sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
6b16c5a7054ddecd714cc4cd5d9f303e5cc624b8dabd5494c55d11f47265976e | MATLAB | 3,195 | 99 | % read_eeglabdata() - import EEGLAB dataset files
%
% Usage:
% >> dat = read_eeglabdata(filename);
%
% Inputs:
% filename - [string] file name
%
% Optional inputs:
% 'begtrial' - [integer] first trial to read
% 'endtrial' - [integer] last trial to read
% 'chanindx' - [integer] list with channel indices to ... |
260516e325ab4f63ae9659a798fc360a3e03acc5f0ad3f5194d8baf124d39d9e | MATLAB | 3,196 | 155 | function leftClickCallback(self,p)
if self.verbosity > 9
disp(mfilename)
end
if isempty(self.channel_to_work_with)
return
end
channel = self.channel_to_work_with;
if self.channel_stage(channel) == 0
return
end
xlimits = self.handles.ax.ax(channel).XLim;
xrange = (xlimits(2) - xlimits(1))/self.dt;
p(1) = p(1)/s... |
58da71c3e1a80e690a82d972b7c1e34cfff8b7f01a481f03b331a555607e534b | MATLAB | 3,197 | 112 | % DELCODE-SAME, Table "FADE SAME sgd"
% _
% original paper: Soch*, Richter* et al., HBM, 2022
% Table 2: Between-subject ANOVAs for FADE-classic and FADE-SAME scores
%
% DELCODE paper: Soch et al., medRxiv, 2023
% Figure 2: Effects of site, gender and diagnosis on fMRI scores
%
% written by Joram Soch <Joram.Soch@D... |
0fe2b4a187d066499a2768189c55555eb915f7cf4eeb71064637b69b2b5db26f | MATLAB | 3,198 | 97 | function y = tffilter(tfr,x,t,trace);
%TFFILTER Time frequency filtering of a signal.
% Y=TFFILTER(TFR,X,T,TRACE) filters the signal X
% with a non stationary filter.
%
%
% X : input signal (must be analytic).
% T : time instant(s) (default : 1:length(X)).
% TRACE : if nonzero, the progression... |
2617a8757f966234c7f2b9e51ce862fc1a36d5f5c984ee47888c02784251f7e5 | MATLAB | 3,198 | 125 | function montage = megplanar_orig(cfg, grad)
% This is the original method from Ole. It has a different way of
% making the coordinate transformation that I do not fully understand.
% Copyright (C) 2004, Ole Jensen
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and de... |
058c575f3b1a95cf3933d09d613fb76cd7ec30c4c2eeb546ea329c1dead0fb6f | MATLAB | 3,200 | 120 | function varargout = subfigure(varargin)
% h = subfigure(m,n,p), or subfigure(mnp), divides the screen into an m-by-n
% matrix, creates a figure within the pth matrix element, and returns that
% figure's handle. The figures are counted along the top row of the screen, then
% the second row, etc. For example,
%
% in... |
167cc3a663612cae03332a1363adfc423689310f6c32f8d4bac1f1244f5389e1 | MATLAB | 3,200 | 126 | %% Gauss Imputation Demo
%
%%
% This file is from pmtk3.googlecode.com
function gaussImputationDemoColorHintonDiag()
setSeed(1);
d = 10;
mu = randn(d,1); Sigma = randpd(d);
pcMissing = 0.3;
% Training data is missing data at random
[XfullTrain, XmissTrain] = mkData(mu, Sigma, 100, true, pcMissing);
% Test data omit... |
3bff182fffb45033a4d7d41ce52194a2553835aa5c9d571866f7419ef978eef8 | MATLAB | 3,200 | 107 | function [T, cost] = minSpanTreeKruskal (CostMatrix)
% Kruskal's algorithm for MST
% CostMatrix
% T is adjacency matrix
% cost is overall cost of tree
% This file is from pmtk3.googlecode.com
%PMTKauthor Soshant Bali
%PMTKurl http://www.ittc.ku.edu/~sbali/graphSoftware.htm
% Extract the edge weights from the cos... |
8ce80771185f9daca5c8b0457b446d49e673e40e1a411494d63ed96649acde89 | MATLAB | 3,200 | 109 | function s = getParamString(p,breakLine,omitParams,parPrecision,forFileName)
if (nargin < 2) || isempty(breakLine)
breakLine = false;
end
if (nargin < 3) || isempty(omitParams)
omitParams = {};
end
if (nargin < 4) || isempty(parPrecision)
parPrecision = '%g';%'%.2f'; % either... |
967ad276a568584cbb9934b6536dd38d845e5061016ae667c53b60f911869459 | MATLAB | 3,200 | 73 | %-----------------------------------------------------------------------------------------
% Script to plot the fraction of odor-modulated neuron per recording session
%
% Kehl et al. 2024 (DOI:XX)
% Single-Neuron Representations of Odors in the Human Brain
% Figure 1h
% Author: Marcel Kehl
% License: MIT License
%-... |
b42b28bdde93dd2812a2710b5702c10362e83c4b9da15737267f942872a13c45 | MATLAB | 3,200 | 110 | function [labels,parcels]=parcelate2(X,target_parcel_size,target_num_parcels,opts)
if nargin<1, test_parcelate2; return; end;
if nargin<4, opts=struct; end;
% final_reassign requires knnsearch - which requires a toolbox
if ~isfield(opts,'final_reassign'), opts.final_reassign=0; end;
[M,N]=size(X);
labels=zeros(1,N);
... |
68051cfe40d700fe61890071fd5fbe5c210704d2987ed3149e639439e437df20 | MATLAB | 3,202 | 101 | function [ax,h]=suplabel(text,whichLabel,supAxes)
% PLaces text as a title, xlabel, or ylabel on a group of subplots.
% Returns a handle to the label and a handle to the axis.
% [ax,h]=suplabel(text,whichLabel,supAxes)
% returns handles to both the axis and the label.
