Source code for matchms.filtering.add_losses

import logging
import numpy
from ..Fragments import Fragments
from ..typing import SpectrumType

logger = logging.getLogger("matchms")

[docs]def add_losses(spectrum_in: SpectrumType, loss_mz_from=0.0, loss_mz_to=1000.0) -> SpectrumType: """Derive losses based on precursor mass. Parameters ---------- spectrum_in: Input spectrum. loss_mz_from: Minimum allowed m/z value for losses. Default is 0.0. loss_mz_to: Maximum allowed m/z value for losses. Default is 1000.0. """ if spectrum_in is None: return None spectrum = spectrum_in.clone() precursor_mz = spectrum.get("precursor_mz", None) if precursor_mz: assert isinstance(precursor_mz, (float, int)), ("Expected 'precursor_mz' to be a scalar number.", "Consider applying 'add_precursor_mz' filter first.") peaks_mz, peaks_intensities =, spectrum.peaks.intensities losses_mz = (precursor_mz - peaks_mz)[::-1] losses_intensities = peaks_intensities[::-1] # Add losses which are within given boundaries mask = numpy.where((losses_mz >= loss_mz_from) & (losses_mz <= loss_mz_to)) spectrum.losses = Fragments(mz=losses_mz[mask], intensities=losses_intensities[mask]) else: logger.warning("No precursor_mz found. Consider applying 'add_precursor_mz' filter first.") return spectrum