def synth_apparent_mb(gdir, tstar=None, bias=None):
"""Compute local mustar and apparent mb from tstar.
Parameters
----------
gdir : oggm.GlacierDirectory
tstar: int
the year where the glacier should be equilibrium
bias: int
the associated reference bias
"""
# Ok. Looping over divides
for div_id in list(gdir.divide_ids):
log.info('%s: apparent mb synth')
# For each flowline compute the apparent MB
fls = gdir.read_pickle('inversion_flowlines', div_id=div_id)
# Reset flux
for fl in fls:
fl.flux = np.zeros(len(fl.surface_h))
n_g = gdir.rgi_id
searchf = os.path.join(DATA_DIR, 'itmix', 'glaciers_synth', '*')
searchf = os.path.join(searchf, '04_mb_' + n_g + '*.asc')
for dem_f in glob.glob(searchf):
pass
ds_mb = salem.EsriITMIX(dem_f)
mb = ds_mb.get_vardata() * 1000.
mb = np.where(mb < -9998, np.NaN, mb)
f = os.path.join(DATA_DIR, 'itmix', 'glaciers_synth',
'01_margin_' + n_g + '_0000_UTM00.shp')
ds_mb.set_roi(f)
mb = np.where(ds_mb.roi, mb, np.NaN)
searchf = os.path.join(DATA_DIR, 'itmix', 'glaciers_synth', '*')
searchf = os.path.join(searchf, '02_*_' + n_g + '*.asc')
for dem_f in glob.glob(searchf):
pass
ds_dem = salem.EsriITMIX(dem_f)
dem = ds_dem.get_vardata()
from scipy import stats
pok = np.where(np.isfinite(mb) & (mb > 0))
slope_p, _, _, _, _ = stats.linregress(dem[pok], mb[pok])
pok = np.where(np.isfinite(mb) & (mb < 0))
slope_m, _, _, _, _ = stats.linregress(dem[pok], mb[pok])
def ela_mb_grad(ela_h, h):
return np.where(h < ela_h, slope_m * (h - ela_h),
slope_p * (h - ela_h))
# Get all my hs
hs = []
ws = []
for fl in fls:
hs = np.append(hs, fl.surface_h)
ws = np.append(ws, fl.widths)
# find ela for zero mb
def to_optim(x):
tot_mb = np.average(ela_mb_grad(x[0], hs), weights=ws)
return tot_mb**2
opti = optimization.minimize(to_optim, [1000.],
bounds=((0., 10000), ),
tol=1e-6)
# Check results and save.
final_elah = opti['x'][0]
# print(final_elah)
# pok = np.where(np.isfinite(mb))
# plt.plot(dem[pok], mb[pok], 'o')
# plt.plot(hs, ela_mb_grad(final_elah, hs), 'o')
# plt.show()
# Flowlines in order to be sure
# TODO: here it would be possible to test for a minimum mb gradient
# and change prcp factor if judged useful
for fl in fls:
mb_on_h = ela_mb_grad(final_elah, fl.surface_h)
fl.set_apparent_mb(mb_on_h)
# Check
if div_id >= 1:
if not np.allclose(fls[-1].flux[-1], 0., atol=0.01):
log.warning('%s: flux should be zero, but is: %.2f',
gdir.rgi_id, fls[-1].flux[-1])
# Overwrite
gdir.write_pickle(fls, 'inversion_flowlines', div_id=div_id)
def write_itmix_ascii(gdir, version):
"""Write the results"""
gname = gdir.name.replace('I:', '')
real = gname
gname = gname.replace('_A', '')
gname = gname.replace('_B', '')
log.info('Write ITMIX ' + real)
# Get the data
grids_file = gdir.get_filepath('gridded_data', div_id=0)
with netCDF4.Dataset(grids_file) as nc:
thick = nc.variables['thickness'][:]
vol = np.nansum(thick * gdir.grid.dx**2)
# Transform to output grid
try:
ifile = find_path(os.path.join(DATA_DIR, 'itmix', 'glaciers_sorted'),
'02_surface_' + gname + '*.asc')
except AssertionError:
gname = gdir.rgi_id
searchf = os.path.join(DATA_DIR, 'itmix', 'glaciers_synth')
ifile = find_path(searchf, '02_surface_' + gname + '*.asc')
itmix = salem.EsriITMIX(ifile)
thick = itmix.grid.map_gridded_data(thick, gdir.grid, interp='linear')
# Mask out
itmix.set_roi(shape=gdir.get_filepath('outlines'))
omask = itmix.roi
thick[np.nonzero(omask == 0)] = np.nan
# Output path
bname = os.path.basename(ifile).split('.')[0]
pok = bname.find('UTM')
zone = bname[pok:]
ofile = os.path.join(ITMIX_ODIR, gname)
if not os.path.exists(ofile):
os.mkdir(ofile)
fname = 'Maussion_' + real + '_bedrock_v{}_'.format(
version) + zone + '.asc'
ofile = os.path.join(ofile, fname)
# Write out
with rasterio.drivers():
with rasterio.open(ifile) as src:
topo = src.read(1).astype(np.float)
topo = np.where(topo < -999., np.NaN, topo)
# Also for ours
thick = np.where(topo < -999., np.NaN, thick)
# Be sure volume is conserved
thick *= vol / np.nansum(thick * itmix.grid.dx**2)
assert np.isclose(np.nansum(thick * itmix.grid.dx**2), vol)
# convert
topo -= thick
with rasterio.open(ofile,
'w',
driver=src.driver,
width=src.width,
height=src.height,
transform=src.transform,
count=1,
dtype=np.float,
nodata=np.NaN) as dst:
dst.write_band(1, topo)
# Check
with rasterio.open(ifile) as src:
topo = src.read(1).astype(np.float)
topo = np.where(topo < -9999., np.NaN, topo)
with rasterio.open(ofile) as src:
mtopo = src.read(1).astype(np.float)
mtopo = np.where(mtopo < -9999., np.NaN, mtopo)
if not np.allclose(np.nanmax(topo - mtopo), np.nanmax(thick), atol=5):
print(np.nanmax(topo - mtopo), np.nanmax(thick))
f, (ax1, ax2, ax3, ax4) = plt.subplots(1, 4)
ax1.imshow(topo - mtopo)
ax2.imshow(thick)
ax3.imshow(topo - mtopo - thick)
ax4.imshow(~np.isclose(topo - mtopo, thick, atol=1, equal_nan=True))
plt.show()
import salem
from .itmix import find_path
from .itmix_cfg import DATA_DIR, ITMIX_ODIR, PLOTS_DIR
pdir = os.path.join(PLOTS_DIR, 'submitted') + '/'
if not os.path.exists(pdir):
os.mkdir(pdir)
for dgn in glob.glob(os.path.join(ITMIX_ODIR, '*')):
gname = os.path.basename(dgn)
print(gname)
ifile = find_path(os.path.join(DATA_DIR, 'itmix', 'glaciers_sorted'),
'02_surface_' + gname + '*.asc')
ds = salem.EsriITMIX(ifile)
itmix_topo = ds.get_vardata()
ifiles = find_path(ITMIX_ODIR, '*' + gname + '*.asc', allow_more=True)
for ifile in ifiles:
ds2 = salem.EsriITMIX(ifile)
oggm_topo = ds2.get_vardata()
thick = itmix_topo - oggm_topo
cm = salem.Map(ds.grid)
cm.set_plot_params(nlevels=256)
cm.set_cmap(plt.get_cmap('viridis'))
cm.set_data(thick)
cm.visualize()