Initialize the FLOSS object Parameters ---------- mp : numpy.ndarray The first column consists of the matrix profile, the second column consists of the matrix profile indices, the third column consists of the left matrix profile i
(
self,
mp,
T,
m,
L,
excl_factor=5,
n_iter=1000,
n_samples=1000,
custom_iac=None,
normalize=True,
p=2.0,
T_subseq_isconstant_func=None,
)
| 423 | """ |
| 424 | |
| 425 | def __init__( |
| 426 | self, |
| 427 | mp, |
| 428 | T, |
| 429 | m, |
| 430 | L, |
| 431 | excl_factor=5, |
| 432 | n_iter=1000, |
| 433 | n_samples=1000, |
| 434 | custom_iac=None, |
| 435 | normalize=True, |
| 436 | p=2.0, |
| 437 | T_subseq_isconstant_func=None, |
| 438 | ): |
| 439 | """ |
| 440 | Initialize the FLOSS object |
| 441 | |
| 442 | Parameters |
| 443 | ---------- |
| 444 | mp : numpy.ndarray |
| 445 | The first column consists of the matrix profile, the second column |
| 446 | consists of the matrix profile indices, the third column consists of |
| 447 | the left matrix profile indices, and the fourth column consists of |
| 448 | the right matrix profile indices. |
| 449 | |
| 450 | T : numpy.ndarray |
| 451 | A 1-D time series data used to generate the matrix profile and matrix |
| 452 | profile indices found in `mp`. Note that the the right matrix profile index |
| 453 | is used and the right matrix profile is intelligently recomputed on-the-fly |
| 454 | from `T` instead of using the bidirectional matrix profile. |
| 455 | |
| 456 | m : int |
| 457 | The window size for computing sliding window mass. This is identical |
| 458 | to the window size used in the matrix profile calculation. For managing |
| 459 | edge effects, see the `L` parameter. |
| 460 | |
| 461 | L : int |
| 462 | The subsequence length that is set roughly to be one period length. |
| 463 | This is likely to be the same value as the window size, `m`, used |
| 464 | to compute the matrix profile and matrix profile index but it can |
| 465 | be different since this is only used to manage edge effects |
| 466 | and has no bearing on any of the IAC or CAC core calculations. |
| 467 | |
| 468 | excl_factor : int, default 5 |
| 469 | The multiplying factor for the regime exclusion zone. Note that this |
| 470 | is unrelated to the `excl_zone` used in to compute the matrix profile. |
| 471 | |
| 472 | n_iter : int, default 1000 |
| 473 | Number of iterations to average over when determining the parameters for |
| 474 | the IAC beta distribution |
| 475 | |
| 476 | n_samples : int, default 1000 |
| 477 | Number of distribution samples to draw during each iteration when |
| 478 | computing the IAC |
| 479 | |
| 480 | custom_iac : numpy.ndarray, default None |
| 481 | A custom idealized arc curve (IAC) that will used for correcting the |
| 482 | arc curve |