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function printRobotCmdMsg(address, message, connectionName)
% Useful for receiving getKp, getKi, getStraight messages.
% These are only for diagnostics, hence no way to turn this off.
global COTSBOTS;
RC = COTSBOTS.RC;
switch(message.get_type)
case(RC.GET_STRAIGHT)
temp = message.get_data; disp(spr... |
function embedding=gb_lmnn(X,Y,K,L,varargin)
% Nonlinear metric learning using gradient boosting regression trees.
% 'X' (dxn) is the input training data, 'labels' (1xn) the corresponing labels
% 'L' (kxd) is an initial linear transformation which can be learned using LMNN
% L corresponds to a metric M=L'*L
% 'mod... |
function count = rollFive() %Simulates yatze with no max number or
%rerolls, and returns the number or
%rolls it took to attain 5 identical
%results
count = 1; %a minimum of one... |
function [mdataell,mdatasph,mdatamad] = hdrobscaleSM(mdata,robpar)
% HDROBSCALE, High Dimensional data ROBust reSCAling
% Does various types of robust normalizations of the data
% for use in robust PCA, etc.
% Can use first 1 or 2 arguments.
% Steve Marron's matlab function
% Inputs:
% mdata ... |
function image = customReaderImage(location)
[img, ~, msk] = imread(location, 'png');
image = struct('original', img, 'mask', msk, 'location', location);
end |
function Hd = LeastSquaresOrder8(stop1,pass1,pass2,stop2)
%LEASTSQUARESORDER8 Returns a discrete-time filter object.
% MATLAB Code
% Generated by MATLAB(R) 9.4 and Signal Processing Toolbox 8.0.
% Generated on: 25-Jul-2019 19:07:11
% FIR least-squares Bandpass filter designed using the FIRLS function.
% All frequenc... |
function [] = imageMask(Filename, Xmax, Xmin, Ymax, Ymin)
% Apply a mask to the RGB image.
iterations = size(Xmax);
lastImage = '';
mkdir(strcat(pwd,'\Dataset\train\images\masked\'));
for i = 1:iterations
originalImage = imread(strcat(pwd,'\Dataset\train\images\', char(Filename(i))));
outputImage = applyMask(or... |
load Cougar_GT1.mat; load Cougar_GT2.mat;
load Cougar_GT3.mat; load Cougar_GT4.mat;
load Cougar_GT5.mat;
% Converting to logical
Cougar_GT1 = logical(Cougar_GT1);
Cougar_GT2 = logical(Cougar_GT2);
Cougar_GT3 = logical(Cougar_GT3);
Cougar_GT4 = logical(Cougar_GT4);
Cougar_GT5 = logical(Cougar_GT5);
% Converting to struc... |
%********** Function decription ***********
% This is a leave-one-out cross-validation (LOO-CV) experiments, which is used to calculate the accuracy and precision of the calibration results of Landmark algorithm.
% It also calculates the Min_AE, Mean_AE, Max_AE, SD, RMSE of the calibration results.
% Input: eul_P_R... |
%% Rotation model images stitcher
% A basic example on image stitching.
%
% <http://docs.opencv.org/3.2.0/d8/d19/tutorial_stitcher.html>
% <https://github.com/opencv/opencv/blob/3.2.0/samples/cpp/stitching.cpp>
%
%% Input images (two or more)
im1 = imread(fullfile(mexopencv.root(),'test','b1.jpg'));
im2 = imread(fullf... |
A = [1 0 0; 2 1 0; 3 6 4];
b = [1; 20; 2+1i*3];
% A = sprand(100,100,1);
% b = rand(100,1);
x = b*0;
M = eye(size(A));
restrt = 3;
max_it = length(b);
tol = 1e-6;
format long
%[x, error, iter, flag] = gmres2( A, x, b, M, restrt, max_it, tol );
[x1,flag1,relres1,iter1,resvec1] = gmres(A,b,restrt,tol,max_it);
... |
%% Parameters
param.L_0 = 0.1; % Range: 0.23m - 1.605m
param.init_x1 = 0;
param.phi_0 = 0;
param.T_K = 0.03032;
param.T_G = 0.0247;
param.K_K = 1;
param.K_G = 1;
param.r_K = 0.046; %m
param.r_G = 0.021975; %m
param.ue_dreh = 75;
param.ue_K = 6;
param.ue_G = 3;
param.d = 0.02; % Daempfung
param.box_sequence = [1,4,5,... |
%% upsample and top hat all the expanded images
% close all; clear; clc;
%% prepare
pixelSize=[0.4 0.4 1];
PSF = [.4 .4 2.5];
pixelSize2=pixelSize./2;
A=eye(4)*2;
A(4,4)=1;
R=makeresampler('cubic','bound');
tform=maketform('affine',A);
structure = distStrel3D(0.5, pixelSize2);
%% all directories under database
[a, nam... |
function statsBoxplotsDraw(~,~,fig,man)
%statsBoxplotsDraw - draw boxplots based on the selection
% Get the guidata
sts = guidata(fig.fig);
% Get the value of the clicked items...
str = man.list.String;
val = man.list.Value;
mzrt = str{val};
% And the groupings
str = man.groups.String;
val = man.groups.Value;
[grp] ... |
%% ZeroCrossing - To ensure segments following Staba method do not cross the zero line more than 10 times
% Megan Entzinger
% 17-Jan-2019
load Mario03_Filter_8min.mat; %load filtered data
datadata = data;
load mario03Staba.mat; %load data containing segments following Staba method
filtereddata = testTable;
i... |
function [X,Y,Z,lightSource,lightIntensity] = defaultAssign(n)
switch n
case 0
X = [];
Y = [];
Z = [];
lightSource = [];
lightIntensity = [];
case 1
X = -100;
Y = [];
Z = [];
lightSource = [];
lightIntensity = [];
ca... |
function openMVG_global(folder,numberOfClusters)
%% Replace matches.e.txt
matchesPath = [folder filesep 'SfM' filesep 'matches'];
matchesFile = [matchesPath filesep 'matches.e.txt'];
matchesFullFile = [matchesPath filesep 'matches_full.e.txt'];
if ~exist(matchesFullFile,'file')
movefile(matchesFile,matchesFullFile);... |
fs = sqrt(10.^(powers/10)/1e3*50)/0.004;
yyaxis right
plot(powers,real(y5v_power_epsilon(75,:)),powers,real(pb_power_epsilon(75,:)),'--',powers,real(yig_power_epsilon(75,:)),'*-')
yyaxis left
plot(sqrt(powers/50),imag(y5v_power_epsilon(75,:)),powers,imag(pb_power_epsilon(75,:)),'--',powers,imag(yig_power_epsilon(75,:))... |
clear all; close all; clc;
load HW1_Testdata.mat
%%% Name: ROSEMICHELLE MARZAN
%%% Course: AMATH 482
%%% Homework 1, Due 1/24/2019
% VARIABLE NAMES FOR SIGNAL
% Undata = raw (noisy) data
% Unt = noisy data in the frequency domain
% Unft = filtered data in frequency domain
% Unf = filtered data in time domain
% setti... |
%% Finding monetary policy instruments
% Interbank Market Equilibrium
MPCC_bankblock_ii;
MPCC_interbank_vecs;
Dr = r_b_vec-r_d_vec;
mu_index=(mu_vec>surplus_cut & mu_vec<deficit_cut);
[~,index_aux] =find(mu_index==1,1,'first');
if index_aux<length(mu_index);
mu_index(index_aux+1)=1;
end
mu_ss_target = interp... |
function [f_model] = mTRFtransform(b_model,resp,recon)
%mTRFtransform mTRF Toolbox transformation function.
% F_MODEL = MTRFTRANSFORM(RECON,RESP,B_MODEL) tansforms the coefficients
% of the backward model B_MODEL to the coefficents of the corresponding
% forward model F_MODEL as described in Haufe et al., (2... |
function hdr = get_hdr( bufferD, hdr )
% hdr = get_hdr( bufferD )
if bufferD.running
try
hdr = buffer('get_hdr', [], bufferD.host, bufferD.port );
catch
%hdr = [];
bufferD.running = false;
warning( 'hdr = buffer(''get_hdr'' : FAILED!' )
end
end |
% [comp_closeprices,comp_closeprices1,residual]= PCA(closeprices,0.9);
function [princomp_closeprices,princomp_closeprices1,residual]= PCA(closeprices,threshold)
% 将closeprices标准化
mean_closeprices = mean(closeprices,1);
std_closeprices = std(closeprices,0,1);
standard_closeprices = (closeprices-repmat(mean_closeprice... |
clear all; clc;close all;
data_set = 'D:\50_set\';
addpath(data_set);
data_1 = (dir(fullfile(data_set,'*.asc')));
data_1 = {data_1(~[data_1.isdir]).name};
for j = 1:length(dir(fullfile(data_set,'*.asc')))
a = char(data_1(j));
X = load(data_1{j});
save
X=X';
filename=[a([1:9]),'.pcd'];
savepcd(filename,X);
x... |
%***********************************************
% COMPUTATIONAL ECONOMICS WS15/16
% Prof. Alexander Ludwig
%
% PROBLEM SET II
% Despoina Balouktsi - 5917774
% Maddalena Davoli - 5701809
% Jorge Quintana - 5702248
%
%**********************************************... |
function m_VarAuxElem = f_OperPosConv_MixStrInj_quad_q1(m_VarAuxElem,m_VarAuxGP,e_DatMatSet,m_CT,e_VG)
%parfor iElem = 1:nElem
% for iElem = 1:nElem
%
% condBif = m_VarAuxElem(1);
% if ~condBif
% %Para el análisis de bifurcación se toma el tensor de punto de gauss 5 para el imp... |
In Matlab kun je met de quote operator (') een vector
veranderen van rijvector naar kolomvector. |
