def test_add_buoyancy_freq_squared(self):
# This is a fairly lousy test, merely ensuring that an N^2 field was
# calculated, and that it's not wildly different than the direct
# calculation.
p = np.arange(10)
t = 20.0 * 0.2 * p
s = 30.0 * 0.25 * p
x = [-20.0 for _ in p]
y = [50.0 for _ in p]
sa = gsw.sa_from_sp(s, p, x, y)
ct = gsw.ct_from_t(sa, t, p)
rho = np.asarray(gsw.rho(sa, ct, p))
cast = CTDCast(p, s, t, coordinates=(-20, 50), density=rho)
cast.add_depth()
cast.add_Nsquared(depthkey="depth")
# Calculate the buoyancy frequency directly
z = cast["depth"].values
drhodz = -np.r_[rho[1]-rho[0], rho[2:]-rho[:-2], rho[-1]-rho[-2]] / \
np.r_[z[1]-z[0], z[2:]-z[:-2], z[-1]-z[-2]]
N2_direct = -9.81 / rho * drhodz
self.assertTrue(
np.mean(np.abs(cast["N2"][1:] - N2_direct[1:])) < 0.0004)
return
def setUp(self):
p = np.arange(1, 1001, 2)
temp = 10. * np.exp(-.008 * p) - 15. * np.exp(-0.005 * (p + 100)) + 2.
sal = -14. * np.exp(-.01 * p) + 34.
self.p = p
self.temp = temp
self.sal = sal
self.cast = CTDCast(p, sal, temp)
return
def setUp(self):
p = np.arange(1, 1001, 2)
temp = 10. * np.exp(-.008*p) - 15. * np.exp(-0.005*(p+100)) + 2.
sal = -14. * np.exp(-.01*p) + 34.
self.p = p
self.temp = temp
self.sal = sal
dt = datetime.datetime(1993, 8, 18, 14, 42, 36)
self.cast = Cast(pres=self.p, temp=self.temp, sal=self.sal, date=dt)
self.ctd = CTDCast(self.p, self.sal, self.temp, date=dt)
self.collection = CastCollection(self.ctd, self.ctd)
return
def test_three_sources_constant(self):
ans = np.array([0.3, 0.2, 0.5])
sources = [(34.0, 2.0), (34.5, 7.0), (34.6, 5.0)]
s = np.array(sources)
x = np.ones(10, dtype=np.float64)
sal = x * np.dot(ans, s[:, 0])
tmp = x * np.dot(ans, s[:, 1])
c = CTDCast(np.arange(10), sal, tmp)
(chi1, chi2, chi3) = narwhal.analysis.water_fractions(c, sources)
self.assertTrue(np.allclose(chi1, 0.3 * np.ones(10)))
self.assertTrue(np.allclose(chi2, 0.2 * np.ones(10)))
self.assertTrue(np.allclose(chi3, 0.5 * np.ones(10)))
return
def test_add_density(self):
p = np.arange(10)
t = 20.0 * 0.2 * p
s = 30.0 * 0.25 * p
x = [-20.0 for _ in p]
y = [50.0 for _ in p]
sa = gsw.sa_from_sp(s, p, x, y)
ct = gsw.ct_from_t(sa, t, p)
rho = gsw.rho(sa, ct, p)
cast = CTDCast(p, s, t, coordinates=(-20, 50))
cast.add_density()
self.assertTrue(np.allclose(rho, cast["density"]))
return
def test_three_sources_varying(self):
ans_chi1 = np.linspace(0.2, 0.35, 10)
ans_chi2 = np.linspace(0.6, 0.1, 10)
ans_chi3 = 1.0 - (ans_chi1 + ans_chi2)
ans = np.c_[ans_chi1, ans_chi2, ans_chi3]
sources = [(34.0, 2.0), (34.5, 7.0), (34.6, 5.0)]
s = np.array(sources)
x = np.ones(10, dtype=np.float64)
sal = x * np.dot(ans, s[:, 0])
tmp = x * np.dot(ans, s[:, 1])
c = CTDCast(np.arange(10), sal, tmp)
(chi1, chi2, chi3) = narwhal.analysis.water_fractions(c, sources)
self.assertTrue(np.allclose(chi1, ans_chi1))
self.assertTrue(np.allclose(chi2, ans_chi2))
self.assertTrue(np.allclose(chi3, ans_chi3))
return
def test_four_sources_varying(self):
ans_chi1 = np.linspace(0.2, 0.35, 10)
ans_chi2 = np.linspace(0.6, 0.1, 10)
ans_chi3 = np.linspace(0.05, 0.12, 10)
ans_chi4 = 1.0 - (ans_chi1 + ans_chi2 + ans_chi3)
ans = np.c_[ans_chi1, ans_chi2, ans_chi3, ans_chi4]
sources = [(34.0, 2.0, 280.0), (34.5, 70.0, 250.0), (34.6, 5.0, 330.0),
(33.9, 18.0, 390.0)]
s = np.array(sources)
x = np.ones(10, dtype=np.float64)
sal = x * np.dot(ans, s[:, 0])
tmp = x * np.dot(ans, s[:, 1])
oxy = x * np.dot(ans, s[:, 2])
c = CTDCast(np.arange(10), sal, tmp, oxygen=oxy)
(chi1, chi2, chi3, chi4) = narwhal.analysis.water_fractions(
c, sources, tracers=["salinity", "temperature", "oxygen"])
self.assertTrue(np.allclose(chi1, ans_chi1))
self.assertTrue(np.allclose(chi2, ans_chi2))
self.assertTrue(np.allclose(chi3, ans_chi3))
self.assertTrue(np.allclose(chi4, ans_chi4))
return
