sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4ec9b04a9275138d478acecb5dc211bcf1a0dd0bb3e2dcb8312c6f2561b93862 | MATLAB | 2,428 | 66 |
%%%% create a random network
nodes=90;
graph=rand(nodes,nodes);
%%%%%%% ABSOLUTE THRESHOLD
thr=0.5;
[binary weighted1]= threshold_abs(graph, thr);
%%%%%%% PROPORTIONAL THRESHOLD
p=0.2; % keep the 20% of the strongest connections
[binary weighted2] = threshold_pro(graph, p);
%%%%%%%% MEAN DEGREE
... |
d54bdc884b0a481169bd52ad9ff52c17d3dc88ddd08a7640fe723d1818e99135 | MATLAB | 2,428 | 91 | function s_cap = sradius_of_cap(dim, area)
%SRADIUS_OF_CAP Spherical radius of spherical cap of given area
%
%Syntax
% s_cap = sradius_of_cap(dim, area);
%
%Description
% S_CAP = SRADIUS_OF_CAP(dim, AREA) sets S_CAP to be the spherical radius of
% an S^dim spherical cap of area AREA.
%
% The argument dim must be a pos... |
e597558970a56c3c8d4a538238d4ebf4491542b700c12c0539c8d1c1e9ea4af7 | MATLAB | 2,428 | 75 | function [LTouchfromPeg,StdLTouchTiming,RTouchfromPeg,StdRTouchTiming,MeanStdTouch,StdTouchfromPeg]=KolmogorovTouch2
%Kolmogorov-Smirnov
% KolmogorovTouch(LpegTouchCell)
%[NXy[XÉLpegTouchCellÈÇðu¢Ä¨«AR}hEChE©ç®©·B
% TouchfromPegÍPeg©çÌ^b`ÌÔA»ê¼ê¶EÅ̽Ï
% St... |
1bccc9d56ee9abf3dd0d290a414bc7e6c60aa9b1a31f56bc3e361ff2ba07ff7d | MATLAB | 2,430 | 90 | function [err,f1,f2] = nufft2_err_mm(om, N1, N2, J1, J2, K1, K2, alpha, beta)
%function [err,f1,f2] = nufft2_err_mm(om, N1, N2, J1, J2, K1, K2, alpha, beta)
% Compute worst-case error for each input frequency for min-max 2D NUFFT.
% in:
% om [M,2] digital frequency omega in radians
% N1,N2 signal length
% J1,J2 # of... |
6a460480d1e57dc08f4fcc9d11a8029c2d5721e9f013a36cf35c46bb1db26991 | MATLAB | 2,430 | 70 | function [ acc,ae_dim,weight_cat ] = get_ae_decoding_dim( p,t_pool_av,t_pool_err,n_rep,n_tr,shuffle_control,tone_idx)
% - function for decoding ae based on collection of a and e trials
% - trials might be expressed in subspaces / nullspaces
% - decoding is repeated for multiple iterations, each iterati... |
59d4a8d5d715e60d80173886a2e8341c9d2c3af901328dbdc5a74eb0f7b4b40b | MATLAB | 2,431 | 79 | % This code is just a front-end to source separation algorithms.
% Purpose:
% 1) generate synthetic data
% 2) call some source separation algorithm
% 3) display the results
% The data are CM (constant modulus signals and QAM4.
% The mixing matrix is randomly generated.
% Comments, bug reports, info requests are apprec... |
53f69202ad4061fada2637735b5be84ed55466456b7c846330c07f73e147a2cf | MATLAB | 2,432 | 84 | function [X,Y] = Generate_DataSet(Frame_Half_Size)
Save_Sample_As_Image = 0;
D = 'D:\Omer\Neuronalizer\Resources\CNN\Input_Samples';
BW_Min_Neuron_Pixels = 20; % 5.
DataSet_MaxSize = 10^6;
Num_Per_Image = 10000; % [5000,25000].
X = zeros(2*Frame_Half_Size+1,2*Frame_Half_Size+1,1,DataSet_MaxSize);
Y = zeros... |
61afb1f70528c2171b5c9a1ab6f60743f226ae9fffa166627d4eb5b242bed37e | MATLAB | 2,435 | 57 | function success = exportQualityScores(obj, zeroIndex, fGui)
%EXPORTQUALITYSCORES Export cluster quality scores to CSV
if nargin < 2
zeroIndex = 0;
end
if nargin < 3
fGui = 0;
end
ID = (1:obj.nClusters)';
SNR = obj.unitSNR(:);
centerSite = obj.clusterSites(:) - double(ze... |
7626d8ec097fed437b316be2dd195f8a2e727a602a93b3066343a273fccb23f7 | MATLAB | 2,435 | 87 | function [BEST,EST,CI,p] = onesampb(x,nboot,alpha,est,q,mu)
% function [BEST,EST,CI,p] = onesampb(x,nboot,alpha,est,q,mu)
%
% Compute a percentile bootstrap confidence interval
%
% INPUTS:
% x (vector)
% nboot (resamples, default 1000)
% alpha (default 5%)
% est (estimator, de... |
4285b5eeaa2df786680786d68530fa8a72d62d0ae7346ca83683f3e9aef59ed9 | MATLAB | 2,437 | 78 | function [ARCoefsKF , ARCoefsKS] = time_variant_ar_kalman(data, order, x0, q, R, p0, alpha)
% time_variant_ar_kalman - Time variant auto-regressive (AR) model estimated by Kalman Filter and Kalman Smoother
%
% Syntax: [ARCoefsKF , ARCoefsKS] = time_variant_ar_kalman(data, order, x0, q, R, p0, alpha)
%
% Inputs:
%... |
8e2a1da9e8ae24fbb16ea1073a02ff8d6e6cda75d4c872f7a54f9a79e3a3b91c | MATLAB | 2,438 | 57 | function [data] = processOpto (data, params)
%Created By: Anya Krok
%Created On: 18 June 2019
%Description: T-Lab specific code for processing optogenetic stimulation
%signal into general T-Lab data structure
%Updated On: 31 October 2019 - added new filter+downsampling
%Updated On: 29 April 2021 - added sigEdge
... |
3afd8e4956d7c8a1297664e64cc5b98456b6c5995e8364b7af2c592a0e0c9ed7 | MATLAB | 2,439 | 67 | function Trials = trial_latencies(Trials, EEGPath, Triggers)
% for all trials, get information of stim time and response time (if
% available). Used for finding eyes closed, bursts, etc.
disp('Getting trial latencies from EEG')
Participants = unique(Trials.Participant);
Sessions = unique(Trials.Session);
Trials.Stim... |
c0bd08c788b742a477901d1bb38d977ea1473e58ae00eb44600c7ecb164176b2 | MATLAB | 2,442 | 81 | function [AUC1, AUC2, meanTIMESERIES1, meanTIMESERIES2, maxTIMES1, maxTIMES2, Pvalues] = notvisualizeBOLDresponses2(BOLDresponse1, BOLDresponse2, ROIname, resultpath, colors, type, stim)
% This program is intended to visualize and calculate the BOLD signal.