function [ ] = removeCol(obj, idx)
% 删去一行，改变obj.yProps和obj.data和obj.Ny
% [ ] = removeCol(obj, idx)
% idx: 待删除列列号
% ----------------
% 程刚，20150519，初版本
% TODO: 能否改成接受参数idx 或 nameStr
%% 预处理
% 判断idx范围正常
if idx < 0 || idx > length(obj.xProps)
error('idx=%d，超出范围！',idx);
end
%% main
obj.xProps(idx) = [];
obj.... |
%% Function, calculate Jacobian
% For the two linkages
function j_out = cal_J_wr(th1, th2, th3, th4, l1, l2)
% thetat degree 2 rad
th1 = deg2rad(th1);
th2 = deg2rad(th2);
th3 = deg2rad(th3);
th4 = deg2rad(th4);
% first col
j_c1_1 = 0;
j_c1_2 = - l2*(cos(th4)*(cos(th3)*sin(th1) + cos... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% function yc = classifyNaiveBayes(trnData, tstData)
%
% Machine Learning Project
% Naive Bayes vs Perceptron
% Muhammad Usman Akram
% muhammadusman.akram[at]studenti.unitn.it
% 08/02/2014
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
clc;
%% Declaração de variáveis
A = input('Digite a matriz A: ');
b = input('Digite o vetor b: ');
nmax = input('Digite o número máximo de iterações: ');
tol = input('Digite a tolerância do método: ');
C = A;
g = b;
it = 0;
m = size(A, 1);
n = size(b, 1);
%% Construção de matrizes
for i=1:m
for j=1... |
function smooth_vec = Gaussian_Smooth_TA2(original_vec, my_N)
if my_N~=0
g = gausswin(1000,my_N);
g = g ./ sum(g);
%% Since this code might be used for EEG, we must rectify first !!
original_vec = abs(original_vec);
% taped_vector=[original_vec(floor(5/my_N):-1:1) original_vec orig... |
%cd('0704');
clear all
code_folder = pwd;
exp_folder = 'D:\GoogleDrive\retina\Chou''s data\211217';
% exp_folder = 'D:\GoogleDrive\retina\Troy''s data\20211126';
cd(exp_folder)
all_file = dir('*.mcd') ; % change the type of the files which you want to select, subdir or dir.
n_file = length(all_file) ;
for m = 1
fi... |
A = [1 2; 3 4; 5 6];
B = [11 12; 13 14; 15 16];
C = [1 1; 2 2];
A * C
A .* B %element wise op multi one by one
V = [1; 2; 3]
1 ./ V
log(V)
exp(V)
abs(V)
-V % same as -1 * V
V + ones(length(V), 1) % add 1 to each element
%or directly
V + 1
A' %transpose (turn left)
max_val = max(V)
[max_val, max_index] = max(V)
%... |
%Example 3.23
%
clf reset;
setfsize(300,300)
echo on
clc
% INITC - 对竞争层初始化
% TRAINC - 训练竞争层
% SIMUC - 仿真竞争层
pause
clc
P = 0.1 ./ [(1/11):0.001:1] - 0.1;
pause
clc
plot(P,P*0,'+r')
pause
clc
net=newc(minmax(P),6,0.02,0.001);
pause
hold on
plot(net.iw{1,1},net.iw{1,1}*0,'ob')
hold off
pause
clc
net.trai... |
function [s,Sol_2,sol] = bvp_tube_2(mesh,alpha0,initSol, C0, R0, Z0, F0, ZF, bpoint)
global k0 lam dc c0 a0 g delta p pw wd P iSol gt r0 z0 f0 aF aa tt
P=0;
r0=R0;
z0=Z0;
aa = bpoint;
x=mesh*aa;
s = x;
c0 = r0*C0; % dimensionless preferred curvature
g = 20;
gt = x;
delta = 1;
k0 = 320;
p = P*R0... |
% % se cargan los datos
A1 = load('289x289/A289.dat');
b1 = load('289x289/b289.dat');
p = load('289x289/nodos.dat'); %289x2
e = load('289x289/fronteras.dat');%64x7
t = load('289x289/elementos.dat');%512 x 4
% se trasponen los nodos, frontera y elementos
p0 = p'; %2x289
e0 = e';%7x64
t0 = t';%4 x 512
u = linsolve(A1,b1... |
%% %%######################################################################
%% %%################## Define Parameters Here ###################
%% %%######################################################################
%%_____________________________Fixed Parameters___________________________
g = 9.81;
... |
function options = checkFields(options,params,value,fieldname)
% checkFields - checks whether fieldname exists in options, if not checks if it exists in params and sets this value; elseif value is used
%
% Syntax:
% options = checkFields(options,params,value,fieldname)
%
% Inputs:
% options - [struct] options str... |
% Copyright 2014
%
% Licensed under the Apache License, Version 2.0 (the "License");
% you may not use this file except in compliance with the License.
