(sizes, dec_lens, level)
| 29 | |
| 30 | |
| 31 | def _check_level(sizes, dec_lens, level): |
| 32 | if np.isscalar(sizes): |
| 33 | sizes = (sizes, ) |
| 34 | if np.isscalar(dec_lens): |
| 35 | dec_lens = (dec_lens, ) |
| 36 | max_level = np.min([dwt_max_level(s, d) for s, d in zip(sizes, dec_lens)]) |
| 37 | if level is None: |
| 38 | level = max_level |
| 39 | elif level < 0: |
| 40 | raise ValueError( |
| 41 | "Level value of %d is too low . Minimum level is 0." % level) |
| 42 | elif level > max_level: |
| 43 | warnings.warn( |
| 44 | f"Level value of {level} is too high: all coefficients will experience " |
| 45 | "boundary effects.") |
| 46 | return level |
| 47 | |
| 48 | |
| 49 | def wavedec(data, wavelet, mode='symmetric', level=None, axis=-1): |
no test coverage detected