sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
bcf3503f8783952bc9fdeb01408d622757f1a169dbfe99a3ea7bafd0e632d7c3 | MATLAB | 9,859 | 227 | %{
ZScoreOnsetOffsetDetect - onset/offset detection by z-scored envelope.
HOW TO USE THIS TEMPLATE
Edit only the three ZONE blocks below:
ZONE 1 set numVar and your parameter labels
ZONE 2 unpack your parameters from UserVar
ZONE 3 write your detection method and fill the outputs
Everything else is ... |
e0d49867c4aea159eb6d03cd8d7f0f260174200d1aafff1a47906895b2bd6a57 | MATLAB | 9,861 | 234 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MAIN - Analysi fatta sul dataset a disposizione - 20 soggetti - Sess. 4 - MEG - Desikan-Killiany
% Authors: MCC
% Date: 21/03/2022
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
close all; clear; clc;... |
108cca3ffa1c50dec0dc26131c28e87c09aacb86a66a9cc2a7c3fa14ca4a06ad | MATLAB | 9,867 | 196 | %% Raspberry Pi: local and remote
% The Raspberry Pi is an inexpensive single board computer that runs Linux
% and Octave, the open source counterpart of MATLAB. We have tested all
% functions of the toolbox on a Raspberry Pi 3 B. They will probably work
% on newer models as well, but we do not know that -- if you use ... |
1978f27b52fe5eba3e50e919d38777fb2a31125434ace296c0a141033a00fbc3 | MATLAB | 9,870 | 304 | % Compare the sampling distribution of a single recurrent network with the
% posterior under different input and/or network parameters.
% Wen-Hao Zhang
% June 24, 2021
% University of Chicago
if ~exist('Path_RootDir', 'var')
setWorkPath;
end
addpath(fullfile(Path_RootDir, 'linearHawkesProcess'));
%% Parameters o... |
d5a34ab6b3e30c112295a28224aa3e881480b594388be8aacf302f0875f077c2 | MATLAB | 9,878 | 263 | function [f,dfdx,D,dfdu] = spm_fx_fmri(x,u,P,M)
% State equation for a dynamic [bilinear/nonlinear/Balloon] model of fMRI
% responses
% FORMAT [f,dfdx,D,dfdu] = spm_fx_fmri(x,u,P,M)
% x - state vector
% x(:,1) - excitatory neuronal activity ue
% x(:,2) - vascular signal s
% ... |
a22309c5db24ae7604e470f1813f77fb2b4eb01d0f8fc405f9fd6a15f9411088 | MATLAB | 9,884 | 227 | function Optical_fitting_finalized(co, cross, s_seg, z_seg, datapath,aip_threshold, mus_depth, bfg_depth, ds_factor, zf, zf_tilt)
% Fitting scattering and retardance of brain tissue
% co: volume data for co pol
% cross: volume data for cross pol
% s_seg: slice number
% Z_seg: tile number
% datapath: datapath for origin... |
342b4723c584588a79aaac3e450b548169c9294c4fda286ca4eb5c110731c226 | MATLAB | 9,890 | 341 | function [L, betas, convergenceFailures] = ridgeMML(Y, X, recenter, L)
% [lambdas, betas, convergenceFailures] = ridgeMML(Y, X [, recenter] [, lambdas])
%
% This is an implementation of Ridge regression with the Ridge parameter
% lambda determined using the fast algorithm of Karabatsos 2017 (see
% below). I also made ... |
a43d6bca08a05489ba4ed0ad9a23ddb6fcebd0820a1f5dba73dd81f10371a1e0 | MATLAB | 9,891 | 300 | % function plot_power_log_baselines(SBJ,proc_id,an_id)
% Filter, extract power, plot distribution of power values
%% Settings
if exist('/home/knight/hoycw/','dir');root_dir='/home/knight/hoycw/';ft_dir=[root_dir 'Apps/fieldtrip/'];
else root_dir='/Volumes/hoycw_clust/';ft_dir='/Users/colinhoy/Code/Apps/fieldtrip/';end... |
9edcb1fceec797298d986551462c425d1325f6cc90062fd66a375fb7153a1e2e | MATLAB | 9,904 | 224 | function [outOriginalSound,outResynthesizedSound,outSampleFreq,outDetectedPeriods,outIndividualSounds] = ...
IPEMDemoStartMEC(varargin)
% Usage:
% [outOriginalSound,outResynthesizedSound,outSampleFreq,outDetectedPeriods,...
% outIndividualSounds] = ...
% IPEMDemoStartMEC(inSoundFile,inSoundFilePath,in... |
dbcb05ca2648c268d60c9f2575763bf33abe54f699dd146d4c06a6c8e7d170c3 | MATLAB | 9,906 | 402 | function psino = rebin_fan2par_helix(fsino, sf, sp, varargin)
%|function psino = rebin_fan2par_helix(fsino, sf, sp, varargin)
%|
%| Rebin fan-beam sinogram into parallel-beam (or mojette) sinogram.
%| (Also useful for parallel-to-mojette rebinning.)
%|
%| in
%| fsino [ns nbeta (L)] fan-beam sinogram (or possibly para... |
9a7bfb6733e08be1e726e169da54b80d517d85a6fc23bf938db8bf8f3faa6ced | MATLAB | 9,913 | 329 | classdef c_InputParser < handle
% c_InputParser - similar to inputParser(), but with extra features such as interactive GUI dialog
%% instance variables
properties
Results = [];
isParsed = false;
end
properties(Dependent)
numParameters;
end
properties(SetAccess=protected)
parameters = [];
end
pr... |
f2771d5f1c89cdafd592099422b9192cf86d85885bba295c858324a7fcef718e | MATLAB | 9,916 | 236 | function [slope,pearson_rho] = findAttractorDynamics_supplement(cells,save_figs,sf)
% A functioning attractor network should preserve correlations between
% pairs of cells.
% E.g. So pairs of cells that are well correlated in trial 1 through 25
% should also be well correlated in trials 26 through 50
slope = nan;
pea... |
bb117d27fe06824a7851799d0c47bdc1f58f25597ce2fd7f660f95a6a2295cb7 | MATLAB | 9,917 | 425 | function [phantom, params] = cylinder_im(ig, params, varargin)
%|function [phantom, params] = cylinder_im(ig, params, varargin)
%|
%| Generate (elliptical) cylinder phantom image from parameters.
%| in
%| ig image_geom()
%| params [ne 8] cylinder parameters. if empty, use 3d Defrise
%| [x_center y_center z_center... |
aeabe9403c6416ac825293c6f0b3e0547d54236fb7763a530a21423c18005243 | MATLAB | 9,920 | 261 | function VisualizeRealtimeTrackingData(Group, pId, trialId, playbackSpeed, varargin)
%% VisualizeRealtimeTrackingData
% Andrea Castegnaro, UCL, 2022 uceeaca@ucl.ac.uk
% Function used to manuyally visualize the reconstructed data from a
% participant.
% Group: group from which we are going to visualize the trial
% pId: ... |
b51528a6ec038f5c29e298cdd904fe3452ea25c19ea5e52ada185fb181f657b1 | MATLAB | 9,921 | 249 | function [outRoughness,outSampleFreq,outFFTMatrix1,outFFTMatrix2] = IPEMRoughnessFFT(varargin)
% Usage:
% [outRoughness,outSampleFreq,outFFTMatrix1,outFFTMatrix2] =
% IPEMRoughnessFFT(inANI,inANIFreq,inANIFilterFreqs,...
% inFrameWidth,inFrameStepSize,inPlotFlag)
%
% Description:
% ... |
1fd03ee4fe0e4c43c9c0134a23a0f4f5d95624a208a824c6e3d5633688dab567 | MATLAB | 9,925 | 258 | %aim to calculate the latency of the response, find the time and CI, and
%the bootstrap
% close all;
clearvars;
addpath ('/data/local/u0114568/ephysio/test');
listname= 'targetLeft' ;
cn1={'sp','color', 'con', 'incon', 'att', 'congruency','fac','int'}; % condition names length=8
cn={ [cn1{1}],[cn1{2}]};
condnames=lis... |
868752be51a837181623dd5761aeb38bea4c850cf90b6e1fdd8137b262407a89 | MATLAB | 9,925 | 258 | %aim to calculate the latency of the response, find the time and CI, and
%the bootstrap
% close all;
clearvars;
addpath ('/data/local/u0114568/ephysio/test');
listname= 'targetLeft' ;
cn1={'sp','color', 'con', 'incon', 'att', 'congruency','fac','int'}; % condition names length=8
cn={ [cn1{1}],[cn1{2}]};
condnames=lis... |
6906d929ecd8749baef1c4909400cbdf919d3a9669889a5af1a1d9d5c70968f1 | MATLAB | 9,934 | 296 | function [EEG, misc] = c_TMSEEG_detectBadChannels(varargin)
%
% output struct `misc` includes the following:
% - misc.badChannelIndices: numeric indices of bad channels
% (if removing bad channels, these indices index into the channels prior to rejection)
% - misc.channelScores: per-ch scores, where greater magnitud... |
11012a1a60e2ee9cf2e9bdaa3202fc5fda2402dba67dab70032d6ce2805eab7e | MATLAB | 9,935 | 273 | function [x0,y0,iout,jout] = intersections(x1,y1,x2,y2,robust)
%INTERSECTIONS Intersections of curves.
% Computes the (x,y) locations where two curves intersect. The curves
% can be broken with NaNs or have vertical segments.
%
% Example:
% [X0,Y0] = intersections(X1,Y1,X2,Y2,ROBUST);
%
% where X1 and Y1... |
70ce8e9e8a021c2b2a4ba5853f52411d126fb2ce976533014aa1316130a81753 | MATLAB | 9,937 | 324 | %% Figure S10b
%%
clear
ft_defaults
%% SUBJECTS
% ID 18 missing because of LP at 50Hz
subjects = {'OSL13', 'OSL14', 'OSL17', 'OSL21', 'OSL24', 'OSL26', 'OSL27', 'OSL28', ...
'OSL29', 'OSL30', 'OSL31', 'OSL32', 'OSL34', 'OSL35', 'OSL36', 'OSL38', 'OSL39', 'OSL40'};
%% PATH SETTINGS
path_data = '/Volumes/IMPECO... |
7db53278a36637ea9da27e84980876ddfe4d12fcde9f52ad3f8ea2dfb48c0b0a | MATLAB | 9,938 | 299 | clear all
close all
dbeh_path='C:\Users\xscogno\MATLAB\Flavio2\Waves\Tracking data\';
rec_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_spikes='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_sorting='C:\Users\xscogno\MATLAB\Flavio2\Waves\Sorting\';
dpath='C:\Users\xscogno\MATLAB\F... |
00f1ce73ad9578569a7757fc0f70c2264f8b8b170082fc5c703e0a93724f1b77 | MATLAB | 9,952 | 173 | function rate_shuffle_population_vector_analysis(bayesian_option,num_shuffles,save_option)
% Marta Huelin_February 2020
% Computes population vectors between shuffled matrices for the same type of comparisons used in the population_vector_analysis.m code (meaning,
% between same track exposures and between different tr... |
2fa017f7e7e655426a4f32fd261e262448d9a2a216fc341fee8da8b0ab4c9fd0 | MATLAB | 9,962 | 246 | GAdir = 'GAoutput';
targetDirectory = '../input';
NRealSubsTotal = 250;
NWavesTotal = 3;
NSubsTotal = NRealSubsTotal * NWavesTotal;
trialLength = 7.5;
load('gammaDists.mat'); % loads variables choiceGammaDSD and discoGammaDSD
%% load up the 200 optimized sequences, assign 4 per 'design'
designFile = ([GAdir,filesep,'k... |
9930840c3ca44b656f393e0bcace4e157295069a87051bb28504649e260491da | MATLAB | 9,973 | 227 | %% Plot dipole model results
%
% Vinding, M. C., & Oostenveld, R. (2022). Sharing individualised template MRI data for MEG source reconstruction: A solution for open data while keeping subject confidentiality. NeuroImage, 119165. https://doi.org/10.1016/j.neuroimage.2022.119165
%
% Plot results of dipole fits (Figure ... |
cd605b4edeeabf133b13c1b039beb427e4b766b27ebdf63126f9b963203b31ac | MATLAB | 9,978 | 324 | %% Figure S10a
%%
clear
ft_defaults
%% SUBJECTS
% ID 18 missing because of LP at 50Hz
subjects = {'OSL13', 'OSL14', 'OSL17', 'OSL21', 'OSL24', 'OSL26', 'OSL27', 'OSL28', ...
'OSL29', 'OSL30', 'OSL31', 'OSL32', 'OSL34', 'OSL35', 'OSL36', 'OSL38', 'OSL39', 'OSL40'};
%% PATH SETTINGS
path_data = '/Volumes/IMPECO... |
f9a37583315c4a62eada8527f85c81247de09c5bdad95651908a416f5a3279be | MATLAB | 9,984 | 394 | %% Analyzing Neural Time Series Data
% Matlab code for Chapter 11
% Mike X Cohen
%
% This code accompanies the book, titled "Analyzing Neural Time Series Data"
% (MIT Press). Using the code without following the book may lead to confusion,
% incorrect data analyses, and misinterpretations of results.
% Mike ... |
c8e663d0cee9bb301e5880d8b5e5d4f95c6c941f6fe4a13790083dea11ff9eb7 | MATLAB | 9,987 | 263 | function [texture, timeIndex] = showVideo(vid, varargin)
% Fetch the next frame of a video and draw it on the stimulus window.
%
% The video has to be loaded with loadVideo and started with startVideo
% first. One call draws ONE frame, so this function belongs in a loop; its
% return value says when the video is over:
... |
ce12ccf0765a08912bba6cdbb277ddc07a5eb6f6b377a156eb4cc2048d8d88a9 | MATLAB | 9,991 | 285 | clear
clc
%% OS detection
currentFolder = pwd;
if ismac
% Code to run on Mac platform
disp('It is Mac OS')
elseif isunix
disp('It is Unix OS')
path = strcat(currentFolder,'/Lifespan18/');
slash='/';
elseif ispc
disp('It is Windows OS')
path = strcat(currentFolder,'\Lifespan18\');
slash=... |
65371371fb515585070f8d18ff8ddb07e024ab63fbc3d1f31d35451b6dcfcfdc | MATLAB | 9,996 | 272 | %% Script to create output for Fig. 5 - receiver operating characteristic curve for each GLAMPI parameter
% Andrea Castegnaro, UCL, 2022 andrea.castegnaro@ucl.ac.uk
% Using support vector machine (SVM) to classify two groups based on their
% fitted parameters using an holdout strategy (60% training set 40% testing
% s... |
5e4b3757d86336cdcaea4ddddeb7c2517dba144a8c9f2efce239e22e6585dcea | MATLAB | 10,007 | 285 | clear
clc
%% OS detection
currentFolder = pwd;
if ismac
% Code to run on Mac platform
disp('It is Mac OS')
elseif isunix
disp('It is Unix OS')
path = strcat(currentFolder,'/Lifespan18_Results/');
slash='/';
elseif ispc
disp('It is Windows OS')
path = strcat(currentFolder,'\Lifespan18_Result... |
f97989aa347a844909c90f8aed094d53d5fb3d0fa0c32242988c4feba052da3a | MATLAB | 10,007 | 215 | function [min_gs,max_gs,mean_interiorLawn_gs,mean_gs_profile_aligned,mean_norm_gs_profile_aligned,LawnBoundary_AlignIdx,LBD_alignedTo_gs_profile,orig_background_afterBlur] = extract_grayscale_minmax(bg_struct,BGVI,pixpermm)
%extract_grayscale_minmax.m
% This function takes in a bg_struct from a tracked video and extr... |
65b19a58979c4c6d1c0f4279aa85339288bf97f59d647dbbd10c591305d4dfa5 | MATLAB | 10,030 | 231 | function [rez, X] = splitAllClusters(rez, flag)
% i call this algorithm "bimodal pursuit"
% split clusters if they have bimodal projections
% the strategy is to maximize a bimodality score and find a single vector projection
% that maximizes it. If the distribution along that maximal projection crosses a
% bimodality t... |
de9f6cc2ce20fd67be38f7f5ee74cca4ff4d32451dd806f63cb3553eba0cb23b | MATLAB | 10,034 | 344 | function [L, betas, convergenceFailures] = ridgeMML(Y, X, recenter, L)
% [lambdas, betas, convergenceFailures] = ridgeMML(Y, X [, recenter] [, lambdas])
%
% This is an implementation of Ridge regression with the Ridge parameter
% lambda determined using the fast algorithm of Karabatsos 2017 (see
% below). I also made ... |
23c58a998e7ee6c130c0c9922f06e898b04f0fff8a3871445ea01be68f28f389 | MATLAB | 10,040 | 369 | function [smap, sinit] = ir_mri_sensemap_admm_3D_linear(ykj, varargin)
%function [smap, sinit] = ir_mri_sensemap_admm_3D_linear(ykj, [options])
%|
%| Regularized estimation of sensitivity maps for parallel MRI
%| using augmented Lagrangian methods with variable splitting.
%| See M.J. Allison et al., IEEE TMI, 32(3), 5... |
2221638a21cb168aa8cba0f1b9df58df103383d4096d7a5fc47143bb1452a3fb | MATLAB | 10,041 | 296 | function [Ep,Cp,F] = spm_nlsi_Newton(M,U,Y)
% Variational Lapalce for nonlinear models - Newton's method
% FORMAT [Ep,Cp,F] = spm_nlsi_Newton(M,U,Y)
%
% Eplicit log-likihood model
%__________________________________________________________________________
%
% M.L - log likelihood function @(P,M,U,Y)
% P - free p... |
511260dd0f8921359ddb5427006e1239f918e48efde414b87564886c59b6ac5f | MATLAB | 10,043 | 280 | % internal function
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
function [hdr, filetype, fileprefix, machine] = load_nii_hdr_bis(fileprefix)
if ~exist('fileprefix','var'),
error('Usage: [hdr, filetype, fileprefix, machine] = load_nii_hdr_bis(filename)');
end
machine = 'ieee-le';
new_ext = 0;
... |
e0859d21706c995c0f533392ae2306e1023c2e78df87b507efc12b3107369d05 | MATLAB | 10,052 | 516 | function fatrix2_tests(A, varargin)
%function fatrix2_tests(A, [option])
%|
%| perform basic tests of fatrix2 objects
%| in
%| A [nd np] fatrix2 object
%|
%| option
%| 'x' [idim] optional input test image
%| 'name' char name of input object (optional for display)
%| 'caller' char name of caller (optional for displ... |
da31b32d93db22c6d3c51b9937887b11d3b5e20804d48f118b5296b9d2076fdc | MATLAB | 10,054 | 239 | function SBJ08d_HFA_plot_grp_GLM_ts_ROI_butt(SBJ_id,proc_id,an_id,model_id,stat_id,...
roi_id,plt_id,save_fig,varargin)
% Plots butteryfly mGLM beta time series by ROI groupings
% COMMENTS NOT YET ADJUSTED
% gROI version: one plot; subplots per gROI (lines still colored by RO... |
06c3de3065888d56456b9dbe3be103c2b00cc7867d6b8ece316ce1f11561bb22 | MATLAB | 10,055 | 202 | function gap_linking_str = fun_graph_get_linker_ep2skl(vessel_image, vessel_mask, vessel_skl, ep_sub, ep_all_sub)
% fun_graph_get_linker_ep2skl use threshold relaxation and shortest path on
% designed metric to find a 3D line segment that connect the inut endpoint
% to a skeleton voxel in the nearby connected compon... |
40fdbb75a4a26071c22667a195ac6995e6f471752b2d345d7660e3d28ab9d3ae | MATLAB | 10,056 | 286 | %% This function is written to plot the result of the gpr based
%% reconstruction analysis of the eye tracking data obtained in the realted
%% fMRI project.
% This script is a merge between a script by Gi-Yeul Bae
% to assess significant clusters in time continuous data
% Bae, Gi-Yeul, and Steven J. Luck. "Decoding ... |
b673be4c97c0f86b4d4712b1a8031eba7b149aef44dff37ef5668c46d4b80635 | MATLAB | 10,060 | 283 | %% Figure 3de Plot Raw Light Readout of Multiple Animals
%Animal list
%EMXJ 3, 4, 7, 8, 9, 10, 11, 12, 13, 15
%% Define Paths of Loading Files and Save Files
currentFolder = mfilename('fullpath'); % determine the filepath based on where the script locates
scriptFN = mfilename;
filePath = erase(erase(currentFolder, scr... |
a37016f6e94f7773af093d8a97ec7bb0c3067c7c864b37694f9a04468b2a49e4 | MATLAB | 10,064 | 324 | clear all;
addpath(genpath(pwd))
glmFlag = 'jumps_absolute';
options = continuous_RDK_set_options('LTHiMac');
% subject list
subjectList = [16 18:21, 24, 26, 27, 28, 29, 31, 33, 34, 35, 42, 43, 47, 50, 51, 52, 54, 55, 57, 58]; %32 taken out
%subjectList = [62:64,66,68,70]; % vertical motion only
csdFlag = 0; % 1 f... |
a7b525d696ed5316c57de801a7e2dbc693468d4de4f75ed690ad1aaecc3a634c | MATLAB | 10,067 | 266 | % Demo of a linear Hawkes process where the E neurons are organized on a
% ring
% Wen-Hao Zhang, July 2, 2019
% University of Pittsburgh
%% Parameters of the model
parsCoupledHawkesNet;
parsMdl.dt = 0.1;
parsMdl.bSample_ufwd = 1;
parsMdl.jxe = 1e-2;
parsMdl.bCutRecConns = 1; % Cut off all recurrent connections to si... |
8090ad2776ba1048fe74ca756f891b7a65e7c6a18a01e8d87ee8c9fb7ef31072 | MATLAB | 10,074 | 180 | % GET PLACE FIELDS WITHIN LAPS
% loads list_of_parameters.m, extracted_clusters.mat,extracted_position.mat, extracted_waveform.mat
% uses function extract_laps.m, skaggs_information.m
% INPUTS:
% track_id: track being analysed
% lap_start & lap_end: set laps to analyise by inputing start and end lap IDs
%... |
d0daf064b1d9be32462d231718003c3ddfafeb52a012c0617fffd9b30fb9eea1 | MATLAB | 10,096 | 218 | %% Getting started
% This guide takes you from the download to your first running experiment:
% installing the toolboxes, setting up a folder for an experiment, the two
% settings files, and three small examples to try out.
%
% If you would rather start from something complete, the folder |Examples|
% of the toolbox ho... |
73359436ad5c8d9ed94dde4148c6f842b92f35f17875e20910573799ecfd532f | MATLAB | 10,111 | 195 | function [Objects] = f_imageAnalysis(Label, ch1, ch2, ch3, ch4, PreviewPath, MetaTable)
%vol(ch1, 0, 5000) Hoechst
%vol(ch2, 0, 4000) 647 MAP2
%vol(ch3, 0, 5000) 568 DCX
%vol(ch4, 0, 5000) 488 TH
ObjectsThisOrganoid = table();
%% Max projections
%NucMax = max(ch1, [],3); imtool(NucMax,[])
... |
4925f783a40630564eee85ce3c7d52b20947b320be4f58d1df8c01ebc75a7822 | MATLAB | 10,112 | 318 | function [skeleton cWidths] = skeletonize(s1, e1, i1, s2, e2, i2, c1, c2, ...
isAcross)
%SKELETONIZE Skeletonize takes the 2 pairs of start and end points on a
%contour(s), then traces the skeleton between them using the specified
%increments.
%
% [SKELETON] = SKELETONIZE(S1, E1, I1, S2, E2, I2, C1, C2)
%
% Inp... |
f317cf375128529750817acf415c96777e8ac4ce1665d6dc6926eddcb88d77de | MATLAB | 10,112 | 305 | N_sh=500;
n_sessions=size(prob_data,1);
for i=1:n_sessions
waveness_prob(i)=sum(prob_data(i,3:end));
for sh=1:N_sh
waveness_prob_sh(i,sh)= sum(prob_data_sh_allsessions{1,i}(sh,3:end));
end
end
thr=prctile(waveness_prob_sh',99);
sig_waveness=find(waveness_prob>thr);
waveness_prob_PaS.wavenes... |
0787b35d125e0de553febf8600ac040a84f11949c3db01cf82c759ab068e7a85 | MATLAB | 10,113 | 243 | function spm_slice_timing(P, sliceorder, refslice, timing, prefix)
% Correct differences in slice acquisition times
% FORMAT spm_slice_timing(P, sliceorder, refslice, timing, prefix)
% P - char array of image filenames
% can also be a cell array of the above (multiple subjects).
