text stringlengths 8 6.12M |
|---|
clear all
close all
res =[256 256 256];
spacing = 320/256; %inputs to mimics
frames = 15;
% Load in mask data
mask_name = 'RV_grayvalues.txt';
mask = zeros(size(image));
[xM,yM,zM,intensity] = textread(mask_name,'%f,%f,%f,%f');
xM = (xM/spacing)+1;
yM = abs((yM/spacing)-256);
zM = abs((zM/spacing)-256)... |
function [csum] = myBin_per_Ares(I, A)
%
h = imhist(I);
%plot(h);
csum = cumsum(h);
lambda = find(csum>A,1);
BW = I > lambda;
imshow(BW,[]);
%plot(csum);
end
|
tic;
times_sim = 5e6;
mu = 1000;
assembly_life = exprnd(mu, times_sim, 5);
route_1 = min(assembly_life(:, [1 2]), [ ], 2);
route_2 = min(assembly_life(:, [3 4]), [ ], 2);
route_3 = min(assembly_life(:, [1 4 5]), [ ], 2);
route_4 = min(assembly_life(:, [2 3 5]), [ ], 2);
mean_life = mean(max([route_1, route_... |
function [ curve, x ] = maxECcurve( maxima, alpha_percentile, increm )
% maxECcurve( maxima ) estimates the tail of the EC curve from the
% distribution of observed maxima over many iid iterations
%--------------------------------------------------------------------------
% ARGUMENTS
% Mandatory
% maxima
% alpha_perc... |
function y=trz(a)
y=eye(4);
y(3,4)=a;
end |
%%% Field length estimation
% Updated 12/5/2015 JRG
% http://www.aerospaceweb.org/question/performance/q0088.shtml
function [FAR_dist] = TO_length_est(parameters)
W0 = parameters.W0; %[lb]
T0 = parameters.T0; %[lb]
Sref = parameters.Sref*0.09290304; %[m^2]
cWing = parameters.cWing*0.3048; %[m]
Dfus = parameters.Dfus*... |
clear all
colormap jet
%%% settings %%%
N = 20; % oscillators placed along one dimension of the grid
Nn = N^2; % total number of oscillators
levels = 20;
dt = 1e-2; % integration time step
t_sim = 1; % simulation ti... |
function [P, X] = vaCurrent(barOffset, params)
%% Vernier acuity experiment on cone absorptions
%
% Testing if people can see the difference between two cases:
% 1) A straight line
% 2) Two straight lines barOffset pixels apart
%
% Vernier acuity in human shows the positional acuity is around 6 sec of
% ... |
function varargout = workloop(varargin)
% function [lennorm,worktot,workpos,workneg,workposact,worknegact,work] = workloop(t, x,y, fmus, act, opts...)
% or workloop(t, xl,yl,fmusl,actl, xr,yr,fmusr,actr, opts...)
% or workloop(t, xl,yl,ul,vl, fmusl,actl, xr,yr,ur,vr, fmusr,actr, opts...)
opt.ordlen = 1... |
%MLS_OCCLUDE_INTERPOLATE --- Combination interpolation-mls while invalidating
% occluded sections
% INPUTS:
% point_cloud Point Cloud data to interpolate
% x_limit maximum dimension for x-axis
% y_limit maximum dimension for y-axis
% h guassian parameter for mls
function resu... |
%% Storage procedure
% Storage procedure for this pupil still is simple.
