sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4cd88fed5aa799b796bf4441d48bd700ceb6dfbbb27782a310cbc03e2657c6fa | MATLAB | 6,987 | 217 | function img = helix(cg, ig, proj, short, varargin)
%|function img = helix(cg, ig, proj, varargin)
%|
%| A single slice rebinning method for cone-beam tomography data
%| collected with a helical source trajectory
%|
%| in
%| cg ct_geom()
%| ig image_geom()
%| proj [ns nt na] cone-beam projection views (line inte... |
0fe94c9bf5f7e0e7b2117ee9277744c31619ed9f34d79d34ccfb52240a78cf16 | MATLAB | 6,990 | 179 | %% Graph refinement pipeline:
% Required input:
% vessel_image: 3D numerical array
% vessel_mask: 3D logical array (vessel voxel = true)
% Running precedure:
% 1. Generate training data
% Set opt.annotation_on_Q = true. GUI for annotation will pop up
% automatically along the way of refinement. Click the "Sa... |
bc9266ab25f49423b78495eb086d551adadd62113b6675741e63a5ee89b3192e | MATLAB | 6,990 | 185 | function SBJ10c_grp_ANOVA_plot_ts_gROIcomb(SBJs,proc_id,stat_id,an_id,...
atlas_id,roi_id,...%gm_thresh,z_thresh,plot_nsig,...
plt_id,save_fig,fig_vis,fig_ftype)
% Plots smANOVA w2 time series by ROI groupings
% gROI version: one plot; subplots p... |
54284b4188f334e863ffead8a41a3dd10aac2f778d737e27744fc01743fadc08 | MATLAB | 6,996 | 162 | function [significantVarWei,significantVarMax,pValWei,pValMax] = long_weighted_cluster_perm_stats(subjects,task_distance,task_RT,category,tail,if_save,numPermutations,method)
%WEIGHTED_CLUSTER_PERM_STATS Perform weighted cluster permutation stats to calculate the
%significance of the timepoints in the distance-to-hyper... |
69ec656231f10b46113714f3b86a1e2026a49ff778058fe6b39e077fe69c1263 | MATLAB | 6,996 | 146 | % % smooth the registration videos form template_matching (ImageJ toolbox)
% % 1) the user has to selecto the registered videos for smoothing
% % 2) if the data given by template_matching (Results) has the same name
% % that the registered video the program automatically find it if not
% % the user has to ch... |
01b67fb6fbf361ccccd16af21a30a906454524aa378fbfce546ae334681c3155 | MATLAB | 7,009 | 253 | function varargout=shadedErrorBar(x,y,errBar,varargin)
% generate continuous error bar area around a line plot
%
% function H=shadedErrorBar(x,y,errBar, ...)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
%
% Inputs (required)
% x - vec... |
a05ee9c7149c8000c3b46460d7a5e1ef60ac9dab5dbce3bbda28d4df84d24a8e | MATLAB | 7,009 | 180 | % Make allTrialsAllCellsMatrix
% sessions = dir('/Volumes/groups/giocomo/export/data/Projects/JohnKei_NPH3/fkm_analysis/fr_corr_matrices/*.mat');
sessions = dir('/Users/KeiMasuda/Desktop/fkm_analysis/fr_corr_matrices_noSpeedFilter/*.mat');
filter = 'mec';
sessions = filterSessions(sessions, filter);
% load(sprin... |
5a583351f95984bc034ff39b04cb5ef2002d35a62461fa34732ee6bd70e2c3a0 | MATLAB | 7,010 | 210 | % Present the population analysis vs shuffle in voilin graphs
% The variable shown is the ratio between time and distance cells numbers on
% the time fixed trials and the ration between distance and time cells
% numbers on the fixed distance trials.
%
% Red line = median of the shuffled distribution
% Black line... |
7e7e832b39b335e9a82008d8ee9d1d3c7abb14e5045e5feb30e75b1570174b3f | MATLAB | 7,010 | 242 | %% mri_example.m
%|
%| A small example illustrating iterative reconstruction for MRI
%| from a few nonuniform k-space samples using edge-preserving regularization.
%| (This example does not include field inhomogeneity or relaxation.)
%|
%| More generally, this scripe shows how to go from nonuniform samples
%| in the fr... |
08367cac600f4dcece1bc176103956426e006cf697c48f74fe29e4afee6c5417 | MATLAB | 7,011 | 163 | function SBJ10c_conn_win(SBJ, method, proc_id, an_id, roi_id, atlas_id, twin, tlags, stepsize, Nbins, chansel)
%% Set up paths
if exist('/home/knight/hoycw/','dir');root_dir='/home/knight/hoycw/';ft_dir=[root_dir 'Apps/fieldtrip/'];
else; root_dir='/Volumes/hoycw_clust/';ft_dir='/Users/colinhoy/Code/Apps/fieldtrip/';en... |
4374d36835a4a0bdd1c92141b73b35a96f24629c7f4a542fa7979fd3c7f65b4c | MATLAB | 7,012 | 254 | function varargout=shadedErrorBar(x,y,errBar,varargin)
% generate continuous error bar area around a line plot
%
% function H=shadedErrorBar(x,y,errBar, ...)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
%
% Inputs (required)
% x - vec... |
c5ec01f21b9ff1183ff0df0b1306cdf45754ee68420a9697f389e777abd28282 | MATLAB | 7,019 | 166 | function plot_TEI_ver2(Animal)
Color_Prop = {rgb('OrangeRed'),rgb('Black')};
[All_Projections] = SaveAllProjections(Animal,'OnDecoder');
dp = All_Projections.passive;
%dp = dp(:,:,[1:14 16:end]);
da = All_Projections.active;
%da = da(:,:,[1:14 16:end]);
[timesteps,stimnb,sessionnb] = size(da);
if strcmp(Animal,'Pelard... |
f99ac4554a78c7856d13fb3589f048d416983f6809085c4efcbb75ded5aec9df | MATLAB | 7,019 | 170 | function cleanFontConfigCache
% Delete the fontconfig cache that GStreamer uses for text rendering.
