deckgl module

Map

Bases: Map

The Map class inherits lonboard.Map.

Returns:

Name	Type	Description
object		lonboard.Map object.

Source code in leafmap/deckgl.py

class Map(lonboard.Map):
    """The Map class inherits lonboard.Map.

    Returns:
        object: lonboard.Map object.
    """

    def __init__(
        self,
        center: Tuple[float, float] = (20, 0),
        zoom: float = 1.2,
        height: int = 600,
        layers: List = [],
        show_tooltip: bool = True,
        view_state: Optional[Dict] = {},
        **kwargs,
    ) -> None:
        """Initialize a Map object.

        Args:
            center (tuple, optional): Center of the map in the format of (lat, lon). Defaults to (20, 0).
            zoom (float, optional): The map zoom level. Defaults to 1.2.
            height (int, optional): Height of the map. Defaults to 600.
            layers (list, optional): List of additional layers to add to the map. Defaults to [].
            show_tooltip (bool, optional): Flag to show tooltips on the map. Defaults to True.
            view_state (dict, optional): The view state of the map. Defaults to {}.
            **kwargs: Additional keyword arguments to pass to lonboard.Map.

        Returns:
            None
        """

        view_state["latitude"] = center[0]
        view_state["longitude"] = center[1]
        view_state["zoom"] = zoom
        kwargs["view_state"] = view_state

        super().__init__(
            _height=height,
            show_tooltip=show_tooltip,
            layers=layers,
            **kwargs,
        )

    def add_gdf(
        self,
        gdf: gpd.GeoDataFrame,
        zoom_to_layer: bool = True,
        pickable: bool = True,
        color_column: Optional[str] = None,
        color_scheme: Optional[str] = "Quantiles",
        color_map: Optional[Union[str, Dict]] = None,
        color_k: Optional[int] = 5,
        color_args: dict = {},
        alpha: Optional[float] = 1.0,
        rescale: bool = True,
        zoom: Optional[float] = 10.0,
        **kwargs: Any,
    ) -> None:
        """Adds a GeoPandas GeoDataFrame to the map.

        Args:
            gdf (GeoDataFrame): A GeoPandas GeoDataFrame with geometry column.
            zoom_to_layer (bool, optional): Flag to zoom to the added layer. Defaults to True.
            pickable (bool, optional): Flag to enable picking on the added layer. Defaults to True.
            color_column (Optional[str], optional): The column to be used for color encoding. Defaults to None.
            color_map (Optional[Union[str, Dict]], optional): The color map to use for color encoding. It can be a string or a dictionary. Defaults to None.
            color_scheme (Optional[str], optional): The color scheme to use for color encoding. Defaults to "Quantiles".
                Name of a choropleth classification scheme (requires mapclassify).
                A mapclassify.MapClassifier object will be used
                under the hood. Supported are all schemes provided by mapclassify (e.g.
                'BoxPlot', 'EqualInterval', 'FisherJenks', 'FisherJenksSampled',
                'HeadTailBreaks', 'JenksCaspall', 'JenksCaspallForced',
                'JenksCaspallSampled', 'MaxP', 'MaximumBreaks',
                'NaturalBreaks', 'Quantiles', 'Percentiles', 'StdMean',
                'UserDefined'). Arguments can be passed in classification_kwds.
            color_k (Optional[int], optional): The number of classes to use for color encoding. Defaults to 5.
            color_args (dict, optional): Additional keyword arguments that will be passed to assign_continuous_colors(). Defaults to {}.
            zoom (Optional[float], optional): The zoom level to zoom to. Defaults to 10.0.
            **kwargs: Additional keyword arguments that will be passed to lonboard.Layer.from_geopandas()

        Returns:
            None
        """

        from lonboard import ScatterplotLayer, PathLayer, SolidPolygonLayer
        import matplotlib.pyplot as plt

        geom_type = gdf.geometry.iloc[0].geom_type
        kwargs["pickable"] = pickable

        if geom_type in ["Point", "MultiPoint"]:
            if "get_radius" not in kwargs:
                kwargs["get_radius"] = 10
            if color_column is not None:
                if isinstance(color_map, str):
                    kwargs["get_fill_color"] = apply_continuous_cmap(
                        gdf[color_column], color_map, alpha, rescale
                    )
                elif isinstance(color_map, dict):
                    kwargs["get_fill_color"] = apply_categorical_cmap(
                        gdf[color_column], color_map, alpha
                    )

            if "get_fill_color" not in kwargs:
                kwargs["get_fill_color"] = [255, 0, 0, 180]
            layer = ScatterplotLayer.from_geopandas(gdf, **kwargs)
        elif geom_type in ["LineString", "MultiLineString"]:
            if "get_width" not in kwargs:
                kwargs["get_width"] = 5
            if color_column is not None:
                if isinstance(color_map, str):
                    cmap = plt.get_cmap(color_map)
                    kwargs["get_color"] = apply_continuous_cmap(
                        gdf[color_column], cmap, alpha, rescale
                    )
                elif isinstance(color_map, dict):
                    kwargs["get_color"] = apply_categorical_cmap(
                        gdf[color_column], color_map, alpha
                    )
            layer = PathLayer.from_geopandas(gdf, **kwargs)
        elif geom_type in ["Polygon", "MultiPolygon"]:
            if color_column is not None:
                if isinstance(color_map, str):
                    kwargs["get_fill_color"] = apply_continuous_cmap(
                        gdf[color_column], color_map, alpha, rescale
                    )
                elif isinstance(color_map, dict):
                    kwargs["get_fill_color"] = apply_categorical_cmap(
                        gdf[color_column], color_map, alpha
                    )
            if "get_fill_color" not in kwargs:
                kwargs["get_fill_color"] = [0, 0, 255, 128]
            layer = SolidPolygonLayer.from_geopandas(gdf, **kwargs)

        self.layers = self.layers + (layer,)

        if zoom_to_layer:
            try:
                bounds = gdf.total_bounds.tolist()
                x = (bounds[0] + bounds[2]) / 2
                y = (bounds[1] + bounds[3]) / 2

                src_crs = gdf.crs
                if src_crs is None:
                    src_crs = "EPSG:4326"

                lon, lat = common.convert_coordinates(x, y, src_crs, "EPSG:4326")

                self.view_state = {
                    "latitude": lat,
                    "longitude": lon,
                    "zoom": zoom,
                }
            except Exception as e:
                print(e)

    def add_vector(
        self,
        vector: Union[str, gpd.GeoDataFrame],
        zoom_to_layer: bool = True,
        pickable: bool = True,
        color_column: Optional[str] = None,
        color_scheme: Optional[str] = "Quantiles",
        color_map: Optional[Union[str, Dict]] = None,
        color_k: Optional[int] = 5,
        color_args: dict = {},
        open_args: dict = {},
        **kwargs: Any,
    ) -> None:
        """Adds a vector layer to the map.

