def test_invert_and_run(self):
from oggm.core.models import flowline, massbalance
glen_a = cfg.A * 2
gdir = utils.GlacierDirectory(self.rgin, base_dir=self.testdir)
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.local_mustar_apparent_mb(gdir, tstar=1975, bias=0.)
inversion.prepare_for_inversion(gdir)
v, a = inversion.invert_parabolic_bed(gdir, glen_a=glen_a)
cfg.PARAMS['bed_shape'] = 'parabolic'
flowline.init_present_time_glacier(gdir)
mb_mod = massbalance.TstarMassBalanceModel(gdir)
fls = gdir.read_pickle('model_flowlines')
model = flowline.FluxBasedModel(fls,
mb_model=mb_mod,
y0=0.,
fs=0,
glen_a=glen_a)
ref_vol = model.volume_m3
model.run_until_equilibrium()
after_vol = model.volume_m3
np.testing.assert_allclose(ref_vol, after_vol, rtol=0.1)
def test_ideal_glacier(self):
# we are making a
glen_a = cfg.A * 1
from oggm.core.models import flowline, massbalance
gdir = utils.GlacierDirectory(self.rgin, base_dir=self.testdir)
fls = self._parabolic_bed()
mbmod = massbalance.ConstantBalanceModel(2800.)
model = flowline.FluxBasedModel(fls, mb_model=mbmod, glen_a=glen_a)
model.run_until_equilibrium()
# from dummy bed
map_dx = 100.
towrite = []
for fl in model.fls:
# Distance between two points
dx = fl.dx * map_dx
# Widths
widths = fl.widths * map_dx
# Heights
hgt = fl.surface_h
# Flux
mb = mbmod.get_mb(hgt) * cfg.SEC_IN_YEAR * cfg.RHO
fl.flux = np.zeros(len(fl.surface_h))
fl.set_apparent_mb(mb)
flux = fl.flux * (map_dx**2) / cfg.SEC_IN_YEAR / cfg.RHO
pok = np.nonzero(widths > 10.)
widths = widths[pok]
hgt = hgt[pok]
flux = flux[pok]
angle = np.arctan(-np.gradient(hgt, dx)) # beware the minus sign
# Clip flux to 0
assert not np.any(flux < -0.1)
# add to output
cl_dic = dict(dx=dx,
flux=flux,
width=widths,
hgt=hgt,
slope_angle=angle,
is_last=True)
towrite.append(cl_dic)
# Write out
gdir.write_pickle(towrite, 'inversion_input', div_id=1)
v, a = inversion.invert_parabolic_bed(gdir, glen_a=glen_a)
v_km3 = v * 1e-9
a_km2 = np.sum(widths * dx) * 1e-6
v_vas = 0.034 * (a_km2**1.375)
np.testing.assert_allclose(v, model.volume_m3, rtol=0.01)
cl = gdir.read_pickle('inversion_output', div_id=1)[0]
assert utils.rmsd(cl['thick'],
model.fls[0].thick[:len(cl['thick'])]) < 10.
def define_g2ti_glacier(path=None, base_dir=None):
fname = os.path.join(path, 'outlines.shp')
ent = gpd.read_file(fname)
rid = ent.RGIId.values[0]
if '5a' in rid:
rid = rid.replace('5a', '60')
ent['RGIId'] = rid
ent['Name'] = '' if ent['Name'][0] == 'None' else ent['Name']
gdir = utils.GlacierDirectory(ent.iloc[0], base_dir=base_dir)
ent.to_file(gdir.get_filepath('outlines'))
proj_out = salem.check_crs(ent.crs)
# Also transform the intersects if necessary
gdf = cfg.PARAMS['intersects_gdf']
if len(gdf) > 0:
gdf = gdf.loc[((gdf.RGIId_1 == gdir.rgi_id) |
(gdf.RGIId_2 == gdir.rgi_id))]
if len(gdf) > 0:
gdf = salem.transform_geopandas(gdf, to_crs=proj_out)
if hasattr(gdf.crs, 'srs'):
# salem uses pyproj
gdf.crs = gdf.crs.srs
gdf.to_file(gdir.get_filepath('intersects'))
else:
# Sanity check
if cfg.PARAMS['use_intersects']:
raise RuntimeError('You seem to have forgotten to set the '
'intersects file for this run. OGGM works '
'better with such a file. If you know what '
'your are doing, set '
"cfg.PARAMS['use_intersects'] = False to "
"suppress this error.")
