text stringlengths 8 6.12M |
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function [lda, Sb, Sw, qda] = smithFigure(dataset);
% This function produces the `classic' plot of the Normal-Psychotic
% data of C.B. Smith's paper "Some examples of discrimination"
%
% Syntax: [lda, Sb, Sw, qda] = smithFigure(dataset);
%
% Inputs:
% dataset : string with the name of a dataset to be used,
%... |
function K = k_mean_cluster(point, k)
%K-mean clusturing - which take data as point and produce K cluster mid
%point
%input - all points and no of cluster (k)
%output - mid point of all k cluster reading
X = point;
m = length(X);
k = k;
K = zeros(k,size(X,2)) ... |
function lrt_make_rtw_hook(hookMethod, modelName, rtwroot, templateMakefile, buildOpts, buildArgs, buildInfo) %#ok<INUSL>
% AUTOSAR_MAKE_RTW_HOOK - This is the standard ERT hook file for the RTW build
% process (make_rtw).
%
% This hook file (i.e., file that implements various RTW callbacks) is
% called by RTW for syst... |
function [input_data, labels] = input_preprocess()
clear all;
clc;
myFolder = 'G:\Probe\Face Rec Workshop\Code\Data set';
filePattern = fullfile(myFolder, '*.jpg'); % Change to whatever pattern you need.
theFiles = dir(filePattern);
for k = 1 : length(theFiles)
baseFileName = theFiles(k).name;
fullFileName = fullfi... |
%testing script for the rotation handling functionality
imageid = 1454;
fprintf('-------------------')
p=squeeze(pred_new(:,:,:,imageid));
SM = new_pca_model(train_labels);
lalala = SM;
for i = 0
n = rotate_heatmaps(p,i);
img=imrotate(squeeze(eval_img(imageid,:,:)./255), i);
ROT = kron(eye(15),rotmat(i));
... |
%% Borrar y almacenar
% simulaciones_a_cargar=47:50;
%
% % c_sensor=1;
% % c_phi1=1;
% % c_phi2=2;
% % c_theta=1;
% % i=1;
% % c_antenas=1; %puede ser 2
% cantidad_realizaciones=35;
% % clusters_fijados=1;
% cd resultados
% for clusters_fijados=0:5
% for num=simulaciones_a_cargar
% num
% for e... |
% This function returns the alteration frequency for mutations and copy
% number data
function pathwayAlterations = findGeneAlterationFreq(metabolicPathways,...
studyMuts,studyCNA)
% This is a table with columns as cancer types and row as metabolic
% pathways
% get the genes involved in a metabolic pathway and re... |
% Calculate the predicted forces using the "validation" method, only for
% the Linearized Sigmoid method. This is used to 'make up' for not running
% the LinSig model on certain data sets originally.
%
% This function splits the force and image data into two sets. Use one set
% to calibrate the model (the Training D... |
load data_c3_2.mat
% Plot the original distribution
x = -2:0.1:14
y = gaussmf(x,[1 2])
z = gaussmf(x,[1 10])
plot(x,y)
hold on
plot(x,z)
xlabel("Guassian Mixture Model") |
clc;
clear all;
cd('D:\ternus_EEG\Raw data1\ternus-eeg');
load('chanlocs.mat');
load('erp_rmbase.mat');
%load('erp_rmbase2.mat');
load('erptimes.mat');
EM=permute(EM_rmbase,[2 1 3]);
GM=permute(GM_rmbase,[2 1 3]);
%% plot erp
EM_erp=squeeze(mean(EM,3));
figure;plot(times,EM_erp(:,28),'b-')
GM_erp=squeez... |
function [Y_int Phi_int]=rbfn_integral(Xc,X1,X2,W,k_i,basisfunction)
%calculates a line integral between X1 [x y] and X2 for a radial basis
%function with center Xc and prescaler k_i
%basis function may be 'gaussian' or 'polyharmonicspline'
%see rbf_integral for more
% Copyright Travis Wiens 2008
%
% Thi... |
%%%%%%%%% simu 和 mfun 结合,用3个一阶并行反应模拟
beta=50; %%%% Heat rate
R=8.314; %%% Universal gas constanet
xlow=[10 1 0.1 ]; %%% lower limit
xup=[400 30 .9 ]; %%% upper limit
x0=[1.2401381456564563e+002, 0.719456218222434e+001, 6.023432453252355e-001 ];
%% Loading data (so that it will only happen 1 time)
load Coal_... |
% Setup AE_TITLE, IP, port for your DICOM PACS
PACSAE='DCM4CHEE'; % PACS AE title
PACSIP='172.17.32.50'; % PACS IP number or Host-name
PACSPORT='11112'; % PACS port
|
%--------------------------------------------------------------
% Welcome to Getscriptall
%--------------------------------------------------------------
% SIMPLE ADDITION OF INTEGER PROGRAM:
%--------------------------------------------------------------
%Addition of one interger number and a character