%
% Call this if drawing text suddenly takes a very long time. A damaged or
% oversized fontconfig cache is the usual reason; it is rebuilt on the next
% text render, so the first text after this call is slow again and e... |
2b6bba63f8fd5cfa99fea02590817fd8283050e1133954d4813e338cb7ccc133 | MATLAB | 7,023 | 276 | function [T, reuse] = nufft_gram(ob, W, reuse)
%function [T, reuse] = nufft_gram(ob, W, reuse)
% construct Toeplitz matrix object T = G'WG for a Gnufft object
% in
% ob Fatrix a [M,np] Gnufft object
% W [M,M] W = diag_sp(wi) (often simply "1" or [])
% reuse struct stuff from the last call that can be reused
% out
%... |
3193534315261e0348f2570ff1ed165e08c3047595a82e5b62b197b4d65950c3 | MATLAB | 7,024 | 203 | function [cSkeleton cWidths] = cleanSkeleton(skeleton, widths, wormSegSize)
%CLEANSKELETON Clean an 8-connected skeleton by removing any overlap and
%interpolating any missing points.
%
% [CSKELETON] = CLEANSKELETON(SKELETON)
%
% Note: the worm's skeleton is still rough. Therefore, index lengths, as
% oppos... |
a5abd3bd60fb70dcb8f12235eda964637c809bbdf3488d17e7a524b70658cb03 | MATLAB | 7,024 | 187 | function rsa_rnn_eeg_subject_by_subject(subjects,with_stats)
%RSA_RNN_EEG_SUBJECT_BY_SUBJECT Compute and plots the RSA between RNN and EEG with stats, if desired.
%RSA is computed by correlating each of the subject-specific EEG RDMs with
%the RNN RDM and averaging over.
%
%Input: subjects' ID (e.g., 1:13), add stats (... |
8da172028fc6b613e6ecd4d93c9b1a5965932c2f3fbfc15f8eda1ade1d7af421 | MATLAB | 7,028 | 168 | clc; clear all; close all;
% data info
dataLoc = 'C:\Users\kmfo8\Dropbox\Rutgers\Firestein Lab\MEA papers -- addl experiments\EXP for BDNF + glu\Glutamate cell death, BDNF treatment\';
replNames = {'Replicate 1'; 'Replicate 2'; 'Replicate 3'};
% filter parameters
filSig = [4, 1];
numSig = 3;
numAng = 30;
... |
7691e8b6ec45eaf1890f0c3fdcecd3f0746c3aceaf56fb0d80d99c9c3f425679 | MATLAB | 7,031 | 143 | function [time, task] = extract_design_info(logs_dir, subj_id)
% _
% Extract design information from RDM experiment in fMRI
%
% Version History:
% - RB, 2017: written
% - RB, 26/10/18: converted into function
% - RB, 17/12/18: added catch trial info
% - RB, 20/02/19: modified for two days
% - JS, 16/04/19: rewritt... |
b4cb58f5a453f805b123691c1beffde91b921ea79039ba8294993594b7a3b974 | MATLAB | 7,031 | 214 | %% Frequency of single cell oscillations - All sessions
clear all
close all
dbeh_path='C:\Users\xscogno\MATLAB\Flavio2\Waves\Tracking data\';
rec_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_spikes='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_sorting='C:\Users\xscogno\MATLAB\... |
f8731bfb09a2682813359e1aa08b08abcc750c76d4d599a95fe97820a34b43bf | MATLAB | 7,031 | 190 | function [DCM,PEB,M,HCM] = spm_dcm_peb_fit(GCM,M,field)
% Bayesian group inversion using empirical Bayes
% FORMAT [DCM,PEB,M] = spm_dcm_peb_fit(DCM,M,field)
%
% DCM - {N [x M]} structure array of DCMs from N subjects
% ------------------------------------------------------------
% DCM{i}.M.pE - prior expectation... |
20879f1e8406ab1b86bfd2d25219d0f387e72df17749bbe676e7406848c4b397 | MATLAB | 7,040 | 197 | function [DCM] = spm_dcm_average(P,name,nocond,graphics)
% Produce an aggregate DCM model using Bayesian FFX averaging
% FORMAT [DCM] = spm_dcm_average(P,name,nocond,graphics)
%
% P - character/cell array of DCM filenames
% name - name of DCM output file (will be prefixed by 'DCM_avg_')
% nocond - op... |
3282ffda12584a910856c90d9cacb9190466e8a62bc4e278886238bccb431bae | MATLAB | 7,045 | 276 | function [xs, info] = pwls_admm1(x, A, W, yi, C, varargin)
%|function [xs, info] = pwls_admm1(x, A, W, yi, C, [options])
%|
%| penalized weighted least squares (PWLS)
%| with convex non-quadratic regularization,
%| cost(x) = (y-Ax)'W(y-Ax)/2 + reg * pot(C * x)
%| minimized via ADMM algorithm with one splits, ala "spl... |
384f3c632dd4c4a0a531127ed42f93f84081a4011db876a6c9e00faf489beadf | MATLAB | 7,046 | 141 | function stats_replay_bias = diff_cumulative_replay_stats(epoch)
% epoch = 'sleep' or 'rest'
%path = 'X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\Chapter 2\Raw_replay_analysis';
%path = 'X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\Chapter 2\Controls\All_controls';
path ='X:\BendorLab\Drobo\Lab Members\M... |
3164793bdc4adc065e8eaa70f13ef1accbf5544d27ef1aac3b5d00c2508339d3 | MATLAB | 7,051 | 149 | function loop_str = fun_analysis_get_loops_in_graph_by_link_label(graph_str, link_label, distance_type)
% fun_analysis_get_loops_in_graph finds loops for the specified link in the
% graph and compute loop length
% Input:
% graph_str: structure generated by fun_analysis_get_connectivity_graph
% link_label: num... |
65449bdfbde42df12c552969c175c761bd2780b800afa08fc9b5c821da98b31c | MATLAB | 7,055 | 246 | function Q = spm_MDP_VB_game(MDP)
% auxiliary plotting routine for spm_MDP_VB - multiple trials
% FORMAT Q = spm_MDP_VB_game(MDP)
%
% MDP.P(M,T) - probability of emitting action 1,...,M at time 1,...,T
% MDP.X - conditional expectations over hidden states
% MDP.R - conditional expectations over... |
605a91f2ce5c4b06e4834057eff7e21998542a9d4a04bd4f1ee4a58dd04c8981 | MATLAB | 7,060 | 221 | function out = spm_shoot_warp(job)
% Register images with template
% format spm_shoot_warp(job)
% Fields of job:
% job.images{1} first set of images (eg rc1*.nii)
% job.images{2} second set of images (eg rc2*.nii)
% etc
% job.templates template files
% Other settings are defined in spm_shoot_defaults.m
... |
78985d3a99a1c34a923df5730181f38ff336c2fba9d62264e4af8dfcd2962b97 | MATLAB | 7,063 | 186 | function [r,d1,d2] = ripleyk(pos,spk,binsize,padding)
%% >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> DESCRIPTION
% FUNCTION short desc.
