source(paste0(mydir,"len_color_scales.R"))  #custom color scale code copied below

fredr_set_key("YOURKEY")

df <- 
  fredr(series_id = "MORTGAGE30US",
        observation_start = as.Date("1971-04-01")
  ) %>%
  #mutate(decade=paste0(floor(year(date)/10),"0s"))%>%
  mutate(decade=case_when(year(date)<1981~"1971-1980",
                          year(date)<1991~"1981-1990",
                          year(date)<2001~"1991-2000",
                          year(date)<2011~"2001-2010",
                          T~"2011-2020")) %>%
  
  group_by(decade) %>% 
  # get decade average
  mutate(vbar=mean(value)) %>% ungroup()

mydate <- format(max(df$date),"%B %d, %Y")

myxy2<- function(dd, in.df=df){
  x<-filter(in.df,decade==dd)$value
  outdf<- data.frame(
    x=density(x)$x[which.max(density(x)$y)],  #find maximum density (in y dimension)
    y=max(density(x)$y,na.rm=T)
  )
}

df.text <- data.frame(decade=unique(df$decade)) %>% mutate(xy=map(decade,myxy2)) %>% unnest(xy) 


myr0 <- function(x, a=0.02){
  geom_ribbon(alpha=a, color=NA, aes(ymin=0,ymax=min(x, value)))    
}

myr <- function(x, a=0.02){
  geom_ribbon(alpha=a, color=NA, aes(ymin=min(x, value )))    
}

df_labels <- df %>% group_by(decade) %>% summarize(date=median(date),value=mean(value,na.rm=TRUE))

# Density + mortgage rate trend (colorful)
g.dens.plain <- 
  ggplot(data= df,
         aes(x=value, fill=decade,color=decade))+
  geom_density(alpha=0.25,color=NA)+
  geom_rug(sides="b",alpha=0.25)+
  theme_minimal()+
  scale_y_continuous(breaks=NULL,sec.axis=dup_axis())+
  theme(legend.position="none",
        panel.grid.minor=element_blank(),
        panel.grid.major=element_blank(),
        plot.title=element_text(face="bold",hjust=0,size=rel(1.2)),
        plot.caption=element_text(hjust=0))+
  ggrepel::geom_text_repel(data=df.text,aes(label=decade, x=x,y=y),size=8)+
  labs(x="30-year fixed mortgage rate (%)",
       title="Estimated density over weekly  values",y="",
       subtitle=paste0("Ticks at bottom weekly observations, dotted line value for ",mydate))+
  scale_color_mycol(palette="mixed")+
  scale_fill_mycol(palette="mixed")+
  geom_vline(aes(xintercept=last(value)),linetype=2)

g.line<-
  ggplot(data=df ,
         aes(x=date,y=value, ymax= value , fill=decade,color=decade))+
  geom_line()+
  geom_ribbon(alpha=0.5, color=NA, aes(ymin=vbar))+
  map(c(0,pull(df,value) %>% last()) %>% pretty(12), myr, a=0.01)+
  geom_hline(aes(yintercept=last(value)), linetype=2)+
  geom_line(aes(y=vbar),linetype=3)+
  geom_line(size=1.05)+
  theme_minimal()  +
  geom_label(data=df_labels, aes(y=1,label=paste0(decade,": ",format(round(value,1),nsmall=1))),color="white")+
  theme(legend.position="none",
        plot.title=element_text(face="bold",size=rel(1.2)),
        plot.caption=element_text(hjust=0))+
  scale_x_date(date_breaks="10 years",date_labels="%Y")+
  labs(x="date (weekly)", 
       y="", subtitle=paste0("U.S. Weekly Average 30-year fixed mortgage rate April 2, 1971 to ",
                             mydate,
                             "\nLine weekly value, dark shaded area from decade average to weekly value"),
       title="Mortgage rates over 5 decades",
       caption="@lenkiefer Source: Freddie Mac Primary Mortgage Market Survey") +  
  scale_color_mycol(palette="mixed")+
  scale_fill_mycol(palette="mixed")


cowplot::plot_grid(g.line,g.dens.plain,ncol=1,rel_heights=c(3,2))