        Args:
            vector (Union[str, GeoDataFrame]): The file path or URL to the vector data, or a GeoDataFrame.
            zoom_to_layer (bool, optional): Flag to zoom to the added layer. Defaults to True.
            pickable (bool, optional): Flag to enable picking on the added layer. Defaults to True.
            color_column (Optional[str], optional): The column to be used for color encoding. Defaults to None.
            color_map (Optional[Union[str, Dict]], optional): The color map to use for color encoding. It can be a string or a dictionary. Defaults to None.
            color_scheme (Optional[str], optional): The color scheme to use for color encoding. Defaults to "Quantiles".
                Name of a choropleth classification scheme (requires mapclassify).
                A mapclassify.MapClassifier object will be used
                under the hood. Supported are all schemes provided by mapclassify (e.g.
                'BoxPlot', 'EqualInterval', 'FisherJenks', 'FisherJenksSampled',
                'HeadTailBreaks', 'JenksCaspall', 'JenksCaspallForced',
                'JenksCaspallSampled', 'MaxP', 'MaximumBreaks',
                'NaturalBreaks', 'Quantiles', 'Percentiles', 'StdMean',
                'UserDefined'). Arguments can be passed in classification_kwds.
            color_k (Optional[int], optional): The number of classes to use for color encoding. Defaults to 5.
            color_args (dict, optional): Additional keyword arguments that will be passed to assign_continuous_colors(). Defaults to {}.
            open_args (dict, optional): Additional keyword arguments that will be passed to geopandas.read_file(). Defaults to {}.
            **kwargs: Additional keyword arguments that will be passed to lonboard.Layer.from_geopandas()

        Returns:
            None
        """

        if isinstance(vector, gpd.GeoDataFrame):
            gdf = vector
        else:
            gdf = gpd.read_file(vector, **open_args)
        self.add_gdf(
            gdf,
            zoom_to_layer,
            pickable,
            color_column,
            color_scheme,
            color_map,
            color_k,
            color_args,
            **kwargs,
        )

    def add_layer(
        self,
        layer: Any,
        zoom_to_layer: bool = True,
        pickable: bool = True,
        **kwargs: Any,
    ) -> None:
        """Adds a layer to the map.

        Args:
            layer (Any): A lonboard layer object.
            zoom_to_layer (bool, optional): Whether to zoom to the layer extent. Defaults to True.
            pickable (bool, optional): Flag to enable picking on the added layer if it's a vector layer. Defaults to True.
            **kwargs: Additional keyword arguments that will be passed to the vector layer if it's a vector layer.

        Returns:
            None
        """

        from lonboard import (
            BitmapLayer,
            BitmapTileLayer,
            HeatmapLayer,
            PathLayer,
            PointCloudLayer,
            PolygonLayer,
            ScatterplotLayer,
            SolidPolygonLayer,
        )

        if type(layer) in [
            BitmapLayer,
            BitmapTileLayer,
            HeatmapLayer,
            ScatterplotLayer,
            PathLayer,
            PointCloudLayer,
            PolygonLayer,
            SolidPolygonLayer,
        ]:
            self.layers = self.layers + (layer,)

            if zoom_to_layer:
                from lonboard._viewport import compute_view

                if hasattr(layer, "table"):
                    try:
                        self.view_state = compute_view([self.layers[-1].table])
                    except Exception as e:
                        print(e)
        else:
            self.add_vector(
                layer, zoom_to_layer=zoom_to_layer, pickable=pickable, **kwargs
            )

    def to_html(self, filename: Optional[str] = None) -> None:
        """Saves the map as an HTML file.

        Args:
            filename (Optional[str], optional): The output file path to the HTML file. Defaults to None.

        Returns:
            str: The HTML content if filename is None.
        """

        if filename is None:
            filename = common.temp_file_path("html")
            super().to_html(filename)
            with open(filename) as f:
                html = f.read()
            return html
        else:
            super().to_html(filename)

    def to_streamlit(
        self,
        width: Optional[int] = None,
        height: Optional[int] = 600,
        scrolling: Optional[bool] = False,
        **kwargs,
    ):
        """Renders `deckgl.Map`in a Streamlit app. This method is a static Streamlit Component, meaning, no information is passed back from Leaflet on browser interaction.

        Args:
            width (int, optional): Width of the map. Defaults to None.
            height (int, optional): Height of the map. Defaults to 600.
            scrolling (bool, optional): Whether to allow the map to scroll. Defaults to False.

        Returns:
            streamlit.components: components.html object.
        """

        try:
            import streamlit.components.v1 as components

            return components.html(
                self.to_html(), width=width, height=height, scrolling=scrolling
            )

        except Exception as e:
            raise e

    def add_basemap(self, basemap="HYBRID", visible=True, **kwargs) -> None:
        """Adds a basemap to the map.

