FREQCOR_LUT_CF.FREQCOR_LUT_CF

FREQCOR_LUT_CF.FREQCOR_LUT_CF(Icos_CF, nspec, sts, gss, WS, Zeta, WD, meteo_df, LUT_cof, classnum, classnumCF, nfreq, freq, freqn, sps, tf_sonic, tf_peltola, outputpath, plot, massman_coef, run_tag)[source]

Build the correction factor (CF) look-up table.

For each half-hourly cospectrum, the routine retrieves cut-off frequencies from LUT_cof, builds transfer functions (Lorentz/Gauss, optionally Peltola form), computes correction factors via numerical integration, then aggregates them into a LUT sorted by a first variable (wind direction for CO2 or relative humidity for H2O) and by wind speed classes.

CF LUT uncertainties: - unc_*_tf: transfer-function-related uncertainty component, computed as the

maximum deviation from the central CF value (“M”) within each WS class.

  • unc_*_sd: within-class spread of CF values, computed as the standard deviation of CF values after outlier removal.

Total uncertainties are not produced; users can recompute them from the component uncertainties if needed.

Parameters:

  • Icos_CF (pandas.DataFrame) – Cospectra used for CF computation.

  • nspec (int) – Number of total initial valid (co)spectra files.

  • sts (int) – Stability class selector (1: unstable, 2: stable).

  • gss (int) – Gas species selector.

  • WS (pandas.Series) – Wind speed, stability parameter, and wind direction time series.

  • Zeta (pandas.Series) – Wind speed, stability parameter, and wind direction time series.

  • WD (pandas.Series) – Wind speed, stability parameter, and wind direction time series.

  • meteo_df (pandas.DataFrame) – Half-hourly meteorological and flux data (used for RH when gss == 2).

  • LUT_cof (dict) – Cut-off frequency look-up table.

  • classnum (int) – Number of wind speed classes used for cut-off frequency LUT construction.

  • classnumCF (int) – Number of wind speed classes used for CF LUT construction.

  • nfreq (int) – Number of frequency bins.

  • freq (pandas.Series) – Natural frequencies (Hz).

  • freqn (pandas.DataFrame) – Normalized frequencies per time step.

  • sps (int) – Approach selector (cospectral or spectral).

  • tf_sonic (int) – If 1, apply theoretical correction to sonic cospectra.

  • tf_peltola (int) – If 1, use the Peltola et al. (2021) transfer function form where applicable.

  • outputpath (str) – Output directory.

  • plot (list[int]) – Plotting options selector.

  • massman_coef (array-like) – Massman coefficients for the site (e.g., [A0, kf0, mu]).

  • run_tag (str) – Run identifier used to generate output filenames.

Returns:

  • LUT_CF (dict) – Correction factor look-up table.

  • matsortCF (pandas.DataFrame) – Sorting matrix with meteorology and correction factors (after filtering missing values).

  • classize_ws (int) – Number of (co)spectra used per wind speed class in the LUT.

Raises: