The packages we will use to make the following test are:
In order to continuously monitor the performance of GeodeciCL the following piece of code is used to generate a profile and inspect the most heavy functions inside of the package:
Function cartesian()
# Point name
Pto <- "St1"
# Longitude
g <- -71
m <- 18
s <- 44.86475
# Value in sexagesimal
sexa_long <- sexagesimal(g,m,s)
# Latitude
g <- -33
m <- 38
s <- 30.123456
# Value in sexagesimal
sexa_lat <- sexagesimal(g, m, s)
print(sexa_lat)
## [1] -33.6417
# ELLIPSOIDAL HEIGHT (h)
h <- 31.885
# Longitude and Latitude as data.frame
longlat_df <- data.frame(Pto, sexa_long, sexa_lat, h)
profile <- profvis(for (i in seq_len(100)) (cartesian(4, longlat_df, digits = 4)))
profile
Function UTMtoLongLat()
# Point name
Pto <- "St1"
# Value for East
East <- 650012.58
# Value for North
North <- 5590735.41
# East and North as data.frame
utm_df <- data.frame(Pto,East,North)
# Zone
zone <- 18
# Hemisphere could be "north" or "south"
hemisphere <- "south"
profile <- profvis(for (i in seq_len(100)) (UTMtoLongLat(utm_df, zone, hemisphere = "south", digits = 4)))
profile
Function LongLatToUTM()
# Point name
Pto <- "St1"
# Longitude
g <- -71
m <- 18
s <- 44.86475
# Value in sexagesimal
sexa_long <- sexagesimal(g, m, s)
# Latitude
g1 <- -33
m1 <- 12
s1 <- 27.11457
# Value in sexagesimal
sexa_lat <- sexagesimal(g1, m1, s1)
# Longitude and Latitude as data.frame
longlat_df <- data.frame(Pto,sexa_long,sexa_lat)
profile <- profvis(for (i in seq_len(100)) (LongLatToUTM(longlat_df, units = 'm', digits = 4)))
profile