def test_downstream(self):
hef_file = get_demo_file('Hintereisferner.shp')
rgidf = gpd.GeoDataFrame.from_file(hef_file)
# loop because for some reason indexing wont work
for index, entity in rgidf.iterrows():
gdir = cfg.GlacierDir(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
centerlines.compute_downstream_lines(gdir)
def init_hef(reset=False):
# test directory
if not os.path.exists(testdir):
os.makedirs(testdir)
reset = True
if not os.path.exists(os.path.join(testdir, 'RGI40-11.00897')):
reset = True
if not os.path.exists(os.path.join(testdir, 'RGI40-11.00897',
'flowline_params.p')):
reset = True
# Init
cfg.initialize()
cfg.set_divides_db(get_demo_file('HEF_divided.shp'))
cfg.paths['srtm_file'] = get_demo_file('hef_srtm.tif')
cfg.paths['histalp_file'] = get_demo_file('histalp_merged_hef.nc')
cfg.params['border'] = 40
# loop because for some reason indexing wont work
hef_file = get_demo_file('Hintereisferner.shp')
rgidf = gpd.GeoDataFrame.from_file(hef_file)
for index, entity in rgidf.iterrows():
gdir = cfg.GlacierDir(entity, base_dir=testdir, reset=reset)
if not reset:
return gdir
gis.define_glacier_region(gdir, entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
centerlines.compute_downstream_lines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
climate.distribute_climate_data([gdir])
climate.mu_candidates(gdir, div_id=0)
hef_file = get_demo_file('mbdata_RGI40-11.00897.csv')
mbdf = pd.read_csv(hef_file).set_index('YEAR')
t_star, bias = climate.t_star_from_refmb(gdir, mbdf['ANNUAL_BALANCE'])
climate.local_mustar_apparent_mb(gdir, t_star[-1], bias[-1])
inversion.prepare_for_inversion(gdir)
ref_v = 0.573 * 1e9
def to_optimize(x):
fd = 1.9e-24 * x[0]
fs = 5.7e-20 * x[1]
v, _ = inversion.inversion_parabolic_point_slope(gdir,
fs=fs,
fd=fd)
return (v - ref_v)**2
import scipy.optimize as optimization
out = optimization.minimize(to_optimize, [1,1],
bounds=((0.01, 1), (0.01, 1)),
tol=1e-3)['x']
fd = 1.9e-24 * out[0]
fs = 5.7e-20 * out[1]
v, _ = inversion.inversion_parabolic_point_slope(gdir,
fs=fs,
fd=fd,
write=True)
d = dict(fs=fs, fd=fd)
gdir.write_pickle(d, 'flowline_params')
return gdir
