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function [ normData ] = normalizeData( data )
%NORMALIZEDATA
%Normalizes training data given that each row is a data point, each column
%is a feature
numFts=size(data,2);
%Normalize the data
meanFts = zeros(1,numFts);
varFts = zeros(1,numFts);
for ft = 1:numFts
%Get feature array from the provided data
... |
figure
data1=importdata('SM4');
x1 = data1(1:1:157152,1);
y1 = data1(1:1:157152,2);
plot(x1,y1);
%axis([0 2000 0.3 1.5]);
title('SM4') |
%V1.1
% % % FUNCTION: compare cards
% % % MTRX5700 Major Assignment 2015
% % % Authors: Sachith Gunawardhana & Kausthub Krishnamurthy & James Ferris
% % % REVISION HISTORY
% % % v0 function stub
% % % v1.1
% % % SUBFUNCTIONS LISTING
% % %
% % % 0000 1111
% % % 0000 1010
% % % 0000 1010
function [matchFlag, matchInd... |
%% Clean environment
close all;
clear;
clc;
%% Model
% As described in in:
% Strogatz, S. H. (1987).
% Human sleep and circadian rhythms: a simple model based on two coupled oscillators.
% Journal of Mathematical Biology, 25(3), 327–347. http://doi.org/10.1007/BF00276440
pars = genPars('strogatz1987');
pars.w2 = 0.8... |
function newmat = inc(oldmat, row, col);
% This function is used to increase an element of a matrix.
% If the matrix does not include the specified element,
% the matrix is extended and the element is set to 1.
matsize = size(oldmat);
if (row > matsize(1)) | (col > matsize(2))
oldmat(row, col) = 1;
else
oldma... |
function varargout = KWDM_Nerki(varargin)
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @KWDM_Nerki_OpeningFcn, ...
'gui_OutputFcn', @KWDM_N... |
% Chapter 8 - Planar Systems.
% Program_8b - Phase Portrait (Fig. 8.8(a)).
% Copyright Birkhauser 2013. Stephen Lynch.
% Phase portrait of a linear system of ODE's.
% IMPORTANT - Program_8a is vectorfield.m.
clear;
% sys=inline('[2*x(1)+x(2);x(1)+2*x(2)]','t', 'x');
sys = @(t,x) [2*x(1)+x(2);x(1)+2*x(2)];
ve... |
function [V_ge,V_ef,V_ge_0_lio,V_ef_0_lio]=window_fun_HEOM2_f2(N,HL,om_3_rng,sup_op_full)
%Changes, this version uses the / lin solver op
% This version works in frequency space, i.e. using
% int_0^inf dt_3 exp(-i \omega_3 t_3) e^(L t_3) = 1/(i \omega_3 - L)
% this version that works in the exciton basis with n... |
clear all
close all
addpath('../MRF/');
% addpath('../Chan-Vese/');
load('../data/prior/shapePriorShift.mat');loadDataFruitfly;
%generateData;
%Run MRF
edgeStruct = createImgStructure(X,nStates);
lambda = 1;
beta = 10;
Epsilon = 1;
prior_phis = Phi(:,:,1:2);
no_ex = size(prior_phis,3);
% Compute kernel sigma
kerne... |
cc=hsv(3);
hold off;
train = load('q1atrain.txt');
test = load('q1atest.txt');
validation = load('q1avalidation.txt');
h1=plot(train(:,1),train(:,2),'color',cc(1,:));
hold on;
h2=plot(validation(:,1),validation(:,2),'color',cc(2,:));
h3=plot(test(:,1),test(:,2),'color',cc(3,:));
legend([h1 h2 h3],{'training','validati... |
close all;
[V, F] = openOFF('../../ex3/model.off', 'newplot');
figure
%P = patch('Vertices', V, 'Faces', F, 'FaceVertexCData',0.3*ones(size(V,1),3));
axis equal;
shading interp;
camlight right;
camlight left;
%% using homogeneous projection matrix
projectedVerts = pinholeProject([0, 0, -1], 5, V);
patch(projected... |
classdef (Hidden) AbstractLevel < amg.level.Level
%LEVEL A single level in the multi-level cycle.
% This class holds all data and operations pertinent to a single
% level in the multi-level cycle: right-hand-side, residual
% computation and single-level processes such as relaxation.
%====... |
function [x, y] = myMin(v)
%This function takes in vector v and outputs the smallest value of the
%vector and the index of the first occurence of that vector.
