sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
dab92b39367c5522dbbef5552787b1c4d19599359331122995d5877028b1112f | MATLAB | 3,811 | 84 | function [ overcomplete_params ] = samples_to_overcomplete(samples, adjacency_matrix)
%CONVERT_SAMPLES_TO_OVERCOMPLETE This functions uses the graph structure
%and the samples in its simple format (one sample per row, one variable per
%column), and converts the samples to the overcomplete parametrization
%necessary to... |
eb1a2f16cceb07e984e65815cfe69d88a8330d2d58cce543aa38fcf1afb92a22 | MATLAB | 3,811 | 110 | my_cells = readtable('/Volumes/groups/giocomo/export/data/Projects/JohnKei_NPH3/F1/F1_190620_johncontrasttrack_train1_sp_cells_by_eye.xlsx');
my_cells = table2array(my_cells);
sp_cells_st = struct('cell_number', [], 'fr', [], 'MI', [], 'early_trial_normalized_correlation', []);
sp_cells_st.cell_number = my_cells;
f... |
341a85444c010509d9dade03a0d0f96a42dbc8523703c7674011081865b30882 | MATLAB | 3,814 | 150 | % ir_ct_fan_beam_os_rlalm.m
% compare FBP and relaxed OS-LALM for a 2D fan-beam CT problem
% see ir_pwls_os_rlalm.m
% 2015-11-30 Hung Nien
if ~isvar('A'), printm 'setup geometry, image, sinogram'
f.down = 4;
ig = image_geom('nx', 512, 'fov', 50, 'down', f.down);
ig.mask = ig.circ > 0;
sg = sino_geom('ge1', 'units'... |
af30156b6ffac73a6807a14da0327bd53c1c60ceb5511b627d8a9283427ce006 | MATLAB | 3,814 | 122 | function [xCent,yCent,distByTime,perAtBound,radialOccupancy,r,tt] = ...
plotRadialPosition(self,border,cond,plotFig,varargin)
% default values
dt = 2.*self.fs;
dr = 0.2;
fe = self.getFirstEntry('H',border);
tMax = self.nPt./2;
clims = [0 1];
stopThresh = 0;
xrange = [0 tMax];yrange = [0 4];nOvlapX = 2*dt/4... |
56dccbfd97ce1b6c6667567436917cbcf0bc09896547bf0c57a664c9c76c50a7 | MATLAB | 3,815 | 115 | function wkwBenchmark(param)
[wkwFile, wkDir, cls, sz, testFilename1, testFilename2] = buildData(param);
wkwCompFile = strcat(wkwFile, '.lz4');
sizeVec = 2 .^ (0:log2(sz));
sizeCount = numel(sizeVec);
repCount = 20;
disp('<< Running benchmark');
data = nan(sizeCount, 5, repCount);
for... |
1c368d4c20c52931e8fffe05bbe703d6100aee0d470b9b1dc2affca9ec0aaa1b | MATLAB | 3,820 | 94 | % compile
%
% Builds the trigger counter for keyboards (triggerCounter3.m) into a
% standalone Windows program with the MATLAB Compiler.
%
% Run it in MATLAB, from any folder. Needs the MATLAB Compiler and
% PsychToolbox; the toolbox itself is not needed. The program is written to
% the subfolder build, together with t... |
d89c1fe9ba8e6545efb0db5cde12be74b84a3176e90ec6e60e448e6a5ae8d0d9 | MATLAB | 3,822 | 76 | function [input_graph, undeleted_info]= fun_graph_delete_dim_short_link(input_graph, link_label_to_remove)
% fun_graph_delete_dim_short_link removes the links specified by the link
% label. If delecting the link result in creating a endpoint, this link
% will be skipped.
%% Remove
th_hair_length = 0;
num_link_to_remo... |
f5b23d855f174316135a4c5fc77b6e353d5ab8aec17485ac701f1cd79101645d | MATLAB | 3,822 | 85 | function compute_num_epochs_final(study_info)
pipeline='NEARICA_behav';
% Number of subjects
n_subjects=size(study_info.participant_info,1);
subj_lext_trials=zeros(n_subjects,1);
subj_ftge_trials=zeros(n_subjects,1);
subj_exgc_trials=zeros(n_subjects,1);
subj_exend_trials=zeros(n_subjects,1);
subj_lobs_trials=zeros... |
2c54f54b5f946510b87ec19337721fba43677c12a6e1d3163d86e259ea37dc50 | MATLAB | 3,823 | 117 | function p = userpath(inArg)
%USERPATH User environment path.
% USERPATH returns a string specifying the first folder on the search path.
% MATLAB adds the userpath to the search path upon startup.
%
% The default userpath is platform-specific:
% Windows: user's "Documents" folder appended with "MATLAB"
% ... |
55a17abda44899f692d60dab22fcf569b68c48e4c621f9e7a048d054e134428d | MATLAB | 3,824 | 154 | function xs = tpl_osps(x, Gb, yi, bi, ri, P, niter, pixmax, curv, gi, denom)
%function xs = tpl_osps(x, Gb, yi, bi, ri, P, niter, pixmax, curv, gi, denom)
% The T-PL-OSPS algorithm for transmission Poisson problem
% (ordered subsets separable paraboloidal surrogates)
% Input
% x [np,1] initial guess
% Gb Gblock sys... |
b8fdede1bcaf9e4ade301926a5497c95b58b29333cf4357be01df7174758b8e4 | MATLAB | 3,824 | 105 | % Plots ratemaps from 16 to 1 laps for the best and worst rat
function plot_track_place_fields_thesis
cd 'X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\Chapter 1\Combined_figs'
axes = Protocols_rate_maps_makeFigure;
sessions = [{'X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\P-ORA\P-ORA_Day5_16x8'},...
{... |
5bb68f7e78287da4124fcbb6872628cc8e5518fc29d42ca8ff50b5ada133972a | MATLAB | 3,825 | 132 |
function proportion_phase_precessing_place_cells
sessions = data_folders;
session_names = fieldnames(sessions);
PP =plotting_parameters;
c = 1;
for p = 1 : length(session_names)
folders = sessions.(sprintf('%s',cell2mat(session_names(p))));
for s = 1: length(folders)
cd(cell2mat(folders(s)))
... |
6e66fe70438474df0f56eae184dc33fdedebfbe8cfaf3308330af3d7d8ff586e | MATLAB | 3,829 | 95 | function [self,stateDistBefore,stateDistEarly,stateDistLate] = getBaselineKinematics(self,condNdx,key)
%close all
spdAll = self.calcSpd;
% separate the track into combinations of state and condition
[condState, stateKey] = self.getCond(condNdx,key);
nCondStates = size(stateKey,1);
nState = numel(self.states.key... |
b1033cb9e9c10645e131f3e3ce2782e44fef97b444e4be1a9450fa64634975ad | MATLAB | 3,830 | 148 | b1 = repmat([0 25 50 100 150 200 250 500 750 1000],[1 10]);
b2 = [zeros([1 10]) 25*ones(1,10) 50*ones(1,10) 100*ones(1,10) 150*ones(1,10)...
