .domain(x.domain())\n                      .thresholds(nbin);\n\n    var bins = histogram(dData);\n\n    y.domain([0, d3.max(bins, d => d.length)]);\n\n    let yaF = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n    yAxis.call(yaF)\n         .call(g => g.select(\".domain\").remove());\n\n    yGrid.call(d3.axisLeft(y)\n                 .ticks(10)\n                 .tickSize(-fdPlotWidth)\n                 .tickFormat(\"\")\n               ).call(g => g.select(\".domain\").remove());\n\n    var bars = FD.selectAll(\"rect\")\n                 .data(bins);\n\n    bars.enter()\n        .append(\"rect\")\n        .attr(\"fill\", fdBarColor)\n        .merge(bars)\n        .attr(\"x\", d => x(d.x0))\n        .attr(\"y\", d => y(0))\n        .attr(\"height\", d => 0)\n        .attr(\"width\", d => x(d.x1) - x(d.x0))\n        .transition()\n        .duration(TIME)\n          .attr(\"y\", d => y(d.length))\n          .attr(\"height\", d => y(0) - y(d.length));\n\n    bars.exit()\n        .remove()\n  }\n}\n\nfunction fdCategoricalPlot(variableName, dData, xMinMax, mData) {\n\n  // equivalent of R table function\n  var tableData = d3.nest()\n                    .key(d => d[variableName])\n                    .rollup(v => v.length)\n                    .entries(dData);\n  // sort tableData\n  var tableDataSorted = [];\n  tableData.forEach(e => {\n    tableDataSorted[xMinMax.indexOf(e.key)] = e;\n  });\n\n  var fdBarCount = tableData.map(d => d.key).length;\n\n  var fdPlotHeight = SCALE_PLOT ? h : fdBarCount*fdBarWidth + (fdBarCount+1)*fdBarWidth/2,\n      fdPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + fdPlotWidth])\n            .domain([0, mData]);\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = FD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + fdPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + fdPlotHeight])\n            .padding(0.33)\n            .domain(xMinMax);\n\n  var xGrid = FD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + fdPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-fdPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = FD.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-fdPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = FD.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  FD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(fdSubtitle);\n\n  FD.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(fdTitle);\n\n  var bars = FD.selectAll()\n               .data(tableDataSorted)\n               .enter()\n               .append(\"g\");\n\n  // add bars\n  bars.append(\"rect\")\n      .attr(\"class\", \"FD-bars\")\n      .attr(\"fill\", fdBarColor)\n      .attr(\"x\", d => x(0))\n      .attr(\"y\", d => y(d.key))\n      .attr(\"height\", y.bandwidth())\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"width\", d => x(d.value)-x(0));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".FD-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  FD.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(0))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(0))\n    .attr(\"y2\", maximumY + y.bandwidth());\n\n  FD.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + fdPlotWidth/2) + \",\" +\n                         (margin.top + fdPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"count\");\n}\n\nfunction tvNumericalPlot(variableName, xData, xMinMax, yMinMax) {\n\n  var tvPlotHeight = h,\n      tvPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + tvPlotWidth - 10])\n            .domain(xMinMax);\n\n  TV.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + tvPlotWidth/2) + \" ,\" +\n                         (margin.top + tvPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + tvPlotHeight, margin.top - additionalHeight])\n            .domain(yMinMax);\n\n  TV.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(tvSubtitle);\n\n  TV.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(tvTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + tvPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = TV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-tvPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  TV.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + tvPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"target\");\n\n  TV.selectAll()\n    .data(xData)\n    .enter()\n    .append(\"circle\")\n    .attr(\"class\", \"point\")\n    .attr(\"cx\", d => x(d[variableName]))\n    .attr(\"cy\", d => y(d[\"_target_\"]))\n    .attr(\"r\", 0)\n    .style(\"fill\", tvPointColor)\n    .transition()\n    .duration(TIME)\n    .attr(\"r\", tvPointSize);\n}\n\nfunction tvCategoricalPlot(variableName, xData, xMinMax, yMinMax) {\n\n  var tvPlotHeight = h,\n      tvPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + tvPlotWidth])\n            .domain(yMinMax);\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + tvPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + tvPlotHeight])\n            .padding(0.33)\n            .domain(xMinMax);\n\n  var xGrid = TV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + tvPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-tvPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = TV.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-tvPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = TV.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  TV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(tvSubtitle);\n\n  TV.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(tvTitle);\n\n  TV.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + tvPlotWidth/2) + \" ,\" +\n                         (margin.top + tvPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"target\");\n\n  TV.selectAll()\n    .data(xData)\n    .enter()\n    .append(\"circle\")\n    .attr(\"class\", \"point\")\n    .attr(\"cx\", d => x(d[\"_target_\"]))\n    .attr(\"cy\", d => y(d[variableName]) + y.bandwidth()\n    - (0.1 + 0.8*Math.random()) * y.bandwidth())\n    .attr(\"r\", 0)\n    .style(\"fill\", tvPointColor)\n    .transition()\n    .duration(TIME)\n    .attr(\"r\", tvPointSize);\n}\n\nfunction atNumericalPlot(variableName, xData, xMinMax, yMinMax, yMean) {\n\n  var atPlotHeight = h,\n      atPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left + 10, margin.left + atPlotWidth - 10])\n            .domain(xMinMax);\n\n  AT.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + atPlotWidth/2) + \" ,\" +\n                         (margin.top + atPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(variableName);\n\n  var y = d3.scaleLinear()\n            .range([margin.top + atPlotHeight, margin.top - additionalHeight])\n            .domain(yMinMax);\n\n  AT.append(\"text\")\n    .attr(\"class\",\"smallTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .text(atSubtitle);\n\n  AT.append(\"text\")\n    .attr(\"class\", \"bigTitle\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .text(atTitle);\n\n  // find 5 nice ticks with max and min - do better than d3\n  var tickValues = getTickValues(x.domain());\n\n  var xAxis = d3.axisBottom(x)\n                .tickValues(tickValues)\n                .tickSizeInner(0)\n                .tickPadding(15);\n\n  xAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\"+ (margin.top + atPlotHeight) + \")\")\n            .call(xAxis);\n\n  var yGrid = AT.