weac.parser.utils.layer_binning module

Group a windowed density profile into WEAC slab layers.

Shared binning helper for the parser package (used by the SMP bin mode and, later, SnowScope / gradient modes). The input is a depth-ordered (surface -> ground) density series; the output is Layer objects in that same top-down order.

Binning model

Each sample owns a “cell” whose thickness is the spacing to the next sample (the native Loewe hop for SMP); the final sample repeats the last spacing so every sample contributes a cell. Layers are contiguous runs of cells, so sum(layer.h) equals the summed cell thickness (times depth_scale).

Thickness (Layer.h) is scaled by depth_scale to convert a plumb probe depth to WEAC’s slope-normal thickness; density (Layer.rho) is the cell-thickness-weighted mean over the run.

weac.parser.utils.layer_binning.bin_profile_to_layers(depth_mm, density_kg_m3, *, layer_thickness_mm=None, min_thickness_mm=1.0, depth_scale=1.0)[source]

Bin a density profile into WEAC slab layers (top-down).

Parameters:

  • depth_mm (ndarray) – Depth-ordered (surface -> ground) sample positions [mm].

  • density_kg_m3 (ndarray) – Density at each sample [kg m^-3]; same shape as depth_mm.

  • layer_thickness_mm (float | None) – Target layer thickness. None groups at the native sample spacing (each cell is its own layer) subject to the min_thickness_mm floor; a value groups adjacent cells until each run reaches roughly that thickness.

  • min_thickness_mm (float) – Minimum layer thickness [mm]. Adjacent cells are merged until a run reaches this floor; a trailing remainder below the floor is folded into the previous layer.

  • depth_scale (float) – Plumb -> slope-normal factor applied to every h (cos(phi)); 1.0 leaves thicknesses unscaled.

Returns:

Layers ordered surface -> ground. sum(layer.h) equals the summed cell thickness times depth_scale.

Return type:

list[Layer]