sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
694412b58631733a4df2b2b4aaee9c3b548c0e7f7027651988b46ce61d3a4e35 | MATLAB | 2,576 | 97 | function [] = test_elasticnet()
clc;
clear;
close all;
%% Set algorithms
if 0
algorithms = gd_solver_list('ALL');
else
algorithms = {'APG-BKT', 'APG-TFOCS-BKT', 'CD-EasticNet', 'FISTA'};
end
%% prepare dataset
if 1
% generate synth... |
0e4b7b1096247017dfcb1d6eb9329dc7b4a3f4829e71a692324ef3900193dfe1 | MATLAB | 2,577 | 97 | clear,clc
num_trials = 20;
Fs = 30000;
num_channels = 4;
trial_dur = 20;
load waveform
Fr = 20;
scaler1 = [6 3 1 4];
scaler2 = [2 6 3 1];
data = [];
for j = 1:num_trials
data{j} = randn([Fs*trial_dur num_channels]);
end
% make waveform block
ws = [];
for j = 1:num_channels
ws1(:,j) ... |
ffedc8b57b450ed9cd25e8e4ce4f6317cf5c5516e02017419e0a14261ace9817 | MATLAB | 2,579 | 86 | function handles = updateResponseHistory_SanesLab(handles,HITind,MISSind,...
FAind,CRind,GOind,NOGOind,variables,...
ntrials,TrialTypeInd,TrialType,...
REMINDind,varargin)
%handles = updateResponseHistory_SanesLab(handles,HITind,MISSind,...
% FAind,CRind,GOind,NOGOind,variables,ntrials,TrialTypeInd,..... |
fa6e52da7a51e5cd26ebf335ea6ac39a10363d4654a743151558da29c2d15b45 | MATLAB | 2,581 | 83 | function [iht, ihbas, ihbasis] = makeRaisedCosBasis(nb, dt, endpoints,b, zflag,symm)
% [iht, ihbas, ihbasis] = makeRaisedCosBasis(nh, hdt, endpoints, b, zflag);
%
% Make nonlinearly stretched basis consisting of raised cosines
% Inputs: nb = # of basis vectors
% dt = time bin separation for representing basis... |
09a505db8eb42bb9f705671f32910fc543949923af0e335909bbe458df06d400 | MATLAB | 2,582 | 75 | function inputStruct = getCurrInput(sceneStruct, obsStruct, frameNum, samplePath)
arguments
sceneStruct struct
obsStruct struct
frameNum double
samplePath char = ''
end
%GETCURRINPUT Returns a struct containing the current input. For optic flow, this is x, y, dx, dy
frameLabel = getFrameLabel(fr... |
00028f581aba4bb96bf662bc421cd344a1e1a20f198d413a39a95d539686b8be | MATLAB | 2,585 | 76 | function subdirs = epsych_startup(rootdir,showsplash)
% epsych_startup;
% epsych_startup(rootdir [,showsplash])
% newp = epsych_startup(...)
%
% Finds all subdirectories in a given root directory, removes any
% directories with 'svn', and adds them to the Matlab path.
%
% Typically, it is a good idea to call th... |
ffc720b9787a337469b4f5e2f37957c65e8338ac8ae0a702cc7e45cdeb8da56e | MATLAB | 2,587 | 73 | %% Generate Data from raw EEG records
% For running this demo, please uncomment and change the address.
% This script is intended to convert the raw EEG files in data matrices.
% It was used within the experiments presented in [1]
% Per each subject, the output file is an EEG data struct in which the EEG
% trials are ... |
620879e5225e19db78d4d68c40703a736f036665f30c3b913edb966daa4f9993 | MATLAB | 2,590 | 70 | %% gets combinations of parameters to optimize for MLE/MAP estimates
function [optSetup, opts_empty] = getOptimizationSettings(obj, alternating_opt, trial_weights, optStruct, includeHyperparams)
if(nargin < 5)
includeHyperparams = false;
end
if(nargin < 4 || isempty(optStruct))
optStruct = obj.getComputeOption... |
5c9601c8367d7e46afccffc76f528b6fab6b8aef0f6a13a8b216ba0f428373ad | MATLAB | 2,591 | 72 | function [embedding, lambdas] = laplacian_eigenmaps(data, n_components, random_state)
%LAPLACIAN_EIGENMAPS Performs non-linear dimensionality reduction using Laplacian Eigenmaps
%
% [embedding, lambda] = LAPLACIAN_EIGENMAPS(data, n_components)
%
% Performs non-linear dimensionality reduction using Laplacian Eigenmaps.
... |
795990fb18deda51689c82948cd63fdbd721f8a1879d517a13ba54ff97971e84 | MATLAB | 2,591 | 69 | function [trials_resp,tot_trial_time,timings,tot_run_time] = sample_lists(...
trial,isi,resptime, IRI)
% Define when the behavioral questions are asked to the subjects and
% compute the timeline of the experiment.
%
% Inputs
% trial total nb of trials in a sequence.
