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HeatmapLayer

Warning

The HeatmapLayer is not currently working.

As of Lonboard v0.10, Lonboard upgraded to version 9.0 of the underlying deck.gl library. deck.gl appears to have a bug with the HeatmapLayer in 9.0, that has not yet been fixed.

Please temporarily downgrade to Lonboard v0.9 if you would like to use the HeatmapLayer.

Screenshot from DuckDB Spatial example

lonboard.HeatmapLayer

Bases: BaseArrowLayer

The HeatmapLayer visualizes the spatial distribution of data.

Example

From GeoPandas:

import geopandas as gpd
from lonboard import Map, HeatmapLayer

# A GeoDataFrame with Point geometries
gdf = gpd.GeoDataFrame()
layer = HeatmapLayer.from_geopandas(gdf)
m = Map(layer)

From an Arrow-compatible source like pyogrio or geoarrow-rust:

from geoarrow.rust.io import read_flatgeobuf
from lonboard import Map, HeatmapLayer

# Example: A FlatGeobuf file with Point geometries
table = read_flatgeobuf("path/to/file.fgb")
layer = HeatmapLayer(
    table,
    get_fill_color=[255, 0, 0],
)
m = Map(layer)

aggregation class-attribute instance-attribute 

aggregation = tag(sync=True)

Defines the type of aggregation operation

Valid values are 'SUM', 'MEAN'.

  • Type: str, optional
  • Default: "SUM"

auto_highlight class-attribute instance-attribute 

auto_highlight = tag(sync=True)

When true, the current object pointed to by the mouse pointer (when hovered over) is highlighted with highlightColor.

Requires pickable to be True.

  • Type: bool
  • Default: False

debounce_timeout class-attribute instance-attribute 

debounce_timeout = tag(sync=True)

Interval in milliseconds during which changes to the viewport don't trigger aggregation.

  • Type: int, optional
  • Default: 500

extensions class-attribute instance-attribute 

extensions = tag(sync=True, **widget_serialization)

A list of layer extension objects to add additional features to a layer.

get_weight class-attribute instance-attribute 

get_weight = FloatAccessor(None, allow_none=True)

The weight of each object.

  • Type: FloatAccessor, optional
    • If a number is provided, it is used as the weight for all objects.
    • If an array is provided, each value in the array will be used as the weight for the object at the same row index.
  • Default: 1.

highlight_color class-attribute instance-attribute 

highlight_color = VariableLengthTuple(
    Int(), default_value=None, minlen=3, maxlen=4
)

RGBA color to blend with the highlighted object (the hovered over object if auto_highlight=true). When the value is a 3 component (RGB) array, a default alpha of 255 is applied.

  • Type: List or Tuple of integers
  • Default: [0, 0, 128, 128]

intensity class-attribute instance-attribute 

intensity = tag(sync=True)

Value that is multiplied with the total weight at a pixel to obtain the final weight.

  • Type: float, optional
  • Default: 1

opacity class-attribute instance-attribute 

opacity = tag(sync=True)

The opacity of the layer.

  • Type: float. Must range between 0 and 1.
  • Default: 1

pickable class-attribute instance-attribute 

pickable = tag(sync=True)

Whether the layer responds to mouse pointer picking events.

This must be set to True for tooltips and other interactive elements to be available. This can also be used to only allow picking on specific layers within a map instance.

Note that picking has some performance overhead in rendering. To get the absolute best rendering performance with large data (at the cost of removing interactivity), set this to False.

  • Type: bool
  • Default: True

radius_pixels class-attribute instance-attribute 

radius_pixels = tag(sync=True)

Radius of the circle in pixels, to which the weight of an object is distributed.

  • Type: float, optional
  • Default: 30

selected_index class-attribute instance-attribute 

selected_index = tag(sync=True)

The positional index of the most-recently clicked on row of data.

You can use this to access the full row of data from a GeoDataFrame

gdf.iloc[layer.selected_index]

Setting a value here from Python will do nothing. This attribute only exists to be updated from JavaScript on a map click. Note that pickable must be True (the default) on this layer for the JavaScript onClick handler to work; if pickable is set to False, selected_index will never update.

