sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5a4d88a64d3b7ff9261b15a96b222e72f8028f9bf880f69af9f87816eae27550 | MATLAB | 914 | 65 | %Produce all NatureComm2024 figures' panels.
%% Set dataset directory and dependent repos:
[~,repo]=define_flicker_root_dir;
for field_name=fieldnames(repo)'
addpath(genpath(repo.(field_name{:})));
end
%note: can use function fetch_flicker_subjectIDs to get list of sessions
%and their details.
%%
clear all; clo... |
996cca707e56040703efd2ea98f58e12619530b0c0e83a1c609ad32c7ccd682b | MATLAB | 914 | 25 | function [t, X] = em(f, sigma_noise, X0, T, dt, N_eq)
% EM f, sigma_noise, X0, T, dt, N_eq
% Euler-Maruyama method for SDEs dX = f(X) dt + sigma dW where the noise is
% applied to the first N_eq equations (the first state variable of each neuron)
% f drift function
% sigma_noise noise coefficient... |
e599cdd5c9d7a63bbfc5077e91fa59b2bd21e9289919e4a36292829f501b79eb | MATLAB | 914 | 27 | function ms = msSelectFluorThresh(ms)
%MSSELECTFLUORTHRESH Summary of this function goes here
% Detailed explanation goes here
userInput = 'N';
while(strcmp(userInput,'N'))
figure(102)
clf
plot(ms.minFluorescence,'y');
hold on
% plot(ms.quant10Fluorescence,'m');
... |
453610d6d8fb0c666f0b2c8a979074129cb496591ab95b007d61919db872f0c5 | MATLAB | 915 | 35 | % @author Farad Khoyratee
% @date 16 Apr 2019
% @copyright
% SPDX-FileCopyrightText: © 2021 Farad Khoyratee <farad.khoyratee@gmail.com>
% SPDX-License-Identifier: GPL-3.0-or-later
function Iexc = StimCurrentForm(Imax, t, dt, Period, DutyCycle, WaveForm)
Iexc = zeros(1, length(t));
if strcmp... |
cb48d83b36774137fc7580da386c6fe3bc1d65e9523b79ab53d61010d2620c6b | MATLAB | 916 | 29 |
centroids1 = centroids(unassignedDetections, :);
bboxes1 = bboxes(unassignedDetections, :);
for i = 1:size(centroids1, 1)
centroid = centroids1(i,:);
bbox = bboxes1(i, :);
% Create a Kalman filter object.
kalmanFilter = configureKalmanFilter('C... |
d91de08aa09953957456582347e590687f16ca95ffb5bb430c7f65d13aa8a5de | MATLAB | 916 | 21 | function [conds, tts, head, target, hevel, PC, sines, light] = addStep(I, conds, ...
tts, head, target, hevel, PC, sines, light)
% Add an ideal VORD step to enforce steady state
tt_step = (1:round(I.T_step/I.dt))'*I.dt + I.T_step_start; % Step time vector
step_in = I.scale_step * double(tt_step>0);
step_in = filte... |
92d0b108b5912cc95e94c7ef10166de2fb24348be54dbec45fd69e07f738d3ba | MATLAB | 918 | 29 | function [coords] = get_coords_from_mask(mask)
% Create nVox x 3 matrix of x,y,z coordinates from mask
%
% [COORDS] = GET_COORDS_FROM_MASK(MASK)
%
% COORDS (nVox x 3) contains the x,y,z coordinate of each active voxel in the
% boolean 3D mask MASK. As always, the order of the nVox
% voxels is the same as that returned... |
f0ee1eabcf6f01b65111564a0493b80695eeb2d9eeba2da88f6f08a8be57daa4 | MATLAB | 919 | 34 | function [isthere] = exist_objfield(subj,objtype,objname,fieldname)
% Checks whether the field exists
%
% [ISTHERE] = EXIST_FIELD(SUBJ,OBJTYPE,OBJNAME,FIELDNAME)
%
% Checks whether the FIELDNAME exists inside the object OBJNAME of
% OBJTYPE.
%
% Returns true if it does, else false.
% License:
%=======================... |
c15ba15f7347efc06ed654f76b3fde99382351492987aca275beba889a3d6d88 | MATLAB | 920 | 30 | function [X] = sympad(X, pad)
% Performs symmetric padding to expand signal X on both ends by n points.
%
% This is useful to avoid falloff when doing convolution.
% X is an N x P matrix of signals.
% License:
%=====================================================================
%
% This is part of the Princeton MVPA... |
d0fab5a81152e0c394370cfc9b01b1e418a386ab3e83a46477eb19b76809f63f | MATLAB | 920 | 32 | function guess=find_bpn1(sv_var,coords,C)
for i=1:size(coords,1)
stds(i)=std(sv_var(i).coords(:,5));
end
[~, sorted_ids]=sort(stds,'descend');
guess=[];
selection=sorted_ids(1:50);
num_neu=3;
additional_factor=1;
selection(ismember(guess(:),selection))=[];
combinations=nchoosek(selection,num_neu);
qs... |
03baf483df022804c6e35743b3e16922ec5e4927b7d88b965e1bc3d698457438 | MATLAB | 921 | 29 | function imageArray = getColormapImageArray(height, width, colormap)
temp_Array = zeros(height,width,3);
switch colormap
case "Greyscale"
colormap_colors = gray(width);
case "Turbo"
colormap_colors = turbo(width);
case "Hot"
colormap_colors = hot(width... |
14db4c1c80e84d7ecc79c26a2b18177452747d6245cd7bd097ee42b34b3dcb7c | MATLAB | 921 | 29 | function vbl = draw_missed(Experiment, flip, flipTime)
% takes flipTime as additional argument to specify exact time of flip
% (script waits until time is reached)
Display = Experiment.Display;
Stimulus = Experiment.Stimulus;
pointList = Stimulus.missedTrials.pointList;
pointList(:,1) = pointList(:,1)+Stimulus.shift... |
b7a7144798861b7b559b7c60bc0f825e9df6274c3e77e53c07fb8288edc7589d | MATLAB | 921 | 35 | function [returnVar,msg] = RemoveDCfromSpk(fbasename,chan)
% USAGE:
% RemoveDCfromDat(fbasename,shankIx,chanIx)
% This function removes DC from dat files by computing the average of
% the first 1e6 samples (or less if file is smaller)
% INPUTS:
% fname: dat file name
% nbChan: total number of chann... |
b9f9f864680fa6edb8c69ff1afa6b56d0da4a7ef1edafc885a4a8e70ca1cf95d | MATLAB | 921 | 36 | function [Traj_cell_noTime, Traj_cell_Time, OccSum, OccSpread] = Occupancy(ptsx, ptsy, Traj, threshold)
