sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e73071a092a220956427b128f213293d68c361a613a03f777827532a9ef53a2c | MATLAB | 3,229 | 83 | function [TmtxS,iFRs,EvtLs,EvtTs,usel_out]=SelTrials(fn,twin,SelectedUnits,iFRtype,trials)
% Select specified cells from PFC and HC data sets & cut out trial periods
%
% Aleksander PF Domanski PhD UoB 2015
% aleks.domanski@bristol.ac.uk
%
% Corrects for mismatched unit numbers if using data generated on Blue Crys... |
96b655bf13fea9671d9e116b32ecd44c8de00b49f492134a4a567c1c33201bfd | MATLAB | 3,230 | 94 | function [stats,st] = lme_mass_fit_vw(X,Zcols,Y,ni,maskvtx,fname,prs,e,Xrows)
% [stats,st] = lme_mass_fit_vw(X,Zcols,Y,ni,maskvtx,fname,prs,e,Xrows)
%
% Vertex/voxel-wise linear mixed-effects estimation.
%
% Input
% X: Ordered (according to time for each subject) design matrix (nmxp, nm
% total # of maps, p # of fixe... |
ba9e66c18a5e6277d51c0caf54e05b5ac74dfec3955904054a9bcbab1e2a0ed0 | MATLAB | 3,236 | 78 | function [c,p] = plotBehFig(dat,behFigP)
k2plt = behFigP.k2plt;
%%
behFigP.plt.alph = .4;
wpatch = 0;
mainFocusOn = 'sound';
switch dat.name
case 'Body motion'
mainCol = ones(size(behFigP.SndColors)).*[0 0 1];
otherwise
mainCol = ones(size(behFi... |
146ab09b77525195fda4153ff9b88324fb6cb6435d440609390cc81d2f56b581 | MATLAB | 3,238 | 97 | function [on,off] = ResponseLatency(psth,binvec,thresh,test,select,minsamps,gsamps)
% [on,off] = ResponseLatency(psth,binvec,thresh)
% [on,off] = ResponseLatency(psth,binvec,thresh,test)
% [on,off] = ResponseLatency(psth,binvec,thresh,test,select,minsamps)
% [on,off] = ResponseLatency(psth,binvec,thresh,test,select,min... |
1e5f397f6c5ff631bc14ef1844ba27da21d2dd68a4d2e420944df3e3dba45179 | MATLAB | 3,244 | 98 |
%==================== ObjectSizeplotSuppFig4.m ====================
% Plot tuning face response and next best object for each neuron
% Plot Cell 17 and Cell 59 to match figure
%==========================================================================
close all
clear all
%================= SET PATHS AND LOAD DAT... |
503555062cb6f52f28c74db9c4028fae270a8dabb2c23145d5b0189c6b437cdc | MATLAB | 3,244 | 123 | function v = TDTpartag(AX,TRIALS,tagname,value)
% v = TDTpartag(AX,TRIALS,tagname,[value])
%
% Inputs:
% AX ... ActiveX handle
% TRIALS ... TRIALS structure found in global structure RUNTIME. If
% running multiple subjects at once, then pass only the
% TRIALS index of the subject ... |
65e99be855b4e9e1bb090f747287b20b3a18f15198e5d0395cc35d5d2f030b1c | MATLAB | 3,244 | 84 | function [qcontributions,q,B] = fcn_get_q(W,M,B,gamma)
%%FCN_GET_Q get modularity of partition
%
% Q = FCN_GET_Q(CI,AIJ) given a partition CI and adjacency matrix AIJ,
% compute the modularity score of the partition. This script is
% applicable to only symmetric networks.
%
% Inputs: W, ... |
fe0d822166001851b84e659464e40bab8e34d2982cab6433b5db7b6d06f820cb | MATLAB | 3,244 | 104 | function [ s, gen_p1, gen_p1g2, gen_p2g1 ] = GenRandSeq( L, p )
%GENRANDSEQ is a simple function generating a random sequence from
%specified theoretical (events or transitions) probabilistic rules.
% - "L": a Nx1 vector (with N being the number of chunks) specifying the
% length of the chunks
% - "p": a Nx... |
20ba428344a8062e855def97debe93de489fa1667eee564a8c7531212e54b080 | MATLAB | 3,245 | 142 | clear all
handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\FM_wave_test.rcx';
%Load in speaker calibration file
% [fn,pn,fidx] = uigetfile('C:\gits\epsych\UserFiles\SanesLab\SpeakerCalibrations\*.cal','Select speaker calibration file');
fidx=1;
pn = 'C:\gits\epsych\UserFiles\SanesLab\SpeakerCalibrati... |
11673d092447d3c4733391fa5e88a06f3de07611b47177bbf8c68f6966563e2e | MATLAB | 3,246 | 109 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 2 - figure supplement 2
clear all; close all; clc;
% GLM1
nPartic = 31; % nr of participants
regr... |
203e624e71cfe863cf800c54935a1e40e5d26eedf4261f2de6e38a3123f0b794 | MATLAB | 3,246 | 138 |
%function FM_sweep_testing()
% close all;
clear all
clc
%---FLAGS---%
sub = 1;
MaskerRate = 32;
SignalRate = 128;
AMphase = 0;
% Define RCX file
handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\Sandbox\JDY\AMRate_ForwardMasking_buffer_v2.rcx';
%Load in speaker calibration file
pn = 'C:\gits\epsych... |
9a281a606eca4cbca8db7789f2296388e6d22444661c08b4d27aa8f69bee7049 | MATLAB | 3,247 | 100 | % FADE-npsy: Figure 3+4
% _
% written by Anni Richter <arichter@lin-magdeburg.de>, 15/08/2022
% reworked by Joram Soch <Joram.Soch@DZNE.de>, 09/02/2023, 22:57
% reworked by Anni Richter <arichter@lin-magdeburg.de>, 22/02/2023
clear
close all
%%% Step 1: load and assign data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
ff43e4b5bfd2da77b45cde681290396dfa17c4bcfa6ae3c92741639b2d39058f | MATLAB | 3,247 | 84 | function D = homogenise2DSubproblem( subproblem, boundary_type, skin_map )
% This function takes an input subproblem (specified in the same format as
% a full problem object) and solves it for two different imposed gradients,
% thus providing the requisite information for determining the effective
% conductivity tenso... |
85e297a5858fd4626dd7f2209c127098633290be902ec77b2857afec24545cc5 | MATLAB | 3,261 | 68 | function h=subtightplot(m,n,p,gap,marg_h,marg_w,varargin)
%% This function has been adopted and edited from a matlab file exchange function. The original function is freely avalibale at the following: "https://www.mathworks.com/matlabcentral/fileexchange/39664-subtightplot".
