sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3f998f56678b40735ad56c27130fa5d1c77c2346bb331a15e601865a129cac14 | MATLAB | 4,430 | 150 | %This script will generate data and then fit pibdfc as an example.
%%
addpath('pibdfc_functions');
rng(34);
%% Generating the data
run('create_gaussian_simset.m');
%% Setting Up for the MCMC
nsims = 1000; %Number of simulations total
nburn = 1000; %Number of burn-in sims
S = 3;
a0 = 0.01; %Prior variance for rho/xi... |
9b2658c3059a7a83211ae05da1f4fe9c473e89c671887e7fe07d2d66a7b29e7c | MATLAB | 4,431 | 120 | function [spMat_src spMat_targ] = GrappaReco3D_arb_idx(sigDims,kernel,stepSize,startPos)
% function out = GrappaReco3D_arb_idx(sig,kernel,ws,stepSize,startPos)
%
% Daniel Gallichan, December 2012. Small modification to code from
% bernd.jung@uniklinik-freiburg.de to allow arbitrary GRAPPA kernel
% and multiple 'startPo... |
5f4f25912839abe3a0d899469d418c019e15b48835b61199abcc1e1cc422ae99 | MATLAB | 4,435 | 146 | function coeff = calc_energy_coeff(dim,N,s,energy)
%CALC_ENERGY_COEFF Coefficient of second term in expansion of energy
%
%Syntax
% coeff = calc_energy_coeff(d,N,s,energy);
%
%Description
% COEFF = CALC_ENERGY_COEFF(dim,N,s,ENERGY) sets COEFF to be the coefficient of
% the second term of an expansion of ENERGY with the... |
0d4050d1bbb0743e0b73d916d4db58251d2aa7bade74375a2cc43ee45b7ab10e | MATLAB | 4,438 | 189 | function plot_diff(f1,f2,tit)
param.mean_line_broadening = 1;
param.xlim=[0 4.5];param.ylim=[-2000 14000];
param.diff_y_lim=[-2000 3500];
param.save_file = '/home/romain/Doc/spectro_doc/Dysto/aaa';
param.xlim=[2.5 4.3];
param.xlim=[0 4.5];
%param.diff_y_lim=[-300 1500];
param.display_var = 0;
param.same_fig=1;
param.... |
55a22d36453385c811a6d8c2d9d016e3c931b93dd020c329ff71101a2c23152c | MATLAB | 4,441 | 136 | clear;
close all;
cd 'C:\Users\Admin\Git\repo\ZS-DeconvNet\Python_MATLAB_Codes\data_augment_recorrupt_matlab'; % change this path to your cloned path
addpath(genpath('./XxUtils'));
addpath(genpath('./GenData4ZS-DeconvNet-SIM'))
% It should be noted that, the raw data loading code of this demo is based on the file stru... |
f01ac3ede023aa61cf2632119c1d19c7cd5c7db00a0c1692545b7e44d47f2aa7 | MATLAB | 4,442 | 140 | function []=mnl_TracesChannelMIPs_Processed_TracesAndSomas(dim,efPxTrace,Somas)
%function that creates MIPs for each channel based on the traces from
%neurolucida
% Inputs
% dim - dimensions of the original image [x y c z]
% efPxTrace - structure containg the relevant inforation
% data - the image matrix
nTrace=size... |
be3d9bf76d6457df5c7db4a2afd1fae7bf59585078809d2db0c61329dfb7c728 | MATLAB | 4,444 | 108 | function rescaleFigProj(hFigProj, projScale, hCfg)
%RESCALEFIGPROJ
rescaleUpdate(hFigProj, projScale, hCfg);
hFigProj.figData.boundScale = projScale;
if strcmp(hCfg.dispFeature, 'vpp')
XLabel = 'Site # (%0.0f \\muV; upper: V_{min}; lower: V_{max})';
YLabel = 'Site # (%0.0f \\muV_{min})'... |
eb3e0a2c663ebf66ed41d2c56ebfeaeced495d238b2697248c7558f59fb7ed2a | MATLAB | 4,444 | 134 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
574c6a744db5ce7ea27500b078b4d1613497d763b41978144ecbded3efb19b9f | MATLAB | 4,449 | 121 | function [spatial, temporal, S] = compute_pca_joint( p,thisSub )
% to be able to work with large movies, we calculate the covariance
% matrix batchwise, in order to avoid loading the whole movie into
% memory
%% get info on movie batches (session movies)
sub = find(p.subjects == thisSub);
used_sessions = s... |
4e6b9e07dd4326179cdf1dc8f544b1cbca941d36b2106bcd352d1399bc47aadb | MATLAB | 4,452 | 149 | % plot distributions of some characteristics of accepted and rejected cells
% - diameter
% - symmetry of mean peak
% - n events per session
% - std of events per session
% - mse of snapshots
%% get necessary data
clear
p = params_2DAA;
fpath = fullfile(p.rootDir,'results','allData.mat');
load(fpath,'evs') % needed fo... |
55c9888507d509fa675bc3ff4ee87b0791df331985f446da8de2771a6bb22f8d | MATLAB | 4,452 | 125 | function [pitchsig,yanalframelen_out,ystep_out,nframes_out] = ...
get_sig_pitch(sig,fs,pitchlimits,yanalframe_ms,yanalstep_ms,yes_verbose)
% function [pitchsig,[yanalframelen_out],[ystep_out],[nframes_out]] = ...
% getwavepitch(sig,fs,pitchlimits,[yanalframe_ms],[yanalstep_ms],[yes_verbose])
% for example:
% pi... |
1e70e1eb0f03e3f5b7de29746c14aafb6ce4baa54b763e6a8f30dead5c1c9976 | MATLAB | 4,457 | 120 | clear
p = params_2DAA;
fpath = fullfile(p.processed_data_dir,'allData.mat');
load(fpath,'evs','tis','bvs','traces')
[cols,alpha] = chooseColors;
%% run DR and decoding procedure for different trial samples
fpath = fullfile(p.data_dir,'identification_of_tone_dim');
saveData = 1;
saveFigs = 1;
n_rep = 80; % ~80 sec. per... |
4c0a2dd03a4aaa83098e3522ce83d966eb10a9f20ec66feaf19f6c9ff49e6626 | MATLAB | 4,461 | 75 | function par = set_parameters()
% LOAD PARAMS
par.segments_length = 5; % length (in minutes) of segments in which the data is cutted (default 5min).
