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function printer = latexPrinter(result, f)
%LATEXPRINTER Result bundle latex PRINTER.
% Detailed explanation goes here
if (nargin < 2)
f = 1;
end
PRINTER_FACTORY = graph.printer.PrinterFactory;
% Create a printer from custom run options.
printer = PRINTER_FACTORY.newInstance('latex', result, f);
%pri... |
function [template, mask]=GenerateTemplate(filename)
%filename='file1.jpg'
%%function [t,m]=GenerateTemplate(filename)
A=imread(filename);
%if ndims(A)>2
% A=rgb2gray(A);
%endif
%v=70;
%C=(A<=v);
%figure, imshow(C);
%% Segmentation
Pupil=PupilBoundary(A); %Centroid and radius of the Pupil
... |
% Anthony Ricciardi
% Reads Nastran .pch file
%
% Inputs:
% InString - string that is the .pch file name
%
% Outputs:
% response - [ngrid x ndofs x ncases]
% frequencies [nmodes x 1]
function [response,frequencies,ev] = punchRead(InFile)
% InFile = 'l_static';
fid = fopen(strcat(InFile,'.pch'),'r');
%... |
function [curves_in_group, from_row, to_row] = parse_group_file(groups_array, first_crv, last_crv)
group_rows = length(groups_array(:,1));
group_cols = length(groups_array(1,:));
groups_array(:, group_cols+1) = {-1};
curves_in_group = [];
%% make an array with a... |
function [predict, coefs] = LI(Xtrain,Ytrain,Xtest,~)
F=scatteredInterpolant(Xtrain(:,1),Xtrain(:,2),Xtrain(:,3),Ytrain,'linear');
predict=F(Xtest(:,1),Xtest(:,2),Xtest(:,3));
coefs=[];
|
clear all;
k0=MyConst.k0*MyConst.ab;
kk=k0*[1 0 0;
-1 0 0;
0 1 0;
0 -1 0;
0 0 1;
0 0 -1];
pot_for_ff(kk(1,:), kk(1,:),'1');
pot_for_ff(kk(2,:), kk(2,:),'2');
pot_for_ff(kk(3,:), kk(3,:),'3');
|
function [ret] = mala(a,b,c)
aux = sqrt(b^2-4*a*c);
f = (-b - aux)/(2*a);
g = (-b + aux)/(2*a);
ret = [f,g]
end
|
duct = DuctNetwork();
duct.AddParameter({'Density(kg/m^3)','Roughness(mm)','Kinematic Viscosity(m^2/s)'},[1.204,9e-5,15.11e-6]);
duct.AddBranch(0,1);
duct.AddFitting(1,'CircularDarcyWeisbach',[4.6,0.3]);%duct1
duct.AddFitting(1,'ED1_3',[0.3,0.06]);%1
duct.AddFitting(1,'CD9_1',[0.3,0.3,0]);%2 damper 1
duct.AddBranch(0,1... |
path = '\\134.130.86.237\projekt\vulnusMON\201802_Bochum\aufnahmen';
addpath(path);
irt_img = 'IRT_19_l';
rgb_img = 'RGB_19_l';
irt_img_bmp = imread(strcat(path,'\',irt_img,'.bmp'));
% get 2D matrix (irt_img) containing temperature values for each pixel in °C
irt_img = dir(strcat(path,'\',irt_img,'*.asc'));... |
function output = updatae_select_molecules(handles)
%sorted_data = handles.proc_data;
select_mol = get(handles.uitable2,'Data');
select_spec = get(handles.uitable3,'Data');
% Only Sort For Selected Molecules
%temp = cellfun(@(x) x(x==true), select_spec(:,1));
select_spec = [cell2mat(select_spec(:,1)) cellfu... |
clear all;
inFilevio = importdata('/home/jixingwu/vins_output/agz/vio.csv');
[rows_vio,cols_vio] = size(inFilevio);
% outFile = zeros(rows_vio, cols_vio-3);
outFile = inFilevio(:,1:cols_vio-3);
writematrix(outFile, 'Agz_vio.txt', 'Delimiter', ' '); |
function [equivalenceClasses, objectClassLabels, notInvolvedNodes] = ...
