sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
aea3eaa6a3542174fad89ea4f08dac9987d60d1f2df131a1763ae295fabf8a03 | MATLAB | 827 | 39 | % Get data from a figure with multiple data sets
function t = getDataFromFigureMultiple(fn,name1,name2,name3,name4)
fig = openfig(fn);
axObjs = fig.Children(2);
dataObjs = axObjs.Children;
x1 = dataObjs(8).XData; % index
y1 = dataObjs(8).YData; % index
x2 = dataObjs(6).XData; % middle
y2 = dataObjs(6).YData; % midd... |
ca01d374000a98f1020e1b3744e40dc4a0890dece4123d233ba1fb9b44d150e2 | MATLAB | 828 | 27 | function show_some2d(folder, n, cmap, savefig, save_path, save_name)
img_names = dir(folder);
assert( length(img_names) >= (n+2));
figure;
set(gcf, 'Units','pixels', 'Position', [0, 0, 400*n, 400])
for i = 3 : n+2
axis equal;
img = imread(fullfile(folder, img_names(i)... |
337e1974b4d895dc078fc2dd9a1af21ea29fb6af1c7998cf28a34408f5636c05 | MATLAB | 837 | 36 | function [z_info, currentZ, totalZ] = zpos(im_str)
%ZPOS gets z-plane information from the image string of bioformats
idx_1 = strfind(im_str,'Z=');
if isempty(idx_1)
warning('No Z information available, assuming 1 Z plane');
z_info = "Z=1/1";
currentZ = uint16(1);
totalZ = ... |
fc147bff0497004ab056f338a66034b356d3c6bec16cd057b4b4f6e4a2bcf6d0 | MATLAB | 838 | 27 | function [percepThresholds, locations] = load_percep_thresh(nerveModel)
%LOAD_PERCEP_THRESH Summary of this function goes here
% Detailed explanation goes here
dataPath = get_data_dir();
load(fullfile(dataPath, ...
'Validation\perceptual thresholds\perceptual threshold experimental data.mat'), ...
'... |
1442ee2d250148b03d7fdf410cf481a030f8c8599fd8d1615697914f54fb1a82 | MATLAB | 839 | 40 | function [a1,a2,d2,eegz] = fitness_calc_swd(A1)
% Simulate model for SWD
Liley_params;
fs = 255.5661;
tcut = 2; % apply for transients
TDatend = 2.3047;
T1=0:1/fs:TDatend+tcut;
T2 = 0:1/fs:TDatend;
T1 = T1*1000; % cnvert to ms
or=-1;
paramstoest = 1:22;
paramsinput = [paramsvec, zeros(1,10)];
paramsi... |
96db6e77cc9c4a4b1afd72e96af826bdd1a95b4494df3b69ae4431b55860865d | MATLAB | 839 | 39 | function [meas] = get_comm_corr(wei,dist)
inv_wei = 1./wei ;
meas = nan(4,1) ;
m = logical(triu(ones(s+ize(wei,1)),1)) ;
% eff (inv shortest path)
try
sp = 1./distance_wei_floyd(inv_wei) ;
meas(1) = corr(sp(m),dist(m),'type','s') ;
catch
warning('could not comput eff')
end
% -search information
try
... |
348c44c4a1b93532c3b67ae32588671e8fec0f5948f3415262a2b117b5001da9 | MATLAB | 840 | 23 | function [cutout,Tcutout]=SelTimesAssem2(twin,Tmtx,data,tRange,bw)
% Select specified time range around trial periods from continuous data in
% workspace
%
% Aleksander PF Domanski PhD UoB 2016
% aleks.domanski@bristol.ac.uk
nTrial = size(tRange,1);
LTr = length([-twin:bw:twin]);
if size(data{1},1)~=length(Tmtx)
Tm... |
065cd82e16f96749f0880329a8880aae45b7d1872ed132dbbe43a9a1715d76f8 | MATLAB | 842 | 23 | function [response] = inputvalue(prompt,dlg_title,num_lines,def)
BackERPLABcolor = erpworkingmemory('ColorB');
if isempty(BackERPLABcolor) || numel(BackERPLABcolor)~=3 || any(BackERPLABcolor(:)>1) || any(BackERPLABcolor(:)<0)
BackERPLABcolor = [0.7020 0.77 0.85];
end
ForeERPLABcolor = erpworkingmemory('ColorF')... |
ceb594fa6b28c2e1beeb54a1838be55e1d9644f88e29b77f9775850ff425bd76 | MATLAB | 842 | 25 | function TRIALS = TrialFcn_BasicCharacterization_SanesLab(TRIALS)
global TONE_CAL NOISE_CAL
%If it's the start
if TRIALS.tidx == 1
% if TRIALS.TrialIndex == 1
%Load tone calibration file
[fn,pn,fidx] = uigetfile('C:\gits\epsych\UserFiles\SanesLab\SpeakerCalibrations\*.cal','Select tone calibration file');... |
c37cae37a0e25a46597d58e90ce25b8e23cbab16321a8e76db15ebf4768307f7 | MATLAB | 843 | 35 | function makevisible_SanesLab(h,dev,module,param)
%makevisible_SanesLab(h,dev,module,param)
%
%Custom function for SanesLab epsych
%
%This function makes certain GUI text and dropdown menus visible if the
%correct parameter tags are available in the circuit.
%
%Inputs:
% h: handles of dropdown menu or text
% dev: ... |
b1c7d149289edbd02e3ff2511d716b30a2ea87d28202bd2681c7afce6cf59d03 | MATLAB | 844 | 28 | function [extrema,inds] = minmax(X)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/08/2010
%
% minmax - Simultaneous overall smallest and largest components.