% Functional purpose: A wrapper functi... |
cfdcc47f92d40fa6379bfb26f76b672d3469e596c0e7a6ce27581992b90e2497 | MATLAB | 3,261 | 104 | function v = readprairieconfig(filename)
% READPRAIRIECONFIG - Read all values from Prairie config file
%
% VALUES = READPRAIRIECONFIG(FILENAME)
%
% Reads values from a Prairie Technologies config file.
% Returns a struct with fieldnames equal to each parameter.
% Differnet categories (e.g., 'Main') are included... |
cc15bc744ad5e0480f208cb96caac96ceb10a6b78f92d497441c85551c341a7b | MATLAB | 3,263 | 130 | function [FracCorr FracCorrShuffCIL FracCorrShuffCIH]=DecodePredErrCrossTemporal_CV(FR,evt0,reg)
%
% (c) 2020 Aleksander PF Domanski PhD UoB
% aleks.domanski@bristol.ac.uk
% Input Variables:
% FR: Firing rate matrix [units,time x no. trials]
% evt0: Event category labels (either 1 or 2) [no. trials]
% reg: Re... |
d2ce7557d9fb4ef23d12cee63c722f6262ae772f57a1b206a9f454bd9b6f0f80 | MATLAB | 3,266 | 126 | function [Accuracy,ValErr,Momentum,L2Reg,InitLR,AUC,C,prb] = func_TrainModel(Parm)
%Train Model (training DeepInsight-FS)
% run Prepare_Data.m %TCGA RNA-seq data will be prepared using tSNE algorithm
% see Prepare_Data.m for details
curr_dir = pwd;
addpath(curr_dir);
Parm.fid=fopen('Results.txt','a+');
Parm.UsePrev... |
cdcb0fb8f79cccdf88cc7b58ce1d6d4aa6f3d099b4a819e177638afe603e4b66 | MATLAB | 3,268 | 95 | function [results] = spkHistPrior5(params, results, spkHistPrior_setup, addDPriorForWB)
% i.i.d non-mean Gaussian over spike history coefficients & constant
K = size(params.B,1);
K2 = K/2;
w_mu_idx = 1;
w_sig_idx = 2;
H = double(params.H);
w_mu = H(w_mu_idx);
log_w_sig = H(w_sig_idx);
if(K > 0)
b_mu_idx = 2 ... |
c4c3326d3fd73d60089fb44ada66bba4a1aed358291879fba2c204d7a6bd715e | MATLAB | 3,273 | 75 | function [TmtxS,iFRs,EvtLs,EvtTs,usel_out]=SelTrialsCells(fn,twin,minFR,critCvBW,iFRtype,trials)
% Select cells from PFC and HC data sets & cut out event periods (trial case)
%
% (c) 2014 Daniel Durstewitz, Bernstein Center for Computational Neuroscience, CIMH/ Heidelberg University
% Edited by Aleksander PF Domanski P... |
be46bab2e3d6c98cb6493f9f32733aff042dbc8488cbe6c688cc9e1796e81ad0 | MATLAB | 3,274 | 85 | %This is a function that gets as input the flick data and then outputs
%response time, amplitude and direction. Created by Haleh Fotowat.
function [resp_time, Pmax, Pmin, PmaxminR, resp_amp, pm_amp, resp_dir,tail_dir_s,resp, pm_amp_isi,resp_dir_isi, resp_isi, resp_amp_isi, resp_time_isi,resp_ISI_cnt,time_window] = quan... |
70d5ca411030b3cbccc9a482fffa92355f0c150d5ae10a106fedffa50608e1a8 | MATLAB | 3,275 | 109 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 2 - figure supplement 2
clear all; close all; clc;
% GLM1
nPartic = 31; % nr of participants
regr... |
4834284eb0b62b73465b0f7cd5ae192210f34a95eee56ca8a2bd1adf6eaee5f8 | MATLAB | 3,276 | 81 | function [pval_elec_mat,hmask_elec_mat,names_elec_mat,idx_elec_mat] = ...
convert_chans_to_topo_matrix(pval_array,hmask_array,all_names)
% Convert the input data, whose row indices correspond to channels from a
% 64 EEG cap, by reshaping this first dim into a 2-way matrix accounting
% for the electrodes adjacen... |
3fc3c335c629e63d235de14422ad4906ffda1d124c31213fdc3152d0bcde5ef9 | MATLAB | 3,281 | 103 | function compare_clusters( spikes, show, alt_assigns )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% compare_clusters -- creates a figure to compare a set of clusters pairwise
%
% Usage:
% compare_clusters( spikes, clusters, alt_assigns )
%
% Description:
% Builds a figure with a ... |
6814e724c69e8a0b9ccde322921b301860d79459a9798aad89760e3f60ac1a7b | MATLAB | 3,281 | 91 | function bootstrap_CCA(sublist_name,target,restdata,bootstrap_index)
debug = false;
rng(bootstrap_index)
% sublist = 'sub_list_small'
% target = 'x20127_0_0'
% restdata = 'resting_state_separate_proj'
% bootstrap_index = 1
% set paths
addpath(genpath('/scratch/janine.bijsterbosch/WAPIAW_2/heterogeneity/src_matlab'))
... |
57c37f2e308a1e4817fd42b4a5a0876e816285f0139a506ebcd7bd3876a3ce3b | MATLAB | 3,282 | 106 | function [pval,rho] = SStat_PHTest(X,d,t,stats_PH)
% [pval,rho] = SStat_PHTest(X,d,t,stats_PH)
%
% Schoenfeld residuals test for the proportional hazards assumption.
%
% Input
% X: Design Matrix with the time-independent covariates. (mxp, m # of
% subjects, p # of covariates).
