mne.io.read_raw_fif#

mne.io.read_raw_fif(fname, allow_maxshield=False, preload=False, on_split_missing='raise', verbose=None)[source]#

Reader function for Raw FIF data.

Parameters:
fnamestr | file-like

The raw filename to load. For files that have automatically been split, the split part will be automatically loaded. Filenames should end with raw.fif, raw.fif.gz, raw_sss.fif, raw_sss.fif.gz, raw_tsss.fif, raw_tsss.fif.gz, or _meg.fif. If a file-like object is provided, preloading must be used.

Changed in version 0.18: Support for file-like objects.

allow_maxshieldbool | str (default False)

If True, allow loading of data that has been recorded with internal active compensation (MaxShield). Data recorded with MaxShield should generally not be loaded directly, but should first be processed using SSS/tSSS to remove the compensation signals that may also affect brain activity. Can also be “yes” to load without eliciting a warning.

preloadbool or str (default False)

Preload data into memory for data manipulation and faster indexing. If True, the data will be preloaded into memory (fast, requires large amount of memory). If preload is a string, preload is the file name of a memory-mapped file which is used to store the data on the hard drive (slower, requires less memory).

on_split_missingstr

Can be 'raise' (default) to raise an error, 'warn' to emit a warning, or 'ignore' to ignore when split file is missing.

New in version 0.22.

verbosebool | str | int | None

Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Returns:
rawinstance of Raw

A Raw object containing FIF data.

Notes

New in version 0.9.0.

When reading a FIF file, note that the first N seconds annotated BAD_ACQ_SKIP are skipped. They are removed from raw.times and raw.n_times parameters but raw.first_samp and raw.first_time are updated accordingly.

Examples using mne.io.read_raw_fif#

Overview of MEG/EEG analysis with MNE-Python

Overview of MEG/EEG analysis with MNE-Python

Overview of MEG/EEG analysis with MNE-Python
Modifying data in-place

Modifying data in-place

Modifying data in-place
Parsing events from raw data

Parsing events from raw data

Parsing events from raw data
The Info data structure

The Info data structure

The Info data structure
Working with sensor locations

Working with sensor locations

Working with sensor locations
Importing data from MEG devices

Importing data from MEG devices

Importing data from MEG devices
The Raw data structure: continuous data

The Raw data structure: continuous data

The Raw data structure: continuous data
Working with events

Working with events

Working with events
Annotating continuous data

Annotating continuous data

Annotating continuous data
Built-in plotting methods for Raw objects

Built-in plotting methods for Raw objects

Built-in plotting methods for Raw objects
Overview of artifact detection

Overview of artifact detection

Overview of artifact detection
Handling bad channels

Handling bad channels

Handling bad channels
Rejecting bad data spans and breaks

Rejecting bad data spans and breaks

Rejecting bad data spans and breaks
Filtering and resampling data

Filtering and resampling data

Filtering and resampling data
Repairing artifacts with ICA

Repairing artifacts with ICA

Repairing artifacts with ICA
Background on projectors and projections

Background on projectors and projections

Background on projectors and projections
Repairing artifacts with SSP

Repairing artifacts with SSP

Repairing artifacts with SSP
Setting the EEG reference

Setting the EEG reference

Setting the EEG reference
Extracting and visualizing subject head movement

Extracting and visualizing subject head movement

Extracting and visualizing subject head movement
Signal-space separation (SSS) and Maxwell filtering

Signal-space separation (SSS) and Maxwell filtering

Signal-space separation (SSS) and Maxwell filtering
The Epochs data structure: discontinuous data

The Epochs data structure: discontinuous data

The Epochs data structure: discontinuous data
Visualizing epoched data

Visualizing epoched data

Visualizing epoched data
Exporting Epochs to Pandas DataFrames

Exporting Epochs to Pandas DataFrames

Exporting Epochs to Pandas DataFrames
Divide continuous data into equally-spaced epochs

Divide continuous data into equally-spaced epochs

Divide continuous data into equally-spaced epochs
The Evoked data structure: evoked/averaged data

The Evoked data structure: evoked/averaged data

The Evoked data structure: evoked/averaged data
EEG analysis - Event-Related Potentials (ERPs)

EEG analysis - Event-Related Potentials (ERPs)