%
% Usage:
% [extrema,inds] = minmax(X)
%
% Description:
% Y = MINMAX(X) returns the minimum and maximum values, of the array X
% such that... |
578914ce7ad34eab43a2cb9bd623a37c6c9b945a3181291ed04ad954c2884889 | MATLAB | 845 | 37 | function [Ix,Iy] = forward_gradient_2d(I)
% Iy = volshift(I,1,0,0) - I;
% Ix = volshift(I,0,1,0) - I;
% Iz = volshift(I,0,0,1) - I;
% Ix(:,n,:) = 0;
% Iy(m,:,:) = 0;
% Iz(:,:,o) = 0;
[m,n] = size(I);
Ix = zeros(size(I));
Iy = Ix;
for y = 1:m-1
for x = 1... |
7c4053d3aeec9ff9f31546d5ce5621dd882a7b95191a04075483ba9d735815a8 | MATLAB | 845 | 36 | function [c_info, currentC, totalC] = channel(im_str)
%CHANNEL gets channel information from the image string of bioformats
idx_1 = strfind(im_str,'C=');
if isempty(idx_1)
warning('No channel information available, assuming 1 color image');
c_info = "C=1/1";
currentC = uint16(1);
... |
a3f7bffa35d0355a9fe42c84874fc175b3706c867c091bbdd30170eb766a6877 | MATLAB | 845 | 32 | function [semValue] = sem(array,weight,dim)
%SEM measure the standard error of the mean for array along a specific
%dimension(dim)
% Author: Ali Karimi <ali.karimi@brain.mpg.de>
if ~exist('dim','var') || isempty(dim)
dim = 1;
end
if ~exist('weight','var') || isempty(weight)
weight = ones(size(array,1),1);
end
... |
8cc8cd778d4db1b77f294a6db5d5b8bd6b580297f1ba9c71c00365c84f79a69a | MATLAB | 846 | 23 |
function [cross_coords,xCenter,yCenter]=initialize_fixation_cross(window,theRect)
[screenXpixels, screenYpixels] = Screen('WindowSize', window);
% Set up alpha-blending for smooth (anti-aliased) lines
Screen('BlendFunction', window, 'GL_SRC_ALPHA', 'GL_ONE_MINUS_SRC_ALPHA');
% Setup the text type f... |
a85e4092d600d1df1135e0aa7166504dc2d9648da66229100538e38d575ebb09 | MATLAB | 847 | 33 | function Qdec2 = getQdecVarData(Qdec1,Vars)
% Qdec2 = getQdecVarData(Qdec1,Vars)
%
% Returns the data for the variables in Qdec table Qdec1 that are named in
% Vars.
%
% Input
% Qdec1: Two dimensional cell string array of Qdec data (eg. read with
% fReadQdec).
% Vars: One dimensional cell string array.
%
% Output
% Q... |
3f692d7a1a575835f9a8aee40f7c49c5bba13e85bc1046a477e212256cc01c27 | MATLAB | 849 | 26 | function [fft_feature] = extract_fft(sig,SR)
L = size(sig,1);
Y = fft(sig);
P2 = abs(Y/L);
P1 = P2(1:round(L/2)+1);
P1(2:end-1) = 2*P1(2:end-1);
f = SR * (0:round(L/2))/L;
block_11 = mean(P1(f<=50));
block_21 = mean(P1(f>50 & f<=100));
block_31 = mean(P1(f>100 & f<=150))... |
5e30c1697023c6d2068e5ab34d6546c4a2015222c5b200b1f8e963dcc428b187 | MATLAB | 851 | 33 | function xc = getCrossCorrelogram(dat1,dat2,lags,noResign)
if ~exist('noResign','var')
noResign = 0;
end
% get cross-correlogram
nMice = numel(dat1);
xc = cell([1,nMice]);
for k = 1:nMice
lagbins = int64(lags{k}/(lags{k}(2)-lags{k}(1)));
xc_tmp = nan(numel(lagbins),1);
sTot = size(dat1{k},1);
for ... |
5e88e36488b0a159ecf5bd63068bc24dd903f24f98a6ad4a0d7f10b8c14e1a7d | MATLAB | 851 | 40 | function [C,Cthr] = get_cohesion_matrix(D, sym)
% https://www.pnas.org/content/119/4/e2003634119
% https://github.com/moorekatherine/pald/blob/main/R/pald_functions.R
if nargin < 2
sym = 1 ;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
n = size(D,1) ;
C = zeros(size(D)) ;
for ... |
588d8abb484b49d105b3019b3a76f83150d2e58afc4bb4f7ee22564f8a99a93c | MATLAB | 854 | 26 | function Name=RegionLabeltoName(Label)
% Creates the name of a folder that will contain the analysis results
%
% INPUTS:
% - Label: region of interest in the analysis. Initialized in RunQUIQI.m.
% OUTPUTS:
% - Name: cell array of strings.
%_____________________________________________________________... |
4a34348cfc386cac308b754995029307e748bbd2e4e34c294df5bda62246521b | MATLAB | 855 | 34 | function out = FCLSU(HIM,M)
% Fully Constrained Linear Spectral Unmixing
% Perform a Linear least squares with nonnegativity constraints.
% --------------------------------------------------------------------
% Input: HIM : hyperspectral image cube [nbands x nsamples]
% M : set of p endmembers [nbands... |
11ab7b38e0b6a804f2a865c51b4906252e1fd4e8fa150cee4cfcb27d1e4ebeea | MATLAB | 858 | 43 | function DI=dunns(distM,ca)
%%%Dunn's index for clustering compactness and separation measurement
% dunns(clusters_number,distM,ind)
% clusters_number = Number of clusters
% distM = Dissimilarity matrix
% ind = Indexes for each data point aka cluster to which each data point
% belongs
uu=unique(ca) ;
nn=length(uu... |
b20166d2b97d88b6746fc816c7d2ff63b95cb64bc5e5875169b9bb727524f573 | MATLAB | 858 | 37 | function [TT,tanks,TDTfig] = TDT_SetupTT(TT)
% TT = TDT_SetupTT
% [TT,tanks] = TDT_SetupTT
% [TT,tanks,TDTfig] = TDT_SetupTT
% TDT_Setup(TT)
%
% Initialize TDT TTankX activex control in invisible window and return
% handle to control (TT), registered tanks, and a handle to the invisible
% figure (should close ... |
025f434df614a1808af7c959e3f5c4770390a3f08bf7435c363bd3ab8312e594 | MATLAB | 859 | 33 | function AddFileAnnotations(self, annotFilePath, overwrite)
% Add annotations contained in 'annotFilePath' to annotations
% table
self = Load(self);
if isempty(self.AnnotationTable)
return
end
fileAnnots = readtable(annotFilePath);
annotT = self.AnnotationTable;
if overwrite
labelsStr = repmat({'UL'}, size(... |
078dda5fc678603a0290fee31339fef2434d6fb18ae8db8a92ddc6d1fbe156e4 | MATLAB | 859 | 26 | function [out_dataSorted,out_forceSteps] = dose_responseSort(in_sweeps, in_sweepsCol,in_row, in_forceSteps,in_sortByForce)
% Sorts force-response data from sweeps{} array by force level
% in_sweeps: sweeps{} array with all data
% in_sweepsCol: column of interest from sweeps{} (7=AUC, 9=peaks)
% in_forceSteps: 1x5... |
52b6fc7a337a906b157f4b2698eaf3253053ac8073308699a6839d62220054a9 | MATLAB | 859 | 20 | % part of https://github.com/LudgerS/MRSartifactRemoval
%
% Normalized Gaussian curve
% follows Bruce et al., "An Analytical Derivation of a Popular Approximation
% of the Voigt Function for Quantification of NMR Spectra", Journal of
% Magnetic Resonance (1999)
%
% lineshape according to Bruce et al.
