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function [fitlines, conturIm] = bwCt_LFt(bwIm, minline, maxdist)
%bwCt_LFt finds foreground object contours only in binary image, and fits
%them into lines
% bwCt_LFt takes a binary image I as its input, and returns a
% binary image BW of the same size as I, denoting only the contours
% of the foreground objects... |
function [subont] = depth_n_subont(ont, d)
%DEPTH_N_SUBONT
%
% [subont] = DEPTH_N_SUBONT(ont, d);
%
% Creates a sub-ontology contain terms up to a specific depth.
%
% Input
% -----
% [struct]
% ont: The ontology structure, see pfp_ontbuild.m.
%
% [double]
% d... |
function computeBaselineNeuron(F)
%computeBaselineNeuron computes baseline per neuron
% Layers are the layers you want to compute the baseline on
% window is the window span in seconds (ex 50 sec)
% window
window = F.Analysis.BaselineWindow; % window is the window span in seconds (ex 50 sec)
dt = F.dt / 10... |
% make2Dgaussian.m
%
% function to make a noisy 2D Gaussian, with which to test particle
% tracking functions.
% z = A*exp(-(x-x0)^2 / (2*sigma_x^2))*exp(-(y-y0)^2 / (2*sigma_y^2))
%
% Should previously initialize random number stream:
% RandStream.setDefaultStream(RandStream('mt19937ar','seed',sum(100*clock))... |
function [Useq] = plotPoissonSeq(n)
fu = fopen('u-seq.m', 'r');
Useq = fread(fu, [n,n], "double");
imagesc(Useq);
print('poissonSeq.eps', '-deps');
end
|
%rng('default');
load('testdata_scz_Z1_ctl_Z0.mat')
mu0=mean(Z0);
sigma0=cov(Z0);
mu1=mean(Z1);
sigma1=cov(Z1);
%%
smpsiz=100:100:2100;
lamdav=1:0.2:5;
Zc=cell(21,21);
%%
for kx=1:21
for ky=1:21
Sz=smpsiz(kx);
Lv=linspace(1,lamdav(ky),round(Sz/4));
p=ones(100,1);
[kx ky]
par... |
clc;
clear;
ImgDirPath = 'D:\Car Side View\';
OutDirPath = 'D:\sun\OUT\';
ImgFiles = dir(strcat(ImgDirPath, '*.jpg'));
OutFiles = dir(strcat(OutDirPath, '*.jpg'));
length = size(ImgFiles,1);
for i = 1 : length
ImgFiles(i).isdir = 0;
end
for j = 1 : size(OutFiles, 1)
for k = 1 : length
if strcmp(ImgFil... |
% [retfitinfo,yfit,amp]=jdmmin(DataX, DataY, fitinfo)
% minimization function, for TCSPC data, loosely based on simplex
% minimization principles.
% yfit is a matrix and amp is a vector such that yfit*amp is the
% overall fit function, while yfit(:,N) is the N-th function, and amp(N) is the N-th
% amplitude.
% [retf... |
clear;
clc;
tic
%% Initials
img_raw = imread('data/chessboard_lightfield.png');
global u v s t c
u = 16;
v = 16;
s = size(img_raw, 1) / u;
t = size(img_raw, 2) / v;
c = 3;
% load('results/focal_stack.mat');
% fprintf('load complete\n'); toc
img_array = zeros(u, v, s, t, c);
img_array = uint8(img_array);
for i = 1... |
function [f_resultant, Mag_resultant, Phase_resultant] = LegFunction(I_mag,I_phase,k,f_o,f_c,The_o,The_c,m_max,n_max)
[f, Mag, Phase] = SwitchingFunction(k,f_o,f_c,The_o,The_c,m_max,n_max);
f_new= 0:f_o:max(f);
y=(f/f_o)+1;
Mag_new=zeros(1,length(f_new));
Phase_new=zeros(1,length(f_new));
for i=1:length(y)
... |
% Linear regression with multiple variables
% House price prediction based on size and number of rooms
%% Initialization
%% ================ Part 1: Feature Normalization ================
%% Clear and Close Figures
clear ; close all; clc
fprintf('Loading data ...\n');
%% Load Data
data = load('houseData.txt');
X ... |
clear;
fid=fopen('/home/scw4750/github/IJCB2017/liufeng/data/protocols/protocols_3parts_bbox/norm/probe3_with_label.txt','rt');
