User Guide

The functionality of GBKFIT can be accessed through a Command Line Interface (CLI, gbkfit-cli), and soon, through a Graphical User Interface (GUI, gbkfit-gui) as well.

If the functionality provided by those two interfaces is not enough, one can use GBKFIT’s Python API. For more information see the Developer Guide.

The command line interface (gbkfit-cli)

The CLI of GBKFIT can be run using the command gbkfit-cli followed by a positional argument indicating the task the user wants to execute, which in turn is followed by a series of positional and optional arguments specific to that task . There are four available tasks: eval, prep, fit, and plot. The first generates mock models; the second provides a series of pre-processing functions to prepare data for fitting; the third fits models to data; and finally, the fourth creates visualisations for the results of the fit task.

The eval task

To generate a mock model, run:

gbkfit-cli eval config.yaml

The prep task

The fit task

The plot task

The graphical user interface (gbkfit-gui)

Attention

The graphical user interface is not available yet.

The configuration file

JSON.

YAML.

Example

# data model
dmodels:
  type: scube
  size: [101, 101, 101]
  step: [1, 1, 5]
  cval: [0, 0, 0]
  scale: [1, 1, 1]
  psf: {type: gauss, sigma: 2}
  lsf: {type: gauss, sigma: 20}

# galaxy model
gmodels:
  type: kinematics_2d
  components:
    type: smdisk
    rnodes: [0, 50]
    nrnodes: 10
    rnodes_min: 0
    rnodes_max: 50
    rnodes_sep: 10
    rptraits: {type: gauss}
    vptraits: {type: tan_arctan}
    dptraits: {type: uniform}

# parameters
params:
  vsys: 0
  xpos: 0
  ypos: 0
  posa: 45
  incl: 45
  rpt_a: 1
  rpt_s: 30
  rpt_b: 10
  vpt_rt: 10
  vpt_vt: 200
  dpt_a: 10