% ax=suplabel(text,whichLabel,supAxes)
% returns ... |
cfadef603dc769d4f695576f900b27e3c80b641f384fbc969662650b2a888cf0 | MATLAB | 3,203 | 124 | classdef TrxUtil
methods (Static)
function ptrx = newptrx(ntrx,npts)
s = struct();
s.id = 0;
s.p = nan(npts,2,0);
s.pocc = nan(npts,0);
s.TS = nan(npts,0);
s.x = nan(1,0);
s.y = nan(1,0);
s.theta = nan(1,0);
s.firstframe = 1;
s.off = 0;
s.n... |
d28fb0587614c1431bf2e59f280dea068b2434545c7aa34d8b0ed1408f455679 | MATLAB | 3,203 | 80 | function wlPlot_plotEventsWithContext(cfg, evlist, evstride, ...
signal, samprate, fnom, contextlengths, contextcycles, ...
figtitle, filelabel)
% function wlPlot_plotEventsWithContext(cfg, evlist, evstride, ...
% signal, samprate, fnom, contextlengths, contextcycles, ...
% figtitle, filelabel)
%
% This functi... |
5116317a89ae8d397bf450d0951a973805e009a6efaf989a12aded9ba5ae77c0 | MATLAB | 3,204 | 108 | function [t,x_new,f_new,g_new,funEvals,H] = ArmijoBacktrack(...
x,t,d,f,fr,g,gtd,c1,LS,tolX,debug,doPlot,saveHessianComp,funObj,varargin)
%
% Backtracking linesearch to satisfy Armijo condition
%
% Inputs:
% x: starting location
% t: initial step size
% d: descent direction
% f: function value at s... |
5fd66c6dc3c6246721de82cf39cc7a6d6d31c6de45d14bf94a1890cf2c5e6fc1 | MATLAB | 3,204 | 108 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% wrapper_full_calibration.m -- A wrapper for the calibration runtime. %%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function []=wrapper_3shell_amr(pat_ix, model, inverse_model)
pat_cell = {'110411','117... |
2fac03d944e3a08fb005c7f387a46453d33758a1f08712862deb0bd91f9fa542 | MATLAB | 3,206 | 74 | function testCondaBackendConfig_(obj, labeler)
% Test the conda backend
obj.testText_ = {sprintf('%s: Testing Conda Configuration...',datestr(now))};
labeler.notifyRetrograde('updateBackendTestText');
% Check if Windows box. Conda backend is not supported on Windows.
obj.testText_{end+1,1} = '';
label... |
1341d9778f81477c15f9ba4b3262634ca62e4b4046b33ee899c98d96ecbef668 | MATLAB | 3,207 | 98 | % _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
% preferences file for crabsort
% crabsort has many preferences, and, instead of wasting time buil... |
6b26cd05ded3ea815a44428d441acad43b40c7260a0ebc77082540d703977ed0 | MATLAB | 3,208 | 91 | %% (predictSDO) anova
% For use within the SDO Analysis Toolkit.
% Stand-alone header for testing the stats within the errorStruct;
% Take observed prediction errors, paired-point bootstrap to produce
% distributions w/ confidence intervals, and evaluate differences in a
% chosen test statistic (sum, mean, media... |
79cbc65dd211339de89f870eaf71e415981097ecccf1f4e479aec4d58fbc39e3 | MATLAB | 3,208 | 94 | function [stats,st] = lme_mass_fit_vw(X,Zcols,Y,ni,maskvtx,fname,prs,e,Xrows)
% [stats,st] = lme_mass_fit_vw(X,Zcols,Y,ni,maskvtx,fname,prs,e,Xrows)
%
% Vertex/voxel-wise linear mixed-effects estimation.
%
% Input
% X: Ordered (according to time for each subject) design matrix (nmxp, nm
% total # of maps, p # of fixe... |
e0920d54762cf89d1c75b1cc1b16be940a69972f4debd678eb3b22f349731d10 | MATLAB | 3,208 | 114 | function [mask] = image_stack_adjust(stack, name, volume_filtering)
% TODO: optimize
%load parameters
parameters;
times_smaller_to_take =5;
Nz = length(stack(1,1,:));
for ii=1:Nz
images{ii} = stack(:,:,ii);
end
clear stack;
max3 = @(x) max(max(max(x)));
%% -------------------------... |
f3add730eb80168d19bd27a58767fea4b79886343cc0df5a5893ad2e4ed21fd6 | MATLAB | 3,208 | 83 |
%% parameters setting
% clear;
hemi={'lh';'rh'};
hm=2;
surf_tpe='sphere';% or surf_tpe='inflated';
% surf_tpe='inflated';
ssname='litong_xyf';
plotdata = COR_for_plot{1};
load COR_for_plot_new_pearson;
sessionix = 2;
% data_dir = '/home/xianchige/TL/foolDNN_zc';
hemis = {'lh','rh'};
surfsuffix='orig'; %Non-dense su... |
2b76b777b94ea8e84dea8f9db357d566ced8e628444835c59d6820accb324adb | MATLAB | 3,209 | 102 | function [D, max_k_val, no_dims] = find_nn_adaptive(X)
%FIND_NN Constructs nearest neighbor graph using adaptive nbhd selection
%
% [D, max_k_val, no_dims] = find_nn_adaptive(X)
%
% Constructs nearest neighbor graph on the data in dataset X using adaptive
% neighborhood selection. In X, rows correspond to the observati... |
4b5e5f4eca2536719012d945e2722d8974eaf041db7eae5a49f447e9dca82c58 | MATLAB | 3,209 | 90 | function process_behavior_folder(basepath,varargin)
% process_behavior_folder adds CellExplorer session, event,
% and behavior files to folders that only contain behavior (no intan generated digitalin.events.
% Dependencies:
% SNLab_ephys/preprocessing/behavior
% FFMPEG added as enviornmental variable so it... |
c0f47aeaa4973bc3021b928ab81d8025b71f74e53e87e95802dccd19a18c30be | MATLAB | 3,209 | 110 | clear
load('20240207f_00005_analysis.mat', 'Dnum', 'data_compressed','stimuli_start_time','total_trials')
load('ROI_cor_20240207f_00005.mat')
load('data_20240207f_00005.mat', 'stimulus_info')
load('position_info.mat')
%
figure
set(gcf,'color','w');
set(gcf, 'Position', [230,430,350,100])
set(gca, 'box', 'off')... |
0c410589122dd7157c857279d999d73ec602fea5ff743bb2c361fe75c4811e51 | MATLAB | 3,211 | 83 | function loc_list_clusters_data_table_short(data)
counter = 0;
for i = 1:length(data)
data_to = unique(data{i}.area);
if length(data_to)>1
counter = counter+1;
data_to_send{counter} = data{i};
end
end
if exist('data_to_send','var')
f = waitbar(0,'Extracting Data Table Informati... |
1f7396a3b7d40b37510c7e78bbda90bd49cc0cc4ea3836292d9e72b97052a744 | MATLAB | 3,212 | 75 | function headshape = prepare_mesh_cortexhull(cfg)
% PREPARE_MESH_CORTEXHULL creates a mesh representing the cortex hull, i.e. the
% smoothed envelope around the pial surface created by FreeSurfer.
