def save_2D(filenameout,var,lat,lon,miss_val):
import numpy as np
from scipy.io.netcdf import netcdf_file as NetCDFFile
n = NetCDFFile(filenameout, 'w',) # open it for writing
n.title = 'saved netcdf variable'
n.createDimension('lat',len(lat))
n.createDimension('lon',len(lon))
latitude = n.createVariable('lat','f',('lat',))
latitude.longname = 'latitude'
latitude.units = 'degrees_north'
latitude[:] = lat.astype(np.float32)
longitude = n.createVariable('lon','f',('lon',))
longitude.longname = 'longitude'
longitude.units = 'degrees_east'
longitude[:] = lon[:].astype(np.float32)
varnc = n.createVariable('varnc','f',('lat','lon',))
varnc.missing_value = np.array(miss_val,np.float32)
varnc.FillValue = np.array(miss_val,np.float32)
varnc[:,:]=var[:,:].astype(np.float32)
n.close()
def save_3D_stack(filenameout, var, varname, lat, lon, miss_val, time_it):
import numpy as np
from scipy.io.netcdf import netcdf_file as NetCDFFile
"""
savenetcdf_3D(filenameout,var,varname,lat,lon,miss_val,time_it)
save a 3D (time,lat,lon) numpy array into netcdf
arguments:
filenameout: string
var: np.array
varname: string
lat: np.array
lon: np.array
miss_val: real
time_it: np.array (dtype=int)
"""
n = NetCDFFile(
filenameout,
'w',
) # open it for writing
n.title = 'saved netcdf variable'
n.createDimension('time', None)
n.createDimension('lat', len(lat))
n.createDimension('lon', len(lon))
latitude = n.createVariable('lat', 'f', ('lat', ))
latitude.longname = 'latitude'
latitude.units = 'degrees_north'
latitude[:] = lat[:].astype(np.float32)
longitude = n.createVariable('lon', 'f', ('lon', ))
longitude.longname = 'longitude'
longitude.units = 'degrees_east'
longitude[:] = lon[:].astype(np.float32)
time = n.createVariable('time', 'i', ('time', ))
time.units = 'days since 1979-1-1 00:00:0.0'
time.delta_t = '0000-00-01 00:00:00'
varnc = n.createVariable(varname, 'f', (
'time',
'lat',
'lon',
))
varnc.missing_value = np.array(miss_val, np.float32)
varnc._FillValue = np.array(miss_val, np.float32)
for l in range(0, var.shape[0]):
time[l] = time_it
varnc[l, :, :] = var[l, :, :].astype(np.float32)
n.close()
def save_3D(filenameout,var,varname,lat,lon,miss_val,time_it):
import numpy as np
from scipy.io.netcdf import netcdf_file as NetCDFFile
"""
savenetcdf_3D(filenameout,var,varname,lat,lon,miss_val,time_it)
save a 3D (time,lat,lon) numpy array into netcdf
arguments:
filenameout: string
var: np.array
varname: string
lat: np.array
lon: np.array
miss_val: real
time_it: np.array (dtype=int)
"""
n = NetCDFFile(filenameout, 'w',) # open it for writing
n.title = 'saved netcdf variable'
n.createDimension('time',None)
n.createDimension('lat',len(lat))
n.createDimension('lon',len(lon))
latitude = n.createVariable('lat','f',('lat',))
latitude.longname = 'latitude'
latitude.units = 'degrees_north'
latitude[:] = lat[:].astype(np.float32)
longitude = n.createVariable('lon','f',('lon',))
longitude.longname = 'longitude'
longitude.units = 'degrees_east'
longitude[:] = lon[:].astype(np.float32)
time = n.createVariable('time','i',('time',))
time.units = 'days since 1979-1-1 00:00:0.0'
time.delta_t = '0000-00-01 00:00:00'
varnc = n.createVariable(varname,'f',('time','lat','lon',))
varnc.missing_value = np.array(miss_val,np.float32)
varnc._FillValue = np.array(miss_val,np.float32)
for l in range(0,var.shape[0]):
time[l]=time_it[l,]
varnc[l,:,:]=var[l,:,:].astype(np.float32)
n.close()
def writeToNc(self, ncFileName):
ncFile = NetCDFFile(ncFileName, 'w')
ncFile.createDimension("nrows", self.RaCoords.shape[0])
ncFile.createDimension("ncols", self.DecCoords.shape[0])
dims = ("nrows", "ncols")
drow = ("nrows", )
dcol = ("ncols", )
ncFile.createVariable("signal", "d", dims)
ncFile.createVariable("weight", "d", dims)
ncFile.createVariable("kernel", "d", dims)
ncFile.createVariable("rowCoordsPhys", "d", drow)
ncFile.createVariable("colCoordsPhys", "d", dcol)
ncFile.createVariable("xCoordsAbs", "d", dims)
ncFile.createVariable("yCoordsAbs", "d", dims)
ncFile.createVariable("filteredSignal", "d", dims)
ncFile.createVariable("filteredWeight", "d", dims)
ncFile.createVariable("filteredKernel", "d", dims)
setattr(ncFile, "source", "%s" % self.source)
setattr(ncFile, "MasterGrid[0]", self.SourceRa / 180.0 * (npy.pi))
setattr(ncFile, "MasterGrid[1]", self.SourceDec / 180.0 * (npy.pi))
ncFile.variables['signal'][:] = self.signal.value
ncFile.variables['weight'][:] = self.weight.value
ncFile.variables['rowCoordsPhys'][:] = self.RaCoords / 180.0 * (npy.pi)
ncFile.variables['colCoordsPhys'][:] = self.DecCoords / 180.0 * (
npy.pi)
ncFile.variables['kernel'][:] = self.kernel
ncFile.variables['xCoordsAbs'][:] = self.AbsRaCoords.to("rad").value
ncFile.variables['yCoordsAbs'][:] = self.AbsDecCoords.to("rad").value
if self.filtered:
ncFile.variables['filteredSignal'][:] = self.fSignal.value
ncFile.variables['filteredWeight'][:] = self.fWeight.value
ncFile.variables['filteredKernel'][:] = self.fKernel
else:
ncFile.variables['filteredSignal'][:] = self.signal.value
ncFile.variables['filteredWeight'][:] = self.weight.value
ncFile.variables['filteredKernel'][:] = self.kernel
ncFile.sync()
ncFile.close()