mne.Report

class mne.Report(info_fname=None, subjects_dir=None, subject=None, title=None, cov_fname=None, baseline=None, image_format='auto', raw_psd=False, projs=False, *, verbose=None)

Object for rendering HTML.

Parameters:

info_fnameNone | str

Name of the file containing the info dictionary.

subjects_dirpath-like | None

The path to the directory containing the FreeSurfer subjects reconstructions. If None, defaults to the SUBJECTS_DIR environment variable.

subjectstr | None

Subject name.

titlestr

Title of the report.

cov_fnameNone | str

Name of the file containing the noise covariance.

baselineNone | tuple of length 2

The time interval to consider as “baseline” when applying baseline correction. If None, do not apply baseline correction. If a tuple (a, b), the interval is between a and b (in seconds), including the endpoints. If a is None, the beginning of the data is used; and if b is None, it is set to the end of the interval. If (None, None), the entire time interval is used.

Note

The baseline (a, b) includes both endpoints, i.e. all timepoints t such that a <= t <= b.

Correction is applied in the following way to each channel:

1. Calculate the mean signal of the baseline period.

2. Subtract this mean from the entire time period.

For Epochs, this algorithm is run on each epoch individually. Defaults to None, i.e. no baseline correction.

image_format‘png’ | ‘svg’ | ‘webp’ | ‘auto’

Default image format to use (default is 'auto', which will use 'webp' if available and 'png' otherwise). 'svg' uses vector graphics, so fidelity is higher but can increase file size and browser image rendering time as well. 'webp' format requires matplotlib >= 3.6.

New in version 0.15.

Changed in version 1.3: Added support for 'webp' format, removed support for GIF, and set the default to 'auto'.

raw_psdbool | dict

If True, include PSD plots for raw files. Can be False (default) to omit, True to plot, or a dict to pass as kwargs to mne.io.Raw.plot_psd().

New in version 0.17.

projsbool

Whether to include topographic plots of SSP projectors, if present in the data. Defaults to False.

New in version 0.21.

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.

Notes

See Getting started with mne.Report for an introduction to using mne.Report.

New in version 0.8.0.

Attributes:

info_fnameNone | str

Name of the file containing the info dictionary.

subjects_dirpath-like | None

The path to the directory containing the FreeSurfer subjects reconstructions. If None, defaults to the SUBJECTS_DIR environment variable.

subjectstr | None

Subject name.

titlestr

Title of the report.

cov_fnameNone | str

Name of the file containing the noise covariance.

baselineNone | tuple of length 2

The time interval to consider as “baseline” when applying baseline correction. If None, do not apply baseline correction. If a tuple (a, b), the interval is between a and b (in seconds), including the endpoints. If a is None, the beginning of the data is used; and if b is None, it is set to the end of the interval. If (None, None), the entire time interval is used.

Note

The baseline (a, b) includes both endpoints, i.e. all timepoints t such that a <= t <= b.

Correction is applied in the following way to each channel:

1. Calculate the mean signal of the baseline period.

2. Subtract this mean from the entire time period.

For Epochs, this algorithm is run on each epoch individually. Defaults to None, i.e. no baseline correction.

image_formatstr

Default image format to use.

New in version 0.15.

raw_psdbool | dict

If True, include PSD plots for raw files. Can be False (default) to omit, True to plot, or a dict to pass as kwargs to mne.io.Raw.plot_psd().

New in version 0.17.

projsbool

Whether to include topographic plots of SSP projectors, if present in the data. Defaults to False.

New in version 0.21.

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.

htmllist of str

A list of HTML representations for all content elements.

includelist of str

Dictionary containing elements included in head.

fnameslist of str

List of file names rendered.

sectionslist of str

List of sections.

langstr

language setting for the HTML file.

