telescope-sim 2.1.1

Composable, config-driven simulation of multi-aperture telescope PSFs, DMs, coronagraphs, and fiber coupling — built on HCIPy.

telescope-sim

Composable, config-driven simulation of multi-aperture telescope PSFs, deformable mirrors, coronagraphs, and fiber coupling — built on HCIPy.

telescope-sim provides a pluggable pipeline of optical stages (aperture, correctors, coronagraph, focal plane, output taps, post-processing), a YAML-driven configuration schema, and a fixture-based regression suite. Users can register their own implementations of any stage without modifying the package.

Status

v2.1.0. The pipeline is wired end-to-end and reproduces 10 reference fixtures spanning segmented/mini-ELF apertures, custom-pupil generators, Zernike-mode DMs, vortex and vector-vortex coronagraphs, angular and physical focal planes, and multi-mode-fiber dual outputs.

What's new since v2.0.0

• Actuator-grid DM — the actuator_grid corrector: an N×N influence-function deformable mirror (gaussian or xinetics actuator shapes) driven by raw per-actuator commands, with DM misalignment (rotation, mirrored command indexing) baked in at construction.
• Atmosphere — pass any HCIPy atmosphere (or any wf→wf callable) as sim.sample(atmos=...). Atmospheres that expose .phase_for(lam) couple automatically into fit-role correctors for cancellation. The reference PSF is atmosphere-free by construction.
• Detector noise — the noisy_detector post-processor wraps HCIPy's NoisyDetector (read noise, dark current, flat-field, photon shot noise) with optional int_phot_flux photometry. Per-sample overrides via sim.sample(output_overrides={...}).
• Extended-source convolution — the convolve_image post-processor convolves the PSF with a caller-supplied scene. Composes with noisy_detector for noisy extended-source imaging.
• Cumulative-OPD fit-role correctors — wavefront_role="fit" with fit_source="cumulative_phase_pre_self" lets a DM auto-fit any upstream disturbance (atmosphere, imposed PTT, …) without bespoke wiring.
• Strehl methods — strehl_method: peak | matched_filter, with the matched-filter variant using a circular core mask of radius strehl_core_rad.
• Extension tutorial — docs/tutorials/05_custom_components.ipynb walks through writing your own Corrector and PostProcessor via the @register(...) registry.

Quick start

from telescope_sim import TelescopeSim
import numpy as np

# Bundled preset (mini-ELF, 15 segments, 2 filters)
sim = TelescopeSim.from_preset("elf_15seg")

# Or a custom YAML
sim = TelescopeSim.from_yaml("path/to/config.yaml")

# Sample at rest with Strehl ratios
out = sim.sample(meas_strehl=True)
out["images"]["psf"]      # (H, W, n_filters)
out["strehls"]            # {filter_name: ratio}

# Apply per-segment piston/tip/tilt actuations
ptt = np.random.normal(scale=0.1, size=(15, 3))
out = sim.sample(actuations={"segments": ptt}, meas_strehl=True)

See docs/tutorials/ for runnable notebooks that exercise the canonical mini-ELF, vortex coronagraph, custom-pupil + Zernike DM, and fiber MMF paths.

Architecture

The pipeline is a linear chain of pupil-plane stages (aperture → correctors → optional coronagraph) followed by a controlled fan-out at the pupil → focal boundary, where one or more named focal planes consume the same pupil-plane wavefront. Each focal plane feeds one or more OutputTaps, whose outputs flow through ordered post-processors. Every stage is a registered, pluggable implementation of a small ABC. Configs are YAML, validated by pydantic v2.

[aperture] → [correctors: c1 → c2 → ... → cN] → [coronagraph?]
                                                    │
                                       ┌────────────┼────────────┐
                                       ▼            ▼            ▼
                                  focal plane  focal plane   focal plane
                                       │            │            │
                                     tap(s)       tap(s)       tap(s)
                                       │            │            │
                                    post-proc    post-proc    post-proc

Corrector roles (actuate / impose / fit plus a target_strategy) express the patterns observed across years of research code: model-driven DMs, imposed atmospheres, fit-residual training targets, and stacked combinations of those. See docs/concepts.rst for the full discussion.

Development

# Create dev environment
conda env create -f envs/env-dev.yaml
conda activate telescope-sim-dev

# If pip discovers a sibling hcipy/ clone (developers often keep one in
# ../external/hcipy/ for cross-reference), force-replace with the PyPI build:
pip uninstall -y hcipy && pip install "hcipy>=0.6"

# Install editable with dev extras
pip install -e ".[dev,doc]"

# Run tests
pytest                  # fast tests only
pytest --runslow        # includes the full fixture regression suite

# Build docs
cd docs && make html

See CONTRIBUTING.md for the full development workflow.

License

MIT — see LICENSE.