text stringlengths 8 6.12M |
|---|
function [n1,val]=zerotest(y,m,w)
[m,n1]=min(abs(y-m));
if sum(w)==0
val=1;
else
val=w(n1);
end |
function hHst = makehist(PixRng,ImgD,histOfFreq,histFreq,histCoord)
%% histogram
hHst.f = figure('Name','Histogram','numbertitle','off',...
'position',histCoord);
hHst.ax = axes('parent',hHst.f);
hHst.br = bar(PixRng,nan(1,length(PixRng)),'parent',hHst.ax);
set(hHst.ax,'xlim',[PixRng(1) PixRng(end)],...
'yl... |
function analysis = initializeAnalysis(deltaT)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Newmark Transient Analysis
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% analysis parameters
beta = 1/4;
gamma = 1/2;
c1 = 1.0;
c2 = gamma/(beta*deltaT);
c3 = 1.0/(beta*deltaT*deltaT);
a1 = (1.0 - gamma/beta);
a2 = (deltaT)*(1.0 - 0.5*gamma/beta);
a3 ... |
function [ ] = completeInpaint( )
global input_puzzle_white
global input_puzzle_red
global try_again
global shrink_factor
% resize images for inpaint
flag=1;
resizeFactor=1;
while (flag == 1)
C = imresize(input_puzzle_red, resizeFactor);
B = imresize(input_puzzle_white, resizeFactor);
[r1, c1, d1] = size(C);
if ... |
% This is material illustrating the methods from the book
% Financial Modelling - Theory, Implementation and Practice with Matlab
% source
% Wiley Finance Series
% ISBN 978-0-470-74489-5
%
% Date: 02.05.2012
%
% Authors: Joerg Kienitz
% Daniel Wetterau
%
% Please send comments, suggestions, bugs,... |
function y=cubicspline3(f,x0,x)
%第三类周期边界条件下三次样条插值；
%x = linspace(-1,1,40);
%x所求点；
%y所求点函数值；
%x0 已知插值点；
%y0 已知插值点函数值；
%f_0左端点一次导数值；
%f_n右端点一次导数值；
% x0 = linspace(0,2*pi,20);
y0=feval(f,x0);
n = length(x0);
z = length(y0);
h = zeros(n-1,1);
k=zeros(n-2,1);
l=zeros(n-2,1);
S=2*eye(n);
for i=1:n-1
h(... |
% Calculates the total communication time if data is sampled at all 128*128
% antennas, and then sent to a subset of those antennas for computation.
% Once the data is in the subset array, the communication time is the same
% as for the original array. This is because the number of hops decreases
% by X, but the packet... |
x = (1:256);
subplot(2, 2, 1);
y = sin(0.1 * x) + 0.1*sin(10*x);
plot(x, y);
title('');
f = 1/3* [1, 1, 1];
x_tmp = [1, 2, 2, 3, 4, 4, 5];
y_tmp = [0, 0, 1/3, 1/3, 1/3, 0, 0];
subplot(2, 2, 2);
line(x_tmp, y_tmp);
F = freqz(f);
subplot(2, 2, 3);
plot(abs(F));
title('');
Y = conv(y, f, 'same');
subp... |
search_seq ='AATACAATTAAAT';
M=length(search_seq);
[header seqs]=fastaread('unique_IDS.fa');
shorter_seqs=cellfun(@(x)(x(2000:end)),seqs,'uniformoutput',false);
[shorter_seqs I J]=unique(shorter_seqs);
header=header(I);
trans_mat=[eye(M);eye(M)*2;eye(M)*3;eye(M)*4];
final_mat=[];
for i=1:M*4
fi... |
%% Examples of |odehybrid|
%
% This script contains numerous examples of using |odehybrid| to simulate
% continuous and discrete systems, from a simple example to more complex
% examples with non-vector states and logging, introducing all primary
% features of |odehybrid|. It's meant for viewing directly in MATLAB by... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% hessian.m %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% function h = mcs_hessian(i,k,x,x0,f,f0,g,G)
% computes the element G(i,k) of the Hessian of the loc... |
% testMatrix = [6,9,12,3;2,3,4,1;4,6,8,2;10,15,20,5];
testMatrix = [8, 10, 12;12, 15, 18];
[rows, cols] = size(testMatrix);
rowVect = zeros(1, cols);
colVect = zeros(rows, 1);
newColVect = zeros(rows, 1);
newRowVect = zeros(1, cols);
usable = 0;
%% get column vector (A)
for irow = 1:rows
for icol = 1:cols
... |
function varargout=roo2prop(varargin)
%ROO2PROP Convert from spectra to various optical properties.
