def _pick_precursor_scan_peaks(self, precursor_scan, chosen_envelopes=None):
"""Pick peaks from the given precursor scan
Parameters
----------
precursor_scan: Scan
Scan to pick peaks from
chosen_envelopes: list, optional
list of m/z intervals to pick peaks for
Returns
-------
PeakSet
"""
if precursor_scan.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
prec_mz, prec_intensity = precursor_scan.arrays
if not self.pick_only_tandem_envelopes and self.envelope_selector is None:
prec_peaks = pick_peaks(prec_mz, prec_intensity, peak_mode=peak_mode, **self.ms1_peak_picking_args)
else:
if chosen_envelopes is None:
chosen_envelopes = self._get_envelopes(precursor_scan)
prec_peaks = pick_peaks(prec_mz, prec_intensity, peak_mode=peak_mode,
target_envelopes=chosen_envelopes,
**self.ms1_peak_picking_args)
return prec_peaks
def pick_precursor_scan_peaks(self, precursor_scan):
logger.info("Picking Precursor Scan Peaks: %r", precursor_scan)
if precursor_scan.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
prec_mz, prec_intensity = precursor_scan.arrays
if not self.pick_only_tandem_envelopes and self.envelope_selector is None:
prec_peaks = pick_peaks(prec_mz,
prec_intensity,
peak_mode=peak_mode,
**self.ms1_peak_picking_args)
else:
if self.envelope_selector is None:
chosen_envelopes = [
s.precursor_information
for s in precursor_scan.product_scans
]
chosen_envelopes = sorted([(p.mz - 5, p.mz + 10)
for p in chosen_envelopes])
else:
chosen_envelopes = self.envelope_selector(precursor_scan)
prec_peaks = pick_peaks(prec_mz,
prec_intensity,
peak_mode=peak_mode,
target_envelopes=chosen_envelopes,
**self.ms1_peak_picking_args)
precursor_scan.peak_set = prec_peaks
return prec_peaks
def _pick_precursor_scan_peaks(self,
precursor_scan,
chosen_envelopes=None):
"""Pick peaks from the given precursor scan
Parameters
----------
precursor_scan: Scan
Scan to pick peaks from
chosen_envelopes: list, optional
list of m/z intervals to pick peaks for
Returns
-------
PeakSet
"""
if precursor_scan.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
prec_mz, prec_intensity = precursor_scan.arrays
if not self.pick_only_tandem_envelopes and self.envelope_selector is None:
prec_peaks = pick_peaks(prec_mz,
prec_intensity,
peak_mode=peak_mode,
**self.ms1_peak_picking_args)
else:
if chosen_envelopes is None:
chosen_envelopes = self._get_envelopes(precursor_scan)
prec_peaks = pick_peaks(prec_mz,
prec_intensity,
peak_mode=peak_mode,
target_envelopes=chosen_envelopes,
**self.ms1_peak_picking_args)
return prec_peaks
def test_empty(self):
peaks = []
x, y = reprofile(peaks)
repicked = pick_peaks(x, y)
assert len(repicked) == 0
peaks = self.make_data()
peaks[0].full_width_at_half_max = 10
x, y = reprofile(peaks, max_fwhm=1.0)
repicked = pick_peaks(x, y)
assert len(repicked) == 0
def pick_peaks(self, *args, **kwargs):
"""A wrapper around :func:`ms_peak_picker.pick_peaks` which will populate the
:attr:`peak_set` attribute of this scan.
Parameters
----------
*args :
Passed along to :func:`ms_peak_picker.pick_peaks`
**kwargs : TYPE
Passed along to :func:`ms_peak_picker.pick_peaks`
Returns
-------
self
"""
mzs, intensities = self.arrays
if self.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
kwargs['peak_mode'] = peak_mode
self.peak_set = pick_peaks(mzs, intensities, *args, **kwargs)
return self
def pick_product_scan_peaks(self, product_scan):
"""Pick the peaks of product scan
Parameter
---------
product_scan: :class:`~.Scan`
The scan to pick peaks from.
Returns
-------
PeakSet
"""
if product_scan.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
product_mz, product_intensity = product_scan.arrays
peaks = pick_peaks(product_mz, product_intensity, peak_mode=peak_mode, **self.msn_peak_picking_args)
if peaks is None:
raise EmptyScanError(
"Could not pick peaks for empty product scan", self)
product_scan.peak_set = peaks
return peaks
def pick_product_scan_peaks(self, product_scan):
"""Pick the peaks of product scan
Parameters
----------
product_scan: :class:`~.Scan`
The scan to pick peaks from.
