Function reference • eeguana

About
`eeguana` `eeguana-package`	eeguana: Flexible Manipulation of EEG Data
Reading and writing functions Functions for reading external files and return an `eeg_lst`.
`read_edf()`	Read an edf/edf+/bdf file into R
`read_fif()`	Read a FIF file into R
`read_ft()`	Read a Fieldtrip file into R
`read_set()`	Read EEGlab set files (Matlab files) into R
`read_vhdr()`	Read a BrainVision file into R
`write_vhdr()`	Write an eeg_lst object to BrainVision file(s) (experimental)
Tidyverse verbs (and extensions) Functions that overload some tidyverse functions and always return an `eeg_lst`.
`eeg_mutate()` `eeg_transmute()` `eeg_filter()` `eeg_summarize()` `eeg_summarise()` `eeg_group_by()` `eeg_ungroup()` `eeg_select()` `eeg_rename()` `eeg_rename_with()` `eeg_groups()` `eeg_group_vars()` `eeg_left_join()` `eeg_semi_join()` `eeg_anti_join()` `eeg_pull()` `across()` `across_ch()` `c_across_ch()` `c_across()`	Dplyr-like functions for manipulating eeg_lst objects.
`drop_incomplete_segments()`	Drop segments with NAs from the eeg_lst
`eeg_bind()` `bind()`	Bind eeg_lst objects.
`eeg_slice_signal()` `slice_signal()`	Choose samples by the position
Specialized summarizing functions Functions that return useful summaries.
`count_complete_cases_tbl()`	Count number of complete segments of an eeg_lst object.
`eeg_ica_cor_tbl()`	Show correlations between ICA sources and eye (EOG) electrodes.
`eeg_ica_summary_tbl()`	Show a table with a summary of the results of the ICA.
`eeg_ica_var_tbl()`	Show the variance explained for each ICA sources.
`channel_names()` `channel_ica_names()` `nchannels()` `component_names()` `ncomponents()` `sampling_rate()` `nsamples()`	Display information of the eeg_lst object.
`summary(<eeg_lst>)`	Summary of eeg_lst information.
EEG-specialized functions Functions for applying specialized actions on the signal table, channel, or the entire `eeg_lst`.
`eeg_artif_minmax()` `eeg_artif_step()` `eeg_artif_amplitude()` `eeg_artif_peak()`	Detect artifacts and add them in the events table of an `eeg_lst`
`eeg_events_to_NA()`	Remove (transform to NA) problematic events from the signal table of an eeg_lst.
`eeg_ica()`	EEG signal decomposition using Independent Component Analysis (ICA)
`eeg_ica_cor_tbl()`	Show correlations between ICA sources and eye (EOG) electrodes.
`eeg_ica_keep()`	Select independent components (or sources) to keep.
`eeg_ica_show()`	Add independent components (or sources) to the signal table for visualization.
`eeg_ica_summary_tbl()`	Show a table with a summary of the results of the ICA.
`eeg_ica_var_tbl()`	Show the variance explained for each ICA sources.
`eeg_baseline()`	Baseline an eeg_lst
`eeg_downsample()`	Downsample EEG data
`eeg_rereference()`	Re-reference a channel or group of channels.
`eeg_segment()` `eeg_unsegment()`	Segment (and unsegment) an eeg_lst.
`eeg_filt_low_pass()` `eeg_filt_high_pass()` `eeg_filt_band_pass()` `eeg_filt_band_stop()`	Apply a zero-phase low-pass, high-pass, band-pass, or band-stop FIR or IIR filter.
`chs_fun()`	Get the by-sample (or by-row) function of the specified channels.
`chs_mean()`	Get the by-sample (or by-row) mean of the specified channels.
`eeg_power_band()`	Compute power bands.
`eeg_psd()`	Compute the power spectral density (PSD) of an EEG signal.
Plot functions Wrappers to `ggplot` functions that first transform the `eeg_lst` to a wide `tibble`, together with some transformation (downsampling, interpolation, etc).
`ggplot(<eeg_lst>)`	Create an ERP plot
`plot(<eeg_lst>)` `plot(<psd_lst>)`	Create a basic signal plot
`plot_components()`	Generates topographic plots of the components after running ICA on an eeg_lst
`plot_in_layout()`	Arrange ERP plots according to scalp layout
`plot_topo()`	Create a topographic plot
`annotate_electrodes()`	Adds the electrode labels to a head shape
`annotate_events()`	Adds a layer with the events on top of a plot of an eeg_lst.
`annotate_head()`	Add a head shape to a ggplot
`theme_eeguana()` `theme_eeguana2()` `default_theme()`	Eeguana ggplot themes
