def test_multiple_inversion():
# test directory
testdir = os.path.join(get_test_dir(), 'tmp_mdir')
if not os.path.exists(testdir):
os.makedirs(testdir)
# Init
cfg.initialize()
cfg.set_intersects_db(get_demo_file('rgi_intersect_oetztal.shp'))
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
cfg.PARAMS['run_mb_calibration'] = True
cfg.PARAMS['baseline_climate'] = 'CUSTOM'
cfg.PATHS['working_dir'] = testdir
# Get the RGI ID
hef_rgi = gpd.read_file(get_demo_file('divides_hef.shp'))
hef_rgi.loc[0, 'RGIId'] = 'RGI50-11.00897'
gdirs = workflow.init_glacier_regions(hef_rgi)
workflow.gis_prepro_tasks(gdirs)
workflow.climate_tasks(gdirs)
workflow.inversion_tasks(gdirs)
fig, ax = plt.subplots()
graphics.plot_inversion(gdirs, ax=ax)
fig.tight_layout()
shutil.rmtree(testdir)
return fig
def prepare_for_initializing(gdirs):
list_tasks = [
tasks.compute_centerlines,
tasks.initialize_flowlines,
tasks.catchment_area,
tasks.catchment_width_geom,
tasks.catchment_width_correction,
tasks.compute_downstream_line,
tasks.compute_downstream_bedshape
]
for task in list_tasks:
workflow.execute_entity_task(task, gdirs)
workflow.climate_tasks(gdirs)
workflow.execute_entity_task(tasks.prepare_for_inversion, gdirs)
glen_a = cfg.A
for gdir in gdirs:
mass_conservation_inversion(gdir, glen_a=glen_a)
workflow.execute_entity_task(tasks.optimize_inversion_params,gdirs)
workflow.execute_entity_task(tasks.volume_inversion, gdirs)
workflow.execute_entity_task(tasks.filter_inversion_output, gdirs)
workflow.execute_entity_task(tasks.init_present_time_glacier,gdirs)
def up_to_inversion(reset=False):
"""Run the tasks you want."""
gdirs = up_to_climate(reset=reset)
with open(CLI_LOGF, 'rb') as f:
clilog = pickle.load(f)
if clilog != 'histalp':
reset = True
else:
try:
tasks.prepare_for_inversion(gdirs[0])
except Exception:
reset = True
if reset:
# Use histalp for the actual inversion test
cfg.PARAMS['temp_use_local_gradient'] = True
cfg.PARAMS['baseline_climate'] = 'HISTALP'
workflow.climate_tasks(gdirs)
with open(CLI_LOGF, 'wb') as f:
pickle.dump('histalp', f)
# Inversion
workflow.inversion_tasks(gdirs)
return gdirs
def prepare_for_initializing(gdirs):
'''
oggm workflow for preparing initializing
:param gdirs: list of oggm.GlacierDirectories
:return None, but creates required files
'''
list_tasks = [
tasks.compute_centerlines,
tasks.initialize_flowlines,
tasks.catchment_area,
tasks.catchment_width_geom,
tasks.catchment_width_correction,
tasks.compute_downstream_line,
tasks.compute_downstream_bedshape
]
for task in list_tasks:
workflow.execute_entity_task(task, gdirs)
workflow.climate_tasks(gdirs)
workflow.execute_entity_task(tasks.prepare_for_inversion, gdirs)
glen_a = cfg.A
for gdir in gdirs:
mass_conservation_inversion(gdir, glen_a=glen_a)
workflow.execute_entity_task(tasks.volume_inversion, gdirs)
workflow.execute_entity_task(tasks.filter_inversion_output, gdirs)
workflow.execute_entity_task(tasks.init_present_time_glacier,gdirs)
def up_to_inversion(reset=False):
"""Run the tasks you want."""
