BeForEpochs#

class befordata.BeForEpochs(dat, sampling_rate, design=<factory>, baseline=<factory>, zero_sample=0)#

Behavioural force data organized epoch-wis

Parameters:

  • dat (: 2d numpy array) – data. Each row of the 2D numpy array represents one epoch. Thus, the number of rows equals the number of epochs and number of columns equals the number of samples in each epoch.

  • sample_rate (float) – sampling rate of the force measurements

  • design (pd.DataFrame) – design data frame

  • baseline (numpy array) – baseline for each epoch at zero_sample

  • zero_sample (int, optional) – sample index that represents the time 0

Methods

adjust_baseline(reference_window)

Adjust the baseline of each epoch using the mean value of a defined range of sample (reference window)

n_epochs()

number of epochs

n_samples()

number of sample of one epoch

to_arrow
n_epochs()#

number of epochs

Return type:

int

n_samples()#

number of sample of one epoch

Return type:

int

adjust_baseline(reference_window)#

Adjust the baseline of each epoch using the mean value of a defined range of sample (reference window)

Parameters:

reference_window (Tuple[int, int]) – sample range that is used for the baseline adjustment