% Calculates the occupancy in X/Y for the selected trials
%Traj Cell Time will be binary matrix of occupancy
%Traj Cell NoTime will be matrix of 2d space, without binary switch
nT=size(Traj,1);
if nT == 0
... |
71d68c26d85c985bb8693cd079247db875d34ebb5567d70f1b2b75c857cddafd | MATLAB | 922 | 24 | function msBatchLinearSFR(dirName, speedThresh, binSize)
%MSBATCHLINEARSFR Summary of this function goes here
% Detailed explanation goes here
dataFolders = msBatchFindBehavFolders(dirName,[]);
for folderNum = 1:length(dataFolders)
currentFolder = dataFolders{folderNum};
dirData = dir(currentF... |
9fa0d616a3e86dbc4d6837da194fa35c0acd45ebd552e5b0c0c5da5572d94db5 | MATLAB | 922 | 35 | %
%prepare groups of trials for plotting of raster (with color info)
%
%indsOfGrps: cell array of list of periods (each a list of trials)
%
%urut/april13; initially derived from getTimestampsBubbles.m
function [spikesToPlot, colortill, nrTrialsTot] = getTimestamps_forSortedRasterPlot( timestampsOfCell, indsOfGrps)
spi... |
f1d014fd5e515bf22a6e33f36a995e118ae8f9c4e926318ff5cd92585102fc67 | MATLAB | 922 | 41 | function [thrlo, thrhi, ix] = percthreshold(x, percent, dim, outflag)
% Helper function to determine the exclusive values of the
% %percent percentile threshold (two-sided) used for
% trimming, winsorizing etc.
%
% Implementation according to Wilcox; Robust Estimation
% and Hypothesis Testing
if nargin<4 || isempty(... |
2a498114e233660507691c0051c9d6633de1d9b51c70e53063983bb4363107c8 | MATLAB | 923 | 38 | function [ X ] = func_ARFIMA( n, d, eps, n_inf )
%UNTITLED31 Summary of this function goes here
% Detailed explanation goes here
switch nargin
case 1
d = 0;
eps = randn(n,1);
n_inf = 100;
case 2
eps = randn(n,1);
n_inf = 100;
case 3
n_inf = 100... |
4a1c7b9606aa560eb52e7a01ec2e2076232df5ac69e566f30a61a14bde6a7c90 | MATLAB | 923 | 39 | function [OutColor, OutIds, v] = GroupScatterColor(InVal, ColorMap, setrange)
switch nargin
case 1
nGradient = 256;
Colors = jet(nGradient);
setrange = [];
case 2
Colors = ColorMap;
nGradient = size(ColorMap, 1);
setrange = [];
case 3
Colors... |
9f3177848442a84686af52d393c13ec3140787f135a6c6d9ca47e75a08496cd2 | MATLAB | 923 | 29 | function jokes=random_json_joke(num, url)
% this example shows how to use the _DataLink_ annotation defined in the
% JData specification
% (https://github.com/NeuroJSON/jdata/blob/master/JData_specification.md#data-referencing-and-links)
% to define linked JSON/binary JSON data using external files or URL on the
% web.... |
533ca7a841ae82e33d5d9fa4dd1878e84edcffac9388ccc4d9e12e2ccbacfdaf | MATLAB | 924 | 23 | function [err_eye, err_pc, Ehat_linear, Phat_linear] = plotLinearPredictions(S_eye, S_pc, R_eye, R_pc, Kb_eye, Kb_pc)
Ehat_linear = S_eye*Kb_eye;
Phat_linear = S_pc*Kb_pc;
err_eye = sqrt(mean((Ehat_linear- R_eye).^2));
err_pc = sqrt(mean((Phat_linear- R_pc).^2));
tt_all = (0:length(Ehat_linear)-1);
figure; subplot... |
f92eabb38f6ee5caadbb94957dcf57b1b2d84efeda773b0b2eb31d2ae59ada37 | MATLAB | 924 | 22 | function str_out = condenseAreas(str_in)
% Remaps strings of brain areas stored in the SB NWB format to a
% de-lateralized naming convension (e.g. 'amygdala_left' -> 'amygdala')
% Input: A string of the lateralized brain area.
% Output: A string of the de-lateralized brain area.
str_mid = str_in;
switch (str_mid)
... |
dcbf76b505f0b229de1c748596e0d87ec032ae793ed78e543d215ddd8a1ac05d | MATLAB | 925 | 24 | function cdf_Paxm = computeCDFpowerlawdistribution(x_vals, a_hat, x_min)
% computes the complementary CDF of a discrete power law distribution using
% the generalized zeta function (Hurwitz zeta)
% cdf_Paxm = hurwitzZeta(a_hat, x_vals)/hurwitzZeta(a_hat, x_min);
[glu_hurwitzZeta, ~] = loadhurwitzZetaLookup();
... |
7f0b07ddcba10e3a5e667811406ec7b321a38558d96d460d9a0ca7da34dc75fc | MATLAB | 926 | 24 | function ms = msFluorFrameProps(ms)
%MSFLOURFRAME Summary of this function goes here
% Detailed explanation goes here
ms.minFluorescence = nan(1,ms.numFrames);
ms.meanFluorescence = nan(1,ms.numFrames);
ms.maxFluorescence = nan(1,ms.numFrames);
for frameNum=1:ms.numFrames
frame = msReadFrame(m... |
89c158964679260408de60e92b42371ad1d5dd4abd48a22f5ebdddcff389b17b | MATLAB | 926 | 51 | function s = horzcat(a, b, varargin)
% Horizontal concatenation of TSD objects (overload of the [a, b] operator)
%
% USAGE:
%
% s = horzcat(a, b)
%
% INPUTS:
%
% a, b (and eventually as many other ts as needed): TS objects
%
% OUTPUTS:
%
% s: the concatenated TS object
%
% copyright (c) 2004 Francesco P. Bat... |
b417c331659a3f736379aaad60eb43e4e382648fe75047714f55450178e2f0d0 | MATLAB | 926 | 38 | function [acts scratchpad] = test_svdlr(testpats,testtargs,scratchpad)
% Generates predictions using a trained logistic regression model
%
% [ACTS SCRATCHPAD] = TEST_RIDGE(TESTPATS,TESTTARGS,SCRATCHPAD)
%
% License:
%=====================================================================
%
% This is part of the Princeto... |
c4d2a0a15a668607d6483f021d68af4fa8d3c6868da63110f3efbca15a136558 | MATLAB | 926 | 26 | function [path] = genpathsafe(dir)
% Generates paths while excluding directories that begin with a dot.
