def testIntegrateRectangles3D(self): # Testing the integration fynction for y = 2*x at [0,1]. The area should be 1
from proteus.WaveTools import reduceToIntervals,returnRectangles3D
x = np.linspace(0,1,101)
dx = 0.01
z = np.linspace(0,1,201)
dz = 0.005
xim = reduceToIntervals(x,dx)
zim = reduceToIntervals(z,dz)
y1 = np.zeros((len(xim),len(zim)),)
for j in range(len(zim)):
for i in range(len(xim)):
y1[i,j] = 2.*xim[i]*zim[j]
A = sum(sum(returnRectangles3D(y1,xim,zim)))
# Integrate function z*(2*x) over x[0,1], z[0,1] result == 0.5
self.assertTrue(round(A,10)== 0.5)
def testIntegrateRectangles(self): # Testing the integration fynction for y = 2*x at [0,1]. The area should be 1
from proteus.WaveTools import reduceToIntervals,returnRectangles
x = np.linspace(0,1,101)
dx = 0.01
xim = reduceToIntervals(x,dx)
y = 2*xim
A = sum(returnRectangles(y,xim))
self.assertTrue(round(A,10) == 1.0)
def testReduceToIntervals(self):
from proteus.WaveTools import reduceToIntervals
fi = np.linspace(0, 100, 101)
df = 1
fr = reduceToIntervals(fi,df)
fi[:-1]+=0.5
fi_te = np.zeros(len(fi)+1,)
fi_te[1:] = fi[:]
self.assertTrue((fr- fi_te == 0).all())
def testDirectional(self):
from proteus.WaveTools import DirectionalWaves
import random
# Assinging a random value at a field and getting the expected output
Tp = 1.
Hs = 0.15
mwl = 4.5
depth = 0.9
g = np.array([0,0,-9.81])
gAbs = 9.81
# Setting the angle to the first quadrant otherwise the acos function further below is confused
theta0 = 2*pi* random.random()
dir1 = cos(theta0)
dir2 = sin(theta0)
waveDir = np.array([dir1,dir2, 0])
N = 5
M = 10
phi = 2.0*pi*np.random.rand(2*M+1,N)
gamma = 1.2
TMA = True
spectName = "JONSWAP"
spectral_params = {"gamma": gamma, "TMA": TMA,"depth": depth}
bandFactor = 2.0
spreadName = "mitsuyasu"
spread_params = {"f0": 1./Tp, "smax": 15.}
phiSymm = False
aa= DirectionalWaves(
M,
Tp,
Hs,
mwl,#m significant wave height
depth , #m depth
waveDir,
g, #peak frequency
N,
bandFactor, #accelerationof gravity
spectName,
spreadName,
spectral_params,
spread_params,
phi,
phiSymm
)
x = random.random()*200. - 100.
y = random.random()*200. - 100.
z = mwl - depth + random.random()*( depth)
t = random.random()*200. - 100.
eta = aa.eta([x, y, z], t)
ux, uy, uz = aa.u([x, y, z], t)
# Testing with a specific phi array
# setDirVector are tested above
from proteus.WaveTools import setDirVector, dispersion, reduceToIntervals, returnRectangles3D, JONSWAP,mitsuyasu, normIntegral
fmin = 1./(Tp * bandFactor)
fmax = bandFactor/(Tp)
fi = np.linspace(fmin,fmax,N)
thetas = np.linspace(theta0 - pi/2,theta0+pi/2,2*M+1)
dth = pi/(2*M)
df = (fmax-fmin)/(N - 1 )
ki = dispersion(2*pi*fi,depth)
waveDirs = np.zeros((2*M+1,3),)
for jj in range(2*M+1):
waveDirs[jj,:] = np.array([cos(thetas[jj]),sin(thetas[jj]),0])
z0 = z - mwl
fim = reduceToIntervals(fi,df)
thetas-=theta0
thetas_m = reduceToIntervals(thetas,dth)
Si_Jm = JONSWAP(fim,1./Tp,Hs,gamma,TMA, depth)
Si_dir = mitsuyasu(thetas_m,fim,1./Tp, 15.)
for ii in range(0,N):
Si_dir[:,ii] = normIntegral(Si_dir[:,ii],thetas_m)
Si_dir[:,ii]*= Si_Jm[ii]
ai = np.sqrt(2.*returnRectangles3D(Si_dir,thetas_m,fim))
omega = 2*pi*fi
etaRef = 0.
uxRef = 0.
uyRef = 0.
uzRef = 0.