% isi (sec) vector of possible ... |
d4069dff19e6e7880f222aaf734af1c79ca66270906ec81e4d2918e2f147934f | MATLAB | 2,592 | 83 | function copySuite2pdata2PrairieView(suite2p_exper_dir, suite2p_source_dir, new_exper_dir, prairie_target_dir_list, channel_in, channel_out, doit);
if nargin<7,
doit = 0;
end;
disp(['Working on Suite2p directory ' suite2p_source_dir '...']);
% Step 1: count the number of suite2p frames
suite2pdir = fullfile(suite... |
22c0290f5675c8117236def27bb2eb7e1d131fd815b9192f659e60b736c42bff | MATLAB | 2,595 | 57 | function [DataL,SF]= Arranging(Data,mainFolder, CSV_filepaths)
SF = strings(1,numel(CSV_filepaths));
% CSV_filepats contains the information about the participant, foot,
% trial (including walking surface), and gait. These information are extracted from the
% CSV_filepaths string and 4 new columns are added to the ... |
e8e20037cb8da55014e953ec24b3572d465724c3003916f5055974a7288ff447 | MATLAB | 2,595 | 116 | %% Enter Tank Info
tank = 'DILL_MGB_1'; % Specify tank name
block = 'Block-2'; % Specify block name
win = [0 0.2]; % Specify peri-stimulus window for field potentials
% optional: electrode remapping (leave empty for no remapping)
emap = [];
% emap = [17 31 19 29 21 27 23 25 18 32 20 30 22 28 24 26 1 15 3 13 5 11 7 9... |
fdf5d7198b37b4ab5f1f021dbce4269a5b4341990da90fb652bbb8b7d1ed90d4 | MATLAB | 2,595 | 68 | function imData=read_file(path_to_file,sframe,num2read,options)
% Reads uncompressed multipage .tiff, .hdf5, .avi or .raw files
% Usage: my_data=read_file('path_to_data_file, start frame, num to read);
% INPUTS:
% path_to_file: location of file to be read
% sframe: first frame to read (optional, defau... |
545c4b59eed13a2d7230cfdfaa9779ee71278010d3a3ee34e7755c205d392487 | MATLAB | 2,597 | 96 | %% Reconstruction
usePCAProjections = false;
if exist('reconstructionPCABasis')
usePCAProjections = true;
end
if ~exist('reconstructionPlotIndices')
reconstructionPlotIndices = 1:size(saveData.FinalStream,1);
end
numTrial = max(saveData.TrialData);
trialLength = size(saveData.FinalStream,1) / numTrial;
plotT... |
a71185f735a9d6fe9ee0093bc26b5a4160de2a727c9161935abda0bbb50cac70 | MATLAB | 2,599 | 97 | function filename = mySaveasFlex(varargin)
%%% 26-01-23 first commit
%%% variable arguments pairs
% 'dimXY' -> vector of two num. Default: see below. If both dimXY and size are specified, size is ignored.
% 'size' -> str: S, M, L, XL (dimXY and size mutually exclusive). Default: M
% 'res' -> num. Default resolutio... |
cd1c38bc895062f9b47bb4f145fd79045affb7308ca1d8cd9da0d14edb27de74 | MATLAB | 2,599 | 90 | function ax = createAxes(N_figs, N_rows, N_cols, ax_properties, single_index)
% This function creates a new set of axes for plotting - axes created are
% equal in size and positioned according to the sizing properties provided.
% Properties that aren't provided are assigned default values, which may be
% changed here
... |
5e6462143fe884023487ff86ceb5da03d3b19efcf0271bc313afd6179ced88a9 | MATLAB | 2,601 | 66 | clear
pat = 'C:\Analysis\AssemblyAnalysis\raw\';
fileList = dir([pat 'allTimestamps' filesep '*SHORT*.mat']);
N_SHORT = [];N_SHORTerr = [];
for iFile =1:length(fileList)
load([pat 'allTimestamps' filesep fileList(iFile).name],'t');
Delays_ = fieldnames(t);
N = zeros(length(Delays_),2);
Ne = ... |
3536fbc56da06bdcccbff3b23ecc8e2c4da8e3c67fd75e0b36a5e23ec1db4797 | MATLAB | 2,604 | 73 | function y=roundsd(x,n,method)
%ROUNDSD Round with fixed significant digits
% ROUNDSD(X,N) rounds the elements of X towards the nearest number with
% N significant digits.
%
% ROUNDS(X,N,METHOD) uses following methods for rounding:
% 'round' - nearest (default)
% 'floor' - towards minus infinity
% 'ceil' - towards ... |
4460632e417c30b073f7ecb34aebfd5001de72b386c4b27880ff450d1a255751 | MATLAB | 2,604 | 105 | function plot_nodes_in_cortex_rsn (V,orient)
%
% Set up the paths to static data, functions and libraries
%
addpath('/Users/HDF/Dropbox/Fran/Academics/PhD/matlab/', genpath('/Users/HDF/Dropbox/Fran/Academics/PhD/matlab/functions'), '/Users/HDF/Dropbox/Fran/Academics/PhD/matlab/static_data','/Users/HDF/Dropbox/Fran/Ac... |
e74dd7dfff6923864d2581846e899beb1bc8c1630b507464dc0be830d2c2bfd2 | MATLAB | 2,606 | 74 | function [pos_signal, neg_signal, region_mask] = run_flatt(signal, window_size, var_threshold)
% RUN_FLATT_SLOPE_VARIANCE Labels signal using linear regression parameters.
%
% Inputs:
% signal - 1D vector containing the input data[
% window_size - Size of the overlapping window (e.g., 16)
% var_threshold... |
88da52367c850cd9e4147edde466181dc74b63fff098a56aec8042549f07de58 | MATLAB | 2,608 | 86 | clc; clear; close all
Fig3d=figure();
Ntrials_2 = 10000;
%Ntrials_2: number of learning cycles to learn the background containing the embedded pattern (step 2).
xax=(1:1:Ntrials_2);
N_mu=500; %There are \mu independent embedded patterns, 500 simulations (number of simulations)
%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
7d37d10dbcb6b15befd91c7498e47f2bb067398fe5ec51b3d8cdecf9305c7053 | MATLAB | 2,609 | 106 | function noise_spectrograms
% function noise_spectrograms
%
% Draws example spectrograms to illustrate the three noise conditions (clean, temporally restricted and continuous)
%
% Stephen Town - 2018
% Options
fS = 48848.125;
t_max = 1.25; % seconds
offset = 0.25;
noise_attn = 10;
vowel_attn = 10;
window_s = 256; %... |
c418593712dbe1f6f4df4e93014ea8ac495340ac8c9ba29d64be86ccbf9d89f6 | MATLAB | 2,611 | 104 | %% 1. Move select files from subdirectories to another directory
indir = 'D:\ownCloud\BIG_DATA\MRI';
outdir = 'D:\DataProcessing\NII';
d = dir(indir);
d(1:2) = []; % get rid of dots
d(~[d.isdir]) = [];
dname = {d.name}';
disp(dname)
%%
istr = cellfun(@fullfile,repmat(cellstr(indir),size(dname)),dname,repmat({'NII'},... |
39dbd9e65dd0dc158f7b0d4ec0d72a99b98ead50efef9ecf25a1ec10777a502e | MATLAB | 2,612 | 87 | % Quality control Q3
% Plot time series from fMRI images and head motion
% Xin Di, July 13, 2022
clear
subjfolder = dir('F:\fMRI_QC\fmri-open-qc-rest_bias_corrected\sub*');
figure
for subji = 1:length(subjfolder)
fprintf('Processing subject %d ...',subji)
% load the raw functional images and calcul... |
b4358ee40f4947de2ced004df3f42e513a35b504492d1dd370f0ef1db49ecffe | MATLAB | 2,612 | 87 | function plot_AMJitter_stimWaveform(buffer)
% Plots a polar histogram of spiking during the AM portion of a stimulus.
