df <- read_csv('data/corrected_conductivity_working.csv')

df_tt <- as_tbl_time(df, index = Time)

We can enter some input data, such as the distance, the mass and the time of injection. From these we can calculate Q and some velocities.

dist <- 20

mass3 <- 312.6

injTime3 <- "15:41:45"

We can use the plotly package to make an intereactive plot. This allows us to hover on the figure and determine what period of data we want for each BTC.

ggplotly(df_tt %>% 
           ggplot(aes(x = Time, y = Cond_cor))+ 
           geom_point()
           )

We see that we have 3 BTCs. We want to break those into separate data frames. Let’s do that for injection 3 now. We know it started at 15:41:45 and we can cut it off at 15:49:30. We can use the tibble time package to filter by time.

# Here we filter from the injection time that we defined above to the end of the time series. 
inj_3 <- df_tt %>% 
  filter_time(injTime3 ~ "15:49:30")

# Then we do a background correction. 
inj_3 <- inj_3 %>% 
  mutate(bg_sc = Cond_cor - 0.756) %>% 
  filter(bg_sc >0)

This is the section where we do the intgration.

inj_3 <- inj_3 %>% 
  mutate(NaCl = bg_sc/2) %>% 
  mutate(IntC_s1 = NaCl + lag(NaCl, default = 0)) %>% 
  mutate(IntC = cumsum(IntC_s1 * 0.5 * 5)) %>% 
  mutate(recovery = IntC/max(IntC))

From that integration Q is calculated as:

Q3 <- mass3/max(inj_3$IntC)

We want some velocities: peak, 5%, median and 95%. I’ll do 5% here. We will use some indexing to return the row at which recovery equals 5%.

# This just makes a column with time since injection in seconds. 
inj_3 <- inj_3 %>% 
  mutate(time_since = Run_time - 3860)

# Using plotly I know the peak was at 40 s
peak = 40

# So the velocity to peak is: 
peak_velo <- dist/peak

# Then we can do the indexing and calculate the arrival velocity, which is the velocity to 5% recovery. 
fiveRcovery.idx1 <-which.min(abs(inj_3$recovery - .05))

five_time <- inj_3[5, 11]

five_velo <- dist/five_time

Then we can make a figure of the recovery.

inj_3 %>% 
  ggplot(aes(x = time_since, y = IntC)) +
  geom_point() +
  ylab("Integral NaCl (g*s/L)") + 
  xlab("Time") +
  theme_linedraw(base_size = 16) +
  ggtitle("Injection 3")