% d: Logical vector (mx1) indicating cens... |
6da45557d2902cf8b61a07b6f3f9900aad55a172de5e0bcc4dc03067006a62db | MATLAB | 3,283 | 90 | function plot_fascs_recruitment(model, Q)
% Can be ran without arguments
% Plotting of recruitment curves for all fascicles in electrode range
if nargin == 0
model = select_and_load_model();
end
if ~exist('Q', 'var')
Q = linspace(0, get_max_threshold(model));
end
%% get active sites and list of fasci... |
ba5cd40a7639c0743f8e391907b1ebb0d58fe0038d485debdfe3a5b3248adedf | MATLAB | 3,288 | 87 |
%==================== SizeRetSimulationPlot.m ====================
% Plot responses for each neuron to the equal retinal angle stimuli
% and plot simulations of the response of retinal angle and physical size
% single factor models as plotted in figure 2C
%============================================================... |
ff4b1f465081497a8f61bfe8fe49382e493dc77c520ab944e8d154310b7eefdf | MATLAB | 3,297 | 84 | function TSL_summary_demographics( )
% Compute the average demographics for the TSL experiment, after
% excluding participants.
all_subj_idx = setdiff(1:36,[1, 11, 15, 28, 33]) ;
% --------------------------------------------------------- %
% subj 1: 500ms stim
% subj 11: difficulty to feel cool (p... |
5b0e7d556871bbac780529e5ea5527fd0ff9ed5c876c73e1a6ca782cee7d25fe | MATLAB | 3,298 | 96 | %% BCI dataset, Ulster University
% preprocessing pipeline
% Writtern by Vahab Youssof Zadeh
% Update: 02/23/2022
clear, clc, close('all'); warning off
%% Initial settings
%- Brainstorm dir
bsdir = '/data/MEG/Research/BCI_Ulster/BCI5';
bs_path = '/opt/matlab_toolboxes/brainstorm3';
addpath ./functions
ft_path = '/op... |
8eec107edb6effa713b94c2d59fd04c492f8fda57043c8318abfce9ca4d81dbc | MATLAB | 3,299 | 83 | function [WAKEdiffspec_anim,NREMdiffspec_anim,REMdiffspec_anim,numDiffspecplotDoseAnim,Ps_Wake_Diff,Ps_NREM_Diff,Ps_REM_Diff]=Plot_SpecDiffs(numanim,DoseColors,DoseLabels,VStitles,FigureID,f,WAKEspec_dose_anim,NREMspec_dose_anim,REMspec_dose_anim,PlotConditions);
%%% This script plots the differences in spectral pow... |
6d0bd0689b4f1f06967e186da1ebb7104b2d18b5fc9c7d835a7b62a4fc91abca | MATLAB | 3,300 | 121 | % SINGLETRIALUCM
function [deltaV,V_UCM,V_ORT] = singletrialUCM(subject,trial,toplot,filename,dataType)
if dataType==0
global filtered blacklist MVCs time;
elseif dataType==1
global filteredLeft blacklistLeft MVCsLeft timeLeft;
filtered = filteredLeft;
blacklist = blacklistLeft;
MVC... |
ee44f32782cd6be09fa44ff8f343450c8270dbc507a854c35bbaaead9079b340 | MATLAB | 3,300 | 113 | %Test2 expects two variables to be present, Verts and Links
function Test3(Verts, Links)
dbstop if error
nmPerPixel = 1;%StructureObj.nmPerPixel;
nmPerSection = 1;%StructureObj.nmPerSection;
iID = 1;
iParentID = 2;
iX = 3;
iY = 4;
iZ = 5;
iRadius = 6;
iType = 7;
i... |
6663c36b1a5988b6f4152cb5b926c78bc49cfb0f410bac598dbae7e2456a4fca | MATLAB | 3,306 | 65 | clear all
addpath (genpath ('C:/Users/gyourga/Documents/code/NiiStat-master/'));
addpath (genpath ('C:/Users/gyourga/Documents/code/spm12'));
cd C:\Users\gyourga\Documents\code\acute_chronic
clipping = 0;
[filename1, pathname1] = uigetfile({'*.xls;*.xlsx', 'Excel file'}, 'Select dataset 1');
cd (pathname1);... |
93dbc54c4c7e6b5b91a646fb9cab52e735e8ab560550dc28483d09422177d390 | MATLAB | 3,307 | 108 | function [sel1, sel2] = match_str(a, b, fullout)
% MATCH_STR looks for matching labels in two lists of strings
% and returns the indices into both the 1st and 2nd list of the matches.
% They will be ordered according to the first input argument.
%
% Use as
% [sel1, sel2] = match_str(strlist1, strlist2)
%
% The strin... |
367537fded20b59a04fdbf36593c35eb166bf6f3e08e73f0baad5ec02f29c867 | MATLAB | 3,308 | 103 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 2 - figure supplement 1b
clear all; close all; clc;
nPartic = 31; % nr of participants
regresso... |
fa0b2ec8ed26b910dde5d306ed0d7bbcb2c464fb752b691157fa3d3cdb53379d | MATLAB | 3,312 | 113 | function clipT = LoadFeatures(self, clipT)
streams = self.ConfigFile.GetParams('Streams');
clipTCollapsed = CollapseClips(clipT);
reduceDim = false;
if self.ConfigFile.GetParams('ReduceDimensionality')
[RICAModel, ~] = LoadRICAModel(self);
if isempty(RICAModel)
reduceDim = false;
else
... |
2814792a03cae180f5310ccd95c3cc17c9326e7d9240f6ab3cc7c16588a2b89b | MATLAB | 3,315 | 86 | function [B,K] = evaluate_distonly_generative_model(A,Atgt,D,modeltype,modelvar,params)
% EVALUATE_GENERATIVE_MODEL Generation and evaluation of synthetic networks
%
% [B,E,K] = EVALUATE_GENERATIVE_MODEL(A,Atgt,D,m,modeltype,modelvar,params)
%
% Generates synthetic networks and evaluates their energy function ... |
0739987bf2a7e08837d023cf68aa000c56f1566143d072c9f2cfe64e4276ac6c | MATLAB | 3,316 | 113 | function [DataEEG, elecIndex]=ExtractTrialsMI(archive, opt, verbose)
%--------------------------------------------------------------------------
%Extract EEG trials from the data that have been converted from ov to mat.