%
% [PATH] = GENPATHSAFE(DIR)
%
% Generates paths while excluding directories that begin with a
% dot. This way it is possible to add source control repositories
% to the path without adding tons of unnecessary paths... |
faeb73163b23b7755d050099b49c7360f41c516588d38df3f559e5279280a47c | MATLAB | 928 | 46 | function input = get_input(transformer, data)
%
%
% (C) Copyright 2022 BIDS-MATLAB developers
assert(isstruct(transformer));
assert(isscalar(transformer));
verbose = true;
if isfield(transformer, 'verbose')
verbose = transformer.verbose;
end
tolerant = true;
if isfield(transformer, 'tolerant... |
45c062c8fa07cab68850cb0c8661f25bd2ac208ae67324808d85b697d809a3fb | MATLAB | 929 | 45 | function vec = ShapeLike(sig,proto)
% ShapeLike -- Make 1-d signal with given shape
% Usage
% vec = ShapeLike(sig,proto)
% Inputs
% sig a row or column vector
% proto a prototype shape (row or column vector)
% Outputs
% vec a vector with contents taken from sig
% and same shape a... |
6736b1780b0528655acfd59e693615d7252eb523296332f7645ff62a32337df9 | MATLAB | 931 | 44 | function y = contrast(x,varargin)
%
% y = contrast(x)
% makes values of y lying in the range [0 1] from the COLUMN vector
%
% y = contrast(x,minVal,maxVal)
% makes values of y lying in the range [minVal maxVal]. Any value outside
% those boundaries will be set to boundary value
%
% Adrien Peyrache 2012
if size(x,1)... |
1935811c786a642fb95c27b4a764f9749b860b1e6dac0e657096c3acd52da64d | MATLAB | 932 | 32 | function y = ME_vMMM_sim(r, mu, ka, N)
% _
% Simulate Date from a von Mises Mixture Model
% FORMAT y = ME_vMMM_Sim(r, mu, ka, N)
%
% r - a 1 x K vector of mixture frequencies
% mu - a 1 x K vector of means
% ka - a 1 x K vector of precisions
%
% y - an N x 1 vector of response deviations
%
% Auth... |
9840748668e37f913e9ef85e7d93e2336ba145ddeb9b20d7053abeb600b0d393 | MATLAB | 932 | 33 | function [s, interval, idxs] = generateSnirfStim(obj, CondNames, nStim)
if ischar(obj)
s = SnirfClass(obj);
s.stim = StimClass.empty();
end
if ~exist('CondNames','var')
CondNames = {1};
end
if ~exist('nStim','var')
nStim = zeros(length(CondNames),1);
end
if length(nStim) < length(CondNames)
nStim = ... |
6c36e96a43e3998b4e2e5009089e2530f82088a09e6a2e045d0996d330bedf70 | MATLAB | 934 | 28 |
function v=plot_zscore_violin(vectors_array,names_array,threshold)
num_groups=length(vectors_array);
vectors=[];
names={};
for i=1:num_groups
vectors=[vectors;vectors_array{i}];
names=[names; repmat(names_array(i),[1 size(vectors_array{i},1)])'];
end
%note: function b... |
c620d47f10bc76d110d5be81c45a1706a96475a86fc074716edbb841120ccac2 | MATLAB | 934 | 29 | % function [predicted_labels decision_values opt] = ldapredict(labels,data,model)
%
% Predict unseen data using pre-calculated Fisher LDA. Currently, only
% binary classification is implemented.
% INPUT (n = n_samples, p = n_features):
% labels: nx1 vector of labels of test data
% data: pxn matrix of test d... |
ac33743598c73614e736841b20387516463058e1bb5386bf2a18be6c1516f414 | MATLAB | 936 | 42 | % [Fet, nFeatures] = LoadFet(FileName, BufSize, CluSubset)
%
% A simple matlab function to load a .fet file
function [Fet, nFeatures] = LoadFet(FileName,varargin);
[BufSize, CluSubset] = DefaultArgs(varargin,{inf, []});
Fp = fopen(FileName, 'r');
if Fp==-1
error(['Could not open file ' FileName]);
end
nFeatur... |
1dc2823b8bd7628df8b85e882495b19e2f0f66459b221f8c72c9b2f4aa542848 | MATLAB | 937 | 54 | function X = gaussFilt(X,N1,varargin)
% Xsm = gaussFiltAng(X,N1)
%
% 1 or 2-d gaussian filtering with border correction
% Input:
% X: vector (or matrix) of angular values to smooth
% N1: sd of gausswin for the first dimension. If N1==0, no smoothing
% Output:
% Xsm: smoothed matrix
%
% Adrien Peyrach... |
e2d704f236b6912624cf558156d106914ac576d49058cb0b9264133eeac96445 | MATLAB | 939 | 24 | function rearrange_data_220228(datafolder)
%datafolder = "D:\Brewer lab data\HFS\Temporal Analysis\No Stim\AFR Output\";
% Rearrange data
source_fb = load(datafolder+'FB_source_AFR_table.mat');
source_ff = load(datafolder+'FF_source_AFR_table.mat');
% Creating if_FF column
source_ff.AFR_table.if_ff = ones(height(sourc... |
395c71a80764786ca598e145ef02d6725f5c827355256cb1d670802e0b53d246 | MATLAB | 941 | 26 | function FigureB_NoImages(fileExportFolder, FigureBParams, imageAshow, vxMatShowA, vyMatShowA, relMatShowA)
xIdxB = FigureBParams.xIdx;
yIdxB = FigureBParams.yIdx;
imageBshow = cell(size(xIdxB));
vxMatShowB = cell(size(xIdxB));
vyMatShowB = cell(size(xIdxB));
relMatShowB = cell(size(xIdxB));
for i = 1:size(xIdxB, 1)
... |
f29c1609af1c3e7084457a23ecc1cdfe0c227e72d31e00e78fc3ced3c77d236b | MATLAB | 941 | 26 | function msBatchMeanFrame(dirName,downsample)
%MSBATCHMEANFRAME Summary of this function goes here
% Detailed explanation goes here
dataFolders = msBatchFindDataFolders(dirName,[]);
parfor folderNum = 1:length(dataFolders)
currentFolder = dataFolders{folderNum};
dirData = dir(currentFolder);
... |
0af7d4b36999d854b099478dff360d6d9135e0892d81120fe342eb1d3dbec4a6 | MATLAB | 942 | 37 | % scaledata.m
% Hannah Payne
% 12/04/2011
%
% SCALEDATA
% dataout = SCALEDATA(datain) scales datain to the interval [0 1]
% dataout = SCALEDATA(datain, [minval, maxval]) scales to [minval maxval]
% dataout = SCALEDATA(datain, minval, maxval) scales to [minval maxval]
% dataout = SCALEDATA(datain, x1, x2, y1, y2... |
2006fab89ff2dab62477ecc581982ea90c6323597bd9d746f231d564af62636a | MATLAB | 942 | 29 | function fh=conffig(y, t)
%CONFFIG Display a confusion matrix.
