Randomly create matching segments from a splicing table without overlaps

Works by randomly varying the gaps between segments assuming that the gap number follow a Poisson process with rate given by the average sample gap length in the input splice. Durations of segments remain the same.

Usage

sample_gap_splice(splicing_dfr, v, num_splices, rejection_list = list())

Arguments

splicing_dfr: Splice object.
v: View object.
num_splices: number of random splices to generate.
rejection_list: list of Splice objects for rejection.

Value

list of splicing data.frames.

Details

Uses rejection sampling to avoid overlaps with the input segments and additional segments from a list of splices.

Other statistical and analysis functions: apply_column_spliceview(), apply_segment_spliceview(), ave_cross_power_over_splices(), ave_cross_power_spliceview(), ave_power_over_splices(), ave_power_spliceview(), calculate_ave_cross_power1(), calculate_ave_power1(), compare_ave_cross_power1(), compare_ave_power1(), compare_avg_cross_power2(), compare_avg_power2(), difference_onsets(), pull_segment_spliceview(), sample_offset_splice(), summary_onsets(), visualise_sample_splices()

Examples

r1 <- get_sample_recording()
d1 <- get_duration_annotation_data(r1)
rv1 <- get_raw_view(r1, "Central", "", "Sitar")
splicing_df <- splice_time(d1, tier ='INTERACTION', comments = 'Mutual look and smile')
# Only first segment relevant for sample data
x <- sample_gap_splice(splicing_df[1,], rv1, num_splices = 10)
#> Accepted splices: 10