find_tpt

PURPOSE

SYNOPSIS

DESCRIPTION

function tpt=find_tpt(tme,tmes)

 Inputs:
   tme  - [scalar] a desired time
   tmes - a vector of times

 Output:
   tpt  - the element of tmes that is closest to tme in terms of absolute
          difference (L1 norm)

 Note: tme and tmes should be in the same units (e.g., milliseconds)

CROSS-REFERENCE INFORMATION

• avgs2GND avgs2GND() - Create a MATLABmk GND struct variable from a set of
• avgs2GND_nobase avgs2GND() - Create a MATLABmk GND struct variable from a set of
• baselineGND baselineGND() - Baseline the ERPs in a Mass Univariate ERP Toolbox GND
• baseline_EEG function EEG=baseline_EEG(EEG,bsln_wind,verblevel)
• clustGND clustGND() - Tests the null hypothesis that the grand average voltage
• clustGRP clustGRP() - Tests the null hypothesis that the grand average voltage
• cont_data_calibrate cont_data_calibrate() - Extract calibration scaling factor based on
• erplab2GND erplab2GND() - Create a Mass Univariate ERP Toolbox GND struct variable from a set of
• gui_avgs2GND avgs2GND() - Create a MATLABmk GND struct variable from a set of
• gui_eim_corr gui_eim_corr() - Open a GUI for exploring the correlation between EEG and
• gui_erp gui_erp() - Open a GUI for visualzing ERP butterfly plots and
• gui_erpORIG gui_erp() - Open a GUI for visualzing ERP butterfly plots and
• gui_pow gui_pow() - Open a GUI for visualzing butterfly plots of EEG power spectra
• ic_distortion ic_distortion() - Quantifies how much ICA distorts artifact free ERPs,
• items_regress items_regress() - Performs multiple regression analysis on ERPs to each
• multiplot_tfrGND multiplot_tfrGND() - Plots bin spectrograms or the difference between bin
• plot_eimcorr plot_eimcorr() - Plots the correlation between EEG an some other experimental
• plot_wave plot_wave() - Plots the ERPs from one or more bins in a GND or GRP
• remove_artifact_ics remove_artifact_ics() - Removes the independent components (ICs) of an
• rm_regress rm_regress() - Performs repeated measures multiple regression analysis
• rm_regress_mass rm_regress() - Performs repeated measures multiple regression analysis
• set2avg set2avg() - Computes ERPs from an EEGLAB set file or EEG variable and writes
• set2tfr set2tfr() - Creates a fieldtrip compatible MATLABmk TFR struct variable
• sets2GND sets2GND() - Create a Mass Univariate ERP Toolbox GND struct variable from a set of
• sets2GNDclocs sets2GND() - Create a Mass Univariate ERP Toolbox GND struct variable from a set of
• sets2TFR add other fields to tfrGND like expdesc
• sets2specGND sets2specGND() - Create a MATLABmk specGND struct variable from a set of
• sig_raster sig_raster() - Plots 2D (electrode x time/frequency) raster diagram of
• sig_raster_coefs sig_raster() - Plots 2D (electrode x time/frequency) raster diagram of
• sig_raster_dif_coefs sig_raster() - Plots 2D (electrode x time/frequency) raster diagram of
• singleplot_tfrGND singleplot_tfrGND() - Plots bin spectrogram or the difference between bin
• spec_topo spec_topo() - Plots scalp topographies of spectral power averaged across
• tfdrGND tfdrGND() - Tests the null hypothesis that the grand average voltage
• tfdrGRP tfdrGRP() - Tests the null hypothesis that the grand average voltage
• tfdr_specGND tfdr_specGND() - Tests the null hypothesis that the grand average power
• tfdr_specGRP tfdr_specGRP() - Tests the null hypothesis that the grand average voltage
• tmaxGND tmaxGND() - Tests the null hypothesis that the grand average voltage
• tmaxGRP tmaxGRP() - Tests the null hypothesis that the grand average voltage
• tmax_specGND tmax_specGND() - Tests the null hypothesis that the grand average power
• tmax_specGRP tmax_specGRP() - Tests the null hypothesis that the grand average voltage

SOURCE CODE

0001 function tpt=find_tpt(tme,tmes)
0002 %function tpt=find_tpt(tme,tmes)
0003 %
0004 % Inputs:
0005 %   tme  - [scalar] a desired time
0006 %   tmes - a vector of times
0007 %
0008 % Output:
0009 %   tpt  - the element of tmes that is closest to tme in terms of absolute
0010 %          difference (L1 norm)
0011 %
0012 % Note: tme and tmes should be in the same units (e.g., milliseconds)
0013 
0014 [dummy tpt]=min(abs(tme-tmes));