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .ticks(10)\n                        .tickSize(-atPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .ticks(5)\n                .tickSize(0);\n\n  yAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + margin.left + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  AT.append(\"text\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"transform\", \"rotate(-90)\")\n    .attr(\"y\", margin.left - margin.ytitle)\n    .attr(\"x\", -(margin.top + atPlotHeight/2))\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average target\");\n\n  AT.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(x.domain()[0]))\n    .attr(\"y1\", y(yMean))\n    .attr(\"x2\", x(x.domain()[1]))\n    .attr(\"y2\", y(yMean));\n\n  var lines = AT.selectAll()\n                .data(xData)\n                .enter()\n                .append(\"g\");\n\n  lines.append(\"line\")\n       .style(\"stroke\", atLineColor)\n       .style(\"stroke-width\", atLineSize)\n       .attr(\"x1\", d => x(d.x0))\n       .attr(\"x2\", d => x(d.x0))\n       .attr(\"y1\", d => y(d.y0))\n       .attr(\"y2\", d => y(d.y0))\n       .transition()\n       .duration(TIME/2)\n       .delay((d,i) => (i+1) * TIME/2)\n       .attr(\"x2\", d => x(d.x1))\n       .attr(\"y2\", d => y(d.y1))\n\n  lines.append(\"circle\")\n       .attr(\"cx\", d => x(d.x0))\n       .attr(\"cy\", d => y(d.y0))\n       .attr(\"r\", 0)\n       .style(\"fill\", atPointColor)\n       .transition()\n       .duration(TIME/2)\n       .delay((d,i) => i * TIME/2)\n       .attr(\"r\", atPointSize);\n\n  let lastPoint = xData.slice(-1)[0]\n\n  AT.append(\"circle\")\n    .attr(\"cx\", x(lastPoint.x1))\n    .attr(\"cy\", y(lastPoint.y1))\n    .attr(\"r\", 0)\n    .style(\"fill\", atPointColor)\n    .transition()\n    .duration(TIME/2)\n    .delay(xData.length * TIME/2)\n    .attr(\"r\", atPointSize);\n}\n\nfunction atCategoricalPlot(variableName, xData, xMinMax, yMinMax, yMean) {\n\n  var atBarCount = xData.length;\n\n  var atPlotHeight = SCALE_PLOT ? h : atBarCount*atBarWidth + (atBarCount+1)*atBarWidth/2,\n      atPlotWidth = w;\n\n  var x = d3.scaleLinear()\n            .range([margin.left, margin.left + atPlotWidth])\n            .domain(yMinMax);\n\n  var xAxis = d3.axisBottom(x)\n                .ticks(5)\n                .tickSize(0);\n\n  xAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\", \"translate(0,\" + (margin.top + atPlotHeight) + \")\")\n            .call(xAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  var y = d3.scaleBand()\n            .rangeRound([margin.top - additionalHeight, margin.top + atPlotHeight])\n            .padding(0.33)\n            .domain(xMinMax);\n\n  var xGrid = AT.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(0,\" + (margin.top + atPlotHeight) + \")\")\n                .call(d3.axisBottom(x)\n                        .ticks(10)\n                        .tickSize(-atPlotHeight - additionalHeight)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yGrid = AT.append(\"g\")\n                .attr(\"class\", \"grid\")\n                .attr(\"transform\", \"translate(\" + margin.left + \",0)\")\n                .call(d3.axisLeft(y)\n                        .tickSize(-atPlotWidth)\n                        .tickFormat(\"\")\n                ).call(g => g.select(\".domain\").remove());\n\n  var yAxis = d3.axisLeft(y)\n                .tickSize(0);\n\n  yAxis = AT.append(\"g\")\n            .attr(\"class\", \"axisLabel\")\n            .attr(\"transform\",\"translate(\" + (margin.left - 10) + \",0)\")\n            .call(yAxis)\n            .call(g => g.select(\".domain\").remove());\n\n  yAxis.selectAll(\"text\").call(wrapText, margin.left - 15);\n\n  AT.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 15)\n    .attr(\"class\", \"smallTitle\")\n    .text(atSubtitle);\n\n  AT.append(\"text\")\n    .attr(\"x\", margin.left)\n    .attr(\"y\", margin.top - 40)\n    .attr(\"class\", \"bigTitle\")\n    .text(atTitle);\n\n  AT.append(\"text\")\n    .attr(\"transform\",\n          \"translate(\" + (margin.left + atPlotWidth/2) + \" ,\" +\n                         (margin.top + atPlotHeight + 45) + \")\")\n    .attr(\"class\", \"axisTitle\")\n    .attr(\"text-anchor\", \"middle\")\n    .text(\"average target\");\n\n  var bars = AT.selectAll()\n               .data(xData)\n               .enter()\n               .append(\"g\");\n\n  bars.append(\"rect\")\n      .attr(\"class\", \"AT-bars\")\n      .attr(\"fill\", atBarColor)\n      .attr(\"x\", d => x(yMean))\n      .attr(\"y\", d => y(d.y))\n      .attr(\"height\", y.bandwidth())\n      .transition()\n      .duration(TIME)\n      .delay((d,i) => i * TIME)\n      .attr(\"x\", d => d.sign == 1 ? x(yMean) : x(d.x0))\n      .attr(\"width\", d => Math.abs(x(d.x0) - x(yMean)));\n\n  // add intercept line\n  var minimumY = Number.MAX_VALUE;\n  var maximumY = Number.MIN_VALUE;\n\n  bars.selectAll(\".AT-bars\").each(function() {\n      if (+this.getAttribute('y') < minimumY) {\n        minimumY = +this.getAttribute('y');\n      }\n      if (+this.getAttribute('y') > maximumY) {\n        maximumY = +this.getAttribute('y');\n      }\n    });\n\n  AT.append(\"line\")\n    .attr(\"class\", \"interceptLine\")\n    .attr(\"x1\", x(yMean))\n    .attr(\"y1\", minimumY)\n    .attr(\"x2\", x(yMean))\n    .attr(\"y2\", maximumY + y.bandwidth());\n}\n\n/// event plot functions\n\nfunction updatePlots(event, variableName, observationId, plotId) {\n  /// main plot controller, not used arguments are passed as null\n\n  switch (event) {\n    case \"observationChange\":\n      CLICKED_OBSERVATION_ID = observationId;\n      removePlots([\"BD\", \"SV\", \"CP\"]);\n      generatePlots([\"BD\", \"SV\", \"CP\"]);\n      break;\n\n    case \"variableChange\":\n      // safeguard\n      if (variableName == \"prediction\" || variableName == \"intercept\" ||\n          variableName == \"other\") { return; }\n      CLICKED_VARIABLE_NAME = variableName;\n      removePlots([\"CP\", \"PD\", \"AD\", \"FD\", \"TV\", \"AT\"]);\n      generatePlots([\"CP\", \"PD\", \"AD\", \"FD\", \"TV\", \"AT\"]);\n      break;\n\n    case \"chosePlot\":\n      removePlots([plotId]);\n      generatePlots([plotId]);\n      break;\n\n    default:\n      console.log(\"Unknown event in updatePlots \" +\n                  [event,variableName, observationId, plotId]);\n      break;\n  }\n}\n\nfunction removePlots(arrPlotId) {\n  /// check if there is something to delete and get rid of it (with tooltip)\n  arrPlotId.forEach((id) => {\n    if (!svg.select(\"#\"+id).selectAll(\"*\").empty()) {\n      svg.select(\"#\"+id).selectAll(\"*\").remove();\n      d3.select(\"body\").select(\"#tooltip\"+id).remove();\n    }\n  });\n}\n\nfunction generatePlots(arrPlotId) {\n  /// check if the plot got removed and make new one\n  arrPlotId.forEach((id) => {\n    if (svg.select(\"#\"+id).selectAll(\"*\").empty()) {\n      // execute plot function\n      mapIdPlotFunction[id]();\n    }\n  });\n}\n\n/* R2D3 Source File:   */\n//:\\\\\\ here are functions for tooltips HTML //:\\\\\\\n\nfunction bdTooltipHtml(d) {\n  var temp = \"<center>\";\n  temp += d.tooltipText;\n  temp += \"<\/center>\";\n  return temp;\n}\n\nfunction cpStaticTooltipHtml(d) {\n  // function formats tooltip text\n  var temp = \"\";\n  for (var [k, v] of Object.entries(d)) {\n    if (k === \"yhat\") {\n      k = \"prediction\";\n      temp += \"<center>\" +  k + \": \" + v + \"<\/br>\";\n      temp += \"<\/br>\";\n    } else {\n      temp += \"<center>\" +  k + \": \" + v + \"<\/br>\";\n    }\n  }\n  return temp;\n}\n\nfunction cpChangedTooltipHtml(d, addData) {\n  // function formats tooltip text with update in red\n  var temp = \"<center>\";\n  for (var [k, v] of Object.entries(addData)) {\n    if (k === \"yhat\") {\n      temp += \"prediction:<\/br>\";\n      temp += \"- before\" + \": \" + v + \"<\/br>\";\n      temp += \"- after\" + \": \" + \"<font color = \\\"red\\\">\" + d.yhat + \"<\/br><\/font>\";\n      temp += \"<\/br>\";\n    } else if (k === d.vname) {\n      temp +=  k + \": \" + \"<font color = \\\"red\\\">\"  +  d.xhat + \"<\/br><\/font>\";\n    } else {\n      temp += k + \": \" + v + \"<\/br>\";\n    }\n  }\n  temp += \"<\/center>\";\n  return temp;\n}\n\nfunction fiStaticTooltipHtml(d) {\n    let sign;\n    if (d.dropout_loss > d.full_model) sign = \"+\"; else sign = \"\";\n    var temp =  \"<center>\" + \"model loss after feature \" + d.variable\n      + \"<\/br>\" + \"<center>\" +\n      \" is permuted: \" +  Math.round(d.dropout_loss * 1000)/1000\n      + \"<\/br>\" + \"<center>\" + \"drop-out loss change: \" +\n      sign + Math.round((d.dropout_loss-d.full_model)*1000)/1000;\n    return temp;\n}\n\nfunction pdStaticTooltipHtml(d, variableName, yMean) {\n  // function formats tooltip text\n  var temp = \"\";\n  for (var [k, v] of Object.entries(d)) {\n    switch(k){\n      case \"xhat\":\n        temp += \"<center>\" +  variableName  + \": \" + v + \"<\/br>\";\n        break;\n      case \"yhat\":\n        temp += \"<center>\" +  \"average prediction\"  + \": \" + v + \"<\/br>\";\n        break;\n      case \"vname\":\n        break;\n      default:\n        temp += \"<center>\" +  k  + \": \" + v + \"<\/br>\";\n        break;\n    }\n  }\n\n  temp += \"<\/br><center>\" +\n          \"mean observation prediction:\" +\n          \"<\/br>\" + yMean + \"<\/br>\";\n  return temp;\n}\n\nfunction adStaticTooltipHtml(d, variableName, yMean) {\n  // function formats tooltip text\n  var temp = \"\";\n  for (var [k, v] of Object.entries(d)) {\n    switch(k){\n      case \"xhat\":\n        temp += \"<center>\" +  variableName  + \": \" + v + \"<\/br>\";\n        break;\n      case \"yhat\":\n        temp += \"<center>\" +  \"accumulated prediction\"  + \": \" + v + \"<\/br>\";\n        break;\n      case \"vname\":\n        break;\n      default:\n        temp += \"<center>\" +  k  + \": \" + v + \"<\/br>\";\n        break;\n    }\n  }\n\n  temp += \"<\/br><center>\" +\n          \"mean observation prediction:\" +\n          \"<\/br>\" + yMean + \"<\/br>\";\n  return temp;\n}\n\nfunction descTooltipHtml(d) {\n  var temp = \"<center>\";\n  temp += d.text;\n  temp += \"<\/center>\";\n  return temp;\n}\nsvg = d3.select(svg.node());\n/* R2D3 Source File:   */\n///:\\\\\\ --------- main modelStudio file --------- ///:\\\\\\\n///:\\\\\\ (for myself to remember):                 ///:\\\\\\\n///:\\\\\\ use CAPITAL for global variables and 'g'  ///:\\\\\\\n///:\\\\\\ use let where possible                    ///:\\\\\\\n///:\\\\\\ use class for css and id for select       ///:\\\\\\\n///:\\\\\\ use lambdas and ifelse where possible     ///:\\\\\\\n///:\\\\\\ ----------------------------------------- ///:\\\\\\\n\n/// prevent modelStudio from reloading onResize\nr2d3.onResize(function() {\n  return;\n});\n\n/// load all data\nvar obsData = data[0],\n    fiData = data[1], pdData = data[2],\n    adData = data[3], fdData = data[4],\n    tvData = data[4], atData = data[5];\n\n/// load options\nvar TIME = options.time,\n    modelName = options.model_name,\n    variableNames = options.variable_names,\n    dim = options.facet_dim,\n    footerText = options.footer_text,\n    dropDownData = options.drop_down_data,\n    EDA = options.eda,\n    WIDGET_ID = options.widget_id,\n    SCALE_PLOT = options.scale_plot,\n    SHOW_BOXPLOT = options.show_boxplot,\n    SHOW_SUBTITLE = options.show_subtitle,\n    subTitle = options.subtitle || modelName,\n    msTitle = options.ms_title,\n    barWidth = options.bar_width,\n    lineSize = options.line_size,\n    pointSize = options.point_size,\n    barColor = options.bar_color,\n    lineColor = options.line_color,\n    pointColor = options.point_color,\n    positiveColor = options.positive_color,\n    negativeColor = options.negative_color,\n    defaultColor = options.default_color,\n    bdTitle = options.bd_title,\n    bdSubtitle = options.bd_subtitle || subTitle,\n    bdBarWidth = options.bd_bar_width || barWidth,\n    bdPositiveColor = options.bd_positive_color || positiveColor,\n    bdNegativeColor = options.bd_negative_color || negativeColor,\n    bdDefaultColor = options.bd_default_color || defaultColor,\n    svTitle = options.sv_title,\n    svSubtitle = options.sv_subtitle || subTitle,\n    svBarWidth = options.sv_bar_width || barWidth,\n    svPositiveColor = options.sv_positive_color || positiveColor,\n    svNegativeColor = options.sv_negative_color || negativeColor,\n    cpTitle = options.cp_title,\n    cpSubtitle = options.cp_subtitle || subTitle,\n    cpBarWidth = options.cp_bar_width || barWidth,\n    cpLineSize = options.cp_line_size || lineSize,\n    cpPointSize = options.cp_point_size || pointSize,\n    cpBarColor = options.cp_bar_color || barColor,\n    cpLineColor = options.cp_line_color || lineColor,\n    cpPointColor = options.cp_point_color || pointColor,\n    fiTitle = options.fi_title,\n    fiSubtitle = options.fi_subtitle || subTitle,\n    fiBarWidth = options.fi_bar_width || barWidth,\n    fiBarColor = options.fi_bar_color || barColor,\n    pdTitle = options.pd_title,\n    pdSubtitle = options.pd_subtitle || subTitle,\n    pdBarWidth = options.pd_bar_width || barWidth,\n    pdLineSize = options.pd_line_size || lineSize,\n    pdBarColor = options.pd_bar_color || barColor,\n    pdLineColor = options.pd_line_color || lineColor,\n    adTitle = options.ad_title,\n    adSubtitle = options.ad_subtitle || subTitle,\n    adBarWidth = options.ad_bar_width || barWidth,\n    adLineSize = options.ad_line_size || lineSize,\n    adBarColor = options.ad_bar_color || barColor,\n    adLineColor = options.ad_line_color || lineColor,\n    fdTitle = options.fd_title,\n    fdSubtitle = options.fd_subtitle || subTitle,\n    fdBarWidth = options.fd_bar_width || barWidth,\n    fdBarColor = options.fd_bar_color || barColor,\n    tvTitle = options.tv_title,\n    tvSubtitle = options.tv_subtitle || subTitle,\n    tvPointSize = options.tv_point_size || pointSize,\n    tvPointColor = options.tv_point_color || pointColor,\n    