sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
adfecc9d4f05c6794e943fc77f8eb4742e5446d8fe8374ae79a4d252ab9e3c80 | MATLAB | 1,881 | 50 | function data = get_one_subject_data(subject, type_stimulation)
%Navigate to the folder with the results
current_folder = pwd;
cd Data
%% Variables of interest
% p.stim_type %1: left tilt, 2: right tilt
% p.speed_accuracy_trial %1: speed, 2: accuracy
% p.cue_validity %0: invalid, 1: valid
% p.cue_direction ... |
0f17e6ec4ea671f9cc5501acf726c43f4c9f7fdca1747f0b59e270ff011af046 | MATLAB | 1,888 | 78 |
%% calculate the mean angle of the right most cluster
cmap = parula(11+1);
cmap = cmap .* repmat([.9 .8 .9],size(cmap,1),1);
ic = 0;
for thresh = 5:15
x = obs2obs(:);
y = exe2obs(:);
ind_min_rel = x>=thresh;
x = x(ind_min_rel);
y = y(ind_min_rel);
% convert to angle
ang... |
57ee68acd47a4ecc1f61fa2e1f08e92623638caa4aae10e94f9cbcf8ae20e70a | MATLAB | 1,890 | 60 | function obj = createObjFromTree(s, g)
%CREATEOBJFROMTREE creates an object from a tree-shaped struct
% Arguments:
% s - a tree-formed struct that serves as a template for object
% construction
% g - an optional struct with global parameters that belong to several
% (sub-) objects.
%
% This function... |
fbadaf65209e15e533f1d2b9d86ea80f4ed01b3a510a333414417ca56adeeb0b | MATLAB | 1,893 | 58 | % rsc = linmap(val,valMin,valMax,mapMin,mapMax)
% ---------------------------------------
%
% Performs a linear mapping of val from the range [valMin,valMax] to the range [mapMin,mapMax]
%
% Inputs:
% val Input value
% valMin Minimum value of the range of val
% valMax Maximum value of the range of val
% m... |
5e973d23f6b539b464fb50db0aaed94ea7fe03dbe36b0078f31d9002c4a67005 | MATLAB | 1,911 | 59 | function [mdp_states, ts_stats] = ...
align_state_times(snr_time, last_idx_before_skip, mdp_states, folder_log)
n_mdp_states = height(mdp_states);
msgs = {sprintf('n-mdp-state %d', n_mdp_states), ...
sprintf('n-snr-state %d', length(snr_time))};
if ismember('strig', mdp_states.Properties.VariableNames)
m... |
45455a2f45078e72bf05e49b8e513efba56a345831b5518f0218c0b440580a83 | MATLAB | 1,917 | 39 | clear;
Totangles = []; %define vector for angle values across all data sets
Totturns = []; %define vector for turn angle across all data sets
NumTurns = []; %define vector for number of turns made by each neuri... |
859c27f1a87f014b2b5cfcc2d9b058ff78890f5ff819b212e6c199a580b4f405 | MATLAB | 1,925 | 45 | function process_NA_from_single_experiment_kilosort2(origin_dir, do_plot, do_print, do_close_all, is_new_layout, neural_mode)
if nargin == 1
do_plot = true;
do_print = true;
do_close_all = false;
end
path_parts = split(origin_dir, '\');
if isunix()
path_parts = split(o... |
616a32646481e573d4d5f2e0ddb2011f413c746cec2001f4c89c84c648c6dfcb | MATLAB | 1,927 | 81 | function gramm_supFromAdapVsOcc_RESP(IDX)
%% Goal
% use gramm and plot the simultaneous congruent, incongruent, and monoc
% preferred.
% line plots using "methods for visualizing repeated trajectories"
%% Initial variables
conditNameForCC = IDX.allV1(1).condition.Properties.RowNames;
TM = IDX.allV1(1).TM(1:560);
cle... |
8c506604f099ea899a1c11cf0c1f5ee2ece1c7d2ad975fe666f0ff67136d2c83 | MATLAB | 1,931 | 68 | %Author: Tatjana Schmitt, 2019-2022
function stats = find_center_of_mass(BF, varargin)
% finds 1 or more centers of mass of chosen BF
narginchk(1,4)
if nargin >= 2; frequency_hub = varargin{1}; else; frequency_hub = 1; end
if nargin >= 3; se = varargin{2}; else; se = strel('disk', 3); end
if nargin >= 4; le... |
a1373e7a0fc71a818fea60eabd043cf3aa738d0d920d0dce9d1749be735b61f5 | MATLAB | 1,940 | 39 | load("timeseries.Yeo2011.mm316.mat");
output_dir = "full_data_linear_downsample";
mkdir(output_dir);
count = 0;
for m = 1:316
subject_mx645_original = subjects(m).mx645;
subject_mx1400_original = subjects(m).mx1400;
subject_std2500_original = subjects(m).std2500;
[mx_645_rows, mx_645_columns] = size(sub... |
bee9f12735592d0f31b9746d30f8e2589d5fb57a5227783c27f02f9543f4c3fa | MATLAB | 1,942 | 67 | %%
% Simulation results for the non-spatial two populations model for networks
% with and without astrocyte ensheathment of exc and inh synapses
%%
%% Figure 7A: Correlation surfaces across different values of p_en^i
% load the data
load('./CompressedData/NonspatialTwoPop/enEandIGridData_2Pop.mat')
% probability of ... |
69d4690a491cdc62f738088c1dd933b9daf7d8c7409d332dfd5c74f01cf54f25 | MATLAB | 1,943 | 81 | % plotIndividualSessionsFromIDX
clear
close all
PostSetup('BrockHome')
flag_SaveFigs = true;
%% Get IDX
global IDXDIR
cd(IDXDIR)
if ~exist(strcat(IDXDIR,'\IDX_iScienceSubmission.mat'),'file')
IDX_iScienceSubmission
end
load(strcat(IDXDIR,'\IDX_iScienceSubmission.mat'))
%% Loop through IDX, to plot indiv... |
48f4c4f7e4d61d4577411a95c3e1a2fb961d9784ab70087b607865ef83353b41 | MATLAB | 1,944 | 73 | function gramm_dCOS(IDX)
%% Goal
% use gramm and plot the simultaneous congruent, incongruent, and monoc
% preferred.