for vvv = 1:NumberOfVariables
switch vvv
case 1; temp = Code;
case 2; temp = i;
case 3; temp = ii; % within trial
case 4; temp = Trial... |
function retval = find_best_split (rows,labels)
best_gain = 0;
best_featue=NaN;
best_value=NaN;
t_r={};
f_r={};
current_uncertainity = gini(rows,labels);
n_features = length(rows)-1;
for i=1:n_features
col = rows{i};
values = intersect(col,col);
for j=1:length(values)
true_rows = {};
... |
% sieve of Erasthotenes third version
max = 10000; % limit for the max prime number
if (nargin > 0)
max = int64(str2num(argv(){1}));
end
tic();
p = [1:max]; % vector of integer numbers
n = int64(sqrt(max)); % limit for dividers
for i = 2:n % remove multipliers of odd numbers
if p(i) > 0 % not cleared yet
p... |
function [width, length] = rectangle(x)
width = x/sqrt(10);
length = width * 3;
end |
function [Svv_channel,Lvj,PSD,Nseg] = cross_spectra(subject, properties)
% Authors:
% - Deirel Paz Linares
% - Eduardo Gonzalez Moreira
% - Pedro A. Valdes Sosa
% Date: March 16, 2019
% Updates
% - Ariosky Areces Gonzalez
% Date: January 30, 2021
%%
%% Preparing params
%%
data = subject.MEEG.... |
% MATLAB code to compute Crank Nicolson for:
% U_t = U_xx
clear all; clf; close all; clc;
% x domain
x_min = 0; x_max = 10;
dx = 0.1; % Arbitrarily Chosen
% t domain
coef = 10; % Some relationship between dt/dx^2 to vary
delta_t = dx.^2.*coef;
t_min = 0; t_max = 2;
Nt = (t_max-t_min)/delta_t;
% Initial Mesh
x = x... |
function w = normalEqWithoutBias(Xtrain, Ytrain)
a = inv(Xtrain'*Xtrain);
b = Xtrain'*Ytrain;
w = a*b;
end |
function ans = your_fcn_name(x)
sum(sum(x));
end |
classdef Arena < handle
%ARENA Arena class modelling an arena
% Arena class modelling an arena
properties
% Simulation parameters
simId = 0; % Simulation identifier
name = 'defaultArena'; % Arena name (used for movie file)
typeName ... |
function [] = lotsa_plots(n, m)
%%%%%%%%%%%%%%%%%%%%%
%%% calculations! %%%
%%%%%%%%%%%%%%%%%%%%%
tic;
% n = 4; m = 1000;
% generate matrix of values - lots of columns, n = 4 rows
x_m_by_n = normrnd(0,1,n,m); % n rows x m columns
% generate mean, variance, and t stat for each column
x_bar = ... |
function converthitranfile()
[filename, pathname] = uigetfile( ...
{'*.par','HITRAN files (*.par)'}, ...
'Choose a file...');
[~,~,fileext] = fileparts(filename);
if isempty(filename)
return
elseif strcmp(fileext,'.par')
% The file is a *.par file ... |
% rewritten for NICO PC, if using MAC, use older version
function [keys RT k] = qkeys(startTime,dur,deviceNumber)
% If dur==-1, terminates after first keypress
myStart = GetSecs;
if IsOSX
KbQueueCreate(deviceNumber);
KbQueueStart();
if dur == -1
while 1
[k.pressed, k.firstPress, k.fir... |
function fname = uigetfilename()
options.Resize='on';
options.WindowStyle='normal';
options.Interpreter='none';
prompt = 'Enter file ending:';
name = 'File Name';
numlines = 1;
defaultanswer = {'_0'};
fname=inputdlg(prompt,name,numlines,defaultanswer,options);
end |
function trialseq = ALTS_backend(settings,trialseq,id)
% SHORTCUTS
FC = settings.layout.color.fixation;
OW = settings.screen.outwindow;
owd = settings.screen.outwindowdims;
% INTRO
ALTS_intro(settings, trialseq, 1);
% Randomly assign to slow/fast haptic nov
if rand >= .5; trialseq(:,id.haptic_id) = 1; else trialseq(... |
function varargout = symcmap(cmap0,ctr,nsteps)
if (nargin < 3),
nsteps = Inf;
if (nargin < 2),
ctr = 0;
end;
end;
if ctr > 1
error('ctr parameter is a fraction < 1');
end
if (isnumeric(cmap0) && (size(cmap0,1) ~= 3)),
error('cmap can only have three entries.');
end;
if (ischar(cmap0)),
... |
function [ X,k ] = Gseid( A, b, X0, eps )
%GSeid Iteration
D = diag(diag(A));%Get diag(A)
L = -tril(A, -1);%Get -L
U = -triu(A, 1);%Get -U
B = D \ (L + U); %Get Bg
f = D \ b; %Get fg
X = B * X0 + f;%First iteration
k = 1;
%Start Iteration
while norm(X - X0) >= eps
X0 = X;
X = B * X0 + f;
k = k + 1;
end
|
function [event event_idx event_common_idx] = get_event_wordPair()
load('SPIC_text.mat');
for i=1:99
event1(i,1) = duet_1(i);
event1(i,2) = duet_1(i+1);
end
for i=1:99
event2(i,1) = duet_2(i);
event2(i,2) = duet_2(i+1);
end
event = [event1;event2];
event_idx = zeros(size(event));
event_common_idx = z... |
% Script for estimating initial parameters
% (C) Copyright 2019 The Huang Lab
%
% All rights reserved Weldon School of Biomedical Engineering
% Purdue University
% West Lafayette, Indiana
% ... |
function theta = estimate_GRF_parameters(loc, ind_o, y_o, bins, nu)
% Only use 10000 pixels at most for estimation
if length(ind_o) > 10000
cap = 10000;
else
cap = length(ind_o);
end
% Get positions for estimation
ind_o_cap = ind_o(1:cap);
loc_o_cap = loc(ind_o_cap,:);
%% Make an estimate of t... |
function out = test
opt = solopt;
load HST_tensor.mat
load materials.mat
load swim_img.mat
load tensor_parafac.mat
load tensor_tucker.mat
% B0= rand(size(A,1), min(size(A,2) - 1, 5));
B0 = rand(size(A));
% Flaw???: No facility to input size of matreces B and C..
