ave_cross_power_over_splices function

Calculate mean average cross power over splices using a splicing table

Randomly generates splices from a splicing table and calculates average cross power for each segment and splice. Calculates the mean average cross power over the random splices for each segment and period. Compares with the average cross power for the original splice.

ave_cross_power_over_splices(
  jv,
  splicing_df,
  num_splices,
  columns,
  sampling_type = "offset",
  rejection_list = list(),
  include_original = TRUE,
  show_plot = TRUE
)

Arguments

• jv: JoinedView object.
• splicing_df: Splice object.
• num_splices: number of randomly chosen splices.
• columns: name of data columns on which to calculate average cross power.
• sampling_type: either 'offset' or 'gap'.
• rejection_list: list of splice objects that random splices must not overlap.
• include_original: include the original splice in output? (Default is TRUE).
• show_plot: show a plot? (Default is TRUE).

Returns

data.frame of splice segments and their average cross power.

Examples

r <- get_sample_recording()
fv_list <- get_filtered_views(r, data_points = "Nose", n = 41, p = 3)
jv <- get_joined_view(fv_list)

d <- get_duration_annotation_data(r)
splicing_tabla_solo_df <- splice_time(d,
  expr = "Tier == 'INTERACTION' & Comments == 'Mutual look and smile'")

# Only do the first splice for sample data
mean_ave_cross_power_df <- ave_cross_power_over_splices(jv,
  splicing_tabla_solo_df[1,], num_splices = 10,
  columns = c('Nose_x_Central_Sitar', 'Nose_y_Central_Sitar'), show_plot = TRUE)

See Also

Other statistical and analysis functions: apply_column_spliceview(), apply_segment_spliceview(), 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_gap_splice(), sample_offset_splice(), summary_onsets(), visualise_sample_splices()