% line plots using "methods for visualizing repeated trajectories"
%% Initial variables
conditNameForCC = IDX.allV1(1).condition.Properties.RowNames;
TM = IDX.allV1(1).TM(1:560);
clear DataForVis
cou... |
e4c4830ae490eaac25fe4ae49ed72d77bdedbfd1d25465a9e240c9321c2bdca1 | MATLAB | 1,945 | 83 | clear all
close all
clc
addpath(genpath('./deconvtv_v1/'));
%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Example 1
%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%fname = 'DMSO1%.tif';
%z = read_hyperdata(fname);
%y = z + 0.1*randn(size(z));
%sigma = estimate_noise_level(y);
%w = estimate_w(sigma,size(y));
%mu ... |
23cbcc9603a4347442251d674ad6945375172b0b708cb038371fb0672d1c1deb | MATLAB | 1,947 | 53 | %---------------------------------------------------------------%
% This is the main script for decoding animal's current %
% position using rate maps -- Wenbo Tang (Jan 05, 2023) %
%---------------------------------------------------------------%
clc;
clear all
close all;
%%
famnov_dir = '/Volumes/Nove... |
bcd1b1a9cd026b5b3f39802067b7d8165e8656baf3d6cf940cdb2309045af5d4 | MATLAB | 1,951 | 64 | % MIRO inizialization file
function [im, Parameters, Transforms] = MIRO_parse_inputs(varargin)
inputcellarray = varargin{1};
if ~isempty(inputcellarray), im = inputcellarray{1};
else, im = []; end
%% Read File
Parameters.UserSelectedCancel = 0;
if ischar(im), [im, Parameters.UserSelectedCancel] = ReadTiff(im); end
i... |
b7546317c3a5ead07fcdbef04e3e4f38d268326f9b9ed19a0f07caa973173818 | MATLAB | 1,952 | 49 | function plotsingleEvents_Fig01(Fig01)
% INPUTS: 'Fig01' data structure from file
% 'Neurovascular_development_Figures_PNAS_2022.mat'
%README:
%Plots 5min trials from 3 ages of Figure 1 panel B
figure(10);
%% Constants
lowPass=0.5; %filter cbv data below 1Hz
[z,p,k]=butter(3,lowPass/(0.5*Fig01.constants.dal_fr)... |
4420d29c7e2eadc0c5b953a79a0b17e8c42384b5a3345a633d806a0bda85b9a5 | MATLAB | 1,953 | 92 | function fb_mat2spark(DATA,varargin)
% takes a dff matrix, assuming X,Y,Z, where Z is the time-series
%
%
% example:
%
% mov_data=fb_retrieve_mov();
% fb_mat2spark(mov_data,'resize',.25,'output_type','txt');
output_file='sparkdata.txt';
output_type='txt';
resize=.25;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
360bb82b18980f2ec539b27e96969d41c8e8d36dd8b592aadbadb3f4ce7ebacc | MATLAB | 1,955 | 54 | function map = createMap(config)
%CREATEMAP creates a containers.Map from a config file.
% Use this class in the dependency injection framework
% (depInj.createObjFromTree()). For the method field, write
% 'depInj.createMap'. The struct config must have a field 'keys' with a
% cell array containing all keys and... |
409abad9e74ad1e292346ce09556f25fecee64e660a4ae6adf1ab1ec81258950 | MATLAB | 1,958 | 47 |
figure;
%% Pup contact
subplot('Position',[0.2 0.61 0.2 0.17]);
shadedErrorBar([],mean_z_score_all_days_all_mice_pup_contact,{@mean,@stderrm},'r')
yticks([-0.4 -0.2 0 0.2 0.4 0.6 0.8 1]);yticklabels({'-0.4' '-0.2' '0' '0.2' '0.4' '0.6' '0.8' '1'});xticks([0 211 422 633 844 1055 1266 1477 1688 1899]);xticklabels({'-4'... |
fe487a9a6f4b50861dc839199d57c0ec4f277eacaeb1b12b3f89ed3c7479c6be | MATLAB | 1,958 | 31 |
figure;
%% All days averaged fathers vs mothers
subplot('Position',[0.2 0.61 0.2 0.17]);
shadedErrorBar([],CAMKII_mean_z_score_all_days_all_mice_pup_contact,{@mean,@stderrm},'c')
yticks([-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1]);yticklabels({'-0.6' '-0.4' '-0.2' '0' '0.2' '0.4' '0.6' '0.8' '1'});xticks([0 211 422 633 844 ... |
165b0e94b19819622f6b3b70b8767485f79aaac88042c8fed241502ea0debaa8 | MATLAB | 1,962 | 60 | function seq = simulate_tracker()
%%% Function that opens an raw .tif file and performs tracking of an
%%% object.
close all;
[file_name,~] = uigetfile('*.tif','Select Movie');
info = imfinfo(file_name);
len = length(info);
h1 = imshow(imread(file_name, 1));
hold on;
bg = create_bg(imread(f... |
11a51fc5a4d488593ec400e41156e9cd19594d45f7f583efa289f72e81012c09 | MATLAB | 1,966 | 31 |
figure;
%% All days averaged fathers vs mothers
subplot('Position',[0.2 0.61 0.2 0.17]);
shadedErrorBar([],fathers_mean_z_score_all_days_all_mice_pup_contact,{@mean,@stderrm},'b')
yticks([-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1]);yticklabels({'-0.6' '-0.4' '-0.2' '0' '0.2' '0.4' '0.6' '0.8' '1'});xticks([0 211 422 633 844... |
af782105b8a80be763be8e5e66cd3f34d96ce8c3eaf78fd81cd16621abb82d3b | MATLAB | 1,968 | 49 | function pipeline_data = create_results_folders(handles, pipeline_data)
%global pipeline_data;
point_paths = keys(pipeline_data.points.pathsToPoints);
pt_path = point_paths{1};
[folder, ~, ~] = fileparts(pt_path);
[folder, ~, ~] = fileparts(folder);
% ask to name this run, save the res... |
83e3b60e8e242c59c239c3749ac8e1085b9554c0c665c60f02a1427b40006d0f | MATLAB | 1,969 | 50 | function [Xout rp] = getLargestCc(Xin, conn, n)
% GETLARGESTCC Returns n largest connected-components in the input N-D array.
%
% Inputs:
% -------
% Xin - input N-D array. Required.