% long description
%
% USAGE:
% [out] = template(in) process with default settings
%
% [out] = template(in,optional1) process using optional argum... |
53a97c6de06cd240544b449d6f6a2c90cab5f2704d6ff15edd641458c709088a | MATLAB | 7,065 | 231 | function nvr_load_hdr(fileparams)
% Load recorded header file information on the control panel for spike
% analysis
global nvr
global Spoint
%Spoint = 8; %(number dots of each sample curve) "spike_template_changed"
Spoint = 12; %(number dots of each sample curve) "spike_template_changed"
usr = get(findob... |
9834052c4cc511468e0b257a66182f48f8f8c7317903ea22fdd868b34f4dc647 | MATLAB | 7,077 | 272 | %% Figure S14
clear
ft_defaults
%% Subjects
% ID 18 missing because of LP at 50Hz
subjects = {'OSL13', 'OSL14', 'OSL17', 'OSL21', 'OSL24', 'OSL26', 'OSL27', 'OSL28', ...
'OSL29', 'OSL30', 'OSL31', 'OSL32', 'OSL34', 'OSL35', 'OSL36', 'OSL38', 'OSL39', 'OSL40'};
%% Paths
path_in = '/Volumes/IMPECOG/iEEG_Data... |
26d1a230e958f9fa7abb7b85c542cc9e5c44642f367df285070090ceb09a95d4 | MATLAB | 7,081 | 168 | function Results=displayAndSaveResults(hbType,OutputHb,selCond,currRep,outputName,NrOfCond,NrOfSelCh,weightName, isMultiTrial, showResults,MultiTrialApproach, allDec,Results,trial,channel )
% input
% hbType: 3D or 4D matrix containing BCIOutput results [bVal bVal tVal rVal] for all channels and conditions
% Output... |
c7509fee999afaba3634683f31f8e15aa1a6fb5c90f3528dc00ace9f9527c141 | MATLAB | 7,083 | 158 | %% ----------------------------------------- %%
% Note Jan 28 2020:
%
% Current version of code does FOV correction, grid correction & MIP/AIP
% generation, surface finding & profiling, mosacing & blending
%
% Suggested parallelization method: one slice per thread
%
% volume stitching is currently in another code
%
% ... |
b19a72e22bfc7fe31df25ec424e49000c97657cfdee1f8bb861db3a32f24a845 | MATLAB | 7,086 | 138 | function MakeStimEvents2_tSC(sessionpath,ppch,varargin)
%MAKESTIMEVENTS2 Create stimulus events structure.
% MAKESTIMEVENTS2_tSC(SESSIONPATH) constructs and saves stimulus events
% structure ('StimEvents') for the stimulation session in the folder
% SESSIONPATH. Stimulation pulses are detected as TTLs recor... |
52f53caa401754e820c979f0868e46bbaad856251cd08c0f956347fdf6d0cc47 | MATLAB | 7,093 | 158 | function [] = fun_interactROIs(hObject, handles, ROI_idx, mouse_pos, mouse_mode)
%FUN_INTERACTROIS Summary of this function goes here
% Function used to interactively draw ROIs
cc_ROIs = fun_HSVcolors(5, 1);
line_width = 2;
switch mouse_mode
case 'Down'
init_pos = mouse_pos... |
668940995ade523d477f7dcf2aaf7ea645505d3e6c3814d1e5d04f90f1839584 | MATLAB | 7,120 | 210 | %% Curve fitting
clear all;
datapath = strcat('C:\Users\jryang\Desktop\Data\191029phantom\20\depth14\');
% add subfunctions for the script
addpath('C:\Users\jryang\Desktop\Data\code\');
tic
% get the directory of all image tiles
cd(datapath);
%% load data
load(strcat('avg.mat'));
opts = optimset('Display','off','T... |
560eb09a60979323695abb06589d954da36dddccb0be1fdcd714d7242ddfd885 | MATLAB | 7,129 | 206 | function LeGUI_Win_Build(varargin)
% -a adds files to compiled executable, -N clears matlab path except for main matlab folder, -p adds toolbox
% cfgroot is the root location of archived files (-a flag) for deployed code (mfilename('fullpath') works in a deployed environment)
Version = '1.2';
if nargin
Vers... |
34df3a49b9ea02379fab01b9401be01ef423064c675a903d81b37aef4e895ec1 | MATLAB | 7,132 | 186 | function[]=BaSiC_shading_and_ref_stitch_PTSD(id, datapath, depth, thickness)
% add path of functions
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addpath('/projectnb/npbssmic/s/Matlab_code/PSOCT_code');
addpath('/projectnb/npbssmic/s/Matlab_code... |
3c2c2b85b41d4791448f51152067284989a4bd0b96f517e71957da8935922859 | MATLAB | 7,132 | 284 | function [xs, info] = ir_pwls_os_lalm(x, Ab, yi, R, varargin)
%function [xs, info] = ir_pwls_os_lalm(x, Ab, yi, R, [options])
%|
%| (This is now superceded by new method in ir_pwls_os_rlalm.m)
%|
%| penalized weighted least squares estimation / image reconstruction
%| using linearized augmented lagrangian method with
... |
0091736e6fe40d395efc559a4ed8217dce38b705b5f6f6960005b6e248d72b9a | MATLAB | 7,135 | 150 | % Main code for replay quantification, analysis and visualisation
% By Marta Huelin Gorriz and Masahiro Takigawa 2023
computer = [];
data_type = 'main';
replay_control = [];
multievents = [];
%% REPLAY TIMES AND QUANTIFICATION
extract_replay_time_periods(computer,[],data_type,[]);
extract_replay_plotting(computer,da... |
0c5eecb267d9ce719ed9af25f3f1584fb9cbb9f9601a6ef12d6b9bcbe1a957f8 | MATLAB | 7,137 | 184 | function [assignment,cost] = munkres(costMat)
% MUNKRES Munkres (Hungarian) Algorithm for Linear Assignment Problem.
