sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
a671fc3587fa5ad730b0273e647129035475af993da5bc6eeb3d0a6aa9c73b7c | MATLAB | 4,763 | 168 |
function pp_prepare_format(BLOCKS,subject,session_label,ConditionFolder,behavior,Path,savedir,time)
%
% pp_prepare_format( BLOCKS, subject, session_label )
% Creates data structures in the desired format for processing. Groups
% together sequentially-recorded blocks, indicated in input argument,
% and make... |
e549b65747ffbce1c27623a62130b6c47a62cb166f7f607745bb64b472b389af | MATLAB | 4,768 | 129 | function [ Faces ] = BuildFacesForSubdividedTriangle( VO, VA, VB, iAddedVerts, OverlappingVerts, InternalVerts)
%BuildFacesForSubdividedTriangle VO, VA, VB defines a triangle which has
%had a line drawn through the interior.
%iAddedVerts contains a sorted list of all indicies that lie on the line
%through the triangl... |
e340ac20126d14781244558f5e6153ca47b1f92d83bcb7a49db81a11925c9632 | MATLAB | 4,773 | 119 | function [fcoefs,cf]=MakeERBFilters2(fs,numChannels,lowFreq)
% function [fcoefs]=MakeERBFilters(fs,numChannels,lowFreq)
% This function computes the filter coefficients for a bank of
% Gammatone filters. These filters were defined by Patterson and
% Holdworth for simulating the cochlea.
%
% The result is returned... |
dd52d74d7c343800a3af8c199ebe11d29c3028d30394086dbfe0ce6b75dbbffd | MATLAB | 4,776 | 151 | function [vx,vy,vfs,wvcfs] = optical_flow_model_gp_surrogate(data,fmin,fmax)
% Sampling frequency (in Hz)
Fs = 100;
% Scale by which to downsample spatially
mouseResize = 1;
% Flag to use mask located in meta.traceMask
useMask = 0;
% Spatial selection of recording to keep (set to empty or zero to use full
% recording... |
1932d5d2c886f2f8dd03f5bdf4153edbe3cdab838db74dd9a3965ea6789bda22 | MATLAB | 4,777 | 208 | % Generate a Dynamic Moving Ripple
%
% SSDMR(t,Xk) = P.M/2 * sin[2 * pi * Omega(t) * Xk + Phi(t)]
% P.M = modulation depth (dB)
% Xk = log2(fk/f1) octave frequency axis relative to f1
% Phi(t) = integral 0-t Fm(tau)d(tau) controls time-varying temporal
% modulation rate Fm(t)
% Spectral [Omega(t)] and temporal [Fm(t)] ... |
125b4e8339c56e52f6c42149cfeb57020c45547f6784491c564b7bacf1f073a0 | MATLAB | 4,782 | 158 | function [stats,st] = lme_fit_NR(X,Zcols,y,ni,e)
% [stats,st] = lme_fit_NR(X,Zcols,y,ni,e)
%
% Linear mixed-effects estimation by Newton-Raphson optimization.
%
% Input
% X: Ordered design Matrix (according to time for each subject).
% Zcols: Vector with the indices of the colums of X that will be considered
% as rando... |
8af8a96f57d3c79e212fcfcca95fe1e52b8bdfa51d5394d3f162ab4c38fe34c1 | MATLAB | 4,785 | 180 | function varargout = BasicClassifier(D,nReps,par)
% R = BasicClassifier(D)
% R = BasicClassifier(D,nReps)
% R = BasicClassifier(D,nReps,par)
% [R,Rshuff] = BasicClassifier(D,...)
%
% D is an MxN data matrix with M observations in N
% categories.
%
% Optionally, the number of repetitions can be specified by the second
%... |
91ebb49dc33e31e56afe65f89ef7f066ec777095cd1459dca73961020d72b81d | MATLAB | 4,788 | 125 | % A tensor component-wise rescaling Metropolis-Hastings step.
% Useful for slighlty faster HMC mixing - plain HMC doesn't force any components to be normalized/orthogonal and this explores the scaling dimension faster.
% Important: This step assumes that the prior distributions are normal with mean 0!
function [params,... |
4e295b01581a4ee56fc69c089d8b2be895d7b8fa5cad15c6ca8635140fbb2e89 | MATLAB | 4,790 | 134 | %% Setup
util.clearAll;
cur_save_dir = fullfile(util.get_paths().figs,'ANOVA_correlations');
util.mkdir(cur_save_dir)
c = util.plot.getColors();
%% Anova analysis for the pairwise region correlations
beta_tables_taste = util.load.all_taste_betas();
taste_names = beta_tables_taste.sep_table.Properties.VariableNames;
%... |
09a43d4831fcdd9f024f04543a4766574adb4ee87821b92ae38585da28002843 | MATLAB | 4,791 | 129 | function Xhat = decodeCrossValidation(cfg0, X, Y)
% [Xhat] = decodeCrossValidation(cfg, X, Y)
% Implements k-fold cross-validation, in which a subset of trials is left out
% in each iteration as testing data, while training on the remaining trials.
%
% cfg Configuration struct that can possess the foll... |
19f52f401532416470b3fc876df360449a4083ce450a59b0725fda885d1e2302 | MATLAB | 4,791 | 73 | function AnalParams=GetAnalParams(AnalType)
% Retrieves parameters specific to each analysis type.
%
% INPUTS:
% - AnalType: string label of the analysis to be conducted.
% OUTPUTS:
% - AnalParams: structure of analysis parameters.
