sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
2c3891a0fb28a687b0b36cdf286e8ab14d26656e8b699848448a27c3ba9bab6b | MATLAB | 6,619 | 154 | % PLOT THETA SEQUENCE SCORES PER LAP
% MH 2020
% Load extracted averaged theta sequence scores per lap and session. Uses only unidirectional laps scores (so, merged both directions).
% Each subplot is a different quantification method, where x axis represent laps and y axis are scores
% Scores per lap are calculated us... |
3273a1d51089669cf52362f0d9e4144d81791fde971a94da94067d30e98af50b | MATLAB | 6,626 | 177 | function [roiHSV,peakParameter,peakResponse,peakParameterStd,im,totalCells,mapData,roiHSVRescaled,peakResponseLabels,peakParameterStdLabels,cellper,pixROIs,mx,cutUp,cutDown,offset,traces,onsets,offsets,responses,responsesStd,prevFrame,eventDuration,params,plotRows,transpa,mapParams,fnameOut,hIm]=MapResponses();
[filena... |
75788a198a6d71e369de563fb88d22e77d4b8677dc63bdffbf997373d8432be0 | MATLAB | 6,627 | 201 | % [succeeded,outmatname,trx] = cadabra2ctrax(featname,roiname,moviename,[outmatname],[doflipup],[dofliplr],[rot])
% inputs cadabra mat file output names, loads in the trajectories, and
% converts to ctrax trx format. these trx will be saved to the file
% outmatname (user will be prompted for this name if none given).
... |
e49d1b84eac798e844a9aba99fda1b0c25a4faf0af3ba83a935015354f0467f7 | MATLAB | 6,627 | 172 | % Generate the control and IPD models model conditions with different conditions using the
% function XomicsToMultipleModels. The current conditions are divided in 9
% groups:
%
% 1. Generic model: noLumpedRxns - wLumpedRxns
% 2. cobraSolver: gurobi - ibm_cplex
% 3. activeGenesApproach: deleteModelGenes - oneRxnP... |
6fdf4f34fd84f6576be7e3837123939980e50134ae0876bca0ad399a35b47c9e | MATLAB | 6,633 | 58 | close all
clear variables
clc
%Varun Mannam
%date: taken from 29th Sep 2019
%date: 30th May 2020
%DnCNN model with diff lr in keras
%calculate the PSNR on test-mix data raw nbn
%new result with lr=1e-3 and diff LR values and weights initalization
%new result with lr=1e-4 and diff LR values and weights initalization
%... |
954dc48ba5cbfb312d3153c6f9e9415d71aef827430c3a9647252f5f58e80ae1 | MATLAB | 6,634 | 116 | % 1. c0001_d0001__dnSamp: Import, Update Channel Information and Downsample (=256 Hz)
% FILES_SOURCE - output of dir() function in directory with files to be preprocessed
% Brain Vision Recorder data
EEG = pop_loadbv(FILES_SOURCE(ii).folder, FILES_SOURCE(ii).name);
% sample Biosig data
temp_refChan = 47; % 47 FCz
tem... |
e4281499696c55f796d30d6839fffb95406a56612caa671a55484b0bfe12d4fe | MATLAB | 6,637 | 150 | function [fNum] = plotF_df_SpacePlots(f_orcoAll,fNum,border)
alldSpk = [];allSpk = [];allRPos = [];
alldSpkSmooth = [];allSpkSmooth = [];
dF_thresh = 20;F_thresh = 15;
for g = 1:numel(f_orcoAll)
f_orco = f_orcoAll{g};
gen = f_orco.id;
hist = ceil(0.2.*f_orco.fs)-1;%200 ms history
% calcu... |
08e28f6ed92e5f48952c7e0ba69704e4bb54a9e91f5822facc183148c7aacffa | MATLAB | 6,642 | 57 | close all
clear variables
clc
%Varun Mannam
%date: taken from 29th Sep 2019
%date: 30th May 2020
%DnCNN model with diff lr in keras
%calculate the PSNR on test-mix data raw nbn
%new result with lr=1e-3 and diff LR values and weights initalization
%new result with lr=1e-4 and diff LR values and weights initalization
%... |
502ef11b7f81cca6f4315ee5d6d6ba474708f425de8f9703a5fc9dc21f9f8eea | MATLAB | 6,646 | 276 | function [ err ] = mmwrite(filename,A,comment,field,precision)
%
% Function: mmwrite(filename,A,comment,field,precision)
%
% Writes the sparse or dense matrix A to a Matrix Market (MM)
% formatted file.
%
% Required arguments:
%
% filename - destination file
%
% A - sp... |
931499a8b3e36e02f3f2f072350c596d3e1fde93775f842b32cc525ed0e8863d | MATLAB | 6,650 | 146 | % Evaluation of S-BLIF model output in respect to the neurophysiological
% data (Heffer et al., 2010) about influence of facilitation and accommodation on
% onset-spiking probability when an auditory nerve fiber is stimulated with a pulsatile
% stimulus. The details are given in Takanen and Seeber: “A Phenom... |
a69f3febf18e51e2094cf5301612fe3e80c497c10a3f01a7914bceacc02b898e | MATLAB | 6,653 | 138 | function [bestDprimeSVM,bestRR,score] = diliCCAnested(stim,eeg,nCompStimAll,nCompEEGAll,shifts,prefixTmpFile)
if ~exist('prefixTmpFile')
prefixTmpFile = '';
end
% Precalculating covariance matrices
% disp('Pre-computing covariance matrices')
% for iEEG = 1:length(nCompEEGAll)
% ... |
217e3e345ec887d9b605b94f790c881ff7dddee87ade776a739d41b4d1891d60 | MATLAB | 6,654 | 121 | %% IR94 Processing Variables
[root_dir, app_dir] = fn_get_root_dir(); ft_dir = [app_dir 'fieldtrip/'];
if isempty(strfind(path,'fieldtrip')); addpath(ft_dir); ft_defaults; end
%--------------------------------------
% Basics
%--------------------------------------
SBJ_vars.SBJ = 'IR94';
SBJ_vars.raw_file = {'IR94_erro... |
477686d8cb732e086047f4d363502cb85439d34a0e41653f07dcdc27705803d0 | MATLAB | 6,656 | 279 | function ugibb = ugibb_form(pic, varargin)
%function ugibb = ugibb_form(pic, [options])
%|
%| form a "ugibb" structure from a 2D or 3D picture,
%| of potential use for regularization with side information.
