def test_mass_conservation(self):
mb = LinearMassBalance(2600.)
fls = dummy_constant_bed()
model = MassConservationChecker(fls, mb_model=mb, y0=0.,
glen_a=self.glen_a)
model.run_until(200)
assert_allclose(model.total_mass, model.volume_m3, rtol=1e-3)
fls = dummy_noisy_bed()
model = MassConservationChecker(fls, mb_model=mb, y0=0.,
glen_a=self.glen_a)
model.run_until(200)
assert_allclose(model.total_mass, model.volume_m3, rtol=1e-3)
fls = dummy_width_bed_tributary()
model = MassConservationChecker(fls, mb_model=mb, y0=0.,
glen_a=self.glen_a)
model.run_until(200)
assert_allclose(model.total_mass, model.volume_m3, rtol=1e-3)
# Calving!
fls = dummy_constant_bed(hmax=1000., hmin=0., nx=100)
mb = LinearMassBalance(450.)
model = MassConservationChecker(fls, mb_model=mb, y0=0.,
glen_a=self.glen_a,
is_tidewater=True)
model.run_until(500)
tot_vol = model.volume_m3 + model.calving_m3_since_y0
assert_allclose(model.total_mass, tot_vol, rtol=2e-2)
def test_mass_conservation(self):
mb = LinearMassBalance(2600.)
fls = dummy_constant_bed()
model = MassConservationChecker(fls, mb_model=mb, y0=0.,
glen_a=self.glen_a)
model.run_until(200)
assert_allclose(model.total_mass, model.volume_m3, rtol=1e-3)
fls = dummy_noisy_bed()
model = MassConservationChecker(fls, mb_model=mb, y0=0.,
glen_a=self.glen_a)
model.run_until(200)
assert_allclose(model.total_mass, model.volume_m3, rtol=1e-3)
fls = dummy_width_bed_tributary()
model = MassConservationChecker(fls, mb_model=mb, y0=0.,
glen_a=self.glen_a)
model.run_until(200)
assert_allclose(model.total_mass, model.volume_m3, rtol=1e-3)
# Calving!
fls = dummy_constant_bed(hmax=1000., hmin=0., nx=100)
mb = LinearMassBalance(450.)
model = MassConservationChecker(fls, mb_model=mb, y0=0.,
glen_a=self.glen_a,
is_tidewater=True)
model.run_until(500)
tot_vol = model.volume_m3 + model.calving_m3_since_y0
assert_allclose(model.total_mass, tot_vol, rtol=2e-2)
def test_noisy_bed(self):
models = [KarthausModel, FluxBasedModel, MUSCLSuperBeeModel]
steps = [15 * SEC_IN_DAY, None, None]
lens = []
surface_h = []
volume = []
yrs = np.arange(1, 500, 2)
fls_orig = dummy_noisy_bed()
for model, step in zip(models, steps):
fls = copy.deepcopy(fls_orig)
mb = LinearMassBalance(2600.)
model = model(fls, mb_model=mb, glen_a=self.glen_a, fixed_dt=step)
length = yrs * 0.
vol = yrs * 0.
for i, y in enumerate(yrs):
model.run_until(y)
length[i] = fls[-1].length_m
vol[i] = fls[-1].volume_km3
lens.append(length)
volume.append(vol)
surface_h.append(fls[-1].surface_h.copy())
if do_plot: # pragma: no cover
plt.figure()
plt.plot(yrs, lens[0], 'r')
plt.plot(yrs, lens[1], 'b')
plt.plot(yrs, lens[2], 'g')
plt.title('Compare Length')
plt.xlabel('years')
plt.ylabel('[m]')
plt.legend(['Karthaus', 'Flux', 'MUSCL-SuperBee'], loc=2)
plt.figure()
plt.plot(yrs, volume[0], 'r')
plt.plot(yrs, volume[1], 'b')
plt.plot(yrs, volume[2], 'g')
plt.title('Compare Volume')
plt.xlabel('years')
plt.ylabel('[km^3]')
plt.legend(['Karthaus', 'Flux', 'MUSCL-SuperBee'], loc=2)
plt.figure()
plt.plot(fls[-1].bed_h, 'k')
plt.plot(surface_h[0], 'r')
plt.plot(surface_h[1], 'b')
plt.plot(surface_h[2], 'g')
plt.title('Compare Shape')
plt.xlabel('[m]')
plt.ylabel('Elevation [m]')
plt.legend(['Bed', 'Karthaus', 'Flux', 'MUSCL-SuperBee'], loc=3)
plt.show()
np.testing.assert_allclose(lens[0][-1], lens[1][-1], atol=101)
np.testing.assert_allclose(volume[0][-1], volume[1][-1], atol=1e-2)
np.testing.assert_allclose(volume[0][-1], volume[2][-1], atol=1e-2)
self.assertTrue(utils.rmsd(lens[0], lens[1]) < 100.)