%Inputs:
% v- vector input of any length
%Outputs:
%x- scalar input that is the smalled value of vector v
%y- scalar input that is the index of the smalles... |
function [T,I,Y]=perfusionResponsepotentP2X4two(y0,ton,toff,Ttot)
ode=modelODEpotentP2X4two(ton,toff);
[T,Y]=ode15s(ode,[0 Ttot],y0,odeset('NonNegative',1:21));
I=getTotalCurrentpotentP2X4two(Y);
end |
function [ ] = test_Heat2d_stream( )
%TEST_HEAT2D_STREAM tests the numerical solution against its analytical one
%given in the book
%
%"Quantitative Hydrogeology" by Ghislain de Marsily (1986)
%
%in section 8.5. We solve the problem in two dimensions but independant of
%the second one.
%
%The problem consist of an aqui... |
% pColumnsForModel lists out what column each part of a JAR3D model should go into when displayed
function [T] = pColumnsForModel(Node,ModelName)
T = pColumnsForModelRecursive(Node,1); % start with Node 1
for i = 1:length(T),
T{i} = [ModelName '_' T{i} ' appears_in_column ' num2str(i)];
end
|
% NODEWISE_CAMD Nodewise elimination procedure: METIS + simple reordering
%
% See also NODEWISE_ABSTRACT, METIS.
function reduced_data = nodewise_amd_dummy( G, is_ext_node, ~ )
p = amd(G);
p_terminals = is_ext_node(p);
Perm = [p(p_terminals==0) p(p_terminals==1)];
reduced_data = struct;
nodewise__fixed_ordering;
end
|
% SNP needs to have at least two fields, "position" and "chr".
% This implementation is very slow and stupid because I was lazy. you can
% just compare the start and end positions of the annotation to the
% position of SNP instead of using the more general genomic intersection
% script.
% Pejman April 2015, This code ... |
clear;
% max_frame 11114
% min_frame 2
% all_ids [0, 1, 2, 3, 4, 5]
% max_frame 17424
% min_frame 11540
% all_ids [1, 3, 4, 2, 0]
% max_frame 23689
% min_frame 18041
% all_ids [0, 1, 2, 3, 4, 6, 7]
% max_frame 35057
% min_frame 24413
% all_ids [2, 3, 4, 0, 1]
% max_frame 46870
% min_frame 41829
% all_ids [0, 1, 2, 4, ... |
function [Filtered, FilteredCov, Predicted, PredictedCov, logLik] = ...
KalmanFilter(Y, TranMX, DistMean, DistCov, MeasMX, ObseCov, State0, StateCov0)
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
[~, d, T] = size(MeasMX);
Filtered = zeros(d, T);
FilteredCov = zer... |
% init_leg
leg.I1 = 0.66;
leg.I2 = 0.33;
leg.I3 = 0.33;
leg.m1 = 2.25;
leg.m2 = 5.2;
leg.m3 = 15;
leg.l1max= 0.3;
leg.d2 = 0.15;
leg.l2 = 0.3;
leg.l3 = 0.2;
leg.spring.Ksp = 2e3;
leg.spring.Ksp2 = 5e5;
leg.spring.kmax = 0.28;
leg.spring.Kb = 1e3;
leg.spring.k0 = 0.25;
leg.damper.Kd = 1e3;
leg.l1min = leg.l1max - le... |
%%%%%%%%%%%
% Algorithm for estimating the rate constants for thorium and particle
% cycling. Fits a single particle class model for thorium and particle
% cycling to 228Th, 230Th, and/or 234Th, their resepctive radioactive parents,
% and particle data using a constrained
% optimization routine (either the Algorithm of... |
function bm_ext_base
xib = 0.1e-3;
%% Rl 100 ohm
Rl = 1.0e7;
frlist = logspace(0,3,600);
wlist = 2*pi*frlist;
Vplist = zeros(size(frlist));
Iplist = zeros(size(frlist));
Pplist = zeros(size(frlist));
tic
for k = 1:length(frlist)
[Vp, Ip, Pp] = bm_ext_eig(frlist(k), Rl);
Vplist(k) = Vp;
Iplist(k) = Ip;
... |
function demoFACEclean
%DEMOFACECLEAN demo of image denoising using a binary state Markov Random Field
import brml.*
f=imread('face.jpg');
xclean=f(:,:,1)>125; % binary clean image
Gx=321; Gy=265; N=Gx*Gy;
st = reshape(1:N,Gx,Gy); % assign each grid point a state
if exist('W0.mat')
load W0
else
disp('buildi... |
function f = get_values_at_nodes(xs)
ys = zeros(1,length(xs));
for i =1: length(xs)
x = xs(i);
ys(i) = (1+x^4)/(1+x^6);
end
f = ys; |
function [x_0,P_hidden_L] = block_gibbs(x_0,W,L)
[n_input,n_hidden] = size(W);
for k = 1:L
% Generating h
p = 1./(1+exp(-2*(x_0*W)));
test = double(rand(1,n_hidden)<p);
h = test + (-1).*(1-test);
% Generating x
p = 1./(1+exp(2*(h*W')));
test = double(rand(1,n_input)<p);
... |
dimension = 0;
total_runs = 100;
filtrationgap = .00005;
maxfilt = 0.2;
timesamples = 1000;
%whichModel = 'noInteraction'
whichModel = 'model';
%NOTE ON FILE NAMES: for model exp 1-4, use 'Fullh' instead of 100h. Change
%on BOTH of the below lines. Sorry about my terrible naming practices.
for expnum = 5:9
all... |
%
% Cette énumération contient les type de fichier qu'Analyse pourra ouvrir/convertir.
