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This convenience wrapper is intentionally bar-specific. By default it derives a photometric in-plane bar-angle prior from the white-light image; supplying `bar_phi_deg` overrides that estimate. It never substitutes the disc position angle for a bar angle. For an ordinary rotation model, use [run_kinematic_analysis()] with its axisymmetric default.

Usage

run_manga_bar_model(
  cube_path,
  redshift = NA_real_,
  emission_line = "halpha",
  segmentation_mode = c("kinematic", "path_signature"),
  bar_phi_deg = NA_real_,
  output_dir = NULL,
  object_id = NULL,
  knn_k = 50,
  n_segments = 25,
  n_path_segments = 45,
  support_mode = c("starlet", "line_flux"),
  line_flux_sigma = 3,
  model_control = list(),
  show_plots = interactive()
)

Arguments

cube_path

Path to an IFU FITS cube.

redshift

Redshift. Leave as `NA` for a MaNGA cube with local metadata.

emission_line

Emission-line alias, such as `"halpha"` or `"oiii5007"`.

segmentation_mode

`"kinematic"` for line-map features or `"path_signature"` to also compute path-signature regions.

bar_phi_deg

Optional manual in-plane bar angle in degrees relative to the disc major axis. Leave as `NA` to estimate it from white light.

output_dir

Directory for saved products. Defaults beside the cube.

object_id

Optional output identifier.

knn_k

kNN graph size for kinematic clustering.

n_segments

Number of kinematic-aware segments.

n_path_segments

Number of path-signature segments.

support_mode

Foreground support for the kinematic maps. `"starlet"` keeps the white-light starlet footprint; `"line_flux"` trims it with a robust emission-line-flux threshold.

line_flux_sigma

Border-noise threshold, in robust sigma units, for `"line_flux"` support.

model_control

Named list of model controls. For a bar model, `bar_phi_deg` is an optional manual in-plane prior; when omitted, Capivara estimates it from the inner white-light elongation. See [kinematic_models()] for available modules.

show_plots

Print figures as they are generated.

Value

A `capivara_kinematic_result` with the bisymmetric model and its component decomposition.