set(0,'DefaultAxesFontSize',10)
set(0,'DefaultTextInterpreter','none')
% if nargin<5
% savedir = '/Users/kpenikis/Documents/SanesLab/Data/processed_data';
% savename = sprintf('%s_sess-%s_ra... |
c807f1b7decc456d87b3b429af06535e0a56edfc1ee7196c18854a13ee774bee | MATLAB | 2,612 | 63 | function beta_distributions(dataDir, rootexpnam, betaseries, num_cond)
%% beta_distributions
%
% INPUTS:
% dataDir - default directory by startup.m
% rootexpname - shared experiment name folder prefix (e.g., 'M1_' ...)
% betaseries - was the GLM a beta series GLM? input is binary
% num_cond - number indicating h... |
9b57d250d7790a4bf303da9e1d3257641e9bd54de04391cae4d0552c685c9019 | MATLAB | 2,618 | 70 | function view_3d_model(model, ax)
if nargin < 2
figure;
ax = gca();
else
axes(ax);
end
hold on;
axis equal;
ax.Clipping = 'off';
cmap = colormap(ax, flipud(parula));
c = colorbar(ax);
c.Label.String = 'Charge threshold [nC]';
idCrossStep = 5; % Plot z-resolution, change at will
idCrosses = 1:idCrossStep:si... |
4eeffe0336e91523b4e2b67d40325c3e1c295ce1d1ecf6cbbe82c32bcd2702dd | MATLAB | 2,626 | 36 | % REMOVE BAD CHANNELS - MIXED METHOD %
function [channel_amp_data_Cutoff_logical, channel_grad_data_Cutoff_logical, low_sig_range_all_channels_val_logical] = ...
bst_ast_remove_bad_channels_mixed_formula(all_amp_data, all_grad_data, chanAmpDevThreshold, chanGradDevThreshold, method)
if method == "mix mean"... |
a3227cf76d6b7be523375b410a8dad3f58042301cc4daa076b05955f25a9b3ed | MATLAB | 2,626 | 73 | function [z,dof] = plot_distances( spikes, show, method )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% plot_distances - Histogram the distance of waveforms from cluster center.
%
% Usage:
% [z,dof] = plot_distances( spikes, show, method );
%
% Description:
% Plots histogram of Mahal... |
672603f43f1ddb8db00d333b014351920d5f2e267592546dbb3bb00b43ce1c61 | MATLAB | 2,627 | 61 | function [freq, q, qLo, qUp, effRecrMean, effRecrLo, ...
effRecrUp, collRecrMean, collRecrLo, collRecrUp] = ...
linearCharge_stim(t, var_in, var_in_min, var_in_max, q_min, q_max, ...
freq_stim, recrNormIa, recrNormIb, recrNormAlpha, recrNormII, ...
recrNormIII, recrNormTouch, Q)
% INPUT:
% ... |
79778856cb526003c20ccfcbb5022a36c7c52019153e46b37ceebd8e7c9ba322 | MATLAB | 2,627 | 76 | %% demo_003 fields of the results struct - Which information is contained in the result of Psignifit
% to have some data we use the data from demo_001
data = [...
0.0010, 45.0000, 90.0000;...
0.0015, 50.0000, 90.0000;...
0.0020, 44.0000, 90.0000;...
0.0025, 44.0000, 90.0000;...
0... |
76dc40e8143d3181ec550b8734294bfe0175161c748e25af6caaaa8ce6687080 | MATLAB | 2,628 | 79 | function plot_comparison_per_fiber(model1, model2, normalization)
%PLOT_COMPARISON_PER_FIBER compares models fiber per fiber
% (must have the same distribution)
% See HISTOGRAM for allowed normalization methods.
if nargin == 0
model1 = select_and_load_model();
model2 = select_and_load_model();
end
if ... |
2efa258c9c57e41574147d0652a2f4f98f0adfc9099327df73e868f4f92af534 | MATLAB | 2,631 | 74 | %% Setup
util.clearAll;
outdir = fullfile(util.get_paths().figs,'chord_modularity');
util.mkdir(outdir)
c = util.plot.getColors();
%% Get the correlations
beta_tables_taste = util.load.all_taste_betas();
taste_names = beta_tables_taste.sep_table.Properties.VariableNames;
% Note: Correlations are between tastant (high_l... |
a1cbe8c34bec9ea3f05d3e6ce09d1e10ea020c3fb9646d366aaf0901dae89281 | MATLAB | 2,633 | 80 | %%
clear all
close all
run(['..' filesep 'def_local'])
addpath(path_fieldtrip)
ft_defaults
%%
allfiles={'405','406','407','408','409','410','411','412','413','414','415','416','417','418','419','420','421','422','423'};
% params
frqBand = [1,3; 4,9; 10,15];
filt = [];
filt.hpfilter = 'yes';
filt.hpfilttype = '... |
f371f79742d41b7ceedf4a95a2c5661331c54f89fdfea01062cd7ed453258d8b | MATLAB | 2,633 | 90 | function plotPatternLocs(allLocs, pattTypes, realTime, ntrials, nspacebins, cortexMask, smoothScale)
% Takes the patterns cell array ALLPATTERNLOCS from findAllPatterns.m and
% produces a number of plots
plotTime = true;
if isscalar(realTime)
realTime = 1:realTime;
plotTime = false;
end
if ~exist('ntrials', 'v... |
0053364454b104aa8ef693b0e56ee2799806ce0c394cf2599e6544a561514092 | MATLAB | 2,634 | 91 | function [ims,channels] = tppreview_stdprojection(dirnames, tpparams, channellist, parameters, shortname, dirname)
channels = []; fnameparameters = {};
% lets find parameter files, get the file name prefix pattern
for j=1:length(channellist),
good = 0;
try,
myfnameparameters=tpfnameparams(dirnames{1},channellist... |
6cb885fbce0d49ebc5bc82081a8d25b36962f4d1093f6f2781aab7bef355dcc8 | MATLAB | 2,634 | 92 | function [WMD,mf] = f_interpolate_WMD(L,ED)
N = size(L,1);
% correct for fibers that are shorter than the ED
ff = find((L>0)&((L-ED)<0));
minED = min(min(ED + (1000*eye(N))));
L2remove = find((ED(ff) - L(ff)) > minED);
L(ff(L2remove)) = 0;
ffmask = find(triu(ones(N),1));
[~,orderEDind] = sort(ED(ffmask),'... |
c4eb58556195147685b821954665bada03860566f53d63c41da0a34a91ece457 | MATLAB | 2,634 | 95 | %% Bar Sweeps
% Bars moving across the screen.
