def merge(
ctx,
files,
output,
driver,
bounds,
res,
resampling,
nodata,
dtype,
bidx,
overwrite,
precision,
creation_options,
):
"""Copy valid pixels from input files to an output file.
All files must have the same number of bands, data type, and
coordinate reference system.
Input files are merged in their listed order using the reverse
painter's algorithm. If the output file exists, its values will be
overwritten by input values.
Geospatial bounds and resolution of a new output file in the
units of the input file coordinate reference system may be provided
and are otherwise taken from the first input file.
Note: --res changed from 2 parameters in 0.25.
\b
--res 0.1 0.1 => --res 0.1 (square)
--res 0.1 0.2 => --res 0.1 --res 0.2 (rectangular)
"""
from rasterio.merge import merge as merge_tool
output, files = resolve_inout(files=files,
output=output,
overwrite=overwrite)
resampling = Resampling[resampling]
if driver:
creation_options.update(driver=driver)
with ctx.obj["env"]:
merge_tool(
files,
bounds=bounds,
res=res,
nodata=nodata,
dtype=dtype,
indexes=(bidx or None),
resampling=resampling,
dst_path=output,
dst_kwds=creation_options,
)
def mergeRasters(files, outfile):
""" Function takes a given list of file paths and merges to given output file """
print("Beginning merge of :\n\t%s" % ("\n\t".join(files)))
with rio.open(files[0]) as ras:
dtype = ras.read().dtype
print(dtype)
sources = [rio.open(f) for f in files]
merged_array, output_transform = merge_tool(sources)
profile = sources[0].profile
profile['transform'] = output_transform
profile['height'] = merged_array.shape[1]
profile['width'] = merged_array.shape[2]
profile.update(dtype=np.float32)
#print(merged_array.dtype)
#merged_array = merged_array.astype(dtype)
#print(merged_array.dtype)
# print(profile)
print("Writing merged rasters out to %s outfile...")
with rio.open(outfile, 'w', **profile) as dst:
dst.write(merged_array.astype(np.float32))
return outfile
def merge(ctx, files, output, driver, bounds, res, resampling, nodata, bidx,
overwrite, precision, creation_options):
"""Copy valid pixels from input files to an output file.
All files must have the same number of bands, data type, and
coordinate reference system.
Input files are merged in their listed order using the reverse
painter's algorithm. If the output file exists, its values will be
overwritten by input values.
Geospatial bounds and resolution of a new output file in the
units of the input file coordinate reference system may be provided
and are otherwise taken from the first input file.
Note: --res changed from 2 parameters in 0.25.
\b
--res 0.1 0.1 => --res 0.1 (square)
--res 0.1 0.2 => --res 0.1 --res 0.2 (rectangular)
"""
from rasterio.merge import merge as merge_tool
output, files = resolve_inout(files=files,
output=output,
overwrite=overwrite)
resampling = Resampling[resampling] # get integer code for method
with ctx.obj['env']:
datasets = [rasterio.open(f) for f in files]
dest, output_transform = merge_tool(datasets,
bounds=bounds,
res=res,
nodata=nodata,
precision=precision,
indexes=(bidx or None),
resampling=resampling)
profile = datasets[0].profile
profile['transform'] = output_transform
profile['height'] = dest.shape[1]
profile['width'] = dest.shape[2]
profile['driver'] = driver
profile['count'] = dest.shape[0]
if nodata is not None:
profile['nodata'] = nodata
profile.update(**creation_options)
with rasterio.open(output, 'w', **profile) as dst:
dst.write(dest)
# uses the colormap in the first input raster.
try:
colormap = datasets[0].colormap(1)
dst.write_colormap(1, colormap)
except ValueError:
pass
def merge_rasters(*in_paths, out_path):
dest, xform = merge_tool([str(d) for d in in_paths])
with rasterio.open(in_paths[0], "r") as first:
profile = first.profile
profile["transform"] = xform
profile["height"] = dest.shape[1]
profile["width"] = dest.shape[2]
profile["count"] = dest.shape[0]
with rasterio.open(out_path, "w", **profile) as dst:
dst.write(dest)
def merge(ctx, files, output, driver, bounds, res, nodata, bidx, overwrite,
precision, creation_options):
"""Copy valid pixels from input files to an output file.
All files must have the same number of bands, data type, and
coordinate reference system.
Input files are merged in their listed order using the reverse
painter's algorithm. If the output file exists, its values will be
overwritten by input values.
Geospatial bounds and resolution of a new output file in the
units of the input file coordinate reference system may be provided
and are otherwise taken from the first input file.
Note: --res changed from 2 parameters in 0.25.
\b
--res 0.1 0.1 => --res 0.1 (square)
--res 0.1 0.2 => --res 0.1 --res 0.2 (rectangular)
"""
from rasterio.merge import merge as merge_tool
output, files = resolve_inout(
files=files, output=output, overwrite=overwrite)
with ctx.obj['env']:
datasets = [rasterio.open(f) for f in files]
dest, output_transform = merge_tool(datasets, bounds=bounds, res=res,
nodata=nodata, precision=precision,
indexes=(bidx or None))
profile = datasets[0].profile
profile['transform'] = output_transform
profile['height'] = dest.shape[1]
profile['width'] = dest.shape[2]
profile['driver'] = driver
profile['count'] = dest.shape[0]
if nodata is not None:
profile['nodata'] = nodata
profile.update(**creation_options)
with rasterio.open(output, 'w', **profile) as dst:
dst.write(dest)
# uses the colormap in the first input raster.
try:
colormap = datasets[0].colormap(1)
dst.write_colormap(1, colormap)
except ValueError:
pass
def merge(ctx, files, output, driver, bounds, res, nodata, force_overwrite,
precision, creation_options):
"""Copy valid pixels from input files to an output file.
All files must have the same number of bands, data type, and
coordinate reference system.
Input files are merged in their listed order using the reverse
painter's algorithm. If the output file exists, its values will be
overwritten by input values.
Geospatial bounds and resolution of a new output file in the
units of the input file coordinate reference system may be provided
and are otherwise taken from the first input file.
Note: --res changed from 2 parameters in 0.25.