        Args:
            basemap (str, optional): Can be one of string from basemaps. Defaults to 'HYBRID'.
            visible (bool, optional): Whether the basemap is visible or not. Defaults to True.
            **kwargs: Keyword arguments for the TileLayer.
        """
        import xyzservices

        try:

            map_dict = {
                "ROADMAP": "Google Maps",
                "SATELLITE": "Google Satellite",
                "TERRAIN": "Google Terrain",
                "HYBRID": "Google Hybrid",
            }

            if isinstance(basemap, str):
                if basemap.upper() in map_dict:
                    tile = common.get_google_map(basemap.upper())

                    layer = lonboard.BitmapTileLayer(
                        data=tile.url,
                        min_zoom=tile.min_zoom,
                        max_zoom=tile.max_zoom,
                        visible=visible,
                        **kwargs,
                    )

                    self.add_layer(layer)
                    return

            if isinstance(basemap, xyzservices.TileProvider):
                url = basemap.build_url()
                if "max_zoom" in basemap.keys():
                    max_zoom = basemap["max_zoom"]
                else:
                    max_zoom = 22
                    layer = lonboard.BitmapTileLayer(
                        data=url,
                        min_zoom=tile.min_zoom,
                        max_zoom=max_zoom,
                        visible=visible,
                        **kwargs,
                    )

                    self.add_layer(layer)
            elif basemap in basemaps and basemaps[basemap].name:
                tile = basemaps[basemap]
                layer = lonboard.BitmapTileLayer(
                    data=tile.url,
                    min_zoom=tile.get("min_zoom", 0),
                    max_zoom=tile.get("max_zoom", 24),
                    visible=visible,
                    **kwargs,
                )
                self.add_layer(layer)
            else:
                print(
                    "Basemap can only be one of the following:\n  {}".format(
                        "\n  ".join(basemaps.keys())
                    )
                )

        except Exception as e:
            raise ValueError(
                "Basemap can only be one of the following:\n  {}".format(
                    "\n  ".join(basemaps.keys())
                )
            )

    def add_tile_layer(
        self,
        url: str,
        opacity: float = 1.0,
        visible: bool = True,
        tile_size: int = 256,
        **kwargs: Any,
    ) -> None:
        """
        Adds a TileLayer to the map.

        This method adds a TileLayer to the map. The TileLayer is created from
            the specified URL, and it is added to the map with the specified
            name, attribution, visibility, and tile size.

        Args:
            url (str): The URL of the tile layer.
            opacity (float, optional): The opacity of the layer. Defaults to 1.0.
            visible (bool, optional): Whether the layer should be visible by
                default. Defaults to True.
            tile_size (int, optional): The size of the tiles in the layer.
                Defaults to 256.
            **kwargs: Additional keyword arguments that are passed to the lonboard.BitmapTileLayer class.
                See https://developmentseed.org/lonboard/latest/api/layers/bitmap-tile-layer/#lonboard.BitmapTileLayer.

        Returns:
            None
        """

        layer = lonboard.BitmapTileLayer(
            data=url,
            tile_size=tile_size,
            opacity=opacity,
            visible=visible,
            **kwargs,
        )
        self.add_layer(layer)

    def add_raster(
        self,
        source: str,
        indexes: Optional[int] = None,
        colormap: Optional[str] = None,
        vmin: Optional[float] = None,
        vmax: Optional[float] = None,
        nodata: Optional[float] = None,
        tile_size: Optional[int] = 256,
        attribution: Optional[str] = None,
        layer_name: Optional[str] = "Raster",
        zoom_to_layer: Optional[bool] = True,
        visible: Optional[bool] = True,
        opacity: Optional[float] = 1.0,
        array_args: Optional[Dict] = {},
        client_args: Optional[Dict] = {"cors_all": True},
        **kwargs,
    ) -> None:
        """Add a local raster dataset to the map.
            If you are using this function in JupyterHub on a remote server (e.g., Binder, Microsoft Planetary Computer) and
            if the raster does not render properly, try installing jupyter-server-proxy using `pip install jupyter-server-proxy`,
            then running the following code before calling this function. For more info, see https://bit.ly/3JbmF93.

            import os
            os.environ['LOCALTILESERVER_CLIENT_PREFIX'] = 'proxy/{port}'

        Args:
            source (str): The path to the GeoTIFF file or the URL of the Cloud Optimized GeoTIFF.
            indexes (int, optional): The band(s) to use. Band indexing starts at 1. Defaults to None.
            colormap (str, optional): The name of the colormap from `matplotlib` to use when plotting a single band. See https://matplotlib.org/stable/gallery/color/colormap_reference.html. Default is greyscale.
            vmin (float, optional): The minimum value to use when colormapping the palette when plotting a single band. Defaults to None.
            vmax (float, optional): The maximum value to use when colormapping the palette when plotting a single band. Defaults to None.
            nodata (float, optional): The value from the band to use to interpret as not valid data. Defaults to None.
            attribution (str, optional): Attribution for the source raster. This defaults to a message about it being a local file.. Defaults to None.
            layer_name (str, optional): The layer name to use. Defaults to 'Raster'.
            layer_index (int, optional): The index of the layer. Defaults to None.
            zoom_to_layer (bool, optional): Whether to zoom to the extent of the layer. Defaults to True.
            visible (bool, optional): Whether the layer is visible. Defaults to True.
            opacity (float, optional): The opacity of the layer. Defaults to 1.0.
            array_args (dict, optional): Additional arguments to pass to `array_to_memory_file` when reading the raster. Defaults to {}.
            client_args (dict, optional): Additional arguments to pass to localtileserver.TileClient. Defaults to { "cors_all": False }.
        """
        import numpy as np
        import xarray as xr

        if isinstance(source, np.ndarray) or isinstance(source, xr.DataArray):
            source = common.array_to_image(source, **array_args)

        tile_layer, tile_client = common.get_local_tile_layer(
            source,
            indexes=indexes,
            colormap=colormap,
            vmin=vmin,
            vmax=vmax,
            nodata=nodata,
            opacity=opacity,
            attribution=attribution,
            layer_name=layer_name,
            client_args=client_args,
            return_client=True,
        )

        self.add_tile_layer(
            tile_layer.url,
            opacity=opacity,
            visible=visible,
            tile_size=tile_size,
            **kwargs,
        )
        if zoom_to_layer:
            center = tile_client.center()
            zoom = tile_client.default_zoom

            self.view_state = {
                "latitude": center[0],
                "longitude": center[1],
                "zoom": zoom,
            }

__init__(center=(20, 0), zoom=1.2, height=600, layers=[], show_tooltip=True, view_state={}, **kwargs)

Initialize a Map object.

