import colorcet as cc import geopandas as gpd import param from lonboard import Map, PathLayer from lonboard.colormap import apply_continuous_cmap from lonboard._viewport import compute_view from palettable.palette import Palette import panel as pn pn.extension("ipywidgets") url = "https://naciscdn.org/naturalearth/10m/cultural/ne_10m_roads_north_america.zip" @pn.cache def get_data(): return gpd.read_file(filename=url, engine="pyogrio") gdf = get_data() state_options = sorted(state for state in gdf["state"].unique() if state) description = """# Lonboard A Python library for **fast, interactive geospatial vector data visualization** in Jupyter (and Panel). By utilizing new technologies like `GeoArrow` and `GeoParquet` in conjunction with GPU-based map rendering, Lonboard aims to enable visualizing large geospatial datasets interactively through a simple interface.""" logo = pn.pane.Image( "https://github.com/developmentseed/lonboard/raw/main/assets/dalle-lonboard.jpg" ) def to_rgb(hex: str) -> list: h = hex.strip("#") return list(int(h[i : i + 2], 16) for i in (0, 2, 4)) def to_palette(cmap) -> Palette: """Returns the ColorCet colormap as a palettable Palette""" colors = [to_rgb(item) for item in cmap] return Palette(name="colorcet", map_type="colorcet", colors=colors) class StateViewer(pn.viewable.Viewer): value: Map = param.ClassSelector(class_=Map, doc="The map object", constant=True) state: str = param.Selector(default="California", objects=state_options) cmap: str = param.Selector(default=cc.fire, objects=cc.palette, label="cmap by Colorcet") alpha: float = param.Number(default=0.8, bounds=(0, 1)) data = param.DataFrame() def __init__(self, **params): params["value"] = params.get("value", Map(layers=[], view_state={"longitude": -119.81446785010868, "latitude": 36.08305565437565, "zoom": 5})) super().__init__(**params) self.value.layout.width=self.value.layout.height="100%" self.description = pn.Column(pn.pane.Markdown(description, margin=5), logo) self.settings = pn.Column( pn.widgets.Select.from_param(self.param.state, sizing_mode="stretch_width"), pn.widgets.ColorMap.from_param( self.param.cmap, ncols=3, swatch_width=100, name="cmap by Colorcet", sizing_mode="stretch_width", ), pn.widgets.FloatSlider.from_param( self.param.alpha, sizing_mode="stretch_width" ), margin=5, sizing_mode="fixed", width=300, ) self.view = pn.Column( self._title, pn.pane.IPyWidget(self.value, sizing_mode="stretch_both") ) self._layout = pn.Row( pn.Column(self.settings, sizing_mode="fixed", width=300), self.view, sizing_mode="stretch_both", ) def __panel__(self): return self._layout @param.depends("state", watch=True, on_init=True) def _update_data(self): self.data = gdf[gdf["state"] == self.state] def _get_color(self): palette = to_palette(self.cmap) normalized_scale_rank = (self.data["scalerank"] - 3) / 9 return apply_continuous_cmap(normalized_scale_rank, palette, alpha=self.alpha) @param.depends("data", watch=True) def _update_value(self): layer = PathLayer.from_geopandas(self.data, width_min_pixels=0.8) layer.get_color = self._get_color() self.value.layers = [layer] self._fly_to_center() def _fly_to_center(self): computed_view_state = compute_view(self.value.layers) self.value.fly_to( **computed_view_state, duration=1000, ) @param.depends("cmap", "alpha", watch=True) def _update_layer_get_color(self): self.value.layers[0].get_color = self._get_color() @param.depends("state") def _title(self): return f"# North America Roads: {self.state}" viewer = StateViewer() pn.template.FastListTemplate( logo="https://panel.holoviz.org/_static/logo_horizontal_dark_theme.png", title="Works with Lonboard", sidebar=[viewer.description, viewer.settings], main=[viewer.view], main_layout=None, ).servable()