def _reconstruct(self, update):
data_ll, data_lh, data_hl, data_hh = None, None, None, None
node_ll, node_lh, node_hl, node_hh =\
self._get_node(self.LL), self._get_node(self.LH),\
self._get_node(self.HL), self._get_node(self.HH)
if node_ll is not None:
data_ll = node_ll.reconstruct()
if node_lh is not None:
data_lh = node_lh.reconstruct()
if node_hl is not None:
data_hl = node_hl.reconstruct()
if node_hh is not None:
data_hh = node_hh.reconstruct()
if (data_ll is None and data_lh is None
and data_hl is None and data_hh is None):
raise ValueError(
"Tree is missing data - all subnodes of `%s` node "
"are None. Cannot reconstruct node." % self.path
)
else:
coeffs = data_ll, (data_lh, data_hl, data_hh)
rec = idwt2(coeffs, self.wavelet, self.mode)
if update:
self.data = rec
return rec
def _reconstruct(self, update):
data_ll, data_lh, data_hl, data_hh = None, None, None, None
node_ll, node_lh, node_hl, node_hh =\
self._get_node(self.LL), self._get_node(self.LH),\
self._get_node(self.HL), self._get_node(self.HH)
if node_ll is not None:
data_ll = node_ll.reconstruct()
if node_lh is not None:
data_lh = node_lh.reconstruct()
if node_hl is not None:
data_hl = node_hl.reconstruct()
if node_hh is not None:
data_hh = node_hh.reconstruct()
if (data_ll is None and data_lh is None and data_hl is None
and data_hh is None):
raise ValueError(
"Tree is missing data - all subnodes of `%s` node "
"are None. Cannot reconstruct node." % self.path)
else:
coeffs = data_ll, (data_lh, data_hl, data_hh)
rec = idwt2(coeffs, self.wavelet, self.mode)
if update:
self.data = rec
return rec
def waverec2(coeffs, wavelet, mode='sym'):
"""
Multilevel 2D Inverse Discrete Wavelet Transform.
coeffs - coefficients list [cAn, (cHn, cVn, cDn), ... (cH1, cV1, cD1)]
wavelet - wavelet to use (Wavelet object or name string)
mode - signal extension mode, see MODES
Returns 2D array of reconstructed data.
"""
if not isinstance(coeffs, (list, tuple)):
raise ValueError("Expected sequence of coefficient arrays.")
if len(coeffs) < 2:
raise ValueError("Coefficient list too short (minimum 2 arrays required).")
a, ds = coeffs[0], coeffs[1:]
for d in ds:
a = idwt2((a, d), wavelet, mode)
return a
def waverec2(coeffs, wavelet, mode='sym'):
"""
Multilevel 2D Inverse Discrete Wavelet Transform.
coeffs - coefficients list [cAn, (cHn, cVn, cDn), ... (cH1, cV1, cD1)]
wavelet - wavelet to use (Wavelet object or name string)
mode - signal extension mode, see MODES
Returns 2D array of reconstructed data.
"""
if not isinstance(coeffs, (list, tuple)):
raise ValueError("Expected sequence of coefficient arrays.")
if len(coeffs) < 2:
raise ValueError(
"Coefficient list too short (minimum 2 arrays required).")
a, ds = coeffs[0], coeffs[1:]
for d in ds:
a = idwt2((a, d), wavelet, mode)
return a
