% the data from 42557 till 72580 and from 86107 to 87418 contains huge amount of NAN which is being
% replaced by filtered data so it is better to delete those data in order
% to stop model from learning fake representations
clear all

load('meteodata.mat')
load('rainfiltereddata06-08-16.mat')
load('rainfiltereddatawithsgolayandmedian06-13-16.mat')
load('movingavgrainfilterdata.mat') 
load('lowpassfilteredrainwithorder3freq4.mat')
load('lowpassfilteredrainwithorder2freq35.mat')
load()
HFilt(42557:72580)=[];
HFilt(86107:87418)=[];

TariaFilt(42557:72580)=[];
TariaFilt(86107:87418)=[];

PFilt(42557:72580)=[];
PFilt(86107:87418)=[];

% RainFilt(42557:72580)=[];
% RainFilt(86107:87418)=[];

VelVentoFilt(42557:72580)=[];
VelVentoFilt(86107:87418)=[];

save datafordeepnnrain

load('datafordeepnnrain.mat')
filteredraingolay(42557:72580)=[];
filteredraingolay(86107:87418)=[];

% 90000 data for deep nn training and rest for test
%we have to make data sets so that it is able to predict 3 hour rain from previous history
% normalize all the data parameter Rain temp velocity humidity pressure 

% minval=min(filteredraingolay);
% maxval=max(filteredraingolay);
% norm_rain = (filteredraingolay - minval) / ( maxval - minval );



% minval=min(filteredrainmed);
% maxval=max(filteredrainmed);
% norm_rain = (filteredrainmed - minval) / ( maxval - minval );

%moving average filter 
 minval=min(mvfrain);
 maxval=max(mvfrain);
 norm_rain = (mvfrain - minval) / ( maxval - minval );
 
 
% low pas butterworth filter 
 minval=min(X4);
 maxval=max(X4);
 norm_rain = (X4 - minval) / ( maxval - minval );
 
 
 
minval=min(TariaFilt);
maxval=max(TariaFilt);
norm_temp = (TariaFilt - minval) / ( maxval - minval );

minval=min(VelVentoFilt);
maxval=max(VelVentoFilt);
norm_velocity = (VelVentoFilt - minval) / ( maxval - minval );

minval=min(HFilt);
maxval=max(HFilt);
norm_humidity = (HFilt - minval) / ( maxval - minval );

minval=min(PFilt);
maxval=max(PFilt);
norm_pressure = (PFilt - minval) / ( maxval - minval );

outputrain3hour=[];
inputdata=[];
for i=1:(size(norm_rain,1)-13)
 inputdata=[inputdata; norm_rain(i) norm_temp(i) norm_humidity(i) norm_pressure(i) norm_velocity(i)];
 outputrain3hour=[outputrain3hour; norm_rain(5+i) norm_rain(9+i) RainFilt(13+i)];
 end
save filteredpreprocesseddatafordeepnn

inputdata=[];
outputrain3hour=[];
for i=4:(size(RainFilt,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i)  norm_temp(i) norm_humidity(i) norm_pressure(i) norm_velocity(i)];
 outputrain3hour=[outputrain3hour; norm_rain(4+i) norm_rain(8+i) RainFilt(12+i)];
 end
save preprocesseddatafordeepnn2

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata;  norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) var(norm_rain(i-3:i)) norm_temp(i) norm_humidity(i)];
 outputrain3hour=[outputrain3hour; norm_rain(4+i) norm_rain(8+i) RainFilt(12+i)];
 end
save filteredpreprocesseddatafordeepnn3

inputdata=[];
outputrain3hour=[];
for i=4:(size(RainFilt,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i))];
 outputrain3hour=[outputrain3hour; norm_rain(4+i)];
 end
save preprocesseddatafordeepnn4

inputdata=[];
outputrain3hour=[];
for i=4:(size(RainFilt,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i))];
 outputrain3hour=[outputrain3hour; norm_rain(4+i)];
 end
save preprocesseddatafordeepnn5

inputdata=[];
outputrain3hour=[];
for i=4:(size(RainFilt,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+1)];
 end
save preprocesseddatafordeepnn5


inputdata=[];
outputrain3hour=[];
for i=4:(size(RainFilt,1)-12)
 inputdata=[inputdata;  norm_rain(i-2) norm_rain(i-1) norm_rain(i) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+1)];
 end
save preprocesseddatafordeepnn6



inputdata=[];
outputrain3hour=[];
for i=4:(size(RainFilt,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) var(norm_rain(i-3:i)) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+1)];
 end
save preprocesseddatafordeepnn7

% k=[];
% s=[];
% for i=4:(size(RainFilt,1)-12)
% k=[k; kurtosis(norm_rain(i-3:i))];
% s=[s; skewness(norm_rain(i-3:i))];
%  end

inputdata=[];
outputrain3hour=[];
for i=4:(size(RainFilt,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) var(norm_rain(i-3:i)) std(norm_rain(i-3:i))  kurtosis(norm_rain(i-3:i)) skewness(norm_rain(i-3:i))];
 outputrain3hour=[outputrain3hour; norm_rain(i+1)];

end

save preprocesseddatafordeepnn8


inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) var(norm_rain(i-3:i)) std(norm_rain(i-3:i))  kurtosis(norm_rain(i-3:i)) skewness(norm_rain(i-3:i))];
 outputrain3hour=[outputrain3hour; norm_rain(i+1)];

end

save filteredpreprocesseddatafordeepnn8


inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-2) norm_rain(i-1) norm_rain(i)  norm_humidity(i)  ];
 outputrain3hour=[outputrain3hour; norm_rain(i+1)];

