sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5be22deabf2307e9785d43e753315ebacf196f031132086dc4e5bb64ca06ab1b | MATLAB | 8,289 | 223 | function hdr = read_yokogawa_header(filename)
% READ_YOKOGAWA_HEADER reads the header information from continuous,
% epoched or averaged MEG data that has been generated by the Yokogawa
% MEG system and software and allows that data to be used in combination
% with FieldTrip.
%
% Use as
% [hdr] = read_yokogawa_heade... |
04d4129bfffa8229cb7429be3d2f6f52fee9d84c88b3e65c4c9efdc83ce69dec | MATLAB | 8,295 | 199 | function [optimal_acc, optimal_kernel, optimal_lambda, optimal_threshold] = ...
CBIG_KRR_pick_optima( sub_fold, data_dir, stem, bin_flag, ...
ker_param, lambda_set, threshold_set )
% [optimal_acc, optimal_kernel, optimal_lambda, optimal_threshold] = ...
% CBIG_KRR_pick_optima( sub_fold, data_dir, stem, bin... |
693d4385a9d3ffe4413e97af5b6d6099d5a0b3e1ab8b2d9a47fe3afdd07a09f5 | MATLAB | 8,295 | 309 | clc;clear all;close all
V = BrikLoad ('ambmc_ori_100+orig');
LABEL = BrikLoad ('Allen_label_AMBMC_R+orig');
LABEL_L= BrikLoad ('Allen_label_AMBMC_L+orig');
LABEL_L(LABEL_L~=0)= LABEL_L(LABEL_L~=0)+865;
LABEL=LABEL+LABEL_L;
V=reshape(mapminmax(V(:)',0,1),size(V));
az=45;el=45;
%%
load ADresultallnew.mat
Mcc... |
ed251642f71017bba048a3dd4a77ef2c1020e8d42d4aeccd05a5c453fc5712cc | MATLAB | 8,295 | 214 | function figHandle = plotEventSpikingExampleEvent(clusterMembershipMatrix, anyClusterIsActive, eventClustWiseRateSmoothed, eventRasterE, modelParam, analysisParam)
% figHandle = grid.plotEventSpikingExampleEvent(...);
%
% Plots example event with cluster-wise rates and raster plots.
% Called within
%
% TODO: Index the ... |
74b6a386b72717135aeb39ae41c2d9368d6941562cdfd1a26dd4e357f11b0689 | MATLAB | 8,298 | 223 | function hdr = read_yokogawa_header(filename)
% READ_YOKOGAWA_HEADER reads the header information from continuous,
% epoched or averaged MEG data that has been generated by the Yokogawa
% MEG system and software and allows that data to be used in combination
% with FieldTrip.
%
% Use as
% [hdr] = read_yokogawa_heade... |
cc7167dfd14e407df5d899dae31b373e041437005fbdd857fd5c7e6302e4c1de | MATLAB | 8,300 | 137 | function prepare_data_for_regression(varargin)
% INPUTS: name value pairs
% 'option': 'wcorr','spearman' or 'linear' (in the future)
% 'epoch': any epoch in rate_remapping_TRACK_PAIRS_option.mat
% OUTPUT:
% saves data_for_regression table of cell ID - event - track replayed- num spikes etc..... |
d9f4402bf3bc581e4cc8100adb80f9291eb330dd07626e03e53a6d2247c064de | MATLAB | 8,301 | 229 | function dataMatrixNorm = BF_NormalizeMatrix(dataMatrix,normMethod,isTraining)
% BF_NormalizeMatrix Normalizes all columns of an input matrix.
%
%---INPUTS:
% dataMatrix, the input data matrix
% normMethod, the normalization method to use (see body of the code for options)
% isTraining, learn the normalization param... |
0360f81a067385d23d0468c08a6259c68ac16813f31a1647361511c8fb4bb9fa | MATLAB | 8,304 | 194 | disp(' ');
disp('fdct_wrapping_demo_denoise_enhanced.m - Image denoising using Curvelets');
disp(' ');
disp('This is an extension of the file fdct_wrapping_demo_denoise.m')
disp('We try different tricks to obtain better image denoising: (1) curvelets');
disp('at the finest scale, (2) complex block thresholding, (3) cyc... |
2a2a1296507367e2bd53f2dccc840da899096f955dba9351e06c274db654f6c2 | MATLAB | 8,304 | 243 | classdef MFTSet < handle
% An MFTSet is a set of movies/frames/targets in an APT project.
%
% Conceptually, it is the 4-way cross product of i) a movie
% specification (eg "current movie"), ii) a frameset specification (eg
% "frames 1:100", iii) a target specification (eg "all targets") and iv)
% a decimati... |
2eb067fc81fe0573e6151d730b1c11fc8aab350f2b7e1302f2c6b1de3e908eef | MATLAB | 8,305 | 222 | function [out] = mediationAnalysis0(Y,X,M,options)
% performs a simple mediation analysis
% function [out] = mediationAnalysis0(Y,X,M)
% Let us consider the following regression equations:
% M = X*a + e_M
% Y = M*b + X*c + e_Y
% where X is the independent variable, M is the mediator variable and Y is
% the dependent va... |
e8cbb40308be6fce1f1ab0815a31282f03215dd13e32700708cd59a7566dbd24 | MATLAB | 8,308 | 211 | function [acc, pred_stats] = CBIG_KRR_test_cv_allparams( test_fold, sub_fold, ...
data_dir, y_resid_stem, with_bias, ker_param, lambda_set, threshold_set )
% [acc] = CBIG_KRR_test_cv_allparams( test_fold, sub_fold, ...
% data_dir, y_resid_stem, ker_param, lambda_set, threshold_set )
%
% For a given test fold,... |
f598d1ad6730f01c92c579bd5e128c4b33a32f5df6415df0dcdba8e246bd2882 | MATLAB | 8,310 | 278 | function [P, Tx, Ty] = dTrilinears2d(T,x,y,hx,hy,bc)
%function [P, Tx, Ty, Tz] = dTrilinears(T,x,y,z,hx,hy,hz,bc)
% Rena 02/20/2017: allows mass to enter/leave through boundaries so mass is
% not necessarily conserved.
% Use linear interpolation to evaluate (approximate) the values of T in the
% grid (x,y,z)
% That = T... |
3adbdc2d7fb4879a26f83ec8192cd3ff100d48d267f7b46558f25e392d1a7865 | MATLAB | 8,311 | 266 | %% Creating test problems and initial guesses
% We demonstrate how to use Tensor Toolbox |create_problem| and
% |create_guess| functions to create test problems for fitting algorithms.
