Q-transform of time series — qtransform • beacon

Perform a Q-transform over a time series and interpolate to desired resolution.

Usage

qtransform(
  ts,
  delta_t = NULL,
  delta_f = NULL,
  logfsteps = NULL,
  frange = NULL,
  qrange = c(4, 64),
  mismatch = 0.2,
  return_complex = FALSE
)

Arguments

ts: A ts object. Input time series.
delta_t: A numeric. Time resolution (optional).
delta_f: A numeric. Frequency resolution (optional, mutually exclusive with logfsteps).
logfsteps: A numeric. Number of log-spaced frequency bins (mutually exclusive with delta_f).
frange: A numeric vector. Frequency range (Hz). Default: c(30, Nyquist × 8).
qrange: A numeric vector. Q value range (default: c(4, 64)).
mismatch: A numeric. Mismatch between tiles (default: 0.2).
return_complex: Logical. Whether to return complex data instead of power (default: FALSE).

Value

A list with:

times: Time axis (s)
freqs: Frequency axis (Hz)
q_plane: 2D matrix of interpolated Q-transform (power or complex)

Details

This is a ported implementation based on the original pycbc.filter.qtransform function from the PyCBC library.

References

PyCBC source: https://pycbc.org/pycbc/latest/html/_modules/pycbc/filter/qtransform.html