bluepyopt.ephys.efeatures¶
eFeature classes
- class bluepyopt.ephys.efeatures.eFELFeature(name, efel_feature_name=None, recording_names=None, stim_start=None, stim_end=None, exp_mean=None, exp_std=None, threshold=None, stimulus_current=None, comment='', interp_step=None, double_settings=None, int_settings=None, string_settings=None, force_max_score=False, max_score=250)[source]¶
eFEL feature
Constructor
- Parameters
name (str) – name of the eFELFeature object
efel_feature_name (str) – name of the eFeature in the eFEL library (ex: ‘AP1_peak’)
recording_names (dict) – eFEL features can accept several recordings as input
stim_start (float) – stimulation start time (ms)
stim_end (float) – stimulation end time (ms)
exp_mean (float) – experimental mean of this eFeature
exp_std (float) – experimental standard deviation of this eFeature
threshold (float) – spike detection threshold (mV)
comment (str) – comment
interp_step (float) – interpolation step (ms)
double_settings (dict) – dictionary with efel double settings that should be set before extracting the features
int_settings (dict) – dictionary with efel int settings that should be set before extracting the features
string_settings (dict) – dictionary with efel string settings that should be set before extracting the features
- class bluepyopt.ephys.efeatures.extraFELFeature(name, extrafel_feature_name=None, recording_names=None, somatic_recording_name=None, fcut=None, fs=None, filt_type=None, ms_cut=None, upsample=None, skip_first_spike=True, skip_last_spike=True, channel_ids=None, stim_start=None, stim_end=None, exp_mean=None, exp_std=None, threshold=None, comment='', interp_step=None, double_settings=None, int_settings=None, force_max_score=False, max_score=250)[source]¶
extraFEL feature
Constructor
- Parameters
name (str) – name of the extraFELFeature object
extrafel_feature_name (str) – name of the eFeature in the spikefeatures library (ex: ‘halfwidth’)
recording_names (dict) – eFEL features can accept several recordings as input
somatic_recording_name (str) – intracellualar recording from soma, used to detect spikes. If None, spikes are detected from extracellular trace
fcut (float, array, or None) – cutoff frequency(ies) for filter. If float, a high-pass filter is used. If array-like a bandpass filter is used. If None, traces are note filtered
fs (float) – sampling frequency to resample extracellular traces (in kHz)
filt_type (str) – type of the bandpass filter used (default ‘filtfilt’)
ms_cut (float, list, or None) – cut in ms before and after the intra peak. If scalar, the cut is symmetrical
upsample (int, or None) – upsample factor for average waveform before computing features
skip_first_spike (bool) – if True, the first spike is skipped before computing the average waveform (to avoid artifacts)
skip_last_spike (bool) – if True, the last spike is skipped before computing the average waveform (to avoid artifacts)
channel_ids (int, np.array, or None) – if None, all channels are used to compute the feature and calculate the score (using the cosine_dist). If int, a single channel is used and the score is the normalised deviation form the exp value. If list/array, the cosine distance is computed over a subset of channels
stim_start (float) – stimulation start time (ms)
stim_end (float) – stimulation end time (ms)
exp_mean (list of floats) – experimental mean of this eFeature
exp_std (list of floats) – experimental standard deviation of this eFeature
threshold (float) – spike detection threshold (mV)
comment (str) – comment
interp_step (float) – interpolation step (ms)
double_settings (dict) – dictionary with efel double settings that should be set before extracting the features
int_settings (dict) – dictionary with efel int settings that should be set before extracting the features