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function Cells=FrameSegment_OCT(conn);
%
strDB='D:\Yoan\DukeOCT\AMD\AMD1.LEVER';
conn = database(strDB, '','', 'org.sqlite.JDBC', 'jdbc:sqlite:');
CONSTANTS=Read.getConstants(conn);
im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',1, ...
'timeRange',[1 1],'outType','single','prompt',false... |
function csvToVTK (in_points_csv, in_triangles_csv, out_vtk)
%in_points_csv='INDD100551-R.surf/surf_points_w1.csv'
%in_triangles_csv='INDD100551-R.surf/surf_triangles_w1.csv'
%out_vtk='INDD100551-R.surf/test_surf_tri_w1.vtk'
vertices=dlmread(in_points_csv,',',1,0);
vertices=vertices(:,1:3); %throw away garbage cols 3... |
function shoulder = find_expected_shoulder(observed_face, face_mean, shoulder_face_cov, shoulder_mean, inverse_face_cov)
shoulder = round( shoulder_mean + (shoulder_face_cov * inverse_face_cov * (observed_face - face_mean) ) );
shoulder(1) = min( max(1, shoulder(1)), 240);
shoulder(2) = min( max(1, sho... |
function varargout = seqma(varargin)
%
% SEQMA is the start of the Sequence Maker program.
% It asks the user to select the sequence paradigm.
%
% ---------------------------------------------------------------
% Sequence Maker Copyright (C) 2004 Tuomas Teinonen
%
% The software library is free software; you... |
digit_test;
indeces; |
function [hitted,missed,totalGT] = calculateHitMiss(realGT,prunnedSet)
totalGT = length(realGT);
matchedCnt = 0;
for ii = 1:1:size(realGT,2)
tempGT = realGT{1,ii};
flag = 0;
for jj = 1:1:size(prunnedSet,1)
testGT = prunnedSet{jj,1};
if(strcmp(tempGT,testGT))
matchedCnt =... |
%---Input-------------------------------------------------------------
% feat : Feature vector matrix (Instances x Features)
% label : Label matrix (Instances x 1)
% opts : Parameter settings
% opts.N : Number of solutions / population size (* for all methods)
% opts.T : Maximum number of iterations (* for all ... |
function gen_video_3(step, frame_rate)
img_1 = imread('..\img_data_1\img (1).jpg');
img_2 = imread('..\img_data_1\img (2).jpg');
img_3 = imread('..\img_data_1\img (3).jpg');
img_t1 = [img_1, img_2, img_3];
filename='video_img_slide_1';
fn_out = [filename '_1080_f' num2str(frame_rate,'%02d') ];
video_1 = VideoWriter... |
classdef Settings < fancyclip.internal.FancyclipBase & handle
% Global settings for the fancyclip package
%
% Don't use this class directly. If you want to get or set the settings,
% work with the instance of this in the fancyclip.globals.settings field
properties
end
methods (Static=true)
function out = d... |
function [ X, Phi ] = get_symmetric_mode( params, C, xspan )
% Calculate a symmetric mode using the parameter C of the asymptotic 'asympt'
%
% INPUT:
%
xstart = xspan(1);
% From the asymtote of the solutions
asympt_params = @(x) asympt(params, C, x);
% Derivative
eps = 1e-12;
init = [ asympt_params(xs... |
function [V,Ex,Ey,C,We,We2,gridpointsx,gridpointsy,innerx,innery,outerx,outery] = bvprectangularcoax(a,b,c,d,xo,yo,er,Vo)
%
% This function used the finite difference method to solve the
% two-dimensional electrostatic boundary value problem related to a square
% coaxial cable.
% a = width... |
function varargout = gaussbeam(varargin)
% GAUSSBEAM M-file for gaussbeam.fig
% GAUSSBEAM, by itself, creates a new GAUSSBEAM or raises the existing
% singleton*.
%
% H = GAUSSBEAM returns the handle to a new GAUSSBEAM or the handle to
% the existing singleton*.
