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%% film normal
% localisation dossiers et fichiers
fileFolder = "D:\Documents Importants\Professionnel\Stage 2A\daphnies\2021-07-02 cycles\2021-07-02_daphnies1_40-30_u3.4_i0.44_10fps_1\cycle 3";
dirOutput = dir(fullfile(fileFolder,'traitee *.jpg'));
fileNames = {dirOutput.name}';
numFrames = numel(fileNames);
... |
function sgmga_vcn_ordered_test ( dim_num, importance, level_weight, q_min, ...
q_max )
%*****************************************************************************80
%
%% SGMGA_VCN_ORDERED_TEST tests SGMGA_VCN_ORDERED.
%
% Licensing:
%
% This code is distributed under the GNU LGPL license.
%
% Modified:
%
%... |
function [sol,val] = tsp(sol,options)
global pointMatrix;
global WalkSpeed;
global distMatrix
sol;
numvars=size(sol,2)-1;
score =0;
distance =0;
time =0;
penalty = 0;
speed =0;
toggleStart =0;
for n=1:numvars
if sol(n)==1
toggleStart =1;
end
if toggleStart ==0 && n==1
distance = dis... |
function [ psnr_spl_adapt, rate_spl_adapt, avg_coff] = SPL_adapt( filename, current_image, num_levels, block_size, algorithm )
%SPL 此处显示有关此函数的摘要
% 此处显示详细说明
[num_rows, num_cols] = size(current_image);
x = current_image;
% projection_matrix_file = ['projections.' num2str(block_size) '.mat'];
type = 'dpcm';
filename... |
function centroids = Centroids_Intialize(X, K)
%Centroids_Initialize This function initializes K centroids that are to be used in K-Means on the dataset X
% Initialize the centroids to be random examples
%Randomly reorder the indicies of examples
rng shuffle;
randidx = randperm(size(X,1));
% Take the first K examples... |
function al_lineAndBack(taskParam)
%AL_LINEANDBACK This function draws the background for intructions in the cannon task
%
% Input
% taskParam: structure containing task parameters
%
% Output
% ~
if ~isequal(taskParam.gParam.taskType, 'chinese')
if isequal(taskParam.colors.background, 'black')
... |
function [ES,ED] = computeReliabTime( nBins, binEdges, windowLen, windowType, SpikeTimesCell, P)
%%
for b = 1 : nBins
switch windowType
case 'Sliding'
bin1 = binEdges(b);
bin2 = binEdges(b)+windowLen;
case 'Fixed'
bin1 = timeBins(b);
... |
function [mindistance, polypid] = Matching(x,y,z,FeatureVector)
mindistance = 10000;
polypid = 10000;
for i=1:size(FeatureVector,1)
cmp_dist = (FeatureVector(i,2) - x)^2 + (FeatureVector(i,3) - y)^2 + (FeatureVector(i,4) - z)^2;
if(mindistance > cmp_dist)
mindistance = cmp_dist;
... |
clc,clear
%% add all of the funciton in this folder include sub-folders
addpath(genpath(pwd));
% addpath(genpath('c:/matlab/myfiles')); % add the functions in the folder with certain path
%% the initial setting
figure
figure_all_plot=2;
mesh_mode=0; % the normal mesh size unit
plot_switch=0; % plot or not ... |
classdef LieMapping < handle & matlab.mixin.Copyable & matlab.mixin.Heterogeneous
%This is EKF implemented with the very basic equations
properties
%Lie Group Representation
x_lg;
dim = [];
dim_state = [];
end
properties(SetAccess = protected)
generators ... |
% Universidade do Estado do Rio de Janeiro -UERJ
% Calculo Numerico
% Aula 2 - Noções de Programação para Computação Científica
% Prof. Americo Cunha
% Prof. Augusto Barbosa
% Prof. Luiz Mariano Carvalho
% Profa. Nancy Baygorrea
% Operações lógicas e relacionais
clc
clear
% números guardados em variáveis
a = 5
b... |
%% Output data from controllers
fidData = fopen('output.txt');
tData = textscan(fidData, '%f%f%f%f', 'Delimiter', ';', 'headerlines', 1);
fclose(fidData);
fidData = fopen('err.txt');
eData = textscan(fidData, '%f%f%f%f', 'Delimiter', ';', 'headerlines', 1);
fclose(fidData);
fidData = fopen('ctrl.txt');
cData = textsc... |
[y,Fs]= audioread('X:\My Documents\GitHub\Pattern-Recognition-coursework\Lab 4\corrupted_voice.wav');
y1 = fft(y);
info =audioinfo('X:\My Documents\GitHub\Pattern-Recognition-coursework\Lab 4\corrupted_voice.wav')
T = 1/Fs; % Sampling period
t = (0:length(y)-1)*T; % Time vector
P2 = abs(y1/l... |
%for monto carlo
function y=is_mc(cell_new,cell_old)
%for initial energy
sz=size(cell_new);
cell_new=[zeros(1,sz(2)+2);[zeros(sz(1),1),cell_new,zeros(sz(1),1)];zeros(1,sz(2)+2)];
cell_old=[zeros(1,sz(2)+2);[zeros(sz(1),1),cell_old,zeros(sz(1),1)];zeros(1,sz(2)+2)];
