Fixed some issues in PA code
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9833D3C5A25BD227
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@ -10,10 +10,11 @@ from scipy import signal
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import re
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from scipy.interpolate import griddata
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import scipy.io as sio
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import imageio
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from mpl_toolkits import mplot3d
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from scipy import signal
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from scipy.fftpack import fft, ifft
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from scipy.signal import detrend
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from numpy import angle
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# fonction moyenne glissante
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def lissage(Lx,Ly,p):
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@ -27,143 +28,31 @@ def lissage(Lx,Ly,p):
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Lyout.append(average)
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return Lxout,Lyout
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# import orientation data
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with open('ADV/ARTHA_aut18.sen','r') as n:
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content = n.readlines()
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heading = []
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pitch = []
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roll = []
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i = 0
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for i in range(len(content)-1):
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row = content[i].split()
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heading.append(float(row[10]))
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pitch.append(float(row[11]))
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roll.append(float(row[12]))
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i+=1
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# import Pressure and velocity measurement
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with open('ADV/ARTHA_aut18.dat','r') as n:
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content = n.readlines()
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E = []
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N = []
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Up = []
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P = []
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burstnb = []
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position = []
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i = 0
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for i in range(len(content)-1):
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row = content[i].split()
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burstnb.append(int(row[0]))
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position.append(int(row[1]))
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E.append(float(row[2]))
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N.append(float(row[3]))
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Up.append(float(row[4]))
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P.append(float(row[14]))
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i+=1
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# import seal level pressure and reshape vector to fit the ADV data
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with open('press_socoa_0110_2311_18.data','r') as n:
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content = n.readlines()[1:]
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burstind = []
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date = []
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slp = []
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ind = 1
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i = 0
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for i in range(len(content)-1):
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row = content[i].split(";")
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date.append(int(row[1]))
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slp.append(float(row[3]))
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if date[i] >= 2018101004 and date[i]%2 == 0:
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burstind.append(int(ind))
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ind+=1
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else :
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burstind.append("nan")
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i+=1
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slpind = []
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i=0
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while i<len(slp):
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if burstind[i] != 'nan' :
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slpind.append(slp[i])
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i+=1
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slpind = slpind[:304]
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# height from ground to ADV
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delta = 0.4
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# gravity
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g = 9.81
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#define time vector
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t = np.linspace(0, 1200, 2400)
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burstP = np.zeros((304,2400))
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burstE = np.zeros((304,2400))
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burstN = np.zeros((304,2400))
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i = 0
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j = 0
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n = 1
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while i < len(P) :
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burstP[n,j] = P[i] - slpind[n]/100*0.4/10.13
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burstE[n,j] = E[i]
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burstN[n,j] = N[i]
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if i >= n*2400 - 1:
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n+=1
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j=-1
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i+=1
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j+=1
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burstP = np.delete(burstP,0,0)
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burstE = np.delete(burstE,0,0)
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burstN = np.delete(burstN,0,0)
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# number of point in the burst
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N = 2400
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# time step
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T = 0.5
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#frequency vector
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xf = np.linspace(0.0, 1.0/(2.0*T), N//2)
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# hs calculation interval
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x1 = np.max(np.where(xf < 0.05))
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x2 = np.min(np.where(xf > 0.17))
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# u = vitesse hori
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# p = pression
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# h = profondeur locale
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#fs = fréquence echantillonage
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# zmesP = profondeur de mesure de la pression
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# zmesU = profondeur de mesure de la vitesse
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def PUV_dam(u,p,h,fs,zmesP,zmesU):
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u = detrend(u)
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p = detrend(p)
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#u = detrend(u)
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#p = detrend(p)
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ampliseuil = 0.001
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N = len(u)
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delta = 1.0/T
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delta = fs
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#transformée de fourrier
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Yu = fft(u)