%--------... |
% clear all
clc
%十折
%% load data
% load('TI_Features_324p2GAmrmr_.mat')
% load('TI_Label_169.mat')
% load('Feature_TI_System_521_0628.mat')
% load('Label_TI_System_521.mat')
load('yesornoforsample_521to455.mat')
% load('yesornoforsample_521to181')
% load('yesornoforsample_see521to299.mat')
% load('yesornoforsample_521t... |
%=========================================================================
%
% Program to compute method of moment estimates of various distributions
%
%=========================================================================
clear all
clc
RandStream.setDefaultStream( RandStream('mt19937ar','seed',12) );
t = 10; ... |
function bestguess=kwwmin(fitinfo)
global MAXTIME
% user set parameters
if exist('MAXTIME')==0,
MAXTIME=30;
end
%pin=(lbound+ubound)/2;
%if length(abs(ubound-lbound)<minbndsz)>0,
% bdidx=find(abs(ubound-lbound)<minbndsz);
% ubound(bdidx)=ubound(bdidx)+minbndsz;
% lbound(bdidx)=lbound(bdidx)-minbndsz;
%end
t... |
function [RX, model] = coc_reorder( RX, model, m)
% kmeans for each dimension
[idx, ~] = kmeans(RX, m, 'Start', 'plus');
coc_idx = cell(m:1);
for i=1:m,
coc_idx{i} = find(idx == i);
end
%reordering RX
RX = RX(cat(1, coc_idx{:}),:);
cluster_sizes = cellfun(@(x)size(x,1), coc_... |
function err = naivePerfusionSSEIntegratorP2X4stack(ton,toff,Ttot,amp,T,I)
%#codgen;
naive=zeros(1,25);
naive(1)=1;
V=-60*10^-3;
err=errorIntegratorP2X4stack(ton,toff,Ttot,amp,naive,T,I,V);
end |
function [annBlueVal,spotblueval,Vs,Van]= spotDet(filt,cent,ra,spotRt,n,rows)
c = spotRt(1);
r = spotRt(2);
[rr,cc]= meshgrid(1:size(filt,1), 1:size(filt,2));
for k=1:rows
rak=ra(k);
roOuter=rak*1.5;
Rs = (rr - cent(k,2)).^2 + (cc - cent(k,1)).^2 < (rak).^2;
Ran = ( (rr - cent(k,2)).^2... |
function gof = decoderPerformance(mdl)
confusionMatrix = confusionmat(cell2mat(mdl.io.trueY),cell2mat(mdl.io.predY));
chance = 1/length(confusionMatrix);
accuracy = nan(1,length(mdl.io.trueY));
for g = 1:length(mdl.io.trueY)
confusionMatrix_accuracy = confusionmat(mdl.io.trueY{g},mdl.io.predY{g});
accuracy(g... |
function s = merge_fields(s1,s2)
%
% s = merge_fields(s1,s2)
% Merge the fields of two structures. If there are duplicate
% fields, the fields in s1 are taken.
%
% Inputs:
% s1, s2 are arbitrary structures e.g., containing metadata or settings.
%
% Returns:
% s is a structure containing all of the f... |
function SC = sc_prep(A, In, Out)
ndoms = length(In);
out = horzcat(Out{:});
Aoo = A(out,out);
[Aio, Aoi, L, U, P, Q] = deal( cell(ndoms,1) );
for i = 1 : ndoms
inn = In{i};
Aio{i} = A(inn,out);
Aoi{i} = A(out,inn);
[L{i}, U{i}, P{i}, Q{i}] = lu( A(inn,inn), 'vector' );
end
[SC.L, SC.U, SC.P... |
%% sample_simulation_file.m
%
% DESCRIPTION: just an example simulating a GI
%
%
%
%
%
%
%
%
%
%% Initialization parameters
clear;
% Constants
c = 299792458;
h = 4.135*10^(-15);
delta_PMMA = 0.45e-6;
beta_PMMA = 0.6828e-10;
% Spectral parameters
E_central = 25000;
BW = 0.00001;
N_bands = 3;
DE = E_central*BW;
Ei = li... |
function [ijs,v,ccorr] = templatematch(img, tmpl)
%--------------------------------------------------------------------------
%
% Copyright (c) 2011 Jeffrey Byrne
% $Id: templatematch.m 91 2012-12-12 17:03:07Z jebyrne $
%
%--------------------------------------------------------------------------
%% Options (FIXME)
op... |
clear all;
figure;
N=256;
NFREC=N/2;
NCAS=6;
scale=5;
offset=1;
g= load('G22INT.RES');
ReG22=g(:, 2);
ImG22=g(:, 3);
AbsG22=g(:,4);
ReG22NUM=g(:, 5);
ImG22NUM=g(:, 6);
AbsG22NUM=g(:,7);
for j=1:NCAS;
fi=NFREC*(j-1)+1;
ff=NFREC*j;
plot(g(fi:ff,1), ReG22(fi:ff)*scale+offset*j, 'b');
hold on;
plo... |
function spectralCentroid_criteria = compare_spectralCentroid(target_features,soundset_features)
idx_sc_K = find(strcmp(soundset_features.names,'spectralCentroid'));
sc_matrix_K = soundset_features.matrix(:,find(soundset_features.positions==idx_sc_K));
sc_vector_T = target_features.spectralCentroid;
sc_matrix_T = repm... |
function Yn = pkt_hp_filter(Xn,Xn_k,Yn_k,samp_freq)
% High Pass Filter EEG data packets with cutoff frequency of 0.1 Hz. This is a 4th order
% butterworth filter designed using fdatool.
% To verify that this filter is actually working with the EEG data:
% 1. Run the Brain Vision Recorder software in Simu... |
clear; clc
f = @(y,t) (-1/3)*y+sin(t);
tmin = 0;
tmax = 15;
numpts = 1000;
IC = 1;
[t,y] = MyEuler1D(f,tmin,tmax,numpts,IC);
plot(t,y)
%%
clear clc;
alpha = 1;
beta = .05;
delta = 1;
gamma = .01;
ICx = 1;
ICy = 2;
tmin = 0;
tmax = 15;
numpts = 1000;
f = @(x,y,t) alpha * x - beta * x * y;
g = ... |
function [ profile_length ] = chord_length( y,im )
profile_length = 0;
for i = 1:size(im,1)
if im(i,y) == 1;
profile_length = profile_length +1;
end
end
end
|
function [A] = podijeli_u_matricu( x,h,L)
%Funkcija dijeli ulaznu sekvencu na potreban broj podsekvenci, a iste
%dopunjuje sa Nh-1 nula. Zatim se koristeci implementiran algoritam
%fft_radix_2 racuna DFT te jedne podsekvence i mnozi sa DFT-om impulsnog
%odziva. A onda se dobijena sekvenca koristeci implementiranu funkc... |
function leftMask = splitByPlane(pts, n, sn, prn)
%Dzieli punkty 'pts' na leżące po lewej części płaszczyzny wyznaczonej
%przez 3 punkty (n, sn, prn) i na takie które leżą z jej prawej strony.
% wektory wyznaczajace plaszczyzne:
lv = n - prn;
hv = sn - prn;
% wektor prostopadly do plaszczyzny (skierowany w ... |
pkg load image
function result = atv(img, w, h, M, V, num)
result = zeros(w, h, "double");
for i = 1 : num
result += imnoise(img, "gaussian", M, V) / num;
endfor
endfunction
img = imread("pratica4.png");
sz = size(img);
img = im2double(img);
w = sz(1);
h = sz(2);
figure, imhist(img);
noise = imnoise(img, "g... |
%Andrew Brown Homework 5 Problem 1
clc
clear
%More practice functions and fzero.
%Projectile motion simulated
%Define constants
g=9.8; %acceleration due to gravity in m/s^2
theta=89; %launch angle in degrees
v=13.5; %initial velocity in m/s
%Declare given position functions
x = @(t) [v.*t.*cosd(theta)]; %x distance... |
function std_feature = normalize_feature(raw_feature, deviation, mea)
std_feature = (raw_feature - mea)/deviation;
end |
function gatewayDisconnect
%Disconnect from omero server using Blitz.