200*ones(1,10) 250*ones(1,10) 500*ones(1,10) 750*ones(1,10) 1000*ones(1,10)];
gradechoinv = nan(length(b1),8);
gradechoinv(:,4) = b1;
gradechoinv(:,8) = b2;
%blood
d1 = 0.02... |
c0b902aac6923ac9bcadfb1658d15c1e73731592cd4f1b654f08e59c4378afa6 | MATLAB | 3,830 | 81 | function connect_link_str = fun_graph_shortest_path_through_3pts(metric, ep1_sub, mid_sub, ep2_sub, connectivity)
% fun_graph_shortest_path_between_points finds the shortest path between
% two point, with distance measured by the metric array
% Input:
% metric: 3D numerical array, specify the distance between neigh... |
189ded33eb070d64944e07eec6c9907796c492116d3fce69289ea219c8023a78 | MATLAB | 3,831 | 85 | close all; clear; clc;
saveFigure = 0;
load('SpearmanCorrFullyShuffled.mat');
subjectColors = [rgb(106, 27, 154); rgb(239, 108, 0); rgb(46, 125, 50)];
figX.fig = figure('Name', '');
set(figX.fig, 'Units', 'pixels', 'Position', OSScreenSize([10 6]), 'NumberTitle', 'off');
figX.ax1 = axes('Position', [.05 .15 .425 .75]... |
b8a30d18990eb5267b9b00af0bb58154a7c380e961c4bf89a5250bfa726818e9 | MATLAB | 3,833 | 143 | function [ci_95, ax] = bland_altman(y1,y2,varargin)
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
p = inputParser;
p.addParameter('in_path', pwd, @ischar);
p.addParameter('RecurNum', 1, @isnumeric);
p.addParameter('BlackList', {'user_prefs', 'images','.hg','config\d*','deploy'}, @is... |
9c71be74a12a51b63d35efd02c2a807e078f18afecef499ed28933d56464cad4 | MATLAB | 3,834 | 177 | % clc
% clear all
% close all
set(0,'DefaultAxesFontSize',20);
% b=0.1;%Fading rate
% c=0.08; % acquisition rate
% A=(c/b)^(b/(b-c))-(c/b)^(c/(b-c));
% %x=0:0.1:400;
% F=(exp(-b*x)-exp(-c*x))/A;
%plot(x,F,'b','LineWidth',2);hold on
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
V=xlsr... |
229b992bee86b6e8dfb224e9092ed3f9faa445fba7c1d37022fb55e6581f174b | MATLAB | 3,835 | 94 | function SulciMap = tess_sulcimap(sSurf)
% TESS_SULCIMAP: Compute a sulci map based on curvature and connectivity.
% @=============================================================================
% This function is part of the Brainstorm software:
% http://neuroimage.usc.edu/brainstorm
%
% Copyright (c)2000-2016 Univ... |
38863fb31494d9b1aa89692dfc5512ed288d344fd6c6e73269b4cd6b62221987 | MATLAB | 3,843 | 120 | function eeg_interped = removeBadChannels(eeg, chanlocs, rejectedChannels,highThreshold,lowThreshold)
% This function identifies and replaces bad channels with a spline
% interpolation of all other channels.
% Dependencies: EEGLAB.
%
% Input:
% eeg - eeg data (time x channel)
% chanlocs - channe... |
cc0a4794a41cd9b66703a976ece62ef30c94268bee5605c175400c59ea746ac8 | MATLAB | 3,847 | 84 | datapath='/projectnb2/npbssmic/ns/myelin_content_scattering_correlation_paper_data/cerebellum/';
% add subfunctions for the script. Change directory if not running on BU SCC
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addpath('/projectnb/npbss... |
5c520f42ae8c5eaf109cdc498662641647b5341c7b0c0cf4fbf43116426fd99c | MATLAB | 3,850 | 123 | function img = myFeldkamp(cg, ig, proj, varargin)
%|function img = feldkamp(cg, ig, proj, varargin)
%|
%| FBP reconstruction of cone-beam tomography data collected with
%| a circular source trajectory.
%| See feldkamp_example.m for example.
%|
%| in
%| cg ct_geom()
%| ig image_geom()
%| proj [ns nt na] cone-beam ... |
0dcd6df05e20d2cd968686ad5b0429fdf8317d169284a033e2133e1005390142 | MATLAB | 3,852 | 80 | function out = defineExtraEventCodes(in)
% This function creates predefined event codes and stores them in a variable.
% This variable can be used together with the sendEvent function to conveniently
% send indivisual events to e.g. electrophysiology hardware.
%
% If these functions are used, the following agreements m... |
e705696aa9e573d9a3e0433fd3684b31c6420beb1b53284b5c0779b21abfd774 | MATLAB | 3,853 | 104 | % The script is used to perform wholw-brain searchlight decoding on fMRI data
% add toolbox
addpath(genpath('spm12/'));
addpath(genpath('CoSMoMVPA-v.1.1.0/'));
addpath(genpath('libsvm-3.25/'));
%% trasform beta maps into MNI space
% set input and output paths
beta_path = '../../mri_data/beta_map/';
save_path = '../..... |
155ae7c3892c935237dfab553f4ce5d2cca168e58526750d49433850c47bf70e | MATLAB | 3,856 | 87 | classdef phonemeSequenceTrialParser
% The phonemeSequenceTrialParser class parses phoneme sequence trial information.
properties
syllableUnit % Syllable unit (1 - Consonant, 2 - Vowel)
phonemeUnit % Phoneme unit (1 - 9: a, ae, i, u, b, p, v, g, k)
phonemeClass % Phoneme class (1 - 4... |
5304352ca6368db059b2728e8991bfb87b7718c6f9fd21c0a8e6d4e61b382eaf | MATLAB | 3,857 | 178 | % mri_superres.m
% NOT DONE!