%
% Description
% CONFFIG(Y, T) displays the confusion matrix and classification
% performance for the predictions mat{y} compared with the targets T.
% The data is assumed to be in a 1-of-N encoding, unless there is just
% one column, when it is assumed t... |
9f44ecfc7afae938870f0082a320c0edb688b403e2c5671c557c34c9292421d8 | MATLAB | 942 | 40 | function [vx, vy, relMat] = LKxOptFlow(I1,I2,sig,thresh)
if nargin == 2
sig = 3;
thresh = 0;
elseif nargin == 3
thresh = 0;
end
sz = ceil(6*sig + 1) + mod(ceil(6*sig + 1) + 1, 2);
w=fspecial('gaussian', sz, sig);
I1 = double(I1);
I2 = double(I2);
% [dxI,dyI]=imgradientxy(I1,'central');
f = exp(-(-3*si... |
ac6bba981c09cf387aaa975f3426b2c2dc140339f8e2753db2f1a139cfee74fc | MATLAB | 942 | 42 | %% Plot V4 MI Firing rates cued vs cue-opp (histogram)
%% Code
% cue epoch
win_start = 500;
win_end = 2500;
win_str = num2str(win_start)+"_to_"+num2str(win_end);
load(sprintf('data/V4_FR_full_%d_to_%d.mat',win_start,win_end));
monkey = ["G","B","Combined"];
metric = "MI_FR";
trial_type = "all";
bin_... |
624159d3fdc65e004094307772abc550528fe20867c223db5505d76bf68ed2a1 | MATLAB | 944 | 39 | function [res, fmt] = detUPMEMDperCycle(imf24, epoch, varargin)
%DETUPMEMDPERCYCLE extract cycle to cycle amplitude of the ~24-h component
% extracted from DETUPMEMD
%
% [RES, FMT] = DETUPMEMDPERCYCLE(IMF24, EPOCH, MINCYCLE)
% FMT request the format to write RES to file
%
% $Author: Peng Li
%
... |
c6bba829be583891dca93f79339f9283b7f9f4de2b46ab082bf13e19671e9311 | MATLAB | 944 | 34 | function pp_save(sub_id, p, model)
% function pp_save(sub_id, p, model)
%
% Saves the 'model' structure that holds the parameters of all performed
% preprocessing steps.
%
% Input:
% - i_sub: ID of the current subject.
% - p: Structure with analysis parameters.
% - model: Structure with all SPM settings used dur... |
dc6d3235c9eecd8af155f62f5a379370df14ed1fa70d73bab123f5e657612ea8 | MATLAB | 945 | 38 | function ms = msExtractFiring(ms)
%MSEXTRACTFIRING Summary of this function goes here
% Detailed explanation goes here
decayTime = 1;
V.Ncells = 1;%ms.numSegments;
V.T = ms.numFrames;
V.dt = mode(diff(ms.time))/1000;
V.fast_plot = 0;
for segNum=1:ms.numSegments
if (mod(segNum,30)==0)
display(['Extracti... |
7c3c6d90f1e7495ca567e452c2d3dd2fa2345dccc639472285ed07e393e913b4 | MATLAB | 946 | 51 | function p = bootstraspWelchTTest(x, y)
REPEATS = 10000;
scores = [x,y];
labels = [zeros(size(x)),ones(size(y))];
t_real = statistic(scores,labels);
t_dist = nan(1,REPEATS);
for j=1:REPEATS
prm = permVec(labels);
t_dist(j) = statistic(scores,prm);
end
p = mean(abs(t_dist)>abs(t_real));
end
function g... |
bd6ecc60e39b3a0d0b870c58cee943fa445f4d4db8ab936f39fa15be26ca8807 | MATLAB | 946 | 29 | function [subj] = statmap_glm_multiv(subj,data_patname,regsname,selname,new_map_patname,extra_arg)
% much like STATMAP_SIMST_MULTIV, except using the GLM obj_funct
%
% [SUBJ] = STATMAP_GLM_MULTIV( ...
% SUBJ,DATA_PATNAME,REGSNAME,SELNAME,NEW_MAP_PATNAME,EXTRA_ARG)
% License:
%====================================... |
53df1a35e6e35491c03944d77b8cc5dc93e3e7cd562bf51c59095bd1e57eb46f | MATLAB | 949 | 46 |
load(fullfile('Analysis','HDtuning_xval_moveEp'));
hAllA = hAll1;
hAllB = hAll2;
hAllA_sh = hAll1_sh;
hAllB_sh = hAll2_sh;
[totBins,totC,totTh] = size(hAllA);
%% calculate TC crosscorrs
ac = nan(size(hAllA));
for nTh = 1:totTh
h1 = zscore(hAllA(:,:,nTh));
h2 = zscore(hAllB(:,:,nTh))... |
7f90ebe9a0ec10ac5e4c179c6be49847669f2fe44b57ae5b3f40cf21ff930533 | MATLAB | 950 | 31 | function pSVR_save(sub_id, p, predictions, results, suffix)
% function mtSVR_save(sub_id, p, predictions, results, suffix)
%
% Save final result file during ongoing analysis. Variables include:
% - sub_id: ID of the current subject.