# Topo
shutil.copy(os.path.join(path, 'dem.tif'), gdir.get_filepath('dem'))
mpath = gdir.get_filepath('dem').replace('dem', 'g2ti_mask')
shutil.copy(os.path.join(path, 'mask.tif'), mpath)
# Grid
ds = salem.GeoTiff(gdir.get_filepath('dem'))
ds.grid.to_json(gdir.get_filepath('glacier_grid'))
gdir.write_pickle(['G2TI'], 'dem_source')
return gdir
def single_flowline_glacier_directory(rgi_id, reset=False, prepro_border=80):
"""Prepare a GlacierDirectory for PyGEM (single flowline to start with)
Parameters
----------
rgi_id : str
the rgi id of the glacier
reset : bool
set to true to delete any pre-existing files. If false (the default),
the directory won't be re-downloaded if already available locally in
order to spare time.
prepro_border : int
the size of the glacier map: 10, 80, 160, 250
Returns
-------
a GlacierDirectory object
"""
if type(rgi_id) != str:
raise ValueError('We expect rgi_id to be a string')
if 'RGI60-' not in rgi_id:
raise ValueError('OGGM currently expects IDs to start with RGI60-')
cfg.initialize()
wd = utils.gettempdir(dirname='pygem-{}-b{}'.format(rgi_id, prepro_border),
reset=reset)
cfg.PATHS['working_dir'] = wd
cfg.PARAMS['use_multiple_flowlines'] = False
# Check if folder is already processed
try:
gdir = utils.GlacierDirectory(rgi_id)
gdir.read_pickle('model_flowlines')
# If the above works the directory is already processed, return
return gdir
except OSError:
pass
# If not ready, we download the preprocessed data for this glacier
gdirs = workflow.init_glacier_regions([rgi_id],
from_prepro_level=2,
prepro_border=prepro_border)
# Compute all the stuff
list_talks = [
tasks.glacier_masks,
tasks.compute_centerlines,
tasks.initialize_flowlines,
tasks.compute_downstream_line,
tasks.catchment_area,
tasks.catchment_width_geom,
tasks.catchment_width_correction,
tasks.compute_downstream_bedshape,
tasks.local_t_star,
tasks.mu_star_calibration,
tasks.prepare_for_inversion,
tasks.mass_conservation_inversion,
tasks.filter_inversion_output,
tasks.init_present_time_glacier,
]
for task in list_talks:
# The order matters!
workflow.execute_entity_task(task, gdirs)
return gdirs[0]
def single_flowline_glacier_directory(rgi_id, reset=False, prepro_border=80):
"""Prepare a GlacierDirectory for PyGEM (single flowline to start with)
Parameters
----------
rgi_id : str
the rgi id of the glacier (RGIv60-)
reset : bool
set to true to delete any pre-existing files. If false (the default),
the directory won't be re-downloaded if already available locally in
order to spare time.
prepro_border : int
the size of the glacier map: 10, 80, 160, 250
Returns
-------
a GlacierDirectory object
"""
if type(rgi_id) != str:
raise ValueError('We expect rgi_id to be a string')
if rgi_id.startswith('RGI60-') == False:
rgi_id = 'RGI60-' + rgi_id.split('.')[0].zfill(2) + '.' + rgi_id.split(
'.')[1]
else:
raise ValueError('Check RGIId is correct')
# Initialize OGGM and set up the default run parameters
cfg.initialize(logging_level='WORKFLOW')