% sliceorder - ... |
2e296ada4a5c775ff48234ceca2bab1f2b043609f80d97fd0b01ee55f0e108fb | MATLAB | 10,114 | 171 | function [Objects] = f_imageAnalysis(Label, ch1, ch2, ch3, ch4, PreviewPath, MetaTable)
%vol(ch1, 0, 5000) Hoechst
%vol(ch2, 0, 4000) 647 HPIg
%vol(ch3, 0, 5000) 568 Sox2 (270 Mouse)
%vol(ch4, 0, 5000) 488 HMGB1
ObjectsThisOrganoid = table();
%% Max projections
%NucMax = max(ch1, [],3); imt... |
6c970ff379e95ae80ec391b74e43099615bf647b50dcca3d7aa70b8ceec20793 | MATLAB | 10,114 | 306 | %% Script that will simulate real-time fUS-BMI
% Loads in data, simulates streamining data in to the decoder frame by
% frame, and performs decoding.
%% Initialize workspace
clear; close all; clc;
%% Load project record for reference
% Need to include the simulated results here so that we can properly
% increment the... |
48addf1eeea241b636a59bf0a9a24964280d36ed3cded7ac92d784b23715569e | MATLAB | 10,119 | 182 | function global_shuffle_population_vector_analysis(computer,bayesian_option,num_shuffles,save_option)
% Marta Huelin_February 2020
% Computes population vectors between shuffled matrices for the same type of comparisons used in the population_vector_analysis.m code (meaning,
% between same track exposures and between d... |
92cc1d76f0582cfbc9eb6fa20281a5bbde69b9483757b9c129a64c6f59ab2073 | MATLAB | 10,132 | 209 | function allCells = poolAllCells(filter, sessionMetaDataPath)
% sessions = dir('/Volumes/groups/giocomo/export/data/Projects/JohnKei_NPH3/fkm_analysis/fr_corr_matrices/*.mat');
% sessions = dir('/Users/KeiMasuda/Desktop/fkm_analysis/fr_corr_matrices_noSpeedFilter/*.mat');
% sessions = dir('/Users/KeiMasuda/Desktop/fk... |
c5a4a10a16718ec4676c5ef443b0c12411c8fdb3f8ecb2b605eb17dd945c1b73 | MATLAB | 10,134 | 354 | function [kspace, omega, wi] = mri_trajectory(ktype, arg_traj, N, fov, arg_wi)
%function [kspace, omega, wi] = mri_trajectory(ktype, arg_traj, N, fov, arg_wi)
%|
%| generate kspace trajectory samples and density compensation functions.
%|
%| in
%| ktype string k-space trajectory type. see choices below.
%| arg_traj ... |
04de2db307b10e4d2365ed7d4f02bcdbf0e40d05fb79577a88a09782de7ba664 | MATLAB | 10,137 | 232 | function out = getKeyBufferResult(hostHandle, varName)
% Fetches the result of a keyBuffer call that ran on an experimental
% computer such as a Raspberry Pi. Otherwise the result stays there and
% cannot be saved on the control computer.
%
% varName is the name of the variable that holds the result on the
% experiment... |
152b33cec39ba5e0c2b7c0c79100be48b5cc19fd52a422a2c3fc3bb04bc2ad24 | MATLAB | 10,142 | 190 | % LAP PRE SPIKE TRAIN CIRCULAR SHIFT
% Disrupts temporal domain. Shuffle used when analysing laps separately
% INPUT:
% decoded_thetaSeq, directional_place_fields,theta_spike_count - data structs
% track: current track ID being analysed
% lap_id: current lap ID being analysed
% num_shuffles: integer
... |
15f54f6cbc8f458ec2c9a1ddac10d92486e980ea344ea4832979ea46053995eb | MATLAB | 10,143 | 275 | function [ dsdFeedback ] = discloseDSD(subNumArg, waveNumArg, dirArg)
% % discloseDSD.m $%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% usage: [ dsdFeedback ] = discloseDSD(subNumArg, waveNumArg)
%
% All args are scalar
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
7dcd5540792d07e30295e291f4cba06abd9c9ad4f8959e16dd79c9b8462ffc91 | MATLAB | 10,145 | 303 | function varargout = spm_toolbox(action,varargin)
% Manage third-party SPM toolboxes
% FORMAT spm_toolbox
% FORMAT spm_toolbox install <tbxname>
%
% See https://www.fil.ion.ucl.ac.uk/spm/ext/
%__________________________________________________________________________
% Copyright (C) 2012-2014 Wellcome Trust Centre for ... |
bb2ab17ba58cd907f00cc008d86e8e3b5a03326f635f0ec769379047b2d1afab | MATLAB | 10,148 | 232 | function lf = fun_graph_get_link_features(link_cc, vessel_image, vessel_mask_dt, link_feature)
% fun_graph_get_link_w_1_ep_features computes the features derived from the
% position and orientation of endpoints and their nearest neighbor
% Input:
% ep_sub: N-by-3 numerical array, where N is the number of endpoint an... |
5640c00716b42eb204555c42e115b7a6c465e65fa356d4f8b22267fbed814b5c | MATLAB | 10,164 | 265 | function [results] = runBlock(CondTable,miniBlockOrder,JND,iRun)
% last modified 11/02/2019
% Input:
%
% CondTable = order of trials
% BlockOrder = order of miniblocks (all columns) per run (each row)
% iRun = number of current run
% Output:
% results = 'results' is a numerical... |
e2ad90af72314a1079b605099598e972cf2e846daf01821c9293ca3050dbc4c9 | MATLAB | 10,167 | 340 | %% Frequency of single cell oscillations - All sessions
clear all
close all
dbeh_path='C:\Users\xscogno\MATLAB\Flavio2\Waves\Tracking data\';
rec_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_spikes='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_sorting='C:\Users\xscogno\MATLAB\... |
9afd1975c8bd8ddcc30c0584d0abcb59d69b917d3fccd3449d1e51c3e61f43e7 | MATLAB | 10,170 | 276 | function model = mTRFmultitrain(stim,resp1,resp2,fs,Dir,tmin,tmax,lambda,varargin)
%MTRFMULTITRAIN Train a multisensory additive model.
