pencil.ism_dyn.get_stats
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
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xvar: array 1D.ravel() format of variable |
Module Contents
- pencil.ism_dyn.get_stats.derive_stats(sim_path, src, dst, stat_keys=['Rm', 'uu', 'Ms'], par=[], comm=None, overwrite=False, rank=0, size=1, nghost=3, status='a', chunksize=1000.0, quiet=True, nmin=32, lmask=False, mask_key='hot')
- pencil.ism_dyn.get_stats.plot_hist2d(xvar, yvar, par=[], xlim=None, ylim=None, xbins=100, ybins=100, figsize=[3.5 * 1.61803, 3.5], xlabel='$x$', ylabel='$y$', clabel='${\\cal P}\\,(\\log\\,x,\\log\\,y)$', norm=None, cmap=None, density=True, pad=0.02, fontsize=14)
xvar: array 1D.ravel() format of variable yvar: array length and format matching xvar of complementary variable par: Param object containing simulation parameters xlim: tuple with min & max bin values for xvar ylim: tuple with min & max bin values for yvar xbins: number of bins for xvar histogram ybins: number of bins for yvar histogram figsize: list of length 2 floats with width and height of figure ylabel: plot y-axis label string xlabel: plot x-axis label string clabel: plot colorbar label string norm: color table normalization from colors cmap: color table density: normalize histogram integral to 1 for PDF fontsize: size of plot fonts