Methods

__len__()	Return the number of files processed by the report.
add_bem(subject, title, *[, subjects_dir, ...])	Render a visualization of the boundary element model (BEM) surfaces.
add_code(code, title, *[, language, tags, ...])	Add a code snippet (e.g., an analysis script) to the report.
add_covariance(cov, *, info, title[, tags, ...])	Add covariance to the report.
add_custom_css(css)	Add custom CSS to the report.
add_custom_js(js)	Add custom JavaScript to the report.
add_epochs(epochs, title, *[, psd, projs, ...])	Add Epochs to the report.
add_events(events, title, *[, event_id, ...])	Add events to the report.
add_evokeds(evokeds, *[, titles, noise_cov, ...])	Add Evoked objects to the report.
add_figure(fig, title, *[, caption, ...])	Add figures to the report.
add_forward(forward, title, *[, subject, ...])	Add a forward solution.
add_html(html, title, *[, tags, section, ...])	Add HTML content to the report.
add_ica(ica, title, *, inst[, picks, ...])	Add (a fitted) ICA to the report.
add_image(image, title, *[, caption, tags, ...])	Add an image (e.g., PNG or JPEG pictures) to the report.
add_inverse_operator(inverse_operator, title, *)	Add an inverse operator.
add_projs(*, info[, projs, topomap_kwargs, ...])	Render (SSP) projection vectors.
add_raw(raw, title, *[, psd, projs, ...])	Add Raw objects to the report.
add_stc(stc, title, *[, subject, ...])	Add a SourceEstimate (STC) to the report.
add_sys_info(title, *[, tags, replace])	Add a MNE-Python system information to the report.
add_trans(trans, *, info, title[, subject, ...])	Add a coregistration visualization to the report.
parse_folder(data_path[, pattern, n_jobs, ...])	Render all the files in the folder.
remove(*[, title, tags, remove_all])	Remove elements from the report.
save([fname, open_browser, overwrite, ...])	Save the report and optionally open it in browser.

__len__()

Return the number of files processed by the report.

Returns:

n_filesint

The number of files processed.

add_bem(subject, title, *, subjects_dir=None, decim=2, width=512, n_jobs=None, tags=('bem',), replace=False)

Render a visualization of the boundary element model (BEM) surfaces.

Parameters:

subjectstr

The FreeSurfer subject name.

titlestr

The title corresponding to the BEM image.

subjects_dirpath-like | None

The path to the directory containing the FreeSurfer subjects reconstructions. If None, defaults to the SUBJECTS_DIR environment variable.

decimint

Use this decimation factor for generating MRI/BEM images (since it can be time consuming).

widthint

The width of the MRI images (in pixels). Larger values will have clearer surface lines, but will create larger HTML files. Typically a factor of 2 more than the number of MRI voxels along each dimension (typically 512, default) is reasonable.

n_jobsint | None

The number of jobs to run in parallel. If -1, it is set to the number of CPU cores. Requires the joblib package. None (default) is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a joblib.parallel_backend() context manager that sets another value for n_jobs.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_bem:

Getting started with mne.Report

Getting started with mne.Report

add_code(code, title, *, language='python', tags=('code',), replace=False)

Add a code snippet (e.g., an analysis script) to the report.

Parameters:

codestr | pathlib.Path

The code to add to the report as a string, or the path to a file as a pathlib.Path object.

Note

Paths must be passed as pathlib.Path object, since strings will be treated as literal code.

titlestr

The title corresponding to the code.

languagestr

The programming language of code. This will be used for syntax highlighting. Can be 'auto' to try to auto-detect the language.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_code:

Getting started with mne.Report

Getting started with mne.Report

add_covariance(cov, *, info, title, tags=('covariance',), replace=False)

Add covariance to the report.

Parameters:

covpath-like | instance of Covariance

The Covariance to add to the report.

infopath-like | instance of Info

The Info corresponding to cov.

titlestr

The title corresponding to the Covariance object.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_covariance:

Getting started with mne.Report

Getting started with mne.Report

add_custom_css(css)

Add custom CSS to the report.

Parameters:

cssstr

Style definitions to add to the report. The content of this string will be embedded between HTML <style> and </style> tags.

Notes

New in version 0.23.

add_custom_js(js)

Add custom JavaScript to the report.

Parameters:

jsstr

JavaScript code to add to the report. The content of this string will be embedded between HTML <script> and </script> tags.

Notes

New in version 0.23.

add_epochs(epochs, title, *, psd=True, projs=None, topomap_kwargs=None, drop_log_ignore=('IGNORED',), tags=('epochs',), replace=False)

Add Epochs to the report.

Parameters:

epochspath-like | instance of Epochs

The epochs to add to the report.

titlestr

The title to add.

psdbool | float

If a float, the duration of data to use for creation of PSD plots, in seconds. PSD will be calculated on as many epochs as required to cover at least this duration. Epochs will be picked across the entire time range in equally-spaced distance.