m... |
% summarize conserved clusters as graph
% P1 = vertcat(Pairs_AllClusAllFish{:,1});
% P2 = vertcat(Pairs_AllClusAllFish{:,2});
% Nodes = unique([P1;P2],'rows');
% numNodes = length(Nodes);
%
% [~,IX1] = ismember(P1,Nodes,'rows');
% [~,IX2] = ismember(P2,Nodes,'rows');
%
% G = graph(IX1,IX2); figure;plot(G)
% bins = c... |
function [distVal,jumpcost] = performMatchingOnComponentImg_Old(testMat,realIndexTest,componentRefImg,ImgRef,testImgRw,testImgCol,technique,featureFunc,avgWidth,heightMatter,testImgPath,imageFiePath_1,testName)
distVal = -5;
% if(ceil ( (size(ImgRef,2)) * (30/100) ) <= (testImgCol) )
refComponentMat = AnalyzeComponen... |
function [c,ptr,cw,ck]=de_2n_code_sub(biny,n,z,ptr)
len=length(z); lenw=sum(z);
ptrinc=n*len;
tem=biny(ptr:ptr+ptrinc-1); ptr=ptr+ptrinc;
tem=char(tem+48);
tem=reshape(tem,n,len)';
tem=bin2dec(tem)'+1;
cw=tem(1:lenw); ck=tem(lenw+1:len);
c=separate_inv(z,cw+2^n,ck);
|
function process_phase_circ_plot(filename_h, amp_range)
S = load(['Trials_' filename_h '.mat']);
f_num = length(S.Trials);
for i = 1:f_num
clearvars c_phase
F = figure;
c_phase = S.Trials(i).Phase(S.Trials(i).Amps>amp_range(1)&S.Trials(i).Amps<amp_range(end));
A = circ_plot(c_phase,'pretty');
set(A,... |
function cropImageInfo = batchCropImage(pixel, imfolder, exfolder)
% batch cropping image and throw images too small
% get image paths
imgs = imageDatastore(imfolder,'IncludeSubfolders',true,'FileExtensions','.png','LabelSource','foldernames');
list = [];
h = waitbar(0,'Cropping images...');
for i = 1:length(img... |
function nFiles=FlylabPlotSpeed(dirspec, filespec)
f = gcf;
filenames = GetFilenames(dirspec, filespec);
nFiles = length(filenames);
speedTotal = [];
speedAll = [];
tAll = [];
for i = 1:nFiles
filedata = FlylabReadFile(filenames{i});
if (FlylabIsValidFiledata(filedata))
... |
function bgsubtracted = bgsubtract(mov)
maxproj = uint8(max(mov,[],3));
bgsubtracted = uint8(zeros(size(mov)));
for k = 1:size(mov,3)
bgsubtracted(:,:,k) = maxproj - mov(:,:,k);
end |
function lsFile = trollify(this, varargin)
ASSIGN_TSERIES_FORMAT = 'DO %s = %.16g + dzero; \n';
ASSIGN_SCALAR_FORMAT = 'DO %s = %.16g; \n';
STEADY_REF_FILENAME = 'SteadyRef.inp';
TIME_STAMP = datestr(now( ));
opt = passvalopt('model.trollify', varargin{:});
switch upper(opt.ParametersAs)
case 'EXOGENOUS'
... |
function U0=atgetU0(ring)
%
% computes Energy loss per turn in eV .
%
%see also: ringpara atsetcavity atenergy
%S.Liuzzo modified to use atenergy.m
[~,~,~,~,U0]=atenergy(ring);
return
%
% emass=510998.928/1e6; % electron mass in MeV
%
% a = findcells(ring,'Energy');
% if isempty(a);
% gamma = 3000/emass;
% els... |
function [success_status,img, data_buffer]=rad_mat(scanner,runno,input_data,options)
% [success_status,img, buffer]=RAD_MAT(scanner,runno,input,options)
% Reconstruct All Devices in MATlab
% rad_mat, a quasi generic reconstruction/reformating scanner to archive
% pipeline.
