FES

• Reads Finite Element Solution (FES), Empirical Ocean Tide (EOT), and Hamburg direct data Assimilation Methods for Tides (HAMTIDE) models

  • FES-ascii

  • FES-netcdf

  • FES-native

Calling Sequence

import pyTMD.io
ds = pyTMD.io.FES.open_mfdataset(model_files, group='z', format=format)

Source code

pyTMD.io.FES.open_mfdataset(model_files: list[str] | list[Path], parallel: bool = False, **kwargs)

Open multiple FES model files

Parameters:

model_files: list of str or pathlib.Path

List of FES model files

parallel: bool, default False

Open files in parallel using dask.delayed

kwargs: dict

Additional keyword arguments for opening FES files

Returns:

ds: xarray.Dataset

FES tide model data

pyTMD.io.FES.open_fes_dataset(input_file: str | Path, **kwargs)

Open FES-formatted model files

Parameters:

input_file: str or pathlib.Path

Input transport file

format: str, default ‘netcdf’

Model format

• 'ascii': FES ASCII format

• 'netcdf': FES netCDF4 format

kwargs: dict

Additional keyword arguments for opening FES files

Returns:

ds: xarray.Dataset

FES tide model data

pyTMD.io.FES.open_fes_ascii(input_file: str | Path, chunks: int | dict | str | None = None, **kwargs)

Open FES-formatted ASCII files

Parameters:

input_file: str or pathlib.Path

Input ASCII file

chunks: int, dict, str, or None, default None

Coerce output to specified chunks

compressed: bool, default False

Input file is gzip compressed

Returns:

ds: xarray.Dataset

FES tide model data

pyTMD.io.FES.open_fes_netcdf(input_file: str | Path, chunks: int | dict | str | None = None, **kwargs)

Open FES-formatted netCDF4 files

Parameters:

input_file: str or pathlib.Path

Model file

group: str or NoneType, default None

Tidal variable to read

• 'z': heights

• 'u': zonal currents

• 'v': meridional currents

chunks: int, dict, str, or None, default None

Variable chunk sizes for dask (see xarray.open_dataset)

compressed: bool, default False

Input file is gzip compressed

Returns:

ds: xarray.Dataset

FES tide model data

pyTMD.io.FES.open_fes_native(input_file: str | Path, chunks: int | dict | str | None = None, **kwargs)

Open FES-native netCDF4 files with unstructured finite-element grids

Parameters:

input_file: str or pathlib.Path

Model file

group: str or NoneType, default None

Tidal variable to read

• 'z': heights

• 'u': zonal currents

• 'v': meridional currents

chunks: int, dict, str, or None, default None

Variable chunk sizes for dask (see xarray.open_dataset)

compressed: bool, default False

Input file is gzip compressed

Returns:

ds: xarray.Dataset

FES tide model data

class pyTMD.io.FES.FESDataset(ds)

xarray.Dataset utilities for FES tidal models

to_netcdf(path: str | Path, mode: str = 'w', encoding: dict = {'complevel': 9, 'zlib': True}, **kwargs)

Writes tidal constituents to netCDF4 files in FES2014/2022 format

Parameters:

path: str | pathlib.Path

Output directory for netCDF4 files

mode: str, default ‘w’

netCDF4 file mode

encoding: dict, default {“zlib”: True, “complevel”: 9}

netCDF4 variable compression settings

kwargs: dict

Additional keyword arguments for xarray netCDF4 writer