def asciigrid_to_nc(arcfilename,fileroot):
"""
The main routine that calls the calls other routines to prepare the data
and metadata and create the netCDF file.
"""
# Read ascii grid file
asciihead,asciidata,asciitail = split_asciigrid(arcfilename)
meta = arcasciihdr_to_dict(asciihead)
# Create numpy components
latvec,lonvec,datadict = set_latlon(meta)
data,datadict = asciigrid_to_numpy(asciidata,meta,datadict)
# Resample or edit array
# Add a default no_data value if required.
miss = -999.0
if 'nodata_value' in meta: miss = float(meta['nodata_value'])
datadict['missing'] = miss
#data,latvec,lonvec,datadict = resample_array(data,latvec,lonvec,datadict)
# Prepare time, variable name and metadata
d1,d2,datadict = set_datetime(arcfilename,datadict)
datadict = set_varname(arcfilename,datadict)
attributes = set_attributes(arcfilename,meta,datadict)
# Netcdf options
# http://netcdf4-python.googlecode.com/svn/trunk/docs/netCDF4-module.html
nc_format = 'NETCDF4_CLASSIC'
nc_compress = True
debug = False
# Write netcdf file
if os.path.exists(fileroot+'.nc'): os.remove(fileroot+'.nc')
varname = datadict['varname']
vartype = datadict['datatype']
fillval = datadict['missing']
timevec = [d1]
ncobj = nb.ncopen(fileroot+'.nc','w',format=nc_format)
nb.set_timelatlon(ncobj,None,len(latvec),len(lonvec)) # unlimited time
nb.set_variable(ncobj,varname,dtype=vartype,fill=fillval,zlib=nc_compress)
nb.set_variable(ncobj,'crs',dims=(),dtype="i4") # Grid mapping container
nb.add_time(ncobj,timevec)
nb.add_data(ncobj,'latitude',latvec)
nb.add_data(ncobj,'longitude',lonvec)
if debug:
print varname,data.shape
nb.show_dimensions(ncobj)
# nb.add_data should work but is presently broken. Use direct method
#nb.add_data(ncobj,varname,data)
#ncobj.variables[varname][0,:,:] = data # 2D numpy array
ncobj.variables[varname][:] = data # 3D numpy array
nb.set_attributes(ncobj,attributes)
nb.ncclose(ncobj)
print 'Wrote:',fileroot+'.nc'
# Write metadata to json
if os.path.exists(fileroot+'.json'): os.remove(fileroot+'.json')
jh.json_dump(attributes,fileroot+'.json')
def set_attributes(self, ncdict, delval='DELETE'):
"""
Copy attribute names and values from a dict (or OrderedDict) to a netCDF
object.
Global attributes are keyed in the OrderedDict by the attribute name.
Variable attributes are keyed in the OrderedDict by the variable name and
attribute name separated by a colon, i.e. variable:attribute.
If any value is equal to delval then, if the corresponding attribute exists
in the netCDF object, the corresponding attribute is removed from the
netCDF object. The default value of delval is 'DELETE'. For example,
nc3_set_attributes(self.netcdf_object, {'temperature:missing_value':'DELETE'})
will delete the missing_value attribute from the temperature variable.
A ValueError exception is raised if a key refers to a variable name that
is not defined in the netCDF object.
"""
netcdf_builder.set_attributes(self.netcdf_object, ncdict, delval)
def set_attributes(self, ncdict, delval='DELETE'):
"""
Copy attribute names and values from a dict (or OrderedDict) to a netCDF
object.
Global attributes are keyed in the OrderedDict by the attribute name.
Variable attributes are keyed in the OrderedDict by the variable name and
attribute name separated by a colon, i.e. variable:attribute.
If any value is equal to delval then, if the corresponding attribute exists
in the netCDF object, the corresponding attribute is removed from the
netCDF object. The default value of delval is 'DELETE'. For example,
nc3_set_attributes(self.netcdf_object, {'temperature:missing_value':'DELETE'})
will delete the missing_value attribute from the temperature variable.
A ValueError exception is raised if a key refers to a variable name that
is not defined in the netCDF object.
"""
netcdf_builder.set_attributes(self.netcdf_object, ncdict, delval)
def asciigrid_to_nc(arcfilename, fileroot):
"""
The main routine that calls the calls other routines to prepare the data
and metadata and create the netCDF file.
"""
# Read ascii grid file
asciihead, asciidata, asciitail = split_asciigrid(arcfilename)
meta = arcasciihdr_to_dict(asciihead)
# Create numpy components
latvec, lonvec, datadict = set_latlon(meta)
data, datadict = asciigrid_to_numpy(asciidata, meta, datadict)
# Resample or edit array
# Add a default no_data value if required.
miss = -999.0
if 'nodata_value' in meta: miss = float(meta['nodata_value'])
datadict['missing'] = miss
#data,latvec,lonvec,datadict = resample_array(data,latvec,lonvec,datadict)
# Prepare time, variable name and metadata
d1, d2, datadict = set_datetime(arcfilename, datadict)
datadict = set_varname(arcfilename, datadict)
attributes = set_attributes(arcfilename, meta, datadict)
# Netcdf options
# http://netcdf4-python.googlecode.com/svn/trunk/docs/netCDF4-module.html
nc_format = 'NETCDF4_CLASSIC'
nc_compress = True
debug = False
# Write netcdf file
if os.path.exists(fileroot + '.nc'): os.remove(fileroot + '.nc')
varname = datadict['varname']
vartype = datadict['datatype']
fillval = datadict['missing']
timevec = [d1]
ncobj = nb.ncopen(fileroot + '.nc', 'w', format=nc_format)
nb.set_timelatlon(ncobj, None, len(latvec), len(lonvec)) # unlimited time
nb.set_variable(ncobj,
varname,
dtype=vartype,
fill=fillval,
zlib=nc_compress)
nb.set_variable(ncobj, 'crs', dims=(),
dtype="i4") # Grid mapping container
nb.add_time(ncobj, timevec)
nb.add_data(ncobj, 'latitude', latvec)
nb.add_data(ncobj, 'longitude', lonvec)
if debug:
print varname, data.shape
nb.show_dimensions(ncobj)
# nb.add_data should work but is presently broken. Use direct method
#nb.add_data(ncobj,varname,data)
#ncobj.variables[varname][0,:,:] = data # 2D numpy array
ncobj.variables[varname][:] = data # 3D numpy array
nb.set_attributes(ncobj, attributes)
nb.ncclose(ncobj)
print 'Wrote:', fileroot + '.nc'
# Write metadata to json
if os.path.exists(fileroot + '.json'): os.remove(fileroot + '.json')
jh.json_dump(attributes, fileroot + '.json')