e_new=0;
e_old=0;
kT=1;
tao_s=1;
for i =2:(s... |
function [keypts] = getKeypoints_EdgeFoci(img_info, p)
edgefoci_name = [img_info.full_feature_prefix '_EdgeFoci_keypoints.mat'];
if ~exist(edgefoci_name, 'file')
if ~ispc
warning('EdgeFoci is TURNED OFF on LINUX and MAC (binary not provided by the authors)');
keypts = [];
... |
function x=constrain(x,C)
%CONSTRAIN Constrains a reconstruction solution according to C
% X=CONSTRAIN(X,C)
% * X is the reconstruction before applying the constrains
% * C is the structure of constrains
% ** X is the reconstruction solution after applying the constrains
%
if isempty(C);return;end
if isfie... |
function varargout = dislocateGUI(varargin)
% DISLOCATEGUI MATLAB code for dislocateGUI.fig
% DISLOCATEGUI, by itself, creates a new DISLOCATEGUI or raises the existing
% singleton*.
%
% H = DISLOCATEGUI returns the handle to a new DISLOCATEGUI or the handle to
% the existing singleton*.
%
% DI... |
function [ P ] = image2Pixel( P )
% Tao Du
% taodu@stanford.edu
% Feb 13, 2015
%
% Given pixels in the image space, clamp into pixel space. See README for
% more explanation about these coordinates. Assume i and j are integeres.
% then all the points lie in [i, i + 1) x [j, j + 1) are covered in the
% pixel (j + 1, i +... |
function [n a]=fdivisao (n,a,x,M)
%Aplica Briot Ruffini M vezes
for k=1:M
%nucleo do Briot Ruffini
b(1)=a(1);
for i=2:n+1
b(i)=a(i)+x*b(i-1);
end
%redefinindo o polinomio quociente
n=n-1;
a=b;
%nucleo do Briot Ruffini
end
aux=a(1:n+1);a=aux; %limpa a memoria dos coef... |
%% Read MODIS EOS-HDF file and extract data
import matlab.io.hdfeos.*
% Information to modify
site_lon = -72.1715;
site_lat = 42.5378;
filedir = '/Volumes/XiYangResearch/Data/2.SatelliteData/2.MODIS/MCD15A2/';
filename = dir('/Volumes/XiYangResearch/Data/2.SatelliteData/2.MODIS/MCD15A2/*.hdf');
gridname = 'MOD_Gri... |
% TODO: You write this function!
% input: f -> an 9-joint robot encoded as a SerialLink class
% qInit -> 1x9 vector denoting current joint configuration
% posGoal -> 3x1 vector denoting the target position to move to
% output: q -> 1x9 vector of joint angles that cause the end
% effect... |
function [distance] = DLC_distancefrom(DLC_data, fixed)
%DLC_distancefrom() calculated the distance from a fixed point of each body
%part in a DLC frame
% DLC_data = data in DLC format i.e. numeric matrix with no headers,
% first column is frame number,
% then groups of 3 columns for each tracked part (x,y,confiden... |
% Author: Eseoghene Okonofua <EseO@Eseoghenes-MacBook-Pro.local>
% Created: 2017-09-20
% Intersect-N-Lines
% Input:
% (
% [line1point1x, line1point1y, line1point1z], [line1point2x, line1point2y, line1point2z],
% [line2point1x, line2point1y, line2point1z], [line2point2x, line2point2y, line2point2z],
% [... |
% Adjiman's Function
% Range of initial points: -5 <= xj <= 5 , j=1,2
% Some references: -1 <= x1 <= 2 , -1 <= x2 <= 1 "different global minima"
% Global minima: (x1,x2)=(5,0)
% f(x1,x2)=-5
% Coded by: Ali R. Alroomi | Last Update: 11 May 2015 | www.al-roomi.org
function fitness = Adjiman(ucode)
fitness = ze... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% python script: call numerical_sde_cpp.py (simulate trace + plot result)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Parameters:
%
% dt -- time step size, e.g. 1e-5
% t_interval ... |
% Granger Causality in frequency domain. only a prototype
function [gcy2x, gcx2y, fx2y, fy2x, Sxx, Syy, Hw] = nGrangerFA2(A, noisecov, fftlen)
if (exist('fftlen', 'var')==0)
fftlen = 1024;
end
P = [1 0; -noisecov(1,2)/noisecov(1,1) 1];
Q = [1 -noisecov(1,2)/noisecov(2,2); 0 1];
[p, m] = size(A);
m = round(m/p);
... |
%Program for neural network of OR Gate
clc; clear all;
disp('1.OR');
disp('2.AND');
disp('3.NOR');
disp('4.NAND');
choice = input('Enter Choice - ');
sprintf('\n');
switch choice
case 1
input=[0 0; 0 1;1 0; 1 1];
expected_output=[0 1 1 1];
case 2
input=[0 0; 0 1;1 0; 1 1]; ... |
function tcourse = xtractlist(hdr, data, list)
%
% function tcourse = xtractlist(hdr, data, list)
%
% UNTESTED
%
% extracts a single time series from a list of voxels
% time series of images
%
% hdr - header structure of one of the images in the time series.