list=textscan(fid,'%s %d');
list=list{1};
img_dir='/home/scw4750/github/IJCB2017/liufeng/data/probe_croped';
out_dir='/home/scw4750/github/IJCB2017/liufeng/data/debug/150_200_image';
for i=1:l... |
%% Zhanwen "Phil" Chen
%% CS250
%% Final Project
%% Bird vars
max_speed = 10; %m/s
numBirds = 10;
side_length = 10;
leader_id = randi(numBirds,1);
%% Environment vars
sky_xlim = 200;
sky_ylim = 200;
%% Initialize birds
birds = initBirds(numBirds,side_length,max_speed,sky_xlim,sky_ylim);
birdsList{1} = birds; % birds... |
function Falsapos = Fpos(a,b)
fprintf('a,b,error,iteracion\n');
f=inline('exp(-1*(x^2))-cos(x)');
iteracion=1;
T=0.00001;
E=10;
tic
po=a;
while(T<E)
p=(a*f(b)-b*f(a))/(f(b)-f(a));
if f(a)*f(p)<0
b=p;
end
if f(p)*f(b)<0
a=p;
end
E=abs(((p)... |
clear all
clc
load ProjectTerrain
h=T/1000;
C=1/20000;
g=3.7;
cg=1;
V=0.01;
cycles=100;
constrain='constraints.ini';
[dhdx dhdy]=calc_gradients(x,y,h);
[ segment,TerrainFile,xs,ys,xe,ye,nwp,wp ] = getProjectInput( 'path1.ini' );
[xp_path1,yp_path1,hp_path1,dist_1B1,hplus_1B1,hminus_1B1]=computepath(xs,ys,xe... |
function [new_ft_data] = remove_outliers(mean_ft_data)
%Order data least to greatest
sorted_ft = sort(mean_ft_data);
%Find the median
med_sft = median(sorted_ft);
%Calculate median of lower & upper half of data
half_length = floor(length(sorted_ft/2));
up = sorted_ft(half_length+1:end);
low = sorted_ft(1:half_length... |
function [ePb,eeqm,evar] = eqm(mu, sigma)
nSimu = 3000;
nGenere = 10;
v = 1;
s = 2*v*round(rand(nSimu, nGenere)) - v;
n = randn(nSimu, nGenere) * sqrt(sigma) + mu;
r = s + n;
signal = mean(s < 0 & r > 0,2) + mean(s > 0 & r < 0,2);
% for i = 1:nSimu
% P1 = mean(s(i, :) < 0 & r(i, :) > 0);
% P2 = mean(s... |
function [D,temp2,Eij] = EnergyDistance_wn(data,n_mc,n_types,n_time,n_mod);
% n_mod % # models
% n_types % # observation types
% n_time % # of observations along time
% n_mc % # of realizations per model
tic
% computing fragments "Eij" of D^2
% figure which terms Eij are actually need... |
function ISO = IsoShadow(Y1,Y2,Y3,F,Nlvl,lvl)
% A function for visualizing 3D level sets of a 3D ridge function
% Yi: N by N matrix where N are the number of meshgrid points
% F: N^3 by 1 matrix function evaluations paired with reshaped rows of Yi
% Nlvl: The number of level sets over the observed range of F
% lv... |
function [output] = readData(s)
% Read value returned via Serial communication
output = fscanf(s);
end
|
function vp = CalculezValProprii(d, s, m, tol)
% Se calculeaza intervalele in care se gasesc valori proprii cu functia
% IntervaleValProprii de la cerinta 4;
r = IntervaleValProprii(d, s, m);
n = length(d);
if m > n
m = n;
endif
% Se aplica metoda bisectiei pe fiecare interval in care se gaseste o
% valo... |
% Forest表格
% 数的种类(kind) 胸径(DBH) 株数（num） 受危害株数(num_ill) 幼苗株数(num_new)
%
%郁闭度Y，乔木层密度p1,更新密度p2，多样性指标mul,病虫危害比率p,火险等级h，土壤有机质含量t
%
%输入数据
area=1000*500/10000; %公顷
n_kind=input('请输入树种的数目):');
Forest=zeros(n_kind,5);
for ii=1:n_kind
string=['请输入第' int2str(ii) '种树的[胸径,株数,受危害株数,幼苗株数]:'];
temp=input(string);
For... |
function keypress(hobj,event)
figure('KeyPressFcn',@keypress);% function KEY=keyboardinput()
global KEY;
%设置figure的KeyPressFcn回调函数，以响应键盘按下的事件
% figure('KeyPressFcn',@keypress);
% function keypress(hobj,event)
%取得figure的CurrentCharacter属性值，并在命令窗口显示
% key=get(hobj,'CurrentCharacter');
KEY=0;
... |
function vt=shiftGame(clv,t);
% SHIFTGAME computes from the game v the t-shift game of v.