% ROO2PROP converts spectral values to specified optical values.
%
% Z=ROO2XYZ(ROO, PROPS, CWF, WL) with size(ROO)=[M N ... O W],
% char array PROPS size [1 P] and row vector size [1 W], returns matrix Z
% ... |
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 ... |
function plotMUASpikeRatio(experiments,expType,StimArea,RespArea,channels)
%% By Mattia
Path = get_path;
parameters=get_parameters;
countAnimal=0;
GoodSpikes=[];
for n_animal = 1:length(experiments);
experiment=experiments(n_animal);
if ~isempty(experiment.animal_ID) && experiment.expression(1)==1 && strcmp(exp... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% BME777: LAB 1: Bayesian Decision Theory.
function [output1,output2]=lab1(FeatureX,Data,FeatureForClassification, LabelColumn)
% Get number of samples.
[ro,~] = size(Data);
% Select feature for classification (1 or 2).
SelectedFe... |
function [ Pq, Psi1, Psi2 ] = pairwise_beliefs_gmm_C4( y, x, h, gmm, X_MARG_DOM )
%PAIRWISE_BELIEFS_GMM Computation of approximate outward messages
% Detailed explanation goes here
%
% Created: Monday Sept 7, 2015
% inherited from 'factor_detect_approx_gmm.m'
% Modified: Tuesday Sept 15, 2015
% improv... |
function batch = select_optimal_batch(batch_size, soln, gradients, LB, UB, D, N, K, Y, varargin)
% g = vector of partial derivatives of the cost function w.r.t. a
% g = Q*soln + c;
p = inputParser;
p.addParameter('batch_method', 'probabilistic');
p.KeepUnmatched = true;
p.parse(varargin{:});
batch_method = p.Result... |
function [split_camera_tasks] = generate_split_camera_tasks_single_edge(...
connected_camera_matrix, camera_data, point_data,...
visibility_matrix, max_baseline_angle, max_split_cameras_per_edge,...
group_assignments, group_sizes, group_idx1, group_idx2)
[cams1, cams2] = find(triu(connected_camera_matrix, ... |
function [Lstar] = generate_low_rank_matrix(dynamic_sing_vals,p,inc,rank)
% U = eye(p);
% V = eye(p);
% ins_s = 0;
% temp_vec = linspace(10,1000,1000);
% for i =1:length(temp_vec)
% [U1,~,~] = svd(U(:,1:rank)*U(:,1:rank)' + randn(p)/temp_vec(i));
% [V1,~,~] = svd(V(:,1:rank)*V(:,1:rank)' + randn(p)/temp_vec(i)... |
function [ Data ] = angle_Velocity( Data, start_point)
%compute angle and velocity
initial = zeros(size(Data,1),length(start_point));
for i = 1:length(start_point)
initial(:,i) = Data(:,start_point(i)+1) - Data(:,start_point(i));
end
angle = initial(2,:) ./ initial(3,:);
velocity = initial(2:3,:);
start_point(:,len... |
function [f, df] = myFunNew(X0, x, y, sn)
if nargin == 0
clc; close all;
x = [-20:0.1:60]';
y = rand(length(x), 1);
n = length(x);
sn = 0.1;
X0 = [0.1 0.1 log([2.0 2.0])]';
end
if isrow(x)
x = x';
end
if isrow(y)
y = y';
end
a = X0(1);
b = X0(2);
l = exp(X0(3));
l2 = ... |
function [img1]=afcmclustering(IM1,nc)
[x y]=size(double(IM1));
data=reshape(IM1,[],1);
data_n = size(data, 1);
in_n = size(data, 2);
[center,member,obj_fcn]=fcm(data,nc);
U2=member;
maxU2 = max(U2);
m5=U2';
for i=1:1:nc;
index{i}=find(U2(i,:) == maxU2);
[u{i} v{i}]=size(index{i});
img{i}(1:data_n)=0;
f... |
%批量删除1280*720以外的图片
clear;clc;
Path = pwd; %pwd可获取当前工作目录路径
imagePath = strcat(Path,'\'); %路径后还要拼接\才正确
imageFiles = dir('*.png'); %读取目录文件下的所有图片文件
numFiles = length(imageFiles); %获取图片的数量
for i=1:numFiles
imageFile = strcat(imagePath,imageFiles(i).name);