% PLOTTING PARAMETERS
par.cont_segment = true;
par.max_spikes_plot = 1000; % max. number of spikes to be plotted
par.print2file = true; % If ... |
cef520d1ccb8932f4bd061ed6318757cf21cb70962656c6b33983bd71a9c9036 | MATLAB | 4,461 | 75 | function par = set_parameters()
% LOAD PARAMS
par.segments_length = 5; % length (in minutes) of segments in which the data is cutted (default 5min).
% PLOTTING PARAMETERS
par.cont_segment = true;
par.max_spikes_plot = 1000; % max. number of spikes to be plotted
par.print2file = true; % If ... |
4f74a61428feda6311d9008cb13425742408e52208a03bb57c0350d7a638ce7a | MATLAB | 4,462 | 147 | function [ output_args ] = plot_summary_dim_projections_iti( proj_a, proj_e, dim_ves, saveFigs,out_dir)
n_dims = 5; % leave out PC2
lims = [-2.5 7.5];
cols = chooseColors;
rep_mean_a = squeeze(mean(cat(3,proj_a{:}),3));
rep_mean_e = squeeze(mean(cat(3,proj_e{:}),3));
rep_mean_ve = squeeze... |
91f667217edd68b9e73b73f3b3ea204adb2c6d143adbde2cc3101434974e5cc3 | MATLAB | 4,464 | 150 | function varargout = runOnAllInDir(runDir,testDir,settings)
% Run auto-find test on all structures in runDir
%
% function testDirThisSession = autoROI.tests.runOnAllInDir(runDir,settings)
%
% Purpose
% Batch run of autoROI.test.runOnStackStruc
% Looks for pStack structures in the current dir... |
fdfb8c7f709de25ad67536499397b7f0854f6473acd9c6a46099527822f0d60f | MATLAB | 4,465 | 120 | classdef adi
%
% Class:
% adi
%
% This class is meant to hold simple helpers for the package.
methods (Static)
function view()
%
% adi.view(*file_path)
%
% This is
%TODO: Run the viewer
file_path = adi.... |
9d90c236349f1aa3b3a5f9177d0a86504cfd8478a7c88114674e9411206e3039 | MATLAB | 4,468 | 118 | function avg_psth_PV(cellids1,cellids2,responsespec,resdir,spike)
%AVG_PSTH_PV Average normalized peri-event time histograms.
% AVG_PSTH_PV(CELLIDS1,CELLIDS2,RESPONSESPEC, RESDIR) calculates normalized
% average PSTHs aligned to RESPONSESPEC (cue, reward or punishment) for
% CELLIDS1 and CELLIDS2, respectiv... |
aa801f92204f5c8a23104378b8193fdaecd05c37546443da73be407221aed660 | MATLAB | 4,470 | 99 | function [myArbitrator]=Bayesian_Arb_Init(N_state,N_action,N_transition)
%% create arbitrator + set all initial parameters
myArbitrator.K=3; %trichonomy of PE
myArbitrator.T=10; %memory size = 10
myArbitrator.T_half=6; %half-life
myArbitrator.T_current1=0; % # of accumulated events. cannot exceed T.
myArbitra... |
51eb1777ec4999cb4e0e67293a66e7334c2e278ad5bad36715cc6b2dbe10a94d | MATLAB | 4,471 | 149 | function [kb, alpha, kb_m] = kaiser_bessel(x, J, alpha, kb_m, K_N)
%function [kb, alpha, kb_m] = kaiser_bessel(x, J, alpha, kb_m)
%function [kb, alpha, kb_m] = kaiser_bessel(x, J, 'best', 0, K_N)
%|
%| generalized Kaiser-Bessel function for x in support [-J/2,J/2]
%| shape parameter "alpha" (default 2.34 J)
%| order p... |
f05776adb86c721c33aad6018a59ad26a0df67e0812c8f8721d3b24ae4c9a203 | MATLAB | 4,474 | 135 | %% BOXPLOTS - FW in TISSUES HC vs MS
N1 = length(HCsubj);
N2 = length(MSsubj);
g2 = repmat({'GM-hc'},N1,1);
g3 = repmat({'WM-hc'},N1,1);
g5 = repmat({'GM-ms'},N2,1);
g6 = repmat({'WM-ms'},N2,1);
g7 = repmat({'NAWM-ms'},N2,1);
g8 = repmat({'T1L'},N2,1);
g9 = repmat({'T2L'},N2,1);
g10 = repmat({'periles'},N2,1);
x2... |
3f865aa76cc6678ba973ebd5e613755e88562388e6d3d673b239d61c959a918b | MATLAB | 4,475 | 132 | % This function computes the fluence in the 10-2.5 locations on the
% volumetric head mesh with Toast
%
% INPUTS:
%
% headVolumeMesh The multi-layer volume mesh structure.
% Contains fields: node, face, elem, labels
%
% landmarks A matrix containing the landmarks coordi... |
01759da50f7996cc4e14e620b929dc8a519cf1af272b482bd13dc7c8e20e3bd2 | MATLAB | 4,478 | 131 | clear
clc
%% add togethter meny WF files
[filename path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
datafile = fullfile(path, filename); %save path
all_wf.fr = [];
all_wf.mean = [];
for i = 1:length(datafile)
... |
87b3b1e8f80bcd4f9895d014e58406b13baa89684dea5ae62aea7b3744c85ffd | MATLAB | 4,479 | 166 | function ob = fatrix2_mtimes2(ob1, ob2, varargin)
%function ob = fatrix2_mtimes2(ob1, ob2, options)
%|
%| Construct fatrix2 object that is the product of two objects:
%| ob = ob1 * ob2.
%| Requires size(ob1,2) == size(ob2,1) as in matrix multiplication.