% lineS... |
f0297684677383ff12410b6e296e5674eae4c9d7d223ceba7b6dd85c7c3a3b79 | MATLAB | 860 | 33 | function [pband,ptot,per_power] = bhpower(filepath, Fs,freqRange)
%BHPOWER
% Calculates percentage of power in a specified frequency range, such as
% that of a breath-hold task.
% Reference: https://www.mathworks.com/help/signal/ref/bandpower.html
%%%%%%%%%%%
% Inputs:
%%%%%%%%%%
% filepath = full path to input ... |
63572ff7b8701e829a79c7de112e3186c1b224acf8a42f0b8590d0ffcb810d1d | MATLAB | 863 | 37 | function d=spkd(tli,tlj,cost)
%
% d=spkd(tli,tlj,cost) calculates the "spike time" distance
% (Victor & Purpura 1996) for a single cost
%
% tli: vector of spike times for first spike train
% tlj: vector of spike times for second spike train
% cost: cost per unit time to move a spike
%
% Copyright (c) 1999 by Daniel Re... |
abc16043abad8cf07c47fcfceb8432fca8bfc1619692b90cac69e2f8ff7918d5 | MATLAB | 863 | 35 | %% Initialize the critic
curr_input = input{1};
critic.rewTime = round(find( [0 diff(curr_input(2,:))]>0 , 1 ) / 100);
critic.cueTime = ceil(find( [0 diff(curr_input(1,:))]>0 , 1 ) / 100) + 1;
critic.steps = size(curr_input,2) / 100; % 100 ms long boxcar basis set
critic.rpe_rew = 0;
critic.rpe_cue = 0;
critic.w = zer... |
0d3c1de40557c4cca2879bdf48b2f0e79d68ed4c00a8376ed52b7091d308c93e | MATLAB | 864 | 21 | % Signal Processing Toolbox check
% axs Nov 2020
function SigProcT_here = SignalProcessingToolboxCheck
% Get Toolbox list from ver
tbxs = ver;
[a, tbxs_n] = size(tbxs);
tbx_cell = cell(1,tbxs_n);
tbx_cell = {tbxs.Name};
SigProcT_here = any(ismember(tbx_cell,'Signal Processing Toolbox'));
if SigProcT_here == 0
% ... |
cb93fb5291abedd3fdd5df6b8678f1e76311163613c83e65dd03a9e0f5b68edf | MATLAB | 864 | 38 | function plot_qti_invariant(s,inv_name,disp_range)
% function to plot one invariant for different fits/protocols
%
n_fits = max(size(s));
% by default, we take the middle slice to be shown
tmp_inv = getfield(s{1},inv_name);
slice = round(size(tmp_inv,3)/2);
% open a figure
figure()
% for each fit (invariant structu... |
77cde14f7b39436d32092d5359953f2ffbc4f202175b57d596fd0f0c6e163c6f | MATLAB | 868 | 41 |
function output = erpgettoolversion(field)
output = [];
if nargin<1
help erpgettoolversion;
return
end
if nargin==1 % read
try
output = erplab_session_state('get', field);
if ~isempty(output)
return
end
paths = erplab_user_paths;
if ~isempty(paths.legac... |
89d00edcf82123476ba59ad6d4425efa7c5d271461b16f6d98e01b9594510a7e | MATLAB | 868 | 36 | function varargout = SelectTrial(TRIALS,parameter)
% val = SelectTrial(TRIALS,parameter)
% [val,i] = SelectTrial(TRIALS,parameter)
%
% Select values from a particular trial index in the structure TRIALS. For
% use with custom Trial Selection functions. See help DefaultTrialSelectFcn
% for more info.
%
% NOT... |
eb44565fb4230f78b910684c1f9aa0ec0cdc59ee27274795e35ae8e6ec69b032 | MATLAB | 869 | 28 | function in_use = DB_InUse(table,id,state)
% in_use = DB_InUse(table,id)
% in_use = DB_InUse(table,id,state)
%
% Use to retrieve or alter 'in_use' field of a table. Always returns
% current value of 'in_use' field before changing the state.
%
% state: 'yes','no','toggle'
%
% DJS 2013
if nargin < 2 || nargi... |
23455617432fcd7cd75b99d3fd2558bff4225d810a6f361da37821826771bf08 | MATLAB | 871 | 28 | function FigOnTop(figh,state)
% FigOnTop(figh,state)
%
% Maintain figure (figure handle = figh) on top of all other windows if
% state = true.
%
% No errors or warnings are thrown if for some reason this function is
% unable to keep figh on top.
%
% Daniel.Stolzberg 2014
% narginchk(2,2);
assert(ishand... |
b4282c9d7acb0380a3e6bc14287b214da810e6dc859fac77d961204a92c7bde4 | MATLAB | 872 | 47 | function [X,fixedPoint] = checkDuration3(currentValue, Target, initBuffSize)
% [X,fixedPoint] = checkDuration3(currentValue, Target [initBuffSize])
%
%Takes in the current region number and adds it to a list of default size
%20. When the standard deviation of the list of values is < 1 then X = 1,
%otherwise X = 0.
