Reading converted time series dataΒΆ

For reading time series data, that the era5_reshuffle and eraint_reshuffle command produces, the class ERATs can be used. Optional arguments that are passed to the parent class (OrthoMultiTs, as defined in pynetcf.time_series) can be passed as well:

from ecmwf_models import ERATs
ds = ERATs(ts_path, ioclass_kws={'read_bulk':True}) # read_bulk reads full files into memory
# read_ts takes either lon, lat coordinates to perform a nearest neighbour search
# or a grid point index (from the file) and returns a pandas.DataFrame.
ts = ds.read_ts(45, 15)

Bulk reading speeds up reading multiple points from a cell file by storing the file in memory for subsequent calls. Either Longitude and Latitude can be passed to perform a nearest neighbour search on the data grid ( in the time series path) or the grid point index (GPI) can be passed directly.