%% Creating a CP test problem
% The |create_problem| function allows a user to generate a test problem
% with a known solution having... |
d63846f1c0ac9290e4b453c93e29fcf07038efbca3171c5742343123da2a37e3 | MATLAB | 8,313 | 190 | function [data,varargout] = femdata_FD(mesh, frequency, varargin)
% FEMDATA_FD Calculates data (phase and amplitude) for a given mesh at a
% given frequency (Hz). Outputs phase and amplitude in the structure
% DATA. This function is a wrapper to call mesh-type-specific femdata
% functions.
%
% SYNTAX:
% [DATA] ... |
f7c7fe3f80002ff7d45dd7f79cfe8bda3884d3f19570fbc5df906604be7ec69f | MATLAB | 8,316 | 139 | %% 共空间模式 | common spatial patterns (CSP) 不可在main中调用，仅可单独使用
%% one vs rest Multiclass or two-classes 白化法
% how：N个类别得到N个投影矩阵，对每个投影矩阵取最佳的2m个方向（前后各m个），特征矩阵为2m*N维
% 优点：N类需要计算N个投影矩阵，即使N很大，计算量也不会很大
% 缺点：由于rest类别是混合类别，内部特征并不统一，因此很难找出最优的投影方向，即结果可能并不是最优的
% 注意：在计算CSP投影矩阵时，并非使用整个trial，而是将trial划分出若干segments，
% 对每个segments提取CSP特... |
5379224bb4e593908e9da5cf64633188c45b3a6d05262f99c04968ff72fcdc49 | MATLAB | 8,317 | 201 |
% Written by: Tianyin Xu
% Edited by: Qiuting Wen, Adam Wright
% Last modified: 20240711
% Inputs:
% physio -- the physio file with slicetiming and output physiology measures (output of readCMRRPhysio.m)
% Outputs:
% locs -- locations of peaks on ppg
% pulsesmooth -- smoothed version of the pulse timeseries.
% QC ... |
874bed8614dbf84d713ade6c7f224cc7b98ef1dc562acbb958d8b41588a50fe5 | MATLAB | 8,321 | 243 | function [dat] = ft_fetch_data(data, varargin)
% FT_FETCH_DATA mimics the behavior of FT_READ_DATA, but for a FieldTrip
% raw data structure instead of a file on disk.
%
% Use as
% [dat] = ft_fetch_data(data, ...)
%
% See also FT_READ_DATA, FT_FETCH_HEADER, FT_FETCH_EVENT
% Copyright (C) 2009-2013, Jan-Mathijs Scho... |
927fd5500d943384eb30fc688ed614b17e411e7420417e1e9ef0e0b57a1af045 | MATLAB | 8,321 | 203 | function [stepsize, newx, newkey, lsstats] = ...
linesearch(problem, x, d, f0, df0, options, storedb, key)
% Standard line-search algorithm (step size selection) for descent methods.
%
% function [stepsize, newx, newkey, lsstats] =
% linesearch(problem, x, d, f0, df0, options, st... |
3926dac8230910da2e14ebdb5bd8b655ddbd7c79584ed4c1a5b891622de010d5 | MATLAB | 8,324 | 235 | function [dat] = ft_fetch_data(data, varargin)
% FT_FETCH_DATA mimics the behaviour of FT_READ_DATA, but for a FieldTrip
% raw data structure instead of a file on disk.
%
% Use as
% [dat] = ft_fetch_data(data, ...)
%
% See also FT_READ_DATA, FT_FETCH_HEADER, FT_FETCH_EVENT
% Copyright (C) 2009-2013, Jan-Mathijs Sch... |
f50850edde4d3307002a1cae5d04e61db62f1b021bbdd8a838b8f97cadeea0ef | MATLAB | 8,326 | 218 | function [U,varargout] = lfmm3d(eps,srcinfo,pg,varargin)
% LFMM3D FMM in 3D for Laplace (electrostatic) kernels.
%
% [U,varargout] = lfmm3d(eps,srcinfo,pg,varargin)
%
% Laplace FMM in R^3: evaluate all pairwise particle
% interactions (ignoring self-interactions) and possibly
% interactions with targets, using t... |
40dacae026accb2025248389ed805700373139a796ca6f4600b7d67357c9e1fc | MATLAB | 8,330 | 151 | format compact;
Int_main_folders = ''; % main working directory
ShortNames = {'R1_6hr','R1_24hr','R1_72hr','R2_72hr','R2_24hr','R2_6hr'};
Int_Results_folders = {}; % 6 folders to save the results
Int_RawImage_folders = {'Folder1', 'Folder2', 'Folder3', 'Folder4', 'Folder5', 'Folder6'}; % 6 Raw Tiff image folders
... |
66ba202d174ae626e422944ac3772595785e711a0362389a36f516e79fa82be0 | MATLAB | 8,334 | 227 | function [pos, tri] = headsurface(headmodel, sens, varargin)
% HEADSURFACE constructs a triangulated description of the skin or brain
% surface from a volume conduction model, from a set of electrodes or
% gradiometers, or from a combination of the two. It returns a closed
% surface.
%
% Use as
% [pos, tri] = headsu... |
13dada14f4ed04d509a508a688f443b7c54041f406a694ae335f761cedf73421 | MATLAB | 8,335 | 209 | function varargout = h_makeMovieGUI3(varargin)
% H_MAKEMOVIEGUI3 M-file for h_makeMovieGUI3.fig
% H_MAKEMOVIEGUI3, by itself, creates a new H_MAKEMOVIEGUI3 or raises the existing
% singleton*.
%
% H = H_MAKEMOVIEGUI3 returns the handle to a new H_MAKEMOVIEGUI3 or the handle to
% the existing s... |
66067cd9bfbd984b385d2641529e43f917a45624a52e92cc285d0d59364e8abe | MATLAB | 8,337 | 195 | function [ROISignals] = y_ExtractROISignal_Surf(AllVolume, ROIDef, OutputName, AMaskFilename, IsMultipleLabel, ROISelectedIndex, GHeader, CUTNUMBER)
% [ROISignals] = y_ExtractROISignal_Surf(AllVolume, ROIDef, OutputName, AMaskFilename, IsMultipleLabel, ROISelectedIndex, GHeader, CUTNUMBER)
% E... |
a36445773b23ca562917acefa6ef35bdb12d7c8b4afa049a6c6c5ccac58f41bb | MATLAB | 8,338 | 218 | % Second-kind integral equation on the unit sphere, Laplace double-layer.
