kpic_pipeline reduces data taken with the Keck Planet Imager and Characterizer (KPIC). Written in Python, the code processes high resolution spectroscopy data taken with KPIC to study exoplanet atmospheres; it processes and calibrate the data to enable spectroscopic model fitting. kpic_pipeline can reduce the observed data into 1D spectra for one given science target or can be used to reduce the full nightly data.

APPLESOSS (A Producer of ProfiLEs for SOSS) builds 2D spatial profiles for the first, second, and third diffraction orders for a NIRISS/SOSS GR700XD/CLEAR observation. The profiles are entirely data driven, retain a high level of fidelity to the original observations, and can be used as the specprofile reference file for ATOCA (ascl:2502.016). They can also be used as a PSF weighting for optimal extractions.

ATOCA (Algorithm to Treat Order Contamination) extracts and decontaminates spectroscopic images with multiple sources or diffraction orders. For all orders and sources, the package takes the wavelength solutions, the trace profiles, the throughputs, and the spectral resolution kernels as input. From these, ATOCA simultaneously models the detector and extracts the spectra.

SolAster provides querying, analysis, and calculation methods to independently derive 'sun-as-a-star' RV variations using SDO/HMI data for any time span since SDO has begun observing. Scaling factors are provided in order to calculate RVs comparable to magnitudes measured by ground-based spectrographs (HARPS-N and NEID). In addition, there are routines to calculate magnetic observables to compare with RV variations and determine what is driving Solar activity.