\b
--res 0.1 0.1 => --res 0.1 (square)
--res 0.1 0.2 => --res 0.1 --res 0.2 (rectangular)
"""
from rasterio.merge import merge as merge_tool
verbosity = (ctx.obj and ctx.obj.get('verbosity')) or 1
output, files = resolve_inout(files=files,
output=output,
force_overwrite=force_overwrite)
with Env(CPL_DEBUG=verbosity > 2) as env:
sources = [rasterio.open(f) for f in files]
dest, output_transform = merge_tool(sources,
bounds=bounds,
res=res,
nodata=nodata,
precision=precision)
profile = sources[0].profile
profile.pop('affine')
profile['transform'] = output_transform
profile['height'] = dest.shape[1]
profile['width'] = dest.shape[2]
profile['driver'] = driver
profile.update(**creation_options)
with rasterio.open(output, 'w', **profile) as dst:
dst.write(dest)
def merge_tiles(alldirs, desired_dir, file_patterns, epsg=None):
out_name = 'MOD09GA_{varname}_{date}_HMA{epsg}.tif'.format
print('Merging tiles ...')
for d in bar(alldirs):
gtiffs = glob.glob(os.path.join(os.path.abspath(d), file_patterns))
date = datetime.datetime.strptime(d, 'modscag-historic/%Y/%j')
with rio.Env():
output = out_name(varname=file_patterns.replace('*', '').replace(
'.tif', ''),
date='{:%Y_%m_%d}'.format(date),
epsg='')
sources = [rio.open(f) for f in gtiffs]
data, output_transform = merge_tool(sources)
profile = sources[0].profile
profile.pop('affine')
profile['transform'] = output_transform
profile['height'] = data.shape[1]
profile['width'] = data.shape[2]
profile['driver'] = 'GTiff'
profile['nodata'] = 255
print('Merged Profile:')
print(profile)
with rio.open(os.path.join(desired_dir, output), 'w',
**profile) as dst:
dst.write(data)
if epsg:
try:
reproj_out = out_name(varname=file_patterns.replace(
'*', '').replace('.tif', ''),
date='{:%Y_%m_%d}'.format(date),
epsg='_{}'.format(epsg))
print(output)
reproj_tiff(os.path.join(desired_dir, output),
os.path.join(desired_dir, reproj_out), epsg)
except:
print('Invalid EPSG Code. Go to http://epsg.io/')
if os.path.exists(os.path.join(desired_dir, d)):
shutil.rmtree(os.path.join(desired_dir, d))
shutil.copytree(d, os.path.join(desired_dir, d))
# Cleanup..
shutil.rmtree(os.path.dirname(os.path.dirname(alldirs[0])))
def mergeTile(today, merged, Gtiff_files):
output = os.path.join(merged, '%s.tif' % (today))
with rio.Env():
sources = [rio.open(f) for f in Gtiff_files]
data, output_transform = merge_tool(sources)
profile = sources[0].profile
profile.pop('affine')
profile['transform'] = output_transform
profile['height'] = data.shape[1]
profile['width'] = data.shape[2]
profile['driver'] = 'GTiff'
print(profile)
with rio.open(output, 'w', **profile) as dst:
dst.write(data)
def mergeTile(today, merged, Gtiff_files):
output = os.path.join(merged,'%s.tif' % (today))
with rio.Env():
sources = [rio.open(f) for f in Gtiff_files]
data, output_transform = merge_tool(sources)
profile = sources[0].profile
profile.pop('affine')
profile['transform'] = output_transform
profile['height'] = data.shape[1]
profile['width'] = data.shape[2]
profile['driver'] = 'GTiff'
print(profile)
with rio.open(output, 'w', **profile) as dst:
dst.write(data)
def merge(ctx, files, output, driver, bounds, res, nodata, force_overwrite,
precision, creation_options):
"""Copy valid pixels from input files to an output file.
All files must have the same number of bands, data type, and
coordinate reference system.
Input files are merged in their listed order using the reverse
painter's algorithm. If the output file exists, its values will be
overwritten by input values.
Geospatial bounds and resolution of a new output file in the
units of the input file coordinate reference system may be provided
and are otherwise taken from the first input file.
Note: --res changed from 2 parameters in 0.25.
\b
--res 0.1 0.1 => --res 0.1 (square)
--res 0.1 0.2 => --res 0.1 --res 0.2 (rectangular)
"""
from rasterio.merge import merge as merge_tool
verbosity = (ctx.obj and ctx.obj.get('verbosity')) or 1
output, files = resolve_inout(
files=files, output=output, force_overwrite=force_overwrite)
with Env(CPL_DEBUG=verbosity > 2) as env:
sources = [rasterio.open(f) for f in files]
dest, output_transform = merge_tool(sources, bounds=bounds, res=res,
nodata=nodata, precision=precision)
profile = sources[0].profile
profile.pop('affine')
profile['transform'] = output_transform
profile['height'] = dest.shape[1]
profile['width'] = dest.shape[2]
profile['driver'] = driver
profile.update(**creation_options)
with rasterio.open(output, 'w', **profile) as dst:
dst.write(dest)
def merge_rasters(raster_input_folder, output_raster):
input_files = [os.path.join(raster_input_folder, f)
for f in os.listdir(raster_input_folder)
if os.path.isfile(os.path.join(raster_input_folder, f))]
sources = [rasterio.open(f) for f in input_files]
dest, output_transform = merge_tool(sources)
profile = sources[0].profile
profile.pop('affine')
profile['transform'] = output_transform
profile['height'] = dest.shape[1]
profile['width'] = dest.shape[2]
with rasterio.open(output_raster, 'w', **profile) as dst:
dst.write(dest)
def define_glacier_region(gdir, entity=None):
"""
Very first task: define the glacier's local grid.
Defines the local projection (Transverse Mercator), centered on the
glacier. There is some options to set the resolution of the local grid.
It can be adapted depending on the size of the glacier with::
dx (m) = d1 * AREA (km) + d2 ; clipped to dmax
or be set to a fixed value. See ``params.cfg`` for setting these options.
Default values of the adapted mode lead to a resolution of 50 m for
Hintereisferner, which is approx. 8 km2 large.
After defining the grid, the topography and the outlines of the glacier
are transformed into the local projection. The default interpolation for
the topography is `cubic`.
