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 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_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_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
