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function [SOIT,SSOIT,FOSIT,FOSPT,FODPT,FOAT1,FOAT2,SONT,SONTsqrt] = rmtens(struhyp,ntens)
% Tensorial operators (en notaci๓n de Voight)
%global SOIT SSOIT FOSIT FOSPT FODPT FOAT1 FOAT2 SONT struhyp ntens
% Second order identity tensor
% จจจจจจจจจจจจจจจจจจจจจจจจจจจจ
SOIT = [1 1 1 0 0 0]';... |
clear all
close all
clc
%data input
GM=398600.44;
w_earth=2*pi()/86164;
data=load('data.txt');
data(1,3:5)= data(1,3:5)*pi()/180;
M = 64.0942*pi/180;
Eo = M;
E(1)=M+data(1,2)*sin(Eo);
for k=1:50
E(k+1)=M+data(1,2)*sin(E(k));
if abs(E(k+1)-E(k))<10e-8
break
end
end
Ec_rad = E(:,end);
K=[cos(data... |
function [DATA, params, FN, nSpikes, Vstr, Zscores,Vstr_list,Zscores_list] = read_data3_minus_spont(dataFN,dataPATH, frame, pflag, flag1, repflag)
% function [DATA, params, FN, nSpikes, Vstr, Zscores,Vstr_list,Zscores_list] = read_data3_minus_spont(dataFN,dataPATH,frame,pflag,flag1,repflag);
%
% to read data creat... |
function analyse_links_file
% Creates the file "links-simple-sorted.txt", using the file
% "links-simple-matlab.txt" created by convert_links_file.m
%
% Henry Haselgrove, January 2009.
load params num_pages
load link_param num_links
global titles_sorted
if ~exist('titles_sorted','var')
load sorted_... |
function [dados] = extrai_haralick(img,mask,janela)
% Projeto CINAPCE
%
% Calcula os paramentros de textura da imagem de hipocampo
%
%janela = 9;
indices = find(mask ~= 0);
len = length(indices);
nErros = 0;
struct = incializa_ed(len);
for t=1:len
try
w = getwindow(indices(t),img,janela);
catch
... |
function d = getInfo(filename)
%GETINFO Loads all the fields for a single Amdar file, prints info.
% This method to provide a means for exploring available data fields,
% identifying units, and reading other metadata associated with the file.
%
%SYNTAX:
% d = Amdar.getInfo(filename)
%
%INPUT:
% filenames - Cell ar... |
function [Pl] = PL_PM_to_PPM(P, mode)
% compute the Plucker projection matrix from a standard projection matrix
% as in Bartoli, Sturm. Only mode == 0 is supported currently.
if (~exist('mode', 'var'))
mode = 0;
end
if (mode==0) % bartoli-sturm
Pbar = P(1:3,1:3);
p = P(1:3, 4);
Pl = [det(Pbar)*inv(Pbar)' skew(p)*... |
function c=movie_maker2(g)
m=length(g(1,1,:));
b=uint8(zeros(144,435,m));
c=struct('cdata', b,'colormap',[]);
for i=1:m
pcolor(g(:,:,i));
shading flat
colormap(gray)
c(i)=getframe;
end |
mex mexTest.cpp
numbers = mexTest(15); |
%% combine all final models for face system analysis
clear;
% combine them into one file!
finalModel{1} = load('finalModels_wholeBrain.mat');
finalModel{2} = load('finalModels_noFace.mat');
finalModel{3} = load('finalModels_faceOnly.mat');
|
% Es 7
% Generate g(n) as a set of 10000 realizations of random variables distrubted as ~ N(0, 1).
% Compute the mean and the variance
% Create h(n) = a * g(n) + b, with a = 0.5; b = 4.
% Is h(n) still a Gaussian random variable?