%
% GAUSSBEAM('CALLBACK'... |
clear; clc;
warning('off')
s = tf('s');
% TRANSFER FUNCTION FROM EXPERIMENTAL MODEL
Km = 1361.48; % CONSTANT
pm = 28.692; % POLE
Gm = Km/(s*(s+pm)); % Open loop motor TF
% CONTROLLERS
% COEFICIENTS
%Integral
tau_i_pi = 0.2;
%Derivative
tau_d_pd = 1/100;
%Both
tau_i_pid = 0.2; % Integral coeff
ta... |
function new_extract_feat_and_pred_cat(setup_data,question,network,experiment)
% new_extract_feat_and_pred_cat( network.caffestuff)
if isfield(question.setlist,'cat_idx_all_trainval')
cat_idx_all_trainval = question.setlist.cat_idx_all_trainval;
else
cat_idx_all_trainval = question.setlist.cat_idx_all;
end
... |
classdef LmfitPolynomialModel < WeakModel
properties %(Access = protected)
weak_modelSpec % model specification for MATLAB fitlm function
% (https://www.mathworks.com/help/stats/fitlm.html#inputarg_modelspec)
weak_model % trained model
end
methods
function obj = LmfitPolynomialModel(mode... |
function [sigx, sigy] = sigma_parabolic(x, y, xnorm)
% SIGMA_PARABOLIC uses a parabola for the variance at each x and y value.
%
% INPUT: X -- the x-values
% Y -- the y-values
%
% OUTPUT: SIGX -- the corresponding sigmax given the x-value
% SIGY -- the corresponding sigmay given the y-v... |
function ij = RouletteWheelSelection(prob)
r=rand;
c=cumsum(prob);
ij=find(r<=c,1,'first');
end |
function log = cora_rr_param_experiments()
HA = rod_reactor_HA_cora();
options.enclosureEnables = [3 5];
options.guardIntersect = 'polytope';
% options
Zcenter = interval([510;20;20],[520;20;20]);
options.R0 = zonotope(Zcenter); %initial state for reachability analysis
options.x0 = center(options.R0); %initial state ... |
% Dynamics of the problem
function [yDyn,vDyn,mDyn] = fDyn(y,v,m,u)
global D;
global b;
g = gFunc(y);
rho = normRhoFunc(y);
% Put here the dynamics
yDyn = v;
vDyn = u./m - g - D./m.*rho.*v.*v;
mDyn = -b*u; |
clear all; close all;
load Xk.mat
task = 'a';
sigma_r = 0.1;
q = 1;
R = sigma_r^2*eye(2);
Xs(:,1) = [Xk(:,1); 0; 0];
% yk = [0; 0];
for i = 2:size(Xk,2)
Xs(:,i) = [Xk(:,i); Xk(:,i)-Xk(:,i-1)];
yk(:,i-1) = Xs(3:4,i)+mvnrnd(zeros(2,1), R)';
end
x_0 = Xs(:,1);
P_0 = zeros(size(Xs(:,1),1));
T = 1;
A = [1 0 T 0;0 1 0... |
function [ I,J,S ] = binary2pts( binary,score )
%turns binary image with score image into x,y,s combo
[I,J] = find(binary);
S = score(sub2ind(size(binary),I,J));
end
|
%Coeficientes del filtro de orden 4
F = [0 221 1764 4410 6615 8820 22050]/22050;
%corrección para entrar en [-32768, 32768]
A_corr = [2.1 2 1.3 1 1 1.2 1.5]*0.8;
%obtencion de coeficientes
[b,a] = yulewalk(4,F,A_corr);
[h,w] = freqz(b,a);
%gráficas
plot(F,A_corr)
hold on
plot(w/pi, abs(h))
title("Respuesta en f... |
function frqspec(w, mag)
n=length(w);
mB=mag(1)*0.707;
j=0;
Mp=max(mag);
if Mp >= mag(1)
for i=1:n
if mag(i) >= Mp
np=i; wr=w(i);
else,end
end
else, np=1
end
for i=np:n-1
if mag(i) >= mB
wB1= w(i); wB2=w(i+1); maglo=mag(i+1);
wB =(wB1+wB2)/2;
else, end
end
if ... |
% value iteration by collocation
clear
clc
clear
close all
clear
%% Given system is
Q=diag([50,50]);
R=diag([5]);
figname='2DVanderpoll_lowCtrlCost_';
saveonoff=1;
d=2;
ep=1;
g=@(x)[0;1];
f=@(x)[x(2);-x(1)+x(2)-ep*x(1)^2*x(2)];
dom=[-3,3;
-3,3];
%%
% -1.2 and -5
K=[-1.2,-1.2];
u=@(x)K*x(:);
u0=u;
% [xx,... |
function v = powerIter(A,v0,m)
v = v0
for i = 1:m
v = A*v/norm(A*v)
end |
% Adapted from extractDataForKerry to extract daily variables needed for
% computing GPI.
