text stringlengths 8 6.12M |
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function class = algorithm(sig1)
X = [real(sig1(1:200)), imag(sig1(1:200))];
E = evalclusters(X,'linkage','silhouette','KList',[4,8,16,32,64]);
plot(E)
if E.OptimalK==4
class = 1;
elseif E.OptimalK ==16
if(abs(hos(sig1,2,0))>0.45)
class=3;
else
if(abs(hos(sig1,4,0))>0.35)
class ... |
function [ sW_v, nmax ] = psdSWMass( DREMass, k, uN, D_v )
%PSDSWMASS Return Particle Size Distribution based on
% Dense Rock Equivalent Mass
% Input: DREMass (g)
% k: Shape factor
% uN: Mode of particle size
% D_v: Vector of diamter sizes
% Output: sW_v: Vector of particle si... |
function [values_spec,n]=getval_spectra_All(P,Q,labelconditions2,label1,s,w,win_size)
n=([length(P.(labelconditions2{1}).(label1{w}){s}) length(P.(labelconditions2{2}).(label1{w}){s})...
length(P.(labelconditions2{3}).(label1{w}){s}) length(P.(labelconditions2{4}).(label1{w}){s})]);
for condition=1:length(lab... |
function [bgProb, bdCon, bgWeight] = EstimateBgProb(colDistM, adjcMatrix, bdIds, clipVal, geoSigma)
% Estimate background probability using boundary connectivity
% Code Author: Wangjiang Zhu
% Email: wangjiang88119@gmail.com
% Date: 3/24/2014
bdCon = BoundaryConnectivity(adjcMatrix, colDistM, bdIds, clipVal, geoSigma... |
function yVal = quadPolation(xPoint, yPoint, xVal)
% Function implementing the Quadratic Spline Interpolation
%
% Input:
% xPoint = given set of independent data
% yPoint = given set of dependent data
% xVal = given value of independent variable
%
% Output:
% yVal = interpolated appx. value of dependent va... |
function [UpperX, LeftY, RoiSize] = ConvertROIs(CenterX, CenterY, Options)
% UpperX, LeftY, RoiSize] = ConvertROIs(CenterX, CenterY, Options)
% inputs: The center of the ROIs in X and Y
% Options - a struct with the following fields regarding the
% referance stack and wanted ROIs ( = ? is default value... |
function rhs = matAssembleRightHandSide(obj)
z = obj.meshUnion.z;
rhs = eval(obj.SecondDiffCexact);
% rhs = -2*ones(size(x));
% Temprhs = diag(obj.meshUnion.J(:,1))*obj.meshUnion.cell.M * rhs;
% rhs = Temprhs;
% Tempdata = -pi^2/4*sin(-pi/2*obj.meshUnion.x);
% rhs = zeros(Np*K, 1);
% for i=1:K
% rhs((i-1)*Np+1:i*Np... |
function [f BlkIdx] = HashingHist(PCANet,ImgIdx,OutImg)
addpath('./Utils')
NumImg = max(ImgIdx);
f = cell(NumImg,1);
map_weights = 2.^((PCANet.NumFilters(end)-1):-1:0); % weights for binary to decimal conversion
for Idx = 1:NumImg
Idx_span = find(ImgIdx == Idx);
NumOs = length(Idx_span)/PCANe... |
% Inverted Pendulum Parameter File
% Physical parameters of the inverted pendulum known to the controller
P.m1 = 0.35; % Mass of the ball, kg
P.m2 = 2.0; % Mass of the beam, kg
P.ell = 0.5; % Length of the rod, m
P.g = 9.8; % Gravity, m/s**2
% parameters for animation
P.w = 0.02; % Width of th... |
function w = SGD(f, v, n, T)
w = zeros(1,T+1);
for i=1:T
x = ceil(rand * size(v,2));
w(i+1) = w(i) - n * f(x);
end
w = 1/T * sum(w);
end |
%% GRID SEARCH FOR SVM. DATA IS REBALANCED BY BORDERLINE SMOTE
%% Dataset, exploratory data analysis and Method
%There are 6497 entries (before removal of missing values and SMOTE), 12 physiochemical wine quality predictors and 1
%target value – the quality of the wine. Continues values would need
%to be normaliz... |
function [hfig,hax1,hax2,hax3,hplot1,hstem2A,hDottedConnection,hstem2B,hstem3] = createVIPAxaxisFigure(figtitle,expStemCallback,simCallback)
if nargin == 1
% Create figure
hfig = figure;
else
hfig = figure('Name',figtitle,'NumberTitle','off');
end
% Create axes
hax1 = axes('Parent',hfig,...