image_data{i}=imread(imageF... |
function adjust_ipopt_opt(N,nbus,ngen,nbranch,nstorage)
A = regexp( fileread('ipopt.opt'), '\n', 'split');
A{2} = ['number_of_timesteps ' num2str(N)];
A{3} = ['number_of_buses ' num2str(nbus)];
A{4} = ['number_of_generators ' num2str(ngen)];
A{5} = ['number_of_lines '... |
function b=dilation(x)
function p=open(A)
alpha = K1*A;
beta = K2*A*alpha;
gamma = K3*A*beta;
p=(beta+gamma)/(1+alpha+beta+gamma);
end
global k1eff k2eff k3eff k4eff k5eff k6eff A EC1 EC2 EC3;
setParamshill3P2X7(x);
setAuxiliaryhill3P2X7();
Alow=0.1*10^-6;
Ahigh=10*10^-6;
A=Ahig... |
function SAME = compareImages(size1,vdim1,size2,vdim2)
SAME = true;
if any(size1(1:3)-size2(1:3))
warning('Image and mask sizes are not the same');
SAME = false;
end
if any(vdim1(1:3)-vdim2(1:3))
warning('Image and mask pixdims are not the same');
SAME = false;
end ... |
%% 2-RSGF-V
if (strcmp(cur_alg, '2-RSGF-V') == 1)
fprintf(' \n');
fprintf('*** Running 2-RSGF-V\n');
num_2RSGF_V = num_2RSGF_V+1;
else
fprintf(' \n');
fprintf('*** Running MD-SA-GF\n');
num_MD_SA_GF = num_MD_SA_GF+1;
end
if N_iter <= 1000
seed_val = data.seed+120;
else
... |
function dx = aofun(t,x)
global m w0 e a gamma E;
dx = zeros(2,1);
dx(1) = x(2);
dx(2) = -(w0^2*x(1) + 2*gamma*x(2) + a*x(1)^2 + e/m*E(t));
end |
%% Monte Carlo Integration Example 6
% We compute a double integral under a surface to find the volume. Again we
% check for convergence of the solution to verify we used enough samples.
% function from example 3
z = @(x,y) 3 + sin(x.*y).*cos(y.^2);
xa = 0; xb = 6; ya = 0; yb = 3;
% +----xa----+----xb
% | | ... |
function [ Sigma ] = my_covariance( X, X_bar, type )
%MY_COVARIANCE computes the covariance matrix of X given a covariance type.
%
% Inputs -----------------------------------------------------------------
% o X : (N x M), a data set with M samples each being of dimension N.
% each co... |
% ½»²æ²ßÂÔC£¬cross_tsp_c
function cnew=cross_tsp_c(c1,c2,n)
j1=ceil(n*rand);
j2=ceil(n*rand);
j3=min(j1,j2);
j4=max(j1,j2);
clear c3
c3=c2(j3:j4);
j5=ceil(n*rand);
k=1;
for i=1:j5-1
if(isempty(find(c3==c1(i))));
cnew(k)=c1(i);
k=k+1;
end
end
cnew(k:k+j4-j3)=c3;
k=k+j4-j3+1;
for i=j5:n
if(isempty... |
function [y_lms, y_rls, y_lms_dd, y_rls_dd] = TimeDomainCancelMod(r, z, pulse, N, Nps, sps, bits, bitsPerSym, eBW, delta, lambda_inv, SequenceLength)
MF = conv(r, pulse);
init_idx = findLoc(bits, bitsPerSym, SequenceLength, sps, Nps, r, z);
x = MF(init_idx:4:end);
%x = ... |
%Task 1 - Train
clear; clc;
load('train.mat'); %load training data
%pre-processing data
std_train_data = standardisation(train_data);
[M,N] = size(std_train_data);
%%for finding H matrix
gram_matrix = zeros(N,N);
h_matrix = zeros(N,N);
C = 10^6; %really large value for hard margin
threshold = 10^-4;... |
A = [1 2 3 4 5 6 7 8 9 0];
found = 0;
i = 0;
for i=1:10
if A(i) == 8
found = 1;
disp("found 8")
break
end
end
if found == 0
disp("no 8")
end
%%%%%%%%%%%%%%
found = 0;
i=1;
while ~found
if A(i) == 8
found = 1;
disp("found 8")
else
i = i+1;
end
end... |
function [error_test] = ...
testError(X, y, Xtest, ytest, lambda_vec, error_val)
% Given an array of lambda values and CV errors, finds the value of
% lambda which minimizes error_val and the correspond test error.
% Returns an array with test errors for each value of lambda.