% You may obtain a copy of the License at
%
% http://www.apache.org/licenses/LICENSE-2.0
%
% Unless required by applicable law or agreed to in writin... |
% circle continuation example
close all
clear all
clc
global gp globalsolution
gp=5; newton('fun1',-3300)
globalsolution=[ans;gp];
gp=7.5; newton('fun1',-3300)
globalsolution=[globalsolution,[ans;gp]];
run_continuation('fun1',12000)
B = globalsolution';
plot(globalsolution(1,:),globalsolution(2,:)); axis('image')
... |
% bruteforce search best patch residents time for two patch types
close all;
clear all;
more off;
PATCH = [50 100];
PN = 2;
TAU = [10 50 100 500 1000 5000 10000 50000 100000 500000];
TN = 10;
prt = zeros(PN, TN);
maxRate = zeros(PN, TN);
collected = zeros(PN, TN);
patchA = load(sprintf('avgGainFct_%d.dat', PATCH(... |
function plotRF(obj,k,varargin)
params.background = 'stim';
params = getParams(params,varargin);
import vis2p.*
% get stims files
[kk.x, kk.y, kk.exp_date] = fetch1(vis2p.Scans(k),'x','y','exp_date');
stims = fetchn(VisStims('exp_type = "MouseDotMapping"') & vis2p.Scans(kk,'problem_type = "none!"'),'stim_file');
s... |
function [tref,tins]=an_href(g,t)
%Genera il vettore dei nodi (partizione estesa) raffinamento del vettore
%dei nodi t
% function [tref,tins]=an_href(g,t)
% g --> grado della spline
% t --> vettore dei nodi partizione estesa
% tref <-- vettore dei nodi raffinato partizione estesa
% tins <-- vettore di nodi inse... |
function a=fun2mat_sym(fun,n)
% return matrix a such that a*u(:) = (fun(u))(:) for 3d u size n
u = zeros(n);
outn = size(fun(u));% size of output
a = sparse([],[],[],prod(outn),prod(n),5*prod(n));
k=0;
for i3=1:n(3)
for i2=1:n(2)
for i1=1:n(1)
u(i1,i2,i3)=1;
k=k+1;
out = ... |
function [w1, w2, ell_angle] = Covariance2EllipseParameters(CovarianceMatrix, Pr)
K_square = -2*log( 1 - Pr ); % log = ln -> (logaritmo naturale)
[ eig_vectors, eig_values ] = eig( CovarianceMatrix );
% Get the largest eigenvalue
max_evl = max(max(eig_values));
% Get the index of the largest eigenvector
... |
% Homework1a
% Engineering 240
% Cody Antonio Gagnon 7/2/15
% Vector and matrix definitions %% Store C, D, y, z
C = [2 9 -3; 0 pi 5]
save A1.dat C -ascii
D = [0 7; 8 3; -3 0];
save A2.dat D -ascii
y = [2; 1]
save A3.dat y -ascii
z = [1; exp(1); -1]
save A4.dat z -ascii
% Loading files and Accessing Elements
T = dlmre... |
function [ distance ] = WassersteinLoss( mu1, Sigma1, mu2, Sigma2 )
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Wasserstein Inverse covariance Shrinkage Estimator
% Viet Anh NGUYEN, Daniel KUHN, Peyman MOHAJERIN ESFAHANI
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
[V... |
function [k,flag] = checkpass(word,password)
k = 0;
for jj = 1:length(password)
if (word(jj) == password(jj))
k=k+1;
disp ('match');
else
disp ('no match');
break;
end
end
if (k == length(password))
flag = 1;
e... |
close all
D = importdata('Wing_Polar_Graph_0CD.csv');
% plot WEISSINGER vs XFLR5 --> Cd vs Cl
figure(10)
plot(D.data(:,1),D.data(:,2),'k','LineWidth',5);
hold on
plot(Cd_vec,Cl_vec,'or','LineWidth',5);
grid on
grid minor
xlabel('$C_{D}$','Interpreter','latex');
ylabel('$C_{L}$','Interpreter','latex');
legend('XFLR5',... |
function [arch_str,archs] = SMAP_retrieve_archs()
r = global_jess_engine;
MAX_ARCHS = 100000;
MAX_INSTRS = 5;
archs = zeros(MAX_ARCHS,MAX_INSTRS);
arch_str = cell(MAX_ARCHS,1);
% results.instrument_orbits = cell(MAX_ARCHS,1);
