Synthetic data generation framework

SimCoordinator

class meqsilhouette.framework.SimCoordinator.SimCoordinator(msname, output_column, input_fitsimage, input_fitspol, input_changroups, bandpass_table, bandpass_freq_interp_order, T_rx, corr_eff, predict_oversampling, predict_seed, atm_seed, aperture_eff, elevation_limit, trop_enabled, trop_wetonly, pwv, gpress, gtemp, coherence_time, fixdelay_max_picosec, uvjones_g_on, uvjones_d_on, parang_corrected, gR_mean, gR_std, gL_mean, gL_std, dR_mean, dR_std, dL_mean, dL_std, feed_angle, thermal_noise_enabled)[source]

Bases: object

add_bjones_manual()[source]: Read in the bandpass info from an ASCII table, interpolate (spline) MS frequencies, and apply to data

add_gjones_manual()[source]: Add time-varying station-based complex gains.

add_noise(tropnoise, thermalnoise)[source]

Add sky and receiver noise components to the visibilities and populate weight columns.

Parameters

tropnoisebool: If True, include tropospheric noise.
thermalnoisebool: If True, include receiver noise.

add_pol_leakage_manual()[source]: Add constant-in-time station-based polarization leakage (D-Jones term) that varies with frequency to data. These can be generated in either antenna frame or sky frame.

add_receiver_noise(load=None)[source]

Adds baseline dependent thermal noise to the data.

Parameters

load(bool, optional): If True, loads the thermal noise from a file. Defaults to None.

Raises

MemoryError: If the arrays are too large to be held in memory.

add_weights(additional_noise_terms=None)[source]

Populate SIGMA, SIGMA_SPECTRUM, WEIGHT, WEIGHT_SPECTRUM columns in the MS.

Parameters

additional_noise_terms(ndarray, optional): Additional noise terms to be added to the receiver RMS.

Raises

MemoryError: If the arrays are too large to be held in memory.

apply_phase_errors(combined_phase_errors)[source]

Apply phase errors that have been generated in previous steps to data and save.

Parameters

combined_phase_errorsndarray: The array containing the combined phase errors.

apply_pointing_amp_error()[source]: Apply pointing amplitude errors to data and save.

calc_ant_rise_set_times()[source]: Calculates the rise and set times for each antenna during the course of the observation. These are used to mask out pointing offsets for stowed antennas.

calculate_baseline_mean_elevation()[source]: Calculates the mean elevation for each baseline. Used in plotting uv-coverage.

calculate_baseline_min_elevation()[source]: Calculates the minimum elevation for each baseline. Used in plotting uv-coverage.

compute_receiver_rms()[source]: Populate the RMS receiver noise array. This will be later used to realise thermal noise.

copy_MS(new_name)[source]

Copies a Measurement Set (MS) to a new location.

Parameters

new_namestr: Path to the new Measurement Set.

Raises

Exception: If the copy operation fails for any reason.

elevation_calc()[source]

Calculates and returns the elevation angle.

Returns

elevation_ant_matrixndarray: The computed elevation angle matrix for each antenna during the course of the observation.

Raises

Exception: If the elevation angle cannot be computed for any reason.

interferometric_sim()[source]

Performs an interferometric simulation.

This method checks for the format of the sky model and generates the forward model (i.e. sky to visibilities) using either MeqTrees or WSClean. It also populates the data array which will be used for the rest of the synthetic data generation.

Raises

Exception: If ‘input_fitspol’ is set to True but not all polarisation images are present.

make_bandpass_plots()[source]: Generate plots of bandpass amplitudes and phases vs frequency.

make_baseline_dictionary()[source]

Creates and returns a dictionary of baselines for the current instance.

Returns

dict: A dictionary with all baselines present in the observation.

Raises

Exception: If the baseline dictionary cannot be created for any reason.

make_ms_plots()[source]: uv-coverage, uv-dist sensitivty bins, etc. All by baseline colour

make_pol_plots()[source]: Generate polarization leakage plots.

parallactic_angle_calc()[source]

Calculates and returns the parallactic angle.

Returns

parang_matrixndarray: The computed parallactic angle matrix for each antenna during the course of the observation.

Raises

Exception: If the parallactic angle cannot be computed for any reason.

plot_pointing_errors()[source]: Generate pointing error plots.

pointing_constant_offset(pointing_rms, pointing_timescale, PB_FWHM230)[source]

Compute pointing amplitude offsets.

Parameters

pointing_rmsndarray: The array containing the pointing RMS for each antenna.
pointing_timescalendarray: The timescale over which pointing errors are applied for each antenna.
PB_FWHM230ndarray: The primary beam FWHM at 230 GHz for each antenna.

