%Class for CO907.
%__________________________________________
%Author: Jiarui Cao
%Date: 19 Nov 2013
%Purpose: Problem Sheet 2. Q2.4


close all;
clear all;
clc;
clf;


%% Load data
%set file path
filepath =['/Users/...'];

%The code below are generated from 'import data'.
filename1=[filepath 'ftse.dat'];
delimiter = '\t';
startRow = 2;
formatSpec = '%f%f%[^\n\r]';
fileID = fopen(filename1,'r');
dataArray = textscan(fileID, formatSpec, 'Delimiter', delimiter, 'EmptyValue' ,NaN,'HeaderLines' ,startRow-1, 'ReturnOnError', false);
Day = dataArray{:, 1};
FTSE = dataArray{:, 2};
fclose(fileID);


filename2=[filepath 'xray.dat'];
delimiter = ' ';
startRow = 6;
formatSpec = '%f%f%*s%*s%*s%*s%[^\n\r]';
fileID = fopen(filename2,'r');
dataArray = textscan(fileID, formatSpec, 'Delimiter', delimiter, 'MultipleDelimsAsOne', true, 'EmptyValue' ,NaN,'HeaderLines' ,startRow-1, 'ReturnOnError', false);
fclose(fileID);
t = dataArray{:, 1};
xray = dataArray{:, 2};


filename3=[filepath 'temperatureanomaly.dat'];
Temp=load(filename3);
Month =1:1:length(Temp);


%% Plot the raw data. 
%%Notice: we only give the simple plots of the unprocessed data here. After
%%that you need find a clever way to pre-process your data, as required by
%%the problem.
% 
% plot(Day,FTSE,'om');
% xlabel('day');
% ylabel('FTSE');
% figure()
% plot(t,xray,'sb');
% xlabel('time');
% ylabel('x-ray');
% figure()
% plot(Month,Temp,'xr');
% xlabel('month');
% ylabel('temp');




%% Generate and plot autocorrelation functions
autocorr(xray,1000); % you need 'autocorr' package in Econometrics Toolbox

%%Or use xcorr to calculate the autocorrelation
figure()
xray=xray-mean(xray); %center data
c=xcorr(xray,'unbiased'); % unbiased is an option of xcorr, say help file for detail
m=(length(c)+1)/2; % take the middle point
c=c./c(m); % normalise correlation
%c2=c(m:length(c));
c2=c(m:m+1000);
plot(c2,'ob');