% - p: Structure with analysis
% parameters.
% - predictions: Structure c... |
abce5befb80de0db98b8bbc0e16ad93da0c4bf295277d8f802b3426c3d9940c7 | MATLAB | 950 | 40 | function awsEC2TerminateInstance(ec2Instance,v)
%Terminates instances
%INPUTSL
% - ec2Instance - instance created by awsEC2StartInstance
% - v - verbose mode
%% Input checks
if ~exist('v','var')
v = true;
end
origRegion = awsGetRegion();
%% Terminate the instance
for i=1:length(ec2Instance)
... |
2a21441f9e2e9ef53fce7944cf389b18affc2dae8a6dc1464a7c27e0b571eadb | MATLAB | 951 | 37 | % kernel unit test
%
% polynomial kernel
tol = 10e-10;
% Random data
N = 10;
F = 5;
X = randn(N,F);
X(1,:) = X(1,:) + X(2,:);
% kernel parameters
param = [];
param.gamma = 1/F;
param.coef0 = 1;
param.degree = 1;
%% polynomial_kernel(X) and polynomial_kernel(X,X) should yield the same result
K1 = polynomial_kernel(pa... |
b822194c90e4213b0df7a7d44fdabf94725c0ce2163596f47ed4a88916b0ccf3 | MATLAB | 951 | 44 | function info=parse_filename(f,varargin)
if isempty(varargin)
info = parse_roman_filenames(f);
else
if strcmp(varargin{1},'Anna')
info = parse_anna_filenames(f);
elseif strcmp(varargin{1},'Roman')
info = parse_roman_filenames(f);
end
end
end
fun... |
f0ae387c5e16654645184851de0fd6b763496ad67de451efd6d10718a5682ff8 | MATLAB | 951 | 25 | function [] = tutorial_hard(varargin)
% This used to be a sample script to accompany
% http://compmem.princeton.edu/mvpa_docs/TutorialAdv.
%
% We've removed it, because it was getting very long and
% unwieldy, and TutorialAdv is designed to be run
% interactively. So instead, just copy and paste the code
% sni... |
f9ccd9e1c2d565bcf1f8d31ccb2adf5b621e137806c04cdc46fb3db5ad33635b | MATLAB | 951 | 34 | function n2 = dist2(x, c)
%DIST2 Calculates squared distance between two sets of points.
%
% Description
% D = DIST2(X, C) takes two matrices of vectors and calculates the
% squared Euclidean distance between them. Both matrices must be of
% the same column dimension. If X has M rows and N columns, and C has
%... |
10139de2615b08c98cfcbd44256b405cd0c6c4964c4c9959a06b82e5f8e06076 | MATLAB | 952 | 39 | function [x,y,button] = PointInput(varargin)
%function [x,y,button] = PointInput(n,figh, axish)
[n, figh, axish] = DefaultArgs(varargin,{1,gcf,gca});
if n>0
for i=1:n
waitforbuttonpress;
whatbutton = get(figh,'SelectionType');
mousecoord = get(axish,'CurrentPoint');
x(i)=mousecoord(... |
d3d2d31c33dd89bc01175f5067303869f8a69eb3e8408bfae188c6c3f59d7eca | MATLAB | 953 | 43 | function [old_dirs,old_stps,Hdiag,Bcompact] = lbfgsUpdate(y,s,corrections,debug,old_dirs,old_stps,Hdiag)
%B0 = eye(length(y))/Hdiag;
S = old_dirs(:,2:end);
Y = old_stps(:,2:end);
k = size(Y,2);
L = zeros(k);
for j = 1:k
for i = j+1:k
L(i,j) = S(:,i)'*Y(:,j);
end
end
D = diag(diag(S'*Y));
N = [S/Hdiag Y... |
f3ddf6c6678b2a73682ecb97f3ef25bf92d39675a239cbe1f7304ca8bf7a5d04 | MATLAB | 953 | 26 |
numAssignedTracks = size(assignments, 1);
for i = 1:numAssignedTracks
trackIdx = assignments(i, 1);
detectionIdx = assignments(i, 2);
centroid = centroids(detectionIdx, :);
bbox = bboxes(detectionIdx, :);
% Correct the estimate of the object'... |
3c8900be7f9a4eb5ecffa6ed6747ec095c46f7fbed56427ef00be77cb1d9b821 | MATLAB | 956 | 40 | %% Wave Clus Output Plotting
% load both the raw data and times files manually
%clc
%close all
format long
figure('Position',[0 0 1920 700])
hold on
data=highpass(data,300,25000);
x=[1:length(data)];
x=x./25000;
plot(x,data,'Color','k')
num_clus=(unique(cluster_class(:,1)));
if any(num_clus==0)
num_clus(num_clus==... |
d0c0dc8a0b666b1f4e2283dd60f5075e490b520e9a84f0cb63b217cadbdcd8ce | MATLAB | 957 | 47 | function [pval, chisq, df] = CircularANOVA(th)
% [pval, chisq, df] = CircularANOVA(sr) Circular Non-parametric ANOVA
%
% INPUTS:
% th: a cell array, each for each group, each being an array of angular
% values
% OUTPUTS
% pval: the p-value of the ANOVA
% chisq: the chi-squared value
% df: the number of degrees of free... |
78102c173443c8d2c828604481fb2e407d01f737f5b18fa64b34132ae7457277 | MATLAB | 958 | 30 | function test_suite = test_bids_query_nirs %#ok<*STOUT>
try % assignment of 'localfunctions' is necessary in Matlab >= 2016
test_functions = localfunctions(); %#ok<*NASGU>
catch % no problem; early Matlab versions can use initTestSuite fine
end
initTestSuite;
end
function test_bids_query_emg_basic()
%
... |
d867e68a5d1b07abc4f61d35c1f9d5ca8e0fb5e7cb9934a9d0e96590bc31d702 | MATLAB | 959 | 25 | function [gx] = g_Hampton(x,P,u,in)
% Hampton's "influence learning" model: observation function
% function [gx] = f_Hampton(x,P,u,in)
% Let P(o=1) be the agent's prediction of the other's next move, ie the
% probability that the other will pick the first alternative option. The
% "influence learner" bases her decision... |
38fca4cffbdfb4657bf4680b6c3faccfe3ad71bd02723228d809e470d728eee2 | MATLAB | 960 | 40 | function phi = CircularMazeAngularCoordinate(X, Y, center, zero_ang)
% phi = CircularMazeAngularCoordinate(X, Y)
%
% gives an angular coordinate for the Warp circular maze used for rats
% 7027, 6985
% INPUTS
% X, Y: tsds containing rat's cartesian coords.