Parameters:

Name	Type	Description	Default
center	tuple	Center of the map in the format of (lat, lon). Defaults to (20, 0).	(20, 0)
zoom	float	The map zoom level. Defaults to 1.2.	1.2
height	int	Height of the map. Defaults to 600.	600
layers	list	List of additional layers to add to the map. Defaults to [].	[]
show_tooltip	bool	Flag to show tooltips on the map. Defaults to True.	True
view_state	dict	The view state of the map. Defaults to {}.	{}
**kwargs		Additional keyword arguments to pass to lonboard.Map.	{}

Returns:

Type	Description
None	None

Source code in leafmap/deckgl.py

def __init__(
    self,
    center: Tuple[float, float] = (20, 0),
    zoom: float = 1.2,
    height: int = 600,
    layers: List = [],
    show_tooltip: bool = True,
    view_state: Optional[Dict] = {},
    **kwargs,
) -> None:
    """Initialize a Map object.

    Args:
        center (tuple, optional): Center of the map in the format of (lat, lon). Defaults to (20, 0).
        zoom (float, optional): The map zoom level. Defaults to 1.2.
        height (int, optional): Height of the map. Defaults to 600.
        layers (list, optional): List of additional layers to add to the map. Defaults to [].
        show_tooltip (bool, optional): Flag to show tooltips on the map. Defaults to True.
        view_state (dict, optional): The view state of the map. Defaults to {}.
        **kwargs: Additional keyword arguments to pass to lonboard.Map.

    Returns:
        None
    """

    view_state["latitude"] = center[0]
    view_state["longitude"] = center[1]
    view_state["zoom"] = zoom
    kwargs["view_state"] = view_state

    super().__init__(
        _height=height,
        show_tooltip=show_tooltip,
        layers=layers,
        **kwargs,
    )

add_basemap(basemap='HYBRID', visible=True, **kwargs)

Adds a basemap to the map.

Parameters:

Name	Type	Description	Default
basemap	str	Can be one of string from basemaps. Defaults to 'HYBRID'.	'HYBRID'
visible	bool	Whether the basemap is visible or not. Defaults to True.	True
**kwargs		Keyword arguments for the TileLayer.	{}

Source code in leafmap/deckgl.py

def add_basemap(self, basemap="HYBRID", visible=True, **kwargs) -> None:
    """Adds a basemap to the map.

    Args:
        basemap (str, optional): Can be one of string from basemaps. Defaults to 'HYBRID'.
        visible (bool, optional): Whether the basemap is visible or not. Defaults to True.
        **kwargs: Keyword arguments for the TileLayer.
    """
    import xyzservices

    try:

        map_dict = {
            "ROADMAP": "Google Maps",
            "SATELLITE": "Google Satellite",
            "TERRAIN": "Google Terrain",
            "HYBRID": "Google Hybrid",
        }

        if isinstance(basemap, str):
            if basemap.upper() in map_dict:
                tile = common.get_google_map(basemap.upper())

                layer = lonboard.BitmapTileLayer(
                    data=tile.url,
                    min_zoom=tile.min_zoom,
                    max_zoom=tile.max_zoom,
                    visible=visible,
                    **kwargs,
                )

                self.add_layer(layer)
                return

        if isinstance(basemap, xyzservices.TileProvider):
            url = basemap.build_url()
            if "max_zoom" in basemap.keys():
                max_zoom = basemap["max_zoom"]
            else:
                max_zoom = 22
                layer = lonboard.BitmapTileLayer(
                    data=url,
                    min_zoom=tile.min_zoom,
                    max_zoom=max_zoom,
                    visible=visible,
                    **kwargs,
                )

                self.add_layer(layer)
        elif basemap in basemaps and basemaps[basemap].name:
            tile = basemaps[basemap]
            layer = lonboard.BitmapTileLayer(
                data=tile.url,
                min_zoom=tile.get("min_zoom", 0),
                max_zoom=tile.get("max_zoom", 24),
                visible=visible,
                **kwargs,
            )
            self.add_layer(layer)
        else:
            print(
                "Basemap can only be one of the following:\n  {}".format(
                    "\n  ".join(basemaps.keys())
                )
            )

    except Exception as e:
        raise ValueError(
            "Basemap can only be one of the following:\n  {}".format(
                "\n  ".join(basemaps.keys())
            )
        )

add_gdf(gdf, zoom_to_layer=True, pickable=True, color_column=None, color_scheme='Quantiles', color_map=None, color_k=5, color_args={}, alpha=1.0, rescale=True, zoom=10.0, **kwargs)

Adds a GeoPandas GeoDataFrame to the map.

Parameters:

Name	Type	Description	Default
gdf	GeoDataFrame	A GeoPandas GeoDataFrame with geometry column.	required
zoom_to_layer	bool	Flag to zoom to the added layer. Defaults to True.	True
pickable	bool	Flag to enable picking on the added layer. Defaults to True.	True
color_column	Optional[str]	The column to be used for color encoding. Defaults to None.	None
color_map	Optional[Union[str, Dict]]	The color map to use for color encoding. It can be a string or a dictionary. Defaults to None.	None
color_scheme	Optional[str]	The color scheme to use for color encoding. Defaults to "Quantiles". Name of a choropleth classification scheme (requires mapclassify). A mapclassify.MapClassifier object will be used under the hood. Supported are all schemes provided by mapclassify (e.g. 'BoxPlot', 'EqualInterval', 'FisherJenks', 'FisherJenksSampled', 'HeadTailBreaks', 'JenksCaspall', 'JenksCaspallForced', 'JenksCaspallSampled', 'MaxP', 'MaximumBreaks', 'NaturalBreaks', 'Quantiles', 'Percentiles', 'StdMean', 'UserDefined'). Arguments can be passed in classification_kwds.	'Quantiles'
color_k	Optional[int]	The number of classes to use for color encoding. Defaults to 5.	5
color_args	dict	Additional keyword arguments that will be passed to assign_continuous_colors(). Defaults to {}.	{}
zoom	Optional[float]	The zoom level to zoom to. Defaults to 10.0.	10.0
**kwargs	Any	Additional keyword arguments that will be passed to lonboard.Layer.from_geopandas()	{}

Returns:

Type	Description
None	None

Source code in leafmap/deckgl.py

def add_gdf(
    self,
    gdf: gpd.GeoDataFrame,
    zoom_to_layer: bool = True,
    pickable: bool = True,
    color_column: Optional[str] = None,
    color_scheme: Optional[str] = "Quantiles",
    color_map: Optional[Union[str, Dict]] = None,
    color_k: Optional[int] = 5,
    color_args: dict = {},
    alpha: Optional[float] = 1.0,
    rescale: bool = True,
    zoom: Optional[float] = 10.0,
    **kwargs: Any,
) -> None:
    """Adds a GeoPandas GeoDataFrame to the map.

