pyscamp.abjoin_knn

pyscamp.abjoin_knn(a: List[float], b: List[float], m: int, k: int, **kwargs) → List[Tuple[int, int, float]]

[GPU ONLY, EXPERIMENTAL] For each subsequence in time series A, returns its Approximate K nearest neighbors in time series B

Parameters:

  • a (1D array) – Time series to compute the KNN matrix profile for.`

  • b (1D array) – Time series in which to search for matches.

  • m (int) – Subsequence length to use for computing the matrix profile.

  • k (int) – Number of neighbors to return for each subsequence

  • threshold (float, optional) – Correlation threshold [0,1] (Default 0), matches which have a correlation less than the threshold will be ignored

Returns:

List of tuples (col, row, distance) containing the matches (up to K) for each column of the distance matrix, col is the index in A, row is the index in B of the match, and d is the distance between the two subsequences

Return type:

List of tuple[int, int, float]