def test_input_both(self):
res = nsev_inverse(self.xivec, self.tvec, self.cont_b_ana, self.bound_states, self.disc_norming_const_ana,
cst=1, dst=0)
with self.subTest('FNFT nsev_inverse return value'):
self.assertEqual(res['return_value'], 0, "nsev_inverse input variation both return value not 0")
with self.subTest('both : q value'):
self.assertTrue(check_array(res['q'][0:-1:40], self.expected['q_both']), "both: q values not as expected")
def nsev_inverse_example2():
"""nsev_inverse_example: create a N=2.2 Satsuma-Yajima pulse from nonlinear spectrum."""
D = 1024
M = 2 * D
Tmax = 15
tvec = np.linspace(-Tmax, Tmax, D)
# calculate suitable frequency bonds (xi)
rv, xi = nsev_inverse_xi_wrapper(D, tvec[0], tvec[-1], M)
xivec = xi[0] + np.arange(M) * (xi[1] - xi[0]) / (M - 1)
# analytic field: chirp-free N=2.2 Satsuma-Yajima pulse
q = 2.2 / np.cosh(tvec)
# semi-analytic nonlinear spectrum
bound_states = np.array([0.7j, 1.7j])
disc_norming_const_ana = [1.0, -1.0]
cont_b_ana = 0.587783 / np.cosh(xivec * np.pi) * np.exp(1.0j * np.pi)
# call the function
res = nsev_inverse(xivec, tvec, cont_b_ana, bound_states, disc_norming_const_ana, cst=1, dst=0)
print("\n----- options used ----")
print(res['options'])
print("\n------ results --------")
print("FNFT return value: %d (should be 0)" % res['return_value'])
# compare result to analytic function
print("nsev-inverse example: Satsuma-Yajima N=2.2")
print("Difference analytic - numeric: sum((q_ana-q_num)**2) = %.2e (should be approx 0) " % np.sum(
np.abs(q - res['q']) ** 2))
return res
def test_return_value_none(self):
res = nsev_inverse(self.xivec, self.tvec, None, None, None,
cst=1, dst=0)
with self.subTest('FNFT nsev_inverse return value'):
self.assertEqual(res['return_value'], 7,
"nsev_inverse input variation none return value not 7")
with self.subTest('none : q value'):
self.assertTrue(check_array(res['q'][0:-1:40], self.expected['q_none']),
"none: q values not as expected")
def test_input_cont3(self):
res = nsev_inverse(self.xivec, self.tvec, self.cont_b_ana, self.bound_states, None,
cst=1, dst=0)
with self.subTest('FNFT nsev_inverse return value'):
self.assertEqual(res['return_value'], 0,
"nsev_inverse input variation cont3 return value not 0")
with self.subTest('cont3 : q value'):
self.assertTrue(check_array(res['q'][0:-1:40], self.expected['q_cont']),
"cont3: q values not as expected")
def test_q_value_cont3(self):
res = nsev_inverse(self.xivec,
self.tvec,
self.cont_b_ana,
self.bound_states,
None,
cst=1,
dst=0)
self.assertTrue(
check_array(res['q'][0:-1:40], self.expected['q_cont']),
"cont3: q values not as expected")
def test_q_value_cont2(self):
res = nsev_inverse(self.xivec,
self.tvec,
self.cont_b_ana,
None,
self.disc_norming_const_ana,
cst=1,
dst=0)
self.assertTrue(
check_array(res['q'][0:-1:40], self.expected['q_cont']),
"cont2: q values not as expected")
def test_q_value_none(self):
res = nsev_inverse(self.xivec,
self.tvec,
None,
None,
None,
cst=1,
dst=0)
self.assertTrue(
check_array(res['q'][0:-1:40], self.expected['q_none']),
"none: q values not as expected")
def nsev_inverse_example():
"""Mimics the C example for calling fnft_nsev_inverse."""
print("\nnsev inverse example")
# set values
M = 2048
D = 1024
tvec = np.linspace(-2, 2, D)
T1 = tvec[0]
T2 = tvec[-1]
alpha = 2.0
beta = 0.55
gamma = np.sqrt( np.abs(alpha)**2 + np.abs(beta)**2)
kappa = 1
# get the frequency intervall suited for the given time vector
rv, XI = nsev_inverse_xi_wrapper(D, T1, T2, M)
Xi1 = XI[0]
Xi2 = XI[1]
xivec = XI[0] + np.arange(M) * (XI[1] - XI[0]) / (M - 1)
# set continuous spectrum
contspec = alpha / (xivec - beta * 1.0j)
# set discrete spectrum
bound_states = np.array([1.0j * beta])
normconst_or_residues = np.array([-1.0j * alpha / (gamma + beta)])
# call function
res = nsev_inverse(xivec, tvec, contspec, bound_states, normconst_or_residues)
# print results
print("\n----- options used ----")
print(res['options'])
print("\n------ results --------")
print("FNFT return value: %d (should be 0)" % res['return_value'])
print("Total number of samples calculated: %d" % D)
print("some samples:")
for i in range(0, D, 64):
print(" %d : q(t=%.5f) = %.5e + %.5e j " % (i, tvec[i],
np.real(res['q'][i]),
np.imag(res['q'][i])))
res['Xi'] = np.array([Xi1,Xi2])
return res