fact_archs = r.listFacts();
ii = 1;
while(fact_ar... |
T = 1000
numInputs = 100
probInputSpike = 1e-2;
%X = double(rand(numInputs, T) <= probInputSpike);
X = double(rand(numInputs, T));
w = randn(numInputs, 1);
th = 1;
u = X'*w;
z = double(y-th);
y = double(u >= th)
figure(1); clf;
subplot(4,1,1); imagesc(X); colormap(1 - gray(255));
title('Raw')
%ylabel('No')
subplot(4,... |
close all;
clear all;
%JMA: uiPtbCorgiData loads project data
ptbCorgiData = uiGetPtbCorgiData();
%Set some figure options:
figurePosition = [0 0 1000 500];
%JMA: Next let's loop through each participant and each condition.
%
for iParticipant = 1 : ptbCorgiData.nParticipants,
%JMA: get the data for this par... |
%%
addpath ./eeglabfuncs/
% Load wavelet or hanning TFR:
%load ../new/TFRhann_avg_bc2.mat
%load ../TFRs/TFRhann_avg_bc3.mat
%load ../TFRs/TFRmult1_avg_bc2.mat
load TFRwave_bc_st_cl.mat
%load TFRmult_bc_st_cl.mat
%% Prepare data structure for statcond
nSubj=size(TFRwave_CTR_bc, 2);
% Data structure: (1,2) cell array... |
function []= plot_result_matrix(input_matrix, input_labels)
[rows, columns]= size(input_matrix);
figure; imagesc(input_matrix); title('Confusion Matrix'); xlabel('Predicted Class'); ylabel('True Class');
set(gca, 'XTick', 1:rows, 'XTickLabel', input_labels, 'YTick', 1:columns, 'YTickLabel', input_labels);
for ii=... |
function error = checkTrackingBoris(data, ids)
teMap = [0, 0]; % maps true objects to estimated ones
nAllObjs = 0;
nMissed = 0;
for iFrame=1:data.nFrames
frame = data.Frames(iFrame);
id = ids{iFrame};
nObjs = frame.nObjects;
trueId = getIdsFromDataFrame(frame);
for i = 1:nObjs
ti... |
function [centroids,idx,J] = best_result(X,K);
centroids_cell = cell(50,3);
%%
%%
for i = 1:30,
initial_centroids = Kmeans_intialization(X,K);
[centroids idx] = MYkmeans(X,initial_centroids,15);
J = costFunction(X,centroids,idx);
centroids_cell{i,1} = centroids;
centroids_cell{i,2} = J;
... |
% Es 8
% Given x(n) = [3, 11, 7, 0, -1, 4, 2] , n in [-3, 3]
% Given h(n) = [2, 3, 0, -5, 2, 1], n in [-1, 4]
% Compute y(n) as x(n) convolved with h(n), n in [-7, 7].
close all
clearvars
clc
%% signals
% let us define the signals in the same n-domain. --> put zeros where
% signals are not defined.
n_x = -3:3;
n... |
%MRI_CLASSIFY Perform statistical image classification (requires updates)
% While this script is mostly complete, you are responsible for modifying the
% contents of this function to make it fully operational. Be sure to create an
% "output/classification" directory within your personal directory and modify
% ... |
clc; clear all; close all;
x=input('enter the first sequence');
h=input('enter the second sequence');
y=conv(x,h);
figure; subplot(3,1,1);
stem(x); ylabel('amplitude-->');
xlabel('(a)n-->');
title('first sequence');
subplot(3,1,2);
stem(h);ylabel ('amplitude-->');
xlabel ('(b) n-->0');
title('second sequence');
subplo... |
pkg load symbolic;
clear -g; % clear all global variables
if(~exist('netlist', 'var'))
[baseName, folder] = uigetfile({"*.net","LTSpice Netlist"});
netlist = fullfile(folder, baseName);
end
%%%%%%%%%%%%%%%%%% Helper Functions %%%%%%%%%%%%%%%%%%%%%%%%%
global nets numNets;
global numAddIds;
glob... |
function [ ] = convert_to_tif()
Maindatapath = uigetdir('D:/','Select DATA directory for files');
Maindatapath = ([Maindatapath '/']);
cd (Maindatapath);
prompt = {'\bf \fontsize{12} Please enter the format of your videos (eg .avi):',...
