update README

sgratzl · May 18, 2020 · 54176fc · 54176fc
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diff --git a/README.md b/README.md
@@ -27,57 +27,71 @@ four new types: `boxplot`, `horizontalBoxplot`, `violin`, and `horizontalViolin`
 
 ## Config
 
-// TODO
+The config can be done on a per dataset `.data.datasets[0].minStats` or for all datasets under the controllers name. e.g., `.options.boxplot.datasets.minStats`.
+
+```ts
+interface IBaseOptions {
+  /**
+   * statistic measure that should be used for computing the minimal data limit
+   * @default 'min'
+   */
+  minStats: 'min' | 'q1' | 'whiskerMin';
+
+  /**
+   * statistic measure that should be used for computing the maximal data limit
+   * @default 'max'
+   */
+  maxStats: 'max' | 'q3' | 'whiskerMax';
+
+  /**
+   * from the R doc: this determines how far the plot ‘whiskers’ extend out from
+   * the box. If coef is positive, the whiskers extend to the most extreme data
+   * point which is no more than coef times the length of the box away from the
+   * box. A value of zero causes the whiskers to extend to the data extremes
+   * @default 1.5
+   */
+  coef: number;
+
+  /**
+   * the method to compute the quantiles.
+   *
+   * 7, 'quantiles': the type-7 method as used by R 'quantiles' method.
+   * 'hinges' and 'fivenum': the method used by R 'boxplot.stats' method.
+   * 'linear': the interpolation method 'linear' as used by 'numpy.percentile' function
+   * 'lower': the interpolation method 'lower' as used by 'numpy.percentile' function
+   * 'higher': the interpolation method 'higher' as used by 'numpy.percentile' function
+   * 'nearest': the interpolation method 'nearest' as used by 'numpy.percentile' function
+   * 'midpoint': the interpolation method 'midpoint' as used by 'numpy.percentile' function
+   * @default 7
+   */
+  quantiles:
+    | 7
+    | 'quantiles'
+    | 'hinges'
+    | 'fivenum'
+    | 'linear'
+    | 'lower'
+    | 'higher'
+    | 'nearest'
+    | 'midpoint'
+    | ((sortedArr: number[]) => { min: number; q1: number; median: number; q3: number; max: number });
+}
+
+interface IBoxplotOptions extends IBaseOptions {
+  // no extra options
+}
+
+interface IViolinOptions extends IBaseOptions {
+  /**
+   * number of points that should be samples of the KDE
+   * @default 100
+   */
+  points: number;
+}
 