%
% Le nom doit rester exactement comme il est écrit ici car nous utilisons ce nom pour
% former le nom de la fonction qui sera appelé pour lire le fichier voulu.
%
% ex: pour un fichier texte, la classe s'appelle: CLireTexte
% ... |
function [ycomb_noage, summary, tr, tr_] = gather_outputs(y1,y2,TT)
global Tin num_pops num_cascade num_age num_intervention num_engagement num_region
ycomb=[y1(1:end-1,:,:,:,:,:,:,:);y2];
%Make everyone susceptible for R0 calculation
ycomb_S = zeros(length(TT),num_pops, num_cascade, num_age, num_intervention, num_eng... |
%% Plotting the time series of bacteria and virus populations, and immune response
lwidth=3; lbsize=25; tlbsize=20;
set(0,'DefaultLineLinewidth',lwidth)
set(0,'DefaultAxesLinewidth',lwidth)
set(0,'DefaultAxesFontSize',tlbsize)
bpop(bpop<para.thres)=0;
vpop(vpop<para.thres)=0;
% Time s... |
%Create Tyre data structure in car structure%
% Car.Tyre = struct();
% Car.Tyre = addParametersFromFile(Car.Tyre,'TyreCoefficientsHoosierLC0_LatCombinedFrom13R25B.xlsx');
Fz=1000;
Camber=0;
SRinc=0.01;
SRmax=0.2;
SAinc=0.01;
SAmax=15;
SR=-SRmax:SRinc:SRmax;
SA=-SAmax:SAinc:SAmax;
Fx=zeros(length(SR),leng... |
%%%%%%%%%%%%%%%% FIND SNAKE %%%%%%%%%%%%%%%%
% Finds the blob boundaries using a snake algorithm. This program requires
% code found in sdemo (Prince and Xu). The snake algorithm is initialized with
% the convex hulls outputted by findBoundaries.m
%
% Inputs:
% params - contains many snaking parameters (... |
n = 1e6;
x = rand(1,n);
fun = sqrt(1-x.^2);
y = rand(1,n);
ns = sum(y <= fun); % счетчик попаданий внутрь окружности
pi_ = 4*ns/n |
function dataStruct = loadDataStruct(dictors, utterances,...
variance, data, noise, voice, noiseValue, mode)
if strcmp(noise, '_orig')
noiseValue = '';
end
names = getFileNames(dictors,...
utterances, voice, variance, data, noise, noiseValue);
struct_data = loadData(names);
flat_data = [];
for i=1:length(n... |
t = linspace(0,2*pi);
r1 = sin(4*t)+2; x1 = r1.*cos(t); y1 = r1.*sin(t);
r2 = sin(8*t)+2; x2 = r2.*cos(t); y2 = r2.*sin(t);
P = InterX([x1;y1],[x2;y2]);
plot(x1,y1,x2,y2,P(1,:),P(2,:),'ro') |
function A = fem_compute_A_lin(lambda,mu)
%COMPUTE_A_LIN
% A = COMPUTE_A_LIN(LAMBDA,MU)
% This function was generated by the Symbolic Math Toolbox version 7.0.
% 06-Jul-2016 17:00:24
t2 = mu.*2.0;
t3 = lambda+t2;
A = reshape([t3,0.0,0.0,0.0,mu,0.0,0.0,0.0,mu,0.0,lambda,0.0,mu,0.0,0.0,0.0,0.0,0.0,0.0,0.0,lamb... |
clc;
clear;
close all;
% Electrical Parameters
Rc = 0.33;
Rl = 2;
Ron = 0.05;
Ro = 100;
C = 56e-6;
L = 10e-3;
Vin = 15;
Vj = 0.1;
% Sampling period
Ts = 1e-4;
% Compute the equilibrium point
x2_eq = 5;
x1_eq = x2_eq/Ro;
x_eq = [x1_eq;x2_eq];
u_eq = (Ro*Vj + Rl*x2_eq + Ro*x2_eq)/(Ro*Vin + Ro*Vj - Ron*x2_eq);
% Crea... |
function Vxterm = get_Vx_term(x, V0, a, E)
% get the RHS of Schrodinger's equation ...