%
% Daniel.Stolzberg@gmail.com 2016
barwidth = 50; % pixels (1x1 integer)
angle = 0:30:340; % starting angle in degrees (1xN)
rate = 1000*ones(size(angle)); % rate, pixels per flip (1xN)
contrast = 100; % contrast between background and bar
[window,ScreenRect,fra... |
fa699cdd3d9c916f0c94cd7685a4eefd54fc7b174ee93ec94944e8ea94c2fffd | MATLAB | 2,636 | 95 | function make_chord_plots
%
% Function to make mode chord plots
% Fran Hancock
% July 2022
% fran.hancock@kcl.ac.uk
%
PROJECT = '/Users/HDF/Dropbox/Fran/Academics/PhD/matlab/projects/COBRA_COMPLEXITY_PHASE_FD/';
CondMax=2;
N_areas=116;
Smax=5;
CON_PROJECT = ([PROJECT 'RUN1']);
PAP_PROJECT = ([PROJECT 'RUN2']);
% co... |
9d25c2f39c661fdf375a0871759e859f472d481ad08c6d9f6ec74367538b2cea | MATLAB | 2,638 | 85 | % run codes in "Model simulation programs" to get simulation data
% run codes in "model analysis" to obtain the data for figures
% load intermedia data for reproduce the results in a quicker way (Deposited data links provided in the paper)
load('fig7ac.mat')
%% Fig7a,plot example
% plot example mean+std
% variable f ... |
fa197e5d091fefa8b9fc9f9d288d153ae3a769ee36191cdb9bae663eee1c1685 | MATLAB | 2,638 | 94 | function plot_axonal_sel_cross(model, args, plotArgs)
arguments
model Model
args.iActiveSites = []
args.Fasc = [];
args.SeparateElectrodes (1,1) logical = false
args.SavePlot = true;
args.PlotDir = [];
plotArgs.?CrossPlotProps;
plotArgs.LabelAS = true;
plotArgs.clabel... |
08875431ea0ae1429d8492e1dd58fbda2aa734a0e5de9f7d027ba6e07197c7f6 | MATLAB | 2,639 | 77 | addpath('./utils');
%%%%%%%%%%%%%%%%%%%%%%%%% Substacks Parameters%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
substack_depth = 61;
overlap = 0;
z_sampling = 1;
dx = 11;
Nnum = 11;
range_adjust = 0.9;
rotation_step = 90;
rectification_enable = 1;
rotation_enable = 0;
complement_stack = 1;
flip_x = 0;
flip_y = 0;
flip_z = 0;
save_p... |
fb5f7987de014b7845502b207c041b3020b4491fc59a6203ab9b2a32c9863793 | MATLAB | 2,641 | 117 | function [y,xf,cf,t] = ERBgram2(x,fs,compress,lowfreq,numchan,smoothcut,envcut,toPlot)
% function [y,xf,cf] = ERBgram2(x,fs,compress,lowfreq,numchan,smoothcut,envcut,toPlot)
% Plots a gammatone filterbank output of signal x, plus marginal spectrum
% and envelope.
% fs: sampling frequency [default 44100]
% compress: app... |
b858db0c4479aa6642e9288a6bc8d82d2ced366508d4841e07c0a1aaf32e4612 | MATLAB | 2,645 | 95 | function [log_rate, xx, R] = computeLogRate_host_v2(obj, params)
obj.setupComputeStructuresHost();
LL_info = obj.LL_info;
X_groups = obj.X_groups;
X_lin = LL_info.X_lin;
Y = LL_info.Y;
J = numel(X_groups);
D = [X_groups(:).dim_D];
A = [X_groups(:).dim_A];
T = size(Y,1);
P = size(Y,2);
isPop = P > 1;
%% linear term
... |
6a2aabe4be259e664747c7360d68be316056ba06036f1780a53f9fdb2d36b89c | MATLAB | 2,648 | 81 |
%==================== MF3D_PlotResponses_PCAIdentity.m ====================
% Plot face-space object tuning for STS cells tested in 'StereoFace' pilot
% experiments.
%
%==========================================================================
close all
clear all
%================= SET PATHS AND LOAD DATA
if isma... |
f94beab0d8e12b078a9413cc77227928f91e845e68e7f9b5e97b128a20801132 | MATLAB | 2,652 | 81 | function [VG] = fast_HVG(signal_var,coords_var,weight)
% Code edited from the following: https://www.mathworks.com/matlabcentral/fileexchange/72889-fast-horizontal-visibility-graph-hvg-for-matlab
%
% Implementation of horizontal visibility graph based on:
% Luque, B., Lacasa, L., Ballesteros, F., & Luque, J. (200... |
129bd094ef431986602534bb2018f4e7e51d71307b7aa64e562ce1a94eddd463 | MATLAB | 2,653 | 72 | % Get the number of sessions per animal segmented by the taste quality
util.clearAll;
cur_save_dir = fullfile(util.get_paths().figs,'betas_taste_animal');
util.mkdir(cur_save_dir)
% Get the beta tables from matfiles
beta_tables_taste = util.load.all_taste_betas().combined;
%% return locations of which set for all rows... |
6df33fe32d09f1b9a723e2989beb2abd44ee642d8bd155e6930c8c52b7ab8ac9 | MATLAB | 2,654 | 92 | % PURPOSE: Creates default Y ticks for EStudio plotting GUI
%
% FORMAT
%
% def = default_amp_ticks_viewer(yrange)
%
% INPUTS
%
% yrange - min and max ERP amplitudes [ymin ymax]
%
% OUTPUT
%
% def - tick values to show in Y axis (string via vect2colon)
%
% *** This function is part of ERPLAB Toolbox ***
% Auth... |
1ee853c44e49c86b1c01098f14d82a1bef78a0840d9f356f24ad97c70b53a10a | MATLAB | 2,657 | 82 | function [order, meanMag, meanDir, fullStruct] = orderParameter(vx, vy)
% ORDERPARAMETER calculates order parameters of a vector field.
