sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
65d8887cfdd9cce790aae4f76ee7557ae63a04358e476380c4da4ce38a3dd34d | MATLAB | 5,380 | 194 | % Connecting parallel pool
c = parcluster;
parpool(c, 14);
if not(isfolder('init_data'))
%
% Create a unique RNG stream if using poissonP or constructConnections/GJ
sc = parallel.pool.Constant(RandStream('Threefry','seed','shuffle'));
seed = sc.Value.Seed;
%}
%Sim variables
var_rep = 1:150;
var_recip_prob = 0:0.2:1... |
2206e41c08bbf43d4f4fcc377092d0ef712ba2e6687588f1c2a1902750744b25 | MATLAB | 5,395 | 147 | classdef CrossRegionInformation < handle
% CrossRegionInformation
% Manages information between source and target brain regions, such as distance and domain definition.
properties
SourceRegionInfo BrainRegionInformation
TargetRegionInfo BrainRegionInformation
DistanceMatrix double =... |
252533b7473ea158f4642d7ce7873d70198570ad9a026a6435e5c01e40d928a7 | MATLAB | 5,405 | 158 | %% Gergely Tarcsay, 2024, Ewell lab. Script to calculate % of type of trial errors made during the lesion experiments.
close all
if ~exist("lesion_struct", "var")
load ("G:\HPC lesion\LesionData.mat")
end
if ~exist("behavior_struct", "var")
load ("G:\Behavior\BehaviorData.mat")
end
%%get baselin... |
b23e10f89623624abcef70f0f33ea65218d67dda862ae456a02112a470261a39 | MATLAB | 5,411 | 184 | function varargout = gettfm(mat,varargin)
% A = GETTFM(MODEL,{SPEC})
% [A OFFSET] = GETTFM(MODEL,{SPEC})
% Generate the color transformation matrix for conversion
% between RGB and various luma-chroma models. Transformation
% matrices are calculated from scratch and are not truncated.
%
% MODEL specifies ... |
d67e5476bee837271bbcf0d9371b9759703f20237b6a2413f55d1e48058cfc2e | MATLAB | 5,411 | 148 | clc
clear all
Q_N = 23;
Q = 2^23-1;%%量化位宽，整数8位小数23位
Q_FIL = Q;
data = readNPY('D:\YCB\YCB\PROJECT\EEG_signal_processing\python\raw_signal.npy');
data_Q = floor(data.*Q);
%ese
a0 =[ 1. -0.93906251];
b0 =[ 0.96953125 -0.96953125];
a0_Q =floor(a0 .*Q_FIL) ;
b0_Q =floor(b0 .*Q_FIL) ;
x_filtered_band0 = f... |
1aade7216d5ff021331ec12bd29fe13832971bb8de34d237f768f9d0e1496eb6 | MATLAB | 5,426 | 127 | function writeSpykingCircusParameters_new(cfg)
% WRITESPYKINGCIRCUSPARAMETERS writes .params and .prb file for Spyking Circus
%
% use as
% writeSpykingCircusParameters(cfg)
%
% The .params file is based on the one in the template folder of EpiCode.
% Change this file to have new default values.
%
% Mandatory inputs
... |
4fb25e4a2abf8b6f66508b1b2d0e7cfdfe1e3d28bbeb90b68c9600605aa2f796 | MATLAB | 5,428 | 196 | % Connecting parallel pool
c = parcluster;
parpool(c, 14);
if not(isfolder('init_data'))
%
% Create a unique RNG stream if using poissonP or constructConnections/GJ
sc = parallel.pool.Constant(RandStream('Threefry','seed','shuffle'));
seed = sc.Value.Seed;
%}
%Sim variables
var_rep = 1:150;
var_recip_prob = 0:0.2:1... |
e8067feeea3b9dae8d771d6af8663a6782818f27783aa66b07645562e9da0e3e | MATLAB | 5,433 | 158 | %% ============================================================
% Brightfield + fluorescence prep → training images + label map
% Author: Pei-Hsun Wu @ JHU | Cleaned: 2025-12-05
%
% Output:
% - Example Data\TrainData\im\xy01_bf.tif
% - Example Data\TrainData\label\xy01_allLabel.tif
%
% Label codes... |
2768e2d2d10d9829b7ced8e1f33398c6aa7ed05f39d897b65e43d9b609d77927 | MATLAB | 5,451 | 158 | function [y, h] = resample( x, p, q, N, bta )
%RESAMPLE Change the sampling rate of a signal.
%
%!!!!!
% Lower LP corner than Matlab's resample (Matlab's gives inadequate
% antialias filtering).
% Works with multidimensional arrays (Matlab's doesn't).
%!!!!!