%
% Usage: vt=clv.shiftGame(t)
%
% Define variables:
% output:
% vt -- Returns the characteristic function of the
% t-shfit game of v.
%
% input:
% clv -- TuGame class object.
% t -- epsilon ... |
function [Tex_Euler, Axes_Euler, Axes_Aspect, strain] = ReadTexFile(pname, it_start, it_end,phase_index)
% Reads texture and morphology matrices from TEX_PH#.OUT files for each
% step
% Input:
% pname: path to texture files for a given point
% it_start: the first deformation iteration
% it_end: the final deforma... |
function idx = closestval(a,b,w)
% function closestval - find closest match to a given value
%
% syntax: idx = closestval(a,b)
% idx = closestval(a,b,w)
%
% closestval(a,b) finds the index idx of the value in vector a closest to
% the scalar b. For several identical nearest values, idx only returns the
% first... |
function [disconnected_inlier_point_indices, all_disconnected_inlier_point_indices] =...
find_disconnected_inlier_point_indices(...
disconnected_inliers, common_point_flags, group_assignments,...
group_idx1, group_idx2)
disconnected_inlier_point_indices = [];
all_disconnected_inlier_point_indices =... |
theta_timeline_corr=theta_timeline;
end_ts=length(theta_timeline);
theta_prev=theta_timeline(1);
DTHETA_INF=-0.9*pi;
DTHETA_SUP=0.9*pi;
inf_chunk=zeros(end_ts,1);
sup_chunk=zeros(end_ts,1);
for t=2:end_ts-1
theta_prev=theta_timeline(t-1);
theta_next=theta_timeline(t);
Dtheta=theta_next-theta_prev;
if... |
function outp(~, value)
disp(value); |
function [Utr,S1]=slepEigsLaplacian(A,D,CONST_W,opts)
[Utr,S1]=eigs(@Binline,size(A,1),max(CONST_W),'sa',opts);
function y=Binline(x)
y=D*x-A*x;
end
end
|
function [d, indices, newIndices]=findBedsWithVoxelizing()
load('compsSideViewsAll')
load('../../dataStructureForStatistics/bedrooms_2_with_dist_nametags.mat')
load('compsHeightViewsAll')
tic
j=0;
distToGround=zeros(0, 1);
sizes=zeros(0, 3);
distsToWalls=zeros(0, 4);
indices=zeros(0,1);
% clear comps;
for ... |
% ============================================
% Author: Alex Chen
% email: alextpf@gmail.com
% 2014
% ============================================
function tri = Triangulation(verts)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 1. Do Delaunay triangulation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
verts = ve... |
function [dj] = dJ(q, dq)
global l1 l2
t1 = q(1);
t2 = q(2);
dt1= dq(1);
dt2= dq(2);
dj = [ -l1*cos(t1)*dt1 - l2*sin(t1+t2)*(dt1+dt2), -l2*cos(t1+t2)*(dt1+dt2)
-l1*sin(t1)*dt1 - l2*sin(t1+t2)*(dt1+dt2), -l2*sin(t1+t2)*(dt1+dt2) ];
end |
function [labels, data, word] = prep()
load('./nips_1-17.mat');
cn = find(contains(docs_names, 'CN'));
lt = find(contains(docs_names, 'LT'));
ns = find(contains(docs_names, 'NS'));
rows = sort([cn lt ns]);
mycounts = counts(:, rows)';
labels = ones(1, length(rows));
names = docs_names(ro... |
function [radar_UL,cov_UL] = tsp_radar_code_UL(ULcomm, radar_UL, radar_comm_UL, cov_UL,k)
% radar code matrix update
I = ULcomm.UL_num;
Mr = radar_UL.TX;
K = radar_UL.codelength;
Nr = radar_UL.RX;
%eta_B = radar_comm.Bmrchannelgains;
eta_rt = radar_UL.channelgain;
H_rB = radar_comm_UL.radar2BSchannels;
%% Ar_k
xi_UL_k ... |
function test_label = improved_Recognition(X_trn_subt, X_tst_subt, W_trn, train_face_id)
num_test_imgs = size(X_tst_subt, 2);
X_test_Proj = X_tst_subt * W_trn(1:num_test_imgs, :) * W_trn(1:num_test_imgs, :)';
X_train_Proj = X_trn_subt * W_trn * W_trn';
num_train_imgs = size(X_train_Proj, 2);
test_label ... |
function StableObject_SSF(varargin)
global screen
try
InitScreen(0);
Add2StimLogList();
p=ParseInput(varargin{:});
objColors = p.Results.objColors;
objRect = p.Results.rects;