% It relies on a dumpheader perl script which ... |
%% Set environment
addpath(genpath('nifti_utils'));
addpath(genpath('dwmri_visualizer'));
data_path = 'data';
%% Volume test
% Load data
fa_vol = nifti_utils.load_untouch_nii_vol_scaled(fullfile(data_path,'fa.nii.gz'),'double');
mask_vol = nifti_utils.load_untouch_nii_vol_scaled(fullfile(data_path,'mask.nii.gz'),'log... |
classdef PaperRaceEnv < handle
%PAPERRACEENV Paper Race környezet
% Osztály, ami környezetet biztosít a paper race játékhoz.
properties
TrkPic
Trk
GGPic
SzakLis
lepesek = 0 % az eddig megtett lépések száma
Szak = 6 % a következő átszakítandó szakasz ... |
classdef xmon < sqc.qobj.qubit
%
% Copyright 2016 Yulin Wu, USTC
% mail4ywu@gmail.com/mail4ywu@icloud.com
properties
aczSettings@sqc.qobj.aczSettings
end
end |
function [X, time] = solve_implicit(A, b)
tic
[L, R] = Householder_implicit(A);
right = Apply_Q(L, b);
opts.UT = true;
X = linsolve(R,right,opts);
time = toc;
end |
% Parallel_call_function_10000
% This script calls ABC_Algorithm in a parallel way so that the particles
% are computed in parallel subsets.
%% For loop
function Parallel_function_VTD_AbsDist_Modelv5_v1_019()
%%
%Here we fit a data set that has been simulated with a parameter vector
%that we choose.
functionname = mfil... |
[x,t] = wine_dataset;
size(x)
size(t)
setdemorandstream(391418381)
net = patternnet(10);
% net.divideFcn='divideblock';
% net.divideParam.trainRatio=75/100;
% net.divideParam.valRatio=15/100;
% net.divideParam.testRatio=10/100;
view(net)
[net,tr] = train(net,x,t);
nntraintool
plotperform(tr)
testX = x(:,tr.testInd);
t... |
classdef MaskFft
properties
adjoint = 0;
maskSize
xSize
ySize
zSize
mask
end
methods
function self = MaskFft(mask)
% Get original dimensions mask
self.maskSize = size(mask);
% Put rest of dimensions into zSize
[self.xSize, self.ySize, self.zSize] = size(mask);
... |
%simple function - looks for missing issue dates
function [T,ind]=timefix(time)
ind = ~ismember(time,'') & ~ismember(time,'NaT');
time=time(ind);
%ind = ~ind;
T = datenum(time,'mmm-yyyy');
|
% initiate variables
clearvars;
load('QMDA_HW_05.mat');
% A. plot data kernal G & observed data a a function of x
% plot initialization
figure(1);
clf;
axis ij;
set(gca,'LineWidth',1,'FontSize',14);
colormap(flipud(gray)*0.93);
hold on;
% plot kernal G
imagesc(G);
colorbar;
% figure settings
title('Kernal ... |
function px_theta = samplePDF(h,w,sp_theta,Sigma)
% SAMPLEPDF : sample probability density function
% ---------------------------------------------------------
% h : scale
% w : scale
% sp_theta: sample points of theta, cell array {theta1, theta2}
% Sigma: standard deviation vector
% px_theta: p(x|theta), mesh values
... |
addpath('harris')
addpath('transformation')
vis = 0;
readnew = 1;
tic
for scale = [1,1/2,1/3]
if readnew
% I1 = imread('images/boat/img1.pgm');
% I1 = imread('images/rescaled/00.jpg');
I1 = imread('images/own/origrot.jpg');
I2 = imread('images/own/rot2.jpg');
I1 = imresize(... |
function [trasfData] = tsEvaTransformSeriesToStationaryTrendOnly_ciPercentile( timeStamps, series, timeWindow, percentile, varargin )
disp('computing the trend ...');
[statSeries, trendSeries, filledTimeStamps, filledSeries, nRunMn] = tsEvaDetrendTimeSeries(timeStamps, series, timeWindow, varargin{:});
disp(['computi... |
function [PC_back,intmem_back,cycle_back]=DivAB(PC,cycle,intmem)
intmem_back=intmem;
%load ACC,B
ACC=intmem(225,1);
