python-interface/mspy/obj_scan.py at master · astams/python-interface · GitHub

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# -------------------------------------------------------------------------

# This program is free software; you can redistribute it and/or modify

# it under the terms of the GNU General Public License as published by

# the Free Software Foundation; either version 3 of the License, or

# (at your option) any later version.

# This program is distributed in the hope that it will be useful,

# but WITHOUT ANY WARRANTY; without even the implied warranty of

# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the

# GNU General Public License for more details.

# Complete text of GNU GPL can be found in the file LICENSE.TXT in the

# main directory of the program.

# -------------------------------------------------------------------------

#load libs

import numpy

import copy

# load stopper

from mod_stopper import CHECK_FORCE_QUIT

# load objects

import obj_peak

import obj_peaklist

# load modules

import mod_signal

import mod_peakpicking

# SCAN OBJECT DEFINITION

# ----------------------

class scan:

"""Scan object definition."""

def __init__(self, profile=[], peaklist=[], **attr):

self.title = ''

self.scanNumber = None

self.parentScanNumber = None

self.polarity = None

self.msLevel = None

self.retentionTime = None

self.totIonCurrent = None

self.basePeakMZ = None

self.basePeakIntensity = None

self.precursorMZ = None

self.precursorIntensity = None

self.precursorCharge = None

# buffers

self._baseline = None

self._baselineParams = {'window': None, 'offset': None}

# convert profile to numPy array

if not isinstance(profile, numpy.ndarray):

profile = numpy.array(profile)

self.profile = profile

# convert peaks to peaklist

if not isinstance(peaklist, obj_peaklist.peaklist):

peaklist = obj_peaklist.peaklist(peaklist)

self.peaklist = peaklist

# get additional attributes

self.attributes = {}

for name, value in attr.items():

self.attributes[name] = value

# ----

def __len__(self):

return len(self.profile)

# ----

def __add__(self, other):

"""Return A+B."""

new = self.duplicate()

new.combine(other)

return new

# ----

def __sub__(self, other):

"""Return A-B."""

new = self.duplicate()

new.subtract(other)

return new

# ----

def __mul__(self, y):

"""Return A*y."""

new = self.duplicate()

new.multiply(y)

return new

# ----

def reset(self):

"""Clear scan buffers."""

self._baseline = None

self._baselineParams = {'window': None, 'offset': None}

# ----

# GETTERS

def duplicate(self):

"""Return copy of current scan."""

return copy.deepcopy(self)

# ----

def noise(self, minX=None, maxX=None, mz=None, window=0.1):

"""Return noise level and width for specified m/z range or m/z value.

minX (float) - lower m/z limit

maxX (float) - upper m/z limit

mz (float) - m/z value

window (float) - percentage around specified m/z value to use for noise calculation

"""

# calculate noise

return mod_signal.noise(

signal = self.profile,

minX = minX,

maxX = maxX,

x = mz,

window = window

)

# ----

def baseline(self, window=0.1, offset=0.):

"""Return spectrum baseline data.

window (float or None) - noise calculation window (%/100)

offset (float) - baseline offset, relative to noise width (in %/100)

"""

# calculate baseline

if self._baseline == None \

or self._baselineParams['window'] != window \

or self._baselineParams['offset'] != offset:

self._baseline = mod_signal.baseline(

signal = self.profile,

window = window,

offset = offset

)

self._baselineParams['window'] = window

self._baselineParams['offset'] = offset

return self._baseline

# ----

def normalization(self):

"""Return normalization params."""

# calculate range for spectrum and peaklist

if len(self.profile) > 0 and len(self.peaklist) > 0:

spectrumMax = numpy.maximum.reduce(self.profile)[1]

spectrumMin = numpy.minimum.reduce(self.profile)[1]

peaklistMax = max([peak.ai for peak in self.peaklist])

peaklistMin = min([peak.base for peak in self.peaklist])

return max(spectrumMax, peaklistMax)/100.

