User API

Routines

GeoCAT-comp native routines

geocat.comp.climatologies.anomaly(dset, freq)

Compute anomalies for a specified time frequency.

geocat.comp.climatologies.calendar_average(...)

This function divides the data into time periods (months, seasons, etc) and computes the average for the data in each one.

geocat.comp.climatologies.climatology(dset, freq)

Compute climatologies for a specified time frequency.

geocat.comp.climatologies.climatology_average(...)

This function calculates long term hourly, daily, monthly, or seasonal averages across all years in the given dataset.

geocat.comp.climatologies.month_to_season(...)

Computes a user-specified three-month seasonal mean.

geocat.comp.crop.actual_saturation_vapor_pressure(tdew)

Compute 'actual' saturation vapor pressure [kPa] as described in the Food and Agriculture Organization (FAO) Irrigation and Drainage Paper 56 entitled:

geocat.comp.crop.max_daylight(jday, lat)

Computes maximum number of daylight hours as described in the Food and Agriculture Organization (FAO) Irrigation and Drainage Paper 56 entitled:

geocat.comp.crop.psychrometric_constant(pressure)

Compute psychrometric constant [kPa / C] as described in the Food and Agriculture Organization (FAO) Irrigation and Drainage Paper 56 entitled:

geocat.comp.crop.saturation_vapor_pressure(...)

Compute saturation vapor pressure as described in the Food and Agriculture Organization (FAO) Irrigation and Drainage Paper 56 entitled:

geocat.comp.crop.saturation_vapor_pressure_slope(...)

Compute the slope [kPa/C] of saturation vapor pressure curve as described in the Food and Agriculture Organization (FAO) Irrigation and Drainage Paper 56 entitled:

geocat.comp.eofunc.eofunc_eofs(data[, ...])

Computes empirical orthogonal functions (EOFs, aka: Principal Component Analysis).

geocat.comp.eofunc.eofunc_pcs(data[, npcs, ...])

Computes the principal components (time projection) in the empirical orthogonal function analysis.

geocat.comp.fourier_filters.fourier_band_block(...)

Filter a dataset by frequency.

geocat.comp.fourier_filters.fourier_band_pass(...)

Filter a dataset by frequency.

geocat.comp.fourier_filters.fourier_filter(...)

Filter a dataset by frequency.

geocat.comp.fourier_filters.fourier_low_pass(...)

Filter a dataset by frequency.

geocat.comp.fourier_filters.fourier_high_pass(...)

Filter a dataset by frequency.

geocat.comp.interpolation.interp_hybrid_to_pressure(...)

Interpolate data from hybrid-sigma levels to isobaric levels.

geocat.comp.interpolation.interp_sigma_to_hybrid(...)

Interpolate data from sigma to hybrid coordinates.

geocat.comp.meteorology.dewtemp(temperature, ...)

This function calculates the dew point temperature given temperature and relative humidity using equations from John Dutton's "Ceaseless Wind" (pp 273-274)

geocat.comp.meteorology.heat_index(...[, ...])

Compute the 'heat index' as calculated by the National Weather Service.

geocat.comp.meteorology.relhum(temperature, ...)

This function calculates the relative humidity given temperature, mixing ratio, and pressure.

geocat.comp.meteorology.relhum_ice(...)

Calculates relative humidity with respect to ice, given temperature, mixing ratio, and pressure.

geocat.comp.meteorology.relhum_water(...)

Calculates relative humidity with respect to water, given temperature, mixing ratio, and pressure.

geocat.comp.polynomial.detrend(data[, deg, axis])

Estimates and removes the trend of the leftmost dimension from all grid points.

geocat.comp.polynomial.ndpolyfit(x, y, deg)

An extension to numpy.polyfit function to support multi-dimensional arrays, Dask arrays, and missing values.

geocat.comp.polynomial.ndpolyval(p, x[, axis])

Extended version of numpy.polyval to support multi-dimensional outputs provided by geocat.comp.ndpolyfit.

geocat.comp.skewt_params.get_skewt_vars(p, ...)

This function processes the dataset values and returns a string element which can be used as a subtitle to replicate the styles of NCL Skew-T Diagrams.

geocat.comp.skewt_params.showalter_index(...)

Calculate Showalter Index from pressure temperature and 850 hPa lcl.

geocat.comp.spherical.decomposition(data, ...)

Calculate the spherical harmonics of a dataset.

geocat.comp.spherical.recomposition(data, ...)

Calculate a dataset from spherical harmonics.

geocat.comp.spherical.scale_voronoi(theta, phi)

Calculate the area weighting for dataset.

GeoCAT-comp routines from GeoCAT-f2py

geocat.comp.dpres_plevel(pressure_levels, ...)

Calculates the pressure layer thicknesses of a constant pressure level coordinate system.

geocat.comp.grid_to_triple(data[, x_in, ...])

Converts a two-dimensional grid with one-dimensional coordinate variables to an array where each grid value is associated with its coordinates.

geocat.comp.linint1(fi, xo[, xi, icycx, msg_py])

Interpolates from one series to another using piecewise linear interpolation across the rightmost dimension.

geocat.comp.linint2(fi, xo, yo[, xi, yi, ...])

Interpolates a regular grid to a rectilinear one using bi-linear interpolation.

geocat.comp.linint2pts(fi, xo, yo[, icycx, ...])

Interpolates from a rectilinear grid to an unstructured grid or locations using bilinear interpolation.

geocat.comp.moc_globe_atl(lat_aux_grid, ...)

Facilitates calculating the meridional overturning circulation for the globe and Atlantic.

geocat.comp.rcm2points(lat2d, lon2d, fi, ...)

Interpolates data on a curvilinear grid (i.e.

geocat.comp.rcm2rgrid(lat2d, lon2d, fi, ...)

Interpolates data on a curvilinear grid (i.e.

geocat.comp.rgrid2rcm(lat1d, lon1d, fi, ...)

Interpolates data on a rectilinear lat/lon grid to a curvilinear grid like those used by the RCM, WRF and NARR models/datasets.

geocat.comp.triple_to_grid(data, x_in, y_in, ...)

Places unstructured (randomly-spaced) data onto the nearest locations of a rectilinear grid.