% Compute the mean and the variance of h(n).
close all
clearvars
clc
%% parameters
N =... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Technische Universität Berlin
% Fakultät Verkehrs- und Maschinensystem
% Fachgbiet Kraffahrzeuge
% M.Sc. Osama Al-Saidi
%
% Fahrzeugregelung: Projekt - ESP WS16/17
% File: Parameter Sinusfahrt
% Datum: 28.12.2016
%
%%%%%%%%%%%%... |
%2020.7.30--
%子函数，输出前提项Item和结论项<Item,s>的支持度
%输入：Class_set-1*M cell,类标签集合， s--对应Class_set中的哪一个类别
% Label_mass--N*2cell, 每个训练样本的软标签以及对应的Mass值
function [Sup_item,Sup_ruleitem]=Support_Ruleitem(itemset,Data,Class_set,s,Label_mass)
N=length(Data); %表示的是训练样本的个数
Matching_degree=zeros(1,N);
Sup_item=0;
Sup_ru... |
% CMPU250 - Professor Eric Aaron
% HW2 - Kyle Patterson
% April 2018
% ####################################################################
% ### ###
% # ... |
% This script draws the theta-direction EXB and electron diamagnetic velocities
% versus time
% Copy this script to the folder of the data and then run it
clear; close all;
global den Te pe vi jz ve phi vEx vEy vdex vdey dt inv_nustar calc ddx
%%
load('parameters.mat');
addpath(code_path)
last_file = get_last_fil... |
function [frequences_triees,indices_frequences_triees] = tri(selection_frequences)
%TRI Summary of this function goes here
% Detailed explanation goes here
[frequences_triees indices_frequences_triees]=sort(selection_frequences, 'descend');
end
|
function [ vals ] = gen_small_peaks ( len, n_peaks, sigma_mod )
% can be negative
vals = zeros(1, len);
for i = 1:n_peaks
peak = sign(randn()) * normpdf((1:len), randi(len), sigma_mod * (1 + abs(randn()))); % multiply random by s.d.
vals = vals + peak;
end
%standarize
vals = vals / m... |
function link_next_versus = enfrentar_marcadores_multiples(N1,N2,N3,marker_versus,link_prev_versus,d3)
marker_versus = marker_versus(link_prev_versus>0);
link_prev_versus = link_prev_versus(link_prev_versus>0);
trayectorias_versus = [];
for i=1:length(marker_versus)
if nargin>5
... |
%Titus John
%Leventhal Lab, University of Michigan
%2/8/2016
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%This script will shoot out the plots for a given rat and produce
%comparison for the fine reaching analysis after the trajectory analys
%ihaws been completed
%Will compoare the traje... |
function evaluateConfig(config)
disp("--Config--")
disp(["Sampling Count: ", config.samplingCount]); % 0 - Import all images
disp(["Balance Data: ", config.balanceData]);
disp(["Pre-processing?: ", config.prepro]);
if config.prepro == 1
disp(["Pre-processing method: ",config.preproMethod]);
end
disp(["Feature Extra... |
clear all
close all
% Specify data subdir
dataDir = 'data/';
LabelFiles;
fprintf('Loading dataset...');
% Label data according to spoken digit
data = audioDatastore(dataDir, 'IncludeSubfolder', true, 'LabelSource','foldernames');
% Split data into train and test data ( 80/20 - train/test split )
[trainData, testD... |
% DEMOSCEN は、 Wavelet Toolbox で、ウェーブレットの代表的な1次元ウェー
% ブレットのシナリオのデモを行います。
% DEMOSCEN は、Short 1次元 シナリオのデモを行います。
%
% DEMOSCEN('auto') は、Short 1次元 シナリオのデモを自動実行モードで行い
% ます。
%
% DEMOSCEN('loop') は、Short 1次元 シナリオのデモをループモードで行いま
% す。
% Copyright 1995-2003 The MathWorks, Inc.
|
%% Plot Script
% Plots Graphs of Demand and Production on ceratain days
format compact
format bank
% Script is meant to be run after LoadData
% Demand and totalProd will be defined
demand=Demand;
production=totalProd;
% Input time frame to analyze
% Calculates time interval Domain for February 2, 2014
startInd... |
function f = GP_LCB(x, da)
%calculate the lower confidence bound function with given data set in da
%x is a vector for a new point
%da contains all evaluated data
% Xmat, all points in its columns
% invKmat, = inv(Kmat+sig^2*I)
%
%created by X. Huang, 1/18/2019
%this is for minimization problem
%
if 0
nu=1;
del... |
function [ct] = how_many ( prefix, x, ct_f )
% init ctr
ct = zeros ( 1, numel ( ct_f ) );
% for all frames to count
for i = 1:numel(ct_f)
% read image and convert to gray
fileName = sprintf('%s%05d.png', prefix, ct_f(i));
input_im = rgb2gray ( imread(fileName) );
input_im = imadjust(input_im);
... |
% test EVB (Enhanced Variational Bayes)
clear all; clc;
%% Generate data from linear model
% param are the natural parameters
N = 100; % Number of observations
M = 10; % Number of parameters
[y param] = generateDataLinear(M, N);
param.post = {};
%% configuration
conf.MaxIter = 500;
conf.alpha = 0.01; % learning... |
function population = InsertBestIndividual(population, best, copies)
for i = 1:copies
population(i,:) = best;
end
end |
function Store(dataObject, varargin)
%STORE - Saves a data object to the hard drive.
