def plot_inversion(gdirs, ax=None, smap=None, linewidth=3, vmax=None):
"""Plots the result of the inversion out of a glacier directory."""
gdir = gdirs[0]
with netCDF4.Dataset(gdir.get_filepath('gridded_data')) as nc:
topo = nc.variables['topo'][:]
# Dirty optim
try:
smap.set_topography(topo)
except ValueError:
pass
toplot_th = np.array([])
toplot_lines = []
toplot_crs = []
vol = []
for gdir in gdirs:
crs = gdir.grid.center_grid
geom = gdir.read_pickle('geometries')
inv = gdir.read_pickle('inversion_output')
# Plot boundaries
poly_pix = geom['polygon_pix']
smap.set_geometry(poly_pix, crs=crs, fc='none', zorder=2, linewidth=.2)
for l in poly_pix.interiors:
smap.set_geometry(l, crs=crs, color='black', linewidth=0.5)
# plot Centerlines
cls = gdir.read_pickle('inversion_flowlines')
for l, c in zip(cls, inv):
smap.set_geometry(l.line,
crs=crs,
color='gray',
linewidth=1.2,
zorder=50)
toplot_th = np.append(toplot_th, c['thick'])
for wi, cur, (n1, n2) in zip(l.widths, l.line.coords, l.normals):
l = shpg.LineString([
shpg.Point(cur + wi / 2. * n1),
shpg.Point(cur + wi / 2. * n2)
])
toplot_lines.append(l)
toplot_crs.append(crs)
vol.extend(c['volume'])
cm = plt.cm.get_cmap('YlOrRd')
dl = salem.DataLevels(cmap=cm,
nlevels=256,
data=toplot_th,
vmin=0,
vmax=vmax)
colors = dl.to_rgb()
for l, c, crs in zip(toplot_lines, colors, toplot_crs):
smap.set_geometry(l, crs=crs, color=c, linewidth=linewidth, zorder=50)
smap.plot(ax)
return dict(cbar_label='Section thickness [m]',
cbar_primitive=dl,
title_comment=' ({:.2f} km3)'.format(np.nansum(vol) * 1e-9))
def plot_region_inversion(gdirs, ax=None, salemmap=None):
"""Plots the result of the inversion for a larger region."""
if ax is None:
ax = plt.gca()
toplot_th = np.array([])
toplot_lines = []
vol = []
crs_list = []
# loop over the directories to get the data
for gdir in gdirs:
crs = gdir.grid.center_grid
for i in gdir.divide_ids:
geom = gdir.read_pickle('geometries', div_id=i)
inv = gdir.read_pickle('inversion_output', div_id=i)
# Plot boundaries
poly_pix = geom['polygon_pix']
salemmap.set_geometry(poly_pix,
crs=crs,
fc='none',
zorder=2,
linewidth=.2)
for l in poly_pix.interiors:
salemmap.set_geometry(l, crs=crs, color='black', linewidth=0.5)
# plot Centerlines
cls = gdir.read_pickle('inversion_flowlines', div_id=i)
for l, c in zip(cls, inv):
salemmap.set_geometry(l.line,
crs=crs,
color='gray',
linewidth=1.2,
zorder=50)
toplot_th = np.append(toplot_th, c['thick'])
for wi, cur, (n1, n2) in zip(l.widths, l.line.coords,
l.normals):
l = shpg.LineString([
shpg.Point(cur + wi / 2. * n1),
shpg.Point(cur + wi / 2. * n2)
])
toplot_lines.append(l)
crs_list.append(crs)
vol.extend(c['volume'])
# plot the data
cm = plt.cm.get_cmap('YlOrRd')
dl = salem.DataLevels(cmap=cm, nlevels=256, data=toplot_th, vmin=0)
colors = dl.to_rgb()
for l, c, crs in zip(toplot_lines, colors, crs_list):
salemmap.set_geometry(l, crs=crs, color=c, linewidth=1, zorder=50)
salemmap.plot(ax)
cb = dl.append_colorbar(ax, "right", size="5%", pad=0.2)
cb.set_label('Section thickness [m]')
def plot_domain_with_gtd(gdirs, ax=None, smap=None):
"""Plot the glacier directory."""