atTitle = options.at_title,\n    atSubtitle = options.at_subtitle || subTitle,\n    atBarWidth = options.at_bar_width || barWidth,\n    atLineSize = options.at_line_size || lineSize,\n    atPointSize = options.at_point_size || pointSize,\n    atBarColor = options.at_bar_color || barColor,\n    atLineColor = options.at_line_color || lineColor,\n    atPointColor = options.at_point_color || pointColor;\n\n/// for observation choice\nvar observationIds = Object.keys(obsData);\n\n/// set global variables\nvar CLICKED_VARIABLE_NAME = variableNames[0],\n    CLICKED_OBSERVATION_ID = observationIds[0],\n    IS_BUTTON_CLICKED = false;\n\n/// set dimensions\nvar margin = {top: options.margin_top, right: options.margin_right,\n              bottom: options.margin_bottom, left: options.margin_left,\n              inner: options.margin_inner,\n              small: options.margin_small, big: options.margin_big,\n              ytitle: options.margin_ytitle};\n\nvar w = options.w, h = options.h;\n\nvar plotWidth = w + margin.left + margin.right,\n    plotHeight = h + margin.top + margin.bottom;\n\nvar studioMargin = {top: 50, bottom: 50},\n    studioWidth = dim[1]*plotWidth,\n    studioHeight = studioMargin.top + dim[0]*plotHeight + studioMargin.bottom;\n\n/// should subtitle be displayed and plot height be extended\nvar additionalHeight = 0;\nif (!SHOW_SUBTITLE) {\n  additionalHeight = 25;\n  bdSubtitle = null;\n  svSubtitle = null;\n  cpSubtitle = null;\n  fiSubtitle = null;\n  pdSubtitle = null;\n  adSubtitle = null;\n  fdSubtitle = null;\n  tvSubtitle = null;\n  atSubtitle = null;\n}\n\n/// for plot chosing\nvar notVisiblePlots = EDA ?\n                       [{id:\"BD\", text: bdTitle + \" [Local]\"},\n                       {id:\"SV\", text: svTitle + \" [Local]\"},\n                       {id:\"CP\", text: cpTitle + \" [Local]\"},\n                       {id:\"FI\", text: fiTitle + \" [Global]\"},\n                       {id:\"PD\", text: pdTitle + \" [Global]\"},\n                       {id:\"AD\", text: adTitle + \" [Global]\"},\n                       {id:\"FD\", text: fdTitle + \" [EDA]\"},\n                       {id:\"TV\", text: tvTitle + \" [EDA]\"},\n                       {id:\"AT\", text: atTitle + \" [EDA]\"}] :\n                       [{id:\"BD\", text: bdTitle + \" [Local]\"},\n                       {id:\"SV\", text: svTitle + \" [Local]\"},\n                       {id:\"CP\", text: cpTitle + \" [Local]\"},\n                       {id:\"FI\", text: fiTitle + \" [Global]\"},\n                       {id:\"PD\", text: pdTitle + \" [Global]\"},\n                       {id:\"AD\", text: adTitle + \" [Global]\"}];\n\nvar visiblePlots = [];\n\n/// generate facet x,y coordinates with grid index\nvar facetData = [], id = 0;\nfor (let i = 0; i < dim[0]; i++) {\n  for (let j = 0; j < dim[1]; j++) {\n    facetData.push({x: 0 + j*plotWidth,\n                    y: studioMargin.top + i*plotHeight,\n                    index: id});\n    id++;\n  }\n}\n\n///:\\\\\\\ninitializeStudio();\n///:\\\\\\\n\nfunction initializeStudio() {\n  /// this function initializes modelStudio (used only once, at start)\n\n  // top decorations\n  var TOP_G = svg.append(\"g\")\n                 .attr(\"class\", \"TOP_G\");\n\n  TOP_G.append(\"text\")\n       .attr(\"class\", \"mainTitle\")\n       .attr(\"x\", 15)\n       .attr(\"y\", 30)\n       .text(msTitle);\n\n  TOP_G.append(\"line\")\n       .attr(\"class\", \"mainLine\")\n       .attr(\"x1\", 10)\n       .attr(\"x2\", studioWidth - 10)\n       .attr(\"y1\", studioMargin.top - margin.big)\n       .attr(\"y2\", studioMargin.top - margin.big);\n\n  ///:\\\\\\ add select observation input\n  let tempW = calculateTextWidth(dropDownData.map(e => e.text))*1.6 + 18; // 15px bold 600\n\n  // center the ms\n  d3.select(\"#\" + WIDGET_ID)\n    .style('position', 'absolute')\n    .style('left', 0)\n    .style('right', 0)\n    .style('margin', 'auto');\n\n  var input = d3.select(\"#\" + WIDGET_ID)\n                .append(\"select\")\n                .attr(\"id\",\"input\")\n                .style(\"position\", \"absolute\") // to make input appear on top\n                .style(\"left\", (studioWidth - margin.big - tempW)+\"px\")\n                .style(\"top\", -studioHeight + 180)\n                .style(\"font-size\", \"15px\")\n                .style(\"font-weight\", 600)\n                .style(\"color\", \"#371ea3\");\n\n  input.selectAll()\n       .data(dropDownData)\n       .enter()\n       .append(\"option\")\n       .attr(\"value\", d => d.id)\n       .text(d => d.text)\n       .style(\"font-size\", \"15px\")\n       .style(\"font-weight\", 600)\n       .style(\"color\", \"#371ea3\");\n\n  input.on(\"change\", function() {\n\n    // update observation specific plots\n    updatePlots(event = \"observationChange\",\n                variableName = null,\n                observationId = this.value,\n                plotId = null);\n  });\n  ///:\\\\\\\n\n  // bottom decorations\n  var BOTTOM_G = svg.append(\"g\")\n                    .attr(\"class\", \"BOTTOM_G\");\n\n  BOTTOM_G.append(\"text\")\n          .attr(\"class\", \"footerTitle\")\n          .attr(\"x\", studioWidth - 15 - getTextWidth(footerText, 12, 'Fira Sans, sans-serif'))\n          .attr(\"y\", studioHeight - studioMargin.bottom + 25)\n          .text(footerText);\n\n  BOTTOM_G.append(\"line\")\n          .attr(\"class\", \"footerLine\")\n          .attr(\"x1\", 10)\n          .attr(\"x2\", studioWidth - 10)\n          .attr(\"y1\", studioHeight - studioMargin.bottom + margin.big)\n          .attr(\"y2\", studioHeight - studioMargin.bottom + margin.big);\n\n  // middle buttons\n  var MIDDLE_G = svg.append(\"g\")\n                    .attr(\"class\", \"MIDDLE_G\");\n\n  var enterChoiceButtons = MIDDLE_G.selectAll()\n                                   .data(facetData)\n                                   .enter()\n                                   .append(\"rect\")\n                                   .attr(\"class\", \"enterChoiceButton\")\n                                   .attr(\"id\", (d,i) => \"enterChoiceButton\"+i)\n                                   .attr(\"width\", plotWidth)\n                                   .attr(\"height\", plotHeight)\n                                   .attr(\"x\", d => d.x)\n                                   .attr(\"y\", d => d.y);\n\n  // add `+` to buttons\n  MIDDLE_G.selectAll()\n          .data(facetData)\n          .enter()\n          .append(\"line\")\n          .attr(\"class\", \"mainLine\")\n          .attr(\"id\", (d,i) => \"enterChoiceButton\"+i)\n          .attr(\"x1\", d => d.x + plotWidth/2)\n          .attr(\"x2\", d => d.x + plotWidth/2)\n          .attr(\"y1\", d => d.y + plotHeight/2 - margin.big)\n          .attr(\"y2\", d => d.y + plotHeight/2 + margin.big);\n\n  MIDDLE_G.selectAll()\n          .data(facetData)\n          .enter()\n          .append(\"line\")\n          .attr(\"class\", \"mainLine\")\n          .attr(\"id\", (d,i) => \"enterChoiceButton\"+i)\n          .attr(\"x1\", d => d.x + plotWidth/2 - margin.big)\n          .attr(\"x2\", d => d.x + plotWidth/2 + margin.big)\n          .attr(\"y1\", d => d.y + plotHeight/2)\n          .attr(\"y2\", d => d.y + plotHeight/2);\n\n  // events\n  enterChoiceButtons.on('mouseover', function() { d3.select(this).style(\"opacity\", 1);})\n                    .on('mouseout', function() { d3.select(this).style(\"opacity\", 0.5);})\n                    .on(\"click\", function(d,i) {\n\n                      // block other buttons\n                      if (!IS_BUTTON_CLICKED) {\n                        IS_BUTTON_CLICKED = true;\n                        // allow for plot choice or exit choice\n                        showChoiceButtons(this, i);\n                      }\n                    });\n\n  var exitChoiceButtons = MIDDLE_G.selectAll()\n                                  .data(facetData)\n                                  .enter()\n                                  .append(\"rect\")\n                                  .attr(\"class\", \"exitChoiceButton\")\n                                  .attr(\"id\", (d,i) => \"exitChoiceButton\"+i)\n                                  .attr(\"width\", plotWidth - margin.big)\n                                  .attr(\"height\", plotHeight - margin.big)\n                                  .attr(\"x\", d => d.x + margin.small)\n                                  .attr(\"y\", d => d.y + margin.small)\n                                  .style(\"visibility\", \"hidden\");\n\n  // events\n  exitChoiceButtons.on(\"click\", function(d,i) {\n\n                     // delete chosePlotButtons\n                     svg.select(\"#chosePlotButton\"+i).remove();\n                     // hide this button\n                     svg.select(\"#exitChoiceButton\"+i).style(\"visibility\", \"hidden\");\n                     // show enterChoiceButton\n                     svg.selectAll(\"#enterChoiceButton\"+i).style(\"visibility\", \"visible\");\n                     // let the user click other buttons\n                     IS_BUTTON_CLICKED = false;\n                   });\n\n  var exitPlotButtons = MIDDLE_G.selectAll()\n                                .data(facetData)\n                                .enter()\n                                .append(\"g\")\n                                .attr(\"id\", (d,i) => \"exitPlotButton\"+i)\n                                .attr(\"transform\", d => \"translate(\" +\n                                (d.x + margin.left + w - 2*margin.big) + \",\" +\n                                (d.y + margin.small) + \")\")\n                                .style(\"visibility\", \"hidden\");\n\n  exitPlotButtons.append(\"rect\")\n                 .attr(\"class\", \"descriptionBox\")\n                 .attr(\"width\", 2*margin.big)\n                 .attr(\"height\", 2*margin.big)\n                 .attr(\"rx\", 2*margin.big)\n                 .attr(\"ry\", 2*margin.big);\n\n  exitPlotButtons.append(\"text\")\n                 .attr(\"class\", \"descriptionLabel\")\n                 .attr(\"dy\", \"1.05em\")\n                 .attr(\"x\", 6)\n                 .text(\"X\");\n\n  // events\n  exitPlotButtons.selectAll(\"*\")\n                 .on(\"mouseover\", function() { d3.select(this).style(\"cursor\", \"pointer\");})\n                 .on(\"mouseout\", function() { d3.select(this).style(\"cursor\", \"auto\");})\n                 .on(\"click\", function(d) {\n\n                   let j = d.index;\n                   // available only when no enterPlotButton clicked\n                   if (!IS_BUTTON_CLICKED) {\n                     // which plot is in this place?\n                     let temp = visiblePlots.filter(el => el.index == j)[0];\n                     // add this plot to not visible\n                     notVisiblePlots.push({text: temp.text, id: temp.id});\n                     // delete this plot from visible\n                     visiblePlots = visiblePlots.filter(el => el.id !== temp.id);\n                     // hide this button\n                     svg.select(\"#exitPlotButton\"+j).style(\"visibility\", \"hidden\");\n                     // hide plot\n                     svg.select(\"#\"+temp.id)\n                        .style(\"visibility\", \"hidden\");\n                     // show enterChoiceButton\n                     svg.selectAll(\"#enterChoiceButton\"+j).style(\"visibility\", \"visible\");\n                   }\n                 });\n\n  function showChoiceButtons(object, j) {\n    /// chosePlotButtons controller\n\n    // hide this 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            .text(d => d.text)\n             .on(\"mouseover\", function() { d3.select(this).style(\"cursor\", \"pointer\");})\n             .on(\"mouseout\", function() { d3.select(this).style(\"cursor\", \"auto\");})\n             .on(\"click\", function(d) {\n\n               // when clicking on text, hide exitChoiceButton\n               svg.selectAll(\"#exitChoiceButton\"+j).style(\"visibility\", \"hidden\");\n               // delete chosePlotButtons\n               svg.select(\"#chosePlotButton\"+j).remove();\n               // add this plot to visible\n               visiblePlots.push({text: d.text, id: this.id, index: j });\n               // delete this plot from not visible\n               notVisiblePlots = notVisiblePlots.filter(el => el.id !== this.id);\n\n               updatePlots(event = \"chosePlot\",\n                           variableName = null,\n                           observationId = null,\n                           plotId = this.id);\n\n               // show plot and move it to the right place\n               // margin.big added because translate 0 is -10\n               svg.select(\"#\"+this.id)\n                  .attr(\"transform\",\"translate(\" + (x) + \",\" + (y + 1.5*margin.big) + \")\")\n                  .style(\"visibility\", \"visible\");\n\n               // make exit button visible\n               svg.select(\"#exitPlotButton\"+j).style(\"visibility\", \"visible\");\n\n               // let the user click other buttons\n               IS_BUTTON_CLICKED = false;\n             });\n  }\n\n  if (facetData.length >= 1) {\n    svg.selectAll('.enterChoiceButton').filter('#enterChoiceButton0').dispatch('click');\n    svg.select(\"#chosePlotButton0\").select(\"#BD\").dispatch('click');\n  }\n\n  if (facetData.length >= 2) {\n    svg.selectAll('.enterChoiceButton').filter('#enterChoiceButton1').dispatch('click');\n  }\n}\n};","style":"/* R2D3 Source File:   */\ntext {\n  font-family:'Fira Sans';\n  font-style:normal;\n  fill: 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+<script type="application/htmlwidget-sizing" data-for="widget-885d187ac1050eef43a1e9da6779043f">{"viewer":{"width":1090,"height":900,"padding":10,"fill":false},"browser":{"width":1090,"height":900,"padding":10,"fill":false}}</script>
 </body>
 </html>
diff --git a/vignettes/vignette_examples.Rmd b/vignettes/vignette_examples.Rmd
index 400cd4b..9b42e54 100644
--- a/vignettes/vignette_examples.Rmd
+++ b/vignettes/vignette_examples.Rmd
@@ -53,7 +53,7 @@ test <- data[-index, ]
 # mlr ClassifTask takes target as factor
 train$survived <- as.factor(train$survived)
 
