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function [px,py,ang] = find_radiais(grd,varargin)
% [px,py]=find_radiais(grd,p_reta,x1,x2,y1,y2);
% Raquel Toste - 2019/11/25
% Adaptado de: calcula_vazao (Anderson Soares)
lon = ncread(grd,'lon_rho');
lat = ncread(grd,'lat_rho');
h = ncread(grd,'h');
m = ncread(grd,'mask_rho');
m(m==0)=nan;
if nargin > 1
p... |
function call=hestoncallquad(kappa,theta,sigma,rho,v0,r,T,s0,K)
warning off
call=s0*hestonp(kappa,theta,sigma,rho,v0,r,T,s0,K,1)-K*exp(-r*T)*hestonp(kappa,theta,sigma,rho,v0,r,T,s0,K,2);
function ret=hestonp(kappa,theta,sigma,rho,v0,r,T,s0,K,type)
ret=0.5+1/pi*quadl(@hestonpintegrand,0,100,[],[],kappa,theta,sigma,r... |
load stretchReflexTrials
numSubject = length(experiment.PF2.MVC{1});
frequencyBands = [1; 5; 6; 12];
normalize = true;
for i = 1 : numSubject
pulseTrials = experiment.DF.pulseTrials{i};
reflexAmplitude = [];
for j = 1 : length(pulseTrials)
positionMeasured = flbReadMeasuredPosition(experiment.fileN... |
% EJERCICIOS RESUELTOS DE VISIÓN POR COMPUTADOR
% Autores: Gonzalo Pajares y Jesús Manuel de la Cruz
% Copyright RA-MA, 2007
% Ejercicio 11.2: Visión estereoscópica
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 11.5.1 Geometría del sistema
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
function extreme_GHK_Fit_GO_test(saltName,polarity,varargin)
ORG = Matlab2OriginPlot();
ORG.cd_TopLevel();
dirName = ['GHK_response_' saltName] ;
ORG.mkdir(dirName);
ORG.cd(dirName);
% subDir = [saltName '_Anion'];
% ORG.mkdir(subDir);
ORG.Disconnect;
paramsTotal = [];
if(strcmp(saltName,'KCl_HfCl4'))... |
function xp = spm_dirichlet_exceedance(alpha,Nsamp)
% Compute exceedance probabilities for a Dirichlet distribution
% FORMAT xp = spm_dirichlet_exceedance(alpha,Nsamp)
%
% Input:
% alpha - Dirichlet parameters
% Nsamp - number of samples used to compute xp [default = 1e6]
%
% Output:
% xp - exceedance ... |
addpath('/home/raleman/Documents/MATLAB/analysis-tools-master'); %Open Ephys data loader.
addpath('/home/raleman/Documents/GitHub/CorticoHippocampal')
addpath('/home/raleman/Documents/internship')
nFF=[
% {'rat26_Base_II_2016-03-24' }
% {'rat26_Base_II_2016-03-24_09-47-13' ... |
function Open_2P(hfig_handle, p, r, s)
global hfig
global imgobj
%%
h_name = 'two_photon';
hfig.two_photon = figure('Position', [10, 20, 1100, 500], 'Name', 'Two-photon Traces',...
'NumberTitle', 'off', 'Menubar', 'none', 'Resize', 'off',...
'DeleteFcn', {@Close_subwindow, hfig_handle, h_name},...
'KeyPress... |
%% plot_autocorrelation.m
% Usage: plot_autocorrelation(ROOT_DIR)
% Purpose: Plots the autocorrelations over time
%
% User Inputs:
% ROOT_DIR - directory which contains the desired data/stats.mat
% printFlag - print them (1) or dont (0)
%
% Function Requirements:
% stats.mat
function plot_auto... |
function [X,info] = IRfista(A,b,varargin)
%IRfista FISTA algorithm for constrained least squares problems
%
% options = IRfista('defaults')
% [X,info] = IRfista(A,b)
% [X,info] = IRfista(A,b,K)
% [X,info] = IRfista(A,b,options)
% [X,info] = IRfista(A,b,K,options)
%
% This function uses the first-order optimization met... |
% calculate rate of H + HO2 --> H2 + O2
% Updated 7/13/06 AEP
% Based on JPL Data Evaluation #15
% rate = kHHO2c(T,M)
function j=kHHO2c(T,M)
j=6.9e-12.*exp(0../T); |
function [pn,PN] = Pink_Noise_Generation(N,dt)
% [pn,PN] = Pink_Noise_Generation(N,dt)
% Inputs:
% N = number of saples
% dt = time differential
% Outputs:
% wn = Time Domain white noise
% WN = Frequency Domain white noise
% Info:
% By: Matthew Luu
% Last Edit: 9/17/2020
% Pink Noise generation through freq... |
function dataStruct = dataStructConvertBRIK(dataStruct)
%DATASTRUCTCONVERTBRIK Converts BRIK images from AFNI into the SPM-compatible NIFTI format.
