def test_catchment_area(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.catchment_area(gdir)
for div_id in gdir.divide_ids:
cis = gdir.read_pickle("catchment_indices", div_id=div_id)
# The catchment area must be as big as expected
with netCDF4.Dataset(gdir.get_filepath("gridded_data", div_id=div_id)) as nc:
mask = nc.variables["glacier_mask"][:]
mymask_a = mask * 0
mymask_b = mask * 0
for i, ci in enumerate(cis):
mymask_a[tuple(ci.T)] += 1
mymask_b[tuple(ci.T)] = i + 1
self.assertTrue(np.max(mymask_a) == 1)
np.testing.assert_allclose(mask, mymask_a)
def test_centerlines(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
for div_id in gdir.divide_ids:
cls = gdir.read_pickle('centerlines', div_id=div_id)
for cl in cls:
for j, ip, ob in zip(cl.inflow_indices, cl.inflow_points,
cl.inflows):
self.assertTrue(cl.line.coords[j] == ip.coords[0])
self.assertTrue(
ob.flows_to_point.coords[0] == ip.coords[0])
self.assertTrue(
cl.line.coords[ob.flows_to_indice] == ip.coords[0])
lens = [
len(gdir.read_pickle('centerlines', div_id=i)) for i in [1, 2, 3]
]
self.assertTrue(sorted(lens) == [1, 1, 3])
def test_catchment_area(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.catchment_area(gdir)
for div_id in gdir.divide_ids:
cis = gdir.read_pickle('catchment_indices', div_id=div_id)
# The catchment area must be as big as expected
nc = netCDF4.Dataset(
gdir.get_filepath('gridded_data', div_id=div_id))
mask = nc.variables['glacier_mask'][:]
nc.close()
mymask_a = mask * 0
mymask_b = mask * 0
for i, ci in enumerate(cis):
mymask_a[tuple(ci.T)] += 1
mymask_b[tuple(ci.T)] = i + 1
self.assertTrue(np.max(mymask_a) == 1)
np.testing.assert_allclose(mask, mymask_a)
def test_catchment_area(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.catchment_area(gdir)
for div_id in gdir.divide_ids:
cis = gdir.read_pickle('catchment_indices', div_id=div_id)
# The catchment area must be as big as expected
nc = netCDF4.Dataset(gdir.get_filepath('gridded_data', div_id=div_id))
mask = nc.variables['glacier_mask'][:]
nc.close()
mymask_a = mask * 0
mymask_b = mask * 0
for i, ci in enumerate(cis):
mymask_a[tuple(ci.T)] += 1
mymask_b[tuple(ci.T)] = i+1
self.assertTrue(np.max(mymask_a) == 1)
np.testing.assert_allclose(mask, mymask_a)
def test_distribute_climate_cru(self):
hef_file = get_demo_file('Hintereisferner.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdirs = []
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gdirs.append(gdir)
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir_cru)
gis.define_glacier_region(gdir, entity=entity)
gdirs.append(gdir)
climate.distribute_climate_data([gdirs[0]])
cru_dir = get_demo_file('cru_ts3.23.1901.2014.tmp.dat.nc')
cru_dir = os.path.dirname(cru_dir)
cfg.PATHS['climate_file'] = '~'
cfg.PATHS['cru_dir'] = cru_dir
climate.distribute_climate_data([gdirs[1]])
cfg.PATHS['cru_dir'] = '~'
cfg.PATHS['climate_file'] = get_demo_file('histalp_merged_hef.nc')
gdh = gdirs[0]
gdc = gdirs[1]
with xr.open_dataset(os.path.join(gdh.dir, 'climate_monthly.nc')) as nc_h:
with xr.open_dataset(os.path.join(gdc.dir, 'climate_monthly.nc')) as nc_c:
# put on the same altitude
# (using default gradient because better)
temp_cor = nc_c.temp -0.0065 * (nc_h.ref_hgt - nc_c.ref_hgt)
totest = temp_cor - nc_h.temp
self.assertTrue(totest.mean() < 0.5)
# precip
totest = nc_c.prcp - nc_h.prcp
self.assertTrue(totest.mean() < 100)
def test_mu_candidates(self):
hef_file = get_demo_file('Hintereisferner.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdirs = []
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
gdirs.append(gdir)
climate.distribute_climate_data(gdirs)
climate.mu_candidates(gdir, div_id=0)
se = gdir.read_pickle('mu_candidates')
self.assertTrue(se.index[0] == 1802)
self.assertTrue(se.index[-1] == 2003)
df = pd.DataFrame()
df['mu'] = se
# Check that the moovin average of temp is negatively correlated
# with the mus
with netCDF4.Dataset(get_demo_file('histalp_merged_hef.nc')) as nc_r:
ref_t = nc_r.variables['temp'][:, 1, 1]
ref_t = np.mean(ref_t.reshape((len(df), 12)), 1)
ma = np.convolve(ref_t, np.ones(31) / float(31), 'same')
df['temp'] = ma
df = df.dropna()
self.assertTrue(np.corrcoef(df['mu'], df['temp'])[0, 1] < -0.75)
def test_distribute_climate_parallel(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdirs = []
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gdirs.append(gdir)
climate.process_custom_climate_data(gdir)
ci = gdir.read_pickle("climate_info")
self.assertEqual(ci["hydro_yr_0"], 1802)
self.assertEqual(ci["hydro_yr_1"], 2003)
with netCDF4.Dataset(get_demo_file("histalp_merged_hef.nc")) as nc_r:
ref_h = nc_r.variables["hgt"][1, 1]
ref_p = nc_r.variables["prcp"][:, 1, 1]
ref_t = nc_r.variables["temp"][:, 1, 1]
with netCDF4.Dataset(os.path.join(gdir.dir, "climate_monthly.nc")) as nc_r:
self.assertTrue(ref_h == nc_r.ref_hgt)
np.testing.assert_allclose(ref_t, nc_r.variables["temp"][:])
np.testing.assert_allclose(ref_p, nc_r.variables["prcp"][:])
def test_flowlines(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
for div_id in gdir.divide_ids:
cls = gdir.read_pickle("inversion_flowlines", div_id=div_id)
for cl in cls:
for j, ip, ob in zip(cl.inflow_indices, cl.inflow_points, cl.inflows):
self.assertTrue(cl.line.coords[j] == ip.coords[0])
self.assertTrue(ob.flows_to_point.coords[0] == ip.coords[0])
self.assertTrue(cl.line.coords[ob.flows_to_indice] == ip.coords[0])
lens = [len(gdir.read_pickle("centerlines", div_id=i)) for i in [1, 2, 3]]