%
% This is essentially the 3D version of IE_CIRCLE, where now the geometry is the
% unit sphere represented using flat triangles. The system is discretized via
% collocation with tensor-product Gauss-Legendre integration for the near-field
% pan... |
7a0fb50645140b80a5aea2b5aa34e2c9f954e7ce8df8b1dae26647c814ca66d8 | MATLAB | 8,350 | 295 | function model_handcrafted = handcraft_model(model,fixed_points,fp_linsys,components1,components2)
factor_weights = 1;
components1=abs(components1);
components1=components1/sum(components1);
components2=abs(components2);
components2=components2/sum(components2);
n_units=length(model.wO);
%%% output of the network... |
996b1e437345ccd0bb6f00697aad609b74a298d369cbe38bca99ec1f540cd406 | MATLAB | 8,350 | 211 | function [first2PCs,analysisInfo] = PCA_DN_analysis(thresh,plotFig)
rng("default")
addpath(genpath('Utils'));
%clear;
close all;
dataLoc = [pwd '\Data\'];%\RConnectomicsAnalysis\Data\
dataFile = 'CL_aIPg_pC1_2ndOrderConn.mat';
load([dataLoc dataFile],'effDF_singleNeuron','inpN','inpN_hemisphere','inpN_type','out... |
825a006fca2f4582f65dd88bd537c98e0ccc3fca98a69d50c6caa2a981bdfbff | MATLAB | 8,353 | 252 | % Seizure Imaging Using FATS-IRES
% 3D - Rotational Dipole
% Abbas Sohrabpour
% 5/8/2018
% Load the lead field, etc.
close all; clear all; clc
cd('../Grid Location and Defined Parameters')
load('UnconstCentLFD.mat')
Norm_K = svds(K,1)^2;
load('Gradient.mat')
load('Laplacian.mat')
load('NewMesh.mat')
load... |
2c44e8ae8e3f8c5ced6f07d3f3998744069a6976b6ebc74aad00631720e6b8ff | MATLAB | 8,354 | 178 | function DynamicFC_plot(config)
% DynamicFC_plot creates ROI x ROI heatmap of dfc values for all specified
% participants and visits, from data calculated by Step4c_DynamicFC
%
% Configuration structure (config.DFCplot) must contain:
% pids: patient ids to be included in heatmap
% visitnum: cell array conta... |
48cf15736c8be67e7f2aca40c534440d0de3e12c92fd6f03e2806a377f409d4d | MATLAB | 8,360 | 236 | function dataOut=fcBx_Enrich_1tp(fc,Bx,IM,params)
% Perform the correlation analysis (type = {Pearson, Spearman}),
% and enrichment analyses using Chi-square and Hypergeometric stats.
% fc is the Fisher-z fc-data; Nseeds-Nseeds-Nsubj
% Bx is the behavior data; Nsubj
% IM is the ROI-to-module key.
% params.type determ... |
2466ab21d6bc02281a8d7d3954be40c5a4086c08b1f5300ae48a67759592fa35 | MATLAB | 8,363 | 206 | function CBIG_MMLDA_example_wrapper(out_dir, queue)
% Written by Nanbo Sun and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
CBIG_CODE_DIR = getenv('CBIG_CODE_DIR');
addpath([CBIG_CODE_DIR '/stable_projects/disorder_subtypes/Sun2019_ADJointFactors/step2_MMLDA'])
doc_dir = [CBIG... |
dcdfd41b1950292ef64ee8bda2b8ad34bef83c41add21fdfd5cbcbfb121de6df | MATLAB | 8,364 | 205 | function varargout = w_ApplyAdditionalMask(varargin)
% W_APPLYADDITIONALMASK MATLAB code for w_ApplyAdditionalMask.fig
% W_APPLYADDITIONALMASK, by itself, creates a new W_APPLYADDITIONALMASK or raises the existing
% singleton*.
%
% H = W_APPLYADDITIONALMASK returns the handle to a new W_APPLYADDITIONALMA... |
e307401337f38960fa91fbfa2b579c96ebefae1f2b1557588330314aaabd6945 | MATLAB | 8,368 | 223 | function [str, tag, cind] = gencode(item, tag, tagctx)
% GENCODE Generate code to recreate any MATLAB struct/cell variable.
% For any MATLAB variable, this function generates a .m file that
% can be run to recreate it. Classes can implement their class specific
% equivalent of gencode with the same calling syntax. By... |
7a937fba7483fbde621b4926b6a674f1123f785e4d0b14f0b3f48984f6f13586 | MATLAB | 8,373 | 190 | function [hc] = read_ctf_hc(filename)
% READ_CTF_HC reads the MEG headcoil marker positions from an ascii file
% and computes the coordinate transformation required to get from from
% dewar to head-coordinates
%
% the definition of head coordinates is according to CTF standard:
% - the origin is exactly between LPA an... |
6b5bf3abf42678b31c6062ded368a9e2a8773e8ba6a17aaca88c76a8be7e1976 | MATLAB | 8,376 | 210 | function [ind, int_func] = mytsearchn(mesh, coord)
% MYTSEARCHN carries out a spatial point location search within the MESH.
%
% [IND, INT_FUNC] = MYTSEARCHN(MESH, COORD) Determines which, if any,
% MESH element a given point (COORD) falls in:
% MESH - FEM mesh in NIRFAST format, can be 2D (triangels) or 3D
% ... |
ea77fdd74d3b50161ac4b6b549b056173b2b40a530738b244bedd8d4abe6d298 | MATLAB | 8,381 | 257 | function smoothed = Smooth(data,smooth,varargin)
%Smooth - Smooth using a Gaussian kernel.
%
% USAGE
%
% smoothed = Smooth(data,smooth,<options>)
%
% data data to smooth
% smooth vertical and horizontal kernel size:
% - gaussian: standard deviations [Sv Sh]
% ... |
24d866d86341fcc96bd8a701764f970bb07e3588caae87cf8be60cfa20991d1f | MATLAB | 8,383 | 233 | function [data] = ft_determine_coordsys(data, varargin)
% FT_DETERMINE_COORDSYS plots a geometrical object, allowing you to perform
% a visual check on the coordinatesystem, the units and on the anatomical
% labels for the coordinate system axes.
%
% Use as
% [dataout] = ft_determine_coordsys(datain, ...)
% where th... |
7b457382e316ddde801f8a70130fc001003b93317ab432e70b4a5d98bc3ac29d | MATLAB | 8,397 | 202 | % Bone aging test script.
