def drift(lat, lon, gcomps, order=10):
theta = numpy.deg2rad(90 - lat)
phi = numpy.deg2rad(lon)
declinations = numpy.empty_like(data.years)
inclinations = numpy.empty_like(data.years)
for i, y in enumerate(data.years):
dec, inc, f, h = xyzfield.xyz2difh(*xyzfield.xyzfieldv2(gcomps[i, :], phi, theta, order))
declinations[i] = dec
inclinations[i] = inc
intensities[i] = f
return declinations, inclinations, intensities
def invert_dif(thetav, phiv, data, order=13, g0=-30000, steps=5):
g=numpy.zeros(order*(order+2)); g[0]=g0
Ax,Ay,Az = condition_array_xyz(thetav,phiv,order)
dec0, inc0, int0 = data
dec0_f = dec0[~numpy.isnan(dec0)]
inc0_f = inc0[~numpy.isnan(inc0)]
int0_f = int0[~numpy.isnan(int0)]
dif0=numpy.concatenate((dec0_f,inc0_f,int0_f))
dif=dif0.copy()
for iteration in range(steps):
x,y,z=xyzfield.xyzfieldv2(g,phiv,thetav, rparam=1.0, order=order)
#pyplot.show(xyzfield.xyzcontour(thetav,phiv,x,y,z,regular=False))
dec,inc,intensity,horizontal=xyzfield.xyz2difh(x,y,z)
Ad, Ai, Af = condition_array_dif(x,y,z,intensity,horizontal, Ax, Ay, Az, order)
#remove emptys
Ad=Ad[:,~numpy.isnan(dec0)]
Ai=Ai[:,~numpy.isnan(inc0)]
Af=Af[:,~numpy.isnan(int0)]
dec=dec[~numpy.isnan(dec0)]
inc=inc[~numpy.isnan(inc0)]
intensity=intensity[~numpy.isnan(int0)]
Adif=numpy.concatenate((Ad,Ai,Af), axis=1)
dif = numpy.concatenate((dec,inc,intensity))
#get delta
delta=dif0-dif
#g = numpy.linalg.inv(Adif @ Adif.transpose()) @ Adif @ dif0
g = g + numpy.linalg.inv(Adif @ Adif.transpose()) @ Adif @ delta
#print(g[:5], sum(abs(delta)))
if (sum(abs(delta)) > 1000): warnings.warn("inversion might not have converged (╯°□°)╯︵ ┻━┻")
return g
