Multilevel nD Inverse Discrete Wavelet Transform. coeffs : array_like Coefficients list [cAn, {details_level_n}, ... {details_level_1}] wavelet : Wavelet object or name string, or tuple of wavelets Wavelet to use. This can also be a tuple containing a wavelet to
(coeffs, wavelet, mode='symmetric', axes=None)
| 459 | |
| 460 | |
| 461 | def waverecn(coeffs, wavelet, mode='symmetric', axes=None): |
| 462 | """ |
| 463 | Multilevel nD Inverse Discrete Wavelet Transform. |
| 464 | |
| 465 | coeffs : array_like |
| 466 | Coefficients list [cAn, {details_level_n}, ... {details_level_1}] |
| 467 | wavelet : Wavelet object or name string, or tuple of wavelets |
| 468 | Wavelet to use. This can also be a tuple containing a wavelet to |
| 469 | apply along each axis in ``axes``. |
| 470 | mode : str or tuple of str, optional |
| 471 | Signal extension mode, see :ref:`Modes <ref-modes>`. This can |
| 472 | also be a tuple containing a mode to apply along each axis in ``axes``. |
| 473 | axes : sequence of ints, optional |
| 474 | Axes over which to compute the IDWT. Axes may not be repeated. |
| 475 | |
| 476 | Returns |
| 477 | ------- |
| 478 | nD array of reconstructed data. |
| 479 | |
| 480 | Notes |
| 481 | ----- |
| 482 | It may sometimes be desired to run ``waverecn`` with some sets of |
| 483 | coefficients omitted. This can best be done by setting the corresponding |
| 484 | arrays to zero arrays of matching shape and dtype. Explicitly removing |
| 485 | list or dictionary entries or setting them to None is not supported. |
| 486 | |
| 487 | Specifically, to ignore all detail coefficients at level 2, one could do:: |
| 488 | |
| 489 | coeffs[-2] = {k: np.zeros_like(v) for k, v in coeffs[-2].items()} |
| 490 | |
| 491 | Examples |
| 492 | -------- |
| 493 | >>> import numpy as np |
| 494 | >>> from pywt import wavedecn, waverecn |
| 495 | >>> coeffs = wavedecn(np.ones((4, 4, 4)), 'db1') |
| 496 | >>> # Levels: |
| 497 | >>> len(coeffs)-1 |
| 498 | 2 |
| 499 | >>> waverecn(coeffs, 'db1') |
| 500 | array([[[ 1., 1., 1., 1.], |
| 501 | [ 1., 1., 1., 1.], |
| 502 | [ 1., 1., 1., 1.], |
| 503 | [ 1., 1., 1., 1.]], |
| 504 | [[ 1., 1., 1., 1.], |
| 505 | [ 1., 1., 1., 1.], |
| 506 | [ 1., 1., 1., 1.], |
| 507 | [ 1., 1., 1., 1.]], |
| 508 | [[ 1., 1., 1., 1.], |
| 509 | [ 1., 1., 1., 1.], |
| 510 | [ 1., 1., 1., 1.], |
| 511 | [ 1., 1., 1., 1.]], |
| 512 | [[ 1., 1., 1., 1.], |
| 513 | [ 1., 1., 1., 1.], |
| 514 | [ 1., 1., 1., 1.], |
| 515 | [ 1., 1., 1., 1.]]]) |
| 516 | |
| 517 | """ |
| 518 | if len(coeffs) < 1: |
nothing calls this directly
no test coverage detected