sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4770752a5d1b4077c3c4e77b68e2ca2b4e70404efd7cb8390537e71276cc620f | MATLAB | 6,294 | 224 | function ob = Gtomo2_wtmex(arg1, varargin)
%function ob = Gtomo2_wtmex(sg, ig, options)
%function ob = Gtomo2_wtmex(file, options)
%function ob = Gtomo2_wtmex(arg_pairs, options)
%|
%| Generate a 2D tomographic system model based on aspire's wtfmex() routine.
%|
%| in
%| sg strum sino_geom()
%| ig strum image_geom()... |
94596e30003cb07ebcf0cd36e8bcae5bb26cee4681d05ae3721ee964710cebcb | MATLAB | 6,297 | 148 | load('ProcessedData_220328.mat');
fig6.fig = figure('Name', 'Figure 6: Motor Activity is Modulated by Task Conditions');
set(fig6.fig, 'Units', 'centimeters', 'Position', [40 15 8.8 6.5], 'NumberTitle', 'off');
xActive = .04;
xGrasp = .215;
xCarry = .39;
fig6.active(1) = axes('Position', [xActive .05 .15 .225]); fig... |
c7ba4a4e2d789db25df1ede304bde49b845e10e14a28c3f555eb7e684306a5dd | MATLAB | 6,301 | 92 | % LAP THETA SEQUENCE SIGNIFICANCE
%MH 2020
% Compares average theta sequence scores to shuffles. Takes the 95% for each shuffle (pre spike train circ shuffle, position circ shuffle & time
% bin suffle), and takes the maximum value between the three of them. A theta sequence will be significant if it's higher than the m... |
cb673cf012f447bc0c8341e3d0d1b8a7ee9ee4121fd5cb9e12965c756b68dce7 | MATLAB | 6,304 | 230 | function [img sino] = fbp_helix_gh(cg, ig, proj, varargin)
%|function [img sino] = fbp_helix_gh(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 project... |
c8d94e7c120b9689fe54d07434d6f89d7959c1ce3af07fab0b425bf9620f6e39 | MATLAB | 6,311 | 226 | % mri_phase_denoise_sim1.m
% simulation using mri_phase_denoise()
if ~isvar('xtrue'), printm 'xtrue'
if 0
% first form "true" smooth phase map
f.pmap = './brain,pmap,o2,l2b-6.fld';
if exist(f.pmap, 'file')
xtrue = fld_read(f.pmap);
else
xtrue = mri_phase_denoise(yi, 'pl', 1, 'order', 2, 'l2b', -6);
im(xtrue... |
f47f3423088b79feed1f97f5bfc9ca4d31f4f1e3e36dbda8af2bf546b52541c1 | MATLAB | 6,311 | 290 | % Gtomo2_table_test
% Test the Gtomo2_table obect by comparing with exact methods
% Jeff Fessler
% paces and adjoint
if ~isvar('At2'), printm 'test Gtomo2_table and its adjoint'
sgt = sino_geom('par', 'nb', 20, 'na', 10);
igt = image_geom('nx', 7, 'ny', 12, 'dx', 1);
igt.mask = igt.circ > 0;
table = {'square/strip... |
d1c78c86d0c8e43c64469d2aa99be53aa622407c1d238ed4df42fa7127d0120d | MATLAB | 6,313 | 159 | function [outANI,outANIFreq,outANIFilterFreqs] = IPEMCalcANI (varargin)
% Usage:
% [outANI,outANIFreq,outANIFilterFreqs] = ...
% IPEMCalcANI (inSignal,inSampleFreq,inAuditoryModelPath,...
% inPlotFlag,inDownsamplingFactor,...
% inNumOfChannels,inFirstCBU,inCBUStep)
%
% Des... |
ca9e1e4d50611871e5493faa41b3b1ade96efbd8574ba538d5d26b96430b67c4 | MATLAB | 6,314 | 134 | function [patch_Vrange, patch_Irange, numtoelim] = spikewave_wc(thesespikes, ...
fileloc,chunknum,filtereddata,chunksize,spikeiter,spikeelectrode,totalT, ...
fs,numChannels)
%rename inputs
filtchunk = filtereddata;
chunkN = chunknum;
rawfileloc = fileloc;
chunkspikes = thesespikes;
fileInfo = datast... |
dc9078659ef13541b40d9bb801a98f2436ccc90aab688cdb4d4657cf962b3a4f | MATLAB | 6,317 | 241 | function proj = cuboid_proj(cg, params, varargin)
%function proj = cuboid_proj(cg, params, varargin)
%|
%| Compute set of 2d line-integral projection views of cuboids.
%| Works for both parallel-beam and cone-beam geometry.
%|
%| in
%| cg ct_geom()
%| params [ne 9] cuboid parameters:
%| [x_center y_center z_cente... |
a63d0956b0870fcecb01b71f2887f90c555975f20d6207d887b380fbfdfcff6c | MATLAB | 6,331 | 171 | function [fly] = Tracking2(Inside,vertices,readframe,bgvid,bgvid2,frames,fileNum,regions)
fly = cell(1,regions);maxVals = cell(1,regions);minVals = cell(1,regions);
for k = 1:regions
fly{k}.ang = zeros(1,frames);
maxVals{k} = ceil(max(vertices{k}));
minVals{k} = floor(min(vertices{k}));
end
se = st... |
5b7dfd8d9dff5562d80ad564db3ba4f075f26bb202273cbe94380c2e711b198b | MATLAB | 6,333 | 290 | function ob = Gdft(varargin)
%function ob = Gdft([args])
%| Construct Gdft object that computes samples of the DFT of a signal
%| with dimensions [(N)]. This is useful for "under-sampled" MRI.
%|
%| options (at least one of first two must be provided):
%| 'mask' logical [(N)] image-domain mask, usually: true(nx,ny)
%... |
ada23c4d4fc0f51ac0491b7c43b1e18f5928fa238df0206e19a69aea327f6062 | MATLAB | 6,333 | 198 | function s = num2str(x, f)
%NUM2STR Convert numbers to a string.
% T = NUM2STR(X) converts the matrix X into a string representation T
% with about 4 digits and an exponent if required. This is useful for
% labeling plots with the TITLE, XLABEL, YLABEL, and TEXT commands.