gdirs = up_to_climate(reset=reset)
with open(CLI_LOGF, 'rb') as f:
clilog = pickle.load(f)
if clilog != 'histalp':
reset = True
else:
try:
tasks.prepare_for_inversion(gdirs[0])
except Exception:
reset = True
if reset:
# Use histalp for the actual inversion test
cfg.PARAMS['temp_use_local_gradient'] = True
cfg.PARAMS['baseline_climate'] = 'HISTALP'
cru_dir = get_demo_file('HISTALP_precipitation_all_abs_1801-2014.nc')
cfg.PATHS['cru_dir'] = os.path.dirname(cru_dir)
workflow.climate_tasks(gdirs)
with open(CLI_LOGF, 'wb') as f:
pickle.dump('histalp', f)
# Inversion
workflow.inversion_tasks(gdirs)
return gdirs
def up_to_inversion(reset=False):
"""Run the tasks you want."""
gdirs = up_to_climate(reset=reset)
with open(CLI_LOGF, 'rb') as f:
clilog = pickle.load(f)
if clilog != 'histalp':
reset = True
else:
try:
tasks.prepare_for_inversion(gdirs[0])
except Exception:
reset = True
if reset:
# Use histalp for the actual inversion test
cfg.PARAMS['temp_use_local_gradient'] = True
cfg.PARAMS['baseline_climate'] = 'HISTALP'
cru_dir = get_demo_file('HISTALP_precipitation_all_abs_1801-2014.nc')
cfg.PATHS['cru_dir'] = os.path.dirname(cru_dir)
workflow.climate_tasks(gdirs)
with open(CLI_LOGF, 'wb') as f:
pickle.dump('histalp', f)
# Inversion
workflow.inversion_tasks(gdirs)
return gdirs
def preprocessing(gdirs):
"""
oggm workflow for preparing initializing
:param gdirs: list of oggm.GlacierDirectories from preprocessed level 2 onwards
:return None, but creates required files
"""
workflow.climate_tasks(gdirs)
workflow.inversion_tasks(gdirs)
workflow.execute_entity_task(tasks.init_present_time_glacier, gdirs)
def plot_issue(gdir, plot_dir):
#plt.style.use('ggplot')
workflow.gis_prepro_tasks([gdir])
workflow.climate_tasks([gdir])
workflow.inversion_tasks([gdir])
tasks.init_present_time_glacier(gdir)
# Observed length changes
df = gdir.get_ref_length_data()
df = df.loc[1855:2003]['dL']
df = df - df.iloc[-1]
tasks.run_from_climate_data(gdir,
ys=1855,
ye=2003,
output_filesuffix='hist_from_current')
ds = xr.open_dataset(
gdir.get_filepath('model_diagnostics', filesuffix='hist_from_current'))
(ds.length_m.to_series().rolling(36, center=True).mean() -
ds.length_m.to_series().iloc[0]).plot(c='C0', label='OGGM')
#s = s - s.iloc[-1]
#print(s)
ax = df.plot(c='k', label='Observations')
#s.plot(c='C0', label='OGGM');
plt.legend()
ax.set_ylabel('Glacier Length Change [m]')
plt.title('Hintereisferner length changes Experiment 2')
plt.tight_layout()
plt.show()
'''
fls = gdir.read_pickle('model_flowlines')
x = np.arange(fls[-1].nx) *fls[-1].dx * fls[-1].map_dx
plt.figure(figsize=(13,10))
rc('axes', linewidth=3)
plt.plot(x,fls[-1].surface_h,linewidth=3, label='Surface Elevation')
plt.plot(x,fls[-1].bed_h,'k',linewidth=3,label='Bed Topography')
plt.ylabel('Altitude (m)',size=30)
plt.xlabel('Distance along the Flowline (m)',size=30)
plt.legend(loc='best',fontsize=30)
#plt.annotate('?', xy=(5000, 2700), fontsize=40)
plt.tick_params(axis='both', which='major', labelsize=30)
plt.title(gdir.rgi_id+ ': '+gdir.name,size=35)
plt.savefig(os.path.join(plot_dir, 'issue_today.png'),dpi=200)
'''
#plt.savefig(os.path.join(plot_dir, 'issue_1850.pdf'),dpi=200)
plt.show()
return
def test_multiple_models():