% MODEL = MTRFMULTITRAIN(STIM,RESP1,RESP2,FS,DIR,TMIN,TMAX,LAMBDA) trains
% a forward encoding model (stimulus to neural response) or a backward
% decoding model (neural respons... |
776e6ace1f6e425aed9a3e075938a2520671538d84b464221dc98f997dc1587a | MATLAB | 10,171 | 265 | function a=rdrawhd(d)
% rdrawhd - Parses MCS data header vers. 1 (datastream method)
% a=rdrawhd(d) Parse MCS data header
% To use this function data-files must be open already (fid is
% input parameter). ChannelID is incremented by 1 because the
% first channel sampled is 0, i.e. its index in the sampling
% s... |
309f6f83adb75f9e17f10d567396a3efa68561f525e03a8bf1c1c58779937db6 | MATLAB | 10,173 | 260 | function plots_control_one_lap
cd('X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\Chapter 2\Raw_replay_analysis\Short_exposures_control_ONE_lap')
load extracted_replay_plotting_info_MultiEvents.mat
control_data = track_replay_events;
clear track_replay_events
cd('X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP... |
a4b8117e66fae3d7a433b2717dbebb7f4de8d0ef66b3ca06d63d5bb461863b00 | MATLAB | 10,186 | 215 | % REPLAY AWAKE (LOCAL AND REMOTE) IN TRACK - CUMULATIVE SUM
% MH 2020
% Plots cumulative sum of awake replay in track, divided by protocols
% (subplots), and plotting both local (decodes current track) and remote (decodes other tracks) awake replay.
% INPUT: multievents. 1 for selection. If multievents, loads data with... |
d0d2d3f5b0f0227fc64022e35f5adf45cf845b2bb98a5161282b15966f2e6b57 | MATLAB | 10,193 | 269 | function SBJ06b_ERP_plot_stack_mean(SBJ, conditions, proc_id, an_id,...
plt_id, save_fig, varargin)
%% Plots single trial stack and condition averaged ERP per electrode with activation vs. baseline
% sorts by condition, then by RT; scatter for events to show conditions
% Opti... |
50f12a24d41f9c9f38e87a30c4eb52c467a5a39d9bf3bb523ff9b920489db88d | MATLAB | 10,202 | 193 | clear; close all; clc;
% SHAWEEN_HRV_FEATURES_W_CAP Main driver: EDF/annotation ingest, CAP A1/A2/A3
% epoching, R-peak detection (Pan-Tompkins) and HRV feature extraction.
%
% HRV is computed by calling the PhysioZoo mhrv toolbox DIRECTLY (per Reviewer 2).
% The previous edited copies (hrv_time_edit / hrv_freq_edit /... |
209b64a58698b80b989af9f989e1fed13f090f5e69b7814858e694eb54763989 | MATLAB | 10,205 | 273 | %% Load data, get spikes from good cells
addpath(genpath('/Volumes/groups/giocomo/export/data/Users/KMasuda/Neuropixels/MalcolmFxn/'));
addpath(genpath('/Users/KeiMasuda/Documents/MATLAB/Add-Ons/Functions/gramm (complete data visualization toolbox, ggplot2_R-like)/code'));
addpath(genpath('/Volumes/groups/giocomo/expo... |
c49c05ffc2335ea416214b7472239a9239e0b8a013902e007dd8fb7acffdaa2a | MATLAB | 10,217 | 297 | % Example of varargin: 'partialGradientRetinaA',0.3, 'withNoise'
% Note that withNoise should be last, otherwise the noise gets
% removed from the clamped part of the trace
function makeNaiveGradients(obj,varargin)
disp('Setting up naive gradients')
assert(strcmp(obj.eyeType,'disk'));
% Set up default grad... |
d4f356dc3f2f33c02afe1af2fe194debd24903550f99f267c6e53b38d9d757bc | MATLAB | 10,252 | 231 | % flight_orientation extracts key descriptors of the animals' flight
% during the approach, the probing phase and the departure.
% These are forward and rotational flight speed and predominant rotation direction,
% as well as body angle relative to the pattern axis.
% The output is saved as a flightORI_filename... |
c7ae2e0f9a74b2672061c9d89071a5f7aa78a0fb6651d43958d2577cc708b0dc | MATLAB | 10,264 | 310 | function [x,f,info] = lbfgsb( fcn, l, u, opts )
% x = lbfgsb( fcn, l, u )
% uses the lbfgsb v.3.0 library (fortran files must be installed;
% see compile_mex.m ) which is the L-BFGS-B algorithm.
% The algorithm is similar to the L-BFGS quasi-Newton algorithm,
% but also handles bound constraints via an acti... |
9bbe20089d834406f94953769367fd9c44f4ca8a621dbefb49eaaf788b56ce4b | MATLAB | 10,272 | 239 | clear; clc;
subjectID = 'P3';
sessionDate = 20230831;
stimElectrode = [2:30, 32:61, 63,64];
motorChannel = [1:64, 97:192, 225:256];
freqId = 100;
numData = length(motorChannel);
sortedSpikes = 0;
saveData = 1;
% PTA Folds
numFolds = 10;
dataFolder = sprintf('/%i/', sessionDate);
%% Analysis Start
sm.subjectID = su... |
8ee33a81199e4635ec293f5ae1db125902dd7f4ca2b93a89b2aa5d354649df93 | MATLAB | 10,284 | 306 | function nvr_begin_sampling
% This function will setup and begin data acquisition.