%
% Explore super-resolution in MRI with rotated propeller sequences
% Inspired by Benoit Desjardins' work.
% Copyright 2003-7-23, Jeff Fessler, The University of Michigan
%
% create k-space samples, in units of 1/mm
%
if ~isvar('kspaces'), printm 'setup kspace'
fov = 256; % [mm] typical ... |
28eaeb76ab9491f0e2ebc1ef90d31a71e24b51823f3ca9cec16cf76ee5c60fdb | MATLAB | 3,858 | 95 |
function [CustomAnalysisOpts, UserVar] = createAnalysisPluginFigure(existFig,appCustomAnalysisOpts, PluginsFolderName, numVar, ListofVariableLabels, PluginName, DefaultValues)
settingsFile = fullfile(PluginsFolderName, [PluginName '_Settings.mat']);
existSettings = isfile(settingsFile);
CustomAnalysisOpts=appCustom... |
75e648f69d023b51f617a618eeb02f540f4e6770621e09087f91386e85ec2541 | MATLAB | 3,859 | 119 | From smalone@engin.umich.edu Wed Jul 15 13:37:52 1998
To: "Jeffrey A. Fessler" <fessler@eecs.umich.edu>
Subject: Re: pwls_sor
Prof. Fessler,
I'm sending along two of my pwls_sor routines. Both compute one iteration
of the routine. One uses precomputed diag[G'*W*G]. The other does not.
I could combine the two, if y... |
022788f3a298b76516149ea5c9cfe1c5a569bbaab997841abe9152f1026ac5ef | MATLAB | 3,860 | 100 | close all
clear variables
clc
%Varun Mannam
%date: taken from 29th Sep 2019
%date: 7th June 2020
%DnCNN model with diff lr in keras
%calculate the PSNR on test-mix data raw nbn (with -0.5 subtraction and 200
%epochs)
%lr1 = 1e-3, lr2 = 1e-4, lr3 = 5e-4, lr4 = 5e-5, lr5 = 1e-5
format long
font = 14;
%data
addpath('/Us... |
8567d65cf794e337f132628a210e1b1e78d4650eaaf36cdf55a9a54ce3437c76 | MATLAB | 3,860 | 86 | % CHAPTER 2 PIPELINE
% Marta Huelin
% REPLAY TIMES AND QUANTIFICATION
extract_replay_time_periods(computer,data_folders,data_type,[]);
extract_replay_plotting(computer,data_type,replay_control);
merge_sleep_rest_replay(multievents,bayesian_controls);
% Raster plot with replay event times
raster_replay_times('awake');... |
98e9fcffa7069844b198a432c335c691acc1d5f22061fcced90aa20d28e886af | MATLAB | 3,861 | 116 | function [eeg_timelock, data_trials, trials, indx2, ibi2, overlap] = compute_eeg_segments(data_eeg, indx, time_onset, time_offset, maxamp)
% This function computes timelocked EEG segments to random timings. This
% function emulates what is done in the function compute_her.m and random
% timings are considered as heartb... |
b281bcf821272e6bb46ba770f19b6c00d4538963d0378e7d536cb145ff0461ad | MATLAB | 3,861 | 117 | function neural_prediction
%NEURAL_PREDICTION Neural prediction example.
% NEURAL_PREDICTION loads an example dataset and trains a forward
% encoding model (TRF) that predicts 128-channel EEG responses from 2
% minutes of speech as per Crosse et al. (2016).
%
% Example data is loaded from SPEECH_DATA.MAT and c... |
fba0a758476be0031b0d00277e27f18c57fe6bc2a8e672f7974854ff35d31fc7 | MATLAB | 3,861 | 122 | function [H, HC] = spm_browser(url,F,pos,format)
% Display an HTML document within a MATLAB figure
% FORMAT H = spm_browser(url,F,pos,[format])
%
% url - string containing URL (e.g. 'http://...' or 'file://...')
% F - figure handle or Tag [Default: Graphics]
% pos - position within figure in pixel units with... |
100433f024634f2af66ed5810a870d5ff30a263b503275c82bd707ea23ee213a | MATLAB | 3,862 | 92 | function [linker, paired_ep_ind, found_idx_str] = fun_graph_get_linker_for_int_link(vessel_image, vessel_mask, vessel_skl, int_link)
% fun_graph_get_linker_for_int_link use threshold relaxation to find the
% linkers for internal link with endpoints.
% Input:
% vessel_image: 3D numerical array, image stack
% vesse... |
4e589ffd164357ed3630bfa6b773d54826c765577c926059669dcb67e0851f33 | MATLAB | 3,863 | 113 | function [ix] = spm_fieldindices(X,varargin)
% Returns the indices of fields in a structure (and vice versa)
% FORMAT [i] = spm_fieldindices(X,field1,field2,...)
% FORMAT [field] = spm_fieldindices(X,i)
%
% X - structure
% field1,.. - fields
%
% i - vector of indices or fieldname{s}
%
% Note: Fields... |
65c63959a9e26f4a9184ca8153b6f54b40682aa475f39d9c4b9e05503b75bb7d | MATLAB | 3,865 | 98 | % LEARN_STRUCTURES_BY_DENSITY
% ADOPTED AND EDITED BY DARIK ONEIL YUSTE LABORATORY 11/19
%% Documentation
%function input is:
%x_train: logical, binary matrix i = time and j = node
%densities: vector of densities to be tried
%variable groups: optional cell array that marks which variable belongs to
%each group to... |
f3d554d6552f93a63715fccaf8e2bbcaf52c6a467226189519790268bfbc9624 | MATLAB | 3,865 | 119 | % SENSE_homodyne_recon_demo.m
% demos use of SENSE_homodyne_recon.m, which combines
% SENSE and partial Fourier reconstruction. Input image can be rectangular,
% but both dimensions should be even
%
% resulting figure shows the improvement from demodulating with the
% reference image and compares MSE to reconstruction ... |
f4f2e38304454441863e50c7fa9d1033fbd8e0a0e552ee82dcd69c481be92106 | MATLAB | 3,872 | 107 | function F = spm_Gcdf(x,h,l,tail)
% Cumulative Distribution Function (CDF) of Gamma distribution
% FORMAT F = spm_Gcdf(x,h,l,tail)
%
% x - Gamma-variate (Gamma has range [0,Inf) )
% h - Shape parameter (h>0)
% l - Scale parameter (l>0)
% tail - if 'upper', return the upper tail probability of the Gamma
% ... |
19057c41d93ca7082ab0d828fbc4e4dc4de20b91030ab22c2d0a5397d82eb7ee | MATLAB | 3,873 | 88 | function analyze_opto_Fig6
rootdir = 'C:\TKlab_agingPFC\';
cd(rootdir)
load behavior_opto
num2stimperiod = {'whole delay','early delay'};
shade_color = [0 1 1]; FaceAlpha = 0.3;
figure;hold on
for stim_period =1:2
if stim_period==1
off_ustim_y = CR.y_off_whole_ustim;
on... |
9cbfb49c232e8d956738775152af8caf11f429ee190a83449a1c1e429d74ef7b | MATLAB | 3,874 | 79 | function pm = pm_merge_regions(pm,rima,ii,jj,nn,pp,rs)
% Merges regions as defined in connectogram to minimise
% total costfunction (sum of phase-differences across
% region borders).