%
% This function relies on FreeSurfer's command line functions and
% 'make_outer_surface' in the FreeSurfer/matlab folder... |
5fe94a17af3a8ff37f7b948c9bb51be2b665d73558bfb3b43b4823466d5a6c18 | MATLAB | 3,212 | 72 | function [IDX,M] = meanShift(X, radius, rate, maxIter, minCsize, blur )
% meanShift clustering algorithm.
%
% Based on code from Sameer Agarwal <sagarwal-at-cs.ucsd.edu>.
% For a broad discussion see:
% Y. Cheng, Mean-shift, mode seeking, and clustering, IEEE Transactions on
% Pattern Analysis and Machine Intelligence,... |
61d468bce46f5a2c17059db6c602c01fb8ff5b7bee95591c6b88b7179af8f4ca | MATLAB | 3,212 | 100 |
% load data
% contact Lead Author for data
%% run-consistency in AUDIO vs VISUAL
% panel 5N
figure; hold on
useR = 3;
% ao
iidx = [34 48 68 116]; xidx = 1;
xx = cat(1, cueConsistencies{useR,:}); xx = xx(:, iidx);
bar(xidx, nanmean(xx, 'all'), 'm', 'FaceAlpha', 0.5);
errorbar(xidx, nanmean(xx, 'a... |
e094ea8475de6a08ee255f6455589bbfe27d71718a4da025a6ef8598e2352c38 | MATLAB | 3,212 | 83 | function out=rate_remapping_ONE_TRACK(folders)
if isempty(folders)
a=pwd;
folders={a};
cd ..
end
cd(folders{1});
data=compare_replay_across_tracks;
for epoch=1:size(data,1)
for track=1:size(data,2)
out(epoch,track).experiment=[];
out(epoch,track).place_fields_BAYESIAN=[];
ou... |
4bbcb75e35a395fcb7b405eb73ede90cd86a601b7c9c77e3399c22c708134ad0 | MATLAB | 3,214 | 105 | function [ newevent, error ] = wlProc_fitAmpGrid(hilmag, oldevent, gsteps)
% function [ newevent, error ] = wlProc_fitAmpGrid(hilmag, oldevent, gsteps)
%
% This function estimates oscillatory burst amplitude by curve fitting a
% logarithmic or linear ramp in the region of interest. Roll-on and roll-off
% are chosen vi... |
c5667308d1ec4ff434e9ed3a1968f447150c19d9e12fe13121efb8c31501d77d | MATLAB | 3,216 | 87 | function result = genContainerMountPathBsubDocker_(obj, tracker, cmdtype, jobinfo)
% Return a list of paths that will need to be mounted inside the
% Apptainer/Docker container. Returned paths are wsl-locale MetaPaths.
assert(obj.type==DLBackEnd.Bsub || obj.type==DLBackEnd.Docker);
aptRootAsChar = APT.Root... |
0c3e051f27219add8caa2523a7f28695f5b9ce758078fe38265281d99facbdb8 | MATLAB | 3,217 | 72 | function shuffled_track = ground_truth_parallel_shuffles(shuffle_choice,analysis_type,num_shuffles,decoded_replay_events,place_fields_BAYESIAN,BAYSESIAN_NORMALIZED_ACROSS_TRACKS)
%runs run_shuffles on multiple cores in parallel
% shuffle_choice- determines what type of shuffles will be performed, entered as a string
%... |
3af9a319e3652ddf0c6220f2dd521298422ce95d1cd672d3e68f5da372b47f63 | MATLAB | 3,217 | 95 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% To remove the duplicates (MUs that share most of their discharge times,
% the threshold is defined in the script main.m)
% Input:
% PulseT = Pulse train of each MU
% distime = discharge times of the motor units
% distime2 = di... |
75ecdeedc26b12d0891360a0076960fc8819096a5274f8c0f077f301ff4618e3 | MATLAB | 3,218 | 93 | function F = VBA_spm_Ncdf(x,u,v)
% Cumulative Distribution Function (CDF) for univariate Normal distributions
% FORMAT F = spm_Ncdf(x,u,v)
%
% x - ordinates
% u - mean [Defaults to 0]
% v - variance (v>0) [Defaults to 1]
% F - pdf of N(u,v) at x (Lower tail probability)
%________________________________... |
0a62b9c707c76b044d585124ae2755fc01fe8c87f933fc01750343c7a01a8a32 | MATLAB | 3,220 | 122 | function [Iphi,SigmaPhi,deltaMuPhi,suffStat] = VBA_Iphi_binomial(phi,y,posterior,suffStat,dim,u,options)
% Gauss-Newton update of the observation parameters, for binomial data
if options.DisplayWin % Display progress
if isequal(options.g_fname,@VBA_odeLim)
STR = 'VB Gauss-Newton on observation/evolution p... |
4768344ab04b5db01a23cfd2aa010ee720b0a7021e91f795b458ddf33a931b10 | MATLAB | 3,220 | 111 | function img = getframe_invisible(img,sz,GRAYBORDER)
if nargin < 1,
img = get(0,'currentfigure');
if isempty(img),
error('No window open');
end
end
issize = nargin == 2 && ~isempty(sz);
if ~ishandle(img)
error('Input is not a handle');
end
if nargin < 3,
GRAYBORDER = 204;
end
inputType = getInputType(... |
9e8ebb58a443076df58de21a316e61e824ebb95d68c465e8d5ee1f4f61345867 | MATLAB | 3,220 | 155 | %load data: contact lead author
%%
aoCellIdx=aoRewardIdx;
vsCellIdx=vsRewardIdx;
i=find(nRuns(:,1)>1);
%% rbr consistencies
rbrConsistenciesUse=rbrConsistencies(i);
ddAO = cat(1, rbrConsistenciesUse{:});
% ddAO=ddAO(iUse);
ddAO = ddAO(aoCellIdx);
ddVS = cat(1, rbrConsistenciesUse{:});
% ddVS=ddVS(iUs... |
1f01bcecb5fa672231312722d5f8c5071644c843c0e16157bfb8ccba0c2f519c | MATLAB | 3,221 | 73 | function d = meshsegtrintersection(orig0, dir0, dist0, P0, t0)
% This function checks whether or not a segment characterized by orig0,
% dir0, dist0 intersects a manifold mesh P0, t0.