%
% Y = RESAMPLE(X,P,Q) resamples the sequence in vec... |
ea41cd1ce5b2b61f316447fa93cbdf5f4fb83ff6fc11c56474ce2517ed900997 | MATLAB | 5,452 | 82 | %-----------------------------------------------------------------------
% Job saved on 11-Oct-2023 10:43:05 by cfg_util (rev $Rev: 7345 $)
% spm SPM - SPM12 (7771)
% cfg_basicio BasicIO - Unknown
%-----------------------------------------------------------------------
load('tmp_workspace_batch_ANOVA_2_groups.ma... |
240a8fa1764d81d7d3a017969266c4fc95c172683338987b4a47fbac6c229d4d | MATLAB | 5,453 | 135 | %% wrapping function for vector analysis - second version
function [All,Individual]= WrapVectorRemap2(workdir, discrimination, LightBin)
All.AngleDiff = {[]; []};
All.IsOrthogonal = {[]; []};
All.MeanRate = {[]; []};
All.TuningStrength = {[]; []};
All.TuningBin = {[]; []};
All.RewardTuning = {[]; []};
All.... |
b1e2201971abd1b3a0b732fc3c19618a3a5079631559dbc1b2a23688b316b53e | MATLAB | 5,453 | 150 | function [data_out, Tr_pp, Tr, bin_center] = histeqSmooth(data, arg2, arg3, arg4, arg5)
% Performs histogram equilization using parzen window estimates of histogram and pchip based
% mapping of CDFs. It should produce smoother output images and more continueous and smooth
% intensity transformation than matlab based hi... |
4834810bcbe28035f2ac8aa992fe4c13434844f38e0b5b638a142c4c2b9a85ca | MATLAB | 5,454 | 83 | %-----------------------------------------------------------------------
% Job saved on 11-Oct-2023 10:43:05 by cfg_util (rev $Rev: 7345 $)
% spm SPM - SPM12 (7771)
% cfg_basicio BasicIO - Unknown
%-----------------------------------------------------------------------
load('tmp_workspace_batch_ANOVA_2_groups.ma... |
a1ec24e18957202cc18918e997dc67dfed5657ae132567c7ff6c0dbf136de43f | MATLAB | 5,472 | 116 |
%% load experiment info and set a few variables for analysis
clear
% load experiments and generic stuff
experiments = 'Load your experiments';
repeatCalc = 0;
save_data = 1;
% loading and filtering variables
fs = 32000; % from data
downsampling_factor = 320; % downsample for LFP analysis
fs_LFP = fs / downsampling_f... |
e8048804c38ade7789915583a01ebab1a257c826d676f91a5980af354b34323b | MATLAB | 5,476 | 160 | function clusterInfo = cluster_data(locAll,varargin)
% the returned index contains noise data with idx=1
% locAll %um
prmAll = varargin{2};
prmAll.cluster = set_default_parameters(varargin{:});
prm = prmAll.cluster;
for ll=1:numel(locAll)
if ~isempty(locAll{ll})
locAll{ll} = locAll{ll}*1e3;
... |
8c414ef3fca29886cfd10e2725967286bd436ee3b86e8660cdd554333980c551 | MATLAB | 5,479 | 135 | function PET_project_per_patient(ipatient)
restoredefaultpath
if ispc
addpath (genpath('\\l2export\iss02.charpier\analyses\vn_pet\EpiCode\shared'))
addpath (genpath('\\l2export\iss02.charpier\analyses\vn_pet\EpiCode\external'))
addpath (genpath('\\l2export\iss02.charpier\analyses\vn_pet\EpiCode\templates')... |
e9d0bbc82856b820b4a1d495409c7a0db5e1f1f0923205136cafb564b0cdc652 | MATLAB | 5,488 | 196 | % Connecting parallel pool
parpool("Threads");
if not(isfolder('init_data'))
%
% Create a unique RNG stream if using poissonP or constructConnections/GJ
sc = parallel.pool.Constant(RandStream('Threefry','seed','shuffle'));
seed = sc.Value.Seed;
%}
%Sim variables
var_rep = 1:150;
var_pv_prob = 0:0.2:1;
var_som_prob =... |
7cd01ad152f85f90930b70c8616d97b7f2a08746d1aa5335a8d14d1adbbe5e88 | MATLAB | 5,498 | 131 | function [Sc,Cmat,Ctot,Cvec,Cent,f]=CrossSpecMatpt(data,win,T,params)
%
%
% Multi-taper cross-spectral matrix - another routine, this one allows for multiple trials and channels
% but does not do confidence intervals. Also this routine always averages
% over trials - point process as times
%
% Usage:
%
% [Sc,Cmat,Ctot... |
28e4b227604786d0593a6f0716b94b61f33fac45ccc279dfcbea1c9e42e28f68 | MATLAB | 5,508 | 182 | function [] = modelDiagnostics(mixed_folder, file_name, data, lme)
close_figs = 0;
fit_plot =0;
Y = data;
diag_folder = fullfile(mixed_folder, 'Diagnostics');
if ~exist(diag_folder)
mkdir(diag_folder);
end
% model fit
model_fit = lme.ModelCriterion
save(fullfile(diag_... |
b6eedb980e649aea644c3c1361c1c0ba166c4be6358a1558ac477567e0ead184 | MATLAB | 5,508 | 154 | % analysis of behavioural data
exgaussdir = 'C:\Users\admin\Documents\MATLAB\bramzandbelt-exgauss-7cf8c4c';
addpath(exgaussdir)
clear all
pps = setdiff(9:31,[12 20]);
for s = 1:length(pps)
datadir = 'D:\ES_data_Hannah\data';
cd(datadir)
if pps(s)<10
cd(strcat('P0',num2str(pps(s))))... |
86fbff92d062c37f72d893766e6bddf1f556158323d997f11de61d252b1e8e74 | MATLAB | 5,515 | 135 | function smoothedPhi = CBIG_AuthorTopic_SmoothPhi(params)
% smoothedPhi = CBIG_AuthorTopic_SmoothPhi(params)
%
% Spatially smooth the parameters of the variational distribution phi.
%
% Input:
% - params: struct containing parameters of the author-topic model and
% the Collapsed Variational Bayes (CVB) algo... |
fd35442c73d7575698a64e9b868d30caace05676d190b49a22413331a6d76878 | MATLAB | 5,517 | 133 | %% wrapping function for vector analysis - second version
function [All, Cohort, Individual]= WrapVectorRemap3_FINAL(workdir, discrimination, LightBin)
All.AngleDiff = {[]; []};
All.IsOrthogonal = {[]; []};
All.MeanRate = {[]; []};
All.TuningStrength = {[]; []};
All.TuningBin = {[]; []};
All.RewardTuning = ... |
84cc4d64283a303bef64313e083feb017b9990de5dddeaf7f692770061cf584d | MATLAB | 5,521 | 185 | function kbboxchart(paramArray, varargin)
% KBBOXCHART - Draws multiple stylized boxcharts with explicitly defined parameters,
% mimicking the style of MATLAB's boxchart.
%
% Inputs:
% paramArray - struct array, each with fields:
% bottomWhisker, bottomBox, bottomNotch, median,
% topNotch, top... |
fcbf28db320b1eb67bcbb93c60c63e51314b16cb64b457586d40efc6cbfe23f5 | MATLAB | 5,523 | 159 |
function [Best_Finfo,Best_Pinfo,Historical_Info]=IAO(N,Max_iter,LB,UB,Dim,fobj)
% Initialize
Info=initialization(N,Dim,UB,LB); % solution
New_Info=Info;
Ffun=zeros(1,size(Info,1)); % fitness value
Ffun_new=zeros(1,size(New_Info,1));
Best_Pinfo=zeros(1,Dim); % best solution position
Best_Finfo=inf; % best... |
5c29b6504aadafeb7fbd90ac95b5ae811f679683ae2b0a6ffb42bcbc4c594161 | MATLAB | 5,534 | 161 | function U = nullspace_vectors_C_matrix_2D(kCal, varargin)
% Function that returns the nullspace vectors of the C matrix.