    Args:
        gdf (GeoDataFrame): A GeoPandas GeoDataFrame with geometry column.
        zoom_to_layer (bool, optional): Flag to zoom to the added layer. Defaults to True.
        pickable (bool, optional): Flag to enable picking on the added layer. Defaults to True.
        color_column (Optional[str], optional): The column to be used for color encoding. Defaults to None.
        color_map (Optional[Union[str, Dict]], optional): The color map to use for color encoding. It can be a string or a dictionary. Defaults to None.
        color_scheme (Optional[str], optional): The color scheme to use for color encoding. Defaults to "Quantiles".
            Name of a choropleth classification scheme (requires mapclassify).
            A mapclassify.MapClassifier object will be used
            under the hood. Supported are all schemes provided by mapclassify (e.g.
            'BoxPlot', 'EqualInterval', 'FisherJenks', 'FisherJenksSampled',
            'HeadTailBreaks', 'JenksCaspall', 'JenksCaspallForced',
            'JenksCaspallSampled', 'MaxP', 'MaximumBreaks',
            'NaturalBreaks', 'Quantiles', 'Percentiles', 'StdMean',
            'UserDefined'). Arguments can be passed in classification_kwds.
        color_k (Optional[int], optional): The number of classes to use for color encoding. Defaults to 5.
        color_args (dict, optional): Additional keyword arguments that will be passed to assign_continuous_colors(). Defaults to {}.
        zoom (Optional[float], optional): The zoom level to zoom to. Defaults to 10.0.
        **kwargs: Additional keyword arguments that will be passed to lonboard.Layer.from_geopandas()

    Returns:
        None
    """

    from lonboard import ScatterplotLayer, PathLayer, SolidPolygonLayer
    import matplotlib.pyplot as plt

    geom_type = gdf.geometry.iloc[0].geom_type
    kwargs["pickable"] = pickable

    if geom_type in ["Point", "MultiPoint"]:
        if "get_radius" not in kwargs:
            kwargs["get_radius"] = 10
        if color_column is not None:
            if isinstance(color_map, str):
                kwargs["get_fill_color"] = apply_continuous_cmap(
                    gdf[color_column], color_map, alpha, rescale
                )
            elif isinstance(color_map, dict):
                kwargs["get_fill_color"] = apply_categorical_cmap(
                    gdf[color_column], color_map, alpha
                )

        if "get_fill_color" not in kwargs:
            kwargs["get_fill_color"] = [255, 0, 0, 180]
        layer = ScatterplotLayer.from_geopandas(gdf, **kwargs)
    elif geom_type in ["LineString", "MultiLineString"]:
        if "get_width" not in kwargs:
            kwargs["get_width"] = 5
        if color_column is not None:
            if isinstance(color_map, str):
                cmap = plt.get_cmap(color_map)
                kwargs["get_color"] = apply_continuous_cmap(
                    gdf[color_column], cmap, alpha, rescale
                )
            elif isinstance(color_map, dict):
                kwargs["get_color"] = apply_categorical_cmap(
                    gdf[color_column], color_map, alpha
                )
        layer = PathLayer.from_geopandas(gdf, **kwargs)
    elif geom_type in ["Polygon", "MultiPolygon"]:
        if color_column is not None:
            if isinstance(color_map, str):
                kwargs["get_fill_color"] = apply_continuous_cmap(
                    gdf[color_column], color_map, alpha, rescale
                )
            elif isinstance(color_map, dict):
                kwargs["get_fill_color"] = apply_categorical_cmap(
                    gdf[color_column], color_map, alpha
                )
        if "get_fill_color" not in kwargs:
            kwargs["get_fill_color"] = [0, 0, 255, 128]
        layer = SolidPolygonLayer.from_geopandas(gdf, **kwargs)

    self.layers = self.layers + (layer,)

    if zoom_to_layer:
        try:
            bounds = gdf.total_bounds.tolist()
            x = (bounds[0] + bounds[2]) / 2
            y = (bounds[1] + bounds[3]) / 2

            src_crs = gdf.crs
            if src_crs is None:
                src_crs = "EPSG:4326"

            lon, lat = common.convert_coordinates(x, y, src_crs, "EPSG:4326")

            self.view_state = {
                "latitude": lat,
                "longitude": lon,
                "zoom": zoom,
            }
        except Exception as e:
            print(e)

add_layer(layer, zoom_to_layer=True, pickable=True, **kwargs)

Adds a layer to the map.

Parameters:

Name	Type	Description	Default
layer	Any	A lonboard layer object.	required
zoom_to_layer	bool	Whether to zoom to the layer extent. Defaults to True.	True
pickable	bool	Flag to enable picking on the added layer if it's a vector layer. Defaults to True.	True
**kwargs	Any	Additional keyword arguments that will be passed to the vector layer if it's a vector layer.	{}

Returns:

Type	Description
None	None

Source code in leafmap/deckgl.py

def add_layer(
    self,
    layer: Any,
    zoom_to_layer: bool = True,
    pickable: bool = True,
    **kwargs: Any,
) -> None:
    """Adds a layer to the map.