% Inputs:
% orig0 - Origin of the segment (1 x 3)
% dir0 - Normalized direction of the segment from origin (1 x 3)
% di... |
3406d356fc095a8a92dedc7f361021fcc89739e33892614f32d3ddb633c62351 | MATLAB | 3,222 | 96 | %% NeVRo HEP preprocessing pipeline
%
% Runs the full preprocessing pipeline over all data sets by calling the
% single helper functions. It does this in seperate iterations for (a) the
% movement ("mov") vs. the non-movement ("nomov") condition as well as
% (b) either including ("SBA" := Space Coaster + Break + And... |
2b500dabef30dda59d852fd2cb0341d5443462d6c743d72cd9cfa8518f01649e | MATLAB | 3,223 | 93 | function result = interpSurfTriLinear(inputGrids, stack)
% interpolate 3D data set over gridded 2D inputs
%
% interpSurfTriLinear(inputgrids, stack)
%
% inputGrids is cell array of 2D grids {X,Y,Z}
% stack is a 3D numeric array
%----------------------------------------------------------... |
370ad3f780430fc184ab6db8cdec5e67afa09e36af118062849f6dc95e51b317 | MATLAB | 3,223 | 59 | clear all
%%
%Identify optimal SNR Efficiency as function of b-value
%%
%Define Parameters
[optScanner,optSample,optSSFP,optSE] = ParameterOptionsSNROscillating();
%%
%Define b-value associated with single Gradient instance (ms/um2) - Used to calculate relative effective b-value with DW-SSFP only
bOsc=1;
%%
%Define T1 ... |
ae9c2171659172f406f02012de23721ae7b1960a984e7adfa66a6f884b49d41f | MATLAB | 3,223 | 166 | %% Kmeans Model Selection in 1D
% Uses netlab since haven't had time to switch over to pmtk
%%
% This file is from pmtk3.googlecode.com
clear all
setSeed(0);
mix = gmm(1, 3, 'spherical');
mix.centres = [-1 0 1]';
mix.covars = [0.1 0.1 0.1];
%e = 1e-2; e2 = e/2;
%mix.priors = [0.5-e2, 0.5-e2, e];
bins = -2:0.1:2;
n ... |
ee1948788ef13d8e0958caf51dd4f32b81e9280710356cfe53fd7922f20ef42b | MATLAB | 3,223 | 72 | function shuffled_track = global_remapped_parallel_shuffles(shuffle_choice,analysis_type,num_shuffles,decoded_replay_events,place_fields_BAYESIAN,BAYSESIAN_NORMALIZED_ACROSS_TRACKS)
%runs run_shuffles on multiple cores in parallel
% shuffle_choice- determines what type of shuffles will be performed, entered as a strin... |
221342737dd5ccc05cf1061c6451f046bed9200b74964429d88a59aab3ec07b1 | MATLAB | 3,224 | 87 | function x=irfft(y,n,d)
%IRFFT Inverse fft of a conjugate symmetric spectrum X=(Y,N,D)
%
% Inputs: Y(M) The first half of a complex spectrum
% N The number of output points to generate (default: 2M-2)
% D The dimension along which to perorm the transform
% (default: fir... |
a8501e8c34119a4475452ccc59c0a3dd2d7f579004a97841cdc5423010f3a23a | MATLAB | 3,224 | 59 | clear all
%%
%Identify optimal SNR Efficiency as function of b-value
%%
%Define Parameters
[optScanner,optSample,optSSFP,optSE] = ParameterOptionsSNROscillating();
%%
%Define b-value associated with single Gradient instance (ms/um2) - Used to calculate relative effective b-value with DW-SSFP only
bOsc=1;
%%
%Define T1 ... |
f04559d6bfbaaa9260d90d5cce6832b1286cb7d6097b92dfa005f9b0b2b60110 | MATLAB | 3,225 | 91 | function figHandle = nXnSequenceRaster(network_spike_sequences, plotIDs, spikes_V_m, parameters, network, varargin)
% Plots plotIDs' sequences from network_spike_sequences(ithTrial).spike_ranks
% sorted against each of the other plotIDs sequences in an nToPlot by nToPlot
% grid of subplots
%
% network_spike_sequences: ... |
0521389e1f6b12b91856da14c42a38b5a2183283f0b8ad53e596ec63c6380cbe | MATLAB | 3,226 | 98 | function CBIG_ABCD_proc_task_qc(id,proc_dir,bbr_thr,maxFD_thr,length_thr,FD_th,DV_th)
%
% CBIG_ABCD_proc_task_qc(id,proc_dir,bbr_thr,maxFD_thr,length_thr,FD_th,DV_th)
%
% This function reads some qc measures and then remove runs that failed qc from the bold list
%
% Inputs:
%
% - id:
% subject id
%
% - proc_dir... |
a375679c71b8fe096229f80870dd266a11ed2463453b924a79bd91be85307f7c | MATLAB | 3,228 | 95 | function filelist = depfunFast(fn,recursive)
% Variation on the built-in depfun function, which skips toolbox files
%
% filelist = mydepfun(fn)
% filelist = mydepfun(fn,recursive)
%
% Returns a list of files which are required by the specified
% function, omitting any which are inside $matlabroot/toolbox.
%
% "fn" is ... |
f253ad6b21b9af292848726a653ca20cb5f35a16865d874a083624379d1ccad1 | MATLAB | 3,228 | 99 | function [hdr] = ft_fetch_header(data)
% FT_FETCH_HEADER mimics the behavior of FT_READ_HEADER, but for a FieldTrip
% raw data structure instead of a file on disk.