% This function creates two standard MAT files (.mat) representing a human data object on the hard drive. Both files
% are stored either at the user-specified location or, by default, wherever the current working path is.
%
% ... |
%% Load the data matrices
%main;
load('gamma10.mat');
load('normal10.mat');
load('lognormal10.mat');
%% Which is a better distribution for each gene?
%we answer that by calculating the median of scores in each column(struct
%field) and comparing the three distributions.
%also, when we answer that question, we might ... |
function J = computeCost(X, y, theta)
%COMPUTECOST Compute cost for linear regression
% J = COMPUTECOST(X, y, theta) computes the cost of using theta as the
% parameter for linear regression to fit the data points in X and y
% Initialize some useful values
m = length(y); % number of training examples
% You need to... |
function arch = PACK_sats2arch(sats)
% PACK_sats2arch.m
% Example:
% sats{1} = [1,2,3,7];
% sats{2} = [4,5,6,8];
% sats{3} = [9];
% arch = PACK_sats2arch(sats)
% arch = [1,1,1,2,2,2,1,2,3]
nsats = length(sats);
ninstr = sum(cellfun(@length,sats));
arch = zeros(1,ninstr);
for i = 1:nsats
sat = sats{i};
arch(sa... |
function [xc,d,MTX,para] = InvM(MTX,para,x0)
% [xc,d,MTX] = InvMainN(MTX,para,x0)
%
%% Approximate Unconstrained Gauss-Newton with Armijo rule line search
%
% Input: MTX = Structure of global (see generateMTX)
% para = parameter structure
% x0 = initial iterate
%
% Output: xc = solution
% ... |
function [sol, z]=MyCost(model,q)
%% NFE
global NFE;
if isempty(NFE)
NFE=0;
end
NFE=NFE+1;
%% Run Topsis
sol=TOPSIS(model, q);
pause(0.05);
%% Run Simio and get the results
%z=[rand*1000 rand*20 rand]';
F=RunSimio();
z=[F(1).z ,F(2).z, F(4).z]';
end |
function [ matConf, txCat ] = multiClassprediction( predictionclassifieurs, yGtest, imCatTest )
%MULTICLASSPREDICTION Summary of this function goes here
% Detailed explanation goes here
% for i=1:size(imCatTest)
% for j=imCatTest(i):size(yGtest,2)
% yGtest(i,j)=0;
% end
% end
txCat=zeros(size(... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% This learns the discriminative patch svm in the method from "Unsupervised
% Discovery of Discriminative Patches" Singh et al.
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% the inputs should all be structs w... |
function mutatedChromosome = Mutate(chromosome, mutationProbability)
chromosomeLength = length(chromosome);
mutatedChromosome = chromosome;
creepRate = 0.1;
for iGene = 1:chromosomeLength
r = rand;
if (r < mutationProbability)
%q = rand;
mutatedChromosome(iGene) = rand;
%mutatedChro... |
function FrzData=FindFreezing2(VelData,FPS,ThreshC)
% ThreshC=Thresh;
FragThresh=FPS*0;
AllBouts=cell(size(VelData,1),1);
for k=1:size(VelData,1)
Input=VelData{k};
dInput=(sign(Input(:,:,1)-ThreshC)); % sign of Input - ThreshC ... will be 2 at + crossings, -2 at - crossings, 0 otherwise
for i=1:size(dInput... |
xx = x'; zz = z';
plot(xx,zz,'.')