%
% Meg D. Fowler, 2017-10-27
%
%% Set path to variable files and read in dimensions
load('/Users/meganfowler/Documents/MATLAB/TCs/SavedMatlabData/MJOindex&time_monthPhase'); % MJOindex_monthPhase, MJOtime_monthPhase
% -----... |
%Assignment No.4: High Dynamic Range Imaging and Tone-mapping
%__Jishnu Pradeep__
%This function selects random pixels from the scenes as samples. Open f().
function Z = sampling(imgs)
imgNum = size(imgs,3);
smpNum = round(2*256/(imgNum - 1));
height = size(imgs,1);
width = size(imgs,2);
Z = zeros(smpNum,imgNum);
k... |
function [x,u,delM,alpha] = ptMR(delT,simTime,xDes,delMat,delMatTrue,dataLimit)
% MPC parameter
horizon = 20;
% state,input matrices
% t = 0:simTime/delT;
x = zeros(6,simTime / delT);
u = zeros(2,simTime / delT);
alpha = zeros(2, simTime / delT);
x0 = [0;0;10;0;0;0];
u0 = zeros(2,horizon);
hMat = [];
tMat = [];
delM =... |
%% Limpar console, variaveis e fechar janelas aberta
clc;
clear;
close all;
%% Definir massas e comprimentos dos bra�os do Rob� RR
m1 = 1;
m2 = 1;
L1 = 1;
L2 = 1;
%% Definir passo e tempo final da simula��o e pegar informa��es de tamanho dos vetores gerados
delta_time = 0.001;
final_time = 10;
t = 0:delta_time:fi... |
function [q,lambda] = PowerMethod(A,q0,m)
% function [q,lambda] = PowerMethod(A,q0,m)
% Power method.
% A is nxn, q0 is nx1, and m is a positive integer.
% q is a unit 2-norm vector in the direction of A^m*x0.
% lambda is mx1 and lambda(k) is the kth estimate of the dominant eigenvalue.
% A call of the form q =... |
function plot_spots(spots)
% plot_spots Plot targeted patches for stimulation.
if nargin<1 || isempty(spots)
disp('spots not provided')
return
end
xcoordsAll = spots.xcoordsAll;
ycoordsAll = spots.ycoordsAll;
sizesAll = spots.sizesAll;
for convert=1:size(xcoordsAll,2)
rectangle('Position',[... |
%% Uczenie maszynowe AiR, 2018
%%
%% Cwiczenie: Drzewa decyzyjne
% Cel: Ilustracja roznych aspektow budowania drzew decyzyjnych i ich weryfikowania
% Prosze uzupelnic brakujace fragmenty zgodnie z instrukcja (FIXME)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Decision Trees
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
%% Stelling 1
%
% Met de functie save() kun je data-bestanden aanmaken.
%
Antwoord = 1;
|
function varargout = mrip(image,x,y,a,b)
%MRIP Summary of this function goes here
% Detailed explanation goes here
xMax = min(ceil(x+b),size(image,2));
xMin = max(floor(x-b),1);
yMax = min(ceil(y+b),size(image,1));
yMin = max(floor(y-b),1);
[xx,yy] = meshgrid(xMin:xMax,yMin:yMax);
zz = image(yMin:yMax,xMin:xMax);
... |
function weights = helicalSimpleRedundancyWeights( gammas, beta, Delta )
a = Delta / 2;
b = Delta / 2 - 0.5;
lambda = beta - a;
lambdas = lambda + (-3:3) * pi;
lambda1 = abs( lambdas );
weights = zeros( size(gammas) );
for i = 1:length(gammas)
lambda2 = abs( lambdas + [-2 0 -2 0 -2 0 -2] * gammas(i) );
... |
classdef eval
%EVAL Summary of this class goes here
% Detailed explanation goes here
properties
end
methods (Access = 'public', Static = true, Hidden = false)
alpha = Alpha( navOrRate, benchmark, rf, flag);
beta = Beta( navOrRate, benchmark, flag);
burkeR = Burke... |