%
% Use as
% hdr = ft_fetch_header(data)
%
% See also FT_READ_HEADER, FT_FETCH_DATA, FT_FETCH_EVENT
% Copyright (C) 2008, Esther Meeuwissen
%
% This fil... |
756b7abd0ee8dfc0a2406204e17be60e05b228aa1038fd78a2401553263b8111 | MATLAB | 3,229 | 115 | K = 50;
D = 2;
T = 100;
dampen = .25;
sigmareal = .1;
sigmaobs = .0;
appearancemu = .9;
appearancesig = .2;
badappearancemu = .1;
badappearancesig = .2;
poslambda = .1;
misscost = (appearancemu+badappearancemu)/2 + sigmareal*poslambda;
pmiss = .3;
Xreal = nan(D,T);
noise = randn([D,T])*sigmareal;
Xreal(:,1) = noise(:... |
b75ed7db5c0c5b8172f3b1855400cc2d211510547c0073a6829981eb6c82786f | MATLAB | 3,230 | 89 | function [ ] = run_physIO(phys_file, fmri_file, sf, save_dir, per_slice, overwrite)
% Runs TAPAS PhysIO RETROICOR/HRV/RVT estimation
% load sf from json and tr/n_slices/n_vols from nii
% assumes that the following "package" is installed:
% https://nl.mathworks.com/matlabcentral/fileexchange/8797-tools-for-nifti-and-a... |
4644f6f50c756a939421db3e4240f7c683f5fd71167d484de596e072c0175b86 | MATLAB | 3,231 | 115 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function figure_spinal_isopotentialplot(dat, subjects, condition, srmr_nr, is_au)
% get info
[cond_info] = get_conditionInfo(condition, srmr_nr);
cond_name = cond_info.cond_name;
[~, esg_chans, ~] = get_channels(15, false, false, srmr_nr);
%% merge data
all_chanvalues ... |
b58e227324df854fe67ef2537a2d155fee2999e533489cde32e53ee3cb02aa05 | MATLAB | 3,231 | 117 | function [in] = selectpoints(POL, ObsPoints, Pof, Eof, Plane)
% Select indexes "in" of ObsPoints within multiple tissue(s) cross-sections
% defined by vector POL
% SNM 2024
if isempty(POL) % nothing selected
Points = ObsPoints;
return;
end
%% Initialize
Points = [];
%% ... |
1eab4da634fff1016f00cea8457e6e5003292bfeabc04c7e00d54d639a4286c9 | MATLAB | 3,232 | 100 | function varargout = motion_c3d(filename, hdr, begsample, endsample, chanindx)
% MOTION_C3D reads motion tracking data from a C3D file, see https://www.c3d.org
%
% Use as
% hdr = motion_c3d(filename);
% dat = motion_c3d(filename, hdr, begsample, endsample, chanindx);
% evt = motion_c3d(filename, hdr);
%
% See al... |
e6ff5af25047172f047a65721c7adaa81be8be40f9dc6746ae2677466741ec7d | MATLAB | 3,232 | 64 | % BoutonArray is a structure: BoutonArray(BotuonNumber).Field with fields
% .ImageArea, .ImageDeltaGFP, etc. The function will add fields .DeltaX and .DeltaY
% BeforeGFPImageArray(y-coord, x-coord, ImageNumber)
function BoutonArray = ArrayReg(BoutonArray, BeforeGFPImageArray, MaxShift, MinCorrValue, Jitters);
... |
069776ed61226bc7d0422737459961b9dbd84dd2a2b4e7832c73dba1d0293954 | MATLAB | 3,234 | 104 | function [data_compressed, TP_count_compressed, TP_count_original, photodiode_count_compressed, stimuli_start_time, stim_time_method] = compress_data_file_v4(dataset_name, photodiode_threshold, total_trials, Dnum)
load(['data_' dataset_name '.mat'])
timepoint = length(data(1,:));
data_compressed = zeros(Dnum, timepoin... |
0abb0c890fabd07fdb4936744f4f3d174b7830c5f0fb2536c018a4f9d6599bc8 | MATLAB | 3,234 | 113 | function p = myredbluecmap(m,varargin)
%MYREDBLUECMAP creates a red and green colormap.
%
% MYREDBLUECMAP(M) returns an M-by-3 matrix containing a red and green
% colormap. Low values are bright green, values in the center of the map
% are black, and high values are red. If M is empty, the length of the
% map w... |
4db213014bcfd890f02ec6d6db4898d7754c4735c45506f8cb41a56f6b759844 | MATLAB | 3,234 | 91 | function [fnorm,t,rejratio]=ifestar2(x,t);
%IFESTAR2 Instantaneous frequency estimation using AR2 modelisation.
% [FNORM,T2,RATIO]=IFESTAR2(X,T) computes an estimate of the
% instantaneous frequency of the real signal X at time
% instant(s) T. The result FNORM lies between 0.0 and 0.5. This
% estimate is based o... |
c368e9998513ef6e8a66d74c507b9b1fdf5a096863bba74a5b478a50cbad7363 | MATLAB | 3,234 | 130 | function [pval] = stata_cluster_3d(cls, stat, nrandom,elec)
% Realiza Cluster-Randomization-Analysis en cartas timepo-frecuencia
% por electrdo
% recomendado primero hacer correci{on cluster por cada electrodo
% cls -> custers detectados por corrention.m , en { [cluste1] [cluster2] }
%
% P Billeke
% 9 agosto 2009
% s... |
40ee8c23501fa2040190a599f72c33acac1728f9dd4793f24dce7a2474ae73d6 | MATLAB | 3,235 | 181 | xx = h5read('02_b3_000_000.hdf5','/estimates/F_dff');
load('02_b7_000_001.mat');
b=size(xx)
%x1=posTrials02
peak_num = [];
Prom = [];
SorWh=size(fields(info))
if SorWh(1)==24
x=info.frame;
x=x+1;
else
i=1
end
i=1
for l=1:b(2)
w=[];
w1=[];
w2=[];
i=1
w=xx(:,l);
for n =... |
75f5283504b6c1a728ff19c2caea07241e35250c85ec998daad2935b721e1491 | MATLAB | 3,237 | 80 | function Obj = SOFAconvertBTDEI2SOFA(BTDEI)
% OBJ=SOFAconvertBTDEI2SOFA(BTDEI) converts the HRTFs described in BT-DEI
% to a SOFA object.
%
% BTDEI format is used by Michele Geronazzo, University of Padova.
