def test_nansat_reproject(self):
if len(self.test_data.asar)==0:
raise IOError('No ASAR data - try adding some as ' \
'described in templates/openwind_local_archive.py' )
asar = Nansat(self.test_data.asar[0])
asar.resize(pixelsize=500, eResampleAlg=1)
mw = Nansat(self.test_data.ncep4asar[0])
mw.reproject(asar, eResampleAlg=1)
if sys.version_info < (2, 7):
type(mw[1]) == np.ndarray
else:
self.assertIsInstance(mw[1], np.ndarray)
def test_nansat_reproject(self):
if len(self.test_data.asar) == 0:
raise IOError('No ASAR data - try adding some as ' \
'described in templates/openwind_local_archive.py' )
asar = Nansat(self.test_data.asar['agulhas'])
asar.resize(pixelsize=500, eResampleAlg=1)
mw = Nansat(self.test_data.ncep4asar['agulhas'])
mw.reproject(asar, eResampleAlg=1)
if sys.version_info < (2, 7):
type(mw[1]) == np.ndarray
else:
self.assertIsInstance(mw[1], np.ndarray)
def resize(self, rsfile):
sys.stderr.write('\nresize:'+rsfile+'\n')
n = Nansat(rsfile)
inc_max = float(n.get_metadata()['FAR_RANGE_INCIDENCE_ANGLE'])+0.5
n.resize(0.5, eResampleAlg=0)
assert (np.nanmax(n['incidence_angle']) <= inc_max)
n.undo()
n.resize(0.5, eResampleAlg=1)
assert (np.nanmax(n['incidence_angle']) <= inc_max)
n.undo()
n.resize(0.5, eResampleAlg=2)
assert (np.nanmax(n['incidence_angle']) <= inc_max)
n.undo()
n.resize(0.5, eResampleAlg=3)
assert (np.nanmax(n['incidence_angle']) <= inc_max)
n.undo()
n.resize(0.5, eResampleAlg=4)
assert (np.nanmax(n['incidence_angle']) <= inc_max)
n.undo()
def resize(self, rsfile):
sys.stderr.write("\nresize:" + rsfile + "\n")
n = Nansat(rsfile)
inc_max = float(n.get_metadata()["FAR_RANGE_INCIDENCE_ANGLE"]) + 0.5
n.resize(0.5, eResampleAlg=0)
assert np.nanmax(n["incidence_angle"]) <= inc_max
n.undo()
n.resize(0.5, eResampleAlg=1)
assert np.nanmax(n["incidence_angle"]) <= inc_max
n.undo()
n.resize(0.5, eResampleAlg=2)
assert np.nanmax(n["incidence_angle"]) <= inc_max
n.undo()
n.resize(0.5, eResampleAlg=3)
assert np.nanmax(n["incidence_angle"]) <= inc_max
n.undo()
n.resize(0.5, eResampleAlg=4)
assert np.nanmax(n["incidence_angle"]) <= inc_max
n.undo()
def resize(self, rsfile):
sys.stderr.write('\nresize:'+rsfile+'\n')
n = Nansat(rsfile)
inc_max = float(n.get_metadata()['FAR_RANGE_INCIDENCE_ANGLE'])+0.5
n.resize(0.5, eResampleAlg=0)
assert (np.nanmax(n['incidence_angle']) <= inc_max)
n.undo()
n.resize(0.5, eResampleAlg=1)
assert (np.nanmax(n['incidence_angle']) <= inc_max)
n.undo()
n.resize(0.5, eResampleAlg=2)
assert (np.nanmax(n['incidence_angle']) <= inc_max)
n.undo()
n.resize(0.5, eResampleAlg=3)
assert (np.nanmax(n['incidence_angle']) <= inc_max)
n.undo()
n.resize(0.5, eResampleAlg=4)
assert (np.nanmax(n['incidence_angle']) <= inc_max)
n.undo()
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)
# set Dataset entry_title
ds.entry_title = 'SAR NRCS'
ds.save()
# Unless reprocess==True, we may not need to do the following... (see
# managers.py in sar doppler processor)
#visExists = ... # check if visualization(s) already created
#if visExists and not reprocess:
# warnings.warn('NO VISUALISATIONS CREATED - update managers.py')
# return ds, created
n = Nansat(nansat_filename(uri))
n.reproject_GCPs()
n.resize(pixelsize=500)
lon, lat = n.get_corners()
lat_max = min(lat.max(), 85)
d = Domain(
NSR(3857), '-lle %f %f %f %f -ts %d %d' %
(lon.min(), lat.min(), lon.max(), lat_max, n.shape()[1],
n.shape()[0]))
# Get all NRCS bands
s0bands = []
pp = []
for key, value in n.bands().iteritems():
try:
if value['standard_name'] == standard_name:
s0bands.append(key)
pp.append(value['polarization'])
except KeyError:
continue
''' Create data products
'''
mm = self.__module__.split('.')
module = '%s.%s' % (mm[0], mm[1])
mp = media_path(module, n.fileName)
# ppath = product_path(module, n.fileName)
# Create png's for each band
num_products = 0
for band in s0bands:
print 'Visualize', band
s0_tmp = n[band]
n_tmp = Nansat(domain=n, array=s0_tmp)
n_tmp.reproject_GCPs()
n_tmp.reproject(d)
s0 = n_tmp[1]
n_tmp = None
mask = np.ones(s0.shape, np.uint8)
mask[np.isnan(s0) + (s0 <= 0)] = 0
s0 = np.log10(s0) * 10.
meta = n.bands()[band]
product_filename = '%s_%s.png' % (meta['short_name'],
meta['polarization'])
nansatFigure(s0, mask, polarization_clims[meta['polarization']][0],
polarization_clims[meta['polarization']][1], mp,
product_filename)
# Get DatasetParameter
param = Parameter.objects.get(short_name=meta['short_name'])
dsp, created = DatasetParameter.objects.get_or_create(
dataset=ds, parameter=param)
# 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, product_filename),
title='%s %s polarization' %
(param.standard_name, meta['polarization']),
geographic_location=geom)
# Create VisualizationParameter
vp, created = VisualizationParameter.objects.get_or_create(
visualization=vv, ds_parameter=dsp)
return ds, True