findConnectedComponents(sparseAdjMatrixOrEdgeList, keepOnlyAboveSize1, keepOnlyConnectedNodes, nrNodes)
% Finds connected components in undirected graph
%INPUT:
% sparseAdjMatrixOrEdgeList:
% either sparse adjanceny matrix (should be sym... |
% Graphs GKK Wealth Tax
% Sergio Ocampo Diaz
javaaddpath('jxl.jar');
javaaddpath('MXL.jar');
import mymxl.*;
import jxl.*;
%% Parameters
% Grids
n_a = 201 ;
n_z = 7 ;
n_l = 5 ;
n_e = 5 ;
Max_Age = 81 ;
Ret_Age = 45 ;
% Utility and technology
sigma = 4.00 ;
gamm... |
function directed_planning(i)
global robot direction zone task
dist_to_zone = [-(robot(i).path(1,1) - zone(robot(i).target_zone(1), robot(i).target_zone(2)).corner(1)),... % up edge
robot(i).path(1,1) - zone(robot(i).target_zone(1), robot(i).target_zone(2)).corner(3),... % down
-(robot(i).path(1,2) - zone(robo... |
clear
rng(941);
%%% construct data
n1 = 20; n2 = 30; n3 =40;
sz = [n1,n2,n3]; nd = length(sz);
ntotal = prod(sz);
r = 2; % rank
[U,~,~] = svd(randn(n1));
U = U(:, 1:r);
[V,~,~] = svd(randn(n2));
V = V(:, 1:r);
[W,~,~] = svd(randn(n3));
W = W(:, 1:r);
comp1 = kolda3(1, U(:,1), V(:,1), W(:,1));
comp2 = kolda3(1, U(:... |
function E = edges(F)
% EDGES Compute the unique undireced edges of a simplicial complex
%
% E = edges(F)
%
% Input:
% F #F x simplex-size matrix of indices of simplex corners
% Output:
% E edges in sorted order, direction of each is also sorted
%
% Example:
% % get unique undirected edges
... |
% Temperature
for i=2:length(Int)
T_raw(i) = 1/(1/T_raw(1)- k*a1{1,i}/q);
T_plus_raw(i)=1/(1/T_raw(1)- k*a1_plus{1,i}/q);
T_min_raw(i)=1/(1/T_raw(1)- k*a1_min{1,i}/q);
delta_T_interval_raw(i)=max(abs(T_plus_raw(i)-T_raw(i)),abs(T_raw(i)-T_min_raw(i)));
delta_T_slope_raw(i)=T_raw(i)^2*sqrt((del... |
%@(#) cycall.m 1.3 95/03/29 08:19:26
%
function cycall(num)
hmat=get(gcf,'userdata');
hvec=hmat(1,:);
ll=length(hvec);
for i=1:ll-2
set(hvec(i),'value',0)
end
set(hvec(num),'value',1)
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Lab 3: The geometry of two views
% (application: photo-sequencing)
addpath('sift'); % ToDo: change 'sift' to the correct path where you have the sift functions
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%... |
traindataFM = csvread('../data/trainFM4.csv');
valdataFM = csvread('../data/valFM4.csv');
testdataFM = csvread('../data/testFM4.csv');
m = length(traindataFM);
C = 2;
theta1 = linspace(0, 100, 11);
theta2 = linspace(0, 100, 11);
theta3 = linspace(-50, 50, 11);
[T1, T2, T3] = ndgrid(theta1, theta2, theta3);
evalFunc = ... |
clear all;
clf;
wb
y=data(:,3:4);
u=data(:,5);
dat=iddata(y,u,5);
%plot(dat)
na=[2 2; 2 2];
% na=[1 2; 0 2];
na=[3 3; 3 3];
nb=[1;1];
k=[1; 1];
ns=[na nb k];
th=arx(dat,ns);
present(th) |
function res = parallelPlane(plane, point)
%PARALLELPLANE Parallel to a plane through a point or at a given distance.
%
% PL2 = parallelPlane(PL, PT)
% Constructs the plane parallel to plane PL and containing the point PT.
%
% PL2 = parallelPlane(PL, D)
% Constructs the plane parallel to plane PL, and lo... |
function [roiInd] = getROI(params)
% Outputs the ROI indices specifed by `params` inputs
%
% Usage:
% [roiInd] = getROI(params)
%
% Required:
% params.sessionDir = '/path/to/session/directory'
%
% Defaults:
% params.runNum = 1; % first bold directory
% params.roiType = 'V1'; ... |
function data_trl = AMPX_to_FT_trial_split(cfg_in,evts_in, data_remap_FT)
%% AMPX_trial_split_data: converts the iv times for the gamma events to
% data trials in the FieldTrip format
%
% Inputs:
% - data_remap [struct]: data in the FT format after the channels
% have been remapped.
% - evts_in [struct]: ... |
function colorize_documentbar(varargin)
%% COLORIZE_DOCUMENTBAR Colorize the document bar of the Matlab editor
% The file names in the document bar of the Matlab editor are colorized
% according to the folders they are stored in.
