def getCorrelation2InRotatedFrame(beta,vals):
# lon0, lat0 : main vehicle lat and lon used as initial conditions for debris propagation
# beta : main vehicle heading angle (counterclockwise starting East) [deg]
lonlat = vals[0]
nSamples = vals[1]
lon0 = vals[2]
lat0 = vals[3]
R1 = Rotz(lon0*np.pi/180.) # generating rotation matrices
R2 = Roty(-lat0*np.pi/180.)
R3 = Rotx(beta*np.pi/180.)
Uint = np.dot(R2,R1)
U = np.dot(R3,Uint)
UT = U.T
xyz,x,y,z = getxyz(lonlat)
pqr = np.dot(U,xyz) # rotating point to new frame...(P frame)
p = pqr[0,:]
q = pqr[1,:]
r = pqr[2,:]
lonlatPframe = getlonlat(p,q,r)
lonlatPframe = lonlatChecks.fixlon4pdf(lonlatPframe,nSamples)
mean,covar = meancov.meancovmatrix(lonlatPframe,nSamples)
#D,Ulocal = np.linalg.eig(covar)
#lonlatAframe = np.dot(lonlatPframe,Ulocal)
#lonlatAframe = lonlatChecks.fixlon4pdf(lonlatAframe,nSamples)
#mean,covar = meancov.meancovmatrix(lonlatAframe,nSamples)
sigma1 = (covar[0,0])**.5
sigma2 = (covar[1,1])**.5
correlation = covar[0,1]/(sigma1*sigma2)
#print sigma1,sigma2,correlation
return abs(correlation)*sigma2 # objective function for optimization part (minimizing rho)
def originalFrame2Pframe(lonlat, U):
xyz, x, y, z = getxyz(lonlat)
pqr = np.dot(U, xyz) # rotating point to new frame...(P frame)
p = pqr[0, :]
q = pqr[1, :]
r = pqr[2, :]
lonlatPframe = getlonlat(p, q, r)
lonlatPframe = lonlatChecks.fixlon4pdf(
lonlatPframe,
len(x)) # P frame should be technically in the principal axis
return lonlatPframe
# driver for lonlatChecks import lonlatChecks import numpy as np nsamples = 100 lon = np.linspace(-10, 220, nsamples) lat = np.linspace(33, 70, nsamples) lonlat = np.zeros((nsamples, 2)) lonlat[:, 0] = lon lonlat[:, 1] = lat print lonlat lonlat2 = lonlatChecks.boundlon(lonlat, nsamples) lonlat3 = lonlatChecks.fixlon4pdf(lonlat2, nsamples) print lonlat - lonlat3
def getPDF4KLDiv(lonlat, nSamples, pdfoption, lonMesh, latMesh, R1, R2, R3,
xlen, ylen):
# lon0, lat0 : main vehicle lat and lon used as initial conditions for debris propagation
# beta : main vehicle heading angle (counterclockwise starting East) [deg]
# this routine should only be used for KL Divergence check.
# SIMPLE MODIFICATION FROM pdfCoordTrans.py
xyz, x, y, z = pdf.getxyz(lonlat)
Uint = np.dot(R2, R1)
U = np.dot(R3, Uint)
#U = Uint
UT = U.T
pqr = np.dot(U, xyz) # rotating point to new frame...(P frame)
p = pqr[0, :]
q = pqr[1, :]
r = pqr[2, :]
lonlatPframe = pdf.getlonlat(p, q, r)
lonlatPframe = lonlatChecks.fixlon4pdf(lonlatPframe, nSamples)
'''
mean,covar = meancov.meancovmatrix(lonlatPframe,nSamples)
#print 'Mean in P frame =',mean
D,Ulocal = np.linalg.eig(covar)
lonlatAframe = np.dot(lonlatPframe,Ulocal)
#lonlatAframe = lonlatChecks.fixlon4pdf(lonlatAframe,nSamples)
mean,covar = meancov.meancovmatrix(lonlatAframe,nSamples)
if pdfoption=='KDE':
ZZpdf = meancov.kde(lonlatAframe,XX,YY,[nSamples, xlen,ylen])
elif pdfoption=='normal':
ZZpdf = meancov.normalbivariate(mean,covar,XX,YY,xlen,ylen) #fortran version
'''
lonVec = np.reshape(lonMesh, np.size(lonMesh))
latVec = np.reshape(latMesh, np.size(latMesh))
lonlatVec = np.zeros((len(lonVec), 2))
lonlatVec[:, 0] = lonVec
lonlatVec[:, 1] = latVec
lonlatVecP = pdf.originalFrame2Pframe(lonlatVec, U)
ylen, xlen = np.shape(lonMesh)
lonMeshP = np.reshape(lonlatVecP[:, 0], [ylen, xlen])
latMeshP = np.reshape(lonlatVecP[:, 1], [ylen, xlen])
pqrVec, pVec, qVec, rVec = pdf.getxyz(
lonlatVecP) # mesh locations in P frame
if pdfoption == 'KDE':
ZZpdf = meancov.kde(lonlatPframe, lonMeshP, latMeshP,
[nSamples, xlen, ylen])
elif pdfoption == 'normal' or pdfoption == 'gaussian' or pdfoption == 'gauss':
mean, covar = meancov.meancovmatrix(lonlatPframe, nSamples)
ZZpdf = meancov.normalbivariate(mean, covar, lonMeshP, latMeshP, xlen,
ylen) #fortran version
pdfN = pdf.transformPDF(U, pqrVec, np.pi / 180 * lonlatVec[:, 0],
np.pi / 180 * lonlatVec[:, 1],
np.reshape(ZZpdf, xlen * ylen))
ZZpdfN = np.reshape(pdfN, [ylen, xlen])
return (ZZpdfN)