% This function uses AFNI to convert images from BRIK format into ANALYZE format, which is
% compatible with the SPM preprocessing used in later steps. Because this fun... |
% Parameter selection
function [bestnfactors,bestnloadings,bestperformance,pergrid] = findparameters(X,Y,nfac,nload)
bestperformance =-inf;
bestnfactors = [];
bestnloadings =[];
pergrid =[];
for iload = 1:size(nload,2)
[bestnfac, bestper, allper] = loo_hopls(X,Y,nfac,nload(:,iload));
pergrid(:,iload) = allp... |
function [h,x] = compute_histogram(M, options)
% compute_histogram - compute the (symmetric) histogram of a vector after threshold.
%
% [h,x] = compute_histogram(M,options);
%
% If M contains only entry in 1...p, where p=max(M), then h is of size p
% h(k) = #{i \ M(i)=k} / length(M)
% If M contains o... |
V=[3,5,0];
static_potential=[];
for j=1:num_total_electrode
if (j==1)
static_potential=potential_basis(:,:,1)*V(1);
else
static_potential=static_potential+potential_basis(:,:,j)*V(j);
end
end
%%%%%%%%%%%%% compare with analysis equation %%%%%%%%%%%%%%%%%%%%%%
static_potential=st... |
function driveData
cd('/Volumes/LAB (FAT32)/Data'); |
function kept_pts=parseandmarkwsc(data,sc)
if exist('sc')==1,sc=sc*std(data)+mean(data);end
kept_pts=[];
key='n';
windowsize=5000;
curr_start=1;
fid2=figure;
moveon=0;
m_pos=[];
while moveon==0
%plot data and marked points
clf,plot(curr_start:(curr_start+windowsize-1),data(curr_start:(curr_start+windowsize-1)))... |
start=1;
classes={{16};{22}};
APLO3.d1.default.diff_wave('classes',classes,'channels',38,'blocks_in',1:4,'trials',start:start-1+5);
APLO3.d1.default.diff_wave('classes',classes,'channels',38,'blocks_in',1:4,'trials',start:start-1+10);
APLO3.d1.default.diff_wave('classes',classes,'channels',38,'blocks_in',1:4,'trials',... |
function [T A B] = predprey(a, b, c, d, A0, B0, n)
% T vector of time
% A prey population
% B predator population
% n number of time intervals
% a natural growth rate of A
% b death rate from predation
% c natural mortality rate of B
% d growth rate from eating prey
T = 1:n;
A = zeros(1,n);
B = zeros(1,n);
... |
function goToGoal(a,b,c)
nargin
arg = {0.02 100 -100};
arg(1:nargin) = varargin(1:nargin);
end
|
function [ output_args ] = mzDeviation(all)
%mzDeviation - given the cell output from annotation2text, produce a
%diagnostics style plot to show how the mz values deviate when provided
%with a annotations, i.e. plot the true and experimentally measured values
%for inspection of e.g. systematic drift.
% First we should... |
function show(varargin)
spl = strsplit(varargin{1}, '.');
x = irisopt.(spl{1});
x = x.(spl{2});
disp(x(1:3:end)');
end
|
% svm classifier
%data_PF
%popular_f
A = data_PF;
% get size of data o = observations, f = features
[o f] = size(A);
% to summarise data, calculate mean and sd
PF_mean = mean(A);
PF_std = std(A);
% standardize the data
B = zscore(A);
% calculate pc
[coeff score latent] = princomp(B);
var_score = var(score);
cum_v... |
function out = convertBeamHardeningAtt( in,spectrum, mode )
% Compute Beam Hardening Correction in sinogram space using Joseph's method.