% conn - connectivity definition, can be either a scalar or connectivity
% array, with same number of dimensions as the input ... |
9da39b8c206b0807b18ed325f02c3c272627c6a31108aac4085c3ee51d96dd6d | MATLAB | 1,970 | 58 | classdef SineSampleSource < SampleSource
%SINESAMPLESOURCE provides samples from a single sine.
% This is a very simple wavetable oscillator. For simplicity, the output
% frequency is the nearest to the desired frequency that results in
% an integer wavetable length.
% Author: Lasse Osterhagen
properties (SetAc... |
894b22424e482aa40b113f331f08805bf1294d9298762708f494eaa21d267586 | MATLAB | 1,974 | 55 | function samp_points=synth(sig,samp_rate,trial_dur,varargin)
% SYNTH is FLANKING_BAND synth function.
% SAMP_POINTS=SYNTH(SIG,SAMP_RATE,TRIAL_DUR,VARARGIN) Samples the signal
% according to the givan SAMP_RATE and TRIAL_DUR. Returns the sampled
% points.
% varargin holds the requested Center frequency and the bandwidt... |
5a0a798c0a300e5f7bb5b62742a1910b1271967f42f4e010e3fc154190ea4f5a | MATLAB | 1,979 | 47 | function phi = phi_comp_probs(type_of_dist, type_of_phi, Z, probs)
%-----------------------------------------------------------------------
% FUNCTION: phi_comp_probs.m
% PURPOSE: Compute phi from probability distributions
%
% INPUTS:
% type_of_dist:
% 'Gauss': Gaussian distribution
% ... |
bacdf7eb76ad5c12714d6228490b1bd77b8c2e3080f3c63ae451e031f1f33e80 | MATLAB | 1,981 | 33 |
figure;
%% All days and all days averaged sires vs dams
% Pup contact
subplot('Position',[0.2 0.61 0.2 0.17]);
shadedErrorBar([],CAMKII_mean_z_score_all_days_all_mice_pup_contact,{@mean,@stderrm},'c')
yticks([-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1]);yticklabels({'-0.6' '-0.4' '-0.2' '0' '0.2' '0.4' '0.6' '0.8' '1'});xti... |
38b3d92e2eb8695e3f5b702158e7ac418c75fe28779a514391bbad84c31262af | MATLAB | 1,982 | 75 | function mask = MIBI_get_mask(rawMaskData,cap,t,gausRad,plot,titletext,reuseFigure)
% NOTE: to get original behavior, simply call
% MibiGetMask(rawMaskDAta,cap,t,gausRad,1,'');
% function mask = MibiGetMask(rawMaskData)
% function gets a 2d matrix of raw MIBI data to use for generating a mask
% and returns a mask of t... |
c80474419f2e3231d0a0eceb1b73fdd91ffb6e98006b4c5d650a5f667f2fc727 | MATLAB | 1,992 | 69 | function gramm_2x2_line_NSNDEvariation(IDX)
%% Goal
% use gramm and plot the simultaneous congruent, incongruent, and monoc
% preferred.
% line plots using "methods for visualizing repeated trajectories"
%% Initial variables
conditNameForCC = IDX.allV1(1).condition.Properties.RowNames;
TM = IDX.allV1(1).TM(1:560);
c... |
e19fa370a13ca013ec594a9486c638c8105679bd220dd37b5b00050fbae0a918 | MATLAB | 1,994 | 101 | function [IMAGE,F,T]=pretty_sonogram(SIGNAL,FS,varargin)
%simple 2-taper histogram (Gauss and DGauss)
%
%
% [s,f,t]=fb_pretty_sonogram(filtfilt(b,a,mic_data./abs(max(mic_data))),fs,'low',2.5,'zeropad',0);
%
if nargin<2 | isempty(FS)
disp('Setting FS to default: 48e3');
FS=48e3;
end
overlap=2000;
tscale=2;
N=2048;
p... |
cb9bdfc7a045565ae8a289b1a5cc146cdf15775cd7b0b7832c17aac29e08a387 | MATLAB | 1,996 | 80 | param.font_name = "Nimbus Sans";
param.fontsize_ax = 9;
param.fontsize_label = 10;
param.fontsize_letters = 12;
param.color_options.time_colors = [[0 0 0]; ...
[0.466 0.674 0.188]; ...
[0.494 0.184 0.556]];
param.color_options.cluster_colors = [[.5 .5 .5]; ...
[0 0.4470 0.7410]; ...
[0.8500 0.3250 0... |
172196832db5e9a6a5838d8051f944d2b925bf6b46d0d32ea15ae16caa1b602f | MATLAB | 2,001 | 73 | clear all;
addpath(genpath('../PhiToolbox'))
%% parameters for computing phi
Z = [1 2]; % partition
tau = 1; % time delay
N_s = 2; % number of states
%% important
params.tau = tau;
params.number_of_states = N_s;
%% generate time series from Boltzman machine
N = 2; % number of units
T = 10^6; % number of iterations... |
b7da6fd11c8d55149e5f0b26ae27b065fe958dc43eaced86280c28edb3243b6c | MATLAB | 2,001 | 51 | clear all
addpath(genpath('.'))
%Connectivity of triangular faces
mid_gifti_L=gifti('S1200_7T_Retinotopy181.L.midthickness_MSMAll.32k_fs_LR.surf.gii');
mid_gifti_R=gifti('S1200_7T_Retinotopy181.R.midthickness_MSMAll.32k_fs_LR.surf.gii');
tri_faces_L=mid_gifti_L.faces;
save('tri_faces_L','tri_faces_L')
tri_faces_R=mi... |
12b8d44d9d46a66e8771783968fbad1ad5e164f6319788ef50f914a5e7830d36 | MATLAB | 2,003 | 44 | function s_comp= update_input_method(s_comp,input_method,varargin)
% UPDATE_INPUT_METHOD changes the input method of this signal component.
% There are 3 input methods possible: 'STATIC_VALUE', 'SWEEP', 'SEQ_VALUES'.
% if input_method is none of the above an error occurs.