%|
%| in
%| ob1 *atrix any object that can do "mtimes" and "size... |
d87ab1e7d542d24591450365ec427a27147615367485b4d08f316c10d2da73a2 | MATLAB | 4,479 | 112 | function ROI_indices = select_ROIs_from_full_AAL(cfg);
% function ROI_indices = select_ROIs_from_full_AAL(cfg);
%
% Gives the indices of the ROIs in the AAL atlas that are needed for
% further analysis -- only cortical ROIs
%
% ROI order is the same as in Gong et al. 2009 (Figure 1g and Supplementary Table 1), a... |
007aa95477e210008834fe340273989c3a04dbe379097c131649b4aba88d4645 | MATLAB | 4,491 | 169 | classdef circularFit<ellipticalFit
%A class for executing and managing 2D circle fits
properties (Dependent)
radius
end
properties(Dependent,Hidden)
rad
end
methods %Accessors
function val=get.radius(obj)
val=obj.minorDiam/2;
end... |
ac9f2f6f1ace628a002a5fc4e2767aa982167fcb1aebaf643838d5602dab5cfa | MATLAB | 4,492 | 157 | function SpikeArray1=GetSpike
global StartTime FinishTime Spname
% StartTime
% FinishTime
DurationB=FinishTime-StartTime;
CurrentPath=pwd;
% cd C:\Users\B133\Desktop\WR_LVdata\6721_160218
% load 6721_160218.mat
cd C:\Users\B133_2\Desktop\CheetahData
%dpath='C:\Documents and Settings\kit\ƒfƒXƒNƒgƒbƒv\WR L... |
f6cab42e72aba09dc48b73ce4f6e955212af9c9cc16fadeee94f2cb0e7c48cfb | MATLAB | 4,495 | 160 | % nufft_tune_kaiser
% tune the shape parameter for kaiser-bessel interpolation in 1D NUFFT
% to minimize the worst-case error
% explore scaling factors
if ~isvar('N') && 0
N = 2^8; K = 2*N;
J = 6; alpha = 2.34 * J; kb_m = 0;
n = [0:(N-1)]'-(N-1)/2;
kernel = kaiser_bessel('inline', [], alpha, kb_m, K/N);
sn_zn = r... |
62cf1ae4b0d437284f736cc1038fc5835c031191edaf142ad33fe33a32c4933c | MATLAB | 4,498 | 117 | function [UC, UC_onsets, UC_counts, UC_counts_avg, Tachysystolic] = UterineContractions(UA, input_type, Fs, alpha, UC_iden_wlen, UC_avg_wlen, Tachysystolic_th, plotflag, varargin)
%
% [UC, UC_onsets, UC_counts, UC_counts_avg, Tachysystolic] = UterineContractions(UA, input_type, Fs, alpha, UC_iden_wlen, UC_avg_wlen, Tac... |
961680d641c3a6d15b722d29ef97ecf8d1d6df3025837b9d0460d8e34048aed0 | MATLAB | 4,501 | 169 | clear
p = params_2DAA;
fpath = fullfile(p.processed_data_dir,'allData.mat');
load(fpath,'evs','tis','bvs','traces')
[cols,alpha] = chooseColors;
speed_control = 0;
saveFigs = 1;
this_ses = 7;
%%
[av_trials_all, err_trials_all, trans_data_all, trans_data_err_all, err_trials_full_all, trans_data_all_dr, tone_idx] = ...... |
301bf922ee0889b07c5f5f70dd55611a04dd3f06644f87351eadf56498c24c3b | MATLAB | 4,503 | 140 | function [bestParams, char, bestR2] = fitGaussianTemplates_meanPSTH(response,customOffset, plotFlag)
%% template matching gaussian fits
gaussFun = @(params,xdata) params(1) + params(2).*exp(-(((xdata-params(3)).^2)/(2*(params(4).^2))));
opts = optimset('Display','off');
%% get x and y train vals
ytrainvals = respons... |
10f1da2e1abf2ad41bebf3a8cd72dcdfd8c23bcc08a51ef7a42daea9c92d84c4 | MATLAB | 4,505 | 108 | % Script to MERGE Datasets of the Following Caterogry of Features:
% 'Raster Activity': Nerual Activity
% 'General Ensembles': Neural Ensembles Features
% 'Detailed Ensembles': Single Neural Ensembles Features
%% Intro
fprintf('\n\nGet CSV Tables from Analsysis Features.\n')
fprintf('Table_Raster_Featur... |
af2dd6ab925b4ac6292580364c1c02b2cc74f0a0b54895e749942af251ccaa5e | MATLAB | 4,509 | 144 | function [count edges mid loc] = histcn(X, varargin)
% function [count edges mid loc] = histcn(X, edge1, edge2, ..., edgeN)
%
% Purpose: compute n-dimensional histogram
%
% INPUT
% - X: is (M x N) array, represents M data points in R^N
% - edgek: are the bin vectors on dimension k, k=1...N.
% If it is a... |
3d985e2ee492b4757ba087326cfab95bca8983d5da48c222c8e5aec6af47d556 | MATLAB | 4,513 | 136 |
%{
----------------------------------------------------------------------------
First_take number of frames in each tif files
Analyzing imaging data simply
At least for the correct rate
----------------------------------------------------------------------------
%}
function Figure3e_Task_kaiseki_tokyo1_2022021... |
d66261d2691fe3f6c64a22f806126d17a57bb039a06b0ab34b7dadbfe8b48803 | MATLAB | 4,517 | 125 | function loadParams(obj, filename)
%LOADPARAMS Load parameters from file
if nargin < 2
filename = obj.configFile;
end
if ischar(filename)
filename_ = jrclust.utils.absPath(filename);
userParams = jrclust.utils.mToStruct(filename_); % raises error if not a file
elseif isstruc... |
a3b09c58d15ec309a0655c3d61ff0c6072f47989e5be4a9a18ef7c1cd29e35cc | MATLAB | 4,518 | 144 | %% Date: 03-03-2022 Programmed by: Deirdre BOLGER
% Script to isolate choosen conditions in already segmented data.
% This script should run for several datasets.
%
%**********************************************************************
%% LOAD IN ALL THE DATASETS THAT YOU WISH TO SEPARATE.