% * processing of different datasets such as IXI, CAMCAN and NKI datasets
% of healthy (adults) subjects with full age range
%
% * Evaluation of the current version by (not including image data but CSV files?) ...
% * BMD measures in the UKB (non public by UKB)
% * Hammers data?
% * ... |
e6d7bd587ad13f1146eb8acf736b611214e7a7982e65a855bbc8d6792ba6539f | MATLAB | 8,400 | 200 | function [seizureCell, seizurePaths] = getAllSeizureInfo(subjectNames, dataPath, electrodeLocation, varargin)
% subjectNames = names;
% dataPath = datapath;
% electrodeLocation = params.electrodeLocation;
% bilateral = false;
% FUNCTION INFORMATION: Lick task analysis pipeline
% Created by: Abdo Sharaf - abdo.sharaf@... |
fa8d800860434b395a6f88eb232c0c339052fc4793251ad4b7cb41affc46fc66 | MATLAB | 8,400 | 272 | function [tets, points_from_tetgen] = checkerboard3d(e,p,myargs)
% Creates a solid (tetrahedral mesh) using the surface mesh defined in 'e'
% and 'p'.
% myargs is a structure of following format:
% myargs.{silentflag,bdyfn,regions,edgesize,examineinpmesh}:
%
% myargs.silentflag: if it is 1, it will assume that user d... |
72c625001e87528b5b5d6dfd71a9671e488dd0da685664985235326951484312 | MATLAB | 8,408 | 198 | function [cfg] = ft_definetrial(cfg)
% FT_DEFINETRIAL defines the segments of data that will be used for
% further processing and analysis, i.e. the pieces of data that will
% be read in by FT_PREPROCESSING. Trials are defined by their begin
% and end sample in the data file and each trial has an offset that
% defines... |
81a7b3950e64cbc93a07614897577993d65f01670132640ce0a4796de88a6ff5 | MATLAB | 8,410 | 242 | function varargout = eval_objfun(net, init_condition, v_u_t, m_target_t, forward_pass)
%% Setup.
% Network structure.
[n_Wru_v, n_Wrr_n, m_Wzr_n, n_x0_c, n_bx_1, m_bz_1] = unpackRNN(net, net.theta);
[V,T] = size(v_u_t);
[M,N] = size(m_Wzr_n);
% Transfer functions.
rec_transfun = net.layers(2).transfun;
out_transfun = ... |
0df5fe29f7c1a630fa42d29e121fb5936e2a64985775c6d00b7c6fcae6630207 | MATLAB | 8,414 | 191 | function varargout = ManuallySelectSeries(varargin)
% MANUALLYSELECTSERIES MATLAB code for ManuallySelectSeries.fig
% MANUALLYSELECTSERIES, by itself, creates a new MANUALLYSELECTSERIES or raises the existing
% singleton*.
%
% H = MANUALLYSELECTSERIES returns the handle to a new MANUALLYSELECTSERIES or t... |
3b94018de91eb2444ffea9462c0b9508375de24b70d463de51c83ebf638fc80e | MATLAB | 8,418 | 310 | %epa_bias Analyze guesses during the endogenous pro/anti experiment
%
% This script analyzes the performance of all the participants during
% the guessing (i.e., short-rPT) trials of the endogenously driven
% pro/antisaccade (EPA) task. It reproduces Figure 5 of the paper by
% Goldstein et al.
%
% Reminder: the... |
83a4577be0e4644fafff3b9d27da46821d6e6b8695dd0064450182ee917384dc | MATLAB | 8,419 | 159 | function BioSigKitPanel(obj)
%% ================= Sets up BioSigKit GUI ====================== %%
%% ============== Licensce ========================================== %%
% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
% "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
% LIMITED... |
e195b616d553e499e7c2d46f5f89b6d84814085750624cf4340a378f0a80cb63 | MATLAB | 8,419 | 153 | function w_DCMSort(DICOMCells, HierarchyValue1, HierarchyValue2, Prefix, IsAddDate, IsAddTime, FolderIndex, AnonyFlag, OutputDir)
% Format w_DCMSort(DICOMCells, HierarchyValue, AnonyFlag, OutputDir)
% Input:
% DICOMCells - The DICOM File from N subjects N by 1 Cells
% HierarchyValue1 - First layer ... |
22d9043b473f5eb9548695431ca74d3cc65d8020631cc4ac92b20f43d7ab9ba5 | MATLAB | 8,420 | 181 | function [ALFFBrain, fALFFBrain, Header] = y_alff_falff(AllVolume,ASamplePeriod, HighCutoff, LowCutoff, AMaskFilename, AResultFilename, TemporalMask, ScrubbingMethod, Header, CUTNUMBER)
% Use ALFF method to compute the brain and return a ALFF brain map which reflects the "energy" of the voxels' BOLD signal
% Ref: Zan... |
7ea5d20e25327c48318a8f4173c959e04ce2f47323325d3bc0cabf9bd7924b0f | MATLAB | 8,421 | 281 | function [tfr,t,f]=tfrspaw(X,time,K,nh0,ng0,fmin,fmax,N,trace);
%TFRSPAW Smoothed Pseudo Affine Wigner time-frequency distributions.
% [TFR,T,F]=TFRSPAW(X,T,K,NH0,NG0,FMIN,FMAX,N,TRACE)
% generates the auto- or cross- Smoothed Pseudo Affine Wigner
% distributions.
%
% X : signal (in time) to be analyzed. If X=[X1 X2]... |
50628e25f2a9b60c893915a748489523bb980f84a18adb3baa1cd57cdbf8da8e | MATLAB | 8,425 | 290 | function h=MyEllipse(varargin)
% ERROR_ELLIPSE - plot an error ellipse, or ellipsoid, defining confidence region
% ERROR_ELLIPSE(C22) - Given a 2x2 covariance matrix, plot the
% associated error ellipse, at the origin. It returns a graphics handle
% of the ellipse that was drawn.
%
% ERROR_ELLIPSE(C33) - Gi... |
3eaad98d47f49e503eab502eba3e10a2109af1b86508ec57bdb7b870e13522b2 | MATLAB | 8,428 | 219 | function [stat] = ft_timelockstatistics(cfg, varargin)
% FT_TIMELOCKSTATISTICS computes significance probabilities and/or critical values of a parametric statistical test
% or a non-parametric permutation test.
%
% Use as
% [stat] = ft_timelockstatistics(cfg, timelock1, timelock2, ...)
