def _get_masked_windspeed(self, landmask=True, icemask=True, windspeedBand="windspeed"):
try:
sar_windspeed = self[windspeedBand]
except:
raise ValueError("SAR wind has not been calculated, " "execute calculate_wind(wind_direction) first.")
sar_windspeed[sar_windspeed < 0] = 0
palette = jet
if landmask:
try: # Land mask
sar_windspeed = np.ma.masked_where(self.watermask()[1] == 2, sar_windspeed)
palette.set_bad([0.3, 0.3, 0.3], 1.0) # Land is masked (bad)
except:
print "Land mask not available"
if icemask:
try: # Ice mask
try: # first try local file
ice = Nansat(
"metno_local_hires_seaice_" + self.SAR_image_time.strftime("%Y%m%d"),
mapperName="metno_local_hires_seaice",
)
except: # otherwise Thredds
ice = Nansat("metno_hires_seaice:" + self.SAR_image_time.strftime("%Y%m%d"))
ice.reproject(self)
iceBandNo = ice._get_band_number({"standard_name": "sea_ice_area_fraction"})
sar_windspeed[ice[iceBandNo] > 0] = -1
palette.set_under("w", 1.0) # Ice is 'under' (-1)
except:
print "Ice mask not available"
return sar_windspeed, palette
def _get_aux_wind_from_str(self, aux_wind_source, *args, **kwargs):
try:
wdir = int(aux_wind_source)
wdir, wdir_time, wspeed = self._get_aux_wind_from_int(wdir)
except ValueError:
import nansat.nansat
mnames = [
key.replace('mapper_', '')
for key in nansat.nansat.nansatMappers
]
# check if aux_wind_source is like 'ncep_wind_online', i.e. only
# mapper name is given. By adding the SAR image time stamp, we
# can then get the data online
if aux_wind_source in mnames:
aux_wind_source = aux_wind_source + \
datetime.strftime(self.SAR_image_time, ':%Y%m%d%H%M')
aux = Nansat(
aux_wind_source,
netcdf_dim={
'time': np.datetime64(self.SAR_image_time),
'height2': '10', # height dimension used in AROME arctic
# datasets
'height3': '10',
},
bands=[ # CF standard names of desired bands
'x_wind',
'y_wind', # or..:
'eastward_wind',
'northward_wind',
])
# Set filename of source wind in metadata
try:
wind_u_bandNo = aux._get_band_number({
'standard_name':
'eastward_wind',
})
except OptionError:
wind_u_bandNo = aux._get_band_number({
'standard_name': 'x_wind',
})
self.set_metadata(
'WIND_DIRECTION_SOURCE',
aux.get_metadata(bandID=wind_u_bandNo)['SourceFilename'])
wdir, wdir_time, wspeed = self._get_wind_direction_array(
aux, *args, **kwargs)
return wdir, wdir_time, wspeed
def export_band(self, rsfile):
sys.stderr.write("\nexport_band:" + rsfile + "\n")
orig = Nansat(rsfile)
ncfile = "test.nc"
orig.export(ncfile, bands=[orig._get_band_number("incidence_angle")])
copy = Nansat(ncfile)
inc0 = orig["incidence_angle"]
inc1 = copy["incidence_angle"]
np.testing.assert_allclose(inc0, inc1)
os.unlink(ncfile)
def export_band(self, rsfile):
sys.stderr.write('\nexport_band:'+rsfile+'\n')
orig = Nansat(rsfile)
ncfile = 'test.nc'
orig.export(ncfile, bands=[orig._get_band_number('incidence_angle')])
copy = Nansat(ncfile)
inc0 = orig['incidence_angle']
inc1 = copy['incidence_angle']
np.testing.assert_allclose(inc0, inc1)
os.unlink(ncfile)
def _get_aux_wind_from_str(self, aux_wind_source, *args, **kwargs):
try:
wdir = int(aux_wind_source)
wdir, wdir_time, wspeed = self._get_aux_wind_from_int(wdir)
except ValueError:
import nansat.nansat
mnames = [key.replace('mapper_','') for key in
nansat.nansat.nansatMappers]
# check if aux_wind_source is like 'ncep_wind_online', i.e. only
# mapper name is given. By adding the SAR image time stamp, we
# can then get the data online
if aux_wind_source in mnames:
aux_wind_source = aux_wind_source + \
datetime.strftime(self.SAR_image_time, ':%Y%m%d%H%M')
aux = Nansat(aux_wind_source, netcdf_dim={
'time': np.datetime64(self.SAR_image_time),
'height2': '10', # height dimension used in AROME arctic
# datasets
'height3': '10',
},
bands = [ # CF standard names of desired bands
'x_wind',
'y_wind', # or..:
'eastward_wind',
'northward_wind',
])
# Set filename of source wind in metadata
try:
wind_u_bandNo = aux._get_band_number({
'standard_name': 'eastward_wind',
})
except OptionError:
wind_u_bandNo = aux._get_band_number({
'standard_name': 'x_wind',
})
self.set_metadata('WIND_DIRECTION_SOURCE',
aux.get_metadata(bandID=wind_u_bandNo)['SourceFilename'])
wdir, wdir_time, wspeed = self._get_wind_direction_array(aux,
*args, **kwargs)
return wdir, wdir_time, wspeed
def _get_masked_windspeed(self,
landmask=True,
icemask=True,
windspeedBand='windspeed'):
try:
sar_windspeed = self[windspeedBand]
except:
raise ValueError('SAR wind has not been calculated, ' \
'execute calculate_wind(wind_direction) first.')
