pydiogment.utils.filters

• Description: implements the scipybased Butterworth filters.

bandpas: https://stackoverflow.com/questions/12093594/how-to-implement-band-pass-butterworth-filter-with-scipy-signal-butter highpass: https://stackoverflow.com/questions/39032325/python-high-pass-filter

pydiogment.utils.filters.butter_bandpass(low_cut, high_cut, fs, order=5)

Design band pass filter.

Args:

• low_cut (float) : the low cutoff frequency of the filter.
• high_cut (float) : the high cutoff frequency of the filter.
• fs (float) : the sampling rate.
• order (int) : order of the filter, by default defined to 5.

pydiogment.utils.filters.butter_filter(sig, fs, ftype='low', low_cut=50, high_cut=2000, order=5)

Apply filter to signal.

Args:

• sig (array) : the signal array to filter.
• fs (float) : the sampling rate.
• ftype (str) : the filter type, by default defined to a low pass filter
• low_cut (float) : the low cutoff frequency, by default defined to 50Hz
• high_cut (float) : the high cutoff frequency, by default defined to 2000Hz.
• order (int) : order of the filter, by default defined to 5.

Returns:

array of the filtered signal.

pydiogment.utils.filters.butter_highpass(cutoff, fs, order=5)

Design a highpass filter.

Args:

• cutoff (float) : the cutoff frequency of the filter.
• fs (float) : the sampling rate.
• order (int) : order of the filter, by default defined to 5.

pydiogment.utils.filters.butter_lowpass(cutoff, fs, order=5)

Design lowpass filter.

Args:

• cutoff (float) : the cutoff frequency of the filter.
• fs (float) : the sampling rate.
• order (int) : order of the filter, by default defined to 5.