%| Specifically can be used with ASPIRE 'ugibb' regularization option.
%| See Fessler et al, IEEE Tr. Nuc. Scienc... |
d086997bcf04ffbefb5c119579ed6ce57f744fd660fa486a11cdbceacfbe095a | MATLAB | 6,656 | 174 | close all;
clear;
load('U:\rg-yoshida\Yoshida_lab_shared_folder\Shared Data\Antonio\In vivo data\Babak\preliminary analysis\Space_bin\Space_bin_filt30Kalman.mat')
load('U:\rg-yoshida\Yoshida_lab_shared_folder\Shared Data\Antonio\In vivo data\Babak\preliminary analysis\Space_bin\GLchc_epoch10.mat')
load('U:\rg... |
4a455bcbb78499d59d669c4f585c2334f7af5b5c78a14378e0d67c32f21dcb3b | MATLAB | 6,658 | 188 |
% The script plots the averaged max firing rate of each run vs the velocity
% For Time Cells and Distance Cells
close all;
clear global;
load('G:\Dropbox (Personal)\Brain\Project\Paper\DataForPaper\AnalyzedData_Onset+5sec_100msBins.mat')
Trials=[1:18];
TrialType = R(:,1); % 1-9 are fixed-Distance trials, 10... |
729e83ed99da39189ea62b64673ce85664ef47dad4f8299075a22a03764165bb | MATLAB | 6,660 | 185 | function [vertices, label, colortable] = fs_read_annotation(filename, varargin)
%
% NAME
%
% function [vertices, label, colortable] = ...
% read_annotation(filename [, verbosity])
%
% ARGUMENTS
% INPUT
% filename string name of annotation file to read
%
... |
436d0393c8de3561d4f09b6e25c371f28cf0ef002ce3ea842a4ef5b3bed0604f | MATLAB | 6,663 | 157 | %% Script to visualize searchlight analysis results
%% Load data
suggested_fname = 'searchlight_results_S*R*_gen*.mat';
title_string = 'Select searchlight results to visualize.';
disp(title_string);
[filename, filepath] = uigetfile(fullfile(get_data_path('path_type', 'output'), ...
suggested_fname), title_string);... |
4567b6d71f76a4da03eb53881477db16221af68148156fa8d8b1df7ac0987f2c | MATLAB | 6,670 | 216 | function [Acc, Y_hat, Score, Gini, features_names] = RandomForest_HER_validation(set1_avg, set1_var, set2_avg, set2_var, set3_avg, set3_var, Y_tst, time_onset, time_offset)
% This function performs a Random Forest validation classification. This
% function uses Random Forest console as implemented in:
% https://code.go... |
4a6b2ae1f63193ed1d01ee66bb36e7a8efe4f89947f0d43d4d1c767e7ca4df08 | MATLAB | 6,672 | 163 | function [] = genDataSyntheticBootCIrand(nParallel,nEXP,nBoots,nTrials,Contrasts,p)
% Generate synthetic data to investigate parametric inference in the model with respect to bootstrapping
% Must be done in parallel in order to be completed in a reasonable timespan.
%% INPUT
% nParallel - number of cores (mu... |
18ff3284a276f207d3cb3243c4aaeeb7696b70a02f50a8cb3ef2b07b807b0c3b | MATLAB | 6,674 | 150 | function [] = network_params_RMonly(binsize, maxlag)
addpath(genpath('D:\kate_dropbox\Dropbox\Rutgers\Matlab - Rutgers\Firestein Lab\BCT\'));
%parameters
totaltime = 300;
%options
raster = 0;
plotme = 0;
extracalcs = 1;
% *** change each time! *** %
% chooseData = 2; %glu injury + BDNF recovery
% *** ... |
47601c357dc87fe881ddaa0fff203db3af1182aa2ca877161ddc0a4cdc14ff7d | MATLAB | 6,676 | 177 | function [f_orco] = getLeavingBoundaryParam(f_orco,fe,plotFig)
% getLeavingBoundaryParam calculates the speed, curvature, and angle at
% which flies leave the physical arena boundary
%
% Inputs: f_orco = fly object
% fe = vector of first entry for each fly
%
% Output: f_orco = fly object updated with t... |
c3307b6de45a8af2e97e4ca8255bf136355574e4da289422fa3e09cae4b1007b | MATLAB | 6,680 | 181 | function [params] = model_parameters(need_set)
persistent params_p
if nargin < 1 || ~need_set
params = params_p;
return;
end
params = struct;
% Self-Repairing modulation of astrocyte
params.SelfRepair = 1; % Active (1), Inactive (0)
params.GluType = 2; % Type 1 Glu is... |
409ef23a724d898ef177c49bf098271752a9d7a6165ad2086a4745045055aafc | MATLAB | 6,689 | 251 | function wbdcb(src,evnt)
global nvr
%nvr.curve_handle
%
% nvr.top_thresh_handle
% nvr.bottom_thresh_handle
if strcmp(get(src,'SelectionType'),'normal')
nvr.thresh_pause =1;
yd = get(nvr.thresh_handle,'YData');
threshold=mean(yd);
xd = get(nvr.top_thresh_handle,'XData');
yd =... |
698a98aef95938e1f45441a148e924cc86c5905102b6d503abd1e959188029d7 | MATLAB | 6,704 | 247 | % combine gf & mm nn (newest)
%% gf_vs_m
clear all
close all
clc
nrmz=10000;
sp=1;
%% load mouse-new (my)
disp('mm-new')
load('/bigdata/all_mouse_dataset/loom_nn.mat','mnn_matrix','mnn_genes','mnn_region','mnn_marker','mnn_location','mnn_cl','mnn_cln','mnn_id','mnn_dev','mnn_ts','mnn_nt','mnn_t3');
m_nt=mnn_nt;
m_data... |
7af021b353f5611a6ec05cbc326f9ed7930790e9860d5b0c839968848e64def2 | MATLAB | 6,704 | 203 | function D = tnueeg_spm_eeg_spatial_confounds(S)
%TNUEEG_SPM_EEG_SPATIAL_CONFOUNDS Modified SPM function.
% This function defines spatial confounds and adds them to MEEG dataset.