% The colors are chosen to allow maximal distinct.
%
% Different modes can be sele... |
function data=DMSPdatafetchMAD(fileNameStr1,fileNameStr2,fileNameStr3)
%% DMSPdatafetch.m DMSP data fetching from MADRIGAL hdf5 file
%--------------------------------------------------------------------------
% Input
%------
% fileNameStr1 - Name of first hdf5 file of DMSP, sampling frequency of 1
% ... |
function N = get_N_dot(sigma,sigma_dot)
% Get the time derivative of N matrix for the given MRP
% Return N_dot
N = -2*sigma_dot'*sigma*eye(3)+2*tilde(sigma_dot)+4*(sigma_dot*sigma');
end
|
function [error] = Problem5_8_a(tol, figDisp, solver)
% odesample.m
% Sample code for solving a system of ODEs in matlab.
% Solves v'' = v^2 + (v')^2 - v -1 with v(0)=1, v'(0)=0
% with true solution v(t) = cos(t).
% Rewritten as a first order system.
% From http://www.amath.washington.edu/~rjl/fdmbook/chap... |
%@(#) ldptox7.m 1.1 00/11/23 10:09:04
%
function ldptox7(refufile, asyid, x, y)
if exist(refufile,'file')
refu=load(refufile);
pool=refu.poolfile;
bocfile=refu.bocfile;
[bocbuid,mminj]=readdist7(bocfile,'asyid');
[right,left]=knumhalf(mminj);
sym=refu.symmetry;
... |
function runMedianFilterOnPIVField(input_PIV_path, output_path, median_order)
% runMedianFilterOnPIVField(input_PIV_path, output_path)
% Runs a median filter on the PIV data located in input_PIV_path and
% saves the data to output_path
%
% Parameters
% ----------
% input_PIV_dir : path to directory containing ... |
function [time, axindex] = get_time_choice_from_axes(fig, axes)
%set(fig, 'Units', 'normalized');
cpnorm = get(fig, 'CurrentPoint');
%figdim = get(fig, 'Position');
%cpnorm = [cpfig(1)/figdim(3) cpfig(2)/figdim(4)];
axindex = 0;
xmargin = 0.03;%figdim(3)/20;
for i=1:length(axes)
axbounds = get(axes(i), 'Po... |
classdef (Hidden, Sealed) ReaderGraphVizPlain < graph.reader.Reader
%READERMAT Reads a graph problem from a GraphViz plain format file.
% This interface reads a GRAPH instance from a plain txt file
% generated by GraphViz.
%
% See also: READER, GRAPH.
%=========================... |
%
% Copyright 2019, Konstantinos A. Tsintotas
% ktsintot@pme.duth.gr
%
% This file is part of HMM-BoTW framework for visual loop closure detection
%
% HMM-BoTW framework is free software: you can redistribute
% it and/or modify it under the terms of the MIT License as
% published by the corresponding authors.
%
%... |
load('../data_tokamak/q_profile.mat');
load('../data_tokamak/flux_geometry.mat');
d_radial=0.01;
radial_scale=0:d_radial:1;
q_profile_radial=interp1(radial_r_value_flux,q_initial_profile,radial_scale);
for(r=2:100)
shear_profile(r)=(q_profile_radial(r+1)-q_profile_radial(r-1))/(2*d_radial);
end
shear_profile(1)... |
function LV500_format = convert_to_LV500(filename, pattern_string, digital_data);
[rows cols] = size(digital_data);
count = 1;
every_second = 1;
if ~isstr(filename)
error('FILENAME must be a string.');
end;
mellanslag = -1;
% Tillfallig struktur, skall goras mer allman senare...