len = length(xx);
xx(len+1) = xx(1); zz(len+1) = zz(1);
k = boundary(xx,zz);% generate boundary of data points. %this is index of all point located in the boundary
hold on;
plot(xx(k),zz(k));
X=xx(k);Y=zz(k);%return the original x,y coordinate corresponding to each index k
... |
%clear all
hold on
polytype = load("../data/EPAPolytypeEdges.m");
nCol = size(polytype,2);
nRow = size(polytype,1);
div = find(polytype(:,1) < 0);
border = 0.4;
camup([0 1 0])
grid on
pbaspect([1 1 1])
rotate3d on
xlabel('X')
ylabel('Y')
zlabel('Z')
triangle = 1;
for (idx = 1:3:nRow)
hold on
triangle
triangl... |
function opt = SE0P_parse_params(opt)
% opt = SE0P_parse_params(opt)
%
% Parse parameters and set up free-space Ewald grid sizes:
% inner = domain containing all sources and targets
% extended = FGG grid (to cancel wrap effects)
% padded = 2x FFT grid (for aperiodic convolution)
% oversampled = FFT grid for truncated G... |
clc
clear all
close all
%% P1 - Specifying Parametors
% Put all data in one time table with the following headers - dateTime, pm1
%, pm2.5 pm10
dataFolder = "/media/teamlary/Team_Lary_1/gitGubRepos/data/mintsData";
dotMatsFolder = dataFolder + "/dotMats";
grimmDataFolder = dataFolder + "/Spectro... |
function file = save(obj, export_path, varargin)
% Save the symbolic expression of a wolframe MX file
%
%
% Parameters:
% export_path: the path to export the file @type char
% varargin: variable input parameters @type varargin
% ForceExport: force the export @type logical
%
% Ret... |
function [net, info] = dcti(varargin)
%Traning DCTI
%Loading Networks
net = dcti_init();
net = vl_simplenn_tidy(net);
%Configuaration
opts.dataDir = fullfile('Data', 'Dataset');
opts.imdbPath = fullfile('Data', 'Experiment', 'imdb.mat');
opts.train.gpus = [];
opts.train.expDir = fullfile('Data', 'E... |
%% This will calculate the hessian of the object function and nonlinear constraint
clear;
modelName='human_3';
warning on verbose
%add share functions
addpath dyn/
addpath obj/
addpath gaitCon/
addpath plotRobot/
dbstop if error
addpath hessian
addpath (['../',modelName,'/robotGen/'])
addpath (['../',modelName,'/robot... |
%% Génération de plusieurs map pour des resonateurs différents
% Donc pour des longueurs de tubes différents
%% Init
close all;
clear;
% Liste de longueurs tels que la fréquence fondamentale est a peu pres in tune
load in_tune_lengths.mat lengths_list;
N_init_samples = 25;
N_edsd = 75;
x1_min = 0;
x1_max = 1;
x2_mi... |
%load Cactus_cfp8_3d_transB_5lev;
%load ParkScene_cfp8_3d_transB_5lev;
%load Kimono_cfp8_3d_transB_5lev;
%load CrowdRun_cfp8_3d_transB_5lev;
%load BQTerrace_cfp8_3d_transB_5lev;
%load OldTownCross_cfp8_3d_transB_5lev;
Ldc=coef(:,:,2); L5=coef(:,:,5); L4=coef(:,:,9:10); L3=coef(:,:,17:20);
L2c=coef(:,:,33:40); L2b... |
function [ F_diag ] = computeFDiag( theta, training_data,training_target,layer_size)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
%% Initialize the parameter
[W,b] = dnnParamToStack(theta,layer_size);
m = length(W);
y = cell(m,1);
dydx = cell(m,1);
F_w = cell(m,1);
F_b = cell(m,1);
%... |
function y=unitVec(pointA,pointB)
vectorAB=pointB-pointA;
y = vectorAB/norm(vectorAB);
|
%% Prep_ImportData Function
% Goal:
% Read in csv files with the first rowing being variable names.
% Save data,label, and map in a struct DATASET_VAR.
% Save data in a matrix.
% Input:
% Input 1: Dataset name.