global nvr
% global daqin
global host
% GQ 09-29-09
%----------------------------------------------
if (isunix)
[rc host] = dos('hostname');
host = lower(strtok(host,'.'));
else
host = lower(getenv('hostname'));... |
0b1abda3f4d7dd2dd42906ea198f39c9776a3a072e6f6d8469b1abd4a12ddd60 | MATLAB | 10,295 | 262 | % Arrange data for statistical testing
close all;clc
regList = {'INS'} % HC CA3 CA1 OFC FRO TEMP CING INS EC
acrsTrls = 'no';
clustercorect = 'maxsum'; %maxsum maxsize ws
addpath('/mnt/yassamri/iEEG/sandra/analysis_pipeline_final')
[fro_chan_idx,MTL_chan_idx,temp_chan_idx,insula_chan_idx,cingulate_chan_id... |
3575f160cc54ad10d43f12cfe74b539d8e95ee92574e71936b3d03c99c99c9fb | MATLAB | 10,298 | 228 | % BATCH ANALYSIS THROUGH FOLDERS PIPELINE
function batch_analysis_folders(option,computer,varargin)
% option: 1- spikes & video ; 2 - position & laps ; 3 - sleep ; 4 - CSC & PSD ;
% 5 - Place cells, bayesian & replay decoding ; 6 - replay section(scores, shuffles) ; 7 - see replay
% varargin: [] or 'all'
% com... |
e0b00ac2d36aa19f4290f1f1ac8c6de69422f847f78e8daead1d1c36fdeac9b3 | MATLAB | 10,307 | 282 | function [outPeakIndices, outImportances] = IPEMOnsetPeakDetection1Channel(inSignal,inSampleFreq)
% Usage:
% [outPeakIndices, outImportances] = ...
% IPEMOnsetPeakDetection1Channel(inSignal,inSampleFreq)
%
% Description:
% Returns the indices of the "important" peaks in the input signal,
% together wit... |
e8783620849e566fb99f87ac594c7bf9cc1234a662223ef12c34371a46380f9e | MATLAB | 10,330 | 260 | function [labels, names, colors, line_styles] = fn_performanceRL_regressor_label_styles(model_id)
%% Converts the name of a model into regressor labels, plotting colors/styles
% Future:
% add unsigned distance metrics
% add categorical 0/1 if becomes necessary
% colors from http://colorbrewer2.org/#type=qualitative... |
cbea5252da2641593898812f6b52047a658c98015446252461eae949b1b34156 | MATLAB | 10,333 | 264 | function [A, bcol] = print2array(fig, res, renderer, gs_options)
%PRINT2ARRAY Exports a figure to an image array
%
% Examples:
% A = print2array
% A = print2array(figure_handle)
% A = print2array(figure_handle, resolution)
% A = print2array(figure_handle, resolution, renderer)
% A = print2array(figure_handle... |
b460e64812fc323757f2024ea589ec7a34dbd8a521860311dde178691cfbe788 | MATLAB | 10,348 | 276 |
%% mapping settings
mapset = struct;
mapset.padding = 0; % in mm
mapset.mindwell = 0; % (default 0.1) total number of seconds that rat has to be in a bin for it to be filled, for adaptive m... |
65e8816220f96e52f7b4d757e44c2312f9755dbca8ea052674e025d2af020d14 | MATLAB | 10,372 | 268 |
[filename,pathname] = uigetfile({'*_CLUSTERS.mat';'*_CLUSTERS.MAT'},'Open file with assemblies data', 'MultiSelect', 'off');
filenameCLUSTER=fullfile(pathname,filename);
load(filenameCLUSTER);
cutName=strfind(filenameCLUSTER,'_CLUSTERS.mat');
dataAllCells=load([filenameCLUSTER(1:cutName-1) '_ALL_CELLS.mat']);
load([... |
4f8ee0e11deecbe4bab3421bec9b6049e147f227951edec21fe056051b39912f | MATLAB | 10,379 | 232 | function lf = fun_graph_get_link_features(link_cc, vessel_image, vessel_mask_dt, link_feature)
% fun_graph_get_link_w_1_ep_features computes the features derived from the
% position and orientation of endpoints and their nearest neighbor
% Input:
% ep_sub: N-by-3 numerical array, where N is the number of endpoin... |
978c34f75ad9df2eb78023c3a6a46716b1950a7c21cb8d7e9fba81ea9b613c67 | MATLAB | 10,381 | 275 | function Figure_8BC_plot
%
% Written by Ayaka Matsumoto, October 2023
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Output: Figures 8B and 8C
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% ... |
0e6cd9db2cd7b5dee19a05d2816d784970f5b1b89fe2c29799f3013a88133019 | MATLAB | 10,387 | 221 | function gap_linking_str = fun_graph_get_linker_ep2skl_same_cc(vessel_image, vessel_mask, vessel_skl, ep_sub, ep_all_sub)
% fun_graph_get_linker_ep2skl use threshold relaxation and shortest path on
% designed metric to find a 3D line segment that connect the inut endpoint
% to a skeleton voxel in the nearby connected c... |
c553924cda187e09839e2994393e1b09fb6197539bb83f52d4f7d3b7652c7c60 | MATLAB | 10,391 | 244 | function SBJ08h_HFA_plot_grp_mLME_chancoef(proc_id, an_id, model_id, stat_id)
if exist('/home/knight/hoycw/','dir'); root_dir='/home/knight/hoycw/';ft_dir=[root_dir 'Apps/fieldtrip/'];
else root_dir='/Volumes/hoycw_clust/'; ft_dir='/Users/colinhoy/Code/Apps/fieldtrip/';end
addpath([root_dir 'PRJ_Error/scripts/']);
add... |
a49dd7a1b97ad21107031c11237b332b12531867347cea6518a5a84702fb8171 | MATLAB | 10,421 | 287 | function [bestIndv,bestScore,report] = ...
copasiep_mod(objfun,numParents,numGeneration,lb,ub,opt)
%%% This function searches x which minimize objfun(x) by using evolutionary
%%% programming method of Copasi (biochemical simulator software). Because
%%% this function uses random generator, you should write wrap... |
599edc29146bbd5935af5cf5ac56d560587f3756b3a88a378ed0d6aa547991a0 | MATLAB | 10,437 | 213 | clear all
rec_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
spath = 'C:\Users\xscogno\Dropbox\SfN2019\Development\Rasterplots\L9M1\';
mouse='L11M2'; %Name of the animal
V1=0;
load([rec_path,strcat('recording_dates_',mouse,'.mat')]);
% Data and... |
f63845dce6e2fc0f6d2a8ac14c8c464ea3b9b3fca60b964eb3228eadf44327e3 | MATLAB | 10,438 | 384 | function ob = Gtomo2_table(sg, ig, table, varargin)
%function ob = Gtomo2_table(sg, ig, table, options)
%|
%| Generate a 2D parallel-beam tomographic system model
%| based on finely tabulated footprints.
