draco.util.testing

draco test utils.

Functions

mock_freq_data(freq, ntime, delaycut[, ...])

Make mock delay data with a constant delay spectrum up to a specified cut.

Classes

`DummyTask`()	Produce an empty data stream for testing.
`RandomFreqData`()	Generate a random sidereal stream with structure in delay.

class draco.util.testing.DummyTask[source]

Bases: SingleTask

Produce an empty data stream for testing.

total_len

Length of output data stream. Default: 1.

Type:: int

tag

What to use as a tag for the produced data.

Type:: str

Initialize pipeline task.

May be overridden with no arguments. Will be called after any config.Property attributes are set and after ‘input’ and ‘requires’ keys are set up.

process()[source]

Produce an empty stream and pass on.

Returns:: cont – Empty data stream.
Return type:: subclass of memh5.BasicCont

class draco.util.testing.RandomFreqData[source]

Bases: RandomTask

Generate a random sidereal stream with structure in delay.

num_realisation: How many to generate in subsequent process calls.

num_correlated: The number of correlated realisations output per cycle.

num_ra: The number of RA samples in the output.

num_base: The number of baselines in the output.

freq_start, freq_end: The start and end frequencies.

num_freq: The number of frequency channels.

delay_cut: The maximum delay in the data in us.

noise: The RMS noise level.

Initialize pipeline task.

May be overridden with no arguments. Will be called after any config.Property attributes are set and after ‘input’ and ‘requires’ keys are set up.

next() → SiderealStream | list[SiderealStream][source]

Generate correlated sidereal streams.

Returns:: Either a single stream (if num_correlated=None), or a list of correlated streams.
Return type:: streams

draco.util.testing.mock_freq_data(freq: ndarray, ntime: int, delaycut: float, ndata: int | None = None, noise: float = 0.0, bad_freq: ndarray | None = None, rng: Generator | None = None) → tuple[ndarray, ndarray][source]

Make mock delay data with a constant delay spectrum up to a specified cut.

Parameters:

freq – Frequencies of each channel (in MHz).
ntime – Number of independent time samples.
delaycut – Cutoff in us.
ndata – Number of correlated data sets. If not set (i.e. None) then do no add a dataset axis.
noise – RMS noise level in the data.
bad_freq – A list of bad frequencies to mask out.
rng – The random number generator to use.

Returns:

data – The 2D/3D data array [dataset, freq, time]. If ndata is None then the dataset axis is dropped.
weights – The 2D weights data [freq, time].