%
% Default analysis settings are set for a standard 'Full' analysis o... |
3675f0908934aee3ec7ad32233fc04e721dbd5f47801932fcbe88e419f78a092 | MATLAB | 4,792 | 118 | % clc; clear; close
function [Partial_coef, Yhat, pval] = MR_Heading(Y,X,selvar)
% y = b1x1 + b2x2 + b3x3 + b4x4 + b5
% let's take data stored in matlab exemples
% load hald;
% Y=hald(:,5) ;
% X=hald(:,1:4);
X(:,[1,selvar]) = X(:,[selvar,1]);
% get a solution,
X = [X ones(length(X),1)];
B = inv(X'*X)*X'*Y; % ... |
0415760bff8dce845c56dd8fccb4a29806fe4ffbf03e72b7900733b0e9589fcd | MATLAB | 4,801 | 92 | %--------------------------------------------------------------------------
function [val, formulaArray]= f_testsyntaxtype(FormulaArrayIn, whocall)
val = 1;
formulaArray = FormulaArrayIn;
if isempty(formulaArray)
return
else
formulaArray = strtrim(cellstr(formulaArray));
end
nformulas = length(formulaA... |
a4b4b2afa60d849198ea59bd6a585fa2b84651b62822271db18eb156a5de12ed | MATLAB | 4,801 | 143 | function [qe,Ee,Se,Sev] = qeq4e(En,Ge,Ue,Sn,Set,Xe)
%***************************************************
% QeQ4E:
% Evaluates the stress and strain for the current
% displacements. Creates the element internal
% force vector for elastic quadrilateral 4-node
% element in plane stress or plane strain.
% If Xe c... |
ef0cc814adc8f3868866e665d067f5cac5c36dc44506637c1ef01559ece0802e | MATLAB | 4,804 | 162 | clc;clear;close all;
Fig9a = figure();
N_mu=50; %There are \mu independent embedded patterns, 500 simulations (number of simulations)
%R1: with pre-synaptic competition
%R(1,1): 4 post-synaptic neurons
%R(1,2): 5 post-synaptic neurons
%R(1,3): 6 post-synaptic neurons
%R(1,4): 7 post-synaptic neurons
R1=z... |
175c2517d114c94cd8254b9eb9e18971d22c6241bd40f54b792e622499cd8e24 | MATLAB | 4,811 | 147 | function [checks,varargout] = dlRNN_Pcheck_transfer(activity,filt_scale,varargin)
option = 'state_simple';
% trans_prob = 'non-linear';
trans_prob = 'pass-thru';
plotFlag = 0;
reaction_time = 100;
if nargin==2
reward=[1*ones(1,1600) 100*ones(1,1400)];
back_p_logic = 1;
else
reward = varargin{1};
back_... |
fac8ea743f89ce23c9b9f06f7686837ab820dd203439ebdb7fd60133965b93c3 | MATLAB | 4,813 | 180 | clc; clear; close all
Fig8a_b=figure();
rng(2^23)
N_psn=1; % number of post-synaptic neuron
resy = 0.0; % resting potential
threshy = 1; % threshold potential
NN = 500; % number of afferents
i_t=randi(500); %i'th trial (choose the i'th trial randomly.);
p1=randi(20);
percI = 0.2; % inhibitory... |
c0ba6934fccb12ff89cc52345127f65bdc79a0df5d5b3823ebcfd36793601bf8 | MATLAB | 4,818 | 126 | function Assemblies = MakebestSUAssems(RankIn_,ScoreIn_, Ltrials_,Rtrials_,MaxSize,DestroyNoiseCorrs,noTrials,nReps)
%@TODO: add shuffling of trial labels between cells to non- trial-resampled version
Areas = {'PFC','HP','Joint'};
InfoCriteria = 'max';
verbose = false;
Ltr = size(Ltrials_{1}{1},1);
noUnitsReal ... |
cd948c160238b1f1800257f5ede1fd0aea2b5ec57aba49e083ca657d74fa0a47 | MATLAB | 4,820 | 203 | function SCRATCH_DB_RRTF
if isempty(which('circ_r'))
a = repmat('*',1,60);
fprintf('%s\n\tRRTF requires the CircStat toolbox for Matlab\n%s\n',a,a)
return
end
%%
IDs = getpref('DB_BROWSER_SELECTION');
st = DB_GetSpiketimes(IDs.units);
P = DB_GetParams(IDs.blocks);
%%
win = [0 0.55];
awin = [0.0 0.52... |
bc0271eba3218018c59d55affbb6bb10cf8900df94b8d60ef82f674567fdaea4 | MATLAB | 4,826 | 135 | function [CVE,... time-dependent mean decoding score [No. Timepoints x 1]
Score,... Time-averaged/Peak decoding score, depending on InfoCriteria [1 x 1]
Score_Shuffled,... Median Time-averaged decoding score from shuffled trials, [1 x 1]
Score_ShuffledCIL,... 5 percentile... |
8c46f644e804a4cb7b67bd34a2e75f1d7c02c950ad055c4e2aa793d42997fa10 | MATLAB | 4,832 | 192 | function [Hits,FA] = Population_Decoder_SVM_PSTH_v2(Data1,Data2,tau,prop_trials,convolve)
if nargin < 3
tau = 10;
prop_trials = 0.80;
convolve = 0;
end
if nargin < 4
prop_trials = 0.80;
convolve = 0;
end
if nargin < 5
convolve = 0;
end
Nogo = Data1;
Go = Data2;
num_iterations = 250; % number of decoder i... |
8488cc456cce41efc04dda4d55773513e2789dfda514d723bacdb4f172733957 | MATLAB | 4,836 | 111 | %NEED TO CHECK
function [PARAMETERS,trials]=initialize_FlickerMemoryTask()
%% Establish memory task parameters
PARAMETERS=set_PARAMETERS(); %set to day 1 parameters
%% Pick and images we'll need for practice, study and test:
num_images=PARAMETERS.num_practice_images+PARAMETERS.num_study_image... |
bdc1270033b9420c31c099aaf639ba0c8b2369c0fd7e4981e118f6bdab99d371 | MATLAB | 4,838 | 108 | function out=driftcorrectbycorrelation(parameters, input)
% DRIFTCORRECTBYCORRELATION - Perform drift correction by correlation
%
% DRIFTCORRECTBYCORRELATION(PARAMETERS, INPUT)
%
% PARAMETERS should be a structure with the following entries:
% prompt_user (0/1) Should we prompt the user every tim... |
01d10a9a4de53a247af1a2550750afceb4740dd21949d53b7af7dee4e81aaf61 | MATLAB | 4,840 | 159 | function [go_indices,nogo_indices,varargout] = ...
getIndices_SanesLab(TRIALS,remind_row,trial_type_ind,varargin)
%Custom function for SanesLab epsych
%
%This function will update valid trial options based on the user's
%selections in the GUI
%
%Inputs:
% TRIALS structure
% remind_row: index of the reminder tri... |
6040b08360a69c24dd20d77ba2d1f95f564525ec2ce42cee9c0ea5dce76c96fc | MATLAB | 4,840 | 122 | function [endo] = import_endo_geom(direndo, fendo, cross_pl)
% IMPORT_ENDO_GEOM Imports the nerve's endoneuria contours.
