# -*- coding: utf-8 -*-

###################
#                 #
#  CONFIGURATION  #
#                 #
###################

# Libraries
library('ggplot2')
library('maps')
library('reshape2')
library('RColorBrewer')

# Future movie configuration
setwd('/path/to/working/directory')
start.date <- '2012-12-31 00:00:00'
finish.date <- '2013-01-01 12:00:00'
seconds.in.frame <- 30
ma.period <- 60 * 30 # Moving averege period for tweet-stats in frame
texttime <- 3 * 24 # Base time for text demonstration (in frames in final movie)

# Loop computations
start.date <- strptime(start.date, format='%Y-%m-%d %H:%M:%S')
finish.date <- strptime(finish.date, format='%Y-%m-%d %H:%M:%S')
frames <- as.numeric(difftime(finish.date, start.date, units='secs'))/seconds.in.frame

# ggplot palette & geometry setup
twits.colors=brewer.pal(9, 'YlOrRd')
roundcoef <- .48
textcolors <- c('deeppink3',
                'coral3',
                'chocolate3',
                'chartreuse3',
                'brown3',
                'blue3',
                'aquamarine3',
                'dodgerblue3',
                'deepskyblue3',
                'deeppink3',
                'darkorchid3',
                'darkorange3',
                'darkgreen',
                'cyan4',
                'gold3',
                'forestgreen',
                'firebrick3',
                'green3',
                'indianred3',
                'hotpink3',
                'maroon3',
                'palegreen3',
                'limegreen',
                'orange3',
                'olivedrab3',
                'red3',
                'royalblue3',
                'springgreen3')

# Function for circle points
draw.circle <- function(center,diameter=1, npoints = 100){
  r = diameter / 2
  tt <- seq(0,2*pi,length.out = npoints)
  xx <- center[1] + r * cos(tt)
  yy <- center[2] + r * sin(tt) * roundcoef
  return(data.frame(x = xx, y = yy))
}

##################
#                #
#  LOADING DATA  #
#                #
##################

# Load tweets with coordinates & convert values to proper format
twits <- read.csv2('ny_tweets.csv', header=F)
colnames(twits) <- c('Link', 'Longitude', 'Latitude', 'Timestamp')
twits$Timestamp <- strptime(twits$Timestamp, format='%Y-%m-%d %H:%M:%S')
twits$Latitude <- round(as.numeric(as.character(twits$Latitude)), digits=1)
twits$Longitude <- round(as.numeric(as.character(twits$Longitude)), digits=1)
twits$Longitude <- sapply(twits$Longitude, function(x){
  if(x < (-169)){
    x<-360+x
  }
  else{x}
})

# Load tweets with texts & convert date-time
twit.texts <- read.csv2('ny_text_tweets.csv', header=F)
colnames(twit.texts) <- c('Link', 'Latitude', 'Longitude', 'Timestamp', 'Text')
twit.texts$Timestamp <- strptime(twit.texts$Timestamp, format='%Y-%m-%d %H:%M:%S')
twit.texts <- twit.texts[, c(4,5)]
twit.texts$t.delta <- rnorm(nrow(twit.texts), mean = 1, sd = .1) * texttime
twit.texts$t.start <- twit.texts$Timestamp - twit.texts$t.delta * seconds.in.frame / 2
twit.texts$t.end <- twit.texts$Timestamp + twit.texts$t.delta * seconds.in.frame / 2
twit.texts$color <- textcolors[round(runif(nrow(twit.texts), 1, length(textcolors)))]
twit.texts$x <- rnorm(nrow(twit.texts), mean = 100, sd = 30)
twit.texts$y <- rnorm(nrow(twit.texts), mean = 56, sd = 15)
twit.texts$size <- rnorm(nrow(twit.texts), mean = 10, sd = 2)
twit.texts$opacity <- 0

