Bokeh Tutorial

1.7 Animate

Exercise: Animate the climate map

Create a loop that updates the data source of the climate_map through time (for every month and year). You'll need to use the bokeh-server.

Note: when using the output_server make sure that your data source doesn't contain nans



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# Imports
import numpy as np
import netCDF4

from bokeh.plotting import vplot, hplot, cursession, output_server, show

from viz import climate_map, timeseries, legend, get_slice



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# Data
data = netCDF4.Dataset('data/Land_and_Ocean_LatLong1.nc')
t = data.variables['temperature']



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# Output option
output_server("climate")









    



Using saved session configuration for http://localhost:5006/
To override, pass 'load_from_config=False' to Session



In [12]:

    
# Plots
climate_map = climate_map()
timeseries = timeseries()
legend = legend()



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# Create layout
map_legend = hplot(climate_map, legend)
layout = vplot(map_legend, timeseries)



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# Show
show(layout)



In [15]:

    
# Select data source for climate_map
renderer = climate_map.select(dict(name="image"))
ds = renderer[0].data_source



In [16]:

    
# Create a loop that goes through month and year and updates the image data
import time

for year_index in np.arange(2000, 2015, 1):
    for month_index in np.arange(1, 13, 1):
        image = get_slice(t, year_index, month_index)
        ds.data["image"] = [image]
        cursession().store_objects(ds)
        time.sleep(0.2)



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