};
dlgtitle = 'Video format';
dims = [1 88];
... |
function mustBeAfter(date, year)
tz = date.TimeZone;
assert(date >= datetime(year, 1, 1, "TimeZone", tz), ...
"Must be after %4i.", year);
end
|
function [C] = FactorialMN(N)
A = [1];
B = [1];
C = [1];
while isSmallerOrEqualMN(A,N)==1
%disp(C);
%disp(A);
%disp(' ');
C = MulMN(A,C);
A = AddMN(A,B);
end
end |
function datasum = sumB1pos(data,param,position)
% function datasum = sumB1pos(data,param,position)
%
% Sample position 'position' overrides sample name, so be careful.
%
% Created 28.11.2007
energies = [];
sd = size(data);
for(p = 1:sd(2)) % Search for all different energies
if(isempty(find(energies==param(p).Ene... |
function Flag = isround(X)
% isround True if variable is round number.
%
% Syntax
% =======
%
% Flag = isround(X)
%
% Input arguments
% ================
%
% * `X` [ numeric ] - Variable that will be tested.
%
% Output arguments
%
% * `Flag` [ `true` | `false` ] - True if the input variable `X` is a... |
function [x] = chinese_remainder(n,b)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
leng = length(n);
product = prod(n);
x = 0;
for i = 1:leng
p = product/n(i);
[g,y,z] = gcd(p,n(i));
x= x + b(i) * p * y;
end
x = mod(x,product)
end
|
function [dObj,dObjGrad]=objFun_d(x,p)
% q = x(1:p.numJ,:);
% dq= x(p.numJ+1:2*p.numJ,:);
u = x(p.numJ+1:2*p.numJ,:);
s_var = x(p.numJ*2+5:p.numJ*2+6,:);
dObj = 0.5*sum(p.jointW.*sum(u.^2,2).');
dObj = dObj-0.5*sum(s_var.^2,'all')*10;
dObjGrad = [zeros(p.numJ,size(x,2));diag(p.jointW)*u;zeros(4,size(x,2));10*s_v... |
function [CORRELATION_VALUES, GAMMA, BETA, ALPHA] = ...
read_soft_results_file(RESULTS_FILE_PATH, BAND_WIDTH, IS_REAL)
% This function reads a correlation volume produced by the c function
% test_soft_fftw_correlate2.
%
% INPUTS
% RESULTS_FILE_PATH = Path to the output file produced by
% test_soft_fftw_corr... |
clc;clear; close all;
% img_name = 'test00.png';
% img_name = 'test01.png';
% img_name = 'test02.png';
% img_name = 'test03.png';
% img_name = 'test04.jpg';
img_name = 'amy_portrait.jpg';
% img_name = 'test05.jpg';
myimg = imread(img_name);
mysize = size(myimg);
if (length(mysize) == 3)
myimg = myimg(:,:,1);
end
% ... |
function [ storeOutputs ] = getRespons(data,weights,theta,T,daysBack,nH)
storeOutputs = zeros(T,1);
for i = 1:T-daysBack
input = data(i:i+daysBack-1,:);
output = RunNetwork(input(:),weights,theta,nH);
storeOutputs(i+daysBack-1) = output{end};
end
storeOutputs(storeOutputs<-0.5)=-1;
storeOutputs(storeOutputs>0.... |
function mat = rotateZ(row, col, ang)
% ROTATEZ Generates rotation matrix
% like rotz in phase array system toolbox
%
% 15Aug2017 - SSP - created
fh = figure();
ax = axes('Parent', fh);
ln = line(row, col, 'Parent', ax);
if isnumeric(ang)
rotate(ln, [0 0 1], ang);
end
mat = [ln.XData... |
function [cepstra,aspectrum,pspectrum] = melfcc(samples, sr, varargin)
%[cepstra,aspectrum,pspectrum] = melfcc(samples, sr[, opts ...])
