plower package#

Submodules#

plower.common module#

This file contains general functions used by other functions

plower.common.add_logpath(logger, log_file_prefix, log_dir='logs', **kwargs)[source]#

Update Logger with log file path.

Here the log file has date and time as suffix.

Parameters

  • logger (loguru.logger) – logger object

  • log_dir (str or Path, optional) – Directory of the log file, default is “log”

  • log_file_prefix (str) – Prefix of the log file

plower.common.count(iterable)[source]#

Count the number of items that iterable yields. Equivalent to the expression len(iterable)

Author: Wouter Bolsterlee

Parameters

iterable (iterable) –

Returns

count

Return type

int

plower.common.get_heading(logger, title, level=0, total_len=79)[source]#

Converts ‘string’ to a heading (‘== string ==’)

Parameters

  • logger (loguru.logger) – logger object

  • title (str) – title string before formatting

  • level (int, optional) – Heading type ranging from 0 to 2, by default 0

  • total_len (int, optional) – Maximum desired length of heading, by default 79

Returns

Outputs logger.info(string)

Return type

logger.info

plower.common.xml2dict(xml, *args, **kwargs)[source]#

Converts xml of list element to dict of list

plower.common.xrmax(dataset, full_dataset=None)[source]#

Return maxima of the dataset with all coordinates

Parameters

  • dataset (scalar, array, Variable, DataArray or Dataset) – dataset

  • full_dataset (scalar, array, Variable, DataArray or Dataset, optional) – superset of the dataset, by default dataset

Returns

dataset_maxima – maxima of the dataset

Return type

float

plower.imports module#

Imports the NDBC data and converts to pandas.DataFrame and perform statistics.

plower.imports.get_ndbc_buoy_details(station_id)[source]#

Returns buoy details from the NDBC website.

The details are taken from the https://www.ndbc.noaa.gov/metadata/stationmetadata.xml

Parameters

station_id (str or iterable) – Buoy station ID (5 lettered ID may contains numbers or alphabet).

Returns

station_dbs – Details of the NDBC buoy.

Return type

List of dict

plower.imports.get_ndbc_db_url(station_id, year)[source]#

Return URL to the NDBC database of the buoy.

Parameters

  • station_id (str) – Buoy station ID (5 lettered ID may contains numbers or alphabet).

  • year (int) – year of the database

Returns

ndbc_db_url – URL to the NDBC database of the buoy

Return type

str

plower.imports.get_ndbc_df(path, tp_range=(0, 24), hs_range=(0, 10), additional_data_names=[])[source]#

Return the NDBC buoy data for a range of peak period (tp) and significant height (hs). The description of data is available at https://www.ndbc.noaa.gov/measdes.shtml.

Parameters

  • path (str) – URL of an year NDBC buoy database

  • tp_range (tuple, optional) – Minimum and Maximum of peak periods, by default (0,21)

  • hs_range (tuple, optional) – Minimum and Maximum of significant heights, by default (0,10)

  • additional_data_names (iterable) – Names of the data to include in output apart from (“DPD”, “WVHT”, “MWD”). The data names details are available at https://www.ndbc.noaa.gov/measdes.shtml.

Returns

buoy_db – Dataframe of an year NDBC buoy database. By default returns (“DPD”, “WVHT”, “MWD”).

Return type

pandas.DataFrame

Notes

The default tp and hs ranges are choosen according to SAM software https://sam.nrel.gov/marine-energy.html

plower.imports.get_probability_of_occurrence(station_id, year_range=range(2011, 2021), tp2te=0.892, hs_edges=array([0., 0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5, 8., 8.5, 9., 9.5, 10.]), dir_edges=array([- 180, - 160, - 140, - 120, - 100, - 80, - 60, - 40, - 20, 0, 20, 40, 60, 80, 100, 120, 140, 160, 180]), te_edges=array([0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21.]), norm_factor=1.0)[source]#

Return probability of occurrence for a ocean wave data at a buoy location.

Parameters

  • station_id (str) – Buoy station ID (5 lettered ID may contains numbers or alphabet).

  • tp2te (float, optional) – Conversion factor from peak peroid to energy period. The default is 0.892.

  • year_range (iterable, optional) – Range of year for the database selection. The default is range(2011,2021).

  • hs_edges (np.ndarray, optional) – Array of significant heights. The default is np.arange(0,10.5,0.5).

  • dir_edges (np.ndarray, optional) – Array of mean directions. The default is np.arange(-180,200,20).

  • te_edges (np.ndarray, optional) – Array of energy periods. The default is np.arange(0.0,22.0,1.0).