'Position',[0.0607... |
close all
clear
clc
source "./bawm_landmarks.m"
#robot pose
#Xr = eye(4);
Xr = v2t([1;2;3;0.1;0.2;0.3]);
## Z = zeros(15,1);
## Z(1:3,1) = [10;5;4];
## #RZ = eye(3);
## RZ = Rx(0.5)*Ry(0.6)*Rz(0.7);
## Z(4:12,1) = RZ(:);
## Z(13:15,1)= [1;1;1];
## Xl = transLand(Z, Xr)
## [e,Jrn,Jln]=landmarkErrorAndJacobian(Xr,Xl... |
function varargout = autoFormatFig(varargin)
% standardizes a figure to Ben approved specifications
%% parse inputs
fh = gcf;
recolor = true;
preset = [];
for i = 1:length(varargin)
arg = varargin{i};
if ishghandle(arg)
switch arg.Type
case 'figure', fh = arg;
case ... |
clc
x = [1 2];
y = [56.1 78.6];
%n = 3; % grado del polinomio
p = 1.5; % El polinomio se evalua en p (valor a hallar)
function suma = lagrange(x, y, p)
% Calcule P(p)
n = length(x) - 1;
suma = 0;
for k=1:1:n+1
ter_sig = (multiplique(k, n, p, x))*y(k);
suma = suma + te... |
function test_divnormpointwise()
test_onepixvalues();
test_manybandsize();
end
function test_onepixvalues()
ims(1, 1, 1) = 10; % three bands of a single-pixel image
ims(1, 1, 2) = 1;
ims(1, 1, 3) = 1;
r = 1;
s = 6;
expect(1, 1, 1) = 1; % avg=4, plus s=6, makes a denominator of 10
... |
classdef fullyConnected3D < nnet.layer.Layer
properties
OutputSize
end
properties (Learnable)
% Layer learnable parameters
Weights
Bias
end
methods
function layer = fullyConnected3D(outputSize,name)
layer.Name = name;
% Set lay... |
%Generate cars, start location and assign reward to the map
function map=Q_generateMap(map, hasCars, pNoCarOnRow, fixedStart)
if nargin==3
fixedStart=false;
end
global actionsRewards;
[sx, sy]=size(map.Grid);
if(fixedStart==false)
%set start position at random
map.Start=[sx... |
% XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX MAR_CRI XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
%
% Author : Mario Hartanto
% Date : Jan 24 2014
% Function : performs fuzzy inference using CRI
% Syntax : mar_cri(data_input, net)
%
% ensemble - FIS net structure
% data_input - input data, can have multiple colu... |
%% Demonstrate trust region methods
%% Setup data for the Rosenbrock function
p = problem2d('rosen');
region = [-1.2 -0.8 0.2 1];
x0 = [-1;0.5];
%% Setup data for Trefethen's wild function
% You should only execute code for one of these functions.
p = problem2d('chebfun_opt_manymin');
region = p.region;
x0 = [0; 0.6... |
%% decode l2 的期权数据
clear all; rehash;
% 输入是经过解码的level2数据，txt格式，按日存储
% 输出是Ticks类，可存成.m
% optionDataPath = 'G:\上海9002期权解码数据\';
% date = '20150207';
% path = [optionDataPath , date , '\'];
% path = 'G:\逗号分隔期权解码数据\';
path = 'W:\逗号分隔期权解码数据\';
filenames = dir(path);
for idt = 23 : length(filenames)
if filenames(... |
%
% ROMS Forcing Fields
% ===================
%
% These functions are used for preparing ROMS forcing NetCDF files.
%
%
% d_core2_frc - Driver template script showing how to create ROMS
% forcing NetCDF file(s) using ROMS metadata
% structure. The data source is the CORE 2 Gl... |
function h9_eqn = h9_eqn(L1,L7,theta3)
%H9_EQN
% H9_EQN = H9_EQN(L1,L7,THETA3)
% This function was generated by the Symbolic Math Toolbox version 7.0.
% 22-Oct-2018 17:33:25
t2 = cos(theta3);
t3 = sin(theta3);
h9_eqn = [0.0;(L1.*7.58692698884342e19+L7.*t2.*7.58692698884342e19-L7.*t3.*5.2272425937558... |
function [barPairSortingStructure, numPhases, epochsOfInterestFirst] = SortBarPairBarLocations(params, epochsOfInterestFirst)
if nargin<2
epochNames = {params.epochName};
epochsOfInterestFirstLeft = find(~cellfun('isempty', strfind(epochNames, 'L++')), 1, 'first');
epochsOfInterestFirstRight = find(~cellfu... |
function [f_1_0, B] = least_square_pond(found_partials)
% This function uses a least square to compute the inharmonicity B and
% the fundamental frequency (f_1_0) corresponding to the given partials.