backContrast = p.Results.backContrast;
backReverseFreq = p.Results.backReverseFreq; % for rev... |
clc;clear;
fprintf('**** Design of Screwjack ****\n\n');
%----------------------------------------
%----Design of screw----%
W = input('Enter Load to be lifted (KN):');
Sst = input('Enter Screw material Tensile Strength (Mpa):');
Sss = input('Enter Screw material Shear Strength (Mpa):');
Pb = input('Enter Bearing press... |
A = [3,2,5,4,6;
2,1,3,-7,8;
5,3,2,5,-4;
4,-7,5,1,3;
6,8,-4,3,8];
%********************************************
Maxtimes = 100;
n = 5;
e = 1e-7;
V = diag(diag(ones(n)));
for i = 1:Maxtimes
Nodiag = abs(A) - diag(diag(A));
Max = max(reshape(Nodiag,numel(A),1));
[p,q] = find(Nodiag == Max);
... |
close all; clear all; clc;
addpath(genpath('./'))
I = im2double(imread('house.tif'));
SNR_0 = zeros(1,20);
SNR_G = zeros(1,20);
SNR_S = zeros(1,20);
i = 0;
for s = 0.01:0.1:2
i=i+1;
[SNR_0(i) ,SNR_G(i), SNR_S(i)]=denoise(I,s)... |
%This is anticausal T(z). The output is a structure with H,F,H such that T(z) = H (z^-1 - F)^-1 G
function T = TF_T(sys)
Klqr = sys.Klqr;
P = sys.P;
R_e = inv (sqrtm(( sys.R + sys.B'*P*sys.B )'));
T.H = R_e*sys.B';
T.F = (sys.A-sys.B*Klqr)';
T.G = (sys.A-sys.B*Klqr)'*sys.W;
% T.dim = siz... |
s = [ 7.4142 4.1611 2.2523; 7.4045 4.4941 2.3438; 7.3988 4.2809 2.3565];
llim = 3.5;
rlim = 5.5;
n1 = 4:0.5:5;
n2 = 4:0.5:5;
cx=zeros(3,1);
cy=zeros(3,1);
figure('Position', [0 0 800 800]);
xlim([llim rlim]);
ylim([llim rlim]);
p = get(gca, 'Position');
lx = get(gca, 'XLim');
ly = get(gca, 'YLim');
for i = 1:3
... |
function r = rand_bac( coherencesteps, totalsteps )
%r = rand_bac( coherencesteps, totalsteps )
% Generate random time series with bounded autocorrelation.
%
% This procedure returns a column vector of random numbers of length
% TOTALSTEPS, whose autocorrelation is zero for lags greater than or
% equal to COHER... |
function haxs = plotXYpanels(t, x, y, tlims, xyaxslims, indz, haxs)
% haxs = PLOTXYPANELS(t, x, y, tlims, xyaxslims, indz, haxs)
%
% inputs
% - t: vector array of the independent variable.
% - x: vector or matrix with first dependent variable.
% - y: the other dependent variables, same size as x.
% ... |
% book : Signals and Systems Laboratory with MATLAB
% authors : Alex Palamides & Anastasia Veloni
%
%
%
% z-Transform computation
% Sequence of finite duration
% problem 1
% a)
f=[-3,5,6,7,8];
n=-2:2;
syms z
F=sum(f.*(z.^-n))
pretty(F)
% b)
n=0:4;
F=sum(f.*(z.^-n));
pretty(F)
%Sequenc... |
function [stego]=conceal(msgVec1_CA,msgVec2_CA,cover,Delta,main_folder)
YCbCr=rgb2ycbcr(cover); % RGB to YCbCr
Cb=YCbCr(:,:,2);
Cr=YCbCr(:,:,3);
[C,R]=size(Cb);
cd(strcat(main_folder,'\curvelet transform'));
scales_fdct_Cb = fdct_wrapping(Cb,1,1); % take curvelet Cb
... |
function rets = loadGenRets(time,bf,gen_rets_file,asset_n,flag)
% this file constructs a path independent matrix of returns, loading
% already generated scenarios and inserting them in such a way that
% nodes belonging to the same time layer have the same descendants
if nargin<5
flag=0;
end
t=length... |
clear all;
expall_init;
atkFreeRevenue = 0.3150;
atkDi=calcDI(50);
attackTestPrHist=zeros(length(timeTrainDay),1);
attackTestRPHist=zeros(length(timeTrainDay),1);
Pr=50*ones(length(atkDi),1);
attackVect=zeros(length(atkDi),1);
maxAttack=10;
PrDiffWindow=10;
lastDecTime=1;
maxDec=floor((max(timeTrainDay)-min(timeT... |
load('GPL6244_Expr_intersect');
N=15507;
ff = @(x)fitnessf(x,C,P);
if max(size(gcp)) == 0 % parallel pool needed
parpool % create the parallel pool
end
%options = gaoptimset('PlotFcns',@gaplotbestf);
gaoptions = gaoptimset('Display','iter','UseParallel',true,...