self.assertTrue(sorted(lens) == [1, 1, 2])
x, y = map(np.array, cls[0].line.xy)
dis = np.sqrt((x[1:] - x[:-1]) ** 2 + (y[1:] - y[:-1]) ** 2)
np.testing.assert_allclose(dis * 0 + cfg.PARAMS["flowline_dx"], dis, rtol=0.01)
def test_flowlines(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
for div_id in gdir.divide_ids:
cls = gdir.read_pickle('inversion_flowlines', div_id=div_id)
for cl in cls:
for j, ip, ob in zip(cl.inflow_indices, cl.inflow_points,
cl.inflows):
self.assertTrue(cl.line.coords[j] == ip.coords[0])
self.assertTrue(
ob.flows_to_point.coords[0] == ip.coords[0])
self.assertTrue(
cl.line.coords[ob.flows_to_indice] == ip.coords[0])
lens = [
len(gdir.read_pickle('centerlines', div_id=i)) for i in [1, 2, 3]
]
self.assertTrue(sorted(lens) == [1, 1, 3])
x, y = map(np.array, cls[0].line.xy)
dis = np.sqrt((x[1:] - x[:-1])**2 + (y[1:] - y[:-1])**2)
np.testing.assert_allclose(dis * 0 + cfg.PARAMS['flowline_dx'],
dis,
rtol=0.01)
def test_nodivide():
# test directory
testdir = TESTDIR_BASE + '_nodiv'
if not os.path.exists(testdir):
os.makedirs(testdir)
# Init
cfg.initialize()
cfg.set_divides_db()
cfg.PATHS['dem_file'] = get_demo_file('hef_srtm.tif')
cfg.PATHS['climate_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 = oggm.GlacierDirectory(entity, base_dir=testdir, reset=True)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
graphics.plot_centerlines(gdir)
def test_distribute_climate(self):
hef_file = get_demo_file('Hintereisferner.shp')
rgidf = gpd.GeoDataFrame.from_file(hef_file)
gdirs = []
# loop because for some reason indexing wont work
for index, entity in rgidf.iterrows():
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gdirs.append(gdir)
climate.distribute_climate_data(gdirs)
with netCDF4.Dataset(get_demo_file('histalp_merged_hef.nc')) as nc_r:
ref_h = nc_r.variables['hgt'][1, 1]
ref_p = nc_r.variables['prcp'][:, 1, 1]
ref_p *= cfg.PARAMS['prcp_scaling_factor']
ref_t = nc_r.variables['temp'][:, 1, 1]
with netCDF4.Dataset(os.path.join(gdir.dir,
'climate_monthly.nc')) as nc_r:
self.assertTrue(ref_h == nc_r.ref_hgt)
np.testing.assert_allclose(ref_t, nc_r.variables['temp'][:])
np.testing.assert_allclose(ref_p, nc_r.variables['prcp'][:])
def test_nodivide():
# test directory
testdir = TESTDIR_BASE + '_nodiv'
if not os.path.exists(testdir):
os.makedirs(testdir)
# Init
cfg.initialize()
cfg.set_divides_db()
cfg.PATHS['dem_file'] = get_demo_file('hef_srtm.tif')
cfg.PATHS['climate_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 = oggm.GlacierDirectory(entity, base_dir=testdir, reset=True)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
graphics.plot_centerlines(gdir)
def test_ice_cap():
testdir = os.path.join(cfg.PATHS['test_dir'], 'tmp_icecap')
utils.mkdir(testdir)
cfg.initialize()
cfg.PATHS['dem_file'] = get_demo_file('dem_RGI50-05.08389.tif')
cfg.PARAMS['border'] = 20
cfg.set_divides_db(get_demo_file('divides_RGI50-05.08389.shp'))
hef_file = get_demo_file('RGI50-05.08389.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=testdir, reset=True)
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 five groups
lines = gdir.read_pickle('downstream_lines', div_id=0)
assert len(np.unique(lines.group))==5
# This just checks that it works
geometry.catchment_area(gdir)
geometry.catchment_intersections(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
fig, ax = plt.subplots()
graphics.plot_catchment_width(gdir, ax=ax, add_intersects=True,
add_touches=True)
fig.tight_layout()
return fig
def test_nodivide():
# test directory
testdir = TESTDIR_BASE + '_nodiv'
if not os.path.exists(testdir):
os.makedirs(testdir)
# Init
cfg.initialize()
cfg.set_divides_db()
cfg.PATHS['dem_file'] = get_demo_file('hef_srtm.tif')
cfg.PATHS['climate_file'] = get_demo_file('histalp_merged_hef.nc')
cfg.PARAMS['border'] = 40
hef_file = get_demo_file('Hintereisferner.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=testdir, reset=True)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
fig, ax = plt.subplots()
graphics.plot_centerlines(gdir, ax=ax)
fig.tight_layout()
return fig
def test_nodivide_corrected():
# test directory
testdir = os.path.join(cfg.PATHS['test_dir'], 'tmp_nodiv')
if not os.path.exists(testdir):
os.makedirs(testdir)
# Init
cfg.initialize()
cfg.set_divides_db()
cfg.PATHS['dem_file'] = get_demo_file('hef_srtm.tif')
cfg.PATHS['climate_file'] = get_demo_file('histalp_merged_hef.nc')
cfg.PARAMS['border'] = 40
hef_file = get_demo_file('Hintereisferner_RGI5.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=testdir, reset=True)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_intersections(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
fig, ax = plt.subplots()
graphics.plot_catchment_width(gdir, ax=ax, corrected=True,
add_intersects=True, add_touches=True)
fig.tight_layout()
shutil.rmtree(testdir)
return fig
def test_mu_candidates(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdirs = []
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
gdirs.append(gdir)
climate.process_histalp_nonparallel(gdirs)
climate.mu_candidates(gdir, div_id=0)
se = gdir.read_pickle("mu_candidates")[2.5]
self.assertTrue(se.index[0] == 1802)
self.assertTrue(se.index[-1] == 2003)
df = pd.DataFrame()
df["mu"] = se
# Check that the moovin average of temp is negatively correlated
# with the mus
with netCDF4.Dataset(get_demo_file("histalp_merged_hef.nc")) as nc_r:
ref_t = nc_r.variables["temp"][:, 1, 1]
ref_t = np.mean(ref_t.reshape((len(df), 12)), 1)