hbar = 1.0546E-34; %hbar in SI units
mp = 1.6726E-27; %mass of proton in SI units
qe = 1.6022E-19; %charge on electron to convert eV -> J
if abs(x) > a
Vx = 0;
else
Vx = V0;
end
Vxterm = 2.*mp.*(Vx-E).*qe/(hbar.^2... |
clear;clc;close all;
global ay;ay=[];
global gun;gun=[];
global ortalamaFiyat;ortalamaFiyat=[];
global ortalamaSicaklik;ortalamaSicaklik=[];
global maxFiyat;maxFiyat=[];
global minFiyat;minFiyat=[];
global minSicaklik;minSicaklik=[];
global maxSicaklik;maxSicaklik=[];
veri=importdata('veri2013.mat');
boyut=size(veri);
... |
function f = lfilter(a, cond)
f = {};
for i=1:length(a)
if (cond(a(i)) == 1)
f(end+1) = {a(i)};
end
end
|
%{
# Rig
rig_manufacturer: varchar(50)
rig_model: varchar(30)
---
rig_note : varchar(100)
%}
classdef Rig < dj.Manual
end |
function[phi_nr,phi_rear,phi_r,B] = all_loss(n_i,n,p,phi_rear_no_bias,Cn,Cp,tau_SRH,SRH_depletion_zero_bias,phi_r_zero_bias,V,Tc,E,alpha,nr,L)
fund_consts;
B = SVR(V,E,n,p,alpha,nr,Tc); % bimolecular recombination coefficient
SRH = (SRH_calc(n,p,n_i,tau_SRH))*L;
Auger =(Auger_ca... |
function [t,x] = extract_anchored_timeseries(ratN,chanN,fileN,offset,len,skip)
% % Return values % %
% x - data values
% t - time in days
plot_on = 0;
if (~exist('ratN','var')); ratN=4; end
if (~exist('chanN','var')); chanN=2; end
if (~exist('fileN','var')); fileN=26; end
if (~exist('of... |
%% prepare mean trajectories - MUA each cell mean only
% one colour per recording
figure; hold on
sp1=subplot(1,2,1);hold on
title('WT (N=15) Mean Burst Trajectories')
cmap=hsv(numel(meta.archive.WT_filenames));
clear X Y Z
for file_idx=1:numel(meta.archive.WT_filenames)
[X{file_idx} Y{file_idx} Z{file_idx}] =tubeplot... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% function loadHistos(type)
% Loads all the histograms and stacks them into several ~500MB structure.
% Should greatly speed up the nearest-neighbor computation
%
% Input parameters:
% - type: either 'sky', 'ground' or 'vertical'. Indicates ... |
% plot coverage of nxn scara discretizations
belt = ConvBelt;
goal_y = belt.robo2goal;
belt_bottom = belt.robo2bottom;
belt_top = belt.robo2top;
blr = belt.left_right;
height = belt.height;
top_corners = [-blr belt_bottom 0;
-blr belt_top 0;
blr belt_top 0;
blr belt_botto... |
function convolvedFeatures = cnnConvolve(patchDim, numFeatures, images, W, b, ZCAWhite, meanPatch)
%cnnConvolve Returns the convolution of the features given by W and b with
%the given images
%
% Parameters:
% patchDim - patch (feature) dimension
% numFeatures - number of features
% images - large images to convolve... |
function Tr = epoch_rmnan(Tr)
kp = [];
for i=1:size(Tr.data,1)
tmp = Tr.data(i,:,:);
tmp2 = sum(tmp(:));
if ~isnan(tmp2)
kp = [kp i];
end
end
ecfg.kp = kp;
Tr = epoch_trs(Tr,ecfg);
end |
%problem parameters
b = 0.5;
h = 0.3;
L = 5;
P = 0.01;
U = @(Y) P*L.^3/4/b/h^3./Y;
%shape parameter
A = 25;
%scale parameter
B = 1200;
%%
%%MONTE CARLO
disp('======================MONTE CARLO========================')
%number of samples, Monte Carlo
Nmc0 = 1e6;
%draw random samples Nmc times
disp('sampling............. |
% written by professor Jay McClelland
function [ ] = Act( )
% here we act according to the action selected
% by selectAction
global w p;
if w.out.chooseHand == 1
w.rS.handPos = w.rS.handPos + w.out.handStep;
w.rS.td = p.handTime;
else
w.rS.eyePos = w.rS.eyePos + w.out.eyeStep;
w.rS.td = p.... |
function varargout = doc_nlpsol(varargin)
%DOC_NLPSOL Get the documentation string for a plugin.
