| import stumpy |
| import numpy as np |
|
|
| class MatrixProfile(): |
| """ |
| Wrapper of the stympy implementation of the MatrixProfile algorithm |
| |
| Parameters |
| ---------- |
| window : int, |
| target subsequence length. |
| |
| Attributes |
| ---------- |
| decision_scores_ : numpy array of shape (n_samples - m,) |
| The anomaly score. |
| The higher, the more abnormal. Anomalies tend to have higher |
| scores. This value is available once the detector is |
| fitted. |
| """ |
|
|
| def __init__(self, window): |
| self.window = window |
| self.model_name = 'MatrixProfile' |
|
|
| def fit(self, X, y=None): |
| """Fit detector. y is ignored in unsupervised methods. |
| |
| Parameters |
| ---------- |
| X : numpy array of shape (n_samples, ) |
| The input samples. |
| y : Ignored |
| Not used, present for API consistency by convention. |
| |
| Returns |
| ------- |
| self : object |
| Fitted estimator. |
| """ |
| self.profile = stumpy.stump(X.ravel(),m=self.window) |
| |
| res = np.zeros(len(X)) |
| res.fill(self.profile[:, 0].min()) |
| res[self.window//2:-self.window//2+1] = self.profile[:, 0] |
| self.decision_scores_ = res |
| return self |
|
|