% OUTPUT
% phi: tsd containing the angular coord
if nargin < 3... |
3b6f2ec36dc088b32dbfcbc8453171104917bb31bb41aea48852be451ac4de3a | MATLAB | 961 | 36 | function Snirf2Tsv(rootdir, options)
if ~exist('rootdir','var')
rootdir = pwd;
end
if ~exist('options','var')
options = pwd;
end
rootdir = filesepStandard(rootdir);
files = DataFilesClass(rootdir, 'snirf');
files = files.files;
for ii = 1:length(files)
if files(ii).IsDir()
continue
end
fname... |
113c8ab69a30ff881e01ea88caa499e62061899ebf21d33bb939fd2fd98a1899 | MATLAB | 962 | 32 | function top_signals = pca_top_signals(neurons,top_sel,zs,final_time)
if nargin < 3
zs = 0;
end
if zs
signal_data = [];
for i_neu= 1:numel(neurons)
signal_data(:,i_neu) = zscore(neurons(i_neu).coords(10:final_time,5));
end
[coeff, ~, ~, ~, explained... |
17799b5b5aa03c7cbf90ff14167c8e46c103557503c78cb44e2994ee487224d6 | MATLAB | 964 | 35 | function [str] = estimate(t)
% Gives an appropriately unitized string of a duration in seconds.
%
% [STR] = ESTIMATE(T)
%
% License:
%=====================================================================
%
% This is part of the Princeton MVPA toolbox, released under
% the GPL. See http://www.csbmb.princeton.edu/mvpa f... |
c1487d3a55975af9b81de96b96c98bb7d11a90734390715ebfa4b12bc9ebf7a5 | MATLAB | 964 | 32 | function Xi = Xi_diff_MT(Xi_T,Xi_L,diff,kmax,N)
% Function to build Xi operator with diffusion effects for MT (4 states per
% k-value).
% This function efficiently uses spdiags to build the large band diagonal
% matrix that results from applying Xi_L and Xi_T to each order of states.
% Diffusion changes the matri... |
3596ef65a594660ae7cea61d44effc93584a778636e986dadfd927d8762413c2 | MATLAB | 966 | 44 | function out = roots_poly4(c,flag)
if nargin<2
flag = false;
end
delta0 = c(:,3).^2 - 3.*c(:,2).*c(:,4) + 12.*c(:,5);
delta1 = 2.*(c(:,3).^3) - 9.*c(:,2).*c(:,3).*c(:,4) + ...
27.*(c(:,2).^2).*c(:,5) + 27.*c(:,4).^2 - ...
72.*c(:,3).*c(:,5);
p = c(:,3) - (3./8).*(c(:,2).^2);
q = (c(:,2).^3)./8 -... |
52952544b6d9936e5f88bf4736183010769f31687e3945518211b8d1b38cd04c | MATLAB | 966 | 38 | function [isok] = check_subj(subj)
% This just runs some quickie tests to see whether your subj
% structure appears to be constructed correctly
%
% Still under development.
% License:
%=====================================================================
%
% This is part of the Princeton MVPA toolbox, released under
... |
ee3bed4eedd08ac1827ce03fe9010ce44fb6ab5baf15c22035aba2b8bdf70bc3 | MATLAB | 966 | 36 | function [post, a] = gmmpost(mix, x)
%GMMPOST Computes the class posterior probabilities of a Gaussian mixture model.
%
% Description
% This function computes the posteriors POST (i.e. the probability of
% each component conditioned on the data P(J|X)) for a Gaussian mixture
% model. The data structure MIX defines th... |
b1352b29cdbfecde59b15d345d066eb38dd544dabb37baf3ccd16268ca93aab7 | MATLAB | 967 | 40 | function [ripTsd ripEp] = LoadRipples_Kenji(fbasename,varargin)
% Load ripple times from Kenji dataset
%
% USAGE:
% [ripTsd ripEp] = LoadRipples_Kenji(fbasename);
%
% INPUT:
% fbasename: session file basename
%
% OUTPUT:
% ripTsd: a tsd of ripple times
% ripEp: a intervalSet of ripple events (beginnings a... |
a3c06d5d72e13c78cb8b2292e61a01bc7506db84c9312280e95d2c098963235c | MATLAB | 968 | 24 | function frame = msReadFrame(ms,frameNum,columnCorrect, align, dFF)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
vidNum = ms.vidNum(frameNum);
vidFrameNum = ms.frameNum(frameNum);
frame = double(ms.vidObj{vidNum}.read(vidFrameNum));
if (columnCorrect)
... |
cd4fc1c4b11cd549a5691f16829714f743b081dedf43e93a3f5690b894ec1b2f | MATLAB | 969 | 55 | function [eta,etaSem,B] = ETAverage2(t1,t2,data,binsize,nbins)
nt1 = length(t1);
nt2 = length(t2);
% we want nbins to be odd */
if floor(nbins / 2)*2 == nbins
nbins = nbins+1;
end
m = - binsize * (nbins / 2);
B = zeros(nbins,1);
for j = 1:nbins
B(j) = m + j * binsize;
end
% cross correlations */
... |
e17c230f6e6e4652140cb6e80e90631f27514f809abc3d73d8b718b6e420cba2 | MATLAB | 969 | 33 | function SO = map(S, cmd_string, varargin)
% Applies function on each element of the array
%
% USAGE:
% SO = map(S, cmd_string, arg1, ..., argN)
%
% Similarly to Python's function, map applies the commands indicated in
% cmd_stirng to each elements of the tsdArray S. In cmd_string, the input
% tsd array must be... |
3c306d469868b6060079fba865beaf04bf2ad3afeb241279419de193ff103c68 | MATLAB | 970 | 34 | classdef PsthAsEmClassifierModel < ClassifierModel
properties
EmPSTHs
end
methods
function mdl = train(mdl,X,y)
psthMap = containers.Map('KeyType','double','ValueType','any');
classes = unique(y);
for i = 1:length(classes)
... |
3a2f4b50b5b66b4c230d7b07be5c2ee467e8d232a2fcbba9f9ff437b051bdd0e | MATLAB | 972 | 33 | function plotInstability(I, K, c)
% Generate input signals
T_smooth = 0.025; % (s)
tbefore = -0.1; % (s) Time before step
tafter = 0.25; % (s) Time after step
amp = 10; % (deg/s) Scale for step
dt = K.dt;
tt = tbefore:dt:tafter;
% Generate smoothed step
head_curr = double(tt>0)*amp;
head_curr = ... |
721737d9cba7ea3524db24633934c5b8fb37340979dd524fe5461632d227391d | MATLAB | 972 | 24 | function info_r_onespin = computeSingleSpinInfo(eta_vals, eps_vals, J_i)
% J_i is the coupling strength and is fixed for each neuron, this in
% information from single sample of single spin
%
%% Compute information for single neuron, using rates.
