cmps_segment_plot: Plot the selected basis segment and its cross-correlation...

In cmpsR: R Implementation of Congruent Matching Profile Segments Method

Plot the selected basis segment and its cross-correlation curve at all scales based on the results of CMPS algorithm

Description

This 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)

Usage

cmps_segment_plot(cmps_result, seg_idx = 1)

Arguments

cmps_result	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.
seg_idx	an integer. The index of a basis segment that we want to plot for.

Value

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.

Examples

library(cmpsR)
library(ggpubr)

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)

cmpsR documentation built on July 18, 2022, 9:07 a.m.