% input:
% in - sinogram or image in attenuation
% spectrum - spectrum infomation
% mode - 0. assuming ploychromatic image (default)
% 1... |
fig=figure(),
er = method_ers;
csterr = 1.96*method_sterrs/sqrt(3000);
errorbar(costs(1:numel(costs)),er(1:numel(costs),1),csterr(1:numel(costs),1),'LineWidth',3),hold on
errorbar(costs(1:numel(costs)),er(1:numel(costs),2),csterr(1:numel(costs),2),'LineWidth',3),hold on
errorbar(costs(1:numel(costs)),er(1:numel(costs),... |
% This is the main script to show images
clc;
clear;
close all;
load('GT-00001.mat');
imageName = Filename{40};
image = imread(imageName);
imgSign = RedSign(image);
blob = MaxBlob(imgSign);
ratio = AspectRatio(blob);
figure (1), hold on;
imshow(imgSign), hold on;
%Draw boundingBox
rectangle('Po... |
function Parameters = subfnVoxelWiseProcessBatch(InData)
% This program takes the data or the pointer to the data file and prepares
% the data for processing. It is here that multiple voxels are looped over.
% Therfore, it is in this program that one voxel at a time is extracted to
% create a temporary data array w... |
function CreateCircos(Bands, Rho_Thresh)
[AllData, AllNames] = MadeDataFile();
% top 1% of values plotted as fully opaque
MAX_E = prctile(AllData(:,1),98);
load AreaNames
NEWPOWERNAME = AreaNames';
SFile=fopen('Connectivity.txt', 'wt');
SFile2=fopen('chr-highlights.txt', 'wt');
for Counter = 1:length... |
function model = build_model_cell_population(env, model)
%
% Model information carried in V1 complex cells as a function of Hebbian
% learning
%
% Emily Cooper, Stanford University, 2014
%
% params structure:
% params.popDensity -- 'uniform' or 'optimal'
% params.popGain -- 'uniform' or 'optimal'
% params.N, params.R ... |
%{
-> reso.FluorescenceTrace
-> olf.RespOpt
---
resp_on : mediumblob # on response matrix [stimuli trials]
resp_off : mediumblob # off response matrix [stimuli trials]
stimuli : mediumblob # stimuli
%}
cl... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Charles Chen - SID: 810797715
% CSCI5722 - Computer Vision
% Final Project - Ear Segmentation Demo
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Based on work of Milad Lankarany and Alireza Ahmadyfard:
% "Ear S... |
function D1 = ddz(z,endvalues)
%% Generate a first derivative matrix for independent variable z using
% second order centered differences. z is assumed to be evenly spaced
% for j=1,N.
%
% If endvalues = 0, the function is assumed to vanish at j=0 and j=N+1.
% If endvalues ~=0, the function is not assum... |
function [C, sigma] = dataset3Params(X, y, Xval, yval)
%DATASET3PARAMS returns your choice of C and sigma for Part 3 of the exercise
%where you select the optimal (C, sigma) learning parameters to use for SVM
%with RBF kernel
% [C, sigma] = DATASET3PARAMS(X, y, Xval, yval) returns your choice of C and
% sigma. You... |
load('A.mat');
B = A';
[row, col, val] = find(B);
[n, m] = size(B);
for i = 1:n
num = sum(B(:,i));
if(num ~= 0 && num ~=1)
B(:,i) = B(:,i)/num;
end
end
B = B'; |
function initializeAudapter (genderSubject)
%% Initialize Audapter
addpath c:/speechres/commonmcode;
cds('audapter_matlab');
audioInterfaceName = 'ASIO4ALL';%'MOTU MicroBook';%
sRate = 48000; % Hardware sampling rate (before downsampling)
downFact = 3;
frameLen = 96; % Before downsampling
noiseWavFN = 'mtbabble48k.w... |
function f=Gaussian2(xp,xdata)
[a b]=size(xdata);
Xd=xdata(:,1:b/2);
Yd=xdata(:,b/2+1:b);
f=xp(1,5)*(exp(-0.5*(Xd-xp(1,1)).^2./(xp(1,3)^2)-0.5*(Yd-xp(1,2)).^2./(xp(1,4)^2)))+...
