Source code for geemap.geemap

"""Main module for interactive mapping using Google Earth Engine Python API and ipyleaflet.
Keep in mind that Earth Engine functions use both camel case and snake case, such as setOptions(), setCenter(), centerObject(), addLayer().
ipyleaflet functions use snake case, such as add_tile_layer(), add_wms_layer(), add_minimap().
"""

import math
import os
import pkg_resources
import time

import ee
import ipyevents
import ipyleaflet
import ipywidgets as widgets
from box import Box
from bqplot import pyplot as plt
from ipyfilechooser import FileChooser
from IPython.display import display
from ipytree import Node, Tree
from .basemaps import xyz_to_leaflet
from .common import *
from .conversion import *
from .legends import builtin_legends
from .timelapse import *
from .osm import *
from .plot import *

from . import examples


basemaps = Box(xyz_to_leaflet(), frozen_box=True)


[docs]class Map(ipyleaflet.Map): """The Map class inherits from ipyleaflet.Map. The arguments you can pass to the Map can be found at https://ipyleaflet.readthedocs.io/en/latest/api_reference/map.html. By default, the Map will add Google Maps as the basemap. Set add_google_map = False to use OpenStreetMap as the basemap. Returns: object: ipyleaflet map object. """ def __init__(self, **kwargs): import warnings warnings.filterwarnings("ignore") # Authenticates Earth Engine and initializes an Earth Engine session if "ee_initialize" not in kwargs.keys(): kwargs["ee_initialize"] = True if kwargs["ee_initialize"]: ee_initialize() # Default map center location (lat, lon) and zoom level latlon = [20, 0] zoom = 2 # Interchangeable parameters between ipyleaflet and folium if "height" not in kwargs.keys(): kwargs["height"] = "600px" elif isinstance(kwargs["height"], int): kwargs["height"] = str(kwargs["height"]) + "px" if "width" in kwargs.keys() and isinstance(kwargs["width"], int): kwargs["width"] = str(kwargs["width"]) + "px" if "location" in kwargs.keys(): kwargs["center"] = kwargs["location"] kwargs.pop("location") if "center" not in kwargs.keys(): kwargs["center"] = latlon if "zoom_start" in kwargs.keys(): kwargs["zoom"] = kwargs["zoom_start"] kwargs.pop("zoom_start") if "zoom" not in kwargs.keys(): kwargs["zoom"] = zoom if "max_zoom" not in kwargs.keys(): kwargs["max_zoom"] = 24 if "add_google_map" not in kwargs.keys() and "basemap" not in kwargs.keys(): kwargs["add_google_map"] = True if "scroll_wheel_zoom" not in kwargs.keys(): kwargs["scroll_wheel_zoom"] = True if "lite_mode" not in kwargs.keys(): kwargs["lite_mode"] = False if kwargs["lite_mode"]: kwargs["data_ctrl"] = False kwargs["zoom_ctrl"] = True kwargs["fullscreen_ctrl"] = False kwargs["draw_ctrl"] = False kwargs["search_ctrl"] = False kwargs["measure_ctrl"] = False kwargs["scale_ctrl"] = False kwargs["layer_ctrl"] = False kwargs["toolbar_ctrl"] = False kwargs["attribution_ctrl"] = False if "data_ctrl" not in kwargs.keys(): kwargs["data_ctrl"] = True if "zoom_ctrl" not in kwargs.keys(): kwargs["zoom_ctrl"] = True if "fullscreen_ctrl" not in kwargs.keys(): kwargs["fullscreen_ctrl"] = True if "draw_ctrl" not in kwargs.keys(): kwargs["draw_ctrl"] = True if "search_ctrl" not in kwargs.keys(): kwargs["search_ctrl"] = False if "measure_ctrl" not in kwargs.keys(): kwargs["measure_ctrl"] = True if "scale_ctrl" not in kwargs.keys(): kwargs["scale_ctrl"] = True if "layer_ctrl" not in kwargs.keys(): kwargs["layer_ctrl"] = False if "toolbar_ctrl" not in kwargs.keys(): kwargs["toolbar_ctrl"] = True if "attribution_ctrl" not in kwargs.keys(): kwargs["attribution_ctrl"] = True if "use_voila" not in kwargs.keys(): kwargs["use_voila"] = False if ( "basemap" in kwargs.keys() and isinstance(kwargs["basemap"], str) and kwargs["basemap"] in basemaps.keys() ): kwargs["basemap"] = basemaps[kwargs["basemap"]] if os.environ.get("USE_VOILA") is not None: kwargs["use_voila"] = True # Inherits the ipyleaflet Map class super().__init__(**kwargs) self.baseclass = "ipyleaflet" self.layout.height = kwargs["height"] if "width" in kwargs: self.layout.width = kwargs["width"] # sandbox path for Voila app to restrict access to system directories. if "sandbox_path" not in kwargs: if os.environ.get("USE_VOILA") is not None: self.sandbox_path = os.getcwd() else: self.sandbox_path = None else: if os.path.exists(os.path.abspath(kwargs["sandbox_path"])): self.sandbox_path = kwargs["sandbox_path"] else: print("The sandbox path is invalid.") self.sandbox_path = None self.clear_controls() # The number of shapes drawn by the user using the DrawControl self.draw_count = 0 # The list of Earth Engine Geometry objects converted from geojson self.draw_features = [] # The Earth Engine Geometry object converted from the last drawn feature self.draw_last_feature = None self.draw_layer = None self.draw_last_json = None self.draw_last_bounds = None self.user_roi = None self.user_rois = None self.last_ee_data = None self.last_ee_layer = None self.geojson_layers = [] self.roi_start = False self.roi_end = False if kwargs["ee_initialize"]: self.roi_reducer = ee.Reducer.mean() self.roi_reducer_scale = None # List for storing pixel values and locations based on user-drawn geometries. self.chart_points = [] self.chart_values = [] self.chart_labels = None self.plot_widget = None # The plot widget for plotting Earth Engine data self.plot_control = None # The plot control for interacting plotting self.random_marker = None self.legend_widget = None self.legend = None self.colorbar = None self.ee_layers = [] self.ee_layer_names = [] self.ee_raster_layers = [] self.ee_raster_layer_names = [] self.ee_vector_layers = [] self.ee_vector_layer_names = [] self.ee_layer_dict = {} self.search_locations = None self.search_loc_marker = None self.search_loc_geom = None self.search_datasets = None self.screenshot = None self.toolbar = None self.toolbar_button = None self.vis_control = None self.vis_widget = None self.colorbar_ctrl = None self.colorbar_widget = None self.tool_output = None self.tool_output_ctrl = None self.layer_control = None self.convert_ctrl = None self._expand_point = False self._expand_pixels = True self._expand_objects = False # Adds search button and search box search_button = widgets.ToggleButton( value=False, tooltip="Search location/data", icon="globe", layout=widgets.Layout( width="28px", height="28px", padding="0px 0px 0px 4px" ), ) search_type = widgets.ToggleButtons( options=["name/address", "lat-lon", "data"], tooltips=[ "Search by place name or address", "Search by lat-lon coordinates", "Search Earth Engine data catalog", ], ) search_type.style.button_width = "110px" search_box = widgets.Text( placeholder="Search by place name or address", tooltip="Search location", layout=widgets.Layout(width="340px"), ) search_output = widgets.Output( layout={ "max_width": "340px", "max_height": "350px", "overflow": "scroll", } ) search_results = widgets.RadioButtons() assets_dropdown = widgets.Dropdown( options=[], layout=widgets.Layout(min_width="279px", max_width="279px"), ) import_btn = widgets.Button( description="import", button_style="primary", tooltip="Click to import the selected asset", layout=widgets.Layout(min_width="57px", max_width="57px"), ) def get_ee_example(asset_id): try: pkg_dir = os.path.dirname( pkg_resources.resource_filename("geemap", "geemap.py") ) with open( os.path.join(pkg_dir, "data/gee_f.json"), encoding="utf-8" ) as f: functions = json.load(f) details = [ dataset["code"] for x in functions["examples"] for dataset in x["contents"] if x["name"] == "Datasets" if dataset["name"] == asset_id.replace("/", "_") ] return js_snippet_to_py( details[0], add_new_cell=False, import_ee=False, import_geemap=False, show_map=False, ) except Exception as e: pass return def import_btn_clicked(b): if assets_dropdown.value is not None: datasets = self.search_datasets dataset = datasets[assets_dropdown.index] id_ = dataset["id"] code = get_ee_example(id_) if not code: dataset_uid = "dataset_" + random_string(string_length=3) translate = { "image_collection": "ImageCollection", "image": "Image", "table": "FeatureCollection", "table_collection": "FeatureCollection", } datatype = translate[dataset["type"]] id_ = dataset["id"] line1 = "{} = ee.{}('{}')".format(dataset_uid, datatype, id_) action = { "image_collection": f"\nMap.addLayer({dataset_uid}, {{}}, '{id_}')", "image": f"\nMap.addLayer({dataset_uid}, {{}}, '{id_}')", "table": f"\nMap.addLayer({dataset_uid}, {{}}, '{id_}')", "table_collection": f"\nMap.addLayer({dataset_uid}, {{}}, '{id_}')", } line2 = action[dataset["type"]] code = [line1, line2] contents = "".join(code).strip() create_code_cell(contents) with search_output: search_output.clear_output(wait=True) print(contents) import_btn.on_click(import_btn_clicked) html_widget = widgets.HTML() def dropdown_change(change): dropdown_index = assets_dropdown.index if dropdown_index is not None and dropdown_index >= 0: with search_output: search_output.clear_output(wait=True) print("Loading ...") datasets = self.search_datasets dataset = datasets[dropdown_index] dataset_html = ee_data_html(dataset) html_widget.value = dataset_html search_output.clear_output(wait=True) display(html_widget) assets_dropdown.observe(dropdown_change, names="value") assets_combo = widgets.HBox() assets_combo.children = [import_btn, assets_dropdown] def search_result_change(change): result_index = search_results.index locations = self.search_locations location = locations[result_index] latlon = (location.lat, location.lng) self.search_loc_geom = ee.Geometry.Point(location.lng, location.lat) marker = self.search_loc_marker marker.location = latlon self.center = latlon search_results.observe(search_result_change, names="value") def search_btn_click(change): if change["new"]: search_widget.children = [search_button, search_result_widget] search_type.value = "name/address" else: search_widget.children = [search_button] search_result_widget.children = [search_type, search_box] search_button.observe(search_btn_click, "value") def search_type_changed(change): search_box.value = "" search_output.clear_output() if change["new"] == "data": search_box.placeholder = ( "Search GEE data catalog by keywords, e.g., elevation" ) search_result_widget.children = [ search_type, search_box, assets_combo, search_output, ] elif change["new"] == "lat-lon": search_box.placeholder = "Search by lat-lon, e.g., 40, -100" assets_dropdown.options = [] search_result_widget.children = [ search_type, search_box, search_output, ] elif change["new"] == "name/address": search_box.placeholder = "Search by place name or address, e.g., Paris" assets_dropdown.options = [] search_result_widget.children = [ search_type, search_box, search_output, ] search_type.observe(search_type_changed, names="value") def search_box_callback(text): if text.value != "": if search_type.value == "name/address": g = geocode(text.value) elif search_type.value == "lat-lon": g = geocode(text.value, reverse=True) if g is None and latlon_from_text(text.value): search_output.clear_output() latlon = latlon_from_text(text.value) self.search_loc_geom = ee.Geometry.Point(latlon[1], latlon[0]) if self.search_loc_marker is None: marker = ipyleaflet.Marker( location=latlon, draggable=False, name="Search location", ) self.search_loc_marker = marker self.add_layer(marker) self.center = latlon else: marker = self.search_loc_marker marker.location = latlon self.center = latlon with search_output: print(f"No address found for {latlon}") return elif search_type.value == "data": search_output.clear_output() with search_output: print("Searching ...") self.default_style = {"cursor": "wait"} ee_assets = search_ee_data(text.value, source="all") self.search_datasets = ee_assets asset_titles = [x["title"] for x in ee_assets] assets_dropdown.options = asset_titles search_output.clear_output() if len(ee_assets) > 0: html_widget.value = ee_data_html(ee_assets[0]) with search_output: display(html_widget) self.default_style = {"cursor": "default"} return self.search_locations = g if g is not None and len(g) > 0: top_loc = g[0] latlon = (top_loc.lat, top_loc.lng) self.search_loc_geom = ee.Geometry.Point(top_loc.lng, top_loc.lat) if self.search_loc_marker is None: marker = ipyleaflet.Marker( location=latlon, draggable=False, name="Search location", ) self.search_loc_marker = marker self.add_layer(marker) self.center = latlon else: marker = self.search_loc_marker marker.location = latlon self.center = latlon search_results.options = [x.address for x in g] search_result_widget.children = [ search_type, search_box, search_output, ] with search_output: search_output.clear_output(wait=True) display(search_results) else: with search_output: search_output.clear_output() print("No results could be found.") search_box.on_submit(search_box_callback) search_result_widget = widgets.VBox([search_type, search_box]) search_widget = widgets.HBox([search_button]) search_event = ipyevents.Event( source=search_widget, watched_events=["mouseenter", "mouseleave"] ) def handle_search_event(event): if event["type"] == "mouseenter": search_widget.children = [search_button, search_result_widget] # search_type.value = "name/address" elif event["type"] == "mouseleave": if not search_button.value: search_widget.children = [search_button] search_result_widget.children = [search_type, search_box] search_event.on_dom_event(handle_search_event) data_control = ipyleaflet.WidgetControl( widget=search_widget, position="topleft" ) if kwargs.get("data_ctrl"): self.add_control(control=data_control) search_marker = ipyleaflet.Marker( icon=ipyleaflet.AwesomeIcon( name="check", marker_color="green", icon_color="darkgreen" ) ) search = ipyleaflet.SearchControl( position="topleft", url="https://nominatim.openstreetmap.org/search?format=json&q={s}", zoom=5, property_name="display_name", marker=search_marker, ) if kwargs.get("search_ctrl"): self.add_control(search) if kwargs.get("zoom_ctrl"): self.add_control(ipyleaflet.ZoomControl(position="topleft")) if kwargs.get("layer_ctrl"): layer_control = ipyleaflet.LayersControl(position="topright") self.layer_control = layer_control self.add_control(layer_control) if kwargs.get("scale_ctrl"): scale = ipyleaflet.ScaleControl(position="bottomleft") self.scale_control = scale self.add_control(scale) if kwargs.get("fullscreen_ctrl"): fullscreen = ipyleaflet.FullScreenControl() self.fullscreen_control = fullscreen self.add_control(fullscreen) if kwargs.get("measure_ctrl"): measure = ipyleaflet.MeasureControl( position="bottomleft", active_color="orange", primary_length_unit="kilometers", ) self.measure_control = measure self.add_control(measure) if kwargs.get("add_google_map"): self.add_layer(basemaps["ROADMAP"]) if kwargs.get("attribution_ctrl"): self.add_control(ipyleaflet.AttributionControl(position="bottomright")) draw_control = ipyleaflet.DrawControl( marker={"shapeOptions": {"color": "#3388ff"}}, rectangle={"shapeOptions": {"color": "#3388ff"}}, circle={"shapeOptions": {"color": "#3388ff"}}, circlemarker={}, edit=True, remove=True, ) draw_control_lite = ipyleaflet.DrawControl( marker={}, rectangle={"shapeOptions": {"color": "#3388ff"}}, circle={"shapeOptions": {"color": "#3388ff"}}, circlemarker={}, polyline={}, polygon={}, edit=False, remove=False, ) # Handles draw events def handle_draw(target, action, geo_json): try: self.roi_start = True geom = geojson_to_ee(geo_json, False) self.user_roi = geom feature = ee.Feature(geom) self.draw_last_json = geo_json self.draw_last_feature = feature if action == "deleted" and len(self.draw_features) > 0: self.draw_features.remove(feature) self.draw_count -= 1 else: self.draw_features.append(feature) self.draw_count += 1 collection = ee.FeatureCollection(self.draw_features) self.user_rois = collection ee_draw_layer = ee_tile_layer( collection, {"color": "blue"}, "Drawn Features", False, 0.5 ) draw_layer_index = self.find_layer_index("Drawn Features") if draw_layer_index == -1: self.add_layer(ee_draw_layer) self.draw_layer = ee_draw_layer else: self.substitute_layer(self.draw_layer, ee_draw_layer) self.draw_layer = ee_draw_layer self.roi_end = True self.roi_start = False except Exception as e: self.draw_count = 0 self.draw_features = [] self.draw_last_feature = None self.draw_layer = None self.user_roi = None self.roi_start = False self.roi_end = False print("There was an error creating Earth Engine Feature.") raise Exception(e) draw_control.on_draw(handle_draw) if kwargs.get("draw_ctrl"): self.add_control(draw_control) self.draw_control = draw_control self.draw_control_lite = draw_control_lite # Dropdown widget for plotting self.plot_dropdown_control = None self.plot_dropdown_widget = None self.plot_options = {} self.plot_marker_cluster = ipyleaflet.MarkerCluster(name="Marker Cluster") self.plot_coordinates = [] self.plot_markers = [] self.plot_last_click = [] self.plot_all_clicks = [] self.plot_checked = False self.inspector_checked = False inspector_output = widgets.Output( layout={ "border": "1px solid black", "max_width": "600px", "max_height": "530px", "overflow": "auto", } ) inspector_output_control = ipyleaflet.WidgetControl( widget=inspector_output, position="topright", ) tool_output = widgets.Output() self.tool_output = tool_output tool_output.clear_output(wait=True) save_map_widget = widgets.VBox() save_type = widgets.ToggleButtons( options=["HTML", "PNG", "JPG"], tooltips=[ "Save the map as an HTML file", "Take a screenshot and save as a PNG file", "Take a screenshot and save as a JPG file", ], ) file_chooser = FileChooser(os.getcwd(), sandbox_path=self.sandbox_path) file_chooser.default_filename = "my_map.html" file_chooser.use_dir_icons = True ok_cancel = widgets.ToggleButtons( value=None, options=["OK", "Cancel"], tooltips=["OK", "Cancel"], button_style="primary", ) def save_type_changed(change): ok_cancel.value = None # file_chooser.reset() file_chooser.default_path = os.getcwd() if change["new"] == "HTML": file_chooser.default_filename = "my_map.html" elif change["new"] == "PNG": file_chooser.default_filename = "my_map.png" elif change["new"] == "JPG": file_chooser.default_filename = "my_map.jpg" save_map_widget.children = [save_type, file_chooser] def chooser_callback(chooser): save_map_widget.children = [save_type, file_chooser, ok_cancel] def ok_cancel_clicked(change): if change["new"] == "OK": file_path = file_chooser.selected ext = os.path.splitext(file_path)[1] if save_type.value == "HTML" and ext.upper() == ".HTML": tool_output.clear_output() self.to_html(file_path) elif save_type.value == "PNG" and ext.upper() == ".PNG": tool_output.clear_output() self.toolbar_button.value = False time.sleep(1) screen_capture(filename=file_path) elif save_type.value == "JPG" and ext.upper() == ".JPG": tool_output.clear_output() self.toolbar_button.value = False time.sleep(1) screen_capture(filename=file_path) else: label = widgets.Label( value="The selected file extension does not match the selected exporting type." ) save_map_widget.children = [save_type, file_chooser, label] self.toolbar_reset() elif change["new"] == "Cancel": tool_output.clear_output() self.toolbar_reset() save_type.observe(save_type_changed, names="value") ok_cancel.observe(ok_cancel_clicked, names="value") file_chooser.register_callback(chooser_callback) save_map_widget.children = [save_type, file_chooser] tools = { "info": {"name": "inspector", "tooltip": "Inspector"}, "bar-chart": {"name": "plotting", "tooltip": "Plotting"}, "camera": { "name": "to_image", "tooltip": "Save map as HTML or image", }, "eraser": { "name": "eraser", "tooltip": "Remove all drawn features", }, "folder-open": { "name": "open_data", "tooltip": "Open local vector/raster data", }, # "cloud-download": { # "name": "export_data", # "tooltip": "Export Earth Engine data", # }, "retweet": { "name": "convert_js", "tooltip": "Convert Earth Engine JavaScript to Python", }, "gears": { "name": "whitebox", "tooltip": "WhiteboxTools for local geoprocessing", }, "google": { "name": "geetoolbox", "tooltip": "GEE Toolbox for cloud computing", }, "map": { "name": "basemap", "tooltip": "Change basemap", }, "globe": { "name": "timelapse", "tooltip": "Create timelapse", }, "fast-forward": { "name": "timeslider", "tooltip": "Activate timeslider", }, "hand-o-up": { "name": "draw", "tooltip": "Collect training samples", }, "line-chart": { "name": "transect", "tooltip": "Creating and plotting transects", }, "random": { "name": "sankee", "tooltip": "Sankey plots", }, "adjust": { "name": "planet", "tooltip": "Planet imagery", }, "info-circle": { "name": "cog-inspector", "tooltip": "Get COG/STAC pixel value", }, "spinner": { "name": "placehold2", "tooltip": "This is a placehold", }, "question": { "name": "help", "tooltip": "Get help", }, } # if kwargs["use_voila"]: # voila_tools = ["camera", "folder-open", "cloud-download", "gears"] # for item in voila_tools: # if item in tools.keys(): # del tools[item] icons = list(tools.keys()) tooltips = [item["tooltip"] for item in list(tools.values())] icon_width = "32px" icon_height = "32px" n_cols = 3 n_rows = math.ceil(len(icons) / n_cols) toolbar_grid = widgets.GridBox( children=[ widgets.ToggleButton( layout=widgets.Layout( width="auto", height="auto", padding="0px 0px 0px 4px" ), button_style="primary", icon=icons[i], tooltip=tooltips[i], ) for i in range(len(icons)) ], layout=widgets.Layout( width="109px", grid_template_columns=(icon_width + " ") * n_cols, grid_template_rows=(icon_height + " ") * n_rows, grid_gap="1px 1px", padding="5px", ), ) self.toolbar = toolbar_grid def tool_callback(change): if change["new"]: current_tool = change["owner"] for tool in toolbar_grid.children: if tool is not current_tool: tool.value = False tool = change["owner"] tool_name = tools[tool.icon]["name"] if tool_name == "to_image": if tool_output_control not in self.controls: self.add_control(tool_output_control) with tool_output: tool_output.clear_output() display(save_map_widget) elif tool_name == "eraser": self.remove_drawn_features() tool.value = False elif tool_name == "inspector": self.inspector_checked = tool.value if not self.inspector_checked: inspector_output.clear_output() elif tool_name == "plotting": self.plot_checked = True plot_dropdown_widget = widgets.Dropdown( options=list(self.ee_raster_layer_names), ) plot_dropdown_widget.layout.width = "18ex" self.plot_dropdown_widget = plot_dropdown_widget plot_dropdown_control = ipyleaflet.WidgetControl( widget=plot_dropdown_widget, position="topright" ) self.plot_dropdown_control = plot_dropdown_control self.add_control(plot_dropdown_control) if self.draw_control in self.controls: self.remove_control(self.draw_control) self.add_control(self.draw_control_lite) elif tool_name == "open_data": from .toolbar import open_data_widget open_data_widget(self) elif tool_name == "convert_js": from .toolbar import convert_js2py convert_js2py(self) elif tool_name == "whitebox": import whiteboxgui.whiteboxgui as wbt tools_dict = wbt.get_wbt_dict() wbt_toolbox = wbt.build_toolbox( tools_dict, max_width="800px", max_height="500px", sandbox_path=self.sandbox_path, ) wbt_control = ipyleaflet.WidgetControl( widget=wbt_toolbox, position="bottomright" ) self.whitebox = wbt_control self.add_control(wbt_control) elif tool_name == "geetoolbox": from .toolbar import build_toolbox, get_tools_dict tools_dict = get_tools_dict() gee_toolbox = build_toolbox( tools_dict, max_width="800px", max_height="500px" ) geetoolbox_control = ipyleaflet.WidgetControl( widget=gee_toolbox, position="bottomright" ) self.geetoolbox = geetoolbox_control self.add_control(geetoolbox_control) elif tool_name == "basemap": from .toolbar import change_basemap change_basemap(self) elif tool_name == "timelapse": from .toolbar import timelapse_gui timelapse_gui(self) self.toolbar_reset() elif tool_name == "timeslider": from .toolbar import time_slider time_slider(self) self.toolbar_reset() elif tool_name == "draw": from .toolbar import collect_samples self.training_ctrl = None collect_samples(self) elif tool_name == "transect": from .toolbar import plot_transect plot_transect(self) elif tool_name == "sankee": from .toolbar import sankee_gui sankee_gui(self) elif tool_name == "planet": from .toolbar import split_basemaps split_basemaps(self, layers_dict=planet_tiles()) self.toolbar_reset() elif tool_name == "cog-inspector": from .toolbar import inspector_gui inspector_gui(self) elif tool_name == "help": import webbrowser webbrowser.open_new_tab("https://geemap.org") current_tool.value = False else: tool = change["owner"] tool_name = tools[tool.icon]["name"] if tool_name == "to_image": tool_output.clear_output() save_map_widget.children = [save_type, file_chooser] if tool_output_control in self.controls: self.remove_control(tool_output_control) if tool_name == "inspector": inspector_output.clear_output() self.inspector_checked = False if inspector_output_control in self.controls: self.remove_control(inspector_output_control) elif tool_name == "plotting": self.plot_checked = False plot_dropdown_widget = self.plot_dropdown_widget plot_dropdown_control = self.plot_dropdown_control if plot_dropdown_control in self.controls: self.remove_control(plot_dropdown_control) del plot_dropdown_widget del plot_dropdown_control if self.plot_control in self.controls: plot_control = self.plot_control plot_widget = self.plot_widget self.remove_control(plot_control) self.plot_control = None self.plot_widget = None del plot_control del plot_widget if ( self.plot_marker_cluster is not None and self.plot_marker_cluster in self.layers ): self.remove_layer(self.plot_marker_cluster) if self.draw_control_lite in self.controls: self.remove_control(self.draw_control_lite) self.add_control(self.draw_control) elif tool_name == "whitebox": if self.whitebox is not None and self.whitebox in self.controls: self.remove_control(self.whitebox) elif tool_name == "convert_js": if ( self.convert_ctrl is not None and self.convert_ctrl in self.controls ): self.remove_control(self.convert_ctrl) for tool in toolbar_grid.children: tool.observe(tool_callback, "value") toolbar_button = widgets.ToggleButton( value=False, tooltip="Toolbar", icon="wrench", layout=widgets.Layout( width="28px", height="28px", padding="0px 0px 0px 4px" ), ) self.toolbar_button = toolbar_button layers_button = widgets.ToggleButton( value=False, tooltip="Layers", icon="server", layout=widgets.Layout(height="28px", width="72px"), ) toolbar_widget = widgets.VBox() toolbar_widget.children = [toolbar_button] toolbar_header = widgets.HBox() toolbar_header.children = [layers_button, toolbar_button] toolbar_footer = widgets.VBox() toolbar_footer.children = [toolbar_grid] toolbar_event = ipyevents.Event( source=toolbar_widget, watched_events=["mouseenter", "mouseleave"] ) def handle_toolbar_event(event): if event["type"] == "mouseenter": toolbar_widget.children = [toolbar_header, toolbar_footer] elif event["type"] == "mouseleave": if not toolbar_button.value: toolbar_widget.children = [toolbar_button] toolbar_button.value = False layers_button.value = False toolbar_event.on_dom_event(handle_toolbar_event) def toolbar_btn_click(change): if change["new"]: layers_button.value = False toolbar_widget.children = [toolbar_header, toolbar_footer] else: if not layers_button.value: toolbar_widget.children = [toolbar_button] toolbar_button.observe(toolbar_btn_click, "value") def layers_btn_click(change): if change["new"]: layers_hbox = [] all_layers_chk = widgets.Checkbox( value=False, description="All layers on/off", indent=False, layout=widgets.Layout(height="18px", padding="0px 8px 25px 8px"), ) all_layers_chk.layout.width = "30ex" layers_hbox.append(all_layers_chk) def all_layers_chk_changed(change): if change["new"]: for layer in self.layers: if hasattr(layer, "visible"): layer.visible = True else: for layer in self.layers: if hasattr(layer, "visible"): layer.visible = False all_layers_chk.observe(all_layers_chk_changed, "value") layers = [ lyr for lyr in self.layers[1:] # if ( # isinstance(lyr, ipyleaflet.TileLayer) # or isinstance(lyr, ipyleaflet.WMSLayer) # ) ] # if the layers contain unsupported layers (e.g., GeoJSON, GeoData), adds the ipyleaflet built-in LayerControl if len(layers) < (len(self.layers) - 1): if self.layer_control is None: layer_control = ipyleaflet.LayersControl(position="topright") self.layer_control = layer_control if self.layer_control not in self.controls: self.add_control(self.layer_control) # for non-TileLayer, use layer.style={'opacity':0, 'fillOpacity': 0} to turn layer off. for layer in layers: visible = True if hasattr(layer, "visible"): visible = layer.visible layer_chk = widgets.Checkbox( value=visible, description=layer.name, indent=False, layout=widgets.Layout(height="18px"), ) layer_chk.layout.width = "25ex" if layer in self.geojson_layers: try: opacity = max( layer.style["opacity"], layer.style["fillOpacity"] ) except KeyError: opacity = 1.0 else: opacity = layer.opacity layer_opacity = widgets.FloatSlider( value=opacity, min=0, max=1, step=0.01, readout=False, layout=widgets.Layout(width="80px"), ) layer_settings = widgets.ToggleButton( icon="gear", tooltip=layer.name, layout=widgets.Layout( width="25px", height="25px", padding="0px 0px 0px 5px" ), ) def layer_opacity_changed(change): if change["new"]: layer.style = { "opacity": change["new"], "fillOpacity": change["new"], } def layer_vis_on_click(change): if change["new"]: layer_name = change["owner"].tooltip # if layer_name in self.ee_raster_layer_names: if layer_name in self.ee_layer_names: layer_dict = self.ee_layer_dict[layer_name] if self.vis_widget is not None: self.vis_widget = None self.vis_widget = self.create_vis_widget(layer_dict) if self.vis_control in self.controls: self.remove_control(self.vis_control) self.vis_control = None vis_control = ipyleaflet.WidgetControl( widget=self.vis_widget, position="topright" ) self.add_control((vis_control)) self.vis_control = vis_control else: if self.vis_widget is not None: self.vis_widget = None if self.vis_control is not None: if self.vis_control in self.controls: self.remove_control(self.vis_control) self.vis_control = None change["owner"].value = False layer_settings.observe(layer_vis_on_click, "value") def layer_chk_changed(change): layer_name = change["owner"].description if layer_name in self.ee_layer_names: if change["new"]: if "legend" in self.ee_layer_dict[layer_name].keys(): legend = self.ee_layer_dict[layer_name]["legend"] if legend not in self.controls: self.add_control(legend) if "colorbar" in self.ee_layer_dict[layer_name].keys(): colorbar = self.ee_layer_dict[layer_name][ "colorbar" ] if colorbar not in self.controls: self.add_control(colorbar) else: if "legend" in self.ee_layer_dict[layer_name].keys(): legend = self.ee_layer_dict[layer_name]["legend"] if legend in self.controls: self.remove_control(legend) if "colorbar" in self.ee_layer_dict[layer_name].keys(): colorbar = self.ee_layer_dict[layer_name][ "colorbar" ] if colorbar in self.controls: self.remove_control(colorbar) layer_chk.observe(layer_chk_changed, "value") if hasattr(layer, "visible"): widgets.jslink((layer_chk, "value"), (layer, "visible")) if layer in self.geojson_layers: layer_opacity.observe(layer_opacity_changed, "value") else: widgets.jsdlink((layer_opacity, "value"), (layer, "opacity")) hbox = widgets.HBox( [layer_chk, layer_settings, layer_opacity], layout=widgets.Layout(padding="0px 8px 0px 8px"), ) layers_hbox.append(hbox) toolbar_footer.children = layers_hbox toolbar_button.value = False else: toolbar_footer.children = [toolbar_grid] layers_button.observe(layers_btn_click, "value") toolbar_control = ipyleaflet.WidgetControl( widget=toolbar_widget, position="topright" ) if kwargs.get("toolbar_ctrl"): self.add_control(toolbar_control) tool_output_control = ipyleaflet.WidgetControl( widget=tool_output, position="topright" ) # self.add_control(tool_output_control) expand_label = widgets.Label( "Expand ", layout=widgets.Layout(padding="0px 0px 0px 4px"), ) expand_point = widgets.Checkbox( description="Point", indent=False, value=self._expand_point, layout=widgets.Layout(width="65px"), ) expand_pixels = widgets.Checkbox( description="Pixels", indent=False, value=self._expand_pixels, layout=widgets.Layout(width="65px"), ) expand_objects = widgets.Checkbox( description="Objects", indent=False, value=self._expand_objects, layout=widgets.Layout(width="70px"), ) def expand_point_changed(change): self._expand_point = change["new"] def expand_pixels_changed(change): self._expand_pixels = change["new"] def expand_objects_changed(change): self._expand_objects = change["new"] expand_point.observe(expand_point_changed, "value") expand_pixels.observe(expand_pixels_changed, "value") expand_objects.observe(expand_objects_changed, "value") inspector_checks = widgets.HBox() inspector_checks.children = [ expand_label, widgets.Label(""), expand_point, expand_pixels, expand_objects, ] def handle_interaction(**kwargs): latlon = kwargs.get("coordinates") if kwargs.get("type") == "click" and self.inspector_checked: self.default_style = {"cursor": "wait"} if inspector_output_control not in self.controls: self.add_control(inspector_output_control) sample_scale = self.getScale() layers = self.ee_layers with inspector_output: inspector_output.clear_output(wait=True) display(inspector_checks) display(self.inspector(latlon)) self.default_style = {"cursor": "crosshair"} if ( kwargs.get("type") == "click" and self.plot_checked and len(self.ee_raster_layers) > 0 ): plot_layer_name = self.plot_dropdown_widget.value layer_names = self.ee_raster_layer_names layers = self.ee_raster_layers index = layer_names.index(plot_layer_name) ee_object = layers[index] if isinstance(ee_object, ee.ImageCollection): ee_object = ee_object.mosaic() try: self.default_style = {"cursor": "wait"} plot_options = self.plot_options sample_scale = self.getScale() if "sample_scale" in plot_options.keys() and ( plot_options["sample_scale"] is not None ): sample_scale = plot_options["sample_scale"] if "title" not in plot_options.keys(): plot_options["title"] = plot_layer_name if ("add_marker_cluster" in plot_options.keys()) and plot_options[ "add_marker_cluster" ]: plot_coordinates = self.plot_coordinates markers = self.plot_markers marker_cluster = self.plot_marker_cluster plot_coordinates.append(latlon) self.plot_last_click = latlon self.plot_all_clicks = plot_coordinates markers.append(ipyleaflet.Marker(location=latlon)) marker_cluster.markers = markers self.plot_marker_cluster = marker_cluster band_names = ee_object.bandNames().getInfo() if any(len(name) > 3 for name in band_names): band_names = list(range(1, len(band_names) + 1)) self.chart_labels = band_names if self.roi_end: if self.roi_reducer_scale is None: scale = ee_object.select(0).projection().nominalScale() else: scale = self.roi_reducer_scale dict_values_tmp = ee_object.reduceRegion( reducer=self.roi_reducer, geometry=self.user_roi, scale=scale, bestEffort=True, ).getInfo() b_names = ee_object.bandNames().getInfo() dict_values = dict( zip(b_names, [dict_values_tmp[b] for b in b_names]) ) self.chart_points.append( self.user_roi.centroid(1).coordinates().getInfo() ) else: xy = ee.Geometry.Point(latlon[::-1]) dict_values_tmp = ( ee_object.sample(xy, scale=sample_scale) .first() .toDictionary() .getInfo() ) b_names = ee_object.bandNames().getInfo() dict_values = dict( zip(b_names, [dict_values_tmp[b] for b in b_names]) ) self.chart_points.append(xy.coordinates().getInfo()) band_values = list(dict_values.values()) self.chart_values.append(band_values) self.plot(band_names, band_values, **plot_options) if plot_options["title"] == plot_layer_name: del plot_options["title"] self.default_style = {"cursor": "crosshair"} self.roi_end = False except Exception as e: if self.plot_widget is not None: with self.plot_widget: self.plot_widget.clear_output() print("No data for the clicked location.") else: print(e) self.default_style = {"cursor": "crosshair"} self.roi_end = False self.on_interaction(handle_interaction)
[docs] def set_options(self, mapTypeId="HYBRID", styles=None, types=None): """Adds Google basemap and controls to the ipyleaflet map. Args: mapTypeId (str, optional): A mapTypeId to set the basemap to. Can be one of "ROADMAP", "SATELLITE", "HYBRID" or "TERRAIN" to select one of the standard Google Maps API map types. Defaults to 'HYBRID'. styles (object, optional): A dictionary of custom MapTypeStyle objects keyed with a name that will appear in the map's Map Type Controls. Defaults to None. types (list, optional): A list of mapTypeIds to make available. If omitted, but opt_styles is specified, appends all of the style keys to the standard Google Maps API map types.. Defaults to None. """ self.clear_layers() self.clear_controls() self.scroll_wheel_zoom = True self.add_control(ipyleaflet.ZoomControl(position="topleft")) self.add_control(ipyleaflet.LayersControl(position="topright")) self.add_control(ipyleaflet.ScaleControl(position="bottomleft")) self.add_control(ipyleaflet.FullScreenControl()) self.add_control(ipyleaflet.DrawControl()) measure = ipyleaflet.MeasureControl( position="bottomleft", active_color="orange", primary_length_unit="kilometers", ) self.add_control(measure) try: self.add_layer(basemaps[mapTypeId]) except Exception: raise ValueError( 'Google basemaps can only be one of "ROADMAP", "SATELLITE", "HYBRID" or "TERRAIN".' )
setOptions = set_options
[docs] def add_ee_layer( self, ee_object, vis_params={}, name=None, shown=True, opacity=1.0 ): """Adds a given EE object to the map as a layer. Args: ee_object (Collection|Feature|Image|MapId): The object to add to the map. vis_params (dict, optional): The visualization parameters. Defaults to {}. name (str, optional): The name of the layer. Defaults to 'Layer N'. shown (bool, optional): A flag indicating whether the layer should be on by default. Defaults to True. opacity (float, optional): The layer's opacity represented as a number between 0 and 1. Defaults to 1. """ image = None if vis_params is None: vis_params = {} if name is None: layer_count = len(self.layers) name = "Layer " + str(layer_count + 1) if ( not isinstance(ee_object, ee.Image) and not isinstance(ee_object, ee.ImageCollection) and not isinstance(ee_object, ee.FeatureCollection) and not isinstance(ee_object, ee.Feature) and not isinstance(ee_object, ee.Geometry) ): err_str = "\n\nThe image argument in 'addLayer' function must be an instance of one of ee.Image, ee.Geometry, ee.Feature or ee.FeatureCollection." raise AttributeError(err_str) if ( isinstance(ee_object, ee.geometry.Geometry) or isinstance(ee_object, ee.feature.Feature) or isinstance(ee_object, ee.featurecollection.FeatureCollection) ): features = ee.FeatureCollection(ee_object) width = 2 if "width" in vis_params: width = vis_params["width"] color = "000000" if "color" in vis_params: color = vis_params["color"] image_fill = features.style(**{"fillColor": color}).updateMask( ee.Image.constant(0.5) ) image_outline = features.style( **{"color": color, "fillColor": "00000000", "width": width} ) image = image_fill.blend(image_outline) elif isinstance(ee_object, ee.image.Image): image = ee_object elif isinstance(ee_object, ee.imagecollection.ImageCollection): image = ee_object.mosaic() if "palette" in vis_params: if isinstance(vis_params["palette"], tuple): vis_params["palette"] = list(vis_params["palette"]) if isinstance(vis_params["palette"], Box): try: vis_params["palette"] = vis_params["palette"]["default"] except Exception as e: print("The provided palette is invalid.") raise Exception(e) elif isinstance(vis_params["palette"], str): vis_params["palette"] = check_cmap(vis_params["palette"]) elif not isinstance(vis_params["palette"], list): raise ValueError( "The palette must be a list of colors or a string or a Box object." ) map_id_dict = ee.Image(image).getMapId(vis_params) tile_layer = ipyleaflet.TileLayer( url=map_id_dict["tile_fetcher"].url_format, attribution="Google Earth Engine", name=name, opacity=opacity, visible=shown, max_zoom=24, ) layer = self.find_layer(name=name) if layer is not None: existing_object = self.ee_layer_dict[name]["ee_object"] if isinstance(existing_object, ee.Image) or isinstance( existing_object, ee.ImageCollection ): self.ee_raster_layers.remove(existing_object) self.ee_raster_layer_names.remove(name) if self.plot_dropdown_widget is not None: self.plot_dropdown_widget.options = list(self.ee_raster_layer_names) elif ( isinstance(ee_object, ee.Geometry) or isinstance(ee_object, ee.Feature) or isinstance(ee_object, ee.FeatureCollection) ): self.ee_vector_layers.remove(existing_object) self.ee_vector_layer_names.remove(name) self.ee_layers.remove(existing_object) self.ee_layer_names.remove(name) self.remove_layer(layer) self.ee_layers.append(ee_object) if name not in self.ee_layer_names: self.ee_layer_names.append(name) self.ee_layer_dict[name] = { "ee_object": ee_object, "ee_layer": tile_layer, "vis_params": vis_params, } self.add_layer(tile_layer) self.last_ee_layer = self.ee_layer_dict[name] self.last_ee_data = self.ee_layer_dict[name]["ee_object"] if isinstance(ee_object, ee.Image) or isinstance(ee_object, ee.ImageCollection): self.ee_raster_layers.append(ee_object) self.ee_raster_layer_names.append(name) if self.plot_dropdown_widget is not None: self.plot_dropdown_widget.options = list(self.ee_raster_layer_names) elif ( isinstance(ee_object, ee.Geometry) or isinstance(ee_object, ee.Feature) or isinstance(ee_object, ee.FeatureCollection) ): self.ee_vector_layers.append(ee_object) self.ee_vector_layer_names.append(name)
addLayer = add_ee_layer
[docs] def remove_ee_layer(self, name): """Removes an Earth Engine layer. Args: name (str): The name of the Earth Engine layer to remove. """ if name in self.ee_layer_dict: ee_object = self.ee_layer_dict[name]["ee_object"] ee_layer = self.ee_layer_dict[name]["ee_layer"] if name in self.ee_raster_layer_names: self.ee_raster_layer_names.remove(name) self.ee_raster_layers.remove(ee_object) elif name in self.ee_vector_layer_names: self.ee_vector_layer_names.remove(name) self.ee_vector_layers.remove(ee_object) self.ee_layers.remove(ee_object) self.ee_layer_names.remove(name) if ee_layer in self.layers: self.remove_layer(ee_layer)
[docs] def draw_layer_on_top(self): """Move user-drawn feature layer to the top of all layers.""" draw_layer_index = self.find_layer_index(name="Drawn Features") if draw_layer_index > -1 and draw_layer_index < (len(self.layers) - 1): layers = list(self.layers) layers = ( layers[0:draw_layer_index] + layers[(draw_layer_index + 1) :] + [layers[draw_layer_index]] ) self.layers = layers
[docs] def set_center(self, lon, lat, zoom=None): """Centers the map view at a given coordinates with the given zoom level. Args: lon (float): The longitude of the center, in degrees. lat (float): The latitude of the center, in degrees. zoom (int, optional): The zoom level, from 1 to 24. Defaults to None. """ self.center = (lat, lon) if zoom is not None: self.zoom = zoom
setCenter = set_center
[docs] def center_object(self, ee_object, zoom=None): """Centers the map view on a given object. Args: ee_object (Element|Geometry): An Earth Engine object to center on a geometry, image or feature. zoom (int, optional): The zoom level, from 1 to 24. Defaults to None. """ maxError = 0.001 if isinstance(ee_object, ee.Geometry): geometry = ee_object.transform(maxError=maxError) else: try: geometry = ee_object.geometry(maxError=maxError).transform( maxError=maxError ) except Exception: raise Exception( "ee_object must be an instance of one of ee.Geometry, ee.FeatureCollection, ee.Image, or ee.ImageCollection." ) if zoom is not None: if not isinstance(zoom, int): raise Exception("Zoom must be an integer.") else: centroid = geometry.centroid(maxError=maxError).getInfo()["coordinates"] lat = centroid[1] lon = centroid[0] self.set_center(lon, lat, zoom) else: coordinates = geometry.bounds(maxError).getInfo()["coordinates"][0] x = [c[0] for c in coordinates] y = [c[1] for c in coordinates] xmin = min(x) xmax = max(x) ymin = min(y) ymax = max(y) bounds = [[ymin, xmin], [ymax, xmax]] self.fit_bounds(bounds)
centerObject = center_object
[docs] def zoom_to_me(self, zoom=14, add_marker=True): """Zoom to the current device location. Args: zoom (int, optional): Zoom level. Defaults to 14. add_marker (bool, optional): Whether to add a marker of the current device location. Defaults to True. """ lat, lon = get_current_latlon() self.set_center(lon, lat, zoom) if add_marker: marker = ipyleaflet.Marker( location=(lat, lon), draggable=False, name="Device location", ) self.add_layer(marker)
[docs] def zoom_to_bounds(self, bounds): """Zooms to a bounding box in the form of [minx, miny, maxx, maxy]. Args: bounds (list | tuple): A list/tuple containing minx, miny, maxx, maxy values for the bounds. """ # The ipyleaflet fit_bounds method takes lat/lon bounds in the form [[south, west], [north, east]]. self.fit_bounds([[bounds[1], bounds[0]], [bounds[3], bounds[2]]])
[docs] def zoom_to_gdf(self, gdf): """Zooms to the bounding box of a GeoPandas GeoDataFrame. Args: gdf (GeoDataFrame): A GeoPandas GeoDataFrame. """ bounds = gdf.total_bounds self.zoom_to_bounds(bounds)
[docs] def get_scale(self): """Returns the approximate pixel scale of the current map view, in meters. Returns: float: Map resolution in meters. """ zoom_level = self.zoom # Reference: https://blogs.bing.com/maps/2006/02/25/map-control-zoom-levels-gt-resolution resolution = 156543.04 * math.cos(0) / math.pow(2, zoom_level) return resolution
getScale = get_scale
[docs] def get_bounds(self, asGeoJSON=False): """Returns the bounds of the current map view, as a list in the format [west, south, east, north] in degrees. Args: asGeoJSON (bool, optional): If true, returns map bounds as GeoJSON. Defaults to False. Returns: list | dict: A list in the format [west, south, east, north] in degrees. """ bounds = self.bounds coords = [bounds[0][1], bounds[0][0], bounds[1][1], bounds[1][0]] if asGeoJSON: return ee.Geometry.BBox( bounds[0][1], bounds[0][0], bounds[1][1], bounds[1][0] ).getInfo() else: return coords
getBounds = get_bounds
[docs] def add_basemap(self, basemap="HYBRID"): """Adds a basemap to the map. Args: basemap (str, optional): Can be one of string from basemaps. Defaults to 'HYBRID'. """ try: if basemap in basemaps.keys() and basemaps[basemap] not in self.layers: self.add_layer(basemaps[basemap]) except Exception: raise ValueError( "Basemap can only be one of the following:\n {}".format( "\n ".join(basemaps.keys()) ) )
[docs] def add_marker(self, location, **kwargs): """Adds a marker to the map. More info about marker at https://ipyleaflet.readthedocs.io/en/latest/api_reference/marker.html. Args: location (list | tuple): The location of the marker in the format of [lat, lng]. **kwargs: Keyword arguments for the marker. """ if isinstance(location, list): location = tuple(location) if isinstance(location, tuple): marker = ipyleaflet.Marker(location=location, **kwargs) self.add_layer(marker) else: raise TypeError("The location must be a list or a tuple.")