%
% input:
% BOLDresponse1
% BOLDresponse2
% ROIname
% ... |
d2377fa217d83b2670017a911b3d16ab7bcc01b38314af1e37a59d574a49e676 | MATLAB | 2,444 | 118 | % Costruzione del DataMatrix per la 3-way PCA
dc = questdlg ('You must create the datamatrix to do the 3-way PCA. Did you create it?');
if dc(1:2) == 'No'
creation;
end;
olddir = pwd; %così sto in NE.MO.
mkdir(sprintf('%s\\PLOT', olddir'));
pathname1 = sprintf('%s\\PLOT', olddir');
mkdir(sprintf('%s\\P_... |
de8dc8178b63cd9062f8c4aa49d4f5192af46796a7a05d3c7a38e595f7b9f6d0 | MATLAB | 2,445 | 62 | % Generate Table of Features for Merged and NO Merged Cells
% Input
% Raster w/dimension: Cells x Frames
% Type of Cells: Merged or No Merged
% Output
% CSV: File with all the Features
function DATApdf=gen_feat_table_merged(R,fs,typecells,Experiment,Names_Conditions)
%% GET FEATURES
% [~,~]=size(R);
[Descriptive,... |
965a536849149dd58b99574207e1e7897d9ad6647d0c15ed53b365e1b268bcaf | MATLAB | 2,448 | 44 | classdef DensityPeakClustering < handle
%DENSITYPEAKCLUSTERING Legacy class
properties (Hidden, SetAccess=protected, SetObservable)
sRes; % sorting results
dRes; % detection results
end
properties (SetAccess=private, SetObservable)
clusterCenters; ... |
b4ad53e086fb2a8ca6e5194f76d07067f95e37fa43f845324736ed04430153b7 | MATLAB | 2,448 | 44 | function hFigWav = plotFigWav(hFigWav, hClust, maxAmp, channel_idx, showSubset)
%PLOTFIGWAV Plot the main view (FigWav)
if nargin < 5
if ~isfield(hFigWav.figData, 'showSubset')
hFigWav.figData.showSubset = 1:hClust.nClusters;
end
showSubset = hFigWav.figData.showSubset;
... |
fa9164390e306deee0a01d923d53dcd3abf5d99b2bf94054bbe7561aa75ec1ae | MATLAB | 2,452 | 84 | % rotate (and flip ICs)
% varargin: Mirind: true for flip, false for not flip
% LDEequv contains SCI
function [LDEequvUse] = HCRot(LDEequv,rotID,N_HCOut,NPixX,NPixY, varargin)
if ~isempty(varargin)
Mirind = varargin{1};
else
Mirind = false;
end
if Mirind
flipDim = mod(rotID,2); %1 for col 2 ofr row
if ... |
274b729ae7d38cf4e1114db2fe108861e3680be59db119408d33bf06fbe26801 | MATLAB | 2,453 | 50 | % *************************************************************************
% * This code calculates and illustrates the probability of signal *
% * detectability versus required SNR by using the probability of false *
% * alarm (represented in [2]). *
% * >>> Refer to... |
bc1435d9b1ac6663aacdb3375b0b0d55b1a720eec7945e59aa4193bb4ccdd702 | MATLAB | 2,453 | 58 | %Authors: Simon Wadle, 2019-2023
%function uses dF/F activity from each cell and analyzes baseline activity
%between days to exclude cells being not atice at certain days
root_path = 'directory';
smooth_flag = 1;
all_mat_files = dir([root_path, '\**\complete_data_Fall.mat']);
fprintf('file %3d of %3d', 1, siz... |
ef7b8f40a98503b83aa523cdbc9b115f881691de7caacbf0f8d49fc0cc03c947 | MATLAB | 2,459 | 59 | function SpikeFormfigSave20200129
%SpikeFormÌFigÛ¶p
% ScNumbersÍS×EH4×EÌêÍ3D
% CellNumbersÍ×EÔA1,2,3,4...A½¾µA0à éBÇÌ×EÉàYµÈ¢L^iHj
% DataPointsÌ1³ÚÍ32_ÌdÊA2³ÚÍeg[hÌ`lA3³ÚÍ»ê¼êÌXpCNiModeArrayÅwèµ½àÌj
clear all;c... |
a13523c06e3a8729b75630036b669d1903c6a2480353fb845f23bd7526297ec5 | MATLAB | 2,462 | 51 | % function [Ion1,Vals1] = InRect(Mat1,Rxy)
function Vals1 = InRect(Mat1,Rxy)
% TODO:
% flipud. the y-axis is now upside-down.
% maybe I can use the sign(+\-) of the distance and check only 2 perpendicular side (instead of 4).
% Scale 'S' based of the # of pixels in the smallest bounding matrix.
% Make sure t... |
acf672f04c38ab31960eb1796e6b3a2418a17e4220dfaf1fb01a926adbd91c54 | MATLAB | 2,462 | 75 | function reset_results(app,res_data,res_derived)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
if res_data
app.data = [];
app.comments = [];
app.settings = struct('interval', [nan, nan; nan, nan],...
'channel_sheet', [nan, nan],...