%
% [ASSIGN,COST] = munkres(COSTMAT) returns the optimal column indices,
% ASSIGN assigned to each row and the minimum COST based on the assignment
% problem represented by the COSTMAT, where the... |
64a118f336dffcc0d831c63703c436c12e67d3b35b3b157f3259980b0dd90ffd | MATLAB | 7,137 | 251 | function [A_lh, A_rh]=cortical_label_adf(subject, p_val)
% Computes the area of the different cortical labels
% and compare them to the normal range
% Uses p_value to detect the abnormal areas
% Uses the lh/rh.parc.txt files
%
%
% cortical_labeling_afd_txt.m
%
% Original Author: Laurence Wastiaux
% CVS Revision Info... |
3c9a63cea119dc1c01d4405553de4e7f38b21ddee0aa4c0e9c9f5663a2ebd1c0 | MATLAB | 7,147 | 185 | function [seg_spktimes,seg_spikes,current]= Spike_detector1(bigdata,chans,thresh,filt_para,current,sr,pre_seg,post_seg1)
% do not consider spikes in 1st pre-seg, and last post_seg period.
global nvr
src=sr;
%adjust data to column, to make sure each column holds one
%channel data
[m,n]=size(bigdata);
if n>m
... |
a7e88351e848fc42e5b7f6015e92a2ec18e9d423ea8571ee4aadf70ee07c3f2f | MATLAB | 7,147 | 280 | function h=grPlot(V,E,kind,vkind,ekind,sa)
% Function h=grPlot(V,E,kind,vkind,ekind,sa)
% draw the plot of the graph (digraph).
% Input parameters:
% V(n,2) or (n,3) - the coordinates of vertexes
% (1st column - x, 2nd - y) and, maybe, 3rd - the weights;
% n - number of vertexes.
% If V(n,2), we write l... |
23e1bec7cafd2c0973911f23e3f60382907ced60fc1fabe66ed81244b71f155f | MATLAB | 7,148 | 184 | function answer = bIO(pinNr, status, parEv)
% Use this function for simulating the IO hardware (e.g. pecking-keys or
% feeder) with your keyboard. This is useful for programming or debugging
% an experiment in the office and not at the setup itself. To use this
% feature, edit the function myHardwareSetup.m and set opt... |
7f510fcff101e3fb0a837e563537d4b497a3438e3bdbcc5ecf3d1c01832ffb3a | MATLAB | 7,148 | 184 | function SBJ08a_HFA_actv(SBJ,proc_id,an_id,actv_win)
% Calculates high frequency activity, computes cluster-based statistics, and plots the results
% clear all; %close all;
% Set up paths
addpath('/home/knight/hoycw/PRJ_Error/scripts/');
addpath('/home/knight/hoycw/PRJ_Error/scripts/utils/');
addpath('/home/knight/hoyc... |
d6502987aedbb6d253178f2de25a7bc5eac6baf0b50144226d315249467cbd01 | MATLAB | 7,151 | 277 | function [C, rj] = penalty2_design(type, varargin)
%|function [C, rj] = penalty2_design(type, ['leak'|'tight'], wang, ang, mask)
%|
%| Design the penalty matrix "C" (and penalty coefficients "rj")
%| for a quadratic penalty R(x) = 1/2 x' C * C * x with:
%| 1st-order differences and a 2nd-order neighborhood (8 neighbor... |
d13d5d9c11ff8fa81533f990a067d8a707bd999968b93d315cdf6535f407a7a9 | MATLAB | 7,157 | 288 | function varargout=notBoxPlot_dotcolor(y,x,jitter,style,dotcolor)
% notBoxPlot - Doesn't plot box plots!
%
% function notBoxPlot(y,x,jitter,style)
%
%
% Purpose
% An alternative to a box plot, where the focus is on showing raw
% data. Plots columns of y as different groups located at points
% along the x axis defined b... |
80999eb841d5932f507ed8e9c89d806f01bf16be2e8a1a594ffa99178a4de45e | MATLAB | 7,163 | 232 | function handles = c_plot_scatter3(varargin)
% c_plot_scatter3 - 3D scatterplot
% Various improvements over built-in scatter3, including plotting of 3D spheres rather than 2D markers,
% and various size, color, scaling, and labeling options.
%
% Syntax:
% handles = c_plot_scatter3(Name,Value,...)
%
% (Name,Value) in... |
47590da16c191a16b051af9a587892a03706a0a87fd0ca162f91e5aa2c364e5b | MATLAB | 7,167 | 153 | function Compute_Avalanches_MEG_DK(path_file_MI, path_file_Rest, subject_IDs, db_path, labels_DK, freq_band_def, z_thresh, fs, min_size_aval)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Compute Avalanches x dataset - 20 subj. - Sess. 4 - MEG - Desikan-Killiany
% Authors: MCC
... |
8808641e66ec74f31b5310ebe350267525900a54905afeeccd251efe6bac88da | MATLAB | 7,168 | 179 | %% Graph refinement pipeline:
% Required input:
% vessel_image: 3D numerical array
% vessel_mask: 3D logical array (vessel voxel = true)
% Running precedure:
% 1. Generate training data
% Set opt.annotation_on_Q = true. GUI for annotation will pop up
% automatically along the way of refinement. Click ... |
f61af80a17219ec16aafd1ac75329617a97a4ff88fd0f402dee48e30f4e960fd | MATLAB | 7,168 | 233 | % ir_mri_al_p2_example.m
% Example of MRI SENSE reconstruction from under-sampled k-space data
% using the AL-P2 algorithm from Mar. 2011 T-MI paper.
