def test_fit_real_numpy(self):
log = logging.getLogger('TestFitZern.test_fit_real_numpy')
z = RZern(4)
F = FitZern(z, self.L, self.K)
theta_i = F.theta_i
rho_j = F.rho_j
c = 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))
time1 = time()
ce2 = F.fit(np.array(Phi, order='F'))
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_fit_real_numpy(self):
log = logging.getLogger('TestFitZern.test_fit_real_numpy')
z = RZern(4)
F = FitZern(z, self.L, self.K)
theta_i = F.theta_i
rho_j = F.rho_j
c = 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))
time1 = time()
ce2 = F.fit(np.array(Phi, order='F'))
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_fit_real(self):
log = logging.getLogger('TestFitZern.test_fit_real')
z = RZern(4)
F = FitZern(z, self.L, self.K)
theta_i = F.theta_i
rho_j = F.rho_j
c = 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 = norm(np.array(c) - np.array(ce))
max1 = max([abs(c[i] - ce[i]) for i in range(z.nk)])
log.debug('err1 {:e} max1 {:e}'.format(err1, max1))
self.assertTrue(err1 < self.max_fit_norm)
def test_fit_real(self):
log = logging.getLogger('TestFitZern.test_fit_real')
z = RZern(4)
F = FitZern(z, self.L, self.K)
theta_i = F.theta_i
rho_j = F.rho_j
c = 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 = norm(np.array(c) - np.array(ce))
max1 = max([abs(c[i] - ce[i]) for i in range(z.nk)])
log.debug('err1 {:e} max1 {:e}'.format(err1, max1))
self.assertTrue(err1 < self.max_fit_norm)