% S_COMP=UPDATE_INPUT_METHOD(S_COMP,'STATIC_VAL... |
41597a06fc77db00382adea38093bee667d384a76681277cdec718cd0b370fbe | MATLAB | 2,006 | 55 | function comp = set(comp,varargin)
% SET Set Freq_comp properties and return the updated object
% Property names are:
% Name,Sig_comp,Swp_on,Seq_on,Static_value,Sweep,Seq_values.
property_argin = varargin;
while length(property_argin) >= 2,
prop = property_argin{1};
if ~isa(prop,'char')
treat_error(['The p... |
3cce34f7ccdc783d304a25e36e5a01733003ccc2a19a130eb89b0c4f57aec335 | MATLAB | 2,013 | 43 | function [condition,conditionarray] = getCond(DE,NDE,PS,NS)
condition= table(...
[DE NDE DE NDE DE DE DE DE DE DE NDE NDE DE DE NDE NDE DE DE NDE NDE DE DE NDE NDE ]',... %the eye is identified by the suppressor
[PS NS NS PS PS NS PS NS PS PS NS NS NS NS PS PS NS PS PS NS PS NS NS PS]',... %the tilt must be ... |
ffd91d534341c416c51eff860de9ed7a7ed691916cae1fa3c3699ebbaba63c5c | MATLAB | 2,025 | 64 | %% LaBGAS_deriv_unzip_nii_smooth
%
% This script will unzip fMRIprep output images, smooth them, zip the
% smoothed images, and delete all the unzipped images again
%
% DEPENDENCIES
% SPM12 on your Matlab path
%
% INPUTS
% preprocessed .nii.gz images outputted by fMRIprep
%
% OUTPUT
% smoothed .nii.gz images
%
%_____... |
3b14a27355cf3023602fe39facf0b1ed7fd4ca818c28c83460c0c67457b058f5 | MATLAB | 2,030 | 52 | % Copyright (C) Alex A. Bhogal, 2021, University Medical Center Utrecht,
% a.bhogal@umcutrecht.nl
% <loadRAMRgen3: imports GEN3 RespirAct data >
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foun... |
0f5ac5931ef8563fa7bcc499e42cb147b8d11ef0aa1430f59b81261a35c8cc80 | MATLAB | 2,031 | 68 | function plot_error_data(ax, param)
% Last modification: JN 2021-01-28
S = load(fullfile('..', 'data', 'error_data.mat'));
data_table = S.data_table;
axes(ax);
ax.NextPlot = "add";
grid on;
cols = {'N_correct', 'N_at_prev_port', 'N_other_err', 'N_not_at_port'};
%colors = {[0 .5 0], [.7 .4 0], 'b', 'k'};
colors = {[0... |
9f56a66fd79f72017b7110fc155288c9df41594470b84a88230bad22745422ea | MATLAB | 2,032 | 63 | function export_to_xls(diff_attention_effect, diff_SAT_effect, type2AUC, fmri_attention_effect, fmri_SAT_effect, fmri_type2AUC)
number_subjects = size(diff_attention_effect,1);
%% EACH OF THE 3 MEASURES SEPARATELY (4 REGIONS)
%File name
output_path = pwd;
file_name_separateMeasures = fullfile(output_path,'R mixed-ef... |
c8bfffb5420c93a13da4d3782db184511d4e7d1d415618feb581b874eec8a0b6 | MATLAB | 2,036 | 53 | function makeToneThresholdExpFiles(subjectID)
%MAKETONETHRESHOLDEXPFILES creates tone detection experiment files from fixed
%parameters.
% Arguments:
% subjectID - a string identifying the subject for which the session
% files are constructed.
%
% All parameters are fixed according to our current practice f... |
d5935a64b3838006de1651e26e8aae229bb5791b8dee931e3f687baa2e7fbc5a | MATLAB | 2,037 | 78 | function [adjMatSNR,embDistSNR] = segmentSNR(measure,DataSet,varargin)
%compareSNR Compare variation across vs within over time
% For optional arguments, see '+ecogutils/postHocOptionsParser.m' and the
% help for +patientSummaries/stateAverage.m
%
threshold = 1/3;
o = ecogutils.postHocOptionsParser(measure,... |
f067b862b079cb9d2d0df2513454febb4544ff94c2ad40e31a42c87f315edd4e | MATLAB | 2,038 | 59 | classdef (Abstract) AudioObject < matlab.mixin.Heterogeneous
%AUDIOOBJECT can be played by an AudioPlayer.
% This class is the base class for all classes that can be read
% by an AudioPlayer for sending data to the sound interface.
% It implements the matlab.mixin.Heterogeneous interface to allow the
% creation... |
87b530041bd861e07e38dfcaedf305fedcad270d71c064e3600836ee582a50a7 | MATLAB | 2,049 | 91 | function visIDX_monocPlots(IDX,dataType)
%% Initial variables
conditNameForCC = IDX.allV1(1).condition.Properties.RowNames;
%
% {'Monocualr PS DE' }
% {'Monocualr NS NDE' }
% {'Monocualr NS DE' }
% {'Monocualr PS NDE' ... |
a21f13df6a24e2129ad6263ba04e7ff7dd3aeb2cc2d71d502912a0817c1fd8af | MATLAB | 2,049 | 85 |
clc
clear
close all
load for_fig02_N1_exe.mat
figure('Units','normalized','OuterPosition',[.1 .1 .08 .45])
plotit(FR_b, t_b, 0);
load for_fig02_N1_obs.mat
hold on
plotit(FR_b, t_b, 1);
load for_fig02_N2_exe.mat
figure('Units','normalized','OuterPosition',[.18 .1 .08 .45])
plotit(FR_b, t_b, 0);
load for_fig02_N2_obs... |
ed2a6347355cb8e46bb5f4d0c730dbedc227e153a5228428b965c7d5e16ebdc5 | MATLAB | 2,049 | 53 | %%
% Function Inputs
% total_synapses: total number of synapses
% distribution: binomial with parameter p (prob. of success)
% 0 for not ensheathed
% 1 for ensheathed
% d_parameter: distribution parameter
% p (probability of selecting zero ensheathment
% synapse_type (Note: IE reads, excitato... |
1bb3355dc7a59ef109bb8743180d53d471fcc07777604d80e9252b30a2f734ff | MATLAB | 2,054 | 57 | function val = get(coord,prop_name)
% GET Get Coordinator property from the specified object
% and return the value. Property names are:
% Components - list of the components of the object this Coordinator handle
% Num_of_comp - number of components of the object this Coordinator handle
% Old_ooord_indices - the origin... |
7663ff237afb33177b3806e6bd0d587672430e2cdf1588c5d9e75010798b5541 | MATLAB | 2,055 | 41 | function file_format_data=get_file_format_vals(env,signal_table,line_num,chan_num,line_trial_num,env_num,line_trials)
% FILE_FORMAT_DATA returns a string that consist of a number of MATLAB
% commands. These are initialization and setting commands.
