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_tributary(self):
models = [KarthausModel, FluxBasedModel]
steps = [15 * SEC_IN_DAY, None]
flss = [dummy_width_bed(), dummy_width_bed_tributary()]
lens = []
surface_h = []
volume = []
yrs = np.arange(1, 500, 2)
for model, step, fls in zip(models, steps, flss):
mb = LinearMassBalance(2600.)
model = model(fls,
mb_model=mb,
fs=self.fs_old,
glen_a=self.aglen_old,
fixed_dt=step)
length = yrs * 0.
vol = yrs * 0.
for i, y in enumerate(yrs):
model.run_until(y)
assert model.yr == y
length[i] = fls[-1].length_m
vol[i] = np.sum([f.volume_km3 for f in fls])
lens.append(length)
volume.append(vol)
surface_h.append(fls[-1].surface_h.copy())
np.testing.assert_allclose(lens[0][-1], lens[1][-1], atol=101)
np.testing.assert_allclose(volume[0][-1], volume[1][-1], atol=2e-2)
np.testing.assert_allclose(utils.rmsd(lens[0], lens[1]), 0., atol=70)
np.testing.assert_allclose(utils.rmsd(volume[0], volume[1]),
0.,
atol=6e-3)
np.testing.assert_allclose(utils.rmsd(surface_h[0], surface_h[1]),
0.,
atol=5)
if do_plot: # pragma: no cover
plt.plot(lens[0], 'r')
plt.plot(lens[1], 'b')
plt.show()
plt.plot(volume[0], 'r')
plt.plot(volume[1], 'b')
plt.show()
plt.plot(fls[-1].bed_h, 'k')
plt.plot(surface_h[0], 'r')
plt.plot(surface_h[1], 'b')
plt.show()
def test_flux_gate_with_trib(self):
mb = ScalarMassBalance()
model = FluxBasedModel(dummy_width_bed_tributary(), mb_model=mb,
flux_gate_thickness=150, flux_gate_build_up=50)
model.run_until(1000)
assert_allclose(model.volume_m3, model.flux_gate_m3_since_y0)
if do_plot: # pragma: no cover
plt.plot(model.fls[-1].bed_h, 'k')
plt.plot(model.fls[-1].surface_h, 'b')
plt.show()
def test_tributary(self):
models = [KarthausModel, FluxBasedModel]
steps = [15 * SEC_IN_DAY, None]
flss = [dummy_width_bed(), dummy_width_bed_tributary()]
lens = []
surface_h = []
volume = []
yrs = np.arange(1, 500, 2)
for model, step, fls in zip(models, steps, flss):
mb = LinearMassBalance(2600.)
model = model(fls, mb_model=mb, fs=self.fs_old,
glen_a=self.aglen_old,
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] = np.sum([f.volume_km3 for f in fls])
lens.append(length)
volume.append(vol)
surface_h.append(fls[-1].surface_h.copy())
np.testing.assert_allclose(lens[0][-1], lens[1][-1], atol=101)
np.testing.assert_allclose(volume[0][-1], volume[1][-1], atol=2e-2)
np.testing.assert_allclose(utils.rmsd(lens[0], lens[1]), 0., atol=70)
np.testing.assert_allclose(utils.rmsd(volume[0], volume[1]), 0.,
atol=6e-3)
np.testing.assert_allclose(utils.rmsd(surface_h[0], surface_h[1]), 0.,
atol=5)
if do_plot: # pragma: no cover
plt.plot(lens[0], 'r')
plt.plot(lens[1], 'b')
plt.show()
plt.plot(volume[0], 'r')
plt.plot(volume[1], 'b')
plt.show()
plt.plot(fls[-1].bed_h, 'k')
plt.plot(surface_h[0], 'r')
plt.plot(surface_h[1], 'b')
plt.show()
def test_staggered_diagnostics(self):
mb = LinearMassBalance(2600.)
fls = dummy_constant_bed()
model = FluxBasedModel(fls, mb_model=mb, y0=0.)
model.run_until(700)
assert_allclose(mb.get_specific_mb(fls=fls), 0, atol=10)
# Check the flux just for fun
fl = model.flux_stag[0]
assert fl[0] == 0
# Now check the diags
df = model.get_diagnostics()
fl = model.fls[0]
df['my_flux'] = np.cumsum(mb.get_annual_mb(fl.surface_h) *
fl.widths_m * fl.dx_meter *
cfg.SEC_IN_YEAR).clip(0)
df = df.loc[df['ice_thick'] > 0]
# Also convert ours
df['ice_flux'] *= cfg.SEC_IN_YEAR
df['ice_velocity'] *= cfg.SEC_IN_YEAR
df['tributary_flux'] *= cfg.SEC_IN_YEAR
assert_allclose(np.abs(df['ice_flux'] - df['my_flux']), 0, atol=35e3)
assert df['ice_velocity'].max() > 25
assert df['tributary_flux'].max() == 0
fls = dummy_width_bed_tributary()
model = FluxBasedModel(fls, mb_model=mb, y0=0.)
model.run_until(500)
df = model.get_diagnostics()
df['ice_velocity'] *= cfg.SEC_IN_YEAR
df['tributary_flux'] *= cfg.SEC_IN_YEAR
df = df.loc[df['ice_thick'] > 0]
assert df['ice_velocity'].max() > 50
assert df['tributary_flux'].max() > 30e4
df = model.get_diagnostics(fl_id=0)
df = df.loc[df['ice_thick'] > 0]
df['ice_velocity'] *= cfg.SEC_IN_YEAR
df['tributary_flux'] *= cfg.SEC_IN_YEAR
assert df['ice_velocity'].max() > 10
assert df['tributary_flux'].max() == 0