def test_test_files(self):
fn = local_TestFiles_path + "wetb/utils/tests/test_files/test_file.txt"
if os.path.isfile(fn):
os.remove(fn)
fn1 = get_test_file(tfp + 'test_file.txt')
self.assertTrue(os.path.isfile(fn1))
fn2 = get_test_file('test_file.txt')
self.assertEqual(fn1, fn2)
def test_fit_ae2var(self):
u = mann_turbulence.load(
get_test_file("h2a8192_8_8_16384_32_32_0.15_10_3.3u.dat"),
(8192, 8, 8))
self.assertAlmostEqual(fit_ae(spatial_resolution=2, u=u, L=10, G=3.3),
.15,
delta=.02)
def test_time_series(self):
constraint_file = ConstraintFile(center_gl_xyz=(-5, 4, -90), box_transport_speed=10, no_grid_points=(16, 8, 8), box_size=(30, 70, 70))
constraint_file.load(get_test_file('constraints_test.con'))
time,uvw = constraint_file.time_series(-4)
u,v,w = uvw.T
m = ~np.isnan(u)
np.testing.assert_array_equal(time[m],[0,1,2])
np.testing.assert_array_equal(u[m],[-2,0,2])
def test_spectra_from_timeseries(self):
fn_lst = [
get_test_file('h2a8192_8_8_16384_32_32_0.15_10_3.3%s.dat' % uvw)
for uvw in 'uvw'
]
u, v, w = load_uvw(fn_lst, (8192, 8, 8))
dx = 16384 / 8192
fx = 1 / dx # spatial resolution
k1, uu, vv, ww, uw = logbin_spectra(*spectra(fx, u, v, w))
U = u + 4
sample_frq = 2
k12, uu2, vv2, ww2, uw2 = logbin_spectra(
*spectra_from_time_series(sample_frq, [(
U_, v_, w_) for U_, v_, w_ in zip(U.T, v.T, w.T)]))
np.testing.assert_allclose(uu, uu2, 0.02)
U = u + 8
sample_frq = 2
k13, uu3, vv3, ww3, uw3 = logbin_spectra(*spectra_from_time_series(
sample_frq, [(U_[::2], v_[::2], w_[::2])
for U_, v_, w_ in zip(U.T, v.T, w.T)]))
np.testing.assert_allclose(uu[:-3], uu3[:-2], 0.1)
# One set of time series with U=4
U = u + 4
Uvw_lst = [(U_, v_, w_) for U_, v_, w_ in zip(U.T, v.T, w.T)]
# Another set of time series with U=8 i.e. only every second point to have
# same sample_frq. (nan added to have same length)
U = u + 4
Uvw_lst.extend([(np.r_[U_[::2], U_[::2] + np.nan],
np.r_[v_[::2],
v_[::2] + np.nan], np.r_[w_[::2],
w_[::2] + np.nan])
for U_, v_, w_ in zip(U.T, v.T, w.T)])
sample_frq = 2
with warnings.catch_warnings():
warnings.simplefilter("ignore")
k14, uu4, vv4, ww4, uw4 = logbin_spectra(
*spectra_from_time_series(sample_frq, Uvw_lst))
np.testing.assert_allclose(uu[:-3], uu3[:-2], rtol=0.1)
if 0:
import matplotlib.pyplot as plt
plt.semilogx(k1, uu * k1)
plt.semilogx(k12, uu2 * k12)
plt.semilogx(k13, uu3 * k13)
plt.semilogx(k14, uu4 * k14)
plt.show()
def test_fit_mann_parameters_turbulence_box(self):
# for uvw in 'uvw':
# move2test_files(tfp + 'h2a8192_8_8_16384_32_32_0.15_10_3.3%s.dat'%uvw)
fn_lst = [
get_test_file('h2a8192_8_8_16384_32_32_0.15_10_3.3%s.dat' % uvw)
for uvw in 'uvw'
]
u, v, w = load_uvw(fn_lst, (8192, 8, 8))
dx = 16384 / 8192
fx = 1 / dx # spatial resolution
plt = None
ae, L, G = fit_mann_parameters(fx, u, v, w, plt=plt)
self.assertAlmostEqual(ae, .15, delta=0.01)
self.assertAlmostEqual(L, 10, delta=0.3)
self.assertAlmostEqual(G, 3.3, delta=0.06)
def test_var2ae_U(self):
u = mann_turbulence.load(
