docs: Pass on CARTO docs for v9.2 (#9795)

Author: felixpalmer

docs/api-reference/carto/cluster-tile-layer.md

@@ -1,12 +1,13 @@
 # ClusterTileLayer
 
-`ClusterTileLayer` is a layer for visualizing point data aggregated using the [Quadbin Spatial Index](https://docs.carto.com/data-and-analysis/analytics-toolbox-for-bigquery/key-concepts/spatial-indexes#quadbin) with dynamic clustering. It provides efficient visualization of large point datasets with automatic clustering based on zoom level and customizable aggregation strategies.
+`ClusterTileLayer` is a layer for visualizing point data aggregated using spatial indexes like [Quadbin](https://docs.carto.com/data-and-analysis/analytics-toolbox-for-bigquery/key-concepts/spatial-indexes#quadbin) or [H3](https://docs.carto.com/data-and-analysis/analytics-toolbox-for-bigquery/key-concepts/spatial-indexes#h3) with dynamic clustering. It provides efficient visualization of large point datasets with automatic clustering based on zoom level and customizable aggregation strategies. The layer automatically detects the spatial index type and renders cells accordingly.
 
-## Usage 
+## Usage
 
 ```tsx
 import {DeckGL} from '@deck.gl/react';
-import {ClusterTileLayer, quadbinTableSource} from '@deck.gl/carto';
+import {ClusterTileLayer} from '@deck.gl/carto';
+import {quadbinTableSource} from '@carto/api-client';
 
 function App({viewState}) {
   const data = quadbinTableSource({
@@ -77,13 +78,19 @@ Required. A valid `TilejsonResult` object.
 
 Use one of the following [Data Sources](./data-sources.md) to fetch this from the CARTO API:
 
+**Quadbin sources:**
 - [quadbinTableSource](./data-sources#quadbintablesource)
 - [quadbinQuerySource](./data-sources#quadbinquerysource)
 - [quadbinTilesetSource](./data-sources#quadbintilesetsource)
 
+**H3 sources:**
+- [h3TableSource](./data-sources#h3tablesource)
+- [h3QuerySource](./data-sources#h3querysource)
+- [h3TilesetSource](./data-sources#h3tilesetsource)
+
 ### Clustering Options
 
-The following props control how the data is grouped into clusters. The accessor methods will be called on each quadbin cell in the data to retrieve the position and weight of the cell. All of the properties are then aggregated and made available to the `GeoJsonLayer` accessors for styling.
+The following props control how the data is grouped into clusters. The accessor methods will be called on each spatial index cell (quadbin or H3) in the data to retrieve the position and weight of the cell. All of the properties are then aggregated and made available to the `GeoJsonLayer` accessors for styling.
 
 #### `clusterLevel` (number, optional) {#clusterlevel}
 
@@ -93,7 +100,7 @@ The number of aggregation levels to cluster cells by. Larger values increase the
 
 #### `getPosition` ([Accessor<Position>](../../developer-guide/using-layers.md#accessors), optional) {#getposition}
 
-The (average) position of points in a cell used for clustering. If not supplied the center of the quadbin cell is used.
+The (average) position of points in a cell used for clustering. If not supplied the center of the spatial index cell (quadbin or H3) is used.
 
 #### `getWeight` ([Accessor<number>](../../developer-guide/using-layers.md#accessors)) {#getweight}
 
@@ -107,7 +114,7 @@ When using the `GeoJsonLayer` accessors to style the clusters, aggregated values
 
 ### Aggregation types
 
-The type aggregation is infered based on the property name, for example `population_average` will be aggregated using a (mean) average operation across all the quadbin cells that are present in the cluster, while `age_min` will give the minimum value present in the cluster.
+The type aggregation is infered based on the property name, for example `population_average` will be aggregated using a (mean) average operation across all the spatial index cells that are present in the cluster, while `age_min` will give the minimum value present in the cluster.
 
 The following suffixes are supported:
 
@@ -129,7 +136,7 @@ In addition to the aggregated values across the cluster, the features passed to
 Display clusters using an `'cluster'` icon scaled between 20 and 80, switching to an icon defined by the `icon_any` property once the cluster only contains a single point.
 