% Calculate Mel-frequency cepstral coefficients by:
% - take the absolute value of the STFT
% - warp to a Mel frequency scale
% - take the DCT of the log-Mel-spectrum
% - retu... |
%% Parameters for Techinal indicators
inc_macd = 1; % Moving Average Convergence/Divergence (MACD)
inc_stochosc = 1; % Stochastic oscillator
inc_tsmovavg = 1; % simplean and exponential moving average
inc_tsmom = 0; % Momentum between times
inc_rsindex = 1; % Relative Strength Inde... |
clc;
clear all;
% close all;
warning('off', 'all');
Clk_M = 1;
Clk_M_Value = 5e-9;
mu = 5;
sigma = 2;
leftDiscard = 0;
rightDiscard = 2;
numIter = 100;
numAddresses = 100;
numBits = 32;
bitReadTime = 1* Clk_M;
switchDetectTime = 0.2 * Clk_M;
global rwArray;
% Offset Multiplier Tests
writeBufferSize = 5; % 1:10;
ma... |
function FeatureStore=SyncFeatureParams(Module, FeatureStore, FeaturePrefixStr, ModulePara)
TempIndex=strmatch(FeaturePrefixStr, Module);
if ~isempty(TempIndex)
FeatureName={FeatureStore.Name}';
TempIndex=strmatch(FeaturePrefixStr, FeatureName);
if ~isempty(TempIndex)
for i=1:length(Temp... |
%clear all
%load('dt_0.001000 damp_30.000000 N_800 k=80.000000 br=14.000000 cr=92.000000 var=1.mat');
load('Two_BDAC_offset_dist_330_184core_GNC_sep_1nm_copy.mat');
[Xs,Ys,Zs]=sphere(20);
%hf=figure;
%ha=axes;
hold on
for i=1:1600
xs1=(Xs*16e-9)+xt(i,1)*1e-9;
ys1=(Ys*16e-9)+xt(i,2)*1e-9;
zs1=(Zs*16e-9)+xt(i,3)*1e-9;
... |
function [ b ] = beta( g,g_old )
%Actualización de Fletcher-Reeves
b=(g'*g)./(g_old'*g_old);
b=diag(b,length(b)-1);
end
|
classdef TPA_PositionManager
% TPA_PositionManager - Detects position info and update this info according to view.
% Resonsible for time zone and data rescaling
% Inputs:
% different
% Outputs:
% different
%-----------------------------
% Ver Date Who Descr
%------... |
function [ out ] = moving_avg( in, windowSize, overlap)
%MOVING_AVG Summary of this function goes here
% Detailed explanation goes here
l_in = length(in);
halfWindow = windowSize/2;
i = halfWindow;
iMax = l_in - halfWindow;
noOverlap = windowSize - overlap;
%window = (hamming(windowSize))'; % hamming window
wind... |
% Copyright 2014
%
% Licensed under the Apache License, Version 2.0 (the "License");
% you may not use this file except in compliance with the License.
% You may obtain a copy of the License at
%
% http://www.apache.org/licenses/LICENSE-2.0
%
% Unless required by applicable law or agreed to in writin... |
NET.addAssembly('C:\Users\sunsh\source\repos\Spectrometer\Spectrometer\bin\x64\Debug\Spectrometer.dll');
instance = Spectrometer.Detect();
x = 'flower';
raw = instance.Test(1);
spectrum = double(raw);
ds = datastore
% for i=1:8
% raw = instance.Test(i);
% spectrum = double(raw);
% save(x,'spectrum... |
fol_name = 'data/behav_w_css';
all = dir(strcat(fol_name,'/*.mat'));
load('data/metadata.mat');
for k = 1:length(all)
load(strcat(fol_name,'/',all(k).name));
css_input = metadata.stimuli==metadata.cues;
css_response_neutral = ((subject.behav.raw.responses(1,:))'==metadata.cues)*1;
css_response_aversive ... |
function [A,V] = VMT_ProcessTransectsV3_new(z,A,setends)
% Not used by current version
%This routine acts as a driver program to process multiple transects at a
%single cross-section for velocity mapping.
