def smooth_tv(self,
smoothing_parameter=None,
show_progressbar=None,
parallel=None):
"""Total variation data smoothing in place.
Parameters
----------
smoothing_parameter: float or None
Denoising weight relative to L2 minimization. If None the method
is run in interactive mode.
show_progressbar : None or bool
If True, display a progress bar. If None the default is set in
`preferences`.
parallel : {Bool, None, int}
Perform the operation parallely
Raises
------
SignalDimensionError if the signal dimension is not 1.
"""
self._check_signal_dimension_equals_one()
if smoothing_parameter is None:
smoother = SmoothingTV(self)
smoother.edit_traits()
else:
self.map(_tv_denoise_1d,
weight=smoothing_parameter,
show_progressbar=show_progressbar,
parallel=parallel)
def smooth_tv(self, smoothing_parameter=None, show_progressbar=None):
"""Total variation data smoothing in place.
Parameters
----------
smoothing_parameter: float or None
Denoising weight relative to L2 minimization. If None the method
is run in interactive mode.
show_progressbar : None or bool
If True, display a progress bar. If None the default is set in
`preferences`.
Raises
------
SignalDimensionError if the signal dimension is not 1.
"""
self._check_signal_dimension_equals_one()
if smoothing_parameter is None:
smoother = SmoothingTV(self)
smoother.edit_traits()
else:
self.map(_tv_denoise_1d, weight=smoothing_parameter,
show_progressbar=show_progressbar)
def smooth_tv(self, smoothing_parameter=None, differential_order=0):
'''Lowess data smoothing'''
smoother = SmoothingTV(self)
smoother.differential_order = differential_order
if smoothing_parameter is not None:
smoother.smoothing_parameter = smoothing_parameter
if smoothing_parameter is None:
smoother.edit_traits()
else:
smoother.apply()