 ```ts
-// Data present in quadbin cell
+// Data present in spatial index cell (quadbin or H3)
 type PropertiesType = {
   longitude_count: number; // count of points in cell
   longitude_average: number;
@@ -138,12 +145,12 @@ type PropertiesType = {
 };
 
 const layer = new ClusterTileLayer<PropertiesType>({
-  data, // Defined using `quadbinTableSource` or similar
+  data, // Defined using `quadbinTableSource`, `h3TableSource` or similar
 
   // Clustering props
   getWeight: d => d.properties.longitude_count,
   getPosition: d => [d.properties.longitude_average, d.properties.latitude_average];
-  
+
   // Style
   pointType: 'icon',
   iconAtlas,

docs/api-reference/carto/data-sources.md

@@ -7,7 +7,7 @@ To ease interacting with the CARTO platform, the CARTO deck.gl module includes a
 The data source functions are a compact way to describe the data that you want to fetch. For example, to fetch a table from a data warehouse from the connection `carto_dw`:
 
 ```js
-import {vectorTableSource} from '@deck.gl/carto';
+import {vectorTableSource} from '@carto/api-client';
 const data = vectorTableSource({
   accessToken: 'XXX',
   connectionName: 'carto_dw',
@@ -20,7 +20,8 @@ const data = vectorTableSource({
 All data source functions return a Promise, which can be resolved to obtain the actual Tilejson. However, as the [core deck.gl Layer prop supports Promises](../core/layer#data), it is often not necessary to resolve or await the Promise and the data source can be directly passed to the data prop:
 
 ```jsx
-import {H3TileLayer, h3TilesetSource} from '@deck.gl/carto';
+import {H3TileLayer} from '@deck.gl/carto';
+import {h3TilesetSource} from '@carto/api-client';
 new H3TileLayer({
   data: h3TilesetSource({
     accessToken: 'XXX',

docs/api-reference/carto/h3-tile-layer.md

@@ -6,7 +6,8 @@
 
 ```tsx
 import {DeckGL} from '@deck.gl/react';
-import {H3TileLayer, h3QuerySource} from '@deck.gl/carto';
+import {H3TileLayer} from '@deck.gl/carto';
+import {h3QuerySource} from '@carto/api-client';
 
 function App({viewState}) {
   const data = h3QuerySource({

docs/api-reference/carto/heatmap-tile-layer.md

@@ -1,12 +1,13 @@
 # HeatmapTileLayer
 
-`HeatmapTileLayer` is a layer for visualizing point data aggregated using the [Quadbin Spatial Index](https://docs.carto.com/data-and-analysis/analytics-toolbox-for-bigquery/key-concepts/spatial-indexes#quadbin) using a heatmap. 
+`HeatmapTileLayer` is a layer for visualizing point data aggregated using spatial indexes like [Quadbin](https://docs.carto.com/data-and-analysis/analytics-toolbox-for-bigquery/key-concepts/spatial-indexes#quadbin) or [H3](https://docs.carto.com/data-and-analysis/analytics-toolbox-for-bigquery/key-concepts/spatial-indexes#h3) using a heatmap. The layer automatically detects the spatial index type and renders cells accordingly. 
 
-## Usage 
+## Usage
 
 ```tsx
 import {DeckGL} from '@deck.gl/react';
-import {HeatmapTileLayer, quadbinTableSource} from '@deck.gl/carto';
+import {HeatmapTileLayer} from '@deck.gl/carto';
+import {quadbinTableSource} from '@carto/api-client';
 
 function App({viewState}) {
   const data = quadbinTableSource({
@@ -72,10 +73,16 @@ Required. A valid `TilejsonResult` object.
 
 Use one of the following [Data Sources](./data-sources.md) to fetch this from the CARTO API:
 
+**Quadbin sources:**
 - [quadbinTableSource](./data-sources#quadbintablesource)
 - [quadbinQuerySource](./data-sources#quadbinquerysource)
 - [quadbinTilesetSource](./data-sources#quadbintilesetsource)
 
+**H3 sources:**
+- [h3TableSource](./data-sources#h3tablesource)
+- [h3QuerySource](./data-sources#h3querysource)
+- [h3TilesetSource](./data-sources#h3tilesetsource)
+
 ### Render Options
 
 #### `radiusPixels` (number, optional) ![transition-enabled](https://img.shields.io/badge/transition-enabled-green.svg?style=flat-square") {#radiuspixels}
@@ -117,7 +124,7 @@ Value that is multiplied with the total weight at a pixel to obtain the final we
 
 * Default: `1`
 
-Method called to retrieve weight of each quadbin cell. By default each cell will use a weight of `1`.
+Method called to retrieve weight of each spatial index cell (quadbin or H3). By default each cell will use a weight of `1`.
 