EEG analysis - Event-Related Potentials (ERPs)
Plotting whitened data

Plotting whitened data

Plotting whitened data
Frequency and time-frequency sensor analysis

Frequency and time-frequency sensor analysis

Frequency and time-frequency sensor analysis
Source alignment and coordinate frames

Source alignment and coordinate frames

Source alignment and coordinate frames
Computing a covariance matrix

Computing a covariance matrix

Computing a covariance matrix
Source localization with MNE, dSPM, sLORETA, and eLORETA

Source localization with MNE, dSPM, sLORETA, and eLORETA

Source localization with MNE, dSPM, sLORETA, and eLORETA
Source reconstruction using an LCMV beamformer

Source reconstruction using an LCMV beamformer

Source reconstruction using an LCMV beamformer
EEG source localization given electrode locations on an MRI

EEG source localization given electrode locations on an MRI

EEG source localization given electrode locations on an MRI
Brainstorm Elekta phantom dataset tutorial

Brainstorm Elekta phantom dataset tutorial

Brainstorm Elekta phantom dataset tutorial
Non-parametric 1 sample cluster statistic on single trial power

Non-parametric 1 sample cluster statistic on single trial power

Non-parametric 1 sample cluster statistic on single trial power
Non-parametric between conditions cluster statistic on single trial power

Non-parametric between conditions cluster statistic on single trial power

Non-parametric between conditions cluster statistic on single trial power
Spatiotemporal permutation F-test on full sensor data

Spatiotemporal permutation F-test on full sensor data

Spatiotemporal permutation F-test on full sensor data
Permutation t-test on source data with spatio-temporal clustering

Permutation t-test on source data with spatio-temporal clustering

Permutation t-test on source data with spatio-temporal clustering
Repeated measures ANOVA on source data with spatio-temporal clustering

Repeated measures ANOVA on source data with spatio-temporal clustering

Repeated measures ANOVA on source data with spatio-temporal clustering
Mass-univariate twoway repeated measures ANOVA on single trial power

Mass-univariate twoway repeated measures ANOVA on single trial power

Mass-univariate twoway repeated measures ANOVA on single trial power
Decoding (MVPA)

Decoding (MVPA)

Decoding (MVPA)
Corrupt known signal with point spread

Corrupt known signal with point spread

Corrupt known signal with point spread
Getting averaging info from .fif files

Getting averaging info from .fif files

Getting averaging info from .fif files
Generate simulated evoked data

Generate simulated evoked data

Generate simulated evoked data
Generate simulated raw data

Generate simulated raw data

Generate simulated raw data
Cortical Signal Suppression (CSS) for removal of cortical signals

Cortical Signal Suppression (CSS) for removal of cortical signals

Cortical Signal Suppression (CSS) for removal of cortical signals
Define target events based on time lag, plot evoked response

Define target events based on time lag, plot evoked response

Define target events based on time lag, plot evoked response
Transform EEG data using current source density (CSD)

Transform EEG data using current source density (CSD)

Transform EEG data using current source density (CSD)
Show EOG artifact timing

Show EOG artifact timing

Show EOG artifact timing
Find MEG reference channel artifacts

Find MEG reference channel artifacts

Find MEG reference channel artifacts
Compare the different ICA algorithms in MNE

Compare the different ICA algorithms in MNE

Compare the different ICA algorithms in MNE
Maxwell filter data with movement compensation

Maxwell filter data with movement compensation

Maxwell filter data with movement compensation
Removing muscle ICA components

Removing muscle ICA components

Removing muscle ICA components
Plot sensor denoising using oversampled temporal projection

Plot sensor denoising using oversampled temporal projection

Plot sensor denoising using oversampled temporal projection
XDAWN Denoising

XDAWN Denoising

XDAWN Denoising
How to convert 3D electrode positions to a 2D image

How to convert 3D electrode positions to a 2D image

How to convert 3D electrode positions to a 2D image
Visualize channel over epochs as an image

Visualize channel over epochs as an image

Visualize channel over epochs as an image
Plotting EEG sensors on the scalp

Plotting EEG sensors on the scalp

Plotting EEG sensors on the scalp
Whitening evoked data with a noise covariance

Whitening evoked data with a noise covariance

Whitening evoked data with a noise covariance
Plotting sensor layouts of MEG systems

Plotting sensor layouts of MEG systems

Plotting sensor layouts of MEG systems
Make figures more publication ready

Make figures more publication ready

Make figures more publication ready
Show noise levels from empty room data

Show noise levels from empty room data

Show noise levels from empty room data
Compare evoked responses for different conditions

