def BillerBiemann(im: IntensityMatrix,
points: int = 3,
scans: int = 1) -> List[Peak]:
"""
Deconvolution based on the algorithm of Biller and Biemann (1974)
:param im: An :class:`~pyms.IntensityMatrix.IntensityMatrix` object
:type im: ~pyms.IntensityMatrix.IntensityMatrix
:param points: Number of scans over which to consider a maxima to be a peak. Default ``3``
:type points: int, optional
:param scans: Number of scans to combine peaks from to compensate for spectra skewing. Default ``1``
:type scans: int, optional
:return: List of detected peaks
:rtype: List[:class:`pyms.Peak.Class.Peak`]
:authors: Andrew Isaac, Dominic Davis-Foster (type assertions)
"""
if not isinstance(im, IntensityMatrix):
raise TypeError("'im' must be an IntensityMatrix object")
if not isinstance(points, int):
raise TypeError("'points' must be an integer")
if not isinstance(scans, int):
raise TypeError("'scans' must be an integer")
rt_list = im.time_list
mass_list = im.mass_list
peak_list = []
maxima_im = get_maxima_matrix(im, points, scans)
numrows = len(maxima_im)
for row in range(numrows):
if sum(maxima_im[row]) > 0:
rt = rt_list[row]
ms = MassSpectrum(mass_list, maxima_im[row])
peak = Peak(rt, ms)
peak.bounds = [0, row, 0] # store IM index for convenience
peak_list.append(peak)
return peak_list
def BillerBiemann(im: BaseIntensityMatrix,
points: int = 3,
scans: int = 1) -> List[Peak]:
"""
Deconvolution based on the algorithm of Biller and Biemann (1974).
:param im:
:param points: Number of scans over which to consider a maxima to be a peak.
:param scans: Number of scans to combine peaks from to compensate for spectra skewing.
:return: List of detected peaks
:authors: Andrew Isaac, Dominic Davis-Foster (type assertions)
"""
if not isinstance(im, BaseIntensityMatrix):
raise TypeError("'im' must be an IntensityMatrix object")
if not isinstance(points, int):
raise TypeError("'points' must be an integer")
if not isinstance(scans, int):
raise TypeError("'scans' must be an integer")
rt_list = im.time_list
mass_list = im.mass_list
peak_list = []
maxima_im = get_maxima_matrix(im, points, scans)
for row_idx, row in enumerate(maxima_im):
if sum(row) > 0:
rt = rt_list[row_idx]
ms = MassSpectrum(mass_list, row)
peak = Peak(rt, ms)
peak.bounds = (0, row_idx, 0) # store IM index for convenience
# TODO: can the bounds be determined from the intensity matrix?
peak_list.append(peak)
return peak_list