% The code import the .STL files of the nerve's endoneuria and convert
% the geometry file in a tomogrpaphy representation of the 3D scapes of the
% endoneurium
% All the imported contours ar... |
9ab37fa49f4d3190a7b499b91a125be76f83a5fb34a8f538c3db9db6295c61f8 | MATLAB | 4,844 | 133 | %% Multimodal IMS Multivariate Analysis Script
% This script concatenates (registered) IMS matrices and exports them for
% multivariate data analysis in SIMCA software. In a second step scores
% images from MVA are reconstructed from SIMCA scores export.
%
% (1a) Supply at least one dataset and m/z vector for i... |
56455ed18a5498b1ba4412eb21a8f6599200dd04164fb032778c5fb21d1dc8de | MATLAB | 4,848 | 191 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% read in proc spreadsheet
% filename = [ DD_PROC '/MamiNum_corrected_proc.txt' ] ;
% ssheet = readtable(filename,'Delimiter','\t') ;
%
% animal_names = regexprep(ssheet.file_prefix,'... |
79a6a52c16b31b8c439c3fe7b892d371c4a349c5d0dd1a2f45bc3c759c9cd91a | MATLAB | 4,848 | 228 | function varargout = DB_ManageAnalysisTools(varargin)
% h = DB_ManageAnalysisTools(varargin)
% Edit the above text to modify the response to help DB_ManageAnalysisTools
% Last Modified by GUIDE v2.5 19-May-2016 08:43:44
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', ... |
491c0efed744ffa1a1c3d07b6616d548333cbb824dfce39ed19efe303b49fe90 | MATLAB | 4,850 | 139 | function TCS2 = initialize_TCS2_NI(samplingrate)
% This function requires two NI devices (Dev{i} and Dev{j}, i \neq j
% in {1,2,3}).
% Allows to control the 5 stimulation zones of TCS2 separately.
%
%Analog OUTPUTS on DEV1 :
%DEV1/AO1 : neutral temperature
%DEV1/AO2 : active temperature zone 1
%DEV1/AO3 : ac... |
88427477177250694e907144cc44de06f9e557fe74cbcd06178f56cc90a1bcaf | MATLAB | 4,852 | 156 | function p = DB_GetParams(id,type,conn)
% P = DB_GetParams(id)
% P = DB_GetParams(id,type)
% P = DB_GetParams(id,type,conn)
%
% P = DB_GetParams(id)
% Simply retrieves parameters from the protocols table into structure P.
% If only the id is specified, then this function will assume it is a block
% id.
%
% ... |
0489e6d6cf05d612caae53b9f9d632aa058ba404a983fbef5343e8adac2c4747 | MATLAB | 4,854 | 155 | % Note: very preliminary alfa version. Only for testing purpose. May 2008
%
% Usage:
%
% >> [EEG com] = pop_emghunter(EEG, chan, evecode, newcod, twin, thres)
%
% HELP PENDING for this function
% Write erplab at command window for help
%
% See analog2code()
%
% *** This function is part of ERPLAB Tool... |
5144bbc5928cd61ce3e74ab6e32bf7a13a26800d5510b34c32544e3e1a779195 | MATLAB | 4,854 | 163 | function my_histograms(data_struct, varargin)
% Plot histograms of input data.
%
% used in TSL_fit_on_ratings.
%
% data_struct
% Structure array with one entry per group of data, which will be
% associated with a different histogram. Required fields:
% 'x' for the data set.
n_gr = length(data_st... |
b9947fa6fbe3c7a2f04dd9a00296d9b8870861dac2ebfb8d0c90922f271b191c | MATLAB | 4,863 | 171 | function pp_plot_rasters(subject, session, channel, clu)
%
% pp_plot_rasters(subject, session, channel, clu)
% Plots a raster and psth for each unique stimulus. Clu is the label
% given by UMS (not an index), found in Spikes.sorted.labels.
%
% KP, 2016-04; last updated 2016-04
%
set(0,'DefaultAxesFontSize',... |
d588eec9cd2944f376bb8475661948920766627ab842440763908772eb143a17 | MATLAB | 4,864 | 106 | function Assemblies = MakeAverageAssems(unitIDs,Ltrials_,Rtrials_,MaxSize)
Areas = {'PFC','HP','Joint'};
ResampleTrials = true;
InfoCriteria = 'max';
nReps = 10; % Draw from trials
nDraws= 10; % Draw from unit pool
noTrials = 20; % how many trials to use for each decoder
verbose = false;
Ltr = size(Ltrial... |
8181491000289b37b128100af4d17c2f6b61bd9eb7e39a3d750a1a87202c1fbf | MATLAB | 4,872 | 167 | function [tfVMVariates] = vmrand(fMu, fKappa, varargin)
% vmrand - FUNCTION Draw random variates from the Von Mises circular distribution
%
% Usage: [tfVMVariates] = vmrand(fMu, fKappa)
% [tfVMVariates] = vmrand(..., M)
% [tfVMVariates] = vmrand(..., M, N, P, ...)
% [tfVMVariates] = vmrand(..., [M... |
8a29b2902b93998d11d9a093e3ec37140d027ebac40e3f34122109b401edb1ed | MATLAB | 4,877 | 132 | function result=psignifitCore(data,options)
% this is the Core processing of psignifit, call the frontend psignifit!
%function result=psignifitCore(data,options)
% Data nx3 matrix with values [x, percCorrect, NTrials]
%
% sigmoid should be a handle to a function, which accepts
% X,parameters as inputs and gives back a ... |
aa06e4962132629ee11934f6d5148c8254983862767fffd58b735bea06f9d340 | MATLAB | 4,877 | 181 | function self = EvaluateNetwork(self)
verboseLevl = self.VerboseLevel;
if verboseLevl > 0
fprintf('Evaluating network...\n')
end
summaryT = table(zeros(3, 1), zeros(3, 1), ...
