def __find_limits(self):
"""
Find the beginning and the end of signal just after excitation buffer
"""
# if script is available, get limits according excitation length
if self.scriptable:
s = Script(self.filename)
duration = s.get_excit_duration()
self.start = round(duration / self.step)
self.end = round(self.points / 2)
# if script is not available, fix arbitrary limits
else:
self.start = 0
self.end = round(self.points / 2)
def __find_limits(self):
"""
Find the beginning and the end of signal just after excitation buffer
"""
# if script is available, get limits according excitation length
if self.scriptable:
s = Script(self.filename)
duration = s.get_excit_duration()
self.start = round(duration / self.step)
self.end = round(self.points / 2)
# if script is not available, fix arbitrary limits
else:
self.start = 0
self.end = round(self.points / 2)
def __process_file(self):
""" operations on files """
self.raw = RawDataset(self.filename)
self.step = self.raw.step
self.points = self.raw.points
self.scr = None
# if script is available, get limits according excitation length
if self.raw.scriptable:
self.scr = Script(self.filename)
duration = self.scr.get_excit_duration()
self.start = round(duration / self.step)
self.end = self.points
# if script is not available, fix arbitrary limits
else:
self.start = 0
self.end = self.points
def __process_file(self):
""" operations on files """
self.raw = RawDataset(self.filename)
self.step = self.raw.step
self.points = self.raw.points
self.scr = None
# if script is available, get limits according excitation length
if self.raw.scriptable:
self.scr = Script(self.filename)
duration = self.scr.get_excit_duration()
self.start = round(duration / self.step)
self.end = round(self.points / 2)
# if script is not available, fix arbitrary limits
else:
self.start = 0
self.end = round(self.points / 2)
class Pipeline(object):
"""
classdocs
"""
def __init__(self, filename=""):
"""
Constructor
"""
self.filename = filename
self.__process_file()
def __process_file(self):
""" operations on files """
self.raw = RawDataset(self.filename)
self.step = self.raw.step
self.points = self.raw.points
self.scr = None
# if script is available, get limits according excitation length
if self.raw.scriptable:
self.scr = Script(self.filename)
duration = self.scr.get_excit_duration()
self.start = round(duration / self.step)
self.end = self.points
# if script is not available, fix arbitrary limits
else:
self.start = 0
self.end = self.points
def process_signal(self,
start=0,
end=0,
hann=False,
half=False,
zero=False,
zero_twice=False):
self.signal = self.raw.truncate(start, end)
if hann:
self.signal = self.raw.hann(self.signal, half=False)
if half:
self.signal = self.raw.hann(self.signal, half=True)
if zero:
dummy = np.zeros(self.points)
if (end > self.points):
end = self.points
dummy[0:(end - start)] = self.signal
self.signal = dummy
if zero_twice:
dummy = np.zeros(self.points * 2)
if (end > self.points):
end = self.points
dummy[0:(end - start)] = self.signal
self.signal = dummy
def process_spectrum(self,
factor=1000.0,
ref_mass=0.0,
cyclo_freq=0.0,
mag_freq=0.0):
# t = time.time()
fs = FrequencySpectrum(self.signal, self.step)
# t1 = time.time() - t
self.spectrum = fs.spectrum * factor
self.freq = fs.freq # in Hz
ms = MassSpectrum(self.freq, ref_mass, cyclo_freq, mag_freq)
self.mass = ms.mass
# def get_excit_duration(self):
# buffer, excitation = self.scr.get_excit()
# if excitation:
# return buffer[0][3]
# else:
# return 0.0
def mass_recalibrate(self, ref_mass=0.0, accuracy=0.1):
# Auto calib
self.ref_mass = ref_mass
self.accuracy = accuracy
if ref_mass > 0.0:
self.ms.basic_recalibrate(self.ref_mass, self.accuracy)
def process_peaks(self, mph=0.0, mpd=0, startx=0.0, endx=0.0):
if mph > 0:
self.mph = mph
if mpd > 0:
self.mpd = mpd
x = self.mass
y = self.spectrum
p = Peaks()
ref = startx + (abs(endx - startx) / 2)
delta = 1.0
mph, mpd, mask = p.prepare_detect(ref, delta, x, y, startx, endx)
# Detect peak on rising edge
edge = 'rising'
# Detect peak greater than threshold
threshold = 0.0
# Don't use default plot
ind = p.detect_peaks(y[mask], self.mph, self.mpd, threshold, edge)
# print("mass =", x[mask][ind])
# print("inten=", y[mask][ind])
self.mph = mph
self.mpd = mpd
self.mask = mask
self.ind = ind
class Pipeline(object):
"""
classdocs
"""
def __init__(self, filename=""):
"""
Constructor
"""
self.filename = filename
self.__process_file()
def __process_file(self):
""" operations on files """
self.raw = RawDataset(self.filename)
self.step = self.raw.step
self.points = self.raw.points
self.scr = None
# if script is available, get limits according excitation length
if self.raw.scriptable:
self.scr = Script(self.filename)
duration = self.scr.get_excit_duration()
self.start = round(duration / self.step)
self.end = round(self.points / 2)
# if script is not available, fix arbitrary limits
else:
self.start = 0
self.end = round(self.points / 2)
def process_signal(self, start=0, end=0, hann=False, half=False, zero=False, zero_twice=False):
self.signal = self.raw.truncate(start, end)
if hann:
self.signal = self.raw.hann(self.signal, half=False)
if half:
self.signal = self.raw.hann(self.signal, half=True)
if zero:
dummy = np.zeros(self.points)
dummy[0:(end - start)] = self.signal
self.signal = dummy
if zero_twice:
dummy = np.zeros(self.points * 2)
dummy[0:(end - start)] = self.signal
self.signal = dummy
def process_spectrum(self, factor=1000.0, ref_mass=0.0, cyclo_freq=0.0, mag_freq=0.0):
# t = time.time()
fs = FrequencySpectrum(self.signal, self.step)
# t1 = time.time() - t
self.spectrum = fs.spectrum * factor
self.freq = fs.freq # in Hz
ms = MassSpectrum(self.freq, ref_mass, cyclo_freq, mag_freq)
self.mass = ms.mass
# def get_excit_duration(self):
# buffer, excitation = self.scr.get_excit()
# if excitation:
# return buffer[0][3]
# else:
# return 0.0
def mass_recalibrate(self, ref_mass=0.0, accuracy=0.1):
# Auto calib
self.ref_mass = ref_mass
self.accuracy = accuracy
if ref_mass > 0.0:
self.ms.basic_recalibrate(self.ref_mass, self.accuracy)
def process_peaks(self, mph=0.0, mpd=0, startx=0.0, endx=0.0):
if mph > 0:
self.mph = mph
if mpd > 0:
self.mpd = mpd
x = self.mass
y = self.spectrum
p = Peaks()
ref = startx + (abs(endx - startx) / 2)
delta = 1.0
mph, mpd, mask = p.prepare_detect(ref, delta, x, y, startx, endx)
# Detect peak on rising edge
edge = 'rising'
# Detect peak greater than threshold
threshold = 0.0
# Don't use default plot
ind = p.detect_peaks(y[mask], self.mph, self.mpd, threshold, edge)
# print("mass =", x[mask][ind])
# print("inten=", y[mask][ind])
self.mph = mph
self.mpd = mpd
self.mask = mask
self.ind = ind