-```typescript
 interface IChartJSOptions {
   boxplot: {
-    datasets: {
-      /**
-       * statistic measure that should be used for computing the minimal data limit
-       * @default 'min'
-       */
-      minStats: 'min' | 'q1' | 'whiskerMin';
-
-      /**
-       * statistic measure that should be used for computing the maximal data limit
-       * @default 'max'
-       */
-      maxStats: 'max' | 'q3' | 'whiskerMax';
-
-      /**
-       * from the R doc: this determines how far the plot ‘whiskers’ extend out from
-       * the box. If coef is positive, the whiskers extend to the most extreme data
-       * point which is no more than coef times the length of the box away from the
-       * box. A value of zero causes the whiskers to extend to the data extremes
-       * @default 1.5
-       */
-      coef: number;
-
-      /**
-       * the method to compute the quantiles.
-       *
-       * 7, 'quantiles': the type-7 method as used by R 'quantiles' method.
-       * 'hinges' and 'fivenum': the method used by R 'boxplot.stats' method.
-       * 'linear': the interpolation method 'linear' as used by 'numpy.percentile' function
-       * 'lower': the interpolation method 'lower' as used by 'numpy.percentile' function
-       * 'higher': the interpolation method 'higher' as used by 'numpy.percentile' function
-       * 'nearest': the interpolation method 'nearest' as used by 'numpy.percentile' function
-       * 'midpoint': the interpolation method 'midpoint' as used by 'numpy.percentile' function
-       * @default 7
-       */
-      quantiles:
-        | 7
-        | 'quantiles'
-        | 'hinges'
-        | 'fivenum'
-        | 'linear'
-        | 'lower'
-        | 'higher'
-        | 'nearest'
-        | 'midpoint'
-        | ((sortedArr: number[]) => { min: number; q1: number; median: number; q3: number; max: number });
-    };
+    datasets: {};
   };
 }
 ```
@@ -86,7 +100,7 @@ interface IChartJSOptions {
 
 The boxplot element is called `boxandwhiskers`. The basic options are from the `rectangle` element. The violin element is called `violin` also based on the `rectangle` element.
 
-```typescript
+```ts
 interface IBaseStyling {
   /**
    * @default see rectangle
@@ -103,18 +117,27 @@ interface IBaseStyling {
   borderColor: string;
 
   /**
-   * @default null takes the current borderColor
+   * @default 1
    * @scriptable
    * @indexable
    */
-  medianColor: string;
+  borderWidth: number;
 
   /**
-   * @default 1
-   * @scriptable
-   * @indexable
+   * item style used to render outliers
+   * @default circle
    */
-  borderWidth: number;
+  outlierStyle:
+    | 'circle'
+    | 'triangle'
+    | 'rect'
+    | 'rectRounded'
+    | 'rectRot'
+    | 'cross'
+    | 'crossRot'
+    | 'star'
+    | 'line'
+    | 'dash';
 
   /**
    * radius used to render outliers
@@ -132,20 +155,17 @@ interface IBaseStyling {
   outlierBackgroundColor: string;
 
   /**
-   * to fill color below the median line of the box
-   * @default transparent
+   * @default see rectangle.borderColor
    * @scriptable
    * @indexable
    */
-  lowerBackgroundColor: string;
-
+  outlierBorderColor: string;
   /**
-   * radius used to render items
-   * @default 0 so disabled
+   * @default 1
    * @scriptable
    * @indexable
    */
-  itemRadius: number;
+  outlierBorderWidth: number;
 
   /**
    * item style used to render items
@@ -163,25 +183,41 @@ interface IBaseStyling {
     | 'line'
     | 'dash';
 
+  /**
+   * radius used to render items
+   * @default 0 so disabled
+   * @scriptable
+   * @indexable
+   */
+  itemRadius: number;
+
   /**
    * background color for items
-   * @default see rectangle backgroundColor
+   * @default see rectangle.backgroundColor
    * @scriptable
    * @indexable
    */
   itemBackgroundColor: string;
 
   /**
    * border color for items
-   * @default see rectangle backgroundColor
+   * @default see rectangle.borderColor
    * @scriptable
    * @indexable
    */
   itemBorderColor: string;
 
+  /**
+   * border width for items
+   * @default 0
+   * @scriptable
+   * @indexable
+   */
+  itemBorderColor: number;
+
   /**
    * padding that is added around the bounding box when computing a mouse hit
-   * @default 1
+   * @default 2
    * @scriptable
    * @indexable
    */
@@ -197,23 +233,33 @@ interface IBaseStyling {
 }
 
 interface IBoxPlotStyling extends IBaseStyling {
-  // no extra styling options
-}
+  /**
+   * separate color for the median line
+   * @default 'transparent' takes the current borderColor
+   * @scriptable
+   * @indexable
+   */
+  medianColor: string;
 
-interface IViolinStyling extends IBaseStyling {
   /**
-   * number of sample points of the underlying KDE for creating the violin plot
-   * @default 100
+   * color the lower half (median-q3) of the box in a different color
+   * @default 'transparent' takes the current borderColor
+   * @scriptable
+   * @indexable
    */
-  points: number;
+  lowerBackgroundColor: string;
+}
+
+interface IViolinElementStyling extends IBaseStyling {
+  // no extras
 }
 ```
 
 ## Data structure
 
 Both types support that the data is given as an array of numbers `number[]`. The statistics will be automatically computed. In addition, specific summary data structures are supported:
 
-```typescript
+```ts
 interface IBaseItem {
   min: number;
   median: number;
@@ -256,24 +302,36 @@ interface IViolinItem extends IBaseItem {
 