% where the input data is the... |
dbc36f9951e1a12e624cab20aed8fc8631740bdf3e676e21ed20131be6fc4666 | MATLAB | 8,435 | 206 | function [FailedID WaitingID SuccessID]=y_GetfmriprepFailedSubjects(Cfg,WorkingDir,SubjectListFile, SubjectID)
% FORMAT [FailedID WaitingID SuccessID]=y_ReRunfmriprepFailedSubjects(Cfg,WorkingDir,SubjectID)
% Cfg - the parameters for auto data processing.
% WorkingDir - Define the working directory to replace t... |
79a973d89b7450ec15c414e0e52e9d4461fdd0401d7d2cbe0b018841048d5226 | MATLAB | 8,437 | 217 | function [avg_nDays, shift, span] = plotPercentiles(prctPerDay_avg, epochs, subEpochs,...
epochs_forAvg, varargin)
% PLOTPERCENTILES Plots repertoire dating percentiles.
%
% Inputs
% ------
% prctPerDay_avg: numel(prct) X numel(epochs) X numel(subEpochs)
%
% subEpochs: 1..nDi... |
89deb7c4bdcdda676ca535a5ad9abc668f0b24973edb8b9914e14899c8d34617 | MATLAB | 8,439 | 234 | %% Plot cortical sources for NeVRo study
% Project the spatial patterns from SSD, CSP, and SPoC into source space
% by using eLORETA.
%
% Launch this script from top level of the NeVRo repository.
% BEFORE RUNNING:
% - Download the "New York Head" Leadfield from https://www.parralab.org/nyhead/
% - make sure the file... |
d06a48b995d63e70dc62dc3622dd92b2c589399dfee0b1f2e3fc9e69685ce7b9 | MATLAB | 8,440 | 204 | %% Parse data out across FOV
%clear
pathname = 'C:\Users\khan332\Documents\GitHub\NNTEphysGrids\Figure3datatouch\statsLate';
directory = dir(fullfile(pathname,'*.mat'));
%%
HitrhoVal = {};CRrhoVal = {};MissrhoVal = {};FArhoVal = {};
HitwaveDir = {};CRwaveDir = {};MisswaveDir = {};FAwaveDir = {};
HitwaveDur = {... |
e59298c66995b304a1048d9e377f05f389c64463f53f80b05907ecc9ea1900c8 | MATLAB | 8,440 | 207 | % Second-kind integral equation on the unit sphere, Laplace double-layer.
%
% This is essentially the 3D version of IE_CIRCLE, where now the geometry is the
% unit sphere represented using flat triangles. The system is discretized via
% collocation with tensor-product Gauss-Legendre integration for the near-field
% pan... |
54106fa8c2903072bf104cf3fa112089962cb895200d60f97d5e0ee65630ffb0 | MATLAB | 8,443 | 307 | function [x,fval,exitflag,output]=fminsearchbnd(fun,x0,LB,UB,options,varargin)
% FMINSEARCHBND: FMINSEARCH, but with bound constraints by transformation
% usage: x=FMINSEARCHBND(fun,x0)
% usage: x=FMINSEARCHBND(fun,x0,LB)
% usage: x=FMINSEARCHBND(fun,x0,LB,UB)
% usage: x=FMINSEARCHBND(fun,x0,LB,UB,options)
% usag... |
6175fd8d71da0f7f60bc37943db77fadfc900c0e91c47c9f4cad0a44870a9d6d | MATLAB | 8,451 | 199 | function [seizureCell, seizurePaths] = getAllSeizureInfo(subjectNames, dataPath, electrodeLocation, varargin)
% subjectNames = names;
% dataPath = datapath;
% electrodeLocation = params.electrodeLocation;
% bilateral = false;
% FUNCTION INFORMATION: Lick task analysis pipeline
% Created by: Abdo Sharaf - abdo.sharaf@... |
b0fa0b1e069c0d61ed614bb6c71feadeda33a88bbfed07d6a6f23f9ad6486125 | MATLAB | 8,451 | 246 | function [Matrix_Coeff,Reconstruction,Residual,Error,dError,Max_Coeff] = Snake_kSVD_reconst_general(Data,Dictionary,NoAtoms,Overlap,sdRemoved,draw,filename,smooth)
if nargin==7
smooth = 0;
elseif nargin==6
smooth = 0;
filename ='ASLR Example_Layer1';
elseif nargin==5
s... |
0f45c23906fd9b0480cd44c4d789189eb96c32d8183d4d3d0df0c741c29fc7dc | MATLAB | 8,453 | 271 | %% Ridge regression: visualize effect of changing lambda and selecting it with CV and EB
%
%%
%ns = [21 50];
%for n=ns(:)'
clear all
n = 21;
setSeed(0);
[xtrain, ytrain, xtest, ytestNoisefree, ytest, sigma2] =...
polyDataMake('sampling','thibaux','n',n);
deg = 14;
addOnes = false;
if ~addOnes
% To avoid the n... |
703e159c5f28b47e5910ce64f36493943f60a48da5152a3047effa3bfa2e7068 | MATLAB | 8,455 | 258 | function [gaussians,outputs] = fooof_matlab_v9(psd_in_db,frequency_domain)
%FOOOF_MATLAB_V1 Summary of this function goes here
% Detailed explanation goes here
% psd_in_db and frequency_domain should be column vector
% frequency_domain should avoid 0
%% functions for fitting
modelfun = @(b,x) b(1) - log10(b(2) + x(:... |
03eb4593923ed53a7b8dae182df747d4f3acb2f7bcacd95aa08eb695a58fffff | MATLAB | 8,458 | 263 | function [varargout] = ft_plot_patch(hdat, vdat, varargin)
% FT_PLOT_PATCH plot a colored shape, similar to the MATLAB patch() function. It is
% similar in usage as ft_plot_vector, and they can be combined, for example,
% to plot an area equivalent to a SEM or STD-DEV around a line.
%
% Use as
% ft_plot_patch(X, Y,... |
017a9fe9015ed39b2d2a73409959cd7bb7a38d6b1923900f0ea26c7db7aedc86 | MATLAB | 8,464 | 169 | function results = predict_cv(datadir, kerneldir, resultsdir, HMM_name, varN, iterN, Fn, Kn, CVn)
% results = predict_cv(datadir, kerneldir, resultsdir, HMM_name, varN, iterN, Fn, Kn, CVn)
%
% runs kernel ridge regression to predict behavioural variables (here age
% and intelligence in HCP dataset) using different emb... |
c416bd1858628dabe6400c1ef3c6d9ea8f7ca873f239c23eb8c1f157e63227eb | MATLAB | 8,466 | 244 | function varargout = w_ChangeDf(varargin)
% W_CHANGEDF MATLAB code for w_ChangeDf.fig
% W_CHANGEDF, by itself, creates a new W_CHANGEDF or raises the existing
% singleton*.
