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()