%
%... |
514cd58cc9bff2b06640085c8093fcf7b854881d423fa913f1b2d54286ca8425 | MATLAB | 873 | 29 | function [band_sig] = ieeg_butterpass(signal,band,srate)
% function to dobandpass filtering for specified band
% input:
% signal = time X channels;
% band= [start:stop] or [start stop];
%automatic stuff:
num_chans=size(signal,2); % number of channels
Rp = 3; Rs = 60; % third order Butterworth
delta = 0.001*2/srate;
lo... |
445017558e68a3ee8cd2dbea82dd2440a8232e5397ad88e77d3dd4ade3c0800f | MATLAB | 874 | 39 | function h = drawPerformance_SNR(X, ax, color)
if isempty(X)
h = nan; return
end
% Get signal levels
attns = unique(X.Atten);
nAttn = numel(attns);
% Preassign
N = zeros(1, nAttn);
Y = zeros(1, nAttn);
% Get performance
for j = 1 : nAttn
rows = X.Atten == attns(j);
N(j) = sum(rows);
Y(j) =... |
4e221fe3b3fed8e4f16546a545ef0a4c74e4289392e7f017aa6f532f8be1013a | MATLAB | 874 | 21 | function [XTrainNewClass,YTrainNewClass] = augmentDeepInsightClass(XTrain,YTrain,num,j,inx)
inx_class = inx(double(YTrain)==j);
cnt=1;
for k=1:length(inx_class)
for n=k+1:length(inx_class)
XTrainNewClass(:,:,:,cnt) = uint8(0.5*(double(XTrain(:,:,:,inx_class(k)))+double(XTrai... |
d76dae6d935c506cf978059ae33bf1152fdbe90fa4e729a4bf6294b6ef1a703f | MATLAB | 874 | 34 | function [Y,mri] = fs_read_Y(Y_fname)
% [Y,mri] = fs_read_Y(Y_fname)
%
% Reads Freesurfer's .mgh or .mgz data files (eg. cortical thickness data
% files generated with mris_preproc).
%
% Input
% Y_fname: A Freesurfer's cortical data file.
%
% Output
% Y: Data matrix (nmxnv, nm total # of maps, nv #vertices).
% mri: ... |
44dad4001fbc1697f4ac5f12aa272ee9362129cff6d16bf99451eba3baadb968 | MATLAB | 875 | 30 | function Plot_individual_VSspecs(DoseColors,FigureID,mousenames,numanim,f,WAKEspec_dose_anim,NREMspec_dose_anim,REMspec_dose_anim,PlotConditions)
VS_spectra_allVS={WAKEspec_dose_anim,NREMspec_dose_anim,REMspec_dose_anim};
pcolor=cell(length(PlotConditions),1);
for pcol=1:length(PlotConditions)
pcolor{pcol}=rgb... |
29a7bad622bcbf715459f1688753befa95b47a47a99c519a05d49890e3ca66f9 | MATLAB | 879 | 36 |
function [yticksLabel, msgboxText]= f_decimal(yticksLabel,ytick_precision)
msgboxText = '';
if nargin<1
help f_decimal;
return;
end
if isnumeric(yticksLabel)
yticksLabel = num2str(yticksLabel);
end
if nargin<2
ytick_precision=0;
end
yticksLabel = char(yticksLabel);
if isempty(str2num(yticksLabel... |
82dddbe963bfe2be5f2c7d2559cff8b4ea0cd95ee17c059d7ed17fd00dbd0865 | MATLAB | 880 | 26 | function [mti2,starttime] = tpcorrectmti(mti, filename,globaltime)
% TPCORRECTMTI - Correct NewStim MTI based on recorded times
%
% [MTI2,STARTTIME] = TPCORRECTMTI(MTI, STIMTIMEFILE,[GLOBALTIME])
%
% Returns a time-corrected MTI timing file given actual timings
% recorded by the Spike2 machine and saved in a file na... |
1c6d01c7f6df9c0b3878c9cca90b9538f0f8334c5f0bdfa15991ab37e53140fa | MATLAB | 883 | 30 | function [RestEMG]=ExtractRestEMG(address,ID, begin, opt)
% in=[address '\EMG\' ID '\' ID '_S1R' int2str(run)];
%in=[address '\EMG\' ID '\' ID '_S1REST'];
in=[address '\EMG\' ID '\' ID '_S1R0'];
load(in);
% Ancho de la ventana de inactividad
Window=0.25;
% Índices de comienzo de señal de EMG a considerar
... |
a6f0c8ae9711ee77327c645c84bd2eab3d8243a9bcdaf9920d8db0fbf82d2a4f | MATLAB | 884 | 30 | function CreateProject(self)
%CREATEPROJECT Creates new DeepActionProject
% CREATEPROJECT(SELF) creates project folder in SELF.PROJECTPATH and
% config file (if already exists, asks user whether to overwrite)
if ~isfolder(self.ProjectPath)
mkdir(self.ProjectPath)
else
msg = sprintf('Project with path %s al... |
16f444c2425f781761b6bbab925d5e12b9bcff94ad6addd2fcb0e8cd8e1fe3c2 | MATLAB | 885 | 30 | function criticals = compute_criticals(perm_cluster_t, n_betas)
% Compute the criticals based on the distributions in perm_cluster_t.
%
% perm_cluster_t: (n_perm, n_betas, 2, 2)
cluster_threshold = 95 ;
% indices:
% n_betas
% 2: I1 and I2
% 2: mean cluster, max cluster
criticals = zeros(n_beta... |
78d7a4e6c92728376ba08b31fa2dd010e758a989d461f754f8fc3a32b34a10c9 | MATLAB | 885 | 37 | function [n,J] = quadlength(x)
% quadlength -- Find length and dyadic length of square matrix
% Usage
% [n,J] = quadlength(x)
% Inputs
% x 2-d image; size(n,n), n = 2^J (hopefully)
% Outputs
% n length(x)
% J least power of two greater than n
%
% Side Effects
% A warning message is i... |
715e045c82d400da48124ebf2b7356403646d52548084b932d7e591ac5a5316c | MATLAB | 888 | 28 | function Gradient=gradientinterpol_noGPU(Gradient_ori,node_iris,pointsTetra,bar)
DT=Gradient_ori(pointsTetra,:);
DT1=reshape(DT',3,node_iris,4);
DT2=permute(DT1,[3 1 2]);
bar2=reshape(b... |
8bb41457b771eab45fb11d49e16a3d1a97f00abe3ba7d555bcc0a9aefe8dc7c8 | MATLAB | 888 | 32 | function tH = ieeg_RenderGifti(g,varargin)
% function to render a gifti
%
% input:
% g: gifti file with faces and vertices
% varargin{1}: sulcal_map, can be loaded with read_curv('lh/rh.sulc')
%
% Viewing Angle: can be changed with ecog_ViewLight(90,0), changes both
% angle and light accordingly
%
% DH 2017
% co... |
a0568a29ac440e23dfd21bae56f1d9cde4c841d6a9fcd9857dbc24c85759ceb9 | MATLAB | 890 | 28 | function [n, npw, ts, wave] = plx_waves(filename, channel, unit)
% plx_waves(filename, channel, unit): Read waveform data from a .plx file
%
% [n, npw, ts, wave] = plx_waves(filename, channel, unit)
%
% INPUT:
% filename - if empty string, will use File Open dialog
% channel - 1-based channel number
% uni... |
a6ca899fc757ca8c44bfcec0342cdcb13aaed22a449858ca324c3db35fddd789 | MATLAB | 890 | 31 | %% Set some variables
tank = 'TankName';
block = 1;
%% Read continuous LFP from tank
cfg = [];
cfg.tank = tank;
cfg.blocks = block;
fullLFP = ft_read_lfp_tdt(cfg.tank,cfg.blocks);
%% Call custom trial function (trialfun_tdt) to segment continuous LFP data
cfg = [];
cfg.tank = tank;
cfg.blocks ... |
85031d5fa0b1137be33bea02bb474eb7b52a513c78ae497aebf097cf77a05c6e | MATLAB | 896 | 35 | function [prior_setup] = getNscales(prior_setup, dim_T, dim_P)
D = numel(prior_setup.T) + 1;
for ss = 1:D
if(ss == 1) % V
prior_setup_ss = prior_setup.V.setup;
dim_U = dim_P;
else %T{ss-1}
prior_setup_ss = prior_setup.T(ss-1).setup;
dim_U = dim_T(ss-1);
end
NS = 0;
... |
4e9fa5e1f026145ba23d5a8595b0ee01420bc6ed7b6cac7aeef13ffd6af77152 | MATLAB | 898 | 34 | function cvals = Calibrate(vals,C)
% cvals = Calibrate(vals,C)
%
% This function uses the Matlab PCHIP function in order to estimate values
% between points (e.g. tone frequencies) which were measured.
