In [ ]:
import hvplot.xarray  # noqa


vectorfield accepts 2d arrays of magnitude and angle on a grid and produces an array of vectors. x and y can be 2d or 1d coordinates.

In [ ]:
import numpy as np
import xarray as xr
import geoviews as gv
import cartopy.crs as ccrs

In [ ]:
def sample_data(shape=(20, 30)):
"""
Return (x, y, u, v, crs) of some vector data
computed mathematically. The returned crs will be a rotated
pole CRS, meaning that the vectors will be unevenly spaced in
regular PlateCarree space.

"""
crs = ccrs.RotatedPole(pole_longitude=177.5, pole_latitude=37.5)

x = np.linspace(311.9, 391.1, shape[1])
y = np.linspace(-23.6, 24.8, shape[0])

x2d, y2d = np.meshgrid(x, y)
u = 10 * (2 * np.cos(2 * np.deg2rad(x2d) + 3 * np.deg2rad(y2d + 30)) ** 2)
v = 20 * np.cos(6 * np.deg2rad(x2d))

return x, y, u, v, crs

xs, ys, U, V, crs = sample_data()

mag = np.sqrt(U**2 + V**2)
angle = (np.pi/2.) - np.arctan2(U/mag, V/mag)

ds = xr.Dataset({'mag': xr.DataArray(mag, dims=('y', 'x'), coords={'y': ys, 'x': xs}),
'angle': xr.DataArray(angle, dims=('y', 'x'), coords={'y': ys, 'x': xs})},
attrs={'crs': crs})
ds

In [ ]:
ds.hvplot.vectorfield(x='x', y='y', angle='angle', mag='mag', hover=False).opts(magnitude='mag')


## Geographic Data¶

If a dataset has an attr called crs which is a cartopy object or a proj4 string, then just by setting the option geo=True will use the correct crs.

In [ ]:
ds.hvplot.vectorfield(x='x', y='y', angle='angle', mag='mag',
hover=False, geo=True).opts(magnitude='mag') * gv.tile_sources.CartoLight