%V2 adds the cpability to set the endpoints of the mean cross section
%V3 adds the Rozovskii computations ... |
function genplot_err_func_lambda_mu_fine_mmx(mu, lambda, id)
addpath ../
addpath ../Datasets/Synthetic' data'/
addpath ../mmx_package/
addpath ../Tools
fprintf('%f - %f - %f', mu, lambda, id);
% clear;
% close all;
% clc;
synthdata_2;
% lambda = [1 8:1e-1:12 20 50];
% mu = 5:5:110;
% lambda = [10];
% mu = 1e3;
N... |
% test for in-circle test
n = 100;
vertex = randn(2,n);
face = compute_delaunay(vertex);
% every edge should pass the test
T = check_incircle_edge(vertex,face);
% should be 0
sum(T~=1) |
function noiseless_EDGE = detect_that_edge(I,stripewidth)
%This is the main edge detection algorithm used
%Input: Image (.JPG)
%Output: EDGE2 variable with detected edges and 2 images plotted to show
%the results visually
%
%Created by: Jaco Verster (versterrie@gmail.com)
%Manual override
%imagename = 'canoncrop.jpg'... |
function [newImg,pixelCount] = BorderObjects(img)
%Invert to make the objects white:
img = imcomplement(img);
%Apply morphology:
%newImg=bwmorph(img,'remove');
SE = strel('square',3);
i = imdilate(img, SE);
%Create border:
newImg = i-img;
%Count border pixels:
pixelCount = ... |
function movieList = loadMovieList()
%GETMOVIELIST reads the fixed movie list in movie.txt and returns a
%cell array of the words
% movieList = GETMOVIELIST() reads the fixed movie list in movie.txt
% and returns a cell array of the words in movieList.
%% Read the fixed movieulary list
fid = fopen('movie_ids.txt... |
function gen_BEMs
%% assemble path
restoredefaultpath;
addpath(genpath(...
'/usr/pubsw/packages/MMPS/MMPS_238/matlab'));
addpath(genpath(...
'/usr/pubsw/packages/MMPS/external/external.2013.11.08/matlab/'));
%%
subjs_dir = '/home/bqrosen/projects/bqrosen/CC/RECON';
subjs = dir([subjs_dir '/CCEP*']); subjs = {subj... |
% Initialize Constants for F16 Simulation
clear
clc
%% Define Constants
% x - State Vector
% VT = x(1); % Freestream Airspeed
% Alpha = x(2)*RTOD; % Angle of Attack normalized to Degrees
% Beta = x(3)*RTOD; % Angle of Sideslip normalized to Degrees
% ... |
function [dX_dEta] = dX_dEta(p,eta,xi)
dX_dEta = 0;
end |
function image = customImageCrop( image )
% parameter definition
format longg;
format compact;
fontSize = 20;
% Crops and image automatically
grayImage = image;
% Get the dimensions of the image.
% numberOfColorBands should be = 1.
[rows columns numberOfColorBands] = size(grayImage);
% Get all rows and columns wher... |
load('iris.mat')
n_train = length(X_data_train(:,1));
n_test = length(X_data_test(:,1));
%Only Consider features X2 and X4
d = 2;
X_test = [X_data_test(:,2),X_data_test(:,4)];
X_train = [X_data_train(:,2),X_data_train(:,4)];
m = 3;
ytrain_binary = [ones(35,1);-1*ones(35,1)];
ytest_binary = [ones(15,1);-1*ones(15,1)];... |
classdef pepitoTools < fourierTools & imageTools & covarianceTools & psfTools & fittingTools
end
|
function vp_param_experiments()
timeHorizon = 12;
% Create Automaton
automaton = MHyProHAutomaton();
dummy_reset = MHyProReset();
dummy_reset.setMatrix(eye(11));
dummy_reset.setVector(zeros(11,1));
% Add basic settings
settings.timeBound = 12;
settings.jumpDepth = 20;
%settings.uniformBloating = false;
settings.cl... |
clear, close all
load('finnstats.merged.corrected.mat');
data = trigrams;
gutenb = data(strcmp(cellstr(squeeze(meta(:,2,1:9))), 'gutenberg'), :);
punk = data(strcmp(cellstr(squeeze(meta(:,2,1:9))), 'punkinfin'), :);
yle = data(strcmp(cellstr(squeeze(meta(:,2,1:3))), 'yle'), :);
sample_size = 100;
... |
% This script breaks down the differences between the Bayesian
% metropolis-hastings acceptance probability in textbooks and papers, and
% the form in takes when it is implemented in algorithms. In books it
% written as p(y|theta')*p(theta')/p(y|theta'')*p(theta''). However in
% algorithms in term is evaluated as it's ... |
%Function which return the perpendicular distance between a point and a
%line
%
%Input:
% [x,y]: point coordinates
% l: struct with the segment defining the first line : l.A and l.B
%
%Return:
% dist: The perperdicular distance between the point [x,y] and the line l
%
%Example of use:
% l=struct('A',[-4,0],'B',... |
function [ret_checks, ret_names] = uq_check_toolboxes()
% UQ_CHECK_TOOLBOXES checks the availability of Matlab toolboxes
fun = @(x)100*(x(2)-x(1)^2)^2 + (1-x(1))^2;
x0 = [-1,2];
A = [1,2];
b = 1;
%% check optimization toolbox
try
x = fmincon(fun,x0,A,b,[],[],[],[],[], ...
optimset('Maxiter',1,'Display',... |
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