%
%Author Michael Porter
%Copyright 2009 University of Dundee. All rights reserved
global client;
global session;
global gateway;
global clientAlive;
try
clientAlive.stop;
catch
%If the client is no longer alive then there's nothing to clo... |
function [ ] = cal_accuracy( handles )
global LMS_net;
global RLMS_net;
global IF_net;
global GD_net;
global MGD_net;
global BPD_net;
global train_status;
global init_status;
if ~init_status || ~train_status
return;
end
set(handles.create_networks,'Ena... |
clc;clear;
format long
%% 原始数据
Wrr = load('lncRNAsimilarity.txt');
Wdd = load('diseasesimilarity.txt');
interaction = load('known_lncRNA_disease_interaction.txt');
interaction_ori = interaction;
[nl,~]=size(Wrr);
n=1;
%% 数据处理方法
% for gama=1:1:9
gama=1;
Wrr1=reSimilarity(Wdd,interaction_ori); % reSimilarity：ln... |
function conf = proposal_config(varargin)
% conf = proposal_config(varargin)
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed under The MIT License [see LICENSE for details]
% --------------------------------------------------------
ip = inputP... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% nome_q1a.m
%%% Matlab function to detect spikes
%%% by Antonio Padilha L. Bo (antonio.plb@lara.unb.br)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function spikeTimes = nome_q1a(time, electro... |
%identyfikacja parametrów modelu matematycznego
c1=10;
x01=33;
LB=[0.1 25]';
UB=[200 40]';
ym=poziom_zawor1_poprawiony(1);
parametry_optymalne1=lsqnonlin('cel1',[c1 x01]',LB,UB,[],czas_zawor1_poprawiony,poziom_zawor1_poprawiony);
[T1,X1]= ode45(@(t,x) rownanie1(t,x,parametry_optymalne1(1)),czas_zawor1_poprawiony,par... |
clear all ; close all
subs = {'alex','dina','genevieve','jeremie','karl','russell','tegan','sukhman','valerie'} ;
for sub=9%:length(subs)
cd(['c:/shared/badger_eeg2/',subs{sub}]) ; ls
mov = dir('bcgica*rest*set') ;
EEG = pop_loadset(mov(1).name) ;
EEG = pop_chanedit(EEG,'lookup','C:\eeglab8_0_3_5b\plugins\dipf... |
function smoothingKernel = createPaddedGaussianKernel(h, w, d, sigma, K)
% CREATEPADDEDGAUSSIANKERNEL create a 3D Gaussian kernel
%
% smoothingKernel = createPaddedGaussianKernel(h, w, d, sigma, K) create a
% gaussian kernel of standard deviation sigma in a 3D volume of size h x w
% x d: smoothingKernel. K is a cuto... |
function plot_figures
param_fname = 'lc18_model_param';
load( strcat(param_fname, '.mat'), 'x' ); % load optimized parameters
vstim_dir = './vstim/';
x_orig = x; % make a copy of optimized param
param = convX2param(x);
fun = @simulateXcontrast;
% ---------------------------------------------------------------... |
%% A
load('A')
YInjured=FRMat/60/5;
% Is it different than baseline?
[p,tbl,stats] = anova1(YInjured);
c=multcompare(stats);
figure
bar(0:5:95,mean(YInjured),'barwidth',1,'facecolor',[1 31 91]/255,'linewidth',1.5)
hold on
errorbar(0:5:95,mean(YInjured),zeros(1,20),std(YInjured),'k.')
K=max([mean(YI... |
function [mag,theta] = orientedFilterMagnitude(im, NSCALE)
%Computes the boundary magnitude and orientation using a set of oriented filters
% One way to combine filter responses is
% to compute a boundary score for each filter (simply by filtering with it)
% and then use the max and argmax over filter responses
% to... |
function [z,err]=args2struct(Defaults, Args, generror)
%ARGS2STRUCT Parse input parameters into a struct.
% ARGS2STRUCT aids parsing of parameters, so that the call of
% a function can contain both positional and named parameters
% as e.g Handle Graphics calls.
% Part of the OptProp toolbox, $Version: 2.1 ... |
function h = histogram(data, bins)
h = zeros(bins, 1);
for i = 1:size(data)
h(data(i)+1) = h(data(i)+1) + 1;
end
end |
function d=derivxy(x,y)
% First derivative of y with respect to x using 2-point central difference.
