cmps_segment_plot.RdThis function plots the selected basis segment with the comparison signature. One can visualize the
scaled segment and its corresponding cross-correlation curve. The number of marked correlation peaks
at each segment scale is determined by npeaks_set of extract_feature_cmps. The red vertical dashed
line indicates the congruent registration position for all segments; the green vertical dashed line
indicates the position of the consistent correlation peak (if any); the blue vertical dashed line
indicates the tolerance zone (determined by Tx)
cmps_segment_plot(cmps_result, seg_idx = 1)a list generated by extract_feature_cmps. cmps_result is required to have
the following names: parameters, congruent_pos, segments, nseg, i.e. one should at least have
include = c("parameters", "congruent_pos", "segments", "nseg") when computing cmps_result.
However, include = "full_result is still recommended.
an integer. The index of a basis segment that we want to plot for.
a list of n elements, where n is the length of npeaks_set, i.e. the number of scales for
each basis segment. And each one of these n elements is also a list, a list of two plots:
segment_plot: The basis segment of current scale is plotted at different positions where the
segment obtains correlation peak. The comparison signature is also plotted.
scale_ccf_plot: This is the plot of the cross-correlation curve between the comparison signature
and the segment of the current scale.
library(cmpsR)
library(ggpubr)
#> Loading required package: ggplot2
data("bullets")
land2_3 <- bullets$sigs[bullets$bulletland == "2-3"][[1]]
land1_2 <- bullets$sigs[bullets$bulletland == "1-2"][[1]]
# compute cmps
# algorithm with multi-peak insepction at three different segment scales
cmps_with_multi_scale <- extract_feature_cmps(land2_3$sig, land1_2$sig, include = "full_result" )
# generate plots using cmps_signature_plot
seg_plot <- cmps_segment_plot(cmps_with_multi_scale, seg_idx = 3)
pp <- ggarrange(plotlist = unlist(seg_plot, recursive = FALSE), nrow = 3, ncol = 2)
#> Warning: Removed 14 row(s) containing missing values (geom_path).