def run_random_task(tupel,gdir,y0):
seed = tupel[0]
temp_bias = tupel[1]
fls = gdir.read_pickle('model_flowlines')
suffix = str(y0)+'_random_'+str(seed)+'_'+ str(temp_bias)
# test if file already exist:
path = gdir.get_filepath('model_run', filesuffix=suffix)
# does file already exists?
if not os.path.exists(path):
try:
tasks.run_random_climate(gdir, nyears=400, y0=y0, bias=0,
seed=seed, temperature_bias=temp_bias,
init_model_fls=copy.deepcopy(fls),
output_filesuffix=suffix)
return path
# oggm failed --> probaly "glacier exeeds boundaries"
except:
return None
else:
# does file contain a model?
try:
fmod = FileModel(path)
return path
except:
return None
def _run_random_task(tupel, gdir, y0, bias):
"""
Run random model to create lots of possible states
"""
seed = tupel[0]
temp_bias = tupel[1]
fls = gdir.read_pickle('model_flowlines')
suffix = str(y0) + '_random_' + str(seed) + '_' + str(temp_bias)
#path = gdir.get_filepath('model_run', filesuffix=suffix)
path = os.path.join(gdir.dir, str(y0), 'model_run' + suffix + '.nc')
# does file already exists?
if not os.path.exists(path):
try:
tasks.run_random_climate(gdir,
nyears=600,
y0=y0,
bias=bias,
seed=seed,
temperature_bias=temp_bias,
init_model_fls=copy.deepcopy(fls),
output_filesuffix=suffix)
return path
# oggm failed --> probaly "glacier exeeds boundaries"
except:
return None
else:
# does file contain a model?
try:
fmod = FileModel(path)
return path
except:
return None
def _single_calibration_run(gdir, mb_offset, ys, ye):
"""
Creates the synthetic experiment for one glacier. model_geometry_experiment.nc
will be saved in working directory.
"""
# check, if this model_geometry already exists
try:
rp = gdir.get_filepath('model_geometry',
filesuffix='_calibration_past_' +
str(mb_offset))
model = FileModel(rp)
# otherwise create calibration_run with mb_offset
except:
try:
fls = gdir.read_pickle('model_flowlines')
# run a 600 years random run with mb_offset
tasks.run_random_climate(gdir,
nyears=600,
y0=ys,
bias=mb_offset,
seed=1,
init_model_fls=fls,
output_filesuffix='_calibration_random_' +
str(mb_offset))
# construct s_OGGM --> previous glacier will be run forward from
# ys - ye with past climate file
tasks.run_from_climate_data(
gdir,
ys=ys,
ye=ye,
init_model_filesuffix='_calibration_random_' + str(mb_offset),
bias=mb_offset,
init_model_yr=600,
output_filesuffix='_calibration_past_' + str(mb_offset))
# return FileModel
rp = gdir.get_filepath('model_geometry',
filesuffix='_calibration_past_' +
str(mb_offset))
model = FileModel(rp)
except:
with open(os.path.join(gdir.dir, 'log.txt')) as log:
error = list(log)[-1].split(';')[-1]
return error
return model
def _run_parallel_experiment(gdir, t0, te):
"""
Creates the synthetic experiment for one glacier. model_run_experiment.nc
will be saved in working directory.
"""
try:
fls = gdir.read_pickle('model_flowlines')
# try to run random climate with temperature bias -1
model = tasks.run_random_climate(gdir,
nyears=600,
y0=t0,
bias=0,
seed=1,
temperature_bias=-1,
init_model_fls=fls)
# construct observed glacier, previous glacier will be run forward from
# 1850 - 2000 with past climate file
b = fls[-1].bed_h
fls = copy.deepcopy(model.fls)
model = tasks.run_from_climate_data(gdir,
ys=t0,
ye=te,
init_model_fls=fls,
output_filesuffix='_experiment')
except:
print('experiment failed : ' + str(gdir.rgi_id))
def _run_experiment(gdir, temp_bias, bias, ys, ye):
"""
Creates the synthetic experiment for one glacier. model_run_experiment.nc
will be saved in working directory.
"""
# check, if this experiment already exists
try:
rp = gdir.get_filepath('model_run',
filesuffix='_advanced_experiment_' +
str(temp_bias) + '_' + str(bias))
model = FileModel(rp)
# otherwise create experiment
except:
try:
fls = gdir.read_pickle('model_flowlines')
model = tasks.run_random_climate(
gdir,
nyears=600,
y0=ys,
bias=bias,
seed=1,
temperature_bias=temp_bias,
init_model_fls=fls,
output_filesuffix='_random_experiment_' + str(temp_bias) +
'_' + str(bias))
# construct observed glacier, previous glacier will be run forward from
# 1917 - rgi_date with past climate file
fls = copy.deepcopy(model.fls)
tasks.run_from_climate_data(
gdir,
ys=ys,
ye=ye,
init_model_fls=fls,
bias=bias,
output_filesuffix='_advanced_experiment_' + str(temp_bias) +
'_' + str(bias))
# to return FileModel
rp = gdir.get_filepath('model_run',
filesuffix='_advanced_experiment_' +
str(temp_bias) + '_' + str(bias))
model = FileModel(rp)
except:
with open(os.path.join(gdir.dir, 'log.txt')) as log:
error = list(log)[-1].split(';')[-1]
return error
return model
def _run_parallel_experiment(gdir, t0, te):
"""
Creates the synthetic experiment for one glacier. model_geometry_synthetic_experiment.nc
will be saved in working directory.