'StallGenLimit',150);
for k=16:30
tic... |
%mnist data visualization
clear
clc
%close all
indices = [1 110 210 310 410 510 610 710 810 910];%randsample(COLS, 10000);
if 0
figure;
suptitle('Cross-encoder results part1');
ROWS=10;
COLS=11;
offset = 0;
k = 1;
for digit1 = 1:5
k = 1;
digit2 = digit1+1;
str_digit... |
function sig_mix = conductivity_mixture(sig1,sig2,alpha)
% Input:
% sig1: conductivity of first component
% sig2: conductivity of second component
% alpha: ratio of two components. alpha = 1 for pure 2nd component
% Output:
% sig_mix: conductivity of mixture
... |
function [ output_bits ] = brute_force_decode( input_bits, generators )
code_rate = 1/size(generators, 2);
N = length(input_bits)*code_rate;
best_dist = inf;
% For every possibe N-bit sequence, s
% 2^N-1 iterations
for i=0:2^N-1
seq = dec2bin(i, N) == '1';
% encode sequence s as ... |
function setColorSwitchRaw(colorSwitch)
global trackingParams;
trackingParams.colorSwitch = colorSwitch;
|
clear all; close all;
addpath('./feature_util');
addpath('./edison_matlab_interface');
addpath('./matlabPyrTools');
%run('./vlfeat/toolbox/vl_setup');
datasets = {'PASCAL_S', 'ECSSD', 'DUTS_Test', 'HKU_IS', 'DUT_OMRON'};
gt_all_path = '../DATASETS/TEST/';
for dataset_id = 1:length(datasets)
MatSaveDir = ['... |
% vim: sw=2:ts=2
function sys=parse_netlist()
ckt=Ckt;
sys.E=ckt.C;
sys.A=-ckt.G;
sys.B=ckt.B;
end
|
function [ x ] = triangular_pulse( input_args )
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
x = zeros(M,1);
for n = 0:M-1
if (n <= M/2)
end
|
function scrollfcn(hfig,evnt)
gd=guidata(hfig);
mousenew = get(gd.ax1,'CurrentPoint');
xy=mousenew(1,1:2);
xl=get(gd.ax1,'xlim');
yl=get(gd.ax1,'ylim');
xrange=diff(xl);
yrange=diff(yl);
gd.xlims=[xy(1)-(xrange/2) xy(1)+(xrange/2)];
gd.ylims=[xy(2)-(yrange/2) xy(2)+(yrange/2)];
set(gd.ax1,'xlim',gd.xlims,...
... |
function varargout = has_linsol(varargin)
%HAS_LINSOL Check if a particular plugin is available.
%
% bool = HAS_LINSOL(char name)
%
%
%
%
[varargout{1:nargout}] = casadiMEX(838, varargin{:});
end
|
function [eta c finalError] = findSolution(iniGuessEta, iniGuessC, g, h, L, sigma, options)
%
%
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
% [eta c finalError] = findSolution(iniGuess, period, c,sigma,h)
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
%
% Usi... |
% FINDENDSJUNCTIONS - find junctions and endings in a line/edge image
%
% Usage: [rj, cj, re, ce] = findendsjunctions(edgeim, disp)
%
% Arguments: edgeim - A binary image marking lines/edges in an image. It is
% assumed that this is a thinned or skeleton image (or
% nearly s... |
close all, clear all, clc;
z =load('d2noisy.txt');
x1 = z(:,1:2);
y = z(:,3);
figure
plot3(x1(:,1),x1(:,2), y, 'o');
x = [ones(size(x1,1),1) x1];
trainingSamples = 50 ;%//number of rows in x
numFeatures = 3 ;%//number of cols in x or number of constants
theta = [0 0 0]';
maxIterations = 500000; %500000 iterations, e... |
% Harris detector
clear, clc, close all
imageFiles = {'pink.jpg'};
for nImage = 1:length(imageFiles)
% Load image
img = imread(imageFiles{nImage});
img = im2double(img);
imgGray = rgb2gray(img);
figure(1); clf;
imshow(img); title('Original Image');
% Calculate Harris corn... |
% Chapter 4 - Electromagnetic Waves and Optical Resonators.
% Program_4a - Iteration of the Ikeda Map.
% Copyright Birkhauser 2013. Stephen Lynch.