digital_data
for i = 1:rows
L... |
classdef ArrayIndexClass < handle
%ARRAYINDEXCLASS Summary of this class goes here
% Detailed explanation goes here
properties
array;
end
methods
function this = ArrayIndexClass(init, type)
%
%
switch nargin
... |
%Compares orbital elements from STK vs orekit. csv file is assumed to
%contain data in the order of "Semi-major Axis (m)","Eccentricity","Inclination (deg)","RAAN (deg)","Arg of Perigee (deg)","Mean Anomaly (deg)"
%assumes that the rows are taken at the same time during the simulation
<<<<<<< HEAD
path = 'C:\Users\SEAK... |
function [Wx,Wy,MSE]=trainMLP(E,Ce,S,Ta,alfa,X,D,epocaMax,MSETarget)
%E = Numero de entradas
%Ce = Numero de camadas escondidas
%S = Numero de saidas
%Ta = Taxa de aprendizado
%alfa = contante
[p1 N] = size(X);
bias = -1;
X = [bias*ones(1,N) ; X];
%Wx e Wy são pesos inicializados com valores aleatorios
%MSETemp a... |
function [acc,lst,p] = kyu_LR_classify(data,b,RPratio)
num_nodes = size(data,1);
evidence = cell(1,num_nodes);
outcome = data(num_nodes);
for k = 1:num_nodes-1
evidence{k} = data(k);
end
evidence2 = cell2mat(evidence);
eta = [evidence2 1] * b;
mu = drxlr_invlogit(eta);
p = [outcome; mu];
if mu<RPratio RP_predict ... |
function varargout = DAQmxFunctionPool(varargin)
switch varargin{1}
case 'GetCounts'
%[meanCounts, stdCOunts] = GetCounts(SamplingFreq,Samples);
[varargout{1},varargout{2}] = GetCounts(varargin{2},varargin{3});
case 'WriteVoltage'
%[varargout{1}] = WriteVoltage(Device,Voltage);
... |
function [pairs triples_view error] ...
= cut_chromosome(family_range, kinship, kinship2ex, ...
family_genotype, viterbi, posterior, posteriorIBD1, oblist, parameters)
error = 0;
pairs = [];
triples_view = [];
time = cputime;
[pairs, corrected_viterbi, error] = generate_consistent... |
clear; close all;
addpath('../matlab_lib');
% filename_list = {
% 'PRO_1', 'PRO_2', 'PRO_3', 'PRO_4', 'PRO_5', ...
% 'SUP_1', 'SUP_2', 'SUP_3', 'SUP_4', 'SUP_5', ...
% 'FLX_1', 'FLX_2', 'FLX_3', 'FLX_4', 'FLX_5', ...
% 'EXT_1', 'EXT_2', 'EXT_3', 'EXT_4', 'EXT_5', ...
% 'PROSUP_1', 'PROSUP_2', 'PROS... |
function objs = dedrift(objs, dispopt)
% dedrift : drift correction for tracked objects
%
% Determines the mean x and y positions of objects in each frame
% Median Deltax, Deltay characterize the drift, which is then subtracted
% from the x and y positions for the output matrix.
% Does not use a linear fitt... |
%% ========================================================================
% score function (Multivariate Gaussian)
% written by Dongjin Lee (dongjin-lee@uiowa.edu)
%% ========================================================================
function [output]=scoreGauss(X, mu, cov)
%Multivariate Gaussian score... |
% Create diagram
function Example
figure(1)
clf
hold on
x = [1:10];
plot(x, x + 0.0, 'b', 'LineWidth', 2, 'DisplayName', 'First')
plot(x, x + 0.2, 'r', 'LineWidth', 2, 'DisplayName', 'First')
plot(x, x + 0.4, 'g', 'LineWidth', 2, 'DisplayName', 'First')
plot(x, x + 0.6, 'c', 'LineWidth', 2, 'DisplayName', ... |
%% Neural Network using PCA+LDA reduced data
% Clear workspace
clear
close all
clc
% Load PCA+LDA reduced data and labels.
% Change 'PCA_and_LDA' to 'PCA' or 'LDA' to run with different data
% reduction methodology of our dimensionality reduction in Step 2.
load('Reduced_data_PCA_and_LDA.mat');
load('CW2Data.mat','tr... |
% load 10-FMT results
load fmtdata
% load MovieLens 100K results
% load mldata
% for 10fmt, let cutf = 5000; for movielens, let cutf = 50000
% cutf is the number of the differences (N) fall into [-10^{-5},10^{-5}] selected for draw histogram.
% note that, N is very large, and the number of other differen... |
%hw1-1
%first number = 0.03
bit = [0 0 1 1 1 1 0 0 1 1 1 1 0 1 0 1 1 1 0 0 0 0 1 0 1 0 0 0 1 1 1 1];
ansnum = SngBinToNum(bit);
num = 0.03;
[ansbit] = NumToSngBin(num);
fprintf(1,'The binary representation of %.6f is [',num);
for i=1:32
fprintf(1,'%d',ansbit(i));
end
fprintf(1,']\nThe decimal representation of [');... |
global key
InitKeyboard();
x = distance == brick.UltrasonicDist(2);
while distance > 12
brick.MoveMotor ('AB', -50);
distance = brick.UltrasonicDist(2);
disp(distance);
if distance < 12
brick.StopMotor('AB')
brick.MoveMotor('B', -50)
distance = brick.UltrasonicDist(2);... |
%% Record data
clear, clc, close all
addpath('C:\Users\Joe\Dropbox\research\codes\f')
Fs = 8e3;
recObj = audiorecorder(Fs, 16, 2);
disp('Start speaking.')
