def test_histalp_mb(self):
gdir = init_hef(border=DOM_BORDER)
flowline.init_present_time_glacier(gdir)
mb_mod = massbalance.TodayMassBalanceModel(gdir)
ofl = gdir.read_pickle('inversion_flowlines', div_id=0)
h = np.array([])
w = np.array([])
for fl in ofl:
h = np.append(h, fl.surface_h)
w = np.append(w, fl.widths)
ref_mbh = mb_mod.get_mb(h, None) * 365 * 24 * 3600
mb_mod = massbalance.HistalpMassBalanceModel(gdir)
# Climate period
yrs = np.arange(1983, 2003.1, 1)
my_mb = ref_mbh * 0.
for yr in yrs:
my_mb += mb_mod.get_mb(h, yr)
my_mb = my_mb / len(yrs) * 365 * 24 * 3600
np.testing.assert_allclose(ref_mbh, my_mb, rtol=0.01)
def test_tstar_mb(self):
gdir = init_hef(border=DOM_BORDER)
flowline.init_present_time_glacier(gdir)
mb_mod = massbalance.TstarMassBalanceModel(gdir)
ofl = gdir.read_pickle('inversion_flowlines', div_id=0)
h = np.array([])
w = np.array([])
for fl in ofl:
h = np.append(h, fl.surface_h)
w = np.append(w, fl.widths)
ombh = mb_mod.get_mb(h, None)
otmb = np.sum(ombh * w)
np.testing.assert_allclose(0., otmb, atol=0.26)
mb_mod = massbalance.TodayMassBalanceModel(gdir)
ofl = gdir.read_pickle('inversion_flowlines', div_id=0)
h = np.array([])
w = np.array([])
for fl in ofl:
h = np.append(h, fl.surface_h)
w = np.append(w, fl.widths)
mbh = mb_mod.get_mb(h, None)
tmb = np.sum(mbh * w)
self.assertTrue(tmb < otmb)
if do_plot: # pragma: no cover
plt.plot(h, ombh, 'o')
plt.plot(h, mbh, 'o')
plt.show()
def test_tstar_mb(self):
gdir = init_hef(border=DOM_BORDER)
flowline.init_present_time_glacier(gdir)
mb_mod = massbalance.TstarMassBalanceModel(gdir)
ofl = gdir.read_pickle('inversion_flowlines', div_id=0)
h = np.array([])
w = np.array([])
for fl in ofl:
h = np.append(h, fl.surface_h)
w = np.append(w, fl.widths)
ombh = mb_mod.get_mb(h, None)
otmb = np.sum(ombh * w)
np.testing.assert_allclose(0., otmb, atol=0.26)
mb_mod = massbalance.TodayMassBalanceModel(gdir)
ofl = gdir.read_pickle('inversion_flowlines', div_id=0)
h = np.array([])
w = np.array([])
for fl in ofl:
h = np.append(h, fl.surface_h)
w = np.append(w, fl.widths)
mbh = mb_mod.get_mb(h, None)
tmb = np.sum(mbh * w)
self.assertTrue(tmb < otmb)
if do_plot: # pragma: no cover
plt.plot(h, ombh, 'o')
plt.plot(h, mbh, 'o')
plt.show()
def test_histalp_mb(self):
gdir = init_hef(border=DOM_BORDER)
flowline.init_present_time_glacier(gdir)
mb_mod = massbalance.TodayMassBalanceModel(gdir)
ofl = gdir.read_pickle('inversion_flowlines', div_id=0)
h = np.array([])
w = np.array([])
for fl in ofl:
h = np.append(h, fl.surface_h)
w = np.append(w, fl.widths)
ref_mbh = mb_mod.get_mb(h, None) * 365 * 24 * 3600
mb_mod = massbalance.HistalpMassBalanceModel(gdir)
# Climate period
yrs = np.arange(1983, 2003.1, 1)
my_mb = ref_mbh * 0.