ma = np.convolve(ref_t, np.ones(31) / float(31), "same")
df["temp"] = ma
df = df.dropna()
self.assertTrue(np.corrcoef(df["mu"], df["temp"])[0, 1] < -0.75)
def test_mb_climate(self):
hef_file = get_demo_file('Hintereisferner.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdirs = []
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gdirs.append(gdir)
climate.distribute_climate_data(gdirs)
with netCDF4.Dataset(get_demo_file('histalp_merged_hef.nc')) as nc_r:
ref_h = nc_r.variables['hgt'][1, 1]
ref_p = nc_r.variables['prcp'][:, 1, 1]
ref_p *= cfg.PARAMS['prcp_scaling_factor']
ref_t = nc_r.variables['temp'][:, 1, 1]
ref_t = np.where(ref_t < 0, 0, ref_t)
hgts = np.array([ref_h, ref_h, -8000, 8000])
time, temp, prcp = climate.mb_climate_on_height(gdir, hgts)
ref_nt = 202*12
self.assertTrue(len(time) == ref_nt)
self.assertTrue(temp.shape == (4, ref_nt))
self.assertTrue(prcp.shape == (4, ref_nt))
np.testing.assert_allclose(temp[0, :], ref_t)
np.testing.assert_allclose(temp[0, :], temp[1, :])
np.testing.assert_allclose(prcp[0, :], prcp[1, :])
np.testing.assert_allclose(prcp[3, :], ref_p)
np.testing.assert_allclose(prcp[2, :], ref_p*0)
np.testing.assert_allclose(temp[3, :], ref_p*0)
yr = [1802, 1802]
time, temp, prcp = climate.mb_climate_on_height(gdir, hgts,
year_range=yr)
ref_nt = 1*12
self.assertTrue(len(time) == ref_nt)
self.assertTrue(temp.shape == (4, ref_nt))
self.assertTrue(prcp.shape == (4, ref_nt))
np.testing.assert_allclose(temp[0, :], ref_t[0:12])
np.testing.assert_allclose(temp[0, :], temp[1, :])
np.testing.assert_allclose(prcp[0, :], prcp[1, :])
np.testing.assert_allclose(prcp[3, :], ref_p[0:12])
np.testing.assert_allclose(prcp[2, :], ref_p[0:12]*0)
np.testing.assert_allclose(temp[3, :], ref_p[0:12]*0)
yr = [1803, 1804]
time, temp, prcp = climate.mb_climate_on_height(gdir, hgts,
year_range=yr)
ref_nt = 2*12
self.assertTrue(len(time) == ref_nt)
self.assertTrue(temp.shape == (4, ref_nt))
self.assertTrue(prcp.shape == (4, ref_nt))
np.testing.assert_allclose(temp[0, :], ref_t[12:36])
np.testing.assert_allclose(temp[0, :], temp[1, :])
np.testing.assert_allclose(prcp[0, :], prcp[1, :])
np.testing.assert_allclose(prcp[3, :], ref_p[12:36])
np.testing.assert_allclose(prcp[2, :], ref_p[12:36]*0)
np.testing.assert_allclose(temp[3, :], ref_p[12:36]*0)
def test_glacierdir(self):
hef_file = get_demo_file('Hintereisferner.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
# this should simply run
mygdir = oggm.GlacierDirectory(entity.RGIID, base_dir=self.testdir)
def test_glacierdir(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
# this should simply run
mygdir = oggm.GlacierDirectory(entity.RGIID, base_dir=self.testdir)
def test_distribute(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
climate.process_histalp_nonparallel([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, prcp_fac = climate.t_star_from_refmb(gdir, mbdf["ANNUAL_BALANCE"])
t_star = t_star[-1]
bias = bias[-1]
climate.local_mustar_apparent_mb(gdir, tstar=t_star, bias=bias, prcp_fac=prcp_fac)
# OK. Values from Fischer and Kuhn 2013
# Area: 8.55
# meanH = 67+-7
# Volume = 0.573+-0.063
# maxH = 242+-13
inversion.prepare_for_inversion(gdir)
ref_v = 0.573 * 1e9
def to_optimize(x):
glen_a = cfg.A * x[0]
fs = cfg.FS * x[1]
v, _ = inversion.invert_parabolic_bed(gdir, fs=fs, glen_a=glen_a)
return (v - ref_v) ** 2
import scipy.optimize as optimization
out = optimization.minimize(to_optimize, [1, 1], bounds=((0.01, 10), (0.01, 10)), tol=1e-1)["x"]
glen_a = cfg.A * out[0]
fs = cfg.FS * out[1]
v, _ = inversion.invert_parabolic_bed(gdir, fs=fs, glen_a=glen_a, write=True)
np.testing.assert_allclose(ref_v, v)
inversion.distribute_thickness(gdir, how="per_altitude", add_nc_name=True)
inversion.distribute_thickness(gdir, how="per_interpolation", add_slope=False, add_nc_name=True)
grids_file = gdir.get_filepath("gridded_data")
with netCDF4.Dataset(grids_file) as nc:
t1 = nc.variables["thickness_per_altitude"][:]
t2 = nc.variables["thickness_per_interpolation"][:]
np.testing.assert_allclose(np.sum(t1), np.sum(t2))
if not HAS_NEW_GDAL:
np.testing.assert_allclose(np.max(t1), np.max(t2), atol=30)
def test_define_region(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
tdf = gpd.GeoDataFrame.from_file(gdir.get_filepath("outlines"))
myarea = tdf.geometry.area * 10 ** -6
np.testing.assert_allclose(myarea, np.float(tdf["AREA"]), rtol=1e-2)
def test_downstream(self):
hef_file = get_demo_file('Hintereisferner.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
centerlines.compute_downstream_lines(gdir)
def test_define_region(self):
hef_file = get_demo_file('Hintereisferner.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
tdf = gpd.GeoDataFrame.from_file(gdir.get_filepath('outlines'))
myarea = tdf.geometry.area * 10**-6
np.testing.assert_allclose(myarea, np.float(tdf['AREA']), rtol=1e-2)
def test_downstream(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
centerlines.compute_downstream_lines(gdir)
def test_coxe():
testdir = os.path.join(cfg.PATHS['test_dir'], 'tmp_coxe')
utils.mkdir(testdir)
# Init
cfg.initialize()
cfg.PATHS['dem_file'] = get_demo_file('dem_RGI50-01.10299.tif')
cfg.PARAMS['border'] = 40
cfg.PARAMS['use_multiple_flowlines'] = False
hef_file = get_demo_file('rgi_RGI50-01.10299.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=testdir, reset=True)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
centerlines.compute_downstream_lines(gdir)