%
% char = DOC_NLPSOL(char name)
%
%
%
%
[varargout{1:nargout}] = casadiMEX(812, varargin{:});
end
|
clear all;
close all;
image = imread('../data/desert/sun_adpbjcrpyetqykvt.jpg');
I = im2double(image);
[filterBank] = createFilterBank();
[filterResponses] = extractFilterResponses(I, filterBank);
for k = [3,8,13,18]
figure(k)
resp = filterResponses(:,:,k*3-2:k*3);
for i = 1:3
subplot(1,3,i),imshow(... |
function linearODESSEP2X4Inact2factor2(T,I)
global k1 k2 k3 k4 k5 k6 L1 L2 L3 L4 L5 L6 W1 W2 H0 H11 H5 kd1 kd2 kd3 kd4 ks1 ks2 ks3 ks4 H3 H3D H4 g1 g2 E1 E2 delta epsilon mu A J V n1 n2 n3 r1 r2 r3 v1 v2 v3 Acell p0 err Q;
%#codegen
generatorMatrixP2X4Inact2factor2();
Nt=length(T);
for i=1:Nt
p0=p0*expm(Q*... |
function [C X Y X_nonorthogonal fhandle] = sgplvmDisplayPrivate(model,x,type,N,display,fid,verbose)
% SGPLVMDISPLAYPRIVATE Display orthogonal subspace of sgplvm model
% FORMAT
% DESC Displays the output variance over observation orthogonal
% latent subspace
% ARG x : latent location
% ARG type : type of display
% ARG ... |
%%---------------------------------------------------------------
%% Function to generate tone (DDS) at any sampling frequency
%%
%% (C) MMRFIC Technology Pvt. Ltd., Bangalore INDIA
%%---------------------------------------------------------------
%% Version History: (in reverse chronological order please)
%%
%% V0.1 ... |
function r_rot=rotate_points(pr,dir,rot_cen,angdeg)
% Rotate points around vector, parallel to one of 3 cartezian axis.
% Inputs:
% pr -- 3xNpoints in 3D space
% dir -- 1,2 or 3 -- selector for one of the rotation axis
% rot_cen -- centre of rotation : row vector of 3 elements
% (size(rot... |
function render_SHREC( subset, reverse_flg )
% subset = 'train_normal'
addpath(genpath('mvcnn_utils'));
fig = figure('Visible','off');
if nargin < 2
reverse_flg = false
end
dirpath = ['data/' subset]
imdirpath = ['images/' subset]
mkdir(imdirpath)
files = dir(dirpath)
inds = 3:length(files);
if reverse_flg
ind... |
%% Redes Neuronales Competitivas Multi Capa
clear all %limpiar Workplace
close all %limpia ventanas
clc %limpia command window
%% Cargar Datos
load LogReg1.txt;
data = LogReg1;
Y = data(:,3)';
X = data(:,1:2)';
%% Conjunto de Entrenamiento y Prueba
ndat = round(0.9*size(Y,2));
Ytrain = Y(:,1:ndat);
Xtrain = X(:,1:ndat)... |
% this function generates an input vector according to the number of
% heterozygous and homozygous carriers
%input:
%NumOfPersons - the number of persons in the test
%NumHeterozygousCarriers - the number of Heterozygous in the Subject groups
%NumHomozygousCarriers - the number of Homozygous in the Subject groups
func... |
function [U,ELEM,d] = assembleSolution(ELEM,BSpline,BC,solutionVector)
% Extract information from BSpline
eCONN = BSpline.elementConnectivity;
C = BSpline.decomposition.localExtractionOperator;
x = sym("x","real");
d = solutionVector;
nElem = length(ELEM);
% Node->DOF mapping
DOFS = fieldnames(BC);
nDOF = length(DOFS... |
%% Equation 3
omega = logspace(0, 5, 1000);
eqn = 20*log10(0.00006) + 20*log10(omega/2 + 1) + 20*log10(omega/100 + 1) - 20*log10(omega/1000 +1) - 20*log10(omega/10000 + 1);
semilogx(omega, eqn, '-*');
grid on;
title('Equation 3: H(s)');
xlabel('Frequency(Hz)');
ylabel('H(s) = Gain(dB)');
print('equation3db', '-dpng'); |
function [mCHE, mCVE, mCHS, mCVS] = idCalcFeedForwardCorTables(idName, idParams, fileNamesMeasCOD, dirMeasCOD, dirMeasCorResp, arIndsBPMsToSkip)
%Calculate Feed-Forward Correction Tables vs Undulator Parameters for 2 Horizontal and 2 Vertical correctors.