% FORMAT: pm = pm_merge_regions(pm,rima,ii,jj,nn,pp,rs)
%
% Input:
% pm : Phase-map
% rima : Label map consisting of connect... |
e42a6b0d56e1d4063b505f7443919619573f08393a2e3b3b4c701e9732cf4ee8 | MATLAB | 3,874 | 109 | function [] = SVD_embeddingAnalysis(f_orco,meta,figureFile)
% SVD_embeddingAnalysis Compares state space dimensions from taking
% derivatives vs from truncated SVD. Uses the false nearest neighbor
% algorithm to determine embedding dimensions
%
% Inputs: f_orco = a fly object
% meta = a structure with... |
e48bdb9bb7c31d50962485e4ad960418ebabafdb340d7f68bf4f0533737908e6 | MATLAB | 3,877 | 86 | function [OoBInfo] = CalculateOoB(FlagPos, TrigPos, OutOfBoundPos, CondTable)
%% CalculateOoBTrials
% Andrea Castegnaro, UCL, 2022 uceeaca@ucl.ac.uk
% Further preprocessing for OoB trials. If out of bound (OoB) trial
% we set the return distance as the mean value of all good trials for that
% environmental condition.... |
461853318f741741d017a488db29131de6c372608947a6c2f170a5c0af9672f7 | MATLAB | 3,879 | 95 | % Script reproducing the results in Table 1 of the paper:
% [1] M. Mäkitalo and A. Foi, "Optimal inversion of the generalized Anscombe transformation for Poisson-Gaussian noise", IEEE Trans. Image Process., doi:10.1109/TIP.2012.2202675
%
% Alessandro Foi and Markku Mäkitalo - Tampere University of Technology - 2011-20... |
adeef8aa3abb42cc603e8c65b4bacdf010a7fd4789f3c62302eaa72cb76d56c6 | MATLAB | 3,879 | 88 | function [I_frame] = fun_calcROIoverlap(handles, slice_idx)
%FUN_CALCROIOVERLAP Summary of this function goes here
% Detailed explanation goes here
cc = fun_HSVcolors(5, 1);
I_stack = handles.imageI;
G_stack = handles.imageG;
S_stack = handles.imageS;
if get(handles.Check_AutoI, 'Value')
... |
d63cbc648294c608fee07d244ad917a2b17ddaab1de420b27d493c47c018f963 | MATLAB | 3,879 | 103 | function significant_timepoints = fdr_correction_dth(subjects,task,category)
%FDR_CORRECTION_DTH Perform permutation tests + FDR correction on the p-values to calculate the
%significance of the timepoints in the distance-to-hyperplane analysis.
%
%Input: subject IDs, with_stats (1 plot with stats, 0 plot without),
%cat... |
bd433c66413b3e0e780d63ba23a0f8153da28d50d24043f582376d51a5053921 | MATLAB | 3,880 | 92 | % Combined Data reading from mvx neural file and aftifact removal
% The neural data are read one channel at a time in increments of N samples
%########## Reading the Individual Neural Channels mvx file
N = 100000; %number of sample points to load or read
artf_thr = 30000; % artifact threshold ********NEGATIVE or ... |
40d4d030a935361ee87185d108c39c4b5bbcd89f5ba453df2534aa9e7b22d86c | MATLAB | 3,881 | 118 | %% This file shows how to use 'saveastiff' function.
clearvars;
[~,~,Z] = peaks(100);
Z = single(Z);
Z_index = uint8((Z - min(Z(:))) * (255 / (max(Z(:)) - min(Z(:)))));
Z_color = uint8(ind2rgb(Z_index, hsv(256)*256));
Z_alpha = Z_color; Z_alpha(:,:,4) = repmat(0:1/100:1-1/100, 100, 1)*255;
Z_color_multiframe =... |
0d02c130d7b9766ae2cc8353faf09fdc898ea6c217f2eb4a0ed018524583cd95 | MATLAB | 3,882 | 107 | % Simulate the network model with varieties of parameters to compute the
% mutual information and linear Fisher information
% Note: This code needs to be ran on a high performance cluster!!
% Wen-Hao Zhang
% Feb 20, 2020
% University of Pittsburgh
setWorkPath;
addpath(fullfile(Path_RootDir, 'linearHawkesProcess'));
... |
ae5c64840c869c1ab9bb281f936977e457ccdbd726ab06d266ac21fe378061af | MATLAB | 3,882 | 99 | function metadata = createMinimalOMEXMLMetadata(I, varargin)
% CREATEMINIMALOMEXMLMETADATA Create an OME-XML metadata object from an input matrix
%
% createMinimalOMEXMLMetadata(I) creates an OME-XML metadata object from
% an input 5-D array. Minimal metadata information is stored such as the
% pixels dimensio... |
61eeb352e7f535f7a9175c9950b193cbe9f440f48c04ad3fa74912f250bccb25 | MATLAB | 3,883 | 67 | %% Normalise individual structural scans and electric field magnitude images produced by ROAST
% (c) Carys Evans, UCL
% carys.evans@ucl.ac.uk
% October 2019
%This script requires SPM12
%To run this script, make sure you have run your current flow models
%through ROAST. This script converts structural MRI and ... |
910fe837e0376dfb330c645867e76040d2dc6f8441a49e945381acb13a5a2cd3 | MATLAB | 3,884 | 94 | function check_event_timing(study_info)
all_obs_base=[];
all_obs_reach=[];
all_obs_grasp=[];
all_exe_base=[];
all_exe_reach=[];
all_exe_grasp=[];
for s_idx=1:size(study_info.participant_info,1)
% Get subject ID from study info
subject=study_info.participant_info.participant_id{s_idx};
% Where or... |
c27f5f991b103df9f5e187d7ba92e00a1273dd1a5c6fe51dd3fabe8247fe6fc4 | MATLAB | 3,884 | 96 | function outSignal = IPEMGenerateBandPassedNoise(varargin)
% Usage:
% outSignal = ...