% found_partials : the computed partials
n = size(found_partials,2); % number of partials
base = (1:n).'; ... |
syms x y z
eqn = cos(y)^2+sin(y)^2-z^2+z*z-5*y+6*x;
tic
simplify(eqn,'Steps',3);
toc |
clear,close all;
clc;
points = [245,508,117,592,238,455,335;410,386,321,275,230,214,161];
%%
%compute the rate from pixel to distances
P1 = [points(1,1) points(2,1)];
P2 = [points(1,2) points(2,2)];
Pixel_D = norm(P1 - P2,'fro');
Real_D = 300*sqrt(2);
global rate;
rate = Real_D / Pixel_D; %mm
%%
%get th... |
function J_out = eval_J(k,Jcoeffs,Jpowers,N)
% J_out = eval_J(k,Jcoeffs,Jpowers,N)
%
% Given a Jacobian matrix represented as a coefficients matrix and a powers
% matrix (see diff_wk_wrt_k), evaluate the jacobian at the point k (2-by-1)
J_out = zeros(N,2) ;
J_out(:,1) = Jcoeffs(:,1:N)'*(prod(repmat(k',size(Jpo... |
% Script for ME 106 Problem Set 5
% Problem 1)
% By Chiyu 'Max' Jiang, 03/06/2016
% Time Span:
tspan = linspace(0,20,1001);
t0 = 0;
% Solve 1st Order Diff Eqn Systems
[t,x] = ode45(@velocity,tspan,[0;0]);
% Plot
figure()
xlabel('X');ylabel('Y');title('Trajectory of Particle')
comet(x(:,1),x(:,2))
|
function [Y2, F2, B2, E2, r, A2] = oneStepBackMean(s, time, Pe, A0, F0, YDelta, D, r)
% oneStepBackMean One-step backward smoothing for point estimates.
%
% Backend IRIS function.
% No help provided.
% -IRIS Macroeconomic Modeling Toolbox.
% -Copyright (c) 2007-2017 IRIS Solutions Team.
%-------------------... |
% aggregate stats for each AS according to topology
function [data_as] = aggregate_as(data)
data_as{1} = data{1}+data{2};
data_as{2} = sum_as(data,3:7);
data_as{3} = sum_as(data,8:11);
data_as{4} = sum_as(data,12:14);
data_as{5} = sum_as(data,15:20);
data_as{6} = data{21}+data{22};
data_as{7} = data{23};
data_as{8} =... |
figure
scatter(1e3*dx*(freq_data.HM_y_max-(Ny/2)),1e3*dx*(freq_data.HM_x_max-(Nx/2)) );
ylabel('x-position [mm]');
xlabel('y-position [mm]');
set(gca,'YDir','reverse');
title('FWHM centre as a function of frequency');
for i = 1:Num_steps+1
txt = sprintf(' %i' ,freq_data.frequency(i)/1e3');
text(1e3*dx*(freq_dat... |
function [x, f] = calculatePDF2(sample, nPoints, normalize)
%intervallumok
s=(max(sample)-min(sample))/nPoints;
for i=1:nPoints
x(i) = min(sample)+(2*i-1)/2*s;
end
%minta elemeinek berakása az intervallumokba
f(1)=0;
for j=1:length(sample)
if sample(j)>=min(sample) && sample(j)<=min(sample)+s;
f(1)=f(... |
clear all; clc;
addpath(genpath([cd '\Codes']));
% Graphs
path_g = [cd '\Graphs'];
imprime = @(x) print( gcf, '-depsc2', [path_g filesep x]);
imprpdf = @(x) eps2pdf( [path_g filesep x '.eps']);
formataxis = @(x) set(x, 'Fontname', 'Times', 'FontWeight', 'normal', 'Fontsize', 19, 'Box', 'On', 'PlotBox... |
function new_q = projection_eval_q( q, normal, points )
% ABSTRACTING PLANE Hx FORMED BY <q, normal>,
% 1. Project points onto Hx
% 2. Find weighted-squared-distances from projected Hx_points to q
end
|
%% Use a network with 4 binary input elements,
%%4 hidden units for the R st layer, and
%% one output unit for the second layer.
conv = 0;
n = 0;
while (n <= .5)
epochcount = 0;
n = n + .05;
lrate = n;
conv = conv + 1;
disp(n)
data = [0 0 0 0 0
0 0 0 1 1... |
function FFPlotFreq(Outbreak_tot,whichcase,logo)
% FFPlotFreq(Outbreak_tot,whichcase,logo)
%
% Plots outbreak probability as function of Test Frequency and Compliance
% or Sensitivity.