%
% Input parameters:
% --kCal: N1_cal x N2_cal x Nc block of calibration data, where
% N1_cal and N2_cal are the dimensions of a rectangular
%... |
40dd62a0e5e31fbd17c65f1b845c82a07665be3b65bd6b69abca64f5a246c4ca | MATLAB | 5,538 | 194 | function outpict = bwfilmemu(inpict,film,varargin)
% OUTPICT = BWFILMEMU(INPICT,FILMTYPE,{FILTER},{OPTIONS})
% Roughly emulate the appearance of color scene as represented by one
% of various B&W film types. The result is a simple weighted sum of sRGB
% components. Obviously, this shouldn't be taken as an accura... |
8c4c72bae368feb66e7bb77a4acc696d0d7a59c084085227a16d421bca1e2de7 | MATLAB | 5,538 | 198 | % Connecting parallel pool
parpool('Threads');
if not(isfolder('init_data'))
%
% Create a unique RNG stream if using poissonP or constructConnections/GJ
sc = parallel.pool.Constant(RandStream('Threefry','seed','shuffle'));
seed = sc.Value.Seed;
%}
%Sim variables
var_rep = 1:150;
var_pv_prob = 0:0.2:1;
var_som_prob = ... |
d2968dd02ab5563aa8940bba6640fa31ab5a6c3e8800ddd57020683c63853ca4 | MATLAB | 5,541 | 58 | %%% This code is designed for visualizing rank changes and annotating behavioral observations in the tube test.
clear all
close all
clc
%%% Plot for social rank changes for a cohort of hM4Di-EGFP mice before and after CNO administration to the rank-3 mouse at time 0.
rankchange=[1 1 1 1 1 3 1 1 1 %% Crea... |
72477decf1183aade326ce33e56766b7cfa7a29be5b310d646f2b1591bbbf7a7 | MATLAB | 5,544 | 184 | %% Downloads example data (900MB), runs GLM analysis and extracts timeseries
% Settings
% Directory into which to download example dataset
data_root_dir = 'D:\samdata\';
data_dir = fullfile(data_root_dir,'Example','pRF');
surf_dir = fullfile(data_root_dir,'Example','surf');
% Directory for creating GLM
glm... |
6124fc414bd08f5631bb9c7d45900d6fc92fc8b2dbc09095967de5ba7ed04512 | MATLAB | 5,547 | 138 | function [OPS_object_data_pos] = Object_detection_OPS(settings,pos_idx,phase)
% [OPS_object_data_pos] = Object_detection_OPS(settings,pos_idx,phase)
% Detects object locations and saves data in a struct
%
% inputs:
% settings - Analysis and experimental settings
% pos_idx - position number to analyse
% phase - ... |
e3bf4bc7db2e0dd844cb162685a2643d310df5c36bf7dde5debe410c71e7be6e | MATLAB | 5,552 | 154 | function Figure_hypnograms
MuseStruct{8} = [];
LFP_cluster{8} = [];
LFP_cluster_detected{8} = [];
clusterindx{8} = [];
config = hspike_setparams;
for ipatient = 1 : 8
MuseStruct{ipatient} = readMuseMarkers(config{ipatient}, fal... |
2635c7b7ef377e341edef328b3761c83ec1285efc24437dfb3f0ef9a8a8766bd | MATLAB | 5,555 | 98 | function neurons_table = summarized_neurons_table(cfg, markername, force, spikestats, waveformstats, spiketrials)
% Use as :
% neurons_table = summarized_neurons_table(cfg, ipart, markername, force, spikestats, waveformstats, spiketrials)
% summarized_neurons_table creates a table with the summary of the main
... |
847d98f9cfcdee9905a5445d247887fe7e0feb8efbadc7dbaf164789bd62ca95 | MATLAB | 5,558 | 200 | % Connecting parallel pool
parpool('Threads');
if not(isfolder('init_data'))
%
% Create a unique RNG stream if using poissonP or constructConnections/GJ
sc = parallel.pool.Constant(RandStream('Threefry','seed','shuffle'));
seed = sc.Value.Seed;
%}
%Sim variables
var_rep = 1:150;
var_recip_prob = 0:0.2:1;
var_div_prob... |
bacaf35d75a924c773cf62385e6bf025221313229b350ee6196eec2d39a007e6 | MATLAB | 5,560 | 163 | function [data] = ft_appendspike(cfg, varargin)
% FT_APPENDSPIKE combines continuous data (i.e. LFP) with point-process data
% (i.e. spikes) into a single large dataset. For each spike channel an
% additional continuos channel is inserted in the data that contains
% zeros most of the time, and an occasional one at the... |
509e20aa0e7659b093a1bbf85c78630ca8edb3ae0908c1876bec7f091cee9d4f | MATLAB | 5,564 | 161 | function U = nullspace_vectors_C_matrix_3D(kCal, varargin)
% Function that returns the nullspace vectors of the C matrix.
%
% Input parameters:
% --kCal: N1_cal x N2_cal x N3_cal x Nc block of calibration data, where
% N1_cal, N2_cal, and N3_cal are the dimensions ... |
bae6890bae08a6bd4b6d59dbea1218a5c134504964bf77b8ed88f8d34d6cb69e | MATLAB | 5,567 | 139 | function [output_data] = filter_downsample(path_extract,fs,plot_duration)
% On-Demand Seizures Facilitate Rapid Screening of Therapeutics for Epilepsy
% Authors: Yuzhang Chen, Brian Litt, Flavia Vitale, Hajime Takano
% DOI: https://doi.org/10.7554/eLife.101859
% Function Purpose: Filter Raw EEG Data.