recordblocking(recObj, 15);
disp('End of Recording.');
% Play back the recording.
play(recObj);
% Store data in double-precision array.
myRecording = getaudioda... |
function [imdb, imdbName] = get_imdb(opts)
if ~isempty(strfind(opts.modelType, 'fc')) || opts.imageSize <= 0
imdbName = sprintf('%s_fc7', opts.dataset);
else
imdbName = opts.dataset;
end
imdbFunc = str2func(['IMDB.' imdbName]);
% complete imdbName
imdbName = sprintf('%s_split%d', imdbName, opts.split);
if opts... |
function [ThermCapacity]= LJThermCapFunc(equilibrium_pos,Temp)
global nPeriods
cutoff=3;
UnitLenght=15;
xpos=equilibrium_pos(:,1:25);
ypos=equilibrium_pos(:,26:50);
V_t=[];
for Time=1:(nPeriods+1-49000)
V_point=zeros(25,25);
for j=1:25
for i=1:25
if j~=i
if abs (x... |
function new_image_ = resize_image(image_,new_size_)
new_image_ = [];
size_ = size(image_);
if ndims(size_) < 3
size_ = [size_ 1];
end
for z_ = 1:size_(3)
new_image_(:,:,z_) = interpn(double(image_(:,:,z_)), ...
1+(0:new_size_(1)-1)'*512/n... |
% Name: Main.m
% Description: Run the trajectory extraction and classification algorithms
% Authors:Meena AbdelMaseeh, Tsu-Wei Chen and Daniel Stashuk
% Data: March 23, 2015
%% Prepare the work space
clc;
clearvars;
close all;
clear global Settings;
%% Read the Settings
global Settings;
Settings = ExperimentFil... |
%%%%
% kNN tests with each data set.
% Tests can be commented in and out.
%%%%
% SPIRALS 1 DATA SET TEST:
load spiral1_train;
load spiral1_test;
[spiral1_plot_pts] = knn_k_test(30, inputs_train, target_train, inputs_test, target_test);
% SPIRALS 2 DATA SET TEST:
load spiral2_train;
load spiral2_test;
[spiral2_plot_p... |
function result = cel1( kc )
%CEL1 Evaluates the complete Bulirsch's elliptic integral of the 1st kind
%
% inf
% | |
% | dt
% cel1 = | ------------------------------
% | sqrt((1 + t^2)*(1 + kc^2*t^2))
% | |
% 0
%
% Result:
% ... |
function r=ksrmv(x,y,hx,z)
% KSRMV Multivariate kernel smoothing regression
%
% r=ksrmv(x,y) returns the Gaussian kernel regression in structure r such that
% r.f(r.x) = y(x) + e
% The bandwidth and number of samples are also stored in r.h and r.n
% respectively.
%
% r=ksrmv(x,y,h) performs the regression u... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% FDIR Research: Fault Detection Using an Extended Kalman Filter
% MATLAB-GAZEBO Simulation
%
% ROS MASTER Configuration
% - NODE1: GAZEBO
% - NODE2: MATLAB
% This simulation will generate an attack alarm by following steps.
% - An EKF-bas... |
A1=0.55;
A2=0.126;
A3=0.158;
U1=6.5;
U2=7.4;
U3=9;
A10=0.51;
A20=0.106;
A30=0.145;
beta1=466;
beta2=2866;
beta3=2246;
rho=1021;
fprintf('%2.16f\n',1/sqrt(5.^3))
fprintf('%2.16f\n',5.^(-1.5))
tic
parfor i=1:1000
data=NewtonRhapson(@(x) splitJunction(x,A1,U1,A2,U2,A3,U3,A10,A20,A30,beta1,beta2,be... |
load mp.mat
map = robotics.BinaryOccupancyGrid(40,40,1);
for y=1:40
for x=1:40
setOccupancy(map, [x y], map2(y,x))
end
end
show(map); |
function [OutputImage,OutputHist,InputHist]=HistMatch_11510714(InputImage,SpecHist)
L=256;
[M,N]=size(InputImage);
% input hist
InputHist=zeros(1,L);
for m=1:M
for n=1:N
InputHist(InputImage(m,n)+1)=InputHist(InputImage(m,n)+1)+1;
end
end
sk=zeros(1,L);
for j=1:L
sk(j)=round((L-1)*sum(InputHist(1:... |
% 2nd-order Richardson extropolation for integral approximation
% - use three results from trapzoidal to get the integral result with
% higher accuracy.
