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%function: netcdf_ecco_read |
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%object: read netcdf data files in the "MIT format" |
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%author: Gael Forget (gforget@mit.edu) |
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%date: june 21th, 2006 |
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% |
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%usage: [depth,myvars,prof_descr,mystruct,mystruct1D]=... |
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% netcdf_ecco_read(rep_data,file_data); |
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% ---> loads a data set |
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% [depth,myvars,prof_descr,mystruct,mystruct1D]=... |
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% netcdf_ecco_read(rep_equi,file_equi); |
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% ---> loads model counterparts |
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% [depth,myvars,prof_descr,mystruct,mystruct1D]=... |
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% netcdf_ecco_read(rep_data,file_data,rep_equi,suff_equi); |
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% ---> loads both the data set and model counterparts |
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% |
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%inputs: rep_data data file directory |
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% file_data data file name |
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% rep_equi model file directory |
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% suff_equi model file suffix |
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% |
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%asumption: file_data is 'blabla.nc', and the |
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% model file is named ['blabla' suff_equi] |
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% |
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%outputs: depth depth vector |
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% myvars list of the variables |
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% prof_descr instruments/cruises id |
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% mystruct struct array containing the |
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% data(+model counterparts) and weights(+model mask) |
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% mystruct1D struct array of dates and positions |
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|
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function [depth,myvars,prof_descr,mystruct,mystruct1D]=... |
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netcdf_ecco_read(rep_data,file_data,varargin); |
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|
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list_vars=strvcat('T','S','U','V','ptr','ssh'); |
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|
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if isempty(varargin) |
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%either observations or model counterparts: |
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ncload(deblank([rep_data file_data])); |
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mystruct_txt='mystruct=struct('; myvars=''; |
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for num_var=1:size(list_vars,1) |
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name_var=deblank(list_vars(num_var,:)); |
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if ~isempty(who(['prof_' name_var])); |
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myvars=strvcat(myvars,name_var); |
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mystruct_txt=[mystruct_txt '''prof_' name_var ''',{prof_' name_var '}']; |
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%for observations: |
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if ~isempty(who(['prof_' name_var 'weight'])); |
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mystruct_txt=[mystruct_txt ',''prof_' name_var 'weight'',{prof_' name_var 'weight},']; |
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%or for model counterparts case: |
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else mystruct_txt=[mystruct_txt ',''prof_' name_var 'mask'',{prof_' name_var 'mask},']; end; |
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end; |
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end; |
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|
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else |
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%read both observations and model: |
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rep_equi=varargin{1}; suff_equi=varargin{2}; |
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tmp1=strfind(file_data,'.nc'); |
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% read the model: |
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ncload(deblank([rep_equi file_data(1:tmp1-1) suff_equi])); |
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mystruct_txt='mystruct=struct('; myvars=''; |
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for num_var=1:size(list_vars,1) |
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name_var=deblank(list_vars(num_var,:)); |
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if ~isempty(who(['prof_' name_var])); |
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myvars=strvcat(myvars,name_var); |
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mystruct_txt=[mystruct_txt '''prof_' name_var ''',{prof_' name_var '},']; |
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mystruct_txt=[mystruct_txt '''prof_' name_var 'weight'',{prof_' name_var 'weight},']; |
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mystruct_txt=[mystruct_txt '''prof_' name_var 'equi'',{prof_' name_var 'equi},']; |
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mystruct_txt=[mystruct_txt '''prof_' name_var 'mask'',{prof_' name_var 'mask},']; |
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eval(['prof_' name_var 'equi=prof_' name_var ';']); |
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end |
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end |
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% then read the observations: |
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tmp1=strfind(file_data,'.nc'); |
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ncload(deblank([rep_data file_data(1:tmp1-1) '.nc'])); |
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end |
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|
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%structure the 2D arrays: |
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mystruct_txt=[mystruct_txt(1:end-1) ');']; |
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eval(mystruct_txt); |
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|
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%structure the 1D arrays: |
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mystruct1D=struct('prof_YYYYMMDD',prof_YYYYMMDD,'prof_HHMMSS',prof_HHMMSS,... |
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'prof_lon',prof_lon,'prof_lat',prof_lat); |
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|
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%accomodate new prof_depth convention: |
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if isempty(whos('depth')); depth=prof_depth; end; |
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