% T. C. O'Haver, 2011. Corrected 2/4/14
% Example:
% x = [1 2 4 7 10 14];y = 2*x;derivxy(x,y)
% ans =
% 2 2 2 2 2 2
n=length(y);
d=zeros(size(y));
d(1)=(y(2)-y(1))./(x(2)-x(1));
d(n)=(y(n)-y(n-1... |
function nearest_neighbor(obj, z, params)
% number of features
num_of_extracted_features= size(z,2);
% initialize with zero, if SLAM --> initialize with (-1)
obj.association= zeros(num_of_extracted_features, 1);
% initialize variables
spsi= sin(obj.XX(3));
cpsi= cos(obj.XX(3));
z_estimated= zeros(2,1);
% select la... |
function [k, TempAmb, Temp0, tStart, tMax] = ProblemConstants
% Constants of the problem
k = 0.08;
TempAmb = 20;
Temp0 = 250;
tStart = 0;
tMax = 30;
|
function afniCreateAffine(subject,mriVol,histoVol,path)
% vol2volWarp(subject,mriVol,histoVol,path)
%
% This code creates an affine tranform to roughly align the mri volume anatomy of a PM subject to the 3D histological reconstuction
% generates a new volume: fullfile(path, [subject '_3dAllin_Qwarp.nii.gz']);
% and... |
function B = convert_ldr(A, a, b)
rad = convert_hdr(A, a);
B = hdr_ldr(rad, b);
end
|
function runAll_vot15
visualization = false;
gpus = 1;
seq={
'vot15_bag'
'vot15_ball1'
'vot15_ball2'
'vot15_basketball'
'vot15_birds1'
'vot15_birds2'
'vot15_blanket'
'vot15_bmx'
'vot15_bolt1'
'vot15_bolt2'
'vot15_book'
'vot15_butterfly'
'vot15_car1'
... |
classdef Tingey_s1505528_GUIEffects < matlab.apps.AppBase
% Properties that correspond to app components
properties (Access = public)
AudioEffectsGUIUIFigure matlab.ui.Figure
UIAxes matlab.ui.control.UIAxes
PlotthesignalafterapplyingtheeffectPanel matlab.ui.container... |
% I have -> botpos, newpos
function botpos = move(botpos, pad_inpolygonMapformatX, pad_inpolygonMapformatY)
vec_botpos = [botpos(1) - 1 botpos(2) + 1;
botpos(1) - 1 botpos(2) - 1;
botpos(1) + 1 botpos(2) - 1;
botpos(1) + 1 botpos(2) + 1];
inside = inpolygon(vec_botpos(:,1), vec_botpos(:,2), ... |
function [best,tr,val_fail] = trackBestNetwork(best,tr,val_fail,net,perf,vperf,epoch)
% Copyright 2010-2014 The MathWorks, Inc.
validationDataExists = ~isempty(tr.valInd);
if validationDataExists
[best,tr,val_fail] = trackByValidationPerformance(best,tr,val_fail,net,perf,vperf,epoch);
else
[best,tr] = trackBy... |
% N = length_MSD; Note to self
% epsilon = loc_uncert; Note to self
% function sigma = myMichaletFun(N, epsilon_val, alpha_val)
function MSD_data = myMichaletFun(MSD_data)
for i = 1:length(MSD_data)
%From the paper, the varience of the mean squared displacement is:
N = length(MSD_data(i).MSD);
alpha_val = MSD_d... |
function x = gpu2nndata(y,Q,N,TS)
%GPU2NNDATA Reformats neural data back from GPU.
%
% Training and simulation of neural networks requires that matrices be
% transposed, and do not require but are more efficient when the column
% length is padded so that each column is memory aligned. This function
% copies data b... |
%% --- 1. CLASSICAL AND MODERN SPECTRUM ESTIMATION --- %%
%% 1.4 Spectrum of Autoregressive Processes %%
% (a) While using the unbiased ACF estimate when finding the AR parameters,
% this estimate can be highly erratic for larger lags close to N, where
% fewer samples are available to estiamte to estimate the PSD. AC... |
% Generate groundtruth detection log for cpp code
function log = temp
addpath(genpath('C:\zxk\Research\code3.0.0'));
% filePath = 'C:\zxk\Research\monkeyData\Camera1_extractedVideos';
filePath = 'C:\zxk\Research\monkeyData\Camera2_labeledVideos';
firstVideoNumber = 100;