'VariableNames', {'Accuracy', 'F1'}, ...
'RowNames', {'Train', 'Validate', 'Test'});
classScoresS = struct;
% TRAIN
if verboseL... |
26c41b9c27edadf64d40ace9e5d7dbd47044760ddc3a0ebad53eb8bb3dc9cab9 | MATLAB | 4,879 | 100 | %
% sourceSignal=PRODUCEEXPERIMENTSIGNALS(experimentType,duty_cycle_LED,duty_cycle_sound,sound_frequency,type_of_burst,sample_rate)
%
% Produces a structure that provides information about trials of sensory
% flicker stimulation, to be eventually run on the NIDAQ. This is the
% data that the apps "SafetyTesting" and "R... |
85dde75af8b1fdbe4a89c51532442f10d18432bf4d09e1d8a6c0339d8557f6bd | MATLAB | 4,888 | 155 |
% Nodes are somewhat similar to layers in that they have "activity" values,
% have outputs, and can connect to layers via projections, but they are governed
% by arbitrary functions or code. They typically provide control or timing
% signals
%
%
% Properties
% vals - vector of values, analagous to activiti... |
9a8afac8efe0926c91e4430aeb374bf3869fd2baeaf44d628e2ef542420f27f0 | MATLAB | 4,889 | 123 | %%
clear all
close all
run(['..' filesep 'def_local'])
addpath(path_fieldtrip)
ft_defaults
%%
load wsws_ERD
elec = ft_read_sens(path_chanlocs);
cfg_neighb = [];
cfg_neighb.method = 'distance';
neighbours = ft_prepare_neighbours(cfg_neighb, elec);
cfg = [];
cfg.method =... |
d63b6df31c441e770e2c4f58eed43e460cb02e1bcb1acf2caf9c2131e2d153df | MATLAB | 4,889 | 189 | function varargout = TC4controller(varargin)
% TC4CONTROLLER MATLAB code for TC4controller.fig
%
% Daniel.Stolzberg@gmail.com 2016
% Edit the above text to modify the response to help TC4controller
% Last Modified by GUIDE v2.5 28-May-2016 18:01:31
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_Sta... |
6010c97fd02688129d1bc85376d60847cddcdb2e33bb05f79a98c1826d377906 | MATLAB | 4,891 | 165 | function [results] = computeLogLikelihood_host_v2(obj, params, opts, results)
obj.setupComputeStructuresHost();
if(nargin < 4 || isempty(results))
results = obj.getEmptyResultsStruct(opts);
end
LL_info = obj.LL_info;
X_groups = obj.X_groups;
X_lin = LL_info.X_lin;
Y = LL_info.Y;
dt = LL_info.bin_size;
dim_N_r... |
402cda2cbf059dd54261e51d240738e55cbf85cdb6af8e5a5a755b1efe2c8309 | MATLAB | 4,899 | 104 | % Explores behaviour of Assemblies in Pre-sleep/Task/Post-sleep epochs
%
% Aleksander PF Domanski PhD UoB 2015
% aleks.domanski@bristol.ac.uk
%
% NB Run Explore_Factor_activations.m first for each of Pre/Task/Post datasets.
%
% NB currently this code assumes that FA Assembly detection is run for each
% experim... |
7b67e65de822b14834d541c34c39ed1c8bce9a52db3d916fdbe7b79ed28c6e41 | MATLAB | 4,900 | 130 | % drawing violin plots for RMSE values across various surfaces, foot,
% methods (Linear regression, ANN, and LSTM), and MoCap outputs (Flexion
% and Inversion)
% RMSE results are saved in a cell array (4,3) called "results", and each cell again is a cell array(1,2) for
% keeping RMSE results from the right and left f... |
08d190ad2b38628f112a0d1d2be97dda4f3fa296724372c93e6f5fc0131fca39 | MATLAB | 4,907 | 90 | %
% Reorders an electrode table or file according to the row order of channel names in a channels.tsv table or file
%
% This is relevant because the channels.tsv channel names match the electrophysiological data channels, but the rows in
% electrodes.tsv are often arbitrarily sorted. Therefore the electrodes.tsv ... |
814fea6623ed189947131cd1ff1d8171ce38e844aa2d8f96a7f05cf55ca88712 | MATLAB | 4,909 | 168 | clc; clear; close all
rng(1101)
Fig1=figure();
i_t=randi(500); %i'th trial (choose the i'th trial randomly.)
N_psn=1; %number of post-synaptic neuron
desired_S = 2; % desired number of spikes r0 = 2 Hz
w_max = 1; % maximum amount of synapsis.
resy = 0.0; %resting potential
threshy = 1; % thresh... |
64c497e9d322f79ef40fc7d4a84b5f358eef362edcdfa7276ffdb1235802e739 | MATLAB | 4,912 | 180 | function [w, infos] = shooting_lasso(problem, options)
% Shooting algorithm for LASSO problem.
%
% Inputs:
% problem function (cost/grad/hess)
% options options
% Output:
% w solution of w
% infos information
%
% This file is part of SparseGDLibrary.
%
% Created by H.Kasa... |
4df15b5bd193d2c6019462858d26d4ffd9c1c8b25cbe48fc42f30b79c503e0e5 | MATLAB | 4,914 | 113 | function m_tilde = get_M_9x9_from_d_c_SL(d,c,l,D0)
%
% returns the 9x9 form of the matrix M from the 3x3 and 3x3x3x3 tensors
%
dij = eye(3);
dij_1x6 = convert_3x3_to_1x6(dij);
DijDkl = D0^2 * convert_1x21_to_3x3x3x3(convert_1x6_to_1x21(dij_1x6));
% this is D0^2IijIkl - Mijkl
% switching to Magnus convetion for the l... |
85805339e5a8a1869ff746f4b3c255f07f2160ba55c0595d89d35cf802ad7815 | MATLAB | 4,917 | 149 | function EyeTrackGUI(varargin)
% EyeTrackGUI('Parameter',value,...)
