| 906 | self._n_appended = 0 |
| 907 | |
| 908 | def update(self, t): |
| 909 | self._T[:] = np.roll(self._T, -1) |
| 910 | self._T_isfinite[:] = np.roll(self._T_isfinite, -1) |
| 911 | if np.isfinite(t): |
| 912 | self._T_isfinite[-1] = True |
| 913 | self._T[-1] = t |
| 914 | else: |
| 915 | self._T_isfinite[-1] = False |
| 916 | self._T[-1] = 0 |
| 917 | self._n_appended += 1 |
| 918 | |
| 919 | self._P = np.roll(self._P, -1, axis=0) |
| 920 | self._I = np.roll(self._I, -1, axis=0) |
| 921 | self._left_P[:] = np.roll(self._left_P, -1) |
| 922 | self._left_I[:] = np.roll(self._left_I, -1) |
| 923 | |
| 924 | D = cdist( |
| 925 | core.rolling_window(self._T[-self._m :], self._m), |
| 926 | core.rolling_window(self._T, self._m), |
| 927 | metric="minkowski", |
| 928 | p=self._p, |
| 929 | )[0] |
| 930 | T_subseq_isfinite = np.all( |
| 931 | core.rolling_window(self._T_isfinite, self._m), axis=1 |
| 932 | ) |
| 933 | D[~T_subseq_isfinite] = np.inf |
| 934 | if np.any(~self._T_isfinite[-self._m :]): |
| 935 | D[:] = np.inf |
| 936 | |
| 937 | apply_exclusion_zone(D, D.shape[0] - 1, self._excl_zone, np.inf) |
| 938 | for j in range(D.shape[0]): |
| 939 | if D[j] < self._P[j, -1]: |
| 940 | pos = np.searchsorted(self._P[j], D[j], side="right") |
| 941 | self._P[j] = np.insert(self._P[j], pos, D[j])[:-1] |
| 942 | self._I[j] = np.insert( |
| 943 | self._I[j], pos, D.shape[0] - 1 + self._n_appended |
| 944 | )[:-1] |
| 945 | |
| 946 | # update top-k for the last, newly-updated index |
| 947 | I_last_topk = np.argsort(D, kind="mergesort")[: self._k] |
| 948 | self._P[-1] = D[I_last_topk] |
| 949 | self._I[-1] = I_last_topk + self._n_appended |
| 950 | self._I[-1][self._P[-1] == np.inf] = -1 |
| 951 | |
| 952 | # for the last index, the left matrix profile value is self.P_[-1, 0] |
| 953 | # and the same goes for the left matrix profile index |
| 954 | self._left_P[-1] = self._P[-1, 0] |
| 955 | self._left_I[-1] = self._I[-1, 0] |
| 956 | |
| 957 | @property |
| 958 | def P_(self): |