In [1]:

    

cd ..
clc; clear all; close all;
addpath(genpath(pwd));
zones_Prec = get_zones_Prec_weekly();
OISST      = dlmread('data/OISST_19811101-20161116.dat');
uwnd       = dlmread('data/uwnd_WIND_CCMP_merge_OISST_weekly.dat');
vwnd       = dlmread('data/vwnd_WIND_CCMP_merge_OISST_weekly.dat');

% Intercept SST to make them time consistent
OISST = OISST(1:size(zones_Prec, 1), :);
uwnd  = uwnd(1:size(zones_Prec, 1), :);
vwnd  = vwnd(1:size(zones_Prec, 1), :);
x_train = [OISST uwnd vwnd];
y_train = zones_Prec;


    

In [3]:

    

whos


    

    




Name               Size                   Bytes  Class     Attributes

  OISST           1688x20800            280883200  double              
  uwnd            1688x20800            280883200  double              
  vwnd            1688x20800            280883200  double              
  x_train         1688x62400            842649600  double              
  y_train         1688x9                   121536  double              
  zones_Prec      1688x9                   121536  double

In [ ]:

    

% idx   hiddenLayerSize delay_weeks trainPerformance    valPerformance  testPerformance performance trainR  valR    testR   R   region1 region2 region3 region4 region5 region6 region7 region8 region9
% result = tdnn_train(X, Y, delay_times, hiddenLayerSize)
result = [];
for delay_times = 1:20
    for repeat = 1:5
        result_one = tdnn_train(x_train, y_train, delay_times, 30);
        result = [result; result_one];
    end
end
dlmwrite('result/20161220_2_result_repeat_5_delay_1-20_hid_30.dat', result, 'delimiter', '\t');


    

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