%
% logo = 0: Absolute probability (maximum nomalized to 1)
% logo = 1: Log2(Absolute Probability)
% logo = 2: Ratio to Best
%
% load... |
%% Genertate a Gaussian Mixture Function(Protein)
N = 10;
M = 5;
radius = 5;
range = [-2*M,2*M,-2*M,2*M];
[X,Y] = Generate_Centers(N,M/2);
x1 = -2*M:0.1:2*M;
y1 = -2*M:0.1:2*M;
[x2,y2] = meshgrid(x1,y1);
G = Gaussian_Mixture(X,Y); % Fucntion what we want to reconstruct
%% Show the 2_D picture
figure
h... |
function obj = setHessianPattern(obj, hes_sp, sp_form)
% This function configure the sparsity pattern of the Hessian
% of the function
%
% The form of given sparsity pattern is determined by the input
% argument 'sp_form'. It can be one of the followings:
% 'MatrixForm': the sparsity pattern is... |
function T = repmatPMTK(T, sizes)
% repmatPMTK Like the built-in repmat, except repmatPMTK(T,n) == repmat(T,[n 1])
% T = repmatPMTK(T, sizes)
if length(sizes)==1
T = repmatC(T, [sizes 1]);
else
T = repmatC(T, sizes(:)');
end
|
% best pops why plots
%%
clear projFilters
projFilters = [pMatrixA(:,1:5)];
%
%
% projFilters = [pMatrixK(:,1:numEigsK) pMatrixH(:,1:numEigsH) pMatrixB(:,1:numEigsB)];
%
% projFilterMeans = mean(projFilters);
% projFilterStds = std(projFilters);
%
% projFilters = zscore(projFilters);
%
% projFilters = [pMatrixA(... |
function plotSolution(mesh,nodes,solution)
hold off;
N = length(mesh(:,1));
CAXIS([0.8 1.2]);
for iCell=1:N
n = nodes(mesh(iCell,:),:);
X = [ [n(1,1) n(2,1)] ; [n(4,1) n(3,1)] ];
Y = [ [n(1,2) n(2,2)] ; [n(4,2) n(3,2)] ];
C = ones(2)*solution(iCell);
sur... |
clc
clear
close all
load('data_1');
load('data_2');
Fs = 120 ; % sampling rate [Hz]
Ts = 1/Fs; % sampling period [sec]
t_end=0.2 ; % [sec]
t_countinues = 0:1e-4:t_end;
t_sampling = 0:Ts:t_end;
x_original = data_2;
x_sampling = data_1;
N = length(t_sampling); % number of samples
% x... |
%% snaps any state to the center of the appropriate cell in the current grid
function X_snapped = snapToGrid(X,grid_eps)
% X_snapped = truncate(X./grid_eps).*grid_eps + grid_eps/2;
grid_eps_mat = repmat(grid_eps,rows(X),1);
% why use truncate when fix is there?
% doesn't handle sign(0) properly! returns 0!!
% X_snappe... |
% SR_DEMO_BATCH
%
% Example script for super-resolving all images in folder in a batch mode
%
% Jia-Bin Huang
% Electrical and Computer Engineering
% University of Illinois, Urbana-Champaign
% www.jiabinhuang.com
% =========================================================================
% Environment settings
% =====... |
function o = clamp(in,lowerbound,upperbound);
if(nargin == 2)
if(length(lowerbound == 2))
upperbound = lowerbound(2);
lowerbound = lowerbound(1);
end
end
o = min(upperbound,max(lowerbound,in));
|
function B = opumbral(I,p)
[y, x] = size(I);
B = zeros(y,x);
for i = 1:y
for j = 1:x
if I(i,j) <= p
B(i,j) = 0;
else
B(i,j) = 255;
end
end
end
B = uint8(B);
end |
function E = electric_field(Pr,Tr, R, TX, RX,varargin)
%ELECTRIC_FIELD Retourne le champ electrique d'une composante multi-trajet
% Detailed explanation goes here
global beta G_TX P_TX;
if ~isempty(varargin)
D = varargin{1};
end
E = zeros(size(Pr,3),1);
%gamma = propagation_... |
function [output] = fact(n)
n = int32(n); % Screen out non-integers
%Do work
if (n > 1)
output = n * fact(n-1) ; %recursiion
else
output = 1; %end recursion
end
end |
function im(t,sc)
filename=sprintf('t%07d.dat',t);
tt=load(filename);
n=length(tt); n=sqrt(n);
tt=reshape(tt,n,n);
% tt=tt-mean(mean(tt));