[docs] def find_layer(self, name): """Finds layer by name Args: name (str): Name of the layer to find. Returns: object: ipyleaflet layer object. """ layers = self.layers for layer in layers: if layer.name == name: return layer return None
[docs] def show_layer(self, name, show=True): """Shows or hides a layer on the map. Args: name (str): Name of the layer to show/hide. show (bool, optional): Whether to show or hide the layer. Defaults to True. """ layer = self.find_layer(name) if layer is not None: layer.visible = show
[docs] def find_layer_index(self, name): """Finds layer index by name Args: name (str): Name of the layer to find. Returns: int: Index of the layer with the specified name """ layers = self.layers for index, layer in enumerate(layers): if layer.name == name: return index return -1
[docs] def layer_opacity(self, name, opacity=1.0): """Changes layer opacity. Args: name (str): The name of the layer to change opacity. opacity (float, optional): The opacity value to set. Defaults to 1.0. """ layer = self.find_layer(name) try: layer.opacity = opacity except Exception as e: raise Exception(e)
[docs] def add_wms_layer( self, url, layers, name=None, attribution="", format="image/png", transparent=True, opacity=1.0, shown=True, **kwargs, ): """Add a WMS layer to the map. Args: url (str): The URL of the WMS web service. layers (str): Comma-separated list of WMS layers to show. name (str, optional): The layer name to use on the layer control. Defaults to None. attribution (str, optional): The attribution of the data layer. Defaults to ''. format (str, optional): WMS image format (use ‘image/png’ for layers with transparency). Defaults to 'image/png'. transparent (bool, optional): If True, the WMS service will return images with transparency. Defaults to True. opacity (float, optional): The opacity of the layer. Defaults to 1.0. shown (bool, optional): A flag indicating whether the layer should be on by default. Defaults to True. """ if name is None: name = str(layers) try: wms_layer = ipyleaflet.WMSLayer( url=url, layers=layers, name=name, attribution=attribution, format=format, transparent=transparent, opacity=opacity, visible=shown, **kwargs, ) self.add_layer(wms_layer) except Exception as e: print("Failed to add the specified WMS TileLayer.") raise Exception(e)
[docs] def add_tile_layer( self, url="https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png", name="Untitled", attribution="", opacity=1.0, shown=True, **kwargs, ): """Adds a TileLayer to the map. Args: url (str, optional): The URL of the tile layer. Defaults to 'https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png'. name (str, optional): The layer name to use for the layer. Defaults to 'Untitled'. attribution (str, optional): The attribution to use. Defaults to ''. opacity (float, optional): The opacity of the layer. Defaults to 1. shown (bool, optional): A flag indicating whether the layer should be on by default. Defaults to True. """ try: tile_layer = ipyleaflet.TileLayer( url=url, name=name, attribution=attribution, opacity=opacity, visible=shown, **kwargs, ) self.add_layer(tile_layer) except Exception as e: print("Failed to add the specified TileLayer.") raise Exception(e)
[docs] def add_cog_layer( self, url, name="Untitled", attribution="", opacity=1.0, shown=True, bands=None, titiler_endpoint="https://titiler.xyz", **kwargs, ): """Adds a COG TileLayer to the map. Args: url (str): The URL of the COG tile layer. name (str, optional): The layer name to use for the layer. Defaults to 'Untitled'. attribution (str, optional): The attribution to use. Defaults to ''. opacity (float, optional): The opacity of the layer. Defaults to 1. shown (bool, optional): A flag indicating whether the layer should be on by default. Defaults to True. bands (list, optional): A list of bands to use for the layer. Defaults to None. titiler_endpoint (str, optional): Titiler endpoint. Defaults to "https://titiler.xyz". **kwargs: Arbitrary keyword arguments, including bidx, expression, nodata, unscale, resampling, rescale, color_formula, colormap, colormap_name, return_mask. See https://developmentseed.org/titiler/endpoints/cog/ and https://cogeotiff.github.io/rio-tiler/colormap/. To select a certain bands, use bidx=[1, 2, 3] """ tile_url = cog_tile(url, bands, titiler_endpoint, **kwargs) bounds = cog_bounds(url, titiler_endpoint) self.add_tile_layer(tile_url, name, attribution, opacity, shown) self.fit_bounds([[bounds[1], bounds[0]], [bounds[3], bounds[2]]]) if not hasattr(self, "cog_layer_dict"): self.cog_layer_dict = {} params = { "url": url, "titizer_endpoint": titiler_endpoint, "bounds": bounds, "type": "COG", } self.cog_layer_dict[name] = params
[docs] def add_cog_mosaic(self, **kwargs): raise NotImplementedError( "This function is no longer supported.See https://github.com/giswqs/leafmap/issues/180." )
[docs] def add_stac_layer( self, url=None, collection=None, item=None, assets=None, bands=None, titiler_endpoint=None, name="STAC Layer", attribution="", opacity=1.0, shown=True, **kwargs, ): """Adds a STAC TileLayer to the map. Args: url (str): HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json collection (str): The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2. item (str): The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1. assets (str | list): The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"]. bands (list): A list of band names, e.g., ["SR_B7", "SR_B5", "SR_B4"] titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "https://planetarycomputer.microsoft.com/api/data/v1", "planetary-computer", "pc". Defaults to None. name (str, optional): The layer name to use for the layer. Defaults to 'STAC Layer'. attribution (str, optional): The attribution to use. Defaults to ''. opacity (float, optional): The opacity of the layer. Defaults to 1. shown (bool, optional): A flag indicating whether the layer should be on by default. Defaults to True. """ tile_url = stac_tile( url, collection, item, assets, bands, titiler_endpoint, **kwargs ) bounds = stac_bounds(url, collection, item, titiler_endpoint) self.add_tile_layer(tile_url, name, attribution, opacity, shown) self.fit_bounds([[bounds[1], bounds[0]], [bounds[3], bounds[2]]]) if not hasattr(self, "cog_layer_dict"): self.cog_layer_dict = {} if assets is None and bands is not None: assets = bands params = { "url": url, "collection": collection, "item": item, "assets": assets, "bounds": bounds, "titiler_endpoint": titiler_endpoint, "type": "STAC", } self.cog_layer_dict[name] = params
[docs] def add_minimap(self, zoom=5, position="bottomright"): """Adds a minimap (overview) to the ipyleaflet map. Args: zoom (int, optional): Initial map zoom level. Defaults to 5. position (str, optional): Position of the minimap. Defaults to "bottomright". """ minimap = ipyleaflet.Map( zoom_control=False, attribution_control=False, zoom=zoom, center=self.center, layers=[basemaps["ROADMAP"]], ) minimap.layout.width = "150px" minimap.layout.height = "150px" ipyleaflet.link((minimap, "center"), (self, "center")) minimap_control = ipyleaflet.WidgetControl(widget=minimap, position=position) self.add_control(minimap_control)
[docs] def marker_cluster(self): """Adds a marker cluster to the map and returns a list of ee.Feature, which can be accessed using Map.ee_marker_cluster. Returns: object: a list of ee.Feature """ coordinates = [] markers = [] marker_cluster = ipyleaflet.MarkerCluster(name="Marker Cluster") self.last_click = [] self.all_clicks = [] self.ee_markers = [] self.add_layer(marker_cluster) def handle_interaction(**kwargs): latlon = kwargs.get("coordinates") if kwargs.get("type") == "click": coordinates.append(latlon) geom = ee.Geometry.Point(latlon[1], latlon[0]) feature = ee.Feature(geom) self.ee_markers.append(feature) self.last_click = latlon self.all_clicks = coordinates markers.append(ipyleaflet.Marker(location=latlon)) marker_cluster.markers = markers elif kwargs.get("type") == "mousemove": pass # cursor style: https://www.w3schools.com/cssref/pr_class_cursor.asp self.default_style = {"cursor": "crosshair"} self.on_interaction(handle_interaction)
[docs] def set_plot_options( self, add_marker_cluster=False, sample_scale=None, plot_type=None, overlay=False, position="bottomright", min_width=None, max_width=None, min_height=None, max_height=None, **kwargs, ): """Sets plotting options. Args: add_marker_cluster (bool, optional): Whether to add a marker cluster. Defaults to False. sample_scale (float, optional): A nominal scale in meters of the projection to sample in . Defaults to None. plot_type (str, optional): The plot type can be one of "None", "bar", "scatter" or "hist". Defaults to None. overlay (bool, optional): Whether to overlay plotted lines on the figure. Defaults to False. position (str, optional): Position of the control, can be ‘bottomleft’, ‘bottomright’, ‘topleft’, or ‘topright’. Defaults to 'bottomright'. min_width (int, optional): Min width of the widget (in pixels), if None it will respect the content size. Defaults to None. max_width (int, optional): Max width of the widget (in pixels), if None it will respect the content size. Defaults to None. min_height (int, optional): Min height of the widget (in pixels), if None it will respect the content size. Defaults to None. max_height (int, optional): Max height of the widget (in pixels), if None it will respect the content size. Defaults to None. """ plot_options_dict = {} plot_options_dict["add_marker_cluster"] = add_marker_cluster plot_options_dict["sample_scale"] = sample_scale plot_options_dict["plot_type"] = plot_type plot_options_dict["overlay"] = overlay plot_options_dict["position"] = position plot_options_dict["min_width"] = min_width plot_options_dict["max_width"] = max_width plot_options_dict["min_height"] = min_height plot_options_dict["max_height"] = max_height for key in kwargs.keys(): plot_options_dict[key] = kwargs[key] self.plot_options = plot_options_dict if add_marker_cluster and (self.plot_marker_cluster not in self.layers): self.add_layer(self.plot_marker_cluster)
[docs] def plot( self, x, y, plot_type=None, overlay=False, position="bottomright", min_width=None, max_width=None, min_height=None, max_height=None, **kwargs, ): """Creates a plot based on x-array and y-array data. Args: x (numpy.ndarray or list): The x-coordinates of the plotted line. y (numpy.ndarray or list): The y-coordinates of the plotted line. plot_type (str, optional): The plot type can be one of "None", "bar", "scatter" or "hist". Defaults to None. overlay (bool, optional): Whether to overlay plotted lines on the figure. Defaults to False. position (str, optional): Position of the control, can be ‘bottomleft’, ‘bottomright’, ‘topleft’, or ‘topright’. Defaults to 'bottomright'. min_width (int, optional): Min width of the widget (in pixels), if None it will respect the content size. Defaults to None. max_width (int, optional): Max width of the widget (in pixels), if None it will respect the content size. Defaults to None. min_height (int, optional): Min height of the widget (in pixels), if None it will respect the content size. Defaults to None. max_height (int, optional): Max height of the widget (in pixels), if None it will respect the content size. Defaults to None. """ if self.plot_widget is not None: plot_widget = self.plot_widget else: plot_widget = widgets.Output(layout={"border": "1px solid black"}) plot_control = ipyleaflet.WidgetControl( widget=plot_widget, position=position, min_width=min_width, max_width=max_width, min_height=min_height, max_height=max_height, ) self.plot_widget = plot_widget self.plot_control = plot_control self.add_control(plot_control) if max_width is None: max_width = 500 if max_height is None: max_height = 300 if (plot_type is None) and ("markers" not in kwargs.keys()): kwargs["markers"] = "circle" with plot_widget: try: fig = plt.figure(1, **kwargs) if max_width is not None: fig.layout.width = str(max_width) + "px" if max_height is not None: fig.layout.height = str(max_height) + "px" plot_widget.clear_output(wait=True) if not overlay: plt.clear() if plot_type is None: if "marker" not in kwargs.keys(): kwargs["marker"] = "circle" plt.plot(x, y, **kwargs) elif plot_type == "bar": plt.bar(x, y, **kwargs) elif plot_type == "scatter": plt.scatter(x, y, **kwargs) elif plot_type == "hist": plt.hist(y, **kwargs) plt.show() except Exception as e: print("Failed to create plot.") raise Exception(e)
[docs] def plot_demo( self, iterations=20, plot_type=None, overlay=False, position="bottomright", min_width=None, max_width=None, min_height=None, max_height=None, **kwargs, ): """A demo of interactive plotting using random pixel coordinates. Args: iterations (int, optional): How many iterations to run for the demo. Defaults to 20. plot_type (str, optional): The plot type can be one of "None", "bar", "scatter" or "hist". Defaults to None. overlay (bool, optional): Whether to overlay plotted lines on the figure. Defaults to False. position (str, optional): Position of the control, can be ‘bottomleft’, ‘bottomright’, ‘topleft’, or ‘topright’. Defaults to 'bottomright'. min_width (int, optional): Min width of the widget (in pixels), if None it will respect the content size. Defaults to None. max_width (int, optional): Max width of the widget (in pixels), if None it will respect the content size. Defaults to None. min_height (int, optional): Min height of the widget (in pixels), if None it will respect the content size. Defaults to None. max_height (int, optional): Max height of the widget (in pixels), if None it will respect the content size. Defaults to None. """ import numpy as np if self.random_marker is not None: self.remove_layer(self.random_marker) image = ee.Image("LANDSAT/LE7_TOA_5YEAR/1999_2003").select([0, 1, 2, 3, 4, 6]) self.addLayer( image, {"bands": ["B4", "B3", "B2"], "gamma": 1.4}, "LANDSAT/LE7_TOA_5YEAR/1999_2003", ) self.setCenter(-50.078877, 25.190030, 3) band_names = image.bandNames().getInfo() # band_count = len(band_names) latitudes = np.random.uniform(30, 48, size=iterations) longitudes = np.random.uniform(-121, -76, size=iterations) marker = ipyleaflet.Marker(location=(0, 0)) self.random_marker = marker self.add_layer(marker) for i in range(iterations): try: coordinate = ee.Geometry.Point([longitudes[i], latitudes[i]]) dict_values = image.sample(coordinate).first().toDictionary().getInfo() band_values = list(dict_values.values()) title = "{}/{}: Spectral signature at ({}, {})".format( i + 1, iterations, round(latitudes[i], 2), round(longitudes[i], 2), ) marker.location = (latitudes[i], longitudes[i]) self.plot( band_names, band_values, plot_type=plot_type, overlay=overlay, min_width=min_width, max_width=max_width, min_height=min_height, max_height=max_height, title=title, **kwargs, ) time.sleep(0.3) except Exception as e: raise Exception(e)
[docs] def plot_raster( self, ee_object=None, sample_scale=None, plot_type=None, overlay=False, position="bottomright", min_width=None, max_width=None, min_height=None, max_height=None, **kwargs, ): """Interactive plotting of Earth Engine data by clicking on the map. Args: ee_object (object, optional): The ee.Image or ee.ImageCollection to sample. Defaults to None. sample_scale (float, optional): A nominal scale in meters of the projection to sample in. Defaults to None. plot_type (str, optional): The plot type can be one of "None", "bar", "scatter" or "hist". Defaults to None. overlay (bool, optional): Whether to overlay plotted lines on the figure. Defaults to False. position (str, optional): Position of the control, can be ‘bottomleft’, ‘bottomright’, ‘topleft’, or ‘topright’. Defaults to 'bottomright'. min_width (int, optional): Min width of the widget (in pixels), if None it will respect the content size. Defaults to None. max_width (int, optional): Max width of the widget (in pixels), if None it will respect the content size. Defaults to None. min_height (int, optional): Min height of the widget (in pixels), if None it will respect the content size. Defaults to None. max_height (int, optional): Max height of the widget (in pixels), if None it will respect the content size. Defaults to None. """ if self.plot_control is not None: del self.plot_widget if self.plot_control in self.controls: self.remove_control(self.plot_control) if self.random_marker is not None: self.remove_layer(self.random_marker) plot_widget = widgets.Output(layout={"border": "1px solid black"}) plot_control = ipyleaflet.WidgetControl( widget=plot_widget, position=position, min_width=min_width, max_width=max_width, min_height=min_height, max_height=max_height, ) self.plot_widget = plot_widget self.plot_control = plot_control self.add_control(plot_control) self.default_style = {"cursor": "crosshair"} msg = "The plot function can only be used on ee.Image or ee.ImageCollection with more than one band." if (ee_object is None) and len(self.ee_raster_layers) > 0: ee_object = self.ee_raster_layers[-1] if isinstance(ee_object, ee.ImageCollection): ee_object = ee_object.mosaic() elif isinstance(ee_object, ee.ImageCollection): ee_object = ee_object.mosaic() elif not isinstance(ee_object, ee.Image): print(msg) return if sample_scale is None: sample_scale = self.getScale() if max_width is None: max_width = 500 band_names = ee_object.bandNames().getInfo() coordinates = [] markers = [] marker_cluster = ipyleaflet.MarkerCluster(name="Marker Cluster") self.last_click = [] self.all_clicks = [] self.add_layer(marker_cluster) def handle_interaction(**kwargs2): latlon = kwargs2.get("coordinates") if kwargs2.get("type") == "click": try: coordinates.append(latlon) self.last_click = latlon self.all_clicks = coordinates markers.append(ipyleaflet.Marker(location=latlon)) marker_cluster.markers = markers self.default_style = {"cursor": "wait"} xy = ee.Geometry.Point(latlon[::-1]) dict_values = ( ee_object.sample(xy, scale=sample_scale) .first() .toDictionary() .getInfo() ) band_values = list(dict_values.values()) self.plot( band_names, band_values, plot_type=plot_type, overlay=overlay, min_width=min_width, max_width=max_width, min_height=min_height, max_height=max_height, **kwargs, ) self.default_style = {"cursor": "crosshair"} except Exception as e: if self.plot_widget is not None: with self.plot_widget: self.plot_widget.clear_output() print("No data for the clicked location.") else: print(e) self.default_style = {"cursor": "crosshair"} self.on_interaction(handle_interaction)
[docs] def add_marker_cluster(self, event="click", add_marker=True): """Captures user inputs and add markers to the map. Args: event (str, optional): [description]. Defaults to 'click'. add_marker (bool, optional): If True, add markers to the map. Defaults to True. Returns: object: a marker cluster. """ coordinates = [] markers = [] marker_cluster = ipyleaflet.MarkerCluster(name="Marker Cluster") self.last_click = [] self.all_clicks = [] if add_marker: self.add_layer(marker_cluster) def handle_interaction(**kwargs): latlon = kwargs.get("coordinates") if event == "click" and kwargs.get("type") == "click": coordinates.append(latlon) self.last_click = latlon self.all_clicks = coordinates if add_marker: markers.append(ipyleaflet.Marker(location=latlon)) marker_cluster.markers = markers elif kwargs.get("type") == "mousemove": pass # cursor style: https://www.w3schools.com/cssref/pr_class_cursor.asp self.default_style = {"cursor": "crosshair"} self.on_interaction(handle_interaction)
[docs] def set_control_visibility( self, layerControl=True, fullscreenControl=True, latLngPopup=True ): """Sets the visibility of the controls on the map. Args: layerControl (bool, optional): Whether to show the control that allows the user to toggle layers on/off. Defaults to True. fullscreenControl (bool, optional): Whether to show the control that allows the user to make the map full-screen. Defaults to True. latLngPopup (bool, optional): Whether to show the control that pops up the Lat/lon when the user clicks on the map. Defaults to True. """ pass
setControlVisibility = set_control_visibility
[docs] def add_layer_control(self): """Adds the layer control to the map.""" if self.layer_control is None: layer_control = ipyleaflet.LayersControl(position="topright") self.layer_control = layer_control self.add_control(layer_control)
addLayerControl = add_layer_control
[docs] def split_map( self, left_layer="HYBRID", right_layer="ROADMAP", add_close_button=False ): """Adds split map. Args: left_layer (str, optional): The layer tile layer. Defaults to 'HYBRID'. right_layer (str, optional): The right tile layer. Defaults to 'ROADMAP'. add_close_button (bool, optional): Whether to add a close button. Defaults to False. """ try: controls = self.controls layers = self.layers self.clear_controls() self.add_control(ipyleaflet.ZoomControl()) self.add_control(ipyleaflet.FullScreenControl()) if left_layer in basemaps.keys(): left_layer = basemaps[left_layer] elif isinstance(left_layer, str): if left_layer.startswith("http") and left_layer.endswith(".tif"): url = cog_tile(left_layer) left_layer = ipyleaflet.TileLayer( url=url, name="Left Layer", attribution=" ", ) else: left_layer = ipyleaflet.TileLayer( url=left_layer, name="Left Layer", attribution=" ", ) elif isinstance(left_layer, ipyleaflet.TileLayer): pass else: raise ValueError( f"left_layer must be one of the following: {', '.join(basemaps.keys())} or a string url to a tif file." ) if right_layer in basemaps.keys(): right_layer = basemaps[right_layer] elif isinstance(right_layer, str): if right_layer.startswith("http") and right_layer.endswith(".tif"): url = cog_tile(right_layer) right_layer = ipyleaflet.TileLayer( url=url, name="Right Layer", attribution=" ", ) else: right_layer = ipyleaflet.TileLayer( url=right_layer, name="Right Layer", attribution=" ", ) elif isinstance(right_layer, ipyleaflet.TileLayer): pass else: raise ValueError( f"right_layer must be one of the following: {', '.join(basemaps.keys())} or a string url to a tif file." ) control = ipyleaflet.SplitMapControl( left_layer=left_layer, right_layer=right_layer ) close_button = widgets.ToggleButton( value=False, tooltip="Close split-panel map", icon="times", layout=widgets.Layout( height="28px", width="28px", padding="0px 0px 0px 4px" ), ) def close_btn_click(change): if change["new"]: self.controls = controls self.layers = layers[:-1] self.add_layer(layers[-1]) close_button.observe(close_btn_click, "value") close_control = ipyleaflet.WidgetControl( widget=close_button, position="bottomright" ) self.add_control(control) if add_close_button: self.add_control(close_control) except Exception as e: print("The provided layers are invalid!") raise ValueError(e)
[docs] def ts_inspector( self, left_ts, left_names=None, left_vis={}, left_index=0, right_ts=None, right_names=None, right_vis=None, right_index=-1, width="130px", date_format="YYYY-MM-dd", add_close_button=False, **kwargs, ): """Creates a split-panel map for inspecting timeseries images. Args: left_ts (object): An ee.ImageCollection to show on the left panel. left_names (list): A list of names to show under the left dropdown. left_vis (dict, optional): Visualization parameters for the left layer. Defaults to {}. left_index (int, optional): The index of the left layer to show. Defaults to 0. right_ts (object): An ee.ImageCollection to show on the right panel. right_names (list): A list of names to show under the right dropdown. right_vis (dict, optional): Visualization parameters for the right layer. Defaults to {}. right_index (int, optional): The index of the right layer to show. Defaults to -1. width (str, optional): The width of the dropdown list. Defaults to '130px'. date_format (str, optional): The date format to show in the dropdown. Defaults to 'YYYY-MM-dd'. add_close_button (bool, optional): Whether to show the close button. Defaults to False. """ controls = self.controls layers = self.layers if left_names is None: left_names = image_dates(left_ts, date_format=date_format).getInfo() if right_ts is None: right_ts = left_ts if right_names is None: right_names = left_names if right_vis is None: right_vis = left_vis left_count = int(left_ts.size().getInfo()) right_count = int(right_ts.size().getInfo()) if left_count != len(left_names): print( "The number of images in left_ts must match the number of layer names in left_names." ) return if right_count != len(right_names): print( "The number of images in right_ts must match the number of layer names in right_names." ) return left_layer = ipyleaflet.TileLayer( url="https://mt1.google.com/vt/lyrs=m&x={x}&y={y}&z={z}", attribution="Google", name="Google Maps", ) right_layer = ipyleaflet.TileLayer( url="https://mt1.google.com/vt/lyrs=m&x={x}&y={y}&z={z}", attribution="Google", name="Google Maps", ) self.clear_controls() left_dropdown = widgets.Dropdown(options=left_names, value=None) right_dropdown = widgets.Dropdown(options=right_names, value=None) left_dropdown.layout.max_width = width right_dropdown.layout.max_width = width left_control = ipyleaflet.WidgetControl( widget=left_dropdown, position="topleft" ) right_control = ipyleaflet.WidgetControl( widget=right_dropdown, position="topright" ) self.add_control(control=left_control) self.add_control(control=right_control) self.add_control(ipyleaflet.ZoomControl(position="topleft")) self.add_control(ipyleaflet.ScaleControl(position="bottomleft")) self.add_control(ipyleaflet.FullScreenControl()) def left_dropdown_change(change): left_dropdown_index = left_dropdown.index if left_dropdown_index is not None and left_dropdown_index >= 0: try: if isinstance(left_ts, ee.ImageCollection): left_image = left_ts.toList(left_ts.size()).get( left_dropdown_index ) elif isinstance(left_ts, ee.List): left_image = left_ts.get(left_dropdown_index) else: print("The left_ts argument must be an ImageCollection.") return if isinstance(left_image, ee.ImageCollection): left_image = ee.Image(left_image.mosaic()) elif isinstance(left_image, ee.Image): pass else: left_image = ee.Image(left_image) left_image = ee_tile_layer( left_image, left_vis, left_names[left_dropdown_index] ) left_layer.url = left_image.url except Exception as e: print(e) return left_dropdown.observe(left_dropdown_change, names="value") def right_dropdown_change(change): right_dropdown_index = right_dropdown.index if right_dropdown_index is not None and right_dropdown_index >= 0: try: if isinstance(right_ts, ee.ImageCollection): right_image = right_ts.toList(left_ts.size()).get( right_dropdown_index ) elif isinstance(right_ts, ee.List): right_image = right_ts.get(right_dropdown_index) else: print("The left_ts argument must be an ImageCollection.") return if isinstance(right_image, ee.ImageCollection): right_image = ee.Image(right_image.mosaic()) elif isinstance(right_image, ee.Image): pass else: right_image = ee.Image(right_image) right_image = ee_tile_layer( right_image, right_vis, right_names[right_dropdown_index], ) right_layer.url = right_image.url except Exception as e: print(e) return right_dropdown.observe(right_dropdown_change, names="value") if left_index is not None: left_dropdown.value = left_names[left_index] if right_index is not None: right_dropdown.value = right_names[right_index] close_button = widgets.ToggleButton( value=False, tooltip="Close the tool", icon="times", # button_style="primary", layout=widgets.Layout( height="28px", width="28px", padding="0px 0px 0px 4px" ), ) def close_btn_click(change): if change["new"]: self.controls = controls self.clear_layers() self.layers = layers close_button.observe(close_btn_click, "value") close_control = ipyleaflet.WidgetControl( widget=close_button, position="bottomright" ) try: split_control = ipyleaflet.SplitMapControl( left_layer=left_layer, right_layer=right_layer ) self.add_control(split_control) if add_close_button: self.add_control(close_control) except Exception as e: raise Exception(e)
