UTide

Python re-implementation of the Matlab package UTide.

Calculates astronomy seperately from the solve harmonic analysis, so the function solve_m is more efficient for multiple time series with the same time vector. Still in heavy development--everything is subject to change!

Note: the user interface differs from the Matlab version, so consult the Python function docstrings to see how to specify parameters. Some functionality from the Matlab version is not yet available. For more information see:

Codiga, D.L., 2011. Unified Tidal Analysis and Prediction Using the
UTide Matlab Functions. Technical Report 2011-01. Graduate School
of Oceanography, University of Rhode Island, Narragansett, RI.
59pp. ftp://www.po.gso.uri.edu/pub/downloads/codiga/pubs/
2011Codiga-UTide-Report.pdf

UTide v1p0 9/2011 d.codiga@gso.uri.edu
 http://www.po.gso.uri.edu/~codiga/utide/utide.htm

Installation

pip install utide

If you are using conda,

conda install utide -c conda-forge

The public functions can be imported using

from utide import solve, reconstruct

A sample call would be

from utide import solve

coef = solve(time, time_series_u, time_series_v,
             lat=30,
             nodal=False,
             trend=False,
             method='ols',
             conf_int='linear',
             Rayleigh_min=0.95,)

if use model data you can doing this to speed up the calculation

from utide import solve_m

def benchmark_solve(t, ssh, repeat=10):

out = None for _ in range(repeat):

out = ut.solve(

t, ssh, lat=LATITUDE, method="ols", conf_int="none", constit=CONSTITUENTS, order_constit="frequency", trend=False, nodal=True, verbose=False

)

return out

def benchmark_solve_m(t, ssh, out1, repeat=10):

F,U,V = FUV(_normalize_time(t, None), out1["aux"]["reftime"], out1["aux"]["lind"], 30.0, [1, 0, False, False]) fuv_cache = (F, U, V, out1["aux"]["lind"]) freqs = linearized_freqs(out1["aux"]["reftime"]) for _ in range(repeat):

out = ut.solve_m(

t, ssh, lat=LATITUDE, method="ols", conf_int="none", constit=CONSTITUENTS, order_constit="frequency", fuv_cache=fuv_cache, freqs=freqs, trend=False, nodal=True, verbose=False

)

return out

For more examples see the notebooks folder.