% FORMAT D = spm_eeg_spatial_confounds(S)
%
% S - optional input struct
% fields of S:
% D - MEEG object or filename of M/EE... |
45136bc1b31eb2b8f7002d15da3bc761b64e58060f6dae13c50dfff87d1540fa | MATLAB | 6,706 | 197 | function [meta] = Initialize_Params(Destination_path) % clc
% clear all;
% close all;
% Dataset = 'Dataset'
% if ~exist(Dataset, 'dir')
% mkdir(Dataset);
% end
addpath(genpath([pwd '/Util']))
addpath(genpath([pwd '/Subroutines']))
addpath(genpath([pwd '/Main Analysis']))
... |
fd904842aeee5a554413c6e226a6ae36ded64facd9d0e384da926250ab31ac9c | MATLAB | 6,708 | 137 | function lap_thetaseq_shuffles(computer)
if isempty(computer)
sessions = data_folders;
elseif strcmp(computer,'GPU')
sessions = data_folders_GPU;
elseif strcmp(computer,'08')
sessions = data_folders_08;
end
session_names = fieldnames(sessions);
num_shuffles = 1000;
for p = 1 : length(session_names... |
abe5b97579e2813fc936232cc1e54364b5a921e87d6a793c4210500588e5101b | MATLAB | 6,711 | 183 | function varargout = IPEMReadSoundFile (varargin)
% Usage:
% [outSignal,outSampleFreq,outSize,outFile] = ...
% IPEMReadSoundFile(inFileName,inFilePath,inSection,inPlotFlag)
%
% Description:
% Reads (part of) a sound file into memory.
%
% Input arguments:
% inFileName = name of the sound file (with ex... |
8ddbac6b317d55b653b96b3d080feec9d5e94e9684cc373e8f8e9eef4661bc27 | MATLAB | 6,722 | 105 | % BATCH ANALYSIS FOR REPLAY CONTROL FOR 1 LAP TRACK
% MH_2020
% For 1 lap session, this code takes each lap from T1, calculate it's place fields and compares it to T2 1 LAP (e.g. ratemaps Lap 5 T1 vs Lap1 T2).
% Then it used these new place fields to decode replay events, and runs the same shuffle analysis as for norma... |
f314e147ec9da1b9c629482392a97f24c7bf732db556664a4a8eaccce1c8f3ce | MATLAB | 6,725 | 341 | function hh = cbar(varargin)
%function hh = cbar(varargin)
%|
%| colorbar with options
%| 'h' 'horiz' horizontal
%| 'v' 'vert' vertical
%| 'below' horizontal colorbar below current plot (jf)
%| 'hide' make room for it, but hide it (invisible)
%| 'fSIZE' font size
%| 1d-array ytick
%| 'notick' disable tick marks
%|
... |
6932927bb61fa2277f5ebbc304e4266c7f94d28d03a07d6d77311995d58fc94d | MATLAB | 6,733 | 185 | function [vertices, label, colortable] = Read_Brain_Annotation(filename, varargin)
%
% NAME
%
% function [vertices, label, colortable] = ...
% read_annotation(filename [, verbosity])
%
% ARGUMENTS
% INPUT
% filename string name of annotation file to read... |
8def4f1a47ed6d6c15ff58fe6f43f9e2c8da4649744077b0ccb97fd7cd5698aa | MATLAB | 6,733 | 180 | function [baseline] = getBaselineKinematics2(f_orco,border,condNdx,key)
% getBaselineKinematics2 calculates the speed, curvature, and duration of
% each state instance that occur when the fly is experiencing baseline
% firing rate. This is split between before first entry and after first
% entry.
%
% Inputs: f... |
b1889ed4bb4c260eb70249a13c58db87d34d2b1cdacdc29db0e89fbb14a8c313 | MATLAB | 6,735 | 146 | % Evaluation of S-BLIF model output in respect to the neurophysiological
% data (Hartmann and Klinke, 1990; Dynes and Delgutte, 1992; Miller et al., 2008) about
% synchronization (vector-strength) between neuron's input and spiking output
% as described in Takanen and Seeber: “A Phenomenological Model Repro... |
732a4a07be5463660910219b0c71231f68dfbbc2436ba6424be79fc9efb9b0e8 | MATLAB | 6,737 | 142 | function create_configs(varargin)
% Expects to be run in the working directory
% Remove old config files
system('rm -f config*.m');
system('rm -f yeti_config.sh');
% guarantees folders exist
system('mkdir -p job_logs');
system('mkdir -p results');
system('mkdir -p yeti_logs');
parser =... |
30bb7e19f020742ba1b385145bb7b89603ee46c813b73d8e7b5456b10ac2ab69 | MATLAB | 6,742 | 182 |
% NOTE: this script is meant to be run with the matlab GUI to make figures
clear all
% Add package to read NPY files into matlab
addpath('/Users/askeller/Documents/npy-matlab/')
%% Get predicted scores -- NULL model (ADI only)
% Load in prediction results
folder_name='/Users/askeller/Documents/Kellernet_PrelimAna... |
354b2295a2c4ac7927b9ff513cf2fbb5aae23530390d79ecd0326d975232396e | MATLAB | 6,743 | 251 |
master_startup;
saving = true;
datapath = fullfile(path.data_save,'pbupsRT/');
filenames = get_reaction_time_filenames(datapath);
[gamma, pokedR, T, RT, hits] = deal([]);
nquantiles = 6;
%% Initialize figure for plotting
fig = figure('Name', 'data'); hold on;
ax_rts = subplot(1,6,1); hold on;
ax_pc = subplot(1,... |
8cb64d71fb73cae583eb14726a1ac0693f99c4404c660bde3ab6719aa73af10b | MATLAB | 6,746 | 202 | %% Script to create output for Supp Fig. 2 - analysis of triangle lenghts
% Andrea Castegnaro, UCL, 2022 andrea.castegnaro@ucl.ac.uk
% Calculate length of outbound paths and visualize them in boxplots for
% different groups
% Preparing the data
GLAMPI_PrepareBaseConfig
% Preprocessing the data
GLAMPI_PreprocessData
... |
95bfbe3bd5a9b81b5099504cd19d65b1b397b82a61c912a87a292734892ddea0 | MATLAB | 6,750 | 237 | function pot = potential_func(type, delta, param)
%function pot = potential_func(type, delta, param)
%|
%| Define roughness penalty potential functions (using function handles).