imagesc((tt')); colorbar;
caxis(sc)
set(gca,'YDir','normal');
axis square
set(gca,'XTick',[1,n])
set(gca,'XTickLabel',{"0","2\pi"})
... |
clear all;
close all;
fs=1000;
f=50;
mida=0.1;
n=0:fs*mida;
y1=sin(2*pi*n*f/fs);
y2=sin(2*pi*n*f/fs+pi/2); % senyal desfasada 90º
figure(1);
% senyals y1 i y2
stem(n, y1);
hold on;
stem(n,y2);
hold off;
legend('y1(n)=sin(2pinf/fs)','y2(n)=sin(2pinf/fs + pi/2)'); grid;
% correlacio(y1, y2)
[c1,lags... |
close all;
clear all;
clc
x = [1 3 5 6];
y = [4 8 15 9];
polyfit(x, y, 1) % Doğrusal denklemin katsayılarını verir
|
% FactorProduct calcula el producto de dos factores
% C = FactorProduct(A,B) calcula el producto de dos factores, A y B,
% donde cada factor esta definido sobre un computo de variables con dimension dada
% La estructura del factor tiene los siguientes campos:
% .var Vector de variables en el factor, ... |
%Nhom 1
%53
%Pham Ba Tung
%B15DCDT221
Xmin=0;Xmax = 10
Ymin =0;Ymax = 10
detalX = 1
detalY = 1
i = Xmin
while i <= Xmax
i = detalX;
j = Ymin;
while j <= Ymax
j = detalY;
fprintf("6.1f" ,(i^2 + j^2) )
end;
fprintf("\n");
end;
|
% Given a (blended) Laplacian pyramid, starting from the smallest scale,
% expand it, then add this previous scale. Repeat this until we get to the
% original scale and this is the output
function [col_output] = collapse(lapl_pyr)
lapl_pyr_copy = lapl_pyr;
for i = length(lapl_pyr) : -1 : 2
% S... |
%% 使用的solve方法求解微分方程的解析解
clc, clear
syms x y % 定义符号变量
diff_equ = 'x^2+y+(x-2*y)*Dy=0';
dsolve(diff_equ, 'x')
% 此外，还有常微分方程组，齐次、非齐次常微分方程组
% 用时直接查 |
function [X_estimate,t_b_estimate,length_estimate]=GMTCPHD_estimation(weights_u, means_u,t_ini_u,length_u,Lscan,means_k_old_u,cardinality_u)
%Estimation for the GM-TCPHD filter
%We take the N highest peaks (according to the maximum of the cardinality) and report the mean of the trajectories at
%these peaks
%Author: A... |
image=[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;
0 0 1 1 1 1 0 0 0 0 0 0 0 0 0;% structure A
0 0 1 1 1 1 0 0 0 0 0 1 0 0 0;
0 0 1 1 1 1 0 0 0 0 1 1 1 0 0;% structure C
0 0 1 1 1 1 0 0 0 1 1 1 1 1 0;
0 0 1 1 1 1 0 0 1 1 1 1 1 1 1;
0 0 1 1 1 1 0 0 0 0 0... |
% for interface
figure(101);
nam = char('exper');
ht = uicontrol('Style','text', ...
'Position',[left1 bot4-0.2*bot14 wid1 1.5*height], ...
'String','Name data file',...
'BackgroundColor', roza);
hnam = uicontrol('Style','edit', ...
'Position',[left2 bbot4-0.2*bbot16 wid2+0.2 1.5*height], ...
'... |
function model = generate_model_lin()
function frequency = activation(potential)
frequency = potential;
frequency(frequency < 0) = 0.0;
end
function I = solution_by_input(model)
I = model.mu .* (model.potential .* model.Q + model.thr - model.frequency .* model.alpha ./ model.mu);
end
model.mu ... |
% Plot J_KIR against Kp using v_i
% vi_max = vi_max(2:2:end);
% vi_min = vi_min(2:2:end);
% K_p = K_p(2:2:end);
% Extract different parts of graph
K_p_oscillations = smooth(K_p(2253:end), 0.1,'rloess').*1e3;
K_p_top = smooth(K_p(1:740), 0.1,'rloess').*1e3;
K_p_bottom = smooth(K_p(1110:2248), 0.1,'rloess').*1e3;
vi_m... |
function [y] = funcderiv(a)
%this function returns value of derivative in point
y = 1.4 * cos(a) - 1.4 * a * sin(a) - 1/a;
end
|
function [fragments, frames] = dicom_encode_jpeg_lossless(X, bits)
%DICOM_ENCODE_JPEG_LOSSLESS Encode pixel cells using lossless JPEG.
% [FRAGMENTS, LIST] = DICOM_ENCODE_JPEG_LOSSLES(X) compresses and
% encodes the image X using baseline lossles JPEG compression.
