Example DataFrame roundtripping for OrthogonalMultidimensionalTimeseriesProfile

portho_ts_profile.py

import datetime
import numpy as np
import random
import pandas as pd

# construct fake dataframe

then = datetime.datetime.utcnow()

n_times = 2
n_levels = 4
n_stations = 3

times = [then + datetime.timedelta(hours=h) for h in np.cumsum(np.random.uniform(size=n_times))]
stations = ['station{}'.format(i) for i in range(n_stations)]
levels = range(n_levels)
zs = np.cumsum(np.random.uniform(size=n_levels))
lats = np.random.uniform(size=n_stations) * 180 - 90
lons = np.random.uniform(size=n_stations) * 360 - 180

ob = range(n_times * n_stations * n_levels)

time = np.repeat(times, n_stations * n_levels)
z = np.tile(np.repeat(zs, n_stations), n_times)
station = np.tile(stations, n_levels * n_times)
lat = np.tile(lats, n_times * n_levels)
lon = np.tile(lons, n_times * n_levels)

d = dict(station=station, t=time, ob=ob, z=z, y=lat, x=lon)
df = pd.DataFrame(d)

print(df)

from pocean.dsg.timeseriesProfile.om import OrthogonalMultidimensionalTimeseriesProfile

omtp = OrthogonalMultidimensionalTimeseriesProfile.from_dataframe(df, 'omtp.nc')

df2 = omtp.to_dataframe()

print('')

print(df2)