pynapple.Ts.trial_count#
- Ts.trial_count(ep, bin_size, align='start', padding_value=nan, time_unit='s')[source]#
Return trial-based count tensor from an IntervalSet object. The shape of the tensor array is (number of trials, number of time bins).
The bin_size parameter determines the number of time bins.
The align parameter controls how the time series are aligned. If align=”start”, the time series are aligned to the start of each trial. If align=”end”, the time series are aligned to the end of each trial.
If trials have uneven durations, the returned array is padded. The parameter padding_value determines which value is used to pad the array. Default is NaN.
- Parameters:
ep (IntervalSet) – Epochs holding the trials. Each interval can be of unequal size.
bin_size (Number) – The size of the time bins.
align (str, optional) – How to align the time series (‘start’ [default], ‘end’)
padding_value (Number, optional) – How to pad the array if unequal intervals. Default is np.nan.
time_unit (str, optional) – Time units of the bin_size parameter (‘s’ [default], ‘ms’, ‘us’).
- Return type:
numpy.ndarray
- Raises:
RuntimeError – If time_unit not in [“s”, “ms”, “us”]