%
% H = W_CHANGEDF returns the handle to a new W_CHANGEDF or the handle to
% the existing singleton*.
%
% W_CHANGEDF('CALL... |
fded995ee722a74ba696e86bfb1b5016364abdf3c8840e4e4c7d206dda92129f | MATLAB | 8,466 | 391 | function [fc_2,Rc_2,Tc_2,H_2,distance,V_vert,V_hori,x_all_c,V_hori_pix,V_vert_pix,V_diag1_pix,V_diag2_pix]=Distor2Calib(k_dist,grid_pts_centered,n_sq_x,n_sq_y,Np,W,L,Xgrid_2,f_ini,N_iter,two_focal);
% Computes the calibration parameters knowing the
% distortion factor k_dist
% grid_pts_centered are the grid point coo... |
d6d9541b5355609f6061c7b71bcf27fcba36cc02d2273eec74ba5ea4d06db741 | MATLAB | 8,468 | 214 | function homo_with_weight = CBIG_ComputeParcellationHomogeneity_FS(lh_labels,rh_labels,mesh,lh_input_filename,rh_input_filename)
% homo_with_weight = CBIG_ComputeParcellationHomogeneity_FS(lh_labels,rh_labels,input_filename)
%
% This function is used to compute the homogeneity metric with a given
% parcellation lh_la... |
6678d5549d40c4bc9d66b95e61d26e5678ae4d2a7e449ca1aa19b3bd74bb290e | MATLAB | 8,471 | 152 | format compact;
Int_main_folders = ''; % main working directory
ShortNames = {'R1_6hr','R1_24hr','R1_72hr','R2_72hr','R2_24hr','R2_6hr'};
Int_Results_folders = {}; % folders to save the results
Int_RawImage_folders = {'Folder1', 'Folder2', 'Folder3', 'Folder4', 'Folder5', 'Folder6'}; % Raw Tiff image folders
for... |
767426249b10f51cff974541422613a516503bd68edd001b3fde88e2d55c7274 | MATLAB | 8,473 | 168 | function [] = spearman_global_remapped_re_analysis(folders)
for nfolder = 1:length(folders)
cd(folders{nfolder})
disp(folders{nfolder})
% spearman correlation
load extracted_place_fields_BAYESIAN
cd global_remapped_shuffles
DIR = dir('shuffle_*');
DataPath = natsortfiles({DIR.name})'
... |
8879018251a6c4d2f1ca6e622b34aa88a926ff48f106b9a26dc6bde106e54e27 | MATLAB | 8,473 | 229 | function [PhaseLockingData] = bz_PhaseModulation(varargin)
% USAGE
%[PhaseLockingData] = bz_PhaseModulation(varargin)
%
% INPUTS
% spikes -spike time cellinfo struct
%
% lfp -lfp struct with a single channel from bz_GetLFP()
%
% passband -frequency range for phase modulation [lowHz highHz] form
... |
11cbbac8000ed97049da36abe0e9e221a418266155cd4033dcb3ff0aa14791c2 | MATLAB | 8,478 | 200 | %%Script to get beta values for each condition for each trial in a given
%%ROI. Written by Chris McNorgan many moons ago (as far as JY knows)
%%%%%%%%%%%%%%%%%%%%%%%%%
% None of this works without Marsbar being turned on
%%%%%%%%%%%%%%%%%%%%%%%%%
%initialize SPM and path
addpath(genpath('/dors/gpc/JamesBooth/JB... |
206e7a206ba1b223feb570cb267333bfcb0c5057e266db99b2f84a8fa11d5494 | MATLAB | 8,480 | 193 | function CSC=extract_CSC(varargin)
% INPUTS:
% - 'all','hpc', 'ofc' or 'vc'
% LOADS:
% - best CSC for each type of oscillation
% - dropped_samples
% all filtering is FIR with a set to 1 (b varies with frequency range)
parameters= list_of_parameters;
CSC_filter_length= parameters.CSC_filter_length; %default 11 w... |
85feb55094edec1331d5f960ddd86217d8b83e29c98ef1a3ca7b55c98238ccd7 | MATLAB | 8,485 | 291 | function [A,fH,figNames] = meg_alpha(eyesClosedFile,sessionDir)
% MEG_ALPHA(eyesClosedFile,sessionDir)
%
% INPUTS
% eyesClosedFile
% sqd
% sessionDir
% eg: 'R1507_20190627'
%
% OUPUT
% fH
% figure handle
% topo plot of individual peak alpha power ± 2Hz
% figNames
% alpha
% peak individual alpha (Hz)
%
% ... |
a941b53db2e655da004ba0b2b1bf078e21c1a2e7294879e650c74231126908d9 | MATLAB | 8,497 | 308 | classdef TrxVisualizerMA < handle
% Shows a trx/centroid marker, text label, trajectory traces
%
% Non-gobject model state lives on the associated
% TrxVisualizerMAModel (accessed via obj.tvm_).
properties
parent_ % LabelerController reference
tvm_ % TrxVisualizerMAModel reference, set in construct... |
b7de0660fbaa7e58beb808e6b367732b8f48139810d397c6a14369e9a05a3437 | MATLAB | 8,502 | 213 | classdef CoordinateMap < diffgeometry.Map
% Map whose image represent coordinates
% for example: embedding, chart, transition map.
%
% For coordinate maps we can calculate Jacobians,
% bijective coordinate maps have an inverse.
%-----------------------------------------------------------... |
b1ad6963c050d542daa8b82dcede378e7f71f21208a72132ad1a6eeb2455018d | MATLAB | 8,506 | 222 | function [biclusterRows, biclusterCols, rowPostProb, colPostProb, traceRow, traceCol] = biclusteringGibbs(data, varargin)
% Performs biclustering using Gibbs Sampling.
% Reference:
%@misc{sheng2003biclustering,
% title={{Biclustering microarray data by Gibbs sampling}},
% author={Sheng, Q. and Moreau, Y. and De Moor... |
9ac0bafbf2b5ac3d2edb0385f352a78d4ab1ee33bcf9345fbe92382375c7a3ee | MATLAB | 8,508 | 213 | % FindStrides.m
% Sarah West
% 7/7/2
% FindStrides.m finds mouse strides from smoothed velocity traces of the
% paws, taken from DeepLabCut. Velocity traces should be segmented by
% behavior of interest. Uses peakdet.m to find peaks and depressions in the
% trace around the mean velocity value.
