[ENH] Integrate trials object with Fano factor #645
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Moritz-Alexander-Kern
added
the
enhancement
| Default: False | ||
| pool_spike_trains : bool, optional | ||
| If True, pool spike trains within each trial before computing the Fano factor. | ||
| Default: False |
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add to docs: if spiketrains is a list, parameters are ignored
| f"different duration (minimum: {np.min(durations)}s, maximum " | ||
| f"{np.max(durations)}s).") | ||
| else: | ||
| warnings.warn(f"Spiketrains was of type {type(spiketrains)}, which does not support automatic duration" |
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remove warning
| pool_trials : bool, optional | ||
| If True, pool spike trains across trials before computing the Fano factor. | ||
| Default: False | ||
| pool_spike_trains : bool, optional |
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remove pool_spiketrains_parameter
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This pull request introduces an enhancement to Fano factor using the the
elephant.trialsmodule to represent trials. This change is part of a greater effort to provide a more structured and unified approach for handling trial data in Elephant.Trial representations
This pull request adds two new parameters,
pool_trialsandpool_spike_trains, to the function. These parameters allow to control how spike trains are aggregated across trials and within individual trials.Changes
fanofactornow handles trial objectpool_trialsparameterpool_spike_trainsparameter