Reads netCDF format tidal solutions provided by Ohio State University and ESR
Spatially interpolates tidal constituents to input coordinates
Calling Sequence
import pyTMD.ioamp,ph,D,c = pyTMD.io.ATLAS.extract_constants(ilon, ilat, grid_file, model_files, type='z', method='spline')
- pyTMD.io.ATLAS.extract_constants(ilon: ndarray, ilat: ndarray, grid_file: str | pathlib.Path | None = None, model_files: str | list | pathlib.Path | None = None, **kwargs)[source]
Reads files for ATLAS netCDF4 tidal models
Makes initial calculations to run the tide program
Spatially interpolates tidal constituents to input coordinates
- Parameters
- ilon: np.ndarray
longitude to interpolate
- ilat: np.ndarray
latitude to interpolate
- grid_file: str, pathlib.Path or NoneType, default None
grid file for model
- model_files: str, list, pathlib.Path or NoneType, default None
list of model files for each constituent
- type: str, default ‘z’
Tidal variable to read
'z': heights'u': horizontal transport velocities'U': horizontal depth-averaged transport'v': vertical transport velocities'V': vertical depth-averaged transport
- method: str, default ‘spline’
Interpolation method
'bilinear': quick bilinear interpolation'spline': scipy bivariate spline interpolation'linear','nearest': scipy regular grid interpolations
- extrapolate: bool, default False
Extrapolate model using nearest-neighbors
- cutoff: float, default 10.0
Extrapolation cutoff in kilometers
Set to
np.infto extrapolate for all points- compressed: bool, default False
Input files are gzip compressed
- scale: float, default 1.0
Scaling factor for converting to output units
- Returns
- amplitude: np.ndarray
amplitudes of tidal constituents
- phase: np.ndarray
phases of tidal constituents
- D: np.ndarray
bathymetry of tide model
- constituents: list
Tide model constituent names
- pyTMD.io.ATLAS.read_constants(grid_file: str | pathlib.Path | None = None, model_files: str | list | pathlib.Path | None = None, **kwargs)[source]
Reads files for ATLAS netCDF4 tidal models
- Parameters
- grid_file: str, pathlib.Path or NoneType, default None
grid file for model
- model_files: str, list, pathlib.Path or NoneType, default None
list of model files for each constituent
- type: str, default ‘z’
Tidal variable to read
'z': heights'u': horizontal transport velocities'U': horizontal depth-averaged transport'v': vertical transport velocities'V': vertical depth-averaged transport
- compressed: bool, default False
Input files are gzip compressed
- Returns
- constituents: obj
complex form of tide model constituents
- pyTMD.io.ATLAS.interpolate_constants(ilon: ndarray, ilat: ndarray, constituents, **kwargs)[source]
Interpolate constants from ATLAS tidal models to input coordinates
Makes initial calculations to run the tide program
- Parameters
- ilon: np.ndarray
longitude to interpolate
- ilat: np.ndarray
latitude to interpolate
- constituents: obj
Tide model constituents (complex form)
- type: str, default ‘z’
Tidal variable to read
'z': heights'u': horizontal transport velocities'U': horizontal depth-averaged transport'v': vertical transport velocities'V': vertical depth-averaged transport
- method: str, default ‘spline’
Interpolation method
'bilinear': quick bilinear interpolation'spline': scipy bivariate spline interpolation'linear','nearest': scipy regular grid interpolations
- extrapolate: bool, default False
Extrapolate model using nearest-neighbors
- cutoff: float, default 10.0
Extrapolation cutoff in kilometers
Set to
np.infto extrapolate for all points- scale: float, default 1.0
Scaling factor for converting to output units
- Returns
- amplitude: np.ndarray
amplitudes of tidal constituents
- phase: np.ndarray
phases of tidal constituents
- D: np.ndarray
bathymetry of tide model
- pyTMD.io.ATLAS.read_netcdf_grid(input_file: str | pathlib.Path, variable: str, **kwargs)[source]
Read grid file to extract model coordinates and bathymetry
- Parameters
- input_file: str or pathlib.Path
input grid file
- variable: str
Tidal variable to read
'z': heights'u': horizontal transport velocities'U': horizontal depth-averaged transport'v': vertical transport velocities'V': vertical depth-averaged transport