# Countries to show on map
countries <- c('USSR',
               'Albania',
               'Andorra',
               'Austria',
               'Belgium',
               'Bulgaria',
               'Czechoslovakia',
               'Denmark',
               'Finland',
               'France',
               'Germany',
               'Hungary',
               'Ireland',
               'Italy',
               'Liechtenstein',
               'Luxembourg',
               'Malta',
               'Monaco',
               'Netherlands',
               'Norway',
               'Poland',
               'Portugal',
               'Romania',
               'San Marino',
               'Sicily',
               'Spain',
               'Sweden',
               'Switzerland',
               'UK',
               'Wales',
               'Yugoslavia')

# Load cities to mark on map (capitals etc)
cities <- read.csv2('cities.csv', header=F)
colnames(cities) <- c('name', 'Lat', 'Long')
cities$Lat <- as.numeric(as.character(cities$Lat))
cities$Long <- as.numeric(as.character(cities$Long))
cities$Long <- sapply(cities$Long, function(x){
  if(x < (-169)){
    x<-360+x
  }
  else{x}
})

# Load base map data
full_map <- map_data('world')
table(full_map$region)
need.map <- subset(full_map, region %in% countries & long>-25 & long<190 & lat>25)

#################
#               #
#   HISTOGRAM   #
#               #
#################

p <- ggplot()
p <- p + geom_histogram(aes(x=twits$Timestamp, fill = ..count..), binwidth = 3600)
p <- p + ylab('Количество') + xlab('Время (по часам)')
p <- p + theme(legend.position = 'none')
p <- p + ggtitle(expression('Распределение "новогодних" твитов'))
p

###################
#                 #
#   UTILITY LOOP  #
#    (PALETTE)    #
#                 #
###################

max.color <- 0
for(i in 1:frames){
  # Select only needed tweets
  frame.time <- start.date + i*seconds.in.frame
  frame.twits <- subset(twits, Timestamp <= frame.time & Timestamp > frame.time - ma.period)
  
  # Create table with values
  frame.twits <- melt(table(frame.twits$Latitude, frame.twits$Longitude))
  colnames(frame.twits) <- c('Lat', 'Long', 'Volume')
  frame.twits$Lat <- as.numeric(as.character(frame.twits$Lat))
  frame.twits$Long <- as.numeric(as.character(frame.twits$Long))
  frame.twits <- frame.twits[frame.twits$Volume>0 & 
                               frame.twits$Long>=-25 & frame.twits$Long<=190 & 
                               frame.twits$Lat>=25 & frame.twits$Lat<=85,]
  
  if(max.color < max(log(frame.twits$Volume))){
    max.color <- max(log(frame.twits$Volume))
  }
}

#################
#               #
#   MAIN LOOP   #
#               #
#################

for(i in 1:frames){
  ################
  # CALCULATIONS #
  ################
  
  # Select only needed tweets
  frame.time <- start.date + i*seconds.in.frame
  frame.twits <- subset(twits, Timestamp <= frame.time & Timestamp > frame.time - ma.period)
  
  # Create table with values
  frame.twits <- melt(table(frame.twits$Latitude, frame.twits$Longitude))
  
  # Filter empty cells
  colnames(frame.twits) <- c('Lat', 'Long', 'Volume')
  frame.twits$Lat <- as.numeric(as.character(frame.twits$Lat))
  frame.twits$Long <- as.numeric(as.character(frame.twits$Long))
  frame.twits <- frame.twits[frame.twits$Volume>0 & 
                               frame.twits$Long>=-25 & frame.twits$Long<=190 & 
                               frame.twits$Lat>=25 & frame.twits$Lat<=85,]
  
  frame.colors <- round(1 + (8*log(frame.twits$Volume)/max.color), digits=0)
  
  # Clock calculations
  curtime <- c(as.numeric(format(frame.time, '%H')), as.numeric(format(frame.time, '%M')))
  clock.center <- c(180, 35)  # Clock center
  arrow.r = c(5.5,8.8)        # Arrows length
  circdat <- draw.circle(clock.center, diameter=20)  # Clock background - 1st layer
  circdat2 <- draw.circle(clock.center, diameter=19.7) # Clock background - 2nd layer
  cirdat3 <- draw.circle(clock.center, diameter=18, npoints=13) # Hour points on clock
  