Note

In rare edge cases, we may not be able to create a grid of equally-spaced epochs that cover the entire requested time range. In these situations, a warning will be emitted, informing you about the duration that’s actually being used.

If True, add PSD plots based on all epochs. If False, do not add PSD plots.

projsbool | None

Whether to add SSP projector plots if projectors are present in the data. If None, use projs from Report creation.

topomap_kwargsdict | None

Keyword arguments to pass to the topomap-generating functions.

drop_log_ignorearray_like of str

The drop reasons to ignore when creating the drop log bar plot. All epochs for which a drop reason listed here appears in epochs.drop_log will be excluded from the drop log plot.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_epochs:

Getting started with mne.Report

Getting started with mne.Report

add_events(events, title, *, event_id=None, sfreq, first_samp=0, tags=('events',), replace=False)

Add events to the report.

Parameters:

eventspath-like | array, shape (n_events, 3)

An MNE-Python events array.

titlestr

The title corresponding to the events.

event_iddict

A dictionary mapping event names (keys) to event codes (values).

sfreqfloat

The sampling frequency used while recording.

first_sampint

The first sample point in the recording. This corresponds to raw.first_samp on files created with Elekta/Neuromag systems.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_events:

Getting started with mne.Report

Getting started with mne.Report

add_evokeds(evokeds, *, titles=None, noise_cov=None, projs=None, n_time_points=None, tags=('evoked',), replace=False, topomap_kwargs=None, n_jobs=None)

Add Evoked objects to the report.

Parameters:

evokedspath-like | instance of Evoked | list of Evoked

The evoked data to add to the report. Multiple Evoked objects – as returned from mne.read_evokeds – can be passed as a list.

titlesstr | list of str | None

The titles corresponding to the evoked data. If None, the content of evoked.comment from each evoked will be used as title.

noise_covpath-like | instance of Covariance | None

A noise covariance matrix. If provided, will be used to whiten the evokeds. If None, will fall back to the cov_fname provided upon report creation.

projsbool | None

Whether to add SSP projector plots if projectors are present in the data. If None, use projs from Report creation.

n_time_pointsint | None

The number of equidistant time points to render. If None, will render each Evoked at 21 time points, unless the data contains fewer time points, in which case all will be rendered.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

topomap_kwargsdict | None

Keyword arguments to pass to the topomap-generating functions.

n_jobsint | None

The number of jobs to run in parallel. If -1, it is set to the number of CPU cores. Requires the joblib package. None (default) is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a joblib.parallel_backend() context manager that sets another value for n_jobs.

Notes

New in version 0.24.0.

Examples using add_evokeds:

Getting started with mne.Report

Getting started with mne.Report

add_figure(fig, title, *, caption=None, image_format=None, tags=('custom-figure',), section=None, replace=False)

Add figures to the report.

Parameters:

figmatplotlib.figure.Figure | Figure3D | array | array_like of matplotlib.figure.Figure | array_like of Figure3D | array_like of array

One or more figures to add to the report. All figures must be an instance of matplotlib.figure.Figure, mne.viz.Figure3D, or numpy.ndarray. If multiple figures are passed, they will be added as “slides” that can be navigated using buttons and a slider element.

titlestr

The title corresponding to the figure(s).

captionstr | array_like of str | None

The caption(s) to add to the figure(s).

image_format‘png’ | ‘svg’ | ‘gif’ | None

The image format to be used for the report, can be 'png', 'svg', or 'gif'. None (default) will use the default specified during Report instantiation.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

sectionstr | None

The name of the section (or content block) to add the content to. This feature is useful for grouping multiple related content elements together under a single, collapsible section. Each content element will retain its own title and functionality, but not appear separately in the table of contents. Hence, using sections is a way to declutter the table of contents, and to easy navigation of the report.

New in version 1.1.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_figure:

Getting started with mne.Report

Getting started with mne.Report

add_forward(forward, title, *, subject=None, subjects_dir=None, tags=('forward-solution',), replace=False)

Add a forward solution.

Parameters:

forwardinstance of Forward | path-like

The forward solution to add to the report.

titlestr

The title corresponding to forward solution.

subjectstr | None

The name of the FreeSurfer subject forward belongs to. If provided, the sensitivity maps of the forward solution will be visualized. If None, will use the value of subject passed on report creation. If supplied, also pass subjects_dir.

subjects_dirpath-like | None

The FreeSurfer SUBJECTS_DIR.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_forward:

Getting started with mne.Report

Getting started with mne.Report

add_html(html, title, *, tags=('custom-html',), section=None, replace=False)

Add HTML content to the report.