% data - a 2D matrix where each row is an image and each ... |
function XX = theory_qualitativeRT_type1_v1(A1, A6, sigma1, sigma6, rho, changeFlag)
% horizon 1 parameters
cMu_R_1 = sqrt( 1 / (2 *sqrt(2)*sigma1 * rho) );
cBeta_0_1 = rho * cMu_R_1;
cMu_I_1 = A1 / (2 * sqrt(2) * sigma1 * cBeta_0_1);
% horizon 6 parameters
switch changeFlag
case 1
% cMu_R changes
... |
% Création d'un grid sag adapté à l'exportation dans zemax.
%Création d'une deuxième surface pour corriger la première
clear
%Configuration des paramètres
run config.m
s_max = hfov.*(1-z/f);
%Création de la fonction de grandissement
G = fun_creation(type_dist,r1,r2,g1,g2);
%Calcul du profil de distortion recherché
[... |
dolphin = imread('dolphin.png');
bicycle = imread('bicycle.png');
|% Absolute difference
abs_diff = abs(bicycle - dolphin);
imshow(abs_diff);
% Better: Use image package
pkg load image;
imabsdiff(dolphin, bicycle); % order doesn't matter |
function [Names IsMorph IsIntensity IsTexture IsGradient IsCyto IsHema IsEosin IsGray] = FeatureNames(Augmented)
if(~Augmented)
Names = {'AREA',...
'PERIMETER',...
'ECCENTRICITY',...
'CIRCULARITY',...
'MAJOR_AXIS',...
'MINOR_AXIS',...
'EXTENT_RATIO',...
'MEAN_INTENSITY',... %8
... |
% vesselSim NP Blockley's simple vessel simulator. Usage:
%
% [storedPhase, p] = vesselSim(p)
%
% This is the workhorse of the simple vessel simulator, and should be called by
% Run_Simulation.m
%
% Created by NP Blockley, March 2016
%
%
% Copyright (C) University of Oxford, 2016-2019
%
%
% CHANGELOG:
%
% ... |
% ~~~~ prior distribution ~~~~ %
function logpriorprob = prior(chi)
% chi = (gamma,pi,r,xip,phipi,phiy,rhoR,rhoz,rhob,...
% sigMP,sigz,sigtheta,sigb) is the parameter vector
% nu is a constant
gamma = chi(1);
pi = chi(2);
r = chi(3);
xi = chi(4);
phipi = chi(5);
phiy = chi(6);
rhoR = chi(7);
rhoz = chi(8);
rhob ... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Vortex: basic statistics
%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Generates the data for plots of 1B and 1C and writes a datafile to produce
% the plots in R.
