This documentation is for development version 0.18.dev0.

mne.time_frequency.fit_iir_model_raw

mne.time_frequency.fit_iir_model_raw(raw, order=2, picks=None, tmin=None, tmax=None, verbose=None)[source]

Fit an AR model to raw data and creates the corresponding IIR filter.

The computed filter is fitted to data from all of the picked channels, with frequency response given by the standard IIR formula:

\[H(e^{jw}) = \frac{1}{a[0] + a[1]e^{-jw} + ... + a[n]e^{-jnw}}\]
Parameters:
raw : Raw object

an instance of Raw.

order : int

order of the FIR filter.

picks : str | list | slice | None

Channels to include. Slices and lists of integers will be interpreted as channel indices. In lists, channel type strings (e.g., ['meg', 'eeg']) will pick channels of those types, channel name strings (e.g., ['MEG0111', 'MEG2623'] will pick the given channels. Can also be the string values “all” to pick all channels, or “data” to pick data channels. None (default) will pick good data channels.

tmin : float

The beginning of time interval in seconds.

tmax : float

The end of time interval in seconds.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

Returns:
b : ndarray

Numerator filter coefficients.

a : ndarray

Denominator filter coefficients

Examples using mne.time_frequency.fit_iir_model_raw