compmus_summarise: Summarise possibly vector-valued columns

In jaburgoyne/compmus: Support Functions for Computational Musicology

Summarise possibly vector-valued columns

Description

Summarises vector-based features in nested list columns.

Usage

compmus_summarise(dat, feature, method = "mean", norm = "id", na.rm = FALSE)

compmus_summarize(dat, feature, method = "mean", norm = "id", na.rm = FALSE)

Arguments

dat	A tibble containing list columns.
feature	The vector-valued column of dat to summarise (unquoted).
method	A character string indicating which summarisation method to use (see Details). Default is the arithmetic mean.
norm	An optional character string indicating the method for pre-normalising each vector with compmus_normalise.
na.rm	Remove NA values?

Details

The following methods are supported.

Functions

• compmus_summarize: Summarize possibly vector-valued columns

Central Tendency

mean

arithmetic mean

aitchison,acentre,acenter

Aitchison centre

rms

root mean square

max

maximum

Dispersion

sd

standard deviation

asd

standard deviation of clr-transformed components

sdsq

standard deviation of squares

varration

variation ratio

Examples

library(tidyverse)
get_tidy_audio_analysis("5ZLkc5RY1NM4FtGWEd6HOE") %>%
  compmus_align(bars, segments) %>%
  select(bars) %>%
  unnest(bars) %>%
  mutate(
    pitches =
      map(
        segments,
        compmus_summarise, pitches,
        method = "rms", norm = "euclidean"
      )
  )

jaburgoyne/compmus documentation built on Feb. 26, 2023, 3:44 a.m.