Parameters:

htmlstr

The HTML content to add.

titlestr

The title corresponding to html.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

sectionstr | None

The name of the section (or content block) to add the content to. This feature is useful for grouping multiple related content elements together under a single, collapsible section. Each content element will retain its own title and functionality, but not appear separately in the table of contents. Hence, using sections is a way to declutter the table of contents, and to easy navigation of the report.

New in version 1.1.

New in version 1.3.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_html:

Getting started with mne.Report

Getting started with mne.Report

add_ica(ica, title, *, inst, picks=None, ecg_evoked=None, eog_evoked=None, ecg_scores=None, eog_scores=None, n_jobs=None, tags=('ica',), replace=False)

Add (a fitted) ICA to the report.

Parameters:

icapath-like | instance of mne.preprocessing.ICA

The fitted ICA to add.

titlestr

The title to add.

instpath-like | mne.io.Raw | mne.Epochs | None

The data to use for visualization of the effects of ICA cleaning. To only plot the ICA component topographies, explicitly pass None.

picksint | list of int | slice | None

Indices of the independent components (ICs) to visualize. If an integer, represents the index of the IC to pick. Multiple ICs can be selected using a list of int or a slice. The indices are 0-indexed, so picks=1 will pick the second IC: ICA001. None will pick all independent components in the order fitted. This only affects the behavior of the component topography and properties plots.

ecg_evoked, eog_evokedpath-line | mne.Evoked | None

Evoked signal based on ECG and EOG epochs, respectively. If passed, will be used to visualize the effects of artifact rejection.

ecg_scores, eog_scoresarray of float | list of array of float | None

The scores produced by mne.preprocessing.ICA.find_bads_ecg() and mne.preprocessing.ICA.find_bads_eog(), respectively. If passed, will be used to visualize the scoring for each ICA component.

n_jobsint | None

The number of jobs to run in parallel. If -1, it is set to the number of CPU cores. Requires the joblib package. None (default) is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a joblib.parallel_backend() context manager that sets another value for n_jobs.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_ica:

Getting started with mne.Report

Getting started with mne.Report

add_image(image, title, *, caption=None, tags=('custom-image',), section=None, replace=False)

Add an image (e.g., PNG or JPEG pictures) to the report.

Parameters:

imagepath-like

The image to add.

titlestr

Title corresponding to the images.

captionstr | None

If not None, the caption to add to the image.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

sectionstr | None

The name of the section (or content block) to add the content to. This feature is useful for grouping multiple related content elements together under a single, collapsible section. Each content element will retain its own title and functionality, but not appear separately in the table of contents. Hence, using sections is a way to declutter the table of contents, and to easy navigation of the report.

New in version 1.1.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_image:

Getting started with mne.Report

Getting started with mne.Report

add_inverse_operator(inverse_operator, title, *, subject=None, subjects_dir=None, trans=None, tags=('inverse-operator',), replace=False)

Add an inverse operator.

Parameters:

inverse_operatorinstance of InverseOperator | path-like

The inverse operator to add to the report.

titlestr

The title corresponding to the inverse operator object.

subjectstr | None

The name of the FreeSurfer subject inverse_op belongs to. If provided, the source space the inverse solution is based on will be visualized. If None, will use the value of subject passed on report creation. If supplied, also pass subjects_dir and trans.

subjects_dirpath-like | None

The FreeSurfer SUBJECTS_DIR.

transpath-like | instance of Transform | None

The head -> MRI transformation for subject.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_inverse_operator:

Getting started with mne.Report

Getting started with mne.Report

add_projs(*, info, projs=None, title, topomap_kwargs=None, tags=('ssp',), replace=False)

Render (SSP) projection vectors.

Parameters:

infoinstance of Info | path-like

An Info structure or the path of a file containing one. This is required to create the topographic plots.

projsiterable of mne.Projection | path-like | None

The projection vectors to add to the report. Can be the path to a file that will be loaded via mne.read_proj. If None, the projectors are taken from info['projs'].

titlestr

The title corresponding to the Projection object.

topomap_kwargsdict | None

Keyword arguments to pass to the topomap-generating functions.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_projs:

Getting started with mne.Report

Getting started with mne.Report

add_raw(raw, title, *, psd=None, projs=None, butterfly=True, scalings=None, tags=('raw',), replace=False, topomap_kwargs=None)

Add Raw objects to the report.