xp(2,5)*(exp(-0.5*(Xd-xp(2,1)).^2./(xp(2,3)^2)-0.5*(Yd-xp(2,2)).^2./(xp(2,4)^2)))+xp(1,6); |
function [root,ic] = N5(f,Jacobian,intialGuess,maxIterations,tol)
ic = 0;
root = intialGuess;
error = 10000;
while (ic <= maxIterations)&&(error > tol)
ic = ic +1;
display(Jacobian(root));
display(Jacobian(root));
root = root - Jacobian(root)\f(root)';
error = abs(norm(f(root))/norm(f(int... |
function outHex = ByteXOR(n1Hex, n2Hex)
% outHex = NibbleXOR(n1Hex, n2Hex)
% inputs: two length 2 hex strings (bytes)/ upper or lower case format
% output: an (upper case) length 2 hex string that is the XOR of the
% inputted strings
n1BinVec = int2baseb(hex2dec(n1Hex),2,8);
n2BinVec = int2baseb(hex2dec(n2Hex),2,8);
... |
% AnovaVoxelwise.m
%
% calculates variation between fabber data-sets, on a voxel-wise basis using
% ANOVA. Derived from FabberAverages.m
%
% MT Cherukara
% 2 July 2018
%
% Changelog:
%
% 2019-02-14 (MTC). Added functionality for simulated grids. This now works, but
% it doesn't actually do the thing we want it to... |
function diagnostic7()
g = 9.8;
k = 100;
l0 = 1;
m = 1;
x0 = -1;
y0 = -1;
vx0 = 0;
vy0 = 0;
[~,Y] = ode45(@derivatives, [0,5], [x0;y0;vx0;vy0]);
comet(Y(:,1), Y(:,2));
function res = derivatives(~,S)
x = S(1);
y = S(2);
vx = S(3);
vy = S(4);
... |
% Generated through Matlab
% Author: Killian Keller
% E-Mail: killian.keller@ief.ee.ethz.ch
% Organization: ETHZ ITET IEF
function [Ep, Es, Ei] = test_ExtractField(model, varargin)
% Summary Here
% Detailed Summary Here
warning('off','all');
hbar = 1.0545718e-34;
eps0 = 8... |
k=1;
p=1;
[patch]=textread('/home/xiaogao/Downloads/screen_content/SCIQAD/distorted_after/mappings/scores_val_1.txt','%s%*[^\n]')
[val]=textread('/home/xiaogao/Downloads/screen_content/SCIQAD/distorted_after/mappings/val.txt','%s');
output=textread('/home/xiaogao/下载/NR-IQA-CNN-master1/outputs/output_1.txt','%s');
... |
%The name of this file appears on (or around) line #170 in newSturgeonWalk
function enviroSetUp
steps = 43200; %time steps number of minutes in 30 days
N = 30; % half tidal periods, gets doubled +/- start time
t1 = -N*pi;
t2 = N*pi;
t = linspace(t1, t2, steps);
tideArr = cos(t); %creates tides for 30 day interval m... |
function U = uq_NatafTransform( Xin, marginals, copula )
% U = UQ_NATAFTRANSFORM(Xin, marginals, copula):
% performs (Generalised) Nataf Transformation of samples (X)
% from the physical to the standard normal space (U)
%
% References:
%
% Lebrun, R. and Dutfoy (2009), A., A generalization of the Nataf
% ... |
clc
clear all
close all
x=[1 2 3 4]; % entry point to the function of FFT decimation in time
p=nextpow2(length(x)); % checking the size of the input array
x=[x zeros(1,(2^p)-length(x))]; ... |
clc,clear,close all
N_atoms=3200;
defect_type_id = 4;
critial_part_ratio = 0.4;
switch defect_type_id
case 1
defect_type = 'rand_as';
case 2
defect_type = 'neib_as';
case 3
defect_type = 'Bn';
case 4
defect_type = 'Nb';
otherwise
error('wrong de... |
% script_bicycleModel_Integrator.m
% Plots the results of a outputs of a simulink model: the all-integrator
% form and ODE45 implemented as MATLAB functions.
% Note that both are same (which is the point). It also tests this across
% 3 vehicles.
%
% This script was originally written on 2007_06_25 by S. Brennan... |
function y=fitfun2(c,x)
%曲线拟合例子模型函数
y=c(1)*exp(c(2)*x);
|
%% inorm_ternary.m
% Usage: inorm_ternary()
% Purpose: Plots the pdf of and traces the trajectory of the normalized tetrad
% eigenvalues
%
% User Inputs:
%
%
% Function Requirements:
% tetrad_stats.mat
function inorm_ternary(ts, te)
load('data/tetrad_stats.mat', 'I', 'time');
% Sort out times
i... |
% Find the conjugate of a quaternion.
function quat = quatConj(q)
% Assumes the scalar component is q(4)
quat = q;
quat(1:3) = -quat(1:3);
end
|
function PlotConsensusMatrix(Ordered, Labels, Indices, LineSpec)
%Plots the consensus matrix 'Ordered' with cluster labels.
%inputs:
%Ordered - NxN consensus matrix, as obtained from ModelSelection functions.
%Labels - N-length vector of sample labels, as obtained from ModelSelection functions.