% Input Variabl... |
4fb63cbf705b89d49fc5f5dd8a5a92891198cb8abefd460ae2702ec811c4896f | MATLAB | 5,568 | 153 | function wod_project_lfp(slurm_task_id)
if ispc
addpath (genpath('\\lexport\iss01.charpier\analyses\wod\EpiCode\shared'))
addpath (genpath('\\lexport\iss01.charpier\analyses\wod\EpiCode\external'))
addpath (genpath('\\lexport\iss01.charpier\analyses\wod\EpiCode\templates'))
addpath (genpath('\\lexport\... |
61c28b34b34ce8bd834302b164fa3c424b8f5808d9b174c8745b1998a3901f81 | MATLAB | 5,576 | 176 | function [D,E,R]=nt_cca_aad(xA,xB,y,ssize)
%[D,E,R]=nt_cca_match_aad(xA,xB,y,ssize) - calculate metrics for match-mismatch task
%
% D: d-prime
% E: error rate
% R: correlation coefficient over entire trial
%
% xA,xB: stimulus streams
% y: response
% ssize: samples, segment size [default: all]
if nargin<3; erro... |
d96b8d58adfb3a97b46109d82317c914c0a18ce75aeeae855950e9865a4ca4b9 | MATLAB | 5,579 | 118 | %% Import data from text file
txtfileFullName = ['.txt']; % Text File location
OutputSaveLocation = ['\dataStruct.mat']; % Enter location of folder where output is desired
% import .txt. file (lick times and state)
opts = delimitedTextImportOptions("NumVariables", 5);
% Specify range and delimiter
opts.DataLines = [... |
05c3157d0b8ac96629524f5b8a173f5759b2014b46879b1c62ec63b63cb45c07 | MATLAB | 5,585 | 202 | % Connecting parallel pool
parpool('Threads');
if not(isfolder('init_data'))
%
% Create a unique RNG stream if using poissonP or constructConnections/GJ
sc = parallel.pool.Constant(RandStream('Threefry','seed','shuffle'));
seed = sc.Value.Seed;
%}
%Sim variables
var_rep = 1:150;
var_recip_prob = 0:0.2:1;
var_div_prob... |
07a6b14de31b8a7590fce27b6af83f28c6a460be257947de3ef0ba12cf518fb5 | MATLAB | 5,588 | 116 | function [lh_proj_data, rh_proj_data] = CBIG_ProjectMNI2fsaverage_Ants(data, average, interp_type, lh_index_mat, rh_index_mat)
% Usage: [lh_proj_data, rh_proj_data] = CBIG_ProjectMNI2fsaverage_Ants(data, average, interp_type, lh_index_mat, rh_index_mat)
%
% Function projects MNI data to fsaverage
% Also see reverse tr... |
ebbd84e576b6bd2557948e4d274ec278eda93b1a2228f56c270b646c9be80965 | MATLAB | 5,590 | 123 | [textFileName, textFilePathName] = uigetfile('*.txt', 'Pick txt file specifying input');
fid = fopen(strcat(textFilePathName,textFileName));
% filename pathname conditions
textFileInput = textscan(fid, '%s %s %s %s %s', 'Delimiter', '\t', 'HeaderLines', 1);
fclose(fid);
numFiles = length(textFileInput{1});
fullPathFi... |
21cae4ebe4ba257fa0f547a167ff06fd695859cbca4d01ad261d66069c271f73 | MATLAB | 5,600 | 162 |
% Correlate varA with varB accounting for confounds (SPM)
clear, clc, close all
%% Paths / data
path_batches = 'D:\Projects\2023_multib\MK_multi_b\Scripts';
cd(path_batches)
% load('Table_demographics_biomarkers_2024_04_09.mat')
load('Table_297_subjs_demographics_biomarkers_2024_05_03.mat')
n_subjects = ... |
d60fa960eb2806e317096d4514a3f221223e193f5a740720a16980c2734be321 | MATLAB | 5,606 | 202 | % Connecting parallel pool
parpool('Threads');
if not(isfolder('init_data'))
%
% Create a unique RNG stream if using poissonP or constructConnections/GJ
sc = parallel.pool.Constant(RandStream('Threefry','seed','shuffle'));
seed = sc.Value.Seed;
%}
%Sim variables
var_rep = 1:150;
var_recip_prob = 0:0.2:1;
var_div_prob... |
13da0f440f350846edee17ad7b79c6425066286090c43a02ba93e8109bc70e4c | MATLAB | 5,610 | 171 | classdef SynapseLive < handle
%SynapseLive TDT online data streamer.
% obj = SynapseLive() connects to TTank server and opens currently
% recording block in Synapse
%
% obj.data reference to all available data from block
% obj.update get latest data from current block
% obj.TT... |
5dd854fa650c5bf463a0ba110a5af5f2a12f5423bb77b58726f5994ac34f8a75 | MATLAB | 5,629 | 190 | function outpict = mono(inpict,channel,weights)
% MONO(INPICT,CHANNEL,{WEIGHTS})
% Extracts a single channel from RGB images or triplets
%
% INPICT is an RGB/RGBA image. Multiframe images are supported
% If INPICT is I/IA, it will be expanded and processed as usual,
% though the results may be tr... |
ed81f82d28a0a481c4fdc7c772c5bd32700d95641a9297b197923525e88c6a0e | MATLAB | 5,646 | 156 | %% ============================================================
% Semantic segmentation training (DeepLabv3+)
% Author: Pei-Hsun Wu @ JHU | Cleaned: 2025-12-05
%
% Labels (must match your label TIFFs):
% 1 = background, 2 = dapi, 3 = pi
% ============================================================
c... |
3efbb5bd4614baf181ef3e0f3156ee80a5c68f0cefd2f6bb12001a11313d453a | MATLAB | 5,648 | 197 | function outpict = replacepixels(FG,BG,mask,varargin)
% OUTPICT = REPLACEPIXELS(FG,BG,MASK,{LINEAR})
% Simple image composition tool. Loosely speaking, the output image will
% be equal to BG in regions where MASK is dark, and equal to FG in regions
% where MASK is bright. This tool can be used with either ... |
fd75df5e32ddf0adcdcff3ed5dc0d935288708cd95473feefa5c80d13d3a8e23 | MATLAB | 5,657 | 182 | function inpict = imfold(inpict,varargin)
% IMFOLD(INPICT,{SEQUENCE},{METHOD},{OPTIONS})
% Generate an image stack as if repeatedly fan-folding an image.
% Optionally unfold the stack back into a flat image.