for yr in yrs:
my_mb += mb_mod.get_mb(h, yr)
my_mb = my_mb / len(yrs) * 365 * 24 * 3600
np.testing.assert_allclose(ref_mbh, my_mb, rtol=0.01)
def test_find_t0(self):
gdir = init_hef(border=DOM_BORDER, invert_with_sliding=False)
flowline.init_present_time_glacier(gdir)
glacier = gdir.read_pickle('model_flowlines')
df = pd.read_csv(utils.get_demo_file('hef_lengths.csv'), index_col=0)
df.columns = ['Leclercq']
df = df.loc[1950:]
vol_ref = flowline.FlowlineModel(glacier).volume_km3
init_bias = 100. # 100 so that "went too far" comes once on travis
rtol = 0.005
flowline.find_inital_glacier(gdir,
y0=df.index[0],
init_bias=init_bias,
rtol=rtol,
write_steps=False)
past_model = gdir.read_pickle('past_model')
vol_start = past_model.volume_km3
bef_fls = copy.deepcopy(past_model.fls)
mylen = []
for y in df.index:
past_model.run_until(y)
mylen.append(past_model.fls[-1].length_m)
df['oggm'] = mylen
df = df - df.iloc[-1]
vol_end = past_model.volume_km3
np.testing.assert_allclose(vol_ref, vol_end, rtol=0.05)
rmsd = utils.rmsd(df.Leclercq, df.oggm)
self.assertTrue(rmsd < 1000.)
if do_plot: # pragma: no cover
df.plot()
plt.ylabel('Glacier length (relative to 2003)')
plt.show()
fig = plt.figure()
lab = 'ref (vol={:.2f}km3)'.format(vol_ref)
plt.plot(glacier[-1].surface_h, 'k', label=lab)
lab = 'oggm start (vol={:.2f}km3)'.format(vol_start)
plt.plot(bef_fls[-1].surface_h, 'b', label=lab)
lab = 'oggm end (vol={:.2f}km3)'.format(vol_end)
plt.plot(past_model.fls[-1].surface_h, 'r', label=lab)
plt.plot(glacier[-1].bed_h, 'gray', linewidth=2)
plt.legend(loc='best')
plt.show()
def test_backwards_mb(self):
gdir = init_hef(border=DOM_BORDER)
flowline.init_present_time_glacier(gdir)
mb_mod_ref = massbalance.TstarMassBalanceModel(gdir)
mb_mod = massbalance.BackwardsMassBalanceModel(gdir, use_tstar=True)
ofl = gdir.read_pickle('inversion_flowlines', div_id=0)
h = np.array([])
w = np.array([])
for fl in ofl:
h = np.append(h, fl.surface_h)
w = np.append(w, fl.widths)
ombh = mb_mod_ref.get_mb(h, None) * SEC_IN_YEAR
mbh = mb_mod.get_mb(h, None) * SEC_IN_YEAR
mb_mod.set_bias(100.)
mbhb = mb_mod.get_mb(h, None) * SEC_IN_YEAR
np.testing.assert_allclose(ombh, mbh, rtol=0.001)
self.assertTrue(np.mean(mbhb) > np.mean(mbh))
if do_plot: # pragma: no cover
plt.plot(h, ombh, 'o')
plt.plot(h, mbh, 'x')
plt.plot(h, mbhb, 'x')
plt.show()
mb_mod_ref = massbalance.TodayMassBalanceModel(gdir)
mb_mod = massbalance.BackwardsMassBalanceModel(gdir)
ofl = gdir.read_pickle('inversion_flowlines', div_id=0)
h = np.array([])
w = np.array([])
for fl in ofl:
h = np.append(h, fl.surface_h)
w = np.append(w, fl.widths)
ombh = mb_mod_ref.get_mb(h, None) * SEC_IN_YEAR
mbh = mb_mod.get_mb(h, None) * SEC_IN_YEAR
mb_mod.set_bias(-100.)
