core¶

Read and analyze electrophysiological data.

Classes¶

`ReaderSmr`	A class for reading smr-files and accessing stimulus times and voltage traces.
`ReaderLabView`	A class for reading LabView binary data files and accessing stimulus times and voltage traces.
`SpikeDetectionCreastTrough`	Detects spikes by creast and trough amplitude.
`STAPlugin_TEMPLATE`	Base class for spike time analysis plugins.
`STAPlugin_ISIn`	SpikeTimeAnalysis (STA) plugin to compute the inter spike interval (ISI) to the next, second next, nth spike.
`STAPlugin_bursts`	SpikeTimeAnalysis (STA) plugin to detect high frequency events (doublet, triplet, …) that occur within a timewindow.
`STAPlugin_annotate_bursts_in_st`	SpikeTimeAnalysis (STA) plugin to annotate bursts in a spike times dataframe.
`STAPlugin_ongoing`	SpikeTimeAnalysis (STA) plugin to compute the ongoing activity.
`STAPlugin_quantification_in_period`	SpikeTimeAnalysis (STA) plugin to quantify the activity in a period.
`STAPlugin_extract_column_in_filtered_dataframe`	SpikeTimeAnalysis (STA) plugin to extract a column from a filtered dataframe.
`STAPlugin_spike_times_dataframe`	SpikeTimeAnalysis (STA) plugin to create a spike times dataframe.
`STAPlugin_response_probability_in_period`	SpikeTimeAnalysis (STA) plugin to compute the response probability in a period.
`STAPlugin_response_latency_in_period`	SpikeTimeAnalysis (STA) plugin to compute the response latency in a period.
`SpikeTimesAnalysis`	Class for applying event_analysis routines on a spike times dataframe.

`read_smr_file`(path)	Reads a Spike2 file and returns its content as a neo.core.block.Block object.
`read_labview_junk1_dat_files`(path, scale, sampling_rate)	Read in LabView binary data files.
`highpass_filter`(y, sr)	Apply a highpass filter to the data.
`load_reader`(dict_)	Load a reader object from a dictionary.
`get_peaks_above`(t, v, lim)	Compute timepoints of maxima above a threshold.
`get_upcross`(t, v, lim)	Finds the times and corresponding voltages of upcrossings of a given threshold.
`filter_spike_times`(spike_times, spike_times_trough, creast_trough_interval, mode, spike_times_amplitude, upper_creast_threshold, creast_upcross_times)	Filter spike times based on timepoints of detected creasts and troughs.
`filter_short_ISIs`(t, tdelta)	Filters out any events that occur in an interval shorter than tdelta.
`stimulus_interval_filter`(stim_times, period_length, offset)	Filters periodic stimuli such that only the first stimulus of each period is retained.
`get_st_from_spike_times_and_stim_times`(spike_times, stim_times, offset, mode)	Computes spike times dataframe based on list of spike times and stimulus times.
`strip_st`(st)	Get a DataFrame containing only spike times, without metadata.
`get_spike_times_from_row`(row)	Returns a list containing all non-NaN elements in the given pandas Series.
`get_period_label_by_time`(periods, t)	Classifies timepoint based on whether it falls within a period.