... |
e029d0b701ff6f4b4ade504ebccee34f50d8df1bc9849f85fc1eabf89445a2c1 | MATLAB | 2,464 | 37 | %----------------------------------------------------------------------
%BrainAmpConverter v1.2 defaults
%EJH 2011-15
%----------------------------------------------------------------------
%Calibration setting: How many microVolts (the measured unit) corresponds
%to 1 microSiemens? When calibration has not been done ... |
ebd5ff32ac302ad080d8ff19a0dcd958e5d3ddc968f3d7760faa1d9268d24a9a | MATLAB | 2,464 | 80 | function [x_SAVE,y_SAVE,eb_SAVE] = eventwindowPlotFormatV2(DataAVG,Dts,varnamesDATA,setupParam,allTrials)
% Setup group info (if there are groups)
allTrialsID = allTrials.ID;
if setupParam.CompareGroups == 1
% GroupParam = TrialParam.GroupParam;
groupnames1 = fieldnames(allTrialsID);
groupidx = zeros(1,nu... |
0a8336d27b5682b32c2c051f09b7eb46b9d08429c6e9e7522fdc0a3c6a9f124e | MATLAB | 2,466 | 73 |
%Please cited this Toolbox as:
%Dimitriadis SI, Laskaris NA, Tsirka V, Vourkas V, Micheloyannis S, Fotopoulos S.
%Tracking brain dynamics via time-dependent network analysis.
%Journal of Neuroscience Methods Volume 193, Issue 1, 30 October 2010, Pages 145-155
%CAUTION:oNLY OUR APPROACH BASED ON DIJKSTRA'S ALG... |
9a7d2b8a44a0dccab0935cef8db5ccb2cf9756bdd8322cf4d97c4c8a7e8f3fae | MATLAB | 2,466 | 62 | function MakeMultimerProb20160830
%½èÅ100000ñÆ©½ÊÌärðµÄA»ÌyAªðìém¦ðZo·éí@
% %züÌû@@C
% %ÝF¯ÌñÅwè·éêAC=0A×EyA ½èÌñðMatchingÅwèB
% %ðwè·éêAC=1A{ÍConnectionsÅwèB½dÓð·×ÄJEg·éB
% %×EÌð... |
2af3cc032198654141c1349a8caefc20e33f60a137c4e42c62165c6591686653 | MATLAB | 2,468 | 77 | clear all
% this script contains code to reproduce Figure S5a-c
%% load data
% drag and drop corresponding file (S6 Data)
%% data content description
% weight contains the raw weight of animals (grams) over 10 days after
% surgery
% animal id contains the animal identifier of either COMBO or Ctrl
... |
daac89697944b1c7888204af8c300ea6b306525e04955ff417702dfadeab7a6d | MATLAB | 2,468 | 113 | %% activation function
V_max = 130/3; % mV
V_min = 3.2/3; % mV
thetarinf = 40; % mV
sigmarinf = 2.5; % mV
%% B34
% capacitance of B34
Cm_B34 = 0.01; % uF
% leaky conductance of B34
gL_B34 = 0.1; % uS
RL_B34 = 0; % uS
% reversal potential of the leaky channel of B34
EL_B34 = -60; % mV
% sodium currents to B34
% ma... |
e22ef98141772ddf542afd3c9f88c8e9fbc2b839b09a46d73d574fb1f0d46b5f | MATLAB | 2,469 | 52 | function W = Adjust_Rect_Width_Rot(Workspace1,Step_Parameters,Im_Rows,Im_Cols)
% Description:
% This function detects the local apparent width of the neuron.
% Calling functions: Find_Cell_Body, Add_CB_Branch, Trace1.
% Input:
% Workspace1 and Step_Parameters: structures containing general and step-specific p... |
45408ab30581c3c08ee66c16341504d2b468ee76dd7e3c1772cf7e48f2de4dbc | MATLAB | 2,471 | 73 | function data = processMov(data,params)
%Process Behavior
%
% [data] = processMov(data,params)
%
% Description: This function is designed to convert rotary encoder information into velocity
% traces and quickly find onsets. The parameters for the analysis are found in the params
% structure, which is cre... |
d9cd0f529ea9ac231e81a3f2b83303504132a10f51b6b564d2fd8ab1d61256fd | MATLAB | 2,472 | 74 | classdef Recording < jrclust.interfaces.RawRecording
%RECORDING Model of a single SpikeGLX recording
%% SPIKEGLX-SPECIFIC PROPERTIES
properties (SetAccess=protected, SetObservable, Transient)
rawData; % raw data in memmapped form
end
properties (SetAccess=protected, SetObservable)
... |
264bb2c2d4d5b3dd8687a5da18eed129068a419531932b55c096a54cfe97d550 | MATLAB | 2,473 | 67 | function [Training_Frames,Training_Classes] = Generate_Training_Set_XY(Frame_Half_Size,BG_Samples_Num)
D = 2*Frame_Half_Size + 1;
TrainingSet_MaxSize = 50*10^6;
TrainingSet_MaxSize0 = 10^6;
Min_Num_of_Neuron_Pixels = 0;
Training_Frames = zeros(D,D,1,TrainingSet_MaxSize);
Training_Classes = zeros(2,TrainingS... |
42420b1324601c6d872125430855e2453dbbccecc1ac46e6d9ea7ca14731c689 | MATLAB | 2,474 | 80 | function [AUC1, AUC2, meanTIMESERIES1, meanTIMESERIES2, maxTIMES1, maxTIMES2, Pvalues] = notvisualizeBOLDresponses(BOLDresponse1, BOLDresponse2, ROIname, resultpath, colors, type, stim)
% This program is intended to visualize and calculate the BOLD signal.
%
% input:
% BOLDresponse1
% BOLDresponse2
% ROIname
% ... |
6edea969877d6400e8ce14714af96d82bb637fa54e8461285c5d6ae3505d51e0 | MATLAB | 2,476 | 59 | % *************************************************************************
% * Test program for Calculating Phase Locking Value (PLV) matrix *
% * (Pairwise) using raw signals. Refer to the User Guide for further *
% * details. *
% **************... |
8b4709c3253e536748a30b89af216c17d6b98cd125ea643115516e3354dc0e37 | MATLAB | 2,477 | 52 | function [baseline, bl1, bl2, bl3] = baseline_filter(x_raw, baseline_removal_method, params)
% baseline_filter - Different approaches for baseline wander estimation using OSET functions.