mbhb = mb_mod.get_mb(h, None) * SEC_IN_YEAR
np.testing.assert_allclose(ombh, mbh, rtol=0.005)
self.assertTrue(np.mean(mbhb) < np.mean(mbh))
if do_plot: # pragma: no cover
plt.plot(h, ombh, 'o')
plt.plot(h, mbh, 'x')
plt.plot(h, mbhb, 'x')
plt.show()
def test_backwards_mb(self):
gdir = init_hef(border=DOM_BORDER)
flowline.init_present_time_glacier(gdir)
mb_mod_ref = massbalance.TstarMassBalanceModel(gdir)
mb_mod = massbalance.BackwardsMassBalanceModel(gdir, use_tstar=True)
ofl = gdir.read_pickle('inversion_flowlines', div_id=0)
h = np.array([])
w = np.array([])
for fl in ofl:
h = np.append(h, fl.surface_h)
w = np.append(w, fl.widths)
ombh = mb_mod_ref.get_mb(h, None) * SEC_IN_YEAR
mbh = mb_mod.get_mb(h, None) * SEC_IN_YEAR
mb_mod.set_bias(100.)
mbhb = mb_mod.get_mb(h, None) * SEC_IN_YEAR
np.testing.assert_allclose(ombh, mbh, rtol=0.001)
self.assertTrue(np.mean(mbhb) > np.mean(mbh))
if do_plot: # pragma: no cover
plt.plot(h, ombh, 'o')
plt.plot(h, mbh, 'x')
plt.plot(h, mbhb, 'x')
plt.show()
mb_mod_ref = massbalance.TodayMassBalanceModel(gdir)
mb_mod = massbalance.BackwardsMassBalanceModel(gdir)
ofl = gdir.read_pickle('inversion_flowlines', div_id=0)
h = np.array([])
w = np.array([])
for fl in ofl:
h = np.append(h, fl.surface_h)
w = np.append(w, fl.widths)
ombh = mb_mod_ref.get_mb(h, None) * SEC_IN_YEAR
mbh = mb_mod.get_mb(h, None) * SEC_IN_YEAR
mb_mod.set_bias(-100.)
mbhb = mb_mod.get_mb(h, None) * SEC_IN_YEAR
np.testing.assert_allclose(ombh, mbh, rtol=0.005)
self.assertTrue(np.mean(mbhb) < np.mean(mbh))
if do_plot: # pragma: no cover
plt.plot(h, ombh, 'o')
plt.plot(h, mbh, 'x')
plt.plot(h, mbhb, 'x')
plt.show()
def test_init_present_time_glacier(self):
gdir = init_hef(border=DOM_BORDER)
flowline.init_present_time_glacier(gdir)
fls = gdir.read_pickle('model_flowlines')
lens = [
len(gdir.read_pickle('centerlines', div_id=i)) for i in [1, 2, 3]
]
ofl = gdir.read_pickle('inversion_flowlines',
div_id=np.argmax(lens) + 1)[-1]
self.assertTrue(gdir.rgi_date.year == 2003)
self.assertTrue(len(fls) == 5)
vol = 0.
area = 0.
for fl in fls:
refo = 1 if fl is fls[-1] else 0
self.assertTrue(fl.order == refo)
ref = np.arange(len(fl.surface_h)) * fl.dx
np.testing.assert_allclose(ref,
fl.dis_on_line,
rtol=0.001,
atol=0.01)
self.assertTrue(
len(fl.surface_h) == len(fl.bed_h) == len(fl.bed_shape) == len(
fl.dis_on_line) == len(fl.widths))
self.assertTrue(np.all(fl.bed_shape >= 0))
self.assertTrue(np.all(fl.widths >= 0))
vol += fl.volume_km3
area += fl.area_km2
if refo == 1:
rtol = 0.07 if HAS_NEW_GDAL else 0.05
np.testing.assert_allclose(ofl.widths * gdir.grid.dx,
fl.widths_m[0:len(ofl.widths)],
rtol=rtol)
np.testing.assert_allclose(0.573, vol, rtol=0.001)
np.testing.assert_allclose(7350.0, fls[-1].length_m)
rtol = 0.01 if HAS_NEW_GDAL else 0.001
np.testing.assert_allclose(gdir.rgi_area_km2, area, rtol=rtol)
if do_plot: # pragma: no cover
plt.plot(fls[-1].bed_h)
plt.plot(fls[-1].surface_h)
plt.show()
def test_init_present_time_glacier(self):
gdir = init_hef(border=DOM_BORDER)
flowline.init_present_time_glacier(gdir)
fls = gdir.read_pickle('model_flowlines')
lens = [len(gdir.read_pickle('centerlines', div_id=i)) for i in [1,
2, 3]]
ofl = gdir.read_pickle('inversion_flowlines',
div_id=np.argmax(lens)+1)[-1]
self.assertTrue(gdir.rgi_date.year == 2003)
self.assertTrue(len(fls) == 5)
vol = 0.
