def wavedec(data, wavelet, mode='sym', level=None):
"""
Multilevel 1D Discrete Wavelet Transform of data.
Returns coefficients list - [cAn, cDn, cDn-1, ..., cD2, cD1]
data - input data
wavelet - wavelet to use (Wavelet object or name string)
mode - signal extension mode, see MODES
level - decomposition level. If level is None then it will be
calculated using `dwt_max_level` function.
"""
if not isinstance(wavelet, Wavelet):
wavelet = Wavelet(wavelet)
if level is None:
level = dwt_max_level(len(data), wavelet.dec_len)
elif level < 0:
raise ValueError("Level value of %d is too low . Minimum level is 0." %
level)
coeffs_list = []
a = data
for i in xrange(level):
a, d = dwt(a, wavelet, mode)
coeffs_list.append(d)
coeffs_list.append(a)
coeffs_list.reverse()
return coeffs_list
def wavedec(data, wavelet, mode='sym', level=None):
"""
Multilevel 1D Discrete Wavelet Transform of data.
Returns coefficients list - [cAn, cDn, cDn-1, ..., cD2, cD1]
data - input data
wavelet - wavelet to use (Wavelet object or name string)
mode - signal extension mode, see MODES
level - decomposition level. If level is None then it will be
calculated using `dwt_max_level` function.
"""
if not isinstance(wavelet, Wavelet):
wavelet = Wavelet(wavelet)
if level is None:
level = dwt_max_level(len(data), wavelet.dec_len)
elif level < 0:
raise ValueError("Level value of %d is too low . Minimum level is 0." % level)
coeffs_list = []
a = data
for i in xrange(level):
a, d = dwt(a, wavelet, mode)
coeffs_list.append(d)
coeffs_list.append(a)
coeffs_list.reverse()
return coeffs_list
def __init__(self, data, wavelet, mode='sp1', maxlevel=None):
super(WaveletPacket2D, self).__init__(None, data, "")
if not isinstance(wavelet, Wavelet):
wavelet = Wavelet(wavelet)
self.wavelet = wavelet
self.mode = mode
if data is not None:
data = numerix.as_float_array(data)
assert len(data.shape) == 2
self.data_size = data.shape
if maxlevel is None:
maxlevel = dwt_max_level(min(self.data_size), self.wavelet)
else:
self.data_size = None
self._maxlevel = maxlevel
def __init__(self, data, wavelet, mode='sp1', maxlevel=None):
super(WaveletPacket2D, self).__init__(None, data, "")
if not isinstance(wavelet, Wavelet):
wavelet = Wavelet(wavelet)
self.wavelet = wavelet
self.mode = mode
if data is not None:
data = numerix.as_float_array(data)
assert len(data.shape) == 2
self.data_size = data.shape
if maxlevel is None:
maxlevel = dwt_max_level(min(self.data_size), self.wavelet)
else:
self.data_size = None
self._maxlevel = maxlevel
def __init__(self, data, wavelet, mode='sp1', maxlevel=None):
Node.__init__(self, None, data, "")
if not isinstance(wavelet, Wavelet):
wavelet = Wavelet(wavelet)
self.wavelet = wavelet
self.mode = mode
if data is not None:
self.data_size = len(data)
if maxlevel is None:
maxlevel = dwt_max_level(self.data_size, self.wavelet.dec_len)
else:
self.data_size = None
self.maxlevel = maxlevel
self.level = 0
self.frequency = (0., 1.)
def wavedec2(data, wavelet, mode='sym', level=None):
"""
Multilevel 2D Discrete Wavelet Transform.
data - 2D input data
wavelet - wavelet to use (Wavelet object or name string)
mode - signal extension mode, see MODES
level - decomposition level. If level is None then it will be
calculated using `dwt_max_level` function .
Returns coefficients list - [cAn, (cHn, cVn, cDn), ... (cH1, cV1, cD1)]
"""
data = as_float_array(data)
if len(data.shape) != 2:
raise ValueError("Expected 2D input data.")
if not isinstance(wavelet, Wavelet):
wavelet = Wavelet(wavelet)
if level is None:
size = min(data.shape)
level = dwt_max_level(size, wavelet.dec_len)
elif level < 0:
raise ValueError("Level value of %d is too low . Minimum level is 0." %
level)
coeffs_list = []
a = data
for i in xrange(level):
a, ds = dwt2(a, wavelet, mode)
coeffs_list.append(ds)
coeffs_list.append(a)
coeffs_list.reverse()
return coeffs_list
def wavedec2(data, wavelet, mode='sym', level=None):
"""
Multilevel 2D Discrete Wavelet Transform.
data - 2D input data
wavelet - wavelet to use (Wavelet object or name string)
mode - signal extension mode, see MODES
level - decomposition level. If level is None then it will be
calculated using `dwt_max_level` function .
Returns coefficients list - [cAn, (cHn, cVn, cDn), ... (cH1, cV1, cD1)]
"""
data = as_float_array(data)
if len(data.shape) != 2:
raise ValueError("Expected 2D input data.")
if not isinstance(wavelet, Wavelet):
wavelet = Wavelet(wavelet)
if level is None:
size = min(data.shape)
level = dwt_max_level(size, wavelet.dec_len)
elif level < 0:
raise ValueError(
"Level value of %d is too low . Minimum level is 0." % level)
coeffs_list = []
a = data
for i in xrange(level):
a, ds = dwt2(a, wavelet, mode)
coeffs_list.append(ds)
coeffs_list.append(a)
coeffs_list.reverse()
return coeffs_list
def _evaluate_maxlevel(self, evaluate_from='parent'):
"""
Try to find the value of maximum decomposition level if it is not
specified explicitly.
"""
assert evaluate_from in ('parent', 'subnodes')
if self._maxlevel is not None:
return self._maxlevel
elif self.data is not None:
return self.level + dwt_max_level(min(self.data.shape),
self.wavelet)
if evaluate_from == 'parent':
if self.parent is not None:
return self.parent._evaluate_maxlevel(evaluate_from)
elif evaluate_from == 'subnodes':
for node_name in self.PARTS:
node = getattr(self, node_name, None)
if node is not None:
level = node._evaluate_maxlevel(evaluate_from)
if level is not None:
return level
return None
def _evaluate_maxlevel(self, evaluate_from='parent'):
"""
Try to find the value of maximum decomposition level if it is not
specified explicitly.
"""
assert evaluate_from in ('parent', 'subnodes')
if self._maxlevel is not None:
return self._maxlevel
elif self.data is not None:
return self.level + dwt_max_level(
min(self.data.shape), self.wavelet)
if evaluate_from == 'parent':
if self.parent is not None:
return self.parent._evaluate_maxlevel(evaluate_from)
elif evaluate_from == 'subnodes':
for node_name in self.PARTS:
node = getattr(self, node_name, None)
if node is not None:
level = node._evaluate_maxlevel(evaluate_from)
if level is not None:
return level
return None
