Warning in fun(libname, pkgname): mzR has been built against a different Rcpp version (1.0.14)
than is installed on your system (1.1.0). This might lead to errors
when loading mzR. If you encounter such issues, please send a report,
including the output of sessionInfo() to the Bioc support forum at
https://support.bioconductor.org/. For details see also
https://github.com/sneumann/mzR/wiki/mzR-Rcpp-compiler-linker-issue.
data("heart_data")data("step_data")result<-lagci::calculate_lagged_correlation( x =heart_data$heart, y =step_data$step, time1 =heart_data$time, time2 =step_data$time, time_tol =0.5, step =1/60, align_method ="linear", cor_method ="spearman")
8.2 Alignment Plot
Here is an example plot:
This call draws an alignment view of the two series in result at the peak lag (which = "max"), coloring the x-series blue and the y-series red (x_color, y_color) with axis labels set by x_name = "x" and y_name = "y".
It limits the plotted x-values to the numeric range c(1, 100000) (x_limit), plots points for matched samples (add_point = TRUE) with sizes controlled by x_point_size and y_point_size, and renders any unmatched observations with a tiny marker (non_matched_point_size = 0.1) so they’re visible but unobtrusive.
With integrated = FALSE the two time series are shown on separate tracks rather than overlaid; add_connect_line = FALSE suppresses segment lines between matched pairs (turn this on to emphasize pairings).
Finally, time_gap = 12 spaces major time ticks about every 12 hours, which helps readability over long windows; if the figure looks cramped, either increase time_gap, reduce the point sizes, and if you want a direct overlay switch to integrated = TRUE.
These two calls produce the same alignment view except for whether matched pairs are drawn as points.
p_points enables add_point = TRUE, so matched x–y samples appear as dots (sizes set by x_point_size and y_point_size), while unmatched observations are shown very small via non_matched_point_size = 0.1;
this is useful to judge how dense and well-aligned the pairings are. p_points_no switches add_point = FALSE, hiding those pairing dots so you can focus on the aligned trajectories without point clutter.
In both, x_limit = c(1, 10000) restricts the plotted range of the x-series (handy for clipping extreme values). Print both objects (p_points; p_points_no) to compare clarity; if overplotting remains heavy, shrink point sizes or widen the limits, and if you want an overlay instead of separate tracks, set integrated = TRUE.