%
% INPICT is an I/IA/RGB/RGBA image of any standard image class
% SEQUENCE the intended fold se... |
691db73b312e3701a93500785fccce72fa26c5b455ce63e370162e15f487db86 | MATLAB | 5,677 | 123 | classdef AnalysisDataFactory
properties
ConnectionMatrix ConnectionMatrix
GeneExpressionLevels GeneExpressionLevels
CrossRegionInformation CrossRegionInformation
Description string = "" % explanation
end
methods
function obj = AnalysisDataFactory(con... |
9aba2630040cfb267aa805c0160adce61bdadbe7d08f874d648ab36445a67c14 | MATLAB | 5,696 | 84 | %% Analysis script
%
% (c) Stephen Whitmarsh, stephen.whitmarsh@gmail.com
%
% requires bandpassFilter.m from Mario
% requires releaseDec2015 from Neuralynx website
addpath /network/lustre/iss01/charpier/analyses/stephen.whitmarsh/scripts/epilepsy/shared/
addpath /network/lustre/iss01/charpier/analyses/stephen.whitmars... |
8f9b678d9584927e677d3e216fd52da4eea5695d27ff8613515ee8537551c1d4 | MATLAB | 5,710 | 138 | function nested_lasso_ms_fatigue()
% NESTED_LASSO_MS_FATIGUE
%
% Nested elastic-net / LASSO logistic regression for MS fatigue classification.
%
% - Outcome coding (IMPORTANT):
% y = 1 -> fatigued (MS_F)
% y = 0 -> non-fatigued (MS_NF)
% - Theory-driven candidate predictors; NO outcome-based pre-screening... |
408a6bbbddbea159bfdace53b90865a601a93cb1989145f0f16d52f3f53df5ca | MATLAB | 5,711 | 169 | function CT = im2ct(inpict,varargin)
% CT = IM2CT(INPICT,{OPTIONS});
% Create a color table of specified length using the dominant colors of an image.
% This is a simple tool, and it should be expected that there are many configurations
% of images and options which will yield completely garbage results. Often w... |
c77d9db2a448cebca2c9456f65360754226de03381af9586d201b9088604842f | MATLAB | 5,713 | 111 | function [all_data,indx] = generate_spectral_data(EEG_integrals_am,EEG_integrals_nam, participant, indx, all_data, options)
%% Creates a placeholder cell with the datasets of all participants for plotting of results
%
% **Usage:** [all_data,indx] = generate_spectral_data(EEG_integrals_am,EEG_integrals_nam, participant,... |
aae87920dedee4564fa19985f983dab299165a1e0f1f358be4002156f494607d | MATLAB | 5,731 | 159 | function ArgStruct=parseArgs(args,ArgStruct,varargin)
% Helper function for parsing varargin.
%
%
% ArgStruct=parseArgs(varargin,ArgStruct[,FlagtypeParams[,Aliases]])
%
% * ArgStruct is the structure full of named arguments with default values.
% * Flagtype params is params that don't require a value. (the value will ... |
7344b8ed801df544cb60ce553f5d762f01f14d702ab2cb0a1d4e902fec8afece | MATLAB | 5,736 | 172 | function [z] = plot_single_voxel(PRF, idx, plot_names, transformers, ...
transform_names, num_samples, posterior, show_grid)
% Plotting function for a single PRF with many possibilities, needs to be
% rewritten significantly in the near future.
% TODO: Rewrite
%
% Fo... |
68970642d3bb8c4af96894699fdd8b9627f2eaf88aa3dfddbc0656677a6808f9 | MATLAB | 5,739 | 112 | function preictal_project_LC
restoredefaultpath
if ispc
addpath (genpath('\\lexport\iss01.charpier\analyses\vn_preictal\scripts\EpiCode\shared'))
addpath (genpath('\\lexport\iss01.charpier\analyses\vn_preictal\scripts\EpiCode\external'))
addpath (genpath('\\lexport\iss01.charpier\analyses\vn_preictal\scrip... |
e9380ad3ed6691070452558979dfe7c16abb8de6fd758d283d62fea4bdd956d0 | MATLAB | 5,741 | 119 | function [TCA2B, TCB2A] = fasterTilingCoeff(spike_matrix, maxLag)
%% by Mattia 01.20 - this version has an improved unwrapping part and is
% faster than the standard (fastTilingCoeff) one
% inputs:
% spike_matrix: units * time
% maxLag: the maximum lag for which xcorr will be computed. in the same
% units as the spike... |
452eff59b63f6c8a9bdb011c55f45ac97d69a2814cb71197c2323c3749bcc9c9 | MATLAB | 5,748 | 129 | %% Gergely Tarcsay, 2024. Main analysis to classify cells as spatially stable cells after shuffling.
%% 0. load data & set params
main_path = "C:\Users\ewell\Desktop\TestCodeGitHub\"; % change this according to your path
rootdir = strcat(main_path, "\Discrimination 2025 data\CA1 miniscope data");
addpath(strca... |
e69dd86a1de765039729b5883502303040820cdb94435bff47f4921912c0bc48 | MATLAB | 5,752 | 152 | function colors = distinguishable_colors(n_colors,bg,func)
% DISTINGUISHABLE_COLORS: pick colors that are maximally perceptually distinct
%
% When plotting a set of lines, you may want to distinguish them by color.
