pyfar.dsp.filter contains different filter types that are briefly
introduced in the following. The filters can be used to directly
Signal or can return a
Filter object described in
High-pass, low-pass, band-pass, and band-stop filters¶
These are the classic filters that are wrapped from
available from the functions
crossover returns Linkwitz-Riley
cross-over filters that are often used in loudspeaker design.
Filter banks are commonly used in audio and acoustics signal processing, pyfar contains the following types of filter banks:
fractional_octave_bandsare often used for calculating room acoustic parameters
reconstructing_fractional_octave_bandscan be used if a perfect reconstruction is required, e.g., in room acoustical simulations.
auditory gammatone filterscan be used for binaural modeling.
The corresponding center frequencies are accessible via
filters shown on the left are specific filters for digital audio signal
processing and are often used for audio effects and loudspeaker or room
compensation. Bell filters manipulate the magnitude response around a
center-frequency. Low- and high-shelve filters manipulate the magnitude
response below and above a characteristic frequency. The cascaded shelving
high_shelve_cascade shown on the right can be used
to generate filters with a user definable slope given in dB per octaves within
a certain frequency region.