 ### Callbacks
 

docs/api-reference/carto/overview.md

@@ -38,7 +38,8 @@ fetchMap({cartoMapId}).then(map => new Deck(map));
 
 ```jsx
 import {DeckGL} from '@deck.gl/react';
-import {VectorTileLayer, vectorQuerySource} from '@deck.gl/carto';
+import {VectorTileLayer} from '@deck.gl/carto';
+import {vectorQuerySource} from '@carto/api-client';
 
 function App() {
   const data = vectorQuerySource({

docs/api-reference/carto/quadbin-tile-layer.md

@@ -6,7 +6,8 @@
 
 ```tsx
 import {DeckGL} from '@deck.gl/react';
-import {QuadbinTileLayer, quadbinTilesetSource} from '@deck.gl/carto';
+import {QuadbinTileLayer} from '@deck.gl/carto';
+import {quadbinTilesetSource} from '@carto/api-client';
 
 function App({viewState}) {
   const data = quadbinTilesetSource({

docs/api-reference/carto/raster-tile-layer.md

@@ -6,7 +6,8 @@
 
 ```tsx
 import {DeckGL} from '@deck.gl/react';
-import {RasterTileLayer, rasterSource} from '@deck.gl/carto';
+import {RasterTileLayer} from '@deck.gl/carto';
+import {rasterSource} from '@carto/api-client';
 
 function App({viewState}) {
   const data = rasterSource({

docs/api-reference/carto/vector-tile-layer.md

@@ -6,7 +6,8 @@
 
 ```tsx
 import {DeckGL} from '@deck.gl/react';
-import {VectorTileLayer, vectorTableSource} from '@deck.gl/carto';
+import {VectorTileLayer} from '@deck.gl/carto';
+import {vectorTableSource} from '@carto/api-client';
 
 function App({viewState}) {
   const data = vectorTableSource({
@@ -59,7 +60,7 @@ new deck.carto.VectorTileLayer({});
 
 ## Properties
 
-The properties of [`MVTLayer`](../geo-layers/mvt-layer.md) will be inherited.
+Inherits all properties from [`MVTLayer`](../geo-layers/mvt-layer.md).
 
 #### `data` (TilejsonResult) {#data}
 
@@ -71,6 +72,16 @@ Use one of the following [Data Sources](./data-sources.md) to fetch this from th
 - [vectorQuerySource](./data-sources#vectorquerysource)
 - [vectorTilesetSource](./data-sources#vectortilesetsource)
 
+#### `autoLabels` (boolean | object, optional) {#autolabels}
+
+* Default: `false`
+
+If `true`, automatically creates labels for lines and polygons at their centroids.
+
+For more control over labeling, pass an object with the following properties:
+
+* `uniqueIdProperty` (string): Property name to use for deduplication. Only creates a single label for each unique feature value.
+
 ## Source
 
 [modules/carto/src/layers/vector-tile-layer.ts](https://github.com/visgl/deck.gl/tree/master/modules/carto/src/layers/vector-tile-layer.ts)

docs/upgrade-guide.md

@@ -253,7 +253,8 @@ map.addLayer(new MapboxLayer({type: ArcLayer, ...}))
 
 ```ts
 // deck.gl v9
-import {VectorTileLayer, vectorQuerySource} from '@deck.gl/carto';
+import {VectorTileLayer} from '@deck.gl/carto';
+import {vectorQuerySource} from '@carto/api-client';
 const data = vectorQuerySource({
   accessToken: 'XXX',
   connectionName: 'carto_dw',

docs/whats-new.md

@@ -50,7 +50,7 @@ See documentation about how to [test WebGPU support](./developer-guide/webgpu.md
 ### CARTO
 
 - [ClusterTileLayer](./api-reference/carto/cluster-tile-layer) and [HeatmapTileLayer](./api-reference/carto/heatmap-tile-layer) support H3 data
-- [VectorTileLayer](./api-reference/carto/vector-tile-layer) supports labels for line & polygon data, via new `autoLabels` prop
+- [VectorTileLayer](./api-reference/carto/vector-tile-layer) supports labels for line & polygon data, via new [`autoLabels`](./api-reference/carto/vector-tile-layer#autolabels) prop
 
 ### Mapbox