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.

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. heel along x with y = 0. (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

## Value

dataframe of crosscut

## Details

# TODO: are missing values only on the right hand side (leading shoulder)?

## Examples

if (FALSE) {
# 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()
}