function Data = ImportDataTianjinfeiyue(fileToRead,Flag_Single)
newData = cell2mat(importdata(fileToRead));
Temperature = str2num(newData(:,21:end));
Time = newData(:,1:19);
clear newData
num = length(Temperature);
Day = zeros(num,1);
Hour = zeros(num,1);
Min = zeros(num,1);
Sec = zeros(num,1);
if Fla... |
function yhat = fullPrediction(obj,x)
% For some input data get mixture model prediction
% i.e. y_n = sum_k (weights_k,n * y_n,k)
if strcmpi(x,'val') || isequal(x,obj.x_val)
% gamma = k x n
% ypred = n x k
% gamma.*ypred --> one line per data point
% sum --> sum out the columns to get one prediction fo... |
function [dist1, dist2] = dist_orig(pts1,pts2)
%% Initializing
n1 = size(pts1,1);
n2 = size(pts2,1);
dist1 = zeros(n1,n1);
dist2 = zeros(n2,n2);
%% Computing the distances betwen every feature points of img1
for i=1:n1
for j=i+1:n1
dist1(i,j) = sqrt(sum((pts1(i,:)-pts1(j,:)).^2));
... |
function [c] = DiffusionReactionSolver(x_min, x_max, NElem, D, Lambda, bndry_1, bndry_1_val, bndry_2, bndry_2_val)
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
% Create mesh
msh = OneDimLinearMeshGen(x_min, x_max, NElem);
% Preallocate matrix sizes
RHS = zeros(NElem+1, 1);
Gl... |
% build a grid
function gridBuilder(size, divisions)
sq = ones(size);
d = ceil(size(sq,1)/divisions);
c = 0;
for i = 1:d:size(sq,1)
if mod(c, 2)==0
sq(i:i+d, :)=0;
sq(:, i:i+d)=0;
end
c = c+1;
end
imshow(sq);
end |
% SetInfo_altIR
% combines all the other 'set...' scripts into one
%check ILDAloneFlag
% XStimParams.space_flag == 1 for ILDalone
% == 0 for fully cued
% uses .STD HRIRs, therefore make sure earphone filters are also selected
XStimParams.ephone_flag = 1;
set(H.ephoneuseit,'Value',1);
... |
%% Set input to simulation
%% set input trajectory
q_dot = [-0.1,0,0,0,0.2,0];
vbb = [0,0.1,0,0.1,0,0.1];
%% set initial configuration of system
xi_euler_init = [0,0,0,0,0,0 ...
,0,pi/2.8,-pi/1.3,pi/3,-pi/2 ,0];
xi_init = [0,0,0, ...
1,0,0,0, ...
0,pi/2.8,-pi/1.3,pi/3,-pi/2 ,0
];
q_init... |
function [] = reAdjustOpenClose(obj)
% 重新调整开平
% 潘其超，20131121，V1.0
% 潘其超，20140814，V2.0
% 1. 重新修订，适应新结构。
currPos = zeros(obj.latest+1,1);
for i = 2:obj.latest+1
if obj.direction(i-1)==1
currPos(i) = currPos(i-1)+ obj.volume(i-1);
else
currPos(i) = currPos(i-1)- obj.volume(i-1);
end
end
ob... |
function [CSD,interpCSD]=CSDmovie(WF,ch,neuronNames,preMs,Fs,En,varargin)
% CSDmovie(WF,ch,neuronNames,preMs,Fs,En,varargin)
% Function purpose : Calculate distribution of post spike fields (PSF)
%
% Function recives : avgWF - average spike STAs over all electrodes in ch [Double [neurons x ch x samples]
% ... |
%stlデータの読み出し
%実行時間短縮のために、stlデータを読み出し、xlsファイルとして保存する
%initialize
clear all
clc;
tic;
%input & output
inName = 'rawData/om%d.stl';
outName = 'omvertex%d.xls';
%the number of sample
sample = 2;
%read dataset--------------------------------------------------------------
for Num = 1:sample,
facedata = sprintf(inNam... |
function [obj, varargout] = plot(obj,varargin)
%@jointevents/plot Plot function for jointevents object.
% OBJ = plot(OBJ) creates plot of the jointevents analysis result
%
Args = struct('showTitle',1,'GroupPlots',0,'GroupPlotIndex',0, ...