%%%%%% finds value of lambda whic... |
clc
clear
info = audioinfo('author.wav')
[x, Fs] = audioread('author.wav');
delay_sec = 0.05;
N = 16000 * delay_sec;
% Difference equation
% y(n) = b0 x(n) + G x(n - N)
G = 0.8;
a = 1;
b = [1 zeros(1,N-1) G];
r = 0.9; % pole radius
% Pole-zero plot
figure(1)
zplane(b, a)
title('Pole-z... |
clear;clc;close all;
timer = 0;
if timer==2
tic
end
tt =-40;
original_RGB = imread('10.jpeg');
original_YUV = rgb2ycbcr(original_RGB);
width = size(original_RGB,1);
height = size(original_RGB,2);
if ~timer
subplot(2,3,1);
imshow(original_RGB);
title('original');
subplot(2,3,2);
imshow(origina... |
function [ fibers_p, deg ] = OrientedNetworkPare(orient, fibers, num_nodes, str )
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
abs_min_deg = 6; % absolute minimum degree for network
fibers_pared = [];
node1 = fibers(:,1);
node2 = fibers(:,2);
for m = 1:num_nodes
deg(m) = sum... |
function [] = plotData(data, dataTitle,col, type)
%Extracting color channels
switch type
case 'mean'
plotMeanIntensity(data, dataTitle, col);
case 'threshold'
%We use col here as the cutoff for
plotThresh(data, dataTitle, col);
end
end
function [] = plotThresh... |
function nameTXT = toTXT(XYZ, outputName, folderName)
%TOtxt - takes an Nx3 matrix and outputs an txt coordinate file
%
%Syntax:
%
% nameTXT = ejovo.fn.totxt(XYZ, outputName, folderName, atomName)
%
%Inputs:
%
% XYZ - an Nx3 matrix of XYZ coordinates
% outputName - the name of the output file
% ... |
function mu = mu_t(data, phi, a_0, b_0, Sigma, d, k)
sum_n = data' * phi;
mu = zeros(k, d);
for j = 1:k
x = (a_0(j) * inv(b_0(:,:,j)) * sum_n(:,j));
mu(j,:) = Sigma(:,:,j) * x;
end
|
x = zeros(1,100)
for i= 1:length(x)
x(i)= power(i,2)
end
save('file','x')
|
% compile_sfm_chanvese
%
% compiles sfm_chanvese_mex
disp('Compiling sfm_chanvese_mex...');
mex sfm_local_chanvese_mex.cpp llist.cpp energy3c.cpp lsops3c.cpp
disp('Compilation complete.');
disp('');
|
%画图
function plotdata(X,y)
figure;
hold on;
pos = find(y == 1); %计算正项
neg = find(y == 0); %计算负项
plot(X(pos,1),X(pos,2),'k+','LineWidth',2,'MarkerSize',5);
plot(X(neg,1),X(neg,2),'ko','MarkerFaceColor','y','MarkerSize',5); |
function [A_bas,A_val] = get_eig_basis_3(A)
[A_vec,A_val] = eig(A);
A_bas = zeros(3,3,3);
for ii = 1 : 3
A_bas(:,:,ii) = A_vec(:,ii) * A_vec(:,ii)';
end
end |
function [auc_val, auc_p,varargout]=slidingROC(stim, nostim, varargin)
% [auc_val, auc_p,varargout]=slidingROC(stim, nostim, [boots, alph])
% takes 2 matrices , stim & nostim, of equal number of columns.
% using ROC analysis (see auc.m)
% returns a vector whose length is the column width of stim
% # of columns must b... |
function particlePositions = icyParticleInSelectedFrames( xlsFileName, frames )
% icyParticleInSelectedFrames is a function that extract icy spot detection results into a
% strcuture array
% Input:
% (1) Xlsfilename: file path with file name.
% (2) Frames: frames for extracting particle locations. input [] if applyin... |
function [ilat_lim, lat_limits, h, coastlat,coastlon] = plotmap(lat,lon,latlim,maps,docbar,cbarPosition,icmap)
% plot the coast line in a limited latitude
absdlat = abs(abs(lat)-latlim); % |dlat|
ilat_lim = find(absdlat==min(absdlat));
lat_limits = [lat(ilat_lim(1)) lat(ilat_lim(2))];
switch maps
case 1... |
function [aafA, aaafB, aafC, aafE ] = BuildingTemperatureSystemMatrices( afVentilationMassFlow )
%
try %
%
BuildingTemperatureSystemMatrixOccupancyTestMatrixNonAdiabatic;
%
aafA = Ac_room;
aafB = Bc_room;
aafC = zeros(1,size(aafA,2));
aafC(1) = 1;
aafE = Ec_room_r;
%
catch exception
... |
close all;
clear;
clc;
cols = ['r','b','k','g','y','c','m','r','b','k'];
for p = 1:10
x = 0:0.01:1;
y = (1 - abs(x) .^ p).^(1/p);
plot(-x, y, cols(p));
hold on;
plot(x, -y, cols(p));
plot(x, y, cols(p));
plot(-x, -y, cols(p));
end
for i = 1:10
h(i) = plot(NaN,NaN,cols(i));
end
legend(h, 'L1','L2','L3','L4','L5','... |
function halfwayBreak(wPtr,b)
global params;
halfwayMsg = sprintf('You are halfway through the block!', (b-1), params.blockVars.numBlocks);
getExpter = sprintf('Press space to continue with this block');
Screen('TextSize', wPtr, params.textVars.size);
Screen('TextColor', wPtr, params.textVars.color);
Screen('TextBac... |
function [mag,phi,mag0]=compare_eigvec(e0,e1)
%compare_eigvec
%
%[mag,phi,mag0]=compare_eigvec(e0,e1);
%Gives the magnitudes and phase-angle for
%eigenvectors. mag is the difference in magnitude
%phi is phase difference and mage0 is magnitude of
%reference vector e0.