%Indices - N-length... |
function K = U(K)
[r,c] = size(K);
for i=1:r
for j=1:c
K(i,j) = -((K(i,j)^2)*log(K(i,j)^2));
end
end
end |
function [Ve_L_f] = CellComp_VeL_f(Xi, Yi, Zi, I_M, I_D, z_max, t_max, d_z, d_t)
%%CELLCOMP_VEL_F
% CELLCOMP_VEL_F returns the longitudinal component of the
% extracellular voltage for a neurite in tissue comprised of parallel
% fibers given a set of stimulating electrodes, modelled as point sources.
% The extracellula... |
function rect = findLargestSquare(img)
% finds the largest inscribed square for a given binary image.
% Algorithm Source:
% http://www.imagingshop.com/articles/automatic-cropping-non-rectangular-images
% img = input binary image
% rect = [x, y, w, h] of largest square, (x,y) = top left coordinate,
% w = h = width and... |
function plotMotion
global P;
global E;
global plotState;
global T;
if isempty(plotState)
initPlotState;
end
figure(plotState.SNfignum);
hold on;
% plot pursuer & evader
if ishandle(plotState.P) delete(plotState.P); end
if ishandle(plotState.E) delete(plotState.E); end
plotState.P = plot(P.pos(1,end),P.pos(2,end),'... |
function [zt,p] = MarkovAR(size,nz,rho,sigma)
% Purpose: Markov function discribes the productivity shock
%
% Input: size := size of the grid for the productivity shock
% nz := number of grid points for the productivity shock
% rho := autoregressive parameter
% sig... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Numerische Mathematik fuer Physik und Ingenieurwissenschaften 2020 %%%
%%% Programmierabgaben (Praktischer Teil des Uebungungsblattes) %%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
... |
close all; clear; clc;
img = imread('fig1.tif');
%img = rgb2gray(img);
img = double(img);
[H, W] = size(img);
%%
hist = zeros(256,1);
for i = 1:H
for j = 1:W
hist(img(i,j)+1) = hist(img(i,j)+1)+1;
end
end
cdf = zeros(256 , 1);
for i = 1:256
cdf(i) = sum(hist(1:i));
end
cdf = cdf/cdf(end);
%ro... |
%% Spawn random models in gazebo
gazebo = ExampleHelperGazeboCommunicator();
for i = 1:10
ball = ExampleHelperGazeboModel('Ball');
spherelink = addLink(ball,'sphere',1,'color',[0 0 1 1]);
spawnModel(gazebo,ball,[randi([-100, 100]),randi([-50, 50]),1]);
end
for i = 1:10
ball = ExampleHelperGazeboModel... |
function M = nmodeM_1(I1,L1,d1,g,m1,omega1,theta1)
%NMODEM_1
% M = NMODEM_1(I1,L1,D1,G,M1,OMEGA1,THETA1)
% This function was generated by the Symbolic Math Toolbox version 8.1.
% 11-Dec-2018 19:16:11
M = [I1+d1.*m1.*conj(d1)];
|
function [i,j,new_lat,new_lon]= fixpt(w,pt,varargin)
% compute the nearest point in the fire mesh to the given coordinates
% w - w = read_wrfout_tign(f) , struct with fxlong,fxlat or red =
% subset_domain(w)
% pt - point to be fixed to fire mesh pt = [lat,lon]
%
... |
namelist=dir('*.bmp');
for i=1:length(namelist)
[img map]=imread(namelist(i).name);
img=ind2gray(img,map);
graphs{i}.name=namelist(i).name;
graphs{i}.img=img;
title(namelist(i).name);
subplot(2,2,1)
imshow(img);
subplot(2,2,2)
img=histeq(img);
imshow(img);
subplot... |
%% Stelling 9
%
% Met een semi-colon (;) maak je een nieuwe rij aan
% binnen een matrix.
%
Antwoord = NaN; % vul hier het juiste antwoord in 1 (WAAR) of 0 (ONWAAR)
|
function [T,Flag_Loop,M,R,Loop_Stop]=Try_Links(na,nb,T,x,y,R,Loop_Stop,Counter)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Try_lins: Programm that tries to put a link in the process of union
% between 2 networks A and B.