% You can select tho... |
e86f9b1468d677bac1e42ec633b1339fb89adac286cd7ef229d3de58b338dc6b | MATLAB | 4,518 | 114 | function [spikeTimes, spikeAmps, spikeSites] = mergePeaks(spikesBySite, ampsBySite, hCfg)
%MERGEPEAKS Merge duplicate peak events
nSites = numel(spikesBySite);
spikeTimes = jrclust.utils.neCell2mat(spikesBySite);
spikeAmps = jrclust.utils.neCell2mat(ampsBySite);
spikeSites = jrclust.utils.neCell2mat... |
c0dff762c882f8725ed4d0ca00460fe94d10610cc7ceb9825d5d15be411326d1 | MATLAB | 4,523 | 82 | function [fig_touch PTpegHistoCell PegTouchBypegCell]=TouchAlignByPeg(PegTouchCell,pegTimeArray2D,yhight)
%TouchAlignByPeg(PegTouchCell,pegTimeArray2D,100,30)
%Called by PegTouch,Detach
%Touch aligned By Pegs
global PTpegHistoCell ShowFig
PegTouchBypeg1=[];PegTouchBypeg2=[];PegTouchBypeg3=[];PegTouchBypeg4=[];P... |
d63be3e48e582966d2f133659c6b250b5d8e29811dcb46077600db327a0826f7 | MATLAB | 4,523 | 150 | % Sample fetal-maternal ECG generator
clc
clear;
close all;
fs = 500;
N = 10000;
dim1 = 8;
SIR = -10;
SNR = 30;
% beta = 2;
beta = 1.5; % noise color (for noisetype = 1)
w_bw = 1; % weight of baseline wander noise in the generated noise (for noisetype = 5)
w_em = 1; % weight of elect... |
8ef2097e1fb7860284494920c00bb5372e9d5be5326320111c15f5db1a491534 | MATLAB | 4,524 | 164 | % read .COORD file and plot data
% PGH Oct 2001
function lcmodelresults=readcoord(filename)
% define output structure for results
%lcmodelresults=struct('spectrumppm',0,'spectrumdata',0,'spectrumfit',0,'spectrumbasl',0,'metabconc',0,'linewidth',0,'SN',0);
%lcmodelresults.metabconc=struct('name',0,'relconc',0,'abscon... |
720d9545e29c5f552c84bacaa6795ee9102510f50aaa1ab71fd1f1553e34a182 | MATLAB | 4,527 | 116 | function V = model_ther_tIVI(param, time, t_start, k_e, Ci, Vc, tI, VI) % param: alpha0, beta, k. time > tI
alpha0 = param(1); % relative growth rate at size V0 = 1 cell
beta = param(2);
k = param(3);
M = length(Ci); % note: length of Ci defines number of administrations and total treatment duration
Ci ... |
90250525c08c72d735055dbd1f551f412291fd9637372d293f6a204e79d22b4b | MATLAB | 4,530 | 110 | % This script reproduces Figures 8 and 9 of the main article.
%%
load('SPMap_features.mat'); % Loading SP map features extracted from MNI and CHUGA
addpath('functions');
addpath('demo_data')
addpath('perturbation')
addpath(genpath('results_figures\sp_results'))
% Specify center (1=MNI,2=CHUGA)
center = 1;
... |
e8f19486613cd9b072bb54abcfc32ced99ad382dd7399e8cf04e0796d541d2b7 | MATLAB | 4,530 | 152 | function Stats = paired_ttest(Data1, Data2, StatsP)
% Calculates t-tests, p values, fdr corrected p values, and effect sizes.
% Input options:
% A) Data1 = P x S, Data2 = []: t-tests done for every S with every S. Returns
% a S x S matrix, filled only in the upper triangle. Used in
% ConfettiSpaghetti.
% B) Data1 = P x... |
a0a4458a2b51c35dc4fd0691237a11e81072c29e405559b2d791695c1fc1b2fd | MATLAB | 4,532 | 106 | function [ p, yhat, ci ] = polypredci( x, y, n, alfa, xv )
% POLYPREDCI Calculates the prediction intervals for a polynomial
% regression produced by ‘polyfit’.
%
% DESCRIPTION:
% The function takes the vector data in ‘x’ and ‘y’ arguments,
% polynomial degree ‘n’, and significance level ‘alfa’... |
8d266ef286e842b6067832d81259c0cee74a73fbcfda7faa5578c791b18c1458 | MATLAB | 4,533 | 105 | % Example end-to-end pipeline of extracting data, preprocessing,
% feature extraction and spatial perturbation. The first part of the script
% reads five minutes of MNI SEEG data that was downsampled to 200Hz due
% to file size limitations. The data is notch filtered, and the Janca
% detector [1] is used to detec... |
282535169e41a94488bdf87034a966a55753365fd5f674fbf5aa179b86f0c4cb | MATLAB | 4,536 | 112 | function Both_RLt_Pattern_3Seq_20200304
path=['C:\Users\C238\Desktop\touchcellLtRt_terashita'];
cd(path);
LS=ls;
RLtouchPoint=zeros(1,8);
RLtouchFire=zeros(1,8);
X=[];
RLtouchUnit=[];
RLtouchPointUnit=[];
for i=1:length(LS(:,1))
TrimFolder=strtrim(LS(i,:));
if ~strcmp(TrimFolder,'.') &&... |
c9d80abd78360bec26e08265d752d03518525c05e82535f5253d4bda7f7a4cb6 | MATLAB | 4,538 | 111 | %% msBatchRun2018
% Version 1.0 GE
% Updated version of the msBatchRun script originally proposed by Daniel B
% Aharoni to analyse miniscope 1p calcium imaging data on large batches of
% data.
% This version is build on top of the original package to maximize compatibility.
% It includes NormCorre for image registratio... |
07ffe6975164b1d7f88010218db293bbe11f27c71d440c836f3796554bf82849 | MATLAB | 4,540 | 110 | function [peaks, peak_indexes, peak_indexes_consensus, qrs_likelihood] = peak_det_likelihood_long_recs(data, fs, varargin)
% PEAK_DET_LIKELIHOOD_LONG_RECS - Block-wise ECG R-peak detector for long records.