% IPEMGenerateBandPassedNoise(inPassBands,inDuration,inSampleFreq,...
% indBLevel,inFFTWidth)
%
% Description:
% Generates a band passed noise signal using inverse FFT.
%
% Input argume... |
f362355e7dd04e261798c53b36c96ee0c5f30a0411843eab897d17fa540c1d3c | MATLAB | 3,888 | 125 | function [fNum] = plotRasters2(fNum,dataFile,functionFile,dataTraceFolder)
load(dataFile,'emp')
spikes = emp.rast;
fs = emp.fs1;
load(functionFile,'convVI','p')
I = convVI(emp.I);
nTrials_per_stim = size(spikes,2);
nTrials_tot = numel(spikes);
nStim = size(spikes,1);
tt = (1:size(I,2))./fs;
for i = 1:nTri... |
996f088572ea9bdc1a3527cf60f179a41e6c661d59789e0a914ee0b3d2fd91a3 | MATLAB | 3,890 | 132 | function [table_motion,table_still,motion_2]=get_table_motion_updated(speed_d,threshold_still,gap_for_motion,gap_for_still)
% threshold_still=3;
% gap_for_motion=1; %in seconds
speed_d(speed_d<threshold_still)=0;
T=length(speed_d)+1;
motion=ones(1,T);
motion(speed_d==0)=0;
d_motion=diff(motion);
motion_start=zeros(1,... |
677eb08aa0a5f5a91a2119841d1d6413adf3f3524c8931e9e5d358bf94d3b532 | MATLAB | 3,891 | 121 | function plt = create_confusion_matrix(counting_matrix, varargin)
% create_confusion_matrix Create a confusion matrix using imagesc
% X-axis is predicted value
% Y-axis is true value
%
% INPUTS:
% counting_matrix: (n x m) 2D matrix; Each row reflects the predicted
% guesses for that ... |
68046fd8ba10170e15baa73a1f2e4044cc6e63e169e9d4840d3bb277a7cd85ff | MATLAB | 3,892 | 91 | datapath = '/projectnb2/npbssmic/ns/PSOCT-qBRM_fiber_struct/sample03/';
P2path = '/projectnb2/npbssmic/ns/PSOCT-qBRM_fiber_struct/sample03_2P/'; % 2P file path
reconpath=strcat(datapath,'dist_corrected/');
% add subfunctions for the script. Change directory if not running on BU SCC
addpath('/projectnb/npbssmic/s/M... |
ac353f0effcf114319a6cc24873918a80876f17855b412d19654de3dc18f85ad | MATLAB | 3,892 | 154 | function f = localregression(x,y,x0,degree,kernel,h,mode)
% function f = localregression(x,y,x0,degree,kernel,h,mode)
%
% <x>,<y> are vectors with the data
% <x0> is a vector with the points to evaluate at
% <degree> (optional) is non-negative integer. default: 1.
% <kernel> (optional) is 'epan'. default: 'epan'.
% ... |
7fb2483fea9f11df0f15d56296857299666e313fcc4d3cf25cea7a71452cdb77 | MATLAB | 3,894 | 124 | function [f_orco] = calcKNN_Habituation_PermutationTest(f_orco,states)
% calcKNN_Habituation_PermutationTest performs a permutation test to
% compare KNN distributions across time. Each state instance retains it's
% f/df location, but the time since first entry is shuffled. The KNN
% space is then calculated bas... |
de0f268aa5ea9dbcf56067dd3d13f69fe8dfbcaf864613091e65ee0cdd569a96 | MATLAB | 3,894 | 97 | function [link_cc, varargout] = fun_skeleton_get_link_cc(voxel_list, voxel_neighbor_idx_list, l_link_start_voxel_idx, voxel_unvisited_Q)
% fun_skeleton_get_link_cc is a subfunction of fun_skeleton_to_graph, which
% finds the link connected components. Except for the beginning voxels,
% each voxels in the link has exact... |
ee38307049b64fa4469e34b71c73f7ff333b36e4c18a1a1b6b736d7dcf48f7da | MATLAB | 3,894 | 85 | datapath='/projectnb2/npbssmic/ns/myelin_content_scattering_correlation_paper_data/somatosensory/';
% add subfunctions for the script. Change directory if not running on BU SCC
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addpath('/projectnb/np... |
23ac0b00f67f1e34794ae15712a3f79bd88bdc60cf13c98479bdbe7e296c3e68 | MATLAB | 3,897 | 133 | function [nodes, edges, validatedNodes,validatedEdges] = regraphNodes_new(nodes, edges,validatedNodes,ds_rate)
% Re-graph
nodePos = nodes;
nodeEdges = edges;
nNodes = size(nodePos,1);
nEdges = size(nodeEdges,1);
if ~exist('nodeDiam')
nodeDiam = zeros(nNodes,1);
end
hxy = ds_rate;
hz = ds_rate;
nNodesUnique = ... |
f5d7758d9d24f65dcf5cf90e1790216699fd675813195a1e0d122b0a8b9b2330 | MATLAB | 3,897 | 76 | function [input_graph, undeleted_info]= fun_graph_delete_dim_short_link(input_graph, link_label_to_remove)
% fun_graph_delete_dim_short_link removes the links specified by the link
% label. If delecting the link result in creating a endpoint, this link
% will be skipped.
