Add psd math
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2 changed files with 102 additions and 43 deletions
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@ -10,7 +10,7 @@ from numpy import loadtxt, array
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from scipy.io.matlab import loadmat
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# maths
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from numpy import mean, zeros, pi, sin, cos, arange
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from numpy import mean, zeros, pi, sin, cos, arange, sqrt
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from scipy.signal import welch as psd
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from scipy.interpolate import CubicSpline
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@ -121,7 +121,9 @@ class Analyzer:
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self.movement = array(
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[
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self.bench_movement[0],
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self.bench_movement[1] - self.mirror_movement[1],
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(self.settings.calib_bench * self.bench_movement[1])
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- (self.settings.calib_mirror
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* self.mirror_movement[1]),
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]
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)
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self.movement[1] -= mean(self.movement[1])
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@ -161,20 +163,29 @@ class Analyzer:
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]
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)
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def interpolate_abciss(self, abcisses):
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"""
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Return the axis that would be used by the interpolate method
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"""
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rates = 1 / array(
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[abciss[1] - abciss[0] for abciss in abcisses]
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)
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start = max([abciss[0] for abciss in abcisses])
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end = min([abciss[-1] for abciss in abcisses])
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return arange(start, end, 1 / max(rates))
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def interpolate(self, signals):
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"""
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Interpolate multiple signals with a single abciss list, which
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has the smallest interval and the biggest rate
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"""
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rates = 1 / (signals[:, 0, 1] - signals[:, 0, 0])
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start = max(signals[:, 0, 0])
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end = min(signals[:, 0, -1])
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splines = [
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CubicSpline(signal[0], signal[1]) for signal in signals
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]
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x = arange(start, end, 1 / max(rates))
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x = self.interpolate_abciss([signal[0] for signal in signals])
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signals = [array([x, spline(x)]) for spline in splines]
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@ -187,44 +198,87 @@ class Analyzer:
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"""
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coupling = self.modelisation[self.settings.coupling_name()]
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nperseg = int(len(coupling[0]) * 2) - 1
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freq_sample = 1 / (self.movement[0, 1] - self.movement[0, 0])
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nperseg = (
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int(2 * len(coupling[0])) - 1 + len(coupling[0])
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) # minimum to keep same length than coupling, but not for
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# the same frequency range, so more
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rate = 1 / (self.movement[0, 1] - self.movement[0, 0])
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result = zeros(
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len(
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self.interpolate_abciss(
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[
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psd(
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self.movement[1],
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fs=freq_sample,
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nperseg=nperseg,
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)[0],
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self.modelisation["freq"][0],
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]
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)
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)
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)
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result = zeros(coupling.shape[1])
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scattering_factor = [0, 0]
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frequencies = 0
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for index in range(len(coupling)):
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argument = (
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self.movement[1]
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* 4
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* pi
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* (index + 1)
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/ self.settings.wavelength
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phase = (index + 1) * 4 * pi / self.settings.wavelength
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factor_n = array(
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[
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*psd(
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sin(phase * self.movement[1]),
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fs=freq_sample,
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nperseg=nperseg,
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)
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]
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)
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coupling_n = array(
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[
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self.modelisation["freq"][0],
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abs(coupling[0]),
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]
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)
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factor_d = array(
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[
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*psd(
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cos(phase * self.movement[1]),
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fs=freq_sample,
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nperseg=nperseg,
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)
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]
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)
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coupling_d = array(
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[
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self.modelisation["freq"][0],
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abs(coupling[1]),
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]
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)
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unpack = self.interpolate(
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[factor_n, coupling_n, factor_d, coupling_d]
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)
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factor_n, coupling_n, factor_d, coupling_d = (
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unpack[0],
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unpack[1],
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unpack[2],
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unpack[3],
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)
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frequencies = factor_n[0]
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result += (
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scattering_factor[index]
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* (self.settings.wavelength / 4 * pi) ** 2
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sqrt(self.settings.scattering_factor[index])
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* self.settings.power_in
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/ self.settings.power_out
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* (
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(
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psd(
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sin(argument),
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fs=rate,
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nperseg=nperseg,
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)[1]
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* abs(coupling[0])
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)
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** 2
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+ (
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psd(
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cos(argument),
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fs=rate,
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nperseg=nperseg,
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)[1]
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* abs(coupling[1])
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)
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** 2
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coupling_n[1] * factor_n[1]
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+ coupling_d[1] * factor_d[1]
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)
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)
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return result
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return array(
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[
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frequencies,
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result,
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]
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)
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@ -17,7 +17,12 @@ class Settings:
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self.date = "2023_03_24"
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self.folder = Path("/home/demagny/data")
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self.modelisation = "scatterCouplingO4.mat"
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self.wavelength = 1.064e-6
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self.calib_bench = 1.15
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self.calib_mirror = 1.15
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self.wavelength = 1.064e-6 # m
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self.power_in = 23 # W
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self.power_out = 8e-3 # W
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self.scattering_factor = [1e-17, 0] # parameter to change
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index = 0
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while index < len(options):
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