%
% 'X_UB' ... X axis Upper Bound tag name
% 'X_LB' ... X axis Lower Bound tag name
% 'Y_UB' ... Y axis Upper Bound tag name
% 'Y_LB' ... Y axis Lower Bound tag name
% 'P_LB' ..... |
0dcb5d8e7c867ccd1288986d76545484c9657e3e7f573313d94327c23b08254d | MATLAB | 4,929 | 118 | clear
Targets = {'SHORT','MEDIUM','LONG'};
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Dirs = {'Left','Right'};
bw=0.05;
if ispc
pat = 'C:\Analysis\AssemblyAnalysis\raw';
cd(pat)
fileList=dir('allTimestamps\*.mat');
elseif ismac
pat = '/Volumes/HDD2/DNMTP/raw/';
... |
433b93d9c9ecc13b6d44920450f04c1eec2b66b85e4c3f8eec3ef0ea43a4a633 | MATLAB | 4,930 | 132 | function [result,indimages] = tpsinglecondition(dirname, channel, thetrials, timeint, sponttimeint, plotit,name)
% TPSINGLECONDITION - Simple image math
%
% [RESULT,INDIMAGES] = TPSINGLECONDITION(DIRNAME,CHANNEL,
% TRIALLIST,[T0 T1], [SP0 SP1], PLOTIT,NAME)
%
% Computes simple image math for twophoton imag... |
009148527bf019bb917259748d47e893ed3b60c10caae33b4630fd5c4d800301 | MATLAB | 4,934 | 124 | function violins = violinplot(data, cats, varargin)
%Violinplots plots violin plots of some data and categories
% VIOLINPLOT(DATA) plots a violin of a double vector DATA
%
% VIOLINPLOT(DATAMATRIX) plots violins for each column in
% DATAMATRIX.
%
% VIOLINPLOT(TABLE), VIOLINPLOT(STRUCT), VIOLINPLOT(DATASET... |
2b8c5acb610ab372568f3d04800470a79f724437b094d8519200f68f3b933174 | MATLAB | 4,940 | 205 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
VIZIT = 0 %#ok<NOPTS>
%% big loop
for tDx = 1:length(THRDENS)
%%
filename = [ DD_INTERM '/con_mat_gn_repani_stack_thr' num2str(THRDENS(tDx)) '_.mat' ] ;
ll = load(filename) ;
c_aCon... |
00db7194acd1e4a210bb64a07618a6fd99dd8f5d12ec203c70eed8e45fae23e4 | MATLAB | 4,943 | 144 | function Phase_sync_metrics_reduced
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% LEADING EIGENVECTOR DYNAMICS ANALYSIS
%
%
% Function to compute the META and VAR
% anaysis for all subjects
%
%
% Fran Hancock
% Oct 2022
% fran.hancock@kcl.ac.uk
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Run seperately for run1 (CON) and r... |
8d0b21f8f3779eebd357d14eba56bcf318a9dacd660bed5078a107595bae2256 | MATLAB | 4,944 | 156 | %%
% Compares continuous L/R discrimination during the delay period,
% calcluated on short/medium/long delay trials independently
%% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
DelaysDur = [4,8,16];
Target = 'LONG';
tlimsAll = [-30 30];
tlimsTrials = [... |
ea28dcf4c8d7c4e1d464315c7ba225056d3580f78a16802802d3d4b64b107f83 | MATLAB | 4,947 | 153 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
shift = 0;
plotOnline = false;
bw=0.05;
Nbs = 500;
warning ('off')
if ispc
pat = 'C:\Analysis\AssemblyAnalysis\raw';
else
pat = '/Volumes/HDD2/DNMTP/raw/';
end
cd(pat)
fileList=dir(sprintf('Mixe... |
644f7e6989b826c867bdc8dc4d80e4e1dae6818e136063287947cae4c8e14f8e | MATLAB | 4,953 | 105 | %
% Extract the conditions from the BIDS events
% [stim_pair_nr, stim_pair_name, stim_pair_current] = ccep_bidsEvents2conditions(events_table, events_include)
%
% events_table = loaded table with bids events
% events_include = optional vector with included trials, set to [] if using ... |
4718035ffabea37e334a483dc9c15655d8febaeb5acb94b366ca718352f96fb2 | MATLAB | 4,964 | 169 | function varargout = f_ERP_suffix_gui(varargin)
% F_ERP_SUFFIX_GUI MATLAB code for f_ERP_suffix_gui.fig
% F_ERP_SUFFIX_GUI, by itself, creates a new F_ERP_SUFFIX_GUI or raises the existing
% singleton*.
%
% H = F_ERP_SUFFIX_GUI returns the handle to a new F_ERP_SUFFIX_GUI or the handle to
% the exis... |
157dd9a88ad880de61f4e3de34d6527de574e2bd2be8c80aea855ee38f15a0fb | MATLAB | 4,965 | 139 | % Example script
% step 1. simulates activity over time in V1 in condition 1 and hMT+ in
% condition 2 for a montage with 32 electrodes. [go directly to next steps
% for examples in using the toolbox]
% step 2. the templates corresponding to the 32 electrodes montage are
% created using createCustomTemplates. (For ... |
c83176fc03b63bcf242b087376374a4dfd4f2a5bdd9c250e257035703d1f45b3 | MATLAB | 4,966 | 102 | function Parm = Parameters(DSETnum)
% Paramaters for the DeepInsight-3D model
Parm.Method = ['tsne']; % 1) tSNE 2) kpca or 3) pca 4) umap 5) lda (supervised)
Parm.Dist = 'euclidean';% For tSNE only 1) mahalanobis 2) cosine 3) euclidean 4) chebychev 5) correlation 6) hamming (default: cosine)
Parm.Blur = 'no'; % type '... |
a9d48214ab09104108f0813669854d3c3157bf4c008270bfa2453e44dc6ae263 | MATLAB | 4,980 | 246 | function varargout = ep_BoxFig(varargin)
% ep_BoxFig
%
% Default figure for displaying behavior results during runtime.
%
% Daniel.Stolzberg@gmail.com 2014
% Last Modified by GUIDE v2.5 12-Aug-2014 14:20:27
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ... |
95bd7f42e152905fb7e673f9cd518dad9ddd724698beed2728930bbed7831cf3 | MATLAB | 4,981 | 127 | function violins = violinplot(data, cats, varargin)
%Violinplots plots violin plots of some data and categories
% VIOLINPLOT(DATA) plots a violin of a double vector DATA
%
% VIOLINPLOT(DATAMATRIX) plots violins for each column in
% DATAMATRIX.
