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 test_workflow(self):
# This is a check that the inversion workflow works fine
# Download the RGI file for the run
# Make a new dataframe of those
rgidf = gpd.read_file(get_demo_file('SouthGlacier.shp'))
# Go - initialize working directories
gdirs = workflow.init_glacier_directories(rgidf)
# Preprocessing tasks
task_list = [
tasks.define_glacier_region,
tasks.glacier_masks,
tasks.compute_centerlines,
tasks.initialize_flowlines,
tasks.catchment_area,
tasks.catchment_intersections,
tasks.catchment_width_geom,
tasks.catchment_width_correction,
tasks.compute_downstream_line,
tasks.compute_downstream_bedshape,
]
for task in task_list:
execute_entity_task(task, gdirs)
execute_entity_task(tasks.process_cru_data,
gdirs,
tmp_file=self.tf,
pre_file=self.pf)
execute_entity_task(tasks.local_t_star, gdirs)
execute_entity_task(tasks.mu_star_calibration, gdirs)
# Inversion tasks
execute_entity_task(tasks.prepare_for_inversion, gdirs)
# We use the default parameters for this run
execute_entity_task(tasks.mass_conservation_inversion, gdirs)
execute_entity_task(tasks.filter_inversion_output, gdirs)
df = utils.compile_glacier_statistics(gdirs)
df['inv_thickness_m'] = df['inv_volume_km3'] / df['rgi_area_km2'] * 1e3
assert df.inv_thickness_m[0] < 100
df = utils.compile_fixed_geometry_mass_balance(gdirs)
assert len(df) > 100
if do_plot:
import matplotlib.pyplot as plt
from oggm.graphics import plot_inversion
plot_inversion(gdirs)
plt.show()
def test_single_flowline_glacier_directory():
rid = 'RGI60-15.03473'
gdir = oggm_compat.single_flowline_glacier_directory(rid)
assert gdir.rgi_area_km2 == 61.054
if do_plot:
from oggm import graphics
import matplotlib.pyplot as plt
f, (ax1, ax2) = plt.subplots(1, 2)
graphics.plot_googlemap(gdir, ax=ax1)
graphics.plot_inversion(gdir, ax=ax2)
plt.show()
def test_plot_region_inversion():
gdirs = up_to_inversion()
# We prepare for the plot, which needs our own map to proceed.
# Lets do a local mercator grid
g = salem.mercator_grid(center_ll=(10.86, 46.85), extent=(27000, 21000))
# And a map accordingly
sm = salem.Map(g, countries=False)
sm.set_topography(get_demo_file('srtm_oetztal.tif'))
# Give this to the plot function
fig, ax = plt.subplots()
graphics.plot_inversion(gdirs, smap=sm, ax=ax, linewidth=1.5, vmax=250)
fig.tight_layout()
return fig
def test_plot_region_inversion():
gdirs = up_to_inversion()
# We prepare for the plot, which needs our own map to proceed.
# Lets do a local mercator grid
g = salem.mercator_grid(center_ll=(10.86, 46.85),
extent=(27000, 21000))
# And a map accordingly
sm = salem.Map(g, countries=False)
sm.set_topography(get_demo_file('srtm_oetztal.tif'))
# Give this to the plot function
fig, ax = plt.subplots()
graphics.plot_inversion(gdirs, smap=sm, ax=ax, linewidth=1.5, vmax=250)
fig.tight_layout()
return fig
def test_workflow(self):
# This is a check that the inversion workflow works fine
# Download the RGI file for the run
# Make a new dataframe of those
rgidf = gpd.read_file(get_demo_file('SouthGlacier.shp'))
# Go - initialize working directories
gdirs = workflow.init_glacier_regions(rgidf)
# Preprocessing tasks
task_list = [
tasks.glacier_masks,
tasks.compute_centerlines,
tasks.initialize_flowlines,
tasks.catchment_area,
tasks.catchment_intersections,
tasks.catchment_width_geom,
tasks.catchment_width_correction,
]
for task in task_list:
execute_entity_task(task, gdirs)