% Chaotic attractor for the Ikeda map (Figure 4.11(b)).
clear
echo off
A=10;
B=0.15;
N=10000;
E=zeros(1,N);x=zeros(1,N);y=zeros(1,N);
E(1)=A;x(1)=A;y(1)=0;
for ... |
%define a line of a specified length
n = input('Number of Needles:\n');
for i = 1:n
x = 10*rand;
y = 10*rand;
theta = 2*pi*rand;
x_values = [x,x + cos(theta)];
y_values = [y, y + sin(theta)];
line(x_values, y_values)
end
axis([0, 10, 0, 10])
% for j=1:n
% if floor(x_values(j,1))==floor(x_values(j,2))
% ... |
clear all
close all
clc
tf = 20;
p = [1;9.81;0.1];
x0 = [0;0];
%x0 = [pi;0];
u0 = 0.0;
f0 = DynFunc(0,x0,u0,p);
display(['Steady-state? f(x0,u0)= [',num2str(f0.'),']'])
[A,B] = LinFunc(x0,u0,p);
dx0 = [90*pi/180;0];
opt = odeset('MaxStep',1e-1);
Dyn = @(t,x) DynFunc(t,x,u0,p);
[t,x]=ode45(Dyn,[0 tf],x0+dx0,op... |
%Graficos SVM
% HP LS-SVM MSE
load(['','results.mat']);
figure(1)
plot (Data.x, Data.y, 'b--o');
xlabel('Topología');
ylabel('LS-SMV MSE'); |
ALPHA = 0.5;
SIGMA = 0.1;
N = 500; % Total no. of customers
K = 1; % Current no. of occupied tables
TABLES = zeros(1,N);
TABLES(K) = 1;
THETA = zeros(2,N);
THETA(:,K) = [rand;rand];
for i = 2:N
table_prob = zeros(1,K+1);
for k = 1:K
table_prob(k) = TABLES(k)/(i-1+ALPHA);
end ... |
function [ sobel_img ] = SobelFilter(img)
[m,n]=size(img); %m=height n=width
disp('Begin SobelFilter');
sobel_img = img;
SOBEL_CAP = 31;
for y=2:n-1;
for x=2:m-1;
val = ((img (x + 1,(y - 1)) - img(x - 1,(y - 1) )) + (img(x + 1,y) - img( x - 1,y)) * 2 + (img(x + 1,(y + 1)) - img( x - 1,(y + 1))));
... |
function [box] = min_bounding_box_aligned(data_column_vectors)
%minimum volume axis-aligned box bounding the given vectors
%
%usage
%-----
% min_bounding_box_aligned(data_column_vectors)
%
%input
%-----
% data_column_vectors = coordinates of data points as matrix of column
% vectors
% ... |
%%%%%%%% PLOT ACCUMULATED MOTION DM %%%%%%%%
function plotAccumMotionDM(motionA, accumParams)
motionA.eccCount
% notmalize protrusions and retractions
for b=1:accumParams.numBinsEcc
protrusionFront(b,:) = motionA.protrusionEccSum(b,:)/motionA.eccCount(b);
retractionFront(b,:) = motionA.retractionEccSum(b,:)/mo... |
clc, clear all
params = load('results/optimize/inriaParametersGoChosenSmall.mat');
test = load('results/inriaTestSvmGoChosenSmallFinal.mat');
paths = load('paths');
% params.method.detectorArgs = {'type','square','scales',2.^(0:0.1:2),'spacing',1};
params.method.detectorArgs = {'type','square','scales',2.^(1.32:0.005... |
clear all ; close all ;
cd('C:\shared\badger\alex\Russell BADGER 2015-11-12') ; ls
ref1 = load_untouch_nii('reg_mc_Test_Russell_2015_11_12_WIP_EEG-fMRI_MB3_3.75mm_SENSE_6_1.nii.gz') ;
topup = load_untouch_nii('Test_Russell_2015_11_12_WIP_revEEG-fMRI_MB3_3.75mm_SENSE_12_1.nii') ;
reptopup = repmat(topup.img,[1,1... |
function [retVoterMask] = generate_voter_mask(voterec,scoresK,scoresK_id,...