%%
function Prep_ImportData(Dataset)
DATAS... |
clear all
load digit
% convert train data set
% M=1, N=300
[M,N] = size(train);
for i=1:N
img = train{i};
data(i,:) = reshape(img,1,size(img,1)*size(img,2)); % training data set
end
data = data.';
[PC,V] = pca2(data);
lamda = sum(V);
tmp = 0;
for j = 1:size(V)
tmp = tmp + V(j)/lamda;
POV(j) = tmp;
... |
%***********************************************************%
% INPUT:
% DB: price data series
%***********************************************************%
% OUTPUT:
% Asset: the evolution of the trading account
%***********************************************************%
function Asset = TradingAccount_Evolution(... |
function [C, sigma] = dataset3Params(X, y, Xval, yval)
C = 1;
sigma = 0.3;
% ----- %
values = [0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 1, 2, 5, 10, 25, 50, 100];
results = [];
l = length(values);
for c=1:l,
for sigma=1:l,
testC = values(c);
testSigma = values(sigma);
model= svmTrain(X... |
clc; close all; clear; format short e;
headers;
generateNet;
generateTrainTestData;
createEmptyFigs;
learnAndTest;
% continueRun; |
function [cc_add, c_add_mye, c_add_unmye, pct_mye, xvals] = predict_cc_add(brwt, bvol, xvals, pct_mye, fit_distn, frac)
%function [cc_add, c_add_mye, c_add_unmye, pct_mye, xvals] = predict_cc_add(brwt, bvol, xvals, fit_distn, frac, regress_type)
%
% Fit Wang et al. (2008) data (myelinated & unmyelinated ADD),
% using... |
clc
clear all
fprintf('The False Postion method\n');
Xl = input('lower bound = ? ');
Xu = input('Upper bound = ? ');
tol_x = input('tolerance x = ? ');
tol_y = input('tolerance y = ? ');
while(1)
if(fun(Xl) * fun(Xu) > 0)
fprintf('There is no answer');
else
Xr = (Xl * fun(Xu) - Xu * fun(Xl)) / ... |
close all; clear all; clc
[N,T] = xlsread('../data/dox_231_time.xls');
tvec = linspace (0,34,5);
colorsets = varycolor(5);
N(2:end,2:end) = N(2:end,2:end);
for i = 1:length(N)-1
barcode(i).cellnum = N(:,1);
barcode(i).time = N(:,i+1);
barcode(i).well = T(i+1);
barcode(i).color = colorsets(i, ... |
function MAC_sendPacket(radio, txType, txData, txSeqNo, txEop, maxCapacity)
%% Packet Header Structure
% First 12 bits for length in Byte
% 4 bits for packet type DATA, DATA_ACK, CTRL, CTRL_ACL
% 8 bits sequence number
% 8 Bits = First bit for EOP, 7 bits reserved
% 32 bits data CRC
% 8 CRC for Packet
packet... |
clear;clc;
load data2015
%load data2016
[n,p]=size(score);
D=score;
t1=clock;
for K=1:40 %set different K-values.
%tic;
for i=1:n
for j=1:p
D(i,j)=0;
D(i,j)=(sum(D(:,j)))/(n-1);
dis=pdist(D);
dis=squareform(dis); %calculate the distances based on the other sujects.
dis_n=dis(... |
function [xf,vf] = move(xi,vi,T,u)
% this function computes dynamics of second order linear system with no damping
% along one direction when input u is applied for T second
% xi - initial position
% vi - initial velocity
% xf - final position
% vf - final velocity
% Copyright by Luca Schenato and UC Berkeley... |
clear all
close all
%% prueba gong
%load gong;
%refsig = y;
%delay1 = 0.1; %segs
%sig1 = delayseq(refsig,delay1,Fs);
%soundsc(sig1,Fs)
%tau_est = gccphat(sig1,refsig,Fs);
%tau1 = utils.tau_correlacion_cruzada(sig1,refsig,Fs);
%tau2 = utils.tau_gcc_phat(sig1,refsig,Fs,@rectwin);
%window_size = Fs;
%tau3 = utils.tau_... |
function [X,Z] = randnlatin(P,N)
% randnlatin Latin hypercube sample from standard normal distribution.
X = randn(P,N);
if nargout > 1
Z = X;
end
for i = 1 : P
X(i,:) = xxRank(X(i,:));
end
X = X - rand(size(X));
X = X / N;
X = xxNormInv(X);
end
% Subfunctions.
%************************... |
function B=sa_act(A,C,tol)
%SA_ACT Structural Assignment via Actuator Selection
%
% B = sa_act(A,C)
%
% For a given unsensed system:
% .