%|
%| The penalty will have the form
%| R(x) = sum_k w_k * potential_k([Cx]_k, delta_k)
%| where w_k is provided elsewhere, not here!
%|
%| i... |
de34cfa6d2b50d2ff8e9991958ba28dbb7ce55ab268d2c3ae55320604a1e3ff7 | MATLAB | 6,753 | 221 | %| ir_mri_sensemap_admm_test
%| A test script for the toolbox version of ir_mri_sensemap_admm.
%| Note: This function is not optimized like the one in the paper
%| (uses Fatrix etc.) so the test results will not match those published.
%|
%| See M.J. Allison et al., IEEE TMI, 32(3), 556-564, Mar. 2013.
%|
%| Copyright 2... |
14fbae6faf89b5276ef370ece049d8113a707186128cfe41563da18b3b078785 | MATLAB | 6,759 | 136 |
function plots_bayesian_controls(computer)
% Load name of data folders
if strcmp(computer,'GPU')
sessions = data_folders_GPU;
session_names = fieldnames(sessions);
else
sessions = data_folders;
session_names = fieldnames(sessions);
end
for p = 1 : length(session_names)
folders = sessions.(sprint... |
fb5cbd7ea24cafa7e96d03bc14951884402f38fddb178570cb8b8bd787aacffa | MATLAB | 6,759 | 213 | %% PLV Analysis
% Compute the PLV between a seed motor electrode that explains most of the
% behavioral variance and electrodes within frontal cortex
% ##########################################################################
% Input:
% - cleaned and segmented data and HFA signal after ANOVA in order to
% quanitfy w... |
39787979488b424fa0b8b592ee0db6fe0bddd128974a1684b1b482bbf41dc9bf | MATLAB | 6,760 | 195 | % by Sathish Ramani
function [xnew, CAL, TAL, EAL, ERR] = ...
SENSERecon_ALP2(img, SP3, Data, recon_F, d, z, xnew, params)
%% Compute SER at current estimate
dispitr = params.dispitr;
dispitrnum = params.dispitrnum;
dispfig = params.dispfig;
Npix = params.Npix;
mn = params.mn;
mx = params.mx;
rs = params.rs;
cs = pa... |
b36b6f80e986f4724c84ba7a1d917b82567c63643358a6c96bba78d33499d32e | MATLAB | 6,765 | 165 | function [raftery_lewis] = rafteryLewis(runs,q,r,s)
% function raftery_lewis(runs,q,r,s)
% Computes the convergence diagnostics of Raftery and Lewis (1992), i.e. the
% number of draws needed in MCMC to estimate the posterior cdf of the q-quantile
% within an accuracy r with probability s
%
% Inputs:
% - draws [n_dra... |
5909aec9e4e18e0f65daccb18e47f55ec0ae3ddf5fe2fa46aac8523f7d7e0c0d | MATLAB | 6,771 | 216 | function [smap, sinit] = ir_mri_sensemap_admm_3D_linear(ykj, varargin)
%function [smap, sinit] = ir_mri_sensemap_admm_3D_linear(ykj, [options])
%|
%| Regularized estimation of sensitivity maps for parallel MRI
%| using augmented Lagrangian methods with variable splitting.
%| See M.J. Allison et al., IEEE TMI, 32(3), 5... |
ce921ba8722b2dccab8ac7fd6ce5cc1498e593b977fd7b571f4f8edf33d58f07 | MATLAB | 6,774 | 140 | function [] = agentModelHandle(genAll,meta,agentModelMeta,generateFlies)
delay = agentModelMeta.delay;
dur = agentModelMeta.dur;
for g = 1:numel(genAll)
gen = genAll{g};
for ii = 1:numel(dur)
for jj = 1:numel(delay)
currDur = dur(ii);
currDelay = delay(jj);
cond = ... |
06247d3c8fd49eadee763e7a24a0baf5eca32a9a246036dbe3efe9839aea4090 | MATLAB | 6,779 | 163 | function SBJ08b_HFA_plot_crRT_nANOVA_single(SBJ, elec_lab, an_id, stat_id, plt_id, save_fig, fig_vis, fig_ftype)
% Plots ANOVA results
% clear all; %close all;
% fig_filetype = 'png';
if ischar(save_fig); save_fig = str2num(save_fig); end
%% Data Preparation
% Set up paths
if exist('/home/knight/hoycw/','dir');root_di... |
df19f9c768cfdb86f1c3fed4008f0f65ab082e25ba4413c6fb6e2def16333536 | MATLAB | 6,779 | 189 | function [str, sts] = gencode_rvalue(item, cflag)
% GENCODE_RVALUE Code for right hand side of MATLAB assignment
% Generate the right hand side for a valid MATLAB variable
% assignment. This function is a helper to GENCODE, but can be used on
% its own to generate code for the following types of variables:
% * scalar... |
3eb9496c5ff78e22b1a0eea07410e99f68f020ccd1ebad6cfaae327d0ee624aa | MATLAB | 6,784 | 197 | function [Old_audio_buffer,Old_spikes_buff ]=draw_spikes(chans,thresh,pre_sipke,post_spike,seg_spikes,seg_spikes1,pre_seg,sr,AD_step,debug_flag1,OldEEG,Speaker,src1,Old_audio_buffer,Old_spikes_buff)
% draw_spikes(chans,pre_sipke,post_spike,seg_spikes,pre_seg,sr,AD_step,debug_flag1);
global nvr
figure(100... |
61d7757eda69bc86e44739d1d4b36c9fb26eff94db651ab6cd442e40f2fca519 | MATLAB | 6,787 | 290 | function coef = bspline_1d_coef(fn, varargin)
%function coef = bspline_1d_coef(fn, varargin)
%|
%| Given f[n], uniformly spaced samples of a 1D signal f(t),
%| compute the bspline coefficients so that the following model interpolates:
%| f(t) = \sum_{k=0}^{N-1} coef[k] b(t - k)
%|
%| in
%| fn [N (L)] 1d signal(s) of ... |
8f08968558d18ce855dd9a175fbc7663115c9eb3c26e487ef7a71ad1f16d6dae | MATLAB | 6,793 | 241 | function img = feldkamp(proj, window, mask, args, varargin)
%function img = feldkamp(proj, window, mask, args, [options])
%
% FBP reconstruction of cone-beam tomography data collected with
% a circular source trajectory.