# Climate tasks -- only data IO and tstar interpolation!
execute_entity_task(tasks.process_cru_data, gdirs)
tasks.distribute_t_stars(gdirs)
execute_entity_task(tasks.apparent_mb, gdirs)
# Inversion tasks
execute_entity_task(tasks.prepare_for_inversion, gdirs)
# We use the default parameters for this run
execute_entity_task(tasks.volume_inversion, gdirs, glen_a=cfg.A, fs=0)
execute_entity_task(tasks.filter_inversion_output, gdirs)
df = utils.glacier_characteristics(gdirs)
assert df.inv_thickness_m[0] < 100
if do_plot:
import matplotlib.pyplot as plt
from oggm.graphics import plot_inversion
plot_inversion(gdirs)
plt.show()
def test_workflow(self):
# This is a check that the inversion workflow works fine
# Download the RGI file for the run
# Make a new dataframe of those
rgidf = gpd.read_file(get_demo_file('SouthGlacier.shp'))
# Go - initialize working directories
gdirs = workflow.init_glacier_regions(rgidf)
# Preprocessing tasks
task_list = [
tasks.glacier_masks,
tasks.compute_centerlines,
tasks.initialize_flowlines,
tasks.catchment_area,
tasks.catchment_intersections,
tasks.catchment_width_geom,
tasks.catchment_width_correction,
tasks.process_cru_data,
tasks.local_t_star,
tasks.mu_star_calibration,
]
for task in task_list:
execute_entity_task(task, gdirs)
# Inversion tasks
execute_entity_task(tasks.prepare_for_inversion, gdirs)
# We use the default parameters for this run
execute_entity_task(tasks.mass_conservation_inversion, gdirs)
execute_entity_task(tasks.filter_inversion_output, gdirs)
df = utils.compile_glacier_statistics(gdirs)
assert df.inv_thickness_m[0] < 100
if do_plot:
import matplotlib.pyplot as plt
from oggm.graphics import plot_inversion
plot_inversion(gdirs)
plt.show()
graphics.plot_catchment_width(gdir,
ax=axs[3],
title='',
corrected=True,
add_colorbar=False,
lonlat_contours_kwargs=llkw,
add_scalebar=False)
axs[3].text(xt, yt, 'd', **letkm)
f.delaxes(axs[3].cax)
graphics.plot_inversion(gdir,
ax=axs[4],
title='',
linewidth=1.5,
add_colorbar=False,
vmax=650,
lonlat_contours_kwargs=llkw,
add_scalebar=False)
axs[4].text(xt, yt, 'e', **letkm)
graphics.plot_modeloutput_map(gdir,
ax=axs[5],
modelyr=120,
title='',
linewidth=1.5,
add_colorbar=True,
cbar_ax=axs[5].cax,
vmax=650,
lonlat_contours_kwargs=llkw,
add_scalebar=False)
# For final inversions - no calving
gdirs = [gd for gd in gdirs if 'I:' in gd.name]
col_gdir = [gd for gd in gdirs if 'Columbia' in gd.name]
cfg.PARAMS['calving_rate'] = 0
addt = ' no calving'
tasks.distribute_t_stars(col_gdir)
execute_entity_task(tasks.prepare_for_inversion, col_gdir)
execute_entity_task(tasks.volume_inversion, gdirs)
pdir = os.path.join(PLOTS_DIR, 'out_raw') + '/'
if not os.path.exists(pdir):
os.mkdir(pdir)
for gd in gdirs:
_addt = addt if 'Columbia' in gd.name else ''
graphics.plot_inversion(gd, add_title_comment=_addt)
plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_inv.png')
plt.close()
# V1
distrib = partial(distribute_thickness, how='per_altitude',
add_slope=True,
smooth=True)
execute_entity_task(distrib, gdirs)
pdir = os.path.join(PLOTS_DIR, 'out_dis') + '/'
if not os.path.exists(pdir):
os.mkdir(pdir)
