tempogram: Compute a tempogram from Spotify segment onsets

In jaburgoyne/compmus: Support Functions for Computational Musicology

Compute a tempogram from Spotify segment onsets

Description

Computes a Fourier-based tempogram based on onsets of Spotify segments. Returns a tibble with time, bpm, and power columns. Power is normalised to a max of 1 (Chebyshev norm) within each time point.

Usage

tempogram(
  track_analysis,
  window_size = 8,
  hop_size = 1,
  cyclic = FALSE,
  bpms = if (cyclic) 80:160 else 30:600,
  window_function = signal::hamming
)

Arguments

track_analysis	Spotify audio analysis as returned by get_tidy_audio_analysis.
window_size	Window size in seconds (default 8).
hop_size	Hop size in seconds (default 1).
cyclic	Boolean stating whether the tempogram should be cyclic (default not).
bpms	Vector of tempi in beats per minute to include in the tempogram (default 30–200 for non-cyclic and 80–160 for cyclic, inclusive of all integer tempi).
window_function	Window function for the Fourier analysis (default Hamming).

Examples

library(tidyverse)
get_tidy_audio_analysis("6PJasPKAzNLSOzxeAH33j2") %>%
  tempogram(window_size = 4, hop_size = 2)

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