% Sathish Ramani, circa 2011
% 2013-07-14, modified by Jeff Fessler
%% Test image - Shepp-Logan Phantom
if ~isvar('img')
N = 256;
if exist('phantom') % matlab with ima... |
d32f50bd39a773137b058e3712a18b57d5f7ef4ab1b14a6fc3a6ce57d723ca76 | MATLAB | 7,173 | 156 | function [ ev_ho_x, ev_ho_y, lawn_limit_line] = geteventhorizon022119(background, outer_boundary_mask, lawn_limit_line, pixpermm, th)
%GETEVENTHORIZON_ROUGH.M this function takes in the background image (not
%blurred) and extracts the convex hull -- the limits of the lawn boundary,
%not taking into consideration all of... |
eae9202d6e549705caf2786a6b44acf1408e0674d2386720ab5a26b33b879e16 | MATLAB | 7,179 | 138 | function [meal, mealDelayed, mealAnnouncement] = mealSetup(data,model,modelParameters,environment)
% function mealSetup(data,model,modelParameters,environment)
% Generates the vector containing the CHO intake events to be used to
% simulate the physiological model.
%
% Inputs:
% - data: a timetable which conta... |
be96f012c744c14a2d36ed3f66d8a6a83782f9af5da9fefe3fccc92fe4e1f9aa | MATLAB | 7,181 | 244 | function [ img ] = xilin_cluster_single(w,ind_img,no_cluster)
% w = distance matrix (sparse)
% ind_img = image where each value is indexed into matrix (image where voxels are numbered in some order and correspond to elements in w)
% w(4,7) is similarity between voxel #4 and voxel #7
% no_cluster = number of cluster... |
b63d947047ac1eda2d31c2ba6fbbd7796bb70bc1794a268d7739e76abe6ea953 | MATLAB | 7,185 | 228 |
function moduleOutput= xilin_raw()
moduleOutput.my_ncut=@my_ncut;
moduleOutput.discretisation=@discretisation;
moduleOutput.discretisationEigenVectorData=@discretisationEigenVectorData;
return
function [Eigenvectors,Eigenvalues, vbar] = my_ncut(W,nbEigenValues,dataNcut)
% function [Eigenvectors,Eigenv... |
ea30cc88a9d142fca81a2a2f52f0fa6fa87dedb40cedd51a2120df9a1fc460a7 | MATLAB | 7,185 | 295 | classdef c_FigureRecorder < handle
%FigureRecorder Summary of this class goes here
% Detailed explanation goes here
properties(SetAccess=protected)
size = [];
outputDir;
filename;
doOverwriteExisting;
doVerbose;
method;
frameRate;
isInProgress = false;
vidObj;
outputPath;
printPrefix = 'Fig... |
64b9349e2efeb5fa52e94d70e5b21f2c7ef74778430e162fe4576d24b879d2f9 | MATLAB | 7,194 | 201 | %% Script to create output for Supp Fig. 2 - analysis of walking speed during outbound path
% Andrea Castegnaro, UCL, 2022 andrea.castegnaro@ucl.ac.uk
% Display walking speed for different groups during the outbound path.
% Calculate difference between group means. For details of speed
% calculation please refer to Cal... |
12a6d364348c47577dc9c9f13d0d9ebdafe2576f61510be50cadcac399ac5ba1 | MATLAB | 7,195 | 263 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%
%% 4-level multiresulution nonrigid image registration with New penalty
%% Conjugate gradient with Newton's first step was used
%% Cubic B-spline bases are used for both image and deformation models
%%
%% Copyright April 2008, Se Yo... |
c00a764cd51eab6b6eae155ef025086b1d0b2789752c935d47082a4d08daa085 | MATLAB | 7,203 | 259 | %% Figure 2e
% this script rungs additional analysis required for the plots of figure
% 2e.
%%
clear
ft_defaults
%% - SUBJECTS - %%
subjects = {'OSL24'};
%% - PATH SETTINGS - %%
path_in = '/Volumes/IMPECOG/iEEG_Data_JW/SingleSubjects';
path_out = '/Users/Janweber 1/Desktop/PhD_HelfrichLab/Project_1_Prediction... |
12d733384acd62ebe6dacac12bed4d018bfc63368a84693904c73b1df8f0b025 | MATLAB | 7,206 | 209 | function [ztc, zf, zsh] = ztrans(tc, dim, tp)
%ZTRANS Perform z-transformation (setting STD to 1 and MEAN to 0).
% Z = ZTRANS(S) transforms the signal S to a scaled version with MEAN of
% 0 and STD of 1. This is a typical application in functional magnetic
% resonance imaging (fMRI) to account for scanner hardwa... |
34a25f5abf6701463e2b1e7deb8c26d4a3a40a9a2a9a7dd52ede4f5a6c41b7ac | MATLAB | 7,209 | 205 | function LeGUI_Linux_Build(varargin)
% -a adds files to compiled executable, -N clears matlab path except for main matlab folder, -p adds toolbox
% cfgroot is the root location of archived files (-a flag) for deployed code (mfilename('fullpath') works in a deployed environment)
Version = '1.2';
if nargin
Ve... |
d231735cd2d385c8ad82c50d5666e78504e665c9487185079c38087474ee5244 | MATLAB | 7,213 | 154 | function Compute_Avalanches_EEG_DK(path_file_MI, path_file_Rest, subject_IDs, db_path, labels_DK, freq_band_def, z_thresh, fs, min_size_aval)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Compute Avalanches x dataset - 20 subj. - Sess. 4 - EEG - Desikan-Killiany
% Authors: MCC
... |
57c8701bf3aa8b23f2f4143def954fca71764b7d31da74e8b53a7a6e53c5fc89 | MATLAB | 7,215 | 187 | function a = nextsweep(d,varargin);
% nextsweep - reads the next sweep (datastream method)
% a = nextsweep(d,varargin) takes an datastrm object and
% starttime / endtime (within sweep) as optional 2. and 3. parameter
%
% optional 4. and further parameters:
% 'hold' for holding file position (don't move to next ... |
c60d8610a2a3499685cc4812dd6189c33b431ce309b9025aeec423705022a165 | MATLAB | 7,215 | 262 |
%% gf_vs_m
clear all
close all
clc
nrmz=10000;
sp=1;
%% load: mouse N
disp('mn')
cd('/data/Technion_analysis/Amygdala/Amy_FC_final')
load('all_neurons_cluster_ave.mat', 'geneid_all');
load(['amyFC_neurons_sc_celltypes_muhammad_25-Nov' ...
