Time Series Analysis Toolkit Based on Symbolic Aggregate Discretization, i.e. SAX
Translates an alphabet size into the array of corresponding SAX cut-li...
Computes a TF-IDF weight vectors for a set of word bags.
Computes the cosine similarity between numeric vectors
Computes the cosine distance value between a bag of words and a set of...
Finds the Euclidean distance between points, if distance is above the ...
A PHYSIONET dataset
Finds the Euclidean distance between points.
Finds a discord using brute force algorithm.
Finds a discord (i.e. time series anomaly) with HOT-SAX. Usually works...
Finds a discord with RRA (Rare Rule Anomaly) algorithm. Usually works ...
Get the ASCII letter by an index.
Compares two strings using mindist.
Compares two strings using natural letter ordering.
Get the index for an ASCII letter.
Get an ASCII indexes sequence for a given character array.
Converts a set of time-series into a single bag of words.
Computes the mindist value for two strings
Computes a Piecewise Aggregate Approximation (PAA) for a time series.
Discretize a time series with SAX using chunking (no sliding window).
Generates a SAX MinDist distance matrix (i.e. the "lookup table") for ...
Discretizes a time series with SAX via sliding window.
Transforms a time series into the char array using SAX and the normal ...
Transforms a time series into the string.
Converts a single time series into a bag of words.
Runs the repair on a string.
Extracts a subseries.
Z-normalizes a time series by subtracting its mean and dividing by the...
Implements time series z-normalization, SAX, HOT-SAX, VSM, SAX-VSM, RePair, and RRA algorithms facilitating time series motif (i.e., recurrent pattern), discord (i.e., anomaly), and characteristic pattern discovery along with interpretable time series classification.