%
% This function is an efficient version of peak_det_likelihood,
% designed for long ECG records. It processes th... |
66f8b22a9c936515663a88f02493d1c95876f0e947455cbf0162c30153765d31 | MATLAB | 4,540 | 163 | function varargout=shadedErrorBar(x,y,errBar,lineProps,transparent)
% function H=shadedErrorBar(x,y,errBar,lineProps,transparent)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
% Inputs
% x - vector of x values [optional, can be... |
77546239ee0dc43c4242e483054ae9cdba7515db97f0ddf0bc994ee9886f6d94 | MATLAB | 4,540 | 170 | function mnl_DisplayShiftsOfChosenBead(f2Beads,ChosenBead,Scale,Zrange_um)
%Function designed to plot the effects of chromatic aberration in each
%channel as RGB components
%Initial Set up
Bead=f2Beads(ChosenBead);
nChan=size(Bead.ChromaticAberration,2);
nplots=2+nChan;
cmap=colormap(lines(nChan));
BeadLocation=Bead.Be... |
f189760ab7757aec11b9197fe979821af9e0fa798fa25214bbc113f48fba5df6 | MATLAB | 4,540 | 99 | function [ av_trials,err_trials,tone_idx ] = collect_ae_trials_all_ses(p, traces, evs, bvs, tis, speed_control,tone_start_control)
spd_dims = 18:22; %dlc
pre_steps = 15;
post_steps = 5;
for sub = 1:p.nSubjects
% first collect all av trials and keep track of the action
% start times ... |
2f008494d235934fcda72b6cd117ea1a319f734a3427a7a8bd7dc4b743dbf3f2 | MATLAB | 4,543 | 141 | close all;clear
%addpath(genpath('..\Entropy_measures\'))
display('Calcul duree activite-silence par cellule');
prompt = {'frequence echantillonage(Herz):'};
dlg_title = 'Calcul duree activite-silence par cellule';
num_lines = [1 30];
def = {'2'};
opts.Resize='on';
opts.WindowStyle='normal';
answer = inpu... |
3678c60faffc391be69e884808a79998045d99129311464cfba403a02426a685 | MATLAB | 4,547 | 136 | function [y_smoothed, a, y_hat, y_bar] = lp_filter_kalman(y, fc, varargin)
%
% Applies lowpass filtering using a first-order Kalman Smoother.
%
% Usage:
% [y_smoothed, a, y_hat, y_bar] = lp_filter_kalman(y, fc, VarWinlen, VarWinlen1, gamma)
%
% Inputs:
% y: Vector or matrix of input data (channels x sample... |
cae90bf25b9a0cd1daeccbbd9d51d90cd624d17547412ca8c8e27f1128b12e7e | MATLAB | 4,547 | 93 | clear all
eegdir_orig = 'D:\Bori\BEDREST\RENDEZETT\Bedrest_RawEEG\'; %raw eeg data
eegdir_new = 'D:\Bori\BEDREST\RENDEZETT\Bedrest_PreEEG\EEGLocs\'; % matlab will not create this folder automatically, you need to create it manually
eegl_dir = 'D:\Bori\eeglab12_0_1_0b'; %eeglab toolbox directory
%HDBR first campai... |
21869f4d9a0ace9e1e8b8a3b2032b99eb2990169aa9208bd2e30c9a4e33dba99 | MATLAB | 4,549 | 125 | function [ind, rank] = ECGChannelRanking(x, fs)
% Ranking channels based on multiple indexes
% Reza Sameni, Copyright
% December 2008
%
L1 = size(x,1);
L2 = size(x,2);
t = (0:L2-1)/fs;
%//////////////////////////////////////////////////////////////////////////
% preprocessing
% mean removal (not really ne... |
2de1618556e477af1353ccdb318c3b34894e0ff845aa0c3ea7ef21dd2f869ef2 | MATLAB | 4,549 | 178 | function fid = import_brucker_raw(fi)
if ~exist('fi')
fi = get_subdir_regex;
end
if iscell(fi)
%ff = get_subdir_regex_files(fi,'fid$');
ff = get_subdir_regex_files(fi,'fid.raw$');
if isempty(ff)
ff = get_subdir_regex_files(fi,'fid$');
end
for kk=1:length(ff)
fid(kk) = import_brucker_raw(ff{kk});
end
return
en... |
a28c46031fb0b152a452d282796d70af8d74f720931fc395b97a8ce68773f28b | MATLAB | 4,550 | 121 | % A script for generating illustrations in the following publication:
% Sameni, R. (2017). Online filtering using piecewise smoothness priors:
% Application to normal and abnormal electrocardiogram denoising. In
% Signal Processing (Vol. 133, pp. 52–63). Elsevier BV.
% https://doi.org/10.1016/j.s... |
46124313aa39a6f6d9985dc7284cd0b5fda0d5cdd29caa96afe2a6dd6f9b7e95 | MATLAB | 4,555 | 143 | %% Date: 03-03-2022 Programmed by: Deirdre BOLGER
% Script to isolate choosen conditions in already segmented data.
% This script should run for several datasets.
%
%**********************************************************************
%% LOAD IN ALL THE DATASETS THAT YOU WISH TO SEPARATE.
% You can select tho... |
265edf70279abf954fbbb77b860e43f2d045e467531fe1898c384db8a9da3472 | MATLAB | 4,563 | 116 | function [varargout] = etaSquared2(inData1,inData2,varargin)
% -------------------------------------------------------------------------
% [eta2] = etaSquared(inData1,inData2);
% [eta2,eta2Idx] = etaSquared(inData1,inData2,'Distance','true','Smallest',10);
% -------------------------------------------------------------... |
31161855074617b1da74c3e4cc0776475d4bc8bc3e60d9cab3313294d909ccb2 | MATLAB | 4,563 | 160 | function controlfilename = createLCmodel_control_laser(metabname,l1,l2,l3,preproc_dir)
do_water_scaling=1;
doecc=0;
TEMET=0;
basis_set_file_path = '//home/romain/data/spectro/Basis_set/Laser_TE52/basis_LASER_TE52_CENIR.BASIS';
basis_set_file_path = '//home/romain/data/spectro/Basis_set/Laser_TE52/basis_LASER_TE_60_C... |
8d841939ea5eb41b0496d617ea970f59722ed893f1859111fc0e89136ec9512c | MATLAB | 4,576 | 131 | function [stat] = get_B(sref,s,par)
% GET_B Moment ratios to test for modularizations.
% STAT = GET_B(SREF,S,PAR) for reference variable SREF (1-by-sample), observable components S (component-by-sample) and
% threshold PAR.THRESH returns
%
% STAT.B moment ratios matrix
% STAT.SIG2 var... |
ec9d8a1b4f40759f5164fce470dafd9180f5748e54dcfa4b7113762fa1fce23b | MATLAB | 4,576 | 123 | function cluster_runMultiEchoGRE_eachEcho_skipMoCo(reconParsFile,iE)
% _skipMoCo version strips out all MoCo to speedup getting through ASPIRE
% pipeline for testing
load(reconParsFile)
run([RETROMOCOBOX_PATH '/addRetroMoCoBoxToPath.m']);
% run([MIRT_PATH '/setup.m']);
addpath(SPM_PATH);
% if nEco <= 10
% parpo... |
be7e32ea0f7d3cedf6bc2cc88d33a27cf378f10a694d01f5888410277310813d | MATLAB | 4,577 | 178 | function [movie_frame] = show_s2_partition(N,varargin)
%SHOW_S2_PARTITION 3D illustration of an EQ partition of S^2
%
%Syntax
% [movie_frame] = show_s2_partition(N,options);
%
%Description
% SHOW_S2_PARTITION(N) uses a 3d plot to illustrate the partition of
% the unit sphere S^2 into N regions.