%
% Syntax: baseline = baseline_filter(x_raw, baseline_removal_method, params)
%
% Inputs:
% x_raw: Raw input signal (channels x ti... |
2268151ab06809be9aefacfe112416b4703852012a36b0b8ead36b5107141593 | MATLAB | 2,479 | 63 | function f = ifm_correlator(x, f0, BW, tau)
% ifm_correlator - An instantaneous frequency estimator based on lagged correlations
%
% Syntax: f = ifm_correlator(x, f0, BW, tau)
%
% Inputs:
% x: input signal as a row vector
% f0: initial estimate of the frequency
% BW: bandwidth for low-pass filtering
% tau: time... |
0a2fa040db484b085b4edfd6459199872c06f43a443980660174da83c50796a6 | MATLAB | 2,480 | 80 | % Function to get Raster choosing Method:
% 1: Driver Seignal by Sparse Deconvolution
% 2: Oopsi algorithm
% 3: Derivative method
% Input
% Method: [1,2,3]->{Sparse,oopsi,derivative}
% VARARGIN: according to the method
% Mode 1: Sparse Deconvolution
% Driver Signal
% ActiveNeurons-> Raster Row to Modify
% ... |
9f2238e553b39b735bef0f313453cfb0cbaf557b810602b9b82e55f7b94c976e | MATLAB | 2,480 | 83 | function [plotKey, YOffsets] = multiplot(obj, plotKey, scale, XData, YData, YOffsets, doScatter)
% Create (nargin > 2) or rescale (nargin <= 2) a multi-line plot
% TODO: separate these (presumably multiple plots are passed in somewhere)
if nargin <= 2 % rescale
obj.rescalePlot(plotKey, scale);
... |
1948dd64e9a59c753bf5d4aed0a5fede321c491a8597c2c876ecb9c25f68cdcf | MATLAB | 2,482 | 84 | new_folder = [];
max_memo_GB = [];
% This code requires the file read_Intan_RHD2000_file.m which is provided
% on the Intan Technologies web site.
% new_folder: output folder with the parsed channels and metadata.
% If it doen't exist or is [], it will be 'wc_data'.
% max_memo_GB is an idea of the number of GB allocat... |
5aeb690d8601e1ea6bdce22d226c37ad4b22d0643214e212c16d0c32a632465d | MATLAB | 2,483 | 54 | function AllWaterFig20180703(CrossCoWonCellClean,CrossCoWoffCellClean,NumWonC,NumWoffC,SubP,WORD,m)%,WaterFigA)
global OnSize bin fname SpikeName CleanInterval FigureSave
%CleanWater
% for m=1:OnSize(2)
OnAll=[];OffAll=[];
for n=1:OnSize(1)
OnAll=[OnAll; CrossCoWonCellClean{n,m}];
O... |
852b71b5fc2afa6317efc3c50d2d56a55b4af6ec17bdab3d1e02f80c67a5e64d | MATLAB | 2,483 | 92 | %% compare accs of time-independent decoder (evaluated per timestep) and time-dependent decoders
[cols,alpha] = chooseColors;
ind_col = [44,162,95]/255;
figure('Position',[100 100 300 300])
hold on
% set lims and labels
xlim([0 21])
set(gca,'XTick',[0 5 10 15 20])
set(gca,'XTickLabel',[-3 -2 -1 0 1])
xlabel('time (s... |
bf2d6b80a4954235861eb84fef556b06912831b142d649dea035db1815bd43f5 | MATLAB | 2,484 | 105 | function [list_k_cores]=k_core_decomposition(binary,k)
%[1]Alvarez-Hamelin (2006) Large scale networks fingerprinting and
%visualization using the k-core decomposition
%[2]Hagmann et al.,"Mapping the Structural Core of Human Cerebral Cortex",
%Plos Biology, 2008
%a technique that first introduced for the visua... |
635a13b26bebd7486ed2e75e5d52b82c1c3c553a78b7a52f9ba96ec0226225c5 | MATLAB | 2,485 | 69 | function [index, rank] = sqi_negentropy(x, varargin)
% sqi_negentropy - Signal quality index based on negentropy estimation.
%
% Usage:
% [index, rank] = sqi_negentropy(x, ranking_mode)
%
% Inputs:
% x: Input signal matrix with dimensions [L1, L2]
% ranking_mode: Optional argument for sorting mode ('ascen... |
8dc39e7a48c676c7e62869c3f035b90cbbc9c79447b132f6ef597a0150e2be22 | MATLAB | 2,485 | 82 | %% Example run for jointly analyzing two sessions from one subject
% go through the sections step by step
%% set general parameters and create folder structure
% create structure p, which holds all parameters. Parameters are
% initialized as set in params.m, some of them are overwritten in this script
clear
p = pa... |
ef1b0bf7e82146197dbc05c4b584c8ae633f091c6e45c657c3ad4a6580090876 | MATLAB | 2,485 | 74 | function file_path_out = convert_mat_file(file_path_in)
dot_idx = find (char(file_path_in)=='.',1,'last');
file_path_out = [file_path_in(1:dot_idx-1) '_tmp.mat' ];
file_in = load(file_path_in);
file_meta.n_records = size(file_in.datastart,2);
file_meta.n_channels = size(file_in.datastart,1);
file_version = 1;
for i = ... |
6140efc3f4d86f6b0c24c82a70b89b0da1a03844e6d169f21b2b2b397805710e | MATLAB | 2,487 | 63 | function g = plotFeatureSpace(X,label,centroid)
% plotFeatureSpace produces a scatter plot of the feature space with the
% parameters used to figure 7 in the manuscript.
%
% g = plotFeatureSpace(X,label,centroid) takes as input
% an Nx3 vector containing the features and an Nx1 vector containing the
% lab... |
2f739662d09ad3131d43edbe70574371f646ebac2df210cae6e609670ed52125 | MATLAB | 2,488 | 98 | function [binary threshold globalcosteffmax costmax ef]=threshold_global_cost_efficiency_bd(w,th)
%define the threshold in a a network as the max value of global cost efficiency versus cost
%adopted from Bassett & Bullmore Cognitive fitness of COST EFFICIENCT BRAIN
%FUNCTIONAL NETWORKS PNAS, 2009
%needs efficie... |
4ca1c308eb0075d07e905dc7f8eae5d755b8a81700503f6453fbe4fd1de8915d | MATLAB | 2,490 | 108 | function [f_METAB_inf,f_METAB_sup,f_METAB_ref] = get_peak_bound(type)
%[f_METAB_inf,f_METAB_sup,f_METAB_ref] = get_peak_bound(par)
% it will return the search bound around a reference in ppm for a peak name given by
% par.ref_metab. possible values ar 'NAA' 'CRE' 'CRE_2' 'CRE_SMALL' ...