% FRAGMENTS is a cell array containing the e... |
polynomialCoefficients = [10 -2 -1 1]; %Defines the polynomial 10 - 2x - x^2 + x^3.
startingPoint = 2;
tolerance = 0.0001;
iterationValues = NewtonRaphson(polynomialCoefficients, startingPoint, tolerance);
if (length(iterationValues) > 0)
PlotIterations(polynomialCoefficients, iterationValues);
end |
function [parts] = parts_push(parts)
if isempty(parts.trajectories)
return;
end;
parts.trajectories = cellfun(@(t, p) cat(1, t, p), parts.trajectories, num2cell(parts.positions, 2), 'UniformOutput', false);
end |
classdef EDF8 < handle
%UNTITLED Summary of this class goes here
% Detailed explanation goes here
properties(GetAccess= 'private', SetAccess= 'private')
%state vars
cur_state;
start_state;
desired_state;
%recorded vars
phi;
theta;
... |
clc, clear
load('/Users/jovo/Research/projects/papers/priority/ind_edge_classifier/data/BLSA0317_Count_Lhats.mat')
%%
%
AA=As;
for i=1:49
AA(:,:,i)=AA(:,:,i)+AA(:,:,i)';
end
A0=mean(AA(:,:,constants.y0),3);
A1=mean(AA(:,:,constants.y1),3);
eps=1/(10*constants.s);
params.lnprior0=log(constants.s0/constants.s);
... |
global MPI_COMM_WORLD;
load 'MatMPI/MPI_COMM_WORLD.mat';
MPI_COMM_WORLD.rank = 58;
Alluxio_Row_mv_version3;
|
function t = globalGridSearch(t, xyInitialize, gridSpacing, stressCutoff)
%xy = globalGridSearch(t, xyInitialize, gridSpacing, stressCutoff)
%this function imposes a grid on the bounding box and finds the position on
%the grid that minimizes stress for all nodes. It returns that position
%for each node.
%
%kd - ... |
%%% Autor: Francisco Rossi
%%% Materia: 86.54 - Redes Neuronales, Facultad de Ingeniería (U.B.A)
%%% +-+-+-+-+ +-+ +-+ +-+-+-+-+-+-+-+-+-+ +-+
%%% |G|U|I|A| |1| |-| |E|J|E|R|C|I|C|I|O| |4|
%%% +-+-+-+-+ +-+ +-+ +-+-+-+-+-+-+-+-+-+ +-+
%%% Temperatura critica en el modelo de Ising 1D
%% Cleaning
clear all;
close all;
c... |
function [tri_area] = get_TriArea(AB, AC)
AB_temp = [AB, 0]; % re-sizing AB to have dim = 3 for cross product
AC_temp = [AC, 0]; % re-sizing AC to have dim = 3 for cross product
Pgram_area = abs(cross(AB_temp, AC_temp)); % parallelogram area = ||ABxAC||
tri_area = max(Pgram_area/2); % triangle area = h... |
function [OE2PTBfit, PTB2OEfit,PTB2OE, maxreconstructionerror ] = sync2OeClock_trial(PDS, filenameE)
% SYNCOPENEPHYSCLOCK synchronizes the pdlaps PTB clock with open-ephys recording
% Inputs:
% PDS - PDS struct (or cell-array of PDS structs)
% filenameE - string (or cell-array of strings) path to OE event... |
function [b, have, want] = hPassFct1(Hhat, dimWeights)
[rows, cols] = size(Hhat);
have = rows;
want = dimWeights * cols;
b = rows >= dimWeights * cols;
end |
function []=DrawSnowSegment(sx,sy,l,angle);
%Drawing a segment of showflake
sl = l/( 2 + 2/sqrt(2));
ex = sx+sl*cos(angle);
ey = sy+sl*sin(angle);
DrawLine(sx,sy,ex,ey);
sx = ex;
sy = ey;
ex = ex+sl*cos(angle+pi/4);
ey = ey+sl*sin(angle+pi/4);
DrawLine(sx,sy,ex,ey);
sx = ex;
sy = ey;
ex = ex+sl*cos(angle+pi/4-pi/2);
ey... |
function[F V] = mergevertex(F,V,v1,v2,X)
%MERGEVERTEX - merges 2 vertices together
%by removing one vertex and have it's neighbors link to the new
%the other vertex
f1 = V(v1).f;
f2 = V(v2).f;
fboth = intersect(f1,f2);
f1only = setdiff(f1,fboth);
f2only = setdiff(f2,fboth);
... |
function [ u ] = u_gen( A, ind )
%u_gen Generate u matrix of combinations.
