import pandas as pd
import holoviews as hv
spike_train = pd.read_csv('../assets/spike_train.csv.gz')
spike_train.head(n=3)

curve = hv.Curve(spike_train, 'milliseconds', 'Hertz', group='Firing Rate')
spikes = hv.Spikes(spike_train.sample(300), kdims='milliseconds', vdims=[], group='Spike Train')
curve + spikes

hv.extension('bokeh', 'matplotlib')

curve + spikes

%%output size=150
%%opts Curve  [height=100 width=600 xaxis=None tools=['hover']]
%%opts Curve (color='red' line_width=1.5)
%%opts Spikes [height=100 width=600 yaxis=None] (color='grey' line_width=0.25)
curve  = hv.Curve( spike_train, 'milliseconds', 'Hertz')
spikes = hv.Spikes(spike_train, 'milliseconds', [])
(curve + spikes).cols(1)

curve_opts = dict(height=100, width=600, xaxis=None, tools=['hover'], color='red', line_width=1.5)
spike_opts = dict(height=100, width=600, yaxis=None, color='grey', line_width=0.25)

curve = hv.Curve(spike_train, 'milliseconds', 'Hertz')
spikes = hv.Spikes(spike_train, 'milliseconds', [])

(curve.options(**curve_opts) + spikes.options(**spike_opts)).cols(1)

layout = (curve + spikes).options({'Curve': curve_opts, 'Spikes': spike_opts}).cols(1)

%%output size=200 backend='matplotlib' fig='svg'
%%opts Layout [sublabel_format='' vspace=0.1]
%%opts Spikes [aspect=6 yaxis='bare'] (color='red' linewidth=0.25 )
%%opts Curve [aspect=6 xaxis=None show_grid=False] (color='blue' linewidth=2 linestyle='dashed')
(hv.Curve(spike_train, 'milliseconds', 'Hertz')
 + hv.Spikes(spike_train, 'milliseconds', vdims=[])).cols(1)

%output size=150
spikes.select(milliseconds=(2000,4000))

spikes= spikes.redim.label(milliseconds='Time in milliseconds (10⁻³ seconds)')
curve  = curve.redim.label(Hertz='Frequency (Hz)')
(curve + spikes).select(milliseconds=(2000,4000)).cols(1)