Compare average power distribution using a splicing table
compare_ave_power1( jv, splicing_df, splice_name, num_segment_samples, num_splice_samples, column, sampling_type = "offset", rejection_list = list(), show_plot = TRUE )
jv
: JoinedView
object.splicing_df
: Splice
object.splice_name
: Name to give randomly spliced segments.num_segment_samples
: number of segments to randomly sample.num_splice_samples
: number of randomly chosen splices.column
: name of data column on which to calculate average power.sampling_type
: either 'offset' or 'gap'.rejection_list
: list of splice objects that random splices must not overlap.show_plot
: show the plot? (Default is TRUE).list of two data frames: one containing average power on the first splice and the other containing the average power on randomly generated splices.
r <- get_sample_recording() fv_list <- get_filtered_views(r, data_points = 'Nose', n = 41, p = 3) jv <- get_joined_view(fv_list) splicing_df <- splice_time(list(a = c(0, 5), b = c(10, 15))) output_list <- compare_ave_power1(jv, splicing_df, 'Random Splices', 5, 5, 'Nose_x_Central_Tabla')
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_avg_cross_power2()
, compare_avg_power2()
, difference_onsets()
, pull_segment_spliceview()
, sample_gap_splice()
, sample_offset_splice()
, summary_onsets()
, visualise_sample_splices()
Useful links