Parameters
----------
gdir : :py:class:`oggm.GlacierDirectory`
where to write the data
entity : geopandas GeoSeries
the glacier geometry to process
"""
# choose a spatial resolution with respect to the glacier area
dxmethod = cfg.PARAMS['grid_dx_method']
area = gdir.rgi_area_km2
if dxmethod == 'linear':
dx = np.rint(cfg.PARAMS['d1'] * area + cfg.PARAMS['d2'])
elif dxmethod == 'square':
dx = np.rint(cfg.PARAMS['d1'] * np.sqrt(area) + cfg.PARAMS['d2'])
elif dxmethod == 'fixed':
dx = np.rint(cfg.PARAMS['fixed_dx'])
else:
raise ValueError('grid_dx_method not supported: {}'.format(dxmethod))
# Additional trick for varying dx
if dxmethod in ['linear', 'square']:
dx = np.clip(dx, cfg.PARAMS['d2'], cfg.PARAMS['dmax'])
log.debug('%s: area %.2f km, dx=%.1f', gdir.rgi_id, area, dx)
# Make a local glacier map
proj_params = dict(name='tmerc',
lat_0=0.,
lon_0=gdir.cenlon,
k=0.9996,
x_0=0,
y_0=0,
datum='WGS84')
proj4_str = "+proj={name} +lat_0={lat_0} +lon_0={lon_0} +k={k} " \
"+x_0={x_0} +y_0={y_0} +datum={datum}".format(**proj_params)
proj_in = pyproj.Proj("+init=EPSG:4326", preserve_units=True)
proj_out = pyproj.Proj(proj4_str, preserve_units=True)
project = partial(pyproj.transform, proj_in, proj_out)
# transform geometry to map
geometry = shapely.ops.transform(project, entity['geometry'])
geometry = _check_geometry(geometry)
xx, yy = geometry.exterior.xy
# Corners, incl. a buffer of N pix
ulx = np.min(xx) - cfg.PARAMS['border'] * dx
lrx = np.max(xx) + cfg.PARAMS['border'] * dx
uly = np.max(yy) + cfg.PARAMS['border'] * dx
lry = np.min(yy) - cfg.PARAMS['border'] * dx
# n pixels
nx = np.int((lrx - ulx) / dx)
ny = np.int((uly - lry) / dx)
# Back to lon, lat for DEM download/preparation
tmp_grid = salem.Grid(proj=proj_out,
nxny=(nx, ny),
x0y0=(ulx, uly),
dxdy=(dx, -dx),
pixel_ref='corner')
minlon, maxlon, minlat, maxlat = tmp_grid.extent_in_crs(crs=salem.wgs84)
# save transformed geometry to disk
entity = entity.copy()
entity['geometry'] = geometry
# Avoid fiona bug: https://github.com/Toblerity/Fiona/issues/365
for k, s in entity.iteritems():
if type(s) in [np.int32, np.int64]:
entity[k] = int(s)
towrite = gpd.GeoDataFrame(entity).T
towrite.crs = proj4_str
# Delete the source before writing
if 'DEM_SOURCE' in towrite:
del towrite['DEM_SOURCE']
towrite.to_file(gdir.get_filepath('outlines'))
# Also transform the intersects if necessary
gdf = cfg.PARAMS['intersects_gdf']
gdf = gdf.loc[(gdf.RGIId_1 == gdir.rgi_id) | (gdf.RGIId_2 == gdir.rgi_id)]
if len(gdf) > 0:
gdf = salem.transform_geopandas(gdf, to_crs=proj_out)
if hasattr(gdf.crs, 'srs'):
# salem uses pyproj
gdf.crs = gdf.crs.srs
gdf.to_file(gdir.get_filepath('intersects'))
# Open DEM
source = entity.DEM_SOURCE if hasattr(entity, 'DEM_SOURCE') else None
dem_list, dem_source = get_topo_file((minlon, maxlon), (minlat, maxlat),
rgi_region=gdir.rgi_region,
source=source)
log.debug('%s: DEM source: %s', gdir.rgi_id, dem_source)
# A glacier area can cover more than one tile:
if len(dem_list) == 1:
dem_dss = [rasterio.open(dem_list[0])] # if one tile, just open it
dem_data = rasterio.band(dem_dss[0], 1)
src_transform = dem_dss[0].transform
else:
dem_dss = [rasterio.open(s) for s in dem_list] # list of rasters
dem_data, src_transform = merge_tool(dem_dss) # merged rasters
# Use Grid properties to create a transform (see rasterio cookbook)
dst_transform = rasterio.transform.from_origin(
ulx,
uly,
dx,
dx # sign change (2nd dx) is done by rasterio.transform
)
# Set up profile for writing output
profile = dem_dss[0].profile
profile.update({
'crs': proj4_str,
'transform': dst_transform,
'width': nx,
'height': ny
})
# Could be extended so that the cfg file takes all Resampling.* methods
if cfg.PARAMS['topo_interp'] == 'bilinear':
resampling = Resampling.bilinear
elif cfg.PARAMS['topo_interp'] == 'cubic':
resampling = Resampling.cubic
else:
raise ValueError('{} interpolation not understood'.format(
cfg.PARAMS['topo_interp']))
dem_reproj = gdir.get_filepath('dem')
with rasterio.open(dem_reproj, 'w', **profile) as dest:
dst_array = np.empty((ny, nx), dtype=dem_dss[0].dtypes[0])
reproject(
# Source parameters
source=dem_data,
src_crs=dem_dss[0].crs,
src_transform=src_transform,
# Destination parameters
destination=dst_array,
dst_transform=dst_transform,
dst_crs=proj4_str,
# Configuration
resampling=resampling)
dest.write(dst_array, 1)
for dem_ds in dem_dss:
dem_ds.close()
# Glacier grid
x0y0 = (ulx + dx / 2, uly - dx / 2) # To pixel center coordinates
glacier_grid = salem.Grid(proj=proj_out,
nxny=(nx, ny),
dxdy=(dx, -dx),
x0y0=x0y0)
glacier_grid.to_json(gdir.get_filepath('glacier_grid'))
gdir.write_pickle(dem_source, 'dem_source')