for gd in gdirs:
itmix.write_itmix_ascii(gd, 1)
graphics.plot_distributed_thickness(gd)
plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_d1.png')
# While the above should work always, this here is no piece of fun
execute_entity_task(tasks.random_glacier_evolution, gdirs)
# Write out glacier statistics
df = utils.glacier_characteristics(gdirs)
fpath = os.path.join(cfg.PATHS['working_dir'], 'glacier_char.csv')
df.to_csv(fpath)
# Plots (if you want)
if PLOTS_DIR == '':
exit()
utils.mkdir(PLOTS_DIR)
for gd in gdirs:
bname = os.path.join(PLOTS_DIR, gd.name + '_' + gd.rgi_id + '_')
graphics.plot_googlemap(gd)
plt.savefig(bname + 'ggl.png')
plt.close()
graphics.plot_domain(gd)
plt.savefig(bname + 'dom.png')
plt.close()
graphics.plot_centerlines(gd)
plt.savefig(bname + 'cls.png')
plt.close()
graphics.plot_catchment_width(gd, corrected=True)
plt.savefig(bname + 'w.png')
plt.close()
graphics.plot_inversion(gd)
plt.savefig(bname + 'inv.png')
plt.close()
def test_inversion():
fig, ax = plt.subplots()
gdir = init_hef()
graphics.plot_inversion(gdir, ax=ax)
fig.tight_layout()
return fig
def test_inversion():
gdir = init_hef()
graphics.plot_inversion(gdir)
def test_inversion():
gdir = init_hef()
graphics.plot_inversion(gdir)
cbar_location="left",
cbar_mode="each",
cbar_size="7%",
cbar_pad=1.5,
aspect=True)
graphics.plot_centerlines(gdirs[1], ax=grid2[0], title='', add_colorbar=True,
lonlat_contours_kwargs=llkw,
cbar_ax=grid2[0].cax, add_scalebar=True)
grid2[0].text(xt, yt, 'b', **letkm)
graphics.plot_inversion(gdirs[1], ax=grid2[1], title='', add_colorbar=True,
linewidth=2, lonlat_contours_kwargs=llkw,
cbar_ax=grid2[1].cax,
add_scalebar=False)
grid2[1].text(xt, yt, 'd', **letkm)
grid2.axes_all
plt.tight_layout()
#plt.show()
plt.savefig(os.path.join(plot_path,'workflow_together.pdf'),
dpi=150, bbox_inches='tight')
title='',
linewidth=2,
add_colorbar=False,
vmax=1600,
lonlat_contours_kwargs=llkw,
add_scalebar=False)
xt, yt = 2.45, 2.45
xvol, yvol = 185, 2.45
axs[0].text(xt, yt, 'a', **letkm)
axs[0].text(xvol, yvol, '{:.2f} km$^3$'.format(total_vol), **letkm)
graphics.plot_inversion(gdir,
ax=axs[1],
title='',
linewidth=2,
add_colorbar=True,
vmax=1600,
lonlat_contours_kwargs=llkw,
cbar_ax=axs[1].cax,
add_scalebar=True)
axs[1].text(xt, yt, 'b', **letkm)
axs[1].text(xvol, yvol, '{:.2f} km$^3$'.format(total_vol_c), **letkm)
plt.tight_layout()
#plt.show()
plt.savefig(os.path.join(plot_path, 'inversion_columbia.pdf'),
dpi=150,
bbox_inches='tight')
# figure 3 -------------
Plot_fig_3 = True
z = sm.set_topography('/home/mowglie/disk/OGGM_INPUT/tmp/ISL.tif')
sm.set_data(z)
# Figs
f = 0.9
f, axs = plt.subplots(2, 1, figsize=(7*f, 10*f))
graphics.plot_domain(gdirs, ax=axs[0], smap=sm)
sm.set_data()
sm.set_lonlat_contours()
sm.set_geometry()
sm.set_text()
graphics.plot_inversion(gdirs, ax=axs[1], smap=sm,
linewidth=1, add_scalebar=False,
title='', vmax=250)
plt.tight_layout()
plt.savefig(PLOT_DIR + 'iceland.pdf', dpi=150, bbox_inches='tight')
exit(0)
lw = 1
graphics.plot_modeloutput_map(gdirs, smap=sm, filesuffix='_tbias',
modelyr=0, linewidth=lw)
plt.savefig('/home/mowglie/yr000.png', dpi=150)