  • sam_wave_res_path (str or pathlib.Path, optional) – Path of the SAM wave resource datafile. The default is None.

  • norm_factor (float, optional) – Histogram is normalized such that the sum of the histograms is norm_factor. The default is 1.0.

Returns

te_hs_dir_hist – Histogram of energy period, significant height and mean direction. Note: te_hs_dir_hist is normalized to the

Return type

np.ndarray

plower.imports.get_sam_dataset()[source]#

Returns a sample significant height, energy period and mean direction ranges based on the SAM model wave resource ranges. https://sam.nrel.gov/marine-energy.html

plower.wave_spectrum module#

This file contains functions to compute wave spectrums

plower.wave_spectrum.get_2n_cosine_spread(rel_dir, n)[source]#

Cosine 2l-power type directional spreading function.

Parameters

  • rel_dir (scalar, array, Variable, DataArray or Dataset) – Relative direction with the mean direction.

  • n (scalar, array, Variable, DataArray or Dataset) – Cosine power.

Returns

spread – Directional spreading.

Return type

scalar, array, Variable, DataArray or Dataset

plower.wave_spectrum.get_2n_half_cosine_spread(rel_dir, n=1)[source]#

Half cosine 2l-power type directional spreading function.

Parameters

  • rel_dir (scalar, array, Variable, DataArray or Dataset) – Relative direction with the mean direction.

  • n (scalar, array, Variable, DataArray or Dataset) – Spreading Parameter.

Returns

spread – Directional spreading.

Return type

scalar, array, Variable, DataArray or Dataset

References

Yoshimi Goda (1999) A Comparative Review on the Functional Forms of Directional Wave Spectrum, Coastal Engineering Journal, 41:1, 1-20, DOI: https://doi.org/10.1142/S0578563499000024

plower.wave_spectrum.get_avail_power_simple(hs, tp, density=1000, g=9.80665, kh=inf, tp2te=0.8)[source]#

Compute the Available Power in the ocean waves with respect to significant height and wave period

Parameters

  • hs (scalar, array, Variable, DataArray or Dataset) – ignificant Height.

  • tp (scalar, array, Variable, DataArray or Dataset) – Peak Peroid.

  • density (scalar, optional) – Water Density (kg/m^3). The default is 1000.

  • g (scalar, optional) – Gravity. The default is 9.80665.

  • kh (scalar, optional) – wave number to depth ratio. The default is np.inf (deep water).

Returns

avail_power – Available Power in the ocean wave spectrum.

Return type

scalar, array, Variable, DataArray or Dataset

References

Pecher, A., & Kofoed, J. P. (2017). Handbook of ocean wave energy. Springer Nature. pg. 59

plower.wave_spectrum.get_jonswap_coef(hs, tp, gamma, coef_type='abs')[source]#

Compute the Coefficient of JONSWAP Spectrum.

Parameters

  • hs (scalar, array, Variable, DataArray or Dataset) – Significant Height.

  • tp (scalar, array, Variable, DataArray or Dataset) – Peak Period.

  • gamma (scalar, array, Variable, DataArray or Dataset) – Peak Enchancement Factor.

Returns

jonswap_coef – Coefficient of JONSWAP Spectrum.

Return type

scalar, array, Variable, DataArray or Dataset

plower.wave_spectrum.get_jonswap_spectrum(hs, tp, omega, gamma, coef_type='goda')[source]#

Compute the JONSWAP Spectrum.

Parameters

  • hs (scalar, array, Variable, DataArray or Dataset) – Significant Height.

  • tp (scalar, array, Variable, DataArray or Dataset) – Peak Period.

  • omega (scalar, array, Variable, DataArray or Dataset) – Frequency (rad/s).

  • gamma (scalar, array, Variable, DataArray or Dataset) – Peak Enchancement Factor.

Returns

jonswap_spectrum – JONSWAP Spectrum.

Return type

scalar, array, Variable, DataArray or Dataset

References

Jensen, J. J. (2001). Load and global response of ships. Elsevier.

plower.wave_spectrum.get_jonswap_unit_spectrum(norm_omega, gamma)[source]#

Compute the proportional term of JONSWAP Spectrum.

Parameters

  • norm_omega (scalar, array, Variable, DataArray or Dataset) – Frequency normalized with spectrum peak frequency.

  • gamma (scalar, array, Variable, DataArray or Dataset) – Peak Enchancement Factor.

Returns

jonswap_unit_spectrum – Proportional term of JONSWAP Spectrum.