% By default, Matlab chooses a small set of colors and cycles among them,
% and so if you have more than ... |
81d4cb434dc1e9ed2204d212b15b9f463704ad6ea61ca73f1f0a64a152fc75ac | MATLAB | 5,756 | 143 | function plotSeizureSegmentation(config,MuseStruct)
% remove empty structs
MuseStruct = MuseStruct(~cellfun('isempty',MuseStruct));
MuseStruct_append = []; %rmfield(MuseStruct{1},'filenames');
MuseStruct_append.markers = [];
% adding next directories
for idir = 1 : size(MuseStruct,2)
fprintf('Working on directory... |
18673db995b043d57019fbebe853a8c454b0ded5e81950af8f0d6873b5c7e1d5 | MATLAB | 5,757 | 126 | function [fig_clust] = plot_clusters(clusterInfo,varargin)
p = set_default_parameters(varargin{:});
for ll=1:numel(clusterInfo.locAll)
if ~isempty(clusterInfo.locAll{ll})
edges = [0:0.5:20 Inf];
edgesNumEl = [0:1:100 Inf];
fig_clust(ll) = figure(345+ll);
... |
2567c5eff719283b0469c39c06f2dfb947d01ed2625f5ef12b56cced80df6d93 | MATLAB | 5,761 | 125 |
config = dtx_spikes_setparams;
ipart = 1;
irat = 1;
%% plot example of raw intercritic
SpikeTrials = readSpikeTrials_MuseMarkers(config{irat}, [], [], false);
%same trial length as the intracellular example :
trialsel = find((SpikeTrials{ipart}.Interictal.trialtime(:,2) - SpikeTrials{ipart}.Interictal.trialti... |
15b8f5f56add863165f72746b3a609d77e4abac964e32e20abb1989d1ae7c208 | MATLAB | 5,763 | 209 | % Connecting parallel pool
parpool("Threads");
if not(isfolder('init_data'))
%
% Create a unique RNG stream if using poissonP or constructConnections/GJ
sc = parallel.pool.Constant(RandStream('Threefry','seed','shuffle'));
seed = sc.Value.Seed;
%}
%Sim variables
var_rep = 1:350;
var_cell_inh = 0:2;
var_conn = 1:5;
... |
d616be912f85772a4d7424723e52c6063a866573033c6fed119edfc57f846cdc | MATLAB | 5,767 | 160 | function outpict = husl2rgb(inpict,varargin)
% HUSL2RGB(INPICT, {MODE})
% converts an RGB input image from HUSL (human-friendly HSL), which is an adaptation
% of CIELCHuv with normalized chroma. This is particularly useful for tasks such as
% avoiding out-of-gamut values when rotating hue at high c... |
94a587f9a138d6e1ba5f9a30d437ae93078dd40c59c1d5f3489e48abbca828e4 | MATLAB | 5,768 | 42 | function headers = decode_acquisition_headers(bytes, dims)
% Convert from a byte array to a ISMRMRD AcquisitionHeaders
% This conforms to the memory layout of the C-struct
bytes = reshape(bytes, 340, []);
N = size(bytes, 2);
dims = num2cell(dims);
headers.version = ... |
aa59c7370e6b7a0535bda693826c2d105dde9b335aa5bbe11f8f061f196656bd | MATLAB | 5,777 | 177 | % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% RECOVERING LOST 'BOMB' MODE TRANSFER FUNCTIONS
% So you used imblend() 'bomb' modes and found a random mesh that you really like
% but you weren't using the 'verbose' option, so now it's gone forever!
% Well don't worry (too much... |
eca486f311ff09bdf7ec715c1e63dfb27671229447491edeb1f30b3554e7ecab | MATLAB | 5,784 | 343 |
%%
% CEC2005
function [lb,ub,dim,fobj] = Get_CEC2005_details(F)
% Obtain the upper and lower bounds and dimensions of the test function
switch F
case 'F1'
fobj = @F1;
lb=-100;
ub=100;
dim=30;
case 'F2'
fobj = @F2;
lb=-10;
ub=10;
dim=30;
... |
78dbb1d2e06039f50b849de06fe694d87ef3306cdc4440582d523dcc75d26ad1 | MATLAB | 5,788 | 101 | function writeSpykingCircusDeadFile_concatinated(MuseStruct)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% function writeSpykingCircusDeadFile(MuseStruct)
%
% Crawls and searches through patient- and recording-directories and writes
% artifact definitions for SpykingCircus. The input st... |
31911033497a73f0bc3ca12a507ee05921bb18c666fa0e17021719a41e370759 | MATLAB | 5,798 | 156 | function results = gcmi_cpp_mex_test(varargin)
p = inputParser;
p.addParameter('Compile', true, @(x) islogical(x) && isscalar(x));
p.addParameter('LegacyPath', fullfile(fileparts(fileparts(fileparts(fileparts(mfilename('fullpath'))))), 'extern', 'gcmi_mex'), @(x) ischar(x) || isstring(x));
p.parse(varargin{:});
opts = ... |
be6809e6aa6c980533b3d75f333983b4cdc451f7d8d54e790703831717b58351 | MATLAB | 5,820 | 150 | %WAVELET 1D Wavelet transform with optional singificance testing
%
% [WAVE,PERIOD,SCALE,COI] = wavelet(Y,DT,PAD,DJ,S0,J1,MOTHER,PARAM)
%
% Computes the wavelet transform of the vector Y (length N),
% with sampling rate DT.
%
% By default, the Morlet wavelet (k0=6) is used.
% The wavelet basis is normalized t... |
179eb04f733d8c329a52d230798d24addf3dc15b2a82b7d73f604a5ce4d1c66f | MATLAB | 5,834 | 102 | function S = reCalcCoefSparse(data, D, S, lambda, varargin)
% S = recalcCoefSparse(data, D, S)
%
% Function to recalulate the sparse coefficients given a dictionary D and
% data "data". The current coefficeints S are used to identify support.