% alternatively you can diretly ... |
7d25f0565a82af72787ae35b040b7110b8d493ac5faebdf7d2ffe90ae45083f3 | MATLAB | 2,491 | 52 | function plotRewAlignData(data,choice)
% Author: Pratik Mistry, 2020
% Updated: Anya Krok, June 2021. Code now works for output from
% processReward and accounts for multi-sweep recordings. Updated to match
% updated alignData2Rew
%
if isfield(data,'rew')
incldVel = menu('Include Velocity in Plot?','... |
c23e83a1d0130257415ac2be09c5c1e424dd05fb279baeb01a843266c6b3cdea | MATLAB | 2,495 | 77 | classdef (Hidden) h5_file_sdk < adi.mat_file_sdk
%
% Class:
% adi.h5_file_sdk
%
% This should expose the SDK in a similar manner as the regular SDK
% but it should do it from a h5 file.
%
% JAH 2014-6-15: This code layout will likely change although the
% interface will ... |
382454d0bb6efad639a9165c7f81c2d8328bbe3b5b98a309cfd69d4bb9905e6b | MATLAB | 2,496 | 71 | %% save all_data files to breain render table with out spliting
clc
clear
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
flip_ml = 1; %if to flip the ML axe... |
9a800d83a4a1ac1da7ecf55459f07b1879e38e3f0e175a0232b2b845d11480b4 | MATLAB | 2,498 | 75 | % Funtion that reads Names and Directory of Videos
% and loads coordinates
% Input (same directory) from dialogue:
% ALL (XY).csv
% Condition_A_00.avi
% Condition_A_01.avi
% ...
% Condition_B_00.avi
% ...
% Condition_Z_XX.avi
% Output
% Names_Conditions
% NumberofVideos (per condition)
% FN{}: Str... |
d15dbabea9cbc5b8bf2b0674a63a6bae1a6e634313f22adc3b2b3a5f74770c4e | MATLAB | 2,501 | 66 | function [coarse_grid_res, fine_grid_res] = ecg_grid_size_from_paper(img, paper_width, unit)
% ecg_grid_size_from_paper - Estimates the size of the standard ECG coarse
% grid on a given image, based on a given ECG with
%
% This function calculates the grid size of an ECG image based on the physical
% dimensions (width... |
cff588b500824ba1477dd8a2b6285964016e292bc2726e0487af905691a0c087 | MATLAB | 2,502 | 76 | function RaguDumpToVision(rd)
DirName = uigetdir(rd.LastPath,'Select directory to store the data');
if DirName == 0
return
end
for s = 1:size(rd.Names,1)
for c = 1:size(rd.Names,2)
fn = rd.Names{s,c};
idx = find(fn == '.',1,'last');
if isempty(idx)
idx = numel(fn)+1;
... |
b1b16c12a1d08bb27bd674e5b352bec7be7d6cb20e2158399511ea7ad904f8d7 | MATLAB | 2,505 | 75 | function [states, trans_prob] = Holsclaw_State(Xi, Z, Exo, Sig, Y)
%% Inputs:
% Xi : parameters controlling the transition probabilities and the log linear regression term
% Z : Matrix with the Markov property, binary matrix showing which states are present at each time point
% Exo : Exogenous variables used in the tra... |
83470af6c5fede28ed5c02e4f8005389bf81b5a744f7ad7ef92e87010be75cf0 | MATLAB | 2,507 | 64 | classdef hTestVennEulerDiagram < vennEulerDiagram
% hTestVennEulerDiagram Class for testing vennEulerDiagram properties
% and methods. Used in tVennEulerDiagram.
%
% Copyright 2021 The MathWorks, Inc.
methods
function callSetup(obj)
setup(obj)
end
fun... |
d71a82f5a1a2003ba5080fe757f3450e534a77ea7c28fd4d079165efd60337f1 | MATLAB | 2,508 | 59 | function [Somas,BkgMean,BkgStd,Thresh]=mnl_ProcessTracesFromNeurolucida_Somas(fname,cData,Scale,dim)
% Process the traces that have been extracted from Neurolucida and then get
% the corresponding raw voxel values for each trace (NB Trace=the
% neurolucida identified fragment/branch/axon. This version also splits the
%... |
17653eed343e2ad82ff39c9d299146372fac9ebf344b38e2bbdcc32d74f4dac6 | MATLAB | 2,509 | 62 | clear;clc; close all;
initialize_human_anxiety;
HO = 1; %heading offset (m=1 is the headings for INstring. INnum, however, starts at 1)
condLabel={'VES_all','VIS_all'};
for firstCond=1:2 %1 for ves, 2 for vis
%read in subject information
[INnum, INstring] = xlsread(strcat(DATA_DIR,'\All input_',[condLabel{firs... |
5524072a9b73d4eba1a9b20badcea5a0a1ec261ddeff1ed5ffd4247bc07fe650 | MATLAB | 2,509 | 76 | function reset_results(app,res_data,res_derived)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
if res_data
app.data = [];
app.comments = [];
app.settings = struct('interval', [nan, nan; nan, nan],...
'channel_sheet', [nan, nan],...
... |
7e0d4a05e1810c097a6ac0b59533f8b5dad7179e74a79b3a3239073ae4ff4c94 | MATLAB | 2,510 | 86 | function plot_all_bursts(EEG, YGap, Bursts, ColorCategory)
arguments
EEG
YGap = 20;
Bursts = [];
ColorCategory = [];
end
% function to view bursts in the EEG
% Type is either 'ICA' or 'EEG', and will appropriately plot the bursts
% over the channels or the components, accordingly.