% Input:
% na, nb: Size of networks A and B
% T: C... |
%(vpa(inv(s*eye(2) - A),5))
%vpa((C*inv(s*eye(2) - A)*B + D),5)
%tf(sys)
%Laplace a transf Z
so = 0.3356; ro = 0.0683 ; uo= 0.12;
%Cambio punto en el cual esta linealizado y sistema utilizado
[A,B,C,D] = linmod('resistenciaBacterias_entrada',[so,ro],uo);
% Transformada Z
Ts = 0.2;
% t = k*Ts;
%Sistema l... |
function f = objectiveFunc(X, trajData, objType)
nState = 12; nControl = 6; nOptim = nState + nControl;
if strcmp(trajData.shape, 'loiter')
if strcmp(trajData.type, 'not-same')
N = (length(X)-3)/nOptim;
VR = X(nOptim*N+2); trajData.VR = VR;
else
N = (length(X)... |
function subjectParams = getSubjectParams(dataDir, subjectParams)
% function subjectParams = getSubjectParams(dataDir)
% get subject name & comments
% set file name and path for saving expt data
if ~exist('subjectParams','var') || ~isfield(subjectParams,'name')
subjectParams.name = 'demo';
end
subjectParams.c... |
function bvhResultsDynamic(dataSet, number, dataType, bvhStruct, velocityIndices)
% BVHRESULTSDYNAMIC Load a results file and visualise them.
[model, bvhStruct, frameLength] = bvhLoadResult(dataSet, number);
if size(model.X, 2) ~=2
error('Visualisation only works for 2-D latent spaces.')
end
mocapVisualise(model... |
function [T,R,states]=GaussianSamplingMetaMDP(start_state,cost)
sigma0=start_state.sigma;
resolution=sigma0/50;
delta_mu_values=-2*sigma0:resolution:2*sigma0;
sigma_values=sigma0:-resolution:0.1;
[MUs,SIGMAs]=meshgrid(delta_mu_values,sigma_values);
nr_states=numel(MUs)+1; %each combination of mu and sigma is a state ... |
function iout = IntersectIntervals(i1,i2)
maxl = max(i1(1),i2(1));
minr = min(i1(2),i2(2));
if (maxl > minr)
iout = [];
else
iout = [maxl minr];
end
|
clear; clc; close all
% Figure 4 (left panel) in main text: This script plots the boundary lines
% that defines the FC Nash equilibrium region in (p,log(kappa))-space
% % % % %
mydir = pwd; % get current directory
idcs = strfind(mydir,'\');
parent_dir = mydir(1:idcs(end)-1);
addpath(parent_dir) % add parent dire... |
function MFO_result=MFO_Find(FunctionName,TH_num,RunTimes,MAX_Iterations)
% function MFO_result=MFO_Find(FunctionName,TH_num,RunTimes,MAX_Iterations)
% The Moth-Flame Optimization Algorithm (MFO),proposed S. Mirjalili,
% Moth-Flame Optimization Algorithm: A Novel Nature-inspired Heuristic Paradigm, Knowledge-B... |
function S=csfit(x,y,dx0,dxn)
% x,y分别为n个节点的横坐标所组成的向量及纵坐标组成的向量
% dx0,dn分别为S的导数在x0,xn处的值
n=length(x)-1;
h=diff(x);
d=diff(y)./h;
a=h(2:n-1);
b=2*(h(1:n-1)+h(2:n));
c=h(2:n);
u=6*diff(d);
b(1)=b(1)-h(1)/2;
u(1)=u(1)-3*(d(1)-dx0);
b(n-1)=b(n-1)-h(n)/2;
u(n-1)=u(n-1)-3*(dxn-d(n));
for k=2:n-1
temp=a(k-1)/b(k-1);
b(k... |
clear; close all; clc;
Y = zeros(12, 1);
t = 0:0.01:50;
global T P Q r P1 u omega_r omega
% global P;
% global Q;
% global r;
% global P1;
T=50;
P=zeros(12,12,T);
Q=eye(12);
Jxx = 0.0075;
Jyy = 0.0075;
Jzz = 0.0013;
Q(2,2) = Jxx;
Q(4,4) = Jyy;
Q(6,6) = Jzz;
r=rand(4);
Kj=zeros(4,12);
P1=rand(12);
P(:,:,1)=P1;
% global ... |
function [] = plot_neurometric(evoked, clevs)
% neurometric function for each cell
evokedZeroContrast = mean(evoked(:,clevs.Zero),2);
evokedLowContrast = mean(evoked(:,clevs.Low),2);
evokedMidContrast = mean(evoked(:,clevs.Mid),2);
evokedHighContrast = mean(evoked(:,clevs.High),2);
evokedHundredContrast = mean(evoked... |
% function songreader(file)
clear all
file='chorus';
filename=[file '.txt'];
song=load(filename);
% songstrct=load('binopus01_32beats.mat');
% song=songstrct.textformat;
NN=2;
showsong=1;
error=0;