geometry.initialize_flowlines(gdir)
# 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')
p = gdir.read_pickle('linear_mb_params')
mb_mod = massbalance.LinearMassBalanceModel(ela_h=p['ela_h'],
grad=p['grad'])
mb_mod.temp_bias = -0.3
model = flowline.FluxBasedModel(fls,
mb_model=mb_mod,
y0=0,
is_tidewater=True)
# run
model.run_until(200)
assert model.calving_m3_since_y0 > 0
fig, ax = plt.subplots()
graphics.plot_modeloutput_map(gdir, ax=ax, model=model)
fig.tight_layout()
return fig
def test_log(self):
hef_file = get_demo_file('Hintereisferner.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
# Make it large to raise an error
cfg.PARAMS['border'] = 250
cfg.CONTINUE_ON_ERROR = True
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
def test_glacierdir(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
# this should simply run
mygdir = oggm.GlacierDirectory(entity.RGIID, base_dir=self.testdir)
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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
centerlines.compute_downstream_lines(gdir)
def test_geom_width(self):
hef_file = get_demo_file('Hintereisferner.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
centerlines.compute_downstream_lines(gdir)
def test_log(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
# Make it large to raise an error
cfg.PARAMS["border"] = 250
cfg.CONTINUE_ON_ERROR = True
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
def test_geom_width(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
def test_coxe():
testdir = os.path.join(cfg.PATHS['test_dir'], 'tmp_coxe')
utils.mkdir(testdir)
# Init
cfg.initialize()
cfg.PATHS['dem_file'] = get_demo_file('dem_RGI50-01.10299.tif')
cfg.PARAMS['border'] = 40
cfg.PARAMS['use_multiple_flowlines'] = False
hef_file = get_demo_file('rgi_RGI50-01.10299.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=testdir, reset=True)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
centerlines.compute_downstream_lines(gdir)
geometry.initialize_flowlines(gdir)
# 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')
p = gdir.read_pickle('linear_mb_params')
mb_mod = massbalance.LinearMassBalanceModel(ela_h=p['ela_h'],
grad=p['grad'])
mb_mod.temp_bias = -0.3
model = flowline.FluxBasedModel(fls, mb_model=mb_mod, y0=0,
is_tidewater=True)
# run
model.run_until(200)
assert model.calving_m3_since_y0 > 0
fig, ax = plt.subplots()
graphics.plot_modeloutput_map(gdir, ax=ax, model=model)
fig.tight_layout()
return fig
def test_define_region(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
tdf = gpd.GeoDataFrame.from_file(gdir.get_filepath('outlines'))
myarea = tdf.geometry.area * 10**-6
np.testing.assert_allclose(myarea, np.float(tdf['AREA']), rtol=1e-2)
def test_define_region(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
tdf = gpd.GeoDataFrame.from_file(gdir.get_filepath('outlines'))
myarea = tdf.geometry.area * 10**-6
np.testing.assert_allclose(myarea, np.float(tdf['AREA']), rtol=1e-2)
def test_glacier_masks(self):
# The GIS was double checked externally with IDL.
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
with netCDF4.Dataset(gdir.get_filepath("gridded_data")) as nc:
area = np.sum(nc.variables["glacier_mask"][:] * gdir.grid.dx ** 2) * 10 ** -6
np.testing.assert_allclose(area, gdir.rgi_area_km2, rtol=1e-1)
def test_log(self):
hef_file = get_demo_file('Hintereisferner.shp')
rgidf = gpd.GeoDataFrame.from_file(hef_file)
# Make it large to raise an error
cfg.PARAMS['border'] = 250
cfg.CONTINUE_ON_ERROR = True
# loop because for some reason indexing wont work
for index, entity in rgidf.iterrows():
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
def test_glacier_masks(self):
# The GIS was double checked externally with IDL.
hef_file = get_demo_file('Hintereisferner.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
with netCDF4.Dataset(gdir.get_filepath('gridded_data')) as nc:
area = np.sum(
nc.variables['glacier_mask'][:] * gdir.grid.dx**2) * 10**-6
np.testing.assert_allclose(area, gdir.rgi_area_km2, rtol=1e-1)
def test_log(self):
hef_file = get_demo_file('Hintereisferner.shp')
rgidf = gpd.GeoDataFrame.from_file(hef_file)
# Make it large to raise an error
cfg.PARAMS['border'] = 250
cfg.CONTINUE_ON_ERROR = True
# loop because for some reason indexing wont work
for index, entity in rgidf.iterrows():
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
def test_geom_width(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
def test_width(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
area = 0.
otherarea = 0.
hgt = []
harea = []
for i in gdir.divide_ids:
cls = gdir.read_pickle('inversion_flowlines', div_id=i)
for cl in cls:
harea.extend(list(cl.widths * cl.dx))
hgt.extend(list(cl.surface_h))
area += np.sum(cl.widths * cl.dx)
nc = netCDF4.Dataset(gdir.get_filepath('gridded_data', div_id=i))
otherarea += np.sum(nc.variables['glacier_mask'][:])
nc.close()
nc = netCDF4.Dataset(gdir.get_filepath('gridded_data', div_id=0))
mask = nc.variables['glacier_mask'][:]
topo = nc.variables['topo_smoothed'][:]
nc.close()
rhgt = topo[np.where(mask)][:]
tdf = gpd.GeoDataFrame.from_file(gdir.get_filepath('outlines'))
np.testing.assert_allclose(area, otherarea, rtol=0.1)
area *= (gdir.grid.dx)**2
otherarea *= (gdir.grid.dx)**2
np.testing.assert_allclose(area * 10**-6,
np.float(tdf['AREA']),
rtol=1e-4)
# Check for area distrib
bins = np.arange(utils.nicenumber(np.min(hgt), 50, lower=True),
utils.nicenumber(np.max(hgt), 50) + 1, 50.)