%
% INPUTS: VX and VY are NxMxtime vectors giving the x and y components of
% the vector field. If VX and VY have more than 3 dimensions, extra
% dimensions will be reshaped into t... |
56269850d9d517dd318192866b018b3e6edb5e6a64efbc7bc60fa67affb219f5 | MATLAB | 2,657 | 84 | function decoder = train_probClass(cfg0, X, Y)
% [decoder] = train_probClass(cfg, X, Y)
% Trains a multiclass probabilistic classifier. It (if I'm not mistaking) is identical to logistic
% regression under the assumptions that 1) the data within each class are Gaussian distributed
% and 2) the covariances are ... |
9f228a4f122b05a27adce76f506f04502f4d33c1b9635b8ea4f3f74b3247d0bb | MATLAB | 2,657 | 67 | function [ DOM ] = CreateColladaFile( )
%CREATECOLLADAFILE Summary of this function goes here
% Detailed explanation goes here
DOM = com.mathworks.xml.XMLUtils.createDocument('COLLADA');
DOMNode = DOM.getDocumentElement;
DOMNode.setAttribute('version', '1.4.1');
DOMNode.setAttribute('xmlns', 'ht... |
f974eab516404c7ac3e54cb4c80c4352cb2f918a32188cc55b07091d36b6e0cd | MATLAB | 2,662 | 125 | function h = PlotRaster(varargin)
% PlotRaster(raster,values)
% PlotRaster(ax,raster,values)
% PlotRaster(...,colors)
% h = PlotRaster(...)
%
% Plots raster (a cell array of spike times relative to some event onset)
% against associated values (numerical array matching size of raster) on
% the y axis.
%
% colors can... |
9c51178281e4527022c8298758abe5f42b19e5e0f4d7b4490aa1cf72a925d92b | MATLAB | 2,664 | 96 | function varargout = ep_CompiledProtocolTrials(protocol,varargin)
% cp = ep_CompiledProtocolTrials(protocol,varargin)
% [cp,fail] = ep_CompiledProtocolTrials(...)
% return and/or view compiled protocol trials
%
% Parameter ... Value
% showgui ... true/false (default = true)
% trunc ... truncate to some sca... |
268cd386cc098e3a9a51d7e0047385847b798768127a0b730334acb3b9f72e28 | MATLAB | 2,667 | 78 | function show_clusters(spikes, clusters, alt_assigns)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% show_clusters -- creates a figure to plot various statistics of a set of clusters
%
% Usage:
% show_clusters( spikes, clusters, alt_assigns )
%
% Description:
% Builds a figure with... |
ad1a20a19395bf0c05635278d72086cc04507aa9ed19fae01507b074b7ec8d88 | MATLAB | 2,668 | 94 | clc; clear; close all
Fig7a=figure();
Ntrials=5e3; %number of learning cycles
N_mu=500; %There are \mu independent embedded patterns, 500 simulations (number of simulations)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%R=1
yline(1,'--','LineWidth',2,'HandleVisibility','off');
hold ... |
9dc8ab0acfb7bcac7380aad6654ef645199808c727a3f827eacd7a220d77b8dc | MATLAB | 2,671 | 104 | classdef o_EEGDATA < handle
properties
ALLEEG
EEG
CURRENTSET
count_current_eeg
eeg_panel_message
eeg_two_panels
Reset_eeg_paras_panel
end
events
alleeg_change
eeg_change
current_change
count_current_eeg_ch... |
0e832b0b8c25df36bc13abe60d8b70700d5d3557e84bed6b2d572c4771ea291a | MATLAB | 2,672 | 95 | function [t] = ieeg_curry2tsv(t1File,pomFile)
%
% Function writes a tsv file with electrodes names and xyz coordinates that
% should match the T1.
%
% Inputs
% t1File: name of the t1File that was used to localize electrodes
% pomFile: name of the .pom file created by Curry with electrodes in XYNo coordinates
%
% O... |
79f97f2cee462386d5fff9fe7cdded75216a2c043ca301587481aea2b1948e78 | MATLAB | 2,674 | 69 | function invariants = compute_invariants(model)
% function compute_invariants()
%
% returns the invariants derived from the estimated D and C tensors
% reshape model for convenience
siz = size(model);
mreshape = reshape(model, prod(siz(1:3)), 28);
% extract D and C & change units
D = mreshape(:,2:7) * ... |
738438158e46e8b2c3519a7d8b1a290e5a4052e8a23c0dc4504b6c34746eacee | MATLAB | 2,677 | 83 | function tptilefigs(tile,border)
% Tiles all figure windows except main TP analysis windows
% (twophotonbulkload and analyzetpstack).
%
% GS / modified tilefigs script below:
%
% <cpp> tile figure windows usage: tilefigs ([nrows ncols],border_in pixels)
% Restriction: maximum of 100 figure windows
% Without arguments,... |
459cd5bac364fc65569471e42f86aa0861201a6633ab556ec15b76450d69e353 | MATLAB | 2,683 | 68 | function Dist = lme_mass_RgDist(Surf,maskvtx,vtxInd,Dtype)
% Dist = lme_mass_RgDist(Surf,maskvtx,vtxInd,Dtype)
%
% This function computes the distances among all vertices inside a region.