cfg.PARAMS['border'] = 10
# Usually we recommend to set dl_verify to True - here it is quite slow
# because of the huge files so we just turn it off.
# Switch it on for real cases!
cfg.PARAMS['dl_verify'] = True
cfg.PARAMS['use_multiple_flowlines'] = False
# temporary directory for testing (deleted on computer restart)
cfg.PATHS['working_dir'] = pygem_prms.oggm_gdir_fp
# Check if folder is already processed
if not pygem_prms.overwrite_gdirs:
try:
gdir = utils.GlacierDirectory(rgi_id)
gdir.read_pickle('inversion_flowlines')
# If the above works the directory is already processed, return
return gdir
except:
process_gdir = True
else:
process_gdir = True
if process_gdir:
# ===== SELECT BEST DEM =====
# gdirs = rgitopo.init_glacier_directories_from_rgitopo([rgi_id]) # removed 10/20/2020
# gdirs = workflow.init_glacier_directories([rgi_id])
# Download preprocessed data
gdirs = workflow.init_glacier_regions([rgi_id],
from_prepro_level=1,
prepro_border=prepro_border)
# Start after the prepro task level
# base_url = 'https://cluster.klima.uni-bremen.de/~fmaussion/gdirs/prepro_l2_202010/single_fl'
# gdirs = workflow.init_glacier_directories([rgi_id], from_prepro_level=2, prepro_border=40,
# prepro_base_url=base_url, prepro_rgi_version='62')
# Compute all the stuff
list_tasks = [
tasks.glacier_masks,
tasks.compute_centerlines,
tasks.initialize_flowlines,
tasks.compute_downstream_line,
tasks.compute_downstream_bedshape,
tasks.catchment_area,
tasks.catchment_intersections,
tasks.catchment_width_geom,
tasks.catchment_width_correction,
# # Consensus ice thickness
# icethickness.consensus_gridded,
# icethickness.consensus_binned,
# Mass balance data
mbdata.mb_df_to_gdir
]
# Debris tasks
if pygem_prms.include_debris:
list_tasks.append(debris.debris_to_gdir)
list_tasks.append(debris.debris_binned)
for task in list_tasks:
workflow.execute_entity_task(task, gdirs)
return gdirs[0]
def single_flowline_glacier_directory_with_calving(rgi_id,
reset=False,
prepro_border=10,
k_calving=2):
"""Prepare a GlacierDirectory for PyGEM (single flowline to start with)
k_calving is free variable!
Parameters
----------
rgi_id : str
the rgi id of the glacier
reset : bool
set to true to delete any pre-existing files. If false (the default),
the directory won't be re-downloaded if already available locally in
order to spare time.
prepro_border : int
the size of the glacier map: 10, 80, 160, 250
Returns
-------
a GlacierDirectory object
"""
assert 1 == 0, 'UPDATE LATEST GLACIER DIRECTORY OPTIONS FROM NON-CALVING'
if type(rgi_id) != str:
raise ValueError('We expect rgi_id to be a string')
if rgi_id.startswith('RGI60-') == False:
rgi_id = 'RGI60-' + rgi_id.split('.')[0].zfill(2) + '.' + rgi_id.split(
'.')[1]
else:
raise ValueError('Check RGIId is correct')
cfg.initialize()
wd = '/Users/davidrounce/Documents/Dave_Rounce/HiMAT/Output/oggm-pygem-{}-b{}-k{}'.format(
rgi_id, prepro_border, k_calving)
cfg.PATHS['working_dir'] = wd
cfg.PARAMS['use_multiple_flowlines'] = False
cfg.PARAMS['use_multiprocessing'] = False
# Check if folder is already processed
try:
gdir = utils.GlacierDirectory(rgi_id)
gdir.read_pickle('model_flowlines')
# If the above works the directory is already processed, return
return gdir
except:
pass
# If not ready, we download the preprocessed data for this glacier
gdirs = workflow.init_glacier_regions([rgi_id],
from_prepro_level=2,
prepro_border=prepro_border)
if not gdirs[0].is_tidewater:
raise ValueError('This glacier is not tidewater!')
# Compute all the stuff
list_tasks = [
tasks.glacier_masks,
tasks.compute_centerlines,
tasks.initialize_flowlines,
tasks.compute_downstream_line,
tasks.compute_downstream_bedshape,
tasks.catchment_area,
tasks.catchment_intersections, # added 10/20/2020
tasks.catchment_width_geom,
tasks.catchment_width_correction,
# Consensus ice thickness
icethickness.consensus_gridded,
icethickness.consensus_binned,
# Mass balance data
# mbdata.mb_bins_to_glacierwide
mbdata.mb_df_to_gdir
]
# Debris tasks
if pygem_prms.include_debris:
list_tasks.append(debris.debris_to_gdir)
list_tasks.append(debris.debris_binned)
for task in list_tasks:
# The order matters!
workflow.execute_entity_task(task, gdirs)
# Calving according to Recinos et al. 2019
# solves equality between ice derformation and Oerleman's calving law
# reduces temperature sensitivity
from oggm.core.inversion import find_inversion_calving
cfg.PARAMS['k_calving'] = k_calving
df = find_inversion_calving(gdirs[0])
print('Calving results:')
print('k calving:', k_calving)
for k, v in df.items():
print(k + ':', v)
list_tasks = [
# THIS WILL NOW FAIL BECAUSE OF USING HUSS
tasks.init_present_time_glacier,
]
for task in list_tasks:
# The order matters!
workflow.execute_entity_task(task, gdirs)
return gdirs[0]