CLI Entry Points (Callables)¶

All CLI commands are registered as entry points in pyproject.toml and become available as shell commands after the package is installed. Each command wraps a single Python function; click on the function name to see its full documentation.

Workflow Management¶

Command	Python function	Description
`dataflow`	`dataflow()`	Top-level CLI for installing software and executing commands inside the data-production environment (supports `install` and `exec` sub-commands).
`build-filedb`	`build_filedb()`	Scan a directory of raw LH5 files and build a `FileDB` with per-file first timestamps.

Data Tier Building¶

Command	Python function	Description
`build-tier-dsp`	`build_tier_dsp()`	Build the DSP tier for all channels in a run file; supports multiprocessing.
`build-tier-dsp-single-channel`	`build_tier_dsp_single_channel()`	Build the DSP tier for a single detector channel.
`build-tier-hit`	`build_tier_hit()`	Build the HIT tier for all channels from DSP output.
`build-tier-hit-single-channel`	`build_tier_hit_single_channel()`	Build the HIT tier for a single detector channel.

DSP Parameter Optimisation (`par-geds-dsp-*`)¶

These scripts are run during the calibration phase to determine optimal digital signal processing parameters for each HPGe detector channel. They are typically executed in the order shown below.

Command	Python function	Description
`par-geds-dsp-pz`	`par_geds_dsp_pz()`	Fit the pole-zero decay constant(s) from waveform tail slopes. Supports single-exponential (`mode: single`) and double-exponential (`mode: double`) models.
`par-geds-dsp-nopt`	`par_geds_dsp_nopt()`	Optimise DSP filter shaping for noise rejection using low-energy baseline events.
`par-geds-dsp-evtsel`	`par_geds_dsp_evtsel()`	Select calibration peak events from raw data files for use by the energy optimiser and DPLMS filter builder.
`par-geds-dsp-eopt`	`par_geds_dsp_eopt()`	Bayesian optimisation of CUSP, ZAC, and trapezoidal filter shaping parameters for best energy resolution.
`par-geds-dsp-dplms`	`par_geds_dsp_dplms()`	Compute DPLMS optimal filter coefficients from FFT baseline and calibration peak data.
`par-geds-dsp-svm-build`	`par_geds_dsp_svm_build()`	Train a Support Vector Machine classifier on discrete wavelet transform features for pulse-shape discrimination.
`par-geds-dsp-svm`	`par_geds_dsp_svm()`	Register a pre-trained SVM model file path in the DSP parameter database.

HIT Parameter Optimisation (`par-geds-hit-*`)¶

These scripts are run after the DSP tier is built to calibrate physics observables at the hit level.

Command	Python function	Description
`par-geds-hit-qc`	`par_geds_hit_qc()`	Derive data-driven quality-cut classifiers from calibration and FFT run data.
`par-geds-hit-ecal`	`par_geds_hit_ecal()`	HPGe energy calibration: peak finding, fitting, and FWHM curve extraction for multiple energy parameters.
`par-geds-hit-aoe`	`par_geds_hit_aoe()`	Calibrate the A/E (current amplitude over energy) pulse-shape discriminant with optional drift-time and energy-dependent corrections.
`par-geds-hit-lq`	`par_geds_hit_lq()`	Calibrate the LQ (late charge) pulse-shape discriminant with DEP-based cut determination.

Typical Invocation¶

Commands are usually invoked by Snakemake rules, but can be called directly for debugging:

$ par-geds-dsp-pz \
    --processing-chain dsp_config.yaml \
    --config-file pz_config.yaml \
    --raw-table-name ch1057600/raw \
    --raw-files /data/raw/run001.lh5 \
    --output-file /output/pz_pars.yaml

$ build-tier-dsp \
    --configs /path/to/configs \
    --datatype cal \
    --timestamp 20230401T000000Z \
    --tier dsp \
    --input /data/raw/run001.lh5 \
    --output /data/dsp/run001.lh5 \
    --n-processes 4