% This function is not designed to be used instead of the inference step, ... |
7352afbe2e0dd27611fc19c77870e7f5ea4707eac97d64f5863ed84f6839517f | MATLAB | 5,845 | 123 | z%% Objective function: minimum envelope entropy, minimum sample entropy, minimum information entropy, minimum permutation entropy, permutation entropy/mutual information entropy (select one)
clear
clc
fullpath = mfilename(“fullpath”);
[path,name] = fileparts(fullpath);
addpath(path)
addpath(genpath(pwd)) % Add all fi... |
83d739e8f7b8350b99a5bb86788178f7767f68f8c20df35dc1b7d313c5ed7559 | MATLAB | 5,852 | 123 | z%% Objective function: minimum envelope entropy, minimum sample entropy, minimum information entropy, minimum permutation entropy, permutation entropy/mutual information entropy (select one)
clear
clc
fullpath = mfilename(“fullpath”);
[path,name] = fileparts(fullpath);
addpath(path)
addpath(genpath(pwd)) % Add all fi... |
ea2de2ff2b5ceee6343fc9b596aecd62c8e48f09b64e2f89c3624c75b1a93266 | MATLAB | 5,869 | 136 | function CBIG_AuthorTopic_RunInference(seed, K, alpha, eta, doSmoothing, baseDirectory, dataPath, burnin, isSavingPhi)
% CBIG_AuthorTopic_RunInference(seed, K, alpha, eta, doSmoothing, baseDirectory, dataPath, burnin, isSavingPhi)
%
% Wrapper function to estimate the author-topic models parameters using the Colla... |
3f69c88f5f9a13ccba8d6921f25b942956fe1dcdac00d1f26d163369b227ad3b | MATLAB | 5,873 | 146 | classdef SpatialAutocorrelationCalculator
methods (Static)
function moransIMatrix = calculateMoransIMatrix(valueMatrix,distanceMatrix,hList)
arguments(Input)
valueMatrix (:,:) double % [NRegion, DimComponents]
distanceMatrix (:,:) double % [NRegion, NRegion]
... |
8a6039d0d95c0ac74c0a42637c857c110d00f3895bb293343f5a466b082097f0 | MATLAB | 5,873 | 110 | function [EEG] = set_parameters(EEG, feature, params, all_eventtypes)
%% Extract the features used for GLM
% **Usage:** [EEG] = set_parameters(EEG, feature, params, all_eventtypes)
%
% Input(s):
% - EEG = EEG struct
% - feature = cell with the feature name (either delta and integral)
% - params = struct with resu... |
9bea8da4653b31b004507d7b321b192a069edaaf6776c883d872202a235c1299 | MATLAB | 5,873 | 202 | function [x,w,ww]=nt_star(x,thresh,closest,depth)
% [y,w,ww]=nt_star(x,thresh,closest,depth) - sensor noise suppression
%
% y: denoised data
% w: 0 for parts that needed fixing, 1 elsewhere (time*1)
% ww: 0 for parts that needed fixing, 1 elsewhere (time*chans)
%
% x: data to denoise (time*chans or time*chans*tria... |
f7360cc9edd27664140c8a0560ec8c504a249b93ba7600a129d9a9d9c477b660 | MATLAB | 5,902 | 198 | clear; close all;
trials = 2;
base_path = '../Simulations/Simulation results';
save_dir = '../Figures/Supplementaries/Supplementary NI';
% Create folder if it does not exist
if ~exist(save_dir, 'dir')
mkdir(save_dir);
fprintf('Created directory: %s\n', save_dir);
end
root_path = fullfile(base_path, 'd... |
fe1d0b1544cba3e1a69f10feb5cb66ece90a2229b60bd5de0e8cc4bb8bb38d37 | MATLAB | 5,902 | 93 | function [SUAinfo, features] = loadKlusta(animal, PRMfolder, DATfolder, save_data, directory2save)
% by Mattia 25/01
% 30.06.2022 Irina: fixed RVP calculation, was using spikes from all clusters
% 04.10.2024 Tony: fixed problem with adding last spike from the previous
% recording into the next one
% instead of current... |
01d452c7382ca6ac4ce85a517b102f6b3b034e2017f60726fa53be01d882ab1b | MATLAB | 5,956 | 214 | %% Cluster-based permutation test
function [Sig, p_stat] = CBP_AB_single(data, opt)
switch opt
case 'Cue'
time = 1:1:1500;
case 'Pursuit'
time = -99:500;
case 'Saccade'
time = -399:200;
case 'VS'
time = 1:size(data,2);
case 'la... |
3e38ff351efd8a4e48faafbf0b6b11fd38f9669ed84355fbbc5b3b147b6a7f3c | MATLAB | 5,957 | 223 | function outpict = rgb2lch(rgb,varargin)
% RGB2LCH(INPICT, {MODE}, {LIMIT}, {NOGC}, {WP})
% Convert an sRGB image to the cylindrical mappings of CIELUV, CIELAB, SRLAB2, OKLAB, or YPbPr
%
% INPICT is a single RGB image of any standard image class
% MODE is either 'luv' (default), 'lab', 'srlab', 'okla... |
1154cc006f424944728aa8dfe38a777744593353e6b44e0a2d0e323323255502 | MATLAB | 5,963 | 120 | %% DSCATTER() -- Dynamic scatter plot where the point details depends on zoom level.
%
% Arguments:
% px : list of x locations of points
% py : list of y locations of points
% minPixels : minimum number of pixels for the correspondingly indexed
% point re... |
f00f29ce7eed01f589bc5c02db17ba488713f2cb843ecebfa6ca8fe7f39b1a3a | MATLAB | 5,987 | 132 | function [stats] = spikeTrialDensity(cfg, SpikeTrials, force)
% SPIKERATESTATSEVENTS calculates spike statistics
%
% use as
% [stats] = spikeTrialDensity(cfg, SpikeTrials, force)
% This file is part of EpiCode, see
% http://www.github.com/stephenwhitmarsh/EpiCode for documentation and details.
%
% EpiCode is free... |
61b18dbffe669d4a6d95bfc9270e523062eadc6432af84801d86357fb9fd1dce | MATLAB | 5,994 | 116 | %% demo_005 Plotting Functions
% Here the basic plot functions which come with the toolbox are explained.
% Most of the functions return the handle of the axis they plotted in
% to enable you to plot further details and change axis properties after the plot.
% In our Wiki on Github you will find a file explaining ... |
c9de3a3687256fcdd60b5ac129875851996af8cd9fd32e4a591241676d6e2749 | MATLAB | 6,001 | 160 | % ************************************************************************
%
% Code for preprocessing EEG data
%
% Author: Eduardo Gonzalez Moreira
% email: eduardo.moreira@nki.rfmh.org
% date: 11/01/2022
%
% ************************************************************************
%% cleaning
c... |
d8a74620a50b949ed94ef82ab65acb4b907c47150facdc240ca95a63f11afc74 | MATLAB | 6,007 | 126 | function neurons_table = PET_neurons_table_timelocked(cfg, ipart, statsPSTH, spiketrials, markername, force)
fname = fullfile(cfg.tablesavedir,[cfg.prefix, 'p', num2str(ipart), '-neurons_table_timelocked_', char(markername), '.xlsx']);
if exist(fname, 'file') && force == false
fprintf('Reading %s\n', fname);
... |
423e1b0c1c004a5e460da3e621f364ee6ee71f14578c45a47923cbd3dc3bfec7 | MATLAB | 6,009 | 133 | function [SpikeRaw, SpikeTrials] = readSpykingCircus_selected_stim(cfg)
addpath /network/lustre/iss01/charpier/stephen.whitmarsh/WhitmarshEpilepsy
addpath /network/lustre/iss01/charpier/stephen.whitmarsh/fieldtrip/
ft_defaults
%% use spiking circus output
% SpikeRaw{height(cfg.markers)} = [];
SpikeTrials{height(cfg.... |
6a839955353e2060396ea8e15ac1bcc311a58f25a1ff677ffd0a89f87abd6ebc | MATLAB | 6,017 | 150 | function t = Table1(cfg, MuseStruct)
fname_in = fullfile(cfg{1}.datasavedir, 'pattern_quantifications.xlsx');
dat = readtable(fname_in);
for ipatient = 1 : size(cfg, 2)
intervals{ipatient} = inter_trial_intervals(cfg{ipatient}, MuseStruct{ipatient}, false);
end
% distance between discharges - absolute time
dat.i... |
933cc14c335291373cdf7e2a07cf0dcf4482346ca4269bf34ffc2e6f5393af59 | MATLAB | 6,020 | 148 | function T = analyze_periodicity(cfg, MuseStruct)
fname = fullfile(cfg{1}.datasavedir, 'Manual periodicity annotation.xlsx');
dat = readtable(fname);
fname_out = fullfile(cfg{1}.datasavedir, 'Periodicity.xlsx');
for ipatient = 1 : size(cfg, 2)
intervals{ipatient} = inter_trial_intervals(cfg{ipatient}, MuseStruct{... |
1d616ba1d613a4374ab20a3decbbc06131889b44bf1e4bca25e95fb6b6b8c162 | MATLAB | 6,034 | 133 | function tf=ifversion(test,Rxxxxab,Oct_flag,Oct_test,Oct_ver)
%Determine if the current version satisfies a version restriction
%
% To keep the function fast, no input checking is done. This function returns a NaN if a release
% name is used that is not in the dictionary.