Note that you can use observe to call a function whenever a new value is received from JavaScript. Refer here for an example.

table class-attribute instance-attribute 

table = ArrowTableTrait(allowed_geometry_types={POINT})

A GeoArrow table with a Point column.

This is the fastest way to plot data from an existing GeoArrow source, such as geoarrow-rust or geoarrow-pyarrow.

If you have a GeoPandas GeoDataFrame, use from_geopandas instead.

threshold class-attribute instance-attribute 

threshold = tag(sync=True)

Ratio of the fading weight to the max weight, between 0 and 1.

For example, 0.1 affects all pixels with weight under 10% of the max.

Ignored when color_domain is specified.

  • Type: float, optional
  • Default: 0.05

visible class-attribute instance-attribute 

visible = tag(sync=True)

Whether the layer is visible.

Under most circumstances, using the visible attribute to control the visibility of layers is recommended over removing/adding the layer from the Map.layers list.

In particular, toggling the visible attribute will persist the layer on the JavaScript side, while removing/adding the layer from the Map.layers list will re-download and re-render from scratch.

  • Type: bool
  • Default: True

weights_texture_size class-attribute instance-attribute 

weights_texture_size = tag(sync=True)

Specifies the size of weight texture.

  • Type: int, optional
  • Default: 2048

__init__ 

__init__(
    table: ArrowStreamExportable, **kwargs: Unpack[HeatmapLayerKwargs]
) -> None

Construct a Layer from a GeoArrow table.

This accepts Arrow data from any library implementing the Arrow PyCapsule Interface, including pyarrow, arro3, DuckDB, and others.

The geometry column will be reprojected to EPSG:4326 if it is not already in that coordinate system.

Parameters:

  • table (ArrowStreamExportable) –

    An Arrow table or stream object from a library implementing the [Arrow PyCapsule Interface]. This object must contain a column with a geometry type that has the geoarrow extension metadata.

Other Parameters:

  • kwargs (Unpack[BaseLayerKwargs]) –

    parameters passed on to __init__

Returns:

  • None –

    A Layer with the initialized data.

from_duckdb classmethod 

from_duckdb(
    sql: str | DuckDBPyRelation,
    con: DuckDBPyConnection | None = None,
    *,
    crs: str | CRS | None = None,
    **kwargs: Unpack[HeatmapLayerKwargs]
) -> Self

Construct a Layer from a duckdb-spatial query.

DuckDB Spatial does not currently expose coordinate reference system information, so the user must ensure that data has been reprojected to EPSG:4326 or pass in the existing CRS of the data in the crs keyword parameter.

Parameters:

  • sql (str | DuckDBPyRelation) –

    The SQL input to visualize. This can either be a string containing a SQL query or the output of the duckdb sql function.

  • con (DuckDBPyConnection | None, default: None ) –

    The current DuckDB connection. This is required when passing a str to the sql parameter.

Other Parameters:

  • crs (str | CRS | None) –

    The CRS of the input data. This can either be a string passed to pyproj.CRS.from_user_input or a pyproj.CRS object. Defaults to None.

  • kwargs (Unpack[BaseLayerKwargs]) –

    parameters passed on to __init__

Returns:

  • Self –

    A Layer with the initialized data.

from_geopandas classmethod 

from_geopandas(
    gdf: GeoDataFrame,
    *,
    auto_downcast: bool = True,
    **kwargs: Unpack[HeatmapLayerKwargs]
) -> Self

Construct a Layer from a geopandas GeoDataFrame.

The GeoDataFrame will be reprojected to EPSG:4326 if it is not already in that coordinate system.

Parameters:

  • gdf (GeoDataFrame) –

    The GeoDataFrame to set on the layer.

Other Parameters:

  • auto_downcast (bool) –

    If True, automatically downcast to smaller-size data types if possible without loss of precision. This calls pandas.DataFrame.convert_dtypes and pandas.to_numeric under the hood.

  • kwargs (Unpack[BaseLayerKwargs]) –

    parameters passed on to __init__

Returns:

  • Self –

    A Layer with the initialized data.