def smooth_savitzky_golay(self,
polynomial_order=None,
window_length=None,
differential_order=0):
"""Apply a Savitzky-Golay filter to the data in place.
If `polynomial_order` or `window_length` or `differential_order` are
None the method is run in interactive mode.
Parameters
----------
window_length : int
The length of the filter window (i.e. the number of coefficients).
`window_length` must be a positive odd integer.
polynomial_order : int
The order of the polynomial used to fit the samples.
`polyorder` must be less than `window_length`.
differential_order: int, optional
The order of the derivative to compute. This must be a
nonnegative integer. The default is 0, which means to filter
the data without differentiating.
Notes
-----
More information about the filter in `scipy.signal.savgol_filter`.
"""
if not savgol_imported:
raise ImportError("scipy >= 0.14 needs to be installed to use"
"this feature.")
self._check_signal_dimension_equals_one()
if (polynomial_order is not None and window_length is not None):
axis = self.axes_manager.signal_axes[0]
self.data = savgol_filter(x=self.data,
window_length=window_length,
polyorder=polynomial_order,
deriv=differential_order,
delta=axis.scale,
axis=axis.index_in_array)
self.events.data_changed.trigger(obj=self)
else:
# Interactive mode
smoother = SmoothingSavitzkyGolay(self)
smoother.differential_order = differential_order
if polynomial_order is not None:
smoother.polynomial_order = polynomial_order
if window_length is not None:
smoother.window_length = window_length
smoother.edit_traits()
def smooth_savitzky_golay(self,
polynomial_order=None,
window_length=None,
differential_order=0):
"""Apply a Savitzky-Golay filter to the data in place.
If `polynomial_order` or `window_length` or `differential_order` are
None the method is run in interactive mode.
Parameters
----------
window_length : int
The length of the filter window (i.e. the number of coefficients).
`window_length` must be a positive odd integer.
polynomial_order : int
The order of the polynomial used to fit the samples.
`polyorder` must be less than `window_length`.
differential_order: int, optional
The order of the derivative to compute. This must be a
nonnegative integer. The default is 0, which means to filter
the data without differentiating.
Notes
-----
More information about the filter in `scipy.signal.savgol_filter`.
"""
if not savgol_imported:
raise ImportError("scipy >= 0.14 needs to be installed to use"
"this feature.")
self._check_signal_dimension_equals_one()
if (polynomial_order is not None and
window_length is not None):
axis = self.axes_manager.signal_axes[0]
self.data = savgol_filter(
x=self.data,
window_length=window_length,
polyorder=polynomial_order,
deriv=differential_order,
delta=axis.scale,
axis=axis.index_in_array)
self.events.data_changed.trigger(obj=self)
else:
# Interactive mode
smoother = SmoothingSavitzkyGolay(self)
smoother.differential_order = differential_order
if polynomial_order is not None:
smoother.polynomial_order = polynomial_order
if window_length is not None:
smoother.window_length = window_length
smoother.edit_traits()
def smooth_savitzky_golay(self, polynomial_order = None,
number_of_points = None, differential_order = 0):
'''Savitzky-Golay data smoothing'''
if polynomial_order is not None and number_of_points is not None:
for index in np.ndindex(
tuple(self.axes_manager.navigation_shape)):
self.axes_manager.set_not_slicing_indexes(index)
self.data[self.axes_manager._getitem_tuple] = \
utils.sg(self(), number_of_points,
polynomial_order, differential_order)
else:
smoother = SmoothingSavitzkyGolay(self)
smoother.differential_order = differential_order
if polynomial_order is not None:
smoother.polynomial_order = polynomial_order
if number_of_points is not None:
smoother.number_of_points = number_of_points
smoother.edit_traits()
def smooth_savitzky_golay(self, polynomial_order = None,
number_of_points = None, differential_order = 0):
"""Savitzky-Golay data smoothing
"""
if (polynomial_order is not None and
number_of_points) is not None:
for spectrum in self:
spectrum.data[:] = utils.sg(self(),
number_of_points,
polynomial_order,
differential_order)
else:
smoother = SmoothingSavitzkyGolay(self)
smoother.differential_order = differential_order
if polynomial_order is not None:
smoother.polynomial_order = polynomial_order
if number_of_points is not None:
smoother.number_of_points = number_of_points
smoother.edit_traits()