N=65;
ptime=0.1; % speed of playback
nmark=0;
jjmark=0;
equalcount=0;
equalindex=0;
score=zeros(size(song... |
A = [2 1; 0 5; 7 4];
B = [5 3; -2 -4];
C = [2 3; -5 -2; 0 3];
D = [1 2];
% (a)
getInverse(A*C', "(a)");
% (b)
disp("(b)");
disp(abs(B));
disp(det(abs(B)));
% (c)
disp("(c)");
disp(abs(A*C'));
disp(det(abs(A*C')));
% (d)
getInverse(C'*A, "(d)");
function getInverse(T, c)
disp(c);
if round(det(T)) ~= 0
... |
function h = hVlassak(C,yVector,normalVector)
yVecDir = yVector;
% Outer loop needs to handle generation of vectors
v1=(cross(yVecDir,[0 1 0]));
if v1==0
v1=(cross(yVecDir,[1 0 0]));
end
v1=v1/norm(v1);
v2=(cross(yVecDir,v1));
v2=v2/norm(v2);
nint=60;
theta=[0:nint-1]/nint*(2*pi);
dtheta = (2*pi)/nint;
B = zeros(... |
currentpath = pwd;
currentpath(end-6:end)
if ~strcmpi(currentpath(end-6:end), 'scripts')
error('Make sure to run the OAT from the scripts directory.')
end
% add path to Offline Analysis Toolbox
addpath('../../../../../tools/offline_analysis_toolbox/')
% add path to Visual Stimulus Toolbox
addpath('../../../../../... |
function sppongb()
close all
set(0,'DefaultFigureWindowStyle','docked')
%% 200 X 200
% Volume fraction = 1.50% or 0.015
% TRIAL 1,2,3
figure(1),hold on
totalZPT1_200sq = 606;
nslspgb200sq_mcsT1 = [000 0 ;041 5E2;058 1E3;081 2E3;111 4E3;122 7.5E3;126 1E4;127 2E4;...
131 4E4;131 6E4;129 8... |
function nii_mirror (V);
% Generates 3 images: right mirror, left mirror, mean of left+right
% The first step is to align the image along its axis of symmetry
% this step uses nii_align
% The second step generates the new images
% Example
% nii_mirror('C:\dir\img.nii');
% You can also pass multiple images ... |
function [g4,g6,g4_pos,g6_pos,g4s,g6s] = girth_4_6(H_c,Z,g4,g6,g4_pos,g6_pos, rst)
% clc;
% clear all;
% close all;
[M, N] = size(H_c);
H_c_0=zeros(M,N);
for ii=1:1:M
for jj=1:1:N
if (H_c(ii,jj)>=0)
H_c_0(ii,jj)=1;
else
H_c_0(ii,jj)=H_c(ii,jj);
end
% fprintf(... |
function [ validationX, validationY ] = LoadValidationSet( X, Y, n_len )
% Load the indices of validation set and convert them into matrix format
% X: Vectorized input matrix
[d_nlen, ~] = size(X);
validation_fname = 'Validation_Inds.txt';
fid = fopen(validation_fname,'r');
validation_index = fscanf(fid,'%d '... |
% Used to add imported vectors to a cell
% The offset is used for the native app collection which has NaNs
% at the beginning.
% prefix = 'i4s_';
% prefix = 'i4_';
% prefix = 'i6_';
% prefix = 'andro_';
prefix = 'table';
offset = 10;
% offset = 1;
for i = 2:10
name = strcat(prefix, num2str(i))
x = eval(... |
function color = createColorMapForCtSlice(ctSlice, center, window)
%CREATECOLORMAPFORCTSLICE creates a color map using window/center settings for a certain CtSlice
%
% color = createColorMapForCtSlice(ctSlice, center, window)
%
% See also: CtSlice, plotCtSlice
huMin = min(ctSlice.scaledImageData(:));
huMax = max(ctSli... |
function plotHandles = PlotXvsY(x,y,varargin)
%set up default values. all default values can be changed by varargin
%by putting them in the command line like so
%plotXvsY(...,'color','[0,0,1]');
if(size(x,1) > 1)
graphType = 'line';
else
graphType = 'scatter';
end
color ... |
% Uses command-line CGAL implementation of SHAPE DIAMETER FUNCTION (SDF)
function [diameterVals, segmentIDs] = analyze_getSDFvalues(fileNameForMesh, options)
if nargin == 2
disp('"options" is a lazy placeholder if we need to pass some parameters eventually')
elseif nargin == 1
options = [];
... |
function varargout = srf(This,Time,varargin)
% srf Shock (impulse) response function.