%% Remove
th_hair_length = 0;
num_link_t... |
38d1bfc642e00ecd008943152a11440a78182d9e1759c21aa15c70027545ae97 | MATLAB | 3,903 | 129 | function y = Gtomo_nufft_filter_3D_par(omega, ob, do_phase)
%function y = Gtomo_nufft_filter_3D_par(omega, ob, do_phase)
% build the sinogram-spectrum-sized matrix
% that is .* multiplied after 3D FT, before iFFT or NUiFFT
% in
% omega [M 3] frequency sample locations (radians)
% out
% y [M 3] filter
% Based on Gtomo_... |
21f98c042ef9e277afd01649c70d5ac0e83e998c04e6918c99c453af844434b7 | MATLAB | 3,905 | 103 | function singleSessionRasterplots(data_dir,session_name, trackLength, plotWidth, plotHeight, preDrugTrials)
% plots rasters for all cells in 1 session given data directory and name of
% mat file that has neuropixel data synched with unity information
% Requires Access ot the serer
% Inputs:
% data_dir = '/Volumes/gro... |
b07d34bd4a20867792fda27e776841fdec64df808f825ff9ccb40deda03aa5c1 | MATLAB | 3,906 | 101 | function stimfeedback_tSC(mainPath, animal, session, ch)
%TSC_RATIO_OSCSTATE calculates the ratio of different theta cycles during
%stimulation and control periods.
% stimfeedback_tSC(MAINPATH, ANIMAL, SESSION, CH, ISSTIM, EXP) detects
% oscillation states in the hippocampal LFP (long and short theta epocs,
% ... |
32f650a64e36a02e88e4966d02fb0eb12695fd55714aedd85961f5f9fff3eb0a | MATLAB | 3,907 | 119 | % sense_homodyne_recon_demo.m
% demos use of sense_homodyne_recon.m, which combines
% SENSE and partial Fourier reconstruction. Input image can be rectangular,
% but both dimensions should be even
%
% resulting figure shows the improvement from demodulating with the
% reference image and compares MSE to reconstruction ... |
8f887cb245b1b65d459142a411b2dcb4f51cfe0098a9dfc96ee65989f37efebd | MATLAB | 3,908 | 157 | function [toDelete]=checkCells(fluoTraces,baseline,data, params)
%v = ver;
%parOn=any(strcmp('Parallel Computing Toolbox', {v.Name}));
parOn=0;
%parOn=1; %UNCOMMENT THIS FOR PARALLELIZATION
if parOn
numCores=feature('numcores');
isOpen = matlabpool('size') > 0;
if ~isOpen
matlabpool('open','l... |
f947838022ca1509a2f81cc7edcb7123f97c39ed69f769b3edbde7a903f1ad40 | MATLAB | 3,911 | 81 | function connect_link_str = fun_graph_shortest_path_through_3pts(metric, ep1_sub, mid_sub, ep2_sub, connectivity)
% fun_graph_shortest_path_between_points finds the shortest path between
% two point, with distance measured by the metric array
% Input:
% metric: 3D numerical array, specify the distance between n... |
7ab780edd98563dc3e244f8a81e04a377fea6c7fe6081a9f7477b5dd529175a5 | MATLAB | 3,913 | 161 | function [Af, Aa, dif] = test_adjoint(A, varargin)
%function [Af, Aa, dif] = test_adjoint(A, varargin)
%|
%| test that the adjoint of a 'matrix object' A really is its transpose
%|
%| in
%| A Fatrix or fatrix2 typically
%|
%| option
%| 'tolre' dbl tolerance (relative) for equality (default: 0)
%| 'big' 0|1 for big ob... |
dc21e3ad096ea5a1e18516683cef6c1a03fb44c0e495418bf65ce2a68fefd03b | MATLAB | 3,914 | 104 | function [I_signals, full_timeline, timeline_signal_id, timeline_signal_id_movie] = make_experiment(images)
params = model_parameters();
num_images = length(images);
% Make image signals --------------------------
if isfield(params, 'learn_order')
learn_order = params.learn_order;
else... |
2941eda5983330426fda1b27c241d0c79578bf20b0d6d55944ec55ca6be954bb | MATLAB | 3,921 | 121 | function recon_im = SENSE_recon(smap, reduced_fft, reduced_dim, np, regularizer, mask, figs_on)
% function recon_im = SENSE_recon(smap, reduced_fft, reduced_dim, np,
% regularizer, figs_on)
% in:
% smap [N M nc] complex sensitivity maps
% reduced_fft [N/np M] or [N M/np] undersamp... |
f7768e25e850ebb0cd4fb3609fa68f60592d10601fd765f89763e791aa32fde8 | MATLAB | 3,921 | 143 | clearvars -except MCmean0
%input image variables
prompt = {'Pixel width (microns):','Day:','Position:','Enhancement factor:','Image length:','Dilation factor:'};
dlgtitle = 'Input';
dims = [1 35];
definput = {'0.3405','1','1','20','500','1'};
answer = inputdlg(prompt,dlgtitle,dims,definput);
D=str2double(answe... |
ba6b1e40034368d193a581a11857d48542f03cbd74c396ff5e3468f92c6f266e | MATLAB | 3,928 | 117 | function pointsI = circOpposingPoints(pointsI, startI, endI, vLength, ...
varargin)
%CIRCOPPOSINGPOINTS Find the equivalent point indices on the opposing side
% of a circular vector.
%
% POINTSI = CIRCOPPOSINGPOINTS(POINTSI, STARTI, ENDI, VSIZE)
%
% POINTSI = CIRCOPPOSINGPOINTS(POINTSI, STARTI, ENDI, VSIZE,
%... |
fec961484902bc54869a9700cbcca316390a5259c78973772c352c2b27fe7e45 | MATLAB | 3,928 | 139 | function xs = de_pl_osps(x, Gb, ymi, Im, rmi, R, ftab, Gtab, masseff, niter, pixmax, gi, denom)
%function xs = de_pl_osps(x, Gb, ymi, Im, rmi, R, ftab, Gtab, masseff, niter, pixmax, gi, denom)
% The Dual-Energy PL-OS-SPS algorithm for transmission Poisson problem
% (ordered subsets, separable paraboloidal surrogates)
... |
b7a87a624daa7118a6c960ff17fc89b26b9c2ff1f76b5b10e0c3d4e81970551f | MATLAB | 3,930 | 113 |
function plot_replay_events(significant_replay_events,place_fields_BAYESIAN,events,track)
load significant_replay_events_wcorr.mat
load extracted_place_fields_BAYESIAN.mat
load extracted_position.mat
load('X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\Chapter 2\Raw_replay_analysis\extracted_replay_plotting_inf... |
680efc842854f69c673073db0f3c833a459ae6e26d2a553742be1ad2039015b7 | MATLAB | 3,931 | 153 | function xs = tpl_os_sps(x, Gb, yi, bi, ri, R, niter, pixmax, curv, ...
gi, denom, relax0, chat)
%function xs = tpl_os_sps(x, Gb, yi, bi, ri, R, niter, pixmax, curv, ...