% colorcode indicates ... |
e5f8998b8a7123d97e8c1667252008182534f1071edde61949f1468c114de652 | MATLAB | 2,511 | 88 | clc, clear;
addpath('/home/li-lab/Documents/rDL-LLS-SIM-Matlab/GenerateDataset/XxUtils');
%% save otf as mrc file
% read psf
psfPath = 'Simulated_PSF_642.tif';
% psfPath = 'Illum642_Cyc1_Ch2_St1.mrc';
% psfPath = 'TIRF560_Cyc1_Ch2_St1.mrc';
% psfPath = 'Sheetscan488_Cyc1_Ch1_St1.mrc';
% psfPath = 'TestDetectionOTF/TIR... |
7d7e42d71a54b8a43966402af8588cab983cc6aa7c8c1c607072108f262cbdec | MATLAB | 2,513 | 56 | %Author: Raul Adell
%Description: Function to estimate Fano factor along the cognitive task for each neuron separately
%Date: 9/9/2023
function est_fano = Fano(spikeCounts, timesEvents, num_intervals, min_trials_per_amplitude)
% Fano computes the Fano factor for neural spiking data across different stimulus... |
5c3a4af1b1e3d4cd949360df704623359d8662d3363c9acc4a62ed4ac77ce939 | MATLAB | 2,515 | 47 | % This program is intended to extract contrast of parameter estimate (COPE)
%clear all; close all;
% set ROIs info% list of the data
% session3, tph blue stimulation,
datapath_tph_blue = fullfile(pwd, '/data/COPEResults/session3/BLUE/TPH');
ContrastList_session3_tphblue = makeList(datapath_tph_blue, 'TPH*.nii');
% se... |
65b76f050dabb28d92158373f684c4f9823db64e7d8bb17cf1343604039cc751 | MATLAB | 2,515 | 47 | % This program is intended to extract contrast of parameter estimate (COPE)
%clear all; close all;
% set ROIs info% list of the data
% session2, tph blue stimulation,
datapath_tph_blue = fullfile(pwd, '/data/COPEResults/session2/BLUE/TPH');
ContrastList_session2_tphblue = makeList(datapath_tph_blue, 'TPH*.nii');
% se... |
787b40860210c57ee35d02f07896139199ef259e13436136b3c2926785ac3a50 | MATLAB | 2,517 | 98 | function x = dtft_adj(X, omega, Nd, n_shift, useloop)
%function x = dtft_adj(X, omega, Nd, n_shift, useloop)
%|
%| Compute adjoint of d-dim DTFT for spectrum X at frequency locations omega
%|
%| in
%| X [M L] dD DTFT values
%| omega [M d] frequency locations (radians)
%| n_shift [d 1] use [0:N-1]-n_shift (default [... |
b1b22f67888f191085a859d02d978f7899404c76907510f1ceb07bc8be5b1487 | MATLAB | 2,518 | 49 | % This program is intended to extract contrast of parameter estimate (COPE)
%clear all; close all;
% set ROIs info% list of the data
% session4, tph blue stimulation,
datapath_tph_blue = fullfile(pwd, '/data/COPEResults/session4/BLUE/TPH');
ContrastList_session4_tphblue = makeList(datapath_tph_blue, 'TPH*.nii');
% se... |
a8f456a167b721be8ccece8210ae7eb3ddf7affa4721150d122038b25b17b8a8 | MATLAB | 2,521 | 79 | % *************************************************************************
% * Test program for Instantaneous Phase (IP) estimation using the *
% * traditional analytic representation approach through FIR filtering *
% * and Hilbert Transform. Refer to the User Guide for further details. *
% *************... |
57e44011fba946be2806302abdeb11a606f7ad02d1d7bba69d8431eea241c67e | MATLAB | 2,522 | 75 | %% convertH5
%
% Test Comment 191114
% Description: This function will convert as many H5 files into MAT files
% that follow an organization pattern agreed upon by fellow lab members
% of the Tritsch Lab.
%
% This function requires h5 data files to be in the following format:
% - AN_ExpDate_Cond_00... |
fe435bab3d8588a4c0fde4ed52e363a81e6fae1ffee021b99e8268a220da1c27 | MATLAB | 2,523 | 79 | [cols,alpha] = chooseColors;
%% plot with CI
for k = 1:2
figure('Position',[100 100 300 300])
hold on
lims = [40 100];
this_cols = {'k','m','k','m',[.7 .7 .7],[.7 .7 .7],[.7 .7 .7],[.7 .7 .7]};
if k == 1
is = 1:2;
elseif k == 2
is = 3:... |
72c5a734df1807b47bf36598698de6a210b4a956c1781680620d67e30ad40196 | MATLAB | 2,527 | 85 | function [ws, src, targ] = GrappaCalib3D_arb(acs,kernel,lambda, bDoInversion)
%
%
% Daniel Gallichan: modification of Bernd Jung's code for GRAPPA - to
% specify manually the kernel
%
% - 5/2/14 - changed the definition of lambda so that it is relative to
% norm of the ACS data
%
% - 11/3/16 - change default when no re... |
76f3f0876d26afc138eaf291decd71bc60bca9d3fa23167d7d847a1a7212cd0c | MATLAB | 2,527 | 97 | function [binary threshold globalcosteffmax costmax ef]=threshold_global_cost_efficiency_wd(w,th)
%define the threshold in a a network as the max value of global cost efficiency versus cost
%adopted from Bassett & Bullmore Cognitive fitness of COST EFFICIENCT BRAIN
%FUNCTIONAL NETWORKS PNAS, 2009
%needs efficie... |
378b8afcadffee11772909f9487a0d9049c26483ed8c8d5f8cd64c5d7e7c8c20 | MATLAB | 2,531 | 73 | %% ramp statistics
clear
clc
ploting = 1 ;
norm = 1;
ploting2 =1;
%%
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
%%
%laod ramp intensites
load('C:\Users... |
48ac9419979de3c7e62f922011c887795ad2e75cb66cdc1c98a375e74713ac1c | MATLAB | 2,533 | 105 | function out = fatrix2_subsref_colon(ob, sub2, varargin)
%function out = fatrix2_subsref_colon(ob, sub2, varargin)
%
% handle subscript references like ob(:,sub2)
% This will called from ../subsref with (ob, subs{2})
%
% Copyright 2010-12-02, Jeff Fessler, University of Michigan
if streq(sub2, ':') % ob(:,:)
% do by... |
570528e18abe19d218a1abf6085a3583a568475d1449a58d1049e4392cd997fe | MATLAB | 2,533 | 115 | function plot_lcmodel_result(r,field_name)
if ~exist('field_name')
field_name={'gaba_cor','naa_cor','glu_cor'};
%field_name2={'SDgaba','SDnaa','SDglu'};
end
%w1_r = r(1).water_real.*29000000000;
%w2_r = r(2).water_real.*29000000000;
legend_str = {r(1).pool,r(2).pool};
for k=1:length(field_name)
y1 = getfield(... |
72d55343bbf3f419c78056d455cd9657d0038edca55249e9fbfcbf924359b7b2 | MATLAB | 2,533 | 63 | % this script creates a violinplot of the FWF in the various brain tissues
%clearvars
close all
addpath(genpath('/storage/stella/MATLAB_toolboxes/'));
addpath('/storage/stella/Analysis/matlab_scripts/');
%% RUN MATLAB_12_Statistics_Final_Final.m
%%
data = struct([]);
data(1).a01 = x3; % wm
%data(1).a02 = x... |
83b8d0bb9d86320f2414efbefda1e6f576a33baff36b5a3ed84713a81cf0d9a3 | MATLAB | 2,534 | 96 | function Xs = fftn_fast(xs, ns)
%function Xs = fftn_fast(xs, ns)
%|
%| For some reason, in matlab versions before about 7.4 (R2007a),
%| matlab's fftn routine was suboptimal for the case of 2D FFTs,
%| at least on some machines.