plt.figure()
sm.set_geometry()
graphics.plot_modeloutput_map(gdirs, smap=sm, filesuffix='_tbias',
modelyr=150, linewidth=lw)
plt.savefig('/home/mowglie/yr150.png', dpi=150)
plt.figure()
for gd in gdirs:
itmix.write_itmix_ascii(gd, 2)
graphics.plot_distributed_thickness(gd)
plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_d2.png')
plt.close()
pdir = PLOTS_DIR
if not os.path.exists(pdir):
os.makedirs(pdir)
for gd in gdirs:
# graphics.plot_googlemap(gd)
# plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_ggl.png')
# plt.close()
# graphics.plot_domain(gd)
# plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_dom.png')
# plt.close()
graphics.plot_centerlines(gd)
plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_cls.png')
plt.close()
graphics.plot_catchment_width(gd, corrected=True)
plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_w.png')
plt.close()
graphics.plot_inversion(gd)
plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_inv.png')
plt.close()
# graphics.plot_distributed_thickness(gd, how='per_altitude')
# plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_dis1.png')
# plt.close()
pass
# For final inversions - no calving
gdirs = [gd for gd in gdirs if 'I:' in gd.name]
col_gdir = [gd for gd in gdirs if 'Columbia' in gd.name]
cfg.PARAMS['calving_rate'] = 0
addt = ' no calving'
tasks.distribute_t_stars(col_gdir)
execute_entity_task(tasks.prepare_for_inversion, col_gdir)
execute_entity_task(tasks.volume_inversion, gdirs)
pdir = os.path.join(PLOTS_DIR, 'out_raw') + '/'
if not os.path.exists(pdir):
os.mkdir(pdir)
for gd in gdirs:
_addt = addt if 'Columbia' in gd.name else ''
graphics.plot_inversion(gd, add_title_comment=_addt)
plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_inv.png')
plt.close()
# V1
distrib = partial(distribute_thickness, how='per_altitude',
add_slope=True,
smooth=True)
execute_entity_task(distrib, gdirs)
pdir = os.path.join(PLOTS_DIR, 'out_dis') + '/'
if not os.path.exists(pdir):
os.mkdir(pdir)
for gd in gdirs:
itmix.write_itmix_ascii(gd, 1)
graphics.plot_distributed_thickness(gd)
plt.savefig(pdir + gd.name + '_' + gd.rgi_id + '_d1.png')
# print('Calving results:')
# for k in ['calving_front_width', 'calving_flux', 'calving_thick',
# 'calving_free_board']:
# print(k + ':', diags[k])
# if do_plot:
# from oggm import graphics
# import matplotlib.pyplot as plt
# f, (ax1, ax2) = plt.subplots(1, 2)
# graphics.plot_googlemap(gdir, ax=ax1)
# graphics.plot_inversion(gdir, ax=ax2)
# plt.show()
rid = 'RGI60-01.03622'
gdir = oggm_compat.single_flowline_glacier_directory_with_calving(rid,
k_calving=2)
diags = gdir.get_diagnostics()
print('Calving results:')
for k in [
'calving_front_width', 'calving_flux', 'calving_thick',
'calving_free_board'
]:
print(k + ':', diags[k])
do_plot = True
if do_plot:
from oggm import graphics
import matplotlib.pyplot as plt
f, (ax1, ax2) = plt.subplots(1, 2)
graphics.plot_googlemap(gdir, ax=ax1)
graphics.plot_inversion(gdir, ax=ax2)
plt.show()
def test_inversion():
fig, ax = plt.subplots()
gdir = init_hef()
graphics.plot_inversion(gdir, ax=ax)
fig.tight_layout()
return fig
