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 = 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 = 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 = 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())
)
)
__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 = 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 = 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_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 = 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.Map
in 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)