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
def to_minimize(ela_h):
mbmod = LinearMassBalance(ela_h[0], grad=mb_gradient)
smb = mbmod.get_specific_mb(h, w)
return (smb - cmb)**2
def test_constant_bed(self):
models = [KarthausModel, FluxBasedModel, MUSCLSuperBeeModel]
lens = []
surface_h = []
volume = []
yrs = np.arange(1, 700, 2)
for model in models:
fls = dummy_constant_bed()
mb = LinearMassBalance(2600.)
model = model(fls, mb_model=mb, y0=0., glen_a=self.glen_a,
fs=self.fs, fixed_dt=10 * SEC_IN_DAY)
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] = fls[-1].volume_km3
lens.append(length)
volume.append(vol)
surface_h.append(fls[-1].surface_h.copy())
# We are almost at equilibrium. Spec MB should be close to 0
assert_allclose(mb.get_specific_mb(fls=fls), 0, atol=10)
if do_plot:
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_almost_equal(lens[0][-1], lens[1][-1])
np.testing.assert_allclose(volume[0][-1], volume[2][-1], atol=3e-3)
np.testing.assert_allclose(volume[1][-1], volume[2][-1], atol=3e-3)
assert utils.rmsd(lens[0], lens[2]) < 50.
assert utils.rmsd(lens[1], lens[2]) < 50.
assert utils.rmsd(volume[0], volume[2]) < 2e-3
assert utils.rmsd(volume[1], volume[2]) < 2e-3
assert utils.rmsd(surface_h[0], surface_h[2]) < 1.0
assert utils.rmsd(surface_h[1], surface_h[2]) < 1.0
def test_numerics():
# We test that our model produces similar results than Jarosh et al 2013.
models = [MUSCLSuperBeeModel, ChakraModel]
lens = []
surface_h = []
volume = []
yrs = np.arange(1, 700, 2)
for model_class in models:
mb = LinearMassBalance(2600.)
model = model_class(dummy_constant_bed(), mb_model=mb)
length = yrs * 0.
vol = yrs * 0.
for i, y in enumerate(yrs):
model.run_until(y)
assert model.yr == y
length[i] = model.fls[-1].length_m
vol[i] = model.fls[-1].volume_km3
lens.append(length)
volume.append(vol)
surface_h.append(model.fls[-1].surface_h.copy())
# We are almost at equilibrium. Spec MB should be close to 0
assert_allclose(mb.get_specific_mb(fls=model.fls), 0, atol=10)
if do_plot:
plt.figure()
plt.plot(yrs, lens[0])
plt.plot(yrs, lens[1])
plt.title('Compare Length')
plt.xlabel('years')
plt.ylabel('[m]')
plt.legend(['MUSCL-SuperBee', 'Chakra'], loc=2)
plt.figure()
plt.plot(yrs, volume[0])
plt.plot(yrs, volume[1])
plt.title('Compare Volume')
plt.xlabel('years')
plt.ylabel('[km^3]')
plt.legend(['MUSCL-SuperBee', 'Chakra'], loc=2)
plt.figure()
plt.plot(model.fls[-1].bed_h, 'k')
plt.plot(surface_h[0])
plt.plot(surface_h[1])
plt.title('Compare Shape')
plt.xlabel('[m]')
plt.ylabel('Elevation [m]')
plt.legend(['Bed', 'MUSCL-SuperBee', 'Chakra'], loc=2)
plt.show()
np.testing.assert_almost_equal(lens[0][-1], lens[1][-1])
np.testing.assert_allclose(volume[0][-1], volume[1][-1], atol=1e-3)
assert utils.rmsd(lens[0], lens[1]) < 50.
assert utils.rmsd(volume[0], volume[1]) < 2e-3
assert utils.rmsd(surface_h[0], surface_h[1]) < 1.0