pencil.calc.Gaussian_averages

Derive auxilliary data and other diagnostics from var.h5 file and save to new h5 file

uses:

compute ‘data’ arrays of size [nz,ny,nx] as required store ‘time’ of snapshot compute ‘masks’ for example by temperature phase compute summary statistics ‘stats’ compute ‘structure’ functions as required

Functions

kernel_smooth(sim_path, src, dst[, magic, par, comm, ...])
load_dataset(src, key, lindx, lindy, lindz, nghost)
gauss_3Dsmooth(arr[, sigma, typ, quiet, mode])
smoothed_data(src, dst, key, par, gd, lindx, lindy, ...)

Module Contents

pencil.calc.Gaussian_averages.kernel_smooth(sim_path, src, dst, magic=['meanuu'], par=[], comm=None, gd=[], grp_overwrite=False, overwrite=False, rank=0, size=1, nghost=3, kernel=1.0, status='a', chunksize=1000.0, dtype=np.float64, quiet=True, nmin=32, typ='piecewise', mode=list())

pencil.calc.Gaussian_averages.load_dataset(src, key, lindx, lindy, lindz, nghost)

pencil.calc.Gaussian_averages.gauss_3Dsmooth(arr, sigma=1.0, typ='all', quiet=True, mode=list())

pencil.calc.Gaussian_averages.smoothed_data(src, dst, key, par, gd, lindx, lindy, lindz, nghost, sigma, typ, quiet, mode)