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Yp = fft(p)
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nyquist = 1/2
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#Fu_xb = ((1:N/2)-1)/(N/2)/deltat*nyquist
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xf = np.linspace(0.0, 1.0/(2.0*T), N//2)
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Ampu = np.abs(Yu[1:N/2])/(N/2.0)
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Ampp = np.abs(Yp[1:N/2])/(N/2.0)
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xf = np.linspace(0.0, 1.0/(2.0/fs), N//2)
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Ampu = np.abs(Yu[1:N//2])/(N/2.0)
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Ampp = np.abs(Yp[1:N//2])/(N/2.0)
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#pas de frequence deltaf
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deltaf=1/(N/2)/deltat*nyquist;
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deltaf=1/(N/2)/delta*nyquist;
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#phase
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ThetaU=angle(Yu[1:N/2]);
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ThetaP=angle(Yp[1:N/2]);
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ThetaU=angle(Yu[1:N//2]);
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ThetaP=angle(Yp[1:N//2]);
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#calcul du coefficient de reflexion
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nbf=length(xf);
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nbf=len(xf);
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if max(p) > 0 :
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#si pas de données de pression, jsute Sheremet
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#attention : on commence par le deuxieme point, le premier correspondant a frequence nulle
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@ -205,8 +94,6 @@ def PUV_dam(u,p,h,fs,zmesP,zmesU):
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return Eixb,Erxb,Eprog,F
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'test'
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fs =2
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# Calcul du vecteur d'onde en prÈsence d'un courant
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# constant u de sens opposÈ ‡ celui de propagation de l'onde
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@ -229,74 +116,3 @@ def newtonpplus(f,h,u) :
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# fin du calcul de k
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u = signal.detrend(U[1])
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p = signal.detrend(burstP[1])
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ampliseuil = 0.001
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N = len(u)
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deltat = 1.0/fs
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#transformée de fourrier
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Yu = fft(u)
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Yp = fft(p)
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nyquist = 1/2.0
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# h = profondeur locale
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h = np.mean(burstP[1])
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#Fu_xb = ((1:N/2)-1)/(N/2)/deltat*nyquist
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xf = np.linspace(0.0, 1.0/(2.0*T), N//2)
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Ampu = np.abs(Yu[1:N/2])/(N/2.0)
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Ampp = np.abs(Yp[1:N/2])/(N/2.0)
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#pas de frequence deltaf
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deltaf=1.0/(N/2.0)/deltat*nyquist
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#phase
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ThetaU=np.angle(Yu[1:N/2])
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ThetaP=np.angle(Yp[1:N/2])
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#calcul du coefficient de reflexion
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#fs = fréquence echantillonage
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fs = 2
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# zmesP = profondeur de mesure de la pression
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zmesP = h - 0.4
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# zmesU = profondeur de mesure de la vitesse
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zmesU = zmesP
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nbf=len(xf)
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if max(p) > 0 :
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#si pas de données de pression, jsute Sheremet
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#attention : on commence par le deuxieme point, le premier correspondant a frequence nulle
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iicutoff_xb=max(min(np.where(xf>0.5))) #length(Fu_xb)) ?
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#calcul de l'amplitude en deca de la frequence de coupure
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k_xb = []
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omega = []
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ccc = []
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ccs = []
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cccp = []
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aincident13 =[]
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areflechi13 =[]
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r13 =[]
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aprog = []
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ii = 0
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while ii<iicutoff_xb :
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k_xb.append(newtonpplus(xf[ii],h,0))
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a1=Ampu[ii];
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a3=Ampp[ii];
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phi1=ThetaU[ii];
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phi3=ThetaP[ii];
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omega.append(2*math.pi*xf[ii])
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cc=omega[ii]*math.cosh(xf[ii]*(zmesU+h))/math.sinh(xf[ii]*h);
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ccp=omega[ii]*math.cosh(xf[ii]*(zmesP+h))/math.sinh(xf[ii]*h);
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cs=omega[ii]*math.sinh(xf[ii]*(zmesU+h))/math.sinh(xf[ii]*h);
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#Procedure de calcul des ai et ar sans courant
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ccc.append(cc)
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ccs.append(cs)
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cccp.append(ccp)
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#calcul des amplitudes des ondes incidentes a partir de uhoriz et p
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aincident13.append(0.5*math.sqrt(a1*a1/(cc*cc)+a3*a3*g*g*xf[ii]*xf[ii]/(omega[ii]*omega[ii]*ccp*ccp)+2*a1*a3*g*k_xb[ii]*math.cos(phi3-phi1)/(cc*ccp*omega[ii])))
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areflechi13.append(0.5*math.sqrt(a1*a1/(cc*cc)+a3*a3*g*g*k_xb[ii]*k_xb[ii]/(omega[ii]*omega[ii]*ccp*ccp)-2*a1*a3*g*xf[ii]*math.cos(phi3-phi1)/(cc*ccp*omega[ii])))
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cv=g*xf[ii]/(omega[ii]*ccp)
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cp=1/cc
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aprog.append(a3/(g*xf[ii]/(omega[ii]*ccp))) #hypothese progressive Drevard et al |u|/Cv
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#aprog(ii)= a1/cp;
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#|p|/Cp
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if aincident13[ii]<0.18*ampliseuil:
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r13.append(0)
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else:
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r13.append(areflechi13[ii]/aincident13[ii])
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ii+=1
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@ -5,8 +5,8 @@ import math
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import sys
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import numpy as np
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from matplotlib import animation
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import imageio
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import cmath
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from scipy.fft import fft
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def newtonpplus(f,h,u) :
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# calcul de k:
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