‘base’-inspired functions Functions for getting specific information about the objects that compose an `eeg_lst`.
`as_channel_dbl()`	Coerce a vector of real (double) numbers into a channel object
`as_eeg_lst()`	Transforms an object to a eeg_lst
`as_sample_int()`	Convert a time point into a sample.
`as_tibble.eeg_lst()` `as_data_frame.eeg_lst()` `as_long_tbl(<eeg_lst>)`	Convert an eeg_lst to a long table in `tibble` format.
`as_tibble.psd_lst()`	Convert an psd_lst to a long table in `tibble` format.
`as_tidytable.eeg_lst()`	Convert an eeg_lst to a long table in `tidytable` format.
`as_tidytable.psd_lst()`	Convert an psd_lst to a long table in `tidytable` format.
`as_time()`	Convert a sample point into a time point.
`as.data.frame(<eeg_lst>)`	Convert an eeg_lst to a (base) data frame.
`as.data.frame(<psd_lst>)`	Convert a psd_lst to a (base) data frame.
`as.data.table.eeg_lst()`	Convert an eeg_lst to a long table in `data.table` format.
`as.data.table.psd_lst()`	Convert a psd_lst list to a long table in `data.table` format.
`is_channel_dbl()`	Test if the object is a channel or EOG channel
`is_component_dbl()`	Test if the object is a component This function returns TRUE for components.
`is_eeg_lst()`	Test if the object is an eeg_lst.
`is_events_tbl()`	Test if the object is an events_tbl This function returns TRUE for events_tbl.
`is_psd_lst()`	Test if the object is a psd_lst.
`is_psd_tbl()`	Test if the object is a psd_tbl
`is_sample_int()`	Test if the object is a sample This function returns TRUE for samples.
`is_signal_tbl()`	Test if the object is a signal_tbl
`na_omit()`	Handle Missing Values in eeg_lst objects
`channel_names()` `channel_ica_names()` `nchannels()` `component_names()` `ncomponents()` `sampling_rate()` `nsamples()`	Display information of the eeg_lst object.
`ica_matrix_lst()`	Function to get the list of mixing and unmixing matrices of an eeg_ica_lst object.
Editing functions Functions for showing (and sometimes editing) `eeg_lst` objects parts.
`signal_tbl()`	Function to get the signal table of an eeg_lst object.
`events_tbl()` `events_tbl<-`()	Functions to get or set the events table of an eeg_lst object.
`segments_tbl()`	Function to get the segments table of an eeg_lst object.
`channels_tbl()` `channels_tbl<-`()	Functions to get or set the channel information of an eeg_lst object.
Constructor functions Functions for creating objects.
`eeg_lst()`	Create an eeg_lst
`psd_lst()`	Creates a `psd_lst`.
`sample_int()`	Builds a series of sample numbers.
`channel_dbl()`	Builds a channel.
`component_dbl()`	Builds a component.
Others Some other useful functions.
`eeg_interpolate_tbl()`	Create a table with interpolated signals of an eeg_lst object.
`change_coord()`	Change coordinate system from 3D to 2D
`rpink()`	Generates pink noise
`adapt_fast_ICA()` `fast_ICA2()`	Wrapper for FastICA methods for Independent Component Analysis from fICA package
`fast_ICA()`	Wrapper for FastICA method for Independent Component Analysis from fastICA package
`ica_matrix_lst()`	Function to get the list of mixing and unmixing matrices of an eeg_ica_lst object.
`between`	Convenience function for range subsets
`install_py_eeguana()`	Install the Python packages needed for `eeguana`
Example data sets Example data sets in eeg_lst format.
`data_faces_10_trials`	EEGs elicited when one subject saw faces and non-faces objects.
`data_faces_ERPs`	ERPs elicited when one subject saw faces and non-faces objects.
Layouts Layout of caps
`layout_32_1020`	Layout for a 32 electrodes cap at the standard 10-20 system
Signal processing Miscellanous signal processing functions (mostly adapted from python and matlab)
`sig_fft()`	Compute the one-dimensional discrete Fourier Transform.
`sig_ifft()`	Compute the one-dimensional inverse discrete Fourier Transform.

Reference

About

Reading and writing functions

Tidyverse verbs (and extensions)

Specialized summarizing functions

EEG-specialized functions

Plot functions

‘base’-inspired functions

Editing functions

Constructor functions

Others

Example data sets

Layouts

Signal processing