 ## Tooltips
 
-In order to simplify the customization of the tooltips,
-// TODO
-
-```js
-arr = {
-  options: {
-    tooltips: {
-      callbacks: {
-        // TODO
-      },
-    },
-  },
-};
+In order to simplify the customization of the tooltips the tooltip item given to the tooltip callbacks was improved. The default `toString()` behavior should be fine in most cases. The tooltip item has the following structure:
+
+```ts
+interface ITooltipItem {
+  label: string; // original
+  value: {
+    raw: IBoxPlotItem | IViolinItem;
+    /**
+     * in case an outlier is hovered this will contains its index
+     * @default -1
+     */
+    hoveredOutlierRadius: number;
+    /**
+     * toString function with a proper default implementation, which is used implicitly
+     */
+    toString(): string;
+
+    min: string;
+    median: string;
+    max: string;
+    items?: string[];
+
+    //... the formatted version of different attributes IBoxPlotItem or ViolinItem
+  };
+}
 ```
 
 ### ESM and Tree Shaking
 
-The ESM build of the library supports three shaking but having no side effects. As a consequence the chart.js library won't be automatically manipulated nor new controllers automatically registered. One has to manually import and register them.
+The ESM build of the library supports tree shaking thus having no side effects. As a consequence the chart.js library won't be automatically manipulated nor new controllers automatically registered. One has to manually import and register them.
 
 ```js
 import Chart from 'chart.js';
@@ -282,6 +340,11 @@ import { BoxPlot } from '@sgratzl/chartjs-chart-boxplot';
 // register controller in chart.js and ensure the defaults are set
 BoxPlot.register();
 ...
+
+new Chart(ctx, {
+  type: BoxPlot.id,
+  data: [...],
+});
 ```
 
 ## Development Environment

diff --git a/src/elements/base.js b/src/elements/base.js
@@ -9,7 +9,6 @@ export const baseDefaults = Object.assign({}, defaults.elements.rectangle, {
   outlierBackgroundColor: defaults.elements.rectangle.backgroundColor,
   outlierBorderColor: defaults.elements.rectangle.borderColor,
   outlierBorderWidth: 1,
-  outlierHitRadius: 4,
 
   itemStyle: 'circle',
   itemRadius: 0,
@@ -18,6 +17,7 @@ export const baseDefaults = Object.assign({}, defaults.elements.rectangle, {
   itemBorderWidth: 0,
 
   hitPadding: 2,
+  outlierHitRadius: 4,
 });
 
 export const baseOptionKeys = [
@@ -55,7 +55,6 @@ export class StatsBase extends Element {
     ctx.lineWith = options.itemBorderWidth;
     // jitter based on random data
     // use the dataset index and index to initialize the random number generator
-    // TODO
     const random = rnd(this._datasetIndex * 1000 + this._index);
 
     const pointOptions = {

diff --git a/src/elements/boxandwhiskers.js b/src/elements/boxandwhiskers.js
@@ -1,7 +1,7 @@
 import { defaults } from 'chart.js';
 import { StatsBase, baseDefaults, baseOptionKeys } from './base';
 
-export const boxOptionsKeys = baseOptionKeys.concat(['medianColor', 'lowerColor']);
+export const boxOptionsKeys = baseOptionKeys.concat(['medianColor', 'lowerBackgroundColor']);
 
 export class BoxAndWiskers extends StatsBase {
   draw(ctx) {
@@ -198,7 +198,7 @@ export class BoxAndWiskers extends StatsBase {
   }
 }
 
-BoxAndWiskers._type = 'boxAndWhiskers';
+BoxAndWiskers._type = 'boxandwhiskers';
 BoxAndWiskers.register = () => {
   defaults.set('elements', {
     [BoxAndWiskers._type]: Object.assign({}, baseDefaults, {

diff --git a/src/elements/violin.js b/src/elements/violin.js
@@ -102,9 +102,7 @@ export class ViolinElement extends StatsBase {
 ViolinElement._type = 'violin';
 ViolinElement.register = () => {
   defaults.set('elements', {
-    [ViolinElement._type]: Object.assign({}, baseDefaults, {
-      points: 100,
-    }),
+    [ViolinElement._type]: baseDefaults,
   });
   return ViolinElement;
 };