%
% Input
% Surf: Triangular surface. It is a structure with Surf.tri = t x 3 matrix
% of triangle indices, 1-based, t=#triangles... |
9a32130ae69a083bb310a4a4c19b75a46547947d6cd66b70ba5446bb4a2ca6d3 | MATLAB | 2,683 | 108 | function [C,dX,X,Error]=ReadMesh(Set)
% Reads Mesh data from GID datafile using 'embryo' problemtype
% OUTPUT:
% C(e,:)=connectivity of element e
% dX=mean size of one element
% X(i,:)=(x,y,x) coordinates of node i
Error=0;
if Set.Dimensions==2
dX=Set.dx*[1 1];
nx=floor(400/dX(1));
ny=floor(72/dX(... |
afeaee36af57c5f18ce87ac80c8d3f40d4c55927cf287902438203e08068f627 | MATLAB | 2,687 | 87 | function [avgFR,seFR,Ft2,Rt2,Ft2ciL,Ft2ciH,TS,dfnum,dfden]=DecodeStats(FR,evt0,reg)
% Fisher F-test based classifier/decoder
%
% (c) 2014, Daniel Durstewitz, Dept. Theoretical Neuroscience, CIMH
% Mannheim/ Heidelberg University
% Edited by Aleksander PF Domanski PhD UoB 2015
% aleks.domanski@bristol.ac.uk
%
% Input Va... |
92ca30b7ed67fd8343f1eaa2ccc07c757ecdc9c14395fd4700d1d354e88af1ed | MATLAB | 2,688 | 82 | % UNDER CONSTRUCTION
%
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the Univers... |
553cd20ea2c54f954106351e07d63a7ed5d1f7df11e5945aec449c69492763d0 | MATLAB | 2,690 | 84 | clear
subjfolder_task = dir('F:\fMRI_QC\fmri-open-qc-task_bias_corrected\sub*');
for subji = 1:length(subjfolder_task)
rp = load(['F:\fMRI_QC\fmri-open-qc-task_bias_corrected\' subjfolder_task(subji).name '\func\rp_' subjfolder_task(subji).name '_task-pamenc_bold.txt']);
fd_trans = fd_calc(rp(:,1:3));
fd_... |
2c95d827712d8f28638b5dda3404a0038bd1083d01dd716a616481c392aa3721 | MATLAB | 2,691 | 79 | function [ims,channels] = tppreview_filter(dirnames, tpparams, channellist, parameters, shortname, dirname)
channels = []; fnameparameters = {};
% lets find parameter files, get the file name prefix pattern
for j=1:length(channellist),
good = 0;
try,
myfnameparameters=tpfnameparams(dirnames{1},channe... |
303529f1de8ba065400767c757dd9a43334577e3ecd5f4fce2172b08c529bcbe | MATLAB | 2,696 | 73 | % PURPOSE: Simple function to squeeze your EEG event codes.
% The number of apparition of each code (eventtypes) is accumulated into a counter (histo).
% Useful for counting a histogram of your event codes (you have to work with EEGLAB/ERPLAB of course).
%
% FORMAT:
%
% [eventtypes histo] = sque... |
b023a61c6d76b9a9b8a5295631a76c553c8fe206d31b4cf0aac56e57eb83428f | MATLAB | 2,697 | 113 | %% Read a PLX file and estimate how many spikes are likely to be missing based on thresholding errors
% Fits a normal distribution to peak amplitudes of spikes and estimates how
% many peak amplitudes would be expected above the threshold. DJS 5/2016
[fn,pn,fi] = uigetfile('*.plx','Plexon File');
plxfilename = fullfil... |
731d8d9572aedd11f293912e0309ee028dc1eb5d69dafce1946f939f0a4ea67d | MATLAB | 2,699 | 85 | % UNDER CONSTRUCTION
%
% subroutine for pop_summarizebins.m
%
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB ... |
8f9725b22c8dd9e7b6a0a7adf026697bcbb34b16c74dac699bfbd608e6965336 | MATLAB | 2,699 | 84 | function plot_selectivity_and_recruitment(model, Q)
if nargin == 0
model = select_and_load_model();
end
if ~exist('Q', 'var')
Q = linspace(0, get_max_threshold(model));
end
[fascIdsByAs, activeSites] = load_active_sites(model.paths);
elecIds = unique([activeSites.elecId]);
separateElectrodes = nu... |
850c209d11dcdc632638b6f775c18092b9316d0f2362115254ca4339e0ee9d23 | MATLAB | 2,703 | 76 | function checkPriors(data,options)
% this runs a short test whether the provided priors are functional
%function checkPriors(data,options)
% concretely the priors are evaluated for a 25 values on each dimension and
% a warning is issued for zeros and a error for nan and infs and negative
% values
if options.logspace
... |
5efc6c0288194b86379ab218d678326c1803e6b5d672d1b16a32bef36bcb7bf1 | MATLAB | 2,705 | 94 | function [ verts,normals,Faces ] = HemispherePatch( numPts, radius, axis )
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
axis = axis ./ norm(axis);
RhoStep = (pi/2) / ((numPts/2)+1);
ThetaStep = (2*pi) / numPts;
numVerts = numPts * (numPts / 2) + 1
vert... |
633ca3ff88f968ad14741ecca3474797083ba7d5cdd95d8701233b275d5e27df | MATLAB | 2,707 | 111 | function [A_hat, E_hat, iter] = inexact_alm_rpca(D, lambda, tol, maxIter, verbose)
% Oct 2009
% This matlab code implements the inexact augmented Lagrange multiplier
% method for Robust PCA.
%
% D - m x n matrix of observations/data (required input)
%
% lambda - weight on sparse error term in the cost function
%
% to... |
302044e2973cc3d02b6dfbb862c13af7e5a1cfdcea834309cded809232d1f9f7 | MATLAB | 2,711 | 69 | % generate test diffusin MRI data for TOD prediction uisng trained neural network
clc;clear;
% because of the memory limitation, we segment the data into several slabs to run.
% Users can update the code to remove the slab segmentation.
repeat = 1; %repeat is the slab number
sample_img = 1;
function flag = gener... |
2b56cf3dc1900aae9aa80fa79a51d7b953317c2acc8e95955003cb68d7fc67ee | MATLAB | 2,712 | 81 | function y=RoundDecimalSD(x,n,method)
%ROUNDSD Round with fixed significant digits
% ROUNDSD(X,N) rounds the elements of X towards the nearest number with
% N significant digits.