%
% Copyright (C) 2012-2013 Acoustics Research Institute - Austrian Academy of Sciences;
% Licensed under the E... |
c7bf7980056d3158e2d97d62dd3d348186278ead22a3082a6d509bd0a3924538 | MATLAB | 3,237 | 106 | clear
% clc
res=2;
dur=66;
all_trials_loc.glm_dd=nan(dur/res,3495);
all_trials_loc.glm_df=nan(dur/res,3495);
all_trials_loc.glm_fd=nan(dur/res,3495);
all_trials_loc.glm_ff=nan(dur/res,3495);
all_trials_loc.glm_time=nan(length(-1:res/100:2),3495);
all_trials_loc.glm_context=nan(length(-1:res/100:2),3495);
all_trial... |
5b86c04adbbcc6305da9207d60cbc63a88e3c2c2cecb84463c0b34574344843e | MATLAB | 3,238 | 102 | function [sessionNames,subjectNames,ITPCsubject,ITPCsession] = meg_sessions(expt)
% function [sessionNames,subjectNames,ITPCsubject,ITPCsession] = meg_sessions(expt)
%
% INPUT
% expt
% experiment name, 'TANoise' or 'TA2'
%
% OUTPUT
% sessionNames
% cell array of session names
% subjectNames
% cell array of subje... |
2add4a5becd124f397b254d472780721e6d653eadbe77ba5d5b6280cb8e8a5eb | MATLAB | 3,239 | 99 | function [mappedX, mapping] = lpp(X, no_dims, k, sigma, eig_impl)
%LPP Perform linearity preserving projection
%
% [mappedX, mapping] = lpp(X, no_dims, k, sigma, eig_impl)
%
% Perform the Linearity Preserving Projection on dataset X to reduce it to
% dimensionality no_dims. The number of neighbors that is used... |
5c0cbe461c82bbf3e98e37cb0ab68612255f6a51e088e5c5bfc672dcbe75d274 | MATLAB | 3,239 | 77 | function [data_dir, subject_list_file, behavior_csv, HM_file, corr_mat_file, measure_dir, measure_set] ...
= CBIG_KRDNN_mics_load_setup(setup_file)
% [data_dir, subject_list_file, behavior_csv, FD_txt_file, corr_mat_file, measure_dir, measure_set] ...
% = CBIG_KRDNN_mics_load_setup(setup_file)
%
% This function split... |
83e349c595bcc99da891470ba87526b95749d8a1dc6c3e3d455b7afde26e0c52 | MATLAB | 3,240 | 115 | function PlotCCG(t,ccg,varargin)
%PlotCCG - Plot auto/cross-correlograms of point processes.
%
% USAGE
%
% PlotCCG(t,ccg)
%
% t time bins obtained using <a href="matlab:help CCG">CCG</a>
% ccg data obtained using <a href="matlab:help CCG">CCG</a>
% <options> optional list of p... |
ddc839bc74cf377503767cc4b2372db55951d677aab4f77acc49ffd26f592f56 | MATLAB | 3,240 | 108 | function [U,s,Vt]=compute_svd(M, method, n_components)
%%%%%%%%%%%%%%%%%%
% Compute svd on centered M
% M is d x T
%%%%%%%%%%%%%%%%%%
if nargin<2, method='vanilla'; end
if nargin<3, n_components=100; end
if strcmp(method, 'vanilla')
[U, s, Vt] = svd(M,'econ');
elseif strcmp(method,'randomized')
[U, s, ... |
6aa97a397886b6a6b160ad843fdb8a7526c201d7f984c0e5541518cf4a128ed5 | MATLAB | 3,241 | 120 | function writenodelm_nod_elm(fn,e,p,nodemap,no_of_att,quiet)
% writenodelm_nod_elm(fn,e,p,nodemap,no_of_att)
% writes nodes and elements to two seperate files with .node and .ele
% extension. the format of the files is as follows.
% User should not provide any extension in fn.
% The format of .nod header is:
% <# of po... |
7b66cf17a17bb23e5640915fd1f3f3a6f10ec921fef1910af35b8cf635edc187 | MATLAB | 3,244 | 85 | function [U,mu,vars] = pca( X )
% Principal components analysis (alternative to princomp).
%
% A simple linear dimensionality reduction technique. Use to create an
% orthonormal basis for the points in R^d such that the coordinates of a
% vector x in this basis are of decreasing importance. Instead of using all
% d bas... |
7a0c26ff96767b2c7032e1866ceefbfdf91393e927b2958a2a5f17be09dd69c6 | MATLAB | 3,245 | 96 |
%% general options
elec_path = fullfile(patient_path,'dipoles',strcat(patno,'_',model_name,'_', ...
dipole_name,'_electrodes.mat'));
%% load BEM-FMM Engine
addpath(fullfile('../engines/bem_fmm_engine'));
%% load data
V_skin = Ptot(Indicator==skin_id,strength_ix,sim... |
bbc4e8a9a86cb65d776d0585ee3560d10159ea1746f6ce43d609b8acded4f98b | MATLAB | 3,246 | 97 | function peaks = houghcirclepeaks(varargin)
%HOUGHCIRCLEPEAKS Identify peaks in 3-D accumulator for Hough
%transform.
% PEAKS = HOUGHCIRCLEPEAKS(H,NUMPEAKS) locates peaks in the Hough
% transform matrix, H, generated by the HOUGHCIRCLES
% function. NUMPEAKS specifies the maximum number of peaks to
% identify. ... |
83ba0a57815fc4709a397e0299d51a49b56b21e68625eab23319a568ae4138b1 | MATLAB | 3,247 | 91 | function headmodel = ft_headmodel_halfspace(mesh, Pc, varargin)
% FT_HEADMODEL_HALFSPACE creates an EEG volume conduction model that
% is described with an infinite conductive halfspace. You can think
% of this as a plane with on one side a infinite mass of conductive
% material (e.g. water) and on the other side non-... |
2a7b27b05dc0912fd140b8fa6f343c77abc39c25a54205a6e85e0ccb7457fe44 | MATLAB | 3,249 | 72 | function shuffled_track = randomised_data_parallel_shuffles(shuffle_choice,analysis_type,dataset_type,num_shuffles,decoded_replay_events,place_fields_BAYESIAN,BAYSESIAN_NORMALIZED_ACROSS_TRACKS)
%runs run_shuffles on multiple cores in parallel
% shuffle_choice- determines what type of shuffles will be performed, enter... |
3bb8e3cbee6d4b22a4f57697ca0ccdfb1b1aea730afe98d3b06e1928314078f2 | MATLAB | 3,250 | 96 | function varargout = text2( varargin )
% Wrapper for text.m that ensures displayed text fits in figure.