  # Clock arrows calculations
  if(curtime[1]>=12){curtime[1]=curtime[1]-12}
  hourval <- pi*(.5 - (curtime[1]+(curtime[2]/60))/6)
  minval <- pi*(.5 - curtime[2]/30)
  hour.x <- clock.center[1] + arrow.r[1] * cos(hourval)
  hour.y <- clock.center[2] + arrow.r[1] * sin(hourval) * roundcoef
  minute.x <- clock.center[1] + arrow.r[2] * cos(minval)
  minute.y <- clock.center[2] + arrow.r[2] * sin(minval) * roundcoef
  
  # Texts opacity calculation
  twit.texts$opacity <- as.numeric(by(twit.texts, 1:nrow(twit.texts), function(row){
    if(frame.time < row$t.start | frame.time > row$t.end){
      row$opacity <- 0
    } else {
      row$opacity <- 0.7 * 
        (1 - (abs(as.numeric(difftime(row$Timestamp, frame.time, unit='sec'))) / 
                (row$t.delta * seconds.in.frame / 2)))
    }
  }))
  
  ############
  # PLOTTING #
  ############
  
  # Contour map
  p <- ggplot()
  p <- p + geom_polygon(aes(x=need.map$long, y=need.map$lat, group = need.map$group),
                        colour='white', fill='grey20', alpha=.5)
  
  # Plot city points
  p <- p + geom_point(aes(cities$Long, cities$Lat), colour='skyblue', size=1.5)
  
  # Plot twitter data
  if(nrow(frame.twits)>0){
    p <- p + geom_point(aes(frame.twits$Long,frame.twits$Lat, size=frame.twits$Volume * 5), 
                        colour=twits.colors[frame.colors], alpha = .75)
  }
  
  # Plot clock
  p <- p + geom_polygon(aes(x=circdat$x,y=circdat$y), colour='grey100', fill='grey100', alpha = .5)
  p <- p + geom_polygon(aes(x=circdat2$x,y=circdat2$y), colour='grey80', fill='grey80', alpha = .5)
  p <- p + geom_point(aes(cirdat3$x, cirdat3$y), colour='skyblue')
  
  # clock arrows
  p <- p + geom_segment(aes(x=clock.center[1], y=clock.center[2], 
                            xend=hour.x, yend=hour.y), size=3, colour='dodgerblue3')
  p <- p + geom_segment(aes(x=clock.center[1], y=clock.center[2], 
                            xend=minute.x, yend=minute.y), size=1.5, colour='dodgerblue4')
  p <- p + geom_point(aes(clock.center[1], clock.center[2]), colour='blue4')
  
  # Tweet texts plotting
  p <- p + geom_text(aes(x=twit.texts$x, y=twit.texts$y, label=iconv(twit.texts$Text,to='UTF-8')), 
                     colour=twit.texts$color, size=twit.texts$size, alpha = twit.texts$opacity)
  
  # Clear axis, legend, title
  p <- p + theme(axis.line=element_blank(),axis.text.x=element_blank(),
                 axis.text.y=element_blank(),axis.ticks=element_blank(),
                 axis.title.x=element_blank(),
                 axis.title.y=element_blank(),
                 legend.position = 'none',
                 text=element_text(family='mono', size=20, face='bold', colour='dodgerblue3')
  )
  
  p <- p + scale_x_continuous(limits = c(-15, 190))
  p <- p + scale_y_continuous(limits = c(30, 82))
  p <- p + ggtitle(expression('#HappyNewYear in Russian Twitter - 2013'))
  
  # Generate filename with standart length
  f.name <- as.character(i)
  repeat{
    if(nchar(f.name) < nchar(as.character(frames))){
      f.name <- paste('0', f.name, sep='')
    } else {
      break
    }
  } 
  
  # Save frame
  ggsave(p, file=paste('frames/img', f.name, '.png', sep=''), width=6.4, height=3.6, scale = 3, dpi=100)
}