[docs] def basemap_demo(self): """A demo for using geemap basemaps.""" dropdown = widgets.Dropdown( options=list(basemaps.keys()), value="HYBRID", description="Basemaps", ) def on_click(change): basemap_name = change["new"] old_basemap = self.layers[-1] self.substitute_layer(old_basemap, basemaps[basemap_name]) dropdown.observe(on_click, "value") basemap_control = ipyleaflet.WidgetControl(widget=dropdown, position="topright") self.add_control(basemap_control)
[docs] def add_legend( self, title="Legend", legend_dict=None, labels=None, colors=None, position="bottomright", builtin_legend=None, layer_name=None, **kwargs, ): """Adds a customized basemap to the map. Args: title (str, optional): Title of the legend. Defaults to 'Legend'. legend_dict (dict, optional): A dictionary containing legend items as keys and color as values. If provided, legend_keys and legend_colors will be ignored. Defaults to None. labels (list, optional): A list of legend keys. Defaults to None. colors (list, optional): A list of legend colors. Defaults to None. position (str, optional): Position of the legend. Defaults to 'bottomright'. builtin_legend (str, optional): Name of the builtin legend to add to the map. Defaults to None. layer_name (str, optional): Layer name of the legend to be associated with. Defaults to None. """ from IPython.display import display pkg_dir = os.path.dirname( pkg_resources.resource_filename("geemap", "geemap.py") ) legend_template = os.path.join(pkg_dir, "data/template/legend.html") if "min_width" not in kwargs.keys(): min_width = None if "max_width" not in kwargs.keys(): max_width = None else: max_width = kwargs["max_width"] if "min_height" not in kwargs.keys(): min_height = None else: min_height = kwargs["min_height"] if "max_height" not in kwargs.keys(): max_height = None else: max_height = kwargs["max_height"] if "height" not in kwargs.keys(): height = None else: height = kwargs["height"] if "width" not in kwargs.keys(): width = None else: width = kwargs["width"] if width is None: max_width = "300px" if height is None: max_height = "400px" if not os.path.exists(legend_template): print("The legend template does not exist.") return if labels is not None: if not isinstance(labels, list): print("The legend keys must be a list.") return else: labels = ["One", "Two", "Three", "Four", "etc"] if colors is not None: if not isinstance(colors, list): print("The legend colors must be a list.") return elif all(isinstance(item, tuple) for item in colors): try: colors = [rgb_to_hex(x) for x in colors] except Exception as e: print(e) elif all((item.startswith("#") and len(item) == 7) for item in colors): pass elif all((len(item) == 6) for item in colors): pass else: print("The legend colors must be a list of tuples.") return else: colors = [ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", ] if len(labels) != len(colors): print("The legend keys and values must be the same length.") return allowed_builtin_legends = builtin_legends.keys() if builtin_legend is not None: if builtin_legend not in allowed_builtin_legends: print( "The builtin legend must be one of the following: {}".format( ", ".join(allowed_builtin_legends) ) ) return else: legend_dict = builtin_legends[builtin_legend] labels = list(legend_dict.keys()) colors = list(legend_dict.values()) if legend_dict is not None: if not isinstance(legend_dict, dict): print("The legend dict must be a dictionary.") return else: labels = list(legend_dict.keys()) colors = list(legend_dict.values()) if all(isinstance(item, tuple) for item in colors): try: colors = [rgb_to_hex(x) for x in colors] except Exception as e: print(e) allowed_positions = [ "topleft", "topright", "bottomleft", "bottomright", ] if position not in allowed_positions: print( "The position must be one of the following: {}".format( ", ".join(allowed_positions) ) ) return header = [] content = [] footer = [] with open(legend_template) as f: lines = f.readlines() lines[3] = lines[3].replace("Legend", title) header = lines[:6] footer = lines[11:] for index, key in enumerate(labels): color = colors[index] if not color.startswith("#"): color = "#" + color item = " <li><span style='background:{};'></span>{}</li>\n".format( color, key ) content.append(item) legend_html = header + content + footer legend_text = "".join(legend_html) try: legend_output_widget = widgets.Output( layout={ # "border": "1px solid black", "max_width": max_width, "min_width": min_width, "max_height": max_height, "min_height": min_height, "height": height, "width": width, "overflow": "scroll", } ) legend_control = ipyleaflet.WidgetControl( widget=legend_output_widget, position=position ) legend_widget = widgets.HTML(value=legend_text) with legend_output_widget: display(legend_widget) self.legend_widget = legend_output_widget self.legend_control = legend_control self.add_control(legend_control) if not hasattr(self, "legends"): setattr(self, "legends", [legend_control]) else: self.legends.append(legend_control) if layer_name in self.ee_layer_names: self.ee_layer_dict[layer_name]["legend"] = legend_control except Exception as e: raise Exception(e)
[docs] def add_colorbar( self, vis_params=None, cmap="gray", discrete=False, label=None, orientation="horizontal", position="bottomright", transparent_bg=False, layer_name=None, **kwargs, ): """Add a matplotlib colorbar to the map Args: vis_params (dict): Visualization parameters as a dictionary. See https://developers.google.com/earth-engine/guides/image_visualization for options. cmap (str, optional): Matplotlib colormap. Defaults to "gray". See https://matplotlib.org/3.3.4/tutorials/colors/colormaps.html#sphx-glr-tutorials-colors-colormaps-py for options. discrete (bool, optional): Whether to create a discrete colorbar. Defaults to False. label (str, optional): Label for the colorbar. Defaults to None. orientation (str, optional): Orientation of the colorbar, such as "vertical" and "horizontal". Defaults to "horizontal". position (str, optional): Position of the colorbar on the map. It can be one of: topleft, topright, bottomleft, and bottomright. Defaults to "bottomright". transparent_bg (bool, optional): Whether to use transparent background. Defaults to False. layer_name (str, optional): The layer name associated with the colorbar. Defaults to None. Raises: TypeError: If the vis_params is not a dictionary. ValueError: If the orientation is not either horizontal or vertical. ValueError: If the provided min value is not scalar type. ValueError: If the provided max value is not scalar type. ValueError: If the provided opacity value is not scalar type. ValueError: If cmap or palette is not provided. """ import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np if isinstance(vis_params, list): vis_params = {"palette": vis_params} elif isinstance(vis_params, tuple): vis_params = {"palette": list(vis_params)} elif vis_params is None: vis_params = {} if "colors" in kwargs and isinstance(kwargs["colors"], list): vis_params["palette"] = kwargs["colors"] if "colors" in kwargs and isinstance(kwargs["colors"], tuple): vis_params["palette"] = list(kwargs["colors"]) if "vmin" in kwargs: vis_params["min"] = kwargs["vmin"] del kwargs["vmin"] if "vmax" in kwargs: vis_params["max"] = kwargs["vmax"] del kwargs["vmax"] if "caption" in kwargs: label = kwargs["caption"] del kwargs["caption"] if not isinstance(vis_params, dict): raise TypeError("The vis_params must be a dictionary.") if orientation not in ["horizontal", "vertical"]: raise ValueError("The orientation must be either horizontal or vertical.") if orientation == "horizontal": width, height = 6.0, 0.4 else: width, height = 0.4, 4.0 if "width" in kwargs: width = kwargs["width"] kwargs.pop("width") if "height" in kwargs: height = kwargs["height"] kwargs.pop("height") vis_keys = list(vis_params.keys()) if "min" in vis_params: vmin = vis_params["min"] if type(vmin) not in (int, float): raise ValueError("The provided min value must be scalar type.") else: vmin = 0 if "max" in vis_params: vmax = vis_params["max"] if type(vmax) not in (int, float): raise ValueError("The provided max value must be scalar type.") else: vmax = 1 if "opacity" in vis_params: alpha = vis_params["opacity"] if type(alpha) not in (int, float): raise ValueError("The provided opacity value must be type scalar.") elif "alpha" in kwargs: alpha = kwargs["alpha"] else: alpha = 1 if cmap is not None: cmap = mpl.pyplot.get_cmap(cmap) norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax) if "palette" in vis_keys: hexcodes = to_hex_colors(check_cmap(vis_params["palette"])) if discrete: cmap = mpl.colors.ListedColormap(hexcodes) vals = np.linspace(vmin, vmax, cmap.N + 1) norm = mpl.colors.BoundaryNorm(vals, cmap.N) else: cmap = mpl.colors.LinearSegmentedColormap.from_list( "custom", hexcodes, N=256 ) norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax) elif cmap is not None: cmap = mpl.pyplot.get_cmap(cmap) norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax) else: raise ValueError( 'cmap keyword or "palette" key in vis_params must be provided.' ) _, ax = plt.subplots(figsize=(width, height)) cb = mpl.colorbar.ColorbarBase( ax, norm=norm, alpha=alpha, cmap=cmap, orientation=orientation, **kwargs ) if label is not None: cb.set_label(label) elif "bands" in vis_keys: cb.set_label(vis_params["bands"]) output = widgets.Output() colormap_ctrl = ipyleaflet.WidgetControl( widget=output, position=position, transparent_bg=transparent_bg, ) with output: output.clear_output() plt.show() self.colorbar = colormap_ctrl if layer_name in self.ee_layer_names: if "colorbar" in self.ee_layer_dict[layer_name]: self.remove_control(self.ee_layer_dict[layer_name]["colorbar"]) self.ee_layer_dict[layer_name]["colorbar"] = colormap_ctrl if not hasattr(self, "colorbars"): self.colorbars = [colormap_ctrl] else: self.colorbars.append(colormap_ctrl) self.add_control(colormap_ctrl)
[docs] def add_colorbar_branca( self, colors, vmin=0, vmax=1.0, index=None, caption="", categorical=False, step=None, height="45px", transparent_bg=False, position="bottomright", layer_name=None, **kwargs, ): """Add a branca colorbar to the map. Args: colors (list): The set of colors to be used for interpolation. Colors can be provided in the form: * tuples of RGBA ints between 0 and 255 (e.g: (255, 255, 0) or (255, 255, 0, 255)) * tuples of RGBA floats between 0. and 1. (e.g: (1.,1.,0.) or (1., 1., 0., 1.)) * HTML-like string (e.g: “#ffff00) * a color name or shortcut (e.g: “y” or “yellow”) vmin (int, optional): The minimal value for the colormap. Values lower than vmin will be bound directly to colors[0].. Defaults to 0. vmax (float, optional): The maximal value for the colormap. Values higher than vmax will be bound directly to colors[-1]. Defaults to 1.0. index (list, optional):The values corresponding to each color. It has to be sorted, and have the same length as colors. If None, a regular grid between vmin and vmax is created.. Defaults to None. caption (str, optional): The caption for the colormap. Defaults to "". categorical (bool, optional): Whether or not to create a categorical colormap. Defaults to False. step (int, optional): The step to split the LinearColormap into a StepColormap. Defaults to None. height (str, optional): The height of the colormap widget. Defaults to "45px". transparent_bg (bool, optional): Whether to use transparent background for the colormap widget. Defaults to True. position (str, optional): The position for the colormap widget. Defaults to "bottomright". layer_name (str, optional): Layer name of the colorbar to be associated with. Defaults to None. """ from branca.colormap import LinearColormap output = widgets.Output() output.layout.height = height if "width" in kwargs.keys(): output.layout.width = kwargs["width"] if isinstance(colors, Box): try: colors = list(colors["default"]) except Exception as e: print("The provided color list is invalid.") raise Exception(e) if all(len(color) == 6 for color in colors): colors = ["#" + color for color in colors] colormap = LinearColormap( colors=colors, index=index, vmin=vmin, vmax=vmax, caption=caption ) if categorical: if step is not None: colormap = colormap.to_step(step) elif index is not None: colormap = colormap.to_step(len(index) - 1) else: colormap = colormap.to_step(3) colormap_ctrl = ipyleaflet.WidgetControl( widget=output, position=position, transparent_bg=transparent_bg, **kwargs, ) with output: output.clear_output() display(colormap) self.colorbar = colormap_ctrl self.add_control(colormap_ctrl) if not hasattr(self, "colorbars"): self.colorbars = [colormap_ctrl] else: self.colorbars.append(colormap_ctrl) if layer_name in self.ee_layer_names: self.ee_layer_dict[layer_name]["colorbar"] = colormap_ctrl
[docs] def remove_colorbar(self): """Remove colorbar from the map.""" if self.colorbar is not None: self.remove_control(self.colorbar)
[docs] def remove_colorbars(self): """Remove all colorbars from the map.""" if hasattr(self, "colorbars"): for colorbar in self.colorbars: if colorbar in self.controls: self.remove_control(colorbar)
[docs] def remove_legend(self): """Remove legend from the map.""" if self.legend is not None: if self.legend in self.controls: self.remove_control(self.legend)
[docs] def remove_legends(self): """Remove all legends from the map.""" if hasattr(self, "legends"): for legend in self.legends: if legend in self.controls: self.remove_control(legend)
[docs] def image_overlay(self, url, bounds, name): """Overlays an image from the Internet or locally on the map. Args: url (str): http URL or local file path to the image. bounds (tuple): bounding box of the image in the format of (lower_left(lat, lon), upper_right(lat, lon)), such as ((13, -130), (32, -100)). name (str): name of the layer to show on the layer control. """ from base64 import b64encode from io import BytesIO from PIL import Image, ImageSequence try: if not url.startswith("http"): if not os.path.exists(url): print("The provided file does not exist.") return ext = os.path.splitext(url)[1][1:] # file extension image = Image.open(url) f = BytesIO() if ext.lower() == "gif": frames = [] # Loop over each frame in the animated image for frame in ImageSequence.Iterator(image): frame = frame.convert("RGBA") b = BytesIO() frame.save(b, format="gif") frame = Image.open(b) frames.append(frame) frames[0].save( f, format="GIF", save_all=True, append_images=frames[1:], loop=0, ) else: image.save(f, ext) data = b64encode(f.getvalue()) data = data.decode("ascii") url = "data:image/{};base64,".format(ext) + data img = ipyleaflet.ImageOverlay(url=url, bounds=bounds, name=name) self.add_layer(img) except Exception as e: print(e)
[docs] def video_overlay(self, url, bounds, name="Video"): """Overlays a video from the Internet on the map. Args: url (str): http URL of the video, such as "https://www.mapbox.com/bites/00188/patricia_nasa.webm" bounds (tuple): bounding box of the video in the format of (lower_left(lat, lon), upper_right(lat, lon)), such as ((13, -130), (32, -100)). name (str): name of the layer to show on the layer control. """ try: video = ipyleaflet.VideoOverlay(url=url, bounds=bounds, name=name) self.add_layer(video) except Exception as e: print(e)
[docs] def add_landsat_ts_gif( self, layer_name="Timelapse", roi=None, label=None, start_year=1984, end_year=2021, start_date="06-10", end_date="09-20", bands=["NIR", "Red", "Green"], vis_params=None, dimensions=768, frames_per_second=10, font_size=30, font_color="white", add_progress_bar=True, progress_bar_color="white", progress_bar_height=5, out_gif=None, download=False, apply_fmask=True, nd_bands=None, nd_threshold=0, nd_palette=["black", "blue"], ): """Adds a Landsat timelapse to the map. Args: layer_name (str, optional): Layer name to show under the layer control. Defaults to 'Timelapse'. roi (object, optional): Region of interest to create the timelapse. Defaults to None. label (str, optional): A label to show on the GIF, such as place name. Defaults to None. start_year (int, optional): Starting year for the timelapse. Defaults to 1984. end_year (int, optional): Ending year for the timelapse. Defaults to 2021. start_date (str, optional): Starting date (month-day) each year for filtering ImageCollection. Defaults to '06-10'. end_date (str, optional): Ending date (month-day) each year for filtering ImageCollection. Defaults to '09-20'. bands (list, optional): Three bands selected from ['Blue', 'Green', 'Red', 'NIR', 'SWIR1', 'SWIR2', 'pixel_qa']. Defaults to ['NIR', 'Red', 'Green']. vis_params (dict, optional): Visualization parameters. Defaults to None. dimensions (int, optional): a number or pair of numbers in format WIDTHxHEIGHT) Maximum dimensions of the thumbnail to render, in pixels. If only one number is passed, it is used as the maximum, and the other dimension is computed by proportional scaling. Defaults to 768. frames_per_second (int, optional): Animation speed. Defaults to 10. font_size (int, optional): Font size of the animated text and label. Defaults to 30. font_color (str, optional): Font color of the animated text and label. Defaults to 'black'. add_progress_bar (bool, optional): Whether to add a progress bar at the bottom of the GIF. Defaults to True. progress_bar_color (str, optional): Color for the progress bar. Defaults to 'white'. progress_bar_height (int, optional): Height of the progress bar. Defaults to 5. out_gif (str, optional): File path to the output animated GIF. Defaults to None. download (bool, optional): Whether to download the gif. Defaults to False. apply_fmask (bool, optional): Whether to apply Fmask (Function of mask) for automated clouds, cloud shadows, snow, and water masking. nd_bands (list, optional): A list of names specifying the bands to use, e.g., ['Green', 'SWIR1']. The normalized difference is computed as (first − second) / (first + second). Note that negative input values are forced to 0 so that the result is confined to the range (-1, 1). nd_threshold (float, optional): The threshold for extacting pixels from the normalized difference band. nd_palette (str, optional): The color palette to use for displaying the normalized difference band. """ try: if roi is None: if self.draw_last_feature is not None: feature = self.draw_last_feature roi = feature.geometry() else: roi = ee.Geometry.Polygon( [ [ [-115.471773, 35.892718], [-115.471773, 36.409454], [-114.271283, 36.409454], [-114.271283, 35.892718], [-115.471773, 35.892718], ] ], None, False, ) elif isinstance(roi, ee.Feature) or isinstance(roi, ee.FeatureCollection): roi = roi.geometry() elif isinstance(roi, ee.Geometry): pass else: print("The provided roi is invalid. It must be an ee.Geometry") return geojson = ee_to_geojson(roi) bounds = minimum_bounding_box(geojson) geojson = adjust_longitude(geojson) roi = ee.Geometry(geojson) in_gif = landsat_timelapse( roi=roi, out_gif=out_gif, start_year=start_year, end_year=end_year, start_date=start_date, end_date=end_date, bands=bands, vis_params=vis_params, dimensions=dimensions, frames_per_second=frames_per_second, apply_fmask=apply_fmask, nd_bands=nd_bands, nd_threshold=nd_threshold, nd_palette=nd_palette, font_size=font_size, font_color=font_color, progress_bar_color=progress_bar_color, progress_bar_height=progress_bar_height, ) in_nd_gif = in_gif.replace(".gif", "_nd.gif") if nd_bands is not None: add_text_to_gif( in_nd_gif, in_nd_gif, xy=("2%", "2%"), text_sequence=start_year, font_size=font_size, font_color=font_color, duration=int(1000 / frames_per_second), add_progress_bar=add_progress_bar, progress_bar_color=progress_bar_color, progress_bar_height=progress_bar_height, ) if label is not None: add_text_to_gif( in_gif, in_gif, xy=("2%", "90%"), text_sequence=label, font_size=font_size, font_color=font_color, duration=int(1000 / frames_per_second), add_progress_bar=add_progress_bar, progress_bar_color=progress_bar_color, progress_bar_height=progress_bar_height, ) # if nd_bands is not None: # add_text_to_gif(in_nd_gif, in_nd_gif, xy=('2%', '90%'), text_sequence=label, # font_size=font_size, font_color=font_color, duration=int(1000 / frames_per_second), add_progress_bar=add_progress_bar, progress_bar_color=progress_bar_color, progress_bar_height=progress_bar_height) if is_tool("ffmpeg"): reduce_gif_size(in_gif) if nd_bands is not None: reduce_gif_size(in_nd_gif) print("Adding GIF to the map ...") self.image_overlay(url=in_gif, bounds=bounds, name=layer_name) if nd_bands is not None: self.image_overlay( url=in_nd_gif, bounds=bounds, name=layer_name + " ND" ) print("The timelapse has been added to the map.") if download: link = create_download_link( in_gif, title="Click here to download the Landsat timelapse: ", ) display(link) if nd_bands is not None: link2 = create_download_link( in_nd_gif, title="Click here to download the Normalized Difference Index timelapse: ", ) display(link2) except Exception as e: raise Exception(e)
[docs] def to_html( self, filename=None, title="My Map", width="100%", height="880px", add_layer_control=True, **kwargs, ): """Saves the map as an HTML file. Args: filename (str, optional): The output file path to the HTML file. title (str, optional): The title of the HTML file. Defaults to 'My Map'. width (str, optional): The width of the map in pixels or percentage. Defaults to '100%'. height (str, optional): The height of the map in pixels. Defaults to '880px'. add_layer_control (bool, optional): Whether to add the LayersControl. Defaults to True. """ try: save = True if filename is not None: if not filename.endswith(".html"): raise ValueError("The output file extension must be html.") filename = os.path.abspath(filename) out_dir = os.path.dirname(filename) if not os.path.exists(out_dir): os.makedirs(out_dir) else: filename = os.path.abspath(random_string() + ".html") save = False if add_layer_control and self.layer_control is None: layer_control = ipyleaflet.LayersControl(position="topright") self.layer_control = layer_control self.add_control(layer_control) before_width = self.layout.width before_height = self.layout.height if not isinstance(width, str): print("width must be a string.") return elif width.endswith("px") or width.endswith("%"): pass else: print("width must end with px or %") return if not isinstance(height, str): print("height must be a string.") return elif not height.endswith("px"): print("height must end with px") return self.layout.width = width self.layout.height = height self.save(filename, title=title, **kwargs) self.layout.width = before_width self.layout.height = before_height if not save: out_html = "" with open(filename) as f: lines = f.readlines() out_html = "".join(lines) os.remove(filename) return out_html except Exception as e: raise Exception(e)
[docs] def to_image(self, filename=None, monitor=1): """Saves the map as a PNG or JPG image. Args: filename (str, optional): The output file path to the image. Defaults to None. monitor (int, optional): The monitor to take the screenshot. Defaults to 1. """ if filename is None: filename = os.path.join(os.getcwd(), "my_map.png") if filename.endswith(".png") or filename.endswith(".jpg"): pass else: print("The output file must be a PNG or JPG image.") return work_dir = os.path.dirname(filename) if not os.path.exists(work_dir): os.makedirs(work_dir) screenshot = screen_capture(filename, monitor) self.screenshot = screenshot
[docs] def toolbar_reset(self): """Reset the toolbar so that no tool is selected.""" toolbar_grid = self.toolbar for tool in toolbar_grid.children: tool.value = False
[docs] def add_raster( self, source, band=None, palette=None, vmin=None, vmax=None, nodata=None, attribution=None, layer_name=None, **kwargs, ): """Add a local raster dataset to the map. Args: source (str): The path to the GeoTIFF file or the URL of the Cloud Optimized GeoTIFF. band (int, optional): The band to use. Band indexing starts at 1. Defaults to None. palette (str, optional): The name of the color palette from `palettable` to use when plotting a single band. See https://jiffyclub.github.io/palettable. 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 None. """ if in_colab_shell(): print("This add_raster() function is not supported in Colab.") return tile_layer, tile_client = get_local_tile_layer( source, band=band, palette=palette, vmin=vmin, vmax=vmax, nodata=nodata, attribution=attribution, layer_name=layer_name, return_client=True, **kwargs, ) self.add_layer(tile_layer) output = widgets.Output() with output: bounds = tile_client.bounds() # [ymin, ymax, xmin, xmax] bounds = ( bounds[2], bounds[0], bounds[3], bounds[1], ) # [minx, miny, maxx, maxy] self.zoom_to_bounds(bounds) if not hasattr(self, "cog_layer_dict"): self.cog_layer_dict = {} band_names = list(tile_client.metadata()["bands"].keys()) params = { "tile_layer": tile_layer, "tile_client": tile_client, "band": band, "band_names": band_names, "bounds": bounds, "type": "LOCAL", } self.cog_layer_dict[layer_name] = params
add_local_tile = add_raster
[docs] def add_remote_tile( self, source, band=None, palette=None, vmin=None, vmax=None, nodata=None, attribution=None, layer_name=None, **kwargs, ): """Add a remote Cloud Optimized GeoTIFF (COG) to the map. Args: source (str): The path to the remote Cloud Optimized GeoTIFF. band (int, optional): The band to use. Band indexing starts at 1. Defaults to None. palette (str, optional): The name of the color palette from `palettable` to use when plotting a single band. See https://jiffyclub.github.io/palettable. 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 None. """ if isinstance(source, str) and source.startswith("http"): self.add_raster( source, band=band, palette=palette, vmin=vmin, vmax=vmax, nodata=nodata, attribution=attribution, layer_name=layer_name, **kwargs, ) else: raise Exception("The source must be a URL.")
[docs] def add_raster_legacy( self, image, bands=None, layer_name=None, colormap=None, x_dim="x", y_dim="y", ): """Adds a local raster dataset to the map. Args: image (str): The image file path. bands (int or list, optional): The image bands to use. It can be either a number (e.g., 1) or a list (e.g., [3, 2, 1]). Defaults to None. layer_name (str, optional): The layer name to use for the raster. Defaults to None. colormap (str, optional): The name of the colormap to use for the raster, such as 'gray' and 'terrain'. More can be found at https://matplotlib.org/3.1.0/tutorials/colors/colormaps.html. Defaults to None. x_dim (str, optional): The x dimension. Defaults to 'x'. y_dim (str, optional): The y dimension. Defaults to 'y'. """ try: import xarray_leaflet except Exception: # import platform # if platform.system() != "Windows": # # install_from_github( # # url='https://github.com/davidbrochart/xarray_leaflet') # check_install('xarray_leaflet') # import xarray_leaflet # else: raise ImportError( "You need to install xarray_leaflet first. See https://github.com/davidbrochart/xarray_leaflet" ) import warnings # import xarray as xr import matplotlib.pyplot as plt import numpy as np import rioxarray warnings.simplefilter("ignore") if not os.path.exists(image): print("The image file does not exist.") return if colormap is None: colormap = plt.cm.inferno if layer_name is None: layer_name = "Layer_" + random_string() if isinstance(colormap, str): colormap = plt.cm.get_cmap(name=colormap) da = rioxarray.open_rasterio(image, masked=True) # print(da.rio.nodata) multi_band = False if len(da.band) > 1: multi_band = True if bands is None: bands = [3, 2, 1] else: bands = 1 if multi_band: da = da.rio.write_nodata(0) else: da = da.rio.write_nodata(np.nan) da = da.sel(band=bands) # crs = da.rio.crs # nan = da.attrs['nodatavals'][0] # da = da / da.max() # # if multi_band: # da = xr.where(da == nan, np.nan, da) # da = da.rio.write_nodata(0) # da = da.rio.write_crs(crs) if multi_band and type(bands) == list: layer = da.leaflet.plot(self, x_dim=x_dim, y_dim=y_dim, rgb_dim="band") else: layer = da.leaflet.plot(self, x_dim=x_dim, y_dim=y_dim, colormap=colormap) layer.name = layer_name
[docs] def remove_drawn_features(self): """Removes user-drawn geometries from the map""" if self.draw_layer is not None: self.remove_layer(self.draw_layer) self.draw_count = 0 self.draw_features = [] self.draw_last_feature = None self.draw_layer = None self.draw_last_json = None self.draw_last_bounds = None self.user_roi = None self.user_rois = None self.chart_values = [] self.chart_points = [] self.chart_labels = None if self.draw_control is not None: self.draw_control.clear()
[docs] def remove_last_drawn(self): """Removes user-drawn geometries from the map""" if self.draw_layer is not None: collection = ee.FeatureCollection(self.draw_features[:-1]) ee_draw_layer = ee_tile_layer( collection, {"color": "blue"}, "Drawn Features", True, 0.5 ) if self.draw_count == 1: self.remove_drawn_features() else: self.substitute_layer(self.draw_layer, ee_draw_layer) self.draw_layer = ee_draw_layer self.draw_count -= 1 self.draw_features = self.draw_features[:-1] self.draw_last_feature = self.draw_features[-1] self.draw_layer = ee_draw_layer self.draw_last_json = None self.draw_last_bounds = None self.user_roi = ee.Feature( collection.toList(collection.size()).get( collection.size().subtract(1) ) ).geometry() self.user_rois = collection self.chart_values = self.chart_values[:-1] self.chart_points = self.chart_points[:-1]
# self.chart_labels = None
[docs] def extract_values_to_points(self, filename): """Exports pixel values to a csv file based on user-drawn geometries. Args: filename (str): The output file path to the csv file or shapefile. """ import csv filename = os.path.abspath(filename) allowed_formats = ["csv", "shp"] ext = filename[-3:] if ext not in allowed_formats: print( "The output file must be one of the following: {}".format( ", ".join(allowed_formats) ) ) return out_dir = os.path.dirname(filename) out_csv = filename[:-3] + "csv" out_shp = filename[:-3] + "shp" if not os.path.exists(out_dir): os.makedirs(out_dir) count = len(self.chart_points) out_list = [] if count > 0: header = ["id", "longitude", "latitude"] + self.chart_labels out_list.append(header) for i in range(0, count): id = i + 1 line = [id] + self.chart_points[i] + self.chart_values[i] out_list.append(line) with open(out_csv, "w", newline="") as f: writer = csv.writer(f) writer.writerows(out_list) if ext == "csv": print(f"The csv file has been saved to: {out_csv}") else: csv_to_shp(out_csv, out_shp) print(f"The shapefile has been saved to: {out_shp}")
[docs] def create_vis_widget(self, layer_dict): """Create a GUI for changing layer visualization parameters interactively. Args: layer_dict (dict): A dict containning information about the layer. It is an element from Map.ee_layer_dict. Returns: object: An ipywidget. """ import matplotlib as mpl import matplotlib.pyplot as plt ee_object = layer_dict["ee_object"] ee_layer = layer_dict["ee_layer"] vis_params = layer_dict["vis_params"] layer_name = ee_layer.name layer_opacity = ee_layer.opacity band_names = None min_value = 0 max_value = 100 sel_bands = None layer_palette = [] layer_gamma = 1 left_value = 0 right_value = 10000 self.colorbar_widget = widgets.Output(layout=widgets.Layout(height="60px")) self.colorbar_ctrl = ipyleaflet.WidgetControl( widget=self.colorbar_widget, position="bottomright" ) self.add_control(self.colorbar_ctrl) # def vdir(obj): # Get branca colormap list # return [x for x in dir(obj) if not x.startswith("_")] if isinstance(ee_object, ee.Image): band_names = ee_object.bandNames().getInfo() band_count = len(band_names) if "min" in vis_params.keys(): min_value = vis_params["min"] if min_value < left_value: left_value = min_value - max_value if "max" in vis_params.keys(): max_value = vis_params["max"] right_value = 2 * max_value if "gamma" in vis_params.keys(): layer_gamma = vis_params["gamma"] if "bands" in vis_params.keys(): sel_bands = vis_params["bands"] if "palette" in vis_params.keys(): layer_palette = [ color.replace("#", "") for color in list(vis_params["palette"]) ] vis_widget = widgets.VBox( layout=widgets.Layout(padding="5px 5px 5px 8px", width="330px") ) label = widgets.Label(value=f"{layer_name} visualization parameters") radio1 = widgets.RadioButtons( options=["1 band (Grayscale)"], layout={"width": "max-content"} ) radio2 = widgets.RadioButtons( options=["3 bands (RGB)"], layout={"width": "max-content"} ) radio1.index = None radio2.index = None dropdown_width = "98px" band1_dropdown = widgets.Dropdown( options=band_names, value=band_names[0], layout=widgets.Layout(width=dropdown_width), ) band2_dropdown = widgets.Dropdown( options=band_names, value=band_names[0], layout=widgets.Layout(width=dropdown_width), ) band3_dropdown = widgets.Dropdown( options=band_names, value=band_names[0], layout=widgets.Layout(width=dropdown_width), ) bands_hbox = widgets.HBox() legend_chk = widgets.Checkbox( value=False, description="Legend", indent=False, layout=widgets.Layout(width="70px"), ) color_picker = widgets.ColorPicker( concise=False, value="#000000", layout=widgets.Layout(width="116px"), style={"description_width": "initial"}, ) add_color = widgets.Button( icon="plus", tooltip="Add a hex color string to the palette", layout=widgets.Layout(width="32px"), ) del_color = widgets.Button( icon="minus", tooltip="Remove a hex color string from the palette", layout=widgets.Layout(width="32px"), ) reset_color = widgets.Button( icon="eraser", tooltip="Remove all color strings from the palette", layout=widgets.Layout(width="34px"), ) classes = widgets.Dropdown( options=["Any"] + [str(i) for i in range(3, 13)], description="Classes:", layout=widgets.Layout(width="115px"), style={"description_width": "initial"}, ) colormap_options = plt.colormaps() colormap_options.sort() colormap = widgets.Dropdown( options=colormap_options, value=None, description="Colormap:", layout=widgets.Layout(width="181px"), style={"description_width": "initial"}, ) def classes_changed(change): if change["new"]: selected = change["owner"].value if colormap.value is not None: n_class = None if selected != "Any": n_class = int(classes.value) colors = plt.cm.get_cmap(colormap.value, n_class) cmap_colors = [ mpl.colors.rgb2hex(colors(i))[1:] for i in range(colors.N) ] _, ax = plt.subplots(figsize=(6, 0.4)) cmap = mpl.colors.LinearSegmentedColormap.from_list( "custom", to_hex_colors(cmap_colors), N=256 ) norm = mpl.colors.Normalize( vmin=value_range.value[0], vmax=value_range.value[1] ) mpl.colorbar.ColorbarBase( ax, norm=norm, cmap=cmap, orientation="horizontal" ) palette.value = ", ".join([color for color in cmap_colors]) if self.colorbar_widget is None: self.colorbar_widget = widgets.Output( layout=widgets.Layout(height="60px") ) if self.colorbar_ctrl is None: self.colorbar_ctrl = ipyleaflet.WidgetControl( widget=self.colorbar_widget, position="bottomright" ) self.add_control(self.colorbar_ctrl) colorbar_output = self.colorbar_widget with colorbar_output: colorbar_output.clear_output() plt.show() if len(palette.value) > 0 and "," in palette.value: labels = [ f"Class {i+1}" for i in range(len(palette.value.split(","))) ] legend_labels.value = ", ".join(labels) classes.observe(classes_changed, "value") palette = widgets.Text( value=", ".join(layer_palette), placeholder="List of hex color code (RRGGBB)", description="Palette:", tooltip="Enter a list of hex color code (RRGGBB)", layout=widgets.Layout(width="300px"), style={"description_width": "initial"}, ) def add_color_clicked(b): if color_picker.value is not None: if len(palette.value) == 0: palette.value = color_picker.value[1:] else: palette.value += ", " + color_picker.value[1:] def del_color_clicked(b): if "," in palette.value: items = [item.strip() for item in palette.value.split(",")] palette.value = ", ".join(items[:-1]) else: palette.value = "" def reset_color_clicked(b): palette.value = "" add_color.on_click(add_color_clicked) del_color.on_click(del_color_clicked) reset_color.on_click(reset_color_clicked) spacer = widgets.Label(layout=widgets.Layout(width="5px")) v_spacer = widgets.Label(layout=widgets.Layout(height="5px")) radio_btn = widgets.HBox([radio1, spacer, spacer, spacer, radio2]) value_range = widgets.FloatRangeSlider( value=[min_value, max_value], min=left_value, max=right_value, step=0.1, description="Range:", disabled=False, continuous_update=False, readout=True, readout_format=".1f", layout=widgets.Layout(width="300px"), style={"description_width": "45px"}, ) range_hbox = widgets.HBox([value_range, spacer]) opacity = widgets.FloatSlider( value=layer_opacity, min=0, max=1, step=0.01, description="Opacity:", continuous_update=False, readout=True, readout_format=".2f", layout=widgets.Layout(width="320px"), style={"description_width": "50px"}, ) gamma = widgets.FloatSlider( value=layer_gamma, min=0.1, max=10, step=0.01, description="Gamma:", continuous_update=False, readout=True, readout_format=".2f", layout=widgets.Layout(width="320px"), style={"description_width": "50px"}, ) legend_chk = widgets.Checkbox( value=False, description="Legend", indent=False, layout=widgets.Layout(width="70px"), ) linear_chk = widgets.Checkbox( value=True, description="Linear colormap", indent=False, layout=widgets.Layout(width="150px"), ) step_chk = widgets.Checkbox( value=False, description="Step colormap", indent=False, layout=widgets.Layout(width="140px"), ) legend_title = widgets.Text( value="Legend", description="Legend title:", tooltip="Enter a title for the legend", layout=widgets.Layout(width="300px"), style={"description_width": "initial"}, ) legend_labels = widgets.Text( value="Class 1, Class 2, Class 3", description="Legend labels:", tooltip="Enter a a list of labels for the legend", layout=widgets.Layout(width="300px"), style={"description_width": "initial"}, ) colormap_hbox = widgets.HBox([linear_chk, step_chk]) legend_vbox = widgets.VBox() def linear_chk_changed(change): if change["new"]: step_chk.value = False legend_vbox.children = [colormap_hbox] else: step_chk.value = True def step_chk_changed(change): if change["new"]: linear_chk.value = False if len(layer_palette) > 0: legend_labels.value = ",".join( [ "Class " + str(i) for i in range(1, len(layer_palette) + 1) ] ) legend_vbox.children = [ colormap_hbox, legend_title, legend_labels, ] else: linear_chk.value = True linear_chk.observe(linear_chk_changed, "value") step_chk.observe(step_chk_changed, "value") def colormap_changed(change): if change["new"]: n_class = None if classes.value != "Any": n_class = int(classes.value) colors = plt.cm.get_cmap(colormap.value, n_class) cmap_colors = [ mpl.colors.rgb2hex(colors(i))[1:] for i in range(colors.N) ] _, ax = plt.subplots(figsize=(6, 0.4)) cmap = mpl.colors.LinearSegmentedColormap.from_list( "custom", to_hex_colors(cmap_colors), N=256 ) norm = mpl.colors.Normalize( vmin=value_range.value[0], vmax=value_range.value[1] ) mpl.colorbar.ColorbarBase( ax, norm=norm, cmap=cmap, orientation="horizontal" ) palette.value = ", ".join(cmap_colors) if self.colorbar_widget is None: self.colorbar_widget = widgets.Output( layout=widgets.Layout(height="60px") ) if self.colorbar_ctrl is None: self.colorbar_ctrl = ipyleaflet.WidgetControl( widget=self.colorbar_widget, position="bottomright" ) self.add_control(self.colorbar_ctrl) colorbar_output = self.colorbar_widget with colorbar_output: colorbar_output.clear_output() plt.show() # display(colorbar) if len(palette.value) > 0 and "," in palette.value: labels = [ f"Class {i+1}" for i in range(len(palette.value.split(","))) ] legend_labels.value = ", ".join(labels) colormap.observe(colormap_changed, "value") btn_width = "97.5px" import_btn = widgets.Button( description="Import", button_style="primary", tooltip="Import vis params to notebook", layout=widgets.Layout(width=btn_width), ) apply_btn = widgets.Button( description="Apply", tooltip="Apply vis params to the layer", layout=widgets.Layout(width=btn_width), ) close_btn = widgets.Button( description="Close", tooltip="Close vis params diaglog", layout=widgets.Layout(width=btn_width), ) def import_btn_clicked(b): vis = {} if radio1.index == 0: vis["bands"] = [band1_dropdown.value] if len(palette.value) > 0: vis["palette"] = palette.value.split(",") else: vis["bands"] = [ band1_dropdown.value, band2_dropdown.value, band3_dropdown.value, ] vis["min"] = value_range.value[0] vis["max"] = value_range.value[1] vis["opacity"] = opacity.value vis["gamma"] = gamma.value create_code_cell(f"vis_params = {str(vis)}") def apply_btn_clicked(b): vis = {} if radio1.index == 0: vis["bands"] = [band1_dropdown.value] if len(palette.value) > 0: vis["palette"] = [c.strip() for c in palette.value.split(",")] else: vis["bands"] = [ band1_dropdown.value, band2_dropdown.value, band3_dropdown.value, ] vis["gamma"] = gamma.value vis["min"] = value_range.value[0] vis["max"] = value_range.value[1] self.addLayer(ee_object, vis, layer_name, True, opacity.value) ee_layer.visible = False if legend_chk.value: if ( self.colorbar_ctrl is not None and self.colorbar_ctrl in self.controls ): self.remove_control(self.colorbar_ctrl) self.colorbar_ctrl.close() self.colorbar_widget.close() if ( "colorbar" in layer_dict.keys() and layer_dict["colorbar"] in self.controls ): self.remove_control(layer_dict["colorbar"]) layer_dict["colorbar"] = None if linear_chk.value: if ( "legend" in layer_dict.keys() and layer_dict["legend"] in self.controls ): self.remove_control(layer_dict["legend"]) layer_dict["legend"] = None if len(palette.value) > 0 and "," in palette.value: colors = to_hex_colors( [color.strip() for color in palette.value.split(",")] ) self.add_colorbar( vis_params={ "palette": colors, "min": value_range.value[0], "max": value_range.value[1], }, layer_name=layer_name, ) elif step_chk.value: if len(palette.value) > 0 and "," in palette.value: colors = to_hex_colors( [color.strip() for color in palette.value.split(",")] ) labels = [ label.strip() for label in legend_labels.value.split(",") ] self.add_legend( title=legend_title.value, legend_keys=labels, legend_colors=colors, layer_name=layer_name, ) else: if radio1.index == 0 and "palette" in vis: self.colorbar_widget.clear_output() with self.colorbar_widget: _, ax = plt.subplots(figsize=(6, 0.4)) colors = to_hex_colors(vis["palette"]) cmap = mpl.colors.LinearSegmentedColormap.from_list( "custom", colors, N=256 ) norm = mpl.colors.Normalize( vmin=vis["min"], vmax=vis["max"] ) mpl.colorbar.ColorbarBase( ax, norm=norm, cmap=cmap, orientation="horizontal" ) plt.show() if ( "colorbar" in layer_dict.keys() and layer_dict["colorbar"] in self.controls ): self.remove_control(layer_dict["colorbar"]) layer_dict["colorbar"] = None if ( "legend" in layer_dict.keys() and layer_dict["legend"] in self.controls ): self.remove_control(layer_dict["legend"]) layer_dict["legend"] = None def close_btn_clicked(b): if self.vis_control in self.controls: self.remove_control(self.vis_control) self.vis_control = None self.vis_widget.close() if ( self.colorbar_ctrl is not None and self.colorbar_ctrl in self.controls ): self.remove_control(self.colorbar_ctrl) self.colorbar_ctrl = None self.colorbar_widget.close() import_btn.on_click(import_btn_clicked) apply_btn.on_click(apply_btn_clicked) close_btn.on_click(close_btn_clicked) color_hbox = widgets.HBox( [legend_chk, color_picker, add_color, del_color, reset_color] ) btn_hbox = widgets.HBox([import_btn, apply_btn, close_btn]) gray_box = [ label, radio_btn, bands_hbox, v_spacer, range_hbox, opacity, gamma, widgets.HBox([classes, colormap]), palette, color_hbox, legend_vbox, btn_hbox, ] rgb_box = [ label, radio_btn, bands_hbox, v_spacer, range_hbox, opacity, gamma, btn_hbox, ] def legend_chk_changed(change): if change["new"]: linear_chk.value = True legend_vbox.children = [ widgets.HBox([linear_chk, step_chk]), # legend_title, # legend_labels, ] else: legend_vbox.children = [] legend_chk.observe(legend_chk_changed, "value") if band_count < 3: radio1.index = 0 band1_dropdown.layout.width = "300px" bands_hbox.children = [band1_dropdown] vis_widget.children = gray_box legend_chk.value = False if len(palette.value) > 0 and "," in palette.value: import matplotlib as mpl import matplotlib.pyplot as plt colors = to_hex_colors( [color.strip() for color in palette.value.split(",")] ) self.colorbar_widget.clear_output() with self.colorbar_widget: _, ax = plt.subplots(figsize=(6, 0.4)) cmap = mpl.colors.LinearSegmentedColormap.from_list( "custom", colors, N=256 ) norm = mpl.colors.Normalize( vmin=value_range.value[0], vmax=value_range.value[1] ) mpl.colorbar.ColorbarBase( ax, norm=norm, cmap=cmap, orientation="horizontal" ) plt.show() else: radio2.index = 0 if (sel_bands is None) or (len(sel_bands) < 2): sel_bands = band_names[0:3] band1_dropdown.value = sel_bands[0] band2_dropdown.value = sel_bands[1] band3_dropdown.value = sel_bands[2] bands_hbox.children = [ band1_dropdown, band2_dropdown, band3_dropdown, ] vis_widget.children = rgb_box def radio1_observer(sender): radio2.unobserve(radio2_observer, names=["value"]) radio2.index = None radio2.observe(radio2_observer, names=["value"]) band1_dropdown.layout.width = "300px" bands_hbox.children = [band1_dropdown] palette.value = ", ".join(layer_palette) palette.disabled = False color_picker.disabled = False add_color.disabled = False del_color.disabled = False reset_color.disabled = False vis_widget.children = gray_box if len(palette.value) > 0 and "," in palette.value: colors = [color.strip() for color in palette.value.split(",")] _, ax = plt.subplots(figsize=(6, 0.4)) cmap = mpl.colors.LinearSegmentedColormap.from_list( "custom", to_hex_colors(colors), N=256 ) norm = mpl.colors.Normalize(vmin=0, vmax=1) mpl.colorbar.ColorbarBase( ax, norm=norm, cmap=cmap, orientation="horizontal" ) self.colorbar_widget = widgets.Output( layout=widgets.Layout(height="60px") ) self.colorbar_ctrl = ipyleaflet.WidgetControl( widget=self.colorbar_widget, position="bottomright" ) if self.colorbar_ctrl not in self.controls: self.add_control(self.colorbar_ctrl) self.colorbar_widget.clear_output() with self.colorbar_widget: plt.show() def radio2_observer(sender): radio1.unobserve(radio1_observer, names=["value"]) radio1.index = None radio1.observe(radio1_observer, names=["value"]) band1_dropdown.layout.width = dropdown_width bands_hbox.children = [ band1_dropdown, band2_dropdown, band3_dropdown, ] palette.value = "" palette.disabled = True color_picker.disabled = True add_color.disabled = True del_color.disabled = True reset_color.disabled = True vis_widget.children = rgb_box if ( self.colorbar_ctrl is not None and self.colorbar_ctrl in self.controls ): self.remove_control(self.colorbar_ctrl) self.colorbar_ctrl.close() self.colorbar_widget.close() radio1.observe(radio1_observer, names=["value"]) radio2.observe(radio2_observer, names=["value"]) return vis_widget elif isinstance(ee_object, ee.FeatureCollection): vis_widget = widgets.VBox( layout=widgets.Layout(padding="5px 5px 5px 8px", width="330px") ) label = widgets.Label(value=f"{layer_name} visualization parameters") new_layer_name = widgets.Text( value=f"{layer_name} style", description="New layer name:", style={"description_width": "initial"}, ) color = widgets.ColorPicker( concise=False, value="#000000", description="Color:", layout=widgets.Layout(width="140px"), style={"description_width": "initial"}, ) color_opacity = widgets.FloatSlider( value=layer_opacity, min=0, max=1, step=0.01, description="Opacity:", continuous_update=True, readout=False, # readout_format=".2f", layout=widgets.Layout(width="130px"), style={"description_width": "50px"}, ) color_opacity_label = widgets.Label( style={"description_width": "initial"}, layout=widgets.Layout(padding="0px"), ) widgets.jslink((color_opacity, "value"), (color_opacity_label, "value")) point_size = widgets.IntText( value=3, description="Point size:", layout=widgets.Layout(width="110px"), style={"description_width": "initial"}, ) point_shape_options = [ "circle", "square", "diamond", "cross", "plus", "pentagram", "hexagram", "triangle", "triangle_up", "triangle_down", "triangle_left", "triangle_right", "pentagon", "hexagon", "star5", "star6", ] point_shape = widgets.Dropdown( options=point_shape_options, value="circle", description="Point shape:", layout=widgets.Layout(width="185px"), style={"description_width": "initial"}, ) line_width = widgets.IntText( value=2, description="Line width:", layout=widgets.Layout(width="110px"), style={"description_width": "initial"}, ) line_type = widgets.Dropdown( options=["solid", "dotted", "dashed"], value="solid", description="Line type:", layout=widgets.Layout(width="185px"), style={"description_width": "initial"}, ) fill_color = widgets.ColorPicker( concise=False, value="#000000", description="Fill Color:", layout=widgets.Layout(width="160px"), style={"description_width": "initial"}, ) fill_color_opacity = widgets.FloatSlider( value=0.66, min=0, max=1, step=0.01, description="Opacity:", continuous_update=True, readout=False, # readout_format=".2f", layout=widgets.Layout(width="110px"), style={"description_width": "50px"}, ) fill_color_opacity_label = widgets.Label( style={"description_width": "initial"}, layout=widgets.Layout(padding="0px"), ) widgets.jslink( (fill_color_opacity, "value"), (fill_color_opacity_label, "value"), ) color_picker = widgets.ColorPicker( concise=False, value="#000000", layout=widgets.Layout(width="116px"), style={"description_width": "initial"}, ) add_color = widgets.Button( icon="plus", tooltip="Add a hex color string to the palette", layout=widgets.Layout(width="32px"), ) del_color = widgets.Button( icon="minus", tooltip="Remove a hex color string from the palette", layout=widgets.Layout(width="32px"), ) reset_color = widgets.Button( icon="eraser", tooltip="Remove all color strings from the palette", layout=widgets.Layout(width="34px"), ) palette = widgets.Text( value="", placeholder="List of hex code (RRGGBB) separated by comma", description="Palette:", tooltip="Enter a list of hex code (RRGGBB) separated by comma", layout=widgets.Layout(width="300px"), style={"description_width": "initial"}, ) legend_title = widgets.Text( value="Legend", description="Legend title:", tooltip="Enter a title for the legend", layout=widgets.Layout(width="300px"), style={"description_width": "initial"}, ) legend_labels = widgets.Text( value="Labels", description="Legend labels:", tooltip="Enter a a list of labels for the legend", layout=widgets.Layout(width="300px"), style={"description_width": "initial"}, ) def add_color_clicked(b): if color_picker.value is not None: if len(palette.value) == 0: palette.value = color_picker.value[1:] else: palette.value += ", " + color_picker.value[1:] def del_color_clicked(b): if "," in palette.value: items = [item.strip() for item in palette.value.split(",")] palette.value = ", ".join(items[:-1]) else: palette.value = "" def reset_color_clicked(b): palette.value = "" add_color.on_click(add_color_clicked) del_color.on_click(del_color_clicked) reset_color.on_click(reset_color_clicked) field = widgets.Dropdown( options=[], value=None, description="Field:", layout=widgets.Layout(width="140px"), style={"description_width": "initial"}, ) field_values = widgets.Dropdown( options=[], value=None, description="Values:", layout=widgets.Layout(width="156px"), style={"description_width": "initial"}, ) classes = widgets.Dropdown( options=["Any"] + [str(i) for i in range(3, 13)], description="Classes:", layout=widgets.Layout(width="115px"), style={"description_width": "initial"}, ) colormap = widgets.Dropdown( options=["viridis"], value="viridis", description="Colormap:", layout=widgets.Layout(width="181px"), style={"description_width": "initial"}, ) def classes_changed(change): if change["new"]: selected = change["owner"].value if colormap.value is not None: n_class = None if selected != "Any": n_class = int(classes.value) colors = plt.cm.get_cmap(colormap.value, n_class) cmap_colors = [ mpl.colors.rgb2hex(colors(i))[1:] for i in range(colors.N) ] _, ax = plt.subplots(figsize=(6, 0.4)) cmap = mpl.colors.LinearSegmentedColormap.from_list( "custom", to_hex_colors(cmap_colors), N=256 ) norm = mpl.colors.Normalize(vmin=0, vmax=1) mpl.colorbar.ColorbarBase( ax, norm=norm, cmap=cmap, orientation="horizontal" ) palette.value = ", ".join([color for color in cmap_colors]) if self.colorbar_widget is None: self.colorbar_widget = widgets.Output( layout=widgets.Layout(height="60px") ) if self.colorbar_ctrl is None: self.colorbar_ctrl = ipyleaflet.WidgetControl( widget=self.colorbar_widget, position="bottomright" ) self.add_control(self.colorbar_ctrl) colorbar_output = self.colorbar_widget with colorbar_output: colorbar_output.clear_output() plt.show() if len(palette.value) > 0 and "," in palette.value: labels = [ f"Class {i+1}" for i in range(len(palette.value.split(","))) ] legend_labels.value = ", ".join(labels) classes.observe(classes_changed, "value") def colormap_changed(change): if change["new"]: n_class = None if classes.value != "Any": n_class = int(classes.value) colors = plt.cm.get_cmap(colormap.value, n_class) cmap_colors = [ mpl.colors.rgb2hex(colors(i))[1:] for i in range(colors.N) ] _, ax = plt.subplots(figsize=(6, 0.4)) cmap = mpl.colors.LinearSegmentedColormap.from_list( "custom", to_hex_colors(cmap_colors), N=256 ) norm = mpl.colors.Normalize(vmin=0, vmax=1) mpl.colorbar.ColorbarBase( ax, norm=norm, cmap=cmap, orientation="horizontal" ) palette.value = ", ".join(cmap_colors) if self.colorbar_widget is None: self.colorbar_widget = widgets.Output( layout=widgets.Layout(height="60px") ) if self.colorbar_ctrl is None: self.colorbar_ctrl = ipyleaflet.WidgetControl( widget=self.colorbar_widget, position="bottomright" ) self.add_control(self.colorbar_ctrl) colorbar_output = self.colorbar_widget with colorbar_output: colorbar_output.clear_output() plt.show() # display(colorbar) if len(palette.value) > 0 and "," in palette.value: labels = [ f"Class {i+1}" for i in range(len(palette.value.split(","))) ] legend_labels.value = ", ".join(labels) colormap.observe(colormap_changed, "value") btn_width = "97.5px" import_btn = widgets.Button( description="Import", button_style="primary", tooltip="Import vis params to notebook", layout=widgets.Layout(width=btn_width), ) apply_btn = widgets.Button( description="Apply", tooltip="Apply vis params to the layer", layout=widgets.Layout(width=btn_width), ) close_btn = widgets.Button( description="Close", tooltip="Close vis params diaglog", layout=widgets.Layout(width=btn_width), ) style_chk = widgets.Checkbox( value=False, description="Style by attribute", indent=False, layout=widgets.Layout(width="140px"), ) legend_chk = widgets.Checkbox( value=False, description="Legend", indent=False, layout=widgets.Layout(width="70px"), ) compute_label = widgets.Label(value="") style_vbox = widgets.VBox([widgets.HBox([style_chk, compute_label])]) def style_chk_changed(change): if change["new"]: if ( self.colorbar_ctrl is not None and self.colorbar_ctrl in self.controls ): self.remove_control(self.colorbar_ctrl) self.colorbar_ctrl.close() self.colorbar_widget.close() self.colorbar_widget = widgets.Output( layout=widgets.Layout(height="60px") ) self.colorbar_ctrl = ipyleaflet.WidgetControl( widget=self.colorbar_widget, position="bottomright" ) self.add_control(self.colorbar_ctrl) fill_color.disabled = True colormap_options = plt.colormaps() colormap_options.sort() colormap.options = colormap_options colormap.value = "viridis" style_vbox.children = [ widgets.HBox([style_chk, compute_label]), widgets.HBox([field, field_values]), widgets.HBox([classes, colormap]), palette, widgets.HBox( [ legend_chk, color_picker, add_color, del_color, reset_color, ] ), ] compute_label.value = "Computing ..." field.options = ( ee.Feature(ee_object.first()).propertyNames().getInfo() ) compute_label.value = "" classes.value = "Any" legend_chk.value = False else: fill_color.disabled = False style_vbox.children = [widgets.HBox([style_chk, compute_label])] compute_label.value = "" if ( self.colorbar_ctrl is not None and self.colorbar_ctrl in self.controls ): self.remove_control(self.colorbar_ctrl) self.colorbar_ctrl = None self.colorbar_widget = None # legend_chk.value = False style_chk.observe(style_chk_changed, "value") def legend_chk_changed(change): if change["new"]: style_vbox.children = list(style_vbox.children) + [ widgets.VBox([legend_title, legend_labels]) ] if len(palette.value) > 0 and "," in palette.value: labels = [ f"Class {i+1}" for i in range(len(palette.value.split(","))) ] legend_labels.value = ", ".join(labels) else: style_vbox.children = [ widgets.HBox([style_chk, compute_label]), widgets.HBox([field, field_values]), widgets.HBox([classes, colormap]), palette, widgets.HBox( [ legend_chk, color_picker, add_color, del_color, reset_color, ] ), ] legend_chk.observe(legend_chk_changed, "value") def field_changed(change): if change["new"]: compute_label.value = "Computing ..." options = ee_object.aggregate_array(field.value).getInfo() if options is not None: options = list(set(options)) options.sort() field_values.options = options compute_label.value = "" field.observe(field_changed, "value") def get_vis_params(): vis = {} vis["color"] = color.value[1:] + str( hex(int(color_opacity.value * 255)) )[2:].zfill(2) if geometry_type(ee_object) in ["Point", "MultiPoint"]: vis["pointSize"] = point_size.value vis["pointShape"] = point_shape.value vis["width"] = line_width.value vis["lineType"] = line_type.value vis["fillColor"] = fill_color.value[1:] + str( hex(int(fill_color_opacity.value * 255)) )[2:].zfill(2) return vis def import_btn_clicked(b): vis = get_vis_params() create_code_cell(f"vis_params = {str(vis)}") def apply_btn_clicked(b): compute_label.value = "Computing ..." if new_layer_name.value in self.ee_layer_names: old_layer = new_layer_name.value if "legend" in self.ee_layer_dict[old_layer].keys(): legend = self.ee_layer_dict[old_layer]["legend"] if legend in self.controls: self.remove_control(legend) legend.close() if "colorbar" in self.ee_layer_dict[old_layer].keys(): colorbar = self.ee_layer_dict[old_layer]["colorbar"] if colorbar in self.controls: self.remove_control(colorbar) colorbar.close() if not style_chk.value: vis = get_vis_params() self.addLayer(ee_object.style(**vis), {}, new_layer_name.value) ee_layer.visible = False elif ( style_chk.value and len(palette.value) > 0 and "," in palette.value ): colors = ee.List( [ color.strip() + str(hex(int(fill_color_opacity.value * 255)))[2:].zfill(2) for color in palette.value.split(",") ] ) arr = ee_object.aggregate_array(field.value).distinct().sort() fc = ee_object.map( lambda f: f.set({"styleIndex": arr.indexOf(f.get(field.value))}) ) step = arr.size().divide(colors.size()).ceil() fc = fc.map( lambda f: f.set( { "style": { "color": color.value[1:] + str(hex(int(color_opacity.value * 255)))[ 2: ].zfill(2), "pointSize": point_size.value, "pointShape": point_shape.value, "width": line_width.value, "lineType": line_type.value, "fillColor": colors.get( ee.Number( ee.Number(f.get("styleIndex")).divide(step) ).floor() ), } } ) ) self.addLayer( fc.style(**{"styleProperty": "style"}), {}, f"{new_layer_name.value}", ) if ( len(palette.value) and legend_chk.value and len(legend_labels.value) > 0 ): legend_colors = [ color.strip() for color in palette.value.split(",") ] legend_keys = [ label.strip() for label in legend_labels.value.split(",") ] self.add_legend( title=legend_title.value, legend_keys=legend_keys, legend_colors=legend_colors, layer_name=new_layer_name.value, ) ee_layer.visible = False compute_label.value = "" def close_btn_clicked(b): self.remove_control(self.vis_control) self.vis_control.close() self.vis_widget.close() if ( self.colorbar_ctrl is not None and self.colorbar_ctrl in self.controls ): self.remove_control(self.colorbar_ctrl) self.colorbar_ctrl.close() self.colorbar_widget.close() import_btn.on_click(import_btn_clicked) apply_btn.on_click(apply_btn_clicked) close_btn.on_click(close_btn_clicked) vis_widget.children = [ label, new_layer_name, widgets.HBox([color, color_opacity, color_opacity_label]), widgets.HBox([point_size, point_shape]), widgets.HBox([line_width, line_type]), widgets.HBox( [fill_color, fill_color_opacity, fill_color_opacity_label] ), style_vbox, widgets.HBox([import_btn, apply_btn, close_btn]), ] if geometry_type(ee_object) in ["Point", "MultiPoint"]: point_size.disabled = False point_shape.disabled = False else: point_size.disabled = True point_shape.disabled = True return vis_widget
[docs] def add_styled_vector( self, ee_object, column, palette, layer_name="Untitled", **kwargs ): """Adds a styled vector to the map. Args: ee_object (object): An ee.FeatureCollection. column (str): The column name to use for styling. palette (list | dict): The palette (e.g., list of colors or a dict containing label and color pairs) to use for styling. layer_name (str, optional): The name to be used for the new layer. Defaults to "Untitled". """ styled_vector = vector_styling(ee_object, column, palette, **kwargs) self.addLayer(styled_vector.style(**{"styleProperty": "style"}), {}, layer_name)
[docs] def add_shp( self, in_shp, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", encoding="utf-8", ): """Adds a shapefile to the map. Args: in_shp (str): The input file path to the shapefile. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". encoding (str, optional): The encoding of the shapefile. Defaults to "utf-8". Raises: FileNotFoundError: The provided shapefile could not be found. """ in_shp = os.path.abspath(in_shp) if not os.path.exists(in_shp): raise FileNotFoundError("The provided shapefile could not be found.") geojson = shp_to_geojson(in_shp) self.add_geojson( geojson, layer_name, style, hover_style, style_callback, fill_colors, info_mode, encoding, )
add_shapefile = add_shp
[docs] def add_geojson( self, in_geojson, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", encoding="utf-8", ): """Adds a GeoJSON file to the map. Args: in_geojson (str | dict): The file path or http URL to the input GeoJSON or a dictionary containing the geojson. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". encoding (str, optional): The encoding of the GeoJSON file. Defaults to "utf-8". Raises: FileNotFoundError: The provided GeoJSON file could not be found. """ import json import random import requests import warnings warnings.filterwarnings("ignore") style_callback_only = False if len(style) == 0 and style_callback is not None: style_callback_only = True try: if isinstance(in_geojson, str): if in_geojson.startswith("http"): in_geojson = github_raw_url(in_geojson) data = requests.get(in_geojson).json() else: in_geojson = os.path.abspath(in_geojson) if not os.path.exists(in_geojson): raise FileNotFoundError( "The provided GeoJSON file could not be found." ) with open(in_geojson, encoding=encoding) as f: data = json.load(f) elif isinstance(in_geojson, dict): data = in_geojson else: raise TypeError("The input geojson must be a type of str or dict.") except Exception as e: raise Exception(e) if not style: style = { # "stroke": True, "color": "#000000", "weight": 1, "opacity": 1, # "fill": True, # "fillColor": "#ffffff", "fillOpacity": 0.1, # "dashArray": "9" # "clickable": True, } elif "weight" not in style: style["weight"] = 1 if not hover_style: hover_style = {"weight": style["weight"] + 1, "fillOpacity": 0.5} def random_color(feature): return { "color": "black", "fillColor": random.choice(fill_colors), } toolbar_button = widgets.ToggleButton( value=True, tooltip="Toolbar", icon="info", layout=widgets.Layout( width="28px", height="28px", padding="0px 0px 0px 4px" ), ) close_button = widgets.ToggleButton( value=False, tooltip="Close the tool", icon="times", # button_style="primary", layout=widgets.Layout( height="28px", width="28px", padding="0px 0px 0px 4px" ), ) html = widgets.HTML() html.layout.margin = "0px 10px 0px 10px" html.layout.max_height = "250px" html.layout.max_width = "250px" output_widget = widgets.VBox( [widgets.HBox([toolbar_button, close_button]), html] ) info_control = ipyleaflet.WidgetControl( widget=output_widget, position="bottomright" ) if info_mode in ["on_hover", "on_click"]: self.add_control(info_control) def toolbar_btn_click(change): if change["new"]: close_button.value = False output_widget.children = [ widgets.VBox([widgets.HBox([toolbar_button, close_button]), html]) ] else: output_widget.children = [widgets.HBox([toolbar_button, close_button])] toolbar_button.observe(toolbar_btn_click, "value") def close_btn_click(change): if change["new"]: toolbar_button.value = False if info_control in self.controls: self.remove_control(info_control) output_widget.close() close_button.observe(close_btn_click, "value") def update_html(feature, **kwargs): value = [ "<b>{}: </b>{}<br>".format(prop, feature["properties"][prop]) for prop in feature["properties"].keys() ][:-1] value = """{}""".format("".join(value)) html.value = value if style_callback is None: style_callback = random_color if style_callback_only: geojson = ipyleaflet.GeoJSON( data=data, hover_style=hover_style, style_callback=style_callback, name=layer_name, ) else: geojson = ipyleaflet.GeoJSON( data=data, style=style, hover_style=hover_style, style_callback=style_callback, name=layer_name, ) if info_mode == "on_hover": geojson.on_hover(update_html) elif info_mode == "on_click": geojson.on_click(update_html) self.add_layer(geojson) self.geojson_layers.append(geojson) if not hasattr(self, "json_layer_dict"): self.json_layer_dict = {} params = { "data": geojson, "style": style, "hover_style": hover_style, "style_callback": style_callback, } self.json_layer_dict[layer_name] = params
[docs] def add_kml( self, in_kml, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", ): """Adds a GeoJSON file to the map. Args: in_kml (str): The input file path to the KML. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". Raises: FileNotFoundError: The provided KML file could not be found. """ if isinstance(in_kml, str) and in_kml.startswith("http"): in_kml = github_raw_url(in_kml) in_kml = download_file(in_kml) in_kml = os.path.abspath(in_kml) if not os.path.exists(in_kml): raise FileNotFoundError("The provided KML file could not be found.") self.add_vector( in_kml, layer_name, style=style, hover_style=hover_style, style_callback=style_callback, fill_colors=fill_colors, info_mode=info_mode, )
[docs] def add_vector( self, filename, layer_name="Untitled", to_ee=False, bbox=None, mask=None, rows=None, style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", encoding="utf-8", **kwargs, ): """Adds any geopandas-supported vector dataset to the map. Args: filename (str): Either the absolute or relative path to the file or URL to be opened, or any object with a read() method (such as an open file or StringIO). layer_name (str, optional): The layer name to use. Defaults to "Untitled". to_ee (bool, optional): Whether to convert the GeoJSON to ee.FeatureCollection. Defaults to False. bbox (tuple | GeoDataFrame or GeoSeries | shapely Geometry, optional): Filter features by given bounding box, GeoSeries, GeoDataFrame or a shapely geometry. CRS mis-matches are resolved if given a GeoSeries or GeoDataFrame. Cannot be used with mask. Defaults to None. mask (dict | GeoDataFrame or GeoSeries | shapely Geometry, optional): Filter for features that intersect with the given dict-like geojson geometry, GeoSeries, GeoDataFrame or shapely geometry. CRS mis-matches are resolved if given a GeoSeries or GeoDataFrame. Cannot be used with bbox. Defaults to None. rows (int or slice, optional): Load in specific rows by passing an integer (first n rows) or a slice() object.. Defaults to None. style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". encoding (str, optional): The encoding to use to read the file. Defaults to "utf-8". """ if not filename.startswith("http"): filename = os.path.abspath(filename) else: filename = github_raw_url(filename) if to_ee: fc = vector_to_ee( filename, bbox=bbox, mask=mask, rows=rows, geodesic=True, **kwargs, ) self.addLayer(fc, {}, layer_name) else: ext = os.path.splitext(filename)[1].lower() if ext == ".shp": self.add_shapefile( filename, layer_name, style, hover_style, style_callback, fill_colors, info_mode, encoding, ) elif ext in [".json", ".geojson"]: self.add_geojson( filename, layer_name, style, hover_style, style_callback, fill_colors, info_mode, encoding, ) else: geojson = vector_to_geojson( filename, bbox=bbox, mask=mask, rows=rows, epsg="4326", **kwargs, ) self.add_geojson( geojson, layer_name, style, hover_style, style_callback, fill_colors, info_mode, encoding, )
[docs] def add_osm( self, query, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", which_result=None, by_osmid=False, buffer_dist=None, to_ee=False, geodesic=True, ): """Adds OSM data to the map. Args: query (str | dict | list): Query string(s) or structured dict(s) to geocode. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". which_result (INT, optional): Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None. by_osmid (bool, optional): If True, handle query as an OSM ID for lookup rather than text search. Defaults to False. buffer_dist (float, optional): Distance to buffer around the place geometry, in meters. Defaults to None. to_ee (bool, optional): Whether to convert the csv to an ee.FeatureCollection. geodesic (bool, optional): Whether line segments should be interpreted as spherical geodesics. If false, indicates that line segments should be interpreted as planar lines in the specified CRS. If absent, defaults to true if the CRS is geographic (including the default EPSG:4326), or to false if the CRS is projected. """ gdf = osm_to_gdf( query, which_result=which_result, by_osmid=by_osmid, buffer_dist=buffer_dist ) geojson = gdf.__geo_interface__ if to_ee: fc = geojson_to_ee(geojson, geodesic=geodesic) self.addLayer(fc, {}, layer_name) self.zoomToObject(fc) else: self.add_geojson( geojson, layer_name=layer_name, style=style, hover_style=hover_style, style_callback=style_callback, fill_colors=fill_colors, info_mode=info_mode, ) bounds = gdf.bounds.iloc[0] self.fit_bounds([[bounds[1], bounds[0]], [bounds[3], bounds[2]]])