%| The improvement herein was found by Hugo Shi.
%| After 7.4, fftn worked fine so this ro... |
73d120262d014e523e591d7ee6d9205b150a59995ebf6acb3615cae251ba3e57 | MATLAB | 2,535 | 82 | %% compare magnitude vector
clear
clc
[file1, path] = uigetfile('all_magnitude_vector.mat');
cd(path)
dataset1 = load(file1);
dataset1 = dataset1.all_magnitude_vector;
[file2, path] = uigetfile('all_magnitude_vector.mat');
cd(path)
dataset2 = load(file2);
dataset2 = dataset2.all_magnitude_vector;
win_names = ["early... |
237fb6daa26f46eb1380b8860f67742cadbbb33e9bec065f3fa4cceddac9ce1f | MATLAB | 2,536 | 77 | function reset_results(app,res_data,res_derived)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
if res_data
app.data = [];
app.comments = [];
app.settings = struct('interval', [nan, nan; nan, nan],...
'channel_sheet', [nan, nan],...
... |
96d8f658fdbd763979d7d4a1b41c1aa06613b3c62a16f4600d4d3ca8d9dda537 | MATLAB | 2,537 | 90 | function extractRecordToNewFile(source_file_path,record_id,varargin)
%
% adi.extractRecordToNewFile(source_file_path,record_id,varargin)
%
%
% This is a bit buggy but I think it works ...
%
% Optional Inputs:
% ----------------
% new_file_path:
% channels : cell array
% Names of channels whose data yo... |
5b5a64c24689e9878393c5205c44943bd62089fe2973a0b053019eba81eed6cf | MATLAB | 2,540 | 97 | function [binary threshold globalcosteffmax costmax ef]=threshold_global_cost_efficiency_wu(w,th)
%define the threshold in a a network as the max value of global cost efficiency versus cost
%adopted from Bassett & Bullmore Cognitive fitness of COST EFFICIENCT BRAIN
%FUNCTIONAL NETWORKS PNAS, 2009
%needs efficie... |
5048ce77df2c2284c9fb1046d1f03d243484fd672d28588175af47dcc7547ba7 | MATLAB | 2,541 | 74 | clear all
% this script contains code to reproduce Figure S6a-c
%% load data
% drag and drop corresponding file (S7 Data)
%% data content description
% various behavioral measures from the open field foraging task and the
% corresponding animal id and sex. This data is the same as from S2 Data
% but p... |
d3529a08ff1dc9c13563bafce27393c848599c6ef4fb35870a2a4f5b2f5666ba | MATLAB | 2,541 | 76 | function keyPressFigSim(obj, ~, hEvent)
%KEYPRESSFIGSIM Handle callbacks for keys pressed in sim view
if obj.isWorking
jrclust.utils.qMsgBox('An operation is in progress.');
return;
end
hFigSim = obj.hFigs('FigSim');
switch hEvent.Key
case 'uparrow'
selected = o... |
a909f537516dd640ca4804b33510e7dfa317efcdc780e845f2557aac315ee685 | MATLAB | 2,543 | 94 | function rewrite_state_vars(InputFile, OutputFile, y)
% By Alfonso Bueno-Orovio
%
% A function that takes a filename for a given CellML InputFile and
% replaces all the initial state variables with the contents of vector y,
% storing the result in OutputFile.
%
% InputFile: string
% OutputFile: string
% y: re... |
0b1ffc0ade0b89ceaf791d60a290ba2a57255f8a572170ad9ccff13c13bceda3 | MATLAB | 2,544 | 79 | %% high-speed video analysis for whisking
% whisker position captured by DeepLabCut
% input: x, y label position in pixels and the likelihood for each frame
% per body part
% frame rate:
% to-do-list:
% remove outliers in DLC
%
% Hilbert transformation: extracting the complex components from a signal (such as... |
beb8075d0618565964a8f5d130bec38ff93888d49bbc930e5735b41fb9aab893 | MATLAB | 2,548 | 61 | function [PeakToPeak_corrected, PeakToPeak_differences, matched_peaks_indexes] = MFPeakDetector(x, template_start, template_stop, type, wlen, PP_diff_wlen, PP_diff_th, average_peak_det_rate, fs, plotflag)
% ===========================================================
% Matched Filter R-Peak Detector and Smoothed Heart ... |
185d512b6e73782e7cac3babb64de8aa32256968342447c33d4bb73e491a1040 | MATLAB | 2,551 | 72 | %{
----------------------------------------------------------------------------
Analyzing behavioral data
At least for the correct rate
----------------------------------------------------------------------------
%}
function Figure1d_Dual_Full_psycho_analysis_220818_all
analysis_folder = {
'G:\Ishizu_da... |
6fb4bcdd8397fdd641f5de21bd474f7ed97346b047befd8cc7a91f07b39fee2a | MATLAB | 2,553 | 72 | function [data, fs, base_name] = load_and_preprocess_ecg(file_entry, lead_list)
% function [data, fs, base_name] = load_and_preprocess_ecg(file_entry, lead_list)
% Load one WFDB ECG record and prepare it for feature extraction
%
% Inputs:
% file_entry (struct): one element of a dir()-style file ... |
3f1343a9b4a150c0bc2044fd52cef9ea5f5e32f5ded0b439b8bfe63e344d3e79 | MATLAB | 2,555 | 79 | function t001_speedWritingAndWriting
%
% adi.tests.t001_speedWritingAndWriting
%
% STATUS:
FILE_PATH = 'C:\Data\GSK\ChrisRaw\140121 pelvic nerve recordings.adicht';
SAVE_DIR = 'D:\Data\HDF5_test';
%Things to vary:
%- chunk size
%- compression level
%- shuffle or no shuffle
quick_test = false;
if quick_test
... |
5dba71caa7cb0cc16c8123190e067d555e5dbd4c25ccb62ebcae60e76f595f0e | MATLAB | 2,556 | 93 | function plot_s_dll()
% Plot delta log-likelihood of trained s-models
%
% Parameters
% ----------
%
info = get_info();
num_folds = info.num_folds;
filename = fullfile(...