# Files
gdir = gdirs[0]
with netCDF4.Dataset(gdir.get_filepath('gridded_data')) as nc:
topo = nc.variables['topo'][:]
try:
smap.set_data(topo)
except ValueError:
pass
cm = truncate_colormap(colormap.terrain, minval=0.25, maxval=1.0, n=256)
smap.set_cmap(cm)
smap.set_plot_params(nlevels=256)
try:
for gdir in gdirs:
crs = gdir.grid.center_grid
geom = gdir.read_pickle('geometries')
# Plot boundaries
poly_pix = geom['polygon_pix']
smap.set_geometry(poly_pix, crs=crs, fc='white',
alpha=0.3, zorder=2, linewidth=.2)
for l in poly_pix.interiors:
smap.set_geometry(l, crs=crs, color='black', linewidth=0.5)
except FileNotFoundError:
smap.set_shapefile(gdir.get_filepath('outlines'), color='black')
smap.plot(ax)
# Get the ref data
i, j, lon, lat, ref_thick = g2tasks.get_ref_gtd_data(gdir)
grids_file = gdir.get_filepath('gridded_data')
with netCDF4.Dataset(grids_file) as nc:
glacier_mask = nc.variables['glacier_mask'][:]
pok = np.nonzero(glacier_mask[j, i])
assert len(pok[0]) > 0
i, j, ref_thick = i[pok], j[pok], ref_thick[pok]
dl = salem.DataLevels(ref_thick)
ax.scatter(i, j, color=dl.to_rgb(), s=50, edgecolors='k', linewidths=1)
tstr = ' (N: {})'.format(len(ref_thick))
return dict(cbar_label='Alt. [m]', title_comment=tstr)
def plot_modeloutput_map(gdirs,
ax=None,
smap=None,
model=None,
vmax=None,
linewidth=3,
filesuffix='',
modelyr=None):
"""Plots the result of the model output."""
gdir = gdirs[0]
with utils.ncDataset(gdir.get_filepath('gridded_data')) as nc:
topo = nc.variables['topo'][:]
# Dirty optim
try:
smap.set_topography(topo)
except ValueError:
pass
toplot_th = np.array([])
toplot_lines = []
toplot_crs = []
if model is None:
models = []
for gdir in gdirs:
model = FileModel(
gdir.get_filepath('model_run', filesuffix=filesuffix))
model.run_until(modelyr)
models.append(model)
else:
models = utils.tolist(model)
for gdir, model in zip(gdirs, models):
geom = gdir.read_pickle('geometries')
poly_pix = geom['polygon_pix']
crs = gdir.grid.center_grid
smap.set_geometry(poly_pix, crs=crs, fc='none', zorder=2, linewidth=.2)
poly_pix = utils.tolist(poly_pix)
for _poly in poly_pix:
for l in _poly.interiors:
smap.set_geometry(l, crs=crs, color='black', linewidth=0.5)
# plot Centerlines
cls = model.fls
for l in cls:
smap.set_geometry(l.line,
crs=crs,
color='gray',
linewidth=1.2,
zorder=50)
toplot_th = np.append(toplot_th, l.thick)
widths = l.widths.copy()
widths = np.where(l.thick > 0, widths, 0.)
for wi, cur, (n1, n2) in zip(widths, l.line.coords, l.normals):
line = shpg.LineString([
shpg.Point(cur + wi / 2. * n1),
shpg.Point(cur + wi / 2. * n2)
])
toplot_lines.append(line)
toplot_crs.append(crs)
dl = salem.DataLevels(cmap=OGGM_CMAPS['section_thickness'],
data=toplot_th,
vmin=0,
vmax=vmax)
colors = dl.to_rgb()
for l, c, crs in zip(toplot_lines, colors, toplot_crs):
smap.set_geometry(l, crs=crs, color=c, linewidth=linewidth, zorder=50)
smap.plot(ax)
return dict(cbar_label='Section thickness [m]',
cbar_primitive=dl,
title_comment=' -- year: {:d}'.format(np.int64(model.yr)))
def plot_modeloutput_map(gdir, ax=None, salemmap=None, model=None, vmax=None):
"""Plots the result of the model output."""
with netCDF4.Dataset(gdir.get_filepath('gridded_data')) as nc:
topo = nc.variables['topo'][:]
geom = gdir.read_pickle('geometries', div_id=0)
poly_pix = geom['polygon_pix']
ds = salem.GeoDataset(gdir.grid)
mlines = shpg.GeometryCollection([l.line for l in model.fls] + [poly_pix])
ml = mlines.bounds
corners = ((ml[0], ml[1]), (ml[2], ml[3]))
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=RuntimeWarning)
ds.set_subset(corners=corners, margin=10, crs=gdir.grid)
salemmap = salem.Map(ds.grid, countries=False, nx=gdir.grid.nx)
salemmap.set_topography(topo, crs=gdir.grid)
# TODO: center grid or corner grid???
crs = gdir.grid.center_grid
salemmap.set_geometry(poly_pix, crs=crs, fc='none', zorder=2, linewidth=.2)
for l in poly_pix.interiors:
salemmap.set_geometry(l, crs=crs, color='black', linewidth=0.5)
toplot_th = np.array([])
toplot_lines = []
# plot Centerlines
cls = model.fls
for l in cls:
salemmap.set_geometry(l.line,
crs=crs,
color='gray',
linewidth=1.2,
zorder=50)
toplot_th = np.append(toplot_th, l.thick)
widths = l.widths.copy()
widths = np.where(l.thick > 0, widths, 0.)