%NOTE: Horizontal correctors are those displacing electron orbit ... |
function F3rdDraft
% al & bt must be grater than one.. according to paper
global r1 a b c al bt Tau
% Inputs
a=0.1;
b=0.2;
c=0.1;
al=1.5;
bt=3;
Tau=nan; % the treshold valu, nan= mean of data
nn=20000; % the number of samples to plot the graphs
% sample generation data
% n=10000; % number of Series
% k=2; % number of a... |
load('history_734829708443');
r=hisrr(1,:,:);
hp=plot(r(1,:,1),r(1,:,2),'k.');
axis equal;
for lc=1:3:size(hisrr,1)
r=hisrr(lc,:,:);
%hp=plot(r(1,:,1),r(1,:,2),'k.');
set(hp,'Xdata',r(1,:,1),'Ydata',r(1,:,2));
drawnow;
end |
clear; %clear la mémoire
clc; %clear le texte de la console
% --------------- INITIALISATION ---------------
disp('TP3')
%[ Dev vbaf vbof rba rbo tballe ] = Devoir3([ 0 0 0 ]', [ 6.85 0 6.85 ]', 0.66);
%[ Dev vbaf vbof rba rbo tballe ] = Devoir3([ 0 0 0 ]', [ 28 0.5 10 ]', 1.1);
%[ Dev vbaf vbof rba rbo tballe ]... |
%% PERPDIST - Perpendicular Distance Calculator
%
% Usage: perpDist = perpdist(p_x, p_y, grad, y_int, x_int, vertFlag)
%
% Arguments:
% p_x - x coordinate of point
% p_y - y coordinate of point
% grad - gradient of line
% y_int - y intercept of the line
% ... |
classdef downSample
% DOWNSAMPLE contains methods to downsample a signal with consecutive
% integers, or downsample a signal by a factor of two and continue to
% downsample the result by a factor of two. It also plots the results
% Returns a cell array of downsampled signals
% Takes a signa... |
function h = pa_verline(x, style)
% PA_VERLINE(Y)
%
% Plot vertical line through current axis at width X.
%
% PA_VERLINE(...,'LineSpec') uses the color and linestyle specified by
% the string 'LineSpec'. See PLOT for possibilities.
%
% H = PA_VERLINE(...) returns a vector of lineseries handles in H.
%
% See also PA_HO... |
MatFiles=dir('*analysis_matlab.mat');
name=strcat(MatFiles(1).name);
Calcium=load(name, 'DenoisedTraces');
Calcium=Calcium.DenoisedTraces;
MatFiles(1).number=size(Calcium,1);
%Spikes=load(name, 'Spikes');
%Spikes=Spikes.Spikes;
Noise=load(name, 'Noise');
Noise=Noise.Noise;
Fitness=load(name, 'idx_components');... |
function plot_Gaussian_Elimination_Scaling()
% Plots the operation count required to row reduce a square matrix to
% reduced row echelon form versus the size of the matrix for a
% variety of matrix sizes. This script calls the script
% "go_Go_Gaussian_Elimination", which takes number of rows/col... |
function [coordinate] = input_shipcoordinates(prompt, index, length, direction, user_ships)
code = spriteCode();
close(figure(1));
fprintf(prompt,index);
scene = simpleGameEngine('Battleship.png',84,84);
drawScene(scene,user_ships);
% get the coordinate of the mouse
[row,col] = getMouseInput... |
%This file demonstrates the use of the function
%"magnetic_field_current_loop.m".
%Kilian O'Donoghue
%30th July 2013
clc
clear
close all
%Define global variables
global u0
u0=4*pi*1e-7; %permeability of free space
%Define coil parameters
I0=1; %Coil current in Amps
a=.1; %Coil radius in m
x_p... |
function varargout = func_1d_lobatto(varargin)
% Grab input arguments
%-------------------------------------------------------------------------------
verts = varargin{1};
order = varargin{3};
qx = varargin{4};
gbool = (nargout > 1);
% Perform some error checking
%---------------------------------------------------... |
function [MeHgMicroP MeHgNanoP MeHgPicoP] = getPhytoplanktonHg(DOC,MeHgWaterConc)
%GETPHYTOPLANKTONHG
% phytoplankton MeHg concentration in micro, nano, and pico plankton
% Cell Radius
Radius = [1 11 110]; %[pico nano micro] um
%Volume in um3
VolumeOfCell= 4./3.*pi.*Radius.^3 ; % um^3
%uptate rate amole/um... |
function q = example_kinematic_trajectory
% create a trajectory that extends the leg then bends the knee
N = 50;
q = zeros(5,2*N);