lastVideoNumber = 100;
for videoNumber = firs... |
I = imread('C:\Program Files\MATLAB\R2021a\toolbox\images\imdata\kobi.png');
M = double([0.299 0.587 0.114; 0.596 -0.275 -0.321; 0.212 -0.523 0.311]);
YIQI = zeros(size(I));
YIQI(1,1,1) = I(1,1,1)*M(1,1)+I(1,1,2)*M(1,2)+I(1,1,3)*M(1,3);
YIQI(1,1,2) = I(1,1,1)*M(2,1)+I(1,1,2)*M(2,2)+I(1,1,3)*M(2,3);
YIQI(1,1,3) = I... |
function fx = InvChebTrans(fk, x)
N = size(fk, 1) - 1;
T = ChebPoly(N, x);
fx = T * fk;
end
|
function y = NeedleAngel(x)
slope= ( ( x(2,2) - x(1,2) )/( x(2,1) - x(1,1) ) );
angle = atand(slope);
if(angle == 90 || angle == -90)
if(isUpar(x))
y = 0;
else
y = 180;
end
elseif(angle == 0)
if(isAtLeft(x))
y = 270;
else
y= 90;
end
elseif (angle > 0... |
% (* ::Package:: *)
% Area Sources
load 'J:\SHARE\OAQPS 2014-2019\Reduced Form Tools Testing (3-40)\Models\AP2\2011_PM_Worksheet_Area_Low_Western_Adj'
I = eye (3109,3109);
%% NOx NO3
run Area_Reset
NOx_Area_Source = 28761.72.*1.35.*NOx_Cal.*(Area_Source {1,1});
p = 1;
for n = 1:S;
tic
disp... |
function out=selfdwt(in,J)
% 完成J尺度Haar小波变换
% in 是输入信号
% out 是输出的小波系数
%h0,h1是相应的小波和尺度向量
h0=[1/sqrt(2),1/sqrt(2)];
h1=[-1/sqrt(2),1/sqrt(2)];
out=zeros(size(in));
m=size(in);%此处的m为一向量
x=length(in);
k=0;
l=0;
Wl=in;
for i=1:J
%=================此处对应于高频部分，结果中抽取偶数的点=====================
Wh=conv(h1,Wl);
for j=1:(leng... |
h = 0.025;
t = 0:h:6;
x = sin((t.*t) - 6 * t + 3)
y = (1/3) * sin((t.*t) - 6 * t - pi / 6)
D = 4
[~, Q] = size(x);
p = zeros(D, Q);
%%
for i = 1 : D
p(i, i : Q) = x(1 : Q - i + 1);
end
net = newlind(p, y);
Y = net(p);
display(sqrt(mse(Y - y)));
figure;
hold on;
grid on;
plot(t, y, '-b');
plot(t, Y, '-r');
figure;... |
% [x,ret] = Iyajima(K,PL,PU,epsilon,solver)
%
% solve interval DGP SDP formulation with solver 'solver' to
% find a realization of the partial interval EDM [PL,PU]
% in R^K epsilon is used to go from Gram matrix to realization.
% SDP model by Yajima
% x = the realization
% ret: a return data structure wit... |
%% 综合应用：粒子群算法PSO: 求解函数y = 21.5+x(1)*sin(4*pi*x(1))+x(2)*sin(20*pi*x(2))在x1属于[-3,12.1]，x2属于[4.1,5.8]内的最大值(动画演示）
clear; clc % 目标函数参考的最优值：38.8503
%% 绘制函数的图形
% x1 = -3:0.01:12.1;
% x2 = 4.1:0.01:5.8;
% [x1,x2] = meshgrid(x1,x2);
% y = 21.5 + x1.*sin(4*pi*x1) + x2.*sin(20*pi*x2);
% mesh(x1,x2,y)
% xlabel('x1... |
classdef C11GlucoseKinetics < mlkinetics.AbstractC11GlucoseKinetics
%% C11GLUCOSEKINETICS
% $Revision$
% was created 29-Jun-2017 21:03:07 by jjlee,
% last modified $LastChangedDate$ and placed into repository /Users/jjlee/Local/src/mlcvl/mlarbelaez/src/+mlarbelaez.
%% It was developed on Matlab 9.2.0.5380... |
function phi = U(varargin)
assert(nargin == 2, 'U takes tow variables');
if strcmp(varargin{1}.type, 'inner') || strcmp(varargin{1}.type, 'ap')
assert(strcmp(varargin{1}.type, 'inner') ||...
strcmp(varargin{2}.type, 'ap'), ...
'Inner and outer logic formulas cannot be mixed');
phi =... |
% shape_analysis_7b.m
% the curve representing shape transition
% r_a/r_0 vs h/r_0
%cd 'E:\Ben\EVOLVER\chromaffin endocytosis\harbe'
results_folder = 'D:\Ben\EVOLVER\chromaffin endocytosis\results august (mixes ra and h)' ;
cd(results_folder) ;
folders = dir('*'); %%
dirFlags = [folders.isdir];
folders ... |
function sim = sim(D)
%sim Compute the similarity matrix from a distance matrix
sim = exp(-D);
end
|
function A4_Combine_Data
%Step 2, after checking that data is okay, combine all data into
%three matrices containing all responses, SS10, SS30 and SS50.