# Looks in the database if the glacier has divides.
gdf = cfg.PARAMS['divides_gdf']
if gdir.rgi_id in gdf.index.values:
divdf = [g for g in gdf.loc[gdir.rgi_id].geometry]
# Reproject the shape
def proj(lon, lat):
return salem.transform_proj(salem.wgs84, gdir.grid.proj, lon, lat)
divdf = [shapely.ops.transform(proj, g) for g in divdf]
# Keep only the ones large enough
log.debug('%s: divide candidates: %d', gdir.rgi_id, len(divdf))
divdf = [g for g in divdf if (g.area >= (25 * dx**2))]
log.debug('%s: number of divides: %d', gdir.rgi_id, len(divdf))
# Write the directories and the files
for i, g in enumerate(divdf):
_dir = os.path.join(gdir.dir, 'divide_{0:0=2d}'.format(i + 1))
if not os.path.exists(_dir):
os.makedirs(_dir)
# File
entity['geometry'] = g
towrite = gpd.GeoDataFrame(entity).T
towrite.crs = proj4_str
towrite.to_file(os.path.join(_dir, cfg.BASENAMES['outlines']))
else:
# Make a single directory and link the files
log.debug('%s: number of divides: %d', gdir.rgi_id, 1)
_dir = os.path.join(gdir.dir, 'divide_01')
if not os.path.exists(_dir):
os.makedirs(_dir)
linkname = os.path.join(_dir, cfg.BASENAMES['outlines'])
sourcename = gdir.get_filepath('outlines')
for ending in ['.cpg', '.dbf', '.shp', '.shx', '.prj']:
_s = sourcename.replace('.shp', ending)
_l = linkname.replace('.shp', ending)
if os.path.exists(_s):
try:
# we are on UNIX
os.link(_s, _l)
except AttributeError:
# we are on windows
copyfile(_s, _l)
def define_nonrgi_glacier_region(gdir: NonRGIGlacierDirectory):
"""
Very first task: define the glacier's local grid.
Defines the local projection (Transverse Mercator), centered on the
glacier. The resolution of the local grid is dx.
After defining the grid, the topography is transformed into the local
projection. The default interpolation for the topography is `cubic`.
Parameters
----------
gdir : :py:class:`oggm.NonRGIGlacierDirectory`
where to write the data
dx : float
grid spacing
"""
xx, yy = gdir.extent_ll
dx = gdir.case.dx
# Make a local glacier map
proj_params = dict(name='tmerc',
lat_0=0.,
lon_0=gdir.cenlon,
k=0.9996,
x_0=0,
y_0=0,
datum='WGS84')
proj4_str = "+proj={name} +lat_0={lat_0} +lon_0={lon_0} +k={k} " \
"+x_0={x_0} +y_0={y_0} +datum={datum}".format(**proj_params)
# proj_in = pyproj.Proj("+init=EPSG:4326", preserve_units=True)
proj_out = pyproj.Proj(proj4_str, preserve_units=True)
merc_xx, merc_yy = salem.transform_proj(salem.wgs84, proj_out, xx, yy)
# Corners, incl. a buffer of N pix
ulx = np.min(merc_xx)
lrx = np.max(merc_xx)
uly = np.max(merc_yy)
lry = np.min(merc_yy)
# n pixels
nx = np.int((lrx - ulx) / dx)
ny = np.int((uly - lry) / dx)
# Back to lon, lat for DEM download/preparation
tmp_grid = salem.Grid(proj=proj_out,
nxny=(nx, ny),
x0y0=(ulx, uly),
dxdy=(dx, -dx),
pixel_ref='corner')
minlon, maxlon, minlat, maxlat = tmp_grid.extent_in_crs(crs=salem.wgs84)
dem_list, dem_source = get_topo_file((minlon, maxlon), (minlat, maxlat),
rgi_region=None,
rgi_subregion=None,
source='DEM3')
log.debug('(%s) DEM source: %s', gdir.name, dem_source)
# A glacier area can cover more than one tile:
if len(dem_list) == 1:
dem_dss = [rasterio.open(dem_list[0])] # if one tile, just open it
dem_data = rasterio.band(dem_dss[0], 1)
if LooseVersion(rasterio.__version__) >= LooseVersion('1.0'):
src_transform = dem_dss[0].transform
else:
src_transform = dem_dss[0].affine
else:
dem_dss = [rasterio.open(s) for s in dem_list] # list of rasters
dem_data, src_transform = merge_tool(dem_dss) # merged rasters
# Use Grid properties to create a transform (see rasterio cookbook)
dst_transform = rasterio.transform.from_origin(
ulx,
uly,
dx,
dx # sign change (2nd dx) is done by rasterio.transform
)
# Set up profile for writing output
profile = dem_dss[0].profile
profile.update({
'crs': proj4_str,
'transform': dst_transform,
'width': nx,
'height': ny
})
# Could be extended so that the cfg file takes all Resampling.* methods
if cfg.PARAMS['topo_interp'] == 'bilinear':
resampling = Resampling.bilinear
elif cfg.PARAMS['topo_interp'] == 'cubic':
resampling = Resampling.cubic
else:
raise ValueError('{} interpolation not understood'.format(
cfg.PARAMS['topo_interp']))
dem_reproj = gdir.get_filepath('dem')
with rasterio.open(dem_reproj, 'w', **profile) as dest:
dst_array = np.empty((ny, nx), dtype=dem_dss[0].dtypes[0])
reproject(
# Source parameters
source=dem_data,
src_crs=dem_dss[0].crs,
src_transform=src_transform,
# Destination parameters
destination=dst_array,
dst_transform=dst_transform,
dst_crs=proj4_str,
# Configuration
resampling=resampling)
# TODO: ugly
if gdir.case.name == 'Borden Peninsula':
print('Anti icepatch used')
dst_array[32, 27] = gdir.case.ela_h - 5
dst_array[:2, -4:] = gdir.case.ela_h - 5
if gdir.case.name == 'Borden Peninsula HR':
print('Anti icepatch HR used')
dst_array[-21:-16, 32:38] = gdir.case.ela_h - 5
dst_array[-8:-2, 88:98] = gdir.case.ela_h - 5
dst_array[:-109, 120:] = gdir.case.ela_h - 5
dest.write(dst_array, 1)
for dem_ds in dem_dss:
dem_ds.close()
# Glacier grid
x0y0 = (ulx + dx / 2, uly - dx / 2) # To pixel center coordinates
glacier_grid = salem.Grid(proj=proj_out,
nxny=(nx, ny),
dxdy=(dx, -dx),
x0y0=x0y0)
glacier_grid.to_json(gdir.get_filepath('glacier_grid'))
# Write DEM source info
source_txt = DEM_SOURCE_INFO.get(dem_source, dem_source)
with open(gdir.get_filepath('dem_source'), 'w') as fw:
fw.write(source_txt)
def define_glacier_region(gdir, entity=None):
"""Very first task: define the glacier's local grid.
Defines the local projection (Transverse Mercator), centered on the
glacier. There is some options to set the resolution of the local grid.
It can be adapted depending on the size of the glacier with::
dx (m) = d1 * AREA (km) + d2 ; clipped to dmax
or be set to a fixed value. See ``params.cfg`` for setting these options.
Default values of the adapted mode lead to a resolution of 50 m for
Hintereisferner, which is approx. 8 km2 large.