q(2,:) = 1;
q(3,1:N) = linspace(-pi/4,pi/4,N);
q(3,N+1:end) = pi/4;
q(4,N+1:end) = linspace(0,pi/3,N);
end |
%% Noisy Data Test
%% Generate Noisey Trainning Data
probaddnoise = 0.1;
nsample = size(train,1);
temp = rand(size(train));
train(train==0) = temp(train==0)<probaddnoise*1;
%% Train EM based on original EM
for i = 0:9
eval(['lambda = EM' num2str(i) '.lambda;']);
eval(['P = EM' num2str(i) '.P;']);
P(P==0) =... |
function res = log_post_CES(y,X,gamma,h,gamma_0,V_0)
%res ... logaritmus jadra posteriorni hustoty
%CES funkce
fx = gamma(1)*(gamma(2)*X(:,2).^gamma(4) +gamma(3)*X(:,3).^gamma(4)).^(1/gamma(4));
%logaritmus (5.24) z Koop
res = -1/2*h*(y-fx)'*(y-fx) -1/2*(gamma-gamma_0)'*inv(V_0)*(gamma-gamma_0);
%osetreni nulove hustot... |
function pick_ALOT_of_Points()
NVec = [1:1:10 20:5:100 125:50:1000 1500:250:10000 15000:5000:1e5];
for i=1:length(NVec)
distN(i) = estimate_Point_Distance(NVec(i),1);
end
semilogx(NVec, distN, 'r*');
xlabel('N');
ylabel('Estimated Distance');
set(gca, 'Fontsize',18);
|
function [new,win] = iceSkate(cellarr)
skater = cellarr(:,1);
if strcmp(cellarr{1,2},'Long Program')
LP = cellarr(:,2);
elseif strcmp(cellarr{1,2},'Short Program')
SP = cellarr(:,2);
else
BE = cellarr(:,2);
end
if strcmp(cellarr{1,3},'Long Program')
LP = cellarr(:,3);
elseif strcmp(cellarr{1,3},'... |
function [M] = invmat(A,B)
% the objective is to calculate A^{-1}B, A is n*n, B is n *m
% it is better if A is sparse
% tic
[n, m] = size(B);
M = sparse(n,m);
[F,t1] = linfactor(A);
for i = 1: m
M(:,i) = linfactor(F,full(B(:,i)));
end
% toc
% t= toc - tic; |
function [f,xi] = fObj_U(U, theta_rj, T_rj, Vt, L, C, l)
T_rj = double(T_rj);
T_rj(T_rj~=1) = -1;
UV = U*Vt;
xi = max(l-T_rj(:).*(theta_rj(:)-reshape(repmat(UV,L-1,1),[],1)), 0);
f = 0.5*sum(U.^2) + C*sum(xi);
end
|
function result = mxm_write(data)
result = mxMonarch('write',data);
end
|
function ShowGraph(GraphPoint, Arc)
%绘图函数
%输入：
%GraphPoint：计算得到的各点位置
%Arc：图的连接
scatter(GraphPoint(:,1),GraphPoint(:,2),'filled','b');
hold on
len1 = length(Arc);
for i = 1 : len1
len2 = size(Arc{i},1);
for j = 1 : len2
p1 = Arc{i}(j, 1);
p2 = Arc{i}(j, 2);
x1 = GraphPoint(p1, 1);
... |
function SeismicData = getSeismicData(s1, s2, dataNum)
%%% 진동센서로부터의 데이터를 무선으로 받는 함수
value1_Save = []; % initialize seismic data matrix1
value2_Save = []; % initialize seismic data matrix2
dataName = ['Data/Seismic/rawData/test', num2str(dataNum), '.xls'];
disp('Staring to get data..........');
... |
clear all; close all; clc
[X_tr, Y_tr, y_tr] = LoadBatch('Traindata80.mat');
% data = A.data;
% data = data(1:10,:)';
X_tr = uint8(X_tr);
% y_tr = categorical(y_tr);
n = size(X_tr,2);
I = reshape(X_tr, 32,32,3,n);
figure(1)
montage(I(:,:,:,1:3), 'Size', [1,3])
I2 = flipdim(I ,2);
figure(2)
montage(I... |
function [X,Y] = BoxMuller(N)
Var1 = rand(1,N);
Var2 = rand(1,N);
X=(-2*log(Var1)).^(1/2).* cos(2*pi*Var2);
Y=(-2*log(Var1)).^(1/2).* sin(2*pi*Var2);
end
|
clc % Clear command window history
clear % Clear workspace memory
close all % Close all figure frames
n = -50:1:240;
Ts = 0.1;
y = ( ( mod( floor( n), 7 / Ts) < 5 / Ts) .* ( mod( floor( n), 7 / Ts) >= 3 / Ts)) * 4;
close all;
figure(), plot( n, y);
axis([-50,240,-1,5]);
% FSE Coefficients
% f = @(k)... |
%% Markov process model of Fault-Tolerant Switching Mechanism
%% clear all
clear all;
close all;
clc;
%%
n = 3;
% fsw{1}(1,:) = [1];
% fsw{1}(2,:) = [1];
%
% fsw{2}(1,:) = [2 2];
% fsw{2}(2,:) = [3 3];
%
% fsw{3}(1,:) = [1 1 2];
% fsw{3}(2,:) = [3 3 3];
%
% [~, length_fsw] = size(fsw);
fsw{1} = [1 1 2];
fsw{2} =... |
function U_nk = obtain_U(Ux,Uy,N,K)
%obtain_U takes as inputs Ux and Uy for every Nth vehicle and Kth state
%and obtains the 2-norm so that it can be constrained as a euclidean ball in
%cvx. Ux and Uy are the acceleration in a 2-D coordinate system.