%
% T = NUM2STR(X,N) converts the matr... |
3084d8b28bd614d6c6617e6538d28ae4ed37683be1e4a24dcf36bbd9c17b6371 | MATLAB | 6,337 | 144 | function [significantVarWei,significantVarMax,pValWei,pValMax] = weighted_cluster_perm_stats(subjects,medianRT,mean_distances,true_correlation,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... |
1b44857c561e2badd9a363ff15bc02a30e9dd0da463907c4a38d92ea6d38407f | MATLAB | 6,341 | 97 | % AVERAGE THETA SEQUENCE SIGNIFICANCE
%MH 2020
% Compares average theta sequence scores to shuffles. Takes the 95% for each shuffle (pre spike train circ shuffle, position circ shuffle & time
% bin suffle), and takes the maximum value between the three of them. A theta sequence will be significant if it's higher than t... |
a0237305fffde937c435481e0e8d1a78d299063b2f46d1fd5dde9a0793b2615a | MATLAB | 6,346 | 136 | function [input_graph, varargout] = fun_graph_pruning_internal_short_hairs(input_graph, th_hair_length, internal_offset)
% fun_graph_pruning removes all the short links that connected to
% internal endpoints from the graph
% Input:
% input_graph: structure, generated by fun_skeleton_to_graph
% th_hair_length: all ... |
cff3c19058fc1bae543a3012d8a210679e7f2febce20c33854ec096877045bb6 | MATLAB | 6,346 | 171 | % Script to plot Supplementary Figure 4, calculate statistics reported, and
% save data to Excel spreadsheets that are then imported into the Source
% Data file.
% Kit Longden 2023.
addpath ../Shared_functions/
% Plotting parameters
% -------------------
hf40 = figure(40);
set(hf40,'color','w','position',[200 200 800... |
18e2cf630a27fc84959629d0e33120c7c7d4c125be5056d21783bd0ef19003bf | MATLAB | 6,349 | 140 | function create_configs(varargin)
% Expects to be run in the working directory
% Remove old config files
system('rm -f config*.m');
system('rm -f yeti_config.sh');
% guarantees folders exist
system('mkdir -p job_logs');
system('mkdir -p results');
system('mkdir -p yeti_logs');
parser =... |
0850b00e87995a5ad3fc9b9114cf051d3fcf8a9349dec592c7bb5148f21dd2c7 | MATLAB | 6,350 | 248 | % mri_example_epi_b0.m
% Example of B0 field-corrected MR reconstruction using EPI trajectory.
% WORK IN PROGRESS!
% Copyright 2010-03-10, Jeff Fessler, University of Michigan
if ~isvar('xtrue'), printm 'xtrue'
f.dir_xtrue = [path_find_dir('mri') '/../data/mri/'];
f.xtrue = [f.dir_xtrue 'brainweb_t1.jpg'];
xtrue = ... |
642bc053c648851520328fc9a0075d525ddf8c5b3761a446c603696126cf0c54 | MATLAB | 6,350 | 182 | function [new_states]=corrected_states(states)
x = states;
%Remove zeros.
s=find(x==0);
y =isempty(s);
if y==1
states=x;
else
x(x==0) = NaN;
v = fillmissing(x,'previous');
states = fillmissing(v,'next');
end
wake_states=states;
% c0=states(1); %first state.
%Find wake bouts < 4s... |
09240d4505150e2655878e8573f8340e597ed51a6f0885a13267904b9488fc85 | MATLAB | 6,358 | 142 | %% Thomas_Yang_et al, 2023 @Nuo Li lab
%% Fig. 6b norm. FR, early delay SC photoinhibition, ALM record
clear all
close all
addpath('../func/')
load Figure_6_b_data
sig_selective(isnan(sig_selective))=0;
FR_pref = spk_count_yes_screen-spk_count_no_screen;
i_selective = (sig_selective(:,2)) & cellType_all(:... |
4f3fe90b5b6309e2a9fc21d796d596373867a9115ce66294755d3a1c1d77180f | MATLAB | 6,359 | 182 | %% Remove looped segments
%{
This script uses a nested struct "Data.Graph" which contains metadata about
the Graph struct. The Graph struct is created in the script SegtoGraph.m.
TODO:
- Determine meaning of A_idx_end{1,1}
- Determine logic of last two steps (new edges and new nodes)
%}
%% Prep environment & load the ... |
ce22536e8c92d67cc96a9c0db2607c375f55e08ab5ce9edc89d48dab15625d3c | MATLAB | 6,362 | 203 | function [alpha,exp_r,xp,pxp,bor] = spm_BMS (lme, Nsamp, do_plot, sampling, ecp, alpha0)
% Bayesian model selection for group studies
% FORMAT [alpha,exp_r,xp,pxp,bor] = spm_BMS (lme, Nsamp, do_plot, sampling, ecp, alpha0)
%
% INPUT:
% lme - array of log model evidences
% rows: subjects
% ... |
6b67c5d295ee3655db9fb315b44fd0c6ad0796125d27d0027b42f3efd20cc92d | MATLAB | 6,369 | 263 | function fld_write(file, data, varargin)
%function fld_write(file, data, [options])
%|
%| write data into AVS format .fld file
%| see ASPIRE user's guide (or AVS online documentation) for file format.
%|
%| todo: generalize to include 'extent' options and default
%|
%| options
%| 'check' 0|1 1: report error if file e... |
ada111b0a8a03ad27dc6393a143b321b4b49e99fe537f0a79d2d6977311b0202 | MATLAB | 6,371 | 125 | %% LFP analysis
% First, calculate_lfp_power.ipynb to generate lfp freq band csvs
load('\\oak-smb-giocomo.stanford.edu\groups\giocomo\fkmasuda\fkm_analysis\EAJ_revisions\wt_ket_sessions.mat')
[peri_ctrl, peri_ket, delta_ctrl, delta_ket] = deal([]);
[base_trace, ctrl_trace, ket_trace] = deal(NaN(length(wt_ket_sessions)... |
d038fa1323b0fdfef6e3454822f60ad9e116b667afab940ed0a95a8072a1dfba | MATLAB | 6,373 | 145 | function [turnBias,XX,YY,turnBias_baseline,turnBias_during_baseline] = ...
