- syncopy.synthdata.poisson_noise(nTrials=10, nSpikes=10000, nChannels=3, nUnits=10, intensity=0.1, samplerate=10000, seed=None)#
Poisson (Shot-)noise generator
The expected trial length in samples is given by:
Dividing again by the ``samplerate` gives the expected trial length in seconds.
Individual trial lengths get randomly shortened by up to 10% of this expected length.
The trigger offsets are also randomized between 5% and 20% of the shortest trial length.
Lastly, the distribution of the Poisson
intensityalong channels and units has uniformly randomized weights, meaning that typically you get very active channels/units and some which are almost quiet.
The parameters listed below can be provided as is or a via a cfg configuration ‘structure’, see Notes for details.
nTrials (int) – Number of trials
nSpikes (int) – The total number of spikes over all trials to generate
nChannels (int) – Number of channels
nUnits (int) – Number of units
intensity (int) – Expected number of spikes per sampling interval
samplerate (float) – Sampling rate in Hz
seed (None or int, passed on to np.random.default_rng.) – Set to an int to get reproducible results.
sdata – The generated spike data
- Return type:
This function can be either called providing its input arguments directly or via a cfg configuration ‘structure’. For instance, the following function calls are equivalent
>>> spy.poisson_noise(nTrials, nTrials=...) >>> cfg = spy.StructDict() >>> cfg.nTrials = ... >>> spy.poisson_noise(cfg, nTrials) >>> cfg.nTrials = nTrials >>> spy.poisson_noise(cfg)
Please refer to Syncopy for FieldTrip Users for further details.
Originally conceived by Alejandro Tlaie Boria https://github.com/atlaie_
With nSpikes=20_000, samplerate=10_000, nTrials=10 and the default intensity=0.1 we can expect a trial length of about 2 seconds:
>>> spike_data = poisson_noise(nTrials=10, nSpikes=20_000, samplerate=10_000)
Example output of the 1st trial [start, end] in seconds:
>>> spike_data.trialintervals >>> array([-0.3004, 1.6459])
Which is close to 2 seconds.