def plot_surface_difference(surface_difference,
filepath,
title,
cbar_min=None,
cbar_max=None,
ice_mask=None):
if cbar_min is None:
cbar_min = surface_difference.min()
if cbar_max is None:
cbar_max = surface_difference.max()
fig, ax = plt.subplots()
im_b = ax.imshow(surface_difference,
cmap='RdBu_r',
norm=MidpointNormalize(midpoint=0.,
vmin=cbar_min,
vmax=cbar_max))
cbar = fig.colorbar(im_b)
cbar.set_label('$\Delta$surface height (m)')
ax.set_title(title)
if ice_mask is not None:
plot_glacier_contours(ax,
ice_mask,
linestyles='dashed',
linewidths=[0.75])
plt.savefig(filepath)
plt.clf()
def plot_bed_difference(bed_difference,
filepath,
title,
cbar_min=None,
cbar_max=None,
ice_mask=None,
bed_measurements=None):
if cbar_min is None:
cbar_min = bed_difference.min()
if cbar_max is None:
cbar_max = bed_difference.max()
fig, ax = plt.subplots()
im_b = ax.imshow(bed_difference,
cmap='RdBu_r',
norm=MidpointNormalize(midpoint=0.,
vmin=cbar_min,
vmax=cbar_max))
cbar = plt.colorbar(im_b)
cbar.set_label('$\Delta$bed height (m)')
ax.set_title(title)
if ice_mask is not None:
plot_glacier_contours(ax,
ice_mask,
linestyles='dashed',
linewidths=[0.75])
if bed_measurements is not None:
plot_glacier_contours(ax,
~bed_measurements.mask,
colors='k',
linestyles='solid',
linewidths=[1.])
plt.savefig(filepath)
plt.clf()
dl = load_pickle(path)
exp_name = experiment_naming_engine.get_experiment_name2(exp)
if exp_name is not None and len(dl.step_indices) > 0:
ice_mask = np.load(os.path.join(gdir, 'ref_ice_mask.npy'))
bed_measurements = None
if exp_name.startswith('bed measurements'):
bed_measurements = np.load(
os.path.join(idir, 'bed_measurements.pkl'))
diff_first_guess = dl.first_guessed_bed - dl.true_bed
diff_optimized = dl.beds[-1] - dl.true_bed
cbar_min = min(diff_first_guess.min(), diff_optimized.min())
cbar_max = max(diff_first_guess.max(), diff_optimized.max())
cbar_min_max = max(abs(cbar_min), abs(cbar_max))
norm = MidpointNormalize(midpoint=0.,
vmin=-cbar_min_max,
vmax=cbar_min_max)
#my_cmap = sns.diverging_palette(240, 15, l=40, s=99, as_cmap=True)
my_cmap = plt.get_cmap('seismic')
plotpath = os.path.join(
output_dir, '{:s}_{:s}_first_guess_bed_error.{'
':s}'.format(case.name, exp_name.replace('*', ' plus bed'),
file_extension))
plot_bed_difference(diff_first_guess,
plotpath,
case,
ice_mask=ice_mask,
bed_measurements=bed_measurements,
cbar_min=cbar_min,
cbar_max=cbar_max,
show_cbar=False,
if exp_name is not None:
if exp_name.startswith('bed measurements'):
ice_mask = np.load(os.path.join(gdir, 'ref_ice_mask.npy'))
bed_measurements = np.load(
os.path.join(idir, 'bed_measurements.pkl'))
measurement_noise = bed_measurements - dl.true_bed
np.ma.set_fill_value(measurement_noise, np.nan)
cbar_min = measurement_noise.min()
cbar_max = measurement_noise.max()
cbar_min = np.floor(cbar_min / 5) * 5
cbar_max = np.ceil(cbar_max / 5) * 5
cbar_min_max = max(abs(cbar_min), abs(cbar_max))
norm = MidpointNormalize(midpoint=0.,
vmin=-cbar_min_max,
vmax=cbar_min_max,
mask=measurement_noise.mask)
#my_cmap = sns.diverging_palette(240, 15, l=40, s=99, as_cmap=True)
my_cmap = plt.get_cmap('PRGn')
measurement_RMSE = RMSE(bed_measurements, dl.true_bed)
text = 'measurement RMSE: {:.1f} m'.format(measurement_RMSE)
plotpath = os.path.join(
output_dir, '{:s}_{:s}_measurement_noise.{:s}'.format(
case.name, exp_name, file_extension))
plot_bed_measurement(measurement_noise,
plotpath,
case,
ice_mask=ice_mask,
cbar_min=cbar_min,
cbar_max=cbar_max,
show_cbar=True,