-# prepare the model
+# fit a model
 task <- makeClassifTask(id = "titanic",
                         data = train,
                         target = "survived")
@@ -97,7 +97,7 @@ test <- data[-index, ]
 # mlr3 TaskClassif takes target as factor
 train$survived <- as.factor(train$survived)
 
-# prepare the model
+# fit a model
 task <- TaskClassif$new(id = "titanic",
                         backend = train,
                         target = "survived")
@@ -140,7 +140,7 @@ test <- data[-index, ]
 train_matrix <- model.matrix(survived ~.-1, train)
 test_matrix <- model.matrix(survived ~.-1, test)
 
-# prepare the model
+# fit a model
 xgb_matrix <- xgb.DMatrix(train_matrix, label = train$survived)
 params <- list(eta = 0.01, subsample = 0.6, max_depth = 7, min_child_weight = 3,
                objective = "binary:logistic", eval_metric = "auc")
@@ -180,7 +180,7 @@ test <- data[-index, ]
 # caret train takes target as factor
 train$survived <- as.factor(train$survived)
 
-# prepare the model
+# fit a model
 cv <- trainControl(method = "repeatedcv",
                    number = 3,
                    repeats = 10)
@@ -205,111 +205,142 @@ modelStudio(explainer,
             new_observation)
 ```
 
-### h2o
-
-TBD
+### h2o [dashboard](https://modeloriented.github.io/modelStudio/h2o.html)
 
