# Greater plot control with the low-level API
Let's say you have a plot that you're creating with the high-level
API, like the following one.
```
Plot( x -> x^0.5, rec( tool := "canvasjs" ) );
```
You can find out what kind of data is being passed, under the
hood, to the `CreateVisualization` function by running the
following code.
```
dataSeries := JUPVIZMakePlotDataSeries( x -> x^0.5 );;
big := ConvertDataSeriesForTool.canvasjs( [ dataSeries ] );
# yields:
# rec(
# animationEnabled := true,
# data := [
# rec(
# dataPoints := [
# rec( x := 1, y := 1 ),
# rec( x := 2, y := 1.4142135623730951 ),
# rec( x := 3, y := 1.7320508075688772 ),
# rec( x := 4, y := 2. ),
# rec( x := 5, y := 2.2360679774997898 )
# ],
# type := "line"
# )
# ],
# height := 400
# )
```
That record is passed to `CreateVisualization` as follows.
```
CreateVisualization( rec( tool := "canvasjs", data := big ) );
```
If you wanted to change any of the internal options, such as the
default `animationEnabled := true` or the default `height := 400`,
you could alter the record yourself before passing it on to
`CreateVisualization`.
Such options may be specific to the tool you've chosen, and are
not guaranteed to work with other tools. For example, you can't
change `"canvasjs"` to `"anychart"` and expect all the
`animationEnabled` setting to work.
If you had researched other options about CanvasJS and wanted to
include those, you could do so as well, as shown below.
```
big.animationEnabled := false;; # changing an option
big.height := 500;; # changing an option
big.backgroundColor := "#F5DEB3";; # adding an option
CreateVisualization( rec( tool := "canvasjs", data := big ) );
```
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