How to convert date to lunar date in R? - r

Question

I have fisheries data set ( sample data set) . I'm going to study moons impact on the fish catch. I used lunar package to find moon phase of each fishing day.
library(lunar)
data$lunar_phase <- lunar.phase(as.Date(data$fdate))
output as follows
fdate lunar_phase
29/3/2006 3.51789248
28/3/2006 1.255536876
24/3/2006 4.559716361
26/3/2006 2.801242263
25/3/2006 0.538886659
lunar package can be used to categorize lunar phase into 4 or 8 periods.
I need to convert the fishing date to relative lunar cycle date. Lunar cycle is 29.53 days. If lunar day 0 = full moon, then find lunar cycle dates of other dates.
Is there any possible way to do that?
Expected output may be as follows
fdate lunar_day
29/3/2006 6
28/3/2006 4
24/3/2006 10
26/3/2006 5
25/3/2006 1

Answer 1

I don't know of a package that calculates "lunar day" from a date. In theory you could do it from your dataset, by identifying the maximum and minimum values for phase, then converting phases to percentages and rounding up as a proportion of 29.53.
However, the lunar package also calculates illumination (as a fraction of visible surface). I think this is a good proxy for lunar day and also gives you a physical value, rather than something more arbitrary.
Using your data, it's clear that new moon occurs near the start of the month:
library(tidyverse)
library(lunar)
sample_data <- read_csv("sample_data.csv")
sample_data %>%
mutate(Date = as.Date(fdate, "%d/%m/%Y"),
illum = lunar.illumination.mean(Date)) %>%
ggplot(aes(Date, illum)) + geom_point()
We could also fill in the missing dates, which makes the lunar cycle apparent:
all_dates <- data.frame(Date = seq.Date(min(as.Date(sample_data$fdate, "%d/%m/%Y")),
max(as.Date(sample_data$fdate, "%d/%m/%Y")),
by = "1 day")) %>%
mutate(illum = lunar.illumination.mean(Date))
all_dates %>%
ggplot(aes(Date, illum)) + geom_point()
Now, assuming your dataset has a column named catch, we could begin analysis by joining the catch data with the full date range, then plotting catch and lunar illumination. This dataset may also be used for regression, correlation etc.
# simulated catch data
set.seed(123)
sample_data <- sample_data %>%
mutate(catch = rnorm(16, 100, 30))
all_dates %>%
left_join(mutate(sample_data, Date = as.Date(fdate, "%d/%m/%Y"))) %>%
select(Date, illum, catch) %>%
gather(variable, value, -Date) %>%
ggplot(aes(Date, value)) +
geom_point() +
facet_grid(variable~., scales = "free_y")

Answer 2

For each subsequent day from new moon until full moon and the vice versa, the lunar phase increases by 0.212769. So when you run the code below, you get an approximated lunar day :
library(lunar)
lunar_day <- lunar.phase(as.Date("2020-07-21")) /(0.212769)
round(lunar_day, 0)
This works fine , approximately, to 29 days and starting again with new moon. A tidyverse code is given below:
library(lunar)
library(tidyverse)
new_data <-
data %>%
mutate(lunar_day = lunar.phase(as.Date(fdate)) / 0.212769) %>%
mutate_if(is.numeric(lunar_day),round, 0)
Post 14th day, it is the cycle from full-moon to new moon. A function can be written where the cycle can be represented as {new, wax-1, wax-2,...., full, wane-1, wane-2,...., new}.