%
% C is a calibration structure saved from a call to the CalibrationUtil GUI
%
% vals : value to calibrate
... |
7a9705be766aa913be0ea3809e762b2c21cc2125d2ad4b8b2d9b568cf9c1fd1e | MATLAB | 898 | 39 | function step3a_getCooling_nTrials
if nargin ==0
pathname = Cloudstation('Vowels\Perceptual_Constancy');
end
pathname = fullfile( pathname, 'Cooling\Data\Cross-referenced Behavior');
% Get files
files = dir( fullfile(pathname, '*.mat'));
% For each file
for i = 1 : numel(files)
% Load data
load( fu... |
e8c4b7656fd2b1ab2829579e80085f382772ab5f5c21f9041193557ab0892602 | MATLAB | 898 | 22 | function NoiseClean = WienerInDFT(ImNoise,sigma)
% function g = WienerInDFT(ImNoise,sigma) removes periodical patterns (like the blockness) from input noise in frequency domain
% Used to remove blockness and other artefacts from noise extracted from JPEG images
% INPUT:
% ImNoise noise extracted from one i... |
846da0d5cbae6d99cedcc574a3bfbcc85733ba5d5a6aaabe7128f1137c0c97d3 | MATLAB | 899 | 29 | function point = random_point(shape)
% See https://it.mathworks.com/matlabcentral/answers/483706-generate-random-number-inside-a-closed-area
%% Triangulate
tri = triangulation(shape);
XY = tri.Points;
%% Calculate areas
v1 = XY(tri(:,1),:);
v2 = XY(tri(:,2),:);
v3 = XY(tri(... |
b8fd404784a2222a29d927f442c9b47813275b3768b98b98f4738823f2cd35b1 | MATLAB | 900 | 23 | % TWOPHOTONGLOBALS - Declares global variables for TWOPHOTON analysis package
%
% Parameters for configuration -- See help SETTWOPHOTONCONFIGURATION
%
% TwoPhotonPlatform - The name of the Platform we are using
% TwoPhotonSynchronization - The name of the Synchronization method we are using... |
2577e75447a7c27a6dfae326d9f9824ce1f3c7399a92e70aaf5ea0f0d07e594c | MATLAB | 902 | 33 |
p = 0.5:-0.1:0;
for id=1:length(p)
[k,alpha,f]=stability_anesthesia_fieldmodel(p(id),'bottom');
[TheoryWaveVol(id),TheoryWaveVol_largeWave(id)]=speed_by_LR(k,alpha,f);
end
% figure;
% plot(p,TheoryWaveVol,'o-');hold on;
% plot(p,TheoryWaveVol_largeWave,'o-');hold on;
% set(gca,'xdir','reverse');
% ylabel('10... |
f7cb9f3e9a6e64324fa967db64f85da6c71b081ceb8caa003d7d48e50c55a1a3 | MATLAB | 902 | 35 | function save_plot(dirPlots, name, painters)
arguments
dirPlots,
name = [],
painters = true
end
if isempty(name)
t = sgtitle();
if isempty(t)
name = gca().Title.String;
else
name = t.String;
end
end
if ~isfolder(dirPlots); mkdir(dirPlots); end
if painters
... |
1cb6e463c81973ad3081a8b854b9d60917a78f82ebb7c15fb470802ebad144e7 | MATLAB | 903 | 26 | function [volumes] = read_nifti_folder(nifti_path, hemisphere)
%READ_NIFTI_FOLDER read nifti files within a folder
% get .nii and .nii.gz files
nifti_dir = dir(fullfile(nifti_path, '*.nii*'));
nifti_dir_T = struct2table(nifti_dir);
row_names = cellfun(@(x) extractBefore(x, '.nii'),...
nifti_dir_T.name, 'UniformOut... |
815d1ae702283857523c51dfc0b5e467ad102a701a41767af79bf8a806601c65 | MATLAB | 903 | 35 | function handles = findRewardType_SanesLab(handles)
%findRewardType_SanesLab(handles)
%
%Custom function for SanesLab epsych
%
%This function sets GUI parameters based on the reward type.
%
%Inputs:
% handles: GUI handles
%
%Example usage: findRewardType_SanesLab(handles.module,handles.dev)
%
%Written by ML Caras ... |
f629f03a8133671f8f74ee5ef66b23a6620e9b42c0598243a6309c27592fd51a | MATLAB | 904 | 21 | function [outputArg1,outputArg2] = plot_epineurium(epiData)
%PLOT_EPINEURIUM Plot the extracted geometry from STL files.
% can deal with several epineurium regions
% By Carla Hetreau - 10.2021
hold on;
for idCross = 1 : length(epiData)
if ~isempty(epiData{idCross})
nan... |
c320cca8f268c8022e386f60ba41fe7dd2809aed04da25a681a39a808898a113 | MATLAB | 906 | 37 | function fWriteQdec(fname,Qdec)
% fWriteQdec(fname,Qdec)
%
% Writes cell string array Qdec to a Freesurfer's Qdec table data file.