self.assertTrue(utils.rmsd(volume[0], volume[1]) < 1e-1)
self.assertTrue(utils.rmsd(volume[0], volume[2]) < 1e-1)
self.assertTrue(utils.rmsd(surface_h[0], surface_h[1]) < 10)
self.assertTrue(utils.rmsd(surface_h[0], surface_h[2]) < 10)
def test_noisy_bed(self):
models = [KarthausModel, FluxBasedModel, MUSCLSuperBeeModel]
steps = [15 * SEC_IN_DAY, None, None]
lens = []
surface_h = []
volume = []
yrs = np.arange(1, 500, 2)
fls_orig = dummy_noisy_bed()
for model, step in zip(models, steps):
fls = copy.deepcopy(fls_orig)
mb = LinearMassBalance(2600.)
model = model(fls, mb_model=mb, glen_a=self.glen_a, fixed_dt=step)
length = yrs * 0.
vol = yrs * 0.
for i, y in enumerate(yrs):
model.run_until(y)
length[i] = fls[-1].length_m
vol[i] = fls[-1].volume_km3
lens.append(length)
volume.append(vol)
surface_h.append(fls[-1].surface_h.copy())
if do_plot: # pragma: no cover
plt.figure()
plt.plot(yrs, lens[0], 'r')
plt.plot(yrs, lens[1], 'b')
plt.plot(yrs, lens[2], 'g')
plt.title('Compare Length')
plt.xlabel('years')
plt.ylabel('[m]')
plt.legend(['Karthaus', 'Flux', 'MUSCL-SuperBee'], loc=2)
plt.figure()
plt.plot(yrs, volume[0], 'r')
plt.plot(yrs, volume[1], 'b')
plt.plot(yrs, volume[2], 'g')
plt.title('Compare Volume')
plt.xlabel('years')
plt.ylabel('[km^3]')
plt.legend(['Karthaus', 'Flux', 'MUSCL-SuperBee'], loc=2)
plt.figure()
plt.plot(fls[-1].bed_h, 'k')
plt.plot(surface_h[0], 'r')
plt.plot(surface_h[1], 'b')
plt.plot(surface_h[2], 'g')
plt.title('Compare Shape')
plt.xlabel('[m]')
plt.ylabel('Elevation [m]')
plt.legend(['Bed', 'Karthaus', 'Flux', 'MUSCL-SuperBee'], loc=3)
plt.show()
np.testing.assert_allclose(lens[0][-1], lens[1][-1], atol=101)
np.testing.assert_allclose(volume[0][-1], volume[1][-1], atol=1e-2)
np.testing.assert_allclose(volume[0][-1], volume[2][-1], atol=1e-2)
self.assertTrue(utils.rmsd(lens[0], lens[1]) < 100.)
self.assertTrue(utils.rmsd(volume[0], volume[1]) < 1e-1)
self.assertTrue(utils.rmsd(volume[0], volume[2]) < 1e-1)
self.assertTrue(utils.rmsd(surface_h[0], surface_h[1]) < 10)
self.assertTrue(utils.rmsd(surface_h[0], surface_h[2]) < 10)