solver='L-BFGS-B',
minimize_options=minimize_options,
inversion_subdir=subdir,
fg_shape_factor=1.,
bounds_min_max=(2, 300))
# Optional, if not reset=True and already ran once
# only needed once:
if first_run:
create_glacier(gdir)
first_run = False
# compile_first_guess(gdir)
noise = create_perlin_noise(gdir,
noise_parameters[0],
octaves=octaves,
base=noise_parameters[2],
freq=noise_parameters[1],
glacier_only=True)
#plt.figure()
#plt.imshow(noise)
#plt.show()
take_true_bed_as_first_guess(gdir)
add_noise_to_first_guess(gdir, noise)
idir = InversionDirectory(gdir)
# copy this script to inversion directory for reproducibility
path_to_file = '/home/philipp/COBBI/combine/sandbox/Giluwe' \
'/noisy_first_guess_inversion_run.py'
fname = os.path.split(path_to_file)[-1]
fg_shape_factor=1.,
fg_slope_cutoff_angle=2.5,
fg_min_height=-30,
fg_interp_boundary=True,
bounds_min_max=(2, 1000)
)
# Optional, if not reset=True and already ran once
# only needed once:
#create_glacier(gdir)
compile_first_guess(gdir)
if os.path.exists(gdir.get_filepath('dem_noise')):
os.remove(gdir.get_filepath('dem_noise'))
noise = create_perlin_noise(gdir, desired_rmse, octaves=4, base=2, freq=3,
glacier_only=True)
add_surface_noise(gdir, noise)
create_case_table(gdir)
idir = InversionDirectory(gdir)
# copy this script to inversion directory for reproducibility
path_to_file = '/home/philipp/COBBI/combine/sandbox/bonus_runs' \
'/perturbed_surface.py'
fname = os.path.split(path_to_file)[-1]
if not os.path.exists(idir.get_current_basedir()):
os.makedirs(idir.get_current_basedir(), exist_ok=True)
shutil.copy(path_to_file, os.path.join(idir.get_current_basedir(), fname))
res = idir.run_minimize()
np.random.seed(bed_measurements_dict['seed'])
bed_measurements = generate_bed_measurements(
gdir,
bed_measurements_dict['measurement_mask'],
std=bed_measurements_dict['std'])
add_bed_measurements(gdir, bed_measurements)
# First guess options
if not use_preexisting_fg:
compile_first_guess(gdir)
if biased_fg_dict['use']:
compile_biased_first_guess(gdir, biased_fg_dict['desired_mean_bias'])
if rmsed_fg_dict['use']:
# desired_rmse = 5
# desired_rmse = 20.2038 # results in actual rmse of 20
noise = create_perlin_noise(gdir, **rmsed_fg_dict)
take_true_bed_as_first_guess(gdir)
add_noise_to_first_guess(gdir, noise)
if use_measurements_in_fg:
apply_bed_measurements_to_first_guess(gdir)
# Maybe some surface noise?
if surface_noise_dict['use']:
noise = create_perlin_noise(gdir, **surface_noise_dict)
add_surface_noise(gdir, noise)
idir = InversionDirectory(gdir)
res = idir.run_minimize()
eval_identical_twin(idir)