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
print("len signal=", len(data.signal))
print("len truncated=", len(data.truncated))
signal = data.truncated
# Real FFT on complete signal
step = data.step
print("step=", step)
fs = FrequencySpectrum(signal, step)
y = fs.spectrum * 1000.0 # ??? according to Anthony
# x = fs.freq / 1000.0 # in kHz
# Calculate mass
x = fs.freq
ms = MassSpectrum(x, y)
# Auto calib
ref_mass = 300.0939
accuracy = 0.1
# ref_mass = 18.0
ms.basic_recalibrate(ref_mass, accuracy)
x = ms.mass
delta = 10.0
startx = ref_mass - delta / 2
endx = ref_mass + delta / 2
accuracy = 1.0
p = Peaks()
mph, mpd, mask = p.prepare_detect(ref_mass, accuracy, x, y, startx, endx)
print("type mask", type(mask))
# data.truncate(data.start*2, round(len(data.signal)/2))
# excit = 1.2 ms / 0.5 micros ==> signal starts after point 2400
signal = data.signal
print("len signal =", len(signal))
# Real FFT on complete signal
step = data.step
print("step=", step)
fs = FrequencySpectrum(signal, step)
y = fs.spectrum * 1000.0 # ??? according to Anthony
# x = fs.freq / 1000.0 # in kHz
# Calculate mass
x = fs.freq
ms = MassSpectrum(x, y)
# Auto calib
ref_mass = 600.187
ref_mass = 300.0939
accuracy = 0.1
# ref_mass = 18.0
ms.auto_calib(ref_mass, accuracy)
xx = np.array(ms.mass)
# search values to detect peaks around a know mass
# mask1 = [(xx >= 26.0) & (xx < 27.0)]
# mask1 = [(xx >= 299.0) & (xx < 300.0)]
# mask1 = [(xx >= 599.0) & (xx < 600.0)]
# print("lenx=", len(xx[mask1]))
#
# mask = [(xx > 22.0) & (xx < 30.0)]
# step = 0.5 524288
filename = "D:\\PIRENEA\\DATA\\2018\\data_2018_07_20\\P1_2018_07_20_025.A00"
raw = RawDataset(filename)
signal = raw.signal
step = raw.step
# Real FFT on complete signal
fs = FrequencySpectrum(signal, step)
y = fs.spectrum * 1000.0 # ??? according to Anthony
# Calculate mass
x = fs.freq
ms = MassSpectrum(x,
ref_mass=300.0939,
cyclo_freq=255.692e3,
mag_freq=0.001e3)
xx = np.array(ms.mass)
# Auto calib
ref_mass = 300.0939
accuracy = 0.1
x = ms.mass
# Arbitrary limits for peak detection set around ref_mass
delta = 10.0
startx = ref_mass - delta / 2
endx = ref_mass + delta / 2
accuracy = 1.0
p = Peaks()