# test directory
testdir = os.path.join(get_test_dir(), 'tmp_mdir')
utils.mkdir(testdir, reset=True)
# Init
cfg.initialize()
cfg.set_intersects_db(get_demo_file('rgi_intersect_oetztal.shp'))
cfg.PATHS['dem_file'] = get_demo_file('hef_srtm.tif')
cfg.PATHS['climate_file'] = get_demo_file('histalp_merged_hef.nc')
cfg.PATHS['working_dir'] = testdir
cfg.PARAMS['baseline_climate'] = 'CUSTOM'
cfg.PARAMS['trapezoid_lambdas'] = 1
cfg.PARAMS['border'] = 40
apply_test_ref_tstars()
# Get the RGI ID
hef_rgi = gpd.read_file(get_demo_file('divides_hef.shp'))
hef_rgi.loc[0, 'RGIId'] = 'RGI50-11.00897'
gdirs = workflow.init_glacier_directories(hef_rgi)
workflow.gis_prepro_tasks(gdirs)
workflow.climate_tasks(gdirs)
workflow.inversion_tasks(gdirs)
models = []
for gdir in gdirs:
flowline.init_present_time_glacier(gdir)
fls = gdir.read_pickle('model_flowlines')
models.append(flowline.FlowlineModel(fls))
fig, ax = plt.subplots()
graphics.plot_modeloutput_map(gdirs, ax=ax, model=models)
fig.tight_layout()
shutil.rmtree(testdir)
return fig
def test_multiple_models():
# test directory
testdir = os.path.join(get_test_dir(), 'tmp_mdir')
utils.mkdir(testdir, reset=True)
# Init
cfg.initialize()
cfg.PATHS['dem_file'] = get_demo_file('hef_srtm.tif')
cfg.PARAMS['optimize_inversion_params'] = True
cfg.PATHS['climate_file'] = get_demo_file('histalp_merged_hef.nc')
cfg.PATHS['working_dir'] = testdir
cfg.PARAMS['run_mb_calibration'] = True
cfg.PARAMS['border'] = 40
# Get the RGI ID
hef_rgi = gpd.read_file(get_demo_file('divides_hef.shp'))
hef_rgi.loc[0, 'RGIId'] = 'RGI50-11.00897'
gdirs = workflow.init_glacier_regions(hef_rgi)
workflow.gis_prepro_tasks(gdirs)
workflow.climate_tasks(gdirs)
workflow.inversion_tasks(gdirs)
models = []
for gdir in gdirs:
flowline.init_present_time_glacier(gdir)
fls = gdir.read_pickle('model_flowlines')
models.append(flowline.FlowlineModel(fls))
fig, ax = plt.subplots()
graphics.plot_modeloutput_map(gdirs, ax=ax, model=models)
fig.tight_layout()
shutil.rmtree(testdir)
return fig
# remove gdirs that raised error #for gdir in gdirs: # if gdir.rgi_id in rm_list: # gdirs.remove(gdir) # plot catchment areas #graphics.plot_catchment_areas(gdirs, figsize=(8, 7)) ### Climate tasks ### # get tstars t* list and associated model parameters params_url = 'https://cluster.klima.uni-bremen.de/~oggm/ref_mb_params/oggm_v1.4/RGIV62/CRU/centerlines/qc3/pcp2.5' workflow.download_ref_tstars(base_url=params_url) # run climate related entity tasks workflow.climate_tasks(gdirs) # Downloads some files on the first time! # list gdirs that raised error (manual task) #rm_list = ['RGI60-05.01974', 'RGI60-05.02006', 'RGI60-05.02018', 'RGI60-05.02019', 'RGI60-05.02034', 'RGI60-05.02048', 'RGI60-05.02113' 'RGI60-05.02125', 'RGI60-05.02205', 'RGI60-05.02228', 'RGI60-05.02229', 'RGI60-05.02240', 'RGI60-05.02241', 'RGI60-05.02262', 'RGI60-05.02274', 'RGI60-05.02304', 'RGI60-05.02320', 'RGI60-05.02273_2', 'RGI60-05.02328_2', 'RGI60-05.01987_2'] # remove gdirs that raised error #for gdir in gdirs: # if gdir.rgi_id in rm_list: # gdirs.remove(gdir) # define year range years = np.arange(1903, 2020) # create dataframe to store results mb_result = pd.DataFrame() # Flowline Mass Balance
def up_to_inversion(reset=False):
"""Run the tasks you want."""
