def test_fit_complex(self):
log = logging.getLogger('TestFitZern.test_fit_complex')
z = CZern(4)
F = FitZern(z, self.L, self.K)
theta_i = F.theta_i
rho_j = F.rho_j
c = normal(size=z.nk) + 1j*normal(size=z.nk)
time1 = time()
Phi = [z.eval_a(c, rh, th) for rh in rho_j for th in theta_i]
time2 = time()
log.debug('eval Phi {:.4f}'.format(time2 - time1))
time1 = time()
ce = F._fit_slow(Phi)
time2 = time()
log.debug('elapsed time {:.4f}'.format(time2 - time1))
err1 = np.sqrt(sum([abs(c[i] - ce[i])**2 for i in range(z.nk)]))
max1 = max([abs(c[i] - ce[i]) for i in range(z.nk)])
log.debug('err1 {:e} max1 {:e} max {:e}'.format(
err1, max1, self.max_fit_norm))
self.assertTrue(err1 < self.max_fit_norm)
def test_fit_complex_numpy(self):
log = logging.getLogger('TestFitZern.test_fit_complex_numpy')
z = CZern(4)
F = FitZern(z, self.L, self.K)
theta_i = F.theta_i
rho_j = F.rho_j
c = normal(size=z.nk) + 1j*normal(size=z.nk)
Phi = [z.eval_a(c, rh, th) for rh in rho_j for th in theta_i]
time1 = time()
ce = F._fit_slow(Phi)
time2 = time()
log.debug('elapsed FIT_LIST {:.6f}'.format(time2 - time1))
PhiN = np.array(Phi, order='F')
time1 = time()
ce2 = F.fit(PhiN)
time2 = time()
log.debug('elapsed FIT_NUMPY {:.6f}'.format(time2 - time1))
enorm = norm(ce2 - np.array(ce, order='F'))
log.debug('enorm {:e}'.format(enorm))
self.assertTrue(enorm < self.max_enorm)
def test_normalisations_complex(self):
log = logging.getLogger('TestZern.test_normalisations_complex')
n_beta = 6
L, K = 400, 393
# polar grid
pol = CZern(n_beta)
fitBeta = FitZern(pol, L, K)
t1 = time()
pol.make_pol_grid(fitBeta.rho_j, fitBeta.theta_i)
t2 = time()
log.debug('make pol grid {:.6f}'.format(t2 - t1))
# cartesian grid
cart = CZern(n_beta)
dd = np.linspace(-1.0, 1.0, max(L, K))
xx, yy = np.meshgrid(dd, dd)
t1 = time()
cart.make_cart_grid(xx, yy)
t2 = time()
log.debug('make cart grid {:.6f}'.format(t2 - t1))
smap = np.isfinite(cart.eval_grid(np.zeros(cart.nk)))
scale = (1.0/np.sum(smap))
log.debug('')
log.debug('{} modes, {} x {} grid'.format(n_beta, L, K))
for i in range(pol.nk):
a = np.zeros(pol.nk)
a[i] = 1.0
Phi_a = cart.eval_grid(a)
for j in range(pol.nk):
b = np.zeros(pol.nk)
b[j] = 1.0
Phi_b = cart.eval_grid(b)
ip = scale*np.sum(Phi_a[smap]*(Phi_b[smap].conj()))
if i == j:
eip = 1.0
else:
eip = 0.0
iperr = abs(ip - eip)
log.debug('<{:02},{:02}> = {:+e} {:+e}'.format(
i + 1, j + 1, ip, iperr))
self.assertTrue(iperr < self.max_ip_err)