'Color','b','xlabel',0,'stimInfoDir',['..' filesep '..' ],'linkedZoom',1, .... |
function [ Iwarp, minR, minC ] = WarpImage( I, A )
[r,c,color] = size(I);
% get the the four corners of the given image
corners = [1 1 1;
r 1 1;
1 c 1;
r c 1];
% Transform the the corner points using the transformation matrix
cornersNe... |
function [ varargout ] = util_sti_calc_test_score_multiple_arraywide( varargin )
%UTIL_STI_CALC_TEST_SCORE_MULTIPLE_ARRAYWIDE 计算每个电极在刺激期间的Score
% 专用于处理方向性刺激Test Positive/Negative的Score程序。
% 与工具函数util_calc_sti_test_score_arraywide的区别是，
% 本函数能够处理一个Test文件中有多个不同刺激电极的情形。
%
% 输入参数：
% stimulating_chid：一个序... |
% AMIGO_report_DO: reports optimal control profile & constraints
%
%******************************************************************************
% AMIGO2: dynamic modeling, optimization and control of biological systems %
% Code development: Eva Balsa-Canto %
% Address: ... |
clear all ;
aviobj = avifile('mymovie.avi','fps',25) ;
NomDuDossier='../Ghost3/' ;
% NomDuDossier='../Maisons/' ;
for u=-3:3
for v=-3:3
Masque(u+4,v+4) = exp( -( (u*u) + (v*v) ) ) ;
end
end
Masque = Masque / sum(sum(Masque)) ;
for numero = 0:1
if(numero<10)
Nom = strcat(NomDuDos... |
clear all
clc
%% 1. LOAD OCTONION UTILITY FUNCTIONS
% addpath([fileparts(pwd),'/Data']); %add Data directory to path;
addpath('crystal_symmetry_ops');
addpath('octonion_functions/');
addpath('rotation_conversions/');
pgnum = 30; %cubic symmetry
genplot = false;
symnames = load('PGnames.mat'); %need to add crystal_s... |
function [isIntersecting] = checkIntersection(A,B,C,D)
% Check to see if line segments AB and CD are properly intersecting
% INPUTS: points A,B,C,D each with (X,Y) coordinates
% OUTPUTS: boolean giving whether there is an intersection or not
% If lines are colinear in any way or T-intersecting, but not crossing each
% ... |
%Uncomment below if it is the first time loading
% clear;
%load('..\Data\Westpoint\WestpointUnAveraged.mat');
%load('..\Data\Westpoint\WestpointAveraged.mat');
fs = 62.5e6;
x = ((0:length(WestpointAveraged(1).raw)-1)./fs).*1000;
figure;
plot(x,WestpointAveraged(2).raw);
hold on;
plot(x,WestpointUnAvera... |
function [traces,out] = spikeExtraction(traces,fps,traceOpt)
traces = traces(:,:,1);
traces = getCaEvents( traces, fps, traceOpt.tau, traceOpt.highPass );
if nargout>1
out = [];
end |
clc;clear;close;
cd ..\calibration_data_lump;
% This is the source codes for model calibration
files=dir('..\watch_basin_data\WATCH_basin_*_grid.mat');files=struct2cell(files);files=files(1,:)';%basin-specific input data
KGEval=nan(235,2);%basin_id, KGE
bsn_data=nan(240,14,235);% 240 rows of months, 14 cols:P,Robs,Rsim... |
function [tacout,indxout] = AutoCorrRec(t,tmax,nbins)
% AutoCorrRec: compute spike autocorrelations for vectors in a cell array
% Calling syntax is just like AutoCorr, except t may be a cell array
% of spike time vectors
binning = 0;
if (nargin == 3)
binning = 1;
end
if (nargout > 1 & binning)
error('Only one output ... |
Fs = 5120;
t = 0:1/Fs:1;
y = sin(10*2*pi*t);
plot(abs(fft(y)))
|
% Run this script to add subfolders to MATLAB path
addpath(genpath('algorithms'));
addpath(genpath('examples'));
addpath(genpath('experiments'));
addpath(genpath('tools')) |
clear, clc
syms u1 u2 u3 s
u = [u1; u2; u3];
unknown_vars = symvar([u; s]);
R = (2 * s * s - 1) * eye(3) + 2 * (u * transpose(u) - s * skew(u));
q = transpose(sym('q%d%d', [5, 3]));
qq = transpose(sym('qq%d%d', [5, 3]));
eqs = sym(zeros(5 * 6 + 1, 1));
temp = {};
c42 = combinator(4, 2, 'c');
for index = 1:5
... |
% ------------------------------------------------------
% Company: Georgia Tech
% Engineer: Everybody In The Group
%
% Create Date: 11/16/2017
% Design Name: Main (MATLAB model)
% Project Name: VGA Image Transpose and Edge Detection
% ------------------------------------------------------
clear all;
clo... |
function rxy = r1b(x,y,outlier)
% computes lag 1 cross correlation (r(x(2:n),y(1:n-1)))