'-2021.mat'],'c','data','sample');
gabahex = loadCellFile_turbo('GABA-hexa.... |
4abef26610b34e227cb115c4665218f960fd710c1a104439cafacbb4bb5ef303 | MATLAB | 7,218 | 201 | function obj=runMarkerInduction(obj, method)
if (~exist('method'))
method = 'C';
end
try
% Mapping between quantities Willshaw (2006) and Johannes' framework and
%
% RAi - obj.RGCEphA
% RBi - obj.RGCEphB
% TAj - obj.SCephrinA
% TBj - obj.SCephrinB
% Sij -... |
9e27990af47184ccb854afa48c8da33f17172a8e2d050230e5faacd4eaedc840 | MATLAB | 7,219 | 173 | %% to plot the meanfit and mean spectra
% borrowed from the function osp_plotMeansSpec.m of Osprey 2.4.0
% Oeltzschner, G., Zöllner, H. J., Hui, S. C., Mikkelsen, M., Saleh, M. G.,
% Tapper, S., & Edden, R. A. (2020). Osprey: Open-source processing, reconstruction & estimation
% of magnetic resonance spectroscopy... |
095b3e9f6ba077b6a416fc71bbd3d8db90920f875e19f6c9e4b447728fe04241 | MATLAB | 7,224 | 192 | function partialcorr_eeg_rnn_rt(conditions,with_stats,with_rcnn)
%PARTIALCORR_EEG_RNN_RT Calculate the partial correlations of EEG-RT and
%RNN-RT.
%
%Input: conditions ('artificial','natural' or 'both'), with/without stats
%(1/0), with or without average rCNN unique variance (1/0)
%
%Output: results from the GLM analys... |
df53fbfb63b68df6dd514837815ecb0354e15923fb0fdb8db4f2a3528c7812e8 | MATLAB | 7,226 | 211 | function [varargout] = pm_merge_regions_m(opm,N,P,rima,gd)
%
% Merges regions as defined in connectogram to minimise
% total costfunction (sum of phase-differences across
% region borders).
% FORMAT: pm = pm_merge_regions_m(pm,N,P,rima)
% or
% FORMAT: [pm,rima] = pm_merge_regions_m(pm,N,P,rima);
%
% Input:
% pm ... |
f4a0e15fc60b830b3306e004d86ccec4dd7011bdc3b94d2c26ca38eef7365b18 | MATLAB | 7,230 | 221 | function fm = pm_make_fieldmap(P,flags)
% This function creates an unwrapped fieldmap (in Hz) from either
% a single or double echo complex image volume. In the case of a
% "single-echo" image, that will have been created by the vendor
% sequence out of two acquisitions with different echo times.
% The complex image... |
4907ae4351c8624f545d4828f7e3ebd1a068a0cea8494e5b5c0ca1933fff9b8f | MATLAB | 7,236 | 303 | function ob = fatrix2_block(blocks, varargin)
%function ob = fatrix2_block(blocks, options)
%|
%| Construct fatrix2_block object, a meta-object composed of fatrix2 blocks,
%| such as block_diag(A_1, A_2, ..., A_M)
%| See fatrix2_block_test.m for example usage.
%|
%| in
%| blocks {cell} cell array of the blocks
%|
%| o... |
e5522a71619b9a6e0406ff6d7e303da911a2e4a9151080561c631bb8e3fe3f1c | MATLAB | 7,236 | 242 | % Retina -> SC
function [hasEctopic,fig] = virtualInjectionEctopicExperiment(obj,RGCnt, RGCdv, ...
injectionRadius, plotFlag)
fig = [];
if(~exist('plotFlag'))
plotFlag = 1;
end
if(~exist('injectionRadius'))
% Check if injection site ... |
c2623bc9d86fe436d0d9f56c0f491d88406fee110bfa8825ae0e9586b0779f2a | MATLAB | 7,238 | 168 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% generating lipofuscin statistics based on previous ROI definition
% CTE8572 only first three slice is useful. others have bad focus and
% surface, probably stage malfunction during imaging
% NC6047 start from slice3
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');... |
9845297ccf706d7bd9c556aa0fdac6672fb9d24be8f0de28f9e8ab80dc1430fe | MATLAB | 7,240 | 178 | %%%%%% CHOOSE INPUT FILE
clear all
[filename,pathname] = uigetfile({'*_ALL_CELLS.mat';'*_ALL_CELLS.MAT'},'Open file with fluorescence time series', 'MultiSelect', 'off');
filenameALL_CELLS=fullfile(pathname,filename);
cut=strfind(filenameALL_CELLS,'_ALL_CELLS.mat');
filenameARTIFACTS=[filenameALL_CELLS(1:cut-1) '_ART... |
c6035aa88c9afcd5a47da0475cb0a186e61a37991ebcff34255e8f23f5f2c855 | MATLAB | 7,240 | 192 | function[]=BaSiC_shading_and_ori_stitch(id,P2path, datapath, ntiles, depth, thickness)
% add path of functions
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addpath('/projectnb/npbssmic/s/Matlab_code/PSOCT_code');
addpath('/projectnb/npbssmic/s/M... |
5d8af62d158c7c7aeb9558ec67643426493518aed31ae0888cdfd68cb917e58a | MATLAB | 7,244 | 171 | % This driver estimates the flux of each line in silico using the objective
% function unweighted thermodynamic constraint based modeling for fluxes
% (unWeightedTCBMflux) to compare the fold change in order to cluster them
%
% results saved at:
% ~/results/changeAll.csv
% ~/results/changeAll.fig
% ~/results/changeAll.... |
2ea8b13d73b4b718139abf062f353f4abba1b50aaac3e69acbccfe06e5b3732d | MATLAB | 7,255 | 171 | function [] = genDataSingleTrialInference(nParallel,nEXP,nTrials,Contrasts,RhoN,RhoD,p)
% genDataSingleTrialInference Generates synthetic data from the pairwise Ratio of Gaussians model using model fits to previously recorded data to measure single-trial normalization.
