def test_cliff(self):
""" a test case for mass conservation in the flowline models
the idea is to introduce a cliff in the sloping bed and see
what the models do when the cliff height is changed
"""
models = [KarthausModel, FluxBasedModel, MUSCLSuperBeeModel]
lens = []
surface_h = []
volume = []
yrs = np.arange(1, 500, 2)
for model in models:
fls = dummy_constant_bed_cliff()
mb = LinearMassBalance(2600.)
model = model(fls,
mb_model=mb,
y0=0.,
glen_a=self.glen_a,
fs=self.fs,
fixed_dt=2 * SEC_IN_DAY)
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 False: # 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()
# OK, so basically, Alex's tests below show that the other models
# are wrong and produce too much mass. There is also another more
# more trivial issue with the computation of the length, I added a
# "to do" in the code.
# Unit-testing perspective:
# "verify" that indeed the models are wrong of more than 50%
self.assertTrue(volume[1][-1] > volume[2][-1] * 1.5)
# Karthaus is even worse
self.assertTrue(volume[0][-1] > volume[1][-1])
if False:
# TODO: this will always fail so ignore it for now
np.testing.assert_almost_equal(lens[0][-1], lens[1][-1])
np.testing.assert_allclose(volume[0][-1], volume[2][-1], atol=2e-3)
np.testing.assert_allclose(volume[1][-1], volume[2][-1], atol=2e-3)
self.assertTrue(utils.rmsd(lens[0], lens[2]) < 50.)
self.assertTrue(utils.rmsd(lens[1], lens[2]) < 50.)
self.assertTrue(utils.rmsd(volume[0], volume[2]) < 1e-3)
self.assertTrue(utils.rmsd(volume[1], volume[2]) < 1e-3)
self.assertTrue(utils.rmsd(surface_h[0], surface_h[2]) < 1.0)
self.assertTrue(utils.rmsd(surface_h[1], surface_h[2]) < 1.0)
def test_cliff(self):
""" a test case for mass conservation in the flowline models
the idea is to introduce a cliff in the sloping bed and see
what the models do when the cliff height is changed
"""
models = [KarthausModel, FluxBasedModel, MUSCLSuperBeeModel]
lens = []
surface_h = []
volume = []
yrs = np.arange(1, 500, 2)
for model in models:
fls = dummy_constant_bed_cliff()
mb = LinearMassBalance(2600.)
model = model(fls, mb_model=mb, y0=0., glen_a=self.glen_a,
fs=self.fs, fixed_dt=2*SEC_IN_DAY)
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 False: # 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()
# OK, so basically, Alex's tests below show that the other models
# are wrong and produce too much mass. There is also another more
# more trivial issue with the computation of the length, I added a
# "to do" in the code.
# Unit-testing perspective:
# "verify" that indeed the models are wrong of more than 50%
self.assertTrue(volume[1][-1] > volume[2][-1] * 1.5)
# Karthaus is even worse
self.assertTrue(volume[0][-1] > volume[1][-1])
if False:
# TODO: this will always fail so ignore it for now
np.testing.assert_almost_equal(lens[0][-1], lens[1][-1])
np.testing.assert_allclose(volume[0][-1], volume[2][-1], atol=2e-3)
np.testing.assert_allclose(volume[1][-1], volume[2][-1], atol=2e-3)
self.assertTrue(utils.rmsd(lens[0], lens[2]) < 50.)
self.assertTrue(utils.rmsd(lens[1], lens[2]) < 50.)
self.assertTrue(utils.rmsd(volume[0], volume[2]) < 1e-3)
self.assertTrue(utils.rmsd(volume[1], volume[2]) < 1e-3)
self.assertTrue(utils.rmsd(surface_h[0], surface_h[2]) < 1.0)
self.assertTrue(utils.rmsd(surface_h[1], surface_h[2]) < 1.0)
