def scale(self, mz, charge=1, charge_carrier=PROTON):
neutral = neutral_mass(mz, charge, charge_carrier)
scale = neutral / self.base_mass
scaled = {}
for elem, count in self.base_composition.items():
scaled[elem] = round(count * scale)
scaled_mass = calculate_mass(scaled)
delta_hydrogen = round(scaled_mass - neutral)
H = scaled["H"]
if H > delta_hydrogen:
scaled["H"] = H - delta_hydrogen
else:
scaled["H"] = 0
return scaled
def scale(self, mz, charge=1, charge_carrier=PROTON):
neutral = neutral_mass(mz, charge, charge_carrier)
scale = neutral / self.base_mass
scaled = {}
for elem, count in self.base_composition.items():
scaled[elem] = round(count * scale)
scaled_mass = calculate_mass(scaled)
delta_hydrogen = round(scaled_mass - neutral)
H = scaled["H"]
if H > delta_hydrogen:
scaled["H"] = H - delta_hydrogen
else:
scaled["H"] = 0
return scaled
def scale(self, mz, charge=1, charge_carrier=PROTON):
"""Given an m/z and a charge state, interpolate the composition
of the polymer with the matching neutral mass
Parameters
----------
mz : float
The reference m/z to calculate the neutral mass to interpolate from
charge : int, optional
The reference charge state to calculate the neutral mass. Defaults to 1
charge_carrier : float, optional
The mass of the charge carrier. Defaults to the mass of a proton.
Returns
-------
Mapping
The interpolated composition for the calculated neutral mass,
rounded to the nearest integer and hydrogen corrected.
References
----------
Senko, M. W., Beu, S. C., & McLafferty, F. W. (1995). Determination of monoisotopic masses and ion populations
for large biomolecules from resolved isotopic distributions. Journal of the American Society for Mass
Spectrometry, 6(4), 229–233. http://doi.org/10.1016/1044-0305(95)00017-8
"""
neutral = neutral_mass(mz, charge, charge_carrier)
scale = neutral / self.base_mass
scaled = {}
for elem, count in self.base_composition.items():
scaled[elem] = round(count * scale)
scaled_mass = calculate_mass(scaled)
delta_hydrogen = round(scaled_mass - neutral)
H = scaled["H"]
if H > delta_hydrogen:
scaled["H"] = H - delta_hydrogen
else:
scaled["H"] = 0
return scaled
def scale(self, mz, charge=1, charge_carrier=PROTON):
"""Given an m/z and a charge state, interpolate the composition
of the polymer with the matching neutral mass
Parameters
----------
mz : float
The reference m/z to calculate the neutral mass to interpolate from
charge : int, optional
The reference charge state to calculate the neutral mass. Defaults to 1
charge_carrier : float, optional
The mass of the charge carrier. Defaults to the mass of a proton.
Returns
-------
Mapping
The interpolated composition for the calculated neutral mass,
rounded to the nearest integer and hydrogen corrected.
References
----------
Senko, M. W., Beu, S. C., & McLafferty, F. W. (1995). Determination of monoisotopic masses and ion populations
for large biomolecules from resolved isotopic distributions. Journal of the American Society for Mass
Spectrometry, 6(4), 229–233. http://doi.org/10.1016/1044-0305(95)00017-8
"""
neutral = neutral_mass(mz, charge, charge_carrier)
scale = neutral / self.base_mass
scaled = {}
for elem, count in self.base_composition.items():
scaled[elem] = round(count * scale)
scaled_mass = calculate_mass(scaled)
delta_hydrogen = round(scaled_mass - neutral)
H = scaled["H"]
if H > delta_hydrogen:
scaled["H"] = H - delta_hydrogen
else:
scaled["H"] = 0
return scaled
def __init__(self, base_composition):
self.base_composition = dict(base_composition)
self.base_mass = calculate_mass(self.base_composition)
try:
_Averagine = Averagine
_TheoreticalIsotopicPattern = TheoreticalIsotopicPattern
from ms_deisotope._c.averagine import Averagine, TheoreticalIsotopicPattern
except ImportError as e:
print(e, "averagine")
peptide = Averagine({"C": 4.9384, "H": 7.7583, "N": 1.3577, "O": 1.4773, "S": 0.0417})
glycopeptide = Averagine({"C": 10.93, "H": 15.75, "N": 1.6577, "O": 6.4773, "S": 0.02054})
glycan = Averagine({'C': 7.0, 'H': 11.8333, 'N': 0.5, 'O': 5.16666})
permethylated_glycan = Averagine({'C': 12.0, 'H': 21.8333, 'N': 0.5, 'O': 5.16666})
heparin = Averagine({'H': 10.5, 'C': 6, 'S': 0.5, 'O': 5.5, 'N': 0.5})
_neutron_shift = calculate_mass({"C[13]": 1}) - calculate_mass({"C[12]": 1})
def isotopic_shift(charge=1):
return _neutron_shift / float(charge)
@dict_proxy("averagine")
class AveragineCache(object):
def __init__(self, averagine, backend=None, cache_truncation=1.0):
if backend is None:
backend = {}
self.backend = backend
self.averagine = Averagine(averagine)
self.cache_truncation = cache_truncation
def __init__(self, base_composition):
self.base_composition = dict(base_composition)
self.base_mass = calculate_mass(self.base_composition)
permethylated_glycan = Averagine({
'C': 12.0,
'H': 21.8333,
'N': 0.5,
'O': 5.16666
})
heparin = Averagine({'H': 10.5, 'C': 6, 'S': 0.5, 'O': 5.5, 'N': 0.5})
heparan_sulfate = Averagine({
'H': 10.667,
'C': 6.0,
'S': 1.333,
'O': 9.0,
'N': 0.667
})
_neutron_shift = calculate_mass({"C[13]": 1}) - calculate_mass({"C[12]": 1})
def isotopic_shift(charge=1):
return _neutron_shift / float(charge)
@dict_proxy("averagine")
class AveragineCache(object):
"""A wrapper around a :class:`Averagine` instance which will cache isotopic patterns
produced for new (m/z, charge) pairs and reuses it for nearby m/z values
Attributes
----------
averagine : :class:`~Averagine`
The averagine to use to generate new isotopic patterns