Settings#

Every prediction call accepts a Settings object that controls the engine type, astronomical formulae, inference method, nodal-correction options, and parallelism.

Two convenience subclasses provide ready-to-use defaults:

FESSettings - Darwin engine defaults (Schureman formulae, spline inference).
PerthSettings - Doodson engine defaults (IERS formulae, linear inference, long-period equilibrium disabled).

All settings classes expose a fluent builder interface, so calls can be chained:

settings = pyfes.FESSettings() \
    .with_num_threads(4) \
    .with_time_tolerance(3600)

class pyfes.Settings#

Settings for the tide computation.

This class provides a builder-style interface for configuring all parameters controlling tide computation, including the harmonic constituent notation system, astronomic angle formulae, inference method, parallelism, and various physical corrections.

property astronomic_formulae#: Astronomic formulae used to calculate the astronomic angles.

property compute_long_period_equilibrium#: Whether to compute the long period equilibrium tide.

property engine_type#: Engine type for the tidal constituent notation system.

property group_modulations#: Whether to use group modulation nodal corrections. Only effective with the Perth WaveTable.

property inference_type#: Inference (admittance) interpolation type.

property num_threads#: Number of threads to use for computation. If 0, the number of threads is automatically determined.

property time_tolerance#: Time in seconds for which astronomical angles are considered constant. A value of 0 means angles are recomputed for every time step.

with_astronomic_formulae(self: pyfes.core.Settings, formulae: pyfes.core.Formulae) → pyfes.core.Settings#

Set the astronomic formulae.

Parameters:: formulae – Astronomic formulae.
Returns:: self

with_compute_long_period_equilibrium(self: pyfes.core.Settings, compute_long_period_equilibrium: bool) → pyfes.core.Settings#

Set whether to compute the long period equilibrium tide.

Parameters:: compute_long_period_equilibrium – If true, computes the long period equilibrium tide.
Returns:: self

with_engine_type(self: pyfes.core.Settings, engine_type: pyfes.core.EngineType) → pyfes.core.Settings#

Set the engine type for the tidal constituent notation system.

Parameters:: engine_type – The engine type.
Returns:: self

with_group_modulations(self: pyfes.core.Settings, group_modulations: bool) → pyfes.core.Settings#

Set whether to use group modulation nodal corrections.

Parameters:: group_modulations – If true, uses group modulation nodal corrections. Only effective with the Perth WaveTable.
Returns:: self

with_inference_type(self: pyfes.core.Settings, inference_type: pyfes.core.InferenceType) → pyfes.core.Settings#

Set the inference interpolation type.

Parameters:: inference_type – The inference interpolation type.
Returns:: self

with_num_threads(self: pyfes.core.Settings, num_threads: SupportsInt) → pyfes.core.Settings#

Set the number of threads to use for computation.

Parameters:: num_threads – Number of threads. If 0, the number of threads is automatically determined.
Returns:: self

with_time_tolerance(self: pyfes.core.Settings, time_tolerance: SupportsFloat) → pyfes.core.Settings#

Set the time tolerance.

Parameters:: time_tolerance – Time tolerance in seconds during which astronomical angles are considered constant.
Returns:: self

class pyfes.FESSettings#

Bases: Settings

Default settings for FES models.

This class provides pre-configured settings optimized for FES tidal models:

Engine type: Darwin
Astronomic formulae: Schureman order 1
Inference type: Spline
Long period equilibrium: enabled
Group modulations: N/A (not effective with the Darwin WaveTable)

class pyfes.PerthSettings#

Bases: Settings

Default settings for GOT/Perth models.

This class provides pre-configured settings optimized for GOT tidal models:

Engine type: Doodson
Astronomic formulae: IERS
Inference type: Linear
Long period equilibrium: disabled
Group modulations: disabled

Settings

Contents

Settings#