%
% Syntax
% =======
%
% [Resp,Cum] = srf(V,NPer)
% [Resp,Cum] = srf(V,Range)
%
% Input arguments
% ================
%
% * `V` [ SVAR ] - SVAR object for which the impulse response function will
% be computed.
%... |
function RF = uq_EOLE_method(current_input)
%%------------------------------------------------------------%%
% EOLE expansion of random fields
%%------------------------------------------------------------%%
Options = current_input.Internal ;
% !!!!!!!!!!!!!!!!!!!!!!!!!!
% !!!!!!!!!!!!!!!!!!!!!!!... |
%%% This script will generate a 2-d biped model
% the model has 5 segments, calf, thigh, and torso
%%%
%% This is a male model, height 180 cm, body weight 72 kg
% percentage is from de Leva (1996), table 4
clear;
addpath ../
numJ = 6;
totH=1.8; %total height % still not add up to 100%, but these are ju... |
len_name = length(cost_function_names);
len_ran = length(param.cost_functions_ioc);
len_svd = length([output_inverse{ind_windowCount}(1).svd_s]);
len_rmse = length(currRMSE_set(1).arrayName);
len_lambda = size(lambda_array, 1);
len_Jbreakdown = length(direct_check_flags{1}.J_breakdown.report);
len_residual = length(out... |
function [spikeHistoryDesignMatrix] = buildSpikeHistoryDesignMatrix(numOfBaseVectors,...
baseVectors,spikeTrain)
lengthOfSpikesTrain = length(spikeTrain);
% Define the design matrix
spikeHistoryDesignMatrix = zeros(numOfBaseVectors, lengthOfSpikesTrain);
% calculate the base vectors
[len... |
%%% Load Data %%%
%%%%%%%%%%%%%%%% All Data %%%%%%%%%%%%%%%%
LandingData = readtable('Landing.xlsx', 'sheet', 'Data');
%%%%%%% Using Data %%%%%%%
% For All T/W Phase of Aircraft - Technology Level - Seat Num - alltitude
% For all W/S For All W/S WS - Phase of Aircraft - Technology Level - Seat Num - alltitude
%%%%%%%%... |
function [New_Nodes,idx_OuterBound,idx_holeBound,dx] = PressureBasedNodePlacement_v03(x_red,y_red,x,y,preload_red,idx_reduced,bolt_idx,corners_idx,N_Segments,scaleFactor,Setting)
% PressureBasedNodePlacement_v02: Node placement (on contour lines) for BRB
% quarter model
% INPUTS:
% Elements_idx : cell containing... |
function make_class_rpt(ID, Labels, FileName, varargin)
% Generates a powerpoint presentation containing preliminary analysis
%---------------------------------------------------------------------- ----
% make_class_rpt(ID,Labels, FileName, 'SavePath',somePath, 'ModelPath', locOfModel )
%--------------------------... |
function run()
testindex = '/home/chenyang/cydata/sed_subset/annodata/test.txt';
trainindex = '/home/chenyang/cydata/sed_subset/annodata/train.txt';
imagepath = '/home/chenyang/cydata/sed_subset/annodata/images/';
outputpath = '/home/chenyang/lib/CPM/';
annopath = '/home/chenyang/lib/CPM/results_model5/'
control(train... |
%----------------------------------------------------------------------------
% NA_random - generates a uniform random sample to be used
% instead of NA algorithm.
% Assumes random number generator ran3 has been initialized
% Calls ran3.
% M. Sambridge, Oct. 1996
%------------------------... |
function [pose] = MCL_GetPoses(Xt, Wt)
% Returns estimated pose using particles and their weights
% Xt: poses of particles
% Wt: weights
% pose: weighted pose
% Written & updated by Jungseok Hong 08/21/2018
pose = Xt.*Wt;
pose = sum(pose,1);
% below is the old version of this code.
% idx = kme... |
function source = destino (compressed_video_rgb, numfiles)
source=1;
%Para criar o video
video = VideoWriter('compressed_video.avi','Uncompressed AVI');
video.FrameRate = 12;
open(video)
%Processa as Imagens e Cria o Video
for i = 1:numfiles
image(:,:,1) = compressed_video_rgb.R(:,:,i);
image(:,:... |
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