%
% MOVIE_FRAME = SHOW_S... |
8aba5c43f2596ec3abdabb2e4f0e0e097952cf13d6ddc9db8d053e7c53ad533a | MATLAB | 4,585 | 149 | clear all
% this script contains code to reproduce Figure S8b-c, f-g
%% load data
% drag and drop corresponding file (S9 Data)
%% data content description
% behavior contains video energy data form the wheel (behavior.wheel) of the size 1801 frames (fs=20Hz) x 14 trials x 22
% sessions
% fUS contains... |
e0e787a4fdb9958e3ab6ee0a39ab6d00f133f0f0ff2dc6ace1444d4f8cb98366 | MATLAB | 4,586 | 133 | function crosscorrelatemaps(group1,group2,labels,hemi)
%% Compare two experiments in a layered diagram
%
% crosscorrelatemaps(group1,group2,[labels],[hemi])
%
% Input:
% group1,2: experiment ID of a single experiment file (e.g. '100140756'),
% or cell array containing multiple IDs. In the latter case the exper... |
d4de9956510abd0b55211d1291fcc49ce5c90aaf565ef8d80340a5689c51e603 | MATLAB | 4,587 | 118 | function [colorMapInterp] = customColorMapInterpBars(colorMap, colorBins, interpDir)
% Creates a custom interpolated colormap with bar-style blending.
%
% This function interpolates between two given colormaps to create a new colormap
% matrix. The interpolation can occur either uniformly ('same') or with different
% b... |
147168c9f8cf4463304a8ed0fb4ab363205b901c9cca10afcc9e4229c92e832d | MATLAB | 4,588 | 128 | function [gpfa_params gpfa_traj LL] = gpfa_engineDH(D,dims,varargin)
% GPFA_ENGINEDH A modified GPFA_ENGINE for the DataHigh program
%
% Inputs:
% D -- struct of trajectories, make sure it conforms to gpfa's format
% dims --- the dimension you choose for the number of latent variables
% emMaxIters (optional) ---... |
43a880486485d0451b569887cf3f4918d582a29871cce101baa1510b01b3e7f6 | MATLAB | 4,593 | 140 | function timeseries = spmup_extract(fmridata,graymatter,atlas,varargin)
% routine to extract timeseries data as per atlas
%
% FORMAT timeseries = spmup_extract(fmridata,graymatter,atlas)
% timeseries = spmup_extract(fmridata,graymatter,atlas,LowPass,FreqSampling)
%
% INPUT fmridata file name of the fMRI time se... |
4b3bf8be24d93f8c75a40914c2df4a23946f1bdde9b4ed6a13eeb021c8a62d2d | MATLAB | 4,593 | 109 | function table_name = spmup_BIDS_QCtables(subjects, type)
% takes a subjects structure and create a table.tsv of QC metrics along
% with plotting the data
%
% FORMAT table_name = spmup_BIDS_QCtables(subjects, type)
%
% INPUT - subjects is a structure saved by run_spmup_bids
% it is saved on disk as spmup_subje... |
e4fd1e7ce5c2aa3968a89c43dd1b2bdaf944b4c4295dacdd4fe3479e181b5edd | MATLAB | 4,596 | 108 | function save_trans_results(app)
[int_idxs,~] = listdlg('PromptString',{'Please select intervals ',...
'to be plotted/saved.',''},...
'SelectionMode','multiple','ListString',app.popup_int_spect.Items);
[form_idxs,~] = listdlg('PromptString',{'Please select fileformat ',...
''},...
'SelectionMode','mul... |
2ede57422f09695583871bab3256f856af216c985969008e329ed402d59a2078 | MATLAB | 4,598 | 127 | clear
clc
on_window = 40:50;
sus_window = 100:130;
%%
% Needs to be in D:\Data\IR data Shira_May_14_2022
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save... |
525277d01572270b7f352e4bad9868883aca520a85267bee8886c836ef69d3f4 | MATLAB | 4,598 | 146 | function [nCIJtree CIJtree mdeg globalcosteffmax costmax E]=threshold_omst_gce_wu(CIJ,flag)
% threshold_omst_gce_w Optimizing the formula GE-C via orthogonal MSTs.
%
% [nCIJtree CIJtree mdeg degree vector cost ]=threshold_omst_gce_wu(CIJ)
%
% This function thresholds the connectivity matrix by absolute weight... |
90c64c9f2f525fc6b1af67895bf3544000b1c0fd36342301bb75f9e3409bdcda | MATLAB | 4,599 | 149 | function [specReturn,sig_struct] = CalcPermSpec(ersp,time_vec,calc_lims,freqs,cfg)
valid_height = find(~isnan(squeeze(ersp(:,10,100))));
ersp = ersp(valid_height,:,:);
zero_ind = find((time_vec <= calc_lims(1)) | (time_vec >= calc_lims(2)));
ersp_tmp = ersp;
ersp_tmp(:,:,zero_ind) = 0;
%get observed values
[h,... |
f709e3233525b208aa47f1d0f479ef29a705d6af4c2b83b5282d08387cd66771 | MATLAB | 4,602 | 135 | clear
clc
erias = ["AC", "PL", "IL", "DP", "TT"];
cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\figure1_stats\sides')
load("all_psth_T_with_sides.mat")
%% pool ACd ACv, 6a 6b
change_position_name = T.position;
AC_names = find(contains(change_position_name, 'ACA'));
change_position_name(find(contai... |
2fa9b0b3a254a9d1f9a163883cab785a6c842b918fe2101409b94dbdcd243593 | MATLAB | 4,603 | 127 | % Purpose: Convert fsaverage6 SNR maps to .mat matrices, avg over sessions
% and within networks
% Inputs: LH and RH step2 .shape.gii output, individual parc output
% (matched)
% Outputs: subject-avg SNR .mat, .csv file containing network-avg SNR for each subject
%
% Note: This requires the use of the gifti package (pa... |
85f597f74a5f9b67d64129cda6d148037857c205b71085f14ec1fa4c79702e8a | MATLAB | 4,603 | 97 | % This MATLAB code appears to perform several data processing tasks related to a persistence index for a set of neural recordings. Here's a breakdown of what each section of the code does:
%
% File Selection
% The user is prompted to select one or more .mat files containing neural recordings data. The uigetfile functi... |
c3dad38684f47164b8112534dac139fb50865c96900f14dc6a182bf1f7687372 | MATLAB | 4,604 | 108 | function beh = extractBeh(varargin)
%%Extract processed data from multiple recordings into single structure
%
% [beh] = extractBeh() - load from files, will be prompted to select
% [beh] = extractBeh(fPath, fName) - load from specified files
% [beh] = extractBeh(beh) - to add to existing structure
% [beh] = extra... |
c243a2b2bc4aee7b16c8c760f63ff4e9c7a5a4c95d711dc24e6119b02104a1af | MATLAB | 4,606 | 117 | function all_data = calculate_shuffle_ramse_ir(all_data)
%calculate new correct fit
windows = {40:50, 65:125, 140:150}; %windows for calculating the response time - on, sustaneid and off
%%
% Needs to be in D:\Data\IR data Shira_May_14_2022
% all_data = all_data.all_data;
cells = fieldnames(all_data);
for ... |
e71d8ba238dd03a28fa9ce27c11acdaf2a1928b401256c3424c56d3f264931e7 | MATLAB | 4,613 | 121 | function [output]=compute_gamma(segment,fs,p1,n2)
% compute_gamma - Detects preceding gamma activity in a spike segment.