After defining the grid, the topography and the outlines of the glacier
are transformed into the local projection. The default interpolation for
the topography is `cubic`.
Parameters
----------
gdir : :py:class:`oggm.GlacierDirectory`
where to write the data
entity : geopandas.GeoSeries
the glacier geometry to process
"""
# Make a local glacier map
proj_params = dict(name='tmerc', lat_0=0., lon_0=gdir.cenlon,
k=0.9996, x_0=0, y_0=0, datum='WGS84')
proj4_str = "+proj={name} +lat_0={lat_0} +lon_0={lon_0} +k={k} " \
"+x_0={x_0} +y_0={y_0} +datum={datum}".format(**proj_params)
proj_in = pyproj.Proj("+init=EPSG:4326", preserve_units=True)
proj_out = pyproj.Proj(proj4_str, preserve_units=True)
project = partial(pyproj.transform, proj_in, proj_out)
# transform geometry to map
geometry = shapely.ops.transform(project, entity['geometry'])
geometry = multi_to_poly(geometry, gdir=gdir)
xx, yy = geometry.exterior.xy
# Save transformed geometry to disk
entity = entity.copy()
entity['geometry'] = geometry
# Avoid fiona bug: https://github.com/Toblerity/Fiona/issues/365
for k, s in entity.iteritems():
if type(s) in [np.int32, np.int64]:
entity[k] = int(s)
towrite = gpd.GeoDataFrame(entity).T
towrite.crs = proj4_str
# Delete the source before writing
if 'DEM_SOURCE' in towrite:
del towrite['DEM_SOURCE']
# Define glacier area to use
area = entity['Area']
# Do we want to use the RGI area or ours?
if not cfg.PARAMS['use_rgi_area']:
area = geometry.area * 1e-6
entity['Area'] = area
towrite['Area'] = area
# Write shapefile
gdir.write_shapefile(towrite, 'outlines')
# Also transform the intersects if necessary
gdf = cfg.PARAMS['intersects_gdf']
if len(gdf) > 0:
gdf = gdf.loc[((gdf.RGIId_1 == gdir.rgi_id) |
(gdf.RGIId_2 == gdir.rgi_id))]
if len(gdf) > 0:
gdf = salem.transform_geopandas(gdf, to_crs=proj_out)
if hasattr(gdf.crs, 'srs'):
# salem uses pyproj
gdf.crs = gdf.crs.srs
gdir.write_shapefile(gdf, 'intersects')
else:
# Sanity check
if cfg.PARAMS['use_intersects']:
raise InvalidParamsError('You seem to have forgotten to set the '
'intersects file for this run. OGGM '
'works better with such a file. If you '
'know what your are doing, set '
"cfg.PARAMS['use_intersects'] = False to "
"suppress this error.")
# 6. choose a spatial resolution with respect to the glacier area
dxmethod = cfg.PARAMS['grid_dx_method']
if dxmethod == 'linear':
dx = np.rint(cfg.PARAMS['d1'] * area + cfg.PARAMS['d2'])
elif dxmethod == 'square':
dx = np.rint(cfg.PARAMS['d1'] * np.sqrt(area) + cfg.PARAMS['d2'])
elif dxmethod == 'fixed':
dx = np.rint(cfg.PARAMS['fixed_dx'])
else:
raise InvalidParamsError('grid_dx_method not supported: {}'
.format(dxmethod))
# Additional trick for varying dx
if dxmethod in ['linear', 'square']:
dx = np.clip(dx, cfg.PARAMS['d2'], cfg.PARAMS['dmax'])
log.debug('(%s) area %.2f km, dx=%.1f', gdir.rgi_id, area, dx)
# Safety check
border = cfg.PARAMS['border']
if border > 1000:
raise InvalidParamsError("You have set a cfg.PARAMS['border'] value "
"of {}. ".format(cfg.PARAMS['border']) +
'This a very large value, which is '
'currently not supported in OGGM.')
# For tidewater glaciers we force border to 10
if gdir.is_tidewater and cfg.PARAMS['clip_tidewater_border']:
border = 10
# Corners, incl. a buffer of N pix
ulx = np.min(xx) - border * dx
lrx = np.max(xx) + border * dx
uly = np.max(yy) + border * dx
lry = np.min(yy) - border * dx
# n pixels
nx = np.int((lrx - ulx) / dx)
ny = np.int((uly - lry) / dx)
# Back to lon, lat for DEM download/preparation
tmp_grid = salem.Grid(proj=proj_out, nxny=(nx, ny), x0y0=(ulx, uly),
dxdy=(dx, -dx), pixel_ref='corner')
minlon, maxlon, minlat, maxlat = tmp_grid.extent_in_crs(crs=salem.wgs84)
# Open DEM
source = entity.DEM_SOURCE if hasattr(entity, 'DEM_SOURCE') else None
dem_list, dem_source = get_topo_file((minlon, maxlon), (minlat, maxlat),
rgi_region=gdir.rgi_region,
rgi_subregion=gdir.rgi_subregion,
source=source)
log.debug('(%s) DEM source: %s', gdir.rgi_id, dem_source)
log.debug('(%s) N DEM Files: %s', gdir.rgi_id, len(dem_list))
# A glacier area can cover more than one tile:
if len(dem_list) == 1:
dem_dss = [rasterio.open(dem_list[0])] # if one tile, just open it
dem_data = rasterio.band(dem_dss[0], 1)
if LooseVersion(rasterio.__version__) >= LooseVersion('1.0'):
src_transform = dem_dss[0].transform
else:
src_transform = dem_dss[0].affine
else:
dem_dss = [rasterio.open(s) for s in dem_list] # list of rasters
dem_data, src_transform = merge_tool(dem_dss) # merged rasters
# Use Grid properties to create a transform (see rasterio cookbook)
dst_transform = rasterio.transform.from_origin(
ulx, uly, dx, dx # sign change (2nd dx) is done by rasterio.transform
)
# Set up profile for writing output
profile = dem_dss[0].profile
profile.update({
'crs': proj4_str,
'transform': dst_transform,
'width': nx,
'height': ny
})
# Could be extended so that the cfg file takes all Resampling.* methods
if cfg.PARAMS['topo_interp'] == 'bilinear':
resampling = Resampling.bilinear
elif cfg.PARAMS['topo_interp'] == 'cubic':
resampling = Resampling.cubic
else:
raise InvalidParamsError('{} interpolation not understood'
.format(cfg.PARAMS['topo_interp']))
dem_reproj = gdir.get_filepath('dem')
profile.pop('blockxsize', None)
profile.pop('blockysize', None)
profile.pop('compress', None)
nodata = dem_dss[0].meta.get('nodata', None)
if source == 'TANDEM' and nodata is None:
# badly tagged geotiffs, let's do it ourselves
nodata = -32767
with rasterio.open(dem_reproj, 'w', **profile) as dest:
dst_array = np.empty((ny, nx), dtype=dem_dss[0].dtypes[0])
reproject(
# Source parameters
source=dem_data,
src_crs=dem_dss[0].crs,
src_transform=src_transform,
src_nodata=nodata,
# Destination parameters
destination=dst_array,
dst_transform=dst_transform,
dst_crs=proj4_str,
dst_nodata=nodata,
# Configuration
resampling=resampling)
dest.write(dst_array, 1)
for dem_ds in dem_dss:
dem_ds.close()
# Glacier grid
x0y0 = (ulx+dx/2, uly-dx/2) # To pixel center coordinates
glacier_grid = salem.Grid(proj=proj_out, nxny=(nx, ny), dxdy=(dx, -dx),
x0y0=x0y0)
glacier_grid.to_json(gdir.get_filepath('glacier_grid'))
# Write DEM source info
gdir.add_to_diagnostics('dem_source', dem_source)
source_txt = DEM_SOURCE_INFO.get(dem_source, dem_source)
with open(gdir.get_filepath('dem_source'), 'w') as fw:
fw.write(source_txt)
fw.write('\n\n')
fw.write('# Data files\n\n')
for fname in dem_list:
fw.write('{}\n'.format(os.path.basename(fname)))
def define_glacier_region(gdir, entity=None):
"""
Very first task: define the glacier's local grid.
