def test_plot_model():
gdir = init_hef()
flowline.init_present_time_glacier(gdir)
model = flowline.FlowlineModel(gdir.read_pickle('model_flowlines'))
graphics.plot_modeloutput_section(gdir, model=model)
graphics.plot_modeloutput_map(gdir, model=model)
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_modelmap():
gdir = init_hef()
flowline.init_present_time_glacier(gdir)
fls = gdir.read_pickle('model_flowlines')
model = flowline.FlowlineModel(fls)
fig, ax = plt.subplots()
graphics.plot_modeloutput_map(gdir, ax=ax, model=model)
fig.tight_layout()
return fig
def test_modelsection():
gdir = init_hef()
flowline.init_present_time_glacier(gdir)
fls = gdir.read_pickle('model_flowlines')
model = flowline.FlowlineModel(fls)
fig = plt.figure(figsize=(12, 6))
ax = fig.add_axes([0.07, 0.08, 0.7, 0.84])
graphics.plot_modeloutput_section(gdir, ax=ax, model=model)
return fig
def test_chhota_shigri():
testdir = os.path.join(cfg.PATHS['test_dir'], 'tmp_chhota')
utils.mkdir(testdir)
# Init
cfg.initialize()
cfg.PATHS['dem_file'] = get_demo_file('dem_chhota_shigri.tif')
cfg.PARAMS['border'] = 60
cfg.set_divides_db(get_demo_file('divides_RGI50-14.15990.shp'))
hef_file = get_demo_file('RGI50-14.15990.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
centerlines.compute_downstream_lines(gdir)
geometry.initialize_flowlines(gdir)
# We should have two groups
lines = gdir.read_pickle('downstream_lines', div_id=0)
assert len(np.unique(lines.group)) == 2
# Just check if the rest runs
centerlines.compute_downstream_bedshape(gdir)
geometry.catchment_area(gdir)
geometry.catchment_intersections(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
climate.apparent_mb_from_linear_mb(gdir)
inversion.prepare_for_inversion(gdir)
inversion.volume_inversion(gdir, use_cfg_params={'glen_a': cfg.A, 'fs': 0})
inversion.filter_inversion_output(gdir)
flowline.init_present_time_glacier(gdir)
fls = gdir.read_pickle('model_flowlines')
for fl in fls:
fl.thick = np.clip(fl.thick, 100, 1000)
model = flowline.FlowlineModel(fls)
fig, ax = plt.subplots()
graphics.plot_modeloutput_map(gdir, ax=ax, model=model)
fig.tight_layout()
return fig
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)
if not os.path.exists(fn):
graphics.plot_centerlines(gd, title_comment=demsource)
plt.savefig(fn)
plt.close()
fn = bname + '3_fls.png'
if not os.path.exists(fn):
graphics.plot_centerlines(gd,
title_comment=demsource,
use_flowlines=True,
add_downstream=True)
plt.savefig(fn)
plt.close()
fn = bname + '4_widths.png'
if not os.path.exists(fn):
graphics.plot_catchment_width(gd,
corrected=True,
add_intersects=True,
add_touches=True)
plt.savefig(fn)
plt.close()
fn = bname + '5_thick.png'
if not os.path.exists(fn):
fls = gd.read_pickle('model_flowlines')
model = flowline.FlowlineModel(fls)
graphics.plot_modeloutput_map(gd, model=model)
plt.savefig(fn)
plt.close()