%% LOAD DATA
clc
clear
close all
% More variables
Vortex_load;
Vortex_variables; % create some variables
%% Logicals
do.plotting ... |
function display_figures(fig)
addpath("export_fig")
filename = "samples2/C3TextNovoSimple50cmPt1.wav";
[y, Fs] = audioread(filename);
fontsize = 12;
fontaxissize = 10;
if(fig == 1)
%For C3Blank50cmPt1.wav
left = 0.15;
bottom1 = 0.5;
bottom2 = 0.01;
width = 0.8;
height = 0.45;
figur... |
function [f, c, bornes, Mi] = ariane1(m)
%%%--- Cas test 2 : Ariane 1 ---%%%
% indice constructif par étage
k = [0.1101; 0.1532; 0.2154];
% vitesse d'éjection par étage
ve = [2647.2; 2922.4; 4344.3];
% masse sèche
ms = k.*m;
% masse du satelite
mu = 1700;
% vites... |
function ce30_Config(obj)
% % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
% @Func ce30_Config；
% @Brief 初始化ce30的通信配置；
% @Param 属性，IN_BUFF_SIZE：输入缓存大小，IN_BUFF_SIZE：一个数据包大小，SAMPLE_PERIOD：采样周期
% @Retval NONE
% @Date 2019/11/21；
% % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
%% 函数主体
... |
% State-of-the-art and Comparative Review on Adaptive
% Sampling Methods for Ordinary Kriging
clear all;
close all;
%% Essential imports
addpath(genpath('src'))
warning('off', 'all')
global plotFlag
%% Start input prompt
[ methodID, benchmarkId, numberSamples, numberRepetitions, Vis ]= run_input_prompts();
if strcmp(... |
load('perturbations.mat');
N = 10;
[x y z]=ndgrid(-N:N);
data=(x.^2+(1.5*y).^2+z.^2)<N^2; %ellipsoid
data = double(data);
%data = smooth3(data,'box');
L2_data = norm(data(:));
maxL = maximum_l(N);
[ALM, C, N, r_cut, jball, jjorigin,Y, dems_Y, dels_Y, r_select_ratio] = spherical_harm_coeff(data, maxL);
[ALM_eig... |
function binary=en_coef2D_double_deadzone(coef,delta)
N=int16(size(coef)); H0=bitshift(N(1),-3); W0=bitshift(N(2),-3); Nsub=bitshift(int32(numel(coef)),-2);
binary=SFcode(H0,1536); binary=[binary SFcode(W0,1536)];
binary=en_coef2D_double_deadzone_sub(coef,delta,H0,W0,binary);
|
function out = fload(fname)
% FLOAD -- Load in and assign to variable.
%
% out = ... fload( 'file1.mat' ); loads the contents of 'file1.mat' and
% assigns to the variable `out`. 'file1.mat' cannot contain multiple
% variables.
%
% IN:
% - `fname` (char) -- .mat file to load.
% OUT:
% ... |
function y=approx_sum(x)
y=x;
while abs(y^2 - x)> 0.001*x
y = (x/y + y)/2
end
|
function [J, grad] = linearRegCostFunction(X, y, theta, lambda)
%LINEARREGCOSTFUNCTION Compute cost and gradient for regularized linear
%regression with multiple variables
% [J, grad] = LINEARREGCOSTFUNCTION(X, y, theta, lambda) computes the
% cost of using theta as the parameter for linear regression to fit the ... |
descriptor_matrix = [];
image_index = [];
index=1;
for prefix = 0:53
if prefix == 7 || prefix == 25 || prefix == 44 || prefix == 45
continue
end
for suffix = 1:4
image_name = [num2str(prefix),'_',num2str(suffix),'.png'];
[image, descriptors,locs] = sift(image_name);
descripto... |
function [GNCout] = ChooseNA(GNCin)
% Choose number of sensors
global NAMAX
j = 1;
for i = 1:length(GNCin)
for na = 1:NAMAX
GNCout(j) = GNCin(i);
GNCout(j).NA = na;
j = j + 1;
end
end
return;
|
function UpdateEdgeCost(updated_region)
global s_goal;
global neighbour;
global c;
global g;
global rhs;
global xmax;
global ymax;
for i=1:size(updated_region,1)%检测周边点情况
s_updated=updated_region(i,:);
%未越界
if s_updated(1)<1||s_updated(1)>xmax||s_updated(2)<1||s_updated(2)>ymax
co... |
function list = greedy_graphcut_function(similarity_mat, K, lambda1, lambda2)
N = size(similarity_mat, 1);
remain_list = 1:N;
list = [];
for idx = 1:K
max_value = -inf;
for jdx = 1:length(remain_list)
new_list = [list, remain_list(jdx)];
if length(new_list) == 1
value = lambda1 ... |
function [output] = GcodeToMatrix(gcode_file)
%Fucntion reads gcode file, outputs all toolpath data to a matrix.
FID = fopen(strcat(gcode_file,'.gcode'));
line = fgetl(FID);
k=1;
output(k,:)= readGCode2(line);
while line ~= -1
k=k+1;
line = fgetl(FID);
output(k,:)= readGCode2(line);
... |
% Simulate time series EEG-data by controlling source level parameters:
% ---------------------------------------------------------------------------------
% Choose a random dipole position from the whole source space.