Defines the local projection (Transverse Mercator), centered on the
glacier. There is some options to set the resolution of the local grid.
It can be adapted depending on the size of the glacier with::
dx (m) = d1 * AREA (km) + d2 ; clipped to dmax
or be set to a fixed value. See ``params.cfg`` for setting these options.
Default values of the adapted mode lead to a resolution of 50 m for
Hintereisferner, which is approx. 8 km2 large.
After defining the grid, the topography and the outlines of the glacier
are transformed into the local projection. The default interpolation for
the topography is `cubic`.
Parameters
----------
gdir : :py:class:`oggm.GlacierDirectory`
where to write the data
entity : geopandas GeoSeries
the glacier geometry to process
"""
# choose a spatial resolution with respect to the glacier area
dxmethod = cfg.PARAMS['grid_dx_method']
area = gdir.rgi_area_km2
if dxmethod == 'linear':
dx = np.rint(cfg.PARAMS['d1'] * area + cfg.PARAMS['d2'])
elif dxmethod == 'square':
dx = np.rint(cfg.PARAMS['d1'] * np.sqrt(area) + cfg.PARAMS['d2'])
elif dxmethod == 'fixed':
dx = np.rint(cfg.PARAMS['fixed_dx'])
else:
raise ValueError('grid_dx_method not supported: {}'.format(dxmethod))
# Additional trick for varying dx
if dxmethod in ['linear', 'square']:
dx = np.clip(dx, cfg.PARAMS['d2'], cfg.PARAMS['dmax'])
log.debug('%s: area %.2f km, dx=%.1f', gdir.rgi_id, area, dx)
# Make a local glacier map
proj_params = dict(name='tmerc', lat_0=0., lon_0=gdir.cenlon,
k=0.9996, x_0=0, y_0=0, datum='WGS84')
proj4_str = "+proj={name} +lat_0={lat_0} +lon_0={lon_0} +k={k} " \
"+x_0={x_0} +y_0={y_0} +datum={datum}".format(**proj_params)
proj_in = pyproj.Proj("+init=EPSG:4326", preserve_units=True)
proj_out = pyproj.Proj(proj4_str, preserve_units=True)
project = partial(pyproj.transform, proj_in, proj_out)
# transform geometry to map
geometry = shapely.ops.transform(project, entity['geometry'])
geometry = _check_geometry(geometry)
xx, yy = geometry.exterior.xy
# Corners, incl. a buffer of N pix
ulx = np.min(xx) - cfg.PARAMS['border'] * dx
lrx = np.max(xx) + cfg.PARAMS['border'] * dx
uly = np.max(yy) + cfg.PARAMS['border'] * dx
lry = np.min(yy) - cfg.PARAMS['border'] * dx
# n pixels
nx = np.int((lrx - ulx) / dx)
ny = np.int((uly - lry) / dx)
# Back to lon, lat for DEM download/preparation
tmp_grid = salem.Grid(proj=proj_out, nxny=(nx, ny), x0y0=(ulx, uly),
dxdy=(dx, -dx), pixel_ref='corner')
minlon, maxlon, minlat, maxlat = tmp_grid.extent_in_crs(crs=salem.wgs84)
# save transformed geometry to disk
entity = entity.copy()
entity['geometry'] = geometry
# Avoid fiona bug: https://github.com/Toblerity/Fiona/issues/365
for k, s in entity.iteritems():
if type(s) in [np.int32, np.int64]:
entity[k] = int(s)
towrite = gpd.GeoDataFrame(entity).T
towrite.crs = proj4_str
# Delete the source before writing
if 'DEM_SOURCE' in towrite:
del towrite['DEM_SOURCE']
towrite.to_file(gdir.get_filepath('outlines'))
# Also transform the intersects if necessary
gdf = cfg.PARAMS['intersects_gdf']
gdf = gdf.loc[(gdf.RGIId_1 == gdir.rgi_id) | (gdf.RGIId_2 == gdir.rgi_id)]
if len(gdf) > 0:
gdf = salem.transform_geopandas(gdf, to_crs=proj_out)
if hasattr(gdf.crs, 'srs'):
# salem uses pyproj
gdf.crs = gdf.crs.srs
gdf.to_file(gdir.get_filepath('intersects'))
# Open DEM
source = entity.DEM_SOURCE if hasattr(entity, 'DEM_SOURCE') else None
dem_list, dem_source = get_topo_file((minlon, maxlon), (minlat, maxlat),
rgi_region=gdir.rgi_region,
source=source)
log.debug('%s: DEM source: %s', gdir.rgi_id, dem_source)
# A glacier area can cover more than one tile:
if len(dem_list) == 1:
dem_dss = [rasterio.open(dem_list[0])] # if one tile, just open it
dem_data = rasterio.band(dem_dss[0], 1)
if LooseVersion(rasterio.__version__) >= LooseVersion('1.0'):
src_transform = dem_dss[0].transform
else:
src_transform = dem_dss[0].affine
else:
dem_dss = [rasterio.open(s) for s in dem_list] # list of rasters
dem_data, src_transform = merge_tool(dem_dss) # merged rasters
# Use Grid properties to create a transform (see rasterio cookbook)
dst_transform = rasterio.transform.from_origin(
ulx, uly, dx, dx # sign change (2nd dx) is done by rasterio.transform
)
# Set up profile for writing output
profile = dem_dss[0].profile
profile.update({
'crs': proj4_str,
'transform': dst_transform,
'width': nx,
'height': ny
})
# Could be extended so that the cfg file takes all Resampling.* methods
if cfg.PARAMS['topo_interp'] == 'bilinear':
resampling = Resampling.bilinear
elif cfg.PARAMS['topo_interp'] == 'cubic':
resampling = Resampling.cubic
else:
