import xarray as xr
import numpy as np
import holoviews as hv
hv.extension('matplotlib')
%opts Scatter3D [size_index=None color_index=3] (cmap='fire')

img = hv.Image((range(10), range(5), np.random.rand(5, 10)), datatype=['grid'])
img

img.data

arr_img = img.clone(datatype=['image'])
print(type(arr_img.data))

try: 
    xr_img = img.clone(datatype=['xarray'])
    iris_img = img.clone(datatype=['cube'])

    print(type(xr_img.data))
    print(type(iris_img.data))
    
except:
    print('One of the following data backend cannot be imported: xarray or iris')

print("Array type: %s with bounds %s" % (type(arr_img.data), arr_img.bounds))

dataset3d = hv.Dataset((range(3), range(5), range(7), np.random.randn(7, 5, 3)),
                       ['x', 'y', 'z'], 'Value')
dataset3d

hv.Scatter3D(dataset3d)

dataset3d.select(x=1).to(hv.Image, ['y', 'z']) + hv.Scatter3D(dataset3d.select(x=1))

(dataset3d.to(hv.Image, ['y', 'z'], 'Value', ['x']) +
hv.HoloMap({x: hv.Scatter3D(dataset3d.select(x=x)) for x in range(3)}, kdims='x'))

hv.Image(dataset3d.aggregate(['x', 'y'], np.mean)) + hv.Image(dataset3d.reduce(z=np.mean))

hv.Spread(dataset3d.aggregate('z', np.mean, np.std)) * hv.Curve(dataset3d.aggregate('z', np.mean))

dataset3d.to(hv.BoxWhisker, 'x', 'Value', groupby=[])

dataset3d.to(hv.Distribution, 'Value', [], groupby='x').overlay()

heatmap = hv.HeatMap((['A', 'B', 'C'], ['a', 'b', 'c', 'd', 'e'], np.random.rand(5, 3)))
heatmap + heatmap.table()

import xarray as xr
xr_ds = xr.tutorial.load_dataset("air_temperature")
xr_ds

hv_ds = hv.Dataset(xr_ds)[:, :, "2013-01-01"]
print(hv_ds)

%%opts Image [colorbar=True]
%%output size=200
hv_ds.to(hv.Image, kdims=["lon", "lat"], dynamic=False)[:, 220:320, :]

heatmap.dimension_values('x')

heatmap.dimension_values('x', expanded=False)

heatmap.dimension_values('x', flat=False)

heatmap.dimension_values('z')

heatmap.dimension_values('z', flat=False)