quality_control.quicklook.level4

L4 quicklook plots for KPF cross-correlation functions (CCFs) and RVs.

Ports the per-order CCF grid from the v2.12 AnalyzeL2 class (the old pipeline’s “L2” level is vNext’s L4: CCFs and RVs live in the L4 product). The CCF grid shows, for each illuminated orderlet, every order’s CCF stacked vertically so the per-order consistency of the dip is visible at a glance.

Pure visualization — no science computation is written back to the product.

class kpfpipe.quality_control.quicklook.level4.PlotL4(l4_obj, output_dir=None, obs_id=None)

Bases: object

Quicklook plots for KPF L4 (RVs and CCFs) data.

Parameters:

  • l4_obj – KPF4 data object (post-CrossCorrelation + RadialVelocity).

  • output_dir – directory to save PNG files. None = return Figure only.

  • obs_id – observation ID for titles/filenames. If None, falls back to the l4_obj.obs_id attribute (populated on every construction path).

ccf_grid(chip)

Per-orderlet CCF grid for one chip, matching the v2.12 plot_CCF_grid layout: five panels (SCI1, SCI2, SCI3, CAL, SKY), each order’s CCF normalized and offset, colored by the default cycle and labeled by order index. SCI panels add the combined-RV line + value and per-order delta-RV / weight columns. Returns None if the chip has no CCF data.

run(which)

Generate the requested plot(s) for every chip that has CCF data, saving each to output_dir. In that save-to-disk mode the figure is closed so callers don’t accumulate them; when output_dir is None the figures are returned open, so they display when the caller renders them (e.g. interactively in a notebook).

Parameters:

which – ‘all’ to run every implemented plot, or the name of a single plot method (one of self._PLOT_METHODS).

Returns:

dict mapping {method_name}_{chip} to matplotlib.Figure (closed only when saved to output_dir; useful for tests/introspection).