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

%opts Points [size_index=None] (size=8) Scatter (size=5) Image (cmap='Reds')
%opts Bounds (line_width=2 color='black') {+axiswise} Text (fontsize='16pt')

np.random.seed(42)
edges, data = np.histogram(np.random.randn(100))
hist = hv.Histogram(edges, data)
subregion = hist[0:1]
hist * subregion

hist[0.25], hist[0.5], hist[0.55]

xs = np.linspace(0, np.pi*2, 21)
curve = hv.Curve((xs, np.sin(xs)))
subregion = curve[np.pi/2:np.pi*1.5]
curve * subregion * hv.Scatter(curve)

curve[4.05], curve[4.1], curve[4.17], curve[4.3]

curve[4:4.5]

r = np.arange(0, 1, 0.005)
xs, ys = (r * fn(85*np.pi*r) for fn in (np.cos, np.sin))
paths = hv.Points((xs, ys))
paths + paths[0:1, 0:1]

%%output backend='matplotlib'
xs = np.linspace(0, np.pi*8, 201)
scatter = hv.Scatter3D((xs, np.sin(xs), np.cos(xs)))
scatter + scatter[5:10, :, 0:]

%opts Image (cmap='Blues') Bounds (color='red')

np.random.seed(0)
extents = (0, 0, 10, 10)
img = hv.Image(np.random.rand(10, 10), bounds=extents)
img_slice = img[1:9,4:5]
box = hv.Bounds((1,4,9,5))
img*box + img_slice

img[4.2,4.2], img[4.3,4.2], img[5.0,4.2]

xs = np.linspace(0, np.pi*2, 21)
curve = hv.Curve((xs, np.sin(xs)))
print('x: %s, y: %s' % (curve.iloc[8, 0], curve.iloc[8, 1]))
curve * hv.Scatter(curve.iloc[8])

curve + curve.iloc[5:16:2]

curve.iloc[[0, 5, 10, 15, 20]] + curve.iloc[xs>3]

img_coords = hv.Points(img.table(), extents=extents)
labeled_img = img * img_coords * hv.Points([img.closest([(4.1,4.3)])]).options(color='r')
img + labeled_img + img.sample([(4.1,4.3)])

img[4.1,4.3]

sampled = img.sample(y=5)
labeled_img = img * img_coords * hv.Points(zip(sampled['x'], [img.closest(y=5)]*10))
img + labeled_img + sampled

xs = np.arange(10)
samples = [2, 4, 6, 8]
curve = hv.Curve(zip(xs, np.sin(xs)))
curve_samples = hv.Scatter(zip(xs, [0] * 10)) * hv.Scatter(zip(samples, [0]*len(samples))) 
curve + curve_samples + curve.sample(samples)

obs_hmap = hv.HoloMap({i: hv.Image(np.random.randn(10, 10), bounds=extents)
                       for i in range(3)}, kdims='Observation')

%%output backend='matplotlib' size=120
sample_style = dict(edgecolors='k', alpha=1)
all_samples = obs_hmap.table().to.scatter3d().options(alpha=0.15, xticks=4)
sampled = obs_hmap.sample((3,3))
subsamples = sampled.to.scatter3d().options(**sample_style)
all_samples * subsamples + sampled

%%output backend='matplotlib' size=120
sampled = obs_hmap.sample((3,3), bounds=(2,5,5,10))
subsamples = sampled.to.scatter3d().options(**dict(sample_style, xticks=4))
all_samples * subsamples + sampled

xs = np.arange(10)
extents = (0, 0, 2, 10)
curve = hv.HoloMap({(i) : hv.Curve(zip(xs, np.sin(xs)*i))
                    for i in np.linspace(0.5, 1.5, 3)},
                   kdims='Observation')
all_samples = curve.table().to.points()
sampled = curve.sample([0, 2, 4, 6, 8])
sampling = all_samples * sampled.to.points(extents=extents).options(color='r')
sampling + sampled

sampled = curve.table().select(Observation=(0, 1.1), x={0, 2, 4, 6, 8})
sampling = all_samples * sampled.to.points(extents=extents).options(color='r')
sampling + sampled