%input:
% T1,T2,T3 - three results from trapzoidal
%output:
% result
%--------------------------------------------------%
R = zeros(3);
R(1:3,1) = [T1 T2 T3]';
%--... |
%% removeEdge
% Method of the cellNetwork class to remove an edge
%%
%% Syntax
% N = removeEdge(N,ne)
%
%% Description
% Remove an edge from a cellNetwork object.
%
%% Inputs
% * N - a cellNetwork object
% * ne - a row vector containing the indices of the edges to be removed
%
%% Outputs
% * N - a new cellNetwork o... |
function H = TimNormLoo_RSAtoolboxMatrixEoutNanInfAllEv(RowData,SPM)
% RowData: raw data from searchlight
% this is the original Tim analysis with the area under the curve
flagCal = 1;
% take out Nan or inf:
mRowData = mean(RowData);
isNanOrInf = isnan(mRowData) + isinf(mRowData);
RowData2 = RowData(:,isNanOrInf==0);
%... |
function [name]= testResult( tone )
tone_processed = tone(1:20:882000,1);
BuffInDir = dir('Data/Process/*.mat');
BuffName = {BuffInDir.name};
resultCell = zeros(length(BuffName),1);
parfor i = 1:length(BuffName)
fileName = strcat('Data/Process/',BuffName{i})
y = ... |
%% Using the m file
%Do your work
result=rand;
%Now create an event telling you your work is done, reporting results and
%sending you notices:
gcaleventor('username@gmail.com', 'password', 'Finished task',...
['Results were: ' num2str(result)], 'my lab', true, true,0)
%% Using the java class directly
... |
function [xoptim,yoptim,exitflag]=heOptimise10sa%(xoptim)%(thresh2)
%%
load('NNs10.mat','NNs10')
NNsector=NNs10;
load('ddata10.mat','ddata10')
%load('GAxoutR1schools.mat.mat','xoptim')
%%
hospThresh=[18057,1];%38172 53365 74966 82966 % 18057 28115 38172 53365
t0=-59.4613;%Re-fitted as single parameter %-4... |
function [ rotVar ] = ErrorEstR3( sensorData, rotVec )
%OPTR Optimize translation based on inital guess
%--------------------------------------------------------------------------
% Required Inputs:
%--------------------------------------------------------------------------
% sensorData- nx1 cell containing sensor ... |
function fnval = findif_var_fun(times,y,p,more)
fnval = more.var.fn(times,y,p,more.more);
end
|
tic;
average1=0;
average2=0;
vec=5:5:100;
for i=1:30
[T1,Time]=arrayfun( @(x) RGP(x, 1), vec,'un',0);
average1=average1+cell2mat(Time);
end;
average1=average1/30
for i=1:30
[T1,Time]=arrayfun( @(x) RGP(x, 2), vec,'un',0);
average2=average2+cell2mat(Time);
end;
average2=average2/30
x=5:0.1:100;
y ... |
% This is the demo script for the algorithm LDS proposed in [1].
% Reference:
% [1] G. Doretto, A. Chiuso, Y. N. Wu, S. Soatto, Dynamic textures,
% International Journal of Computer Vision 51 (2) (2003) 91-109.
% Copy the mat file from "..\Experimental Results\2. Video for Test\" for
% testing.
clear;clc;
% Setti... |
function G = configuration_goodness(rbm_w, visible_state, hidden_state)
% <rbm_w> is a matrix of size <number of hidden units> by <number of visible units>
% <visible_state> is a binary matrix of size <number of visible units> by <number of configurations that we're handling in parallel>.
% <hidden_state> is a binary m... |
function ErrorCorrect(pathLR,pathT,pathAP,filenameLR,filenameT,filenameAP,fig,instructionText,statusText,txtMaxSpeed,txtMaxSpeedLR,txtMaxSpeedAP,txtRegurgitation,buttonNext, action, framerate)
%read first image to select startpoint of regiongrowing
%select approximite middlepoint of the ascending aorta
... |
clc; clear all; close all; delete(instrfind)
% Note: Please pair the BT with Windows before running this script:
% Windows start button -> Bluetooth & other devices -> Enable Bluetooth and
% pair with ESP32..
%
% Troubleshooting https://se.mathworks.com/help/instrument/troubleshooting-bluetooth-interface.html
%% Creat... |
function varargout = C_ImagebProcessing(varargin)
% C_IMAGEBPROCESSING MATLAB code for C_ImagebProcessing.fig
% C_IMAGEBPROCESSING, by itself, creates a new C_IMAGEBPROCESSING or raises the existing
% singleton*.