%@(#) compare_eigvec.m 1.1 96/08/21 14:00:... |
function hash = hash_recurse(inArr, returnStr)
%HASH_RECURSE (ps-utils): MD5 hash arrays, handles cell/struct recursively
% hash = HASH_RECURSE(inArr)
%
% hash is a 16-element vector of uint8 values
% returnStr: bool (default false): if true, return a 16char hex str. If false, return 16-byte array
%
%
% ... |
function st_sig=get_st_sig(trans_obj,field)
st=trans_obj.ST;
if isempty(st)
st_sig={};
return;
end
st_sig=cell(1,numel(st.Ping_number));
nb_samples=numel(trans_obj.Data.get_samples);
[~,N]=trans_obj.get_pulse_length;
N_st=N(st.Ping_number);
idx_r_st=st.idx_r-N_st;
idx_r_et=st.idx_r+N_st-1;
for ii=1:numel(st... |
clear; clc;
data = readPoints('points3D.txt')';
custom_box = [1 1 0; 1 -1 0; -1 -1 0; -1 1 0; 1 1 2; 1 -1 2; -1 -1 2; -1 1 2];
% Ransac routine
[p_best, n_best, ro_best, X_best, Y_best, Z_best, error_best] = ransac_cus(data, 400, 10, 2, 40);
% Get rotation matrix and translation created box
rot_mat = generate_rotatio... |
function [length1, direction, chosen_vertices] = cell_axes(l,C,V)
%Calculates axial direction based upon distance between furthest vertices.
vertex_list = C{l};
nk = length(vertex_list);
A = -inf*ones(nk);
for i = 1:nk
for j = 1:i-1
A(i,j) = norm(V(vertex_list(i),:)-V(vertex_list(j),:));
end
end
le... |
function [ res ] = T1( G,n )
res = 1;
temp = 0;
for i=1:n
for j=1:n
temp = temp + G(i,j);
end%for
if (temp==0)
res = 0;
%return;
end%if
temp = 0;
end%for
end%T1 |
classdef FileIterator < each.iterators.Iterable
%FILEITERATOR Files Iterator
% Iterator for looping over each file in a directory
%
% Example, a standard FOR loop:
%
% for i = X
% ...% Loop Body
% end
%
% We can think of it as the equivalent loop:
%
% sz = size(X);
% numLoops = prod([sz(2:end)])... |
I=csvread('1010.csv',11,2);
[m,n]=size(I);
avg_temp=0;
sum_temp=0;
max_temp=0;
for x=1:4
avg_temp=0;
sum_temp=0;
for i=1:m
for j=1:n
sum_temp=sum_temp+I(i,j);
end
end
avg_temp=sum_temp/(n*m);
for i=1:m
for j=1:n
if(I(i,j)<avg_temp)
I(i,j)=avg_temp;
end
end
end
en... |
% Demo for aggregate channel features object detector on Caltech dataset.
%
% See also acfReadme.m
%
% Piotr's Computer Vision Matlab Toolbox Version 3.40
% Copyright 2014 Piotr Dollar. [pdollar-at-gmail.com]
% Licensed under the Simplified BSD License [see external/bsd.txt]
%% extract training and testing image... |
function [filter_pts95,filter_pts50]=parfor_gridpoints(app,pt_idx,uni_dpa_index,step_size,cell_all_dpa,cell_75km_dpa)
tic;
%%%%%%Check for grid points
file_name_50pts=strcat('filter_pts50_',num2str(uni_dpa_index(pt_idx)),'_',num2str(step_size),'km.mat');
file_name_95pts=strcat('fil... |
function [ ] = Run_DCE_Perfusion( Subject_name, Subject_Path, Sim_Struct, PefusionOutput, Verbosity )
%Run_DCE_Perfusion Run Full DCE Perfusion Analysis
display('---------------------------------------------------');
display('-I- Started Run_DCE_Perfusion execution at:');
c = clock;
disp(datestr(datenum(c(1),c(2),c(3)... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright 2010 - 2015 Moon Express, Inc.