    Args:
        layer (Any): A lonboard layer object.
        zoom_to_layer (bool, optional): Whether to zoom to the layer extent. Defaults to True.
        pickable (bool, optional): Flag to enable picking on the added layer if it's a vector layer. Defaults to True.
        **kwargs: Additional keyword arguments that will be passed to the vector layer if it's a vector layer.

    Returns:
        None
    """

    from lonboard import (
        BitmapLayer,
        BitmapTileLayer,
        HeatmapLayer,
        PathLayer,
        PointCloudLayer,
        PolygonLayer,
        ScatterplotLayer,
        SolidPolygonLayer,
    )

    if type(layer) in [
        BitmapLayer,
        BitmapTileLayer,
        HeatmapLayer,
        ScatterplotLayer,
        PathLayer,
        PointCloudLayer,
        PolygonLayer,
        SolidPolygonLayer,
    ]:
        self.layers = self.layers + (layer,)

        if zoom_to_layer:
            from lonboard._viewport import compute_view

            if hasattr(layer, "table"):
                try:
                    self.view_state = compute_view([self.layers[-1].table])
                except Exception as e:
                    print(e)
    else:
        self.add_vector(
            layer, zoom_to_layer=zoom_to_layer, pickable=pickable, **kwargs
        )

add_raster(source, indexes=None, colormap=None, vmin=None, vmax=None, nodata=None, tile_size=256, attribution=None, layer_name='Raster', zoom_to_layer=True, visible=True, opacity=1.0, array_args={}, client_args={'cors_all': True}, **kwargs)

Add a local raster dataset to the map. If you are using this function in JupyterHub on a remote server (e.g., Binder, Microsoft Planetary Computer) and if the raster does not render properly, try installing jupyter-server-proxy using pip install jupyter-server-proxy, then running the following code before calling this function. For more info, see https://bit.ly/3JbmF93.

import os
os.environ['LOCALTILESERVER_CLIENT_PREFIX'] = 'proxy/{port}'

Parameters:

Name	Type	Description	Default
source	str	The path to the GeoTIFF file or the URL of the Cloud Optimized GeoTIFF.	required
indexes	int	The band(s) to use. Band indexing starts at 1. Defaults to None.	None
colormap	str	The name of the colormap from matplotlib to use when plotting a single band. See https://matplotlib.org/stable/gallery/color/colormap_reference.html. Default is greyscale.	None
vmin	float	The minimum value to use when colormapping the palette when plotting a single band. Defaults to None.	None
vmax	float	The maximum value to use when colormapping the palette when plotting a single band. Defaults to None.	None
nodata	float	The value from the band to use to interpret as not valid data. Defaults to None.	None
attribution	str	Attribution for the source raster. This defaults to a message about it being a local file.. Defaults to None.	None
layer_name	str	The layer name to use. Defaults to 'Raster'.	'Raster'
layer_index	int	The index of the layer. Defaults to None.	required
zoom_to_layer	bool	Whether to zoom to the extent of the layer. Defaults to True.	True
visible	bool	Whether the layer is visible. Defaults to True.	True
opacity	float	The opacity of the layer. Defaults to 1.0.	1.0
array_args	dict	Additional arguments to pass to array_to_memory_file when reading the raster. Defaults to {}.	{}
client_args	dict	Additional arguments to pass to localtileserver.TileClient. Defaults to { "cors_all": False }.	{'cors_all': True}

Source code in leafmap/deckgl.py

def add_raster(
    self,
    source: str,
    indexes: Optional[int] = None,
    colormap: Optional[str] = None,
    vmin: Optional[float] = None,
    vmax: Optional[float] = None,
    nodata: Optional[float] = None,
    tile_size: Optional[int] = 256,
    attribution: Optional[str] = None,
    layer_name: Optional[str] = "Raster",
    zoom_to_layer: Optional[bool] = True,
    visible: Optional[bool] = True,
    opacity: Optional[float] = 1.0,
    array_args: Optional[Dict] = {},
    client_args: Optional[Dict] = {"cors_all": True},
    **kwargs,
) -> None:
    """Add a local raster dataset to the map.
        If you are using this function in JupyterHub on a remote server (e.g., Binder, Microsoft Planetary Computer) and
        if the raster does not render properly, try installing jupyter-server-proxy using `pip install jupyter-server-proxy`,
        then running the following code before calling this function. For more info, see https://bit.ly/3JbmF93.

        import os
        os.environ['LOCALTILESERVER_CLIENT_PREFIX'] = 'proxy/{port}'

    Args:
        source (str): The path to the GeoTIFF file or the URL of the Cloud Optimized GeoTIFF.
        indexes (int, optional): The band(s) to use. Band indexing starts at 1. Defaults to None.
        colormap (str, optional): The name of the colormap from `matplotlib` to use when plotting a single band. See https://matplotlib.org/stable/gallery/color/colormap_reference.html. Default is greyscale.
        vmin (float, optional): The minimum value to use when colormapping the palette when plotting a single band. Defaults to None.
        vmax (float, optional): The maximum value to use when colormapping the palette when plotting a single band. Defaults to None.
        nodata (float, optional): The value from the band to use to interpret as not valid data. Defaults to None.
        attribution (str, optional): Attribution for the source raster. This defaults to a message about it being a local file.. Defaults to None.
        layer_name (str, optional): The layer name to use. Defaults to 'Raster'.
        layer_index (int, optional): The index of the layer. Defaults to None.
        zoom_to_layer (bool, optional): Whether to zoom to the extent of the layer. Defaults to True.
        visible (bool, optional): Whether the layer is visible. Defaults to True.
        opacity (float, optional): The opacity of the layer. Defaults to 1.0.
        array_args (dict, optional): Additional arguments to pass to `array_to_memory_file` when reading the raster. Defaults to {}.
        client_args (dict, optional): Additional arguments to pass to localtileserver.TileClient. Defaults to { "cors_all": False }.
    """
    import numpy as np
    import xarray as xr

    if isinstance(source, np.ndarray) or isinstance(source, xr.DataArray):
        source = common.array_to_image(source, **array_args)

    tile_layer, tile_client = common.get_local_tile_layer(
        source,
        indexes=indexes,
        colormap=colormap,
        vmin=vmin,
        vmax=vmax,
        nodata=nodata,
        opacity=opacity,
        attribution=attribution,
        layer_name=layer_name,
        client_args=client_args,
        return_client=True,
    )

    self.add_tile_layer(
        tile_layer.url,
        opacity=opacity,
        visible=visible,
        tile_size=tile_size,
        **kwargs,
    )
    if zoom_to_layer:
        center = tile_client.center()
        zoom = tile_client.default_zoom

        self.view_state = {
            "latitude": center[0],
            "longitude": center[1],
            "zoom": zoom,
        }

add_tile_layer(url, opacity=1.0, visible=True, tile_size=256, **kwargs)

Adds a TileLayer to the map.

