import numpy as np
import holoviews as hv
hv.extension('bokeh')

# Styles and plot options used in this user guide
%opts Ellipse [bgcolor='white'] (color='black')
%opts Image (cmap='viridis')
%opts VLine HLine (color='red' line_width=2)
%opts Path [show_grid=False bgcolor='white'] (color='black' line_dash='dashdot')
%opts Area (fill_color='cornsilk' line_width=2 line_color='black')

lin = np.linspace(-np.pi,np.pi,300)

def lissajous(t, a,b, delta):
    return (np.sin(a * t + delta), np.sin(b * t))

def lissajous_curve(t, a=3,b=5, delta=np.pi/2):
    (x,y) = lissajous(t,a,b,delta)
    return hv.Path(lissajous(lin,a,b,delta)) * hv.VLine(x) * hv.HLine(y)

hv.DynamicMap(lissajous_curve, kdims='t').redim.range(t=(-3.,3.))

from holoviews.streams import Stream, param
Time = Stream.define('Time', t=0.0)

hv.help(Time)

Time = Stream.define('Time', t=param.Number(default=0.0, doc='A time parameter'))
hv.help(Time)

time_dflt = Time()
print('This Time instance has parameter t={t}'.format(t=time_dflt.t))

time = Time(t=np.pi/4)
print('This Time instance has parameter t={t}'.format(t=time.t))

dmap = hv.DynamicMap(lissajous_curve, streams=[time])
dmap + lissajous_curve(t=np.pi/4)

dmap.event( t=0.2)

time.event(t=-0.2)

ls = np.linspace(0, 10, 200)
xx, yy = np.meshgrid(ls, ls)

XY = Stream.define('XY',x=0.0,y=0.0)

def marker(x,y):
    return hv.Image(np.sin(xx)*np.cos(yy)) * hv.VLine(x) * hv.HLine(y)

dmap = hv.DynamicMap(marker, streams=[XY()])
dmap

dmap.event(x=-0.2, y=0.1)

xs = np.linspace(-3, 3, 400)

def function(xs, time):
    "Some time varying function"
    return np.exp(np.sin(xs+np.pi/time))

def integral(limit, time):
    curve = hv.Curve((xs, function(xs, time)))[limit:]
    area  = hv.Area ((xs, function(xs, time)))[:limit]
    summed = area.dimension_values('y').sum() * 0.015  # Numeric approximation
    return (area * curve * hv.VLine(limit) * hv.Text(limit + 0.5, 2.0, '%.2f' % summed))

Time = Stream.define('Time', time=1.0)
dmap=hv.DynamicMap(integral, kdims='limit', streams=[Time()]).redim.range(limit=(-3,2))
dmap

dmap.event(time=8)

def integral2(lim, t): 
    'Same as integral with different argument names'
    return integral(lim, t)

dmap = hv.DynamicMap(integral2, kdims='limit', streams=[Time().rename(time='t')]).redim.range(limit=(-3.,3.))
dmap

dmap=hv.DynamicMap(integral, kdims=['time','limit'], streams=[Time()]).redim.range(limit=(-3.,3.))
dmap

dmap[1,0] + dmap.select(time=3,limit=1.5) + dmap[None,1.5]

dmap.reset()  # Reset the cache, we don't want the values from the cell above
# TODO: redim the limit dimension to a default of 0
dmap.event(time=1)
dmap.event(time=1.5)
dmap.event(time=2)
hv.HoloMap(dmap)

def sample_distributions(samples=10, tol=0.04):
    np.random.seed(42)
    while True:
        gauss1 = np.random.normal(size=samples)
        gauss2 = np.random.normal(size=samples)
        data = (['A']*samples + ['B']*samples, np.hstack([gauss1, gauss2]))
        yield hv.BoxWhisker(data, 'Group', 'Value')
        samples+=1
        
sample_generator = sample_distributions()

hv.DynamicMap(sample_generator)

dmap = hv.DynamicMap(sample_generator, streams=[Stream.define('Next')()])
dmap

for i in range(40):
    dmap.event()

dmap.periodic(0.1, 1000, timeout=3)

hv.HoloMap({i:next(dmap) for i in range(10)}, kdims='Iteration')

defineXY = Stream.define('defineXY', x=0.0, y=0.0)

class XY(Stream):
    x = param.Number(default=0.0, constant=True, doc='An X position.')
    y = param.Number(default=0.0, constant=True, doc='A Y position.')

xy = XY(x=2,y=3)

xy.update(x=4,y=50)
xy.rename(x='xpos', y='ypos').contents

xy = XY()
xy.event(x=4,y=50)
xy.contents

def subscriber(xpos,ypos):
    print('The subscriber received xpos={xpos} and ypos={ypos}'.format(xpos=xpos,ypos=ypos))

xy = XY().rename(x='xpos', y='ypos')
xy.add_subscriber(subscriber)
xy.event(x=4,y=50)

xy.clear()
xy.event(x=0,y=0)