raise ValueError('{} interpolation not understood'
.format(cfg.PARAMS['topo_interp']))
dem_reproj = gdir.get_filepath('dem')
with rasterio.open(dem_reproj, 'w', **profile) as dest:
dst_array = np.empty((ny, nx), dtype=dem_dss[0].dtypes[0])
reproject(
# Source parameters
source=dem_data,
src_crs=dem_dss[0].crs,
src_transform=src_transform,
# Destination parameters
destination=dst_array,
dst_transform=dst_transform,
dst_crs=proj4_str,
# Configuration
resampling=resampling)
dest.write(dst_array, 1)
for dem_ds in dem_dss:
dem_ds.close()
# Glacier grid
x0y0 = (ulx+dx/2, uly-dx/2) # To pixel center coordinates
glacier_grid = salem.Grid(proj=proj_out, nxny=(nx, ny), dxdy=(dx, -dx),
x0y0=x0y0)
glacier_grid.to_json(gdir.get_filepath('glacier_grid'))
gdir.write_pickle(dem_source, 'dem_source')
# Looks in the database if the glacier has divides.
gdf = cfg.PARAMS['divides_gdf']
if gdir.rgi_id in gdf.index.values:
div_gdf = gdf.loc[gdir.rgi_id]
# Compute the intersections between them for later bedshapes
gdf_inter = polygon_intersections(div_gdf)
if len(gdf_inter) > 0:
if hasattr(div_gdf.crs, 'srs'):
# salem uses pyproj
gdf_inter.crs = div_gdf.crs.srs
else:
gdf_inter.crs = div_gdf.crs
gdf_inter.to_file(gdir.get_filepath('divides_intersects'))
# Ok go on
divlist = [g for g in div_gdf.geometry]
# Reproject the shape
def proj(lon, lat):
return salem.transform_proj(salem.wgs84, gdir.grid.proj,
lon, lat)
divlist = [shapely.ops.transform(proj, g) for g in divlist]
# Keep only the ones large enough
log.debug('%s: divide candidates: %d', gdir.rgi_id, len(divlist))
divlist = [g for g in divlist if (g.area >= (50 * dx ** 2))]
log.debug('%s: number of divides: %d', gdir.rgi_id, len(divlist))
divlist = np.asarray(divlist)
# Sort them by area
divlist = divlist[np.argsort([g.area for g in divlist])[::-1]]
# Write the directories and the files
for i, g in enumerate(divlist):
_dir = os.path.join(gdir.dir, 'divide_{0:0=2d}'.format(i + 1))
if not os.path.exists(_dir):
os.makedirs(_dir)
# File
entity['geometry'] = g
towrite = gpd.GeoDataFrame(entity).T
towrite.crs = proj4_str
towrite.to_file(os.path.join(_dir, cfg.BASENAMES['outlines']))
else:
# Make a single directory and link the files
log.debug('%s: number of divides: %d', gdir.rgi_id, 1)
_dir = os.path.join(gdir.dir, 'divide_01')
if not os.path.exists(_dir):
os.makedirs(_dir)
linkname = os.path.join(_dir, cfg.BASENAMES['outlines'])
sourcename = gdir.get_filepath('outlines')
for ending in ['.cpg', '.dbf', '.shp', '.shx', '.prj']:
_s = sourcename.replace('.shp', ending)
_l = linkname.replace('.shp', ending)
if os.path.exists(_s):
try:
# we are on UNIX
os.link(_s, _l)
except AttributeError:
# we are on windows
copyfile(_s, _l)
def define_glacier_region(gdir, entity=None):
"""Very first task: define the glacier's local grid.
Defines the local projection (Transverse Mercator), centered on the
glacier. There is some options to set the resolution of the local grid.
It can be adapted depending on the size of the glacier with::
dx (m) = d1 * AREA (km) + d2 ; clipped to dmax
or be set to a fixed value. See ``params.cfg`` for setting these options.
Default values of the adapted mode lead to a resolution of 50 m for
Hintereisferner, which is approx. 8 km2 large.
After defining the grid, the topography and the outlines of the glacier
are transformed into the local projection. The default interpolation for
the topography is `cubic`.
Parameters
----------
gdir : :py:class:`oggm.GlacierDirectory`
where to write the data
entity : geopandas.GeoSeries
the glacier geometry to process
"""
# Make a local glacier map
proj_params = dict(name='tmerc',
lat_0=0.,
lon_0=gdir.cenlon,
k=0.9996,
x_0=0,
y_0=0,
datum='WGS84')
proj4_str = "+proj={name} +lat_0={lat_0} +lon_0={lon_0} +k={k} " \
"+x_0={x_0} +y_0={y_0} +datum={datum}".format(**proj_params)
proj_in = pyproj.Proj("+init=EPSG:4326", preserve_units=True)
proj_out = pyproj.Proj(proj4_str, preserve_units=True)
project = partial(pyproj.transform, proj_in, proj_out)
# transform geometry to map
geometry = shapely.ops.transform(project, entity['geometry'])
geometry = multi_to_poly(geometry, gdir=gdir)
xx, yy = geometry.exterior.xy
# Save transformed geometry to disk
entity = entity.copy()
entity['geometry'] = geometry
# Avoid fiona bug: https://github.com/Toblerity/Fiona/issues/365
for k, s in entity.iteritems():
if type(s) in [np.int32, np.int64]:
entity[k] = int(s)
towrite = gpd.GeoDataFrame(entity).T
towrite.crs = proj4_str
# Delete the source before writing
if 'DEM_SOURCE' in towrite:
del towrite['DEM_SOURCE']
# Define glacier area to use
area = entity['Area']
