def __init__(self,
nodes=None,
adducts=None,
used_as_adduct=None,
feature_id=None):
if nodes is None:
nodes = []
if adducts is None:
adducts = []
if used_as_adduct is None:
used_as_adduct = []
if feature_id is None:
feature_id = uid()
FeatureBase.__init__(self, nodes)
self._total_intensity = None
self._mz = None
self._last_mz = 0.0
self._times = None
self._peaks = None
self._start_time = None
self._end_time = None
self.adducts = adducts
self.used_as_adduct = used_as_adduct
self.feature_id = feature_id
self._peak_averager = RunningWeightedAverage()
if len(self) > 0:
self._feed_peak_averager()
def __init__(self, id=None, groups=None):
self.id = id or uid()
self.groups = sorted(groups or [], key=lambda x: x.order)
self.analyzers = []
for group in self.groups:
if group.type == 'analyzer':
self.analyzers.extend(group)
def __init__(self, time=None, members=None):
if members is None:
members = []
self.time = time
self.members = members
self._most_abundant_member = None
self._mz = 0
self._recalculate()
self.node_id = uid()
def __init__(self, time=None, members=None):
if members is None:
members = []
self.time = time
self.members = members
self._most_abundant_member = None
self._mz = 0
self._recalculate()
self.node_id = uid()
def __init__(self, peak_set, span=None, epsilon=0.02, key=None):
if span is None:
span = 0
if key is None:
key = uid()
self.key = key
self.peak_set = peak_set
self.span = max(span, self._guess_span())
self.epsilon = epsilon
self.indices = None
self.binned_signal = None
self.discretize()
def __init__(self, nodes=None, adducts=None, used_as_adduct=None, feature_id=None):
if nodes is None:
nodes = []
if adducts is None:
adducts = []
if used_as_adduct is None:
used_as_adduct = []
if feature_id is None:
feature_id = uid()
FeatureBase.__init__(self, nodes)
self._total_intensity = None
self._mz = None
self._last_mz = 0.0
self._times = None
self._peaks = None
self._start_time = None
self._end_time = None
self.adducts = adducts
self.used_as_adduct = used_as_adduct
self.feature_id = feature_id
self._initialize_averager()
def __init__(self, nodes=None, adducts=None, used_as_adduct=None, feature_id=None):
if nodes is None:
nodes = []
if adducts is None:
adducts = []
if used_as_adduct is None:
used_as_adduct = []
if feature_id is None:
feature_id = uid()
FeatureBase.__init__(self, nodes)
self._total_intensity = None
self._mz = None
self._last_mz = 0.0
self._times = None
self._peaks = None
self._start_time = None
self._end_time = None
self.adducts = adducts
self.used_as_adduct = used_as_adduct
self.feature_id = feature_id
self._peak_averager = RunningWeightedAverage()
if len(self) > 0:
self._feed_peak_averager()
def __init__(self, methods=None, id=None):
self.methods = methods or []
self.id = id or uid()
def __init__(self, methods=None, id=None):
self.methods = methods or []
self.id = id or uid()