function [ X ] = pniExtractFeaturesA(data)
%PNIALISTAIR	Alistair's initial entry
%	[ pred ] = pniAlistair(data) calculates a mortality prediction for each
%	each row (observation/subject) in data
%
%   The score uses the following variables:
%
%
%	Inputs:
%		data    - Cell array of data.
%           Column 1 - Subject IDs
%           Column 2 - Time stamp vectors for each subject
%           Column 3 - Feature name vectors for each subject
%           Column 4 - Data value vectors for each subject
%
%	Outputs:
%		pred   - Column vector of predictions
%
%	Example
%       %=== Load data in
%       load('data_processed_cell.mat');
%
%       %=== Calculate prediction
%       [ score ] = pniAlistair(data);
%
%	See also PNMAIN PNPREPROCESSDATA

%	References:
%       Physionet Challenge 2012
%       http://physionet.org/challenge/2012/

%	Copyright 2012 Alistair Johnson

%	$LastChangedBy: alistair $
%	$LastChangedDate: 2012-04-24 17:46:42 +0100 (Tue, 24 Apr 2012) $
%	$Revision: 339 $
%	Originally written on GLNXA64 by Alistair Johnson, 15-Apr-2012 14:40:03
%	Contact: alistairewj@gmail.com
%
% pred = zeros(size(data,1),1);
% header_extract = {'Urine','Platelets','BUN','Creatinine','PaO2',...
%     'PaCO2','pH','HR','Temp','Age',...
%     'FiO2','NIMAP','MAP'}; % fields to extract high/low data from
%
% [low,h_L] = pnSubsampleData(data, 60*48,'low',header_extract(2:end)); % Lowest data for 24 hours
% [high,h_H] = pnSubsampleData(data, 60*48,'high',header_extract(2:end)); % Highest data for 24 hours
%
% %=== Split into training + test
% [ idxK, idxTraining, idxTest ] = pnCreateIndices;
% idxTraining = idxTraining(:,4); idxTest = idxTest(:,4);
%
% trainL = low(idxTraining,:);
% trainH = high(idxTraining,:);
% testL = low(idxTest,:);
% testH = high(idxTest,:);
%
% %=== Impute data as needed
% medianL = nanmedian(trainL,1);
% medianH = nanmedian(trainH,1);
%
% for k=1:size(trainL,2)
%     trainL(isnan(trainL(:,k)),k) = medianL(k);
%     testL(isnan(testL(:,k)),k) = medianL(k);
% end
% for k=1:size(trainH,2)
%     trainH(isnan(trainH(:,k)),k) = medianH(k);
%     testH(isnan(testH(:,k)),k) = medianH(k);
% end
%
% train = [trainL, trainH];
% test = [testL, testH];
%
% data = zeros(4000,size(train,2));
% data(idxTraining,:) = train;
% data(idxTest,:) = test;
N = size(data,1);

header = {'GCS_LAST','GCS_MAXIMUM','GCS_DELTA','Age_MAX','Lactate_LAST','ALP_MAXIMUM',...
    'BUN_MV','BUN_MAXIMUM',...
    'WaveCreatClear_4_logabs','Na_Moment4','GCS_Moment3',...
    'StatsHCO3_7','StatsGlucose_9','StatsUrine_9_sqr','StatsAge_1','StatsLactate_12_logder_binary',...
    'StatsOOR_dUrineDt_3','StatsOOR_NISysABP_6_binary','PaFi'};


%=== Extract all the data here

%=== Extract the first row of header
X1 = nan(N,5);

temp = pnExtractField(data,'GCS');
idxEmpty = ~cellfun(@isempty,temp(:,4));
X1(idxEmpty,1:3) = [ cellfun(@(x) x(end), temp(idxEmpty,4)), ...
    cellfun(@(x) max(x), temp(idxEmpty,4)), ...
    cellfun(@(x) x(end)-x(1), temp(idxEmpty,4))];

temp = pnExtractField(data,'Age');
idxEmpty = ~cellfun(@isempty,temp(:,4));
X1(idxEmpty,4) = cellfun(@(x) max(x), temp(idxEmpty,4));

temp = pnExtractField(data,'Lactate');
idxEmpty = ~cellfun(@isempty,temp(:,4));
X1(idxEmpty,5) = cellfun(@(x) x(end), temp(idxEmpty,4));

temp = pnExtractField(data,'ALP');
idxEmpty = ~cellfun(@isempty,temp(:,4));
X1(idxEmpty,6) = cellfun(@(x) max(x), temp(idxEmpty,4));

X2 = nan(N,2);
temp = pnExtractField(data,'BUN');
idxEmpty = ~cellfun(@isempty,temp(:,4));
X2(:,1) = idxEmpty;
X2(idxEmpty,2) = cellfun(@(x) max(x), temp(idxEmpty,4));