% For each component of the Envelope a varaible of the form :
% MTF_1_F... |
4e20766fb84f5fa0d017d5899c8296126aed520d1e3abf37b9ed773143ac4f51 | MATLAB | 2,058 | 79 | % compute several measures of integrated information in a multivariate autoregressive model,
% X^t = A*X^{t-1} + E,
% where A is a connectivity matrix and E is gaussian noise.
clear all;
addpath(genpath('../PhiToolbox'))
%% parameters for computing phi
Z = [1 2]; % partition with which phi is computed
tau = 1; % ti... |
c1e135dd523adbc2247a704964de96f38b2494d443967a09d9c2ccf57eace4dc | MATLAB | 2,059 | 64 | % It is a code to calculate velocity and position from accelerometer
% acc_data: accelerometer data
% sf: sampling frequency ex) sf=600.615;
% Copyright (c) 2023 Hong Gi Yeom
function [velocity, position]=acc2pos(acc_data,sf)
d_ord=10; % detrend oder
eve=length(acc_data);
for i=1:size(acc_data,2)
events_size(i)=s... |
0020acf17e185928e0f5fdb423731c9a2405771bb16884dd5cc8e9e711e735bf | MATLAB | 2,063 | 68 | clc
close all
clear
figure('Units','normalized','OuterPosition',[.1 .1 .03 .2])
hold on
[perc(1), CI(:,1)] = prep4fig5C('action_preference');
[perc(2), CI(:,2)] = prep4fig5C('LDA');
for i = 1:2
line([i i],[CI(1,i) CI(2,i)],'color',[.7 .7 .7],...
'linewidth',3)
end
c = lines(7);
plot(1:2,perc,'color','... |
6ace8d1dabb0727aedc5e68ae21bd9d3b9d7389d9092aeec98500e0a88765a2d | MATLAB | 2,064 | 66 | function NS_SaveFig(chPath, hFIG, cFIGNAME, chOption)
% Utility to save figures. Save figures in the handle vector hFIG in the folder
% provided by chPath under the names provided in the cell array cFIGNAME; By
% default a .eps, .png and .pdf files are saved. This can be controled by the
% option string chOption. To s... |
8669675811914b0b82b503eb76811e4cc929ed61e2c38d35675ca00029f384f1 | MATLAB | 2,068 | 58 | function [table_events, table_filestarts, TTL] = ...
DT_deuteron_preparation(folders)
% JN 2020-04-22
% this function runs all the steps required for a recording session with
% the logger
% Parse the autolog (coming from the transceiver)
fname_ttl = fullfile(folders.results, 'deuteron_autolog_parsed.mat');
if is... |
dc009e431fa3db33dafe7df28ae9b5dc1da4cc9fe367f507b278383852d97b5f | MATLAB | 2,068 | 67 | %% Intensity analysis of fluorescence
%% Preprocessing:
% Images must be processed to the same size (i.e., 5.0 x 5.0 mm)
%% Define the parameters of images
pixelPerMM = 769; %pixel/mm value
radiusOfAnalysis = 1; %radius of circular ROI (mm)
imageSize = 5; %Image size (mm)
imageExtension = 'tif'; %Image file... |
c63e5e423e3fae70b9424ff42840340095b312533093f2a58d83df17102e25c7 | MATLAB | 2,071 | 59 | % iScienceSub_findTimingOffset.m
% Written by BMC - 10/1/2022
% This code needs to help us decide which parameters to use for the BRFS
% iScience submission. These include contrast levels, time period of
% stastical comparison, and format of normalization.
% We will plot monoc vs dCOS in 9 plots (3x3 facit gid)
% X ... |
105837951dd5a1f48846ebc1761d069ce5b14568a56ddad0161a4820b29229f8 | MATLAB | 2,073 | 74 | function stats = getSessionStats(trials, headerStr, adjustedFalseAlarmRate)
%GETSESSIONSTATS calculates statistics for a detection experiment session.
% Arguments:
% trials - an array of trial structs
% headerStr - the field name of the trial struct that identifies the
% grouping factor
% adjustedFalseAla... |
49896db3328caba2d5705018a6e5260a3bc7063b7bc1e3258a8c900afb5c174e | MATLAB | 2,073 | 49 |
figure;
%Heatmaps of mean GCaMP7s fiber photometry signals from ACCVGAT neurons in dams.
%The signals are aligned to the entry of the dam to the nest (F) and the exit of the dam from the nest (G) after retrieval of all pups.
%Each row represents the mean z-score from postnatal day 0-5 for each mouse (n = 5 mice).
%% ... |
67c0f8ffb891a7597ad7da9e7a822e3a90e1b0434cbe1faf831eed576a1f4c7d | MATLAB | 2,078 | 55 | function process_neural_data_kilosort2(in_folder, out_folder, mode, fnums, ...
table_filestarts, is_unfiltered, mpx_prefix)
params = struct();
switch mode
case 'deuteron'
params.relevant_channels = 1:32;
files_per_run = 50;
params.KHz_Orig = 32;
params.KHz = 32;
params... |
b70a070fee9393bc1e19678b022c32988ca6148bb5bf401769db408323bdc35e | MATLAB | 2,079 | 57 | function ASLQASL_SSVBanalysis(SUBJECT, locationASLlabelcontrolPLDNIFTI, locationM0, locationMask, outputmap, PLDlist, artoff, spatialoff)
% ClinicalASL toolbox 2023, JCWSiero
PLDstring = sprintf('%.05g,' , SUBJECT.PLDS(PLDlist));
PLDstring = PLDstring(1:end-1);% strip final comma
if nargin >= 7
if strcmp (a... |
fd45c0c0e237f97fa63cd65190de3685474010c5c900b8560a553778add6a968 | MATLAB | 2,079 | 57 | %%
% Loops over the strengths of the stimuli considered
% Default is fours values (none, low, med, and high)
%
% Returns the firing rates (of the mean field model) and the eigenvalues to
% assess the stability of the system
%%
function [firing_rates_sol,nan_warning,warning_notice, eig_values, d_min, real_eig_max]...