# calculate range for spectrum only

elif len(self.profile) > 0:

spectrumMax = numpy.maximum.reduce(self.profile)[1]

shift = numpy.minimum.reduce(self.profile)[1]

return spectrumMax/100.

# calculate range for peaklist only

elif len(self.peaklist) > 0:

peaklistMax = max([peak.ai for peak in self.peaklist])

shift = min([peak.base for peak in self.peaklist])

return peaklistMax/100.

# no data

else:

return 1.

# ----

def intensity(self, mz):

"""Return interpolated intensity for given m/z.

mz (float) - m/z value

"""

# calculate peak intensity

return mod_signal.intensity(self.profile, mz)

# ----

def width(self, mz, intensity):

"""Return peak width for given m/z and height.

mz (float) - peak m/z value

intensity (float) - intensity of width measurement

"""

# calculate peak width

return mod_signal.width(self.profile, mz, intensity)

# ----

def area(self, minX=None, maxX=None, baselineWindow=0.1, baselineOffset=0.):

"""Return labeled peak in given m/z range.

minX (float) - starting m/z value

maxX (float) - ending m/z value

baselineWindow (float or None) - noise calculation window (%/100)

baselineOffset (float) - baseline offset, relative to noise width (in %/100)

"""

# check data

if len(self.profile) == 0:

return 0.0

# get baseline

baseline = self.baseline(

window = baselineWindow,

offset = baselineOffset

)

# get peak area

area = mod_signal.area(

signal = self.profile,

minX = minX,

maxX = maxX,

baseline = baseline

)

return area

# ----

def hasprofile(self):

"""Return true if scan has profile data."""

return bool(len(self.profile))

# ----

def haspeaks(self):

"""Return true if scan has peaks in peaklist."""

return bool(len(self.peaklist))

# ----

# SETTERS

def setprofile(self, profile):

"""Set new profile data."""

self.profile = profile

self.reset()

# ----

def setpeaklist(self, peaks):

"""Set new peaklist."""

# convert peaks to peaklist

if isinstance(peaks, obj_peaklist.peaklist):

self.peaklist = peaks

else:

self.peaklist = obj_peaklist.peaklist(peaks)

# ----

# MODIFIERS

def swap(self):

"""Swap data between profile and peaklist."""

# make new profile

profile = [[i.mz, i.ai] for i in self.peaklist]

profile = numpy.array(profile)

# make new peaklist

peaks = [obj_peak.peak(i[0],i[1]) for i in self.profile]

peaks = obj_peaklist.peaklist(peaks)

# update scan

self.profile = profile

self.peaklist = peaks

# clear buffers

self.reset()

# ----

def crop(self, minX, maxX):

"""Crop profile and peaklist.

minX (float) - lower m/z limit

maxX (float) - upper m/z limit

"""

# crop spectrum data

self.profile = mod_signal.crop(self.profile, minX, maxX)

# crop peaklist data

self.peaklist.crop(minX, maxX)

# clear buffers

self.reset()

# ----

def multiply(self, y):

"""Multiply profile and peaklist by Y.

y (int or float) - multiplier factor

"""

# multiply spectrum

if len(self.profile):

self.profile = mod_signal.multiply(self.profile, y=y)

# multiply peakslist

self.peaklist.multiply(y)

# clear buffers

self.reset()

# ----

def normalize(self):

"""Normalize profile and peaklist."""

# get normalization params

f = self.normalization()

# normalize profile

if len(self.profile) > 0:

self.profile /= numpy.array((1, f))

# normalize peaklist

if len(self.peaklist) > 0:

for peak in self.peaklist:

peak.setai(peak.ai / f)

peak.setbase(peak.base / f)

self.peaklist.reset()

# clear buffers

self.reset()

# ----

def combine(self, other):

"""Add data from given scan.

other (mspy.scan) - scan to combine with

"""

# check scan

if not isinstance(other, scan):

raise TypeError, "Cannot combine with non-scan object!"