Return type

scalar, array, Variable, DataArray or Dataset

plower.wave_spectrum.get_mitsuyasu_spread(rel_dir, wave_dir_name, smax=12.5, spectrum_type='PM', gamma=1.0)[source]#

Compute the Mitsuyasu directional unnormalized spreading function.

Parameters

  • rel_dir (scalar, array, Variable, DataArray or Dataset) – Relative direction with the mean direction.

  • smax (float, optional) – Maximum spread parameter. The default is 10.

  • spectrum ({"PM", "JONSWAP"}, optional) – spectrum type. The default is “PM”.

Returns

unit_spread – unnormalized spread function.

Return type

scalar, array, Variable, DataArray or Dataset

plower.wave_spectrum.get_pm_coef(hs, tp)[source]#

Compute the Coefficient of Pierson-Moskowitz Spectrum.

Parameters

  • hs (scalar, array, Variable, DataArray or Dataset) – Significant Height.

  • tp (scalar, array, Variable, DataArray or Dataset) – Peak Period.

Returns

pm_coef – Coefficient of Pierson-Moskowitz Spectrum.

Return type

scalar, array, Variable, DataArray or Dataset

plower.wave_spectrum.get_pm_spectrum(hs, tp, omega)[source]#

Compute the Pierson-Moskowitz Spectrum.

Parameters

  • hs (scalar, array, Variable, DataArray or Dataset) – Significant Height.

  • tp (scalar, array, Variable, DataArray or Dataset) – Peak Period.

  • omega (scalar, array, Variable, DataArray or Dataset) – Frequency (rad/s).

Returns

pm_spectrum – Pierson-Moskowitz Spectrum.

Return type

scalar, array, Variable, DataArray or Dataset

References

Jensen, J. J. (2001). Load and global response of ships. Elsevier.

plower.wave_spectrum.get_pm_spectrum_te(hs, te, omega)[source]#

Compute the Pierson-Moskowitz Spectrum.

Parameters

  • hs (scalar, array, Variable, DataArray or Dataset) – Significant Height.

  • tpe (scalar, array, Variable, DataArray or Dataset) – Energy Period.

  • omega (scalar, array, Variable, DataArray or Dataset) – Frequency (rad/s).

Returns

pm_spectrum – Pierson-Moskowitz Spectrum.

Return type

scalar, array, Variable, DataArray or Dataset

References

Jensen, J. J. (2001). Load and global response of ships. Elsevier.

plower.wave_spectrum.get_pm_unit_spectrum(norm_omega)[source]#

Compute the proportional term of Pierson-Moskowitz Spectrum.

Parameters

norm_omega (scalar, array, Variable, DataArray or Dataset) – Frequency normalized with spectrum peak frequency.

Returns

pm_unit_spectrum – Proportional term of Pierson-Moskowitz Spectrum.

Return type

scalar, array, Variable, DataArray or Dataset

plower.wave_spectrum.get_rel_dir(mean_dir, wave_dir)[source]#

Relative direction with the mean direction.

Parameters

  • mean_dir (scalar, Variable, DataArray or Dataset) – Mean wave direction.

  • wave_dir (scalar, Variable, DataArray or Dataset) – Wave direction.

Returns

rel_dir_sym – Relative direction with the mean direction ranging from 0 to pi.

Return type

scalar, array, Variable, DataArray or Dataset

Note

Input mean_dir and wave_dir as xarray variables for boardcasting mean_dir array and wave_dir array to a 2D rel_dir.

plower.wave_spectrum.get_spread_parameter(norm_omega, smax)[source]#

Compute the spread parameter.

Parameters

  • norm_omega (scalar, array, Variable, DataArray or Dataset) – Frequency normalized with spectrum peak frequency.

  • smax (scalar, array, Variable, DataArray or Dataset) – Maximum spread parameter.

Returns

spread_parameter – Spread parameter.

Return type

scalar, array, Variable, DataArray or Dataset

Note

Input norm_omega and smax as xarray variables for boardcasting.

References

Mitsuyasu, Hisashi, et al. “Observations of the directional spectrum of ocean WavesUsing a cloverleaf buoy.” Journal of Physical Oceanography 5.4 (1975): 750-760.

plower.wave_spectrum.get_wraped_normal_spread(rel_dir, std=10)[source]#

Wrapped-normal directional spreading function.

Parameters

  • rel_dir (scalar, array, Variable, DataArray or Dataset) – Relative direction with the mean direction.

  • std (scalar, array, Variable, DataArray or Dataset) – Cosine power.

Returns

spread – Directional spreading.

Return type

scalar, array, Variable, DataArray or Dataset

Module contents#