diagnose_filter: Diagnose digital filter

In ravetools: Signal and Image Processing Toolbox for Analyzing Intracranial Electroencephalography Data

Diagnose digital filter

Description

Generate frequency response plot with sample-data simulation

Usage

diagnose_filter(
  b,
  a,
  fs,
  n = 512,
  whole = FALSE,
  sample = stats::rnorm(n, mean = sample_signal(n), sd = 0.2),
  vlines = NULL,
  xlim = "auto",
  cutoffs = c(-3, -6, -12)
)

Arguments

b	the moving-average coefficients of an ARMA model
a	the auto-regressive coefficients of an ARMA filter; default is 1
fs	sampling frequency in Hz
n	number of points at which to evaluate the frequency response; default is 512
whole	whether to evaluate beyond Nyquist frequency; default is false
sample	sample signal of length n for simulation
vlines	additional vertical lines (frequencies) to plot
xlim	frequency limit of frequency response plot; default is "auto", can be "full" or a numeric of length 2
cutoffs	cutoff decibel powers to draw on the frequency plot, also used to calculate the frequency limit when xlim is "auto"

Value

Nothing

Examples

library(ravetools)

# sample rate
srate <- 500

# signal length
npts <- 1000

# band-pass
bpass <- c(1, 50)

# Nyquist
fn <- srate / 2
w <- bpass / fn

# ---- FIR filter ------------------------------------------------
order <- 160

# FIR1 is MA filter, a = 1
filter <- fir1(order, w, "pass")

diagnose_filter(
  b = filter$b, a = filter$a, n = npts,
  fs = srate, vlines = bpass
)

# ---- Butter filter --------------------------------------------
filter <- butter(3, w, "pass")

diagnose_filter(
  b = filter$b, a = filter$a, n = npts,
  fs = srate, vlines = bpass
)

ravetools documentation built on Sept. 11, 2024, 9:06 p.m.