%
% VIOLINPLOT(TABLE), VIOLINPLOT(STRUCT), VIOLINPLOT(DATASET)
% p... |
2839b08614a3e5f58f9918f08e990cfe4ae4ae20eddaf712f1ef53196f077e9f | MATLAB | 4,982 | 198 | function [phi, C] = solve_system(G, mesh)
%[phi, C] = solve_system(G, mesh)
% Set up matrix for phi
A = set_up_phi_matrix(G, mesh);
if strcmp(G.solver_type, 'iterative')
[LA, UA] = ilu(A);
end
T_phi = 0;
T_matrix = 0;
T_c = 0;
% Set up initial conditions
if isfield(G, 'initial_states_set')
c = G.initial_sta... |
81de693e849e41895dfe577d51974c805246c066acc50ec5d4ac93908cfaff45 | MATLAB | 4,982 | 123 | % pop_runhtb() - Run history template on multiple data files.
% See runhtb for more details.
%
% Usage:
% >> com = pop_runhtb(execmeth,HistFName,HistFPath,BatchFName,BatchFPat);
%
% Inputs:
% execmeth - Execution method. "serial" = run batch serial mode using
% for loop, "parallel" = r... |
8b833faac95bec8841d9bd2ace4e284209d476dc11d479c95b0b30192b32115e | MATLAB | 4,982 | 206 | function NeighboursInd = findNeighbours(Index,MatrixSize ,conn)
%%**************************************************************************
% Module name: findNeighbours.m
% Version number: 2
% Revision number: 02
% Revision date: 9-2018
%%
% 2013 (C) Copyright by Patrick Granton, Maastro Clinic
% Pe... |
b4bc57ea7380585cdf3ed41ad08c0bef83a1aa34c6a5818a0942b2926c12f297 | MATLAB | 4,987 | 193 | function [w, infos] = ista(problem, options)
% Iterative soft (shrinkage)-thresholding algorithm (FISTA) for LASSO problem.
%
% Inputs:
% problem function (cost/grad/hess)
% options options
% Output:
% w solution of w
% infos information
%
% This file is part of SparseGDL... |
44281af9771cde4c641cc9c3834cf81c4ccba87deaa1b158901f7602a54bf3c3 | MATLAB | 4,990 | 144 | function [] = write_latex_table_latencies(row_names, all_data, filename, ...
col_names, col_header, caption_str, empty_nan, h_mask, h_mask_corr,...
permission,table_label,varargin)
% write in a txt file the data from all_data so that it forms a table when
% pasted in latex.
%
% In: - row_names: string arr... |
6198b990a2ecdcd8f24d9de3af4a5fc470b13c9974bbd7edf1aacb2fa600bdd4 | MATLAB | 4,996 | 206 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
VIZIT = 0 %#ok<NOPTS>
%% big loop
for tDx = 1:length(THRDENS)
%%
filename = [ DD_INTERM '/con_mat_gn_repani_stack_thr' num2str(THRDENS(tDx)) '_.mat' ] ;
ll = load(filename) ;
c_aCon... |
d33bccb19ac4cf419b2d841bc250a963d32151cb4715eaf3a4092e1134cdef8b | MATLAB | 5,008 | 160 | function fstats = lme_mass_F(stats,CM,prs)
% fstats = lme_mass_F(stats,CM,prs)
%
% Inference for the fixed-effects in the linear mixed-effects model. Allows
% to test a different model at each voxel/vertex (Depends on the Statistics
% toolbox).
%
% Input
% stats: Structure array containing statistiscs for every voxe... |
4d747353bcca08402aca9d45d03c9e053c605c0926e07526c8a3d22af55fd4db | MATLAB | 5,009 | 199 | function varargout = TDT_TTankInterface(varargin)
% TDT = TDT_TTankInterface
% TDT = TDT_TTankInterface(TDT)
% TDT = TDT_TTankInterface('server','SomeServer','tank','SomeTank')
% h = TDT_TTankInterface(...,'maintain')
%
% Select/Create TDT server, tank, block, etc. using TTankInterface ActiveX
% GUI
%
% TDT output is a... |
0a4a2a6905420b0054161570b74ba5c3ed73d1d9f94d27eeeb84adfface89df2 | MATLAB | 5,015 | 156 | classdef stateSpace < handle
properties
transitions
curState
stateLog = []
adjacencyMat = [];
numStates = 0;
timeInState = [];
rewards = [];
numRewards=0
end
methods
function obj = stateSpace(transitions, curState, rewards)
... |
17e81c19ee9821f627e716babda3d8cb66419d8690d49b0fe73f7764c7e04de9 | MATLAB | 5,015 | 213 | clearvars
setUpPaths
%%
for len=1:23
processData
%%
clear ExpectMeaned Sig
trials=StoreType==1 & NewSupriseStore1==1;
%%
tempOris = StoreX2(trials);
tempData = Store(trials,:,:);
%% create the design matrix
Orientations=0:30:150;
... |
fc6a9be95b1d21cb01fb63a5e3a1059745ab3af7d00f2b2500487b0e44b03374 | MATLAB | 5,019 | 112 | function CrossNobis_Distance = SqrtCrossNobis_Distance(measurementsA, labelsA, measurementsB, labelsB)
%this function calculates the crossvalidated mahalanobis (i.e., "crossnobis")
%distance between the conditions specified in labels across the values specified
%in measurements, cross-validated across se... |
4817e6648f88750256de2ab1c56936926943d2c57798e09feeff8dc673688694 | MATLAB | 5,021 | 126 | function crop_raw_stack(substack_depth, overlap, dx, Nnum, range_adjust, z_sampling, ...
rotation_step, rectification_enable, rotation_enable, compstack_enable,...
flipx, flipy, flipz, file_path, file_name, save_path, bitdepth)
% CROP_RAW_STACK crops the HR data in depth and augments the dataset
% crop_raw_st... |
052147aa89a73785bf6968d8085d89df0612d43d22d4ce63bc937e94ae86cb2e | MATLAB | 5,023 | 128 | %% Flexible Capacity Serial System
% A parallel-serial processing system where a part of the system is a
% limited pool of central resources that can be flexibly assigned to
% modules.
