Identifies a "representative" cross section for a bullet land engraved area. Striation marks on a bullet land are best expressed at the heel (bottom) of a bullet where break-off is still problematic. Using cross-correlation we identify a cross section that is the closest to the bottom of the bullet but does not suffer from break-off. If the resulting cross section is equal to the maximum of the search area (defined in xlimits), there should be some investigation to determine whether this cross section is usable, due to the risk of tank rash. TODO: are missing values only on the right hand side (leading shoulder)?
Usage
x3p_crosscut_optimize(
x3p,
distance = 25,
ylimits = c(50, NA),
minccf = 0.9,
span = 0.03,
percent_missing = 50
)Arguments
- x3p
if character, path to an x3p file. Otherwise a scan in x3p format is expected. The assumption is that the scan is taken across the bullet land, with an upright bullet, i.e. bullet tip points upward. (0,0) defines the bottom left corner of the scan.
- distance
positive numeric value indicating the distance between cross sections to use for a comparison
- ylimits
vector of values between which to check for cross sections in a stable region. In case the upper limit is not specified explicitly, it is determined by the scan itself.
- minccf
minimal value of cross correlation to indicate a stable region
- span
The span for the loess smooth function
- percent_missing
maximum percent missing values allowed on the crosscut to be picked
Examples
if (FALSE) { # \dontrun{
# Set the data up to be read in, cleaned, etc.
library(bulletxtrctr)
library(x3ptools)
library(ggplot2)
example_data <- bullet_pipeline(
location = list(Bullet1 = c(hamby252demo$bullet1[3])),
stop_at_step = "clean",
x3p_clean = function(x) x %>%
x3p_scale_unit(scale_by=10^6) %>%
rotate_x3p(angle = -90) %>%
y_flip_x3p()
)
x3p_crosscut_optimize(example_data$x3p[[1]])
x3p_crosscut(example_data$x3p[[1]], 75) %>%
ggplot(aes(x = x, y = value)) + geom_line()
} # }