% Produces large matrices comparing the mean squa... |
687c0436fee06f3d9ba6c0143fc81d792fa04c03f14219cb85cab6fab5763fe9 | MATLAB | 7,257 | 167 | % This operator is only used for FAE smoothing and for the smoothing
% of T2 distributions
function Dstr = getSpatialDerivOperator3D_wt_Masking(Filter, sz, Mask_ROI, Resol)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% input: 3-D size of T2_Scale spectrum - nrows x ncols x nT2
% ... |
acafc6ebbec59363440a5e7a96ef6b3e755471f2507b12ce2fd72dcaed0b4445 | MATLAB | 7,257 | 210 | function LeGUI_Mac_Build(varargin)
% -a adds files to compiled executable, -N clears matlab path except for main matlab folder, -p adds toolbox
% cfgroot is the root location of archived files (-a flag) for deployed code (mfilename('fullpath') works in a deployed environment)
Version = '1.2';
if nargin
Vers... |
61da0e5f92c4f3931e829f899c897788e044ec723e30b5e3ffe44e12607e9bc6 | MATLAB | 7,258 | 235 | function args = aspire_pair(sg, ig, varargin)
%|function args = aspire_pair(sg, ig, [options])
%| see ASPIRE users guide under tech. reports on web page for details
%|
%| options
%| 'scale' default: 0 - transmission scaling
%| 'strip_width' default: from sg.strip_width
%| or, if empty, then 0 (line integrals)
%| '... |
8b785d2e063a2274dfa48269c16a6e67d235f45af29684f76295b5d280a3bf4b | MATLAB | 7,260 | 166 |
% description: script which will access the null distributions and observed
% data across subjects and regions then plot.
% note: as it stands, script can only be run for chance analysis for lure+
% condition NC-->HC (non-normalized direc) during retrievial and HC--> NC during encoding.
% Would need to update script ... |
e00b1f23d588f52cf36e5b88725db52fe748eb8cfef262be57c73479925816ed | MATLAB | 7,261 | 221 | clear all
close all
dbeh_path='C:\Users\xscogno\MATLAB\Flavio2\Waves\Tracking data\';
rec_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_spikes='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
% clusters=53;
clusters=10;
mice_n... |
5ff7e47f8801bc20fc5cf40ee3c3886e8e432527905394cf75bb39ba804f4e80 | MATLAB | 7,265 | 241 | function [C,h,Ph,F,Fa,Fc] = spm_sp_reml(YY,X,Q,N,hE)
% ReML estimation of covariance components from y*y' (for sparse patterns)
% FORMAT [C,h,Ph,F,Fa,Fc] = spm_sp_reml(YY,X,Q,N);
%
% YY - (m x m) sample covariance matrix Y*Y' {Y = (m x N) data matrix}
% X - (m x p) design matrix
% Q - {1 x q} components Q.q = eig... |
3c2d928e76eefc293430a203758a0098833fb893edd17ab2f74d2557c78abce2 | MATLAB | 7,270 | 191 | function[]=BaSiC_shading_and_ref_stitch_Ann(id,P2path, datapath, ntiles, depth, thickness,stitch)
% add path of functions
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addpath('/projectnb/npbssmic/s/Matlab_code/PSOCT_code');
addpath('/projectnb/n... |
2fc1e57c50760bf3b65aa42079e90a51a427126cc852b7eba3c9634c3a592cf1 | MATLAB | 7,280 | 138 | function [wc_spikevolts, wc_spikeiters, NtoElim] = checkalignment_wc(check_spikevolts, check_spikeiters, ...
myfiltchunk, thiselectrode, chunkN, chunksize, totaltime, rawfileloc)
NtoElim = 0;
fileInfo = datastrm(rawfileloc); % update 2021-05-21
%filter parameters
fs = 20000;
N = 4; %filter order
Wn = [... |
6d04d2151a57b5ae0a17568bddf56620fe249dd6db4cb144747c8d0bd9022db3 | MATLAB | 7,287 | 215 | function [po,pin] = spm_prep2sn(p)
% Convert the output from spm_preproc into an sn.mat file
% FORMAT [po,pin] = spm_prep2sn(p)
% p - the results of spm_preproc
%
% po - the output in a form that can be used by spm_write_sn
% pin - the inverse transform in a form that can be used by spm_write_sn
%
% The outputs are ... |
3f733bce50dbeb31a742905418b405046f034495afe9b604afa8e032abcb9b92 | MATLAB | 7,288 | 169 | % PLOT SHUFFLE DISTRIBUTIONS FOR AVERAGE THETA SEQUENCES
%MH 2020
% INPUT:
% method: either 'quadrant_ratio' or 'weighted_corr'
function plot_1stLAP_thetaseq_shuffles(method)
sessions = data_folders;
session_names = fieldnames(sessions);
PP = plotting_parameters;
f1 = figure;
yn1 = [240,220,200,180,160];
yn34 = [28... |
454b9c77020e8d98e2d7b3352a3158f49bf06513324cbc865b7d1ee1abc52631 | MATLAB | 7,288 | 221 | function [A,rows,cols,entries,rep,field,symm] = mmread(filename)
%
% function [A] = mmread(filename)
%
% function [A,rows,cols,entries,rep,field,symm] = mmread(filename)
%
% Reads the contents of the Matrix Market file 'filename'
% into the matrix 'A'. 'A' will be either sparse or full,
% depending o... |
aaaf87acee4db6cc384278d17c26ffbb71c7f2589d40bd02a8c49236cde8f141 | MATLAB | 7,295 | 233 | function [C, rj] = penalty2_nuyts(type, wang, ang, mask)
%|function [C, rj] = penalty2_nuyts(type, wang, ang, mask)
%|
%| Design the penalty matrix "C" (and penalty coefficients "rj")
%| for a quadratic penalty R(x) = 1/2 x' C * C * x with:
%| 1st-order differences and a 2nd-order neighborhood (8 neighbors).
%| Desig... |
93130d753e568274a73ebc7f7148cfcbeafa05a9e49611b150d7e1bcb7005a0d | MATLAB | 7,327 | 162 | function [] = fun_exportFigures(handles, figureName)
%FUN_EXPORTFIGURES Summary of this function goes here
% Detailed explanation goes here
switch figureName
case 'G'
if isfield(handles, 'imageG')
image_stack = handles.imageG;
% Gmin = str2double(get(handles.Edit_Gmi... |
e60f560f3adff26322cba663f736711b85c7aea7498e46ea04b8d68bfacb1094 | MATLAB | 7,333 | 240 | % function plot_power_RawVsLog(SBJ,proc_id,an_id)
% Filter, extract power, plot distribution of power values
% Set up paths
if exist('/home/knight/hoycw/','dir');root_dir='/home/knight/hoycw/';ft_dir=[root_dir 'Apps/fieldtrip/'];
else root_dir='/Volumes/hoycw_clust/';ft_dir='/Users/colinhoy/Code/Apps/fieldtrip/';end
a... |
eb631cc13e73b3130423c721c75d4f6fde36d4e01955f043b3bfa0769b288ea3 | MATLAB | 7,335 | 304 | function xs = tpl_inc(x, Gb, yi, bi, ri, R, niter, pixmax, curv, ...
subout, enhance, gi, denom, relax0, chat)
%function xs = tpl_inc(x, Gb, yi, bi, ri, R, niter, pixmax, curv, ...
% subout, enhance, gi, denom, relax0, chat)
%
% TRIOT: incremental SPS algorithm for transmission Poisson problem
% (ordered subsets se... |
0b793251b9a11e6a4ca5622d80343c28da0e0dfbb2791b749321d1ef8b674974 | MATLAB | 7,338 | 299 | function [opt, extra] = vararg_pair(opt, varargs, varargin)
%function [opt, extra] = vararg_pair(opt, varargs, [options])
%|
%| Process name / value pairs, replacing the "default" field values
%| of the opt structure with the user-specified values.
%| This allows flexible argument order and "named arguments" somewhat ... |
2e1d04f07b20c63ac9e0966cddf567046a9bd3163a77e24da893ba77f6504ad5 | MATLAB | 7,342 | 167 | function SBJ07b_ERP_plot_SR_stats(SBJ,conditions,an_id_s,an_id_r,plt_id,save_fig,fig_vis)
% Plots ERPs computed in SBJ07a_ERP_stats
% clear all; %close all;
fig_filetype = 'png';
if ischar(save_fig); save_fig = str2num(save_fig); end
%% Data Preparation
% Set up paths
addpath('/home/knight/hoycw/PRJ_Stroop/scripts/')... |
98665046f65e41ba1fedd04f7f66323a28485ef14636dd48bfc72e251d59f867 | MATLAB | 7,346 | 145 | %% Camera tracking
% The OTBR Toolbox can track an animal with Point Grey cameras: the beak of
% a pigeon pecking at a screen in a Skinner box, or the position of an
% animal in an arena. The tracker finds a black object, a white object
% (for example a reflector) or both in every camera frame and writes its
% coordina... |
db699269deb98be23482de8ee05fb6986dd08de34cfdb0bfeba2c0d603083aeb | MATLAB | 7,348 | 113 |
% Analyze the animals with transitions from fixed-time to fixed-distance
% and vice versa, to trace changes in encoding
% BK41
[ByPValue,ByFit,ByCellType,TrialType]= AnalyzePopulation('AnalyzedData_Onset+5sec_250msBinsFirst20Runs.mat',0);
BK41(1,1)=(sum(ByCellType.DistanceCells(TrialType==6))/sum(ByCellType.Tim... |
b9c1c8ac1347b9f3a08b20e39a98e6af8d5a98e29a6d247b836545963a9065d3 | MATLAB | 7,357 | 153 | % CIRCULAR PHASE SHUFFLE
% Disrupts phase domain. Circular shuffle of each position bin (each row),
% keeping the relationship between spikes probability and position, but altering position-phase relationship for each position bin.
% INPUT -
% num_shuffles: integer
function [phase_bin_shuffles,phase_shuffle] = ... |
1acf9265f0b0500cad6272fb76a0312a27142603959aa654679345c362876ba5 | MATLAB | 7,366 | 199 | function [cond1a,cond2a,cond3a,cond4a] = get_power_subj_elecs(subj_list,exp_type,reg, ref, baseline,lock)
% Function output: condition specific spectrogram power from every elec pooled
% from all subjs for a given region
cd('/mnt/yassamri/iEEG/sandra/group_data/groupdata_spectrograms/LM_reref/tuning_correct_onset')
% ... |
664976b4cdbf83b34c9f426e82e41880dc9d8808a3f7bb28a740b7f4a1cb405c | MATLAB | 7,378 | 163 | function analysis = analyzeResults(cgm, glucose, insulinBolus, correctionBolus, insulinBasal, CHO, hypotreatments, mealAnnouncements, vo2, data,environment)
% function analyzeResults(cgm, glucose, insulinBolus, correctionBolus, insulinBasal, CHO, hypotreatments,data,environment)
% Analyses the simulated glucose traces... |
b3e18dc20e6b7dd0f0ccb1bf5830e48fed6805173ced0d95f0e060468d8657be | MATLAB | 7,390 | 187 | function make_figure2(plotVariables, options)
%this used to be known as make_figure5, but has been renamed to align with
%the figure naming in the final submission
glmFlag = 'all_regressors';
% subject list
subjectList = [16 18:21, 24, 26, 27, 28, 29, 31, 33, 34, 35, 42, 43, 47, 50, 51, 52, 54, 55, 57, 58]; %32 ... |
b574d4bb97cdc8f01a2686fbcab2485b613e8449c526cfb0676a2f7aee3644c6 | MATLAB | 7,404 | 274 | %% Figure S6f
% this script rungs additional analysis required for the plots of figure
% S6f
%%
clear
ft_defaults
%% Subjects
% ID 18 missing because of LP at 50Hz
subjects = {'OSL13', 'OSL14', 'OSL17', 'OSL21', 'OSL24', 'OSL26', 'OSL27', 'OSL28', ...
'OSL29', 'OSL30', 'OSL31', 'OSL32', 'OSL34', 'OSL35', 'OSL3... |
d42a72d88f7ed4881c69b872c01725e7937e32f4d3d856814a9cae0c8fb64c85 | MATLAB | 7,423 | 170 | function test_fitting_speed(co, cross, s_seg, z_seg, datapath)
% Fitting code for the data shared by Hui.
% I: volume data for 1 tile
% s_seg: slice number
% Z_seg: tile number
% datapath: datapath for original data
% zf: focus depth matrix, X*Y dimension
I=sqrt(co.^2+cross.^2);
cd(datapath);
for lim=[1e-3, 1e-4, 1e-5... |
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