%
% Syntax:
% tf=ifversion(test,Rxxxxab)... |
6cd0d17e515330aa7d5ce462aa61957560cf39a0472f48ffbde4d654ea2ca4f0 | MATLAB | 6,040 | 162 | function [ripples] = getRipples(experiment, signal, fs, freq_band, thresholds, durations, save_data, repeatCalc)
% by Mattia based on buszaki code:
% https://github.com/buzsakilab/buzcode/blob/master/detectors/detectEvents/bz_FindRipples.m
% Ripples are detected using the normalized squared signal (NSS) by
% ... |
a96b3323d8d521a556a792b6a78a937d3a2de483cec3a217f3f1f1fd847a0cd9 | MATLAB | 6,063 | 214 | function [bstats,wstats]=nt_plotxx(fname,bounds,chans,imageflag)
%nt_plotxx(fname,bounds,chans) - plot using index file
%
% fname: name of file to plot (or of its index file)
% bounds: [start,stop] (s) range to plot [default: all]
% chans: channels to plot [default: all]
%
% Data are plotted using cheap data repres... |
bccd02fe37b1599ebd58bcc0cbe727430af76dd83c889c598f6beccad575ade1 | MATLAB | 6,082 | 57 | function bytes = encode_acquisition_headers(headers)
nheaders = numel(headers.version);
bytes = zeros(340, nheaders, 'int8');
function bytes = byte_view(array)
bytes = typecast(reshape(array, 1, nheaders, []), 'int8');
end
bytes( 1: 2, :) = byte_view(headers.version);
end
functi... |
108a8e0ba5362fa76ffedf75b247007f00e304d995236046f844a1790171dda0 | MATLAB | 6,098 | 159 | function outpic = rectds(inpic,bsize,grid,Nblocks,Nframes,RGBlock,rim,outlines,mode);
% RECTDS(INPICT, BLOCKSIZE, GRID, NBLOCKS, NFRAMES, LOCKRGB, {RIM}, {OUTLINES}, {MODE})
%
% INPICT is an RGB image array (uint8)
% BLOCKSIZE is an array specifying block sizes in pixels at start and end
% [x0 y0; xf yf]
% ... |
fc511467b9dbe1eef3415bdf05a93d8fba5b2c7868e58cb9ef027fb792a515ea | MATLAB | 6,132 | 154 | function CBIG_SPGrad_generate_gradient_matrix(mesh, medial_mask, downsample, output_dir)
% CBIG_SPGrad_generate_gradient_matrix(mesh, medial_mask, downsample, output_dir)
%
% This script reads in the resting-state function connectivity gradient map stored in
% <output_dir>/gradients_edge_density.dtseries.nii, downsam... |
b727924fd716f964e40f9904bac6bae683bf14f41679dc0c14160c0f348b5a17 | MATLAB | 6,151 | 120 | function [SpikeRaw] = readSpikeRaw_SpykingCircus(cfg,force,varargin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% [SpikeRaw] = readSpikeRaw_SpykingCircus(cfg,force,varargin)
% Read results from Spyking-Circus analysis; spike-times and templates.
%
% Necessary input:
%
% cfg.prefix ... |
0d5881d4c860fe42d62019c79af2c173edcf83ab2ee4373270a584fb325fd2b5 | MATLAB | 6,163 | 154 | function cfg = gcmi_cpp_mex_config()
toolingDir = fileparts(mfilename('fullpath'));
cppMexDir = fileparts(toolingDir);
matlabDir = fileparts(cppMexDir);
repoRoot = fileparts(matlabDir);
release = version('-release');
arch = computer('arch');
matlabRootDir = matlabroot;
matlabBinDir = fullfile(matlabRootDir, 'bin', arc... |
7ed9619931d790615c307e971d808ae058b47275bd372fd14713dad2baf77f4c | MATLAB | 6,169 | 109 | function dtx_spikes_project(irat)
if ispc
addpath (genpath('\\lexport\iss01.charpier\analyses\lgi1\Git-Paul\EpiCode\development'));
addpath \\lexport\iss01.charpier\analyses\lgi1\Git-Paul\fieldtrip;
ft_defaults
addpath (genpath('\\lexport\iss01.charpier\analyses\lgi1\Git-Paul\EpiCode\shared'));
add... |
bc9998dffff4a47b9976c07a76581fb6d4cd0dd6b8df3428401677175c43888b | MATLAB | 6,170 | 151 | function [img_n] = filter_image(img, fname, results_folder, biom, kernel, colormap_biom, normalise_img, normalise_brightness);
% %% biomarker info
% [pixel_thresh,min_size,max_size,do_watershed,correct_brightness, kernel, colormap_biom] = get_biomarker_info(biom);
%% close figs
close_figs = 0;
%% Smooth image... |
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