dataset = open_url( 'http://omgsrv1.meas.ncsu.edu:8080/thredds/dodsC/fmrc/sabgom/SABGOM_Forecast_Model_Run_Collection_best.ncd' ) ############################################################################################################### #### get sabgom data and save to .mat file #note: the utils.mk_array was done to get around an issue I was having with my numpy array getting trash values in savemat unless I wrapped the matrix within a 'singleton' dimension # so (320,440) becomes (1,320,440) and then matrix squeezed here and in matlab to give the original (320,440) matrix #obs vars temp = dataset['temp'] #temp = temp[1,:,:,:] temp = temp[fc_offset, :, :, :] temp = utils.mk_array(temp.shape, temp) salt = dataset['salt'] salt = salt[fc_offset, :, :, :] salt = utils.mk_array(salt.shape, salt) u = dataset['u'] u = u[fc_offset, :, :, :] u = utils.mk_array(u.shape, u) v = dataset['v'] v = v[fc_offset, :, :, :] v = utils.mk_array(v.shape, v) chl = dataset['chlorophyll'] chl = chl[fc_offset, :, :, :]
import scipy.io as sio from scipy.io import netcdf filein = netcdf.netcdf_file('sabgom_grd_H.nc','r') import numpy as np import utils # { 'mask_rho','mask_psi','mask_u','mask_v','h','pm','pn','f','angle'}; mask_rho = filein.variables['mask_rho'] mask_rho = utils.mk_array(mask_rho.shape,mask_rho[:,:]) mask_psi = filein.variables['mask_psi'] mask_psi = utils.mk_array(mask_psi.shape,mask_psi[:,:]) mask_u = filein.variables['mask_u'] mask_u = utils.mk_array(mask_u.shape,mask_u[:,:]) mask_v = filein.variables['mask_v'] mask_v = utils.mk_array(mask_v.shape,mask_v[:,:]) h = filein.variables['h'] h = utils.mk_array(h.shape,h[:,:]) pm = filein.variables['pm'] pm = utils.mk_array(pm.shape,pm[:,:]) pn = filein.variables['pn'] pn = utils.mk_array(pn.shape,pn[:,:])