%num_dip=1;
%dippos=sourcemodel.pos(:,:); % The entire sourcemodel is copied to dippos
%ran... |
M = csvread('outputs/sheet_02.csv');
M = [zeros(128, 180); M ;zeros(128, 180)];
phase = 29.4056213110678;
angle = 0.9996;
im_I = iradon(M, [phase:angle:angle*179 + phase], 'cubic', 'Hamming');
imwrite(im_I, 'outputs/im_I.png')
im_B = im2bw(im_I,0.2);
% Get the ratio_de
ratio_de = sum(im_B) / sum(im_I);
... |
function [res] = mostType(data)
[m,n]=size(data);
res_distinct = unique(data(:,n));
res_proc = zeros(length(res_distinct),2);
res_proc(:,1)=res_distinct(:,1);
for i=1:length(res_distinct)
for j=1:m
if res_proc(i,1)==data(j,n)
res_proc(i,2)=res_proc(i,2)+1;
end
end
end
for i=1:l... |
function sps=samplespace(Mu,tsig,jn,r,cl)
for i=1:r
for j=1:cl
sps(i,j,:)=normrnd(Mu(i,j),tsig(i,j),jn,1);
end;
end; |
classdef headstage < handle
%HEADSTAGE class describes headstages
properties
name@char
manufacturer@char
model@char
filter@double
samplingRate@double
connector@char
gains@double
channelMap@double
end
methods
... |
%% the 2D plane with 2D link experiments
clc
clear
% define the auxiliary variables
syms lmd y1 y2 real;
nlink = 2;
% robot configurations
theta1 = pi/3;
theta2 = pi/6;
% forward kinematics
xpos = cos(theta1) + cos(theta2);
ypos = sin(theta1) + sin(theta2);
% arbitrary wall: y <= x + bias
% max_b = 2*(sqrt(2)/2 +... |
%% Prepare environment
clear all;
close all;
clc;
%% Crash course
% X = A*X + B*U + E*N
% Y = C*X + D*U + F*N
% Rows
% size(Y, 1)
% Columns
% size(Y, 2)
%% Parse initial condition
% Open input file
input_data = fopen('input.txt','r');
% Read file
for i = 1:5
command = fgetl(input_data);
eval(command);
end
... |
function [ z ] = isGameDone( board )
if (sum(board(:) == 2 ) == 0)
z = 3;
elseif (sum(board(:) == 3 ) == 0)
z = 2;
else
z = 1;
end
end
|
clc, clear all, close all
tic % start computation time
% for calling helper functions
addpath(genpath('\\bmi-nas-01\Contreras-UH\Infantdata\Infantdata\code\Zachs_Infant_decoding_files'))
%% Generate List of Infant Data Folders
InfantDir = '\\172.27.216.40\Contreras-UH\Infantdata\Infantdata\Data\';
files = ... |
opts_fields = fields( opts );
varargin=[];
for i = 1 : numel( opts_fields )
eval( [ opts_fields{ i } , ' = opts.' , opts_fields{ i } , ';' ] ) ;
varargin{end+1}=opts_fields{i};
varargin{end+1}=opts.(opts_fields{i});
end |
function [BW,maskedImage] = segmentImage(X)
% Adjust data to span data range.
X = imadjust(X);
% Threshold image - manual threshold
BW = X > -5783;
% Invert mask
BW = imcomplement(BW);
% Clear borders
BW = imclearborder(BW);
% Erode mask with rectangle
dimensions = [3 3];
se = strel('rectangle', dimensions);... |
%Analitical solution
dt = 0.0001; %Try different values
m = 70;
k = 10000;
gama = 100;
tf=5;
x = 0:dt:tf;
y = exp(-(gama/(2*m))*x).*cos(sqrt(k/m - gama^2/(4*m^2))*x);
plot(x,y)
%%% |
%%% Codigo para seguimento de trajetoria de um robo RP %%%
%%% Oscar Schmitt Kremer %%%
%%% Controle de robos - 2019-1 %%%
%%% Ganhos proporcionais e derivativos%%%
clear
clc
close all
m = 1;
t = 0:0.002:24;
t = t';
t_plot = 0:0.002:23.996;
t_plot = t_plot';
sizes = size(t);
%Descomentar para segund... |
function [range, faceimg, mask] = findFace(oriImg, tlow, thigh)
%figure, imshow(oriImg)
%get size
[m, n, ~] = size(oriImg);
top = 1;
left = 1;
down = m;
right = n;
%detect skin color region
mask = detectSkin(oriImg, tlow, thigh);
%figure;imshow(mask);
%fill empty region
fmask = imfill(mask);
%figure;imshow(fmask);... |
clc
clear all
% Circular wire
% angle = linspace(0,360,20);
% x= 0.020 * cosd(angle);
% y= 0.020 * sind(angle);
%
% wire(:,1)=x;
% wire(:,2)=y;
% wire(:,3)=0;
% %Figure8coil
angle = linspace(0,360,100);
x1= 0.040* cosd(angle) - 0.040;
y1= 0.040 * sind(angle);
x = [x1(1:end) -x1(1:end)];
y = [y1(1:end) y1(1:end)... |
function [gradient,dInputs]=backwardOneLayerLinearOutNet(net,netState,delta,saturationControl,networkType)
%networkType=0 --> comparisonNet, networkType=1 --> GNN
%saturationControl e networkType sono inutilizzati perché il controllo di saturazione non ha senso qui.
