Correct flips for magnetic part. Some tests.

Former-commit-id: 998f4b8fa5b94447ae75220fbb43c0143d4083a5
This commit is contained in:
Marek Nečada 2016-08-09 14:39:45 +03:00
parent 4badc3f6cf
commit 8fb938961f
2 changed files with 141 additions and 29 deletions

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@ -916,6 +916,18 @@ def xflip_yy(lmax):
b_in = e_in b_in = e_in
return elems return elems
def xflip_tyy(lmax):
fl_yy = xflip_yy(lmax)
return np.array([fl_yy,-fl_yy])
def xflip_tyty(lmax):
fl_yy = xflip_yy(lmax)
nelem = fl_yy.shape[0]
fl_tyty = np.zeros((2,nelem,2,nelem),dtype=int)
fl_tyty[0,:,0,:] = fl_yy
fl_tyty[1,:,1,:] = -fl_yy
return fl_tyty
def yflip_yy(lmax): def yflip_yy(lmax):
""" """
TODO doc TODO doc
@ -927,6 +939,18 @@ def yflip_yy(lmax):
elems[(my % 2)==1] = elems[(my % 2)==1] * -1 # Obvious sign of tiredness (this is correct but ugly; FIXME) elems[(my % 2)==1] = elems[(my % 2)==1] * -1 # Obvious sign of tiredness (this is correct but ugly; FIXME)
return elems return elems
def yflip_tyy(lmax):
fl_yy = yflip_yy(lmax)
return np.array([fl_yy,-fl_yy])
def yflip_tyty(lmax):
fl_yy = yflip_yy(lmax)
nelem = fl_yy.shape[0]
fl_tyty = np.zeros((2,nelem,2,nelem),dtype=int)
fl_tyty[0,:,0,:] = fl_yy
fl_tyty[1,:,1,:] = -fl_yy
return fl_tyty
def zflip_yy(lmax): def zflip_yy(lmax):
""" """
TODO doc TODO doc
@ -942,6 +966,18 @@ def zflip_yy(lmax):
b_in = e_in b_in = e_in
return elems return elems
def zflip_tyy(lmax):
fl_yy = zflip_yy(lmax)
return np.array([fl_yy,-fl_yy])
def zflip_tyty(lmax):
fl_yy = zflip_yy(lmax)
nelem = fl_yy.shape[0]
fl_tyty = np.zeros((2,nelem,2,nelem),dtype=int)
fl_tyty[0,:,0,:] = fl_yy
fl_tyty[1,:,1,:] = -fl_yy
return fl_tyty
def parity_yy(lmax): def parity_yy(lmax):
""" """
Parity operator (flip in x,y,z) Parity operator (flip in x,y,z)
@ -1294,6 +1330,7 @@ def scatter_plane_wave_rectarray(omega, epsilon_b, xN, yN, xd, yd, TMatrices, k_
return ab return ab
returnlist = [ab] returnlist = [ab]
if (return_pq_0): if (return_pq_0):
pq_0_arr.shape = ab.shape
returnlist.append(pq_0_arr) returnlist.append(pq_0_arr)
if (return_pq): if (return_pq):
warnings.warn("return_pq not implemented, ignoring") warnings.warn("return_pq not implemented, ignoring")

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@ -19,26 +19,26 @@ from numpy import newaxis as ň