Notes

Changes the pointing error for each antenna every pointing_timescale which one of could essentially think of as a scan length (e.g. 10 minutes).

save_data()[source]: Saves the contents of data array to the output column specified by the user.

trop_ATM_dispersion()[source]

Calculates extra path length due to mean wet and dry troposphere per frequency channel.

Returns

extra_path_lengthndarray: The calculated extra path length due to mean wet and dry troposphere per frequency channel.

trop_add_sky_noise(load=None)[source]: for non-zero tropospheric opacity, calc sky noise

trop_calc_fixdelay_phase_offsets()[source]: insert constant delay for each station for all time stamps. Used for testing fringe fitters

trop_calc_mean_delays()[source]: Insert mean delays (i.e. non-turbulent) due to mean dry and wet troposphere.

trop_generate_turbulence_phase_errors()[source]

Generates phase offsets/errors due to tropospheric turbulence and save to file.

Returns

None

Raises

Exception: If the turbulence phase errors cannot be generated for any reason.

trop_opacity_attenuate()[source]: Calculates attenuation due to tropospheric opacity and applies to data.

trop_phase_corrupt(normalise=True, percentage_turbulence=100, load=None)[source]: only supports different channels but not different subbands

trop_plots()[source]: Generate plots for tropospheric quantities.

trop_return_opacity_emissivity()[source]

Calculates and returns opacity and sky temperature using the external program AATM.

Returns

opacityndarray: The array containing the wet (and optionally, dry) components of the tropospheric opacity.
emissivityndarray: The array containing the emissivity returned by AATM.

write_flag(elevation_limit)[source]: flag data if below user-specified elevation limit

Create Measurement Set

meqsilhouette.framework.create_ms.compute_casa_offset(msname, input_fits, ms)[source]: fn to compute casa offset

meqsilhouette.framework.create_ms.convertdec(dec)[source]

meqsilhouette.framework.create_ms.convertra(RA)[source]: Convert RA from degrees to hours

meqsilhouette.framework.create_ms.create_ms(msname, input_fits, ms_dict)[source]: create empty MS

meqsilhouette.framework.create_ms.create_msv2(msname, input_fits, ms)[source]: main fn to create MS

meqsilhouette.framework.create_ms.genms(msname, input_fits, antenna_table, starttime, obslength_in_sec, RA, DEC, stokes, tint, nu, dnu, nchan, nscan, scan_lag, datacolumn)[source]: setup ms configuration

meqsilhouette.framework.create_ms.return_simms_string(msname, input_fits, RA, DEC, polproducts, antenna_table, obslength, dnu, tint, nu, StartTime, nchan, nscan, scan_lag, datacolumn, makeplots, correctCASAoffset)[source]: generate simms string to create an empty MS, however, what is first required is a small MS to be generated in order to determine spurious time offset that CASA inserts, and adjust SYMBA start time accordingly

MeqTrees helper functions

meqsilhouette.framework.meqtrees_funcs.copy_between_cols(dest_col, src_col)[source]

meqsilhouette.framework.meqtrees_funcs.make_dirty_image_lwimager(im_dict, ms_dict)[source]

meqsilhouette.framework.meqtrees_funcs.make_image_wsclean()[source]

meqsilhouette.framework.meqtrees_funcs.run_turbosim(input_fitsimage, output_column, taql_string)[source]

meqsilhouette.framework.meqtrees_funcs.run_wsclean(input_fitsimage, input_fitspol, input_changroups, startvis, endvis, oversampling)[source]

Process configuration file

meqsilhouette.framework.process_input_config.load_json_parameters_into_dictionary(config)[source]

Load JSON parameters from a file into a dictionary.

Parameters

configstr
The path to the JSON file.

Returns

paramsdict
A dictionary containing the loaded and refactored JSON parameters.

meqsilhouette.framework.process_input_config.params_refactoring(_params)[source]

Modify input dictionary (hack: be careful!!!).

Parameters

_paramsdict
The path to the JSON file.

Returns

_paramsdict
The updated dictionary.

meqsilhouette.framework.process_input_config.read_json_files(config)[source]

Load JSON parameters from a file into a dictionary.

Parameters

configstr
The path to the JSON file.

Returns

paramsdict
A dictionary containing the loaded JSON parameters.

meqsilhouette.framework.process_input_config.setup_keyword_dictionary(prefix, dictionary)[source]

Create a dictionary from a dictionary with keys that start with a given prefix.

Parameters

prefixstr
The prefix to use for filtering the keys.

dictionarydict
The dictionary to filter.

Returns

dict
The filtered dictionary.