%% RG, RG2, MW,MW2, MW3, HH, HH2, HH3, HH4, RO, RO2, RO3, LJ, LJ2, LJ3, JR
clear all
close all
subject = 'MW4';
switch subject
case 'RG'
... |
function removepr(PR)
%*************************************************
%DATE: 13/8/2007 (created); 13/8/2007 (modified)
%FUNCTION:
%INPUTS:
%OUTPUTS:
%muwn.gu@gmail.com
%*************************************************
global layerMatrix;
layerMatrix (find(layerMatrix == 9)) = 0;
|
clear all;
P=[1 -1.1];
T=[0.5 1];
[R,Q]=size(P);
[S,Q]=size(T);
lr=0.4*maxlinlr(P); % 最佳学习速率
net=newlin(minmax(P),S,[0],lr); %创建线性网络
net.inputWeights{1,1}.initFcn='rands'; %初始化权值
net.biases{1}.initFcn='rands'; %初始化偏差
net=init(net); %把初始化的权值和偏差函数赋给网络
disp('显示初始化... |
% ir = imread("C:/data/FLIR_ADAS_1_3/train/thermal_8_bit/FLIR_04274.jpeg");
% rgb = imread("C:/data/FLIR_ADAS_1_3/train/RGB/FLIR_04274.jpg");
%
% [mp, fp] = cpselect(rgb, ir, 'Wait', true);
%
% t = fitgeotrans(mp, fp, 'projective');
% Rfixed = imref2d(size(ir));
% registered = imwarp(rgb, t, 'OutputView', Rfixed);
% ... |
function [L,U] = forwElimLU_func(A)
%FORWELIMLU_FUNC LU factorisation
% [L,U] = FORWELIMLU_FUNC(A)
% Compute the LU factorisation of a given A. The input A is any square matrix,
% the output U is the final echelon form (an upper triangular matrix) as obtained
% by forward elimination(without row exchanges),L ... |
% CHAPTER 6
%% 6.1 plot
x=linspace(0, 4*pi, 200);
y=cos(x);
plot(x,y,'LineWidth', 2.5,'Color',[0,0,0]);
axis([0 4*pi -1 1]);
%% 6.1a plot 2
plot(y,'LineWidth', 2.5,'Color',[0,0,0]);
%% 6.1.1
t=linspace(0, 4*pi, 200);
y=cos(t);
plot(t,y,'LineWidth', 2.5,'Color',[0,0,0]);
axis([0 4*pi -1 1])
xlabel('time ... |
function min = min_dist(point, point_set)
%MIN_DIST Summary of this function goes here
% Detailed explanation goes here
portion = 100;
min = bitmax;
for j = 1 : idivide(int32(size(point_set, 1)), portion, 'floor')
current = point_set(j*portion,:);
dist = 0;
for k = 1:3
dis... |
function mm = mean_squares(nn)
Matrix = (1:nn);
M_sqr = Matrix.*Matrix;
mm = mean(M_sqr); |
function projection_image=simRodCellShell(radius, lengthVar, width,realCenter, orientation,psf,sizeImage)
Center=[sizeImage(2)/2,sizeImage(1)/2];
projection_imageCylinder=simCylinderShell(radius, lengthVar,width, Center, psf,sizeImage);
Center1=Center;
Center1(2)=Center(2)-lengthVar;
projection_imageSphere1=simHalfSph... |
%% Problem_1
% Define demand function
demand = @(v,p) exp([v-p;0])/sum(exp([v-p;0]));
% Compute demand
v = [2;2];
p = [1;1];
d = demand(v,p);
D_A = d(1) % Demand for product A
D_B = d(2) % Demand for product B
D_0 = d(3) % Demand for outside option
%% Problem_2
v = [2;2];
% Initial guess of p = [p_A;p_B]
p_ini =... |
function [out1, out2] = residual(Pressure,Pressure_old, order, cnt, kx, ky, h, dx, dy, poro)
[row,col] = size(order);
N = zeros(row, col);
S = zeros(row, col);
W = zeros(row, col);
E = zeros(row, col);
C = zeros(row,col);
Q = zeros(row,col);
Z = gasZ(Pressure, order);
... |
function p = predict(Theta1, Theta2, X)
%PREDICT Predict the label of an input given a trained neural network
% p = PREDICT(Theta1, Theta2, X) outputs the predicted label of X given the
% trained weights of a neural network (Theta1, Theta2)
% Useful values
m = size(X, 1);
num_labels = size(Theta2, 1);
% You need ... |
% Function {out parameter}={function name}(in parameter}
%
% input parameter definition
% im = input image
% sizeofkernel = Size of Kernel
%
% output parameter definition
% output = output image
%
function [output]=BoxFilter(im, sizeofkernel)
% kernel generation part
kernel = ones(sizeofkernel);
[ksizey,k... |
function majorityValue = MAJORITY_VALUE(binary_targets)
% majorityValue = MAJORITY_VALUE(binary_targets)
% Function that returns the mode of the targets.
% INPUT : binary_targets - vector containing the targets of the train data.
%
% OUTPUT : majorityValue - the mean of the binary_targets.
... |
function x = removeZeroModes(x, componentIndex)
%REMOVEZEROMODES Orthogonalize x to Laplacian zero modes.