This method adds a TileLayer to the map. The TileLayer is created from the specified URL, and it is added to the map with the specified name, attribution, visibility, and tile size.

Parameters:

Name	Type	Description	Default
url	str	The URL of the tile layer.	required
opacity	float	The opacity of the layer. Defaults to 1.0.	1.0
visible	bool	Whether the layer should be visible by default. Defaults to True.	True
tile_size	int	The size of the tiles in the layer. Defaults to 256.	256
**kwargs	Any	Additional keyword arguments that are passed to the lonboard.BitmapTileLayer class. See https://developmentseed.org/lonboard/latest/api/layers/bitmap-tile-layer/#lonboard.BitmapTileLayer.	{}

Returns:

Type	Description
None	None

Source code in leafmap/deckgl.py

def add_tile_layer(
    self,
    url: str,
    opacity: float = 1.0,
    visible: bool = True,
    tile_size: int = 256,
    **kwargs: Any,
) -> None:
    """
    Adds a TileLayer to the map.

    This method adds a TileLayer to the map. The TileLayer is created from
        the specified URL, and it is added to the map with the specified
        name, attribution, visibility, and tile size.

    Args:
        url (str): The URL of the tile layer.
        opacity (float, optional): The opacity of the layer. Defaults to 1.0.
        visible (bool, optional): Whether the layer should be visible by
            default. Defaults to True.
        tile_size (int, optional): The size of the tiles in the layer.
            Defaults to 256.
        **kwargs: Additional keyword arguments that are passed to the lonboard.BitmapTileLayer class.
            See https://developmentseed.org/lonboard/latest/api/layers/bitmap-tile-layer/#lonboard.BitmapTileLayer.

    Returns:
        None
    """

    layer = lonboard.BitmapTileLayer(
        data=url,
        tile_size=tile_size,
        opacity=opacity,
        visible=visible,
        **kwargs,
    )
    self.add_layer(layer)

add_vector(vector, zoom_to_layer=True, pickable=True, color_column=None, color_scheme='Quantiles', color_map=None, color_k=5, color_args={}, open_args={}, **kwargs)

Adds a vector layer to the map.

Parameters:

Name	Type	Description	Default
vector	Union[str, GeoDataFrame]	The file path or URL to the vector data, or a GeoDataFrame.	required
zoom_to_layer	bool	Flag to zoom to the added layer. Defaults to True.	True
pickable	bool	Flag to enable picking on the added layer. Defaults to True.	True
color_column	Optional[str]	The column to be used for color encoding. Defaults to None.	None
color_map	Optional[Union[str, Dict]]	The color map to use for color encoding. It can be a string or a dictionary. Defaults to None.	None
color_scheme	Optional[str]	The color scheme to use for color encoding. Defaults to "Quantiles". Name of a choropleth classification scheme (requires mapclassify). A mapclassify.MapClassifier object will be used under the hood. Supported are all schemes provided by mapclassify (e.g. 'BoxPlot', 'EqualInterval', 'FisherJenks', 'FisherJenksSampled', 'HeadTailBreaks', 'JenksCaspall', 'JenksCaspallForced', 'JenksCaspallSampled', 'MaxP', 'MaximumBreaks', 'NaturalBreaks', 'Quantiles', 'Percentiles', 'StdMean', 'UserDefined'). Arguments can be passed in classification_kwds.	'Quantiles'
color_k	Optional[int]	The number of classes to use for color encoding. Defaults to 5.	5
color_args	dict	Additional keyword arguments that will be passed to assign_continuous_colors(). Defaults to {}.	{}
open_args	dict	Additional keyword arguments that will be passed to geopandas.read_file(). Defaults to {}.	{}
**kwargs	Any	Additional keyword arguments that will be passed to lonboard.Layer.from_geopandas()	{}

Returns:

Type	Description
None	None

Source code in leafmap/deckgl.py

def add_vector(
    self,
    vector: Union[str, gpd.GeoDataFrame],
    zoom_to_layer: bool = True,
    pickable: bool = True,
    color_column: Optional[str] = None,
    color_scheme: Optional[str] = "Quantiles",
    color_map: Optional[Union[str, Dict]] = None,
    color_k: Optional[int] = 5,
    color_args: dict = {},
    open_args: dict = {},
    **kwargs: Any,
) -> None:
    """Adds a vector layer to the map.

    Args:
        vector (Union[str, GeoDataFrame]): The file path or URL to the vector data, or a GeoDataFrame.
        zoom_to_layer (bool, optional): Flag to zoom to the added layer. Defaults to True.
        pickable (bool, optional): Flag to enable picking on the added layer. Defaults to True.
        color_column (Optional[str], optional): The column to be used for color encoding. Defaults to None.
        color_map (Optional[Union[str, Dict]], optional): The color map to use for color encoding. It can be a string or a dictionary. Defaults to None.
        color_scheme (Optional[str], optional): The color scheme to use for color encoding. Defaults to "Quantiles".
            Name of a choropleth classification scheme (requires mapclassify).
            A mapclassify.MapClassifier object will be used
            under the hood. Supported are all schemes provided by mapclassify (e.g.
            'BoxPlot', 'EqualInterval', 'FisherJenks', 'FisherJenksSampled',
            'HeadTailBreaks', 'JenksCaspall', 'JenksCaspallForced',
            'JenksCaspallSampled', 'MaxP', 'MaximumBreaks',
            'NaturalBreaks', 'Quantiles', 'Percentiles', 'StdMean',
            'UserDefined'). Arguments can be passed in classification_kwds.
        color_k (Optional[int], optional): The number of classes to use for color encoding. Defaults to 5.
        color_args (dict, optional): Additional keyword arguments that will be passed to assign_continuous_colors(). Defaults to {}.
        open_args (dict, optional): Additional keyword arguments that will be passed to geopandas.read_file(). Defaults to {}.
        **kwargs: Additional keyword arguments that will be passed to lonboard.Layer.from_geopandas()