r_h = @(h, eta_h, eps_h) (1 + exp(-eta_h*h*J_i + eps_h)).^(-1);
info_r_o... |
b16fdae7ad6fa733dc62a6f0fbfc56a37b8dd058b00e53d0b9f6b3cf9fbf3e51 | MATLAB | 973 | 38 | function Plot_Ellipse(M,V)
[Ev,D] = eig(V);
d = length(M);
if V(:,:)==zeros(d,d),
V(:,:) = ones(d,d)*eps;
end
iV = inv(V);
% Find the larger projection
P = [1,0;0,0]; % X-axis projection operator
P1 = P * 2*sqrt(D(1,1)) * Ev(:,1);
P2 = P * 2*sqrt(D(2,2)) * Ev(:,2);
if abs(P1(1)) >= abs(P2(1)),
Plen = P1(1);
e... |
baa33f8e929a567af2cef644c327e7c64b5b17b432203a78aafbac0f3725c287 | MATLAB | 973 | 28 | function ta = detTotalActivity(actigraphy, epoch, varargin)
%DETTOTALACTIVITY calculate total activity
%
% TA = DETTOTALACTIVITY(ACTIGRAPHY, EPOCH, STARTTIME, WINDOWLENGTH)
% calculate the total activity level in ACTIGRAPHY of epoch EPOCH second
% with start time at STARTTIME. WINDOWLENGTH specifies the l... |
aa1c2adcb2b719e19a9be124ac97106e5b566255a9903053e854a59a5df3c403 | MATLAB | 974 | 14 | % function for calculating log-likelihood
% inputs:
% b : vector of model parameters. b(1) is the log of scale parameter. The rest are model parameters
% DVH: function handle for calculating decision variable, which is Utility of option 1 minus that of optin 2
% data: a structure that contains variabl... |
be5272df8ffa65344f0e9f4ec258f83b03437f00e768adc22d76153ca2d54dba | MATLAB | 974 | 42 | function yCI95 = get_ci95(y, dim)
% function yCI95 = get_ci95(y, dim)
%
% Compute 95% confidence interval of input data y.
%
% Input:
% - y: 2-D data array
% - dim: Dimension along which to calculate 95% CI (default 1).
%
% Output:
% - yCI95: 95% CI of y.
%
% Simon Weber, sweber@bccn-berlin.de, 2022
% Check id ... |
1e7d57bf4a9147331c1b53929ff7b2f07948b9aa7f037e9871aa07dff2d2d522 | MATLAB | 975 | 33 | function e = mdnerr(net, x, t)
%MDNERR Evaluate error function for Mixture Density Network.
%
% Description
% E = MDNERR(NET, X, T) takes a mixture density network data structure
% NET, a matrix X of input vectors and a matrix T of target vectors,
% and evaluates the error function E. The error function is the
% negat... |
e2d7e2eb98b445c505169524901c3ad1e8be041b87ffef1e78b9f088d0ce3601 | MATLAB | 975 | 36 | function net = gpunpak(net, hp)
%GPUNPAK Separates hyperparameter vector into components.
%
% Description
% NET = GPUNPAK(NET, HP) takes an Gaussian Process data structure NET
% and a hyperparameter vector HP, and returns a Gaussian Process data
% structure identical to the input model, except that the covariance
% ... |
39f93dea262527bdcd9d03ab7cae1b9b2ae6e40411dbe1b0f0b08327d2865948 | MATLAB | 976 | 36 | function [tx,g]=tsample(x,percent)
% function [tx]=tsample(x,percent)
% Returns the trimmed sample of x.
% x must be a vector
% percent must be a number between 0 and 100
% The trimmed sample is calculated by dropping the lower and upper g values from
% x, where g=floor((percent/100)*length(x)). If x is empty, then Na... |
76303735721bae17ace23305c2c4cc4945699b57cec4383b49cc7195e2a0c83b | MATLAB | 976 | 27 | function [rho,theta] = generate_noisy_oscillator( dt, T, base_amplitude, base_frequency, ...
amp_noise_sigma, ...
freq_noise_sigma )
% *WAVE*
%
% GENERATE NOISY OSCILLATOR generates an oscillation with defined
% ... |
dddeb733833ab4bd5979607bfbd0dc042246fcf462750e95ea2f039f41777124 | MATLAB | 976 | 48 | function weights = ComputePeerHDPrediction(q,Q,ang,pf,x1,ep,varargin)
% weights = ComputePeerHDPrediction(S,Q,ep)
% S: ts of the cell
% Q: binned spike train matrix (tsd object) of all other cells
% ang: tsd of angles
% ep: intervalset of interest
q = Data(Restrict(q,ep));
Q = Restrict(Q,ep);
rg = Range(Q);
dt = med... |
aef325999887d667c5c187c66c8c0492e95df8c25a2c9b76d895df731c5e7989 | MATLAB | 977 | 42 | function [returnVar,msg] = MakeLEDFile(fbasename,varargin)
% USAGE:
% [returnVar,msg] = MakeLEDFile(filebasename,channel)
% INPUTS:
% filebasename: file base name
% channel (optionnal): sync pulse channel. Default is last channel in the eeg file.