for wi, cur, (n1, n2) in zip(widths, l.line.coords, l.normals):
l = shpg.LineString([
shpg.Point(cur + wi / 2. * n1),
shpg.Point(cur + wi / 2. * n2)
])
toplot_lines.append(l)
cm = plt.cm.get_cmap('YlOrRd')
dl = salem.DataLevels(cmap=cm,
nlevels=256,
data=toplot_th,
vmin=0,
vmax=vmax)
colors = dl.to_rgb()
for l, c in zip(toplot_lines, colors):
salemmap.set_geometry(l, crs=crs, color=c, linewidth=3, zorder=50)
salemmap.plot(ax)
return dict(cbar_label='Section thickness [m]',
cbar_primitive=dl,
title_comment=' -- year: {:d}'.format(np.int64(model.yr)))
plt.annotate('e)',
xy=(x, 0.32),
xytext=(0, 4),
size=fsiz,
xycoords=('figure fraction', 'figure fraction'),
textcoords='offset points')
plt.tight_layout()
f.subplots_adjust(right=0.89)
# cax = f.add_axes([0.95,0.55,0.025,0.4])
# salem.DataLevels(ds, nlevels=8)
# #kw1=salem.DataLevels.colorbarbase(cax, **kw1)
# mpl.colorbar.ColorbarBase(cax, **kw1)
cax = f.add_axes([0.90, 0.39, 0.017, 0.25])
dl = salem.DataLevels(ds, nlevels=8)
#kw1=salem.DataLevels.colorbarbase(cax, **kw1)
cb1 = mpl.colorbar.ColorbarBase(cax, label='Nocturnal | Afternoon', **kw3)
#dl.set_extend(extend='both')
#cb1.set_ticklabels(['']*6)
#f.colorbar(cax).set_yticklabels(['','','','','',''])
cax = f.add_axes([0.46, 0.07, 0.017, 0.25])
mpl.colorbar.ColorbarBase(cax, label='m', **kw)
cax = f.add_axes([0.9, 0.72, 0.017, 0.25])
mpl.colorbar.ColorbarBase(cax, label='Frequency', **kw2)
plt.savefig(spath + '/scales_map.png', dpi=300)
def plot_inversion(gdirs,
ax=None,
smap=None,
linewidth=3,
vmax=None,
plot_var='thick',
cbar_label='Section thickness (m)',
color_map='YlGnBu'):
"""Plots the result of the inversion out of a glacier directory.
Default is thickness (m). Change plot_var to u_surface or u_integrated
for velocity (m/yr)."""
gdir = gdirs[0]
with utils.ncDataset(gdir.get_filepath('gridded_data')) as nc:
topo = nc.variables['topo'][:]
# Dirty optim
try:
smap.set_topography(topo)
except ValueError:
pass
toplot_var = np.array([])
toplot_lines = []
toplot_crs = []
vol = []
for gdir in gdirs:
crs = gdir.grid.center_grid
geom = gdir.read_pickle('geometries')
inv = gdir.read_pickle('inversion_output')
# Plot boundaries
poly_pix = geom['polygon_pix']
smap.set_geometry(poly_pix, crs=crs, fc='none', zorder=2, linewidth=.2)
for l in poly_pix.interiors:
smap.set_geometry(l, crs=crs, color='black', linewidth=0.5)
# Plot Centerlines
cls = gdir.read_pickle('inversion_flowlines')
for l, c in zip(cls, inv):
smap.set_geometry(l.line,
crs=crs,
color='gray',
linewidth=1.2,
zorder=50)
toplot_var = np.append(toplot_var, c[plot_var])
for wi, cur, (n1, n2) in zip(l.widths, l.line.coords, l.normals):
line = shpg.LineString([
shpg.Point(cur + wi / 2. * n1),
shpg.Point(cur + wi / 2. * n2)
])
toplot_lines.append(line)
toplot_crs.append(crs)
vol.extend(c['volume'])
dl = salem.DataLevels(cmap=plt.get_cmap(color_map),
data=toplot_var,
vmin=0,
vmax=vmax)
colors = dl.to_rgb()
for l, c, crs in zip(toplot_lines, colors, toplot_crs):
smap.set_geometry(l, crs=crs, color=c, linewidth=linewidth, zorder=50)
smap.plot(ax)
out = dict(cbar_label=cbar_label, cbar_primitive=dl)
if plot_var == 'thick':
out['title_comment'] = ' ({:.2f} km3)'.format(np.nansum(vol) * 1e-9)
return out
