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instruments — per-instrument dataset presets

This subpackage owns the per-instrument configuration dicts that drive both the simulators and the profiling cells. Two modules:

  • instruments.imaging — INSTRUMENTS for imaging (hst, jwst, ao, euclid).
  • instruments.interferometer — INSTRUMENTS for interferometer (sma, alma, alma_high, jvla).

Why a separate package?

The INSTRUMENTS dicts used to live inside simulators/imaging.py and simulators/interferometer.py. As the repo grew, multiple consumers ended up reading them:

  • simulators/*.py — drives dataset simulation.
  • likelihood_runtime/{imaging,interferometer,datacube}/*.py — reads pixel_scale, mask_radius, real_space_shape, transformer_chunk_size for setting up the profiling fit.
  • likelihood_breakdown/{imaging,interferometer,datacube}/*.py — same.
  • vram/config.py — uses the instrument keys to index the VMAP_BATCH lookup table.

Splitting the dicts into a dedicated home means:

  • Each consumer imports from one canonical location.
  • Adding a new instrument is one row in one file (plus a probe + a VMAP_BATCH entry).
  • Helpers like mask_radius_pixels(instrument) can centralise math that was previously inlined across multiple files.

Schema

Imaging fields

Field Type Meaning
pixel_scale float arcsec / pixel
mask_radius float arcsec (circular mask)
psf_shape tuple[int, int] PSF kernel shape (n_y, n_x)
psf_sigma float Gaussian PSF width (arcsec)
seed int RNG seed for noise generation

Interferometer fields

Field Type Meaning
pixel_scale float arcsec / pixel
real_space_shape tuple[int, int] (n_y, n_x) real-space image grid
mask_radius float arcsec (circular mask)
n_visibilities int number of (u, v) baselines
uv_scale float RNG sampling scale for (u, v)
noise_sigma float noise per visibility
seed int RNG seed
transformer "dft" or "nufft" transformer class
transformer_chunk_size int or None NUFFT gather-buffer cap

Helpers

  • imaging.mask_radius_pixels(instrument) -> int — mask radius / pixel_scale, rounded.
  • imaging.shape_native(instrument) -> tuple[int, int] — data grid shape derived from mask.
  • interferometer.mask_radius_pixels(instrument) -> int — same math, on interferometer.
  • interferometer.transformer_chunk_size_for(instrument) -> int | None — convenience accessor.

Backward compatibility

The legacy import paths still work:

from simulators.imaging import INSTRUMENTS  # still valid
from simulators.interferometer import INSTRUMENTS  # still valid

These re-export from instruments.{imaging,interferometer} so existing consumers don't have to migrate. New code should prefer from instruments.imaging import INSTRUMENTS.

Adding a new instrument

  1. Add a row to the appropriate INSTRUMENTS dict.
  2. Simulate the dataset by running python simulators/<imaging|interferometer>.py --instrument <name>.
  3. Run a vram/ probe job (see vram/README.md) on the A100.
  4. Add the resulting VMAP_BATCH entry to vram/config.py.
  5. Re-run the regular profile sweep to confirm vmap holds at steady state.