% for MI. We are using only two type of codes:
% 770-rigth hand (MI)
% 772-tonge (REST)
%ou... |
534fe5a340a728c6ffe8ffb7679fa1a890c098917a92f04fa78ce5870b803368 | MATLAB | 3,319 | 274 | function cm_data = my_blues(m)
% Created from http://jdherman.github.io/colormap/.
cm=[...
0,0,0;
0,0,2;
0,0,4;
0,0,6;
0,0,8;
0,0,10;
0,0,12;
0,0,14;
0,0,16;
0,0,17;
0,0,19;
0,0,21;
0,0,23;
0,0,25;
0,0,27;
0,0,29;
0,0,31;
0,0,33;
0,0,35;
0,0,37;
0,0,39;
0,0,41;
0,0,43;
0,0,45;
0,0,47;
0,... |
628c12d575a11f8e04cd9dd92aa0c6aaba2898d4e3eb88af27554ea8f3c72ab3 | MATLAB | 3,319 | 89 |
%==================== AllSizeHeatmapandPlotFigure5.m ====================
% Find the mean response of each neuron to the expanded set of sizes
% and plots heat map of all baseline subtracted responses
% as well as the normalized response to each size across the population.
%==========================================... |
89a1a95128b964f519c9a2f7a5dd6540cdec766bab9fcb030b10d56f165fb6f5 | MATLAB | 3,320 | 114 | function [sID_ext,X_ext,d_ext,t_ext] = SStat_X_ext(sID,X,d,t)
% [sID_ext,X_ext,d_ext,t_ext] = SStat_X_ext(sID,X,d,t)
%
% Extension (by adding new rows) of a design matrix comprising only time-
% independent covariates to a design matrix for which time-dependent
% covariates can be easily added.
%
% Input
% sID: Subjec... |
5e318665c130fd0d807e9624835f29314b68458d6deaa7992a41cefd6fcbdd82 | MATLAB | 3,325 | 101 | function str_model = get_model_param_str(AboutFirst, learned_param, ...
decay, decayF, window, windowF, leaky_int, leakyF_int, window_int, ...
windowF_int, weight, prior_data, model_type,a_LR)
% Parameters describing the model specified by the arguments.
% decayF, windowF, leakyF_int, windowF_int:
% F... |
e15de985dd66561d3fe3d28a82e4702f4db482261f7ce8ec5c1e6e3932671076 | MATLAB | 3,325 | 130 |
function fileLines = FormatTable(t, varargin)
p = inputParser;
p.KeepUnmatched=true;
addOptional(p, 'Title', []);
addOptional(p, 'PrintOutput', false);
parse(p,varargin{:});
varNames = t.Properties.VariableNames;
tableColumns = cell(size(t, 1)+3, length(varNames));
for i = 1:length(varNames)
currColText = Form... |
728641d2311e3d4c406982db5d098270cebb1959b19228c0217fb2e0f8748da7 | MATLAB | 3,327 | 101 | function str_model = get_model_param_str(AboutFirst, learned_param, ...
decay, decayF, window, windowF, leaky_int, leakyF_int, window_int, ...
windowF_int, weight, prior_data, model_type,a_LR)
% Parameters describing the model specified by the arguments.
% decayF, windowF, leakyF_int, windowF_int:
% F... |
ab7623a6bbf18c9b49967cabe4dbe355d154a34c3cda007581bd0646598ab25e | MATLAB | 3,330 | 71 | %% Box Plots Plume Prob PCF
figure(106)
boxplot([PlumeProb_PCF_FH_Cond1,PlumeProb_PCF_SD_Cond1,PlumeProb_PCF_FH_Cond2,PlumeProb_PCF_SD_Cond2,PlumeProb_PCF_FH_Cond3,PlumeProb_PCF_SD_Cond3,PlumeProb_PCF_FH_Cond4,PlumeProb_PCF_SD_Cond4],'Labels',{'PCFFH Cond1','PCFSD Cond1', 'PCFFH Cond2', 'PCFSD Cond2','PCFFH Cond3','P... |
74addcf4a911da124880e97fb6ac65463f06f7bbaffb1b88686a3e4470694c91 | MATLAB | 3,332 | 98 | function [CVE,... time-dependent mean decoding score [No. Timepoints x 1]
Score... Time-averaged/Peak decoding score, depending on InfoCriteria [1 x 1]
] ... mean time-dependent decoding score [No. Timepoints x 2]
= RunDecodeGroupsStats( unitIds , nReps , Ltrials_ , Rtr... |
419be8b89b9ab43a1a69dfc1d87295c5109372a6f9c6cc2f7cc84dc3b49b39d6 | MATLAB | 3,334 | 100 | function tbwrite(table,cols,vecs,varargin)
% tbwrite Write to MySQL table [mym utilities]
% Inputs table - table name, string
% cols - list of input columns, (m*1) cell array of strings
% vecs - list of output vectors, (m*1) cell array of strings
% buffer - number of row... |
45719c93ae37fec6ca51a3e36d32526a2a4a429b2335ab78b1bbabd50b2ce78f | MATLAB | 3,336 | 109 | function [s,fa] = ssbloch(tr,te,fa,t1,t2s,pd)
% [s fa] = ssbloch(tr,te,fa,t1,t2s,<pd>)
%
% Steady-state Bloch Equation
% tr = repetition time
% te = echo time
% fa = flip angle (radians)
% t1 = T1
% t2s = T2 star
% pd = proton density (default = 1)
%
% Time units don't matter as long as they are consitent
%
% if fa=[... |
06d0cbb958202f3d927e23177011737f8bc274be80e1cd725411c7fddc0d65df | MATLAB | 3,337 | 78 | clear;close all;
files = dir('.\Matlab-CODE\Kim');
% Get a logical vector that tells which is a directory.
dirFlags = [files.isdir];
% Extract only those that are directories.