for ii in range(N):
for jj in range(2*M+1):
normDir = waveDirs[jj,:]
etaRef+=ai[jj,ii]*cos(ki[ii]*(normDir[0]*x+normDir[1]*y+normDir[2]*z)-omega[ii]*t +phi[jj,ii])
uxRef += normDir[0]*ai[jj,ii]*omega[ii] *cosh(ki[ii]*(z0+depth)) *cos(ki[ii]*(normDir[0]*x+normDir[1]*y+normDir[2]*z)-omega[ii]*t +phi[jj,ii])/sinh(ki[ii]*depth)
uyRef += normDir[1]*ai[jj,ii]*omega[ii] *cosh(ki[ii]*(z0+depth)) * cos(ki[ii]*(normDir[0]*x+normDir[1]*y+normDir[2]*z)-omega[ii]*t +phi[jj,ii])/sinh(ki[ii]*depth)
uzRef += ai[jj,ii]*omega[ii] *sinh(ki[ii]*(z0+depth)) * sin(ki[ii]*(normDir[0]*x+normDir[1]*y+normDir[2]*z)-omega[ii]*t +phi[jj,ii])/sinh(ki[ii]*depth)
self.assertTrue(round(eta,8) == round(etaRef,8) )
self.assertTrue(round(ux,8) == round(uxRef,8))
self.assertTrue(round(uy,8) == round(uyRef,8))
self.assertTrue(round(uz,8) == round(uzRef,8))
ab= DirectionalWaves(
50,
2.,
0.1,
mwl,
1. ,
np.array([1,1,0]),
g,
51,
1.1, #accelerationof gravity
"JONSWAP",
"cos2s",
spectral_params=None,
spread_params={"s":15},
phi=None,
phiSymm=False
)
def testRandom(self):
from proteus.WaveTools import RandomWaves
import random
# Assinging a random value at a field and getting the expected output
Tp = 1.
Hs = 0.15
mwl = 4.5
depth = 0.9
g = np.array([0,0,-9.81])
gAbs = 9.81
dir1 = 2*random.random() - 1
dir2 = 2*random.random() - 1
waveDir = np.array([dir1,dir2, 0])
N = 100
phi = np.random.rand(N)
gamma = 1.2
TMA = True
spectName = "JONSWAP"
bandFactor = 2.0
a= RandomWaves(Tp,
Hs,
mwl,#m significant wave height
depth , #m depth
waveDir,
g, #peak frequency
N,
bandFactor, #accelerationof gravity
spectName# random words will result in error and return the available spectra
)
x = random.random()*200. - 100.
y = random.random()*200. - 100.
z = mwl - depth + random.random()*( depth)
t = random.random()*200. - 100.
# Just loading functions
eta = a.eta([x, y, z], t)
ux, uy, uz = a.u([x, y, z], t)
# Testing with a specific phi array
a= RandomWaves(
Tp,
Hs,
mwl,#m significant wave height
depth , #m depth
waveDir,
g, #peak frequency
N,
bandFactor, #accelerationof gravity
spectName,
spectral_params = {"gamma": gamma, "TMA": TMA,"depth": depth},
phi = phi# random words will result in error and return the available spectra
)
eta = a.eta([x, y, z], t)
ux, uy, uz = a.u([x, y, z], t)
# setDirVector are tested above
from proteus.WaveTools import setDirVector, dispersion, reduceToIntervals, returnRectangles, JONSWAP
fmin = 1./(Tp * bandFactor)
fmax = bandFactor/(Tp)
fi = np.linspace(fmin,fmax,N)
df = (fmax-fmin)/(N -1 )
ki = dispersion(2*pi*fi,depth)
z0 = z - mwl
normDir = setDirVector(waveDir)
fim = reduceToIntervals(fi,df)
Si_Jm = JONSWAP(fim,1./Tp,Hs,gamma,TMA, depth)
ai = np.sqrt(2.*returnRectangles(Si_Jm,fim))
omega = 2*pi*fi
etaRef = 0.
uxRef = 0.
uyRef = 0.
uzRef = 0.
for ii in range(N):
etaRef+=ai[ii]*cos(ki[ii]*(normDir[0]*x+normDir[1]*y+normDir[2]*z)-omega[ii]*t +phi[ii])
uxRef += normDir[0]*ai[ii]*omega[ii] *cosh(ki[ii]*(z0+depth)) *cos(ki[ii]*(normDir[0]*x+normDir[1]*y+normDir[2]*z)-omega[ii]*t +phi[ii])/sinh(ki[ii]*depth)
uyRef += normDir[1]*ai[ii]*omega[ii] *cosh(ki[ii]*(z0+depth)) * cos(ki[ii]*(normDir[0]*x+normDir[1]*y+normDir[2]*z)-omega[ii]*t +phi[ii])/sinh(ki[ii]*depth)
uzRef += ai[ii]*omega[ii] *sinh(ki[ii]*(z0+depth)) * sin(ki[ii]*(normDir[0]*x+normDir[1]*y+normDir[2]*z)-omega[ii]*t +phi[ii])/sinh(ki[ii]*depth)
self.assertTrue(round(eta,8) == round(etaRef,8) )
self.assertTrue(round(ux,8) == round(uxRef,8))
self.assertTrue(round(uy,8) == round(uyRef,8))
self.assertTrue(round(uz,8) == round(uzRef,8))
aa= RandomWaves(2,
0.1,
0.,#m significant wave height
1. , #m depth
np.array([0.,1,0]),
g, #peak frequency
N,
bandFactor, #accelerationof gravity
spectName# random words will result in error and return the available spectra
)