B=intmem(241,1);
%load PSW
PSW=loadPSW(intmem(209,1));
CY=PSW(1,1);
AC=PSW(2,1);
F0=PSW(3,1);
RS1=PSW(4,1);
RS0=PSW(5,1);
OV=PSW(6,1);
UN=PSW(7,1);
... |
function myVega = Vega(spot,strike,time,interest,sigma)
myExpiry=((169000-aTime)+3600*24*daysact('10-jun-2016', '16-sep-2016'))/(3600*24*252);
d1=(log(spot/strike)+(interest+sigma^2/2)*time)/(sigma*sqrt(time));
myVega = spot*sqrt(1)*normProbDensFun(d1); |
%% ML
% LAB 4, BD: SPAM, Classifier: SVM
% April 2016, MC
clear
close all
clc
i_plot=1; % 1 plot BD
i_lineal=1; % Linear Classifier
i_gauss=1; % Gaussian Kernel Classifier
%% Loading SPAM Database
% load dataspam.txt -a... |
function [TarFileName,TarFileNum] = TargetFile(TarPath)
TarFilePath = dir([TarPath,'*','.txt']);
TarFileNum = 0;
for i = 1 : length(TarFilePath)
TarFileNum = TarFileNum +1;
end
TarFileName = cell(TarFileNum,1);
for i = 1 : TarFileNum
TarFileName{i} = TarFilePath(i).name(1:end-4);
end |
clc;
n = length(lda1);
A = nn.A;
for i = 1 : n
mc1(i, :) = data1(i, :) * log(nn.P0 + eps);
mc2(i, :) = data2(i, :) * log(nn.Q0 + eps);
end;
[p c1] = max(mc1'); [p c2] = max(mc2');
I=log(A./(sum(A')'*sum(A))); I(isnan(I))=0;
I=A;
for i = 1 : n
ILDA(i) = I(lda1(i), lda2(i));
end;
[p ilc]=sort(ILDA);
for i = 1... |
function [A,dA,F,dF,T,dT] = mnlinsinfit(X,Y,F,d)
if nargin < 4
d = false;
end
if size(X,2) > size(X,1), X = X'; end
if size(Y,2) > size(Y,1), Y = Y'; end
if size(F,2) > size(F,1), F = F'; end
if d
YS = max(Y);
Y = Y/YS;
XS = max(X);
X = X/XS;
F = F*XS;
end
[A,dA,T,dT] = mlinsinfit(X,Y,F); %#ok<NASGU... |
%% Decoding LDPC codes using Sum Product Algorithm
clc();
clear all;
close all;
H = xlsread('H_matrix.xlsx'); % Loading the given H matrix in MATLAB
gamma = 3; % Number of 1's in each column of Matrix H
rho = 6; % Number of ... |
function randomFreqPlot(runType, runNb, windowLen, plotQ)
if nargin < 3
windowLen = 4188;
end
if nargin < 4
plotQ = true;
end
accX = 0; accY = 0; accZ = 0; gyroX = 0; gyroY = 0; gyroZ = 0; tau = 0; time = 0;
if strcmpi(runType, 'U')
expFile = sprintf('Experiment... |
clear all; close all;
%
% Digitized data from Gust (Al sample) p.3574
%
xax = [[475 5361];[2887 5361]];
yax = [[475 5361];[475 898]];
dat = [[2427 5293];[2231 5217];[2073 5142];[1907 5082];[1779 4923];[1696 4803];...
[1651 4599];[1636 4449];[1666 4313];[1636 4185];[1560 4011];[1492 3876];...
[1462 3732];[... |
function [imRes] = dpnInterpolate(dx)
%dpnInterpolate - take the ion image and interpolate it across the empty
%rows
% First identify the empty / non-empty rows...
fx = sum(dx.img,2) == 0;
% Create the image subset...
imTmp = dx.img(~fx,:);
% Resize the image to full size
imRes = imresize(imTmp,size(dx.img));
end
|
classdef dimension < double
properties (SetAccess = immutable)
name % name of dimension
value = 1 % value of dimension in terms of other dimensions
dimensions = {} % dimensions
degrees % power of each dimension
end
methods
function dim = dimension(name,value)
... |
clc;clear;
%LOADING DATASET
%load GoodMeasurement_14_bus.mat
load Dataset_B.mat;
%HERE COME USER-DEFINED PARAMETERS OF GN algorithm (using default options is recommended)
eps_tol=10^-5; %stopping criterion for max(abs(delta_x))
Max_iter=100; %maximum number of GN iterations
H_decoupled=0; %use full Jacobian m... |
function y = event_gradient(t,y,k2,thresh,component)
%when the L2 norm of the gradient field is below thresh, the returned y is true, otherwise false.
%note that y is in Fourier space.
