def test_plot_region_model():
gdirs = random_for_plot()
dfc = utils.compile_task_log(gdirs, task_names=['run_random_climate_plot'])
assert np.all(dfc['run_random_climate_plot'] == 'SUCCESS')
# 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_modeloutput_map(gdirs,
smap=sm,
ax=ax,
filesuffix='_plot',
vmax=250,
modelyr=10,
linewidth=1.5)
fig.tight_layout()
return fig
def plot_googlemap(gdir, ax=None):
"""Plots the glacier over a googlemap."""
# TODO: center grid or corner grid???
crs = gdir.grid.center_grid
dofig = False
if ax is None:
fig = plt.figure()
ax = fig.add_subplot(111)
dofig = True
s = salem.read_shapefile(gdir.get_filepath('outlines'))
gm = salem.GoogleVisibleMap(np.array(s.geometry[0].exterior.xy[0]),
np.array(s.geometry[0].exterior.xy[1]),
crs=s.crs,
key='AIzaSyDWG_aTgfU7CeErtIzWfdGxpStTlvDXV_o')
img = gm.get_vardata()
cmap = salem.Map(gm.grid, countries=False, nx=gm.grid.nx)
cmap.set_rgb(img)
cmap.set_shapefile(gdir.get_filepath('outlines'))
cmap.plot(ax)
title = gdir.rgi_id
if gdir.name is not None and gdir.name != '':
title += ': ' + gdir.name
ax.set_title(title)
if dofig:
plt.tight_layout()
def newplotfunc(gdir,
ax=None,
add_colorbar=True,
title=None,
title_comment=None,
horizontal_colorbar=False,
lonlat_contours_kwargs=None,
**kwargs):
dofig = False
if ax is None:
fig = plt.figure()
ax = fig.add_subplot(111)
dofig = True
mp = salem.Map(gdir.grid, countries=False, nx=gdir.grid.nx)
if lonlat_contours_kwargs is not None:
mp.set_lonlat_contours(**lonlat_contours_kwargs)
out = plotfunc(gdir, ax=ax, salemmap=mp, **kwargs)
if add_colorbar and 'cbar_label' in out:
cbprim = out.get('cbar_primitive', mp)
if horizontal_colorbar:
cb = cbprim.append_colorbar(ax, "bottom", size="5%", pad=0.4)
else:
cb = cbprim.append_colorbar(ax, "right", size="5%", pad=0.2)
cb.set_label(out['cbar_label'])
if title is None:
if 'title' not in out:
# Make a defaut one
title = gdir.rgi_id
if gdir.name is not None and gdir.name != '':
title += ': ' + gdir.name
out['title'] = title
if title_comment is None:
title_comment = out.get('title_comment', '')
out['title'] += title_comment
ax.set_title(out['title'])
else:
ax.set_title(title)
if dofig:
plt.tight_layout()
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 plot_googlemap(gdirs, ax=None, figsize=None):
"""Plots the glacier(s) over a googlemap."""
dofig = False
if ax is None:
fig = plt.figure(figsize=figsize)
ax = fig.add_subplot(111)
dofig = True
gdirs = utils.tolist(gdirs)
xx, yy = [], []
for gdir in gdirs:
xx.extend(gdir.extent_ll[0])
yy.extend(gdir.extent_ll[1])
gm = salem.GoogleVisibleMap(xx,
yy,
key='AIzaSyDWG_aTgfU7CeErtIzWfdGxpStTlvDXV_o')
img = gm.get_vardata()
cmap = salem.Map(gm.grid, countries=False, nx=gm.grid.nx)
cmap.set_rgb(img)
for gdir in gdirs:
cmap.set_shapefile(gdir.read_shapefile('outlines'))
cmap.plot(ax)
title = ''
if len(gdirs) == 1:
title = gdir.rgi_id
if gdir.name is not None and gdir.name != '':
title += ': ' + gdir.name
ax.set_title(title)
if dofig:
plt.tight_layout()
# read the lake shapefile (data from http://www.naturalearthdata.com)
lakes = salem.read_shapefile(salem.get_demo_file('ne_50m_lakes.shp'),
cached=True)
# The default is to keep only the pixels which center is within the polygon:
mask_default = grid.region_of_interest(shape=oceans)
mask_default = grid.region_of_interest(shape=lakes, roi=mask_default)
# But we can also compute a mask from all touched pixels
mask_all_touched = grid.region_of_interest(shape=oceans, all_touched=True)
mask_all_touched = grid.region_of_interest(shape=lakes,
all_touched=True,
roi=mask_all_touched)
# Make a map to check our results
sm = salem.Map(grid, countries=False)
sm.set_shapefile(oceans, edgecolor='k', facecolor='none', linewidth=2)
sm.set_shapefile(lakes, edgecolor='k', facecolor='none', linewidth=2)
sm.set_plot_params(cmap='Blues', vmax=2)
# prepare the figure
f, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 3))
# plot 1
sm.set_data(mask_default)
sm.visualize(ax=ax1, addcbar=False, title='Default')
# plot 2
sm.set_data(mask_all_touched)
sm.visualize(ax=ax2, addcbar=False, title='All touched')