% x = A x, y = C x
%
% the function finds an input matrix B such that the resulting system
% characterize... |
%Toy Data set for Q1a and Q1b
X =[1,2;2,4;3,6];
Y = [1;2;3];
disp('Dataset..');
disp('X =');
disp(X);
disp('Y = ');
disp(Y);
disp('Q1a. linear regression MLE');
w = linreg_mle(X,Y)
disp('Q1b. linear regression posterior correctness');
disp('N (0, big)');
priormean = [0;0];
[PosteriorMean,PosteriorCovar] = linreg_pos... |
function os = itermsg(itermeth,tol,~,i,flag,iter,relres)
%ITERMSG Displays the final message for iterative methods.
% ITERMSG(ITERMETH,TOL,MAXIT,I,FLAG,ITER,RELRES)
%
% See also BICG, BICGSTAB, BICGSTABL, CGS, GMRES, LSQR, MINRES, PCG, QMR,
% SYMMLQ, TFQMR.
% Copyright 1984-2013 The MathWorks, Inc.
if flag... |
function [sys,x0,str,ts] = wahadlo_fun(t,x,u,flag,l1,l2,m1,m2,fi1,fi2,t0)
switch flag,
case 0
[sys,x0,str,ts] = mdlInitialzeSizes(l1,l2,m1,m2,fi1,fi2,t0);
case 2,
sys = mdlUpdate(t,x,u,l1,l2,m1);
case {1,3,4,9}
sys = [];
otherwise
error(['Un... |
classdef ResidualObliqueSplit < Split
% ResidualObliqueSplit fits a polynomial model and splits the points into
% two classes based on which side of the line they lie
properties %(Access = protected)
split_degree % degree for fitted polynomial
end
methods
function obj = ResidualObliqueSplit(options)... |
% function [msg_block] = linear_block_encode(n,k,msg_orig)
clc;
clear all;
close all;
n=7;
k=4;
msg_orig = [1 0 1 0];
[h1,g]=hammgen(n-k);
msg_block1 = msg_orig*g;
msg_block = mod(msg_block1,2)
% function [r] = linear_block_decode(n,k,r)
n=7
k=4
r= [ 1 0 1 1 0 1 0];
[h1,g]=hammgen(n-k);
p = [g(... |
mex -v qld_interface.cpp qld.f
|
%% use this script to fix / modify trials if exceptions are discovered after processing.
% Patient PSL003:
% Problem:
% Triggers did not register properly for 2 trials in this patient's data.
% The trials are 2 and 62 (indexed to the behavioral data, which captured all
% trials).
% Solution:
% Add empty (nan) ... |
function varargout = MetricTensGUI(varargin)
% MetricTens (Version: 1.0)-Created by Giovanni Esteves
% Department of Materials Science and Engineering
% North Carolina State University, Nov. 29th, 2015
% Email: gesteve@ncsu.edu
% Anytime this GUI is updated the version info at the very bottom that
% correlates to the ... |
function [tl,br]=xu_selectTiles(bwHimg,top_left,bottom_right,slidePtr,levelforRead,magHigh,magCoarse,magToUseAbove)
Para.thetaStep=pi/9;
Para.largeSigma=7;
Para.smallSigma=4;
Para.sigmaStep=-1;
Para.kerSize=Para.largeSigma*4;
Para.bandwidth=5;
Para.dis=10; % if the seeds is close to image borders less than 10 pixels, ... |
function relres=multigrid_2d_test
N=10;
nc=[4,3]; % the coarsest grid points
a=[1,3]; % domain size
% solve Dirichlet problem with vertex nodes
% homogeneous boundary conditions
% mesh is 0:n1+1 times 0:n2+1 but the boundary is not stored
% refinement:
% 0 1 ... n1 n1+1 level l... |
function [ dt ] = sphere_line_intersection( sphere_center, sphere_radius, line_point, line_direction )
separation = line_point - sphere_center;
ld_dot_ld = dot(line_direction, line_direction);
ld_dot_separation = dot(line_direction, separation);
sep_dot_sep = dot(separation, separation);
p = 2... |
function output = Mutate(point, vector, input, R_angle)
%To Rotate some angle along a given axis, relative to a reference point
r = input-point;
vector = vector/norm(vector); %normalized vector
mu = cross(vector, [0 0 1]);
mu = -mu/norm(mu);
angle = acos(dot([0 0 1],vector)/norm(vector)); %the angle between targ... |
% Subroutine for boundary layer calculation
% using Approximation method: Karman-Pohlhausen
% NOTE: *BL calculation only for laminar region
% *transition checked using Cebeci and Smith (1974) method
% which is an improvement of Michel's method
% *turbulent region is neglected
function [del... |
function [RMS, ZCR] = normalizeFeats(RMS, ZCR)
RMS = RMS/max(RMS);
ZCR = ZCR/max(ZCR);
end |
function [P] = softmax(z)
numerator = exp(z);
denominator = sum(numerator);
P = bsxfun(@rdivide, numerator, denominator);
end |
function [Anew,Wi,Wb,TSnew] = cleanOutput(A,Wi,Wb,TS,P,N,S,T)
% Re-order and normalize the output
% Order elements by the occurence of the maximal element
Anew=zeros(size(A));
% Column-wise for Wi
iP=zeros(1,P);
sP=zeros(1,P); % re-order normalization
for i=1:P
[~,iP(i)]=max(Wi(:,i));
sP(i)=norm(Wi... |
function [ mz,x ] = combCompNeighbours3(mz,x,ppmTol,flag)
%combCompNeighbours2 - this is a new version which is supposed to be better
%than the first version. It does this by merging the most likely ones
%before others; i.e. work on highly populated m/z bins first, and ignore
%ones which look most like noise.