%
% 3 December, 2021
function [finalRate,input_record,output_record] = FlexibleCapacitySerialSystem(systemCapacities,taskModifiers... |
ff0dce48c0be648b72171f23bbee8252ff498787bed59cde2eee1363c5fbf3fa | MATLAB | 5,025 | 127 | function find_placement_comb(iSubject)
% find_placement_comb(1)
% iSubject = 1 for Subject1, 2 for Subject3
[numFibersAtPercepThreshold, placements, endo, percepThresholds, expAS, fascicle, sensation, center, ratio] = ...
fascicle_for_perception(iSubject,false, 13);
% numFibersAtPercepThreshold(iOrientedPlac... |
252c41d516b533634e585a354f7656045d3ede7a42844e0da7529ab3ecc15020 | MATLAB | 5,029 | 93 | % MYM - Interact with a MySQL database server
%
% Copyright notice: this code is a heavily modified version of the original
% work of R. Almgren from University of Toronto. Up to V1.0.9 the code was
% made by Y. Maret (during his work at EPFL). Version 1.36 was updated
% by J.T. Marsh and provided by J. Erlich.
%
% I... |
313e83cf50582fc337a51cf38308c86bcdb9fc7523633ecfb88e5a212e114af7 | MATLAB | 5,037 | 174 | function PPlot(Locs, LocLinks)
iID = 1;
iParentID = 2;
iX = 3;
iY = 4;
iZ = 5;
iRadius = 6;
numCirclePts = 24;
CircleVerts = CirclePatch(numCirclePts, 1, [0 0 1]);
Faces = CylinderFaces(numCirclePts);
numLocs = size(Locs,1);
numLinks = size(LocLinks,1);
... |
3bdff70852fbcf89dcfcfa301b2405a588c4e1175d82eac1ec8fe591f3ce5cc9 | MATLAB | 5,038 | 147 | %%
clear all
close all
run(['..' filesep 'def_local'])
%%
allfiles={'405','406','407','408','409','410','411','412','413','414','415','416','417','418','419','420','421','422','423'};
nc=0;
allres_clarity=[];
for n=1:length(allfiles)
files=dir([behav_path filesep 'SWS_NVS_results_S' allfiles{n} '*.mat']);
l... |
82cb31b38c19275d95d1d5ed6a895836c636790062ede6e757e32aee8bf02632 | MATLAB | 5,038 | 156 | function [EI,Pth,Qthth] = lme_mass_RgEI(X,Zcols,W,CBhat,L,phi,ni,invG,GDa,GDb)
% [EI,Pth,Qthth] = lme_mass_RgEI(X,Zcols,W,CBhat,L,phi,ni,invG,GDa,GDb)
%
% Expected information matrix of the restricted log-likelihood of a whole
% region.
%
% Input
% X: Ordered design Matrix (according to time for each subject).
% Zcols... |
5c7047db2bd03fcc19baf05c838a1f06bcc8f68e697c7ae71a734e5ffcd47fe6 | MATLAB | 5,039 | 138 | function spikes = ss_align( spikes )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% ss_align - Multi-channel alignment of waveforms on negative peaks
%
% Usage:
% spikes = ss_align( spikes )
%
% Description:
% This function uses spline interpolation in order to find the true peak
% ... |
1c92730de6b9b95e07c8982ec85abee123781aafc83233fecbf16a6b2221caa8 | MATLAB | 5,040 | 111 | % Demonstrates how to use the property pane.
%
% See also: PropertyGrid
% Copyright 2010 Levente Hunyadi
function example_propertygrid
properties = [ ...
PropertyGridField('double', pi, ...
'Category', 'Primitive types', ...
'DisplayName', 'real double', ...
'Description', 'Stan... |
25b892144b27fb457e30992ba1425afbaa5876ac5843e00257d9dd1aa14fe8be | MATLAB | 5,057 | 180 | function subPlot_Gen(x,y)
%Creates a 4x4 grid of subplots and graphs each angle separately, followed
%by graphing all of them on a single subplot.
x2 = x((x(:,2)==1),:);
figure('Name','Trial-By-Trial Accuracy')
colorArray = jet(15);
for i = 1:length(y)
if y(i,5)
x3 = x2((x2(:,1)==i),:);
switch x3... |
ca4c155a39d68305aa890f857761291af6a799a06363921f98f0836bad01144f | MATLAB | 5,066 | 166 | % File: GetOMEData.m
% Author: Sebastian Rhode
% Date: 13.09.2015
% Version: 1.3
function OMEData = GetOMEData(filename)
%
% Get OME Meta Information using BioFormats Library 5.1.10
% To access the file reader without loading all the data, use the low-level bfGetReader.m function:
reader = bfGetReader(filename);
% Y... |
5c96e4c23e169293d24f8f099a9dbb201ac88552c418282e48eb9a7667bbed92 | MATLAB | 5,081 | 160 | function [stats,st] = lme_fit_EM(X,Zcols,y,ni,e)
% [stats,st] = lme_fit_EM(X,Zcols,y,ni,e)
%
% Linear mixed-effects estimation by expectation maximization.
%
% Input
% X: Ordered design Matrix (according to time for each subject).
