GOT

Reads files for Richard Ray’s Global Ocean Tide (GOT) models
- ascii format
- netcdf format
Spatially interpolates tidal constituents to input coordinates

Calling Sequence

import pyTMD.io
amp,ph,c = pyTMD.io.GOT.extract_constants(ilon, ilat, model_files,
   method='spline')

Source code

pyTMD.io.GOT.extract_constants(ilon: ndarray, ilat: ndarray, model_files: str | Path | list | None = None, **kwargs)[source]

Reads files for Richard Ray’s Global Ocean Tide (GOT) 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

model_files: str, list, pathlib.Path or NoneType, default None

list of model files for each constituent

grid: str, default ‘ascii’

Tide model file type to read

'ascii': traditional GOT ascii format

'netcdf': GOT netCDF4 format

compressed: bool, default False

Input files are gzip compressed

crop: bool, default False

Crop tide model data to (buffered) bounds

bounds: list or NoneType, default None

Boundaries for cropping tide model data

buffer: int or float, default None

Buffer angle for cropping tide model data

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.inf to 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
constituents: np.ndarray: list of model constituents

pyTMD.io.GOT.read_constants(model_files: str | Path | list | None = None, **kwargs)[source]

Reads files for Richard Ray’s Global Ocean Tide (GOT) models

Parameters:

model_files: str, list, pathlib.Path or NoneType, default None

list of model files for each constituent

grid: str, default ‘ascii’

Tide model file type to read

'ascii': traditional GOT ascii format

'netcdf': GOT netCDF4 format

compressed: bool, default False

Input files are gzip compressed

crop: bool, default False

Crop tide model data to (buffered) bounds

bounds: list or NoneType, default None

Boundaries for cropping tide model data

buffer: int or float, default 0

Buffer angle for cropping tide model data

Returns:

constituents: obj: complex form of tide model constituents

pyTMD.io.GOT.interpolate_constants(ilon: ndarray, ilat: ndarray, constituents, **kwargs)[source]

Interpolate constants from GOT 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)

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.inf to 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

pyTMD.io.GOT.read_ascii_file(input_file: str | Path, **kwargs)[source]

Read Richard Ray’s Global Ocean Tide (GOT) model file

Parameters:

input_file: str or pathlib.Path: Model file
compressed: bool, default False: Input file is gzip compressed

Returns:

hc: np.ndarray: complex form of tidal constituent oscillation
lon: np.ndarray: longitude of tidal model
lat: np.ndarray: latitude of tidal model
cons: str: tidal constituent ID

pyTMD.io.GOT.read_netcdf_file(input_file: str | Path, **kwargs)[source]

Read Richard Ray’s Global Ocean Tide (GOT) netCDF4 model file

Parameters:

input_file: str or pathlib.Path: model file
compressed: bool, default False: Input file is gzip compressed

Returns:

hc: np.ndarray: complex form of tidal constituent oscillation
lon: np.ndarray: longitude of tidal model
lat: np.ndarray: latitude of tidal model
cons: str: tidal constituent ID

pyTMD.io.GOT.output_netcdf_file(FILE: str | Path, hc: ndarray, lon: ndarray, lat: ndarray, constituent: str)[source]

Writes tidal constituents to netCDF4 files in GOT format

Parameters:

FILE: str or pathlib.Path: output GOT model file name
hc: np.ndarray: Eulerian form of tidal constituent
lon: np.ndarray: longitude coordinates
lat: np.ndarray: latitude coordinates
constituent: str: tidal constituent ID

pyTMD.io.GOT._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.GOT._extend_matrix(input_matrix: ndarray)[source]

Extends a global matrix

Parameters:

input_matrix: np.ndarray: matrix to extend

Returns:

temp: np.ndarray: extended matrix

pyTMD.io.GOT._crop(input_matrix: ndarray, ilon: ndarray, ilat: ndarray, bounds: list | tuple, buffer: int | float = 0)[source]

Crop tide model data to bounds

Parameters:

input_matrix: np.ndarray: matrix to crop
ilon: np.ndarray: longitude of tidal model
ilat: np.ndarray: latitude of tidal model
bounds: list, tuple: bounding box: [xmin, xmax, ymin, ymax]
buffer: int or float, default 0: buffer to add to bounds for cropping

Returns:

temp: np.ndarray: cropped matrix
lon: np.ndarray: cropped longitude
lat: np.ndarray: cropped latitude

pyTMD.io.GOT._shift(input_matrix: ndarray, ilon: ndarray, lon0: int | float = 180, cyclic: int | float = 360, direction: str = 'west')[source]

Shift global grid east or west to a new base longitude

Parameters:

input_matrix: np.ndarray

input matrix to shift

ilon: np.ndarray

longitude of tidal model

lon0: int or float, default 180

Starting longitude for shifted grid

cyclic: int or float, default 360

width of periodic domain

direction: str, default ‘west’

Direction to shift grid

'west'

'east'

Returns:

temp: np.ndarray: shifted matrix
lon: np.ndarray: shifted longitude