folder_list = files(dirFlags); folder_list(1:2) = [];
folder_dwi =['.\Matlab-CODE\Kim\'];
folder_tod = ['.\Matlab-CODE\Kim\Z_tod\'];
%%... |
56b5fad8fe54a8504f8593ade3998d46dba3f85e7e63cc8d643ee665832d78e9 | MATLAB | 3,338 | 88 | function [fibersAtPercep, fibersCenter, placements, endo, percepThresholds, expAS, sensation, idCross] = fibers_for_perception(nerveModel, factor)
% returns numFibersAtPercepThreshold(iOrientedPlacement, iElectrode, iAS)
% num_fibers_for_perception(1, 'D:\');
nrnModel = 'MRG';
if nargin < 2
factor = 1;
end
... |
5eb4f51951affd379e4036468394e050d1b683766ff7ef08dce3a3da22738931 | MATLAB | 3,339 | 106 | function ArtifactScanToolCompileLogs
% GET GENERIC PROJECT/SUBJECT/FILE INFO %
% project directory %
filedirs=uigetdir2;
savedir = uigetdir('C:\','Please select save directory');
if length(filedirs)==1
allDirs = genpath(filedirs{1});
allDirs = regexp(allDirs, ';', 'split');
allDirs(ismember(allDirs,{''}... |
6c5b90df2e9e8a2ecec4e8e0e0f630d8fda09ad0f49955b82f98f86857185d2a | MATLAB | 3,353 | 90 | %% Preamble, get file list
clear all; close all
set(0,'DefaultFigureWindowStyle','docked')
% pat{1} - % location of the processed assembly memberships
% pat{2} - % location of raw spike times
if ispc
% pat{1} = 'C:\Analysis\AssemblyAnalysis\Sleep\Decoding vs flanking periods - epoch specific FRs\';... |
fdaa6d506ae4dafda480e3407dbf93ddb0e46141b76e301be790ff60b8a4faee | MATLAB | 3,355 | 100 | function model = qtip_pipe_SDPdcm(model,data,btensors,mask,nvox,mcheckflag,ind,parallel,cvxsolver)
% function model = qtip_pipe_SDPdcm()
%
% reshape data and retain voxels within the mask
siz = size(data);
sizm = size(model);
data = reshape(data, prod(siz(1:3)), siz(4))';
model = reshape(model, prod(sizm(1:3... |
e4e04899e2ae2303167f6219f5f639e5a151baddba65641754f0810941b68fc0 | MATLAB | 3,358 | 96 | function [dsetTag, solTag, FEM] = solve_FEM(model, activeSites, iActiveSite)
arguments
model (1,1) Model
activeSites
iActiveSite
end
log = model.getLogger('potential');
AS = activeSites(iActiveSite);
ASname = AS_name(AS);
solutionPath = model.sol_file(AS);
if(isfile(solutionPath))
log.inf... |
54c9d3283db1c5813ddb8e560925b7a0c123e2b7b2d2f3a379fd80fc9cba2366 | MATLAB | 3,361 | 118 | function [] = test_l1_logistic_regression()
clc;
clear;
close all;
%% Set algorithms
if 0
algorithms = gd_solver_list('ALL');
else
%algorithms = {'PG-BKT', 'PG-TFOCS-BKT', 'APG-BKT', 'APG-TFOCS-BKT', 'Newton-CHOLESKY', 'NCG-BKT','L-BFGS-TFOCS'};
algorithms =... |
0dd6c3a0b6bf0dee60dcfa2957dffcbcbbef84c5576b27922238254b6136636f | MATLAB | 3,362 | 105 | function LEiDA_data
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% LEADING EIGENVECTOR DYNAMICS ANALYSIS
%
% This function preprocesses DMT datasets for LEiDA
%
% - Reads the BOLD data from the folders
% - Computes the BOLD phases
% - Calculates the instantaneous BOLD synchronization matrix
% - Saves the instantane... |
578579e43657b5ae74d0e13f68821c15c4a3c81210288cf3ef7b128852e6f322 | MATLAB | 3,364 | 136 | function MRG_coeff()
% MRG_COEFF Computes coefficient to find linear relations between fiber
% diameter in um and the other parameters of its the MRG model.
% Data is taken from MRG paper.
%% Parameters
% Precision
prec = 5e-3;
% Number of fibers
nb = 9;
% Fiber diameters [um]
D = [5.7, 7.3, 8.7, 10.0, ... |
ba2e9a6ab011e7b6c8eb78cb9f759cfc53da12733431d05dfa4599082d3d47df | MATLAB | 3,369 | 130 | function [alphas,fs,gs] = strong_wolfe_line_search(problem, d, x0, c1, c2)
%function [alphas,fs,gs] = strongwolfe(myFx,d,x0,fx0,gx0)
% Function strongwolfe performs Line search satisfying strong Wolfe conditions
% Input
% myFx: the optimized function handle
% d: the direction we want to search
% x0: ve... |
81854d77d6487f98ba707722a1daea29e58f2294a4eefccf376001d5854109da | MATLAB | 3,371 | 168 | function varargout = TankReg(varargin)
% TankReg
%
% DJS (2011)
% Copyright (C) 2016 Daniel Stolzberg, PhD
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @Tan... |
9c8fc522fb318bb26c209ab44c81e11b2c4ea827f3ac314a5da42acbf17c412c | MATLAB | 3,371 | 111 | function event = ft_read_event_tdt_2BitM(tank,block,blockroot,eventname,eventvalue,Fs)
% EVENT = ft_read_event_tdt
% EVENT = ft_read_event_tdt(TANK)
% EVENT = ft_read_event_tdt(TANK,BLOCK)
% EVENT = ft_read_event_tdt(TANK,BLOCK,BLOCKROOT)
% EVENT = ft_read_event_tdt(TANK,BLOCK,BLOCKROOT,EVENTNAME)
% EVENT = ft_read_eve... |
9c1bb183dff06908af874a9fd085d536cd600c094b92917639790ec6294f8a69 | MATLAB | 3,372 | 95 | classdef ButtonBox < uix.Box
%uix.ButtonBox Button box base class
%
% uix.ButtonBox is a base class for containers that lay out buttons.
% Copyright 2009-2020 The MathWorks, Inc.
properties( Access = public, Dependent, AbortSet )
ButtonSize % button size, in pixels
... |
fd5da0da8945496b2992c0027291cfabf2d7dfd52909c9160790b243034fe5b1 | MATLAB | 3,372 | 140 | function plotTriggered_SanesLab(timestamps,TTL,trigger_TTL,ax,clr,varargin)
%plotTriggered_SanesLab(timestamps,TTL,trigger_TTL,ax,clr,varargin)
%
%Custom function for SanesLab epsych
%
%This function plots TTL data in realtime as a triggered plot.