# use profiles only

if len(self.profile) or len(other.profile):

# combine profiles

self.profile = mod_signal.combine(self.profile, other.profile)

# empty peaklist

self.peaklist.empty()

# use peaklists only

elif len(self.peaklist) or len(other.peaklist):

self.peaklist.combine(other.peaklist)

# clear buffers

self.reset()

# ----

def overlay(self, other):

"""Overlay with data from given scan.

other (mspy.scan) - scan to overlay with

"""

# check scan

if not isinstance(other, scan):

raise TypeError, "Cannot overlay with non-scan object!"

# use profiles only

if len(self.profile) or len(other.profile):

# overlay profiles

self.profile = mod_signal.overlay(self.profile, other.profile)

# empty peaklist

self.peaklist.empty()

# clear buffers

self.reset()

# ----

def subtract(self, other):

"""Subtract given data from current scan.

other (mspy.scan) - scan to subtract

"""

# check scan

if not isinstance(other, scan):

raise TypeError, "Cannot subtract non-scan object!"

# use profiles only

if len(self.profile) and len(other.profile):

# subtract profile

self.profile = mod_signal.subtract(self.profile, other.profile)

# empty peaklist

self.peaklist.empty()

# clear buffers

self.reset()

# ----

def smooth(self, method, window, cycles=1):

"""Smooth profile.

method (MA GA SG) - smoothing method

window (float) - m/z window size for smoothing

cycles (int) - number of repeating cycles

"""

# smooth data

profile = mod_signal.smooth(

signal = self.profile,

method = method,

window = window,

cycles = cycles

)

# store data

self.profile = profile

self.peaklist.empty()

# clear buffers

self.reset()

# ----

def recalibrate(self, fn, params):

"""Apply calibration to profile and peaklist.

fn (function) - calibration model

params (list or tuple) - params for calibration model

"""

# calibrate profile

for x, point in enumerate(self.profile):

self.profile[x][0] = fn(params, point[0])

# calibrate peaklist

self.peaklist.recalibrate(fn, params)

# clear buffers

self.reset()

# ----

def subbase(self, window=0.1, offset=0.):

"""Subtract baseline from profile.

window (float or None) - noise calculation window (%/100)

offset (float) - baseline offset, relative to noise width (in %/100)

"""

# get baseline

baseline = self.baseline(

window = window,

offset = offset

)

# subtract baseline

profile = mod_signal.subbase(

signal = self.profile,

baseline = baseline

)

# store data

self.profile = profile

self.peaklist.empty()

# clear buffers

self.reset()

# ----

# PEAKLIST FUNCTIONS

def labelscan(self, pickingHeight=0.75, absThreshold=0., relThreshold=0., snThreshold=0., baselineWindow=0.1, baselineOffset=0., smoothMethod=None, smoothWindow=0.2, smoothCycles=1):

"""Label centroides in current scan.

pickingHeight (float) - peak picking height for centroiding

absThreshold (float) - absolute intensity threshold

relThreshold (float) - relative intensity threshold

snThreshold (float) - signal to noise threshold

baselineWindow (float) - noise calculation window (in %/100)

baselineOffset (float) - baseline offset, relative to noise width (in %/100)

smoothMethod (None, MA, GA or SG) - smoothing method

smoothWindow (float) - m/z window size for smoothing

smoothCycles (int) - number of smoothing cycles

"""

# get baseline

baseline = self.baseline(

window = baselineWindow,

offset = baselineOffset

)

# pre-smooth profile

profile = self.profile

if smoothMethod:

profile = mod_signal.smooth(

signal = profile,

method = smoothMethod,

window = smoothWindow,

cycles = smoothCycles

)

# label peaks

peaklist = mod_peakpicking.labelscan(

signal = profile,

pickingHeight = pickingHeight,

absThreshold = absThreshold,

relThreshold = relThreshold,

snThreshold = snThreshold,

baseline = baseline

)