# Do we want to use the RGI area or ours?
if not cfg.PARAMS['use_rgi_area']:
area = geometry.area * 1e-6
entity['Area'] = area
towrite['Area'] = area
# Write shapefile
gdir.write_shapefile(towrite, 'outlines')
# Also transform the intersects if necessary
gdf = cfg.PARAMS['intersects_gdf']
if len(gdf) > 0:
gdf = gdf.loc[((gdf.RGIId_1 == gdir.rgi_id) |
(gdf.RGIId_2 == gdir.rgi_id))]
if len(gdf) > 0:
gdf = salem.transform_geopandas(gdf, to_crs=proj_out)
if hasattr(gdf.crs, 'srs'):
# salem uses pyproj
gdf.crs = gdf.crs.srs
gdir.write_shapefile(gdf, 'intersects')
else:
# Sanity check
if cfg.PARAMS['use_intersects']:
raise InvalidParamsError('You seem to have forgotten to set the '
'intersects file for this run. OGGM '
'works better with such a file. If you '
'know what your are doing, set '
"cfg.PARAMS['use_intersects'] = False to "
"suppress this error.")
# 6. choose a spatial resolution with respect to the glacier area
dxmethod = cfg.PARAMS['grid_dx_method']
if dxmethod == 'linear':
dx = np.rint(cfg.PARAMS['d1'] * area + cfg.PARAMS['d2'])
elif dxmethod == 'square':
dx = np.rint(cfg.PARAMS['d1'] * np.sqrt(area) + cfg.PARAMS['d2'])
elif dxmethod == 'fixed':
dx = np.rint(cfg.PARAMS['fixed_dx'])
else:
raise InvalidParamsError(
'grid_dx_method not supported: {}'.format(dxmethod))
# Additional trick for varying dx
if dxmethod in ['linear', 'square']:
dx = np.clip(dx, cfg.PARAMS['d2'], cfg.PARAMS['dmax'])
log.debug('(%s) area %.2f km, dx=%.1f', gdir.rgi_id, area, dx)
# Safety check
border = cfg.PARAMS['border']
if border > 1000:
raise InvalidParamsError("You have set a cfg.PARAMS['border'] value "
"of {}. ".format(cfg.PARAMS['border']) +
'This a very large value, which is '
'currently not supported in OGGM.')
# For tidewater glaciers we force border to 10
if gdir.is_tidewater and cfg.PARAMS['clip_tidewater_border']:
border = 10
# Corners, incl. a buffer of N pix
ulx = np.min(xx) - border * dx
lrx = np.max(xx) + border * dx
uly = np.max(yy) + border * dx
lry = np.min(yy) - border * dx
# n pixels
nx = np.int((lrx - ulx) / dx)
ny = np.int((uly - lry) / dx)
# Back to lon, lat for DEM download/preparation
tmp_grid = salem.Grid(proj=proj_out,
nxny=(nx, ny),
x0y0=(ulx, uly),
dxdy=(dx, -dx),
pixel_ref='corner')
minlon, maxlon, minlat, maxlat = tmp_grid.extent_in_crs(crs=salem.wgs84)
# Open DEM
source = entity.DEM_SOURCE if hasattr(entity, 'DEM_SOURCE') else None
dem_list, dem_source = get_topo_file((minlon, maxlon), (minlat, maxlat),
rgi_region=gdir.rgi_region,
rgi_subregion=gdir.rgi_subregion,
source=source)
log.debug('(%s) DEM source: %s', gdir.rgi_id, dem_source)
log.debug('(%s) N DEM Files: %s', gdir.rgi_id, len(dem_list))
# A glacier area can cover more than one tile:
if len(dem_list) == 1:
dem_dss = [rasterio.open(dem_list[0])] # if one tile, just open it
dem_data = rasterio.band(dem_dss[0], 1)
if LooseVersion(rasterio.__version__) >= LooseVersion('1.0'):
src_transform = dem_dss[0].transform
else:
src_transform = dem_dss[0].affine
else:
dem_dss = [rasterio.open(s) for s in dem_list] # list of rasters
dem_data, src_transform = merge_tool(dem_dss) # merged rasters
# Use Grid properties to create a transform (see rasterio cookbook)
dst_transform = rasterio.transform.from_origin(
ulx,
uly,
dx,
dx # sign change (2nd dx) is done by rasterio.transform
)
# Set up profile for writing output
profile = dem_dss[0].profile
profile.update({
'crs': proj4_str,
'transform': dst_transform,
'width': nx,
'height': ny
})
# Could be extended so that the cfg file takes all Resampling.* methods
if cfg.PARAMS['topo_interp'] == 'bilinear':
resampling = Resampling.bilinear
elif cfg.PARAMS['topo_interp'] == 'cubic':
resampling = Resampling.cubic
else:
raise InvalidParamsError('{} interpolation not understood'.format(
cfg.PARAMS['topo_interp']))
dem_reproj = gdir.get_filepath('dem')
profile.pop('blockxsize', None)
profile.pop('blockysize', None)
profile.pop('compress', None)
nodata = dem_dss[0].meta.get('nodata', None)
if source == 'TANDEM' and nodata is None:
# badly tagged geotiffs, let's do it ourselves
nodata = -32767
with rasterio.open(dem_reproj, 'w', **profile) as dest:
dst_array = np.empty((ny, nx), dtype=dem_dss[0].dtypes[0])
reproject(
# Source parameters
source=dem_data,
src_crs=dem_dss[0].crs,
src_transform=src_transform,
src_nodata=nodata,
# Destination parameters
destination=dst_array,
dst_transform=dst_transform,
dst_crs=proj4_str,
dst_nodata=nodata,
# Configuration
resampling=resampling)
dest.write(dst_array, 1)
for dem_ds in dem_dss:
dem_ds.close()
# Glacier grid
x0y0 = (ulx + dx / 2, uly - dx / 2) # To pixel center coordinates
glacier_grid = salem.Grid(proj=proj_out,
nxny=(nx, ny),
dxdy=(dx, -dx),
x0y0=x0y0)
glacier_grid.to_json(gdir.get_filepath('glacier_grid'))
# Write DEM source info
gdir.add_to_diagnostics('dem_source', dem_source)
source_txt = DEM_SOURCE_INFO.get(dem_source, dem_source)
with open(gdir.get_filepath('dem_source'), 'w') as fw:
fw.write(source_txt)
fw.write('\n\n')
fw.write('# Data files\n\n')
for fname in dem_list:
fw.write('{}\n'.format(os.path.basename(fname)))