% Useage: r1b(x,y[,outlier]) where x & y are column vectors
if (nargin<2)
fprintf(1,'Useage: r(x,y)\n');
return
end
if nargin==3
rxy=r(x(2:size(x,1)),y(1:(size(x,1)-1)),outlier(2:size(x,1)));
else
rxy=r(x(2:si... |
clear all
close all
clc
%% Generate data for Simple Harmoinc Oscillator
M = 5; % mass in KG
K = 0.2; % spring constant
Fext = 1; % external force magnitude
tf = 1000; % time span
gMode = 1; % graphic mode
sigma = 0.04; % standard deviation
[t,y,ytilde,u,X] = SimpleHarmonicOsc(M,K,Fext,t... |
function netPVSystemPower = solModel( time, location, inverterRating, varargin )
%% 0.1) Parameter Parsing =================================================
p = inputParser;
p.addRequired('time',@(x) all(isstruct(x) & isfield(x,'daylightSavings') & isfield(x,'dayOfYear')));
p.addRequired('location',@(x) all(isstr... |
clearvars
close all
addpath('../DS/lib/')
addpath('spectralFEconverge\')
global fonttype
global fontsize
global markerSZ
fonttype = 'Times New Roman';
fontsize = 14;
markerSZ = 80;
rawResults
diffNVDP
goal1StiffPlot
FSRK4ConsistencyPlot
PSConsistencyPlot
accuracyPlot
plotError |
% testOpperGP.m
% Test Opper's method in the GP Case
clear all; clc; close all;
%% DELETE ME
%rng('default');
%% Generate Data from GP prior and Linear Fwd Model
N = 100; % Number of observations
PTRAIN = 0.1;
[data trueParam] = generateDataGPPriorLinearFwd( N, PTRAIN );
%% We use true param that generatd t... |
function P = permute_abundances(A1,A2)
%PERMUTE_ABUNDANCES Permute abundance maps in A2 such that they match the
%abundance maps in A1. Warning: it assumes that most elements in the
%abundance maps are 1s. To permute arbitrary values, use
%permute_endmembers.
% Input:
% A1: N by M_1 matrix of the abundance maps to be... |
% Plot spectrum and add callbacks for peak searching
% Controls (work on both panels):
% BTN: scroll to new position
% CTRL-BTN: add point
% SHIFT-BTN: remove point
% 0-9,+,-: change N_r
% s - save data to <name>_cwpeaks.mat
% t - save peak positions to <name>_cwpeaks.txt
% h - print this help message
% ... |
% ---------------------------------------------------------------------- %
% Get Control Volume Geometry %
% ---------------------------------------------------------------------- %
function Duct = GetThermoDynamState(Duct,StateInfo)
% --------------------------------------... |
function [ kernel ] = GaussianKernel( w, s)
%GAUSSIANKERNEL Returns 2D array containing a gaussian kernel with width
%w and variance s
kernel = zeros(w,w);
for i = 1:w
for j = 1:w
k = (i-(w+1)/2)^2 + (j-(w+1)/2)^2;
kernel(i,j) = exp(-k/(2*s*s));
end
end
kernel = kernel/sum(kernel(:)); |
function [recon_strategy,opt_struct]=get_recon_strategy_test(testcase)
if ~exist('testcase','var')
error(' Did not specify test case, choose one of l_me, s3d, l_m3d');
end
test_case.(testcase)=1;
if isfield(test_case,'l_me')
load('get_recon_strategy_test_large_multi_echo');
[recon_strategy,opt_struct]=get... |
clear all;
clc;
vm = 5;
vc = 10;
fm = 1;
fc = 10;
fs = 100;
wm = 2*pi*fm;
wc = 2*pi*fc;
t = -2:1/fs:2;
n = length(t);
df = fs / n;
f = -fs/2:df:fs/2 - df;
% Modulation
m = vm*cos(wm*t);
c = vc*cos(wc*t);
s = m .* c;
ftm = fftshift(fft(m));
ftc = fftshift(fft(c));
fts = fftshift(fft(s));
subplot(3, 1, 1);
plot(t, ... |
function statsPlotConfMat(res,parent,opts)
% Plot the confusion matrix in the correct axes - this will require a bit
% of good coding to ensure that we can use the axes for something other
% than an image afterwards...
% Define the colour map
cmap = flipud(gray(100));
% Get the conf mat
cm = res.cm.cm;
sz = size(cm,... |
%Honors TA Final Project - Binary to Decimal Converter
%Liu 10/30/2017
%Standard Answer
bin=input('What is the binary number of conversion?(in single quote) ');
%bin needs to be in char array or string ('')
bits=input('How many bits? ');
system=menu('What is the binary system of use?','Unsigned','Signed');
posdec=0;
... |
%% Opdracht 6
%
% Maak een functie met de naam opdracht_6.
