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
from nansat.nansat import Nansat, Domain
iFileName = os.path.join(home,
'python/nansat/nansat/tests/data/gcps.tif')
# Open an input satellite image with Nansat
n = Nansat(iFileName)
# List bands and georeference of the object
print n
# Write picture with map of the file location
n.write_map('map.png')
# Write indexed picture with data from the first band
n.write_figure('rgb.png', clim='hist')
# Reproject input image onto map of Norwegian Coast
# 1. Create domain describing the desired map
# 2. Transform the original satellite image
# 3. Write the transfromed image into RGB picture
dLatlong = Domain("+proj=latlong +datum=WGS84 +ellps=WGS84 +no_defs",
"-te 27 70.2 31 71.5 -ts 2000 2000")
n.reproject(dLatlong)
n.write_figure('pro.png', bands=[1,2,3], clim=[0, 100])
# Export projected satelite image into NetCDF format
n.export('gcps_projected.nc')
# Collect values from interactively drawn transect
# 1. draw transect interactively