%Sono stati mantenuti per uniformità con le a... |
% plot stim
% what's this stim???
DUR = XStimParams.curr_stimdur;
nPts = DUR*round(TDT.Fs/1000);
nEpochmsecs = XStimParams.epoch_duration(1); % duration of each epoch at one SPL
nEpochPts = round(nEpochmsecs * TDT.Fs/1000);
nEpochs = round(nPts / nEpochPts);
nPts = nEpochs * nEpochPts;
DUR = nPts / ... |
%compares MM2 with Laguerre's
LG_val1(1,1) = polyVal(-3); LG_val1(2,1) = -3;
MM2_val1 = polyVal(-3); MM2_val1(2,1) = -3;
LG_val2 = MM1_compare(-5,-4,-3);
MM2_val2 = MM2_compare(-3);
LG_val = [LG_val1 LG_val2];
MM2_val = [MM2_val1 MM2_val2];
x = 0:15;
MM1_plot = abs(LG_val(1,:)); MM2_plot = abs(MM2_val(1,:));
figure... |
A = [2 pi; sqrt(2) log(2);0 -1] % set up the matrix
A(1,:) = A(1,:)/A(1,1) % Row1 = Row1 / 2
A(2,:) = A(2,:)- A(2,1)*A(1,:) % Row2 = Row2 - sqrt(2)*Row1
A(3,:) = A(3,:)- (A(3,2)/A(2,2))*A(2,:) % Row3 = Row3 - (-1/-1.5283)*Row2
A(2,:) = A(2,:)/A(2,2) % Row2 = Row2 / -1.5283
A(1,:) = A(1,:)-A(1,2)*A(2,:) % Row1 = Row1 - ... |
% MAT 240B - 2011/03/18 - Karl Yerkes
%
% this code was written in an effort to prototype an online, realtime
% hrtf-based binaural spatializer. the evetual goal is to run this
% spatializer on an iPhone as part of the AlloScope project, started
% by Danny Bazo and Karl Yerkes, in the Winter of 2010.
%
% this code use... |
% Asumiendo un modelo exponencial de la forma a*exp(b*x), este
% sería el crecimiento del número de casos de COVID-19
% en los próximos días (con límites de confianza del 95%):
%Este modelo fue ajustado usando los datos recopilados entre el 3 y 19 de marzo
close all;
clc
clear all;
y = [1,1,1,3,9,12,12,16,24,45,... |
function queryAll
queryLocations;
queryAnchors;
queryRanging;
|
clear all; close all; clc;
Train = load('train.txt');
Test = load('test.txt');
C = cov(Train(:,2:end)); %find covariance matric
MU = mean(Train(:,2:end))';
[V,D] = eig(C);
%Take the principal eigenvectors
pcs = 32;
E = V(:,end-pcs+1:end);
% from each observation - image, subtract the mean values and proj... |
% Finding circles in an image of an eye
close all;
newD = 250;
filename = 'eye_60.jpg';
A = imread(['cropped/', filename]);
A = imresize(A, [newD NaN]);
A3(:,:,3) = 128; A3(:,:,2) = 128;
A3 = rgb2gray(imresize(A3, [newD NaN]));
A1 = rgb2gray(A);
% figure()
% imshow(A1)
B1 = imbinarize(A(:,:,1), .06);
B2 = imbinari... |
function DenoisedImg = PNLM(ObsImg,PatchSizeHalf,WindowSizeHalf,EstSigma,RhoSq)
% FUNCTION: Probabilistic Non-Local Means (PNLM) for image denoising
% =========================================================================
% INPUT:
% ObsImg = 2D grayscale image
% PatchSizeHalf = half of local square patc... |
function [cell1,cell2] = SplitCells(I,bgcolor)
% Function that performs color image thresholding using
% histogram derived.
% Inputs:
% input - Input image as RGB
% bgcolor – value for bg color eg 256 for white, 0 for black.