Returns
-------
PeakSet
"""
if product_scan.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
product_mz, product_intensity = product_scan.arrays
peaks = pick_peaks(product_mz,
product_intensity,
peak_mode=peak_mode,
**self.msn_peak_picking_args)
if peaks is None:
raise EmptyScanError("Could not pick peaks for empty product scan",
self)
product_scan.peak_set = peaks
return peaks
def pick_peaks(self, *args, **kwargs):
"""A wrapper around :func:`ms_peak_picker.pick_peaks` which will populate the
:attr:`peak_set` attribute of this scan.
Parameters
----------
*args :
Passed along to :func:`ms_peak_picker.pick_peaks`
**kwargs : TYPE
Passed along to :func:`ms_peak_picker.pick_peaks`
Returns
-------
self
"""
mzs, intensities = self.arrays
if self.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
kwargs['peak_mode'] = peak_mode
self.peak_set = pick_peaks(mzs, intensities, *args, **kwargs)
return self
def pick_product_scan_peaks(self, product_scan):
if product_scan.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
product_mz, product_intensity = product_scan.arrays
peaks = pick_peaks(product_mz, product_intensity, peak_mode=peak_mode, **self.msn_peak_picking_args)
product_scan.peak_set = peaks
return peaks
def _get_centroids(self, scan):
mzs, intensities = self.read_spectrum(scan.frame.id, scan.start_scan,
scan.end_scan)
sort_mask = np.argsort(mzs)
mzs = mzs[sort_mask]
intensities = intensities[sort_mask]
centroids = pick_peaks(mzs, intensities, peak_mode="centroid")
if centroids is None:
centroids = PeakIndex(np.array([], float), np.array([], float), [])
return centroids
def pick_product_scan_peaks(self, product_scan):
if product_scan.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
product_mz, product_intensity = product_scan.arrays
peaks = pick_peaks(product_mz,
product_intensity,
peak_mode=peak_mode,
**self.msn_peak_picking_args)
product_scan.peak_set = peaks
return peaks
def pick_precursor_scan_peaks(self, precursor_scan):
logger.info("Picking Precursor Scan Peaks: %r", precursor_scan)
if precursor_scan.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
prec_mz, prec_intensity = precursor_scan.arrays
if not self.pick_only_tandem_envelopes and self.envelope_selector is None:
prec_peaks = pick_peaks(prec_mz, prec_intensity, peak_mode=peak_mode, **self.ms1_peak_picking_args)
else:
if self.envelope_selector is None:
chosen_envelopes = [s.precursor_information for s in precursor_scan.product_scans]
chosen_envelopes = sorted([(p.mz - 5, p.mz + 10) for p in chosen_envelopes])
else:
chosen_envelopes = self.envelope_selector(precursor_scan)
prec_peaks = pick_peaks(prec_mz, prec_intensity, peak_mode=peak_mode,
target_envelopes=chosen_envelopes,
**self.ms1_peak_picking_args)
precursor_scan.peak_set = prec_peaks
return prec_peaks
def pick_peaks(self, *args, **kwargs):
"""A wrapper around :func:`ms_peak_picker.pick_peaks` which will populate the
:attr:`peak_set` attribute of this scan.
Parameters
----------
fit_type : str, optional
The name of the peak model to use. One of "quadratic", "gaussian", "lorentzian", or "apex"
signal_to_noise_threshold : int, optional
Minimum signal-to-noise measurement to accept a peak
intensity_threshold : int, optional
Minimum intensity measurement to accept a peak
threshold_data : bool, optional
Whether to apply thresholds to the data
target_envelopes : list, optional
A sequence of (start m/z, end m/z) pairs, limiting peak picking to only those intervals
transforms : list, optional
A list of :class:`scan_filter.FilterBase` instances or callable that
accepts (mz_array, intensity_array) and returns (mz_array, intensity_array) or
`str` matching one of the premade names in `scan_filter.filter_register`
verbose : bool, optional
Whether to log extra information while picking peaks
start_mz : float, optional
A minimum m/z value to start picking peaks from
stop_mz : float, optional
A maximum m/z value to stop picking peaks after
*args :
Passed along to :func:`ms_peak_picker.pick_peaks`
**kwargs :
Passed along to :func:`ms_peak_picker.pick_peaks`
Returns
-------
Scan
Returns self
"""
mzs, intensities = self.arrays
if len(mzs) == 0:
self.peak_set = PeakIndex(mzs, intensities, PeakSet([]))
return self
if self.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
kwargs.setdefault('peak_mode', peak_mode)
self.peak_set = pick_peaks(mzs, intensities, *args, **kwargs)
return self
def pick_product_scan_peaks(self, product_scan):
if product_scan.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
product_mz, product_intensity = product_scan.arrays
peaks = pick_peaks(product_mz,
product_intensity,
peak_mode=peak_mode,
**self.msn_peak_picking_args)
if peaks is None:
raise EmptyScanError("Could not pick peaks for empty product scan",
self)
product_scan.peak_set = peaks
return peaks
def _scan_arrays(self, scan):
if scan.is_combined():
mzs, intensities = self.read_spectrum(
scan.frame.id, scan.start_scan, scan.end_scan)
if len(mzs) == 0:
return np.array([], dtype=float), np.array([], dtype=float)
sort_mask = np.argsort(mzs)
mzs = mzs[sort_mask]
intensities = intensities[sort_mask]
centroids = pick_peaks(mzs, intensities, peak_mode="centroid")
if centroids is None:
return np.array([], dtype=float), np.array([], dtype=float)
mzs, intensities = reprofile(
centroids, dx=self._scan_merging_parameters['dx'],
override_fwhm=self._scan_merging_parameters['fwhm'])
return mzs, intensities
else:
mzs, intensities = self.read_spectrum(scan.frame.id, scan.start_scan, scan.end_scan)
return mzs, intensities
def _average_ms1(self, precursor_scan):
"""Average signal from :attr:`self.ms1_averaging` scans from
before and after ``precursor_scan`` and pick peaks from the
averaged arrays.