%
% When text is called, Matlab displays the text, but does nothing to ensure
% that all of the text fits in the figure. This function, after calling
% text, shrinks the axes until the text is fully visible. Note t... |
45c7dacccb0282269d09ae8c8e0103462ff22ab216bda0e560ee2c83d4289cd7 | MATLAB | 3,250 | 62 | function [input] = soundExtract(input, sample_rate, baseline, aftermath, type)
for i = 1:length(input.Mouse_Name)
substrings = {'sound', 'saline', 'CNO'};
if any(contains(input.Sweep_Type{i}, substrings))
if type == 1
sound = input.Sweep_MembranePotential{i};
... |
64c4ff684b9bf208e3e0bc857a59f67e8644724717b37a08d37b8d43d8e488d7 | MATLAB | 3,250 | 115 | fid = fopen('~/work/PoseEstimationData/Stephen//bodyAxisTrainingData.csv');
K = textscan(fid,'%s %s %s',inf,'Delimiter','"');
fclose(fid);
%%
npermovie = 100;
cc = jet(5);
J = struct;
ts = zeros(1,0);
pts = zeros(2,2,5,0);
expidx = zeros(1,0);
vid1files = {};
vid2files = {};
for ndx = 1:numel(K{1})
%%
kfile = K{1}{... |
87f3110ba69d071f4673cb12eeea301b618e4461aed8919ca4a70e92c1509f33 | MATLAB | 3,250 | 84 | % Maximum distance within a spherical volume: translation + rotation about
% origin. The formula used is equivalent to 2*R*sin(a/2) where a is the
% angle of the single rotation equivalent to the original
% translation+rotation, and R is the distance from that axis to the
% furthest edge of the sphere. For the sphere... |
6ea248b21464cc632b23d30b25e49dd53fb15c1be0a9961fb6b81a97353b1031 | MATLAB | 3,251 | 84 | function ft_preamble(cmd, varargin)
% FT_PREAMBLE is a helper function that is included in many of the FieldTrip
% functions and which takes care of some general settings and operations at the
% begin of the function.
%
% This ft_preamble m-file is a function, but internally it executes a
% number of private scripts i... |
58233ad2f9d548392b848b4f1589d2b56ec61d493491933acb1bd0a735d34fd1 | MATLAB | 3,252 | 140 | %% Demonstrate inference in a 2d grid of a noisy image of an X
% Based on
% http://www.cs.ubc.ca/~schmidtm/Software/UGM/graphCuts.html
% http://www.cs.ubc.ca/~schmidtm/Software/UGM/ICM.html
% http://people.cs.ubc.ca/~schmidtm/Software/UGM/MCMC.html
% http://www.cs.ubc.ca/~schmidtm/Software/UGM/variational.html
% This... |
7c766483feb62cb75935cbb60750ef7954e9382c13398a399137d7c1b6b55937 | MATLAB | 3,253 | 105 | function [nse] = read_neuralynx_nse(filename, begrecord, endrecord)
% READ_NEURALYNX_NSE reads a single electrode waveform file
%
% Use as
% [nse] = read_neuralynx_nse(filename)
% [nse] = read_neuralynx_nse(filename, begrecord, endrecord)
% Copyright (C) 2005-2007, Robert Oostenveld
%
% This file is part of Field... |
c173456dd6241aab664603e9fdc0e18478d747bc5b4b42d69c4f03a456184792 | MATLAB | 3,253 | 88 | function x=irfft_gpu(y,n,d)
%IRFFT Inverse fft of a conjugate symmetric spectrum X=(Y,N,D)
%
% Inputs: Y(M) The first half of a complex spectrum
% N The number of output points to generate (default: 2M-2)
% D The dimension along which to perorm the transform
% (default:... |
8b59889fe09cf8da7168976cd26346ba46e8ef645db74482c65222bae3146c8b | MATLAB | 3,254 | 84 | function batch_ripples(data_folder,varargin)
% For all session files in Data folder (path to animal folder or csv of basepaths), runs
% findRipple algorithm with default paramters. If session has cell_metrics,
% will also run eventSpikingThreshold to keep keep ripples that have
% increased firing of CA1 units greater t... |
bd2495d6496ac93cc43b7de039885f7782e2070fe7afd4af7fb1210b105ef71f | MATLAB | 3,255 | 135 | %script test recursive
%%%%% quantitative differences: because of the way the level is updated
%%%%% (should be analytically equivalent but not numerically). Small
%%%%% deiations for 2-ToM (but accumulates) larger for 3-ToM
x=zeros(2,101); xtest=x;
y1=VBA_random ('Bernoulli', 0.7, 100, 1);
inF.player=1;
inF.lev=0;
Par... |
0ff3aa318ceb448dcb406f14b4deabf20cfc63a2a31cc77400cebbd573e0f8ad | MATLAB | 3,256 | 89 | % Pairwise interactions on an exponentially graded line, Laplace kernel.
%
% This is basically the same as MV_LINE but now with points placed on a
% dyadically refined grid. The resulting geometry is highly non-uniform and
% provides a good test for adaptivity.
%
% Inputs (defaults are used if not provided or set empty... |
2102ba33cd53b6836c94355dd0cfd94f993a7c0a2325c02fd5092393cbc8855b | MATLAB | 3,256 | 103 | function Perm_1tp_Figs2(dataOut,IM,B,params)
%% Set parameters
if ~exist('B','var'),B=1;end
Pth=0.05./B;
[NNidx,Tidx,TNidx]=IM2idx(IM);
Nnets=max(IM.key(:,2));
NetKey=[[1:Nnets]',[1:Nnets]'];
cMap=[1,1,1;0,0,0];
%% Enrichment
a=reshape(dataOut.Chi_pval0,[],1);b=reshape(dataOut.Chi_EWpval,[],1);
c=res... |
7360bbf732a49b14f596ead7242f059213b22519e96247651425b9a0a222cec4 | MATLAB | 3,256 | 103 | classdef TrackingVisualizerMTModel < TrackingVisualizerModel
% Model layer for TrackingVisualizerMT.