% gi, denom, relax0, chat)
%
% T-PL-OS-SPS algorithm for transmission Poisson problem
% (ordered subsets separable paraboloidal surrogates)
% in
%... |
8a52f9f90cd6764e7568e6388ba2a28dd7bc201e4695cddf2dfc70225471d844 | MATLAB | 3,932 | 83 | folder='/projectnb2/npbssmic/ns/210310_PSOCT_4x4x2cm_BA44_45_milestone/';
datapath=strcat(folder,'dist_corrected/');
% add subfunctions for the script. Change directory if not running on BU SCC
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addp... |
c16eedc27061818ea27ce498637b2bcb6e19e0f6db763abe724c9f3e2ae38d87 | MATLAB | 3,937 | 112 | function [fNum,stateFigure,kinFigure] = plotStatTestRetContKNN(f_orcoAll,state2Cons,tim2Cons,p_cutoff,fNum)
if isempty(p_cutoff)
p_cutoff = nan;
end
k=1;
nGen_per_page = 3;
nGen = size(f_orcoAll,2);
for gen = 1:nGen
m_1 = f_orcoAll{1,gen}.model.params;
m_2 = f_orcoAll{2,gen}.model.params;
tGrid = f_or... |
a0c78aa7f1eda7f3972e61ac0d39e367ceb807b4514c26a91ba102ffe7782035 | MATLAB | 3,941 | 120 | function [outZCR,outZCRFreq] = IPEMCalcZeroCrossingRate (varargin)
% Usage:
% [outZCR,outZCRFreq] =
% IPEMCalcZeroCrossingRate(inSignal,inSignalFreq,
% inFrameWidth,inFrameInterval,
% inZeroTolerance,inPlotFlag)
%
% Description:
% Calculates the... |
90c58a290059e12de7b0ea12fb23db32d8c345e07b54a6ad42431d31d8835b71 | MATLAB | 3,942 | 102 | function [newStateProb,XX,YY,newState,newStateProbBaseline] = getKNNProbStop(f_orco, s, keyNdx, xGrid, yGrid, ...
ratio, Thresh, K, state, genotype, plotFig)
l = cellfun(@(c)strcmp(c,keyNdx),{state},'UniformOutput',false);
l2 = cellfun(@(c)strcmp(c,keyNdx),{'1'},'UniformOutput',false);
l3 = cellfun(@(c)strcm... |
9eab3722e1cf27bed220859f44033a83af69f26d282a5cc27ffc303927d8ace7 | MATLAB | 3,944 | 166 | function xs = epl_inc(x, Gb, yi, ci, ri, R, varargin)
%function xs = epl_inc(x, Gb, yi, ci, ri, R, [options])
% Incremental optimization transfer version of EM algorithm for
% penalized log-likelihood emission image reconstruction from Poisson data.
% see eql_sps_os.m for arguments
%
% options
% niter (#) # of iterat... |
0d2a268b1b40e875f7e16ebeafc75ba332bfa4c50cd39bce2d62342f88edb7fa | MATLAB | 3,945 | 98 | % Title: Generation of Parameters for CEST Pools
% Description: This function is responsible for generating the parameters of
% CEST pools. It initiates the parameters for a set number of pools,
% and then, based on user-defined limits and ranges, it populates the
% parameters needed for each pool such as relaxation ... |
d842d2cf9aa796fda6088f599f056e89b4c1414a6bca84d3f5af5bcfcefb7f1d | MATLAB | 3,946 | 167 | function ob = Gdsft(om, Nd, varargin)
%function ob = Gdsft(om, Nd, varargin)
%| Construct Gdsft object, which computes (nonuniform) FT samples
%| of signals with dimensions [(Nd)] exactly, e.g., for testing Gnufft
%| For faster computation, use Gnufft instead.
%| See Gdsft_test.m for example usage.
%|
%| in
%| om [M D... |
12c13f994c9803561fc1f3c6889e975550af6a831fff83931421ff2a0d4b3013 | MATLAB | 3,949 | 164 | %MTIT creates a major title in a figure with many axes
%
% MTIT
% - creates a major title above all
% axes in a figure
% - preserves the stack order of
% the axis handles
%
%SYNTAX
%-------------------------------------------------------------------------------
% P = MTIT(TXT,[OPT1,...,OPTn])
% P... |
8cff306f737feaa13614025ad75786af1c5131c8701a389225c4684d6d481572 | MATLAB | 3,951 | 124 | basepath = pwd;
%set format
format long
% THIRDPARTY DEPENDENCIES
addpath(fullfile(basepath,'thirdparty'))
addpath(fullfile(basepath,'thirdparty','QPBO-v1.32.src'))
addpath(fullfile(basepath,'thirdparty','glmnet_matlab'))
addpath(fullfile(basepath,'thirdparty','glmnet_matlab','glmnet_matlab'))
addpath(fullfile(basepa... |
b55bc6c5a3c54f9d814628fa48f0f3996dc29d619e312dddac72aea776087870 | MATLAB | 3,952 | 118 | function [ncs_out] = fn_read_neuralynx_ncs_split(fname)
%% Read neuralynx .ncs file using Fieldtrip read_neuralynx_ncs
% Based on ft_read_neuralynx_interp from Martink Vinck and Fieldtrip
error('dont use this, use fn_read_neuralynx_interp');
if exist('/home/knight/','dir');root_dir='/home/knight/hoycw/';app_dir=[root_d... |
e801d4ce9ad438ab8c7cad069bb6f56b741282a17305223e695a060ac48b9901 | MATLAB | 3,952 | 164 | function [sig_tps,p,tbl] = shuffled_permutation_test_Fscore(mean_coherences, lags, thres, repetitions, anova_samples, plt,nS)
% loop through time points and calculate F-scores for original collect
% labelling
Fscore_org = zeros(lags+1,3);
labels = {'Fscore resampled frequency','Fscore resampled trial length', 'Fscore... |
350e2829576215a2ddf38bffcc9b21ad6022edeb54a8baa8b5c83728ba283bf9 | MATLAB | 3,953 | 92 | function [linker, paired_ep_ind, found_idx_str] = fun_graph_get_linker_for_int_link(vessel_image, vessel_mask, vessel_skl, int_link)
% fun_graph_get_linker_for_int_link use threshold relaxation to find the
% linkers for internal link with endpoints.