sar_windspeed[sar_windspeed < 0] = 0
palette = jet
if landmask:
try: # Land mask
sar_windspeed = np.ma.masked_where(
self.watermask(tps=True)[1] == 2, sar_windspeed)
palette.set_bad([.3, .3, .3], 1.0) # Land is masked (bad)
except:
print 'Land mask not available'
if icemask:
try: # Ice mask
try: # first try local file
ice = Nansat('metno_local_hires_seaice_' +
self.SAR_image_time.strftime('%Y%m%d'),
mapperName='metno_local_hires_seaice')
except: # otherwise Thredds
ice = Nansat('metno_hires_seaice:' +
self.SAR_image_time.strftime('%Y%m%d'))
ice.reproject(self, tps=True)
iceBandNo = ice._get_band_number(
{'standard_name': 'sea_ice_area_fraction'})
sar_windspeed[ice[iceBandNo] > 0] = -1
palette.set_under('w', 1.0) # Ice is 'under' (-1)
except:
print 'Ice mask not available'
return sar_windspeed, palette
def _get_masked_windspeed(self, landmask=True, icemask=True,
windspeedBand='windspeed'):
try:
sar_windspeed = self[windspeedBand]
except:
raise ValueError('SAR wind has not been calculated, ' \
'execute calculate_wind(wind_direction) first.')
sar_windspeed[sar_windspeed<0] = 0
palette = jet
if landmask:
try: # Land mask
sar_windspeed = np.ma.masked_where(
self.watermask()[1]==2, sar_windspeed)
palette.set_bad([.3, .3, .3], 1.0) # Land is masked (bad)
except:
print 'Land mask not available'
if icemask:
try: # Ice mask
try: # first try local file
ice = Nansat('metno_local_hires_seaice_' +
self.SAR_image_time.strftime('%Y%m%d'),
mapperName='metno_local_hires_seaice')
except: # otherwise Thredds
ice = Nansat('metno_hires_seaice:' +
self.SAR_image_time.strftime('%Y%m%d'))
ice.reproject(self)
iceBandNo = ice._get_band_number(
{'standard_name': 'sea_ice_area_fraction'})
sar_windspeed[ice[iceBandNo]>0] = -1
palette.set_under('w', 1.0) # Ice is 'under' (-1)
except:
print 'Ice mask not available'
return sar_windspeed, palette
def get_or_create(self, uri, reprocess=False, *args, **kwargs):
# ingest file to db
ds, created = super(DatasetManager,
self).get_or_create(uri, *args, **kwargs)
fn = nansat_filename(uri)
n = Nansat(fn)
# Reproject to leaflet projection
xlon, xlat = n.get_corners()
d = Domain(
NSR(3857), '-lle %f %f %f %f -tr 1000 1000' %
(xlon.min(), xlat.min(), xlon.max(), xlat.max()))
n.reproject(d)
# Get band numbers of required bands according to standard names
speedBandNum = n._get_band_number({'standard_name': 'wind_speed'})
dirBandNum = n._get_band_number(
{'standard_name': 'wind_from_direction'})
# Get numpy arrays of the bands
speed = n[speedBandNum]
dir = n[dirBandNum]
## It probably wont work with nansatmap...
#nmap = Nansatmap(n, resolution='l')
#nmap.pcolormesh(speed, vmax=18)
#nmap.quiver(-speed*np.sin(dir), speed*np.cos(dir), step=10, scale=300,
# width=0.002)
# Set paths - this code should be inherited but I think there is an
# issue in generalising the first line that defines the current module
mm = self.__module__.split('.')
module = '%s.%s' % (mm[0], mm[1])
mp = media_path(module, n.fileName)
ppath = product_path(module, n.fileName)
filename = os.path.basename(n.fileName).split('.')[0] + '.' + \
os.path.basename(n.fileName).split('.')[1] + '.png'
# check uniqueness of parameter
param1 = Parameter.objects.get(standard_name=n.get_metadata(
bandID=speedBandNum, key='standard_name'))
param2 = Parameter.objects.get(standard_name=n.get_metadata(
bandID=dirBandNum, key='standard_name'))
n.write_figure(os.path.join(mp, filename),
bands=speedBandNum,
mask_array=n['swathmask'],
mask_lut={0: [128, 128, 128]},
transparency=[128, 128, 128])
# Get DatasetParameter
dsp1, created = DatasetParameter.objects.get_or_create(
dataset=ds, parameter=param1)
# Create Visualization
geom, created = GeographicLocation.objects.get_or_create(
geometry=WKTReader().read(n.get_border_wkt()))
vv, created = Visualization.objects.get_or_create(
uri='file://localhost%s/%s' % (mp, filename),
title='%s' % (param1.standard_name),
geographic_location=geom)
# Create VisualizationParameter
vp, created = VisualizationParameter.objects.get_or_create(
visualization=vv, ds_parameter=dsp1)
return ds, True