%L2 norm of the gradient field is \int_{|| \nabla y(x) ||^2 dx} = \int_{|| k ||^2 ||y(k)||^2 dk}
%k2 should correspond to each ... |
%% ---------------- Send audio -------------------
close all; clear all; clc;
% connect to tcp/ip server
server_ip = 'localhost';
portNum = 10000;
% create tcp/ip obj
t = tcpi p(server_ip, portNum);
t.OutputBufferSize = 512;
t.ByteOrder = 'littleEndian';
fprintf('Connecting to server ...\n')
fopen(t);
%%
flushoutp... |
%% Stelling 13
%
% Als BT-er gebruik je zowel standaard functies als zelf
% gemaakte functies.
%
Antwoord = NaN; % vul hier het juiste antwoord in 1 (WAAR) of 0 (ONWAAR)
|
% goal: fix h, plot N for different delta
% cd into folder with csv data from paraview
cd ~/Dropbox/FEniCSproj/Ndelta/tests_2D/DiagonalData/
files = dir('2D_adr_h1_20*_u.csv');
a = files(1).name;
= getnames(a);
aaa = getvalues(a);
b = files(2).name;
bb = getnames(b);
bbb =
c = files(3).name;
cc = get names(c);
%%
... |
function flag = IsInPolygon(x,y,X1,Y1,X2,Y2,X3,Y3,X4,Y4,X5,Y5,X6,Y6,X7,Y7,X8,Y8,X9,Y9)
if (inpolygon(x,y,X1,Y1) || inpolygon(x,y,X2,Y2)|| inpolygon(x,y,X3,Y3)||...
inpolygon(x,y,X4,Y4)|| inpolygon(x,y,X5,Y5) || inpolygon(x,y,X6,Y6)||...
inpolygon(x,y,X7,Y7) || inpolygon(x,y,X8,Y8) || inpolygon(x,y,X9,Y9)) ... |
function [X1] = SolveSODERK4(h, u, X0)
% This function solves the forward nonlinear differential equations of the
% onewheel using a fourth order Runge-Kutta method.
% The function arguments are the initial conditions, input and stepsize h
% The function output is the new calculated state
% Define model constants
M = 1... |
function [b, sig, likes, accept_rat] = mcmc_nmr_bsig (Dk, T2ML, z, n, Niter, stepsize, figureson)
if nargin < 5
if nargin < 4
Niter = 1e6;
end
stepsize = 0.8;
end
kk = log10(Dk);
% set bounds on each parameter
maxlogb = inf;
minlogb = -inf;
minsig = 1e-5... |
z_count =1;
load('regress_0kg.mat')
for count = 1:y_count-1
z_kg_acc(z_count,1) = y_kg_acc(count,1);
z_kg_vel(z_count,1) = y_kg_vel(count,1);
z_kg_theta(z_count,1) = y_kg_theta(count,1);
z_mass(z_count,1) = y_mass;
z_kg_power(z_count,1) = y_kg_power(count,1);
z_count = z_count+1;
end
load('reg... |
function [ad,v1,x1,y1,Fl1,Fd1,Nr1,Nf1,T_d1,X_d,p]=FindDeccelerationVectors1(a,v,T_d,x,y,Fl,Fd,Nr,Nf,Va,Straight_Line,k,m,p,dt,beta,Sr,X_d,Vec_p,M,c,b,L,H,Miu,Miur,Miuf,R,A,Cd,Cl,Ro_air,g,Start_ratio,Gr,Final_ratio,T1,T2,T3,T4);
ad=[a(1:p)];
v1=[v(1:p)];
T_d1=[T_d(1:p)];
x1=[x(1:p)];
y1=[y(1:p)];
Fl1=[Fl(1:p)];
Fd1=[Fd... |
load ('g149novickA.mat')
time=0:0.1:10;
tau1=1;
tau2=2;
tau3=3.55;
tau4=4;
x=data(:,1);
y=data(:,2);
V1=1-exp(-time/tau1);
V2=1-exp(-time/tau2);
V3=1-exp(-time/tau3);
V4=1-exp(-time/tau4);
plot(x,y,'bx',time,V1,'g-',time,V2,'r-',time,V3,'c-',time,V4,'m-'),
xlabel('time'),ylabel('Enzyme Activity'),
legend('data','V1','V... |
clc;
clear all;
x = [-10:0.1:10].';
y = 3*x.^4 + 2*x.^3 + 7*x.^2 + 2*x + ones(size(x))*9;
plot(x, y);
title("Polynomial"); |
function transmitter( packet, fc )
%% TRANSMITTER FUNCTION
% Group 13
% Introduction to Communication Engineering. September 2015
%
% Implementation of the receiver.