area = 0.
for fl in fls:
refo = 1 if fl is fls[-1] else 0
self.assertTrue(fl.order == refo)
ref = np.arange(len(fl.surface_h)) * fl.dx
np.testing.assert_allclose(ref, fl.dis_on_line,
rtol=0.001,
atol=0.01)
self.assertTrue(len(fl.surface_h) ==
len(fl.bed_h) ==
len(fl.bed_shape) ==
len(fl.dis_on_line) ==
len(fl.widths))
self.assertTrue(np.all(fl.bed_shape >= 0))
self.assertTrue(np.all(fl.widths >= 0))
vol += fl.volume_km3
area += fl.area_km2
if refo == 1:
rtol = 0.07 if HAS_NEW_GDAL else 0.05
np.testing.assert_allclose(ofl.widths * gdir.grid.dx,
fl.widths_m[0:len(ofl.widths)],
rtol=rtol)
np.testing.assert_allclose(0.573, vol, rtol=0.001)
np.testing.assert_allclose(7350.0, fls[-1].length_m)
rtol = 0.01 if HAS_NEW_GDAL else 0.001
np.testing.assert_allclose(gdir.rgi_area_km2, area, rtol=rtol)
if do_plot: # pragma: no cover
plt.plot(fls[-1].bed_h)
plt.plot(fls[-1].surface_h)
plt.show()
def test_find_t0(self):
gdir = init_hef(border=DOM_BORDER, invert_with_sliding=False)
flowline.init_present_time_glacier(gdir)
glacier = gdir.read_pickle('model_flowlines')
df = pd.read_csv(utils.get_demo_file('hef_lengths.csv'), index_col=0)
df.columns = ['Leclercq']
df = df.loc[1950:]
vol_ref = flowline.FlowlineModel(glacier).volume_km3
init_bias = 100. # 100 so that "went too far" comes once on travis
rtol = 0.005
flowline.find_inital_glacier(gdir, y0=df.index[0], init_bias=init_bias,
rtol=rtol, write_steps=False)
past_model = gdir.read_pickle('past_model')
vol_start = past_model.volume_km3
bef_fls = copy.deepcopy(past_model.fls)
mylen = []
for y in df.index:
past_model.run_until(y)
mylen.append(past_model.fls[-1].length_m)
df['oggm'] = mylen
df = df-df.iloc[-1]
vol_end = past_model.volume_km3
np.testing.assert_allclose(vol_ref, vol_end, rtol=0.05)
rmsd = utils.rmsd(df.Leclercq, df.oggm)
self.assertTrue(rmsd < 1000.)