% Output:
% 2 binary images of cells: cell1,cell2
IG = rgb2gray(I);
%histogram... |
%% Swarm Switching Behaviors for Motion
% Description : Switching Behaviors - Motion
% Author : Sasanka Nagavalli
% Date : February 5, 2016
% Other Files :
%% Clean up
clear;
clc;
clf;
close all;
%% Paths
addpath('../behaviors');
data_folder = '../data';
%% Simulation parameters
N = 10;
ti = 0;
dt = 0.1... |
function [varDistParams, x] = efficientStochOpt(...
x, log_emp_dist, variationalDist, stepWidth, dim, maxCompTime)
%Memory efficient stocastic optimization for parfor loop
%Perform stochastic maximization step
debug = false; %debug mode
updateRule = 'amsgrad';
% beta1 = .7; %the higher, the ... |
function training(args)
%training Train and test the eigenface reconstruction on the first face in the
% test data and make sure it reconstructs correctly. Also display the mean
% face and top 10 and bottom 10 eigenfaces
training = train_eigenface(args);
% Reconstruct first image in training data
image = r... |
clear all;
close all;
data=load('path.txt');
% Data reduction
interval = 1000;
x = data(1:interval:end,1);
y = data(1:interval:end,2);
theta = data(1:interval:end,3);
%Arrow Parameters
pointsize = 100; %pointsize of initial and goal points
ArrowLength = 10;
LineWidth = 1; %LineWidth of the arrow
MaxHeadSize = 2;
u =... |
classdef WindFarm < handle
properties
windTurbine@WindTurbine
WindModel@WindModel
NwindTurbines
Area@Area
Power
end
methods
function obj = WindFarm(windTurbine,WindModel,Area)
obj.windTurbine = windTurbine;
obj.WindModel = WindMode... |
x = simplecluster_dataset;
%x = x + rand(2,1000)*2
plot(x(1,:)', x(2,:)', 'o')
%%
iter = 100;
initHood = 3;
topologyFcn = 'hextop'; % 'hextop'(*), 'gridtop' and 'randtop'
distanceFcn = 'linkdist'; % 'linkdist'(*), 'dist' and 'boxdist'
% [2 2] is very interesting: it clusters the data
net = selforgmap([8 8], iter,... |
%%
% Filename: m3dof_fkin.m
% Desc: calculates the forward kinematics for the planar 3DOF robot
% INPUT:
% q (3x1): joint angles in radians
% l (3x1): length of the links
% OUTPUT:
% f (3x1): planar position [f(1:2)] and rotation angle in radians [f(3)] of EE
%
% 2015 alessandro.giordano@dlr.de
%%
function [f] = m3... |
function res = onedist(z,pt)
% ONEDIST(z,pt) calculates the distance between point pt and each
% row in matrix z
% Copyright (c) 1996 by D. Kaplan, All Rights Reserved
[r,c] = size(z);
if c ~= length(pt)
error('pt and z must have same number of columns');
end
sum = zeros(r,1);
for n=1:c
foo = z(:,n) - pt(n);
su... |
function varargout = ARNquant(varargin)
% ARNQUANT MATLAB code for ARNquant.fig
% ARNQUANT, by itself, creates a new ARNQUANT or raises the existing
% singleton*.
%
% H = ARNQUANT returns the handle to a new ARNQUANT or the handle to
% the existing singleton*.
%
% ARNQUANT('CALLBACK',hObject,ev... |
function [ tanstruct_out_filtered ] = apply_ace_filter_monthly2X( tanstruct_in)
%A function to create zonally averaged climatologies of ACE measurements,
%by each unique calendar month. 'make_ace_climatology.m' is called here.
% *INPUT*
% tanstruct_in: STRUCTURE - contains the gas specific ACE data.
% ... |
function [data] = read_CSV_or_FCSV(filename)
%READ_CSV_OR_FCSV Summary of this function goes here
% Detailed explanation goes here
fcsv_string='.fcsv';
TF = contains(filename,fcsv_string);
if TF
data = FCSV_Read(filename);
else
data = importcsvfile(filename);
end
end
|
function [X_new] = ResampleParticles(X, W, L)
%RESAMPLEPARTICLES Return new particles based on weighted particles.
% Using clustering and normal pdfs.