%
% Syntax:
% [output] = compute_gamma(segment, fs, p1, n2)
%
% Inputs:
% segment: 2-second [30-100] Hz filtered spike segment with the spike peak at
% the center. The spike s... |
bb7c9937f74d67929b291719fa439310c39269d77b8000d35f43312ec7734b6f | MATLAB | 4,614 | 94 | function save_regression_res(app)
[int_idxs,~] = listdlg('PromptString',{'Please select intervals ',...
'to be plotted/saved.',''},...
'SelectionMode','multiple','ListString',app.popup_int_stepwise.Items);
[form_idxs,~] = listdlg('PromptString',{'Please select fileformat ',...
''},...
'SelectionMode',... |
9796c23f256aa49e4ac58955c685cb788187a31b2bdbb9c158560b0afa7fb4db | MATLAB | 4,616 | 140 | function [outlying_volumes,outlying_voxels] = spmup_voxel_outliers(varargin)
%
% this function is similar to 3dToutcount
% http://afni.nimh.nih.gov/pub/dist/doc/program_help/3dToutcount.html
% Note that it requires the statistics toolbox (nansum, icdf are called)
%
% FORMAT [outlying_volumes,outlying_voxels] = spmup_ou... |
99650c50ad76910e74aaa89c78fb7d474f5e7c83c3963d1ec93b6bc5c5afc409 | MATLAB | 4,618 | 99 | function SpikeRhythm
%21sÚÉBreakPointðu¢Ägp·é
close all;
clear all;
cd('C:\Users\kit\Desktop\WR_LVdata');
% dpath = uigetdir('C:\Users\kit\Desktop\WR LVdata');
[fname2,dpath] = uigetfile('*');%ÅÌt@Cðwè
cd C:\Users\kit\Desktop\CheetahData
Spath=uigetdir;
eval(['fnameEV=''',Spath,'\E... |
bd7a22717bc73aac2cb74bd3beec815dd55c0f912e6f55a1dcde282f918eaa0a | MATLAB | 4,621 | 141 | % clear
% organize_tracking_data()
% organize_nidaq_data()
%clear
%p = params_2DAA;
%organize_miniscope_data(p)
clear
p = params_2DAA;
%% load nidaq data
fpath = fullfile(p.rootDir,'results','behavior','full','evs_and_tis');
load(fpath)
ev_len = cellfun(@(x) size(x,2),evs);
%% load tracking data
fpath = fullfile(p.r... |
c59efaa945695cf7e8ea5d2f122a0d3888ceb23ba9ea3518c8afa93059794dd3 | MATLAB | 4,623 | 150 | function previewFilesToStack(dirPath)
% convert a directory of preview images into single stack
%
% function previewFilesToStack(dirPath)
%
% * Purpose
% Running BakingTray with a valid directory defined in hBT.logPreviewImageDataToDir
% will save preview images to mat files in this directory. These are named according... |
c60d41691a1577945f7eb86d7a5a680184f1df2551ff4cc80c8a1eac5ffc672e | MATLAB | 4,631 | 105 | % Script to create markers based on the OptiTrack for the right index
% finger abduction task in MEG. Trigger is when finger returns to
% initial position (i.e. end of finger abduction)
% For this, we need the MEG data and the OT data
% Zelekha Seedat
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
74771ac8d46084034587e6cd81e76886dcc14668d345b2a38fd0f4117bfd1c79 | MATLAB | 4,635 | 108 | function save_trans_results(app)
[int_idxs,~] = listdlg('PromptString',{'Please select intervals ',...
'to be plotted/saved.',''},...
'SelectionMode','multiple','ListString',app.popup_int_spect.Items);
[form_idxs,~] = listdlg('PromptString',{'Please select fileformat ',...
''},...
'SelectionMode','mul... |
6cc6083f09066b2983a22d64fca262c0136d21f5f47523b980d671c1ffd7b87e | MATLAB | 4,636 | 158 | function wc_polytrode_figs(input,show_figs)
%Plot
%if input is a string, load times from that file
%otherwise is a cell(USER_DATA) from wave_clus_gui
if ~exist('show_figs','var')
show_figs = false;
end
if ~exist('input','var') || isempty(input)
h_figs = get(0,'children');
h_fig = findobj(h_figs,'tag','wave_... |
ac3cd4f844f85d19d2726f77259f7ca93a9ed4fbf55ec3309713add23db66a65 | MATLAB | 4,636 | 142 | function [meanPerf, semPerf, pCorrect, cond, meanError, semError, confMatrix] = do_cvDA(dataStruct, options)
%% input args
% datastruct is of format: struct(icondition).data(time,unit,trial)
if ~exist('options','var'), options=struct; end
if ~isfield(options,'kfold'), ... |
fbb538adf857f2de669ad6f0d21014d7466e9908275b1060f8ac0c2c399634fe | MATLAB | 4,639 | 94 | function save_regression_res(app)
[int_idxs,~] = listdlg('PromptString',{'Please select intervals ',...