get_test_file("h2a8192_8_8_16384_32_32_0.15_10_3.3u.dat"),
(8192, 8, 8))
dx = 2
for U in [1, 10, 100]:
# should be independent of U
dt = dx / U
T = 16384 / U
self.assertAlmostEqual(var2ae(variance=u.var(),
L=10,
G=3.3,
U=U,
T=T,
sample_frq=1 / dt),
.15,
delta=.021)
def test_var2ae_T(self):
u = mann_turbulence.load(
get_test_file("h2a8192_8_8_16384_32_32_0.15_10_3.3u.dat"),
(8192, 8, 8))
dx = 2
U = 10
dt = dx / U
for i in np.arange(6):
# reshape to more and shorter series. Variance should decrease while ae should be roughly constant
n = 2**i
u_ = u.T.reshape((u.T.shape * np.array([n, 1 / n])).astype(int)).T
var = u_.var(0).mean()
ae = var2ae(variance=var,
L=10,
G=3.3,
U=U,
T=dx * u_.shape[0] / U,
sample_frq=1 / dt)
self.assertAlmostEqual(ae, .15, delta=.025)
def test_fit_mann_parameters_from_timeseries(self):
fn_lst = [
get_test_file('h2a8192_8_8_16384_32_32_0.15_10_3.3%s.dat' % uvw)
for uvw in 'uvw'
]
u, v, w = load_uvw(fn_lst, (8192, 8, 8))
dx = 16384 / 8192
fx = 1 / dx # spatial resolution
ae, L, G = fit_mann_parameters(fx, u, v, w)
self.assertAlmostEqual(ae, .15, delta=0.01)
self.assertAlmostEqual(L, 10, delta=0.3)
self.assertAlmostEqual(G, 3.3, delta=0.06)
#import matplotlib.pyplot as plt
plt = None
U = u + 4
sample_frq = 2
ae, L, G = fit_mann_parameters_from_time_series(
sample_frq, [(U_, v_, w_) for U_, v_, w_ in zip(U.T, v.T, w.T)],
plt=plt)
self.assertAlmostEqual(ae, .15, delta=0.01)
self.assertAlmostEqual(L, 10, delta=0.3)
self.assertAlmostEqual(G, 3.3, delta=0.06)
# One set of time series with U=4
U = u + 4
Uvw_lst = [(U_, v_, w_) for U_, v_, w_ in zip(U.T, v.T, w.T)]
# Another set of time series with U=8 i.e. only every second point to have
# same sample_frq. (nan added to have same length)
U = u + 4
Uvw_lst.extend([(np.r_[U_[::2], U_[::2] + np.nan],
np.r_[v_[::2],
v_[::2] + np.nan], np.r_[w_[::2],
w_[::2] + np.nan])
for U_, v_, w_ in zip(U.T, v.T, w.T)])
sample_frq = 2
ae, L, G = fit_mann_parameters_from_time_series(sample_frq,
Uvw_lst,
plt=plt)
self.assertAlmostEqual(ae, .15, delta=0.01)
self.assertAlmostEqual(L, 10, delta=0.3)
self.assertAlmostEqual(G, 3.3, delta=0.06)
def test_var2ae_dt(self):
u = mann_turbulence.load(
get_test_file("h2a16384_8_8_65536_32_32_0.15_40_4.0u.dat"),
(16384, 8, 8))
dx = 4
U = 10
T = u.shape[0] * dx / U
for i in np.arange(9):
# average every neighbouring samples to decrease dt.
# Variance should decrease while ae should be roughly constant
n = 2**i
u_ = u.reshape(u.shape[0] // n, n, u.shape[1]).mean(1)
var = u_.var(0).mean()
ae = var2ae(variance=var,
L=40,
G=4,
U=U,
T=T,
sample_frq=1 / (n * dx / U),
plt=False)
#print(u_.shape, var, ae)
self.assertAlmostEqual(ae, .15, delta=.04)
def test_load(self):
constraint_file = ConstraintFile(center_gl_xyz=(-5, 4, -90), box_transport_speed=10, no_grid_points=(16, 8, 8), box_size=(30, 70, 70))
constraint_file.load(get_test_file('constraints_test.con'))
with open(get_test_file('constraints_test.con')) as fid:
self.assertEqual(str(constraint_file), fid.read())