fwdbwd.yaml

inputs:
  _include:
    - (.)gridding.yml
    - (.)pdopts.yml
    - (.)pmopts.yml
    - (.)cgopts.yml
    - (.)dist.yml
    - (.)out.yml
  model-name:
    dtype: str
    abbreviation: mname
    default: MODEL
    info: Name of model in mds
  mask:
    dtype: str
    abbreviation: mask
    info: Either path to mask.fits or set to mds to use the mask contained in the
      mds.
  nband:
    dtype: int
    required: true
    abbreviation: nb
    info: Number of imaging bands
  postfix:
    dtype: str
    default: main
    info: Can be used to specify a custom name for the image space data products
  sigmainv:
    dtype: float
    default: 1e-5
    abbreviation: sinv
    info: Standard deviation of assumed GRF prior
  bases:
    dtype: str
    default: self,db1,db2
    abbreviation: bases
    info: Wavelet bases to use. Give as comma separated str eg. 'self,db1,db2'
  nlevels:
    dtype: int
    default: 3
    abbreviation: nlevels
    info: Wavelet decomposition level
  sigma21:
    dtype: float
    abbreviation: sig21
    info: Wavelet thresholding level
  l1reweight-from:
    dtype: int
    default: 5
    info: Start doing l1reweights after this many iterations
  rmsfactor:
    dtype: float
    default: 3.0
    info: By default will threshold by rmsfactor*rms at every iteration
  gamma:
    dtype: float
    default: 0.5
    info: Step size of update
  positivity:
    dtype: int
    default: 1
    # choices:
    #   - 0
    #   - 1
    #   - 2
    info: How to apply positivity constraint 0 -> no positivity, 1 -> normal positivity
      constraint 2 -> strong positivity i.e. all pixels in a band > 0
  niter:
    dtype: int
    default: 5
    info: Number of iterations. L21 reweighting will take place after every iteration
    abbreviation: niter
  tol:
    dtype: float
    default: 1e-5
    info: Tolerance at which to terminate algorithm. Will stop when norm(x-xp)/norm(x)
      < tol
  fits-mfs:
    dtype: bool
    default: true
    info: Output MFS fits files
  fits-cubes:
    dtype: bool
    default: false
    info: Output fits cubes
  memory-greedy:
    dtype: bool
    default: false
    info: Holds data in memory if set
  parametrisation:
    dtype: str
    default: id
    info: The kind of parametrisation to apply
  restart:
    dtype: bool
    default: false
    info: Restart the deconvolution by initialising the model to zero and the residual
      to the dirty image

outputs: {}