% See feldkamp_example.m for example.
%
% in:
% proj [nh,nv,na] cone-beam projectons (line integ... |
e7ad422ec45410e2c88c16e68c1cc794ba97da0edcf2e979905188fb38dd4943 | MATLAB | 6,799 | 289 | % qpwls_sps_example.m
%
% Complete example m-file illustrating QPWLS-SPS algorithm and its relatives.
%
% Copyright 1999-4, Jeff Fessler, The University of Michigan
%
% generate data
%
if ~isvar('yi'), disp 'setup qpwls_sps_example'
em_wls_test_setup
% wi = ones(size(wi)); warning 'uniform wi' % test circulant precon... |
bde6303c5ac01d1e403bf0a62767181a9e5fa22826f4bc5c2a6fd69b7720b9c9 | MATLAB | 6,804 | 157 | function [slope,pearson_rho] = findAttractorDynamics_figure(cells,save_figs,sf)
% A functioning attractor network should preserve correlations between
% pairs of cells.
% E.g. So pairs of cells that are well correlated in trial 1 through 25
% should also be well correlated in trials 26 through 50
slope = nan;
pearson... |
996c1507e5d990908f618e1c06f10dafc6577b94b890bf97c028683ca360cdb8 | MATLAB | 6,805 | 142 | function [negLogLik prWord_log] = hills2015_model_decay_softmax_hybrid_concat_wordECDF(best_params, obs);
% SOFTMAX local search model (allows saliencies <= 0)
% but allowing arbitration between lexical and semantic similarity in the 'activation' calculation
% _concat version takes in the concatenated [LETTER, CATEGORY... |
ec139f3af8f709671776caa8ce884781c3498267298ada39fecba8a021f66181 | MATLAB | 6,806 | 258 | function st = nufft1_build(J, varargin)
%function st = nufft1_build(J, [option])
%| Build 1D LS-NUFFT interpolation coefficients by brute force.
%|
%| in
%| J neighborhood size: [-J/2,J/2]
%| option
%| om [M 1] frequency locations, if not provided build fine table
%| N # of signal values (default: 2^8)
%| K # of DF... |
06a796379aaba655bb0e108de3c8b453f98ecd923160d53676b91cbf81b2f4f4 | MATLAB | 6,808 | 195 | %% Script to create output for Supp Fig. 2 - analysis of time for completing outbound duration
% Andrea Castegnaro, UCL, 2022 andrea.castegnaro@ucl.ac.uk
% Display outbound path duration for different groups.
% Calculate difference between group means. For details of how duration has
% been calculated please refer to C... |
0b801f9bf39ee20866ba076a72267e47f908009689b8cb655164def3acfa77b0 | MATLAB | 6,808 | 267 | function h = c_subplot(varargin)
% c_subplot - wrapper around subplot() with added features
% Beyond normal subplot features and alternate input formats, adds a right-click context menu
% option to "pop out" specific subplots into their own figure.
%
% Input can be:
% c_subplot(numRows, numColumns, row, column)
% or
... |
27afc23bcefec0d759d84736d2f5efafe8c05b818a26271832b0ab6116626b7e | MATLAB | 6,815 | 104 | % AVERAGE THETA SEQUENCE PER LAP SIGNIFICANCE
%MH 2020
% Compares average theta sequence scores to shuffles. Takes the 95% for each shuffle (pre spike train circ shuffle, position circ shuffle & time
% bin suffle), and takes the maximum value between the three of them. A theta sequence will be significant if it's highe... |
04b00c6efd9e9f64ad22a716a9a064ba178411bb3d840f2ba3fca19a4b88952c | MATLAB | 6,824 | 193 | function [CVA] = spm_cva(Y,X,X0,c,U)
% Canonical Variate Analysis
% FORMAT [CVA] = spm_cva(Y,X,X0,c,[U])
% Y - data
% X - design
% X0 - null space
% c - contrast weights
% U - dimension reduction (projection matrix)
%
%
% CVA.c - contrast weights
% CVA.X ... |
bd8759341831afb1a865067fe0a4fd872e8221854ecb6e1b1ce4ab9f98bdf17c | MATLAB | 6,828 | 238 | function spm_DEM_qU(qU,pU)
% displays conditional estimates of states (qU)
% FORMAT spm_DEM_qU(qU,pU);
%
% qU.v{i} - causal states (V{1} = y = predicted response)
% qU.x{i} - hidden states
% qU.e{i} - prediction error
% qU.C{N} - conditional covariance - [causal states] for N samples
% qU.S{N} - conditio... |
1ec9f4a0e464f94dfe661077feecb7b0f28b3b4c46ac13d2873ff6ea78063968 | MATLAB | 6,831 | 216 | clc;clear;close all;
root='..\';
addpath(genpath([root,'NeuralCorrelateEvidenceAcc']))
%% settings --------------------------------------------------------------
subdir='total';
clusterName='clusterArea_paper';
regCluster=1;
if(regCluster)
subdir=[subdir,'_',clusterName];
end
type='evidence';% cp,dp,evidence
all_u... |
5da6d0ecec34270a2f339c813ed820259e6292b530e78982501e55d897ba7c16 | MATLAB | 6,838 | 186 | function[]=BaSiC_shading_and_ref_stitch(id,P2path, datapath, ntiles, depth, thickness,stitch, aip_threshold, Xoverlap, Yoverlap)
% add path of functions
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addpath('/projectnb/npbssmic/s/Matlab_code/PSOC... |
9e26d03628cf643d9624f2d670a0f38f9a974e107e68704cb78cfee6821e3573 | MATLAB | 6,850 | 195 |
function rezToPhy(rez, savePath)
% pull out results from kilosort's rez to either return to workspace or to
% save in the appropriate format for the phy GUI to run on. If you provide
% a savePath it should be a folder, and you will need to have npy-matlab
% available (https://github.com/kwikteam/npy-matlab)
% spikeT... |
71bb05f2f67b3cb8196b618b6143ee28933a0843fe71469b5b3ff55a82749121 | MATLAB | 6,851 | 201 | function [f_orco] = getTransitionRate2(f_orco,plotFig)
n = -5;%-2
deltaf = 1;
deltaDf = 0.1;
dSpk = f_orco.calcDeltaFR;
% xGrid = [0:deltaf:50];
% yGrid = [-5:deltaDf:5];
xGrid = (-5:deltaDf:5).*f_orco.fs;
yGrid = 0:deltaf:50;
[XX,YY] = meshgrid(xGrid,yGrid);
f = [-deltaf./2:deltaf:50+deltaf./2];
df = ... |
08e79521ee197c764acbba8f3fa6d0f2c65906ad64bc0893cb90edc6a571b4c8 | MATLAB | 6,852 | 241 | %Code for obtaining myonuclei and myocyte counts and density from
%myogenin and DAPI nuclei staining.