# test directory
if not os.path.exists(TEST_DIR):
os.makedirs(TEST_DIR)
if reset:
clean_dir(TEST_DIR)
# Init
cfg.initialize()
# Use multiprocessing
cfg.PARAMS['use_multiprocessing'] = not ON_TRAVIS
# Working dir
cfg.PATHS['working_dir'] = TEST_DIR
cfg.PATHS['dem_file'] = get_demo_file('srtm_oetztal.tif')
# Set up the paths and other stuffs
cfg.set_divides_db(get_demo_file('divides_workflow.shp'))
cfg.PATHS['wgms_rgi_links'] = get_demo_file('RGI_WGMS_oetztal.csv')
cfg.PATHS['glathida_rgi_links'] = get_demo_file('RGI_GLATHIDA_oetztal.csv')
# Read in the RGI file
rgi_file = get_demo_file('rgi_oetztal.shp')
rgidf = gpd.GeoDataFrame.from_file(rgi_file)
# Be sure data is downloaded because lock doesn't work
cl = utils.get_cru_cl_file()
# Params
cfg.PARAMS['border'] = 70
cfg.PARAMS['use_optimized_inversion_params'] = True
# Go
gdirs = workflow.init_glacier_regions(rgidf)
try:
flowline.init_present_time_glacier(gdirs[0])
except Exception:
reset = True
if reset:
# First preprocessing tasks
workflow.gis_prepro_tasks(gdirs)
# Climate related tasks
# See if CRU is running
cfg.PARAMS['temp_use_local_gradient'] = False
cfg.PATHS['climate_file'] = '~'
cru_dir = get_demo_file('cru_ts3.23.1901.2014.tmp.dat.nc')
cfg.PATHS['cru_dir'] = os.path.dirname(cru_dir)
with warnings.catch_warnings():
# There is a warning from salem
warnings.simplefilter("ignore")
workflow.execute_entity_task(tasks.distribute_cru_style, gdirs)
tasks.compute_ref_t_stars(gdirs)
tasks.distribute_t_stars(gdirs)
# Use histalp for the actual test
cfg.PARAMS['temp_use_local_gradient'] = True
cfg.PATHS['climate_file'] = get_demo_file('HISTALP_oetztal.nc')
cfg.PATHS['cru_dir'] = '~'
workflow.climate_tasks(gdirs)
# Inversion
workflow.inversion_tasks(gdirs)
return gdirs
basin.geometry.contains(shpg.Point(x, y))[0]
for (x, y) in zip(rgidf.CenLon, rgidf.CenLat)
]
rgidf = rgidf.loc[in_bas]
# Store them for later
rgidf.to_file(os.path.join(WORKING_DIR, 'rgi_rofental.shp'))
# Sort for more efficient parallel computing
rgidf = rgidf.sort_values('Area', ascending=False)
print('Starting OGGM run')
print('Number of glaciers: {}'.format(len(rgidf)))
# Go - initialize glacier directories
gdirs = workflow.init_glacier_regions(rgidf)
# Tasks shortcuts - see the next examples for more details
workflow.gis_prepro_tasks(gdirs)
workflow.climate_tasks(gdirs)
workflow.inversion_tasks(gdirs)
# Compile output
print('Compiling output')
utils.compile_glacier_statistics(gdirs)
utils.write_centerlines_to_shape(gdirs)
# Log
m, s = divmod(time.time() - start, 60)
h, m = divmod(m, 60)
print('OGGM is done! Time needed: %d:%02d:%02d' % (h, m, s))
def up_to_inversion(reset=False):
"""Run the tasks you want."""