U_nk = cvx(zeros(N,K));%use "cvx" to be solver-friendly
for i = 1:N
... |
function a=input_matrix(str, n)
disp(strcat('Enter matrix: ', str));
a=[];
for i=1:n
disp(strcat('Enter values for row no.', num2str(i)));
for j=1:n
a(i, j)=input('');
end
end
end |
function [simpleGamma, measInt, measCie, lvlSet] = calibDisplay_pldaps(p, mode)
% function [simpleGamma, measInt, measCie, lvlSet] = calibDisplay_pldaps(p, mode)
% [p] = currently running PLDAPS structure
% [mode]: 0 = grey[k] only, no color measurements (Spectral Power Distribution[SPD]);
% [1 2 3 4] == [R ... |
function image_pick = XuPickFramesRadiog(image)
image_pick=image;
image_z_ave = squeeze(mean(mean(image,1),2));
z_incorrect = find(image_z_ave<50);
image_pick(:,:,z_incorrect)=[]; |
% BRRIEF:
% Template for explicit invariant set computation. You MUST NOT change
% the output.
% INPUT:
% Q, R: State and input weighting matrix, dimension (3,3)
% OUTPUT:
% A_x, b_x: Describes polytopic X_LQR = {x| A_x * x <= b_x}
function [A_x, b_x] = compute_X_LQR(Q, R)
% get basic controller parameters... |
function et_loop(input)
gain = input;
doloop('orn_inputs_depr', gain, @ET)
end |
clc
clearvars
rng('shuffle')
addpath('./model/')
all_n = [10, 20, 30, 40, 50];
all_m = [10, 20, 30, 40, 50];
N = 10;
kfold = 5;
N_test = 1000;
radius = 1;
run_count = 100;
epsilon = [1e-4, 5e-4, 1e-3, 5e-3, 1e-2, 5e-2, 1e-1];
param(1:run_count) = struct('W',[],'H',[],'h',[],'C',[],'d',[], ...
... |
% set atten, lock and FSW scan, big piece, dev 30, 20180714, 10:11 PM
%% 20180915, top dev 61, optical M2 (the other NB), red
cfs = [1.972e9, 2.108e9, 2.674e9];
fswconfig = struct('bw', 10e3, 'span', 20e6, 'sweeptime',1);
attens = getAttensFromPowers(linspace(0.5e-5,10e-5, 20), 30e-6, 10);
attens = round(a... |
function adj = meshAdjacencyMatrix(faces, varargin)
%MESHADJACENCYMATRIX Compute adjacency matrix of a mesh from set of faces.
%
% ADJMAT = meshAdjacencyMatrix(FACES)
% Returns a sparse NV-by-NV matrix (NV being the largest vertex index)
% containing vertex adjacency of the mesh represented by FACES.
% FA... |
%global volume_ratio;
%global c_f0;
%global c_d0;
%global delta_h_p;
global volume_ratio;
global c_d0;
global delta_h_p;
global c_f0;
%global c_d0;
%volume_ratio=0.5;
%c_f0=1.71;
%c_d0=600;
%c_f0=.1;
van_coe=73.07/100;
%T=293;
%niu=2;
A=2;
%R=8.3144621;
%r=R;
%global c_d0;
%global c_f0;
%global volume_ratio;
%o_p_ener... |
function F = indirect_fsolver(X, Chaser, Target, Nav, t0, fixed_x0, Opt_sol)
X0 = [fixed_x0; X(1:4)];
tf_rel = X(5);
slack = X(6);
options = odeset('RelTol',1e-12,'AbsTol',1e-12);
odes = @(tau, X) indirect_odes(tau, X, tf_rel, Chaser);
[tau,Y] = ode113(odes, [0 1], X0, options);
Yf = Y(end,:)';
PSI = in... |
%vannes
vannes=tango_get_db_property('anneau','vanne_secteur');
for i=1:48;
state= tango_command_inout2(vannes{i},'State');
fprintf('vannes %d = %s\n',i,state)
end |
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