# check peaklist

if peaklist == None:

return False

# update peaklist

self.peaklist = peaklist

return True

# ----

def labelpeak(self, mz=None, minX=None, maxX=None, pickingHeight=0.75, baselineWindow=0.1, baselineOffset=0.):

"""Return labeled peak in given m/z range.

mz (float) - m/z value to label

minX (float) - m/z range start

maxX (float) - m/z range end

pickingHeight (float) - centroiding height

baselineWindow (float) - noise calculation window (in %/100)

baselineOffset (float) - baseline offset, relative to noise width (in %/100)

"""

# get baseline

baseline = self.baseline(

window = baselineWindow,

offset = baselineOffset

)

# label peak

peak = mod_peakpicking.labelpeak(

signal = self.profile,

mz = mz,

minX = minX,

maxX = maxX,

pickingHeight = pickingHeight,

baseline = baseline

)

# check peak

if not peak:

return False

# append peak

self.peaklist.append(peak)

return True

# ----

def labelpoint(self, mz, baselineWindow=0.1, baselineOffset=0.):

"""Label peak at given m/z value.

mz (float) - m/z value to label

baselineWindow (float) - noise calculation window (in %/100)

baselineOffset (float) - baseline offset, relative to noise width (in %/100)

"""

# get baseline

baseline = self.baseline(

window = baselineWindow,

offset = baselineOffset

)

# label point

peak = mod_peakpicking.labelpoint(

signal = self.profile,

mz = mz,

baseline = baseline

)

# check peak

if not peak:

return False

# append peak

self.peaklist.append(peak)

return True

# ----

def deisotope(self, maxCharge=1, mzTolerance=0.15, intTolerance=0.5, isotopeShift=0.0):

"""Calculate peak charges and find isotopes.

maxCharge (float) - max charge to be searched

zTolerance (float) - absolute m/z tolerance for isotopes distance

intTolerance (float) - relative intensity tolerance for isotopes and model (in %/100)

isotopeShift (float) - isotope distance correction (neutral mass) (for HDX etc.)

"""

# find istopes

self.peaklist.deisotope(

maxCharge = maxCharge,

mzTolerance = mzTolerance,

intTolerance = intTolerance,

isotopeShift = isotopeShift

)

# ----

def deconvolute(self, massType=0):

"""Recalculate peaklist to singly charged.

massType (0 or 1) - mass type used for m/z re-calculation, 0 = monoisotopic, 1 = average

"""

# delete profile data

self.profile = numpy.array([])

# deconvolute peaklist

self.peaklist.deconvolute(massType=massType)

# clear buffers

self.reset()

# ----

def consolidate(self, window, forceWindow=False):

"""Group peaks within specified window.

window (float) - default grouping window if no peak fwhm

forceWindow (bool) - use default window for all peaks instead of fwhm

"""

self.peaklist.consolidate(

window = window,

forceWindow = forceWindow

)

# ----

def remthreshold(self, absThreshold=0., relThreshold=0., snThreshold=0.):

"""Remove peaks below threshold.

absThreshold (float) - absolute intensity threshold

relThreshold (float) - relative intensity threshold

snThreshold (float) - signal to noise threshold

"""

self.peaklist.remthreshold(

absThreshold = absThreshold,

relThreshold = relThreshold,

snThreshold = snThreshold

)

# ----

def remshoulders(self, window=2.5, relThreshold=0.05, fwhm=0.01):

"""Remove shoulder peaks from current peaklist.

window (float) - peak width multiplier to make search window

relThreshold (float) - max relative intensity of shoulder/parent peak (in %/100)

fwhm (float) - default peak width if not set in peak

"""

self.peaklist.remshoulders(

window = window,

relThreshold = relThreshold,

fwhm = fwhm

)

# ----

def remisotopes(self):

"""Remove isotopes from current peaklist."""

self.peaklist.remisotopes()

# ----

def remuncharged(self):

"""Remove uncharged peaks from current peaklist."""

self.peaklist.remuncharged()

# ----

python-interface/mspy/obj_scan.py at master · astams/python-interface · GitHub

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