SimpleDS Parameters¶

These are the standard attributes of DelaySpectrum objects.

Under the hood they are actually properties based on UnitParameter object which themselves are based on a UVParameter.

Required¶

These parameters are required to have a sensible DelaySpectrum object and are required for most kinds of power spectrum estimation.

Nants_data: Number of antennas with data present (i.e. number of uniqueentries in ant_1_array and ant_2_array). May be smallerthan the number of antennas in the array
Nants_telescope: Number of antennas in the array. May be larger than the number of antennas with data
Nbls: Number of baselines
Ndelays: Number of delay channels. Must be equal to (Nfreqs) with FFT usage. However may differ if a more intricate Fourier Transform is used.
Nfreqs: Number of frequency channels per spectral window
Npols: Number of polarizations
Nspws: The number of spectral windows over which the Delay Transform is performed. All spectral windows must be the same size.
Ntimes: Number of times
Nuv: Number of UVData objects which have been read. Only a maximum of 2 UVData objects can be read into a single DelaySpectrum Object. Only 1 UVData must be ready to enable delay transformation and power spectrum estimation.
ant_1_array: Array of first antenna indices, shape (Nbls), type = int, 0 indexed
ant_2_array: Array of second antenna indices, shape (Nbls), type = int, 0 indexed
baseline_array: Array of baseline indices, shape (Nbls), type = int; baseline = 2048 * (ant1+1) + (ant2+1) + 2^16
beam_area: The integral of the power beam area. Shape = (Nspws, Npols, Nfreqs)
beam_sq_area: The integral of the squared power beam squared area. Shape = (Nspws, Npols, Nfreqs)
cosmology: Astropy cosmology object cabale of performing necessary cosmological calculations. Defaults to WMAP 9-Year.
data_type: String indicating which domain the data is in. Allowed values are “delay”, “frequency”
delay_array: Array of delay, shape (Ndelays), units ns
freq_array: Array of frequencies, shape (Nspws, Nfreqs), units Hz
integration_time: Length of the integration in seconds, has shape (Npols, Nbls, Ntime). units s, assumes inegration time is the same for all spectral windows and all frequncies in a spectral window. Assumes the same convention as pyuvdata, where this is the target amount of time a measurement is integrated over. Spectral window dimension allows for frequency dependent filtering to be properly tracked for noise simulations.
k_parallel: Cosmological wavenumber of spatial modes probed along the line of sight. This value is awlays calculated, however it is not a realistic probe of k_parallel over large bandwidths. This code assumes k_tau >> k_perpendicular and as a results k_tau is interpreted as k_parallel. In python 2 this unit is always in 1/Mpc. For python 3 users, it is possible to convert the littleh/Mpc using the littleh_units boolean flag in update_cosmology.
k_perpendicular: Cosmological wavenumber of spatial modes probed perpendicular to the line of sight. In python 2 this unit is always in 1/Mpc. For python 3 users, it is possible to convert the littleh/Mpc using the littleh_units boolean flag in update_cosmology.
lst_array: Array of lsts, center of integration, shape (Ntimes), UVData objects must be LST aligned before adding data to the DelaySpectrum object.units radians
polarization_array: Array of polarization integers, shape (Npols). Uses same convention as pyuvdata: pseudo-stokes 1:4 (pI, pQ, pU, pV); circular -1:-4 (RR, LL, RL, LR); linear -5:-8 (XX, YY, XY, YX).
redshift: Mean redshift of given frequencies. Calculated with assumed cosmology.
taper: Spectral taper function used during Fourier Transform. Functions like scipy.signal.windows.blackmanharris
trcvr: System receiver temperature used in noise simulation. Stored as array of length (Nfreqs), but may be passed as a single scalar. Must be a Quantity with units compatible to K.
uvw: Nominal (u,v,w) vector of baselines in units of meters
vis_units: Visibility units, options are: “uncalib”, “Jy” or “K str”

Optional¶

These parameters are not required to prepare a DelaySpectrum object for power spectrum estimation. However, some become required once the data has been Fourier Transformed into delay space.

data_array: Array of the visibility data, shape: (Nspws, Nuv, Npols, Nbls, Ntimes, Nfreqs), type = complex float, in units of self.vis_units
flag_array: Boolean flag, True is flagged, shape: same as data_array.
noise_array: Array of the simulation noise visibility data, shape: (Nspws, Nuv, Npols, Nbls, Ntimes, Nfreqs), type = complex float, in units of self.vis_units. Noise simulation generated assuming the sky is 180K@180MHz relation with the input receiver temperature, nsample_array, and integration times.
noise_power: The cross-multiplied simulated noise power spectrum estimates. Units are converted to cosmological frame (mK^2/(hMpc^-1)^3).For uncalibrated data the noise simulation is not well defined but is still calculated and will have units (Jy Hz)^2. In python 2 this unit is always in mK^2 Mpc^3. For python 3 users, it is possible to convert the mK^2 / (littleh/Mpc)^3 using the littleh_units boolean flag in update_cosmology.
nsample_array: Number of data points averaged into each data elementself. Uses the same convention as a UVData object:NOT required to be an integer, type = float, same shape as data_array.The product of the integration_time and the nsample_array value for a visibility reflects the total amount of time that went into the visibility.
power_array: The cross-multiplied power spectrum estimates. Units are converted to cosmological frame (mK^2/(hMpc^-1)^3).For uncalibrated data the cosmological power is not well defined the power array instead represents the power in the delay domain adn will have units (Hz^2). In python 2 this unit is always in mK^2 Mpc^3. For python 3 users, it is possible to convert the mK^2 / (littleh/Mpc)^3 using the littleh_units boolean flag in update_cosmology.
thermal_conversion: The cosmological unit conversion factor applied to the thermal noise estimate. Has the form (“Nspws”, “Npols”). Accounts for all beam polarizations.Always has units mK^2 Mpc^3 /( K^2 sr^2 Hz^2)
thermal_power: The predicted thermal variance of the input data averaged over all input baselines.Units are converted to cosmological frame (mK^2/(hMpc^-1)^3). In python 2 this unit is always in mK^2 Mpc^3. For python 3 users, it is possible to convert the mK^2 / (littleh/Mpc)^3 using the littleh_units boolean flag in update_cosmology.
unit_conversion: The cosmological unit conversion factor applied to the data. Has the form (“Nspws”, “Npols”). Accounts for all beam polarizations.Depending on units of input visibilities it may take units of mK^2/(h/Mpc)^3 / (K * sr * Hz)^2 or mK^2/[h/Mpc]^3 / (Jy * Hz)^2
x_orientation: Orientation of the physical dipole corresponding to what islabelled as the x polarization. Options are ‘east’(indicating east/west orientation) and ‘north’ (indicatingnorth/south orientation)

last updated: 2021-01-11