def test_wavelet_repr():
from pywt._extensions import _pywt
wavelet = _pywt.Wavelet('sym8')
repr_wavelet = eval(wavelet.__repr__())
assert_(wavelet.__repr__() == repr_wavelet.__repr__())
def __init__(self, _input=None):
self._input = _input
if _input is None:
self.l = None
self.level = None
else:
self.l = len(_input)
self.level = _dwt.dwt_max_level(data_len=self.l,
filter_len=self.fl)
self.fl = _pywt.Wavelet('haar').dec_len
self.method = _pywt.MODES.smooth
self.wavelet = 'haar'
self.ca = []
self.cd = []
self.eng = []
self.twe = []
self.rwe = []
self.we = []
# # Featrure methods
# self.wavelet_decompose()
# self.total_wavelet_energy()
# self.relative_wavelet_energy()
# self.wavelet_entropy()
pass