import numpy as np
import holoviews as hv
hv.notebook_extension('bokeh')
%opts Curve (line_width=1)

def fm_modulation(f_carrier=220, f_mod=220, mod_index=1, length=0.1, sampleRate=2000):
    sampleInc = 1.0/sampleRate
    x = np.arange(0,length, sampleInc)
    y = np.sin(2*np.pi*f_carrier*x + mod_index*np.sin(2*np.pi*f_mod*x))
    return hv.Curve((x, y), 'Time', 'Amplitude')

%%opts Curve [width=600]
f_carrier = np.linspace(20, 60, 3)
f_mod = np.linspace(20, 100, 5)

curve_dict = {(fc, fm): fm_modulation(fc, fm) for fc in f_carrier for fm in f_mod}

kdims = [hv.Dimension(('f_carrier', 'Carrier frequency'), default=40),
         hv.Dimension(('f_mod', 'Modulation frequency'), default=60)]
holomap = hv.HoloMap(curve_dict, kdims=kdims)
holomap

%%opts GridSpace [plot_size=75] Curve [width=100]
grid = hv.GridSpace(holomap)
grid

%%opts Curve [width=500 height=200]
hv.NdLayout(grid[20, 20:81]).cols(2)

%%opts NdOverlay [width=600 legend_position='right']
holomap.overlay('f_carrier')

%%opts Curve [width=200 height=200]
holomap.overlay('f_carrier').grid('f_mod')

%%opts Curve [width=400]
holomap[20, 40] + holomap.select(f_carrier=20, f_mod=40)

print(grid)

ds = hv.Dataset(grid.table())
ds.data.head()

holomap.kdims

reindexed = holomap.reindex(['f_mod', 'f_carrier'])
reindexed.kdims

new_holomap = holomap.add_dimension('New dimension', dim_pos=0, dim_val=1)
new_holomap.kdims