def _merge(spectra,
mz_tolerance=1.3e-3,
only_common_peaks=False,
verbose=True):
"""merges a list of spectra to one spetrum.
*mz_tolerance* : binning size for grouping peaks.
*only_common_peaks*: if this value is true the resulting spectrum
only consists of dominant peaks which are present
in every input spectrum
*verbose*: print diagnosis messages if this value is True
"""
if not spectra:
return None
if len(spectra) == 1:
return spectra[0]
alignments = Spectrum.compute_alignments(spectra, mz_tolerance)
common = _botton_up_common(alignments)
mz_vecs = [s.peaks[:, 0] for s in spectra]
intensity_vecs = [s.peaks[:, 1] for s in spectra]
if only_common_peaks:
mz_last = mz_vecs[-1]
ii_last = intensity_vecs[-1]
peaks = [(mz_last[i], ii_last[i]) for i in common]
return _final_spectrum(peaks, spectra)
scalings = _determine_scaling_factors(mz_vecs, intensity_vecs, alignments,
common)
if scalings is not None:
peaks = _overlay(mz_vecs, intensity_vecs, scalings, mz_tolerance,
verbose, len(common))
else:
peaks = [np.empty((0, 2))]
return _final_spectrum(peaks, spectra)
def _merge(spectra, mz_tolerance=1.3e-3, only_common_peaks=False, verbose=True):
"""merges a list of spectra to one spetrum.
*mz_tolerance* : binning size for grouping peaks.
*only_common_peaks*: if this value is true the resulting spectrum
only consists of dominant peaks which are present
in every input spectrum
*verbose*: print diagnosis messages if this value is True
"""
if not spectra:
return None
if len(spectra) == 1:
return spectra[0]
alignments = Spectrum.compute_alignments(spectra, mz_tolerance)
common = _botton_up_common(alignments)
mz_vecs = [s.peaks[:, 0] for s in spectra]
intensity_vecs = [s.peaks[:, 1] for s in spectra]
if only_common_peaks:
mz_last = mz_vecs[-1]
ii_last = intensity_vecs[-1]
peaks = [(mz_last[i], ii_last[i]) for i in common]
return _final_spectrum(peaks, spectra)
scalings = _determine_scaling_factors(mz_vecs, intensity_vecs, alignments, common)
if scalings is not None:
peaks = _overlay(mz_vecs, intensity_vecs, scalings, mz_tolerance, verbose, len(common))
else:
peaks = [np.empty((0, 2))]
return _final_spectrum(peaks, spectra)