# test directory
if not os.path.exists(TEST_DIR):
os.makedirs(TEST_DIR)
if reset:
clean_dir(TEST_DIR)
# Init
cfg.initialize()
# Use multiprocessing
cfg.PARAMS['use_multiprocessing'] = not ON_TRAVIS
# Working dir
cfg.PATHS['working_dir'] = TEST_DIR
cfg.set_divides_db(get_demo_file('HEF_divided.shp'))
cfg.PATHS['dem_file'] = get_demo_file('srtm_oeztal.tif')
# Set up the paths and other stuffs
cfg.set_divides_db(get_demo_file('HEF_divided.shp'))
cfg.PATHS['wgms_rgi_links'] = get_demo_file('RGI_WGMS_oeztal.csv')
cfg.PATHS['glathida_rgi_links'] = get_demo_file('RGI_GLATHIDA_oeztal.csv')
# Read in the RGI file
rgi_file = get_demo_file('rgi_oeztal.shp')
rgidf = gpd.GeoDataFrame.from_file(rgi_file)
# Params
cfg.PARAMS['border'] = 70
cfg.PARAMS['use_inversion_params'] = True
# Go
gdirs = workflow.init_glacier_regions(rgidf)
try:
flowline.init_present_time_glacier(gdirs[0])
except Exception:
reset = True
if reset:
# First preprocessing tasks
workflow.gis_prepro_tasks(gdirs)
# Climate related tasks
# See if CRU is running
cfg.PARAMS['temp_use_local_gradient'] = False
cfg.PATHS['climate_file'] = '~'
cru_dir = get_demo_file('cru_ts3.23.1901.2014.tmp.dat.nc')
cfg.PATHS['cru_dir'] = os.path.dirname(cru_dir)
workflow.climate_tasks(gdirs)
# Use histalp for the actual test
cfg.PARAMS['temp_use_local_gradient'] = True
cfg.PATHS['climate_file'] = get_demo_file('HISTALP_oeztal.nc')
cfg.PATHS['cru_dir'] = '~'
workflow.climate_tasks(gdirs)
# Inversion
workflow.inversion_tasks(gdirs)
return gdirs
def up_to_inversion():
"""Run the tasks you want."""