Compare evoked responses for different conditions

Compare evoked responses for different conditions
Plot custom topographies for MEG sensors

Plot custom topographies for MEG sensors

Plot custom topographies for MEG sensors
Compute a cross-spectral density (CSD) matrix

Compute a cross-spectral density (CSD) matrix

Compute a cross-spectral density (CSD) matrix
Compute Power Spectral Density of inverse solution from single epochs

Compute Power Spectral Density of inverse solution from single epochs

Compute Power Spectral Density of inverse solution from single epochs
Compute power and phase lock in label of the source space

Compute power and phase lock in label of the source space

Compute power and phase lock in label of the source space
Compute source power spectral density (PSD) in a label

Compute source power spectral density (PSD) in a label

Compute source power spectral density (PSD) in a label
Compute source power spectral density (PSD) of VectorView and OPM data

Compute source power spectral density (PSD) of VectorView and OPM data

Compute source power spectral density (PSD) of VectorView and OPM data
Compute induced power in the source space with dSPM

Compute induced power in the source space with dSPM

Compute induced power in the source space with dSPM
Temporal whitening with AR model

Temporal whitening with AR model

Temporal whitening with AR model
Explore event-related dynamics for specific frequency bands

Explore event-related dynamics for specific frequency bands

Explore event-related dynamics for specific frequency bands
Permutation F-test on sensor data with 1D cluster level

Permutation F-test on sensor data with 1D cluster level

Permutation F-test on sensor data with 1D cluster level
FDR correction on T-test on sensor data

FDR correction on T-test on sensor data

FDR correction on T-test on sensor data
Regression on continuous data (rER[P/F])

Regression on continuous data (rER[P/F])

Regression on continuous data (rER[P/F])
Permutation T-test on sensor data

Permutation T-test on sensor data

Permutation T-test on sensor data
Representational Similarity Analysis

Representational Similarity Analysis

Representational Similarity Analysis
Decoding source space data

Decoding source space data

Decoding source space data
Decoding sensor space data with generalization across time and conditions

Decoding sensor space data with generalization across time and conditions

Decoding sensor space data with generalization across time and conditions
Analysis of evoked response using ICA and PCA reduction techniques

Analysis of evoked response using ICA and PCA reduction techniques

Analysis of evoked response using ICA and PCA reduction techniques
XDAWN Decoding From EEG data

XDAWN Decoding From EEG data

XDAWN Decoding From EEG data
Compute effect-matched-spatial filtering (EMS)

Compute effect-matched-spatial filtering (EMS)

Compute effect-matched-spatial filtering (EMS)
Linear classifier on sensor data with plot patterns and filters

Linear classifier on sensor data with plot patterns and filters

Linear classifier on sensor data with plot patterns and filters
Compute MNE-dSPM inverse solution on single epochs

Compute MNE-dSPM inverse solution on single epochs

Compute MNE-dSPM inverse solution on single epochs
Compute sLORETA inverse solution on raw data

Compute sLORETA inverse solution on raw data

Compute sLORETA inverse solution on raw data
Compute source power using DICS beamformer

Compute source power using DICS beamformer

Compute source power using DICS beamformer
Compute evoked ERS source power using DICS, LCMV beamformer, and dSPM

Compute evoked ERS source power using DICS, LCMV beamformer, and dSPM

Compute evoked ERS source power using DICS, LCMV beamformer, and dSPM
Compute source power estimate by projecting the covariance with MNE

Compute source power estimate by projecting the covariance with MNE

Compute source power estimate by projecting the covariance with MNE
Computing source timecourses with an XFit-like multi-dipole model

Computing source timecourses with an XFit-like multi-dipole model

Computing source timecourses with an XFit-like multi-dipole model
Compute iterative reweighted TF-MxNE with multiscale time-frequency dictionary

Compute iterative reweighted TF-MxNE with multiscale time-frequency dictionary

Compute iterative reweighted TF-MxNE with multiscale time-frequency dictionary
Compute cross-talk functions for LCMV beamformers

Compute cross-talk functions for LCMV beamformers

Compute cross-talk functions for LCMV beamformers
Optically pumped magnetometer (OPM) data

Optically pumped magnetometer (OPM) data

Optically pumped magnetometer (OPM) data