%
% Input
% fname: The name of a Qdec table data file.
% Qdec: Two dimensional cell string array with the data.
%
% $Revision: 1.2 $ $Date: 2015/01/06 17:14:53 $
% Original Author: Jorge ... |
edb7371719fd0f8910d970565491189a464d1fb73089bf1ca26c268f7cdf6cf7 | MATLAB | 906 | 25 |
function TGM_erp = f_compute_TGM_mvpa(mvpc,svm_predict_TGM,tst_target_TGM,svm_scores_TGM,OutcomeMetric)
% fprintf('Computing Temporal Generalization Matrices (ACC & AUC)...\n');
nTestT = size(svm_predict_TGM,3);
TGM_erp = nan(nTestT, nTestT);
for Numoftest = 1:nTestT
tst_target = squeeze(tst_target_TG... |
ee61acd691b8b0fb6598cebe73ccf63c76f713bc7d8d524bd8b5639045e449c1 | MATLAB | 906 | 29 | function theseSubs = ccep_getSubFilenameInfo(myDataPath)
% input: bids datapath where derivatives from av_ccep are saved
% returns list with all subject names, sessions and runs
%
% dhermes 2020
theseSubs = [];
% get all subjects
tempSubs = dir(fullfile(myDataPath.output,'derivatives','av_ccep','sub-*'));
for kk = 1:... |
5d79594fd342a21373f60ee723269dd0b1c01a48de2a1e1b9eac11736eec85aa | MATLAB | 909 | 37 | function [xmin, xmax, ymin, ymax] = rect_approx(poly, plotr)
% RECT_APPROX Approximates a polygon to a rectangle that passes through its
% farest vertices.
%
% [xmin, xmax, ymin, ymax] = rect_approx(poly, plotr)
%
% Input: - poly: vector of x and y coordinates of the polygon in columns
% - plotr: t... |
f5d404bc33bbd5e1e96a09bbf7fd66b9afd43be432823513a3960ef6dab81d51 | MATLAB | 910 | 36 | function time_idx = compute_time_CC(all_h)
% Based on a h-mask, compute connected components of 1's accounting for
% channel topography.
%
% Inputs
% all_h: (n_chan, nT_data) ;
%
% Outputs
% time_idx: time index of the cluster including all input channels.
[nchan, nT] = size(all_h) ;
h_tot = sum(... |
68c1ceb82085dd381b5f2f41569a739a25917613e25b381fecf3c799829c544a | MATLAB | 912 | 38 | clc; clear; close all
Fig5b=figure();
Ntrials_3=20000;
%Ntrials_3: number of learning cycles to learn the background.
%There is no embedded pattern in afferents.
%(Note initial conditions in this step are from step 2)
N_mu=500; %There are \mu independent embedded patterns, 500 simulations (number of simula... |
26f48570651390e9e2a15bc736a2e9c448e079bba1b4c88280069e3ec4b5d300 | MATLAB | 916 | 26 | function cm_data = my_blues2(m)
% Copied from
%https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/_cm.py
%
cm = [...
0.96862745098039216, 0.98431372549019602, 1.0 ;
0.87058823529411766, 0.92156862745098034, 0.96862745098039216;
0.77647058823529413, 0.85882352941176465, 0.... |
485fad032c3aac533a9d1da4e03c1eea9f43be79f2304605dac6baf4028f0d7a | MATLAB | 916 | 36 | clc; clear; close all
Fig5a=figure();
Ntrials_3=20000;
%Ntrials_3: number of learning cycles to learn the background.
%There is no embedded pattern in afferents.
%(Note initial conditions in this step are from step 2)
N_mu=500; %There are \mu independent embedded patterns, 500 simulations (number of simula... |
a887a523fd17306a3b50079b7652aa2c0a2211f0b23f825d39ba490f8cf3f36a | MATLAB | 917 | 23 | % Quality control Q5
% Display the functional image after normalization with reference to the MNI template
% Xin Di, July 13, 2022
clear
subjfolder = dir('F:\fMRI_QC\fmri-open-qc-rest_bias_corrected\sub*');
for subji = 1:length(subjfolder)
imgs = char(['F:\fMRI_QC\fmri-open-qc-rest_bias_corrected\' subjfolder(su... |
2d6e0ed926f5d95aca677b8c28b97f31679a84f3d5a69e03005b54c2d1bf4d44 | MATLAB | 924 | 20 | function [MAP, m_h, s_h] = mar_ComputeMAPandPrediction(NBgA, NAgB, NAgA, NBgB, pNBgA, pNAgB, pNAgA, pNBgB)
% Compute posterior MAP, mean and standard deviation, using the analytical
% formula for beta distributions.
%
% The advantage of using conjugate distribution is that posterior estimates
% (mean, variance, MAP) ... |
79fe618a122a07a6543cb04d0b09ff2c29b1450551acc134b9c5fdf31099b244 | MATLAB | 924 | 23 | % Quality control Q1c
% Plot the first functional image and check its intitial position with reference to the MNI template
% Xin Di, July 13, 2022
clear
subjfolder = dir('F:\fMRI_QC\fmri-open-qc-rest_bias_corrected\sub*');
for subji = 1:length(subjfolder)
imgs = char(['F:\fMRI_QC\fmri-open-qc-rest_bias_corrected... |
0520c8b74269d407740c9542bde5905e1b7e3c0e3ea934fb2e4920a785ac5024 | MATLAB | 927 | 34 | function pthresh = lme_mass_FDR(p,fdr)
% pthresh = lme_mass_FDR(p,fdr)
% This function has slightly modified the freesurfer's fast_fdrthresh
% function (jbernal modification 2010)
%
% p = list of p values between -1 and 1
% fdr = false discovery rate, between 0 and 1
%
% Based on Tom's FDR.m from
% http://www.sph.um... |
1251ee8dce4a2335c6aa6c326bab83d23b9467d5572bfb1db41852b36e20210c | MATLAB | 928 | 35 | function motif_class = network_motif_classification(n1, n2, t1, t2)
vec = [0,n1,n2];
n_distinct_neurons = length(unique(vec));
list_vec = [n1, n2, t1, t2];
if t1 < t2
n1_new = n1;
n2_new = n2;
t1_new = t1;
t2_new = t2;
else
n1_new = n2;
n2_new... |
851daa87f6dbb30a5804e6b9efaac4217cd59cd7bb9e83a4fca8c4a2a734e92c | MATLAB | 929 | 25 | function [tc, coefVar]=WaveNoise(coef,NoiseVar);
% Model each detail wavelet coefficient as conditional Gaussian random
% variable and use several two-dimensional moving windows to estimate the
% variance of each wavelet coefficient in conjunction with a Wiener-type
% denoising filter
%Input:
% coef: ... |
8c9a166a8474de1d65b1f36929dec285a025efe29db62c4d362ff4213b038220 | MATLAB | 929 | 31 | function [params, precomputedPortion] = scaleWB3(params, couplingGroup)
% i.i.d non-mean Gaussian over spike history coefficients & constant
K = size(params.B,1);
H = double(params.H);
w_mu_idx = 1;
w_mu = H(w_mu_idx);
w = double(params.W);
params.W(:) = w + w_mu;
precomputedPortion.T = [];
%% linear terms
if(K ... |
de3b2286c65e7c28dc86e60653424b7d6a6b5cc4c8909b3c4104651becd23b20 | MATLAB | 932 | 21 | function [roi_info] = get_roi_info(roi_names)
%GET_ROI_INFO get the information about hemisphere and ROI name
roi_info = cellfun(@(x) regexp(x,'([L, R])_(\w*)_roi.mat', 'tokens'), ...