%Includes estimate of cell width
clearvars -except MCmean0
%input image variables
prompt = {'Pixel width (microns):','Day:','Position:','Enhancement factor:','image length:','Dilation factor:','% Myogenin threshol... |
b6346a5feece60a1da6b39300191cc508aeea4a8f2d33ed5ad6c01be94f7192e | MATLAB | 6,853 | 155 |
% This operator is only used for FAE calculation and not for the smoothing
% of T2 distributions
function Dstr = getSpatialDerivOperator3D_wt_MaskingGeneral(Filter, Sz, Mask_ROI, Resol)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% input: 3-D size of T2_Scale spectrum - nrows x ... |
54473d4c71011a5f5206639a723c7cbb5d6598bfb5dd783bf5491a5ec1ba568c | MATLAB | 6,855 | 181 | % function MAP_fig_1_multi(mname,config)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% ################################################################# %% DESCRIPTION
% Script to analyse data for:
% Grieves et al. (2020)
% Quantification of firing rate map procedures
%
% This script
% NO... |
06bb29d77a18874c4ade72c46d5635184e7a75396a1db5e927e85dc37429fa0c | MATLAB | 6,861 | 181 | %% Plot Figure g and h
%% Define Paths of Loading Files and Save Files
currentFolder = mfilename('fullpath'); % determine the filepath based on where the script locates
scriptFN = mfilename;
filePath = erase(erase(currentFolder, scriptFN), strcat('scripts', filesep));
searchPath = strcat(filePath, 'data', filesep, 'Fi... |
52e0b645fb4ac4a322c274ee6efbc7f74a8d83cb672399e6ec711fe0f1b055ac | MATLAB | 6,868 | 207 | %%load data
dataset = load('/Users/KeiMasuda/Desktop/fkm_analysis/AA_190830_1_0927_baseline+ketamine.mat');
% dataset = load('/Users/KeiMasuda/Desktop/fkm_analysis/AA_190709_2_0812_baseline+ketamine.mat');
% dataset = load('/Users/KeiMasuda/Desktop/fkm_analysis/AA_190709_4_RSC_baseline+ketamine.mat');
%% compute metric... |
2023d3b3db02c1fea3b969822f096cb640cb87f05b44b55ca938cd5e4420a871 | MATLAB | 6,870 | 189 | function SBJ08c_HFA_grp_errbar_ROI_nANOVA(SBJs,stat_id,proc_id,an_id,atlas_id,roi_id,...
plot_scat,save_fig,fig_vis,fig_ftype)
% Load HFA analysis results for active, RT correlation, and ANOVA epochs
% RT correlation: any significance in stat_lim
% ANOVA factors: any signif... |
14082fa86d74d2e1555381a73762655ebf293cc4d73ddd3d56c3f908fdf7dbb9 | MATLAB | 6,877 | 256 | % Make NIfTI structure specified by an N-D matrix. Usually, N is 3 for
% 3D matrix [x y z], or 4 for 4D matrix with time series [x y z t].
% Optional parameters can also be included, such as: voxel_size,
% origin, datatype, and description.
%
% Once the NIfTI structure is made, it can be saved into NIfTI fil... |
1e9e898780a86e9706195cf8e3863548b9e54c8d72054ceec589edb47cc0351d | MATLAB | 6,880 | 197 | function [signal, accept, typeeeg, rt, response, chan_names, pnts, nsweeps, rate, xmin, xmax]=loadeeg( FILENAME, chanlist, TrialList, typerange, acceptype, rtrange, responsetype)
% usage [signal, accept, typeeeg, rt, response, chan_names, pnts, nsweeps, rate, xmin, xmax]=loadeeg( FILENAME, chanlist, TrialList, typeran... |
cd68d9bd8c7c3fb57dc073034c37e84915106643a95e3005552ca4b4e4f69e4b | MATLAB | 6,880 | 215 | clear all
close all
dbeh_path='C:\Users\xscogno\MATLAB\Flavio2\Waves\Tracking data\';
rec_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_spikes='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_sorting='C:\Users\xscogno\MATLAB\Flavio2\Waves\Sorting\';
dpath='C:\Users\xscogno\MATLAB\F... |
62161d6211a853e3f59643ec1db88125f0a2898a513f30ff94d843949f92bdde | MATLAB | 6,884 | 155 | function dth_pseudotrials_SVM_full_experiment_cross_validated(subject,task)
%DTH_PSEUDOTRIALS_SVM_FULL_EXPERIMENT_CROSS_VALIDATED Performs the distance-to-hyperplane analysis using SVM on
%a balanced dataset. Instead of creating pseudoconditions out of scenes,
%the trials from across conditions are lumped into pseudotr... |
eaf17fab371827f72ee212d8236fc60c802c15b0a60f315567363a6db54be92a | MATLAB | 6,885 | 145 | %{
HOW TO USE THIS TEMPLATE
Edit only the three ZONE blocks below:
ZONE 1 set numVar, your parameter labels, and optional default values
ZONE 2 unpack your parameters from UserVar
ZONE 3 write your detection method and fill the outputs
Everything else is handled for you by createPluginFigure.
Opti... |
a2b7ed1b540019a52bbfb436d0ae54785cb6a2e1f1c58080de45699067b6763e | MATLAB | 6,886 | 191 | function paths_added = DEV_INITIALIZE(varargin)
% SYNTAX: paths_added = DEV_INITIALIZE(varargin)
%
% METHOD: This script is used for project management in matlab. It is
% placed in the base folder of a matlab project and when executed will
% initialize it for development.