%
% Adrien Peyrache 2011
msg = '';
returnVar = 0;
try
... |
f622f6181acf103e80b374ad4d466cdbfe41ddb2ce78d5c017ec8ce8d05867df | MATLAB | 978 | 58 | function maxTsd = max(tsa,is)
% Returns the maximal value(s) and time(s) of a TSD object (overoads the max function)
%
% USAGE:
% maxTsd = max(tsa,epoch)
%
% INPUTS:
% tsa - a tsd object
% epoch (optional) - an intervalSet object where max values have to be looked for.
%
% OUTPUTS:
% maxTsd - t... |
30f4e3fd74942e59ed375592374887cef3b0c3cfd915717b480aafc7801e11cd | MATLAB | 979 | 30 | function inx_cell = getInxForNoiseCorr(data,epoch)
PROBABILITIES = [25,75];
DIRECTIONS = 0:45:315;
[~,match_p] = getProbabilities (data);
[~,match_d] = getDirections (data);
boolFail = [data.trials.fail] | ~[data.trials.previous_completed];
switch epoch
case 'cue'
inx_cell = cell(1,lengt... |
92cab460987bce70803a1c02167c4518410b1ec071fbcec8e22f5677db7c2b7c | MATLAB | 979 | 18 | %%
%% Script to load spike firing times for a cell
%% c_ts: firing times, root.cel_x{1,1}: spike x coordinates,
%% root.cel_y{1,1}: spike y coordinates
%% reference: https://github.com/hasselmonians/CMBHOME/wiki/Tutorial-2:-Apply-an-epoch-and-get-theta-signal
%%
function [root c_ts] = load_spike_times()
addpath /comp... |
c45be3ceeb3d273f80f9cac4f654cf00d152db46b65b33eb2d3979e7a0348e2b | MATLAB | 980 | 34 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Authors : Khoyratee Farad
% Date : 28/11/2018
% Version : V1.0
%
% Description : GABAb current calculation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [N, Yplot] = rasterplot(t, V, Threshold)
N ... |
e0b2f682a9ea369329387c355c8cb2c301f03fe874cf8a80fdd8fb921b095729 | MATLAB | 980 | 34 | function p=s3SubjectPath(subject,lib,isCalibrationFolder)
%This function returns the library path in S3 to subject
%Example p=s3SubjectPath('01');
%If subject is empty will return the root folder of all subjects
%isCalibrationFolder - when set to true will return the calibrations folder
%in that lib
if (~exist(... |
317d7bdab4c35222fd2f63c8bbe58f81c645c84af05e21cd5925eac054b18e36 | MATLAB | 982 | 23 | % This script is used to compile a few C-mex files necessary to run SIMLR large scale
% first of all, mex projsplx_c.c and Kbeta.cpp
cd src/
mex -largeArrayDims projsplx_c.c
mex -largeArrayDims Kbeta.cpp
% second mex tSNE
mex -largeArrayDims compute_wtsne_obj_grad_repulsive_barneshut.c barnes_hut.c
% next we ... |
700b89e165c237ef90f4b6867b58711b16cef006513c63d63ceb16afa1adf04e | MATLAB | 982 | 39 | function resetGroupFolder(dirname, options)
global maingui
global cfg
if isempty(getNamespace())
setNamespace('Homer3')
end
cfg = InitConfig(cfg);
if ~exist('dirname','var') || isempty(dirname)
dirname = [pwd,'/'];
end
if ~exist('options','var') || isempty(options)
options = 'registry_reset';
end
output... |
e8cc93afe28d9a69314dee9b0bde8d59b42b1daa3d11e6a84504adf773d2c912 | MATLAB | 982 | 38 | function dist=KLDiv(P,Q)
% dist = KLDiv(P,Q) Kullback-Leibler divergence of two discrete probability
% distributions
% P and Q are automatically normalised to have the sum of one on rows
% have the length of one at each
% P = n x nbins
% Q = 1 x nbins or n x nbins(one to one)
% dist = n x 1
if size(P,2)~=size... |
731681f273bf2c9474fc7166a02355516ec4d8b3b4d110cf27da4ea89a175875 | MATLAB | 983 | 34 | function [dim] = pos2dim(pos)
% POS2DIM reconstructs the volumetric dimensions from an ordered list of
% positions.
%
% Use as
% [dim] = pos2dim(pos)
% where pos is an ordered list of positions.
%
% The output dim is a 3-element vector which correspond to the 3D
% volumetric dimensions
%
% See also POS2TRANSFORM
% ... |
b3b983818f6fe4a555a87edf8f0c735a9c760600c6ddecb79ce87e902d167723 | MATLAB | 983 | 33 | function [subj] = move_all_patterns_to_hd(subj)
% [SUBJ] = MOVE_ALL_PATTERNS_TO_HD(SUBJ)
% License:
%=====================================================================
%
% This is part of the Princeton MVPA toolbox, released under
% the GPL. See http://www.csbmb.princeton.edu/mvpa for more
% information.
%
% The ... |
746a9ad9b89266e6a2656bdbccd3d1b7a322d970f6291c5498775a40f0df087c | MATLAB | 984 | 33 | %% Pick the starting and ending points of object exploration
figure
plot(traj1.x1,traj1.y1),axis ij, hold on
[Crd.xR, Crd.yR] = pol2cart(thetaR,median(traj1.rhoPosition,'omitnan'));
scatter(Crd.xR, Crd.yR, 100,'+','r')
disp('Click to pick the locations of objects, double click to finish.')
[Crd.x2s,Crd.y2... |
1753cb180eb1fe5e6eab3dbfd5198caa7ff13504439a34dc874ed273a416269c | MATLAB | 985 | 24 | function struct = matrix_statistics_zscored_event(matrix, bsl_i1, bsl_i2, event_bsl_mean, event_bsl_std)
struct.matrix = matrix;
struct.matrix_mean = mean(matrix);
struct.matrix_std = std(matrix);
struct.bsl_mean = mean(matrix(:,bsl_i1:bsl_i2),2);
struct.bsl_std = std... |
b63d6c8ca7e412baa2bdd690809d2492f5e9aa58c37b1fc60990c3929c1d6b6d | MATLAB | 985 | 29 | function deleteFineAlignmentIfNoHistologySection(slidePath)
% This function deletes fine alignment information if slide doesn't have
% histology section. It cannot be fine aligned!
% Written at May 10, 2020.
%% Load Data
if ~exist('slidePath','var')
slidePath = [s3SubjectPath('18','LE') 'Slides/Slide05_Sect... |
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