roi_names, 'UniformOutput', false);
roi_info = cellfun(@(x) {x{1}{1}, x{1}{2}}, ...
roi_info, 'UniformOutput', false);
roi_info ... |
2bb629e47896b31393f9f96e1ec9b7c523c3ccbf40edda2ccbbb568565ff95ca | MATLAB | 933 | 34 | function pthresh = SStat_mass_FDR(p,fdr)
% pthresh = SStat_mass_FDR(p,fdr)
% This function has slightly modified the freesurfer's fast_fdrthresh
% function (jbernal modification 2010)
%
% p = list of p values between -1 and 1
% fdr = false discovery rate, between 0 and 1
%
% Based on Tom's FDR.m from
% http://www.sp... |
9b389782ac5581f811f269f3b0efce6cd344f92cd631751d760a6ae8f317166e | MATLAB | 933 | 27 | %% read cortex surface from gifti
gifti_name = dir(fullfile(util.get_data_dir, ...
'template_surfaces/*.gii'));
template_surf = cell(size(gifti_name));
for i = 1:length(template_surf)
cur_name = gifti_name(i);
template_surf{i} = util.get_surface_from_gifti...
(fullfile(cur_name.folder, cur_name.name... |
68d59b421c998593a0823f08148df04c61bee32f4b3bb93d9cd0c844b92afacc | MATLAB | 934 | 36 | function [pid P] = calcpid(SA, Na, SB, Nb, T, Nt, Ntrl)
% Sample probablity distributions from discrete data and use them
% to calculate a PID with Iccs
% SA - source A (integer values in range [0, Na-1]
% Na - number of bins for SA
% SB - source B (integer values in range [0, Nb-1]
% Nb - number of bins for SB
% T -... |
21af4e4d16945881dbe01828dba9183114aa116754c8e9b33d3fcd318321a660 | MATLAB | 935 | 27 | function [p_anova_corr, pvals_T] = anova1(cur_split, taste_names, stub_rows)
%ANOVA1
arguments
cur_split
taste_names
stub_rows = ''
end
g_ids = cellfun(@(taste_names, beta_array) repmat(categorical({taste_names}), ...
length(beta_array), 1), taste_names, cur_split,'UniformOutput', false);
cur_split_arr... |
736648b068d4aa33a58d57ec81073da0098829b7f864ae5bedcaf65339188a99 | MATLAB | 935 | 31 | function R=shuffwei_partial(W,frac)
% R = shuffwei_partial(W,frac)
% Shuffle a fraction frac of the weights in connectivity matrix W to give
% random matrix R, preserving adjacency matrix (i.e., zeros do not move).
%
% Inputs
% W = weighted connectivity matrix
% frac = scalar 0<frac<=1, shuffle thi... |
65212be934ea76bff79c8a5a075e74e0a18d856e81598dd757f57b35b218f940 | MATLAB | 936 | 37 | function [ ] = show_state(params, res_file, fr, cm, range)
%show_state(params, res_file, fr, cm, range)
% Display linear drive in 3D
%
% Input: params - model parameters (with cells' coordinates)
% res_file - path to a file containing the simulation results
% fr - simulation step to display
... |
6c652f130bec8481410b66213a7232bd469a30d6e87dab567c55a1b120c96e6b | MATLAB | 936 | 48 | function run_simulation_Part1(Le)
filename = sprintf('rest_Ly300nm_Li1000nm_Le%dnm', Le);
% Set up parameters
Li = 1000; % nm
Lm = 5; % nm
Ly = 300; % nm
Lz = 300; % nm
w_K_channel = 6; % nm
w_Na_channel = 2; % nm
dx_min = 0.5; % nm
dy_min = 1; % nm
dz_min = 1; % nm
dt = 2e-8; % ms
Tstop = 1e-2; % ms
G ... |
8aa068850fd3084f53db78123d0f3dde67af9823e961b172e465f45126dfd573 | MATLAB | 936 | 28 | function mydata = analyzetpstack_loadrawfile(ds,stackname,dirname)
% ANALYZETPSTACK_LOADRAWFILE - Load a raw tuning curve file
%
% MYDATA = ANALYZETPSTACK_LOADRAWFILE(DS,STACKNAME,DIRNAME)
%
% will attempt to load raw tuning curve data from the experiment data
% that is being read by a DIRSTRUCT object DS, with ANA... |
3e6ff88d3836de09e5b15ae4a8cbbc95278c6dd38d742022887d7fb882fc4067 | MATLAB | 938 | 29 | function [overlap_raw,overlap_norm,labelnum]= maskoverlap(labeledmask1,mask2)
% MASKOVERLAP - Compute overlap of spots from 2 masks
%
% [OVERLAP_RAW,OVERLAP_NORM,LABELNUM]=MASKOVERLAP(LABELEDMASK1,mask2)
%
% Computes the 'overlap' of each spot in the labeled mask
% LABELEDMASK1 (labeled with a function like BWLABE... |
89deffcb7d8cc85cbdc4cdf3fbb125909ed48013514fde8c490f4943e921758e | MATLAB | 938 | 31 | % Publicly accessible dependent properties of an object.