Parameters:

rawpath-like | instance of Raw

The data to add to the report.

titlestr

The title corresponding to the raw object.

psdbool | None

Whether to add PSD plots. Overrides the raw_psd parameter passed when initializing the Report. If None, use raw_psd from Report creation.

projsbool | None

Whether to add SSP projector plots if projectors are present in the data. If None, use projs from Report creation.

butterflybool | int

Whether to add butterfly plots of the data. Can be useful to spot problematic channels. If True, 10 equally-spaced 1-second segments will be plotted. If an integer, specifies the number of 1-second segments to plot. Larger numbers may take a considerable amount of time if the data contains many sensors. You can disable butterfly plots altogether by passing False.

scalings‘auto’ | dict | None

Scaling factors for the traces. If a dictionary where any value is 'auto', the scaling factor is set to match the 99.5th percentile of the respective data. If 'auto', all scalings (for all channel types) are set to 'auto'. If any values are 'auto' and the data is not preloaded, a subset up to 100 MB will be loaded. If None, defaults to:

dict(mag=1e-12, grad=4e-11, eeg=20e-6, eog=150e-6, ecg=5e-4,
     emg=1e-3, ref_meg=1e-12, misc=1e-3, stim=1,
     resp=1, chpi=1e-4, whitened=1e2)

Note

A particular scaling value s corresponds to half of the visualized signal range around zero (i.e. from 0 to +s or from 0 to -s). For example, the default scaling of 20e-6 (20µV) for EEG signals means that the visualized range will be 40 µV (20 µV in the positive direction and 20 µV in the negative direction).

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

topomap_kwargsdict | None

Keyword arguments to pass to the topomap-generating functions.

Notes

New in version 0.24.0.

Examples using add_raw:

Getting started with mne.Report

Getting started with mne.Report

add_stc(stc, title, *, subject=None, subjects_dir=None, n_time_points=None, tags=('source-estimate',), replace=False, stc_plot_kwargs=None)

Add a SourceEstimate (STC) to the report.

Parameters:

stcpath-like | instance of SourceEstimate

The SourceEstimate to add to the report.

titlestr

The title to add.

subjectstr | None

The name of the FreeSurfer subject the STC belongs to. The name is not stored with the STC data and therefore needs to be specified. If None, will use the value of subject passed on report creation.

subjects_dirpath-like | None

The FreeSurfer SUBJECTS_DIR.

n_time_pointsint | None

The number of equidistant time points to render. If None, will render stc at 51 time points, unless the data contains fewer time points, in which case all will be rendered.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

stc_plot_kwargsdict

Dictionary of keyword arguments to pass to mne.SourceEstimate.plot. Only used when plotting in 3D mode.

Notes

New in version 0.24.0.

Examples using add_stc:

Getting started with mne.Report

Getting started with mne.Report

add_sys_info(title, *, tags=('mne-sysinfo',), replace=False)

Add a MNE-Python system information to the report.

This is a convenience method that captures the output of mne.sys_info and adds it to the report.

Parameters:

titlestr

The title to assign.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

add_trans(trans, *, info, title, subject=None, subjects_dir=None, alpha=None, tags=('coregistration',), replace=False)

Add a coregistration visualization to the report.

Parameters:

transpath-like | instance of Transform

The head -> MRI transformation to render.

infopath-like | instance of Info

The Info corresponding to trans.

titlestr

The title to add.

subjectstr | None

The name of the FreeSurfer subject the trans`` belong to. The name is not stored with the trans and therefore needs to be specified. If None, will use the value of subject passed on report creation.

subjects_dirpath-like | None

The FreeSurfer SUBJECTS_DIR.

alphafloat | None

The level of opacity to apply to the head surface. If a float, must be between 0 and 1 (inclusive), where 1 means fully opaque. If None, will use the MNE-Python default value.

tagsarray_like of str | str

Tags to add for later interactive filtering. Must not contain spaces.

replacebool

If True, content already present that has the same title and section will be replaced. Defaults to False, which will cause duplicate entries in the table of contents if an entry for title already exists.

Notes

New in version 0.24.0.

