footprintinit

Purpose

Batch-run ISIS footprintinit on all cubes in a list file, with parallel execution for speed.

This is needed because spiceinit wipes the Polygon blob from cube files. If you re-run spiceinit (e.g., after jigsaw update=True), you must re-run footprintinit before any tool that reads footprints (findimageoverlaps, isistools footprints, etc.).

Usage

# Default: 4 parallel workers
isistools footprintinit cubes.lis

# 8 parallel workers
isistools footprintinit cubes.lis -j 8

# Single-threaded
isistools footprintinit cubes.lis -j 1

Options

Option	Default	Description
--jobs, -j	4	Number of parallel workers

Example output

Running footprintinit on 11 cubes (8 workers)...
  OK: K05_055343_1840_XI_04N287W.lev1.cub
  OK: V05_082075_1840_XN_04N287W.lev1.cub
  OK: B08_012740_1840_XN_04N287W.lev1.cub
  ...

All 11 cubes done.

When to use

A typical ISIS coregistration pipeline should include footprintinit after every spiceinit:

spiceinit → footprintinit → findimageoverlaps → autoseed → pointreg → jigsaw

If jigsaw is run with update=True, the SPICE blobs are rewritten. Before generating new Level 2 products or re-running the tie point pipeline, run footprintinit again:

jigsaw (update=True) → footprintinit → cam2map

Why parallel?

Each footprintinit call is an independent ISIS subprocess that reads one cube file. With many cubes, running them sequentially wastes time. The ThreadPoolExecutor parallelism gives near-linear speedup since the work is I/O-bound (reading the cube, computing the footprint polygon, writing back).