[docs] def add_osm_from_geocode( self, query, which_result=None, by_osmid=False, buffer_dist=None, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", ): """Adds OSM data of place(s) by name or ID to the map. Args: query (str | dict | list): Query string(s) or structured dict(s) to geocode. which_result (int, optional): Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None. by_osmid (bool, optional): If True, handle query as an OSM ID for lookup rather than text search. Defaults to False. buffer_dist (float, optional): Distance to buffer around the place geometry, in meters. Defaults to None. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". """ gdf = osm_gdf_from_geocode( query, which_result=which_result, by_osmid=by_osmid, buffer_dist=buffer_dist ) geojson = gdf.__geo_interface__ self.add_geojson( geojson, layer_name=layer_name, style=style, hover_style=hover_style, style_callback=style_callback, fill_colors=fill_colors, info_mode=info_mode, ) self.zoom_to_gdf(gdf)
[docs] def add_osm_from_address( self, address, tags, dist=1000, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", ): """Adds OSM entities within some distance N, S, E, W of address to the map. Args: address (str): The address to geocode and use as the central point around which to get the geometries. tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop. dist (int, optional): Distance in meters. Defaults to 1000. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". """ gdf = osm_gdf_from_address(address, tags, dist) geojson = gdf.__geo_interface__ self.add_geojson( geojson, layer_name=layer_name, style=style, hover_style=hover_style, style_callback=style_callback, fill_colors=fill_colors, info_mode=info_mode, ) self.zoom_to_gdf(gdf)
[docs] def add_osm_from_place( self, query, tags, which_result=None, buffer_dist=None, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", ): """Adds OSM entities within boundaries of geocodable place(s) to the map. Args: query (str | dict | list): Query string(s) or structured dict(s) to geocode. tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop. which_result (int, optional): Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None. buffer_dist (float, optional): Distance to buffer around the place geometry, in meters. Defaults to None. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". """ gdf = osm_gdf_from_place(query, tags, which_result, buffer_dist) geojson = gdf.__geo_interface__ self.add_geojson( geojson, layer_name=layer_name, style=style, hover_style=hover_style, style_callback=style_callback, fill_colors=fill_colors, info_mode=info_mode, ) self.zoom_to_gdf(gdf)
[docs] def add_osm_from_point( self, center_point, tags, dist=1000, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", ): """Adds OSM entities within some distance N, S, E, W of a point to the map. Args: center_point (tuple): The (lat, lng) center point around which to get the geometries. tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop. dist (int, optional): Distance in meters. Defaults to 1000. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". """ gdf = osm_gdf_from_point(center_point, tags, dist) geojson = gdf.__geo_interface__ self.add_geojson( geojson, layer_name=layer_name, style=style, hover_style=hover_style, style_callback=style_callback, fill_colors=fill_colors, info_mode=info_mode, ) self.zoom_to_gdf(gdf)
[docs] def add_osm_from_polygon( self, polygon, tags, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", ): """Adds OSM entities within boundaries of a (multi)polygon to the map. Args: polygon (shapely.geometry.Polygon | shapely.geometry.MultiPolygon): Geographic boundaries to fetch geometries within tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". """ gdf = osm_gdf_from_polygon(polygon, tags) geojson = gdf.__geo_interface__ self.add_geojson( geojson, layer_name=layer_name, style=style, hover_style=hover_style, style_callback=style_callback, fill_colors=fill_colors, info_mode=info_mode, ) self.zoom_to_gdf(gdf)
[docs] def add_osm_from_bbox( self, north, south, east, west, tags, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", ): """Adds OSM entities within a N, S, E, W bounding box to the map. Args: north (float): Northern latitude of bounding box. south (float): Southern latitude of bounding box. east (float): Eastern longitude of bounding box. west (float): Western longitude of bounding box. tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". """ gdf = osm_gdf_from_bbox(north, south, east, west, tags) geojson = gdf.__geo_interface__ self.add_geojson( geojson, layer_name=layer_name, style=style, hover_style=hover_style, style_callback=style_callback, fill_colors=fill_colors, info_mode=info_mode, ) self.zoom_to_gdf(gdf)
[docs] def add_osm_from_view( self, tags, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", ): """Adds OSM entities within the current map view to the map. Args: tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". """ bounds = self.bounds if len(bounds) == 0: bounds = ( (40.74824858675827, -73.98933637940563), (40.75068694343106, -73.98364473187601), ) north, south, east, west = ( bounds[1][0], bounds[0][0], bounds[1][1], bounds[0][1], ) gdf = osm_gdf_from_bbox(north, south, east, west, tags) geojson = gdf.__geo_interface__ self.add_geojson( geojson, layer_name=layer_name, style=style, hover_style=hover_style, style_callback=style_callback, fill_colors=fill_colors, info_mode=info_mode, ) self.zoom_to_gdf(gdf)
[docs] def add_gdf( self, gdf, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", zoom_to_layer=True, encoding="utf-8", ): """Adds a GeoDataFrame to the map. Args: gdf (GeoDataFrame): A GeoPandas GeoDataFrame. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". zoom_to_layer (bool, optional): Whether to zoom to the layer. encoding (str, optional): The encoding of the GeoDataFrame. Defaults to "utf-8". """ data = gdf_to_geojson(gdf, epsg="4326") self.add_geojson( data, layer_name, style, hover_style, style_callback, fill_colors, info_mode, encoding, ) if zoom_to_layer: import numpy as np bounds = gdf.to_crs(epsg="4326").bounds west = np.min(bounds["minx"]) south = np.min(bounds["miny"]) east = np.max(bounds["maxx"]) north = np.max(bounds["maxy"]) self.fit_bounds([[south, east], [north, west]])
[docs] def add_gdf_from_postgis( self, sql, con, layer_name="Untitled", style={}, hover_style={}, style_callback=None, fill_colors=["black"], info_mode="on_hover", zoom_to_layer=True, **kwargs, ): """Reads a PostGIS database and returns data as a GeoDataFrame to be added to the map. Args: sql (str): SQL query to execute in selecting entries from database, or name of the table to read from the database. con (sqlalchemy.engine.Engine): Active connection to the database to query. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to {}. hover_style (dict, optional): Hover style dictionary. Defaults to {}. style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. fill_colors (list, optional): The random colors to use for filling polygons. Defaults to ["black"]. info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". zoom_to_layer (bool, optional): Whether to zoom to the layer. """ gdf = read_postgis(sql, con, **kwargs) gdf = gdf.to_crs("epsg:4326") self.add_gdf( gdf, layer_name, style, hover_style, style_callback, fill_colors, info_mode, zoom_to_layer, )
[docs] def add_time_slider( self, ee_object, vis_params={}, region=None, layer_name="Time series", labels=None, time_interval=1, position="bottomright", slider_length="150px", date_format="YYYY-MM-dd", opacity=1.0, **kwargs, ): """Adds a time slider to the map. Args: ee_object (ee.Image | ee.ImageCollection): The Image or ImageCollection to visualize. vis_params (dict, optional): Visualization parameters to use for visualizing image. Defaults to {}. region (ee.Geometry | ee.FeatureCollection): The region to visualize. layer_name (str, optional): The layer name to be used. Defaults to "Time series". labels (list, optional): The list of labels to be used for the time series. Defaults to None. time_interval (int, optional): Time interval in seconds. Defaults to 1. position (str, optional): Position to place the time slider, can be any of ['topleft', 'topright', 'bottomleft', 'bottomright']. Defaults to "bottomright". slider_length (str, optional): Length of the time slider. Defaults to "150px". date_format (str, optional): The date format to use. Defaults to 'YYYY-MM-dd'. opacity (float, optional): The opacity of layers. Defaults to 1.0. Raises: TypeError: If the ee_object is not ee.Image | ee.ImageCollection. """ import threading if isinstance(ee_object, ee.Image): if region is not None: if isinstance(region, ee.Geometry): ee_object = ee_object.clip(region) elif isinstance(region, ee.FeatureCollection): ee_object = ee_object.clipToCollection(region) if layer_name not in self.ee_raster_layer_names: self.addLayer(ee_object, {}, layer_name, False, opacity) band_names = ee_object.bandNames() ee_object = ee.ImageCollection( ee_object.bandNames().map(lambda b: ee_object.select([b])) ) if labels is not None: if len(labels) != int(ee_object.size().getInfo()): raise ValueError( "The length of labels must be equal to the number of bands in the image." ) else: labels = band_names.getInfo() elif isinstance(ee_object, ee.ImageCollection): if region is not None: if isinstance(region, ee.Geometry): ee_object = ee_object.map(lambda img: img.clip(region)) elif isinstance(region, ee.FeatureCollection): ee_object = ee_object.map(lambda img: img.clipToCollection(region)) if labels is not None: if len(labels) != int(ee_object.size().getInfo()): raise ValueError( "The length of labels must be equal to the number of images in the ImageCollection." ) else: labels = ( ee_object.aggregate_array("system:time_start") .map(lambda d: ee.Date(d).format(date_format)) .getInfo() ) else: raise TypeError("The ee_object must be an ee.Image or ee.ImageCollection") # if labels is not None: # size = len(labels) # else: # size = ee_object.size().getInfo() # labels = [str(i) for i in range(1, size + 1)] first = ee.Image(ee_object.first()) if layer_name not in self.ee_raster_layer_names: self.addLayer(ee_object.toBands(), {}, layer_name, False, opacity) self.addLayer(first, vis_params, "Image X", True, opacity) slider = widgets.IntSlider( min=1, max=len(labels), readout=False, continuous_update=False, layout=widgets.Layout(width=slider_length), ) label = widgets.Label( value=labels[0], layout=widgets.Layout(padding="0px 5px 0px 5px") ) play_btn = widgets.Button( icon="play", tooltip="Play the time slider", button_style="primary", layout=widgets.Layout(width="32px"), ) pause_btn = widgets.Button( icon="pause", tooltip="Pause the time slider", button_style="primary", layout=widgets.Layout(width="32px"), ) close_btn = widgets.Button( icon="times", tooltip="Close the time slider", button_style="primary", layout=widgets.Layout(width="32px"), ) play_chk = widgets.Checkbox(value=False) slider_widget = widgets.HBox([slider, label, play_btn, pause_btn, close_btn]) def play_click(b): play_chk.value = True def work(slider): while play_chk.value: if slider.value < len(labels): slider.value += 1 else: slider.value = 1 time.sleep(time_interval) thread = threading.Thread(target=work, args=(slider,)) thread.start() def pause_click(b): play_chk.value = False play_btn.on_click(play_click) pause_btn.on_click(pause_click) def slider_changed(change): self.default_style = {"cursor": "wait"} index = slider.value - 1 label.value = labels[index] image = ee.Image(ee_object.toList(ee_object.size()).get(index)) if layer_name not in self.ee_raster_layer_names: self.addLayer(ee_object.toBands(), {}, layer_name, False, opacity) self.addLayer(image, vis_params, "Image X", True, opacity) self.default_style = {"cursor": "default"} slider.observe(slider_changed, "value") def close_click(b): play_chk.value = False self.toolbar_reset() self.remove_ee_layer("Image X") self.remove_ee_layer(layer_name) if self.slider_ctrl is not None and self.slider_ctrl in self.controls: self.remove_control(self.slider_ctrl) slider_widget.close() close_btn.on_click(close_click) slider_ctrl = ipyleaflet.WidgetControl(widget=slider_widget, position=position) self.add_control(slider_ctrl) self.slider_ctrl = slider_ctrl
[docs] def add_xy_data( self, in_csv, x="longitude", y="latitude", label=None, layer_name="Marker cluster", to_ee=False, ): """Adds points from a CSV file containing lat/lon information and display data on the map. Args: in_csv (str): The file path to the input CSV file. x (str, optional): The name of the column containing longitude coordinates. Defaults to "longitude". y (str, optional): The name of the column containing latitude coordinates. Defaults to "latitude". label (str, optional): The name of the column containing label information to used for marker popup. Defaults to None. layer_name (str, optional): The layer name to use. Defaults to "Marker cluster". to_ee (bool, optional): Whether to convert the csv to an ee.FeatureCollection. Raises: FileNotFoundError: The specified input csv does not exist. ValueError: The specified x column does not exist. ValueError: The specified y column does not exist. ValueError: The specified label column does not exist. """ import pandas as pd if not in_csv.startswith("http") and (not os.path.exists(in_csv)): raise FileNotFoundError("The specified input csv does not exist.") df = pd.read_csv(in_csv) col_names = df.columns.values.tolist() if x not in col_names: raise ValueError(f"x must be one of the following: {', '.join(col_names)}") if y not in col_names: raise ValueError(f"y must be one of the following: {', '.join(col_names)}") if label is not None and (label not in col_names): raise ValueError( f"label must be one of the following: {', '.join(col_names)}" ) self.default_style = {"cursor": "wait"} if to_ee: fc = csv_to_ee(in_csv, latitude=y, longitude=x) self.addLayer(fc, {}, layer_name) else: points = list(zip(df[y], df[x])) if label is not None: labels = df[label] markers = [ ipyleaflet.Marker( location=point, draggable=False, popup=widgets.HTML(str(labels[index])), ) for index, point in enumerate(points) ] else: markers = [ ipyleaflet.Marker(location=point, draggable=False) for point in points ] marker_cluster = ipyleaflet.MarkerCluster(markers=markers, name=layer_name) self.add_layer(marker_cluster) self.default_style = {"cursor": "default"}
[docs] def add_points_from_xy( self, data, x="longitude", y="latitude", popup=None, layer_name="Marker Cluster", color_column=None, marker_colors=None, icon_colors=["white"], icon_names=["info"], spin=False, add_legend=True, **kwargs, ): """Adds a marker cluster to the map. Args: data (str | pd.DataFrame): A csv or Pandas DataFrame containing x, y, z values. x (str, optional): The column name for the x values. Defaults to "longitude". y (str, optional): The column name for the y values. Defaults to "latitude". popup (list, optional): A list of column names to be used as the popup. Defaults to None. layer_name (str, optional): The name of the layer. Defaults to "Marker Cluster". color_column (str, optional): The column name for the color values. Defaults to None. marker_colors (list, optional): A list of colors to be used for the markers. Defaults to None. icon_colors (list, optional): A list of colors to be used for the icons. Defaults to ['white']. icon_names (list, optional): A list of names to be used for the icons. More icons can be found at https://fontawesome.com/v4/icons. Defaults to ['info']. spin (bool, optional): If True, the icon will spin. Defaults to False. add_legend (bool, optional): If True, a legend will be added to the map. Defaults to True. """ import pandas as pd data = github_raw_url(data) color_options = [ "red", "blue", "green", "purple", "orange", "darkred", "lightred", "beige", "darkblue", "darkgreen", "cadetblue", "darkpurple", "white", "pink", "lightblue", "lightgreen", "gray", "black", "lightgray", ] if isinstance(data, pd.DataFrame): df = data elif not data.startswith("http") and (not os.path.exists(data)): raise FileNotFoundError("The specified input csv does not exist.") else: df = pd.read_csv(data) df = points_from_xy(df, x, y) col_names = df.columns.values.tolist() if color_column is not None and color_column not in col_names: raise ValueError( f"The color column {color_column} does not exist in the dataframe." ) if color_column is not None: items = list(set(df[color_column])) else: items = None if color_column is not None and marker_colors is None: if len(items) > len(color_options): raise ValueError( f"The number of unique values in the color column {color_column} is greater than the number of available colors." ) else: marker_colors = color_options[: len(items)] elif color_column is not None and marker_colors is not None: if len(items) != len(marker_colors): raise ValueError( f"The number of unique values in the color column {color_column} is not equal to the number of available colors." ) if items is not None: if len(icon_colors) == 1: icon_colors = icon_colors * len(items) elif len(items) != len(icon_colors): raise ValueError( f"The number of unique values in the color column {color_column} is not equal to the number of available colors." ) if len(icon_names) == 1: icon_names = icon_names * len(items) elif len(items) != len(icon_names): raise ValueError( f"The number of unique values in the color column {color_column} is not equal to the number of available colors." ) if "geometry" in col_names: col_names.remove("geometry") if popup is not None: if isinstance(popup, str) and (popup not in col_names): raise ValueError( f"popup must be one of the following: {', '.join(col_names)}" ) elif isinstance(popup, list) and ( not all(item in col_names for item in popup) ): raise ValueError( f"All popup items must be select from: {', '.join(col_names)}" ) else: popup = col_names df["x"] = df.geometry.x df["y"] = df.geometry.y points = list(zip(df["y"], df["x"])) if popup is not None: if isinstance(popup, str): labels = df[popup] markers = [] for index, point in enumerate(points): if items is not None: marker_color = marker_colors[ items.index(df[color_column][index]) ] icon_name = icon_names[items.index(df[color_column][index])] icon_color = icon_colors[items.index(df[color_column][index])] marker_icon = ipyleaflet.AwesomeIcon( name=icon_name, marker_color=marker_color, icon_color=icon_color, spin=spin, ) else: marker_icon = None marker = ipyleaflet.Marker( location=point, draggable=False, popup=widgets.HTML(str(labels[index])), icon=marker_icon, ) markers.append(marker) elif isinstance(popup, list): labels = [] for i in range(len(points)): label = "" for item in popup: label = ( label + "<b>" + str(item) + "</b>" + ": " + str(df[item][i]) + "<br>" ) labels.append(label) df["popup"] = labels markers = [] for index, point in enumerate(points): if items is not None: marker_color = marker_colors[ items.index(df[color_column][index]) ] icon_name = icon_names[items.index(df[color_column][index])] icon_color = icon_colors[items.index(df[color_column][index])] marker_icon = ipyleaflet.AwesomeIcon( name=icon_name, marker_color=marker_color, icon_color=icon_color, spin=spin, ) else: marker_icon = None marker = ipyleaflet.Marker( location=point, draggable=False, popup=widgets.HTML(labels[index]), icon=marker_icon, ) markers.append(marker) else: markers = [] for point in points: if items is not None: marker_color = marker_colors[items.index(df[color_column][index])] icon_name = icon_names[items.index(df[color_column][index])] icon_color = icon_colors[items.index(df[color_column][index])] marker_icon = ipyleaflet.AwesomeIcon( name=icon_name, marker_color=marker_color, icon_color=icon_color, spin=spin, ) else: marker_icon = None marker = ipyleaflet.Marker( location=point, draggable=False, icon=marker_icon ) markers.append(marker) marker_cluster = ipyleaflet.MarkerCluster(markers=markers, name=layer_name) self.add_layer(marker_cluster) if items is not None and add_legend: marker_colors = [check_color(c) for c in marker_colors] self.add_legend( title=color_column.title(), colors=marker_colors, labels=items ) self.default_style = {"cursor": "default"}
[docs] def add_circle_markers_from_xy( self, data, x="longitude", y="latitude", radius=10, popup=None, **kwargs, ): """Adds a marker cluster to the map. For a list of options, see https://ipyleaflet.readthedocs.io/en/latest/api_reference/circle_marker.html Args: data (str | pd.DataFrame): A csv or Pandas DataFrame containing x, y, z values. x (str, optional): The column name for the x values. Defaults to "longitude". y (str, optional): The column name for the y values. Defaults to "latitude". radius (int, optional): The radius of the circle. Defaults to 10. popup (list, optional): A list of column names to be used as the popup. Defaults to None. """ import pandas as pd data = github_raw_url(data) if isinstance(data, pd.DataFrame): df = data elif not data.startswith("http") and (not os.path.exists(data)): raise FileNotFoundError("The specified input csv does not exist.") else: df = pd.read_csv(data) col_names = df.columns.values.tolist() if popup is None: popup = col_names if not isinstance(popup, list): popup = [popup] if x not in col_names: raise ValueError(f"x must be one of the following: {', '.join(col_names)}") if y not in col_names: raise ValueError(f"y must be one of the following: {', '.join(col_names)}") for row in df.itertuples(): html = "" for p in popup: html = html + "<b>" + p + "</b>" + ": " + str(getattr(row, p)) + "<br>" popup_html = widgets.HTML(html) marker = ipyleaflet.CircleMarker( location=[getattr(row, y), getattr(row, x)], radius=radius, popup=popup_html, **kwargs, ) super().add_layer(marker)
[docs] def add_planet_by_month( self, year=2016, month=1, name=None, api_key=None, token_name="PLANET_API_KEY" ): """Adds a Planet global mosaic by month to the map. To get a Planet API key, see https://developers.planet.com/quickstart/apis Args: year (int, optional): The year of Planet global mosaic, must be >=2016. Defaults to 2016. month (int, optional): The month of Planet global mosaic, must be 1-12. Defaults to 1. name (str, optional): The layer name to use. Defaults to None. api_key (str, optional): The Planet API key. Defaults to None. token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY". """ layer = planet_tile_by_month(year, month, name, api_key, token_name) self.add_layer(layer)