# plot!
def newplotfunc(gdirs,
ax=None,
smap=None,
add_colorbar=True,
title=None,
title_comment=None,
horizontal_colorbar=False,
lonlat_contours_kwargs=None,
cbar_ax=None,
autosave=False,
add_scalebar=True,
figsize=None,
savefig=None,
savefig_kwargs=None,
**kwargs):
dofig = False
if ax is None:
fig = plt.figure(figsize=figsize)
ax = fig.add_subplot(111)
dofig = True
# Cast to list
gdirs = utils.tolist(gdirs)
if smap is None:
mp = salem.Map(gdirs[0].grid, countries=False, nx=gdirs[0].grid.nx)
else:
mp = smap
if lonlat_contours_kwargs is not None:
mp.set_lonlat_contours(**lonlat_contours_kwargs)
if add_scalebar:
mp.set_scale_bar()
out = plotfunc(gdirs, ax=ax, smap=mp, **kwargs)
if add_colorbar and 'cbar_label' in out:
cbprim = out.get('cbar_primitive', mp)
if cbar_ax:
cb = cbprim.colorbarbase(cbar_ax)
else:
if horizontal_colorbar:
cb = cbprim.append_colorbar(ax,
"bottom",
size="5%",
pad=0.4)
else:
cb = cbprim.append_colorbar(ax,
"right",
size="5%",
pad=0.2)
cb.set_label(out['cbar_label'])
if title is None:
if 'title' not in out:
# Make a defaut one
title = ''
if len(gdirs) == 1:
gdir = gdirs[0]
title = gdir.rgi_id
if gdir.name is not None and gdir.name != '':
title += ': ' + gdir.name
out['title'] = title
if title_comment is None:
title_comment = out.get('title_comment', '')
out['title'] += title_comment
ax.set_title(out['title'])
else:
ax.set_title(title)
if dofig:
plt.tight_layout()
if autosave:
savefig = os.path.join(cfg.PATHS['working_dir'], 'plots')
utils.mkdir(savefig)
savefig = os.path.join(
savefig, plotfunc.__name__ + '_' + gdirs[0].rgi_id + '.png')
if savefig is not None:
plt.savefig(savefig, **savefig_kwargs)
plt.close()
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)))
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()
pname = os.path.basename(ifile).split('.')[0]
plt.savefig(os.path.join(pdir, pname) + '.png')
plt.close()
size_x=400,
size_y=400)
ggl_img = g.get_vardata()
# Get each level draining into the lake, then into the last level, and so on
gds = []
prev_id = [gdf.iloc[0].MAIN_BAS]
while True:
gd = gdf.loc[gdf.NEXT_DOWN.isin(prev_id)]
if len(gd) == 0:
break
gds.append(gd)
prev_id = gd.HYBAS_ID.unique()
# make a map of the same size as the image
sm = salem.Map(g.grid, factor=1)
sm.set_rgb(ggl_img) # add the background rgb image
# add all the draining basins
cmap = plt.get_cmap('Blues')
for i, gd in enumerate(gds):
# here we use a trick. set_shapefile uses PatchCollections internally,
# which is fast but does not support legend labels.
# so we use set_geometry instead:
for g, geo in enumerate(gd.geometry):
# we don't want more than one label per level
label = 'Level {:02d}'.format(i + 1) if g == 0 else None
sm.set_geometry(geo,
facecolor=cmap(i / (len(gds) - 1)),
alpha=0.8,
label=label)
filesuffix='_tbias')
utils.compile_run_output(gdirs, filesuffix='_defaults')
utils.compile_run_output(gdirs, filesuffix='_tbias')
# ds = xr.open_dataset(os.path.join(base_dir, 'run_output_defaults.nc'))
# (ds.volume.sum(dim='rgi_id') * 1e-9).plot()
# plt.show()
# exit()
# We prepare for the plot, which needs our own map to proceed.
# Lets do a local mercator grid
g = salem.mercator_grid(center_ll=(-19.61, 63.63),
extent=(18000, 14500))
# And a map accordingly
sm = salem.Map(g, countries=False)
sm.set_lonlat_contours(add_xtick_labels=False)
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()
# -*- coding: utf-8 -*-
"""
==============================
Add a Natural Earth background
==============================
An alternative to Google Static Maps
"""
import salem
import matplotlib.pyplot as plt
# get the map from a predefined grid
grid = salem.mercator_grid(transverse=False,
center_ll=(16., 0.),
extent=(8e6, 9e6))
smap = salem.Map(grid)
# Add the background (other resolutions include: 'mr', 'hr')
smap.set_rgb(natural_earth='lr')
# done!
smap.visualize()
plt.show()
# create the correct projection
x0 = -4e5
y0 = -5e5
pwrf = '+proj=lcc +lat_1={:2.5f} +lat_2={:2.5f} ' \
'+lat_0={:2.5f} +lon_0={:2.5f} ' \
'+x_0={:f} +y_0={:f}'.format(lat1,lat2,lat0,lonc,0,0)
grid = salem.Grid(nxny=(nx, ny), x0y0=(x0, y0), dxdy=(dx, dy), proj=pwrf)
lon1d = np.min(grid.ll_coordinates[0])
lon2d = np.max(grid.ll_coordinates[0])
lat1d = np.min(grid.ll_coordinates[1])
lat2d = np.max(grid.ll_coordinates[1])
# output an overview of the topography
sm = salem.Map(grid)
if preview:
print ' * approximate boundaries (WESN):{:3.0f},{:3.0f},{:3.0f},{:3.0f}'.format(
lon1d, lon2d, lat1d, lat2d)
if plots:
sm.visualize()
print ' creating preview file...'
plt.savefig('./{:s}_preview.pdf'.format(name))
sys.exit(0)
else:
print ' * {:3.1f}N to {:3.1f}N and {:3.1f}W to {:3.1f}W at {:2.1f}m x {:2.1f}m as {:s}'.format(
lon1d, lat1d, lon2d, lat2d, dx, dy, name)
script_path = os.path.dirname(os.path.realpath(__file__))
# calculate an average dlon and dlat to decided which data source to use