%Using the MATLAB plot feature each time the graph must update is very s... |
2d8f67fb1264fe674b07f7c3f7946a6b53872701b90b18fae5ffdaf1c6227b66 | MATLAB | 3,373 | 136 | function model = dtip_data2fit_SDPd(signal,bten,varargin)
% function model = dtip_data2fit_SDPd()
%
% out_flag says which format to use for m :
% out_flag = 1 -> [28*nvox,1]
% out_flag = 0 -> [28, nvox]
nmeas = size(bten,1);
% retriev... |
21ded407d03a8c3e5cf95f65ba21d45eea7bc06be654233e42109f389178fa30 | MATLAB | 3,374 | 119 | function FlyThroughCapture( hFig, hAxes )
%Roll down from XZ to XY and fly through volume
XDim = get(hAxes, 'XLim');
YDim = get(hAxes, 'YLim');
ZDim = get(hAxes, 'ZLim');
FrameNumber = 0;
tilt = 0;
angle = 0;
step = 1;
%Figure out where the camera should be when circling ... |
58d897415cacc0cbbad790dfc37cebf9d0579f0aefdd5ff5fff3d2c1570b827b | MATLAB | 3,375 | 119 | function [D0,phisq0,st] = lme_fit_FSinit(X,Zcols,y,ni,e)
% [phisq0,D0,st] = lme_fit_FSinit(X,Zcols,y,ni,e)
%
% Starting values for linear mixed-effects estimation.This function is
% intended to be used to provide starting values for the lme_fit_NR
% function by mean of some initial iterations of the Fisher scoring a... |
afe83ce21ab9802416a0fb06bea50268dba12e170009432dbb1413ca29ca2659 | MATLAB | 3,375 | 188 | %%
% RPfile = 'C:\Users\Dan\Desktop\SpeakerArrayTest.rcx';
%
%
% RP = TDT_SetupRP('RX8',1,'GB',RPfile);
%
%
%
%
% RP.Halt
%% Approach 1: mask chan X samples signal with gaussian sweep algorithmically
% This allows for arbitrary speaker paths
nChan = 17;
D = 0.5; % siganl duraiton in second... |
001d29a8254a981e56f1d8385459281528e8fff4371d725e988040aa4f955fed | MATLAB | 3,382 | 107 | function TwoPhotonConfigurationInterview
config_string = {'function TwoPhotonConfiguration' '' 'TwoPhotonGlobals;' '' };
path = config_dirname;
twophotonconfigname = [path filesep 'TwoPhotonConfiguration.m'];
if exist(twophotonconfigname),
movefile(twophotonconfigname,[path filesep 'TwoPhotonConfiguration_bkup.m']... |
ab9c658148c86495ae98ed0ea58c879872ce3e7c7b241a9ac5885438032f6e11 | MATLAB | 3,385 | 50 | %-----------------------------------------------------------------------
% Job saved on 05-May-2022 09:40:11 by cfg_util (rev $Rev: 7345 $)
% spm SPM - SPM12 (7771)
% cfg_basicio BasicIO - Unknown
%-----------------------------------------------------------------------
clear matlabbatch
subjfolder = dir('F:\fMRI_QC\fm... |
f2035be0fa4fdd4a54c80a1e0ca52a0e8d368529fbe1e314c7d6769323bcb0cc | MATLAB | 3,387 | 89 | function TRIALS = DefaultTrialSelectFcn(TRIALS)
% TRIALS = DefaultTrialSelectFcn(TRIALS)
%
% This is the default function for selecting the next trial and can be
% overridden by specifying a custom function name in ep_ExperimentDesign.
% The code in this function serves as a good template for custom trial
% sele... |
15ad595ea0a76a5b8ffbc8cdc5b030ddff0189f8ccd8bd1b44242710b188e3c4 | MATLAB | 3,396 | 82 | function [fitted_trend, cleaned_signal] = run_flatt_svd_fitting(signal, region_mask, embedding_dim, sv_keep)
% RUN_FLATT_SVD_FITTING Applies SVD-based filtering to reconstruct the
% signal trend based on pre-defined FLATT structural vs empty regions.
%
% Inputs:
% signal - 1D vector containing the raw input s... |
b2886f14838b230e415e963b8ee3fa853842f484ad8de541a8ee35ca3b5271f6 | MATLAB | 3,399 | 107 |
function [bindata,bindataerror,timesnew] = f_getmvpcdata(ALLMVPC,MVPCArray,qtimeRange)
bindata = [];
bindataerror = [];
timesnew = [];
if nargin<1
help f_getmvpcdata
return
end
if nargin<2
MVPCArray = [1:length(ALLMVPC)];
end
if nargin<3
MVPC = ALLMVPC(MVPCArray(1));
qtimeRange = [MVPC.times(1),M... |
b3242fd747677eb10784d0f2c9000b46bcba113ec1ba1d6450b8f214d5c17808 | MATLAB | 3,401 | 79 | function [TmtxS,iFRs,EvtLs,EvtTs,usel_out]=SelTrialsCells(fn,twin,minFR,critCvBW,iFRtype,trials)
% Select cells from PFC and HC data sets & cut out event periods (trial case)
%
% (c) 2014 Daniel Durstewitz, Bernstein Center for Computational Neuroscience, CIMH/ Heidelberg University
% Edited by Aleksander PF Domans... |
22c6c626675602a1a2a7f103c57c301f6b27396e88ced371c46aa4a2c57be50b | MATLAB | 3,403 | 117 | function plotBayes(result,plotOptions)
% this function creates the plot with the bayesian Posterior distributions
%function plotBayes(result,plotOptions)
% displayed are two dimensional marginal distributions of each parameter
% against each other parameter
% You may then enlarge each panel by clicking on it.