% De functie heeft 1 input genaamd: inputvar.
% De functie heeft 1 output genaamd: outputvar.
%
% De functie geeft bij verschillende numerieke waardes van 'inputvar'
% (de waardes 6 tot en met 10) verschillende tekstuele outputs.
%
% Je mag geen gebruik maken v... |
function R = generateRotation(rx,ry,rz)
Rx = [1 0 0; 0 cosd(rx) -sind(rx); 0 sind(rx) cosd(rx)];
Ry = [cosd(ry) 0 sind(ry); 0 1 0; -sind(ry) 0 cosd(ry)];
Rz = [cosd(rz) -sind(rz) 0; sind(rz) cosd(rz) 0; 0 0 1];
R = Rz*Ry*Rx;
|
function [ B ] = binaryblock( K1 , N0 , N1 , M )
% This function realizes generating the periodic sequences
% K1 : the vertical direction
% N0 : the size of zeros
% N1 : the size of ones
% M : the number of period
% the horizontal direction length K2 = (N0+N1) * (M-1) + N1
% Author : Zhibin Zhao
% Place : ... |
function [S,I,C,R] = model_sicr(beta,epsilon,gamma,Gamma,mu,q,S0,I0,C0,TimeSpan)
%
% RISK_STRUCTURE( beta, epsilon, gamma, Gamma, mu, q, S0, I0, C0, MaxTime)
% This is the MATLAB version of program 2.7 from page 44 of
% "Modeling Infectious Disease in humans and animals"
% by Keeling & Rohani.
%
% It is the SIC... |
% exm3_expm_demo.m
% 例2，求解矩阵指数函数示例
% 北京邮电大学，尹霄丽
% 2018年12月
syms t;
A=[1,-2;1,4];
%e=[heaviside(t);exp(-t)*heaviside(t)];
x0=[3;2];
%求解矩阵指数函数
F=expm(t*A);
F=simplify(F)
x=F*x0;
x=simplify(x)
|
function [perform, classify_rate] = find_performance(net, tr, x, y)
[x2, y2] = ANNdata(x, y);
predictions = testANN(net, x2);
classify_rate = (size(y, 1) - nnz(predictions - y))/size(y, 1);
perform = tr.best_perf;
end
|
function [bestRunRes, runRes] = multiRESCAL(nmRuns, cores, X, errMthd, args, stopVal)
%multiRESCAL Runs RESCAL multiple times and returns all runs and the best run (least error)
% Input:
% nmRuns - number of runs to compute
% cores - number of cores to run runs on
% X - n x n x m multi-graph matrix whe... |
function result = position_tester(package, object, smallest_row, smallest_col)
% The result of this function is true if and only if appending the
% package with the given object on the given row and col doesn't result
% in overlap.
% Remeber that every non-object pixel in package has a value of -1.... |
function RotateMotorAngle(MySerial,curAngle,newAngle)
angleDiff = newAngle - curAngle;
numSteps = round(angleDiff/0.01125)
command=['xymm 1 ',num2str(numSteps),'xy'];%xy is the serial terminator
fprintf(MySerial, command); |
clc; clear;
%% Encoder & preprocessing
FILEPATH = 'charact1.txt';
mode = 1;
fileID = fopen(FILEPATH);
char = fscanf(fileID, '%s', [64, 64]);
fclose(fileID);
% Dictionary-like char to number table using ASCII code
char2num = [zeros(1,'0'-1), 0:9, zeros(1,'A'-'9'-1), (0:('V'-'A')) + 10];
img = char2num(char');
%% Q1 Di... |
function hfigs = plot_particle_distribution(TargetID, pf,k,est,truth,plot_title)
% Input: particles info pf, time index k
% Output: plot
ptk = pf{TargetID}.particles(:,:,k);
pwk = pf{TargetID}.w(:,k);
% pwk = ones(1,pf{TargetID}.Ns)./pf{TargetID}.Ns;
hfig = scatter(ptk(1,:),ptk(2,:),[],pwk,'filled... |
function varargout = zzbl(varargin)
% ZZBL MATLAB code for zzbl.fig
% ZZBL, by itself, creates a new ZZBL or raises the existing
% singleton*.
%
% H = ZZBL returns the handle to a new ZZBL or the handle to
% the existing singleton*.