% INPUT: packet - vector with data
% fc - carrier frequency
%
% OUTPUT: SOUND to the speaker
... |
function unique_cycles = remove_duplicate_cycles(cycles)
% Removes duplicate cycles from <cycles> (mxn string array where
% m is the number of cycles and n is the number of nodes per cycle)
% Use to clean the output from find_perfect_5cycles because it finds
% duplicates
[~, unique_row_idxs] = uniqu... |
%% Set up input file and set file properties
file_path = 'C:\Users\Ali\Documents\ISML\MEA Data\20170622_400_0\';
lfs_stim_frq = [0,1, 0.5, 0.33, 1, 1, 1, 0.33, 0.33, 0.33, 0, 0];
lfs_file_num = [33,34,37,40, 60,62,65,72,74,76, 73,75, 35,74];
file = 3;
file_name = ['data' num2str(lfs_file_num(file),'%04i') '.mcd'];
... |
function [AN,FN] = reduce_global_matrix(model,model_data,d)
mu = get_mu(model);
model.decomp_mode = 1;
[A,r] = model.operators(model,model_data);
model.decomp_mode = 2;
[Acoeff,rcoeff] = model.operators(model,model_data);
A1_diff = Acoeff{2}(1)*A{2}{1};
A1_adv = Acoeff{2}(3)*A{2}{3};
A1_dir = Acoeff{2}(5)*A{2}{5};
... |
function [p] = singlePro(time,active,inactive)
%% Calculate single probability
%
% Input
% time: date vector
% Matrix active: entry 1 when alarm gets active
% Matrix inactive: entry 1 when alarm gets inactive
%
% Output
% Array p with probability for each id
%% %%%%%%%%%%%%%%%%%%%%%%%%%%%
% Preallocate size
p = ze... |
clc
clear all
close all
format short
%%Data
mu=398600.2;
Re=6378.16;
T=100*60;
a=((T/(2*pi))^2*mu)^(1/3);
alt=a-Re;%km
n=1/sqrt(a^3/mu);
m_start=100;
Isp_chem=200;
g0=9.81;
tf=T/60;
G=[0,0,0;0,0,0;0,0,0;1,0,0;0,1,0;0,0,1];
Gtrans=G';
F=[0,0,0,1,0,0;0,0,0,0,1,0;0,0,0,0,0,1; 3*n^2, 0, 0,0,2*n,0;0,0,0,-2*n,0,0;0,0,-n*n... |
function sig = extractSegment(sig, ndxRange)
ndxRange(1) = max(1,ndxRange(1));
ndxRange(2) = min(length(sig),ndxRange(2));
sig = sig(ndxRange(1):ndxRange(2)); |
%displays the ROI
function showROIbyRadius(AverageImage,ROI,L, ROI_distances, radius)
RASTERFIG = figure('WindowState','maximized');
imshow(rgb2gray(AverageImage));%mat2gray(AverageImage));
%imshow(AverageImage);
hold on;
colors=['b' 'g' 'r' 'c' 'm' 'y'];
for k=1:length(ROI)
if ROI_distances(k) <= radius
... |
function F = subfnModMedFMIN(W, data)
NMed = size(data.M,2);
NMod = size(data.V,2);
b = W(1:NMed);
v = W(NMed+1:NMed+NMod)';
w = W(NMed+NMod+1);
const = W(NMed+NMod+2);
cP = W(NMed+NMod+3);
Y = data.Y;
M = data.M;
V = data.V;
N = length(data.Y);
X = data.X;
est = X*cP + M*b + V*v + w*((M*b).*(V*v)) + const*ones(N... |
function log_modelchar(modelInstance, filepath, currFileEntry, algorithmParam)
if isempty(modelInstance)
[fileID, errmsg] = fopen(filepath, 'a');
fprintf(fileID,'%s,%s,%s',currFileEntry.subjectString, currFileEntry.exerciseName, '');
fprintf(fileID,'%s','error');
fprintf(fileID, '\n'... |
%% CFD Boston University Course -------------------------------------------
% Step 8 of 12 to Navier Stokes Code: Two Dimmensional Burgers Equation
%
% Governing Equation:
% \frac{\partial{u}}{\partial{t}} + u\frac{\partial u}{\partial x} + v\frac{\partial u}{\partial y} = \nu\left(\frac{\partial^2 u}{\partial x^2}+\f... |
function newtonSystem(X0,tol)
% Input: x0 - initial guess vector
% tol - tolerance
X_old = X0;
k = 1;
while( norm(F(X_old))>tol )
Y_new = JF(X_old)\(-F(X_old)');
X_new = X_old+Y_new;
fprintf('(x,y) = (%.16f,%.16f) for k=%d\n',X_new(1),X_new(2),k);
X_old = X_new;... |
function [] = plotbivariate(X,Y,xlab,ylab)
% Function to for the plotting of two random variables against each other.