h1, b = np.histogram(hgt, weights=harea, density=True, bins=bins)
h2, b = np.histogram(rhgt, density=True, bins=bins)
self.assertTrue(utils.rmsd(h1 * 100 * 50, h2 * 100 * 50) < 1)
def test_geom_width(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
def test_width(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
area = 0.
otherarea = 0.
hgt = []
harea = []
for i in gdir.divide_ids:
cls = gdir.read_pickle('inversion_flowlines', div_id=i)
for cl in cls:
harea.extend(list(cl.widths * cl.dx))
hgt.extend(list(cl.surface_h))
area += np.sum(cl.widths * cl.dx)
nc = netCDF4.Dataset(gdir.get_filepath('gridded_data', div_id=i))
otherarea += np.sum(nc.variables['glacier_mask'][:])
nc.close()
nc = netCDF4.Dataset(gdir.get_filepath('gridded_data', div_id=0))
mask = nc.variables['glacier_mask'][:]
topo = nc.variables['topo_smoothed'][:]
nc.close()
rhgt = topo[np.where(mask)][:]
tdf = gpd.GeoDataFrame.from_file(gdir.get_filepath('outlines'))
np.testing.assert_allclose(area, otherarea, rtol=0.1)
area *= (gdir.grid.dx) ** 2
otherarea *= (gdir.grid.dx) ** 2
np.testing.assert_allclose(area * 10**-6, np.float(tdf['AREA']), rtol=1e-4)
# Check for area distrib
bins = np.arange(utils.nicenumber(np.min(hgt), 50, lower=True),
utils.nicenumber(np.max(hgt), 50)+1,
50.)
h1, b = np.histogram(hgt, weights=harea, density=True, bins=bins)
h2, b = np.histogram(rhgt, density=True, bins=bins)
self.assertTrue(utils.rmsd(h1*100*50, h2*100*50) < 1)
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_glacier_masks(self):
# The GIS was double checked externally with IDL.
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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
nc = netCDF4.Dataset(gdir.get_filepath('gridded_data'))
area = np.sum(nc.variables['glacier_mask'][:] * gdir.grid.dx**2) * 10**-6
np.testing.assert_allclose(area, gdir.rgi_area_km2, rtol=1e-1)
nc.close()
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_glacier_masks(self):
# The GIS was double checked externally with IDL.
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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
nc = netCDF4.Dataset(gdir.get_filepath('gridded_data'))
area = np.sum(
nc.variables['glacier_mask'][:] * gdir.grid.dx**2) * 10**-6
np.testing.assert_allclose(area, gdir.rgi_area_km2, rtol=1e-1)
nc.close()
def test_width(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
area = 0.0
otherarea = 0.0
hgt = []
harea = []
for i in gdir.divide_ids:
cls = gdir.read_pickle("inversion_flowlines", div_id=i)
for cl in cls:
harea.extend(list(cl.widths * cl.dx))
hgt.extend(list(cl.surface_h))
area += np.sum(cl.widths * cl.dx)
with netCDF4.Dataset(gdir.get_filepath("gridded_data", div_id=i)) as nc:
otherarea += np.sum(nc.variables["glacier_mask"][:])
with netCDF4.Dataset(gdir.get_filepath("gridded_data", div_id=0)) as nc:
mask = nc.variables["glacier_mask"][:]
topo = nc.variables["topo_smoothed"][:]
rhgt = topo[np.where(mask)][:]
tdf = gpd.GeoDataFrame.from_file(gdir.get_filepath("outlines"))
np.testing.assert_allclose(area, otherarea, rtol=0.1)
area *= (gdir.grid.dx) ** 2
otherarea *= (gdir.grid.dx) ** 2
np.testing.assert_allclose(area * 10 ** -6, np.float(tdf["AREA"]), rtol=1e-4)
# Check for area distrib
bins = np.arange(utils.nicenumber(np.min(hgt), 50, lower=True), utils.nicenumber(np.max(hgt), 50) + 1, 50.0)
h1, b = np.histogram(hgt, weights=harea, density=True, bins=bins)
h2, b = np.histogram(rhgt, density=True, bins=bins)
self.assertTrue(utils.rmsd(h1 * 100 * 50, h2 * 100 * 50) < 1)
def test_centerlines(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
for div_id in gdir.divide_ids:
cls = gdir.read_pickle("centerlines", div_id=div_id)
for cl in cls:
for j, ip, ob in zip(cl.inflow_indices, cl.inflow_points, cl.inflows):
self.assertTrue(cl.line.coords[j] == ip.coords[0])
self.assertTrue(ob.flows_to_point.coords[0] == ip.coords[0])
self.assertTrue(cl.line.coords[ob.flows_to_indice] == ip.coords[0])
lens = [len(gdir.read_pickle("centerlines", div_id=i)) for i in [1, 2, 3]]
self.assertTrue(sorted(lens) == [1, 1, 2])
def test_distribute_climate_cru(self):
hef_file = get_demo_file('Hintereisferner.shp')
rgidf = gpd.GeoDataFrame.from_file(hef_file)
gdirs = []
# loop because for some reason indexing wont work
for index, entity in rgidf.iterrows():
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gdirs.append(gdir)
for index, entity in rgidf.iterrows():
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir_cru)
gis.define_glacier_region(gdir, entity=entity)
gdirs.append(gdir)
climate.distribute_climate_data([gdirs[0]])
cru_dir = get_demo_file('cru_ts3.23.1901.2014.tmp.dat.nc')
cru_dir = os.path.dirname(cru_dir)
cfg.PATHS['climate_file'] = '~'
cfg.PATHS['cru_dir'] = cru_dir
climate.distribute_climate_data([gdirs[1]])
cfg.PATHS['cru_dir'] = '~'
cfg.PATHS['climate_file'] = get_demo_file('histalp_merged_hef.nc')
gdh = gdirs[0]
gdc = gdirs[1]
with xr.open_dataset(os.path.join(gdh.dir,
'climate_monthly.nc')) as nc_h:
with xr.open_dataset(os.path.join(gdc.dir,
'climate_monthly.nc')) as nc_c:
# put on the same altitude
# (using default gradient because better)
temp_cor = nc_c.temp - 0.0065 * (nc_h.ref_hgt - nc_c.ref_hgt)
totest = temp_cor - nc_h.temp
self.assertTrue(totest.mean() < 0.5)
# precip
totest = nc_c.prcp - nc_h.prcp
self.assertTrue(totest.mean() < 100)
def test_find_tstars(self):
hef_file = get_demo_file('Hintereisferner.shp')
