def detrend(self, method='none', nbins=None, order=None, knee=None):
"""
A method to detrend the light curve using a Savitsky-Golay filter (:func:`.savitzky_golay`),
a running median filter (:func:`.running_median`), or a high-pass filter
(:func:`.highpass_filter_lightcurve`).
Parameters
----------
method : string, default: 'none'
The detrending method. Either 'savitzkygolay', 'runningmedian', or
'highpassfilter'.
nbins : int, default: None
The number of bins in the Savitsky-Golay, or running median detrend window
order : int, default: None
The polynomial order of the Savitsky-Golay detrending fit.
knee : float, default: None
The high-pass filter knee frequency (Hz).
"""
self.set_detrend(method=method, nbins=nbins, order=order, knee=knee)
self.detrended = True
# store un-detrending light curve
self.ulc = np.copy(self.clc)
if method == 'savitzkygolay':
if nbins is None or order is None:
raise ValueError("Number of bins, or polynomial order, for Savitsky-Golay filter not set")
ffit = bf.savitzky_golay(self.clc, nbins, order)
self.clc = (self.clc - ffit)
self.detrend_fit = np.copy(ffit)
elif method == 'runningmedian':
if nbins is None:
raise ValueError("Number of bins for running median filter not set")
ffit = bf.running_median(self.clc, nbins)
self.clc = (self.clc - ffit)
self.detrend_fit = np.copy(ffit)
elif method == 'highpassfilter':
if knee is None:
raise ValueError("Knee frequency for high-pass filter not set.")
dlc = bf.highpass_filter_lightcurve(self, knee=knee)
self.clc = np.copy(dlc.clc)
else:
raise ValueError("No detrend method set")
def detrend(self, method='none', nbins=None, order=None, knee=None):
"""
A method to detrend the light curve using a Savitsky-Golay filter (:func:`.savitzky_golay`),
a running median filter (:func:`.running_median`), or a high-pass filter
(:func:`.highpass_filter_lightcurve`).
Parameters
----------
method : string, default: 'none'
The detrending method. Either 'savitzkygolay', 'runningmedian', or
'highpassfilter'.
nbins : int, default: None
The number of bins in the Savitsky-Golay, or running median detrend window
order : int, default: None
The polynomial order of the Savitsky-Golay detrending fit.
knee : float, default: None
The high-pass filter knee frequency (Hz).
"""
self.set_detrend(method=method, nbins=nbins, order=order, knee=knee)
self.detrended = True
# store un-detrending light curve
self.ulc = np.copy(self.clc)
if method == 'savitzkygolay':
if nbins is None or order is None:
raise ValueError("Number of bins, or polynomial order, for Savitsky-Golay filter not set")
ffit = bf.savitzky_golay(self.clc, nbins, order)
self.clc = (self.clc - ffit)
self.detrend_fit = np.copy(ffit)
elif method == 'runningmedian':
if nbins is None:
raise ValueError("Number of bins for running median filter not set")
ffit = bf.running_median(self.clc, nbins)
self.clc = (self.clc - ffit)
self.detrend_fit = np.copy(ffit)
elif method == 'highpassfilter':
if knee is None:
raise ValueError("Knee frequency for high-pass filter not set.")
dlc = bf.highpass_filter_lightcurve(self, knee=knee)
self.clc = np.copy(dlc.clc)
else:
raise ValueError("No detrend method set")
def filter_model(self,
m,
filtermethod='savitzkygolay',
nbins=101,
order=3,
filterknee=(1. / (0.3 * 86400.))):
"""
Use the Savitzky-Golay smoothing (:func:`.savitzky_golay`) to high-pass filter the model m.
Parameters
----------
m : :class:`numpy.ndarray`
An array containing the model.
filtermethod : string, default: 'savitzkygolay'
The method for filtering/detrending the model function. The default is
the Savitzky-Golay method, but this can also be 'runningmedian' to use
a running median detrending, or 'highpass' for a high-pass 3rd order Butterworth
filter.
nbins : int, optional, default: 101
An odd integer width (in bins) for the Savitzky-Golay, or running median, filtering.
order : int, optional, default: 3
The polynomial order for the Savitzky-Golay filtering.
filterknee : float, default: 1/(0.3*86400) Hz
The filter knee frequency (in Hz) for the high-pass filter method.
Returns
-------
The filtered model time series
"""
if filtermethod == 'savitzkygolay':
return (m - bf.savitzky_golay(m, nbins, order))
elif filtermethod == 'runningmedian':
return (m - bf.running_median(m, nbins))
elif filtermethod == 'highpass':
ml = bf.Lightcurve()
ml.clc = np.copy(m)
ml.cts = np.copy(self.ts)
filtm = bf.highpass_filter_lightcurve(ml, knee=filterknee)
del ml
return filtm
else:
raise ValueError('Unrecognised filter method (%s) given' %
filtermethod)
def filter_model(self, m, filtermethod='savitzkygolay', nbins=101, order=3, filterknee=(1./(0.3*86400.))):
"""
Use the Savitzky-Golay smoothing (:func:`.savitzky_golay`) to high-pass filter the model m.
Parameters
----------
m : :class:`numpy.ndarray`
An array containing the model.
filtermethod : string, default: 'savitzkygolay'
The method for filtering/detrending the model function. The default is
the Savitzky-Golay method, but this can also be 'runningmedian' to use
a running median detrending, or 'highpass' for a high-pass 3rd order Butterworth
filter.
nbins : int, optional, default: 101
An odd integer width (in bins) for the Savitzky-Golay, or running median, filtering.
order : int, optional, default: 3
The polynomial order for the Savitzky-Golay filtering.
filterknee : float, default: 1/(0.3*86400) Hz
The filter knee frequency (in Hz) for the high-pass filter method.
Returns
-------
The filtered model time series
"""
if filtermethod == 'savitzkygolay':
return (m - bf.savitzky_golay(m, nbins, order))
elif filtermethod == 'runningmedian':
return (m - bf.running_median(m, nbins))
elif filtermethod == 'highpass':
ml = bf.Lightcurve()
ml.clc = np.copy(m)
ml.cts = np.copy(self.ts)
filtm = bf.highpass_filter_lightcurve(ml, knee=filterknee)
del ml
return filtm
else:
raise ValueError('Unrecognised filter method (%s) given' % filtermethod)