getKNNProbTurnIn(f_orco, s, keyNdx, xGrid, yGrid, zGrid, ratio, Thresh, K, state, genotype, plotFig)%f_orco, condNdx
% condNdx3 = zeros(size(f_orco.spk));
% condNdx3(condNdx<6) = 1;
% condNdx3(condNdx==0) = 3;% not an condition case
% ... |
e865e4bfd0621fdb4ec1cad11381e4958a16daf997016d89de0bf2a3c108fd71 | MATLAB | 6,373 | 123 | %% IR87 Processing Variables
[root_dir, app_dir] = fn_get_root_dir(); ft_dir = [app_dir 'fieldtrip/'];
if isempty(strfind(path,'fieldtrip')); addpath(ft_dir); ft_defaults; end
%--------------------------------------
% Basics
%--------------------------------------
SBJ_vars.SBJ = 'IR87';
SBJ_vars.raw_file = {'IR87_erro... |
524d9aa1ac95839f30dc822e44577944ce0485de1c17bf3c370a60d099824923 | MATLAB | 6,375 | 254 | %% mri_example_b0.m
% Example B0 field-corrected MR reconstruction for a spiral k-space trajectory.
% Copyright 2005-7-29, Jeff Fessler, University of Michigan
%% true zmap
if ~isvar('zmap'), printm 'read fieldmap'
[fmap, mask_orig] = mri_phase_denoise('test');
fmap = fmap / (2*pi*2e-3); % 2ms echo time diff.
[nx, ... |
8f709d254a1d733b4c75fcb24065fdb967cdda480fd196a40f4ab97b2644b06c | MATLAB | 6,376 | 132 | function [event_onsets, event_offsets, data_shades] = read_photodiode(data_photo_orig, min_event_length, n_shades, plot_it)
% This function takes an array of raw photodiode values and outputs event onsets and offsets
%
% NOTE: The lowest values are considered non-events. This function assumes positive values for ON... |
eb699f490efbd003e311f83438e4753bb405da442cc4e82bd9822f6b20a855b9 | MATLAB | 6,378 | 168 | %this script prepare data for the visual garding
clc;clear;close all
root='..\';
addpath(genpath([root,'NeuralCorrelateEvidenceAcc']));
%%
subdir='total';
clusterName='clusterArea_paper';
regCluster=1;
if(regCluster)
subdir=[subdir,'_',clusterName];
end
all_units=0;
rootpath='..\dataset\Mice\spike\result\';
ratepa... |
f9e91780490c7a419b30b69729a78d56e39222d04dc4dcc4f084c6245e23b8dc | MATLAB | 6,379 | 103 | % AVERAGE THETA SEQUENCE SIGNIFICANCE
%MH 2020
% Compares average theta sequence scores to shuffles. Takes the 95% for each shuffle (pre spike train circ shuffle, position circ shuffle & time
% bin suffle), and takes the maximum value between the three of them. A theta sequence will be significant if it's higher than t... |
e0208fac9dbbf1624cfb494f59347a0a5b41f782a74c31607fc219e2d0cb305f | MATLAB | 6,382 | 178 | function fn_elec_import_orig(SBJ,proc_id,view_space,reg_type,reref)
%% Convert recon pipeline elec struct to personal format
% Fix labels, select imported channels (ROI, cleaning), sort alphanumerically
% Rereference: if 1, does bipolar (no difference for ECoG)
% Goes from smallest to largest (ELEC1-ELEC2, EL... |
56528c594279620b1a06fcfc0ecbdc9ad21084ba4f288f8fe8e3361975474b33 | MATLAB | 6,383 | 163 | function out = stopRemoteKeyBuffer(h)
% Stops a keyBuffer call that runs on an experimental computer such as a
% Raspberry Pi. keyBuffer has to be started there with the option
% 'remoteStop'; otherwise it does not listen for the stop.
% The function sends the stop to all computers in h and waits up to 2 s
% for their ... |
17b6a7fb7e13e21dd690a6facc813feb1eb013ffdc31b762ab526fa88a6ba021 | MATLAB | 6,385 | 96 |
%%% FSLNets - simple network matrix estimation and applications
%%% FMRIB Analysis Group
%%% Copyright (C) 2012-2014 University of Oxford
%%% See documentation at www.fmrib.ox.ac.uk/fsl
%%% change the following paths according to your local setup
addpath /Users/wang/Documents/MATLAB/toolbox/FSLNets % ... |
826a68a21e895ff636a7f2c7e000c907d65a058c565bfa6c38f27eb8d203810e | MATLAB | 6,385 | 122 | %clc;
% Jul 31 2014: Updated and commented by AKh from old Jenny's code.
clear;
fprintf('Starting a seizures program\n');
resultFrequency = zeros(6,4);
resultFirstSeizure = zeros(6,1);
resultAvgSeizureLength = zeros(6,1);
figure;
for(sheet=1:6)
a = xlsread('C:\Users\AizenmanLab\Documents\Carolina\Sei... |
771bb3eae66ed9ffbbb444c92abbd5343cfa7ac67b91cbe3f1db6129de3346be | MATLAB | 6,389 | 165 | %% Thomas_Yang_et al, 2023 @Nuo Li lab
%% Fig. 7e direct photoinhibition of SC glutamatergic neurons
% Vglut2-ires-cre x GtACR1 mice, left SC fiber implantation
clear all
close all
addpath('../func/');
load Figure_7_e_data
%% check if the data seems right
% hist(StimOnTime_allSession(Sample_Delay_al... |
17aebfc0995a874a9f0b32e120c1fc7b20f6e80df66042d7df788f3ca9cc3da9 | MATLAB | 6,393 | 156 | function [] = genSTCWDat(genAll,meta,GlobMin)
% This function delineate tracks between sharp turns and curved walks
%
% Inputs:
% genAll: cell array of genotypes to consider
% GlobMin: structure of parameters to delineate sharp turn and curved
% walks
% meta: Type of points we want to return (3 options)
... |
c7ded82168a78ca80d02cc79ac750971dc3844c7b8c7ae05037ae16c302e6e59 | MATLAB | 6,393 | 148 | function xk = modelStepMultiMealExerciseT1D(xkm1,I,CHOB,CHOL,CHOD,CHOS,CHOH,VO2,hourOfTheDay,mP,xk,model)
% function modelStepMultiMealExerciseT1D(xkm1,I,CHOB,CHOL,CHOD,CHOS,CHOH,hourOfTheDay,mP,xk,model)
% Simulates a step of the multi-meal t1d physiological model.