%
% ROUNDS(X,N,METHOD) uses following methods for rounding:
% 'round' - nearest (default)
% 'floor' - towards minus infinity
% 'ceil' - t... |
029b47bf666952aa281c90c85cd2090522609a6c8b7b76bae90389814a13fe04 | MATLAB | 2,713 | 70 | % Goal: Do an anova test to find regions with correlations affected by the taste
%% Setup
util.clearAll;
cur_save_dir = fullfile(util.get_paths().figs,'ANOVA_correlations');
util.mkdir(cur_save_dir)
% Get the beta tables from matfiles
beta_tables_taste = util.load.all_taste_betas().sep;
%% get the Z transform of the c... |
e433afde13382f9f2f7f0e2d029f0ab9816a6b5d50b694ceeec6d9020f0c9c6b | MATLAB | 2,714 | 104 | %
%
% Created:
% 2021-06-??: Jennifer Bizley
% Modified:
% 2021-06-14: Stephen Town
% - Added column headers and documentation
% - Implemented correction for logging error in BlockWE-127 in data
% - Added consistent column headers to source data
% - Saved concatenated data as csv file
cd... |
80563dbc3728a3406809d74e48e8f1e34d3e95dc5fcac347a8b441ba6ea9bd1e | MATLAB | 2,716 | 88 | function [ims,channels] = tppreview_rgb(dirnames, tpparams, channellist, parameters, shortname, dirname)
channels = [];
% lets find parameter files, get the file name prefix pattern
% allow user to choose R, G, and B image; user can choose among other preview images from directories recorded at the same time
% ... |
d51034147f99928e5ca5738602cfd3229c8e55f227211d1c72437d34ee98a40f | MATLAB | 2,716 | 76 | % Magno bar fixation analysis script - originally written by MR 07/27/2020
% Adapted by DL 12/2021 and Last Updated by DL 07/2022
clear ; clc; close all;
root = 'C:\Daniela\Data\Ir68aKir_SD\'; % where the angles of heading trajectory are saved
dirAnaly = 'C:\Daniela\Data\Ir68aKir_SD\angHeadCircAnaly\... |
4905330945c3baaf720dbb9daa78daeadec840c49b39676dd5b64c9af2172da5 | MATLAB | 2,719 | 70 | function [DOM, ParentNode, Node] = AddColladaNode( DOM, ...
ParentNode, ...
StructID, ...
GeometryTarget, ...
Mater... |
dd985a785b53fdb3ab92522e40926c642f3dd4178f1d6c7521a7edf8837e2148 | MATLAB | 2,720 | 97 | %Test2 expects two variables to be present, Verts and Links
function Test2(Verts, Links)
nmPerPixel = StructureObj.nmPerPixel;
nmPerSection = StructureObj.nmPerSection;
iID = 1;
iParentID = 2;
iX = 3;
iY = 4;
iZ = 5;
iRadius = 6;
iType = 7;
iSectionX = 8; %These are the co... |
414c2dd3cf891b6689ad1b0e6643966ddeb64eddf32376524d0e514f1c8466e7 | MATLAB | 2,722 | 93 | % ALPHA VERSION. ONLY FOR TESTING
%
% Usage:
%
% >> ERP = smootherp(ERP, spanvalue);
%
%
% Inputs:
%
% ERP - input average (ERPLAB's) erpset
% spanvalue - number of points used to compute each new (smoothed) sample. It must be odd
%
% Outputs:
%
% ERP - (smoothed) erpset
%
%
% Also... |
5000708382fcb6009258e81b657db4eb501b807711e06277aa6d26b8e794fcfd | MATLAB | 2,728 | 89 | function [C,X,Bij]=GenerateMesh(dx,dy,dz,nx,ny,nz)
% USAGE:
% [X,C]=GenerateMesh(dx,dy,dz,nx,ny,nz)
% INPUT:
% nx = number of elements (divisions) along x (Horizontal)
% dx = size of each element along x
% ny = number of elements (divisions) along y (Vertical)
% dx = size of each element along y
% nz = number... |
7e141b0b1dcd4af9243973c5e71136f3f45854a8a33d3db5c78a51e0fe10aae2 | MATLAB | 2,728 | 113 | function [] = test_group_lasso()
clc;
clear;
close all;
%rng('default');
%% Set algorithms
if 0
algorithms = gd_solver_list('ALL');
else
algorithms = {'SHOOTING-GROUPLASSO'};
end
%% prepare dataset
if 0
data = importdata('d... |
2291589a32360137fa0654490296324a230515ddd9f89db331d0b36d040154c5 | MATLAB | 2,729 | 104 | function [detvtx,sided_pval,pth,m0] = lme_mass_FDR2(pval,sgn,maskvtx,rate,tail)
% [detvtx,sided_pval,pth,m0] = lme_mass_FDR2(pval,maskvtx,rate,tail)
%
% Two-stage FDR approach to achieve tighter control of the FDR. This
% procedure is more powerful than the original FDR procedure implemented in
% lme_mass_FDR.
%
% Inpu... |
2387985acfde0119dd4564508c5d2e2e1e1395164afc19c26aa6ea08b6735302 | MATLAB | 2,729 | 78 | % Plot the L/R preference of each single unit.
