% Count the number of followers and mentions for MATLAB on Twitter.
% 
% time1352 and data1352 available for use
% for Twitter Mentions of @MATLAB
% 
% Number of Followers for MATLAB on Twitter
%   time vector is: time1304
%   data vector is: data1304

subplot(2,1,1)

  % Fit MATLAB Follower growth
  [p,S,mu] = polyfit(time1304,data1304,1);
  p1 = [p(1)/mu(2) p(2)-p(1)*mu(1)/mu(2)];

  % Project into the future
  tf = [time1304; time1304(end)+1];
  df = polyval(p1,tf);

  % Predict the number for the next day
  d=round(df(end));
  t=datestr(time1304(end)+1,1);
  s=sprintf('Prediction for %s: %d followers',t,d);

  % Predict when it will reach a goal
  goal = 8000;
  g = sprintf('Will reach %d followers on ', goal);
  g = [g datestr((goal - p1(2))/p1(1),1)];

  % Was previous prediction correct?
  [p,S,mu] = polyfit(time1304(1:end-1),data1304(1:end-1),1);
  p2 = [p(1)/mu(2); p(2)-p(1)*mu(1)/mu(2)];
  prev = polyval(p2,time1304(end-1)+1);
  prev = round(prev);
  gap = prev-data1304(end);
  t=datestr(time1304(end),1);
  p=sprintf('Prev Prediction for %s off by %d',t,gap);

  % Plot the data and trend
  plot(time1304,data1304,'-');
  hold on
  line(tf,df,'Color','magenta','LineStyle','-')
  plot(time1304(end),prev, 'ro');
  datetick
  title('Twitter followers for MATLAB')
  legend('Followers','Trend','Prev Prediction', 'Location', 'Northwest')
  xlabel(s)
  hold off

  % Get normalized position for annotation
  xrange = xlim;
  xmin = xrange(1);
  xmax = xrange(2);
  yrange = ylim;
  ymin = yrange(1);
  ymax = yrange(2);

  % Add the prediction
  XPos = xmin+0.35*(xmax-xmin);
  YPos1 = ymin+0.2*(ymax-ymin);
  YPos2 = ymin+0.1*(ymax-ymin);
  text(XPos,YPos1,p)
  text(XPos,YPos2,g)

subplot(2,1,2)

  % Pad the data to fit the timeline with another plot
  time = [time1304(1:5); time1352; tf(end)];
  data = [NaN; NaN; NaN; NaN; NaN; data1352; NaN];
  
  % Get z-score of time1352
  % z = (time1352-mean(time1352))/std(time1352); 
  % zfit = linspace(z(1),z(end), size(time1352,2));

  % Get 4th order polynomial fit
  % pz4 = polyfit(z,data1352,4); 
  % yfit = polyval(pz4,zfit); % fitted data
  % xfit = linspace(time1352(1),time1352(end), ...     
  %    size(time1352,2));
  % keep = yfit >=0; %eliminate sub-zero

  % Adjust the Y axis
  % ymin = fix(min(data1352));
  % ymax = ceil(max(data1352));

  % Smoothed Curve - 7 Day Moving Average
  windowSize = 7;
  mv = filter(ones(1,windowSize)/windowSize,1,data1352);
  
  % plot(time, data, 'o-');
  plot(time,data,'Color',[0.8 0.8 1])
  hold on
  % plot(xfit(keep),yfit(keep),'m-')
  line(time1352,mv,'Color','blue','LineWidth',1);
  
  % ylim([ymin-1 ymax+1])
  % set(gca,'YTick',ymin-1:ymax+1)
  datetick
  title('Twitter mentions for @MATLAB')
  % legend('Mentions', 'Trend', 'Location', 'Best')
  legend('Mentions', 'Mvg Avg', 'Location', 'Best')
  hold off