def undecimated(cls, nb_scale, iso_shape, nb_band):
""" Compute undecimated transformation parameters.
Parameters
----------
nb_scale: int
the number of scale of the decomposition that includes the
approximation scale.
iso_shape: int
the data isotropic shape.
nb_band: int
the number of band.
Returns
-------
bands_names: list of str
the name of the different bands.
flatten_fct: int
a function used to reorganize the ISAP decomposition coefficients,
see 'pysap/extensions/formating.py' module for more details.
unflatten_fct: callable
a function used to reorganize the decomposition coefficients using
ISAP convention, see 'pysap/extensions/formating.py' module for
more details.
is_decimated: bool
True if the decomposition include a decimation of the
band number of coefficients.
nb_band_per_scale: ndarray (<nb_scale>, )
vector of int holding the number of band per scale.
bands_lengths: ndarray (<nb_scale>, max(<nb_band_per_scale>, 0))
array holding the length between two bands of the data
vector per scale.
bands_shapes: list of list of 2-uplet (<nb_scale>, <nb_band_per_scale>)
structure holding the shape of each bands at each scale.
"""
if nb_band == 1:
bands_names = ["a"]
elif nb_band == 2:
bands_names = ["d1", "d2"]
elif nb_band == 3:
bands_names = ["v", "d", "h"]
else:
raise ValueError("'{0} bands not yet accepted.".format(nb_band))
flatten_fct = ISAP_FLATTEN[0]
unflatten_fct = ISAP_UNFLATTEN[0]
is_decimated = False
nb_band_per_scale = numpy.ones((nb_scale, 1), dtype=int)
nb_band_per_scale[:-1] = nb_band
bands_lengths = (
(iso_shape * iso_shape)
* numpy.ones((nb_scale, nb_band), dtype=int))
bands_shapes = WaveletTransformBase.bands_shapes(bands_lengths)
return (bands_names, flatten_fct, unflatten_fct, is_decimated,
nb_band_per_scale, bands_lengths, bands_shapes)
def _set_transformation_parameters(self):
raise NotImplementedError(
"This transformation is not yet accessible from the wrapping, "
"please use the Python bindings.")
_map = {128: 5, 512: 6}
self.nb_scale = _map[self._iso_shape] # fixed for this wavelet
self.name = "Line Column Wavelet Transform (1D+1D)"
self.bands_names = ['d%d' % i for i in range(_map[self._iso_shape])]
self.nb_band_per_scale = numpy.array([_map[self._iso_shape]] *
nb_scale)
self.bands_lengths = ((self._iso_shape * self._iso_shape) * numpy.ones(
(nb_scale, _map[self._iso_shape]), dtype=int))
self.bands_shapes = WaveletTransformBase.bands_shapes(bands_lengths)
self.isap_transform_id = 17
self.flatten_fct = ISAP_FLATTEN[0]
self.is_decimated = False