%
% Aleksander PF Domanski PhD UoB 2015
% aleks.domanski@bristol.ac.uk
%
clear
fn='JaroslawLONG2_PFC_iFR50.mat';
% fn = 'JaroslawLONG2_PFC_iFR50_behavOnly.mat';
critCvBW=1e6; % critical max bound on kernel width drift over time (variance)
minFR=0.01; % minim... |
6246c98e9c9fb1a6b982f422db6d0ba1e18203b64c61b7a2c4184ff7598b3305 | MATLAB | 2,729 | 96 | load(['../data/behaviorData.mat']);
tmp = zeros(1,500);
hori_p = [tmp repmat(16.003,1,700)];
hori_n = [tmp repmat(8, 1, 700)];
vert_p = [tmp repmat(0,1,700)];
vert_n = [tmp repmat(-13.86,1,700)];
for n = 1:14
n
tDur = [1:1200];
valid_u = cat(3, hori_p-Sub(n).dir(1).valid.hVel100, vert_p-Sub(n).dir(1... |
0f4ab32675b6199c1bf99c4b6ae67a5b6a65c5fc1d85101f6f9b1d38379f781c | MATLAB | 2,732 | 77 | function [filtx,filtstd,filtstderr,newimage] = prairieviewoptfilter(slowdir, fastdir, channel)
% PRAIRIEVIEWOPTFILTER - Creates an optimal filter for prairieview files
%
% [FILT,FILTSTD,FILTSTDERR]=PRAIRIEVIEWOPTFILTER(SLOWDIR,FASTDIR,CHANNEL)
%
% Creates an optimal linear filter for data acquired quickly in
% Prai... |
bcdcf749249d1883fcfb32f4ee40fa542ab631bc835cd69e6a504a0eb6279a83 | MATLAB | 2,733 | 103 | function ProgressBar(currIdx, endIdx, varargin)
p = inputParser;
addOptional(p, 'TotalUpdates', 1000);
parse(p, varargin{:});
persistent ProgressBar
if currIdx == 1 || isempty(ProgressBar)
ProgressBar = struct;
ProgressBar.Start = tic;
ProgressBar.PrevLineLength = 0;
end
if endIdx > p.Results.TotalUpdate... |
d8a24074ffc90fab51a6b1c1a0e981040359f26f711354ca25064ee3984f579a | MATLAB | 2,733 | 86 | inputname='Gi17546';
timepoint='wk7';
%detect stops(no=0, yes=1)
stopdetect=1;
inputname2=strcat(inputname, '_stimtb.mat');
load(inputname2)
%time resolution for z-score analysis (+/- in sec)
timeres=1
%extract value for control period
d=0;
for c=1:length(LocoSynth);
if LocoSynth(c).time==timepoint;
... |
71066b8fc15326443e5bd21f2413b7a6be3e8b989a3457ce194474f86bfc8960 | MATLAB | 2,734 | 66 | %% load dependencies
addpath(genpath('/scratch/janine.bijsterbosch/WAPIAW_2/heterogeneity/src_matlab'))
basedir = '/scratch/janine.bijsterbosch/WAPIAW_2/heterogeneity';
sublist_name = 'sub_list';
target = 'x20016_2_0';
restdata = 'resting_state_separate_proj';
disp(['base directory is ', basedir])
disp(['target = ',... |
3e137299c4e0810d217325d78d4a4a0f7fed2b1f400cc110120d61adc81fbbbc | MATLAB | 2,735 | 100 | % PURPOSE: updates MVPCset menu
function updatemenumvpc(ALLMVPC,overw)
if nargin<2
overw=0; % overwrite MVPCset menu? 0=no; 1=yes; -1=delete
end
%
% Checks MVPCset menu status
%
MVPCmenu = findobj('tag', 'mvpcsets');
statbestm = get(MVPCmenu, 'Enable');
if strcmp(statbestm,'off')
set(MVPCmenu, 'Enable... |
e08d993df7976a29c186bf038124a9fffd85ea9e25eb799a8d6ce04a1918558c | MATLAB | 2,736 | 71 | function [numFibersAtPercepThreshold, placements, percepThresholds] = num_fibers_for_perception(nerveModel, electrodeType, plot_all)
% returns numFibersAtPercepThreshold(iOrientedPlacement, iElectrode, iAS)
% num_fibers_for_perception(1, 'D:\');
nrnModel = 'MRG';
percepThresholds = load_percep_thresh(nerveModel);... |
976d1bed03e4ccb2a6fe2a1127caa11b1a282d1457f5e267a8a7147e0f4b0664 | MATLAB | 2,737 | 100 | % PURPOSE: updates BESTset menu
function updatemenubest(ALLBEST,overw)
if nargin<2
overw=0; % overwrite bestset menu? 0=no; 1=yes; -1=delete
end
%
% Checks BESTsets menu status
%
BESTmenu = findobj('tag', 'bestsets');
statbestm = get(BESTmenu, 'Enable');
if strcmp(statbestm,'off')
set(BESTmenu, 'Enabl... |
03a0417fa0465e148d747a504a4981c1c4894425bf526d8eaf4c9cb7df135ea3 | MATLAB | 2,738 | 126 | %% Generate random colors for 3d Catlas in Slicer 3D
% This script will read the specified atlas txt file and generate random
% colors and save it as a new file called 'CATLAS_COLORS.txt' in the pwd.
% Manually copy this new file to the Slicer 'ColorFiles' subdirectory.
% Slicer 3D will have to be relaunched if it is a... |
b9ec9298a74d1b1b77b406435945292a7bc8e0f456a38c42b7830559d643083f | MATLAB | 2,739 | 93 | function [datobs, datrnd] = cluster_test_helper(dat, nperm, diffstat)
% CLUSTER_TEST_HELPER is a helper function for doing cluster-corrected
% permutation tests in arbitrary dimensions. The randomizations are
% generated under the assumption that input dat was computed using a paired
% statistic T for which T(a,b) = -T... |
bb09da5f59fe54a64d525b42fa73be2c02fe242bdb291f14371e35ff65fec0bd | MATLAB | 2,741 | 88 | outname='Gi17546';
outname2=strcat(outname, '_stimtb.mat');
%%last update october 21, 2020
nbpulse=1;
%check the directory, count nb of file
datalist=dir;
nbfile=length(datalist);
nbelem=0;
LocoSynth=[];
%read directory. How many file do we have? create a database.
for a=1:nbfile
if datalist(a).isdir... |
26b1877f907cc7e8b7c87bfffe570cec1379e822904e351265e71f3f4d3db6d7 | MATLAB | 2,745 | 94 | function TRIALS = TrialFcn_IncrementReward_EXAMPLE(TRIALS)
% TRIALS = TrialFcn_IncrementReward_EXAMPLE(TRIALS)
%
% Increases reward size (within bounds) with consecutive hits.
%
% A miss resets the reward size to a minimum specified value.
%
% See inline comments for more details.
%
% Daniel.Stolzberg@gmail.com 11/2015... |
db73b74208d31906f1c8507fa8e13005a708243c1c6e6ec896ec75cd0d23f9d3 | MATLAB | 2,745 | 95 | function varargout = PLX2MAT2(plxfilename,trodes)
% [units,ts] = PLX2MAT2(plxfilename)
% [units,ts] = PLX2MAT2(plxfilename,trodes)
% [...,waves] = PLX2MAT2(plxfilename,...)
% [...,waves,channels] = PLX2MAT2(plxfilename,...)
%
% Reads Plexon PLX files
%
% If 'trodes' is not specified, all channels from the plx ... |
92dda66f390e6548cd004183d573026d51acd5007b4828663ec99c4d4afac92d | MATLAB | 2,746 | 87 | function p = plot_detection_criterion(spikes,clus)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% plot_detection_criterion - histogram of detection criterion applied to
% each waveform
%
% Usage:
% [thresh_val,m,stdev,missing] = plot_detection_criterion(spikes,... |
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