%|
%| in
%| sg strum sino_geom()
%| ig strum image_geom()
%| table [Ktab Ltab] footprint table, see book: s,geom,... |
f3713281ff2f8caeada24a130c68c5d4ae5aec949c0f868a11c0e16bab585929 | MATLAB | 10,449 | 296 | %% ============================================================
% FINAL CORRECTED CODE - fNIRS LOSO
% - Proper baseline correction using Rest periods as reference
% - Uniform prior
% - Metrics: Accuracy + Precision, Recall, F1-weighted, F1-macro
% - Classifiers: LDA | SVM (C=0.5) | KNN (Grid 1-27) | QDA (diagQuadr... |
ddf0fab43df211d0aaa55cd6526ae45d280920aa4f771c299b35f1868b252a80 | MATLAB | 10,468 | 306 | function varargout = spm_surf(P,mode,thresh)
% Surface extraction
% FORMAT spm_surf(P,mode,thresh)
%
% P - char array of filenames
% Usually, this will be c1xxx.<ext> & c2xxx.<ext> - grey and white
% matter segments created using the segmentation routine.
% mode - operation mode [1: rendering, ... |
b0f0a7a70e48c4098addaec3dbebb50360728ad5263a044ee49bde54f73a49c0 | MATLAB | 10,470 | 277 | function [strout,R2] = spm_str_manip(strin,options)
% miscellaneous string manipulation options
% FORMAT string_out = spm_str_manip(string_in,options)
% string_in - input string, string matrix, or cell array of strings
% options - a string of options flags, see below
%
% string_out - output string, string mat... |
436a4a5eefc607a9b2bc12d78214c95e103135f307213d3e15497c5223f28269 | MATLAB | 10,477 | 349 | function fig = plotNumberOfSynapses(obj,plotType,oldFig)
if(obj.plotFigures == 0)
disp('plotNumberOfSynapses: plotFigures = 0, hiding figures!')
visFlag = 'off';
else
visFlag = 'on';
end
if(exist('oldFig') & ~isempty(oldFig))
% This is currently only supported for the cumdist plots
ass... |
b723b0a636aaf86828da6529058c0fea94f3b7a612026e598ed365468b10ee7e | MATLAB | 10,478 | 226 | function handles = segmentImage( handles )
%%%%% Start: Perform First Stage of Image Segmentation
if true
%---- Start: Create Vectors Necessary for Proper Neighbor Tallying
row = handles.basePic.ySize;
col = handles.basePic.xSize;
pR = [1 1:row-1];
qR = [2:row row];
pC = [1 1:col-1];
qC = [2:col col];
%-... |
a701cda65dacf6b38e5bbbe4dd7b5c08c817e4f7fe2e5c51ddd6f474a8070655 | MATLAB | 10,479 | 239 | function myHardwareSetup
% This function sets all basic parameters of the hardware in your setup.
% This function needs to be stored on each experimental computer. All
% required hardware definitions are stored in the global variable SETUP
% created by this function. Edit this function when building a new setup.
% Desc... |
4c2a116400c68ec715e7f413b41da3b36b3f5acc1b08ea85f76fad201fd98507 | MATLAB | 10,480 | 239 | function myHardwareSetup
% This function sets all basic parameters of the hardware in your setup.
% This function needs to be stored on each experimental computer. All
% required hardware definitions are stored in the global variable SETUP
% created by this function. Edit this function when building a new setup.
% Desc... |
c62398a09ea841a9981c03d053126106cd666334d1d0c77a4c32a573c2038517 | MATLAB | 10,481 | 239 | function myHardwareSetup
% This function sets all basic parameters of the hardware in your setup.
% This function needs to be stored on each experimental computer. All
% required hardware definitions are stored in the global variable SETUP
% created by this function. Edit this function when building a new setup.
% Desc... |
f91f378163aa8115e076668f9294cc4813d9cedf2150cbf11a44fa56b9e9562e | MATLAB | 10,481 | 310 | function [SPM] = spm_mfx(SPM,c)
% Convert a 1st-level design specification into a MFX specification
% FORMAT [SPM] = spm_mfx(SPM,c)
% SPM {in} - design and estimation structure after a 1st-level analysis
% c - contrast used to define 2nd level design matrix. If this is
% not specified spm_mfx will (1)... |
f89b549e0a1bf6ddfaa82805d042ef8b02b0eefdf79f337714acc4aea1d93420 | MATLAB | 10,493 | 238 | function [fNum] = plotBaselineKinematics(f_orcoAll,border,fNum)
fNumInitial = fNum;
fNum = fNum+2;
nGen = numel(f_orcoAll);
stateDistEarly = cell(4,nGen);stateDistLate = cell(4,nGen);stateDistBefore = cell(4,nGen);
baselineEarlyRankSum = nan(7,nGen);
baselineLateRankSum = nan(7,nGen);
baselineAllRankSum = na... |
b2d25da82a66c36cf683569f90d66cddec7064b718625f3f7e3468bd10149366 | MATLAB | 10,523 | 397 | function wi = ir_mri_density_comp(kspace, dtype, varargin)
%function wi = ir_mri_density_comp(kspace, dtype, varargin)
%|
%| todo: THIS NEEDS A LOT OF WORK!
%|
%| Compute density compensation factors for the conjugate phase method
%| for image reconstruction from Fourier samples.
%|
%| in
%| kspace [M d] kspace sample... |
897fbc6a7b43ecb69048979fc32c8ddccd0f2e30688678143587d1cde2ee1627 | MATLAB | 10,524 | 239 | function myHardwareSetup
% This function sets all basic parameters of the hardware in your setup.
% This function needs to be stored on each experimental computer. All
% required hardware definitions are stored in the global variable SETUP
% created by this function. Edit this function when building a new setup.
% Desc... |
ad4d88d329dd22b74168d397cfac6344eed875cde937c598d682545607a376fd | MATLAB | 10,536 | 225 | function [turnBias,turnBiasRaw,XX,YY,turnBias_baseline,turnBias_during_baseline,turnBias_during_baseline_byRPos] = ...
getKNNProbTurnIn(f_orco, s, keyNdx, xGrid, yGrid, zGrid, ratio, ...
Thresh, K, state, border, genotype, plotFig)%f_orco, condNdx
% getKNNProbTurnIn calculates the turn optimality in the KN... |
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