if ~exis... |
8ab99de6dce6a671603f24af426ff38bfca1cfd5890cfdb49debfdaed57f9b17 | MATLAB | 3,403 | 92 | function [net_eval,net] = dlRNN_run(net,input,target,act_func_handle,learn_func_handle,transfer_func_handle,perturbLogic)
% start timer
tic
[cm] = TNC_CreateRBColormap(1024,'rb');
[cat] = TNC_CreateRBColormap(8,'mapb')
% parameters
max_delta_J = 1e-4;
dt = 1;
tau = 30;
dt_div_tau = dt/tau;
alpha... |
daebecf56ff36ac2adf77f8a885c3fa567c13d602ad2ff67fe04f2eb0649334a | MATLAB | 3,404 | 94 |
%==================== AllSizeSDFSuppFig2.m ====================
% Find the mean response of each neuron to the expanded set of sizes
% across different stimwindows
%==========================================================================
close all
clear all
%================= SET PATHS AND LOAD DATA
if ismac
... |
cfddbe216520cdb8ac5e888aa66759aae4fcbbe179faabef96a229684a89a343 | MATLAB | 3,406 | 104 | %%%%%RUN ON 2500
sublist = table2array(readtable('/scratch/janine.bijsterbosch/WAPIAW_2/subj_lists/sub_list.csv'));
%%load data
addpath(genpath('/scratch/janine.bijsterbosch/WAPIAW_2/heterogeneity/src_matlab'))
D = readtable('/scratch/janine.bijsterbosch/WAPIAW_2/phenotypes/WAPIAW2_clean.tsv','FileType','text');
[~, ... |
6a7a2b87446ffbd635d16750afec003a4e739ca707b81c10483a781f4f017506 | MATLAB | 3,408 | 75 | %Function used to compute the log evidence (sort of --- I also have a prior over the hyperparams, so it's an approximate log posterior over the hyperparams)
% where the evidence is computed using a Laplace approximation of the posterior over the parameters and plugging into Bayes' rule
function [nle, ndle, params, resu... |
f34dd405e3e89d0396f6d169f3f43fd130f0d6cd8c28e3e76a7d5aaa43a26b49 | MATLAB | 3,414 | 92 | function Set=SetDefaults(Set)
%% Set defulats values for variables in Main.m
% Time integration
if ~isfield(Set,'AccumulateU')
Set.AccumulateU=true; %Displacements and stresses are accumulated at each
% time step (assumed true in viscous problems). Otherwise problem solved from previ... |
716756770abcc8e546884630d20a31dc1a27f2783ba01e102c89a5b543ec0d8d | MATLAB | 3,418 | 91 | %
%
% This code is used to create Figure 1B - example CCEPs for a few older and younger subjects
%
%%
% Load the ccepData and ccepAverages from the derivatives
clear
close all
warning('on');
warning('backtrace', 'off')
myDataPath = setLocalDataPath(1);
track_path = fullfile(myDataPath.input, 'sourcedata', 'tr... |
cdfec7e953870630c63673331b45d418f615312eb3d43ec2eb0183f96d9191e9 | MATLAB | 3,418 | 94 |
%==================== AllSizeSDFSuppFig2.m ====================
% Find the mean timecourse across all neuron to the expanded set of sizes
% to examine response changes over time
%==========================================================================
close all
clear all
%================= SET PATHS AND LOAD ... |
f8b5f4e1b9956481d442473551024293823f904685d15b1a1e9d30b1f9039744 | MATLAB | 3,420 | 77 | function [endoCross] = edges_to_branches(segments)
% EDGES_TO_BRANCHES Create the connected segmentation of the extracted
% edges of the endoneurium and correct the obtained closed lines for
% possible holes and electrode placements
%
% [endoCross] = edges_to_branches(segments, roundPrec)
%
% ... |
5653daa6709b6ca10a47278dee57dc4d55bb7a4e76fbf0cc0078513712c79d70 | MATLAB | 3,422 | 107 | % ----------------------------------\\
% ----------------------------------\\
% Recurrent Neural Network Engine \\
% ----------------------------------\\
% ----------------------------------\\
function [outputs,hidden_r,hidden_x,e,e_store] = dlRNN_engine(this_P_perturb,net,curr_input,curr_target,act_func_handle,... |
4f1ea55df5d654ab063393c3204f3710fa6216df73eec44162e866640fe82f42 | MATLAB | 3,424 | 148 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
VIZIT = 0 ;
%% 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 = ll.data ... |
67d3e96d3f3fcc9ff325c58673e1c6b5e9b2aed7cdb412d41160d5287a05f862 | MATLAB | 3,426 | 83 | %
% Determine the hemisphere for each electrode using the iEEGPlacementScheme field in the (first run's) JSON file
%
% hemi = ccep_retrieveElecsHemisphere(jsonFilepathPattern, electrodeTable)
%
% jsonFilePattern = the filepath pattern used to search for JSON files. Each run has a JSON file
% ... |
9fadd241f99da3fb8a200b5cd4819224e3520328824e99917c3e500a8f12c28e | MATLAB | 3,427 | 118 | function fstats = lme_F(stats,C)
% fstats = lme_F(stats,C)
%
% Inference for the fixed-effects in the linear mixed-effects model(Depends
% on the Statistics toolbox).
%
% Input
% stats: Structure obtained from any of the model fitting functions:
% lme_fit_EM, lme_fit_FS and lme_fit_NR.
% C: Contrast matrix.
%
% Out... |
6020463d375f56ddad4b94cfc87919248c88828dc90dc64ee3944511214e5801 | MATLAB | 3,429 | 86 | function confusion = gaussian_overlap( w1, w2 )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% gaussian_overlap - estimate cluster overlap from a 2-mean Gaussian mixture model
%
% Usage:
% C = gaussian_overlap( waveforms1, waveforms2 )
%
% Description:
% Estimates the overlap between ... |
68ce49b4a356cc1698f73598becb7aea4ab2ca23d91db808b9509f5aea11e251 | MATLAB | 3,434 | 93 | %% pursuit aligned
load(fullfile('X:\Woojae\Data(AB)\Analysis\Fitting\Cue_all_rect(alldir;GoodChannel)_JL.mat'));
tVal = 30;
t1 = tVal; t2 = tVal; t3 = tVal; t4 = tVal;
eeg.valid100 = []; eeg.invalid100 =[];
eeg.valid12 = []; eeg.invalid12 = [];
for i = 1:16
eeg.valid100 = [eeg.valid100; Sub(i).valid... |
8b9fbc67f85805868020ec04d2b5b09d757d4477c78e87832a5bc848cf03f796 | MATLAB | 3,439 | 72 | %% GMLM.computeMAP
% optimizes the log-posterior of the GMLM given fixed hyperparameters using quasi-newton optimization
%
% inputs:
% params_init (REQUIRED) :a param struct of the initial value of the optimization.
