Introduction to pypam

Concepts

The idea of pypam is to process all the acoustic data resulting from an underwater acoustic deployment. For a deployment, we understand a single instrument from the moment it gets into the water until the moment it is taken out. This data is usually stored in different files (and folders), and sometimes has to be zipped because of lack of storage space. Don’t panic, you can still work with zipped folders directly from pypam without having to unzip the whole project. Usually these files have a continuity in time, and very often it is interesting to extract time series.

pypam allows to choose “time window” per AcousticSurvey, which will be the time resolution of the computed output. Then each feature will be computed on that time window (independently of the file duration and sampling frequency). The output is an xarray dataset. The dimensions of these arrays are always:

• id: id of the bin (increasing integer)

extra coordinates (metadata)

• datetime: bin start timestamp of the “time window”

• start_sample: start sample of the bin respect to the file

• end_sample: end sample of the bin respect to the file

• id_: id with respect to the file (changes when multiple files per deployment)

Temporal (features) analysis

In bioacoustics, sometimes several frequency bands are interesting to study at the same time and extract features. pypam allows so by passing a list of bands to analyze. Then, a features per “time window” and per frequency band is computed.

For features analysis, the second dimension is:

• bands: all the bands analyzed (just as an int)

extra coordinates (metadata)

• band_lowfreq: low limit of the frequency band

• band_highfreq: high limit of the frequency band

Available features

The available features now are:

Feature name	Type	string
Acoustic Complexity Index (ACI)	acoustic index	aci
Bioacoustic Index (BI)	acoustic index	bi
Spectral Entropy of Shannon (SH)	acoustic index	sh
Temporal Entropy of Shannon (SH)	acoustic index	th
Normalized Difference Sound Index (NDSI)	acoustic index	th
Acoustic Evenness Index (AEI)	acoustic index	aei
Acoustic Diversity Index (ADI)	acoustic index	adi
Zero Crossing Rate (ZCR)	acoustic index	zcr
Acoustic Diversity Index (ADI)	acoustic index	adi
Root Mean Squared Value (rms)	temporal feature	rms
Sound Exposure Level (SEL)	temporal feature	sel
Dynamic Range	temporal feature	dynamic_range
Peak	temporal feature	peak
Root Mean Squared Value Envelope	temporal feature	rms_envelope
Spectrum Slope	temporal feature	spectrum_slope

Frequency domain analysis

pypam allows to compute frequency-domain analysis (spectrum, spectrogram, third octave band levels…) per “time window”

For frequency domain analysis, the second dimension is:

• frequency: central frequency of the frequency band

In case of spectrograms, a third dimension is added:

• time: time in seconds of the spectrogram at that specific time window

Frequency domain features

• spectrogram

• Spectrum - power_spectrum - psd (power spectral density)

• Spectral Probability Density (SPD)

• octave bands