if do_plot: # pragma: no cover
df.plot()
plt.ylabel('Glacier length (relative to 2003)')
plt.show()
fig = plt.figure()
lab = 'ref (vol={:.2f}km3)'.format(vol_ref)
plt.plot(glacier[-1].surface_h, 'k', label=lab)
lab = 'oggm start (vol={:.2f}km3)'.format(vol_start)
plt.plot(bef_fls[-1].surface_h, 'b', label=lab)
lab = 'oggm end (vol={:.2f}km3)'.format(vol_end)
plt.plot(past_model.fls[-1].surface_h, 'r', label=lab)
plt.plot(glacier[-1].bed_h, 'gray', linewidth=2)
plt.legend(loc='best')
plt.show()
def test_present_time_glacier_massbalance(self):
gdir = init_hef(border=DOM_BORDER)
flowline.init_present_time_glacier(gdir)
mb_mod = massbalance.HistalpMassBalanceModel(gdir)
fls = gdir.read_pickle('model_flowlines')
glacier = flowline.FlowlineModel(fls)
hef_file = utils.get_demo_file('mbdata_RGI40-11.00897.csv')
mbdf = pd.read_csv(hef_file).set_index('YEAR')
hgts = np.array([])
widths = np.array([])
for fl in glacier.fls:
hgts = np.concatenate((hgts, fl.surface_h))
widths = np.concatenate((widths, fl.widths_m))
tot_mb = []
refmb = []
grads = hgts * 0
for yr, mb in mbdf.iterrows():
refmb.append(mb['ANNUAL_BALANCE'])
mbh = mb_mod.get_mb(hgts, yr) * SEC_IN_YEAR * cfg.RHO
grads += mbh
tot_mb.append(np.average(mbh, weights=widths))
grads /= len(tot_mb)
# Bias
self.assertTrue(np.abs(utils.md(tot_mb, refmb)) < 50)
# Gradient
dfg = pd.read_csv(utils.get_demo_file('mbgrads_RGI40-11.00897.csv'),
index_col='ALTITUDE').mean(axis=1)
# Take the altitudes below 3100 and fit a line
dfg = dfg[dfg.index < 3100]
pok = np.where(hgts < 3100)
from scipy.stats import linregress
slope_obs, _, _, _, _ = linregress(dfg.index, dfg.values)
slope_our, _, _, _, _ = linregress(hgts[pok], grads[pok])
np.testing.assert_allclose(slope_obs, slope_our, rtol=0.1)
def test_present_time_glacier_massbalance(self):
gdir = init_hef(border=DOM_BORDER)
flowline.init_present_time_glacier(gdir)
mb_mod = massbalance.HistalpMassBalanceModel(gdir)
fls = gdir.read_pickle('model_flowlines')
glacier = flowline.FlowlineModel(fls)
hef_file = utils.get_demo_file('mbdata_RGI40-11.00897.csv')
mbdf = pd.read_csv(hef_file).set_index('YEAR')
hgts = np.array([])
widths = np.array([])
for fl in glacier.fls:
hgts = np.concatenate((hgts, fl.surface_h))
widths = np.concatenate((widths, fl.widths_m))
tot_mb = []
refmb = []
grads = hgts * 0
for yr, mb in mbdf.iterrows():
refmb.append(mb['ANNUAL_BALANCE'])
mbh = mb_mod.get_mb(hgts, yr) * SEC_IN_YEAR * cfg.RHO
grads += mbh
tot_mb.append(np.average(mbh, weights=widths))
grads /= len(tot_mb)
# Bias
self.assertTrue(np.abs(utils.md(tot_mb, refmb)) < 50)
# Gradient
dfg = pd.read_csv(utils.get_demo_file('mbgrads_RGI40-11.00897.csv'),
index_col='ALTITUDE').mean(axis=1)
# Take the altitudes below 3100 and fit a line
dfg = dfg[dfg.index < 3100]
pok = np.where(hgts < 3100)
from scipy.stats import linregress
slope_obs, _, _, _, _ = linregress(dfg.index, dfg.values)
slope_our, _, _, _, _ = linregress(hgts[pok], grads[pok])
np.testing.assert_allclose(slope_obs, slope_our, rtol=0.1)
def setUp(self):
self.gdir = init_hef(border=DOM_BORDER)
d = self.gdir.read_pickle('inversion_params')
self.fs = d['fs']
self.glen_a = d['glen_a']
def setUp(self):
self.gdir = init_hef(border=DOM_BORDER)
d = self.gdir.read_pickle('inversion_params')
self.fs = d['fs']
self.glen_a = d['glen_a']