%
% optional key/value pairs
%
% max_steps (default = 10000) ... |
c914a3bd25c020399122e39b71df0cf66d58d5f3525ab4d3040af0a8150dff65 | MATLAB | 3,439 | 126 | function LMER_MODES_PID_RAW_reduced
% Function to prepare the regression table for Linear Mixed-Effects Regression Model
% in R
% The metric variables are Zscored here
%
% Fran Hancock
% Dec 2021
% fran.hancock@kcl.ac.uk
%
%
% Function to investigate the relationships between time varying measures
% of CHI OCC HC and P... |
37875a0376a5e3335d87c6068f9244f48b10c3a6af89072cf31f17b0668a500d | MATLAB | 3,443 | 136 | function [handles,xmin,xmax,varargout] = update_TTLhistory_SanesLab(handles,starttime,event)
%[handles,xmin,xmax,varargout] = update_TTLhistory_SanesLab(handles,starttime,event)
%
%Custom function for SanesLab epsych
%
%This function updates the TTL history for plotting purposes
%
%Inputs:
% handles: GUI handles str... |
6e2608e625b6e655105a7c93367f8d91d6babcb4c070e7e7023336c7d877fa01 | MATLAB | 3,447 | 121 | function write_vtk_rbm(varargin)
%function write_vtk_rbm(name,N_points,v,N_faces,f,label_1,label_2,label_3,fibers)
name=cell2mat(varargin(1));
N_points=cell2mat(varargin(2));
v=cell2mat(varargin(3));
N_faces=cell2mat(varargin(4));
f=cell2mat(varargin(5));
label_1=cell2mat(varargin(6));
... |
515f73f9e44f1d10068a7178c23237b0f97d63f59e347b205a3b95ab93340f42 | MATLAB | 3,448 | 124 |
% Author: Guosheng Lin (guosheng.lin@gmail.com)
% perform segmentation prediction on user provided images.
% specify the location of your images, e.g., using the following
% folder which contains serveral example images:
% ds_config.img_data_dir='../datasets/custom_data';
function demo_refinenet_test_example_egoha... |
2ddd604d10c74c299433bd86cd4a931482352391bbcecb2fd61ee16bddfd890a | MATLAB | 3,451 | 123 | function ExportAnnotations(self)
revPath = fullfile(self.ProjectPath, 'annotations', 'ClipTable.mat');
load(revPath, 'ClipTable');
uniqueVideos = unique(ClipTable.Video);
exportFolder = fullfile(self.ProjectPath, 'results', 'annotations');
if ~isfolder(exportFolder)
mkdir(exportFolder)
end
summaryT = CreateSumm... |
251a54e211c5c7a1be6e44ab03529f80b04a7ac3ec188a65c1d0d44dc948e74e | MATLAB | 3,453 | 121 | function write_vtk_rbm(varargin)
%function write_vtk_rbm(name,N_points,v,N_faces,f,label_1,label_2,label_3,fibers)
name=cell2mat(varargin(1));
N_points=cell2mat(varargin(2));
v=cell2mat(varargin(3));
N_faces=cell2mat(varargin(4));
f=cell2mat(varargin(5));
label_1=cell2mat(varargin(6));
... |
3dc9e121e501e976a6d1435b3311426eb3e855cda19a92b24aa0b733c7d9a95e | MATLAB | 3,453 | 91 | function [freqsBinned] = cr_bin_power_spectrum(CBF, PowerSpec)
% The resultant powerspectrum has a higher frequency resolution (0.1 Hz)
% than is relevant.
% This functions groups the powerspectrum into coarser bins and adds the
% powers of the original powerspectrum bins together.
% CBF = A structure with at le... |
6b199dae05fa30471749fe275b5b6aaf2e42e1cebc52d23db2186186aca80f6c | MATLAB | 3,454 | 131 | function A = PSTHstats(PSTH,bins,varargin)
% A = PSTHstats(PSTH,bins,varargin)
%
% PSTH is an M by N matrix with each row a sample (bin) and each column a
% different condition (ex, sound level).
%
%
% alpha ... 0.01;
% prewin ... [-0.05 0];
% rspwin ... [0 0.05];
% levels ... 1:n
%
% Daniel.Stolzberg@gmail.com
[... |
d8b938efccb14b5ce329a02ebe98614310781f34fd64d69ae0a7b519bfc96956 | MATLAB | 3,454 | 103 | function [p1_mean, p1_update, confidence] = RescorlaWagner(s, learned_param, a_LR)
% Learns the statistics of the input sequence s according to a
% Rescorla-Wagner model (delta rule) with learning rate a_LR.
%
% Inputs:
% s binary sequence of stimuli. Entries are in {1, 2}.
% learned_param in {'trans... |
64e72bba352a420860f8dc5c796566da5b8fda2145fb0fbc844cd2bc7ff414cb | MATLAB | 3,455 | 128 | % 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 ] ;
filename = [ DD_INTERM '/' OUTSTR '_divergences_n_outlierdetect.mat' ] ;
divo = load(filename) ;
ff = [ PROJ_DIR '/reports/lab_meeting/... |
6f96a6ac39e97bd838419b00e05bc3b632ccbfab5b78d5c325de188edde6a9e6 | MATLAB | 3,457 | 103 | function [result,im1,im2] = tpimagemath(dirname, channel, stimcode1, stimcode2, op,plotit,name)
% TPIMAGEMATH - Simple image math
%
% RESULT = TPIMAGEMATH(DIRNAME,CHANNEL,STIMCODE1,STIMCODE2,OP,PLOTIT,NAME)
%
% Computes simple image math for Prairieview images.
%
% DIRNAME is the name of a two-photon directory. ... |
b0ef60780744fd52d9a7b279f9900d20686d60757e0ea2db1b2fbf7bb143d9a0 | MATLAB | 3,457 | 116 | function coords = bilinearIntersection(cell1, cell2, v)
% BILINERINTERSECTION Finds the coordinates of the intersections of the
% V-level contour lines of unit squares CELLA and CELLB, calculated using
% bilinear interpolation.
%
% Inputs:
% CELLA must be a matrix of size [2 2] giving the values at the 4 vertices
% ... |
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