info.folders.results, ...
'dll.mat');
if ~isfile(filename)
... |
3332d16a9d8543099e653426435f96165c1b31a3180765eb59554360cd09a2a5 | MATLAB | 2,557 | 48 | % This program is intended to extract contrast of parameter estimate (COPE)
%clear all; close all;
% set ROIs info list of the data
% session1, tph blue stimulation,
datapath_tph_blue = fullfile(pwd, '/data/COPEResults/session1/BLUE/TPH/');
ContrastList_session1_tphblue = makeList(datapath_tph_blue, 'TPH*.nii');
% se... |
8d4456305e23b2c7252e43dafe3f0049eac7da73eb4cc133e6b2654628bb4e69 | MATLAB | 2,558 | 93 | [cols,alpha] = chooseColors;
%% get coding dims per subject by projecting dims back into cell spaces
coding_dims = {};
for rep = 1:length(all_dims)
for sub = 1:p.nSubjects
coding_dims{rep,sub} = all_qs{rep}{sub} * all_dims{rep};
end
end
%% calc. normalized weight distributions and weight entropy per c... |
a1f127669b234b038dbf2c7b75652e7dfe707098bc1cad713578646e7528ac90 | MATLAB | 2,559 | 95 | function [PTRANSITION,Pstates] = LEiDA_fix_cluster(BOLD,NumClusters,Center,TR)
[N_areas, Tmax]=size(BOLD);
% Preallocate variables to save FC patterns and associated information
%Leading_Eig=zeros(Tmax,2*N_areas); % All leading eigenvectors %PD
Leading_Eig=zeros(Tmax,N_areas); % All leading eigenvectors %PD
... |
605e70917b2f3ec797c07c928dab97bf1f1ba8426307a8a8fee83cb27f91c4d5 | MATLAB | 2,561 | 60 | function [ext_prediction] = get_extended_predictions(prediction,grnnet,varargin);
% GET_EXTENDED_PREDICTIONS Extend prediction of gene interactions to 100000 interactions if less.
% EXTENDED_PREDICTION = GET_EXTENDED_PREDICTIONS(PREDICTION,GRNNET) for gene regulatory network GRNNET and interactions PREDICTION
% ... |
acc6edf73188607d52d003378c7f0b91f810bae3564385057d4516a69c2946d7 | MATLAB | 2,561 | 78 | function perturb_hopf_noisebynode_UWS(node)
load Modelling_Workspace_UWS.mat
P2emp=nanmean(P2emp);
PERTURB=0:-0.02:-0.2; % Noise
we= 0.04; %% Insert here G from optimal UWS model fitting
ITER=10;
N=214;
a=-0.02*ones(N,2);
C=squeeze(Coptim(find(abs(WE-we)<0.0001),:,:));
TSmax=295;
NSUB=16; %n_Subject... |
3c7882fa75ea5cf87665ac5e43f24908ae5a5fafee1b3cb1a6a53596d703c1e3 | MATLAB | 2,562 | 67 | function [varargout] = calcFFT(y,fs,varargin)
%calcFFT - Calculate the Fourier Power Spectrums
% Created By: Pratik Mistry
% Created On: 31 January 2019
% Edited On: 5 June 2019
%
% calcFFT - Plots fourier magnitude and phase values
% calcFFT(y,fs) - Plots the data
% [fftamp] = calcFFT(y,fs)
% [f... |
843757290c0ae770bed5194c3fae269a1026e5f3936f7982d6cbe330b85a1b5e | MATLAB | 2,563 | 77 | function property = eq_point_set_property(fhandle,dim,N,varargin)
%EQ_POINT_SET_PROPERTY Property of an EQ point set
%
%Syntax
% property = eq_point_set_property(fhandle,dim,N,options);
%
%Description
% PROPERTY = EQ_POINT_SET_PROPERTY(FHANDLE,dim,N) does the following:
% 1) uses the recursive zonal equal area sphere ... |
c192fd1ba17735094e8fc42cdc9fdf401bd53b65046f736545e5429b33cbaf1c | MATLAB | 2,563 | 67 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Load data and build models
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
import_data;
build_models_met_PT;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Settings
%%%%%%%%%%%%%%%%%%... |
d1a6d3057eed62b0b14ee9179ebd04d8ca630905479ed19dfd9de3c68e29d854 | MATLAB | 2,563 | 84 | close all
clear
clc
% Convert all dat files in bash using this command: find ./*/ -type f -execdir wfdb2mat -r {} \;
datafilepath = '../../../../DataFiles/physionet.org/files/ptbdb/1.0.0/';
directory_list = dir([datafilepath 'patient*']);
filelist = dir(fullfile([datafilepath, '**/*lr*.mat'])); % get list of all ma... |
922c4f1a26d51f2ce0e16325d17fe280315baa6fe14e553923fc0cbab797528c | MATLAB | 2,564 | 84 | function coeff = eq_energy_coeff(dim,N,s,varargin)
%EQ_ENERGY_COEFF Coefficient in expansion of energy of an EQ point set
%
%Syntax
% coeff = eq_energy_coeff(dim,N,s,options);
%
%Description
% COEFF = EQ_ENERGY_COEFF(dim,N,s) does the following:
% 1) uses the recursive zonal equal area sphere partitioning algorithm to... |
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