%
% Inputs:
% - xkm1: is a vector containing the m... |
0b27805d11fda4d0c1dfda84cfd6bbd6671bce9896d69adb22178995a77594dc | MATLAB | 6,394 | 217 | % ir_fdk_helix_example.m
% Example of how to use feldkamp_helix.m for cone-beam axial and helical CT reconstruction
% Copyright 2014-11-11, Donghwan Kim and Jeff Fessler, University of Michigan
f.helical = 1;
f.down = 2;
f.pht_ell = 0;
f.pht_cyl = 0;
f.xcat = 1;
if f.xcat
f.down = 1;
end
f.fdk_type = 3; % FDK type: ... |
5d5e788d07f088c49befe5ac3bf26b599ba9a644686cf105013aea2b8fa72b56 | MATLAB | 6,395 | 185 | function Volume=polygon2voxel(FV,VolumeSize,mode,Yxz,hollow)
% This function POLYGON2VOXEL will convert a Triangulated Mesh into a
% Voxel Volume which will contain the discretized mesh. Discretization of a
% polygon is done by splitting/refining the face, until the longest edge
% is smaller than 0.5 voxels. Follo... |
99f13d8478ce67b10b974d6169d915ad033a28613f470ce62f2f3148466d9c29 | MATLAB | 6,395 | 136 | %% IR67 Processing Variables
[root_dir, app_dir] = fn_get_root_dir(); ft_dir = [app_dir 'fieldtrip/'];
if isempty(strfind(path,'fieldtrip')); addpath(ft_dir); ft_defaults; end
%--------------------------------------
% Basics
%--------------------------------------
SBJ_vars.SBJ = 'IR67';
SBJ_vars.raw_file = {'IR67_erro... |
99853d2b7d3357e6ac288915be591d3e5062c929a63f6c4484656261577a82b3 | MATLAB | 6,396 | 169 | function params_out = write_surfs_share(varargin)
% This is a function that will write surfaces on the fsaverage surface.
%
% Specifically, it will go through the specified folder directory
% (specified by ROOTDIR, MODEL_IDENTIFIER, and SUBFOLDER) and writes the surfaces.
% And it writes them to .../written_surfaces/.... |
b67ce21fe49de14b1b834c4d8617e0d818df9ab90d39d34d8a365ed585cafd75 | MATLAB | 6,397 | 143 | function environment = initEnvironment(modality,saveName,saveFolder,saveSuffix,scenario, bolusSource, basalSource, choSource, plotMode,enableLog,verbose)
% function initEnvironment(modality,saveName,saveSuffix,scenario, bolusSource, basalSource, choSource, plotMode,enableLog,verbose)
% Initializes the 'environment' ... |
f2a1dae79985f2d62756e5a0cfde2b9e81e084cdb86333d7408959d987321b8d | MATLAB | 6,400 | 150 | classdef FCSVExperiment < dynamicprops
properties
inputdir
physdata
fcsvdata
usephysio
end
properties (Constant)
repsetregexp = '.*(?<!iso.*)(?<!until.*)(?<!x\s*)(\d+\.\d+)(?!x).*'
repsetxregexp = '.*(?<!x\s?set\s?id\s*)(?<!iso.*)(?<!until.*)(?<!x\s*)(\d+... |
41ef66e135796820594e20b073845bdeff46c146792ca65ab0d9614c86df6494 | MATLAB | 6,403 | 132 | load('../data/simulations/NoiseCorrVsNormalization.mat')
%% - Rho Values are -0.5,0,0.5, so there are 9 possible combinations of rho_N,rho_D.
% % rho vector is -0.5:0.5:0.5, and the pairs below are [rho_N,rho_D]
% % locations, so [2,3] => rho_N = 0, rho_D = 0.5 and similarly
rhoValues = struct();
rhoValues.Positiv... |
688f535eb7c6780c7ec1901fc8e68c447b33114d8a84042c8eadcd4bc15a655c | MATLAB | 6,413 | 165 | clc; clear;
addpath('/data/hu_esraal/Documents/eeglab2019_0/')
addpath('/data/pt_02333/esra_codes/')
eeglab
%%
eegfolder= '/data/p_02186/TMS_ECG2/analyses/EEGtms/merge/old_analyses_tmseeg/'; cd(eegfolder);
save2folder= '/data/p_02186/TMS_ECG2/analyses/EEGtms/merge/reref/cardiacphase_fakecorr/'; mkdir(save2folder); cd(... |
ef3b2425b43f08ce866d2593a441f686bd64ab3ee2e511d7479ace9f64434815 | MATLAB | 6,413 | 163 | classdef MlpExamples < handle
% AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Copyright (c) 2022 The Board of Trustees of the Leland Stanford Jun... |
dc58093190ab4af1f6ff9ac8f8fb6266d12df7e89b11a475a80e0ba8a847ab8d | MATLAB | 6,415 | 146 | function [df_leaving_all,df_entering_all,f_leaving_all,f_entering_all,...
turnProb_leaving,turnProb_entering,turnProb_leaving_std,turnProb_entering_std] = ...
getDf_aligned_turnRates(f_orco,thresh,delay,turnNdxAbs,transitionsOnly,yl,fs,plotFig)
%getDf_aligned_turnRates calculates the firing rate, change in fir... |
afc0e396567e0ce4c6c6f290d6fd55afeb2a105de6d82ad8a9a5ccf288b0702e | MATLAB | 6,422 | 197 | function [Acc, acc_fold, Gini, features_names] = RandomForest_HER_crossvalidation(set1_avg, set1_var, set2_avg, set2_var, nfolds, time_onset, time_offset)
% This function performs a Random Forest crossvalidation classification.
% This function divides the set of patients in folds to perform
% classifications using diff... |
00cbb4fb7da3c184acc60d009797d7bf1713ffe68c7eaf4608d896281ae640f4 | MATLAB | 6,424 | 163 | function fit_linear_Model_M1(exname, include_eye)
results_dir = sprintf('../data/analysis/%s', exname);
% load preprocessed dataset
if ~include_eye
load(sprintf('../data/preprocessed/%s/preprocessed_data.mat', exname), 'D');
else
load(sprintf('../data/preprocessed/%s/preprocessed_data.mat', exname), 'D_eye');... |
bdb1908cb74c9eab260b4a81cc4add2a818a34eff2a5eacc2a8252731a9f2d01 | MATLAB | 6,426 | 182 | % Plot correlation of significant events with track decoding error
% Compares both weighted correlation and spearman correlation
function plot_corr_decodingError_sigEvents
cd('X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\Chapter 1\Decoding_error');
load all_tracks_decoding_error.mat
cd('X:\BendorLab\Drobo\Lab ... |
19450bd7d3e5ed32674abca9cf46020b8881968aa6e683cb20a91a829855da7f | MATLAB | 6,433 | 150 | function [newStateProb,XX,YY,newState,newStateProbBaseline,newStateProbBaselineDuring]...
= getKNNTransProb(f_orco,s,keyNdx,xGrid,yGrid,ratio,Thresh,K,state,plotFig)
% getKNNTransProb calculates the transition probability in the KNN space
%
% Inputs: f_orco = fly object
% s = structure of descriptions... |
ab16731eb0325af9edfce795b7584b6dcad67aa5caefbea2d9774282ea24937b | MATLAB | 6,440 | 176 | function [R2, coefs, vals_m, age] = nc_ModelSelection(AFQpath, sub_ages, excludeSubs, valName, nodes, showFigs, agerange, bootIter, crossval, outfile,models)
% Test different lifespan models
%
% [R2, coefs, vals_m, age] = nc_ModelSelection(AFQpath, sub_ages, ...
% excludeSubs, valName, nodes, showFigs, agerange, ... |
e61d9ec3388127948d22dfc1baac795766f5473a71eb89e52fcf2b6191788441 | MATLAB | 6,440 | 249 | master_startup;
nrats = length(ratdata);
%% Win-stay lose-switch across rats - ignoring session boundaries, effects would be negligible
p_repeat_win = nan(nrats,1);
p_repeat_loss = nan(nrats,1);
ci_win = nan(nrats,2);
ci_loss = nan(nrats,2);
for r = 1:nrats
fprintf('Processing rat %s\n', ratdata(r).name);
... |
5aa85e81389d2f08316f416a664b118df34635b98a55bc9c61640d8888f5e5d0 | MATLAB | 6,442 | 255 | function back = cbct_back(proj, cg, ig, varargin)
% function back = cbct_back(proj, cg, ig, varargin)
%|
%| cone-beam backprojector for feldkamp.m
%| in
%| proj [ns nt na] cone-beam projection views
%| option
%| 'use_mex' 1|2|3 default: 1 mex with loop in mex
%| 2 mex with loop in matlab
%| 3 mex st
%| 0... |
617ed320df1760d92057365e9f0398f34b064b374f76016846579deeee478a49 | MATLAB | 6,443 | 173 | function [seg_spktimes,seg_spikes]= Signle_channel_Spike_detector(bigdata,chans,thresh,filt_para,sr,pre_seg,post_seg1,threshold_channel)
% 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(bi... |
9fd144675576d27794d35b6b84222e688fab918781fd124445fb1708de8749f0 | MATLAB | 6,448 | 197 | function [Acc, time_acc] = RandomForest_HER_crossvalidation_sliding(set1_avg, set1_var, set2_avg, set2_var, nfolds, window)
% This function performs a Random Forest crossvalidation classification.
% Classifications are performed with a sliding time window
% This function divides the set of patients in folds to perform
... |
b02cbb8652e7e7c98c371c2f7de362e9c57e456d56aaa963316df8dc27a7a21e | MATLAB | 6,448 | 138 | %Generates the spike matrix
clear all
dini_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
snr_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\SNR_H\SNR_flavio_new_L8\';
spath = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
mouse='92227'; %Name of the animal
thr_SNR=4;
res=1.5;
count=0... |
ef80edf815e5032a56ccecceeb9562b6ce7f707e77d837635c2a375e268e6183 | MATLAB | 6,448 | 108 | %% Run this files to compute the network-human main effect and interactions for all for the VISION experiments
%% Must specify the paths to the required network data mat files.
function [] = run_anova_human_layer_main_effect(EXP_NUM)
rng(517)
addpath('../matlab_statistics_functions')
NUM_BOOTSTRAPS = 10000
if EXP_N... |
61db4e70c740def871d4e280f10e15fe8c8f8ed9240a39632831fee63cd4c7c9 | MATLAB | 6,454 | 159 | phase_regions_list = {'CING'}
power_regions_list = {'HC'}
% cortex w/ MTL
if strcmp('OFC', phase_regions_list) | strcmp('FRO', phase_regions_list) | strcmp('TEMP', phase_regions_list) && strcmp('MTL', power_regions_list)
group = {'39' '57' '66' '44' '63' '84'}
elseif strcmp('CING', phase_regions_list) &&... |
8b15a9cd8793e122bc376baf25f1298dc9f2970863dff394619d52ae86148f79 | MATLAB | 6,463 | 197 | function [direction,opt] = sampleTurnBias040721(self,state,t,f,df,tt,xPos,yPos,...
tSinceInhibition,sampCurv,sampSpeed,sampDur,sce)
%t = t.*0+1;
nFly = numel(t);
nPt = size(xPos,2);
m = self.model.TurnBias;
turnBias = zeros(size(t));
[~,tSlice]=max(t<(m.tt+m.tt(2)./2),[],2);
uSlice =unique(tSlice);
for s... |
281096ecd5de6da7f8fcd277581efaf352331046afee16ff64ace6679345a3f0 | MATLAB | 6,468 | 158 | %%%%
% save matrix for all subjects in one file
% add column with subject ID, and block ID as well as trial num and session
% num
% save different matrix with coherence traces, subject ID and block ID and
% session num
%% define subjects and and pathways
options = continuous_RDK_set_options('LTHiMac');
subjectList ... |
a41ad3b0795ac6f5a1b19ed54758a5668058d48d51b67efc433af3f21e69ebbf | MATLAB | 6,474 | 227 | function [M_Ru1, M_Ru2, M_v1, M_v2] = vox2ras_rsolve(Vc_C, inPlaneRotation)
%%
%% (USE vox2ras_rsolveAA INSTEAD OF THIS METHOD!)
%%
%% NAME
%%
%% vox2ras_rsolve.m (vox2ras_r{otation matrix}solve)
%%
%% AUTHOR
%%
%% Rudolph Pienaar
%%
%% VERSION
%%
%% $Id: vox2ras_rsolve.m,v 1.5 2007/01/10 22:55:10 nicks Exp $
%%
... |
2f5fb13840beea6f7466b7c51431f7744e93d186465b97f1caba6eb26ee82d78 | MATLAB | 6,480 | 167 | function IPEMPlotMultiChannel (varargin)
% Usage:
% IPEMPlotMultiChannel(inData,inSampleFreq,inTitle,inXLabel,inYLabel,...
% inFontSize,inChannelLabels,inChannelLabelStep,...
% inMinY,inMaxY,inType,inTimeOffset,inYScaleFactor)
%
% Description:
% Plots a multi-cha... |
de6fe74e53551dbefa72a1312db5177046b6c518b3c3eed55b0e340dd6b623cb | MATLAB | 6,480 | 112 | function estimated_position = bayesian_decoding_lap_thetaseq(place_fields,theta_spike_count,track_id)
% INPUTS:
% place fields: matrix or []. Place fields that want to be used as a template in the decoding. If empty, it will load place fields for the whole session (extracted_place_fields_BAYESIAN.mat)
% bayesian ... |
32377f576457ca562c5c248c90bd36803aca91211d8dd655562f08bda1c8a54e | MATLAB | 6,481 | 136 | function [input_graph, varargout] = fun_graph_pruning_internal_short_hairs(input_graph, th_hair_length, internal_offset)
% fun_graph_pruning removes all the short links that connected to
% internal endpoints from the graph
% Input:
% input_graph: structure, generated by fun_skeleton_to_graph
% th_hair_length:... |
0e176c782b8f1b1b79293dc9df169a060311a063cef6ef7ffbd45d1daed09dea | MATLAB | 6,485 | 146 | function dth_all_distances_median_RT_searchlight(subjects,task_distance,task_RT) %distance art, distance nat, RT
%DTH_ALL_DISTANCES_MEDIAN_RT_SEARCHLIGHT Performs the distance-to-hyperplane searchlight analysis using
%the distances from each subject and the median RT across
%subjects.
%
%Input: subjects' ID (e.g., 1:13... |
6e658ac8fb2c009a58843101f0f547f4b2581aa813341329765fd37207c5c072 | MATLAB | 6,485 | 107 | function prior = definePriorPDF(model, environment)
% function definePriorPDF(model, environment)
% Defines the a priori probability density functions of model parameters.
%
% Input:
% - model: a structure that contains general parameters of the
% physiological model;
% - environment: a structure that contains g... |
33d363a038f97b0afd2cf7bce06d74e7883743e803d4f730212f5fb441d838c3 | MATLAB | 6,489 | 151 | %% Thomas_Yang_et al, 2023 @Nuo Li lab
%% Fig. 4b norm. FR, SC photoinhibition, ALM record
clear all
close all
addpath('../func/')
load Figure_4_b_data
sig_selective(isnan(sig_selective))=0;
FR_pref = spk_count_yes_screen-spk_count_no_screen;
i_selective = (sig_selective(:,2)) & cellType_all(:,1)==1 & a... |
b7000fe6824aad8bd02aa7e807ce2f618b8a660aeff3ceecc1e06a516f73676d | MATLAB | 6,492 | 146 | function [outResynthesizedSound,outDetectedPeriods,outIndividualSounds] = IPEMMECSynthesis(varargin)
% Usage:
% [outResynthesizedSound,outDetectedPeriods,outIndividualSounds] = ...
% IPEMMECSynthesis(inPatterns,inPatternLengths,inPatternFreq,...
% inOriginalSignalFreq,inSelectionTime,inDu... |
ad57c5605ab7dbcd606e33e37612272fef4c2fa4a5ba0bab40fb3812520a081e | MATLAB | 6,494 | 168 | function track_cell_count = count_cells_track(computer,method)
% Load name of data folders
if strcmp(computer,'GPU')
sessions = data_folders_GPU;
session_names = fieldnames(sessions);
else
sessions = data_folders;
session_names = fieldnames(sessions);
end
PP = plotting_parameters;
i = 1; % session c... |
678c27668891cf60692d31119fbc684d91a75bb77dc6ec5abdbbff7e8a5e99fc | MATLAB | 6,495 | 182 | classdef SuhDbm < handle
% More efficient alternative to Density.FindClusters that ignores DBSCAN
% and does not incur the cost of transmitting large vector event cluster
% IDs
% AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary Developer: Connor Meehan <conno... |
c11b1b61d7c9a807df7c0b94c2d2c38b83d062fa99dedd26805d41c59c8ddccd | MATLAB | 6,498 | 178 | clear variables
close all
% load matrix of example ca2+ traces, where each coloumn is a time series
% along with acquisition frame time and time of swim onset (in seconds)
load('roisExample.mat')
% visualize plots of processed traces
showfigures = true;
%% Start the main loop
% extract number of frames ... |
2e91f844b731c32740f953757e53671ff017348c52d0ff82faf459763afcfca0 | MATLAB | 6,499 | 169 | function [embedding, method, head, tail, graph_data] = ...
simplicial_set_embedding(data, graph, n_components, initial_alpha, ...
a, b, gamma, varargin)
%SIMPLICIAL_SET_EMBEDDING Perform a fuzzy simplicial set embedding, using a
% specified initialisation method and then minimizing the fuzzy set cross
% entropy... |
2e7f59b64649a7f1156f4bf44a07dea40309a57b5ed1ad74c36ae14b0ea9f564 | MATLAB | 6,501 | 188 | function f = nc_PlotModelFits(coefs,valName,fgNames,fgnums,color)
% Make figures from coeficient estimates (nc_ModelSelection)
%
% f = nc_PlotModelFits(coefs,valName,fgNames,fgnums,color)
%
% Inputs:
%
% coefs - Structure containing model coefficient estimates (see
% nc_ModelSelection)
% valName - The name ... |
267bb659019b14dee5c8a669661c38eb91212ef3c39b2257365a4695af064efb | MATLAB | 6,503 | 276 | %% rename channels
close all; clear;
rename_chan();%from 105_xx (1-72) to 105_CHxx (1-64)
% correct_chan();
%% preview
close all; clear;
preview_data(0.1, 0.6,'led');%pre-trigger post-trigger
%% preview LED
preview_data(0.5, 1.6,'LED');%pre-trigger post-trigger
%% transfermation
transfer_data();% just transfer data ... |
1f486e774a71e0d9d794d9af9748a388c29e0a7bb40591bbe2889c047389dcac | MATLAB | 6,507 | 165 | function plotReplayBGResults(cgm,glucose,insulinBolus, insulinBasal, CHO, hypotreatments, correctionBolus,vo2,data,environment)
% function plotReplayBGResults(glucose,data,enviroment)
% Plot the obtained glucose results against data.
%
% Inputs:
% - cgm: a structure which contains the obtained cgm traces
% simula... |
17d1786b03814b4c9315ea1deb4d74cd0ec603ca584ee721edc46ccda146e396 | MATLAB | 6,508 | 177 |
clear;
clc
close all
%% Step 1: create datatable of both experiments
cd D:\Behavior_7_verbPred_Kim\
resOut = [pwd '\results\'];
outdir = [pwd, '\data_Kim\']
load([resOut,'Exp7_DataTableDP.mat'])
bsize_exp7 = bsize;
cd D:\Behavior_6_strPred_Kim\
resOut = [pwd '\results\'];
outdir = [pwd, '... |
2f476d6359e0d256f9ce3ff7ace8af5f37a234230b96ec0c1e98d038fc8d4708 | MATLAB | 6,509 | 235 | function [xs, info] = qpwls_pcg1(x, A, W, yi, C, varargin)
%function [xs, info] = qpwls_pcg1(x, A, W, yi, C, [options])
%|
%| quadratic penalized weighted least squares (QPWLS) via
%| preconditioned conjugate gradients (PCG) algorithm
%| cost(x) = (y-Ax)'W(y-Ax) / 2 + x'C'Cx / 2
%|
%| in
%| x [np 1] initial estimate
... |
367ec0df63a259be92a933b176c1cbf9f2be1f245e66579750baf01c71346807 | MATLAB | 6,509 | 194 | function [Old_audio_buffer,Old_spikes_buff ]=draw_spikes(chans,thresh,pre_sipke,post_spike,seg_spikes,seg_spikes1,pre_seg,sr,AD_step,debug_flag1,OldEEG,Speaker,src1,Old_audio_buffer,Old_spikes_buff)
% draw_spikes(chans,pre_sipke,post_spike,seg_spikes,pre_seg,sr,AD_step,debug_flag1);
%%%%%%%%%%% ALL PLOT DIS... |
690713690e892d4314b4e6d0283727a6518866895189132877916922cfafb907 | MATLAB | 6,522 | 126 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% generating lipofuscin distribution based on 2PM images
% using channel2 of 2PM
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addpath('/projectnb/npbssmic/s/Matlab_code/PSOCT_code');
addpath('/pr... |
2d4c132de4711cdf1265d9d50aabd63037da123ec350ad6c687df955d87c3b79 | MATLAB | 6,527 | 251 | classdef c_GUI_Text < c_GUI_handle
% c_GUI_Text - GUI class for drawing text
% Similar to uicontrol('style','text') but allows for autoresizing and other misc
properties
doAutoResize
MaxFontSize
end
properties(Dependent)
String
Units
Position
FontWeight
HorizontalAlignment
end
properties(SetAcce... |
e716669083c87a77c3fadce89abd038b21ba4d21435926ce9e7983f9810af5a8 | MATLAB | 6,529 | 110 | %% Run this files to compute the network-human main effect and interactions for all for the VISION experiments
%% Must specify the paths to the required network data mat files.
function [] = run_anova_stats_matlab_network_human_results(EXP_NUM)
rng(517)
addpath('../matlab_statistics_functions')
NUM_BOOTSTRAPS = 1000... |
7e6186f7d22eb439cd337cc99880e2c4194de275de5109a06a750bb2944a03e4 | MATLAB | 6,530 | 221 | function D = spm_eeg_correct_sensor_data(S)
% Remove artefacts from the data based on their topography
% FORMAT D = spm_eeg_correct_sensor_data(S)
%
% S - input structure (optional)
% (optional) fields of S:
% S.D - MEEG object or filename of M/EEG mat-file
% S.mode - 'SSP': simple projection
% - '... |
72bc1e88e70b762bda639a19a74e1fc6fb3974808faa2c44e8c020fcd781da8c | MATLAB | 6,532 | 149 | function [CD_correct, dphi_correct, phi_fit, cc_fit, mask_static_refined] = CDPhaCor_Iter_2D_V3(mag1, mag2, dphi, Z1Z2product, mask_static, mask_brain, deg, Niter, bBatch, nRep)
% MODIFY ON 20230807: nRep input
% this function correct the phase errors in complex difference iteratively,
% based on user input initia... |
e7524d17794e43470308036f84189acaf0dea82c55c1a687100433702cf4a890 | MATLAB | 6,533 | 221 | function img = feldkamp_wt(proj, window, mask, args, varargin)
%function img = feldkamp_wt(proj, window, mask, args, [options])
% modified version by Ajay Paidi
%
% FBP reconstruction of cone-beam tomography data collected with flat detector.
% See feldkamp_example.m for example.
%
% in:
% proj [nh,nv,na] cone-beam pr... |
b13a2130754e7dd21ec18653f961280b852bb1e870799573e13f4bbfedc9a601 | MATLAB | 6,537 | 182 | %%% Marker points %%%
%% #1 [48,51; 109,53]
%% #2 [39,58; 110,61]
%% #5 [56,67; 108,67]
%% #6 [31,60; 105,60]
%% #7 [53,63; 102,64]
%% #8 [48,67; 115,67]
%% #9 [48,65; 107,66]
%% #10 [57,55; 105,56]
ROI_list={'M2L1.tif', ... %Secondary Motor Cortex - Left Hem.
'BCR1.tif', ... %Primary Barrel Cortex - R... |
eb9d5e7b0d1bc7766ef79645177d39fb5a341bec375b0f3b17f60a8d73526d5b | MATLAB | 6,540 | 113 | function estimated_position = bayesian_decoding_lap_thetaseq(place_fields,theta_spike_count,track_id)
% INPUTS:
% place fields: matrix or []. Place fields that want to be used as a template in the decoding. If empty, it will load place fields for the whole session (extracted_place_fields_BAYESIAN.mat)
% bayesian ... |
2f358643cca0a2a444fd44c800c40089fd9c746c70d06d3642eb92e3183a6bdd | MATLAB | 6,542 | 191 | function [sig,a] = spm_shoot_blur(t,prm,its,sig)
% A function for blurring ("smoothing") tissue probability maps
% FORMAT [sig,a_new] = spm_shoot_blur(t,prm,its,sig)
% t - sufficient statistics
% prm - regularisation parameters (1,1,1, 0.01,0.02,1)
% its - max no. iterations (12)
% sig - optional star... |
b33f5fa7d029136f593f3676e9880d50212f8b8ea340c49419fac9369a631c1f | MATLAB | 6,547 | 163 | function SBJ08a_HFA_save(SBJ,proc_id,an_id)
% Calculates high frequency activity, computes cluster-based statistics, and plots the results
% clear all; %close all;
% 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... |
a71fb2c4ffc3d72a07fa54cf1d26eafe675d1959b0f37434ad9cb3c3432571ed | MATLAB | 6,554 | 255 | function [xs, info] = pl_iot(x, Ab, data, R, varargin)
%function [xs, info] = pl_iot(x, Ab, data, R, [options])
%|
%| Generic penalized-likelihood minimization,
%| for arbitrary negative log-likelihood with convex non-quadratic penalty,
%| via incremental optimization transfer using separable quadratic surrogates.
%|
... |
9ef9fe4020fc31521a818fe140a9905a29aad3bc713d963e544e79bdc95520a5 | MATLAB | 6,555 | 137 | function [FieldAssignmentsAll, OrganoidStencilAll, Wells] = Iris_GetOrganoidFields(InPath, MetaData, CoordinatesAll, illustrate)
%extract organoid IDs from CV8000 first pass and second pass integration
% author: Paul Antony 20210213
% Coordinates: example: readtable([InPath, filesep, 'Encoding.csv'], 'ReadVariableN... |
78bf03355087dcb697cbccdce01962a7efcb8554cfe1037c657ddc3e172892a3 | MATLAB | 6,556 | 214 | function [data_avg] = compute_average_single_subject_level(data,average_type, rt_flag, baseline_window,baseline)%
coherence = [0.3,0.4,0.5];
switch average_type
case 'coherence'
for coh = 1:3
if rt_flag
idx_coh = find(abs(data.trialinfo(:,4)) == coheren... |
d85d86cd177a2ac8b82d4fdc6441ca9114150cb089d3bdd5e58b08d1bd859fe5 | MATLAB | 6,558 | 232 | function img = fbp_fan_arc(sino, G, window, varargin)
%function img = fbp_fan_arc(sino, G, window, [options])
%|
%| FBP reconstruction of fan-beam tomography data collected with arc detector.
%| Assumes system 14 geometry and extracts parameters from Gtomo2_dsc object.
%| Assumes that the arc is focused on the source,... |
1abc2eb522a13ab575860409236e56bd9e35d29609cebac9d839a8731a6e02a8 | MATLAB | 6,561 | 201 | function D = spm_eeg_spatial_confounds(S)
% This function defines spatial confounds and adds them to MEEG dataset.
% FORMAT D = spm_eeg_spatial_confounds(S)
%
% S - optional input struct
% fields of S:
% D - MEEG object or filename of M/EEG mat-file with epoched data
% mode - method for definitio... |
2ee5b7d74132ccb04d113d0e56d66488bffa4f7e4e2f78778f07773e40f6e754 | MATLAB | 6,565 | 190 | function seg_to_graph(dpath, filename)
%seg_to_graph Convert the vessel segments to a graph (nodes + vertices)
% This function is the second step in the vessel segmentation pipeline.
% This function can take either a .MAT or .TIF
%
%%% INPUTS:
% dpath (str): absolute path to the data folder
% fname (str): n... |
efe86d07bdaac0a30b6421edc802d1ceddeef6bf65b02d2b175e9baba105c26f | MATLAB | 6,575 | 114 | % SPIKE COUNT FOR BAYESIAN DECODING
% INPUTS:
% place fields: matrix or []. Place fields that want to be used as a template in the decoding. If empty, it will load place fields for the whole session (extracted_place_fields_BAYESIAN.mat)
% start_time & end_time: single value, vector or []. Might want to enter s... |
fc9e28f88efb25dbf120ce5f622c3738b3db935ba661bd4c39008a8f86d481f8 | MATLAB | 6,585 | 173 | function D = tnueeg_spm_eeg_artefact(S)
%TNUEEG_SPM_EEG_ARTEFACT Modified SPM function:
% Simple artefact detection, optionally with robust averaging
% FORMAT D = spm_eeg_artefact(S)
%
% S - input structure
%
% fields of S:
% S.mode 'reject' (default) - reject bad channels and trials... |
3a7a5a9bd64789e14fae9bc030bf250ebbbe847f1216e2df838b0e4fc1e1021d | MATLAB | 6,592 | 176 | function [segmentedHierarchiesCube1] = hierclust2nmfMulti(Hcubes,r)
% Hierarchical custering based on rank-two nonnegative matrix factorization
% applied to hyperspectral image clustering
% B Ravi Kiran, Aug 2015
% Given a data matrix M (m-by-n) representing n data points in an
% m-dimensional space, this algori... |
99d9a9c659c8da73f3958b8f7cc943ed1dd2d312ea2614b892ad261a26e33f71 | MATLAB | 6,596 | 211 | function V = spm_create_vol(V)
% Create a NIfTI image volume
% FORMAT V = spm_create_vol(V)
% V - image volume information (see spm_vol.m)
%__________________________________________________________________________
% Copyright (C) 2005-2018 Wellcome Trust Centre for Neuroimaging
% John Ashburner
% $Id: spm_crea... |
652d18d0431b29613f09f0e9cd1bab356619ae23d534375f775e13a0fe0d9324 | MATLAB | 6,597 | 192 | function D = spm_eeg_inv_datareg_ui(varargin)
% User interface for EEG/MEG data coregistration within original sMRI space
% FORMAT D = spm_eeg_inv_datareg_ui(D,[val], [meegfid, newmrifid, useheadshape])
% D - M/EEG dataset
%
% meegfid - M/EEG fiducials
% mrifid - MRI fiducials
% useheadshape - use... |
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