%=== Third row
X3 = nan(N,3);

temp = pnExtractField(data,'Na');
idxEmpty = ~cellfun(@isempty,temp(:,4));
X3(idxEmpty,2) = cellfun(@(x) ((sum((x-mean(x)).^4)/numel(x)) / (sum((x-mean(x)).^2)/numel(x)).^2)-3,...
    temp(idxEmpty,4));

temp = pnExtractField(data,'GCS');
idxEmpty = ~cellfun(@isempty,temp(:,4));
X3(idxEmpty,3) = cellfun(@(x) sqrt(numel(x)*(numel(x)-1))/(numel(x)-2)*((sum((x-mean(x)).^3) / numel(x)) / (sum((x-mean(x)).^2)/numel(x)).^1.5),...
    temp(idxEmpty,4));

%=== Fourth row, stats
% 1: min day 1
% 2: median
% 3: max
% 4: std day1
% 5: kurtosis day1
% 6: skewness day1
% 7: min day 2
% 8: median
% 9: max
% 10: std day2
% 11: kurtosis day2
% 12: skewness day2
X4 = nan(N,5);

temp = pnExtractField(data,'HCO3');
idxDay = cellfun(@(x) x>1440, temp(:,2), 'UniformOutput',false);
temp(:,4) = cellfun(@(x,y) x(y), temp(:,4), idxDay, 'UniformOutput',false);
idxEmpty = ~cellfun(@isempty,temp(:,4));
X4(idxEmpty,1) = cellfun(@(x) min(x), temp(idxEmpty,4));

temp = pnExtractField(data,'Glucose');
idxDay = cellfun(@(x) x>1440, temp(:,2), 'UniformOutput',false);
temp(:,4) = cellfun(@(x,y) x(y), temp(:,4), idxDay, 'UniformOutput',false);
idxEmpty = ~cellfun(@isempty,temp(:,4));
X4(idxEmpty,2) = cellfun(@(x) max(x), temp(idxEmpty,4));


temp = pnExtractField(data,'Urine');
idxDay = cellfun(@(x) x>1440, temp(:,2), 'UniformOutput',false);
temp(:,4) = cellfun(@(x,y) x(y), temp(:,4), idxDay, 'UniformOutput',false);
idxEmpty = ~cellfun(@isempty,temp(:,4));
X4(idxEmpty,3) = cellfun(@(x) sqrt(max(x)), temp(idxEmpty,4));

temp = pnExtractField(data,'Age');
idxDay = cellfun(@(x) x<1441, temp(:,2), 'UniformOutput',false);
temp(:,4) = cellfun(@(x,y) x(y), temp(:,4), idxDay, 'UniformOutput',false);
idxEmpty = ~cellfun(@isempty,temp(:,4));
X4(idxEmpty,4) = cellfun(@(x) sqrt(min(x)), temp(idxEmpty,4));


temp = pnExtractField(data,'Lactate');
idxDay = cellfun(@(x) x>1440, temp(:,2), 'UniformOutput',false);
temp(:,4) = cellfun(@(x,y) x(y), temp(:,4), idxDay, 'UniformOutput',false);
idxEmpty = ~cellfun(@isempty,temp(:,4));
X4(:,5) = idxEmpty;


X6 = nan(N,4);
%=== harder to extract features


% dUrineDt
temp = pnExtractField(data,'Urine');
idxDay = cellfun(@(x) x<1441, temp(:,2), 'UniformOutput',false);
temp(:,2) = cellfun(@(x,y) x(y), temp(:,2), idxDay, 'UniformOutput',false);
temp(:,4) = cellfun(@(x,y) x(y), temp(:,4), idxDay, 'UniformOutput',false);

idxLen = cellfun(@(x) numel(x) > 2, temp(:,4));
X6(idxLen,1) = cellfun(@(x,y) max(cumtrapz(x,y./x)), temp(idxLen,2), temp(idxLen,4));
        


% OOR_NISysABP
range.NISysABP = {90,180};
temp = pnExtractField(data,'NISysABP');
idxDay = cellfun(@(x) x<1441, temp(:,2), 'UniformOutput',false);
temp(:,2) = cellfun(@(x,y) x(y), temp(:,2), idxDay, 'UniformOutput',false);
idxEmpty = ~cellfun(@isempty,temp(:,2));
X6(:,2) = zeros(N,1);
OORtmp = cellfun(@(x) diff(x), temp(idxEmpty,2), 'UniformOutput',false);
X6(idxEmpty,2) = cellfun(@(x) any(x<120), OORtmp);

temp = pnPaFi(data);
idxEmpty = ~cellfun(@isempty,temp(:,4));
X6(idxEmpty,3) = cellfun(@(x) x(1), temp(idxEmpty,4));
X6(idxEmpty,4) = cellfun(@(x) x(end), temp(idxEmpty,4));


X = [X1,X2,X3,X4,X6];
end