PeakPickerMaxima

class pyopenms.PeakPickerMaxima

Bases: object

Cython implementation of _PeakPickerMaxima

Original C++ documentation is available here

This class implements a fast peak-picking algorithm best suited for high resolution MS data (FT-ICR-MS, Orbitrap). In high resolution data, the signals of ions with similar mass-to-charge ratios (m/z) exhibit little or no overlapping and therefore allow for a clear separation. Furthermore, ion signals tend to show well-defined peak shapes with narrow peak width

This peak-picking algorithm detects ion signals in raw data and reconstructs the corresponding peak shape by cubic spline interpolation. Signal detection depends on the signal-to-noise ratio which is adjustable by the user (see parameter signal_to_noise). A picked peak’s m/z and intensity value is given by the maximum of the underlying peak spline

So far, this peak picker was mainly tested on high resolution data. With appropriate preprocessing steps (e.g. noise reduction and baseline subtraction), it might be also applied to low resolution data

__init__()

Overload:

__init__(self, signal_to_noise: float, spacing_difference: float, sn_window_length: float) → None

Overload:

__init__(self, in_0: PeakPickerMaxima) → None

Methods

__init__	Overload:
findMaxima(self, mz_array, int_array, pc)	Will find local maxima in raw data
pick(self, mz_array, int_array, pc)

findMaxima(self, mz_array: List[float], int_array: List[float], pc: List[PeakCandidate]) → None

Will find local maxima in raw data

Parameters:

• mz_array – The array containing m/z values

• int_array – The array containing intensity values

• pc – The resulting array containing the peak candidates

• check_spacings – Check spacing constraints (recommended settings: yes for spectra, no for chromatograms)

pick(self, mz_array: List[float], int_array: List[float], pc: List[PeakCandidate]) → None