% Example:
% If A = 2 and ind = 1 : 4, then
% u = [0, 0; 1, 0; 0, 1; 1, 1].
% If ind is missing, then return full matrix.
if nargin < 2
ind = 1 : (2^A - 1);
end
u = de2bi(ind, A);
end
|
%% Description
% this code generates visiblity field for a target represented by a
% gaussian model
addpath('..\ASAP1','..\multi_target_tracking\','..\plotregion\');
addpath('..\multi_target_tracking\polytopes_2017_10_04_v1.9')
addpath(genpath('..\robot10.1'))
addpath(genpath('.\Matlab_Polygons_intersection\'))
addpa... |
function out = Laplace_unfold_BIDS(manual_masks,output_dir,quantitative_dir,labeldescription_fn,suppress_visuals)
% performs laplacian unfolding on the image of manually labelled structures
%
% INPUTS:
% manual_masks: BIDS directory containing manually labelled structures.
% This should contain the string 'label-HippUn... |
function [ t ] = absolute_scale( t, ground_truth, frame_id, lastframe_id )
%UNTITLED6 Summary of this function goes here
% Detailed explanation goes here
%% GT pose subject to first frame
true = [reshape(ground_truth(frame_id+1,:),[4,3])'; 0 0 0 1];
prev_true = [reshape(ground_truth(lastframe_id+1,:),[4,3])'; ... |
function []=exp4(facility,delta,windowtype)
% Experiment #4
% -------------
% For gaussian windows, do the resulting offsets depend on the window
% sigmas?
% Plot offsets versus a global sigma multiplier.
% As it turns out, the looks a lot like a step function with the
% limit as mult->0 selecting the largest of the t... |
function [rx_wave] = wave_awgn_channel(tx_wave,S,SNR)
%
% Function of the awgn channel of wave
%
%****************** variables *************************
% tx_wave : the wave at the exit of transmitter
% S : the power of symbol
% SNR : the signal-noise ratio (E_s/n_0)
% rx_wave : the wave at the entrance of receiver
% ... |
function diplayGraph(handles, coef)
if ~isempty(handles.Axes.Graph.Children)
delete(handles.Axes.Graph.Children)
end
if isempty(coef)
return
end
% Seperate the coefficients to get the numbers
coef = strsplit(coef{1},{',','\t',' '});
if i... |
function this = horzcat(varargin)
% A Comprehensive Guide to Object Oriented Programming in MATLAB
% Chapter 13 example cStar::horzcat
% (c) 2005 Andy Register
mismatched = varargin(~cellfun('isclass', varargin, mfilename('class')));
if ~isempty(mismatched)
error('MATLAB:UnableToConvert', ...
['Convers... |
%% %% Analysis of paralysis caused by muscle expression of HyCal receptor...
% & pan-neuronal HyPep
%% Pull data for analysis & sort for bar graph order.
% assumes 'data' folder in working directory
dataDir=fullfile(pwd,'data');
if ~exist(dataDir)
dataDir=uigetdir('C:\', 'Where are data?');
end
[fileList] = pullEs... |
%time_trigger_capturing example
T = 0.033; % Period of data capture
init_time = 1000*T*floor(t(1)/(1000*T));
buffer_idx = 1;
valid_idx = 0;
global_timer = tic;
for i=1:20
while((elapsed_time = toc(global_timer)) < i*T)
read_frame = 1;
while (read_frame)
if ((t(buffer_idx) >= init_time+1000*((i-1)*T... |
%test energy program
sphere
%z_test = [ rand rand rand];
ebs = 0.00001;
H_curva
%Hi is at 220th point
Fold = H_curvature(220,:);
derder = Derivative_Hi (x,v,nt,442,220,A_mat);
x(442,:) = x(442,:) + ebs*z_test;
H_curva
Fnew = H_curvature(220,:);
derderder=0;
for i_test = 1:3
derderder =derderder + z_test(i_test... |
% This script recovers saved annotations from a backup file and uploads
% them to the portal. Can be used to complement
% saveTrainingAnnotations2File.
clear all;
% clear all;
close all; clc; tic;
addpath('C:\Users\jtmoyer\Documents\MATLAB\');
addpath(genpath('C:\Users\jtmoyer\Documents\MATLAB\ieeg-matlab-1.8.3'));... |
clear
close all
%% ---可修改u mix和mix 是否合并所有人的总特征
for u = 2:28
name_mix_En = sprintf('ucd%03d_mixf6_En',u);
name_wake_En = sprintf('ucd%03d_wakef6_En',u);
name_deep_En = sprintf('ucd%03d_deepf6_En',u);
if u~= 4 && u~= 16
%% 以下分出训练集和测试集,合并熵作为特征
%% mix -----------... |
function [sibhfs,manifold,oriented] = determine_sibling_halffaces_tet( nv, elems, varargin)
%DETERMINE_SIBLING_HALFFACE_TET Determine the sibling half-faces.