import warnings import warnings
# Some constants go here. # Some constants go here.
lengthOrdersOfMagnitude = [2.**i for i in range(-15,10,2)]
# The "maximum" argument of the Bessel's functions, i.e. maximum wave number times the distance,
# for the "locally strongly varying fields"
maxx = 3
# The "maximum" argument of the Bessel's function for reexpansion of the waves into regular waves
# in another center
maxxd = 2000
lMax = 50 # To which order we decompose the waves
lengthOrdersOfMagnitude = [2.**i for i in range(-15,10)]
nsamples = 4 # (frequency, direction, polarisation) samples per order of magnitude and test
npoints = 40 # points to evaluate per sample
rtol = 1e-7 # relative required precision
atol = 1. # absolute tolerance, does not really play a role
class PlaneWaveDecompositionTests(unittest.TestCase): class PlaneWaveDecompositionTests(unittest.TestCase):
""" """
covers plane_pq_y and vswf_yr1 covers plane_pq_y and vswf_yr1
""" """
def testRandomInc(self): def testRandomInc(self):
# The "maximum" argument of the Bessel's functions, i.e. maximum wave number times the distance,
# for the "locally strongly varying fields"
maxx = 10
rfailtol = 0.01 # how much of the randomized test will be tolerated
lMax = 80 # To which order we decompose the waves
rtol = 1e-5 # relative required precision
atol = 1. # absolute tolerance, does not really play a role
nsamples = 4 # (frequency, direction, polarisation) samples per order of magnitude and test
npoints = 15 # points to evaluate per sample
failcounter = 0
passcounter = 0
for oom in lengthOrdersOfMagnitude: for oom in lengthOrdersOfMagnitude:
k = np.random.randn(nsamples, 3) / oom k = np.random.randn(nsamples, 3) / oom
ksiz = np.linalg.norm(k, axis=-1) ksiz = np.linalg.norm(k, axis=-1)
@ -52,18 +52,25 @@ class PlaneWaveDecompositionTests(unittest.TestCase):
sph = qpms.cart2sph(ksiz[s]*testpoints[i]) sph = qpms.cart2sph(ksiz[s]*testpoints[i])
M̃_y, Ñ_y = qpms.vswf_yr1(sph, lMax, 1) M̃_y, Ñ_y = qpms.vswf_yr1(sph, lMax, 1)
planewave_2_p = -1j*qpms.sph_loccart2cart(np.dot(p,Ñ_y)+np.dot(q,M̃_y),sph) planewave_2_p = -1j*qpms.sph_loccart2cart(np.dot(p,Ñ_y)+np.dot(q,M̃_y),sph)
self.assertTrue(np.allclose(planewave_2_p, planewave_1[i], rtol=rtol, atol=atol)) #self.assertTrue(np.allclose(planewave_2_p, planewave_1[i], rtol=rtol, atol=atol))
# if not np.allclose(planewave_2_p, planewave_1[i], rtol=rtol, atol=atol): if not np.allclose(planewave_2_p, planewave_1[i], rtol=rtol, atol=atol):
# warnings.warn('Planewave expansion test not passed; r = ' False and warnings.warn('Planewave expansion test not passed; r = '