# Mortgage trends (static) line plot

df2 <- mutate(df,
              id=row_number(),
              dind=case_when(id<52~0,
                             value==max(value)~500,
                             value==min(value)~500,
                             T~1),
              label=as.character(round(value,2)))
df2b <- filter(df2, dind>1) %>% mutate(dind=250)
df2 <- bind_rows(df2, df2b) %>%
  arrange(date) %>%
  mutate(ind=cumsum(dind))

g <- 
  ggplot(data=df2, aes(x=date,y=value,label=label))+
  geom_line(color="dodgerblue",size=1.05)+
  theme_minimal()+
  scale_y_continuous(sec.axis=dup_axis())+
  theme(legend.position="none",
        plot.title=element_text(face="bold",hjust=0,size=rel(1.2)),
        plot.caption=element_text(hjust=0))+
  labs(x="date (weekly)", y="",
       title="Mortgage Rate Trends",
       subtitle="U.S. Weekly Average 30-year fixed mortgage rate (percent)",
       caption=paste0("@lenkiefer Source: Freddie Mac Primary Mortgage Market Survey through ",mydate))
g+  geom_text(data=.%>% filter(value==max(value)|value==min(value)),color="dodgerblue",nudge_x=30,hjust=0)

# animated plot

a.mtg <- g+ geom_point(color="dodgerblue",size=4,alpha=0.25) +geom_text(color="dodgerblue",nudge_x=30,hjust=0)+
transition_reveal(ind)+view_follow()
animate(a.mtg,end_pause=25, nframes=350,fps=12,width=800,height=450)
save_animation(last_animation(), file=paste0(mydir,"mtg_trend.gif"))

# Function for colors ----
# adapted from https://drsimonj.svbtle.com/creating-corporate-colour-palettes-for-ggplot2
#####################################################################################
## Make Color Scale ----  ##
#####################################################################################
my_colors <- c(
  "green"      = rgb(103,180,75, maxColorValue = 256),
  "green2"      = rgb(147,198,44, maxColorValue = 256),
  "lightblue"  =  rgb(9, 177,240, maxColorValue = 256),
  "lightblue2" = rgb(173,216,230, maxColorValue = 256),
  'blue'       = "#00aedb",
  'red'        = "#d11141",
  'orange'     = "#f37735",
  'yellow'     = "#ffc425",
  'gold'       = "#FFD700",
  'light grey' = "#cccccc",
  'purple'     = "#551A8B",
  'dark grey'  = "#8c8c8c")


my_cols <- function(...) {
  cols <- c(...)
  if (is.null(cols))
    return (my_colors)
  my_colors[cols]
}


my_palettes <- list(
  `main`  = my_cols("blue", "green", "yellow"),
  `cool`  = my_cols("blue", "green"),
  `cool2hot` = my_cols("lightblue2","lightblue", "blue","green", "green2","yellow","gold", "orange", "red"),
  `hot`   = my_cols("yellow", "orange", "red"),
  `mixed` = my_cols("lightblue", "green", "yellow", "orange", "red"),
  `mixed2` = my_cols("lightblue2","lightblue", "green", "green2","yellow","gold", "orange", "red"),
  `mixed3` = my_cols("lightblue2","lightblue", "green", "yellow","gold", "orange", "red"),
  `mixed4` = my_cols("lightblue2","lightblue", "green", "green2","yellow","gold", "orange", "red","purple"),
  `mixed5` = my_cols("lightblue","green", "green2","yellow","gold", "orange", "red","purple","blue"),
  `mixed6` = my_cols("green", "gold", "orange", "red","purple","blue"),
  `grey`  = my_cols("light grey", "dark grey")
)


my_pal <- function(palette = "main", reverse = FALSE, ...) {
  pal <- my_palettes[[palette]]
  
  if (reverse) pal <- rev(pal)
  
  colorRampPalette(pal, ...)
}


scale_color_mycol <- function(palette = "main", discrete = TRUE, reverse = FALSE, ...) {
  pal <- my_pal(palette = palette, reverse = reverse)
  
  if (discrete) {
    discrete_scale("colour", paste0("my_", palette), palette = pal, ...)
  } else {
    scale_color_gradientn(colours = pal(256), ...)
  }
}



scale_fill_mycol <- function(palette = "main", discrete = TRUE, reverse = FALSE, ...) {
  pal <- my_pal(palette = palette, reverse = reverse)
  
  if (discrete) {
    discrete_scale("fill", paste0("my_", palette), palette = pal, ...)
  } else {
    scale_fill_gradientn(colours = pal(256), ...)
  }
}