% All Rights Reserved.
%
% PROPRIETARY DATA NOTICE:
% The data herein include Proprietary Data and are restricted under the
% Data Rights provisions of Lunar CATALYST Space Act Agreement
% No. SAAM ID#... |
function cur(n1,n2,val)
% cur.m:
% Add stamp for current source to the global circuit representation
% ELEC4506, Lab-2
% Author: Nathan Lavoy
% Date: October 3rd, 2018
%--------------------------------------------------------------------------
% define global variables
global b;
if (n1 ~= 0)
b(n1) = b(n1) + v... |
function [s] = sum_funct(V)
s = 0;
n = input("Introduceti n");
v1 = V(V < n);
for i = v1(mod(v1, 2) == 1)
s = s + i;
endfor
endfunction
|
clc
clear
close all
%% input arguments
d=4;
n=20;
TRr=5;
SR=0.81;
NR=0.1;
tnsr=TR_rand(n*ones(1,d),TRr*ones(1,d));
%% sampling
P=sampling_uniform(tnsr,SR);
%% adding sparse noise
tnsr_noise=noise_sparse_P(tnsr,P,NR,1);
E=tnsr_noise-tnsr;
%% solve problem via ADMM
[x,y,RC,run_time]=RTRC(tnsr_noise,P,10^-2,false);
%% eva... |
classdef task < handle
%TASK is a handle container for task objects for NIDAQ
% If task is aborted/cleared before completion, the lines in use will
% be in an unknown state!
properties
UserData; % Anything
end
properties(SetAccess=private)
name; % Name ... |
function train2MM()
[f,y] = sampleDetector(@detector1,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_2mm_1.mat' f y;
beta = logist2(y',f');
save 'beta_2mm_1.txt' beta -ascii;
[f,y] = sampleDetector(@detector2,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_2mm_2.mat' f y;
beta = logi... |
function t =Acq(V,c)
% computes an estimate of the trial at which conditioned responding began
% V is the cumsum of poke elevation scores (# pokes during CS minus
% # pokes during immediately pre-CS interval of same duration). c is the
% decision criterion (amount by which cum rec must enduringly rise above
% minimum i... |
function [ output_vec ] = Update_Pos_Delay( delay, input_vec )
%UNTITLED6 Summary of this function goes here
% Detailed explanation goes here
output_vec = zeros(size(input_vec));
output_vec(1 : delay ) = input_vec(end - delay + 1 : end );
output_vec(delay + 1 : end ) = input_ve... |
%Does a compound contour plot over saved creep sweeps, displaying both
%different time averaging and different force contours
clear all;
ramptimevec = [10 15 20];
Tvec = [ 0 1 10];
etavec = logspace(-1,0,5);
alphavec = logspace(-1,0,5);
stylevec = {'-','--','-.'};
colourvec = ['r','b','k','g','y','m','c','r','y','m','c... |
ca;clear;clc;
%% define animate
%%% videos
% th_r_arr = 0:60; th_p_arr = zeros(1,length(th_r_arr)); th_y_arr = th_p_arr; th_b_arr = 45+th_p_arr; vname = 'roll'; ii = 1;
% th_p_arr = 0:-1:-15; th_y_arr = zeros(1,length(th_p_arr)); th_b_arr = 45+th_y_arr; th_r_arr = th_y_arr; vname = 'pitch'; ii = 2;
% th_y_arr = 0:25;... |
clear all
close all
% Load two speech waveforms of the same utterance (from TIMIT)
[fname,fpath]=uigetfile('*.wav'); %selection du fichier audio a ecouter
[d1,sr]=audioread([fpath,fname]);
[fname,fpath]=uigetfile('*.wav'); %selection du fichier audio a ecouter
[d2,sr]=audioread([fpath,fname]);
% Listen to ... |
function res = dmcSim(varargin)
% res = dmcSim(varargin)
%
% DMC model simulation
% Ulrich, R., Schröter, H., Leuthold, H., & Birngruber, T. (2015).
% Automatic and controlled stimulus processing in conflict
% tasks: Superimposed diffusion processes and delta functions.
% Cognitive psychology, 78, 148-174.