% Zcols: Vector with the indices of the colums of X that will be considered
% as random e... |
70ca28dd021fba01b4fcad9fa5a81cc51c819ba42ff93bea5de6cfd2e1cd41b3 | MATLAB | 5,090 | 189 | function [Genes,Genes_compressed,G]= func_FeatureSelection_avgCAM(Parm)
% Feature selection of DeepInsight-FS
model = load('model.mat')
%netName = "squeezenet";
netName = Parm.NetName;
cd DeepResults
net = load(model.fileName);
cd ../
% netName = net.trainedNet.Layers(2).Name;
% Oblique = '|';
% [rmp,cmp] = max(netN... |
f7693c3b134c82e2cc72221d39de0c7157967362d1c306bc95005586ab14c876 | MATLAB | 5,096 | 178 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% setup vars
thr_vals = [ 0 0.05 0.1 0.15 ] ;
odir = [ PROJ_DIR '/reports/figures/commspace/' ] ;
mkdir(odir)
for tDx = 1:4
%% some viz stuff
labs = { 'Efficency' '-Searchi... |
689271cedff660a471a27ca7959421228119fdcc01ece0edd7ba831385ae8de1 | MATLAB | 5,097 | 158 | function [EI,Pth,Qthth] = lme_mass_RgEI1(X,Zcols,W,CBhat,L,phi,ni,G,GDa,GDb)
% [EI,Pth,Qthth] = lme_mass_RgEI1(X,Zcols,W,CBhat,L,phi,ni,G,GDa,GDb)
%
% Expected information matrix of the restricted log-likelihood of a whole
% region. This is less computationally efficient than lme_mass_RgEI
% but more numerically stabl... |
d81e601cafa6456781e0c65def467ba4a7d6e5989b46c3714df976aa1eae6eba | MATLAB | 5,097 | 177 | function H=shadedErrorBar(x,y,errBar,lineProps,transparent)
% function H=shadedErrorBar(x,y,errBar,lineProps,transparent)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
% Inputs
% x - vector of x values [optional, can be left em... |
965011c27585137e00010fc4f5c4cfc99253cb150d2d28a998fe4e333fdecc18 | MATLAB | 5,102 | 152 | function varargout = Appetitive_Training_Menu(varargin)
% This GUI lanuches a menu that allows a user to select a
% appetitive training paradigm. Paradigms are as follows:
%
% Pure Tone Training Stage 1:
% A pure tone is generated by default. Water is available at the spout
% as long as the pure tone is on. The ... |
1e6189a865fac469c223bbc24981c268e8b2e62bb9626df1f2dccbc3c21b40fc | MATLAB | 5,106 | 186 | function pp_plot_rasters_Freq(subject, session, channel, clu)
%
% pp_plot_rasters(subject, session, channel, clu)
% Plots a raster and psth for each unique stimulus. Clu is the label
% given by UMS (not an index), found in Spikes.sorted.labels.
%
% KP, 2016-04; last updated 2016-04
%
set(0,'DefaultAxesFontS... |
bf04f2c8f6a7325221d881b6aa10963435b55127f36a83d69e82fd87643f3933 | MATLAB | 5,110 | 142 | %% Determine when decisions are made during an OH/OHA/TOH/TOHA trial
% Produces lists of decisions in an OH/OHA/TOH/TOHA trial based on two
% criteria: actions represent decisions, so any contact with an object is
% evidence that a decision was made; and that decisions are made on state
% changes in the trial.
% C... |
f7b189b4be0ccdd5485a9716250b6c8ad9d2f59adcb2be750295cb3c580687e0 | MATLAB | 5,120 | 118 | clear;
% Plot perceptual thresholds from experimental data
[rootDir, dataPath, dirNerve, dirPops, dirElecs, dirFEMs, ...
dirPots, dirDist, dirMRG, dirRecrs] = get_base_data_paths();
load(fullfile(dataPath, ...
'Validation\perceptual thresholds\perceptual threshold experimental data.mat'), ...
'p... |
47a77053c9aa6cf0747669696e6fbd4d580b9e7b608c2e1b5f76208f8b43e4f7 | MATLAB | 5,128 | 211 |
function varargout = ep_SchedWAVgui(varargin)
% ep_SchedWAVgui(callingh,filestruct)
%
% Daniel.Stolzberg@gmail.com 2014
% Copyright (C) 2016 Daniel Stolzberg, PhD
% Last Modified by GUIDE v2.5 03-Aug-2014 15:34:21
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfi... |
9fa258b9c59d69a97ecc414b57a2a1dacbace5676459f0487e63f9dd71b16686 | MATLAB | 5,128 | 179 |
%function FM_sweep_testing()
% close all;
% Define RCX file
handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\Sandbox\KP\AM_jitter_pulse.rcx';
%Load in speaker calibration file
pn = 'C:\gits\epsych\UserFiles\SanesLab\SpeakerCalibrations\';
fn = 'rig1012-CeilingB_Noise_Mar072016.cal';
fidx=1;
% [fn,... |
25cfca90b41ba290ab6e6839e5a5c00be3321e8c6fa5123820ddd5b06a44dfbe | MATLAB | 5,133 | 131 | function [p,mu,stdev,n,x] = undetected(w,threshes,criteria_func)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/201
%
% undetected - estimate fraction of events that did not reach threshold
%
% Usage:
% [p,mu,stdev,n,x] = undetected(waveforms,threshes,criteria_func)
%
% Description:
% Estimat... |
e2c552504851f1f912a4f8e6458fa00f8af106a95a67269942fcec82480f1170 | MATLAB | 5,150 | 241 | function RunEuclideanDistanceClassifier
%-Stores Data-%. Created 07/21/2017 JDY-%
clear all
close all
clc
if( isunix )
Path = '/Volumes/JUSTIN EXHD/DataStore/';
else
Path = 'E:\PROJECTS\DataStore\';
end
Gerbil = GetGerbilIDs(Path);
%---Run Analysis---%
N = size(Gerbil,1);
for a=1:N
gerbil = Gerbil(a,:... |
a142d99c21273ceb0f46b09fe8103c4354bda59eaef46a15dd4cb122ac734fbc | MATLAB | 5,160 | 148 | % Decode Left/Right preference of assemblies.
%
% Reports decoding metrics of both each assemblies and assebly population
% with both F-score and Cross-validation error metrics. Bootsrapped
% F-decoding error also calculated.
%
% (c) 2014 Daniel Durstewitz, Bernstein Center for Computational Neuroscience, CIMH/ H... |
5e251972501646ff75b96c60b8016bff9aafc8f468eb79df56215a6a09db6633 | MATLAB | 5,176 | 145 | classdef FrameWriter
properties
Path % path of the output video
% SequenceReader - reader for .seq input type
Writer
CurrentIndex % current frame index
% Opts - options for output
% .OverWriteExisting - whether or not to over-... |
7bb5e8d058a5452f69dcb82e454d9a5c80cc027fdd26f7f79448e932a61fba17 | MATLAB | 5,184 | 196 | 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... |
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