testpos, codebook, valid_vote_idx, imgsz, maskRadius)
if(length(maskRadius)==1)
maskRadius = [maskRadius,maskRadius];
end
annolist = codebook.annolist;
nb_test = size(testpos, 1);
nhypo = length(voterec);
retVoterMa... |
% AERSP 458 Project 1
%% Case1
clear, clc
format long
r0 = [-1.7512, 2.0439, -2.6693]; %[LU]
v0 = [-2.1843, -0.4926, 0.4740]; %[LU/TU]
t0 = 0;
t1 = 1.7; %[TU]
mu = 4*pi^2; %[LU^3/TU^2]
h = cross(r0,v0);
p = norm(h)^2/mu;
a = -mu*norm(r0)/(norm(r0)*norm(v0)^2-2*mu);
e = sqrt(1 - p/a);
alpha = 1/a;
sigm... |
%Stuart McDonald Problem 2 ECEN 5244
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Correlation and standard deviation from problem %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
sigma1 = 1
sigma2 = 2
sigma3 = 3
rho12 = 0.5
rho23 = -0.5'
r... |
%Optimum Alpha taken as 5.5 found from the previous code
clc;
clear all;
close all;
%generating random bits
data = randi([0 1],1024,1,'int8');
%modulating as QPPSK symbols to generate X
sym = nrSymbolModulate(data,'QPSK','OutputDataType','single');
sym = sym * sqrt(2);
X = diag(sym);
%generating F using meshgrid
L =... |
classdef (Abstract,Sealed) Viewer
methods (Static)
commandInfo = Info()
Help(command)
AddPolygons(polygonsStruct)
CaptureSpinMovie()
ImageOut = CaptureWindow()
ClearAllTextures(BufferType)
ClearTextureFrame(Frame,BufferType)
Close()
DeleteAllPolygons()
Init(pathStr)
InitVolum... |
function mapFind(m,k)
|
% This is material illustrating the methods from the book
% Financial Modelling - Theory, Implementation and Practice with Matlab
% source
% Wiley Finance Series
% ISBN 978-0-470-74489-5
%
% Date: 02.05.2012
%
% Authors: Joerg Kienitz
% Daniel Wetterau
%
% Please send comments, suggestions, bugs,... |
function [ Data ] = HighlightRegions( Data, CC, RegionIdx, HighlightVal )
%HighlightRegions returns an image with the selected pixels highlighted
% Pixels are fed by their RegionIdx, which is the pixel location in
% singular array format
if(isfloat(HighlightVal))
for x=(1:numel(RegionIdx))
Data(CC.Pix... |
function out = model
%
% BPMFC.m
%
% Model exported on Sep 11 2019, 15:13 by COMSOL 5.1.0.234.
import com.comsol.model.*
import com.comsol.model.util.*
model = ModelUtil.create('Model');
model.modelPath(['D:\OneDrive - business\Work\2D' native2unicode(hex2dec({'6c' 'e2'}), 'unicode') native2unicode(hex2dec({'6d' '6a'}... |
function [output]=DACss2(fs, Inom, Vini, R, Co, Ri, Rsi, Ci)
% [output]=DACss2(fs, Inom, Vini, R, Co, Ri, Rsi, Ci)
% Creates a state-space model of one output channel of a current-steering
% DAC and simulates one switching period. fs is the sampling frequency, Inom
% is a vector containing the nominal current values o... |
function experimentInfo = getExperimentFeatures()
experimentInfo(1).type = 'chr2_during';
experimentInfo(2).type = 'chr2_between';
experimentInfo(3).type = 'arch_during';
experimentInfo(4).type = 'eyfp';
experimentInfo(5).type = 'arch_between';
for iExpt = 1 : length(experimentInfo)
switch experimentInfo(iExpt).t... |
function [ A_row ] = plate_10_A( plate_idx, p, p0, p1, p2, p3, p4, p5, p6, M_x_max, M_y_max, N_max, N_10, d_x, d_y, d_z, epsilon, epsilon_b, Epsilon_0 )
A_row = zeros(1, 2);
% A_row = zeros( 1, M_x_max * M_y_max * ( N_max + N_10 ) );
if plate_idx
A_row(1) = p0;
A_row(2) = 1; % center point
else
warning(... |
%digitDatasetPath = fullfile(matlabroot,'toolbox','nnet','nndemos', ...
% 'nndatasets','DigitDataset');
addpath ../data/;
trainimages=LoadImage('../data/train-images-idx3-ubyte');
trainimages=reshape(trainimages,28,28,1,[]);
trainlabels=LoadLabel('../data/train-labels-idx1-ubyte');
trainlabels(trainlabels==0)=10;
te... |
function killevery2ndytl
ytl=get(gca,'yticklabel'); for yy=2:2:numel(ytl), ytl{yy}='';end; set(gca,'ytickLabel',ytl) |
function PostWrapper(problemnameArray, solvernameArray, repsSoln)
% Take post-replications at solutions recorded during previous
% runs of solvers on problems.
% Inputs:
% problemnameArray: structure listing the problem names
% solvernameArray: structure listing the solver names
% repsSoln: number of replications for ... |
clear; clc;
% designate a subset of files to process (or leave it empty to process all)
% TODO: Make this a number or the indicators a string?