'to be plotted/saved.',''},...
'SelectionMode','multiple','ListString',app.popup_int_stepwise.Items);
[form_idxs,~] = listdlg('PromptString',{'Please select fileformat ',...
''},...
'SelectionMode',... |
d33ac78d1a788cc1ccd03c42c560fe8f0b434ea559fa8ed8559b0712f52480e1 | MATLAB | 4,642 | 147 | clear all;
close all; clc;
matrixBefore_no = ([0 0 0 1 0 0 1 1 1 0
0 0 0 0 0 1 1 1 0 1
0 0 1 0 1 0 0 1 1 0
0 1 0 0 0 1 1 1 1 0
0 0 0 1 1 1 0 1 1 0
0 0 0 0 0 0 0 0 0 1
0 1 0 0 1 0 1 1 1 1
0 0 1 1 0 1 0 1 0 0
0 0 0 1 0 1 1 0 0 0
0 0 0 0 0 0 0 0 1 0
0 0 1 0 1 0 1 1 1 1
0 0 1 1 1 1 0 1 0 1
0 0 0 0 0 0 1 0 0... |
14349bb1d3d324e82d301738a5125817db52fff063fd45518acc37444a55515c | MATLAB | 4,655 | 155 | function controlfilename = createLCmodel_control(metabname,l1,l2,l3,preproc_dir)
nb=1;
do_water_scaling=1
phantome=0;
basis_set_file_path = '/home/romain/data/spectro/Basis_set/MEGA5_inv/MEGA5_inv.BASIS';
%basis_set_file_path = '/home/romain/data/spectro/Basis_set/MEGA5_inv_no_gln/MEGA5.BASIS';
%basis_set_file_path ... |
d1d013f570da8e606606a7f483a54a20cde8e0701030cbe18a738abea07dea32 | MATLAB | 4,657 | 93 | function [S,f,varS,C,Serr]=mtspectrumsegc(data,win,params,segave)
% Multi-taper segmented spectrum for a univariate continuous process
%
% Usage:
%
% [S,f,varS,C,Serr]=mtspectrumsegc(data,win,params,segave)
% Input:
% Note units have to be consistent. See chronux.m for more information.
% data (single channel) -... |
b7c70aeeec5423523600c2a8d4b91fa830a2f28ac562e0ffc6d162b87ed631d1 | MATLAB | 4,658 | 168 | %% Function to plot raster
% input
% R: Raster Matrix Cells x Frames
% varargin default:
% fs=1 Sampling Frequency
% stepy=2; Step between rows Yticks
% indexes=1:C; Sort
% ColocateIndx=[];Indexes of Colocalized Neurons
% Neurons:Colocalized
% Output... |
0ab19dc2c738aa8be159ba4e2fbb40dbafd1fb85eba381d5eba2e5943bb99a00 | MATLAB | 4,662 | 168 | classdef sphericalFit<ellipsoidalFit
%A class for executing and managing fits to a sphere
properties (Dependent)
radius
end
methods %Accessors
function val=get.radius(obj)
val=obj.aDiam/2;
end
function obj=set.radius(obj,val)
... |
10960467cdf949f4c8c986f6f376bbe30ca6a5f850191f32cde3c911a2921b57 | MATLAB | 4,665 | 114 | function [ensemble_eeg, synch_eeg, trigger_time_sec, time_vec, varargout] = trigger_synch(eeg, fs, onset_time, varargin)
%
% [ensemble_eeg, synch_eeg, trigger_time_sec, time_vec] = trigger_synch(eeg, fs, onset_time)
% [ensemble_eeg, synch_eeg, trigger_time_sec, time_vec, synch_emg] = trigger_synch(eeg, fs, onset_time,... |
d251964750e8f2eb4af8903b56dfd5a34262388c9a0e1fdca21e0d05625f3c33 | MATLAB | 4,672 | 126 | %Author: Tatjana Schmitt, 2019-2023
clearvars
path_to_matlab_file ='directory to whole tonotopy';
load(path_to_matlab_file)
%% set parameter
save_flag = true;
frequency_hub = 1; % select the frequency you want to extract/analyse (1,2,3,4,5 for 4,8,16,32,64 kHz respectively)
se = strel('disk', 1); ... |
2a88321301acbe149c02928052a21c9cbc3128dcb4bd990043a12c8a349f4bb4 | MATLAB | 4,674 | 128 | close all;
clear;
clc;
resultfname = 'testSpectralAnalysis01.txt';
% parameters
subject = {'Dog_1', 'Dog_2', 'Dog_3', 'Dog_4', 'Dog_5', 'Patient_1', 'Patient_2'};
f0 = 60; % powerline frequency Hz
Q = 30; % notch filter Q-factor
wlen = [0.5 1.0 3.0 5.0 10.0]; % energy window lengths in seconds
drop = 200; % remove dat... |
72b2c4197bc2ecdbc61e79f18c1564f46d82c7522430266c3eafef628d4cca5a | MATLAB | 4,674 | 127 | clc
clear
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
%in case of selcting only one file
if ~iscell(datafile)
datafile = {datafile};
end
%%
%change... |
369865155664d64a2979c8ed75e9b8a8533e603ed2df1c747bd9b805514eaaa7 | MATLAB | 4,679 | 127 | function Plot_Brains_COMS_MSPoI_PAPERFIG(FS,A,FRP,nodes_name,coord_node,atlas,options)
atlas_name = options.atlas{atlas};
for n = 1:length(nodes_name)
Name = nodes_name(n);
NodeName(n,:) = string(Name);
end
% TO save data
cd '/netapp/vol7_u923/SEME/SEME_dc/pipeline/MSCD/Results_MSC... |
83adf4a6ce16fcb9e9b81218e04ad3cd091afe6b69dc3bcc9d88bde9892714b9 | MATLAB | 4,681 | 160 | function st = nufft_table_init(om, Nd, Jd, Kd, n_shift, Ld, varargin)
%function st = nufft_table_init(om, Nd, Jd, Kd, n_shift, Ld, ...)
%|
%| Initialize structure for d-dimension NUFFT using table-based interpolator,
%| This should be called only by nufft_init with its 'table' argument!
%| (So this m-file belongs in t... |
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