percThr... |
clear all
close all
maxTime = 3810; %just a test number at the moment, to be amended
%% setup figure
fig = figure('name','Physical Environment','numbertitle','off');
%plot(bounds(:,1),bounds(:,2));
hold on;
grid on;
axis equal; %Axes set to equal for aestheic purposes.
%This sets the labels for the axes and title -... |
load("stack.mat")
a=eval(['frame',sprintf('%.3d',19)])
img = eval(['frame',sprintf('%.3d',6)]) |
function x = subsref(this, s)
% subsref Subscripted reference for model and systemfit objects.
%
% Syntax for retrieving object with subset of parameterisations
% ==============================================================
%
% M(Inx)
%
%
% Syntax for retrieving parameters or steady-state values
% ====... |
function plotAllNrnsAcrossTrials(outputPath, generalProperty, imagingData, BehaveData)
% extract behavioral data stats
[labels, examinedInds, eventsStr, labelsLUT] = getLabels4clusteringFromEventslist(...
BehaveData, generalProperty.labels2cluster, generalProperty.includeOmissions);
% 1. grab counts per trial
% grabCo... |
function [eltime] = GVL_1_1_7(m, n, r)
A = round(100*rand(m,r));
B = round(100*rand(r,n));
C = round(100*rand(m,n));
% [m, r] = size(A);
% [~, n] = size(C);
tic
for j = 1:n
for k = 1:r
C(:,j) = C(:,j) + A(:,k)*B(k,j);
end
end
eltime = toc;
end |
function features = img_to_features(dataset)
n_img = length(dataset);
width = 448;
img_block_sizes = [224 112 56 28];
%img_block_sizes = [224];
thm_block_sizes = [8 4 2 1];
n_bins = 8;
dir_edges = -pi:(2*pi/n_bins):pi;
gd_filter = conv([-1 1],fspecial('gaussian',[1 4],1));
tap_filter = [-1 0 1];
hog... |
function y = avener( x )
%avener Average energy of a signal
% avener(x) finds average energy of a signal x
% if x is a matrix, avener calculates average energy of each column
y=zeros(1,size(x,2));
for k=1:size(x,2)
y(1,k)=sum(x(:,k).*x(:,k))/size(x,1);
end
end
|
function tests = makeInputHandlerFcn_tests
tests = functiontests(localfunctions);
end
function test_input_equals_output(testCase) % must start with test
handler = makeInputHandlerFcn('free_response_robot');
input = 'hello world';
output = '';
while true
key_pressed = handler([], input);
... |
classdef NearestNeighbor < sbfsem.analysis.NeuronAnalysis
properties (Constant = true, Hidden = true)
DisplayName = 'NearestNeighbor';
end
methods
function obj = NearestNeighbor(neurons)
obj@sbfsem.analysis.NeuronAnalysis(neurons);
obj.doAnalysis();
end
function doAnalysis(obj, k)
if nargin < 2
... |
%种群初始化函数
%输入：
%NIND 种群规模大小
%N 个体染色体长度（这里为城市个数）
%输出：
%初始种群
function Chrom=InitPop(NIND,N)
Chrom=zeros(NIND,N); %用于存储种群
for i=1:NIND
Chrom(i,:)=randperm(N);%随机生成初始种群
end |
function [hit FA miss CR performance] = go_nogo_performance(path)
% Hit = 2
% FA = 3
% Miss = 6
% CR = 5
[session] = loadVoyeurH5_result(path);
result = [session{:,1}]';
hit = sum(result==2);
FA = sum(result==3);
miss = sum(result==6);
CR = sum(result==5);
performance = (hit+CR)/length(result);
end |
% IQdata_CloudLocations and Strct_Metadata should be loaded from the *.mat
% files for each of the smart manufacturing measurements. Run this after
% loading the *.mat file.