rgidf = gpd.GeoDataFrame.from_file(hef_file)
# loop because for some reason indexing wont work
gdirs = []
for index, entity in rgidf.iterrows():
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
gdirs.append(gdir)
climate.distribute_climate_data(gdirs)
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_stars, bias = climate.t_star_from_refmb(gdir, mbdf['ANNUAL_BALANCE'])
y, t, p = climate.mb_yearly_climate_on_glacier(gdir, div_id=0)
# which years to look at
selind = np.searchsorted(y, mbdf.index)
t = t[selind]
p = p[selind]
mu_yr_clim = gdir.read_pickle('mu_candidates', div_id=0)
for t_s, rmd in zip(t_stars, bias):
mb_per_mu = p - mu_yr_clim.loc[t_s] * t
md = utils.md(mbdf['ANNUAL_BALANCE'], mb_per_mu)
np.testing.assert_allclose(md, rmd)
self.assertTrue(np.abs(md/np.mean(mbdf['ANNUAL_BALANCE'])) < 0.1)
r = utils.corrcoef(mbdf['ANNUAL_BALANCE'], mb_per_mu)
self.assertTrue(r > 0.8)
def test_find_tstars(self):
hef_file = get_demo_file('Hintereisferner.shp')
rgidf = gpd.GeoDataFrame.from_file(hef_file)
# loop because for some reason indexing wont work
gdirs = []
for index, entity in rgidf.iterrows():
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
gdirs.append(gdir)
climate.distribute_climate_data(gdirs)
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_stars, bias = climate.t_star_from_refmb(gdir, mbdf['ANNUAL_BALANCE'])
y, t, p = climate.mb_yearly_climate_on_glacier(gdir, div_id=0)
# which years to look at
selind = np.searchsorted(y, mbdf.index)
t = t[selind]
p = p[selind]
mu_yr_clim = gdir.read_pickle('mu_candidates', div_id=0)
for t_s, rmd in zip(t_stars, bias):
mb_per_mu = p - mu_yr_clim.loc[t_s] * t
md = utils.md(mbdf['ANNUAL_BALANCE'], mb_per_mu)
np.testing.assert_allclose(md, rmd)
self.assertTrue(np.abs(md / np.mean(mbdf['ANNUAL_BALANCE'])) < 0.1)
r = utils.corrcoef(mbdf['ANNUAL_BALANCE'], mb_per_mu)
self.assertTrue(r > 0.8)
def test_distribute_climate_cru(self):
hef_file = get_demo_file("Hintereisferner.shp")
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdirs = []
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gdirs.append(gdir)
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir_cru)
gis.define_glacier_region(gdir, entity=entity)
gdirs.append(gdir)
climate.process_histalp_nonparallel([gdirs[0]])
cru_dir = get_demo_file("cru_ts3.23.1901.2014.tmp.dat.nc")
cru_dir = os.path.dirname(cru_dir)
cfg.PATHS["climate_file"] = "~"
cfg.PATHS["cru_dir"] = cru_dir
climate.process_cru_data(gdirs[1])
cfg.PATHS["cru_dir"] = "~"
cfg.PATHS["climate_file"] = get_demo_file("histalp_merged_hef.nc")
ci = gdir.read_pickle("climate_info")
self.assertEqual(ci["hydro_yr_0"], 1902)
self.assertEqual(ci["hydro_yr_1"], 2014)
gdh = gdirs[0]
gdc = gdirs[1]
with xr.open_dataset(os.path.join(gdh.dir, "climate_monthly.nc")) as nc_h:
with xr.open_dataset(os.path.join(gdc.dir, "climate_monthly.nc")) as nc_c:
# put on the same altitude
# (using default gradient because better)
temp_cor = nc_c.temp - 0.0065 * (nc_h.ref_hgt - nc_c.ref_hgt)
totest = temp_cor - nc_h.temp
self.assertTrue(totest.mean() < 0.5)
# precip
totest = nc_c.prcp - nc_h.prcp
self.assertTrue(totest.mean() < 100)
def test_nodivide_corrected():
# test directory
testdir = os.path.join(cfg.PATHS['test_dir'], 'tmp_nodiv')
if not os.path.exists(testdir):
os.makedirs(testdir)
# Init
cfg.initialize()
cfg.set_divides_db()
cfg.PATHS['dem_file'] = get_demo_file('hef_srtm.tif')
cfg.PATHS['climate_file'] = get_demo_file('histalp_merged_hef.nc')
cfg.PARAMS['border'] = 40
hef_file = get_demo_file('Hintereisferner_RGI5.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=testdir, reset=True)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
geometry.initialize_flowlines(gdir)
geometry.catchment_area(gdir)
geometry.catchment_intersections(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
fig, ax = plt.subplots()
graphics.plot_catchment_width(gdir,
ax=ax,
corrected=True,
add_intersects=True,
add_touches=True)
fig.tight_layout()
shutil.rmtree(testdir)
return fig
def test_ice_cap():
testdir = os.path.join(cfg.PATHS['test_dir'], 'tmp_icecap')
utils.mkdir(testdir)
cfg.initialize()
cfg.PATHS['dem_file'] = get_demo_file('dem_RGI50-05.08389.tif')
cfg.PARAMS['border'] = 20
cfg.set_divides_db(get_demo_file('divides_RGI50-05.08389.shp'))
hef_file = get_demo_file('RGI50-05.08389.shp')
entity = gpd.GeoDataFrame.from_file(hef_file).iloc[0]
gdir = oggm.GlacierDirectory(entity, base_dir=testdir, reset=True)
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 five groups
lines = gdir.read_pickle('downstream_lines', div_id=0)
assert len(np.unique(lines.group)) == 5
# This just checks that it works
geometry.catchment_area(gdir)
geometry.catchment_intersections(gdir)
geometry.catchment_width_geom(gdir)
geometry.catchment_width_correction(gdir)
fig, ax = plt.subplots()
graphics.plot_catchment_width(gdir,
ax=ax,
add_intersects=True,
add_touches=True)
fig.tight_layout()
return fig
def test_invert_hef_nofs(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(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'])
t_star = t_star[-1]
bias = bias[-1]
climate.local_mustar_apparent_mb(gdir, tstar=t_star, bias=bias)
# OK. Values from Fischer and Kuhn 2013
# Area: 8.55
# meanH = 67+-7
# Volume = 0.573+-0.063
# maxH = 242+-13
inversion.prepare_for_inversion(gdir)
ref_v = 0.573 * 1e9
def to_optimize(x):
glen_a = cfg.A * x[0]
fs = 0.