%
% H = C_IMAGEBPROCESSING returns the handle to a new C_IMAGEBPROCESSING or the handle to
%... |
function [newphi acc] = hyperUpdate(obj,lik_old,samps,sig,phi,drscale)
newphi = phi;
propstep = 0;
acc = 0;
priorfunc = str2func(obj{1}.VariableSettings.HyperSettings{1});
priorvals = num2cell(obj{1}.VariableSettings.HyperSettings{2});
trialphi = priorfunc(priorvals{:});
if length(... |
function [pts] = findFeaturePoints(s1, varargin)
defaultOpt.evecs = [];
defaultOpt.evals = [];
opt = parseOpt(defaultOpt, varargin{:});
if isempty(opt.evecs) || isempty(opt.evals)
[opt.evecs opt.evals] = calcLaplacianBasis(s1, 100);
end
wks1 = calcWKS(opt.evecs, opt.evals, 100);
nv = length(s1.X(:));
% 1-ring nei... |
function mat = agg(d)
% Hierarchical AGG aggregates the parts of a distributed matrix on
% the leader processor using an extended binary tree.
% HAGG(D) is a generalization of BAGG(D) when Np is NOT a power of two
% This functions increments GLOBAL message TAG.
%
% HAGG(D) is renamed to be AGG(D)
% ... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%% Count the number of keys to each portal %%%%%%%%%%%%%%%%%%
%
% Counting how many duplicated keys to each specific portal you have, no
% matter where you put it (INVENTORY or CAPSULE or KEYLOCKER).
%
% Main procedure:
% -... |
function model = ibpmultigpMomentsCompute2(model)
% IBPMULTIGPMOMENTSCOMPUTE
% IBPMULTIGP
if strcmp(model.sparsePriorType,'ibp')
if ~model.asFinale
% Compute moments for multinomials qki
templateqki = zeros(model.nlf);
for q=1:model.nlf
temp = psi(model.tau2(1:q)) - cumsum(psi... |
function symbolic7
syms t w
x = heaviside(t+2) - heaviside(t-2);
X = fourier(x,t,w);
ezplot(X,[-2*pi,2*pi]), axis tight, grid on
|
function plotFFT(x)
if mod(length(x),2) == 1 % x should have an even number of samples
x = [x 0]; % if not, pad with a zero
end
N = length(x);
X = fft(x);
mag(1) = abs(X(1))/N; % DC component
mag(N/2+1) = abs(X(N/2+1))/N; % Nyquist frequency component
mag(2:... |
clear all; clc ;
% ccs directory
ccs_dir = getenv('ScriptDir');
% analysis directory
ana_dir = getenv('ADir');
% subjects list
subs_list = getenv('SubjList');
% func dir name
func_dir_name = getenv('FuncDir');
% func rest name
rest_name = getenv('FuncName');
% group mask prefix
gmask_prefix = 'group_surface';
% freesur... |
function Px = px(x)
Px = (3 - 2 * (x + 1) + (x + 1) * (x) * (x - 1));
|
function readarray=smap_read_array(id,offset,duration)
%id is uuid
%function returns most current reading
%offset is how much time before now to start data read (in hours)
%duration is duration of data read (in hours)
%S4-16 room temp a71dc6d1-420d-56f9-9b02-f63a5d165fcc
%Cory weather station ec2b82c2-aa68-50ad-8... |
function [t_theo t_shell ft f1 f2 fa fr X N_bolts t_head A_actual pitch Bolt_circle_dia] = PED2(OpPressure,fmax,Di,J,Length,CA,head,Sf,rho,rhoflange,apex,h,m,Ya,N,fpermissible)
Wp = (1.1)*OpPressure; %Design pressure is 1.1 times operating pressure%
t = (Wp*Di)/((2*fmax*J)-Wp);
t_theo = t;
if(t<=4) %Minimum thickness o... |
% Fig. 5.26 Feedback Control of Dynamic Systems, 5e
% Franklin, Powell, Emami
%script for Figure 5.26
n=[1 5.4];
d1=conv([1 1 0],[1 7 49]);
d=conv(d1,[1 20]);
pzmap(n,d)
axis([-20 0 -7.5 7.5])
hold on
r=roots([1 7 49]);
plot(r,'*')
title('Fig.5.26 Construction for placing a specific point')
z=... |
function [w,projc1,projc2] = lda(trainc1, trainc2)
% This code implements 2 class LDA
% Ref - Pattern Recognition Christopher M. Bishop
% Input
% trainc1 -class 1 train data in D X N Format
% trainc2 -class 2 train data in D X N Format
% N - NUmber of training samples
% D - Feature Vector Dimen... |
%-----------------------------------------------------------------------