Parameters
----------
precursor_scan: Scan
The scan to use as a point of reference
Returns
-------
PeakSet
"""
new_scan = precursor_scan.average(self.ms1_averaging)
prec_peaks = pick_peaks(*new_scan.arrays,
target_envelopes=self._get_envelopes(precursor_scan),
**self.ms1_peak_picking_args)
return prec_peaks
def _average_ms1(self, precursor_scan):
"""Average signal from :attr:`self.ms1_averaging` scans from
before and after ``precursor_scan`` and pick peaks from the
averaged arrays.
Parameters
----------
precursor_scan: Scan
The scan to use as a point of reference
Returns
-------
PeakSet
"""
new_scan = precursor_scan.average(self.ms1_averaging)
prec_peaks = pick_peaks(
*new_scan.arrays,
target_envelopes=self._get_envelopes(precursor_scan),
**self.ms1_peak_picking_args)
return prec_peaks
def pick_peaks_from_file(path):
reader = PointListReader(path)
return pick_peaks(reader.mzs, reader.intensities, "lorenztian")
def pick_peaks_from_file(path):
reader = PointListReader(path)
return pick_peaks(reader.mzs, reader.intensities, "lorenztian")
def test_reprofile(self):
peaks = self.make_data()
x, y = reprofile(peaks)
repicked = pick_peaks(x, y)
diff = repicked[0].mz - peaks[0].mz
assert abs(diff) < 1e-3
def pick_peaks(self, *args, **kwargs):
"""A wrapper around :func:`ms_peak_picker.pick_peaks` which will populate the
:attr:`peak_set` attribute of this scan.
Parameters
----------
fit_type : str, optional
The name of the peak model to use. One of "quadratic", "gaussian", "lorentzian", or "apex"
signal_to_noise_threshold : int, optional
Minimum signal-to-noise measurement to accept a peak
intensity_threshold : int, optional
Minimum intensity measurement to accept a peak
threshold_data : bool, optional
Whether to apply thresholds to the data
target_envelopes : list, optional
A sequence of (start m/z, end m/z) pairs, limiting peak picking to only those intervals
transforms : list, optional
A list of :class:`scan_filter.FilterBase` instances or callable that
accepts (mz_array, intensity_array) and returns (mz_array, intensity_array) or
`str` matching one of the premade names in `scan_filter.filter_register`
verbose : bool, optional
Whether to log extra information while picking peaks
start_mz : float, optional
A minimum m/z value to start picking peaks from
stop_mz : float, optional
A maximum m/z value to stop picking peaks after
*args :
Passed along to :func:`ms_peak_picker.pick_peaks`
**kwargs :
Passed along to :func:`ms_peak_picker.pick_peaks`
Returns
-------
Scan
Returns self
"""
# Check to see if the user requested one of the ms_peak_picker fits or wanted
# to use the vendor peak picker if provided.
fit_type_k = kwargs.get("fit_type")
if len(args) > 0:
fit_type_a = args[0]
else:
fit_type_a = None
if fit_type_k == 'vendor' or fit_type_a == 'vendor':
try:
peaks = self.source._pick_peaks_vendor(self._data, *args,
**kwargs)
self.peak_set = peaks
return self
except NotImplementedError:
pass
# Prepare the peak picking parameters
mzs, intensities = self.arrays
if len(mzs) == 0:
self.peak_set = PeakIndex(mzs, intensities, PeakSet([]))
return self
if self.is_profile:
peak_mode = 'profile'
else:
peak_mode = 'centroid'
kwargs.setdefault('peak_mode', peak_mode)
self.peak_set = pick_peaks(mzs, intensities, *args, **kwargs)
return self
def test_denoise(self):
x, y = self.make_data()
denoised_x, denoised_y = denoise(x, y, window_size=2.0)
assert y.mean() >= 100.0
assert denoised_y.mean() < 1.0
assert len(pick_peaks(denoised_x, denoised_y)) == 1
