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deckgl module

Map (Map)

The Map class inherits lonboard.Map.

Returns:

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

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(self, 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(self, 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(self, 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(self, 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.

1
2
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(self, 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(self, 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(self, 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:

Type Description
str

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(self, 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:

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:

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)