v, _ = inversion.invert_parabolic_bed(gdir, fs=fs, glen_a=glen_a)
return (v - ref_v)**2
import scipy.optimize as optimization
out = optimization.minimize(to_optimize, [1],
bounds=((0.00001, 100000), ),
tol=1e-4)['x']
self.assertTrue(out[0] > 0.1)
self.assertTrue(out[0] < 10)
glen_a = cfg.A * out[0]
fs = 0.
v, _ = inversion.invert_parabolic_bed(gdir,
fs=fs,
glen_a=glen_a,
write=True)
np.testing.assert_allclose(ref_v, v)
lens = [
len(gdir.read_pickle('centerlines', div_id=i)) for i in [1, 2, 3]
]
pid = np.argmax(lens) + 1
cls = gdir.read_pickle('inversion_output', div_id=pid)
fls = gdir.read_pickle('inversion_flowlines', div_id=pid)
maxs = 0.
for cl, fl in zip(cls, fls):
thick = cl['thick']
_max = np.max(thick)
if _max > maxs:
maxs = _max
atol = 30 if HAS_NEW_GDAL else 10
np.testing.assert_allclose(242, maxs, atol=atol)
# check that its not tooo sensitive to the dx
cfg.PARAMS['flowline_dx'] = 1.
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'])
t_star = t_star[-1]
bias = bias[-1]
climate.local_mustar_apparent_mb(gdir, tstar=t_star, bias=bias)
inversion.prepare_for_inversion(gdir)
v, _ = inversion.invert_parabolic_bed(gdir,
fs=fs,
glen_a=glen_a,
write=True)
np.testing.assert_allclose(ref_v, v, rtol=0.02)
cls = gdir.read_pickle('inversion_output', div_id=pid)
maxs = 0.
for cl in cls:
thick = cl['thick']
_max = np.max(thick)
if _max > maxs:
maxs = _max
np.testing.assert_allclose(242, maxs, atol=atol)
def test_invert_hef(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(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'])
t_star = t_star[-1]
bias = bias[-1]
climate.local_mustar_apparent_mb(gdir, tstar=t_star, bias=bias)
# OK. Values from Fischer and Kuhn 2013
# Area: 8.55
# meanH = 67+-7
# Volume = 0.573+-0.063
# maxH = 242+-13
inversion.prepare_for_inversion(gdir)
lens = [
len(gdir.read_pickle('centerlines', div_id=i)) for i in [1, 2, 3]
]
pid = np.argmax(lens) + 1
# Check how many clips:
cls = gdir.read_pickle('inversion_input', div_id=pid)
nabove = 0
maxs = 0.
npoints = 0.
for cl in cls:
# Clip slope to avoid negative and small slopes
slope = cl['slope_angle']
nm = np.where(slope < np.deg2rad(2.))
nabove += len(nm[0])
npoints += len(slope)
_max = np.max(slope)
if _max > maxs:
maxs = _max
self.assertTrue(nabove == 0)
self.assertTrue(np.rad2deg(maxs) < 40.)
ref_v = 0.573 * 1e9
def to_optimize(x):
glen_a = cfg.A * x[0]
fs = cfg.FS * x[1]
v, _ = inversion.invert_parabolic_bed(gdir, fs=fs, glen_a=glen_a)
return (v - ref_v)**2
import scipy.optimize as optimization
out = optimization.minimize(to_optimize, [1, 1],
bounds=((0.01, 10), (0.01, 10)),
tol=1e-4)['x']
self.assertTrue(out[0] > 0.1)
self.assertTrue(out[1] > 0.1)
self.assertTrue(out[0] < 1.1)
self.assertTrue(out[1] < 1.1)
glen_a = cfg.A * out[0]
fs = cfg.FS * out[1]
v, _ = inversion.invert_parabolic_bed(gdir,
fs=fs,
glen_a=glen_a,
write=True)
np.testing.assert_allclose(ref_v, v)
lens = [
len(gdir.read_pickle('centerlines', div_id=i)) for i in [1, 2, 3]
]
pid = np.argmax(lens) + 1
cls = gdir.read_pickle('inversion_output', div_id=pid)
fls = gdir.read_pickle('inversion_flowlines', div_id=pid)
maxs = 0.
for cl, fl in zip(cls, fls):
thick = cl['thick']
_max = np.max(thick)
if _max > maxs:
maxs = _max
np.testing.assert_allclose(242, maxs, atol=21)
def test_local_mustar(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 = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(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'])
t_star = t_star[-1]
bias = bias[-1]
climate.local_mustar_apparent_mb(gdir, tstar=t_star, bias=bias)
df = pd.read_csv(gdir.get_filepath('local_mustar', div_id=0))
mu_ref = gdir.read_pickle('mu_candidates', div_id=0).loc[t_star]
np.testing.assert_allclose(mu_ref, df['mu_star'][0], atol=1e-3)
# Check for apparent mb to be zeros
for i in [0] + list(gdir.divide_ids):
fls = gdir.read_pickle('inversion_flowlines', div_id=i)
tmb = 0.