% componentIndex contains a graph's components.In particular, if
% componentIndex is, this method is equivalent to x = x - mean(x).
numComponents = numel(componentIndex);
if (isempty(componentIndex) || n... |
function [ x, f ] = kde(data)
% function [ x, f ] = kde(data)
% Calculate the kernel density estimate for data set data, returning two
% row vectors with 1001 elements
% Make sure data is a column vector
data = reshape(data, [ length(data), 1 ]);
dataSTD = std(data);
dataMin = min(data);
dataMax = max(data);
% Make... |
function X = l12_min(A,B,b,bc,C,D)
% L12_MIN Solve the "L12" minimization problem using second-order cone
% programming. L12 is the L2,1 norm applied to the transpose of a matrix
% (i.e., L12 computes the sum of row-wise vector norms).
%
% X = l12_min(A,B,b,bc,C,D)
%
% min ‖ (A X - B)ᵀ ‖_2,1
% X
%
... |
% THIS SCRIPT CALCULATES THE QUARTERNION GIVEN EULER ANGLES
function quat = EulToQuat(angle)
z = angle(1);
y = angle(2);
x = angle(3);
quat = [cos(x/2)*cos(y/2)*cos(z/2)+sin(x/2)*sin(y/2)*sin(z/2);
sin(x/2)*cos(y/2)*cos(z/2)-cos(x/2)*sin(y/2)*sin(z/2);
cos(x/2)*sin(y/2)*cos(z/2)+... |
function [len, validity, return_code] = READ_SAMPLING_MESSAGE(sampling_port_id, msg_addr)
sample = get_sample_by_id(sampling_port_id);
if sample == []
return_code = INVALID_PARAM;
return;
end
if sample.length == 0
len = 0;
validity = INVALID;
return_code = NO_ACT... |
function mapping = nearestDeepFashion(jsonFile)
fileID = fopen(jsonFile,'r');
params = fscanf(fileID,'%s');
data=JSON.parse(params)
% -- settings start here ---
% set 1 to use gpu, and 0 to use cpu
use_gpu = 1;
% top K returned images
top_k = data.TOP_K;
feat_len = data.FEATURE_LEN;
% % set result folder
result_fol... |
addpath('../general_functions')
addpath('../../Chapter 1')
clear variables
%% Figure 5.2a : LL(2) with various \lambda values.
d_iter=2:5;
lam_range = linspace(0.01,1-10^(-8), 400);
w_range = linspace(0,60,10^5);
tol=10^(-6);
EW_quot1 = zeros(length(d_iter), length(lam_range));
EW_quot2 = zeros(length(d_iter), length(... |
function writeexp4(expfile,datdir,theta,phi,id,int,ledon,sndon,dummy,nrdtrials)
% Save known trial-configurations in exp-file
%
%WRITEEXP WRITEEXP(FNAME,DATDIR,THETA,PHI,ID,INT,LEDON,SNDON)
%
% WRITEEXP(FNAME,THETA,PHI,ID,INT,LEDON,SNDON)
%
% Write exp-file with file-name FNAME.
%
%
% See also GENEXPERIMENT
... |
clear all
if exist('ev3ShellHandle')
clear ev3ShellHandle
end
%Square Parameter
l = 50; % in mm
%Circle Parameter
r = l/2; % in mm
centercircle = [25 25]; %in mm from 0,0
%Traingle Parameter
init = [0 0];
mid = [25 50];
final = [50 0];
% Axis as defined in the project
%y | ... |
% virtuoso_importVCSV_AC
% imports AC analysis data that is saved in a .vcsv file from Cadence Virtuoso
% [time, voltage, signalNames, units] = virtuoso_importVCSV_TRANS(folder, filename)
%
% Inputs:
% folder - The folder in which the data file is saved
% filename - name of the .vcsv file to be importe... |
function plotcontrol( title, s, T, data, labels, legendlabels )
if nargin < 6
legendlabels = labels;
end
Tsample = T( 1:s.sampleratio:(s.samplecohtimes*s.cohsteps) );
data = data( 1:s.sampleratio:(s.samplecohtimes*s.cohsteps), : );
fig = figure();
set( fig, 'Name', title );
clf;
... |
% MAximize over the Cholesky decomposition, not the components of sigma!
function loglike = likeliMC(gamma,mu,muu,var_mu,var_u,var_muu)
data = load('C:\Users\padag\Documents\MATLAB\hw5.mat');
X = data.data.X;
Y = data.data.Y;
Z = data.data.Z;
N = data.data.N;
T = data.data.T;
... |
function [P,Z] = eq_typeIII(B)
% Function to compute equilibrium phytoplankton and zooplankton
% concentrations for model using type III response in Freilich et al (in
% review) Biogeosciences
% Input:
% B: parameters for biological model
N_max = 30;
P = zeros(1,365);
Z = zeros(1,365);
for year_day = 1:365
x0 = [... |
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