Examples using add_trans:

Getting started with mne.Report

Getting started with mne.Report

property html

A list of HTML representations for all content elements.

parse_folder(data_path, pattern=None, n_jobs=None, mri_decim=2, sort_content=True, *, on_error='warn', image_format=None, render_bem=True, n_time_points_evokeds=None, n_time_points_stcs=None, raw_butterfly=True, stc_plot_kwargs=None, topomap_kwargs=None, verbose=None)

Render all the files in the folder.

Parameters:

data_pathstr

Path to the folder containing data whose HTML report will be created.

patternNone | str | list of str

Filename pattern(s) to include in the report. For example, [\*raw.fif, \*ave.fif] will include Raw as well as Evoked files. If None, include all supported file formats.

Changed in version 0.23: Include supported non-FIFF files by default.

n_jobsint | None

The number of jobs to run in parallel. If -1, it is set to the number of CPU cores. Requires the joblib package. None (default) is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a joblib.parallel_backend() context manager that sets another value for n_jobs.

mri_decimint

Use this decimation factor for generating MRI/BEM images (since it can be time consuming).

sort_contentbool

If True, sort the content based on tags in the order: raw -> events -> epochs -> evoked -> covariance -> coregistration -> bem -> forward-solution -> inverse-operator -> source-estimate.

New in version 0.24.0.

on_errorstr

What to do if a file cannot be rendered. Can be ‘ignore’, ‘warn’ (default), or ‘raise’.

image_format‘png’ | ‘svg’ | ‘gif’ | None

The image format to be used for the report, can be 'png', 'svg', or 'gif'. None (default) will use the default specified during Report instantiation.

New in version 0.15.

render_bembool

If True (default), try to render the BEM.

New in version 0.16.

n_time_points_evokeds, n_time_points_stcsint | None

The number of equidistant time points to render for Evoked and SourceEstimate data, respectively. If None, will render each Evoked at 21 and each SourceEstimate at 51 time points, unless the respective data contains fewer time points, in which call all will be rendered.

New in version 0.24.0.

raw_butterflybool

Whether to render butterfly plots for (decimated) Raw data.

New in version 0.24.0.

stc_plot_kwargsdict

Dictionary of keyword arguments to pass to mne.SourceEstimate.plot. Only used when plotting in 3D mode.

New in version 0.24.0.

topomap_kwargsdict | None

Keyword arguments to pass to the topomap-generating functions.

New in version 0.24.0.

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.

Examples using parse_folder:

Getting started with mne.Report

Getting started with mne.Report

remove(*, title=None, tags=None, remove_all=False)

Remove elements from the report.

The element to remove is searched for by its title. Optionally, tags may be specified as well to narrow down the search to elements that have the supplied tags.

Parameters:

titlestr

The title of the element(s) to remove.

New in version 0.24.0.

tagsarray_like of str | str | None

If supplied, restrict the operation to elements with the supplied tags.

New in version 0.24.0.

remove_allbool

Controls the behavior if multiple elements match the search criteria. If False (default) only the element last added to the report will be removed. If True, all matches will be removed.

New in version 0.24.0.

Returns:

removed_indexint | tuple of int | None

The indices of the elements that were removed, or None if no element matched the search criteria. A tuple will always be returned if remove_all was set to True and at least one element was removed.

Changed in version 0.24.0: Returns tuple if remove_all is True.

save(fname=None, open_browser=True, overwrite=False, sort_content=False, *, verbose=None)

Save the report and optionally open it in browser.

Parameters:

fnamepath-like | None

Output filename. If the name ends with .h5 or .hdf5, the report is saved in HDF5 format, so it can later be loaded again with open_report(). For any other suffix, the report will be saved in HTML format. If None and Report.parse_folder() was not called, the report is saved as report.html in the current working directory. If None and Report.parse_folder() was used, the report is saved as report.html inside the data_path supplied to Report.parse_folder().

open_browserbool

Whether to open the rendered HTML report in the default web browser after saving. This is ignored when writing an HDF5 file.

overwritebool

If True (default False), overwrite the destination file if it exists.

sort_contentbool

If True, sort the content based on tags before saving in the order: raw -> events -> epochs -> evoked -> covariance -> coregistration -> bem -> forward-solution -> inverse-operator -> source-estimate.

New in version 0.24.0.

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:

fnamestr

The file name to which the report was saved.

Examples using save:

Getting started with mne.Report

Getting started with mne.Report

property tags

All tags currently used in the report.

Examples using mne.Report

Getting started with mne.Report

Getting started with mne.Report