"""
try:
fls = gdir.read_pickle('model_flowlines')
# try to run random climate with temperature bias -1
tasks.run_random_climate(
gdir,
nyears=600,
y0=t0,
bias=0,
seed=1,
temperature_bias=-1,
init_model_fls=fls,
output_filesuffix='_random_synthetic_experiment')
# construct observed glacier, previous glacier will be run forward from
# t0 - te with past climate file
tasks.run_from_climate_data(
gdir,
ys=t0,
ye=te,
init_model_filesuffix='_random_synthetic_experiment',
init_model_yr=600,
output_filesuffix='_synthetic_experiment')
# remove output file from random run
os.remove(
gdir.get_filepath('model_geometry',
filesuffix='_random_synthetic_experiment'))
os.remove(
gdir.get_filepath('model_diagnostics',
filesuffix='_random_synthetic_experiment'))
except:
print('experiment failed : ' + str(gdir.rgi_id))
def _run_experiment(gdir, temp_bias, bias, ys, ye):
"""
Creates the synthetic experiment for one glacier. model_run_experiment.nc
will be saved in working directory.
"""
# check, if this experiment already exists
try:
rp = gdir.get_filepath('model_run',
filesuffix='_advanced_experiment_' +
str(temp_bias) + '_' + str(bias))
model = FileModel(rp)
# otherwise create experiment
except:
fls = gdir.read_pickle('model_flowlines')
try:
model = tasks.run_random_climate(gdir,
nyears=400,
y0=ys,
bias=bias,
seed=1,
temperature_bias=temp_bias,
init_model_fls=fls)
# construct observed glacier, previous glacier will be run forward from
# 1917 - 2000 with past climate file
fls = deepcopy(model.fls)
model = tasks.run_from_climate_data(
gdir,
ys=ys,
ye=ye,
init_model_fls=fls,
bias=bias,
output_filesuffix='_advanced_experiment_' + str(temp_bias) +
'_' + str(bias))
except:
pass
return model
tasks.catchment_width_geom(gdir)
tasks.catchment_width_correction(gdir)
tasks.process_cru_data(gdir)
tasks.local_t_star(gdir)
tasks.mu_star_calibration(gdir)
glen_a = cfg.PARAMS['glen_a']
tasks.prepare_for_inversion(gdir)
tasks.mass_conservation_inversion(gdir, glen_a=glen_a, fs=0)
tasks.filter_inversion_output(gdir)
# run
tasks.init_present_time_glacier(gdir)
tasks.run_random_climate(gdir,
bias=0.,
temperature_bias=-1,
nyears=120,
glen_a=glen_a,
check_for_boundaries=False)
f = 0.9
f = plt.figure(figsize=(7, 10))
from mpl_toolkits.axes_grid1 import ImageGrid
axs = ImageGrid(
f,
111, # as in plt.subplot(111)
nrows_ncols=(3, 2),
axes_pad=0.15,
share_all=True,
cbar_location="right",
cbar_mode="edge",
tasks.catchment_width_geom(gdir)
tasks.catchment_width_correction(gdir)
tasks.process_cru_data(gdir)
tasks.local_t_star(gdir)
tasks.mu_star_calibration(gdir)
tasks.prepare_for_inversion(gdir)
tasks.mass_conservation_inversion(gdir)
tasks.filter_inversion_output(gdir)
tasks.init_present_time_glacier(gdir)
df = utils.compile_glacier_statistics([gdir], path=False)
reset = False
seed = 0
tasks.run_random_climate(gdir, nyears=800, seed=0, y0=2000,
output_filesuffix='_2000_def', reset=reset)
tasks.run_random_climate(gdir, nyears=800, seed=0, y0=1920,
output_filesuffix='_1920_def', reset=reset)
f = gdir.get_filepath('model_diagnostics', filesuffix='_2000_def')
ds1 = xr.open_dataset(f)
f = gdir.get_filepath('model_diagnostics', filesuffix='_1920_def')
ds2 = xr.open_dataset(f)
f = 0.9
f = plt.figure(figsize=(9*f, 6*f))
from mpl_toolkits.axes_grid1 import ImageGrid
axs = ImageGrid(f, 111, # as in plt.subplot(111)
nrows_ncols=(2, 2),
tasks.mu_star_calibration(gdir)
tasks.prepare_for_inversion(gdir)
tasks.mass_conservation_inversion(gdir)
tasks.filter_inversion_output(gdir)
tasks.init_present_time_glacier(gdir)
df = utils.compile_glacier_statistics([gdir], path=False)
reset = False
seed = 0
glen_a = cfg.PARAMS['glen_a']
fs = 5.7e-20
nyears = 800
tasks.run_random_climate(gdir, nyears=nyears, bias=0, seed=seed,
output_filesuffix='_fromzero_def', reset=reset,
zero_initial_glacier=True)
tasks.run_constant_climate(gdir, nyears=nyears, bias=0,
output_filesuffix='_fromzero_ct', reset=reset,
zero_initial_glacier=True)
cfg.PARAMS['fs'] = fs * 0.5
tasks.run_random_climate(gdir, nyears=nyears, bias=0, seed=seed,
output_filesuffix='_fromzero_fs', reset=reset,
zero_initial_glacier=True)
cfg.PARAMS['fs'] = 0
cfg.PARAMS['glen_a'] = glen_a*2
tasks.run_random_climate(gdir, nyears=nyears, bias=0, seed=seed,
output_filesuffix='_fromzero_2A', reset=reset,