%
% See also: meta.property
% Copyright 2010 Levente Hunyadi
function dependent = getdependentproperties(obj)
dependent = {};
if isstruct(obj) % structures have no dependent properties
return;
end
try
clazz = metaclass(obj);
catch %#ok<C... |
86deeaeb815fe7db66fd3d49569cee0b77407a4a0719a9bcbc932f585de27741 | MATLAB | 939 | 34 | function Cov_comp = getCompCov(X,code,P)
dataA = getOrgData(X,code,P);
s = size(dataA);
nStimImp = s(2);
[nfold,folds] = getFolds(s,P.foldtype);
Cov_comp = nan(max(P.dim.pcL),nfold);
for ff = 1:nfold
idxfold = folds{ff};
% Get train set
spkData_train = dataA;
spkData_train(idxfold) = nan;
% Ge... |
fe896200efe2beee0f2a2d0bd817799750dbf8f8d37bbc7a6bdcfba96b394545 | MATLAB | 939 | 31 | function d = DB_GetRIFResp(unit_id)
% d = DB_GetRIFResp(unit_id)
%
% Retrieves Rate-Intensity Function analysis (RIF_mdanalysis) of unit_id of
% the currently selected database.
%
% The function also sorts the subfields by stimulus level in ascending
% order.
%
% June 2014 Daniel.Stolzberg@gmail.com
... |
1f829a00b6ef24fd469381ad55565eecc28ab06f6db1f6792d8d7ace5b1f5af5 | MATLAB | 940 | 22 | % Quality control Q4
% Check registration between the functional and anatomical images
% Xin Di, July 13, 2022
clear
subjfolder = dir('F:\fMRI_QC\fmri-open-qc-rest_bias_corrected\sub*');
for subji = 1:length(subjfolder)
imgs = char(fullfile('F:\fMRI_QC\fmri-open-qc-rest_bias_corrected', subjfolder(subji).name, '... |
36572aed205fc119a38e841b66ed73f6ea3988f02d297f10a7f4d9ad9ed0379b | MATLAB | 940 | 26 | function [xpos_data,ypos_data] = get_data_from_normalized_units(ax_orig,X_norm,Y_norm)
% Convert the xpos_data and ypos_data vectors, expressed in data units, in
% normalized units.
ax_ylim = ylim(ax_orig) ;
ax_xlim = xlim(ax_orig) ;
% Annotation: normalized units so that (0,0) is the lower left corner
% of... |
332ffde090518a2e6f40711c707854ff0ad115fff0eb3a92a525d781edef4d02 | MATLAB | 943 | 34 | function [Dataout, EPStr]= f_checktable_gridlocations_waviewer(Data,LabelStr)
countEp = 0;
EPStr = '';
Dataout = cell(size(Data,1),size(Data,2));
Data = string(Data);
for ii = 1:size(Data,1)
for jj = 1:size(Data,2)
count = 0;
try
[C,IA] =ismember_bc2(strtrim(char(Data(ii,jj))), string(L... |
898a140b31e0efb6775894db52dc34abc62c074094ae52b5c88391c2b810b295 | MATLAB | 943 | 27 | function dirtpexp_assocs
fitzlabtestid; % make sure this is in
tpassociatelistglobals;
s = input('Should we clear current associate list? (y/n) :','s');
if s=='y'|s=='Y', tpassociatelist = tpassociatelist([]); end;
r = input('What is PND of ferret? (enter -1 to skip) :');
if r>0, tpassociatelist = [ tpassociatelis... |
24ba230c96d89cee0111148e70fd385bb79c82541ab91576b3b45d2367195dfb | MATLAB | 945 | 39 | function my_save_fig(fig_h, fn_save, eps_fig, fig_fig, pdf_fig)
% Save figure fig_h.
if nargin<5, eps_fig = 0 ; end
if nargin<4, fig_fig = 0 ; end
if nargin<3, pdf_fig = 0 ; end
if eps_fig
file_extension = '.eps' ;
format_to_save = 'epsc' ;
elseif fig_fig
file_extension = '.fig' ;
for... |
ad9b3e48840181198cfeb9edafc419169e69d4c19dfb9b2dfcdd0372f1785dab | MATLAB | 945 | 29 | function plotPerformance
global gf
if sum([gf.abortTrials, gf.performance(1,:), gf.performance(2,:)]) > 0,
axes(handles.axes2)
cla % clear all current objects
n = 100./gf.TrialNumber; %Percentage conversion up here to save repetition
hold on
bar(1,gf.abortTrials*... |
70cbd833f2bdb19914dbdbe6135bccb20f2cb3f4d5593da296f8801df5d969de | MATLAB | 946 | 34 | %% Produce a Bland-Altman plot for two measures
% Also known as mean-difference plots. The title, axis labels, and legend
% can be produced by uncommenting the appropriate lines.
%
% 6 December, 2021
function f = blandAltmanPlot(x,y,xString,yString,titleString)
average = mean([x y],2);
difference = x-y;
f = figur... |
5f5056ae84ef6e7548f325b3262c9da4ad0894acae8c8482c79ba568a2b1994e | MATLAB | 947 | 32 | function [user_input] = dlgPrompt(context)
%UNTITLED7 Summary of this function goes here
% Detailed explanation goes here
switch context
case 'baseline window'
prompt1 = sprintf(' Already pre-set to (-5s to 0.1s).\n Change to:\n\n Baseline start (s):');
prompt_full = {prompt1, 'Baseline end (s):'... |
b644633ee11abfd9107542a517289e6ae0e80356e23f3279de9e23e0f0de581c | MATLAB | 949 | 35 | function portlist = scanports(portlimit)
% Function that scans for available serial ports.
% Returns cell array of string identifiers for available ports.
% Scans from COM1 - COM15 unless portlimit is specified,
% then scans from COM1 - COM[portlimit].
% version 1 by Robert Slazas, October 2011
% check for existing se... |
d06ac8c55dbd6ade9640c8cda0f81ab948c89bf19a3a8b91e3f8e2004ee97563 | MATLAB | 949 | 32 | function [version, version_string] = readPVScanVersion(fid)
% readPVScanVersion - Read the version of the PrairieView scanning program from a file
%
% [VERSION,VERSION_STRING] = READPVSCANVERSION(FID)
%
% Given a file ID number FID of a PairieView/PrairieScan XML file,
% this function reads the file and looks for... |
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