end

save filteredpreprocesseddatafordeepnn9



inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-2) norm_rain(i-1) norm_rain(i)  norm_humidity(i)];
 outputrain3hour=[outputrain3hour; norm_rain(i+1)];

end

save medianfilteredpreprocesseddatafordeepnn9


inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-2) norm_rain(i-1) norm_rain(i)  norm_humidity(i) norm_temp(i)];
 outputrain3hour=[outputrain3hour; norm_rain(i+1)];

end

save medianfilteredpreprocesseddatafordeepnn10

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-2) norm_rain(i-1) norm_rain(i)  norm_humidity(i) norm_temp(i)];
 outputrain3hour=[outputrain3hour; norm_rain(i+1)];

end

save MovingAvgfilteredpreprocesseddatafordeepnn10

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-2) norm_rain(i-1) norm_rain(i)  norm_humidity(i) norm_temp(i)];
 outputrain3hour=[outputrain3hour; norm_rain(i+1)];

end

save MovingAvgfilteredpreprocesseddatafordeepnn10

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-2) norm_rain(i-1) norm_rain(i)  norm_humidity(i) norm_temp(i)];
 outputrain3hour=[outputrain3hour; norm_rain(i+4)];

end

save MovingAvgfilteredpreprocesseddatafordeepnn11


inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata;  norm_rain(i-1) norm_rain(i)  norm_humidity(i) norm_temp(i)];
 outputrain3hour=[outputrain3hour; norm_rain(i+4)];

end

save MovingAvgfilteredpreprocesseddatafordeepnn12

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-2) norm_rain(i-1) norm_rain(i)  norm_humidity(i)  norm_temp(i)];
 outputrain3hour=[outputrain3hour; norm_rain(i+1) norm_rain(i+2) norm_rain(i+3) norm_rain(i+4) ];

end

save MovingAvgfilteredpreprocesseddatafordeepnn14


inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) std(norm_rain(i-3:i)) norm_humidity(i) norm_pressure(i) norm_temp(i)];
 outputrain3hour=[outputrain3hour; norm_rain(i+1) norm_rain(i+2) norm_rain(i+3) norm_rain(i+4) ];

end
save MovingAvgfilteredpreprocesseddatafordeepnn15

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) std(norm_rain(i-3:i)) norm_humidity(i) norm_pressure(i) norm_temp(i)];
 outputrain3hour=[outputrain3hour; norm_rain(i+4) ];

end
save MovingAvgfilteredpreprocesseddatafordeepnn16


inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) std(norm_rain(i-3:i)) norm_humidity(i) norm_pressure(i) norm_temp(i) norm_humidity(i+4) norm_pressure(i+4) norm_temp(i+4) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+4) ];

end
save lowpassfilteredpreprocesseddatafordeepnn17

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) std(norm_rain(i-3:i)) norm_humidity(i) norm_pressure(i) norm_temp(i) norm_humidity(i-1) norm_pressure(i-1) norm_temp(i-1) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+1) ];

end
save lowpassfilteredpreprocesseddatafordeepnn18

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) std(norm_rain(i-3:i)) norm_humidity(i) norm_pressure(i) norm_temp(i) norm_humidity(i-1) norm_pressure(i-1) norm_temp(i-1) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+4) ];

end
save lowpassfilteredpreprocesseddatafordeepnn19


inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) std(norm_rain(i-3:i)) norm_humidity(i) norm_pressure(i) norm_temp(i) norm_humidity(i-1) norm_pressure(i-1) norm_temp(i-1) norm_humidity(i-2) norm_pressure(i-2) norm_temp(i-2) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+4) ];

end
save lowpassfilteredpreprocesseddatafordeepnn20

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) std(norm_rain(i-3:i)) norm_humidity(i) norm_pressure(i) norm_temp(i) norm_humidity(i-1) norm_pressure(i-1) norm_temp(i-1) norm_humidity(i-2) norm_pressure(i-2) norm_temp(i-2) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+8) ];

end
save lowpassfilteredpreprocesseddatafordeepnn21

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) std(norm_rain(i-3:i)) norm_humidity(i) norm_pressure(i) norm_temp(i) norm_humidity(i-1) norm_pressure(i-1) norm_temp(i-1) norm_humidity(i-2) norm_pressure(i-2) norm_temp(i-2) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+12) ];

end
save lowpassfilteredpreprocesseddatafordeepnn22

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) std(norm_rain(i-3:i)) norm_humidity(i) norm_pressure(i) norm_temp(i) norm_humidity(i-1) norm_pressure(i-1) norm_temp(i-1) norm_humidity(i-2) norm_pressure(i-2) norm_temp(i-2) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+1) norm_rain(i+2) norm_rain(i+3) norm_rain(i+4) ];

end
save lowpassfilteredpreprocesseddatafordeepnn23

inputdata=[];
outputrain3hour=[];
for i=4:(size(norm_rain,1)-12)
 inputdata=[inputdata; norm_rain(i-3) norm_rain(i-2) norm_rain(i-1) norm_rain(i) mean(norm_rain(i-3:i)) std(norm_rain(i-3:i)) norm_humidity(i) norm_pressure(i) norm_temp(i) norm_humidity(i-1) norm_pressure(i-1) norm_temp(i-1) norm_humidity(i-2) norm_pressure(i-2) norm_temp(i-2) ];
 outputrain3hour=[outputrain3hour; norm_rain(i+1) ];

end
save lowpassfilteredpreprocesseddatafordeepnn24