%
% Holds non-gobject properties extracted from TrackingVisualizerMT: tracking
% data, point colors, show/hide flags, cosmetic state, etc.
properties
lObj % Labeler reference
trk % scalar TrkFile, views merg... |
94e64df1f7f10aa52d8368c80471e6b2416b394ab6161d3d01e4ee0c2d370b62 | MATLAB | 3,256 | 78 | function cPPI_without_deconv(stat_path,exp_folder,N,N_ROIs,q_level,ground_truth)
% ========================================================================
% Ruslan Masharipov, October, 2023
% email: ruslan.s.masharipov@gmail.com
% ========================================================================
tic
for subji... |
21250c47cae21c5da74781979e7066ff56c7507b008fadfb184f34c567b176bf | MATLAB | 3,257 | 146 | %% load the labels file
Q = load('/groups/branson/home/bransonk/tracking/code/rcpr/data/MousePaw/M118_M119_M122_M127_M130_M173_M174_M147_M194_20160310.mat');
%% convert to new lbl format with the nrs file locations
nmov = numel(Q.expdirs);
newnames = cell(nmov,1);
lclnames = cell(nmov,1);
nlabels = zeros(nmov,1);
mo... |
4dcabb4fe4c9105787cc5649808d4ea2f1a0a7eed23a6e3c93bc29161dcdd075 | MATLAB | 3,257 | 115 | % _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
% callback when main window is resized
function resize(self,~,~)
if ~isfield(self.handles,'main... |
96acda763cfe03d48d50ba44af19e559a2cc2863a8fe740180211d1605ce36ee | MATLAB | 3,257 | 80 | function Base_batch(FUNCTIONAL_FILE, fs_dir, base_dir, TR, sliceorder, scans_to_remove)
%%% COPY TO THE CONN BASE DIRECTORY TO WORK
% This base example has as input the fmri scan, the t1 scan, and the TR.
% Loads the preprocessing done in the script, denoise, and analyze the RRC,
% saving everything to disk
% sliceorde... |
76a16235fc4560819aa67c38de05132bfcb3cafcb94a533a9b1b17bf0e2f0149 | MATLAB | 3,258 | 81 | function [yRoi, lesioned] = afxRoiTimeseries(rois,y,subjectMasks,brainMask,XYZmm,denoisingOptions)
fprintf(' ROI timeseries extraction ...')
yRoi = nan(size(y,1),length(rois));
lesioned = zeros(length(rois),1);
% initialize atlas cache (avoid repeated resampling of atlas file for
% multip... |
890fe6df97692cd02baa55f7e43ded700a242e19517c22d27ecc96795c9d5151 | MATLAB | 3,258 | 94 | function f=expandstr(str)
%EXPANDSTR Expand indexed strings.
% F = EXPANDSTR('PP[RANGE]SS') returns a cell array of strings in the form
% 'PP0000nSS', where 'PP' and 'SS' are prefix and suffix substrings, n is
% an index lying in the range RANGE, paded with 5 zeros. RANGE is a
% vector, that can be in the for... |
28f4b4302d4c1c0fd01e79338657d075a0fe3730e5a8398f7d5f510092bf5218 | MATLAB | 3,261 | 103 | %% getpxTimeEvolution "getPxTE"
% Utility to generate a feedforward prediction of Px over N_STEPS using an initial
%probability distribution and a linear (L) update operator (SDO) under the
% framework px1 = x0 + dx(0), where dx0 is calculated by an update matrix.
%
% Permits the time evolution of multiple Ls in paral... |
f7bd6f4e4ba5d2583bd7da7f5d63b0430074a4a6efa363746ef0154ccacc6fa5 | MATLAB | 3,261 | 77 | function CBIG_RF_compute_vol2surf_avgMapping(sub_list, input_dir, input_prefix, output_dir, output_prefix)
% CBIG_RF_compute_vol2surf_avgMapping(sub_list, input_dir, input_prefix, output_dir, output_prefix)
%
% This function computes volume-to-surface avgerage mapping of x/y/z index
% across a given list of subjects.
... |
8d4c9abc8223d5bc8586680ff85ba04eb2efdb1cb93ebdf59dc0bda5e7bb0fac | MATLAB | 3,262 | 105 | % This code loads Results and looks at the peak of spikes and determines
% IZ from spike imaging results
% Abbas Sohrabpour
% 13/8/2018
clear all;close all;clc
bad_chan = [];
cd('../Grid Location and Defined Parameters')
load('UnconstCentLFD.mat')
[~, Num_Dip] = size(K);
K([bad_chan],:) ... |
afc2e07d309a856b7285338f2b86d45878843ad1efdc3a3102bb1a58abb8cd9f | MATLAB | 3,262 | 102 | % common plotter for the spike-triggered
% Only for use with the newer components of the parameter validation.
%Breakout from existing functions;
%Here, we passively pass most of the parameters, and hence this is not an
%ideal component for the end user; better to call only from the core method
% stapxt == A [ N... |
d59a30407e1be5721c55dc5d79707f824743f0450333e247e9bc7e0b0a320b83 | MATLAB | 3,262 | 134 | clear;
clc;
% close all;
%%
hist_data = [];
n_subjects = 8;
load ach_data_final.mat
load x_ecog_rt_data.mat;
srate = 400;
%%
all_rt_data = [];
for isub = 1:n_subjects
% subjects = [06 08 10 12 14 15];
load(['s' num2str(isub) '_cho_method_allperiod_v1.mat']);
r... |
5abb99bac33433f501c4c19420232339bcc927280699ef27fb7d4e0963791a99 | MATLAB | 3,265 | 112 | function [trx,savename,timestamps] = cleanup_ctrax_data(matname,moviename,in,ds,varargin)
if ~exist('ds','var')
ds = '';
end
[savename,dosave,annname] = myparse(varargin,...
'savename',strrep(matname,'.mat',['trx',ds,'.mat']),...
'dosave',false,...
'annname','');
if ~dosave,
savename = -1;
end
in.x_pos = in... |
7afa05d4b3f81e3464612909c6cf5d260e90f40efe859e6ac64abc1d62dd2f8e | MATLAB | 3,265 | 104 | % plot_trialAvg_decision_allSess
% new version of plot_bigSbigT_multipleS_trialAvg_decision_normS
pSL = colms - plot_resp_aligned;
for d = 1 : length(plotSig)
dim = plotSig{d};
i = i + 1;
assignSignal
if sub0 == 1; ylims = ylims - diff(ylims)/2; end
% Average traces aligned ... |
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