... |
8f50302d713183794d9668e22dd1bd864df9b7c8f56bcced20ca1022981da940 | MATLAB | 2,086 | 68 | %
% spktrain2fr v1.0
% 07.10.2020
% Mohammad Shams
% m.shamsahmar@gmail.com
%
% Replaces spikes in a spike train with a normalized Gaussian
% NOTE: to avoid artifacts at the endpoints, marginal spikes will be replaced with partial Gaussians of similar energy as the rest.
%
% convolved_spike_train = spktrain2fr(spike_tr... |
0a5ec5014e6f8e0d9fa6915c51845bb08e6bb2485f5c4fe45cb3113f7a6f5bc7 | MATLAB | 2,094 | 77 | function mask = MIBI_get_mask_graded(rawMaskData,cap,t,gausRad,plot,titletext,reuseFigure)
% NOTE: to get original behavior, simply call
% MibiGetMask(rawMaskDAta,cap,t,gausRad,1,'');
% function mask = MibiGetMask(rawMaskData)
% function gets a 2d matrix of raw MIBI data to use for generating a mask
% and returns a ma... |
ad4070bf41b12ecb66dbacb22a7ceb2681c4e88dde9c4f3bdd6fb76d5927bd9b | MATLAB | 2,094 | 67 | % Authors : Tatjana Schmitt & Simon Wadle 2019-2022
%function reads tiff stacks and scales pixels down to end size
function resized_image = tiff_stack_resize_block_process(input_stack, end_size)
[rows, columns, stack_sz] = size(input_stack);
block_size = [rows/end_size(1,1), columns/end_size(1,2)];
single_blo... |
44e89673ccee001e927020f9c6ce0c670f5737844f411e23afa8898eb4c9f677 | MATLAB | 2,095 | 70 | function probs = est_p(X, N_s, tau, isjoint)
%-------------------------------------------------------------------------------------------------
% PURPOSE: estimate probability distributions of past (p_past), present (p_present) and
% joint distribution of past and present (joint) from discretized time series data X
... |
b7e66c1ca95d2487f78398d62804ca3ddca35f1d6902b9b15b59040ee5e4653d | MATLAB | 2,095 | 61 | function info=get_crids_info(sig,crid_arr);
% GET_CRIDS_INFO returns information of components with the specified crids.
comp_crids='';
main_sig=get(sig,'Main_signal');
comp_list=get(main_sig,'Comp_list');
num_env=get(main_sig,'Num_of_env');
len=length(crid_arr);
for k=1:len
counter=1;
crid_title=['Unwrapped... |
c0069b969bd9cf6d2780ded729c0531fa16bb47c41db6bc530cb17d69af76e4f | MATLAB | 2,098 | 55 | function noise=makeSomeNoise(calib, Fs, level, dur, cutoff, gate)
%MAKESOMENOISE creates bandpass noise of a specified level
% Arguments
% calib - calibration struct
% Fs - sample frequency
% level - target level
% dur - duration in seconds
% cutoff - passband frequencies: [low high]
% gate - onset/offset... |
5fe0d9ade1809586cb1ca8925ee64d582094a4d02890b273a314f8cedd725112 | MATLAB | 2,099 | 59 | function [ phi_G, Cov_E_p, A_p ] = phi_G_Gauss( Cov_X, Cov_XY, Cov_Y, Z, method )
%------------------------------------------------------------------------------------------
%PURPOSE: calculate integrated information "phi_G" based on information geometry
% See Oizumi et al., 2016, PNAS for the details
% http://www.pn... |
86dae0ae4ecf00763838fae3962cc3acdf24372b1a2b6c37d01926e8baf6d7b7 | MATLAB | 2,102 | 34 |
figure;
%% All days averaged sires vs dams.
%Plots of the mean Z-scored traces of ACCCAMKII neurons for all mice and all days, contrasting dams (red) and sires (black).
%Pup contact
subplot('Position',[0.2 0.61 0.2 0.17]);
shadedErrorBar([],fathers_mean_z_score_all_days_all_mice_pup_contact,{@mean,@stderrm},'k')
yt... |
f6dff4e25b83ef2b981d047753161f8646b357b092408a7acba824382bbe8d5e | MATLAB | 2,106 | 35 | %written by Alex Bhogal a.bhogal@umcutrecht.nl
%script to save nii images loaded using loadImageData script.
%Data can me manipulated but header should be the same
function [] = saveImageData(data, header, pathname, filename, datatype)
% 0 None (Unknown bit per voxel) % DT_NONE, DT_UNKNO... |
b59bec9e38d24dae09292febbaccacfc3cab3ebb008391f9f82f734b1e2a916f | MATLAB | 2,113 | 63 | classdef LaserBlockCtrl < AudioObject
%LASERBLOCKCTRL is an AudioObject for controlling a Laser.
% Input arguments:
% id,
% channel, % from channel mapping
% duration, % sec
% dcAmplitude % sample value (0 to 1)
%
% The purpose of this class is to let the AudioPlayer play (D... |
1ec5c1d50fa7b287c4dda558e2f3f224fa07073c1d4bae77e36fcadf97942476 | MATLAB | 2,115 | 39 | function [Result,pData,DataCapture,TS_FirstSample] = AO_GetAlignedData(ChannelIdArr,ChannelCount)
%Function used to get aligned data from several channels
%ChannelIdArr :array of channels which we need to get data from,all channels must have the same sampling rate
%ChannelCount :number of channels listed ... |
771b981e20d2ac74b4021d4cf6e727c3c3f904c47c28bb10f0f7796284aa4e32 | MATLAB | 2,117 | 55 | function comp = set(comp,varargin)
% SET Set Depth_comp properties and return the updated object.
% Property names are:
% Sig_comp,Input_method, Static_value, Value_formula, Static_reps, Reps_formula,
% Seq_values, Seq_values_str, Coord_index, Index_formula, Wrap, Fixed_num_data, Sweep.
property_argin = varargin;
whi... |
05e9a483eb09b6547660ec1909d15c683dfc81a9b3155dcdefc112409b9e84d0 | MATLAB | 2,118 | 77 | function gramm_adaptation_line(IDX)
%% Goal
% use gramm and plot the simultaneous congruent, incongruent, and monoc
% preferred.