% Input:
% vessel_image: 3D numerical array, image stack
% ... |
236b995ed574e6623be9c17737eebcfff54ec5c2e4ac11daed8bf00fa85f1583 | MATLAB | 3,956 | 114 | function compare_retina_locations()
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
dataset_path = get_dataset_path();
imgs_path = [ dataset_path '\17. REAVER Data\Exp_300 C57Bl6 Lectin@647 Retina\zsnap'];
img_items = dir([imgs_path '/*.tif']);
metric_tbl = table();
elem = @(x) x{1};
... |
3d5fc97d90b1bd6f41795e7fcb110953bc2284ac81b970a0427201f95e0d6021 | MATLAB | 3,959 | 148 | function [D]=pons_cut_adf(subject, th_pval)
% For the subject "subject": computes the Dice coefficient D=2*Nab/(Na+Nb)
% Na is the volume of the Cerebellum+Brain-stem obtrained trough the volume-based labeling
% Nb is the volume "filled" obtained from the surface-based stream
% Nab is the volume of th... |
cf9ded33a4b3adc10fa680090653cd03631b7e0b1553b57de08d8fda66e324c3 | MATLAB | 3,961 | 139 | function proj = ellipsoid_proj(cg, params, varargin)
%|function proj = ellipsoid_proj(cg, params, varargin)
%|
%| Compute set of 2d line-integral projection views of ellipsoid(s).
%| Works for both parallel-beam and cone-beam geometry.
%|
%| in
%| cg ct_geom()
%| params [ne 9] ellipsoid parameters:
%| [x_center ... |
f66df2b2daac1cc364b87c470efc6aa336dcef05e3a3f2a629112a031e53fdb5 | MATLAB | 3,962 | 95 | %
% plot raster and PSTH, grouped by multiple conditions indicated by
% different colors. Pulls together various code needed to do this with one
% simple call.
%
%
% urut/Oct'22
function [axRaster,axPSTH]=plotSpikeRaster_multiple_simplified( plotMode, offsets, limitRange_forRaster, limitRange_forPSTH, markerPos... |
9235f42845d3f02d01f7f8f68408c41b49ab69d85aececb54c6b2433706c86d0 | MATLAB | 3,964 | 122 | function [design,col_names,col_values] = fn_build_design_predictors_numeric(SBJ,stat_id)
error('check for 2021 updates');
%% Build design matrix of predictors for regression analysis
[root_dir, app_dir] = fn_get_root_dir(); ft_dir = [app_dir 'fieldtrip/'];
%% Variable Handline
eval(['run ' root_dir 'PRJ_Error/scripts/... |
272ee9299bfa72bd2daa10936b79c9f150be1e2e2e3dafb64741944b5d863428 | MATLAB | 3,968 | 110 | %%
function [deltaB,mag,output_chi] = addChiSource(chi_mo,maskErode,Params,n_time,th,filter_flag)
% [deltaB,mag,output_chi] = addChiSource(chi_mo,Mag,maskErode,Params,n_time,th,filter_flag)
% Author: Joe
% Affiliation: XMU
% Create: 2022-12
% Updated Joe: 2023-11
if nargin<5
n_time = 100; % the numeber t... |
d69b69bdbb7ba0c7f87c89aca38b017129a0133b5f98a6f5576cfa8b811759e0 | MATLAB | 3,969 | 136 | clear all
subj = '39'
regList = { 'OFC' 'FRO' 'TEMP' 'MTL'}
if strcmp( '83', subj)
regList = { 'FRO' 'TEMP' }
end
%%
% go to dir/load data
cd('/mnt/yassamri/iEEG/sandra/groupdata_spectrograms_onset')
load(['subj' subj 'spectrograms.mat'])
addpath('/mnt/yassamri/iEEG/sandra/analysis_pipeline_final/fieldtrip-... |
1f4a3c2002e7c4cca8d2cb5322c4292f9f78513025556bb8b5b3f679191e458b | MATLAB | 3,970 | 85 | function add_nans_to_data(subjects,task)
%ADD_NANS_TO_DATA For the subject that are missing data for certain
%conditions, add NaNs so that their data still has 60 conditions.
%
%Input: subject IDs, task (1=categorization,2=distraction), conditions to
%replace
%
%Returns a data matrix of 60 conditions x dimensions of th... |
b3e45997180d131fb3ef44150e3f3ef5187c66b18e83ed110ec34d58eda2c658 | MATLAB | 3,971 | 81 | % specify dataset directory
OCTpath = '/projectnb2/npbssmic/ns/remote_folder/'; % OCT data path.
datapath=strcat(OCTpath,'dist_corrected/');
P2path = '/projectnb2/npbssmic/ns/Ann_Mckee_samples_20T/NC_6839_2P/'; % 2P file path
% add subfunctions for the script. Change directory if not running on BU SCC
addpath('/p... |
f97b42ed9e7cc1a1cfd02cc5562c9535d0ccec14e11602103804f80cd18e4b4e | MATLAB | 3,972 | 99 | % Define figure coordinates and axes
figX.fig = figure('Name', 'Figure X: STAs Across Frequencies');
set(figX.fig, 'Units', 'pixels', 'Position', OSScreenSize([15 4]), 'NumberTitle', 'off');
figX.pta(1) = axes('Position', [.025 .08 .225 .8]); figX.pta(2) = axes('Position', [.275 .08 .225 .8]); figX.pta(3) = axes('Posit... |
a6e719d2dd7a28a70f6da8dda0ea34ceed4ecda6e2817fedd562fe1441739059 | MATLAB | 3,977 | 149 | function plotOneEx(tbl)
thr = 0.8;
nCh = size(tbl,1);
switch nCh
case 1
nrow = 1;
ncol = 1;
case 24
nrow = 6+1;
ncol = 4;
ha_ch = gobjects(4,6);
case 32
nrow = 8+1;
ncol = 4;
ha_ch = gobjects(4,8);
otherwise
end
lcolor = lines(2);
lineW... |
acb9ed08f83a5e415d1b7fb5cdbbb704748db231f3e968cb09ad7cb57957bd55 | MATLAB | 3,979 | 115 | clear all;close all;clc
figure
hold on
addpath('/mnt/yassamri/iEEG/sandra/analysis_pipeline_final')
% define params
group_plots = 'yes'
freq_range = 'deltatheta';
fpass = [4 5];
times1 = {'0' '0' '0.5'};%'0' '0' '0.5'
times2 = {'2' '1' '1.5'};%'2' '1' '1.5'
bidirec = 0.5;
pattern = 1
phase_l... |
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