import datashader as ds
import datashader.transfer_functions as tf
import dask.diagnostics as diag

import spatialpandas as spd
import spatialpandas.io
from datashader.utils import lnglat_to_meters

%%time
df = spd.io.read_parquet_dask('./data/osm-3billion.parq')

df.head()

def bounds(x_range, y_range):
    x,y = lnglat_to_meters(x_range, y_range)
    return dict(x_range=x, y_range=y)

Earth       = ((-180.00, 180.00), (-59.00, 74.00))
France      = (( -12.00,  16.00), ( 41.26, 51.27))
Paris       = ((   2.05,   2.65), ( 48.76, 48.97))

plot_width = 1000
plot_height = int(plot_width*0.5)

cvs = ds.Canvas(plot_width=plot_width, plot_height=plot_height, **bounds(*Earth))

with diag.ProgressBar(), diag.Profiler() as prof, diag.ResourceProfiler(0.5) as rprof:
    agg = cvs.points(df, 'x', 'y')

tf.shade(agg.where(agg > 15), cmap=["lightblue", "darkblue"])

def plot(x_range, y_range):
    cvs = ds.Canvas(plot_width=plot_width, plot_height=plot_height, **bounds(x_range, y_range))
    agg = cvs.points(df, 'x', 'y')
    return tf.shade(agg, cmap=["lightblue","darkblue"])

%time plot(*France)

%time plot(*Paris)

from bokeh.io import output_notebook
from bokeh.resources import CDN
output_notebook(CDN, hide_banner=True)

diag.visualize([prof, rprof]);