%
[yl, xl] = size(L);
zl = double(min(min(L)));
N = size(X, 1);
X_new = X(W>0,:);
missing = N - size(X_new, 1);
n_rand = floor... |
% script to illustrate the properties of the different subtraction methods
% in ASL
figure; set(gcf,'Position',[10 10 650,450]);
TR=1.4;
nyq=1/(2*TR);
%%%%%%
if 1
load ('voxels.mat');
tlen = size(a,1);
NITER = size(a,2);
types=4
else
tlen=500;
NITER = 100;
types=3
end
simp = zeros(NITER,... |
%=========================================================================
function [CellCrop, i1, i2, i3, i4, i5, i6, i7, i8]=crop2(Ibox3,varargin)
%=========================================================================
global i1 i2 i3 i4 i5 i6 i7 i8
Ic=cell2mat(varargin);
if size((Ibox3),2)==3
i1=imcrop(... |
function [radbu] = band_unapod(radbpr);
% function [radbu] = band_unapod(radbpr);
%
% Convert padded & rolled off Hamming CrIS spectra to unapodized spectra.
%
% Input:
% radbpr - [1763/1411/1031 x nobs] padded/rolloed off Hamming spectra
%
% Output:
% radbu [713/433/159 x nobs] unapodized CrIS spectra
%
% Cr... |
% function CPFEM_Tensile_Spec__2D__GRIPS()
global Lattice
xmin = Lattice.size.xmin;
xmax = Lattice.size.xmax;
ymin = Lattice.size.ymin;
ymax = Lattice.size.ymax;
xincr = Lattice.size.i_incr;
yincr = Lattice.size.j_incr;
xlength = Lattice.size.xlength;
ylength = Lattice.size.ylength;
x = Lattice.si... |
N=1000;
figure;
hold on;
x=randn(1, N);
y=randn(1, N);
h = scatter(x, y, 'r.');
xlabel('Condition A');
ylabel('Condition B'); |
set(0,'defaultLineLineWidth',3)
set(0,'DefaultAxesFontSize',15);
mud=textread('../wells/MudWeightAverage.txt');
mud0=textread('../wells/MudWeightAverage0.txt');
mud1=textread('../wells/MudWeightAverage1.txt');
mud2=textread('../wells/MudWeightAverage2.txt');
mud3=textread('../wells/MudWeightAverage3.txt');
mud4=textre... |
function [ssimval, ssimmap ] = ssim_function( A,ref);
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
ssimval = ssim(A,ref);
% diff(getrangefromclass(A))=ssim(diff(getrangefromclass(A)),Name,Value,...);
im_path1 = 'Reference Image.bmp';
ref = imread(im_path1);
im_path2='Blurred Image... |
function Xout = kaVirtualSignalBetaDiv(X,posAlpha,b)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%
%% Input :
%% X : 2 channels actual signal (FFT representation) :
%% 2 (channel) x freq x frames x source
%% posAlpha : Vector of microphone position
%% 1 x # of virtual mic
%% b : beta divergence parameter : scalar
%%... |
%%%% now do the experimental data
figure; set(gcf,'Position',[1 1 450,450]);
warning off
TR=1.4;
nyq=1/(2*TR);
%%%%%%
load ('voxels.mat');
tlen = size(mytimeseries_act,1);
NITER = size(mytimeseries_act,2);
types=2;
simp = zeros(NITER, tlen/2);
run = zeros(NITER,tlen-1);
sinterp=zeros(NITER,tlen);
orig=zeros(NITER... |
function plot_pretty_glms(betas,nBack, gridlines)
if ~exist('gridlines', 'var')
gridlines = false;
end
B=nanmean(betas);
se = nansem(betas,1);
figure; hold on;
grey = [0.7,0.7,0.7];
% Horizontal grey dottend lines behind the data
if gridlines
ys = [-2:0.25:2];
for y = ys
line([0, nBack + 1], [y,... |
function makeLaserPulseTrain()
% Make laser pulse train
trial_duration_s=15+3+25; % total duration of the trial
laser_on_s=[15.75 17.75]; % [start stop] for pulse train
pulse_width_s=0.150;
IPI_s=0.200;
dbstop if error
ephysSettings
% Create blank command
zeroCommand=zeros(1,settings.sampRate*trial_duration_s,1);
... |
clear all;
stateData = importdata("../vision_capture/run12/poses.dat");
xvelactual = stateData.data(:,37);
groundpix = [387, 290];
pix2worldscaling = 1.3476;
pixvel = zeros(length(xvelactual - 1),1);
for j = 0:length(xvelactual) - 2
fr1 = rgb2gray(imread("../vision_capture/run12/ts" + j + ".png"));
fr2 = rgb2g... |
init;
num = 13;
errlist = zeros(1,num);
path = strcat(saveImgTo,'train/');
for i = 1:num;
[~,errlist(i),f] = main(i);
title(strcat('Data Set:',int2str(i), ' error rate: ', num2str(errlist(i)*100), '%'));
saveas(f,strcat(path,'Train-',int2str(i)),'jpg');
end
|
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