 ```{r eval = FALSE}
+# load packages and data
+library(h2o)
 library(DALEXtra)
+library(modelStudio)
+
+data <- DALEX::titanic_imputed
+
+# init h2o
+h2o::h2o.init()
+
+# split the data
+h2o_split <- h2o.splitFrame(as.h2o(data))
+train <- h2o_split[[1]]
+test <- as.data.frame(h2o_split[[2]])
+
+# h2o automl takes target as factor
+train$survived <- as.factor(train$survived)
+
+# fit a model
+automl <- h2o.automl(y = "survived",
+                     training_frame = train,
+                     max_runtime_secs = 30)
+model <- automl@leader
 
-explain_h2o()
+# stop h2o progress printing
+h2o.no_progress()
+
+# create an explainer for the model
+explainer <- explain_h2o(model,
+                         data = test,
+                         y = test$survived,
+                         label = "h2o")
+
+# pick observations
+new_observation <- test[1:2, ]
+rownames(new_observation) <- c("id1", "id2")
+
+# make a studio for the model
+modelStudio(explainer,
+            new_observation,
+            B = 5)
 
+# shutdown h2o
+h2o::h2o.shutdown(prompt = FALSE)
 ```
 
-## Python
 
-### scikit-learn [dashboard](https://modeloriented.github.io/modelStudio/scikit-learn.html)
+## Python
 
-Use `pickle` Python module and `reticulate` R package to easily produce modelStudio for scikit-learn model.
+Use `pickle` Python module and `reticulate` R package to easily make a studio for a model.
 
-In this example we fit a Pipeline MLPClassifier on the titanic data. First install the `dalex` package.
+Install the `dalex` package.
 