% DETERMINE_SIBLING_HALFFACE_TET(NV,ELEMS,SIBHFS) Determines the
% sibling half-faces.
%
% SIBHFS = DETERMINE_SIBLING_HALFFACE_TET(NV,ELEMS)
% SIBHFS = DETE... |
clc
clear all
close all
f=50;
t=linspace(-20,20, 500);
sig= cos(2*pi*f*t);
rect_sig = sig > 0; % Half-Wave Rectification
figure
plot(t(rect_sig), sig(rect_sig));
grid on |
% animal
% slice
% import path
% experimenter
% notes
% check / insert animal
% check / insert slice
% insert new session
% import data
% go directly to new sketch
function NewSession(pb,src,event)
sexes = {'M','F','Unknown'};
strains = {'C57/BLK6','Other'};
figH = f... |
N = 16
fc_q = 1/4
fc_oc = 1/8
time = (0:N-1)
x = cos(2*pi*fc_q*time) + cos(2*pi*fc_oc*time)
C = [1, -1.848, 1.000465]
% 補償項
y(1) = C(1) * x(1)
y(2) = C(1) * x(2) + C(2)*x(1)
% 做convolution的項次
for n = 3:N
y(n) = C(1) * x(n) + C(2)*x(n-1) + C(3)*x(n-2)
end
subplot(3,1,1);plot(time,x,'.-');title('sinusoid signal combin... |
% Crea la matrice di estensione al bordo inferiore di una immagine
%
% E = MATRIX_EXTEND_BORDERS_DOWN( D, EXT, M, N )
%
% D = dimensione della estensione al bordo inferiore
% EXT = stringa per il tipo di estensione al bordo inferiore
% 'e' = estensione pari
% 'o' = estensione dispari
% 'z' = zero padding... |
function c = modifiedfalsepos(f,xl,xu,max_iter,max_rel_err)
if(f(xl)*f(xu)>0)
fprintf('Invalid Input\n');
return;
end
xr=(xl+xu)/2;
x(1)=xr;
fx=f(xr);
N=2;
iter=2;
error=[];
x1=xr;
if(f(xr)*f(xl) > 0)
xl=xr;
else
xu=xr;
end
if(f(xr)~= 0)
while(1)
xr = xu + (-f(xu))*((xu-x... |
clear all
nInstances = 1000;
nVars = 25;
X = [ones(nInstances,1) rand(nInstances,nVars-1)];
w = randn(nVars,1);
y = sign(X*w + randn(nInstances,1));
flipPos = rand(nInstances,1) > .9;
y(flipPos) = -y(flipPos);
funObj = @(w)LogisticLoss(w,X,y);
fprintf('Running L-BFGS\n');
options = [];
%options.Met... |
function [ score ] = gameStatus( board, agentTurn )
[ x dummy ] = find(board == 0);
[ length dummy ] = size(x);
if length > 0
score = 5;
return;
end
if agentTurn == 22
[ x dummy ] = find(board == 2);
end
[ agentScore dummy ] = size(x);
agentScore = agent... |
function [ X ] = KM(M)
% data : cell array that contain location of landmark points. Each cell
% array should be 2xn matrix
% scf : cell array that contain feature representation of all landmark
%-----------------------------------------
% load house.mat
% data = data(1:2);
% scf{2} = [scf{2};scf{2}(1,:)];
% data{2} ... |
function [ TrainingData ] = ExpertSystem(Classifier, TrainingData)
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
x = -0.05:0.01:0.05; % for mesh
y = x;
[X, Y] = meshgrid(x, y);
Plus = 0; Minus = 0;
for i = 1:TrainingData.num
fprintf('%d/%d tra... |
function BB=templateMatching(I,template)
I = rgb2gray(I);
template = rgb2gray(template);
I = double(I);
template = double(template);
[height,width] = size(template);
every = filter2(template,I);
maxVal = max(max(every));
[y,x]= find(every == maxVal);
xmin = x - width/2;
ymin = y - height/2;
BB = [xmin ymin width heigh... |
%% LRA METAMODELLING: DEMONSTRATION OF BASIC USAGE
% In this example, a Low Rank Approximation (LRA) of the Ishigami function
% is computed and the LRA responses are plotted against the actual
% responses at a validation set.
%% 1 - INITIALIZE THE UQLAB FRAMEWORK AND CLEAR THE WORKSPACE
clearvars
uqlab
%%
% set th... |
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