Interpolation

QuartiCal is capable of interpolating any gain term which it can solve for. This functionality is readily available and is triggered automatically when gain.load_from is set, e.g. G.load_from=existing/gains.qc/G. QuartiCal will interpolate the on-disk gains to be compatible with the parameters set on the term which is being loaded/interpolated.

Note

Gain types cannot change during interpolation i.e. if the on-disk gain is of type diag_complex, the term must be loaded as type diag_complex. This functionality may be simplified in future.

Example - Interpolate

This example will attempt to make the interpolation behaviour a little more intuitive. Let us assume that we have solved for the bandpass on a calibrator (FIELD_ID==0) using the following basic config:

input_ms:
    path: path/to.ms
    data_column: DATA
    time_chunk: '0'
    freq_chunk: '0'
    select_fields:
        - 0
input_model:
    recipe: MODEL_DATA
solver:
    terms:
        - B
    iter_recipe:
        - 25
output:
    directory: gains.qc
B:
    type: diag_complex
    time_interval: '0'
    freq_interval: '1'

This will write the bandpass solutions (B) to gains.qc/B. We want to transfer these solutions to the target (FIELD_ID==1). That can be accomplished using the following config:

input_ms:
    path: path/to.ms
    data_column: DATA
    time_chunk: '0'
    freq_chunk: '0'
    select_fields:
        - 1
solver:
    terms:
        - B
    iter_recipe:
        - 0
output:
    products:
        - corrected_data
    columns:
        - CORRECTED_DATA
    gain_directory: interp_gains.qc
B:
    type: diag_complex
    time_interval: '0'
    freq_interval: '1'
    load_from: path/to/gains.qc/B

The above config will read the solutions from path/to/gains.qc/B and apply them to the target. Some important points to note:

• It is not possible to read and write gains to the same place, hence specifying a different output.gain_directory.

• We specified zero iterations for B in solver.iter_recipe - this means so additional solver iterations will be performed.

• We utilised the same solution intervals and chunking as in the original bandpass solution - this is not required as gains will be interpolated to higher or lower resolution as required.

• It is possible to load more than one term at the same time.

Example - Interpolate and Solve

Let us assume the same inital solve for the bandpass as above, but instead of simply interpolating and applying the solutions, we also want to refine the solutions on the target field (selfcal). That can be accomplished with the following config:

input_ms:
    path: path/to.ms
    data_column: DATA
    time_chunk: '0'
    freq_chunk: '0'
    select_fields:
        - 1
input_model:
    recipe: MODEL_DATA
solver:
    terms:
        - B
    iter_recipe:
        - 25
output:
    products:
        - corrected_data
    columns:
        - CORRECTED_DATA
    gain_directory: interp_gains.qc
B:
    type: diag_complex
    time_interval: '0'
    freq_interval: '1'
    load_from: path/to/gains.qc/B

Some more things to note:

• It is perfectly possible to specify both load-only and solvable terms in the same config by setting solver.iter_recipe appropriately.

• Loaded terms can be combined with new solvable terms. This enables on-the-fly transfer and selfcal.