 ```{bash, eval=FALSE, engine="sh"}
 pip3 install dalex --force
 ```
 
-Make an explainer object in Python:
+### scikit-learn [dashboard](https://modeloriented.github.io/modelStudio/scikit-learn.html)
+
+In this example we will fit a Pipeline MLPClassifier model on titanic data.
+
+First, use `dalex` in Python:
 
 ```{r eval = FALSE}
-# import modules
+# load packages and data
 import dalex as dx
-from dalex import datasets
 
-from sklearn.neural_network import MLPClassifier
-from sklearn.preprocessing import StandardScaler, LabelEncoder, OneHotEncoder
-from sklearn.impute import SimpleImputer
+from sklearn.model_selection import train_test_split
 from sklearn.pipeline import Pipeline
-from sklearn.tree import DecisionTreeRegressor
+from sklearn.preprocessing import StandardScaler, OneHotEncoder
+from sklearn.impute import SimpleImputer
 from sklearn.compose import ColumnTransformer
+from sklearn.neural_network import MLPClassifier
 
-# load the data
-data = datasets.load_titanic()
+data = dx.datasets.load_titanic()
 X = data.drop(columns='survived')
 y = data.survived
 
-# make a pipeline model
+# split the data
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=1)
+
+# fit a pipeline model
 numeric_features = ['age', 'fare', 'sibsp', 'parch']
-numeric_transformer = Pipeline(steps=[
+numeric_transformer = Pipeline(
+  steps=[
     ('imputer', SimpleImputer(strategy='median')),
-    ('scaler', StandardScaler())])
-
+    ('scaler', StandardScaler())
+    ]
+)
 categorical_features = ['gender', 'class', 'embarked']
-categorical_transformer = Pipeline(steps=[
+categorical_transformer = Pipeline(
+  steps=[
     ('imputer', SimpleImputer(strategy='constant', fill_value='missing')),
-    ('onehot', OneHotEncoder(handle_unknown='ignore'))])
+    ('onehot', OneHotEncoder(handle_unknown='ignore'))
+    ]
+)
 
 preprocessor = ColumnTransformer(
-    transformers=[
-        ('num', numeric_transformer, numeric_features),
-        ('cat', categorical_transformer, categorical_features)])
-
-
-clf = Pipeline(steps=[('preprocessor', preprocessor),
-                      ('classifier', MLPClassifier(hidden_layer_sizes=(150,100,50),
-                                                   max_iter=500, random_state=0))])
+  transformers=[
+    ('num', numeric_transformer, numeric_features),
+    ('cat', categorical_transformer, categorical_features)
+    ]
+)
 
-clf.fit(X, y)
+model = Pipeline(
+  steps=[
+    ('preprocessor', preprocessor),
+    ('classifier', MLPClassifier(hidden_layer_sizes=(150,100,50), max_iter=500, random_state=0))
+    ]
+)
+model.fit(X_train, y_train)
 
-# make an explainer
-explainer = dx.Explainer(clf, X, y)
+# create an explainer for the model
+explainer = dx.Explainer(model, X_test, y_test, label = 'scikit-learn')
 
-# remove these functions before dump
+#! remove residual_function before dump !
 explainer.residual_function = None
-explainer.predict_function = None
 
 # pack the explainer into a pickle file
-import pickle        
-pickle_out = open("explainer_titanic.pickle","wb")
+import pickle
+pickle_out = open("explainer_scikitlearn.pickle","wb")
 pickle.dump(explainer, pickle_out)
-pickle_out.close()     
+pickle_out.close()
 ```
 
-Then use modelStudio in R:
+Then, use `modelStudio` in R:
 
 ```{r eval = FALSE}
-# use reticulate to load the explainer from a pickle file
+# load the explainer from the pickle file
 library(reticulate)
-explainer <- py_load_object('explainer_titanic.pickle')
-
-# make a predict_function
-predict_function <- function(model, data) {
-  if ("predict_proba" %in% names(model)) {
-    pred <- model$predict_proba(data)
-    if (ncol(pred) == 2) {
-      pred <- pred[,2]
-    }
-  } else {
-    pred <- model$predict(data)
-  }
-  pred
-}
-
-# adjust the explainer
-explainer$predict_function <- predict_function
-explainer$label <- 'scikit-learn'
-class(explainer) <- c(class(explainer), 'explainer')
-
-# make a modelStudio
+explainer <- py_load_object('explainer_scikitlearn.pickle', pickle = "pickle")
+
+# make a studio for the model
 library(modelStudio)
 modelStudio(explainer)
 ```
diff --git a/vignettes/vignette_modelStudio.Rmd b/vignettes/vignette_modelStudio.Rmd
index 5aa0ba7..d4d5fe5 100644
--- a/vignettes/vignette_modelStudio.Rmd
+++ b/vignettes/vignette_modelStudio.Rmd
@@ -18,7 +18,7 @@ knitr::opts_chunk$set(
 )
 ```
 
-`modelStudio::modelStudio` computes various (instance and dataset level) model explanations and produces an interactive, customisable dashboard made with D3.js. It consists of multiple panels for plots with their short descriptions. Easily save and share the dashboard with others. Tools for model exploration unite with tools for EDA (Exploratory Data Analysis) to give a broad overview of the model behavior.
+`modelStudio::modelStudio` computes various (instance and dataset level) model explanations and produces an interactive, customizable dashboard made with D3.js. It consists of multiple panels for plots with their short descriptions. Easily save and share the dashboard with others. Tools for model exploration unite with tools for EDA (Exploratory Data Analysis) to give a broad overview of the model behavior.
 
 Let's use `DALEX::HR` dataset to explore `modelStudio` parameters: