sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
f43ab4c2ad5a9be5d832d87e7f81e991e6553e548d1aae6fd5985eafdf0e85bc | MATLAB | 4,331 | 199 | function output = ILT(sig,gradechoinv,options)
%Dicretized inverse Laplace transform for arbitrary kernal and contrast
%encondings
%solve S = KF for F
% S is the signal
% K is the matrix of kernals
% F is the spectrum
%gradechoinv - values of the MR contrast encodings
%e.g. gradient direction, b-values, echo t... |
c207d548c7303fffcdd8bd3bc52f3364b5f92f142a349b03900e59fae1ece786 | MATLAB | 4,333 | 124 | function [] = SomatotopyGradientPlotting(sm, smData, pd, projectionFields, arrayInfo, arrayOfInterest)
numDigits = 5;
numChannels = 192;
% Use 3 for C1, 1 for P2 and P3
if arrayOfInterest == 1
motChanMask = sm.motorChannel<129;
elseif arrayOfInterest == 3
motChanMask = sm.motorChannel>128;
end
filtSize = 1; ... |
d2a2b0f1c447cbd6fcc8f7d8625aad8889d3f0798f3bd0a7cf6941836777a57b | MATLAB | 4,334 | 152 | function [nodePos,nodeDiam,nodeEdges] = pruneGraph_Loops4( im );
nNodes = size(im.nodePos,1);
nE0 = size(im.nodeEdges,1);
nB=zeros(1,nNodes);
for ii=1:nNodes
nB(ii)=length(find(im.nodeEdges(:,1)==ii | im.nodeEdges(:,2)==ii));
end
nBtmp = nB;
nE0 = size(im.nodeEdges,1);
nodeFlag = zeros(nNodes,1);
... |
3d87a58010c5511441987519af788173c2c77e6072fded9f37f7cdd897658592 | MATLAB | 4,335 | 159 | %% Script to visualize the distribution of l1 l2 and theata2 in different groups
% Zilong Ji, UCL, 2022 zilong.ji@ucl.ac.uk
% Preparing the data
GLAMPI_PrepareBaseConfig
% Preprocessing the data
GLAMPI_PreprocessData
%%
% Model fitting
config.ModelName = "beta_k_g2_g3_m3_sigma_nu";
config.ParamName ... |
fa4f01f3c71006606faf4e47eae0cf58fb90a4db93c026254996abe898fd8303 | MATLAB | 4,336 | 105 | % compile
%
% Builds the trigger counter for the parallel port (triggerCounter3.m) into
% a standalone Windows program with the MATLAB Compiler.
%
% Run it in MATLAB, from any folder. Needs the MATLAB Compiler and
% PsychToolbox; from the toolbox it needs parchat only, which it takes from
% the IO folder of this toolbo... |
f5a6c64a72e99bf89a6e95ccf5bf21218fdd066a2effde0c4a49ff323609b2a8 | MATLAB | 4,337 | 148 | % 0.Load data
session_v1=load('C:\Users\xscogno\MATLAB\Flavio2\Waves\Semi final scripts\Final scripts\Outputs\locking_ensemble_Pearson_V1\locking_ensembles_Pearson_V1.mat');
session_pas=load('C:\Users\xscogno\MATLAB\Flavio2\Waves\Semi final scripts\Final scripts\Outputs\locking_ensemble_Pearson_PaS\locking_ensembles_P... |
483cee18f0832e14b1fbd468c687c9040cac9c36e8f3cb7b8589b036caa06672 | MATLAB | 4,339 | 129 | function EEG = c_TMSEEG_findTMSPulses(EEG,varargin)
% assuming no events available for TMS pulses, try to find based on artifacts
p = inputParser();
p.addRequired('EEG',@isstruct);
p.addParameter('filterMethod','median',@ischar);
p.addParameter('maxPulseRate',100,@isscalar); % in Hz
p.addParameter('addEventsOfType','Pu... |
d5d1fd1edeea29b5fce99b1bf407f79fdcc7c3c67859e1fd192ccbd4387f1865 | MATLAB | 4,343 | 126 | function [wmap, wconv] = call_fmap(yik, etime, func_name, varargin)
% This function is a wrapper for fmap_est_qm.m and fmap_est_pcg_ls.m to
% make them callable in a similar fashion as mri_field_map_reg.m
%| inputs:
%| yik [(N) nset ncoil] complex images at different echo times
%| (these should be undistorted)
%| ... |
5df0ae1bb8a24781ecf8ec1233d9d90372c5c8955543c0d6fbb8de3f1c2dff78 | MATLAB | 4,344 | 191 | function ob = Gmatrix(matrix, varargin)
%function ob = Gmatrix(matrix, [options])
%|
%| Construct fatrix2 object from an object (such as a matrix) that can do
%| multiplication and transpose. The point of this would be to endow
%| the matrix with the masking features provided by fatrix2.
%|
%| in
%| matrix [M N] cou... |
68308e1e41725895f4e84f092a748f8c96de8d01c0a312694aefca23a0229ab1 | MATLAB | 4,345 | 194 |
% Run all sessions and create 'AnalyzedData.mat' containing all data
function AnalyzeAllData(Filename)
RunAllSessionsTimeVsDistance
load('Summary.mat');
clear R;
Cnt = 0;
Mx = size(R,2)+2;
for i=1:size(R1,1)
if R1(i,1)~=0
Cnt=Cnt+1;
... |
71ae265f9a22ed75ef32446fe6a674b85d63a8fc94656b5154987ad33081d42b | MATLAB | 4,345 | 117 | function [negloglikelihood] = Estimate_g2_m3_sigma_nu(g2, m3, sigma, nu, Input, config)
% Zilong Ji, UCL, 2022, zilong.ji@ucl.ac.uk
% Find the likelihood with parameters specified in the model function name
% Args (in common between all estimates functions):
% beta: decay factor for the mental distance (calculation err... |
944eb653aaa5ce7f8c3ec51b189c0c18cfcc0cd9ee5655bed9051986f5a74158 | MATLAB | 4,345 | 108 | function [WC,T] = LeG_autoElecs(app)
Img = app.CTImg;
MaxElecs = app.detect.maxelecs;
ElecRad = 2; %total radius of standard ad-tech grid electrode (4mm dia, 2.3mm exposed)
XYZScale = app.XYZScale; %need to swap x/y if comparing with connected components
MRInfo = app.MRInfo;
ProjSurfRaw = app.ProjSurfRaw;
... |
5f2fc310d387ac981ca3b59259328f7429c082fbfcdd40ded25beaf6c1b0dd2f | MATLAB | 4,346 | 97 | function fn_plot_ts_errbr(plot_info, data, var, event, cond)
% Plot mean time series with shaded error bars on given plot handle
% INPUTS:
% plot_info [struct] - contains general plotting details
% .fig [figure handle] - handle of the figure where the plot should appear
% .ax [axis handle] - handle of the... |
df884b38c6dc3a510029662b5d55c002839348de9dc3b57e405b2fffacfe6ab0 | MATLAB | 4,346 | 143 | %% define dataset path
datapath = '/projectnb/npbssmic/ns/191103_PSOCT_small_blade/';
addpath('/projectnb/npbssmic/s/Matlab_code');
%% define grid pattern
% displacement parameters
xx=199;
xy=-4;
yy=197;
yx=10;
% mosaic parameters
numX=24;
numY=24;
Xoverlap=0.5;
Yoverlap=0.5;
% tile parameters
Xsize=... |
b59e5cf56bed1b84724cd59089be9b17538ab96081e31c934635752eb56f58f3 | MATLAB | 4,349 | 154 | %% Analyzing Neural Time Series Data
% Matlab code for Chapter 16
% Mike X Cohen
%
% This code accompanies the book, titled "Analyzing Neural Time Series Data"
% (MIT Press). Using the code without following the book may lead to confusion,
% incorrect data analyses, and misinterpretations of results.
% Mike X Cohen... |
50e88ac037525a75017d2a92b35e11e100c602d9bf1745423f580314005fb748 | MATLAB | 4,350 | 132 | function cdf = spm_read_netcdf(fname)
% Read the header information from a NetCDF file into a data structure.
% FORMAT cdf = spm_read_netcdf(fname)
% fname - name of NetCDF file
% cdf - data structure
%
% See: http://www.unidata.ucar.edu/packages/netcdf/
% _____________________________________________________________... |
d00593c4853e0ad422575c02edf37f5c2c355fc04271270c3babc420eb393f70 | MATLAB | 4,351 | 130 | function recon_im = sense_recon(smap, reduced_fft, reduced_dim, np, regularizer, mask, figs_on)
% function recon_im = sense_recon(smap, reduced_fft, reduced_dim, np,
% regularizer, figs_on)
% in:
% smap [N M nc] complex sensitivity maps
% reduced_fft [N/np M] or [N M/np] undersamp... |
b485d96ae196b7571e31884376439ba7b77a61decb1fb5f18762313913a323cb | MATLAB | 4,353 | 117 | function [negloglikelihood] = Estimate_beta1_beta2_g2_g3_sigma_nu(beta1, beta2, g2, g3, sigma, nu, Input, config)
% Zilong Ji, UCL, 2022, zilong.ji@ucl.ac.uk
% Find the likelihood with parameters specified in the model function name
% Args (in common between all estimates functions):
% beta: decay factor for the mental... |
38b14fb15995ce99b4777bbc31c939f042fbb24ad0d96f17cf8e1b54186f7d8f | MATLAB | 4,355 | 114 | function[]=ref_vol_stitch_from_AB(id,datapath, depth, thickness)
Xsize=1000;
Ysize=1000;
Xoverlap=0.15;
Yoverlap=0.15;
resize_factor=0.5;
% add path of functions
addpath('/projectnb/npbssmic/s/Matlab_code/PSOCT_code');
addpath('/projectnb/npbssmic/s/Matlab_code/ThorOCT_code');
addpath('/projectnb/npbssmic/s/Matlab_code... |
63677419c342f5e95bfea4f01021b5e01109ec87e7e4e98644d617eb450e1f48 | MATLAB | 4,356 | 119 | function [sliding_mean] = plottingProbInside(empFlys,border,numfliesEmp,fs,startPts,type)
if strcmpi(type,'during')
[bin_inside_rim_sliding_SEM,bin_inside_rim_sliding_mean,inside_rim,framesinBin] = analysisFunc(empFlys,border,numfliesEmp,startPts,type);
endPts = size(empFlys.rHead,2)-startPts+1;
plottin... |
b0011e1a30ef5e08cc807e515f43ee62ef207fe29316929b47b70417d8b46b94 | MATLAB | 4,356 | 102 | % KMEANS K-means clustering.
% IDX = KMEANS(X, K) partitions the points in the N-by-P data matrix
% X into K clusters. This partition minimizes the sum, over all
% clusters, of the within-cluster sums of point-to-cluster-centroid
% distances. Rows of X correspond to points, columns correspond to
% variables. KMEANS ... |
55629162c16e801ddeabc90c169aa4ce8d491a8eebea586a78f07c99f2c3ef69 | MATLAB | 4,357 | 155 |
x_reg = 'INS'
y_reg = 'CA3'
% get regional elecs
[fro_chan_idx,MTL_chan_idx,temp_chan_idx,insula_chan_idx,cingulate_chan_idx,OFC_chan_idx,CA3_chan_idx,...
CA1_chan_idx,HC_chan_idx, ACC_chan_idx] = get_elecs(subj);
if strcmp('OFC',x_reg)
x_elecs = OFC_chan_idx;
elseif strcmp('FRO',x_reg)
x_elecs = fro_chan... |
7b5b896d8ca4a6c9050848aa329553f86202cea1b61ca25cc060806d95ed59fd | MATLAB | 4,358 | 175 | % mri_r2_fit_ist1.m
%| Fit R2=1/T2 and "pd" image using ODWT regularization
%| and iterative soft thresholding (IST), with alternating updates.
%| Use interactive sliders to select soft threshold value.
%| Copyright 2012-05-20, Jeff Fessler, University of Michigan
%| in
%| mask
%| yi [(N) nt] data
%| telist [nt] echo... |
f23ec362b3814d83e5512f325db0df38b35338f7a243e6cb8fa11ec57aca372a | MATLAB | 4,365 | 92 | function input_graph = fun_graph_relabel(input_graph)
% fun_graph_relabel computes the labels for the links and nodes, update all
% graph structure after graph pruning.
% Input:
% input_graph: structure created by fun_skeleton_to_graph. Required
% field:
% num.skeleton_voxel need to be updated.
% ... |
b1f211153c82d87b051de017dddab1d6022952a8ca2c6c50b4cb7d10c118fba6 | MATLAB | 4,367 | 185 | function centers = lloyd_max_hist(data, centers, MM, tol, max_iter, chat)
%function centers = lloyd_max_hist(data, centers, MM, tol, max_iter, chat)
%|
%| "improved" version of the lloyd-max algorithm for scalar quantizer design
%| that saves computation by histogramming the data first.
%| Before using this, try using... |
d9b4fbaae15bc6bc8f78d1e0901c4cfafb4ac512e1905047a9c48cad67d03ae5 | MATLAB | 4,367 | 150 | clc;clear;close all
root='..\';
addpath(genpath([root,'NeuralCorrelateEvidenceAcc']))
%%
subdir='total';
clusterName='clusterArea_paper';
regCluster=1;
if(regCluster)
subdir=[subdir,'_',clusterName];
end
all_units=1;
postfix='';
if(all_units)
postfix='_allUnits';
end
rootpath='..\dataset\Mice\spike\result\';
... |
c5620d3c53a1904cbf653545df41a80d9dda7f916ad213fd620e38e426bfeea3 | MATLAB | 4,368 | 97 | function [outSpectrogram,outTimes,outFrequencies] = IPEMCalcSpectrogram (varargin)
% Usage:
% [outSpectrogram,outTimes,outFrequencies] = ...
% IPEMCalcSpectrogram(inSignal,inSampleFreq,inFrameSize,inFrameInterval,
% inWindowType,inFFTSize,inPlotFlag,inPlotTreshold)
%
% Description:
... |
ee65caeadc4485069770bea3da495333ec191c5b0435651c8bfe790dc90dad6a | MATLAB | 4,369 | 124 | function plot_rate_map_longitudinal(neuronIndividualsf,behavIndividualsf,firingrateAll,cellnumber,thresh,dataType,scale,savefigure)
%% This function is used to plot firing rate map of longitudinally tracked neurons
% Inputs:
% (1) neuronIndividualsf: a cell array of neuron data across different days, each cell is a sou... |
ba93a922051160198429b23636d762d12ec4cda378d53f1ac032f5c1988a4e10 | MATLAB | 4,370 | 113 | % bjli @ Feb 11 2023.
% bjlistat@nus.edu.sg
% refered to Z. Yao, J. Su, B. Li, and S.T., Yau, Manifold Fitting
Jobs = {
1, 'Visualization of the Calabi-Yau';...
2, 'Visualization of the Performance';...
3, 'Boxchart asymptotic property S';...
};
i_job = 3;
job = Jobs{i_job,2};
swit... |
40b2822b0a69fe7ac6e46c7f9a6afaf043cf015cdc965ddc1ec06ebceb4f8f50 | MATLAB | 4,371 | 155 | clear all;
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
xx=20;
xy=0;
yy=20;
yx=0;
% mosaic parameters
numX=33;
numY=29;
Xoverlap=0.5;
Yoverlap=0.5;
% tile parameters
Xsize=40;
Ysize=40;
numTile=numX*numY;
g... |
c6f24406722b7c9cbd3c842391d5820c815f15b2d539df6a13452a8c8d07858b | MATLAB | 4,371 | 142 | function [peakAll,SpikesAllV,Stimulus,IdxInCluster,window,fs] = SpikeClustering(voltageTrace,Stimulus,fs,vis)
% this function will calculate the spike rate of a given given signal and
% index of spiking
% voltageTrace: Vector of the Baseline subtracted voltage (mV)
% Stimulus: Vector of the Stimulus associated wi... |
d2c3bc0b56f3a44ac86e5ca5ea34df8b50acf98024cfcc3624aaef536055df51 | MATLAB | 4,371 | 142 | %% Curve fitting - estimate effective Reylaigh range and focus depth
clear all;
datapath = strcat('C:\Users\jryang\Desktop\30-s3\');
% add subfunctions for the script
addpath('C:\Users\jryang\Desktop\Data\code\');
opts = optimset('Display','off','TolFun',1e-10); % fitting options
% get the directory of all i... |
7d3cb87f6db26a7d3f0e747ae15e10471551d51dc0d0fe9a6cf230dcb9e5ea4c | MATLAB | 4,376 | 149 | function y = Gtomo_nufft_filter(omega, ob, do_phase)
%function y = Gtomo_nufft_filter(omega, ob, do_phase)
%|
%| build the sinogram-spectrum-sized matrix
%| that is .* multiplied after 2D FT, before iFFT or NUiFFT
%|
%| in
%| omega [M 2] frequency sample locations (radians)
%| out
%| y [M 2] filter
%|
%| Copyright 200... |
b758fe133883fdec4e50705fa0423f8df4ef02fd5cf95e28e44dea533a8fb860 | MATLAB | 4,377 | 152 | clear all;close all;clc
% this script saves the behavior log data into matrices
% output: testing_behav_matrix, training_behav_matrix
subj = 7
patient_num = [ 39 57 66 63 44 83 84 85 87] ;
addpath('/mnt/yassamri/iEEG/sandra/analysis_pipeline_final')
cd(['/mnt/yassamri/iEEG/sandra/subj_' num2str(patient_num(subj))]) ... |
40148717a789fc59576398e6ac0b854d95d4ecae74cf880afc73fe0c76d05a55 | MATLAB | 4,378 | 162 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Population data analysis for the local retinotopy of RGC axons / local
% SC neurons
%
% This script generates Figure 4 of the following paper:
%
% Molotkov D., Ferrarese L., Boissonnet T. and Asari H. (2023)
% Topographic axonal projection at s... |
fa4352a162ee792c4d621b03f24aa29999bcf9598601e8a2f52f1ebcfa717a86 | MATLAB | 4,379 | 155 | function y = embed_mult(fun, arg, is_transpose, x, istart, nblock, ...
mask, np, odim, is_array, varargin)
%function y = embed_mult(fun, arg, is_transpose, x, istart, nblock, ...
%| mask, np, odim, is_array, varargin)
%|
%| The matrix-vector versions of the linear forward models used herein
%| expect an input x of si... |
f91e8e3db43075bfae53cf3b267a25d5874b4d912f34d6a3311a5680fd69c9ea | MATLAB | 4,381 | 101 | %% Create conversion matrix
% This script creates a conversionMatrix which translates tracked coordinates of the cameras
% to touched positions on the screen. This script is necessary to use camera tracking in a Skinner Box, to register
% screen packs and touches on a setup without a touchscreen.
% CameraTracking_Bird... |
09af8761c49dbe7ee69476812f852aa28d70c0285b4fc2bb1176b510da3c809c | MATLAB | 4,382 | 83 | function connect_link_str = fun_graph_shortest_path_between_points(metric, point_sub_1, point_sub_2, connectivity)
% fun_graph_shortest_path_between_points finds the shortest path between
% two point, with distance measured by the metric array
% Input:
% metric: 3D numerical array, specify the distance between n... |
945d9aeb892cf8a592b78283a4d86f49cd7dfd1083d298c9138e6d31c6a7d6ad | MATLAB | 4,382 | 118 | function [negloglikelihood] = Estimate_g3_sigma_nu(g3, sigma, nu, Input, config)
% Zilong Ji, UCL, 2022, zilong.ji@ucl.ac.uk
% Find the likelihood with parameters specified in the model function name
% Args (in common between all estimates functions):
% beta: decay factor for the mental distance (calculation error)
% k... |
9810d664beb2165979747c79b4b360233621f54d4bcbf56137cc9b8f69bd1f3b | MATLAB | 4,382 | 164 | % This function takes Dans experimental fits for the different
% ages, and tries to find which
function matchIterationToAgeSegregationExperiment(obj,injectionType,nRep)
switch(injectionType)
case {'MLfix','AP'}
axisDir = 'AP';
case {'APfix','ML'}
axisDir = 'ML';
otherwise
fprintf('Unk... |
b01a9223668c9ff7b2a98e0de3a1e459f4ad7a59e1918b6112458ee82f97cc1b | MATLAB | 4,383 | 124 | function x = spm_invFcdf(F,v,w)
% Inverse Cumulative Distribution (CDF) of F (Fisher-Snedecor) distribution
% FORMAT x = spm_invFcdf(F,df)
% FORMAT x = spm_invFcdf(F,v,w)
%
% F - CDF (lower tail p-value)
% df - Degrees of freedom, concatenated along last dimension
% Eg. Scalar (or column vector) v & w. Then df=[v... |
3ee6b78aef70601985e496fed1d9a897209bd3e0872db3fe83dda582b5fc0619 | MATLAB | 4,384 | 118 | %% Plot Supplementary Figure 8 a, b, e
% Plot single-trial spectrogram of an ROI to compare different regression
% steps
%% Define Paths of Loading Files and Save Files
currentFolder = mfilename('fullpath'); % determine the filepath based on where the script locates
scriptFN = mfilename;
filePath = erase(erase(current... |
f3e9c7d56f3b73b8b9340a159c760386e37b160792015eb18b1186545c8cf936 | MATLAB | 4,384 | 205 | function Fatrix_test_basic(A, mask, varargin)
%|function Fatrix_test_basic(A, mask, [option])
%|
%| perform basic tests of Fatrix objects
%| in
%| A [nd *N] Fatrix object
%| mask [(N)] logical support
%| option
%| 'x' [(N)] optional input test image
%| 'multi' 0|1 if 1, test multiple rhs: A * [x x]. default: 1
%|... |
1fbd7f54c6a19890553be3d7577e158e730ed89e95525010112cb8be597b00df | MATLAB | 4,385 | 112 | function tsc_STA(mainPath, animal, session, ch, isstim, neuron_n)
%TSC_STA Spike triggered average analysis during theta cycles with tSCs
% TSC_STA(MAINPATH,ANIMAL,SESSION,CH,ISSTIM,NEURON_N) performs spike
% triggered average analysis on LFP and on the Wavelet power and phase of
% the LFP. The analysis is re... |
599552f9e542abf16727e14ccbe0217e97252cb031d1d38378e7270ceaad97de | MATLAB | 4,386 | 150 | function handle = c_plotSurface(varargin)
p = inputParser();
p.addRequired('nodes',@isnumeric);
p.addRequired('faces',@isnumeric);
p.addParameter('nodeData',[],@isnumeric);
p.addParameter('faceData',[],@isnumeric);
p.addParameter('elemData',[],@isnumeric);
p.addParameter('renderingMode',0,@isscalar);
p.addParam... |
7a28322e68b230d87e97784948103b390e6e31c45de4d063fa80a48097b9887f | MATLAB | 4,386 | 105 | function [timing]= get_traces(dat, event, behavior)
fprintf('separate interesting periods\n')
type={event.type};
run_mess=find(strcmp(type,'Run:')==1);
value={event.value};
a=strfind(value,'Trail:');
trial_message=find(cellfun(@isempty,a)==0);
%... |
f8c0640d869a8bef47766f12710c4073259848f483ff096a4cfd0ab475f974a0 | MATLAB | 4,386 | 98 | function SVM_object_decoding_full_experiment(subject,task)
%SVM_OBJECT_DECODING_FULL_EXPERIMENT Perform object decoding (average of pairwise object decoding) using the SVM classifier.
%
%Input: subject ID, task (1=categorization, 2=fixation)
%
%Output: NxNxP vector of accuracies in %, where N is the number of conditi... |
87cfc0c01f51026a4044714162b6186cbcaab21db9fb43edb18ba4c05ae948b0 | MATLAB | 4,390 | 142 | %% Goals: input smoothed and aligned data from script 1 in order to evaluate
%signal changes surrounding epocs
%revise to add outputs for group averaging
%revise with if/then statements indicating where to look for TTL epocs if
%manual times are not provided.
function [] = Epoc_Alignment_CF(savedata, savefigs,... |
37bb80723313c6e8352ab7eed1893bb2c2ea10d5ebc60de8cd11b8bc31a64d57 | MATLAB | 4,391 | 145 | function plot_spatialinfo_before_and_after_dchPeriod(cells)
% function constants
plotWidth = 500;
plotHeight = 1000;
spatialBinNum = 200;
MPP = 0.125; %Minimum Peak Prominence
numCells = size(cells.metadata,1);
drawFig = true;
% declare global vaariables
all_Ispike_cntrl = NaN(numCells,1);
all_Ispike_dch = NaN(num... |
d09518c9c412e58f1d4918f8a6a4396552d2f464319602cb703839e3ae66801a | MATLAB | 4,393 | 111 | function [OFC_chan_idx,fro_chan_idx,temp_chan_idx,insula_chan_idx,cingulate_chan_idx,...
ACC_chan_idx,EC_chan_idx, HC_chan_idx ,CA3_chan_idx,CA1_chan_idx, MTL_chan_idx] = get_elecs_clean(subj)
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
if strcmp('57', subj)
fro_chan_idx ... |
cad31e866970b84399d624267f4f9a78a1453d1c1cb9484c24d92f3b7518ad0b | MATLAB | 4,396 | 79 | % EXTRACT THETA SEQUENCES SCORES FOR TRACK AND SESSION
% MH 2020
% Takes the averaged theta sequence score for each session and track calculated in the theta pipeline and saves it in a structure. Within each
% method structure, each row is a track and each column is a session. It's ordered from 16x8 to 16x1 sessions.
... |
b8892b172c60cd8135401c9d45a58786b6d60836c0911c4fb280844f66f27a8f | MATLAB | 4,398 | 134 | % [footblur, radii] = blob_li_blur(R, dR, alpha, kb_m, blur, du, dy, Ny, chat)
% Calculate line integrals of a radially symmetric Kaiser-Bessel blob
% and blur them with each one of a set of 2D blur PSF's
%
% R: Radius of blob support [mm] (default = 2*dy)
% dR: Sample spacing [mm] in radial direction
% of p... |
f85bd35b6e9e373936c80bc94375c21442f9158b633bf1f87ad6dc4d54342862 | MATLAB | 4,402 | 116 | function IPEMPlaySoundWithCursor(varargin)
% Usage:
% IPEMPlaySoundWithCursor(inSignal,inSignalFreq,inAxisHandles,inTimeRange,
% inTimeOffset,inSpeedFactor)
%
% Description:
% Plays the given sound signal while showing a moving cursor in the given axes.
%
% Input arguments:
% in... |
fb47c5ee161a376d5bfb6f0ea7e4576135fce06da31aa023aa656bd1c2586785 | MATLAB | 4,403 | 127 | function SPM = spm_vb_contrasts(SPM,XYZ,xCon,ic)
% Compute and write posterior standard deviation image of given contrast
% FORMAT SPM = spm_vb_contrasts(SPM,XYZ,xCon,ic)
%
% SPM - SPM data structure
% XYZ - voxel list
% xCon - contrast info
% ic - contrast number
%
% Get approximate posterior covariance for gi... |
2ed68b1a2c21b6ed188f69755151be8c26c9b830950b50ae2a7c8584cd3ebf63 | MATLAB | 4,404 | 155 | function [C,B,phi,varargout] = ir_circ_zeroed_reg(order, maskR, sparseR)
%function [C,B,phi,varargout] = ir_circ_zeroed_reg(order, maskR, sparseR)
% Input: order - order of regularizer
% maskR - [nx,ny] - mask of regularizer (changes C,B,and phiR)
% sparseR - binary flag for a sparse output (varargout) instead of Fa... |
585a600b83d2dfa103716c1853f5323744fb88fd1cef09af0e8c22969468c003 | MATLAB | 4,404 | 126 | function varargout = spm_update(update)
% Check (and install) SPM updates from the FIL server
% FORMAT spm_update
% This function will contact the FIL server, compare the version number of
% the updates with the one of the SPM installation currently in the MATLAB
% path and display the outcome.
%
% FORMAT spm_update(up... |
b34e74796e237da664e59ce19c08eed4f3f8488d01ca67cdb6e087d0985732b4 | MATLAB | 4,410 | 150 |
% create design matrix for GLME with criterion predictor
% clear
% close all ; clc
% paths
cd D:\Exp_noInstruction\
resOut = [pwd '\results\'];
outdir = [pwd, '\data\']
% load data
load([resOut,'Exp6_SDTscores.mat'])
% templates
conditionTemplate = categorical(repmat({'periodic','aper... |
88c4ec971e3ad9d33d89c68ad6467159e900cb9e5c0f4fda4733a031128b0157 | MATLAB | 4,411 | 122 | %APPEND_PDFS Appends/concatenates multiple PDF files
%
% Example:
% append_pdfs(output, input1, input2, ...)
% append_pdfs(output, input_list{:})
% append_pdfs test.pdf temp1.pdf temp2.pdf
%
% This function appends multiple PDF files to an existing PDF file, or
% concatenates them into a PDF file if the output fi... |
17ab7cd897a4836ebd22b6cb80bea5c33742cc5e9a075d090bc48907c45d6381 | MATLAB | 4,412 | 91 | function [DEF, stampFileName, dateFormated] = createStructFolder4PackageA( genPathPackage,...
packageName, packageRev, dateFormatedRev)
% Function to create the structure needed to save all the analysis package
% and generate the name of the stamp text file to identify the package used
% as input.
%
% Input
% gen... |
38939e1555555c19e822885231642b498d92379d0869577688e0b12e052d32cd | MATLAB | 4,413 | 89 | function [vessel_graph, varargout] = fun_graph_mask_to_graph(vessel_mask, vessel_image, opt)
% fun_graph_mask_to_graph is a wrap up function for converting the vessel
% mask to vessel graph.
% Input:
% vessel_image: 3D numerical array of vessel image stack
% vessel_mask: 3D logical array of the vessel mask,... |
3e9e8b0dfd43850761be7310471e93cd759d3ddcf87d614fcc1d6138a840bb8e | MATLAB | 4,414 | 142 |
%% create design matrix for GLME with criterion predictor
% clear
% close all ; clc
% paths
cd D:\Exp_withInstruction\
resOut = [pwd '\results\'];
outdir = [pwd, '\data\']
% load data
load([resOut,'Exp7_SDTscores.mat'])
% templates
conditionTemplate = categorical(repmat({'periodic','ape... |
9513d885d4e8b35319f33c17931f1f8cb824fb6d25b7bfcd7d1b250872803688 | MATLAB | 4,414 | 130 | function Experiment_Fiji = ReadFijiStitchingResults10x(pathname, folder, Experiment)
Experiment_Fiji = Experiment;
m = max(Experiment.Z_tile,Experiment.Z_tile*Experiment.NbSlices);
for zz = 1:m
MapIndex = squeeze(Experiment_Fiji.MapIndex_Tot(:,:,zz));
fid = fopen([pathname folder 'Mosaic_depth' sprintf... |
207f0c4032d02582b0cd1bb4f4bd4fd32317ea889edcd17d895c96a76c47b39d | MATLAB | 4,416 | 142 | function y = weighted_prctile(x,p,w,dim,issorted)
% WEIGHTED_PRCTILE Percentiles of a sample.
% Y = WEIGHTED_PRCTILE(X,P,W) returns percentiles of the values in X. P is a scalar
% or a vector of percent values. When X is a vector, Y is the same size
% as P, and Y(i) contains the P(i)-th percentile. When X is a... |
3a9f2ae5bb8219235a56324d9672eda175bb458845da4b55726c7856a425e4dc | MATLAB | 4,416 | 150 | % feldkamp_example.m
% Example of how to use feldkamp.m for cone-beam CT reconstruction
% Copyright 2004-8-28, Nicole Caparanis, Patty Laskowsky, Taka Masuda,
% and Jeff Fessler, University of Michigan
if ~isvar('cg'), printm 'cg: cone-beam CT geometry'
% see book chapter section (ask me) on cone-beam CT recon for no... |
63dfb4afe9a261110905695be8afd60888fefb89d0530bbbf19a7666f7eba9ed | MATLAB | 4,421 | 148 | 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... |
096f66bd5f48f9a4faba834fecee9b026ea59aad3a36c1e18fd1ab512295ee6f | MATLAB | 4,423 | 184 | function xs = epl_inc(x, Gb, yi, ci, ri, R, varargin)
%function xs = epl_inc(x, Gb, yi, ci, ri, R, [options])
%| Incremental optimization transfer version of EM algorithm for
%| penalized log-likelihood emission image reconstruction from Poisson data.
%| see eql_sps_os.m for arguments
%| in
%| Gb cell array or block... |
a3ccdb9f49b259cb1096556ae7633075d81aace3b76c3ded4711e0a612e2bd4e | MATLAB | 4,423 | 129 | function mip = spm_mip(Z,XYZ,M,units)
% SPM Maximum Intensity Projection
% FORMAT mip = spm_mip(Z,XYZ,M,units)
% Z - vector point list of SPM values for MIP
% XYZ - matrix of coordinates of points (mip coordinates)
% M - voxels - > mip matrix or size of voxels (mm)
% units - defining space [defaul... |
c0412af38d4c8d83621366e3d7361cbe7e18242da9ff134558fd35e2465b31e0 | MATLAB | 4,423 | 171 | function ob = Gtomo2_dscmex(arg1, varargin)
%function ob = Gtomo2_dscmex(sg, ig, options)
%function ob = Gtomo2_dscmex(file, options)
%function ob = Gtomo2_dscmex(arg_pairs, options)
%|
%| Tomographic system model based on aspire's wtfmex() routine, using its
%| dsc,proj and dsc,back commands for on-the-fly forward an... |
e0067f78fa344469e7af09d0e718e329a0cfd416655392e3c1221efb4a95a60d | MATLAB | 4,423 | 161 | function [K0,K1,K2,H1] = spm_kernels(varargin)
% returns global Volterra kernels for a MIMO Bilinear system
% FORMAT [K0,K1,K2] = spm_kernels(M,P,N,dt) - output kernels
% FORMAT [K0,K1,K2] = spm_kernels(M0,M1,N,dt) - state kernels
% FORMAT [K0,K1,K2] = spm_kernels(M0,M1,L1,N,dt) - output kern... |
ce7474bc563df697a676bc393acc0f6eb296317889ead54fdb9780d440eb3b48 | MATLAB | 4,426 | 179 | % eml_osem_example.m
%
% a complete example m-file illustrating E-ML-OSEM.
% showing faster "convergence" compared to E-ML-EM
%
% Copyright 1998-1, Jeff Fessler, University of Michigan
% generate data
if ~isvar('yi'), printm 'set up'
f.count = 1e6;
im clf, em_test_setup
f.clim = [0 6];
prompt
end
% ML-EM iterati... |
ffad49e4b60d00c71e153e4993b7e1734b9d61c289e4a50b7ddb4de4bc9f82b5 | MATLAB | 4,427 | 146 | % plot condition traces as a function of delay (either normalize or subtraction plots)
clear all
lock = 'onset'
%lock = 'response'
phase = 'encoding'
%phase = 'retrieval'
reg1_list = {'OFC' 'FRO' 'TEMP' 'CING' 'INS'}; %'
reg2_list = {'HC'};
addpath('/tmp/yassamri/iEEG/sandra/analysis_pipeline_final')
cd (['/tmp/... |
48048b444cd9812813acdfe9cf761baa38247e557d6f0bd3888ba14668cb5013 | MATLAB | 4,428 | 117 | function [fNum] = plotKNNFormulation(f_orco,fNum)
xGrid = -150:15:150;
yGrid = 0:1:55;
% use curved walk as an example
param = 2;
m = f_orco.model.params{param};
allSpk = m.allSpk;
alldSpk = m.alldSpk;
allDat = m.allDat;
% get the KNN parameters
ratio = m.KNN.ratio(1:2);% not counting time
K = m.KNN.K;... |
63760c4ed111313f34b79034cc2c3206a9e67ce570124ab12eaaa07d90f6baae | MATLAB | 4,428 | 117 | function [negloglikelihood] = Estimate_beta1_beta2_g2_g3_m3_sigma_nu(beta1, beta2, g2, g3, m3, sigma, nu, Input, config)
% Zilong Ji, UCL, 2022, zilong.ji@ucl.ac.uk
% Find the likelihood with parameters specified in the model function name
% Args (in common between all estimates functions):
% beta: decay factor for the... |
5e624910775337b6eb17766956161be8483bae093b259df79e12cf40ad4b6d8b | MATLAB | 4,430 | 99 | function fn_compile_einfo(SBJ,proc_id)
%% Compile ROI info from single electrodes into bipolar pairs
% Goes from smallest to largest (ELEC1-ELEC2, ELEC2-ELEC3, etc.)
% Pairs are drawn from preprocessed data labels
%
% new_labels = cell array of strings with combined labels
% can be used with ft_preprocessing as c... |
2caba52964b72a4f4dd63ad1f042fb955f1781c6539ff7a512f673eddbab0ce7 | MATLAB | 4,431 | 169 | %
clc; close all; clear;
%% OPTIONS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% TIME PARAMETERS:
t0 = 0; % Initial Time
tb = 20000; % Final Time for Bifurcation
% INITIAL CONDITIONS:
u0 = [35000; % (C) Tumor Cells
0; % (T) T-Cells
0]; % (M) MDSCs... |
fff012de6d158cf3896175a4c450e632f08c05aea0cbb14c0dadc6f4ecbcd75d | MATLAB | 4,432 | 129 | function [acc_rand] = RandomForest_HRV_chance(data, numrand, train1, train2, test1, test2)
% This function performs a Random Forest classification using arbitrary
% patients label. This function performs several classifications to obtain a
% chance accuracy distribution for unbalanced datasets. This function uses
% Ran... |
05e3c160ba5b847e86d9ed0503e9994cae385cbf07b830c9891c6668bbea8367 | MATLAB | 4,436 | 129 | function [] = plotTimeInsideLightZoneVsBorderRegion(genAll,meta)
close all
%radialProb = cell(numel(genAll),1);
percentTimeSpentInA_before = cell(numel(genAll),1);
percentTimeSpentInA_during = cell(numel(genAll),1);
ttInA = @(x) sum(x<=1);
ttInB = @(x) sum(x>1 & x<=1.3);
for gen = 1:numel(genAll)
load(strcat(... |
d800dc7875d963d55704e95544bbd33e4d6a434edd0b32c5848e298ef82e3b89 | MATLAB | 4,436 | 224 | function out = jf(varargin)
%function out = jf(varargin)
%| various personalization routines
%| 'mv var_old var_new'
%| 'ncore' # of cores this machine has
%| add optional 2nd argument to over-ride, e.g., jf('ncore', 4)
%| 'whos'
%| 'clf'
%| 'nobar' preclude toolbar and menubar from figures to render faster!
%| 'nome... |
5cf00e37ae66f5d1fbf8bd3a84e27cae2d7f3f8f724d130b18b397d604e38d7b | MATLAB | 4,439 | 119 | function cnd = cndDownsample(cnd,downFs)
%CNDDOWNSAMPLE Downsamples the neural data (e.g., EEG) in CND format.
% CND = CNDDOWNSAMPLE(CND,TYPE) downsamples the contant of a CND data
% structure. For time-series of impulses (e.g., word-onset vector)
% the function does its best to preserve all impulses, i... |
32b1ccd8f5f693ea9a1f1c244e1ede36a26d7e3c2aa55686797c277a8952411f | MATLAB | 4,444 | 97 | function [x_pair] = fitRogCrf(spikes,cont,mu_eta,cov_eta,tuning,opts)
arguments
spikes (2,:,:);
cont (1,:);
mu_eta (2,1);
cov_eta (2,2);
tuning function_handle = @contrastResponse;
opts optim.options.Fmincon = optimoptions(@fmincon,...
'Algorit... |
e00a78d5375aa128a581eb2dcd1b2a0e2de61013de67c38be4185817f492c135 | MATLAB | 4,445 | 176 | function plot_fig_1c(path)
% load data
tbl = readtable(fullfile(path.data, 'SourceData.xlsx'), 'sheet', 'Fig_1c');
%% Plot Reaction Time
avg_RT_0 = tbl.Var1(2:end);
avg_RT_25 = tbl.Var2(2:end);
avg_RT_75 = tbl.Var3(2:end);
% create cell array
plotRT = {avg_RT_0, avg_RT_25, avg_RT_75}';
% colors use for plotting
... |
f4a61e85f2ee41180d7a47c1e6eb7c9b3190b4fe609c5c623f345892a6d37ae2 | MATLAB | 4,448 | 106 | %% Find a bipolar colormap, linear in grayscale, close to a template map.
%%
% Linearity in gray is important for a colormap to look reasonable when
% printed in grayscale ("black and white"), but note that precise linearity
% depends on the particular (non-unique) choice for conversion from RGB
% values to grayscal... |
bba66d60be0943c59ef8e647fa2bca3af2b2a9fdb6f3e7258c58357593a2e6d7 | MATLAB | 4,450 | 128 | function make_figure8(plotVariables,options)
glmFlag = 'jumps_absolute';
% 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 taken out
csdFlag = 0; % 1 for csd transformed data
if csdFlag %temporary fix for bug in first subjects' CSD transform
... |
c5370f11897c1438b87866b42625ade745f55d2be53ab3ab6e317765f862a683 | MATLAB | 4,450 | 158 | function [Cxx,Cxy,folds] = olscovmat(x,y,lags,type,zeropad,verbose)
%OLSCOVMAT Covariance matrices for ordinary least squares estimation.
% [CXX,CXY] = OLSCOVMAT(X,Y,LAGS) returns the covariance matrices for
% ordinary least squares (OLS) estimation using time-lagged features of
% X. X and Y are matrices or cell... |
606fb051c825d86e46b843905b1d7a3b6df456340e07fd7cd88a97b184dff23b | MATLAB | 4,452 | 98 | function pipeline_03_behavior(study_info)
pipeline='NEARICA_behav';
% behavior
exe_df=readtable(fullfile(study_info.data_dir,'behavior_exe.csv'));
obs_df=readtable(fullfile(study_info.data_dir,'behavior_obs.csv'));
% Number of subjects
n_subjects=size(study_info.participant_info,1);
epoch_types={'OBM','LOBS','FTGO'... |
9eab73bab3d9b1d2bb26ea15fe157215ddcd2c65edfb072f4061dd8f9c9501fc | MATLAB | 4,452 | 64 | function sensors = initSensors(cgmModel, model, environment)
% function initSensors(cgmModel, model, environment)
% Initializes the 'sensors' core variable.
%
% Inputs:
% - cgmModel: a vector of characters that specifies the glucose;
% - model: a structure that contains general parameters of the
% physiological ... |
223efe6501d01067d452b27d903962f7ea6be30f48ee8babbc6bda114332b72a | MATLAB | 4,453 | 207 | function [SignificantVariables, clusters,clustersize,StatMapPermPV] = permutation_cluster_1sample_alld(data, nperm, cluster_th, significance_th,tail,StatMapPermPV)
% function [SignificantVariables, clusters,clustersize,StatMapPermPV] = permutation_cluster_1sample_alld(data, nperm, cluster_th, significance_th,tail,S... |
e52ca24f6a58114797aaf3669b24b400fff9f99521e8cc35464ec8175e1ba5e7 | MATLAB | 4,453 | 164 | function hdr = load_analyze_hdr(hdrfile)
% hdr = load_analyze_hdr(hdrfile)
%
% hdrfile is the header file (eg, f001.hdr) or a basename (eg, f001).
%
% hdr.dime.dim(1) = number dims
% hdr.dime.dim(2) = number of items in first dim
% hdr.dime.dim(3) = number of items in second dim
% ...
%
% hdr.dime.datatype:
% 0 unk... |
99f69d792f784882666b75ab5074c2a4926bfc3e6e303766f0c66c94bb7588fa | MATLAB | 4,456 | 92 | function input_graph = fun_graph_relabel(input_graph)
% fun_graph_relabel computes the labels for the links and nodes, update all
% graph structure after graph pruning.
% Input:
% input_graph: structure created by fun_skeleton_to_graph. Required
% field:
% num.skeleton_voxel need to be updated.
% ... |
f912754397c0263937da80ac88aa4dda2b03be30064523b81869b67ddcca8ec5 | MATLAB | 4,458 | 97 | folder='/projectnb2/npbssmic/ns/Ann_NC/';
datapath=strcat(folder,'dist_corrected/');
% add subfunctions for the script. Change directory if not running on BU SCC
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addpath('/projectnb/npbssmic/s/Matlab_... |
828549f93ce25834725a71672053086d255bf46c8377410ee6e9fa7948402bb4 | MATLAB | 4,459 | 129 |
% initialize Psychtoolbox
AssertOpenGL;
PsychDefaultSetup(2);
if IsOctave
page_screen_output(0)
end
% INITIALIZE SCREEN
% =================
screenNumber = max(Screen('Screens'));
% Open a window for display
if isunix && strcmp(getenv('USER'), 'meyniel') % for my Linux HP
[w_px, h_px] = Screen('WindowSize',... |
d97051364fe118675c3553d433763930a3a31d0f46e25221677732ecaa601867 | MATLAB | 4,460 | 213 | %% - PLOT FIGURES - %%
% This script plots all figures found in the manuscript "Ramping dynamics and theta oscillations
% reflect dissociable signatures during rule-guided human behavior".
% All necessary data can be found within the subfolder "source_data".
% Data exceptions
%
% Fig. 1a: This figure is an illustr... |
beb110d3004e21964e4e1556134ba7294ff6f59bc87e67ddb4dc0abbae754837 | MATLAB | 4,464 | 100 | function [outSegments,outActualWidth,outActualInterval] = IPEMGenerateFrameBasedSegments(varargin)
% Usage:
% [outSegments,outActualWidth,outActualInterval] = ...
% IPEMGenerateFrameBasedSegments(inSignalOrDuration,inSampleFreq,...
% inFrameWidth,inFrameInterval,...
% ... |
1b818a8d9a643645c5f37939d0d64f56d32a590d697a630604dcfcf5bb0302f9 | MATLAB | 4,465 | 112 | function [] = send2ClientPanel(varargin)
% function [] = send2ClientPanel(varargin)
%
% Use this function to send information from an experimental setup to a
% network computer. Remote computer uses a clientPanel object to monitor
% the incoming data. Refer to clientPanel documentation for a description
% of the data ... |
32b7c6489ef9262aca6a9ec544c7b7406ad0c9f58e193ce907d16e856a022dd8 | MATLAB | 4,465 | 161 | function [b, d, f, z, mm] = compute_rf_spsp_mgh(kp,rfp,gz,kz,kf)
%function [b, d, f, z, mm] = compute_rf_spsp_mgh(kp,rfp,gz,kz,kf)
%Function that computes the complex-valued SPSP RF pulse waveform,
%using parameters specified in structure rfp.
%Inputs:
%kp: k-space trajectory parameter structure, generated by kparamet... |
e3244593e87fa46a51fd69eab148ed05c24fce7710265901638584178ccb32be | MATLAB | 4,465 | 96 | function [] = BackGroundSubtraction()
addpath([pwd '\matlab']);
addpath([pwd '\util']);
clear
s=dir('Videos/*video.ufmf');
filelist={s.name};
for i = 1:length(filelist)
filename = filelist{i};
[readframe,frames,~,headerinfo] = get_readframe_fcn(filename);
% create background
newvidname = ['Videos/... |
02d6ff026de9365fa597baa022dd45f5304ae21ff1ef5f48ae6d4537d300ea66 | MATLAB | 4,467 | 118 | function [] = plotTime2FirstStateTransition(f_orco,plotFig)
% calculate smoothed change in firing rate
dF = f_orco.calcDeltaFR;%gradient(f_orco.spk);
dF(:,end-1:end) = repmat(dF(:,end-2),1,2);
thresh =50;
crossingtype = 'exit';
[~,transitionProb_exit,transProbRand_exit,rast_exit,~] = getExitTrajectory(f_orco,crossingt... |
9de9183b45f6a604546a3e75e2a6ecf8f0d520bf26fba2077e01c45ef7ebe4be | MATLAB | 4,467 | 160 | function [C,B,phi,varargout] = ir_circ_zeroed_reg_3d(order, maskR, sparseR)
%function [C,B,phi,varargout] = ir_circ_zeroed_reg_3d(order, maskR, sparseR)
% Input: order - order of regularizer
% maskR - [nx,ny] - mask of regularizer (changes C,B,and phiR)
% sparseR - binary flag for a sparse output (varargout) instead... |
d0df7a23868184bf7a8d0506de16db8eb440515b2165d3abc443f83ed12f028c | MATLAB | 4,467 | 152 | function weights = inspect_map_weights_update(allimg,currentweights,Fcomp,Kalpha,gradechoinv,options)
%
% Weight update step for inspect continuous mapping version.
% Given canonical spectra, estimates voxelwise spectral weightings.
% INPUTS:
%
% allimg - image data in voxelwise form, typically output from
% inspect... |
a159ac22d86b17c17be1a73c61c9c1b54d0b260d93dda9a775f875d2d6e055f8 | MATLAB | 4,468 | 152 | function Train_Batch(k,Coding,DealyTime)
setGlobalOpts()
global Opts
alpha = Opts.alpha;
beta = Opts.beta;
gamma = Opts.gamma;
C_M1 = Opts.C_M1;
C_V = Opts.C_V;
C_S1 = Opts.C_S1;
C_EBA = Opts.C_EBA;
C_TPJ = Opts.C_TPJ;
C_AI = Opts.C_AI;
N = size(Coding,2);
MoveNum = Opts.MoveNum;
Time = Opts.Time;
Con... |
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