%
% The mean velocity... |
db2ff33403cf393a3b3dd9e589c194b8c8905f2a4275b6732d1fa12dedb4af0a | MATLAB | 8,510 | 232 | function CBIG_KRDNN_test_krr(setup_file, lambda_set)
% CBIG_KRDNN_test_krr(setup_file, lambda_set)
%
% This function runs kernel ridge regression algorithm on training and
% testing data.
%
% Inputs:
% - setup_file
% Path of the setup file (.txt file).
% setup_file has the following fields:
% 1. Line 1
%... |
9dad9b75b82c64585e3f5d18d1fa5fb8ea720914ebbb4a058640b4c4e9ec171d | MATLAB | 8,513 | 220 | function CBIG_VK2019_replication_wrapper
%
% This wrapper runs the main analyses performed in our Biological Psychiatry
% paper. The steps are:
%
% 1. Loading RSFC & behavior data
% 2. Regressing out confounds from RSFC & behavior data
% 3. PLS analysis
% 4. Permutation testing over PLS singular values
% 5. Plotting R... |
9dfe8cd4a3c3d72499be6dc9819ee922882b4cbc31fe742b1f54f72f5f3b3dc1 | MATLAB | 8,514 | 235 | function [h,p,ci,stats,ratio] = myttest2(x,y,varargin)
%TTEST2 Two-sample t-test with pooled or unpooled variance estimate.
% H = TTEST2(X,Y) performs a t-test of the hypothesis that two
% independent samples, in the vectors X and Y, come from distributions
% with equal means, and returns the result of the test i... |
6352366d9f3c2d1bfed8c9afc6a3387b6888d0c0952581cac879c6ef01758509 | MATLAB | 8,515 | 218 | function [data] = ft_appenddata(cfg, varargin)
% FT_APPENDDATA concatenates multiple raw data structures that have been preprocessed
% separately into a single raw data structure.
%
% Use as
% data = ft_appenddata(cfg, data1, data2, data3, ...)
%
% The following configuration options are supported:
% cfg.keepsampl... |
2cd32c8c57f0c6d8fb5ae33515c6d19890104f882b344fce139036fd8b1047aa | MATLAB | 8,516 | 253 | function output = TrioEEGBehAnalysis(runProcess)
% function output = TrioEEGBehAnalysis()
% Process each datafile if not already done. Combine group data, process
% and do quick plots and stats.
% Inputs: runProces: 1 to reprocess datafiles, 0 to load (default)
%
if ~exist('runProcess','var')
runProcess = 0;
end... |
0abe55574549a58564d7b5d06b7c699c0bd4371a6ea19004ab5d305ea43e693f | MATLAB | 8,520 | 288 | function [A,fH,figNames] = meg_plotTF(data,p,selectedChannels,selectedFreq)
% MEG_PLOTTF(data,p,selectedChannels,selectedFreq)
%
% INPUT
% data
% structure of condition cells containing
% data matrix, time x channels x trials
% selectedChannels
% vector of meg channels to inspect
% selectedFreq
% vector of ... |
5b5af5bc6432fa32dd69017f2921abc5277bea6023a53df3b46ece44880216b1 | MATLAB | 8,522 | 332 | function [vol, M, mr_parms, volsz] = load_mgh(fname,slices,frames,headeronly)
% [vol, M, mr_parms, volsz] = load_mgh(fname,<slices>,<frames>,<headeronly>)
%
% fname - path of the mgh file
%
% slices - list of one-based slice numbers to load. All
% slices are loaded if slices is not specified, or
% if slices... |
de6cc91f8faf5e455f3eaf7273b2228be220af993ef2e1e18e0da912c7c6e048 | MATLAB | 8,523 | 192 | function spikeMat = randnet_calculator_memOpt_wGin(modelParam, network, ithEnv, isPFSim, varargin)
% randnet_calculator_memOpt_wGin.m
%
% Simulates network of recurrent LIF neurons. Should produce identical
% spikeMat as randnet_calculator.m but runs slightly faster and with much
% lower memory requirements due to not ... |
edf69d02bf3df4a7326096cea45711cf2508722a221600b866f9e8dbfbf5a147 | MATLAB | 8,528 | 244 | function viewTrialSensors(p_strct, subj_location)
% set defaults
if nargin < 2 || isempty(subj_location)
subj_location = 1; % default show first subject in p-structure
end
%%%%%%%%%%% import raw data
cfg = [];
cfg.dataset = p_strct.subj.subj_ds(subj_location);
cfg.channel ... |
181eaa79ff12b9507855c9c1c980b983b40401b7f03a44af0523282be9b9f978 | MATLAB | 8,540 | 292 | function [mappedX, mapping] = lmvu(X, no_dims, K, LL)
%LMVU Performs Landmark MVU on dataset X
%
% [mappedX, mapping] = lmvu(X, no_dims, k1, k2)
%
% The function performs Landmark MVU on the DxN dataset X. The value of k1
% represents the number of nearest neighbors that is employed in the MVU
% constraints. The val... |
46f160a66ba66f55412c8a9c3f6fb32c0ed247fb16b7e7c2d9f528c3a565e274 | MATLAB | 8,542 | 191 | function [ hsd_header ] = getHSDHeader( input_file_name )
% Read New HSD
%
% started by Jason, 7/26/06
% edited by Greg, 14-Nov-2006
% edited by Dan Leventhal, 9/17/2010
% % % HSD simple data format for high-speed neurophysiological
% % % data acquisition. Created 2006 by Joshua Berke, Jason Breck, and
% ... |
622a83152907e9657d409f9828cc134b8c5d66dea1557a36098a16e5b473a1b2 | MATLAB | 8,543 | 277 | function update_behavioralTracking(varargin)
% Adds behavioral files to session.beahviorTracking by looking for
% videos/dlc/godot output in session file
%
% Assumes basename.session.epochs.name have been annotated for each epoch
%
% inputs:
% basepath: path where session data is kept. (Default is current working
% ... |
e2845b3cd00fc16989b664871e30dc5e9eefea9bb70405c45d6063f9cbfcb9a7 | MATLAB | 8,543 | 204 | %% First level analysis, written by Jin Wang 3/15/2019
% You should define your conditions, onsets, duration, TR.
