Source code for holoviews.plotting.plotly.tiles

import numpy as np

from holoviews.element.tiles import _ATTRIBUTIONS
from holoviews.plotting.plotly import ElementPlot
from holoviews.plotting.plotly.util import STYLE_ALIASES

[docs]class TilePlot(ElementPlot): style_opts = ['min_zoom', 'max_zoom', "alpha", "accesstoken", "mapboxstyle"] _supports_geo = True @classmethod def trace_kwargs(cls, **kwargs): return {'type': 'scattermapbox'} def get_data(self, element, ranges, style, **kwargs): return [{ "type": "scattermapbox", "lat": [], "lon": [], "subplot": "mapbox", "showlegend": False, }] def graph_options(self, element, ranges, style, **kwargs): style = dict(style) opts = dict( style=style.pop("mapboxstyle", "white-bg"), accesstoken=style.pop("accesstoken", None), ) # Extract URL and lower case wildcard characters for mapbox url = if url: layer = {} opts["layers"] = [layer] # is xyzservices.TileProvider if isinstance(, dict): layer["source"] = ["@2x")] layer['sourceattribution'] = layer['minzoom'] ="min_zoom", 0) layer['maxzoom'] ="max_zoom", 20) else: for v in ["X", "Y", "Z"]: url = url.replace("{%s}" % v, "{%s}" % v.lower()) layer["source"] = [url] for key, attribution in _ATTRIBUTIONS.items(): if all(k in for k in key): layer['sourceattribution'] = attribution layer["below"] = 'traces' layer["sourcetype"] = "raster" # Remaining style options are layer options layer.update({STYLE_ALIASES.get(k, k): v for k, v in style.items()}) return opts
[docs] def get_extents(self, element, ranges, range_type='combined', **kwargs): extents = super().get_extents(element, ranges, range_type) if (not self.overlaid and all(e is None or not np.isfinite(e) for e in extents) and range_type in ('combined', 'data')): x0, x1 = (-20037508.342789244, 20037508.342789244) y0, y1 = (-20037508.342789255, 20037508.342789244) global_extent = (x0, y0, x1, y1) return global_extent return extents
[docs] def init_graph(self, datum, options, index=0, **kwargs): return {'traces': [datum], "mapbox": options}
[docs] def generate_plot(self, key, ranges, element=None, is_geo=False): """ Override to force is_geo to True """ return super().generate_plot(key, ranges, element, is_geo=True)