# +str(testpoints[i])+', k = '+str(k[s]) +str(testpoints[i])+', k = '+str(k[s])
# +', E_0 = '+str(E_0[s])+', (original) E = ' +', E_0 = '+str(E_0[s])+', (original) E = '
# +str(planewave_1[i])+', (reexpanded) E = ' +str(planewave_1[i])+', (reexpanded) E = '
# +str(planewave_2_p) +str(planewave_2_p)
# +', x = '+str(np.dot(testpoints[i],k[s])) +', x = '+str(np.dot(testpoints[i],k[s]))
# +'; distance = ' +'; distance = '
# +str(np.linalg.norm(planewave_1[i]-planewave_2_p)) +str(np.linalg.norm(planewave_1[i]-planewave_2_p))
# +', required relative precision = ' +', required relative precision = '
# +str(relprecision)+'.') +str(rtol)+'.')
failcounter += 1
else:
passcounter += 1
self.assertLess(failcounter / (failcounter + passcounter), rfailtol,
'%d / %d (%.2e) randomized numerical tests failed (tolerance %.2e)'
% (failcounter, failcounter + passcounter,
failcounter / (failcounter + passcounter), rfailtol))
return return
def testCornerCases(self): def testCornerCases(self):
@ -71,8 +78,76 @@ class PlaneWaveDecompositionTests(unittest.TestCase):
class SphericalWaveTranslationTests(unittest.TestCase): class SphericalWaveTranslationTests(unittest.TestCase):
def testRandom1to1(self):
# The "maximum" argument of the Bessel's functions, i.e. maximum wave number times the distance,
# for the "locally strongly varying fields"
maxx = 10
rfailtol = 0.01 # how much of the randomized test fail proportion will be tolerated
lMax = 50 # To which order we decompose the waves
lMax_outgoing = 4 # To which order we try the outgoing waves
rtol = 1e-5 # relative required precision
atol = 1. # absolute tolerance, does not really play a role
nsamples = 4 # frequency samples per order of magnitude and test
npoints = 15 # points to evaluate per frequency and center
def sometest(self): ncentres = 3 # number of spherical coordinate centres between which the translations are to be made
maxxd = 2000 # the center position standard deviation
failcounter = 0
passcounter = 0
my, ny = qpms.get_mn_y(lMax)
nelem_full = len(my)
nelem_out = lMax_outgoing * (lMax_outgoing + 2)
for oom in lengthOrdersOfMagnitude:
centres = oom * maxxd * np.random.randn(ncentres, 3)
ksizs = np.random.randn(nsamples)
for ksiz in ksizs:
for i in range(ncentres): # "source"
Rs = centres[i]
testr = oom * maxx * np.random.randn(npoints, 3)
for j in range(ncentres): # "destination"
if j == i:
continue
Rd = centres[j]
shift = Rd - Rs
shift_sph = qpms.cart2sph(shift)
shift_kr = ksiz * shift_sph[0]
shift_theta = shift_sph[1]
shift_phi = shift_sph[2]
A_yd_ys = np.empty((nelem_full,nelem_out), dtype = np.complex_)
B_yd_ys = np.empty((nelem_full,nelem_out), dtype = np.complex_)
for yd in range(nelem_full):
for ys in range(nelem_out):
A_yd_ys[yd, ys] = qpms.Ã(my[yd],ny[yd],my[ys],ny[ys],shift_kr, shift_theta, shift_phi, True, 1)
B_yd_ys[yd, ys] = qpms.B̃(my[yd],ny[yd],my[ys],ny[ys],shift_kr, shift_phi, shift_phi, True, 1)
for r in testr:
sph_ssys = qpms.cart2sph(r+Rd-Rs)
M_ssys, N_ssys = qpms.vswf_yr1(np.array([ksiz * sph_ssys[0], sph_ssys[1], sph_ssys[2]]), lMax_outgoing, J=1)
sph_dsys = qpms.cart2sph(r)
M_dsys, N_dsys = qpms.vswf_yr1(np.array([ksiz * sph_dsys[0], sph_dsys[1], sph_dsys[2]]), lMax, J=1)
for ys in range(nelem_out):
# Electrical waves
E_1 = -1j*qpms.sph_loccart2cart(N_ssys[ys], sph_ssys)
E_2 = -1j*qpms.sph_loccart2cart(np.dot(A_yd_ys[:,ys],N_dsys)+np.dot(B_yd_ys[:,ys],M_dsys),sph_dsys)
if not np.allclose(E_1, E_2, rtol=rtol, atol=atol):
failcounter += 1
else:
passcounter += 1
# Magnetic waves
E_1 = -1j*qpms.sph_loccart2cart(M_ssys[ys], sph_ssys)
E_2 = -1j*qpms.sph_loccart2cart(np.dot(A_yd_ys[:,ys],M_dsys)+np.dot(B_yd_ys[:,ys],N_dsys),sph_dsys)
if not np.allclose(E_1, E_2, rtol=rtol, atol=atol):
failcounter += 1
else:
passcounter += 1
self.assertLess(failcounter / (failcounter + passcounter), rfailtol,
'%d / %d (%.2e) randomized numerical tests failed (tolerance %.2e)'
% (failcounter, failcounter + passcounter,
failcounter / (failcounter + passcounter), rfailtol))
return
def testRandom3to1(self):
pass pass
def main(): def main():