for fl in fls:
self.assertTrue(fl.apparent_mb.shape == fl.widths.shape)
tmb += np.sum(fl.apparent_mb * fl.widths)
np.testing.assert_allclose(tmb, 0., atol=0.01)
if i == 0: continue
np.testing.assert_allclose(fls[-1].flux[-1], 0., atol=0.01)
# ------ Look for gradient
# which years to look at
fls = gdir.read_pickle('inversion_flowlines', div_id=0)
mb_on_h = np.array([])
h = np.array([])
for fl in fls:
y, t, p = climate.mb_yearly_climate_on_height(gdir, fl.surface_h)
selind = np.searchsorted(y, mbdf.index)
t = np.mean(t[:, selind], axis=1)
p = np.mean(p[:, selind], axis=1)
mb_on_h = np.append(mb_on_h, p - mu_ref * t)
h = np.append(h, fl.surface_h)
dfg = pd.read_csv(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(h < 3100)
from scipy.stats import linregress
slope_obs, _, _, _, _ = linregress(dfg.index, dfg.values)
slope_our, _, _, _, _ = linregress(h[pok], mb_on_h[pok])
np.testing.assert_allclose(slope_obs, slope_our, rtol=0.1)
def test_yearly_mb_climate(self):
hef_file = get_demo_file('Hintereisferner.shp')
rgidf = gpd.GeoDataFrame.from_file(hef_file)
# loop because for some reason indexing wont work
gdirs = []
for index, entity in rgidf.iterrows():
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gdirs.append(gdir)
climate.distribute_climate_data(gdirs)
nc_r = netCDF4.Dataset(get_demo_file('histalp_merged_hef.nc'))
ref_h = nc_r.variables['hgt'][1, 1]
ref_p = nc_r.variables['prcp'][:, 1, 1]
ref_p *= cfg.PARAMS['prcp_scaling_factor']
ref_t = nc_r.variables['temp'][:, 1, 1]
ref_t = np.where(ref_t < 0, 0, ref_t)
nc_r.close()
# NORMAL --------------------------------------------------------------
hgts = np.array([ref_h, ref_h, -8000, 8000])
years, temp, prcp = climate.mb_yearly_climate_on_height(gdir, hgts)
ref_nt = 202
self.assertTrue(len(years) == ref_nt)
self.assertTrue(temp.shape == (4, ref_nt))
self.assertTrue(prcp.shape == (4, ref_nt))
yr = [1802, 1802]
years, temp, prcp = climate.mb_yearly_climate_on_height(gdir,
hgts,
year_range=yr)
ref_nt = 1
self.assertTrue(len(years) == ref_nt)
self.assertTrue(years == 1802)
self.assertTrue(temp.shape == (4, ref_nt))
self.assertTrue(prcp.shape == (4, ref_nt))
np.testing.assert_allclose(temp[0, :], np.sum(ref_t[0:12]))
np.testing.assert_allclose(temp[0, :], temp[1, :])
np.testing.assert_allclose(prcp[0, :], prcp[1, :])
np.testing.assert_allclose(prcp[3, :], np.sum(ref_p[0:12]))
np.testing.assert_allclose(prcp[2, :], np.sum(ref_p[0:12]) * 0)
np.testing.assert_allclose(temp[3, :], np.sum(ref_p[0:12]) * 0)
yr = [1803, 1804]
years, temp, prcp = climate.mb_yearly_climate_on_height(gdir,
hgts,
year_range=yr)
ref_nt = 2
self.assertTrue(len(years) == ref_nt)
np.testing.assert_allclose(years, yr)
self.assertTrue(temp.shape == (4, ref_nt))
self.assertTrue(prcp.shape == (4, ref_nt))
np.testing.assert_allclose(prcp[2, :], [0, 0])
np.testing.assert_allclose(temp[3, :], [0, 0])
# FLATTEN -------------------------------------------------------------
hgts = np.array([ref_h, ref_h, -8000, 8000])
years, temp, prcp = climate.mb_yearly_climate_on_height(gdir,
hgts,
flatten=True)
ref_nt = 202
self.assertTrue(len(years) == ref_nt)
self.assertTrue(temp.shape == (ref_nt, ))
self.assertTrue(prcp.shape == (ref_nt, ))
yr = [1802, 1802]
hgts = np.array([ref_h])
years, temp, prcp = climate.mb_yearly_climate_on_height(gdir,
hgts,
year_range=yr,
flatten=True)
ref_nt = 1
self.assertTrue(len(years) == ref_nt)
self.assertTrue(years == 1802)
self.assertTrue(temp.shape == (ref_nt, ))
self.assertTrue(prcp.shape == (ref_nt, ))
np.testing.assert_allclose(temp[:], np.sum(ref_t[0:12]))
yr = [1802, 1802]
hgts = np.array([8000])
years, temp, prcp = climate.mb_yearly_climate_on_height(gdir,
hgts,
year_range=yr,
flatten=True)
np.testing.assert_allclose(prcp[:], np.sum(ref_p[0:12]))
def test_baltoro_centerlines(self):
cfg.PARAMS['border'] = 2
cfg.PATHS['dem_file'] = get_demo_file('baltoro_srtm_clip.tif')
b_file = get_demo_file('baltoro_wgs84.shp')
rgidf = gpd.GeoDataFrame.from_file(b_file)
kienholz_file = get_demo_file('centerlines_baltoro_wgs84.shp')
kdf = gpd.read_file(kienholz_file)
# loop because for some reason indexing wont work
for index, entity in rgidf.iterrows():
# add fake attribs
entity.O1REGION = 0
entity.BGNDATE = 0
entity.NAME = 'Baltoro'
gdir = oggm.GlacierDirectory(entity, base_dir=self.testdir)
gis.define_glacier_region(gdir, entity=entity)
gis.glacier_masks(gdir)
centerlines.compute_centerlines(gdir)
my_mask = np.zeros((gdir.grid.ny, gdir.grid.nx), dtype=np.uint8)
cls = gdir.read_pickle('centerlines', div_id=1)
for cl in cls:
x, y = tuple2int(cl.line.xy)
my_mask[y, x] = 1
# Transform
kien_mask = np.zeros((gdir.grid.ny, gdir.grid.nx), dtype=np.uint8)
from shapely.ops import transform
for index, entity in kdf.iterrows():
def proj(lon, lat):
return salem.transform_proj(salem.wgs84, gdir.grid.proj, lon,
lat)
kgm = transform(proj, entity.geometry)
# Interpolate shape to a regular path
e_line = []
for distance in np.arange(0.0, kgm.length, gdir.grid.dx):
e_line.append(*kgm.interpolate(distance).coords)
kgm = shpg.LineString(e_line)
# Transform geometry into grid coordinates
def proj(x, y):
return gdir.grid.transform(x, y, crs=gdir.grid.proj)
kgm = transform(proj, kgm)
# Rounded nearest pix
project = lambda x, y: (np.rint(x).astype(np.int64), np.rint(y).
astype(np.int64))
kgm = transform(project, kgm)
x, y = tuple2int(kgm.xy)
kien_mask[y, x] = 1
# We test the Heidke Skill score of our predictions
rest = kien_mask + 2 * my_mask
# gr.plot_array(rest)
na = len(np.where(rest == 3)[0])
nb = len(np.where(rest == 2)[0])
nc = len(np.where(rest == 1)[0])
nd = len(np.where(rest == 0)[0])
denom = np.float64((na + nc) * (nd + nc) + (na + nb) * (nd + nb))
hss = np.float64(2.) * ((na * nd) - (nb * nc)) / denom
self.assertTrue(hss > 0.53)