%
% Initialization Step include:
% 1. Reset... |
bf7f5ed1b1aaec78a23d96a9a95d259bed98e2484dac0edb3bd6e98b01c4acbc | MATLAB | 6,888 | 180 | %aim to calculate the latency of the response, find the time and CI, and
%the bootstrap
% close all;
clearvars;
addpath ('/data/local/u0114568/ephysio/test');
listname=['targetRight'];
cn1={'sp','color', 'con', 'incon', 'att', 'congruency','fac','int'}; % condition names length=8
cn={ [cn1{1}],[cn1{2}]};
condnames=li... |
0a587577d1ea75dbb47d23886bfd673b1ec8873d3e2ad2630ae0940d63ef2f5b | MATLAB | 6,891 | 228 | clear all;
FileNum = 2:10;
zf_true0 = (0:50:490);
zf_true = zf_true0(FileNum-1);
load('/space/vault/3/users/Hui/ThorlabsCalibration_101416/sensitivity_10x/rolloff');
Rolloff = (rolloff); % 1.1; 1.1; 1.1; 0.95; 0.9;
SubPath = 'Dil5/';
FileMus = 2;
zoff1 = 30;
for ii = 1:length(FileNum)
load(strcat([SubPath 'dBI_... |
9ae69a20779222083a43d193f032313035149c31107a5e3a55be8dbac7d4bcfc | MATLAB | 6,892 | 165 | function trial = getBasicInformation
% Returns a struct with basic information about the experimental
% computer, the user, the date and time when the experiment was
% started, and the software versions in use. Pass this struct into your
% saved result so that the recording is self-documenting -- months or
% years late... |
7c6198fbad8d556feaf6ac340f1b250d0f4b88369c7c00c526c801f63af3ce52 | MATLAB | 6,897 | 213 | function varargout = spm_colourmap(varargin)
% Colourmap multi-function
% FORMAT map = spm_colourmap
% Return the colourmap of the current figure as a three-column matrix of
% RGB triplets (between 0.0 and 1.0).
%
% FORMAT [map =] spm_colourmap(map)
% Define a colourmap or set it to the current figure.
% map - ... |
a7037a6bc31f8c73e576d18ad26c7046984dfd3286790cb27e5be9e0291dc948 | MATLAB | 6,903 | 149 | function loop_str = fun_analysis_get_loops_in_graph_by_link_label(graph_str, link_label, distance_type)
% fun_analysis_get_loops_in_graph finds loops for the specified link in the
% graph and compute loop length
% Input:
% graph_str: structure generated by fun_analysis_get_connectivity_graph
% link_label: numerica... |
3aadd8e35b50d2d179376fa6a887c6b92af59db664103eeed57925584ced3c83 | MATLAB | 6,911 | 193 | %% Load simulation results
subjects = {''};
results_folder = fullfile('simulations_FC6_TP8-P8_FC5_TP7-P7', 'fsavg_overlays');
fsavg_msh_name = '_TDCS_1_scalar_fsavg.msh';
field_name = 'E_normal';
fields = {};
for i = 1:length(subjects)
sub = subjects{i};
% load mesh with results transformed to fsaverage space
... |
ae5cb85bcab2efa9c4bf5d9c5e0149b8a49e6f7d83a0c5bc3ff208b3142fdd4b | MATLAB | 6,912 | 159 | function [TPP, half_laps_times] = phase_precession_absolute_location
load('extracted_CSC.mat')
load('extracted_place_fields.mat')
load('extracted_clusters.mat')
load('extracted_position.mat')
load('extracted_laps.mat')
%Get timestamps for each half lap
half_laps_times = extract_running_laps(position,lap_times);
... |
7ff577adc7390154012baca87a36edd23e8e213030bbe9ec90a6421ac2353223 | MATLAB | 6,915 | 286 | function varargout=notBoxPlot(y,x,jitter,style)
% notBoxPlot - Doesn't plot box plots!
%
% function notBoxPlot(y,x,jitter,style)
%
%
% Purpose
% An alternative to a box plot, where the focus is on showing raw
% data. Plots columns of y as different groups located at points
% along the x axis defined by the optional vec... |
e0009de6623b62e6057f8fa2ac4d2098954382d196571f830c8c6e93ae63e0f6 | MATLAB | 6,920 | 166 | %% PC1 - test in subsample A (Discovery)
clear all
% note: the coefs matrix is 1010004 (weights at each of 59,412 vertices for each of 17 networks)
coefs = load('/Users/askeller/Documents/Kellernet_PrelimAnalysis/RidgeResults/results_matchedsamples_081822/all_network/thompson_PC1_coefs_testA.mat');
coefs = coefs.PC1_... |
fd9e3a9c79d2fd31d8319c1c0048d79d7169275a5ef3bab7167082e2caabcf01 | MATLAB | 6,921 | 214 | % input-outptu TF: cortex-HC
clear all; close all;clc
subj = '39'
% load data
cd ( ['/media/SSanDra/Pattern_Separation/subj_' subj ])
load(['behavior_subj' subj '.mat'])
load(['trial_data_subj_onset_' subj '_select_chan_3.mat'])
load(['baseline_info_wavelet_32num_20logdb_3hz_350hz_notched_artifact_reject_subj_' subj '... |
5198533f118e2b94bdb7f38fde50238d6aad3785cd6bf352b5f2580045d2d77a | MATLAB | 6,932 | 224 | function spm_plot_ci(E,C,x,j,s)
% Plot mean and conditional confidence intervals
% FORMAT spm_plot_ci(E,C,x,j,s)
% E - expectation (structure or array)
% C - variance or covariance (structure or array)
% x - domain
% j - rows of E to plot
% s - string to specify plot type:e.g. '--r' or 'exp'
%
% If E is a row vector wi... |
fe7aedc2b244e3918265910eb7783b5a934c02d335fa58116addafc41ffe53df | MATLAB | 6,940 | 262 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%
%% 4-level multiresulution nonrigid image registration with Jacobian penalty
%% Conjugate gradient with Newton's first step was used
%% Cubic B-spline bases are used for both image and deformation models
%%
%% Copyright April 2008, ... |
ebe0ed20361f4d066741c7a6c0e519c4b3c6ee9bc9f2eebd860ff498436457b1 | MATLAB | 6,942 | 241 | %Code for obtaining myonuclei and myocyte counts and density from
%myogenin and DAPI nuclei staining.