% Code a... |
function pchoice = GetPChoice(k,sir,ldr,delay,realchoice)
% By Chabris/Laibson 2008 (Likelihood function defined)
% We calculate the likelihood of the data (real choice) which either
% takes value 0 or value 1 (immediate or delayed reward respectively)
% via the logit functions on the right hand... |
function [ p_value, h ] = smk_freq_KTST(cfg,TF1,TF2)
% smk_freq_KTST performs kernel two-sample test for the giving two time-frequency
% representation of MEG data and it plots the topographic map of significant
% channels if needed.
%
%
% TH: As pointed out in nathan's email, convert the function to fieldtrip's
% st... |
function out = simp3D(func,a,b,c,d,e,f,NX,NY,NZ)
% © Whayne Padden and Charlie Macaskill 2008
% The University of Sydney, Sydney, Australia
% function out = simp3D('func',a,b,c,d,e,f,NX,NY,NZ)
% func(x,y,z) returns the 3D function to be integrated at argument x, y and z.
% a and b are x limits of integration, ... |
clc
clear all
%% Monoharmoniczny
f1 = 15;
f2 = 100;
A = 1;
B = 0.5;
t = 0:0.0001:1;
Fs = 10000;
y1 = A*sin(2*f1*pi*t);
%% Wykladniczo malejacy
X0 = 10;
alfa = 1;
y3 = 10*ones(1, length(y1))
while abs(y3(500)) > 5 % warunek na wygluszenie po 0,5 sekundy
y2 = wykladniczy_malejacy(t, X0, alfa);
y3 = y1.*y2... |
function filter_bottom(trans_obj,varargin)
% input parser
p = inputParser;
addRequired(p,'trans_obj',@(x) isa(x,'transceiver_cl'));
addParameter(p,'FilterWidth',10,@isnumeric);
parse(p,trans_obj,varargin{:});
results = p.Results;
bot_data = trans_obj.get_bottom_idx();
% filter the bottom
%bot_data_filt=round(filter2... |
% determine c++ dimension vector
% appropiate for write out as in cmmfile.h
% e.g. via cmm_write_header(f, t, s)
function s = cmm_dim(data)
if isscalar(data) || ischar(data)
s = [];
return
end
s = size(data);
l = length(s);
if s(1)==1 && l==2
s = s(2);
return
end
if l... |
%George Mendez
function comp = leastSQL(X,Y)
%use these points to plot
%X = [1 2 3 4];
%Y = [1.5 1.6 2.1 3];
%Vectorization
[m,n] = size(Y);
sumxy = X*Y';
sumx = sum(X);
sumx2 = 0;
sumy = sum(Y);
%finding the sum of x squared
for i = 1:n
sumx2 = sumx2 + (X(1,i)*X(1,i));
end
%defining our line
... |
alpha = 0.1;
watermark = uint8(randi([0,1],32,32));
embed = ss_embed(alpha);
detect = ss_detect(0, alpha, 1024);
originalImage = "lena_gs.png";
watermarkedImage = "wtma.bmp";
im = imread(originalImage);
watermarked = embed(originalImage, watermark);
imwrite(watermarked, watermarkedImage);
[res, wps, sim] = detect(o... |
function [EEG] = Artifact_removal(EEG, epoch_boundary, ar_rm_from_ch, mwpp_thld, tstep_thld, set_name, output_suffix, output_folder_cur)
EEG = pop_artmwppth( EEG , 'Channel', ar_rm_from_ch:EEG.nbchan, 'Flag', [ 1 3], 'Threshold', mwpp_thld, 'Twindow', epoch_boundary, 'Windowsize', 200, 'Windowstep',...
50 ); % G... |
function p = gammap(q,a)
%GAMMAP Gamma distribution function.
% GAMMAP(Q,A) is Pr(X < Q) where X is a Gamma random variable with
% shape parameter A. A must be scalar.
%
% See also GAMMAQ, GAMMAR.
% GKS 2 August 1998.
if a < 0, error('Gamma parameter A must be positive'); end
p = gammainc(q,a);
k = find(q < 0);
if... |
function [ GC ] = GeneralizedCostMatrix( C, alpha2, lt, demand, k1, k2 )
% According to cost matrix C and other parameters, use objective function 2
% to generate generalized cost matrix GC.
spaceNodeNum = size(C, 1);
T = size(C,3);
GC = k1*C; % Generalized arc cost matrix.
for i2 = 2:spaceNodeN... |
function [Itinerary,Probability,RouteChoiceRelatedPro] = ItineraryExtract(O,D,TapTime,LoopPath,PathIndex)
%UNTITLED2 此处显示有关此函数的摘要
% 此处显示详细说明
global PathLineInf UpAccessTimeParameter UpEgressTimeParameter DownAccessTimeParameter DownEgressTimeParameter...
