astrohack.holog

Module Contents

Functions

holog(holog_name: str, image_name: str = None, grid_size: Union[int, numpy.array, List] = None, cell_size: Union[float, numpy.array, List] = None, padding_factor: int = 10, grid_interpolation_mode: str = 'gaussian', chan_average: bool = True, chan_tolerance_factor: float = 0.005, scan_average: bool = True, alma_osf_pad: str = None, ant: Union[str, List[str]] = 'all', ddi: Union[str, int, List[int]] = 'all', zernike_n_order: int = 4, phase_fit_engine: str = 'perturbations', phase_fit_control: Union[List[bool], Tuple[bool]] = (True, True, True, True, True), to_stokes: bool = True, overwrite: bool = False, parallel: bool = False) → Union[astrohack.io.image_mds.AstrohackImageFile, None]

Process holography data and derive aperture illumination pattern.
holog(holog_name: str, image_name: str = None, grid_size: Union[int, numpy.array, List] = None, cell_size: Union[float, numpy.array, List] = None, padding_factor: int = 10, grid_interpolation_mode: str = 'gaussian', chan_average: bool = True, chan_tolerance_factor: float = 0.005, scan_average: bool = True, alma_osf_pad: str = None, ant: Union[str, List[str]] = 'all', ddi: Union[str, int, List[int]] = 'all', zernike_n_order: int = 4, phase_fit_engine: str = 'perturbations', phase_fit_control: Union[List[bool], Tuple[bool]] = (True, True, True, True, True), to_stokes: bool = True, overwrite: bool = False, parallel: bool = False) → Union[astrohack.io.image_mds.AstrohackImageFile, None][source]

Process holography data and derive aperture illumination pattern.

Parameters

  • holog_name (str) – Name of holography .holog.zarr file to process.

  • image_name (str, optional) – Defines the name of the output image name. If value is None, the name will be set to <base_name>.image.zarr, defaults to None

  • grid_size (numpy.ndarray, dtype int, list optional) – Numpy array specifying the dimensions of the grid used in data gridding. If not specified grid_size is calculated using POINTING_OFFSET in pointing table.

  • cell_size (numpy.ndarray, dtype float, list optional) – Size 2 array defining the cell size of each beam grid bin in radians. If not specified, the used cell_size is the one given in the observation_summary of the input holog file.

  • padding_factor (int, optional) – Padding factor applied to beam grid before computing the fast-fourier transform. The default has been set for operation on most systems. The user should be aware of memory constraints before increasing this parameter significantly., defaults to 10

  • parallel (bool, optional) – Run in parallel with Dask or in serial., defaults to False

  • grid_interpolation_mode (str, optional. Available options: {"gaussian", "linear", "nearest", "cubic"}) – Method of interpolation used when gridding data. For modes ‘linear’, ‘nearest’ and ‘cubic’ this is done using the scipy.interpolate.griddata method. For more information see scipy.interpolate. The remaining mode ‘gaussian’ convolves the visibilities with a gaussian kernel with a FWHM equal HPBW for the primary beam main lobe at the given frequency, this is slower than scipy.interpolate.griddata but better at preserving the small scales variations in the beam. Defaults to “gaussian”.

  • chan_average (bool, optional) – Boolean dictating whether the channel average is computed and written to the output holog file., defaults to True

  • chan_tolerance_factor (float, optional) – Tolerance used in channel averaging to determine the number of primary beam channels., defaults to 0.005

  • scan_average (bool, optional) – Boolean dictating whether averaging is done over scan., defaults to True

  • alma_osf_pad (str, optional) – Pad on which the antenna was poitioned at the ALMA OSF (only relevant for ALMA near field holographies).

  • ant (list or str, optional) – List of antennas/antenna to be processed, defaults to “all” when None, ex. ea25

  • ddi (list or int, optional) – List of ddi to be processed, defaults to “all” when None, ex. 0

  • zernike_n_order (int, optional) – Maximal N order for the Zernike Polynomials to be fitted to the aperture data.

  • phase_fit_engine (str, optional.) – Choose between the two available phase fitting engines, “perturbations” which assumes cassegrain optics and “zernike” which makes no assumption about the optical system but may overfit the aperture phase, default is “perturbations”.

  • phase_fit_control (bool array, optional) –

    Controls which type of optical perturbations are to be fitted when phase_fit_engine is set to “perturbations”.

    Available phase fit controls:

    • [0]: pointing offset;

    • [1]: focus xy offsets;

    • [2]: focus z offset;

    • [3]: subreflector tilt (off by default except for VLA and VLBA)

    • [4]: cassegrain offset

  • to_stokes (bool, optional) – Dictates whether polarization is computed according to stokes values., defaults to True

  • overwrite (bool, optional) – Overwrite existing files on disk, defaults to False

Returns

Holography image object.

Return type

AstrohackImageFile

AstrohackImageFile

Image object allows the user to access image data via compound dictionary keys with values, in order of depth, ant -> ddi. The image object also provides a summary() helper function to list available keys for each file. An outline of the image object structure is show below:

image_mds =
    {
    ant_0:{
        ddi_0: image_ds,
         ⋮
        ddi_m: image_ds
    },
    ⋮
    ant_n: …
}

Example Usage

from astrohack.holog import holog

holog(
    holog_name="astrohack_observation.holog.zarr",
    padding_factor=50,
    grid_interpolation_mode='linear',
    chan_average = True,
    scan_average = True,
    ant='ea25',
    overwrite=True,
    parallel=True
)