%FP_PROC_SUBSET = [ "0129", "0124" ];
FP_PROC_SUBSET = []
% change these to the relevant locations on your disk
FP_RAW_FILE_DIR = 'C:\Users\zls5\Desktop\Zach\Hao'; % raw file ... |
clc; close all; clear;
load('Y.mat');
load('X.mat');
% load('X_noisy.mat');
% X = X_noisy;
iterations = 850;
stepsize = 0.0001;
[~, error_per_iter] = gradient_ascent_fixed(X,Y,stepsize,iterations);
clear weights
X = [X, ones(size(X,1),1)];
[weights, error_per_iter_cons] = gradient_ascent_fixed(X,Y,stepsize,itera... |
sig2 = 0.4;
gam = 10;
crit_L1 = bay_lssvm ({ Xtrain , Ytrain , 'f', gam , sig2 }, 1);
crit_L2 = bay_lssvm ({ Xtrain , Ytrain , 'f', gam , sig2 }, 2);
crit_L3 = bay_lssvm ({ Xtrain , Ytrain , 'f', gam , sig2 }, 3);
%The model can be optimized with respect to these criteria:
[~, alpha ,b] = bay_optimize ({ Xtrain , Ytrai... |
function ode_in = bodies2odein(Bodies)
num_bodies = length(Bodies);
ode_in = zeros(1, 4*num_bodies);
for n = 1:num_bodies
ode_in(2*n-1) = Bodies(n).Xpos;
ode_in(2*n) = Bodies(n).Ypos;
ode_in(2*n-1 + 2*num_bodies) = Bodies(n).Xvel;
ode_in(2*n + 2*num_bodies) = Bodies(n).Yvel;
end
end
|
function retVal = lookInDatabase( A, Database )
% >> Internal fuction. Not really to be used directly.. unless you have
% a Masters in Messing-Around.
% Takes an image A, computes its SURF points and descriptors, and
% matches them with any of those present in `Database` (which is a
% cell-array).
... |
function drawGrid(occupancy_grid, dim, resolution, colour)
%DRAWGRID Draws a cube representation of the occupancy grid
[row, col, plane] = ind2sub(size(occupancy_grid), find(occupancy_grid == 1));
nPoints = numel(row);
for i = 1:nPoints
cell = [row(i); col(i); plane(i)];
pos = dim(:,1) + (cell-0.5) .* resolut... |
function dim = size(s,r,param)
% Copyright 2012 The MathWorks, Inc.
dim = [s r];
|
%% default setting
clear; close all;
% get video
video = VideoReader('./jump/shahar_jump.avi');
% video = VideoReader('./bend/shahar_bend.avi');
% video = VideoReader('./skip/shahar_skip.avi');
w = video.Width;
h = video.Height;
m = int16(video.Duration * video.FrameRate);
% calling with default method which is interfr... |
function G = approxfcn(F, range)
%APPROXFCN Approximation function.
% G = APPROXFCN(F , RANGE) returns a function handle, G, that
% approximates the function handle F by using a lookup table.
% RANGE is an M -by -2 matrix specifying the input range for each of
% the M inputs to F.
num_inputs = size(range, 1);
ma... |
function [sv1,sv2,u]=fpreadsc(fname)
% FPREADSC reads the unformatted data EXPORTED by FlexPDE on a rectangular grid.
%
% Description:
% This utility function reads the unformatted
% data EXPORTED by FlexPDE using SURFACE/CONTOUR
% plot commands.
% Limitation: Acts only on rectangular domains.
% This code has ... |
clear all; clc;
% Replace the strings with the correct numbers
x = -20:1:20; % Replace the strings with the correct numbers
% Calculate the function
y = 2*exp(-0.2*x);
% Plot the function
plot(x,y,'-x','LineWidth', 2, 'Color', 'blue')
xlim([-10 10])
% X label and Y label
xlabel('ap')
ylabel('gr') |
pkg load image
useful_functions; # NB this needs to be included if video_analysis hasn't just been run
STATS_SZ = 120;
BKP_ROOT = '%03d.bkp'; # make directory path match location of bkp files
BKPS = {{10, 10, 0}, # the number of video i.e. ..024.bkp.. padded with zeros to width 3
{11, 6, 0}, # followed by tm ... |
clear
%close all
clc
% INPUTS ===============================================================
g = 9.8;
theta = 30;
b = 0.5;
x0 = 0; y0 = 0;
v0 = 10;
tSpan = [0 2];
% SETUP ===============================================================
vx0 = v0*cosd(theta); vy0 = v0*sind(theta);
s0 = [... |
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