% line plots using "methods for visualizing repeated trajectories"
%% Initial variables
conditNameForCC = IDX.allV1(1).condition.Properties.RowNames;
TM = IDX.allV1(1).TM(1:560);
clear Dat... |
71efb751f3a5b670fc20e07fd0e48bad0c94df3edfee6a7c0feee39a58ccbae9 | MATLAB | 2,120 | 56 | function comp = set(comp,varargin)
% SET Set ETime_comp properties and return the updated object.
% Property names are:
% Sig_comp,Input_method, Static_value, Value_formula, Static_reps, Reps_formula,
% Seq_values, Seq_values_str, Coord_index, Index_formula, Wrap, Fixed_num_data, Sweep.
property_argin = varargin;
whi... |
f68a5f414e003bb329ba204f9d2acbb0f7ad59ba111bd440ac200fe7ded9f8f4 | MATLAB | 2,123 | 63 | classdef LaserBlockCtrlSampleFactory < AudioObjectSampleFactory
%LASERBLOCKCTRLSAMPLEFACTORY creates samples from a LaserBlockCtrl.
% Author: Lasse Osterhagen
properties
% Sample frequency
sF
% Number of channels needed (inclusive sound channel, exclusive
% trigger channel)
numChannels
end
method... |
700df0b83b2a7d9111aa5f514bb71c7e484722ea698746401e6c7692ec159206 | MATLAB | 2,124 | 57 | function comp = set(comp,varargin)
% SET Set Phase_comp properties and return the updated object.
% Property names are:
% Sig_comp,Input_method, Static_value, Value_formula, Static_reps, Reps_formula,
% Seq_values, Seq_values_str, Coord_index, Index_formula, Wrap, Fixed_num_data, Sweep.
property_argin = varargin;
whi... |
794d97e60a832ddd17ecbabb59bb8ab27286b18842b8b37f44e49f806b21c03e | MATLAB | 2,129 | 68 |
clc
close all
clear
figure('Units','normalized','OuterPosition',[.1 .1 .05 .2])
hold on
[perc(1), CI(:,1)] = prep4cibra('discharge');
[perc(2), CI(:,2)] = prep4cibra('action_preference');
[perc(3), CI(:,3)] = prep4cibra('LDA');
for i = 1:3
line([i i],[CI(1,i) CI(2,i)],'color',[.7 .7 .7],...
'linewidth'... |
46b12933747c629047a674ad826208a1c4ee92dd04106d8e31d974ebfdab2d5a | MATLAB | 2,130 | 51 | function objMatrix = createObjMatrix(s)
%CREATEOBJMATRIX creates a matrix of objects of a single class.
% Use this class in the dependency injection framework
% (depInj.createObjFromTree()).
% For the method field, write 'depInj.createObjMatrix'. Another field
% named 'constructor' contains the constructor meth... |
4f7b71e152417ec49c507575e1b3e37b00a0ea19a5c39370bb27b0f05d12616f | MATLAB | 2,130 | 56 | function comp = set(comp,varargin)
% SET Set STime_comp properties and return the updated object.
% Property names are:
% Sig_comp,Input_method, Static_value, Value_formula, Static_reps, Reps_formula,
% Seq_values, Seq_values_str, Coord_index, Index_formula, Wrap, Fixed_num_data, Sweep.
property_argin = varargin;
whi... |
af94f5052311fca04d549ae4c101537f42271ebb9134c03354697386a9b9c1d5 | MATLAB | 2,133 | 79 | function data = D_BAND_BASIC_NODECI( data_in, data_fs, band, band_name, varargin )
% example input
% data = D_BAND_BASIC_NODECI(croppedSDF, 1000, [70 150], 'highGamma')
band_name_fs = [band_name '_fs'];
data.(band_name).hpc = band(2);
data.(band_name).lpc1 = band(1);
data.(band_name).lpc2 = band(1)/2;
filt_order = ... |
2da4e2f24e383d0034826c852340a78ddfaa3a2093d7f1fa74d84c870083dbb7 | MATLAB | 2,134 | 92 | % function [] = grab_frame()
%GRAB_FRAME Function that grabs frames from camera and measures latency of
% hardware and connections.
%
% Run options:
%
% >> grab_frame( input_args )
%
% Written by Alex@Eli_lab 7.9.16
%%% Using tisimaq_r2013
delete(cam);
cam = videoinput('... |
298d75888838b83d857af6d9491743e42aa29f09598f0ec526b1513adc1ca22d | MATLAB | 2,137 | 64 | %Author: Tatjana Schmitt 2019-2022
function FRA_analysis_subfields(root_path)
% get file
temp_filepath_FRAanalysis = [root_path, '\**\FRA analysis retroIC.mat'];
FRA_file = dir(temp_filepath_FRAanalysis);
FRA_path = FRA_file.folder;
FRA_name = FRA_file.name;
load(fullfile(FRA_path, FRA_name), 'tuning_overvie... |
2f9ac22a07f87599928f1edecc704f7c87ffc996f3ede3fcc63306a5aa5875af | MATLAB | 2,137 | 48 | function file_format_data=get_file_format(env,line_num,chan_num,env_num)
% GET_FILE_FORMAT returns a string that consist of a number of MATLAB
% commands. These are setting commands which are based on the Envelope's
% components status at the given line,channel and envelope-index.
% This string is meant to be written ... |
4f419e861a72ec81e3d62f3204d180342fc1c7f1831f6a2077dc071e56149020 | MATLAB | 2,141 | 49 | function filters = MIRO_SLprepareFilters2D(rows,cols,nScales,shearLevels,directionalFilter,scalingFilter,waveletFilter,scalingFilter2)
%% Prepare wedge and bandpass filters for the computation of 2D shearlets.
%%check input arguments
if nargin < 3
error('Too few input arguments!');
end
if nargin < 8
if nargin ... |
0e786dd1b63e16c17bb795328bbce82dec25b9aedfce652cf349f2e4d1b0fb40 | MATLAB | 2,148 | 84 | function [EXTRACTED_SOUND,EXTRACTED_IMAGE,TIME_POINTS]=spectro_navigate(DATA)
%simple GUI for selecting a sound using its spectrogram
%
% [EXTRACTED_SOUND,EXTRACTED_IMAGE]=spectro_navigate(DATA,DIR)
%
%
% DIR
% if given then brings up an interface to select a particular file
%
%
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% par... |
0ee9e638327b9d0cb31884fc3c1b71297bb0ed975340e6c56e099a79cc0e6ab1 | MATLAB | 2,149 | 57 | function comp = set(comp,varargin)
% SET Set Ramp_comp properties and return the updated object.