    Returns:
        None
    """

    if isinstance(vector, gpd.GeoDataFrame):
        gdf = vector
    else:
        gdf = gpd.read_file(vector, **open_args)
    self.add_gdf(
        gdf,
        zoom_to_layer,
        pickable,
        color_column,
        color_scheme,
        color_map,
        color_k,
        color_args,
        **kwargs,
    )

to_html(filename=None)

Saves the map as an HTML file.

Parameters:

Name	Type	Description	Default
filename	Optional[str]	The output file path to the HTML file. Defaults to None.	None

Returns:

Name	Type	Description
str	None	The HTML content if filename is None.

Source code in leafmap/deckgl.py

def to_html(self, filename: Optional[str] = None) -> None:
    """Saves the map as an HTML file.

    Args:
        filename (Optional[str], optional): The output file path to the HTML file. Defaults to None.

    Returns:
        str: The HTML content if filename is None.
    """

    if filename is None:
        filename = common.temp_file_path("html")
        super().to_html(filename)
        with open(filename) as f:
            html = f.read()
        return html
    else:
        super().to_html(filename)

to_streamlit(width=None, height=600, scrolling=False, **kwargs)

Renders deckgl.Mapin a Streamlit app. This method is a static Streamlit Component, meaning, no information is passed back from Leaflet on browser interaction.

Parameters:

Name	Type	Description	Default
width	int	Width of the map. Defaults to None.	None
height	int	Height of the map. Defaults to 600.	600
scrolling	bool	Whether to allow the map to scroll. Defaults to False.	False

Returns:

Type	Description
	streamlit.components: components.html object.

Source code in leafmap/deckgl.py

def to_streamlit(
    self,
    width: Optional[int] = None,
    height: Optional[int] = 600,
    scrolling: Optional[bool] = False,
    **kwargs,
):
    """Renders `deckgl.Map`in a Streamlit app. This method is a static Streamlit Component, meaning, no information is passed back from Leaflet on browser interaction.

    Args:
        width (int, optional): Width of the map. Defaults to None.
        height (int, optional): Height of the map. Defaults to 600.
        scrolling (bool, optional): Whether to allow the map to scroll. Defaults to False.

    Returns:
        streamlit.components: components.html object.
    """

    try:
        import streamlit.components.v1 as components

        return components.html(
            self.to_html(), width=width, height=height, scrolling=scrolling
        )

    except Exception as e:
        raise e

apply_categorical_cmap(values, cmap, alpha=None, **kwargs)

Apply a categorical colormap to a set of values.

This function applies a specified categorical colormap to the input values.

Parameters:

Name	Type	Description	Default
values	array - like	The input values to which the colormap will be applied.	required
cmap	str or Colormap	The colormap to apply. Can be a string name of a matplotlib colormap or a Colormap object.	required
alpha	float	The alpha transparency to apply to the colormap. Defaults to None.	None
**kwargs		Additional keyword arguments to pass to the colormap function.	{}

Returns:

Name	Type	Description
array		The colors mapped to the input values.

Source code in leafmap/deckgl.py

def apply_categorical_cmap(values, cmap, alpha=None, **kwargs):
    """
    Apply a categorical colormap to a set of values.

    This function applies a specified categorical colormap to the input values.

    Args:
        values (array-like): The input values to which the colormap will be applied.
        cmap (str or Colormap): The colormap to apply. Can be a string name of a matplotlib colormap or a Colormap object.
        alpha (float, optional): The alpha transparency to apply to the colormap. Defaults to None.
        **kwargs: Additional keyword arguments to pass to the colormap function.

    Returns:
        array: The colors mapped to the input values.
    """
    return lonboard.colormap.apply_categorical_cmap(values, cmap, alpha=alpha, **kwargs)

apply_continuous_cmap(values, cmap, alpha=None, rescale=True, **kwargs)

Apply a continuous colormap to a set of values.

This function rescales the input values to the range [0, 1] if rescale is True, and then applies the specified colormap.

Parameters:

Name	Type	Description	Default
values	array - like	The input values to which the colormap will be applied.	required
cmap	str or Colormap	The colormap to apply. Can be a string name of a matplotlib colormap or a Colormap object.	required
alpha	float	The alpha transparency to apply to the colormap. Defaults to None.	None
rescale	bool	If True, rescales the input values to the range [0, 1]. Defaults to True.	True
**kwargs		Additional keyword arguments to pass to the colormap function.	{}

Returns:

Name	Type	Description
array		The colors mapped to the input values.

Source code in leafmap/deckgl.py

def apply_continuous_cmap(values, cmap, alpha=None, rescale=True, **kwargs):
    """
    Apply a continuous colormap to a set of values.

    This function rescales the input values to the range [0, 1] if `rescale` is True,
    and then applies the specified colormap.

    Args:
        values (array-like): The input values to which the colormap will be applied.
        cmap (str or Colormap): The colormap to apply. Can be a string name of a matplotlib colormap or a Colormap object.
        alpha (float, optional): The alpha transparency to apply to the colormap. Defaults to None.
        rescale (bool, optional): If True, rescales the input values to the range [0, 1]. Defaults to True.
        **kwargs: Additional keyword arguments to pass to the colormap function.

    Returns:
        array: The colors mapped to the input values.
    """
    import numpy as np
    import matplotlib.pyplot as plt

    if rescale:
        values = np.array(values)
        values = (values - values.min()) / (values.max() - values.min())

    if isinstance(cmap, str):
        cmap = plt.get_cmap(cmap)

    return lonboard.colormap.apply_continuous_cmap(values, cmap, alpha=alpha, **kwargs)