% The plot produced is a bivariate scatter graph with two marginal
% histograms for both X and Y.
%
% INPUT:
% X = random variable 1
% Y = random variable 2
figure
%% Joint distribution
ax1 = subplot(4... |
function [ reliability] = pso_flc1_costfunction( input_args, z, k )
% function [ sum_reliability, node_reliability ] = pso_flc1_costfunction( input_args, z, k )
%pso_flc1_costfunction pso cost funtion for flc1
% input_args is 1*12 matrix
% input_args(1,1:6) cL bL aM cM aH bH for flc1's input z
% input_args(1,7:12... |
function decision_tree()
[attributes, examples, test_examples] = prepare_data('~/ml_data/adult/adult_attr_names', '~/ml_data/adult/sample', '~/ml_data/adult/sample_test');
global SINGLE_NODE_THRESHOLD POSITIVE_VAL
SINGLE_NODE_THRESHOLD = 0;
POSITIVE_VAL = '>50K';
active_attributes = [];
[attr_name, attributes, is_sin... |
classdef rls < FixedEpochLearner
%RLS learns using recursive least squares
properties
%cell array containing error covariance matrices for weights of each neuron
P
G
D
end
methods
function f = rls(nn)
f@FixedEpochLearner(nn) ... |
% Default starting script for Problem 2
clear all;
close all;
f = @(X) ( (X(1).^2 + X(2) - 11).^2 + (X(1) + X(2).^2 - 7).^2 );
df = @(X) [ (4.*X(1).^3 + 4.*X(1).*X(2) - 42.*X(1) + 2.*X(2).^2 - 14); ...
(2.*X(1).^2 - 26.*X(2) - 22 + 4.*X(1).*X(2) + 4.*X(2).^3) ];
d2f = @(X) [ (12.*X(1).^2 + 4.*X(2... |
clear
close
clc
%% **************************************************
% DEFINE SIMULATION PARAMETERS
%
roomDims = [500,500]; % Room dimensions [Lx, Ly, Lz] in meters
srcPos = [roomDims(1)/2,roomDims(2)/2]; % Source position [x,y,z] in meters
c=3000; % Speed of sound in air
simLength ... |
b = 2; L = -1; U = 2; % zadane parametry
d = [ 0 1 ]; % możliwe cyfry w liczbie
indeks = 1; % zmienna do indeksowania wektora liczb
for z = [ -1 1 ]; % znak
for e = L : 1 : U; % cecha
for i = [ 1 2 ]; % pierwsza cyfra
... |
function RasterPlot(spikes,color)
% plots a raster for a cell array of spike times
% INPUTS:
% spikes - cell array of spike times
% color - the color for the plot
hold on;
num_trials = length(spikes);
for i = 1:num_trials
trial = spikes{i};
len_trial = length(trial);
for ... |
function [ port ] = feeMaogugu( tradeVmat, feeRatio )
% 使用交易额矩阵TradeVmat粗略估算手续费：直接算每天的，累加，没有recursive
% [ port ] = feeMaogugu( tradeVmat, feeRatio )
% --------------------
% 程刚，20150524，初版本
%% 前处理：所有手续费率
% 判断类型
if ~isa(tradeVmat, 'TsMatrix')
error('本函数只接受TsMatrix类型的tradeVmat');
end
% 临时
if ~exist('feeRatio', 'v... |
function [x,i] = bisection(a,b,f,tol,maxiter)
i = 0;
fa = f(a); fb = f(b);
if(fa*fb > 0)
disp('Error: Invalid bracket!')
return
end
x = a;
fx = f(x);
while(abs(a-b) > tol && abs(fx) > tol && i < maxiter)
x = (a+b)/2;
fx = f(x);
if(fx*fa < 0)
b = x;
%fb = fx;
else
a = x;
... |
% University of British Columbia, Vancouver, 2017
% Alex Kyriazis
% William Choi
% Custom made gradient descent model used to optimize parameters. If you
% are going to use this, make sure you have a good understanding of the
% parameters and that you correctly set the cost function in the private
% folder
... |
function decp_data = cp_remove(sig,cp_sig_len,cp_num)
recieve_mat = reshape(sig,cp_sig_len,ceil(length(sig)/cp_sig_len))
decp_data = recieve_mat(cp_num+1:cp_sig_len)
end
|
function fxi = f_dim1(f,x,d,x_d)
%create 1-dimensional version of a multi-dimensional function
%the chosen dimension is d
%and the value on that dimension is x_d
xx = x;
xx(d) = x_d;
fxi = f(xx);
end |
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