def init_columbia_eb(dir_name, reset=False):
from oggm.core import gis, centerlines
import geopandas as gpd
# test directory
testdir = os.path.join(get_test_dir(), dir_name)
mkdir(testdir, reset=reset)
# Init
cfg.initialize()
cfg.PATHS['working_dir'] = testdir
cfg.PARAMS['use_intersects'] = False
cfg.PATHS['dem_file'] = get_demo_file('dem_Columbia.tif')
cfg.PARAMS['border'] = 10
entity = gpd.read_file(get_demo_file('01_rgi60_Columbia.shp')).iloc[0]
gdir = oggm.GlacierDirectory(entity)
if gdir.has_file('climate_historical'):
return gdir
gis.define_glacier_region(gdir)
gis.simple_glacier_masks(gdir)
centerlines.elevation_band_flowline(gdir)
centerlines.fixed_dx_elevation_band_flowline(gdir)
centerlines.compute_downstream_line(gdir)
tasks.process_dummy_cru_file(gdir, seed=0)
return gdir
def test_add_consensus(self, class_case_dir, monkeypatch):
# Init
cfg.initialize()
cfg.PARAMS['use_intersects'] = False
cfg.PATHS['working_dir'] = class_case_dir
cfg.PATHS['dem_file'] = get_demo_file('hef_srtm.tif')
entity = gpd.read_file(get_demo_file('Hintereisferner_RGI5.shp'))
entity['RGIId'] = 'RGI60-11.00897'
gdir = workflow.init_glacier_directories(entity)[0]
tasks.define_glacier_region(gdir)
tasks.glacier_masks(gdir)
ft = utils.get_demo_file('RGI60-11.00897_thickness.tif')
monkeypatch.setattr(utils, 'file_downloader', lambda x: ft)
bedtopo.add_consensus_thickness(gdir)
# Check with rasterio
cfg.add_to_basenames('consensus', 'consensus.tif')
gis.rasterio_to_gdir(gdir, ft, 'consensus', resampling='bilinear')
with xr.open_dataset(gdir.get_filepath('gridded_data')) as ds:
mine = ds.consensus_ice_thickness
with xr.open_rasterio(gdir.get_filepath('consensus')) as ds:
ref = ds.isel(band=0)
# Check area
my_area = np.sum(np.isfinite(mine.data)) * gdir.grid.dx**2
np.testing.assert_allclose(my_area, gdir.rgi_area_m2, rtol=0.07)
rio_area = np.sum(ref.data > 0) * gdir.grid.dx**2
np.testing.assert_allclose(rio_area, gdir.rgi_area_m2, rtol=0.15)
np.testing.assert_allclose(my_area, rio_area, rtol=0.15)
# They are not same:
# - interpolation not 1to1 same especially at borders
# - we preserve total volume
np.testing.assert_allclose(mine.sum(), ref.sum(), rtol=0.01)
assert utils.rmsd(ref, mine) < 2
# Check vol
cdf = pd.read_hdf(utils.get_demo_file('rgi62_itmix_df.h5'))
ref_vol = cdf.loc[gdir.rgi_id].vol_itmix_m3
my_vol = mine.sum() * gdir.grid.dx**2
np.testing.assert_allclose(my_vol, ref_vol)
# Now check the rest of the workflow
# Check that no error when var not there
vn = 'consensus_ice_thickness'
centerlines.elevation_band_flowline(gdir, bin_variables=[vn, 'foo'])
# Check vol
df = pd.read_csv(gdir.get_filepath('elevation_band_flowline'),
index_col=0)
my_vol = (df[vn] * df['area']).sum()
np.testing.assert_allclose(my_vol, ref_vol)
centerlines.fixed_dx_elevation_band_flowline(gdir,
bin_variables=[vn, 'foo'])
fdf = pd.read_csv(gdir.get_filepath('elevation_band_flowline',
filesuffix='_fixed_dx'),
index_col=0)
# Check vol
my_vol = (fdf[vn] * fdf['area_m2']).sum()
np.testing.assert_allclose(my_vol, ref_vol)