%
% ZZBL('CALLBACK',hObject,eventData,handles,...) calls the l... |
function [h] = bar2plot(M_X, s_Y)
%
% NAME
%
% function [h] = bar2plot(M_X, s_Y)
%
%
% ARGUMENTS
% INPUTS
% M_X Matrix The x-axis "values"
% for the two groups
% s_Y struct holder for plot values
% ... |
function dist = euclid_dist(map, nodeInd, goalX, goalY)
%euclid_dist Get the heuristic for an input node index
%This hueristic will be euclidean distance from goal
%Get node position
[stateX,stateY] = state_from_index(map,nodeInd);
%Calculate heuristic - Euclidean distance to goal
dist = sqrt((... |
%%%%%% experiments for ANFIS with differents input data size and training
%%%%%% data.
clear
close all
load cpuFiveMinuteInterval
cpuMean = con2seq(cpuMean);
inputOption = 0; % for changing input data size.
OverallMape = []; % using when inputOption == 1
sizeOfStep = 100;
NumberOfSteps = 1;
for step = 1:NumberOfSteps %... |
function [ ] = sample( datadir )
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
R = mmread(strcat(datadir, '/rating'));
F = mmread(strcat(datadir, '/feature'));
[m,n]=size(R);
fprintf('(%d,%d,%d)\n', m, n, nnz(R));
user = sum(R,2)>=10;
R = R(user, :);
item = find(sum(R,1)>=8);
R = R(:,... |
function [dist, od] = distance(pos, timax)
% Get traveling distance from position(lat,lon,hgt) curve.
%
% Prototype: dist = distance(pos, timax)
% Inputs: pos - [lat, lon, hgt, t], must be sampled at same frequency.
% timax - the max calculated time interval
% Outputs: dist - distances with different time inter... |
function run_batch_so1(inV)
% Runs one calibration on kure
%{
Input is a cell array (b/c this is called by a generic startup routine using varargin)
IN
solverStr
'none' just compute results, no calibration
'guess' compute results from intermediate guess, after a job crashed
gNo, setNo
%}
... |
function write_ascii_profile(scene, bands, zenith, meas, model, zmax, z, flux_up, flux_dn);
for iband = 1:length(bands)
if strcmp(zenith,'diffuse')
illum = 'DIFFUSE';
else
zen = str2num(zenith);
azim = zeros(1,91);
azim([56 41 76 42 60 67]+1) = [153 147 155 76 45 41];
illum = spr... |
function frac = cpivSubpixel(val)
% remove negative values
m = min(val);
k = find(m <= 0);
if (~isempty(k)),
m(k) = m(k) - 0.0001; % everything should be slightly positive
val(:,k) = val(:,k) - repmat(m(k), [3 1]);
end;
lval = log(val);
frac = (lval(1,:) - lval(3,:))./(2*(lval(1,:) + lval(3,:) - 2*lval(2,:)));
|
classdef LegPoly < handle
%LEGENDRE Summary of this class goes here
% Detailed explanation goes here
properties
leg = []
legS = []
legInt = []
legIntS = []
legIntNB = []
end
methods
function obj = LegPoly()
%obj.order = order;
end
function computePolynomials(obj,order)
syms x t... |
%---------------------------------------------------------------------
% issosdemo1
%
% Demonstration of the ISSOS function for testing if a polynomial p
% is a sum of squares. This example uses ISSOS to construct an
% SOS decomposition for a degree four polynomial in two variables.
% See ISSOS help for more details ... |
clear, close all; clc;
% regularization parameter
alpha = 1e-4;
% construct matrix
B = [1, 1, 1; 1, 2, 3];
A = B' * B + .001 * eye(3);
% define true solution
xtrue = [1; 2; 3];
% compute right hand side (and add random perturbation)
eta = 0.05*norm( xtrue );
per = eta*randn(3,1);
b = A*xtrue + per;
% define initia... |
x=[-10:0.1:10];
sinx=sin(x);
cosx=cos(x);
y=[-10:0.5:10];
plot(sinx,cosx,y); |
% Descrete VS non-descrete simultation
%clc;
%clear all;
clcl;
%clc;
% Initalizaiton
%----------------------------------------------------------------------
compName =getComputerName;
setCD(compName);
type = 'forFit';
sim = Simulator; % create a new instance of type Simulator
sim ... |
%% Corrupt the image with noise
% should we normalise the image after adding noise or not???
%%
function [imageOut]=CorruptImage(imageIn,percentageInten)
maxIntenOriginal=max(max(imageIn));
imageOut=percentageInten*maxIntenOriginal*randn(size(imageIn))+imageIn;
end |
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