%Includes estimate of cell width
clearvars -except MCmean0
%input image variables
prompt = {'Pixel width (microns):','Day:','Position:','Enhancement factor:','image length:','Dilation factor:','% Pericentrin thres... |
7b7f2f0e7a2fa3b7c2ea8a9508de2f4004d8aad390e0ecbd97952790123a62c2 | MATLAB | 6,947 | 197 | %% Check which root directory
if exist('/home/knight/hoycw/','dir');root_dir='/home/knight/hoycw/';ft_dir=[root_dir 'Apps/fieldtrip/'];
else root_dir='/Volumes/hoycw_clust/';ft_dir='/Users/colinhoy/Code/Apps/fieldtrip/';end
%% Set Up Directories
addpath([root_dir 'PRJ_Error/scripts/']);
addpath([root_dir 'PRJ_Error/sc... |
61cf1270b280bbd6400ab31e09369c2af0ba5ad69279dc7debd42d06b25f9954 | MATLAB | 6,951 | 146 | %{
OnOffsetDetectionPluginExample - simple example script to show users how to make onset/offset detection plugins
HOW TO USE THIS TEMPLATE
Edit only the three ZONE blocks below:
ZONE 1 set numVar, your parameter labels, and optional default values
ZONE 2 unpack your parameters from UserVar
ZONE 3 wri... |
485d6a9c07faee8cb5da088ed1adc87448d4c803089c4b37202a79be9bbf5c59 | MATLAB | 6,958 | 274 | function [vol, M, mr_parms, volsz] = load_mgh(fname,slices,frames,headeronly)
% [vol, M, mr_parms, volsz] = load_mgh(fname,<slices>,<frames>,<headeronly>)
%
% fname - path of the mgh file
%
% slices - list of one-based slice numbers to load. All
% slices are loaded if slices is not specified, or
% if slices is emp... |
3a2f58a408ba5d1d038a61ec294d8cd5b4ad97c9d3990ce1dd48854aa904a00b | MATLAB | 6,959 | 171 | function [outChords,outToneCenters,outContextuality1,outContextuality2,outContextuality3] = IPEMContextualityIndex(varargin)
% Usage:
% [outChords,outToneCenters,...
% outContextuality1,outContextuality2,outContextuality3] = ...
% IPEMContextualityIndex(inPeriodicityPitch,inSampleFreq,inPeriods,...
% ... |
c2e10968ef59dfda2c66b8bb9bf38fb8d72c6ac99191d7d8f4871f4cf9507908 | MATLAB | 6,959 | 267 | function [xs, info] = ir_pwls_os_rlalm(x, Ab, yi, R, varargin)
%function [xs, info] = ir_pwls_os_rlalm(x, Ab, yi, R, [options])
%|
%| penalized weighted least squares estimation / image reconstruction
%| using relaxed linearized augmented lagrangian method with
%| (optionally relaxed) ordered subsets. (relaxed OS-LALM... |
90d14f3892958db53c6d11ac1801691fe51e084e3fb1838cbf0f987b5c7a1d13 | MATLAB | 6,960 | 140 | function [OFC_chan_idx,fro_chan_idx,temp_chan_idx,insula_chan_idx,cingulate_chan_idx,...
ACC_chan_idx,EC_chan_idx, HC_chan_idx ,CA3_chan_idx,CA1_chan_idx, MTL_chan_idx, NC_chan_idx] = get_elecs_clean(subj)
% will provide chan indices for each subj
if strcmp('39', subj)
OFC_chan_idx = [1:2, 58:59];
fr... |
444827cb844679c7e37a87df57fe0a6332a860edd3ed65d8dbf0d95b06471a7b | MATLAB | 6,961 | 276 | function [T, reuse] = nufft_gram(ob, W, reuse)
%function [T, reuse] = nufft_gram(ob, W, reuse)
% construct Toeplitz matrix object T = G'WG for a Gnufft object
% in
% ob Fatrix a [M,np] Gnufft object
% W [M,M] W = diag_sp(wi) (often simply "1" or [])
% reuse struct stuff from the last call that can be reused
% out
%... |
899d4ea7e0378cc1065799a9e1b4ee771861f0cfdcefbaccef96a96882177da9 | MATLAB | 6,964 | 207 | function varargout=shadedErrorBar(x,y,errBar,varargin)
% generate continuous error bar area around a line plot
%
% function H=shadedErrorBar(x,y,errBar, ...)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
%
% Inputs (required)
% x - vec... |
2e63c1539ad5a810b54effa735d5dff0fa0a6e860537a160bfb6b2d8a9834c25 | MATLAB | 6,967 | 189 | clc; clear;
addpath('/data/hu_esraal/Documents/eeglab2019_0/')
addpath('/data/pt_02333/esra_codes/')
eeglab
%%
eegfolder= '/data/p_02186/TMS_ECG2/analyses/EEGsham/merge/'; cd(eegfolder);
save2folder= '/data/p_02186/TMS_ECG2/analyses/EEGsham/merge/reref/cardiacphase_fakecorr/'; mkdir(save2folder); cd(save2folder);
subj... |
226d8d636537dd1dd92b4e5bfc8858299f6fe217a6f2e3ca02b64658dc7c8913 | MATLAB | 6,976 | 148 | % do mixed effect analysis on degree centrality on sad vs. rum, as the
% reviewer suggested
%
%
% Xiao Chen 230228
% chenxiaophd@gmail.com
%% initialization
clear; clc;
work_dir = 'working directory';
data_dir = 'DPABISurf Preprocessing Files';
TemplateDir = 'DPABISurf surf template directory';
load([work_dir, '/sub... |
d3afdea72e0a75f6fc9e57930cd08e8ac9996b6538fa8dee0c271cf448c43a37 | MATLAB | 6,984 | 164 | function SBJ09a_TFR_stats(SBJ,conditions,proc_id,an_id)
% Calculates time frequency representation and saves the results
% INPUTS:
% SBJ [str] - dataset to be processed
% proc_id [str] - which processed data pipeline to get the data
% an_id [str] - which analysis variables to use
%% Check which root directory
if... |
118ccf788c2348f121cbcbc7a0df54abbade74a3cf338e6904d2020146bd0945 | MATLAB | 6,985 | 165 | %% Set variables for saved design info & target directory (to save .txt files)
% This script assumes that in your GA output your trait-categories rotate
% first, and then the prompt types. E.g., with 3 trait-categories and Self
% and change prompts, we'd get conditions 1 2 3 for self, and 4 5 6 for
% change.
pathtofile... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.