def _download_geometric_features(self, componentName, objectType,
featureNames):
'''
Determine a list of requested files and download the any that are
missing from the repo
Parameters
----------
componentName : {'bedmap2', 'iceshelves', 'landice', 'natural_earth', 'ocean'}
The component from which to retieve the geometric features
objectType : {'point', 'transect', 'region'}
The type of geometry to load, a point (0D), transect (1D) or region
(2D)
featureNames : list of str
The names of geometric features to read
Returns
-------
fileList : list of str
File names of the features
'''
# Authors
# -------
# Xylar Asay-Davis
try:
os.makedirs(self.cacheLocation)
except OSError:
pass
fileList = []
filesToDownload = []
for featureName in featureNames:
relativePath = _get_file_name(componentName, objectType,
featureName)
fullPath = os.path.join(self.cacheLocation, relativePath)
fileList.append(fullPath)
if not os.path.exists(fullPath):
filesToDownload.append(relativePath)
if len(filesToDownload) > 0:
baseURL = 'https://raw.githubusercontent.com/MPAS-Dev/' \
'geometric_features/{}/geometric_data'.format(
self.remoteBranch)
download_files(filesToDownload, baseURL, self.cacheLocation)
return fileList
def bedmap2_bin_to_netcdf(outFileName):
if os.path.exists(outFileName):
return
fields = [
'bed', 'surface', 'thickness', 'coverage', 'rockmask',
'grounded_bed_uncertainty', 'icemask_grounded_and_shelves'
]
allExist = True
for field in fields:
fileName = 'bedmap2/bedmap2_bin/bedmap2_{}.flt'.format(field)
if not os.path.exists(fileName):
allExist = False
break
if not allExist:
# download
baseURL = 'https://secure.antarctica.ac.uk/data/bedmap2'
fileNames = ['bedmap2_bin.zip']
download_files(fileNames, baseURL, 'bedmap2')
print('Decompressing Bedmap2 data...')
# unzip
with zipfile.ZipFile('bedmap2/bedmap2_bin.zip', 'r') as f:
f.extractall('bedmap2/')
print(' Done.')
print('Converting Bedmap2 to NetCDF...')
ds = xarray.Dataset()
x = numpy.linspace(-3333000., 3333000., 6667)
y = x
ds['x'] = ('x', x)
ds.x.attrs['units'] = 'meters'
ds['y'] = ('y', y)
ds.y.attrs['units'] = 'meters'
ds.attrs['Grid'] = "Datum = WGS84, earth_radius = 6378137., " \
"earth_eccentricity = 0.081819190842621, " \
"falseeasting = -3333000., " \
"falsenorthing = -3333000., " \
"standard_parallel = -71., central_meridien = 0, " \
"EPSG=3031"
ds.attrs['proj'] = "+proj=stere +lat_0=-90 +lat_ts=-71 +lon_0=0 +k=1 " \
"+x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs"
ds.attrs['proj4'] = "+init=epsg:3031"
# Antarctic stereographic
inProj = pyproj.Proj(init='epsg:3031')
# lon/lat
outProj = pyproj.Proj(init='epsg:4326')
X, Y = numpy.meshgrid(x, y)
Lon, Lat = pyproj.transform(inProj, outProj, X, Y)
ds['lon'] = (('y', 'x'), Lon)
ds.lon.attrs['units'] = 'degrees east'
ds['lat'] = (('y', 'x'), Lat)
ds.lat.attrs['units'] = 'degrees north'
# add Bedmap2 data
for fieldName in fields:
fileName = 'bedmap2/bedmap2_bin/bedmap2_{}.flt'.format(fieldName)
with open(fileName, 'r') as f:
field = numpy.fromfile(f, dtype=numpy.float32).reshape(6667, 6667)
# flip the y axis
field = field[::-1, :]
# switch invalid values to be NaN (as expected by xarray)
field[field == -9999.] = numpy.nan
if fieldName == 'rockmask':
# rock mask is zero where rock and -9999 (now NaN) elsewhere
field = numpy.array(numpy.isfinite(field), numpy.float32)
if fieldName == 'icemask_grounded_and_shelves':
# split into separate grounded and floating masks
ds['icemask_grounded'] = \
(('y', 'x'), numpy.array(field == 0, numpy.float32))
ds['icemask_shelves'] = \
(('y', 'x'), numpy.array(field == 1, numpy.float32))
ds['open_ocean_mask'] = \
(('y', 'x'), numpy.array(numpy.isnan(field), numpy.float32))
else:
ds[fieldName] = (('y', 'x'), field)
ds.to_netcdf(outFileName)
print(' Done.')
def get_longest_contour(contourValue, author):
def stereo_to_lon_lat(x, y):
return pyproj.transform(inProj, outProj, x, y)
bathymetryFileName = 'IBCAO_V3_500m_SM.grd.gz'
if not os.path.exists(bathymetryFileName):
print('Downloading IBCAO bathymetry data...')
# download
baseURL = 'https://www.ngdc.noaa.gov/mgg/bathymetry/arctic/grids/version3_0'
download_files([bathymetryFileName], baseURL, './')
print('Decompressing and reading IBCAO bathymetry data...')
infile = gzip.open(bathymetryFileName, 'rb')
tmp = tempfile.NamedTemporaryFile(delete=False)
shutil.copyfileobj(infile, tmp)
infile.close()
tmp.close()
ds = xarray.open_dataset(tmp.name)
os.unlink(tmp.name)
x = ds.x.values
y = ds.y.values
z = ds.z.values
z[(x==numpy.amin(x)) | (x==numpy.amax(x)) |
(y==numpy.amin(y)) | (y==numpy.amax(y))] = 0.0
# plot contours
plt.figure()
cs = plt.contour(x, y, z, (contourValue,))
paths = cs.collections[0].get_paths()
pathLengths = [len(paths[i]) for i in range(len(paths))]
iLongest = numpy.argmax(pathLengths)
p = paths[iLongest]
v = p.vertices
x = v[:, 0]
y = v[:, 1]
# Arctic stereographic
inProj = pyproj.Proj(init='epsg:3995')
# lon/lat
outProj = pyproj.Proj(init='epsg:4326')
lon, lat = pyproj.transform(inProj, outProj, x, y)
poly = shapely.geometry.Polygon([(i[0], i[1]) for i in zip(x, y)])
epsilon = 1e-14
maxY = numpy.amax(y)
wedge = shapely.geometry.Polygon([(epsilon, maxY),
(epsilon**2, epsilon),
(0, epsilon),
(-epsilon**2, epsilon),
(-epsilon, maxY),
(epsilon, maxY)])
difference = poly.difference(wedge)
difference = shapely.ops.transform(stereo_to_lon_lat, difference)
fc = FeatureCollection()
geometry = shapely.geometry.mapping(difference)
# get rid of the wedge again by rounding the coordinates
geometry['coordinates'] = _round_coords(geometry['coordinates'])
fc.add_feature(
{"type": "Feature",
"properties": {"name": "Contour {}".format(contourValue),
"author": author,
"object": 'region',
"component": 'ocean'},
"geometry": geometry})
return fc