* Resolve canvasgradient is not defined in node
* Remove trailing white space
* export isPaternOrGradient helper with typings
* fix lint failure, single qoute
* Respect `fill: false` with custom draw times
* correctly listen to fill property
* remove console log and lint errors
* implement feedback, still update control points
* Convert axis options from arrays to objects
* Updated all chart type defaults
* Throw errors when axis type or position are not specified
* Avoid raising unnecessary errors when merging options into the default configs
* Fix additional tests
* Ensure scale defaults are set if type is not explicitly defined
* Another step
* Include `scale` as `firstIDs.r`
* update docs
* Update for buildOrUpdateScales
* Update migration guide
* Add test back
Remove the special drawing for an undefined zero grid line since it causes issue when the first tick is not aligned on the scale extremity (ie only linear scales now display a special grid line for the origin). Hide scales in the filler plugin unit test fixtures to avoid future failures due to changes unrelated to the tested features.
The `fill` option now accepts the index of the target dataset (number) or a string starting by "+" or "-" followed by a number representing the dataset index relative to the current one (e.g. `fill: "-2"` on dataset at index 3 will fill to dataset at index 1). It's also possible to "propagate" the filling to the target of an hidden dataset (`options.plugins.filler.propagate`). Fill boundaries `zero`, `top` and `bottom` have been deprecated and replaced by `origin`, `start` and `end`.
Implementation has been moved out of the line element into a new plugin (`src/plugins/plugin.filler.js`) and does not rely anymore on the deprecated model `scaleTop`, `scaleBottom` and `scaleZero` values. Drawing Bézier splines has been refactored in the canvas helpers (note that `Chart.helpers.canvas` is now an alias of `Chart.canvasHelpers`).
Add 3 new examples and extend utils with a pseudo-random number generator that can be initialized with `srand`. That makes possible to design examples starting always with the same initial data.