UpDelayboardingParameter DownDelayboardingParameter ... |
function [] = lookpc()
for i=1:10
A=rand(i*100,1);
B=rand(i*100,1);
C=sin(B.^2);
D=cos(A+C);
M=[A,B,C,D];
% D=[];
% for j=1:size(M,2)
% D=[D,M(:,j)/norm(M(:,j))];
% end
try
kpc(M,0.05)
catch ME
ME
end
end |
function [css_binary_prob] = binary_cssi(css_images)
num_of_images = length(css_images);
css_image_model = ones(100,200);
for i = 1 : num_of_images
x_range = css_images(i).zero_crossings;
y_range = repmat(css_images(i).sigma,[1 length(x_range)]);
for j=1:size(x_range,2)
css_image_model(100-floor... |
% For computation define as function of 1 vector variable
F.f = @(x) 100.*(x(2) - x(1)^2).^2 + (1 - x(1)).^2; % function handler, 2-dim vector
F.df = @(x) [-400*(x(2) - x(1)^2)*x(1) - 2*(1 - x(1));
200*(x(2) - x(1)^2)]; % gradient handler, 2-dim vector
F.d2f = @(x) [-400*(x(2) - 3*x(1)^2) + 2, -400*x(1)... |
#include "java_util_Hashtable_Entry.h"
const struct clazz *base_interfaces_for_java_util_Hashtable_Entry[] = {};
struct clazz class__java_util_Hashtable_Entry = {
DEBUG_GC_INIT &class__java_lang_Class, 999999, 0, 0, 0, 0, &__FINALIZER_java_util_Hashtable_Entry ,0 , &__GC_MARK_java_util_Hashtable_Entry, 0, cn1_class_... |
function Sc = symmxcell(mxcells)
n = length(mxcells);
Sc = cell(size(mxcells));
for i=1:n
Sc{i} = symmxstack(mxcells{i});
end |
% initTrackingParams.m
%
% Sets up initial tracking parameters for tracking algorithms.
% Also initializes variables. Users shouldn't normally need to edit
% this file, except the starting boundingSize.
%
% JSB 11/2010
function trackingParams = initTrackingParams()
global trackingParams; % Tracking P... |
function y = gmode(x)
%GMODE Mode(s) of a grouped sample.
% In some scientific works, once the data have been gathered from a
% population of interest, it is often difficult to get a sense of what
% the data indicate when they are presented in an unorganized fashion.
% Assembling the raw data into a meaning... |
fs=32;
n=0:1:fs;
y=sin(2*pi*n/fs);
subplot(3,2,1);
stem(y);
ylabel('Amplituda');
xlabel('Numer probki');
title('Re(y)');
axis([-inf inf -inf inf]);
subplot(3,2,2);
stem(imag(y));
ylabel('Amplituda');
xlabel('Numer probki');
title('Im(y)');
y1=2*fft(y)/fs;
subplot(3,2,3);
stem(real(y1));
ylabel('Amplituda');
xlabel('Num... |
function [r2p, dbv, oef, dhb] = ase_qbold_3d(nii_name,start_tau,delta_tau,end_tau,nii_out)
% nii_name: Z-averaged ASE dataset
% start_tau [ms] value of tau for first volume
% delta_tau [ms] tau step size
% set end_tau [ms] ... value of tau for last volume
% nii_out ... output nifti's and save figs? 1=Yes,0=No
%% Load... |
%% error distance
function distance_error = S_error(a,b,Sd)
[r,~]=size(b);
distance_error=zeros(1,r);
for i= 1:r
m=dist(a,b(i,:));
distance_error(1,i)=m+randn(1,1)*Sd;
% distance_error(1,i)=m*(1+randn(1,1)*0.01);
end
end
|
function [model, b, free_variables, objective_const_term] = QP_Convert_to_Standard_Form(model)
% ==================================================================================================================== %
% QP_Convert_to_Standard_Form(model):
% This function takes as input the data of an LP in the following ... |
close all
filename = 'ped1_prediction6_train.txt';
delimiterIn = ',';
headerlinesIn = 1;
A = importdata(filename,delimiterIn,headerlinesIn);
train1 = [];
id = 1;
for k = [1,4]
train1(:,id) = A.data(:,k);
id = id + 1;
end
train1 = train1(1:36000,:);
filename = 'ped1_prediction6_test.txt';
delimiterIn = ',';
headerline... |
% needs to be taken as an input parameter
format compact
disp('----------------------------------------------------------------------------------------')
disp('The following parameters are critical for the')
disp('proper representation of your tokamak. Please make sure they have been correctly defined ')
disp('BEFORE ... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.