"""
Module containing utilities for ship data
"""
import dask
import numpy as np
import pyproj
import xarray as xr
[docs]def calc_cog_sog(ds):
"""
This function calculates the course and speed over ground of a moving
platform using the lat/lon. Note,data are resampled to 1 minute in
order to provide a better estimate of speed/course compared with 1 second.
Function is set up to use dask for the calculations in order to improve
efficiency. Data are then resampled to 1 second to match native format.
This assumes that the input data are 1 second. See this `example
<https://ARM-DOE.github.io/ACT/source/auto_examples/correct_ship_wind_data.html
#sphx-glr-source-auto-examples-correct-ship-wind-data-py>`_.
Parameters
----------
ds : xarray.Dataset
ACT xarray dataset to calculate COG/SOG from. Assumes lat/lon are variables and
that it's 1-second data.
Returns
-------
ds : xarray.Dataset
Returns dataset with course_over_ground and speed_over_ground variables.
"""
# Convert data to 1 minute in order to get proper values
new_ds = ds.resample(time='1min').nearest()
# Get lat and lon data
if 'lat' in new_ds:
lat = new_ds['lat']
elif 'latitude' in new_ds:
lat = new_ds['latitude']
else:
return new_ds
if 'lon' in new_ds:
lon = new_ds['lon']
elif 'longitude' in new_ds:
lon = new_ds['longitude']
else:
return new_ds
# Set pyproj Geod
_GEOD = pyproj.Geod(ellps='WGS84')
# Set up delayed tasks for dask
task = []
time = new_ds['time'].values
for i in range(len(lat) - 1):
task.append(
dask.delayed(proc_scog)(
_GEOD, lon[i + 1], lat[i + 1], lon[i], lat[i], time[i], time[i + 1]
)
)
# Compute and process results Adding 2 values
# to the end to make up for the missing times
results = dask.compute(*task)
sog = [r[0] for r in results]
sog.append(sog[-1])
sog.append(sog[-1])
cog = [r[1] for r in results]
cog.append(cog[-1])
cog.append(cog[-1])
time = np.append(time, time[-1] + np.timedelta64(1, 'm'))
atts = {'long_name': 'Speed over ground', 'units': 'm/s'}
sog_da = xr.DataArray(sog, coords={'time': time}, dims=['time'], attrs=atts)
sog_da = sog_da.resample(time='1s').nearest()
atts = {'long_name': 'Course over ground', 'units': 'deg'}
cog_da = xr.DataArray(cog, coords={'time': time}, dims=['time'], attrs=atts)
cog_da = cog_da.resample(time='1s').nearest()
ds['course_over_ground'] = cog_da
ds['speed_over_ground'] = sog_da
return ds
[docs]def proc_scog(_GEOD, lon2, lat2, lon1, lat1, time1, time2):
"""
This procedure is to only be used by the calc_cog_sog function for dask
delayed processing.
"""
cog, baz, dist = _GEOD.inv(lon1, lat1, lon2, lat2)
tdiff = (time2 - time1) / np.timedelta64(1, 's')
sog = dist / tdiff
if cog < 0:
cog = 360.0 + cog
if sog < 0.5:
cog = np.nan
return sog, cog, dist