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3+ Deep scattering transform on segmented time series.
4+
5+ This program contains a series of command-line tools for clustering
6+ continuous time series with a deep scattering network. The following sub-
7+ commands must be run in a specific order from the continuous data to the
8+ cluster results.
9+
10+ 1 . The inventorize command lists and selects the data based on usual meta
11+ parameters (sampling rate, duration, channels) and stores the relevant
12+ datapaths into an inventory file. This first command helps explore the data
13+ coverage in time, selecting appropriate time segments, and running the
14+ remaining steps on the actual data.
15+
16+ 2 . The transform command runs the deep scattering transform on the segmented
17+ time series and stores the scattering coefficients for later feature
18+ extraction.
19+
20+ 3 . With the features command, the large-dimensional scattering coefficients
21+ are reduced to a low-dimensional space which dimensions are considered
22+ features here. These features are used in the clustering step next.
23+
24+ 4 . The command calculates the linkage matrix that helps cluster the data
25+ based on some criteria of similarity (a metric and a method). Once this
26+ matrix is calculated, the clusters are extracted for further analyses.
27+
28+ Created in May 2021 by Leonard Seydoux and Randall Balestriero.
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