% After this script is run, the positions for each record will be held in
% the 'xpos' and 'ypos' variables. For example, IQdata(:,1) correspond... |
%
%Temporal Poincare section algorithm
%
%Parameters:
% input - The dataset (x, y, time) (array)
% n - Number of time step iterations (int)
% T - Time step (float)
function output = temporalPoincare(input, n, T)
output(1:2, :) = 0;
length = size(input);
curr = 1;
for i = 1:n
... |
%% Neural Networks Class Guide
%Objective: Analyze the change in the output of a single neuron when changing the weight, the
%bias and the transfer function.
%% 1)Run demo nnd2n1
nnd2n1; %undo comment to see the output
%% 2) Study how the different values of weight, bias, transfer function and input p modify
%the o... |
%subroutine to compute, plot, and save histograms
function histogram(data,xrange,filename)
global figurepath
clf
h=axes;
hist(data,xrange);
set(h,'FontSize',25)
print('-deps',[figurepath,filename,'.eps']);
|
function divF = div3dFS(Fx,Fy,Fz)
% Subroutine for taking divergence of a vector field in 3D in fourier space
% Chiyu Jiang, Oct 9th, 2015.
global M N P Lx Ly Lz
divFx = Fx.*(1i*M).*(2*pi/Lx);
divFy = Fy.*(1i*N).*(2*pi/Ly);
divFz = Fz.*(1i*P).*(2*pi/Lz);
divF = divFx+divFy+divFz; |
% Matt McDade
% ANM 2
% HW 2 Problem #2
function hw_2
f = @(x) log(x^2 + 1);
fprintf('x = 1.3 h = 0.01:\n')
fprintf('\tCD2: %.8f \tFD2: %.8f\n', CD2(f, 1.3, 0.01), FD2(f, 1.3, 0.01))
fprintf('x = 1.3 h = 0.001:\n')
fprintf('\tCD2: %.8f \tFD2: %.8f\n', CD2(f, 1.3, 0.001), FD2(f, 1.3, 0.001... |
%--------------------------------------------------------------------------
%------------ Metody Systemowe i Decyzyjne w Informatyce ----------------
%--------------------------------------------------------------------------
% Zadanie 2: KNN i Naiwny Bayes
% autorzy: M. Zięba, A. Gonczarek, J.M. Tomczak, S. Zaręba
%... |
function root_id = get_root_id(G, child_id)
isRootId = G.RootIds(1,child_id);
root_id = child_id;
while ( ~isRootId )
root_id = get_parent_node(G, root_id);
isRootId = G.RootIds(1,root_id);
end |
function [Xpred, sigma_xx, sigma_yy, sigma_tt, NEES, t] = q1_ekf_nonlinear_obs(mu,sigma, xtrue, ztrue, t, g, T, rho_0, k_rho, Q, R)
NEES = [];
sigma_xx = [sigma(1, 1)];
sigma_yy = [sigma(2, 2)];
sigma_tt = [sigma(3, 3)];
Xpred =[mu];
mu_posterior = mu;
for i = 1:length(t)
sigma_xx = [sigma_xx, sigma(1, 1)];
... |
Fs=50;
T=1;
N=T*Fs;
t=(0:1/Fs:N)-N/2;
f=linspace(-Fs/N,Fs/N,length(t));
x=cos(pi/4*t);
X=fft(x);
figure()
subplot(3,1,1);
plot(t,x);
xlabel('t');
ylabel('cos(pi/4*t)');
subplot(3,1,2);
plot(f,abs(X));
xlabel('w');
ylabel('magnitude');
subplot(3,1,3);
plot(f,angle(X));
xlabel('w');
ylabel('phase'); |
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