[docs] def add_planet_by_quarter( self, year=2016, quarter=1, name=None, api_key=None, token_name="PLANET_API_KEY" ): """Adds a Planet global mosaic by quarter to the map. To get a Planet API key, see https://developers.planet.com/quickstart/apis Args: year (int, optional): The year of Planet global mosaic, must be >=2016. Defaults to 2016. quarter (int, optional): The quarter of Planet global mosaic, must be 1-12. Defaults to 1. name (str, optional): The layer name to use. Defaults to None. api_key (str, optional): The Planet API key. Defaults to None. token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY". """ layer = planet_tile_by_quarter(year, quarter, name, api_key, token_name) self.add_layer(layer)
[docs] def to_streamlit(self, width=None, height=600, scrolling=False, **kwargs): """Renders map figure in a Streamlit app. Args: width (int, optional): Width of the map. Defaults to None. height (int, optional): Height of the map. Defaults to 600. responsive (bool, optional): Whether to make the map responsive. Defaults to True. scrolling (bool, optional): If True, show a scrollbar when the content is larger than the iframe. Otherwise, do not show a scrollbar. Defaults to False. Returns: streamlit.components: components.html object. """ try: import streamlit.components.v1 as components # if responsive: # make_map_responsive = """ # <style> # [title~="st.iframe"] { width: 100%} # </style> # """ # st.markdown(make_map_responsive, unsafe_allow_html=True) return components.html( self.to_html(), width=width, height=height, scrolling=scrolling ) except Exception as e: raise Exception(e)
[docs] def add_point_layer( self, filename, popup=None, layer_name="Marker Cluster", **kwargs ): """Adds a point layer to the map with a popup attribute. Args: filename (str): str, http url, path object or file-like object. Either the absolute or relative path to the file or URL to be opened, or any object with a read() method (such as an open file or StringIO) popup (str | list, optional): Column name(s) to be used for popup. Defaults to None. layer_name (str, optional): A layer name to use. Defaults to "Marker Cluster". Raises: ValueError: If the specified column name does not exist. ValueError: If the specified column names do not exist. """ import warnings warnings.filterwarnings("ignore") check_package(name="geopandas", URL="https://geopandas.org") import geopandas as gpd self.default_style = {"cursor": "wait"} if not filename.startswith("http"): filename = os.path.abspath(filename) ext = os.path.splitext(filename)[1].lower() if ext == ".kml": gpd.io.file.fiona.drvsupport.supported_drivers["KML"] = "rw" gdf = gpd.read_file(filename, driver="KML", **kwargs) else: gdf = gpd.read_file(filename, **kwargs) df = gdf.to_crs(epsg="4326") col_names = df.columns.values.tolist() if popup is not None: if isinstance(popup, str) and (popup not in col_names): raise ValueError( f"popup must be one of the following: {', '.join(col_names)}" ) elif isinstance(popup, list) and ( not all(item in col_names for item in popup) ): raise ValueError( f"All popup items must be select from: {', '.join(col_names)}" ) df["x"] = df.geometry.x df["y"] = df.geometry.y points = list(zip(df["y"], df["x"])) if popup is not None: if isinstance(popup, str): labels = df[popup] markers = [ ipyleaflet.Marker( location=point, draggable=False, popup=widgets.HTML(str(labels[index])), ) for index, point in enumerate(points) ] elif isinstance(popup, list): labels = [] for i in range(len(points)): label = "" for item in popup: label = label + str(item) + ": " + str(df[item][i]) + "<br>" labels.append(label) df["popup"] = labels markers = [ ipyleaflet.Marker( location=point, draggable=False, popup=widgets.HTML(labels[index]), ) for index, point in enumerate(points) ] else: markers = [ ipyleaflet.Marker(location=point, draggable=False) for point in points ] marker_cluster = ipyleaflet.MarkerCluster(markers=markers, name=layer_name) self.add_layer(marker_cluster) self.default_style = {"cursor": "default"}
[docs] def add_census_data(self, wms, layer, census_dict=None, **kwargs): """Adds a census data layer to the map. Args: wms (str): The wms to use. For example, "Current", "ACS 2021", "Census 2020". See the complete list at https://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_wms.html layer (str): The layer name to add to the map. census_dict (dict, optional): A dictionary containing census data. Defaults to None. It can be obtained from the get_census_dict() function. """ try: if census_dict is None: census_dict = get_census_dict() if wms not in census_dict.keys(): raise ValueError( f"The provided WMS is invalid. It must be one of {census_dict.keys()}" ) layers = census_dict[wms]["layers"] if layer not in layers: raise ValueError( f"The layer name is not valid. It must be one of {layers}" ) url = census_dict[wms]["url"] if "name" not in kwargs: kwargs["name"] = layer if "attribution" not in kwargs: kwargs["attribution"] = "U.S. Census Bureau" if "format" not in kwargs: kwargs["format"] = "image/png" if "transparent" not in kwargs: kwargs["transparent"] = True self.add_wms_layer(url, layer, **kwargs) except Exception as e: raise Exception(e)
[docs] def add_xyz_service(self, provider, **kwargs): """Add a XYZ tile layer to the map. Args: provider (str): A tile layer name starts with xyz or qms. For example, xyz.OpenTopoMap, Raises: ValueError: The provider is not valid. It must start with xyz or qms. """ import xyzservices.providers as xyz from xyzservices import TileProvider if provider.startswith("xyz"): name = provider[4:] xyz_provider = xyz.flatten()[name] url = xyz_provider.build_url() attribution = xyz_provider.attribution if attribution.strip() == "": attribution = " " self.add_tile_layer(url, name, attribution) elif provider.startswith("qms"): name = provider[4:] qms_provider = TileProvider.from_qms(name) url = qms_provider.build_url() attribution = qms_provider.attribution if attribution.strip() == "": attribution = " " self.add_tile_layer(url, name, attribution) else: raise ValueError( f"The provider {provider} is not valid. It must start with xyz or qms." )
[docs] def add_heatmap( self, data, latitude="latitude", longitude="longitude", value="value", name="Heat map", radius=25, **kwargs, ): """Adds a heat map to the map. Reference: https://ipyleaflet.readthedocs.io/en/latest/api_reference/heatmap.html Args: data (str | list | pd.DataFrame): File path or HTTP URL to the input file or a list of data points in the format of [[x1, y1, z1], [x2, y2, z2]]. For example, https://raw.githubusercontent.com/giswqs/leafmap/master/examples/data/world_cities.csv latitude (str, optional): The column name of latitude. Defaults to "latitude". longitude (str, optional): The column name of longitude. Defaults to "longitude". value (str, optional): The column name of values. Defaults to "value". name (str, optional): Layer name to use. Defaults to "Heat map". radius (int, optional): Radius of each “point” of the heatmap. Defaults to 25. Raises: ValueError: If data is not a list. """ import pandas as pd from ipyleaflet import Heatmap try: if isinstance(data, str): df = pd.read_csv(data) data = df[[latitude, longitude, value]].values.tolist() elif isinstance(data, pd.DataFrame): data = data[[latitude, longitude, value]].values.tolist() elif isinstance(data, list): pass else: raise ValueError("data must be a list, a DataFrame, or a file path.") heatmap = Heatmap(locations=data, radius=radius, name=name, **kwargs) self.add_layer(heatmap) except Exception as e: raise Exception(e)
[docs] def add_labels( self, data, column, font_size="12pt", font_color="black", font_family="arial", font_weight="normal", x="longitude", y="latitude", draggable=True, layer_name="Labels", **kwargs, ): """Adds a label layer to the map. Reference: https://ipyleaflet.readthedocs.io/en/latest/api_reference/divicon.html Args: data (pd.DataFrame | ee.FeatureCollection): The input data to label. column (str): The column name of the data to label. font_size (str, optional): The font size of the labels. Defaults to "12pt". font_color (str, optional): The font color of the labels. Defaults to "black". font_family (str, optional): The font family of the labels. Defaults to "arial". font_weight (str, optional): The font weight of the labels, can be normal, bold. Defaults to "normal". x (str, optional): The column name of the longitude. Defaults to "longitude". y (str, optional): The column name of the latitude. Defaults to "latitude". draggable (bool, optional): Whether the labels are draggable. Defaults to True. layer_name (str, optional): Layer name to use. Defaults to "Labels". """ import warnings import pandas as pd warnings.filterwarnings("ignore") if isinstance(data, ee.FeatureCollection): centroids = vector_centroids(data) df = ee_to_df(centroids) elif isinstance(data, pd.DataFrame): df = data elif isinstance(data, str): ext = os.path.splitext(data)[1] if ext == ".csv": df = pd.read_csv(data) elif ext in [".geojson", ".json", ".shp", ".gpkg"]: try: import geopandas as gpd df = gpd.read_file(data) df[x] = df.centroid.x df[y] = df.centroid.y except Exception as _: print("geopandas is required to read geojson.") return else: raise ValueError("data must be a DataFrame or an ee.FeatureCollection.") if column not in df.columns: raise ValueError(f"column must be one of {', '.join(df.columns)}.") if x not in df.columns: raise ValueError(f"column must be one of {', '.join(df.columns)}.") if y not in df.columns: raise ValueError(f"column must be one of {', '.join(df.columns)}.") try: size = int(font_size.replace("pt", "")) except: raise ValueError("font_size must be something like '10pt'") labels = [] for index in df.index: html = f'<div style="font-size: {font_size};color:{font_color};font-family:{font_family};font-weight: {font_weight}">{df[column][index]}</div>' marker = ipyleaflet.Marker( location=[df[y][index], df[x][index]], icon=ipyleaflet.DivIcon( icon_size=(1, 1), icon_anchor=(size, size), html=html, **kwargs, ), draggable=draggable, ) labels.append(marker) layer_group = ipyleaflet.LayerGroup(layers=labels, name=layer_name) self.add_layer(layer_group) self.labels = layer_group
[docs] def remove_labels(self): """Removes all labels from the map.""" if hasattr(self, "labels"): self.remove_layer(self.labels) delattr(self, "labels")
[docs] def add_netcdf( self, filename, variables=None, palette=None, vmin=None, vmax=None, nodata=None, attribution=None, layer_name="NetCDF layer", shift_lon=True, lat="lat", lon="lon", **kwargs, ): """Generate an ipyleaflet/folium TileLayer from a netCDF file. If you are using this function in JupyterHub on a remote server (e.g., Binder, Microsoft Planetary Computer), try adding to following two lines to the beginning of the notebook if the raster does not render properly. import os os.environ['LOCALTILESERVER_CLIENT_PREFIX'] = f'{os.environ['JUPYTERHUB_SERVICE_PREFIX'].lstrip('/')}/proxy/{{port}}' Args: filename (str): File path or HTTP URL to the netCDF file. variables (int, optional): The variable/band names to extract data from the netCDF file. Defaults to None. If None, all variables will be extracted. port (str, optional): The port to use for the server. Defaults to "default". palette (str, optional): The name of the color palette from `palettable` to use when plotting a single band. See https://jiffyclub.github.io/palettable. 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 "netCDF layer". shift_lon (bool, optional): Flag to shift longitude values from [0, 360] to the range [-180, 180]. Defaults to True. lat (str, optional): Name of the latitude variable. Defaults to 'lat'. lon (str, optional): Name of the longitude variable. Defaults to 'lon'. """ if in_colab_shell(): print("The add_netcdf() function is not supported in Colab.") return tif, vars = netcdf_to_tif( filename, shift_lon=shift_lon, lat=lat, lon=lon, return_vars=True ) if variables is None: if len(vars) >= 3: band_idx = [1, 2, 3] else: band_idx = [1] else: if not set(variables).issubset(set(vars)): raise ValueError(f"The variables must be a subset of {vars}.") else: band_idx = [vars.index(v) + 1 for v in variables] self.add_raster( tif, band=band_idx, palette=palette, vmin=vmin, vmax=vmax, nodata=nodata, attribution=attribution, layer_name=layer_name, **kwargs, )
[docs] def add_velocity( self, data, zonal_speed, meridional_speed, latitude_dimension="lat", longitude_dimension="lon", level_dimension="lev", level_index=0, time_index=0, velocity_scale=0.01, max_velocity=20, display_options={}, name="Velocity", ): """Add a velocity layer to the map. Args: data (str | xr.Dataset): The data to use for the velocity layer. It can be a file path to a NetCDF file or an xarray Dataset. zonal_speed (str): Name of the zonal speed in the dataset. See https://en.wikipedia.org/wiki/Zonal_and_meridional_flow. meridional_speed (str): Name of the meridional speed in the dataset. See https://en.wikipedia.org/wiki/Zonal_and_meridional_flow. latitude_dimension (str, optional): Name of the latitude dimension in the dataset. Defaults to 'lat'. longitude_dimension (str, optional): Name of the longitude dimension in the dataset. Defaults to 'lon'. level_dimension (str, optional): Name of the level dimension in the dataset. Defaults to 'lev'. level_index (int, optional): The index of the level dimension to display. Defaults to 0. time_index (int, optional): The index of the time dimension to display. Defaults to 0. velocity_scale (float, optional): The scale of the velocity. Defaults to 0.01. max_velocity (int, optional): The maximum velocity to display. Defaults to 20. display_options (dict, optional): The display options for the velocity layer. Defaults to {}. See https://bit.ly/3uf8t6w. name (str, optional): Layer name to use . Defaults to 'Velocity'. Raises: ImportError: If the xarray package is not installed. ValueError: If the data is not a NetCDF file or an xarray Dataset. """ try: import xarray as xr from ipyleaflet.velocity import Velocity except ImportError: raise ImportError( "The xarray package is required to add a velocity layer. " "Please install it with `pip install xarray`." ) if isinstance(data, str): if data.startswith("http"): data = download_file(data) ds = xr.open_dataset(data) elif isinstance(data, xr.Dataset): ds = data else: raise ValueError("The data must be a file path or xarray dataset.") coords = list(ds.coords.keys()) # Rasterio does not handle time or levels. So we must drop them if "time" in coords: ds = ds.isel(time=time_index, drop=True) params = {level_dimension: level_index} if level_dimension in coords: ds = ds.isel(drop=True, **params) wind = Velocity( data=ds, zonal_speed=zonal_speed, meridional_speed=meridional_speed, latitude_dimension=latitude_dimension, longitude_dimension=longitude_dimension, velocity_scale=velocity_scale, max_velocity=max_velocity, display_options=display_options, name=name, ) self.add_layer(wind)
[docs] def add_data( self, data, column, colors=None, labels=None, cmap=None, scheme="Quantiles", k=5, add_legend=True, legend_title=None, legend_kwds=None, classification_kwds=None, layer_name="Untitled", style=None, hover_style=None, style_callback=None, info_mode="on_hover", encoding="utf-8", **kwargs, ): """Add vector data to the map with a variety of classification schemes. Args: data (str | pd.DataFrame | gpd.GeoDataFrame): The data to classify. It can be a filepath to a vector dataset, a pandas dataframe, or a geopandas geodataframe. column (str): The column to classify. cmap (str, optional): The name of a colormap recognized by matplotlib. Defaults to None. colors (list, optional): A list of colors to use for the classification. Defaults to None. labels (list, optional): A list of labels to use for the legend. Defaults to None. scheme (str, optional): Name of a choropleth classification scheme (requires mapclassify). 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. k (int, optional): Number of classes (ignored if scheme is None or if column is categorical). Default to 5. legend_kwds (dict, optional): Keyword arguments to pass to :func:`matplotlib.pyplot.legend` or `matplotlib.pyplot.colorbar`. Defaults to None. Keyword arguments to pass to :func:`matplotlib.pyplot.legend` or Additional accepted keywords when `scheme` is specified: fmt : string A formatting specification for the bin edges of the classes in the legend. For example, to have no decimals: ``{"fmt": "{:.0f}"}``. labels : list-like A list of legend labels to override the auto-generated labblels. Needs to have the same number of elements as the number of classes (`k`). interval : boolean (default False) An option to control brackets from mapclassify legend. If True, open/closed interval brackets are shown in the legend. classification_kwds (dict, optional): Keyword arguments to pass to mapclassify. Defaults to None. layer_name (str, optional): The layer name to be used.. Defaults to "Untitled". style (dict, optional): A dictionary specifying the style to be used. Defaults to None. style is a dictionary of the following form: style = { "stroke": False, "color": "#ff0000", "weight": 1, "opacity": 1, "fill": True, "fillColor": "#ffffff", "fillOpacity": 1.0, "dashArray": "9" "clickable": True, } hover_style (dict, optional): Hover style dictionary. Defaults to {}. hover_style is a dictionary of the following form: hover_style = {"weight": style["weight"] + 1, "fillOpacity": 0.5} style_callback (function, optional): Styling function that is called for each feature, and should return the feature style. This styling function takes the feature as argument. Defaults to None. style_callback is a function that takes the feature as argument and should return a dictionary of the following form: style_callback = lambda feat: {"fillColor": feat["properties"]["color"]} info_mode (str, optional): Displays the attributes by either on_hover or on_click. Any value other than "on_hover" or "on_click" will be treated as None. Defaults to "on_hover". encoding (str, optional): The encoding of the GeoJSON file. Defaults to "utf-8". """ gdf, legend_dict = classify( data=data, column=column, cmap=cmap, colors=colors, labels=labels, scheme=scheme, k=k, legend_kwds=legend_kwds, classification_kwds=classification_kwds, ) if legend_title is None: legend_title = column if style is None: style = { # "stroke": False, # "color": "#ff0000", "weight": 1, "opacity": 1, # "fill": True, # "fillColor": "#ffffff", "fillOpacity": 1.0, # "dashArray": "9" # "clickable": True, } if colors is not None: style["color"] = "#000000" if hover_style is None: hover_style = {"weight": style["weight"] + 1, "fillOpacity": 0.5} if style_callback is None: style_callback = lambda feat: {"fillColor": feat["properties"]["color"]} self.add_gdf( gdf, layer_name=layer_name, style=style, hover_style=hover_style, style_callback=style_callback, info_mode=info_mode, encoding=encoding, **kwargs, ) if add_legend: self.add_legend(title=legend_title, legend_dict=legend_dict)
[docs] def user_roi_coords(self, decimals=4): """Return the bounding box of the ROI as a list of coordinates. Args: decimals (int, optional): Number of decimals to round the coordinates to. Defaults to 4. """ return bbox_coords(self.user_roi, decimals=decimals)
def _point_info(self, latlon, decimals=3, return_node=False): """Create the ipytree widget for displaying the mouse clicking info. Args: latlon (list | tuple): The coordinates (lat, lon) of the point. decimals (int, optional): Number of decimals to round the coordinates to. Defaults to 3. return_node (bool, optional): If True, return the ipytree node. Otherwise, return the ipytree tree widget. Defaults to False. Returns: ipytree.Node | ipytree.Tree: The ipytree node or tree widget. """ point_nodes = [ Node(f"Longitude: {latlon[1]}"), Node(f"Latitude: {latlon[0]}"), Node(f"Zoom Level: {self.zoom}"), Node(f"Scale (approx. m/px): {self.get_scale()}"), ] label = f"Point ({latlon[1]:.{decimals}f}, {latlon[0]:.{decimals}f}) at {int(self.get_scale())}m/px" root_node = Node( label, nodes=point_nodes, icon="map", opened=self._expand_point ) root_node.open_icon = "plus-square" root_node.open_icon_style = "success" root_node.close_icon = "minus-square" root_node.close_icon_style = "info" if return_node: return root_node else: return Tree(nodes=[root_node]) def _pixels_info(self, latlon, return_node=False): """Create the ipytree widget for displaying the pixel values at the mouse clicking point. Args: latlon (list | tuple): The coordinates (lat, lon) of the point. return_node (bool, optional): If True, return the ipytree node. Otherwise, return the ipytree tree widget. Defaults to False. Returns: ipytree.Node | ipytree.Tree: The ipytree node or tree widget. """ layers = self.ee_layers xy = ee.Geometry.Point(latlon[::-1]) sample_scale = self.getScale() root_node = Node("Pixels", icon="archive") nodes = [] for index, ee_object in enumerate(layers): layer_names = self.ee_layer_names layer_name = layer_names[index] object_type = ee_object.__class__.__name__ if not self.ee_layer_dict[layer_name]["ee_layer"].visible: continue try: if isinstance(ee_object, ee.ImageCollection): ee_object = ee_object.mosaic() if isinstance(ee_object, ee.Image): item = ee_object.reduceRegion( ee.Reducer.first(), xy, sample_scale ).getInfo() b_name = "band" if len(item) > 1: b_name = "bands" label = f"{layer_name}: {object_type} ({len(item)} {b_name})" layer_node = Node(label, opened=self._expand_pixels) keys = sorted(item.keys()) for key in keys: layer_node.add_node(Node(f"{key}: {item[key]}", icon="file")) nodes.append(layer_node) except: pass root_node.nodes = nodes root_node.open_icon = "plus-square" root_node.open_icon_style = "success" root_node.close_icon = "minus-square" root_node.close_icon_style = "info" if return_node: return root_node else: return