% The repaired images will be deweighted from 1 to 0.01 in the first level
% estimation (we changed the art_redo.m, which uses art_deweight.txt as default to deweight the scans to art_redo_jin.txt, which we... |
bda1c93cbf86fce47203304b7d12a144251e0462185755e8d54a970ca2aa837b | MATLAB | 8,544 | 204 | %% First level analysis, written by Jin Wang 3/15/2019
% You should define your conditions, onsets, duration, TR.
% The repaired images will be deweighted from 1 to 0.01 in the first level
% estimation (we changed the art_redo.m, which uses art_deweight.txt as default to deweight the scans to art_redo_jin.txt, which we... |
cc41622b7ee47bc321a519a9fff21b0d810ef07da9844729636100fbb916d6e0 | MATLAB | 8,550 | 261 | function blks_mean = CBIG_ASDf_Plot400Schaefer19Subcor17Networks_NetworksOnly(corr_mat_row, ...
scalelim, filename_prefix, is_sum)
% blks_mean = CBIG_ASDf_Plot400Schaefer19Subcor17Networks_NetworksOnly(corr_mat_row,
% scalelim, filename_prefix, is_sum)
%
% Plots 18x18 matrix by averaging/summing within/between networ... |
94ad1cc6fd1b20cc640fc548d48dae0e5fd9fcc7fb2b182eeeababedc25efcbe | MATLAB | 8,552 | 147 | %% Decription
% Here we demonstrate how the optical properties can depend on the "damage"
% (coagulation/denaturation/reactions) that can occur with elevated
% temperatures, as described in the model.HS.Omega matrix using the
% Arrhenius damage integral formalism. The thermal properties can also
% depend on Omega, alth... |
8dab6f95697bdf9d343ee97f72f4cc063d4ad5f73cc095da926553c4f263643d | MATLAB | 8,571 | 235 | function dataOut=fcBx_Enrich_1tp(fc,Bx,IM,params)
% Perform the correlation analysis (type = {Pearson, Spearman}),
% and enrichment analyses using Chi-square and Hypergeometric stats.
% fc is the Fisher-z fc-data; Nseeds-Nseeds-Nsubj
% Bx is the behavior data; Nsubj
% IM is the ROI-to-module key.
% params.type... |
381dd53ebc85c925bd658ce78d98ce2bf6db702e11ea43caad3b9c354b049e55 | MATLAB | 8,575 | 191 | function [filt] = ft_preproc_dftfilter(dat, Fs, Fl, varargin)
% FT_PREPROC_DFTFILTER reduces power line noise (50 or 60Hz) via two
% alternative methods:
% A) DFT filter (Flreplace = 'zero') or
% B) Spectrum Interpolation (Flreplace = 'neighbour').
%
% A) The DFT filter applies a notch filter to the data to remove th... |
136f429638ea4498041e2d323e009176cb312a1f69a3bfe0c2baafec3e65f271 | MATLAB | 8,579 | 230 | function [cfg] = ft_layoutplot(cfg, data)
% FT_LAYOUTPLOT makes a figure with the 2-D layout of the channel positions
% for topoplotting and the individual channel axes (i.e. width and height
% of the subfigures) for multiplotting. A correct 2-D layout is a
% prerequisite for plotting the topographical distribution o... |
70b696c53ad3b1b33efc6552db4906bed45ded1dc9c443177334e0dfff5045fa | MATLAB | 8,579 | 266 | function mesh = prepare_mesh_headshape(cfg)
% PREPARE_MESH_HEADSHAPE
%
% Configuration options:
% cfg.headshape = a filename containing headshape, a Nx3 matrix with surface
% points, or a structure with a single or multiple boundaries
% cfg.smooth = a scalar indicating the number of non-... |
7f73ff91724a173cdd70d2fc0c3f08e64dbedded04201708c67c3b72b606bcc3 | MATLAB | 8,585 | 237 | function [grandavg] = ft_freqgrandaverage(cfg, varargin)
% FT_FREQGRANDAVERAGE computes the average powerspectrum or time-frequency spectrum
% over multiple subjects
%
% Use as
% [grandavg] = ft_freqgrandaverage(cfg, freq1, freq2, freq3...)
%
% The input data freq1..N are obtained from either FT_FREQANALYSIS with
% ... |
f0dba1ff7f7f1a85b5a2e08b4559db2889813628712ae81f934f091e6e87ef99 | MATLAB | 8,585 | 237 | function [grandavg] = ft_freqgrandaverage(cfg, varargin)
% FT_FREQGRANDAVERAGE computes the average powerspectrum or time-frequency spectrum
% over multiple subjects
%
% Use as
% [grandavg] = ft_freqgrandaverage(cfg, freq1, freq2, freq3...)
%
% The input data freq1..N are obtained from either FT_FREQANALYSIS with
% ... |
70aea7fa62e2ec9298023b095a0aa20cc5061eff56358eb5f7dcce5e90735e9b | MATLAB | 8,586 | 219 | function [acc, pred_stats] = CBIG_KRR_test_cv_allparams_LITE( test_fold, sub_fold, ...
data_dir, y_resid_stem, with_bias, ker_param, lambda_set, threshold_set )
% [acc] = CBIG_KRR_test_cv_allparams_LITE( test_fold, sub_fold, ...
% data_dir, y_resid_stem, ker_param, lambda_set, threshold_set )
%
% For a given ... |
b15e760837139bbbeadd365b0f9172604639d2f7b340f22e455f166409984dd0 | MATLAB | 8,587 | 222 | function AlphaLine(x, y, color, varargin)
% Produces a line plot with the error boundary represented by a shaded area of the same color
% AlphaLine(x [double], y[double, cell], color[double], varargin)
% AlphaLine(x, y, color, 'EdgeAlpha', 0.2, 'ErrorAlpha', 0.2, 'ErrorType', 'SEM')
% Only supports a si... |
c88d505e771f7a08652a5d4c3c11087529adaf1bf24a88fadd832fee2c996869 | MATLAB | 8,588 | 199 | function [U] = stfmm3d(eps,srcinfo,ifppreg,targ,ifppregtarg)
% STFMM3D FMM in 3D for Stokes (viscous fluid hydrodynamic) kernels.
%
% U = stfmm3d(eps,srcinfo,ifppreg,targ,ifppregtarg)
%
% Stokes FMM in R^3: evaluate all pairwise particle
% interactions (ignoring self-interactions) and, possibly,
% interactions wi... |
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