% Job configuration created by cfg_util (rev $Rev: 3599 $)
%-----------------------------------------------------------------------
clear all; close all; clcexit
cd /Volumes/GT/PedMRI07202016/PreProcData2
n_img = 281; % number of images to be rea... |
function Tmatrix = Matrix(gamut, whitePoint)
% The program to compute
% input 2*4
% [xr,xg,xb,wx;yr,yg,yb,wy]
% Here wx and wy is the cooridnates x,y of the reference white point
% [X;Y;Z] = Tmatrix*[R,G,B]
% Here Y=1 of reference white
% Here R,G,B are tristimulus values of three primaries
% R,G,B in the specified g... |
% ONE-DIMENSIONAL MLS APPROXIMATION
clear all
% PROBLEM DIFINITION
l = 10.0;
dx =0.5;
% SET UP NODAL COORDINATES
xi = [0.0 : dx : l];
nnodes = length(xi);
% SET UP COORDINATES OF EVALUATION POINTS
x = [0.0 : 0.05 : l];
npoints = length(x);
% DETERMINE RADIUS OF SUPPORT OF EVERY NODE
scale = 3;
... |
function [Ireg,O_trans,Spacing,M,B,F] = image_registration(Imoving,Istatic,Options)
% This function image_registration is the most easy way to register two
% 2D or 3D images both affine and nonrigidly.
%
% Features:
% - It can be used with images from different type of scans or modalities.
% - It uses both a rigi... |
function [W] = make_each_F35musc(bo, sigma2_a, sigma2_s, biased_sigma2_s, biased_input, lambda, dt, varargin)
% June 2012: var_s scaled by magnitude of each click
% July 2013, include biased_sigma2_s
% The current code will have less noise for more depressed clicks or more "silenced" clicks.
pairs = { ...
'net_in... |
classdef road
%ROAD class definiton for open drive road in matlab
% contains the opendrive fromat with additional information
%
%----------------------------------------------------------------------
% BSD 3-Clause License
%
% Copyright (c) 2020, Jonas Wurst, Alberto Flores Fernánd... |
clear;
addpath(genpath('../..'));
set(0,'defaulttextInterpreter','latex');
fig = figure('Name','Interpolazione f(x)', 'Color','white', 'NumberTitle','off');
fig.ToolBar = 'none';
f = @(x) x.*exp(-(x-1).^2);
zval = linspace(0, 5, 100);
xdata = chebyspace(0, 5, 10);
ydata = f(xdata);
spval = cubicspline(xdata, ydata, z... |
function [R]=codd(H)
%these function clear one by one array of a vector between stat and end
%these function give array with odd indices
q=1;
for g=1:length(H)
if even(g)==0
R(1,q)=H(1,g);
q=q+1;
end
end
|
function status = Output2dArr(filename, Arr, formatSpec)
% 2018-06-13
% ファイル出力
% filename ：出力ファイル名
% Arr ：配列
% formatSpec ：フォーマット
% https://jp.mathworks.com/help/matlab/ref/fprintf.html#btf98dm
status = -1; % 異常終了
fileID = fopen(filename,'w');
if fileID == -1
return
end
fprintf(fileID, formatSpe... |
function varargout = uifitpeaks(ax,varargin)
%UIFITPEAKS Graphical/interactive version of fitpeaks
% Takes all data in axes. User clicks to apply new guesses for peaks and
% can modify existing guesses
% Inputs (optional):
% [Init]: Struct with initial peak guesses. Same format as FITPEAKS
% retur... |
function [f] = p10bar(y)
% global panelty ;
% x;
% clc
% Counter of number of run
% load data.mat;
% kkk = kkk+1;
% save data.mat *kkk;
format shortg
% TLBO result
% y=[];
y=round(y);
Sec=[1.62 1.80 1.99 2.13 2.38 2.62 2.88 2.93 3.09 3.13 3.38 3.47 3.55 3.63...
3.84 3.87 3.88 4.18 4.22 4.49 4.5... |
function [sigma0vvdB, sigma0hhdB, sigma0vvdBr, sigma0hhdBr] = Karam_Fung_GRG1988(thetaid)
% Frequency (GHz)
% % High frequency
f = 9.6;
er = 28.04 - 13.34j;
% % Low frequency case
% f = 1.5; % Frequency(GHz);
% er = 28.52 - 2.13j;
%% Vegetation volume backscattering for non-spherical particles
% % Radar incidence ang... |
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