# test directory
testdir = os.path.join(current_dir, 'tmp')
if not os.path.exists(testdir):
os.makedirs(testdir)
clean_dir(testdir)
# Init
cfg.initialize()
# Prevent multiprocessing
cfg.use_mp = False
# Working dir
cfg.paths['working_dir'] = testdir
cfg.set_divides_db(get_demo_file('HEF_divided.shp'))
cfg.paths['srtm_file'] = get_demo_file('srtm_oeztal.tif')
# Set up the paths and other stuffs
cfg.set_divides_db(get_demo_file('HEF_divided.shp'))
cfg.paths['histalp_file'] = get_demo_file('HISTALP_oeztal.nc')
# Get test glaciers (all glaciers with MB or Thickness data)
cfg.paths['wgms_rgi_links'] = get_demo_file('RGI_WGMS_oeztal.csv')
cfg.paths['glathida_rgi_links'] = get_demo_file('RGI_GLATHIDA_oeztal.csv')
# Read in the RGI file
rgi_file = get_demo_file('rgi_oeztal.shp')
rgidf = gpd.GeoDataFrame.from_file(rgi_file)
# Go
gdirs = workflow.init_glacier_regions(rgidf)
# First preprocessing tasks
workflow.gis_prepro_tasks(gdirs)
# Climate related tasks
workflow.climate_tasks(gdirs)
# Merge climate and catchments
workflow.execute_task(inversion.prepare_for_inversion, gdirs)
fs, fd = inversion.optimize_inversion_params(gdirs)
# Tests
dfids = cfg.paths['glathida_rgi_links']
gtd_df = pd.read_csv(dfids).sort_values(by=['RGI_ID'])
dfids = gtd_df['RGI_ID'].values
ref_gdirs = [gdir for gdir in gdirs if gdir.rgi_id in dfids]
# Account for area differences between glathida and rgi
ref_area_km2 = gtd_df.RGI_AREA.values
ref_cs = gtd_df.VOLUME.values / (gtd_df.GTD_AREA.values**1.375)
ref_volume_km3 = ref_cs * ref_area_km2**1.375
vol = []
area = []
rgi = []
for gdir in ref_gdirs:
v, a = inversion.inversion_parabolic_point_slope(gdir, fs=fs, fd=fd,
write=True)
vol.append(v)
area.append(a)
rgi.append(gdir.rgi_id)
df = pd.DataFrame()
df['rgi'] = rgi
df['area'] = area
df['ref_vol'] = ref_volume_km3
df['oggm_vol'] = np.array(vol) * 1e-9
df['vas_vol'] = 0.034*(ref_area_km2**1.375)
df = df.set_index('rgi')
shutil.rmtree(testdir)
return df
def up_to_inversion(reset=False):
"""Run the tasks you want."""
# test directory
if not os.path.exists(TEST_DIR):
os.makedirs(TEST_DIR)
if reset:
clean_dir(TEST_DIR)
# Init
cfg.initialize()
# Use multiprocessing
cfg.PARAMS['use_multiprocessing'] = not ON_TRAVIS
# Working dir
cfg.PATHS['working_dir'] = TEST_DIR
cfg.set_divides_db(get_demo_file('HEF_divided.shp'))
cfg.PATHS['dem_file'] = get_demo_file('srtm_oeztal.tif')
# Set up the paths and other stuffs
cfg.set_divides_db(get_demo_file('HEF_divided.shp'))
cfg.PATHS['wgms_rgi_links'] = get_demo_file('RGI_WGMS_oeztal.csv')
cfg.PATHS['glathida_rgi_links'] = get_demo_file('RGI_GLATHIDA_oeztal.csv')
# Read in the RGI file
rgi_file = get_demo_file('rgi_oeztal.shp')
rgidf = gpd.GeoDataFrame.from_file(rgi_file)
# Params
cfg.PARAMS['border'] = 70
cfg.PARAMS['use_inversion_params'] = True
# Go
gdirs = workflow.init_glacier_regions(rgidf)
try:
flowline.init_present_time_glacier(gdirs[0])
except Exception:
reset = True
if reset:
# First preprocessing tasks
workflow.gis_prepro_tasks(gdirs)
# Climate related tasks
# See if CRU is running
cfg.PARAMS['temp_use_local_gradient'] = False
cfg.PATHS['climate_file'] = '~'
cru_dir = get_demo_file('cru_ts3.23.1901.2014.tmp.dat.nc')
cfg.PATHS['cru_dir'] = os.path.dirname(cru_dir)
workflow.climate_tasks(gdirs)
# Use histalp for the actual test
cfg.PARAMS['temp_use_local_gradient'] = True
cfg.PATHS['climate_file'] = get_demo_file('HISTALP_oeztal.nc')
cfg.PATHS['cru_dir'] = '~'
workflow.climate_tasks(gdirs)
# Inversion
workflow.inversion_tasks(gdirs)
return gdirs