% Property names are:
% Sig_comp,Input_method, Static_value, Value_formula, Static_reps, Reps_formula,
% Seq_values, Seq_values_str, Coord_index, Index_formula, Wrap, Fixed_num_data, Sweep.
property_argin = varargin;
whil... |
b5b147d20985b2a6cbe6ac91898421ba4c94df3bfd4ea7e8db9cf137a83d907e | MATLAB | 2,153 | 77 | %script for analyzing surface-based data -- clean-up in progress
function analyzeSurfData ( subj_list ,prepdwi_dir,parcellation_name, target_labels_txt,out_folder,bids_tags)
% here, we just want to write out the csv tables
% definitions
data_dir='.';
% read in $target_labels_txt from parcellate_cfg for list of t... |
88433cf8f60cbd2d362a4b73142edeb579397673c8855ceccb96d6900e79d2ae | MATLAB | 2,160 | 94 | classdef (Abstract) DetectionGUI < handle
%DETECTIONGUI is the base class for stimulus detection GUIs.
% Author: Lasse Osterhagen
properties
% Current subject id
subjectID
% Path and file name prefix, where the LogBook will be saved
filePathPrefix
end
properties (Access = protected)
% ExperimentC... |
3824feed2afd8183d331399b321dd49660872158e88c5579b9647cfcd23c4591 | MATLAB | 2,165 | 89 | function visIDX_dCOSFig(IDX,dataType)
%% Initial variables
conditNameForCC = IDX.allV1(1).condition.Properties.RowNames;
TM = IDX.allV1(1).tm;
uctLength = length(IDX.allV1);
% B. pull out all laminar matrices 3x(6,450,el#)
%preallocate
SDF = nan(size(IDX.allV1(1).SDF.raw,1),size(IDX.allV1(1).SDF.raw,2),uctLength);... |
9ddfe3c1a2dec4c951c641d5acb5e34fbed579fd6b42b235c04690ced0543f19 | MATLAB | 2,168 | 61 | function thre = func_threshold(I)
% Compute an optimal threshold for seperating the data into two classes [1].
% This algorithm can be summarized as follows. The histogram is initially segmented into two
% parts using a a randonly-select starting threshold value (denoted as
% T(1)). Then, the data are classified... |
de522e68e23794daf29c74c8f09bb5279d107eb0db10c82a34db22bd773e4ed7 | MATLAB | 2,169 | 50 | function plot_4bars_withinError_3subplots(data, t_values, reference, ylabel_string, ylimit)
figure
for effect=1:3
number_subjects = size(data{effect},1);
for i=1:4
if i~=reference(effect)
SD(i)=compute_sd_from_t(mean(data{effect}(:,reference(effect)) - data{effect}(:,i)), t_values{effect}(... |
b0fb20cefa39cf51c9bc64b56dbb96c85d525a7ca6a849de3b2fdbe762807ab9 | MATLAB | 2,174 | 92 | function plot_supp_1(ax, S, param)
ns_pre = S.ns_pre;
thr = .25;
dset = S.dset;
time_const = 29.997;
rats = 4:5;
days = 22:23;
start_time = .5; % sec after prev_fdb
stop_time = 9; % sec after prev_fdb
start_samp = round(start_time * time_const) + ns_pre;
stop_samp = round(stop_time * time_const) + ns_pre;
time_v... |
196c6299b4fb3a20463f2050cfadcdced176b399f45715dfe4d0d00899f4e76c | MATLAB | 2,177 | 65 | load("timeseries.Yeo2011.mm316.mat");
output_dir = "full_data_positive_linear";
mkdir(output_dir);
total_negative = 0;
for m = 1:316
subject_mx645 = corrcoef(transpose(subjects(m).mx645));
subject_mx1400 = corrcoef(transpose(subjects(m).mx1400));
subject_std2500 = corrcoef(transpose(subjects(m).std2500));
... |
0638ea62b881a39232320723c468a2c81401bbede7d2c1a3cbc574bd428cdfbb | MATLAB | 2,179 | 65 | load("timeseries.Yeo2011.mm316.mat");
output_dir = "full_data_negative_linear";
mkdir(output_dir);
total_positive = 0;
for m = 1:316
subject_mx645 = corrcoef(transpose(subjects(m).mx645));
subject_mx1400 = corrcoef(transpose(subjects(m).mx1400));
subject_std2500 = corrcoef(transpose(subjects(m).std2500));
... |
533373b4591ea268f02e08ca6b55879336bc0e0a4227bf4d7c5e30db94f0d841 | MATLAB | 2,184 | 61 | function [accuracy,p_value,accuracy_shuf] = decoding_dichotomy_linearSVM(dat_all)
%---------------------------------------------------------------%
% This is the function for decoding dichotomies using %
% linear decoder (linear SVMs) %
% -- Wenbo Tang (Jul 13, 2022) ... |
58d369b3ee30dfbba8049ab561c2c768cdbba067c90664136410dfe519e449cf | MATLAB | 2,188 | 55 | function [BI,sigBI,randBI] = compute_behavior_information(calcium_data,calcium_time,calcium_fps,...
behav_data,behav_time,behav_fps,...
nrand)
% This function calculates the 'behavior information' and its significan... |
f7723c846bcc9141f79f5baf22f0a8fa2eaaac3bfef1a349e2c7b60453a41e60 | MATLAB | 2,193 | 57 | function comp = set(comp,varargin)
% SET Set Trial_dur_comp properties and return the updated object.
% Property names are:
% Sig_comp,Input_method, Static_value, Value_formula, Static_reps, Reps_formula,
% Seq_values, Seq_values_str, Coord_index, Index_formula, Wrap, Fixed_num_data, Sweep.
property_argin = varargin;... |
a6802ef9c8c71212a087d95cf0ee571208cfd8b4a5f1b1d49e1aa045538be4da | MATLAB | 2,208 | 68 | %*******Alex Bhogal 1/29/2019
%function to load niftii images untouched. Output is the image data
%and info structure containing matrix and resolution info
function [image info] = loadTimeseries(pathname, filename)
warning('off')
global opts;
if isfield(opts,'verbose'); else opts.verbose = 0; end
if ~ispc
... |
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