- compressed: bool, default False
Input file is gzip compressed
- Returns
- lon: np.ndarray
longitudinal coordinates of input grid
- lat: np.ndarray
latitudinal coordinates of input grid
- bathymetry: np.ndarray
model bathymetry
- pyTMD.io.ATLAS.read_netcdf_file(input_file: str | pathlib.Path, variable: str, **kwargs)[source]
Wrapper function for reading netCDF4 files to extractreal and imaginary components for constituent
- Parameters
- input_file: str or pathlib.Path
input transport file
- variable: str
Tidal variable to read
'z': heights'u': horizontal transport velocities'U': horizontal depth-averaged transport'v': vertical transport velocities'V': vertical depth-averaged transport
- compressed: bool, default False
Input file is gzip compressed
- Returns
- hc: np.ndarray
tidal constituent
- con: str
tidal constituent ID
- pyTMD.io.ATLAS.read_netcdf_elevation(input_file: str | pathlib.Path, **kwargs)[source]
Read elevation file to extract real and imaginary components for constituent
- Parameters
- input_file: str or pathlib.Path
input elevation file
- compressed: bool, default False
Input file is gzip compressed
- Returns
- hc: np.ndarray
tidal elevation
- con: str
tidal constituent ID
- pyTMD.io.ATLAS.read_netcdf_transport(input_file: str | pathlib.Path, variable: str, **kwargs)[source]
Read transport file to extract real and imaginary components for constituent
- Parameters
- input_file: str or pathlib.Path
input transport file
- variable: str
Tidal variable to read
'u': horizontal transport velocities'U': horizontal depth-averaged transport'v': vertical transport velocities'V': vertical depth-averaged transport
- compressed: bool, default False
Input file is gzip compressed
- Returns
- hc: np.ndarray
tidal transport
- con: str
tidal constituent ID
- pyTMD.io.ATLAS.output_netcdf_grid(FILE: str | pathlib.Path, hz: ndarray, hu: ndarray, hv: ndarray, lon_z: ndarray, lat_z: ndarray, lon_u: ndarray, lat_u: ndarray, lon_v: ndarray, lat_v: ndarray)[source]
Writes grid parameters to netCDF4 files in ATLAS format
- Parameters
- FILE: str or pathlib.Path
output ATLAS grid file name
- hz: np.ndarray
model bathymetry at z-nodes
- hu: np.ndarray
model bathymetry at u-nodes
- hv: np.ndarray
model bathymetry at v-nodes
- lon_z: np.ndarray
longitude coordinates at z-nodes
- lat_z: np.ndarray
latitude coordinates at z-nodes
- lon_u: np.ndarray
longitude coordinates at u-nodes
- lat_u: np.ndarray
latitude coordinates at u-nodes
- lon_v: np.ndarray
longitude coordinates at v-nodes
- lat_v: np.ndarray
latitude coordinates at v-nodes
- pyTMD.io.ATLAS.output_netcdf_elevation(FILE: str | pathlib.Path, h: ndarray, lon_z: ndarray, lat_z: ndarray, constituent: str)[source]
Writes elevation constituents to netCDF4 files in ATLAS format
- Parameters
- FILE: str or pathlib.Path
output ATLAS elevation file name
- h: np.ndarray
Eulerian form of tidal elevation oscillation
- lon_z: np.ndarray
longitude coordinates at z-nodes
- lat_z: np.ndarray
latitude coordinates at z-nodes
- constituent: str
tidal constituent ID
- pyTMD.io.ATLAS.output_netcdf_transport(FILE: str | pathlib.Path, u: ndarray, v: ndarray, lon_u: ndarray, lat_u: ndarray, lon_v: ndarray, lat_v: ndarray, constituent: str)[source]
Writes transport constituents to netCDF4 files in ATLAS format
- Parameters
- FILE: str or pathlib.Path
output ATLAS transport file name
- u: np.ndarray
Eulerian form of tidal zonal transport oscillation
- v: np.ndarray
Eulerian form of tidal meridional transport oscillation
- lon_u: np.ndarray
longitude coordinates at u-nodes
- lat_u: np.ndarray
latitude coordinates at u-nodes
- lon_v: np.ndarray
longitude coordinates at v-nodes
- lat_v: np.ndarray
latitude coordinates at v-nodes
- constituents: str
tidal constituent ID
- pyTMD.io.ATLAS._extend_array(input_array: ndarray, step_size: float)[source]
Extends a longitude array
- Parameters
- input_array: np.ndarray
array to extend
- step_size: float
step size between elements of array
- Returns
- temp: np.ndarray
extended array
- pyTMD.io.ATLAS._extend_matrix(input_matrix: ndarray)[source]
Extends a global matrix
- Parameters
- input_matrix: np.ndarray
matrix to extend
- Returns
- temp: np.ndarray
extended matrix
