Code to reproduce figures for TWS presentation

muld915-spring2014.R

dat <- readr::read_csv('sandbox/test-muld.csv')

df <- dat %>%
  filter(ndowid == 915)

mig_df <- df %>%
  filter(timestamp >= mdy('1/1/2014') &
           timestamp <= mdy('6/30/2014'))

mig_df <- mig_df %>%
  mutate(nsd = calc_nsd(x, y, normalize = T)) %>%
  filter(nsd < .25)

## trajectory plot for presentation 
ggplot(mig_df, aes(x = x, y = y, color = as.numeric(timestamp))) +
  geom_point(alpha = .3) +
  viridis::scale_color_viridis(option = 'viridis') +
  theme_void() +
  coord_equal() +
  theme( legend.position = 'none')

## focused trajectory plot
mig_df %>% 
  filter(timestamp < mdy('3/12/2014')) %>% 
  ggplot(aes(x = x, y = y, color = as.numeric(timestamp))) +
  geom_point(alpha = .3) +
  viridis::scale_color_viridis() +
  theme_void() +
  coord_equal() +
  theme( legend.position = 'none')

## NSD plot for presentation
ggplot(mig_df, aes(x = timestamp, y = nsd, color = timestamp)) +
  geom_point(alpha = .4) +
  viridis::scale_color_viridis() +
  theme_minimal() +
  theme( legend.position = 'none' )

# create lch for beginning ----------------------------------------------------
lch_start <- locoh(dat = mig_df %>% filter(nsd < .125), c('x', 'y', 'timestamp', 'ndowid'))

## plot start
ggplot() +
  geom_path(data = lch_start$mcp_df, aes(x = x, y = y, color = id, group = id), alpha = .25) +
  viridis::scale_color_viridis() +
  coord_equal() +
  theme_void() +
  theme(
    legend.position = 'none'
  )

# create lch for end of migration ---------------------------------------------
end_df <- mig_df %>% 
  arrange(desc(timestamp)) %>% 
  mutate(nsd = calc_nsd(x, y, T)) %>% 
  filter(nsd < .125)

ggplot(end_df, aes(x = timestamp, y = nsd, color = timestamp)) +
  geom_point(alpha = .4) +
  viridis::scale_color_viridis() +
  theme_minimal() +
  theme( legend.position = 'none' )

lch_end <- locoh(dat = end_df, c('x', 'y', 'timestamp', 'ndowid'))

# plot end
ggplot() +
  geom_path(data = lch_end$mcp_df, aes(x = x, y = y, color = id, group = id), alpha = .25) +
  viridis::scale_color_viridis() +
  coord_equal() +
  theme_void() +
  theme(
    legend.position = 'none'
  )

# plot start and end together ----
## cool figure bro
ggplot() +
  geom_point(data = mig_df, aes(x = x, y = y), color = 'lightgrey', alpha = .5) +
  geom_path(data = lch_start$mcp_df, aes(x = x, y = y, group = id), alpha = .25, color = ggthemes::gdocs_pal()(2)[1]) +
  geom_path(data = lch_end$mcp_df, aes(x = x, y = y, group = id), alpha = .25, color = ggthemes::gdocs_pal()(2)[2]) +
  coord_equal() +
  theme_void() +
  theme(
    legend.position = 'none'
  )

# filter lch start ----
hullset_start <- filter_hullset(lch_start)

## plot it
ggplot() +
  geom_path(data = hullset_start$hullset, aes(x = x, y = y, group = id), alpha = .25, color = ggthemes::gdocs_pal()(2)[1]) +
  viridis::scale_color_viridis() +
  coord_equal() +
  theme_void() +
  theme(
    legend.position = 'none'
  )

## find start time
start_date <- hullset_start$meta %>%
  extract2('start_date') %>%
  max()
start_date

# filter lch end ----
hullset_end <- filter_hullset(lch_end)

## plot it
ggplot() +
  geom_path(data = hullset_end$hullset, aes(x = x, y = y, group = id), alpha = .25, color = ggthemes::gdocs_pal()(2)[2]) +
  viridis::scale_color_viridis() +
  coord_equal() +
  theme_void() +
  theme(
    legend.position = 'none'
  )

## find end date
end_date <- hullset_end$meta %>%
  extract2('start_date') %>%
  min()
end_date

# label migration ----
mig_df$migratory <- mig_df$timestamp >= start_date & mig_df$timestamp <= end_date

## plotit - trajectory
ggplot(mig_df, aes(x = x, y = y, color = migratory)) +
  geom_point(alpha = .3) +
  ggthemes::scale_color_gdocs(list(title = 'Migratory')) +
  theme_void() +
  coord_equal()

## plotit - nsd
ggplot(mig_df, aes(x = timestamp, y = nsd, color = migratory)) +
  geom_point(alpha = .3) +
  ggthemes::scale_color_gdocs(list(title = 'Migratory')) +
  theme_minimal()