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function finResults = tempvshomophily(numSim, tspan, homophilyValues)
% Yellow Jacket Model version
% Script created 2020-05-27 by jmenard
% previous version sampled new parameters for each different homophily value, while we want to sample
% different params each simulation, not each homophily value.... |
%
% Ingrese el intervalo inferior: 0
% Ingrese el intervalo superior: 2
% Ingrese el porcentaje de error: 0.0001
% Ingrese la funciòn: x+1
% i xf(i) Error aprox (i)
% 1 2.0000000 100.000
% 2 -1.0000000 300.000
% 3 -1.0000000 -0.000
xf(1)=input('Ingrese el intervalo inferior: ');
xf(2)... |
function writetoPAJ(a, fname, arcs)
%WRITETOPAJ Write to Pajek
%
% writetoPAJ(a, fname, arcs);
%
% This function writes a Pajek .net file from a MATLAB matrix
%
% Inputs: a, I/O object handler
% fname, filename minus .net extension
% arcs, 1 for directed... |
classdef Point
properties
x = 0;
y = 0;
end
methods
function p = Point(xx, yy)
p.x = xx;
p.y = yy;
end
function p = PointObj(dot)
p.x = dot.x;
p.y = dot.y;
end
end
end
|
function s = delimlist(c, varargin)
% cslist Convert cellstr to delimited list.
%
% Syntax
% =======
%
% S = textfun.delimlist(C,...)
%
%
% Input arguments
% ================
%
% * `C` [ cellstr ] - Cell array of strings that will be converted to a
% comma-separated list.
%
%
% Output arguments
% ... |
%% check_all.m
% Usage: check_all(ROOT_DIR)
% Purpose: Checks the velocity and gtemperature of simulations in pullSimTime
% to determine statSimeTime
%
% User Inputs:
% ROOT_DIR - Directory where pullSimTime resides
%
% Function Requirements:
% pullSimTime created from simtime.sh
function chec... |
Fs=8192;
y1=gen_wave(1,0.5);
y2=gen_wave(1,0.5);
y3=gen_wave(5,0.5);
y4=gen_wave(5,0.5);
y5=gen_wave(6,0.5);
y6=gen_wave(6,0.5);
y7=gen_wave(5,1);
y=[y1 y2 y3 y4 y5 y6 y7];
y1=gen_wave(4,0.5);
y2=gen_wave(4,0.5);
y3=gen_wave(3,0.5);
y4=gen_wave(3,0.5);
y5=gen_wave(2,0.5);
y6=gen_wave(2,0.5);
y7=gen_wave(... |
function Xinter = findfoot(a,b,c)
% a = [1 1 2]; %line - x1
% b = [20 28 90]; % line - x2
%
% c = [50 30 67]; %point - x0
a= transp(a);
b= transp(b);
c= transp(c);
ab = b - a; %// Find x2 - x1
%// -(x1 - x0).(x2 - x1) / (|x2 - x1|^2)
t = -(a - c)*(ab.') / (ab*ab.'); %// ... |
function [Coarse, F] = CoarseToFineRF(PDS, spikes)
% checks if spatial RF mapping was run, uses a coarse initialization of the
% RF to measure
%%
spatialMap = session.squareFlash(PDS);
%%
SPATIAL_MAPPING_WINDOW = [-15 -10 15 10];
% SPATIAL_MAPPING_BIN_SIZE = 1;
% SPATIAL_MAPPING_WINDOW = ... |
%% uses matlab pointcloud downsampling function to downsample an organised point cloud
function output_OPC = downsample_OPC( input_OPC, gridStep )
input_OPC = cast(input_OPC, 'double'); %convert to double (required)
cloud_object = pointCloud(input_OPC);
ds_cloud_object = pcdownsample(cloud_object,'gridAverage',g... |
function net = cnnapplygrads_new(net, opts) %update weights and biases
for l = 2 : numel(net.layers)
if strcmp(net.layers{l}.type, 'conv')
for j = 1 : numel(net.layers{l}.a)
for ii = 1 : numel(net.layers{l - 1}.a)
%update history including gradient, weight dec... |
% % DIAGNOSIS OF SMALL CELL LUNG CANCER THROUGH ARTIFICIAL NEURAL NETWORKS
% In the code below, we perform the following tasks:
% ------------
%
% 1- Load X-ray image data of diganosed small cell lung cancer patients.
% 2- A sample image (obtained from cancer image archive has 1951*2000
% samples. So, samp... |
function [locs,sifts] = calculate_sift_for_image_set(image_name_set)
locs = cell(numel(image_name_set),1);
sifts = cell(numel(image_name_set),1);
for i = 1:numel(image_name_set)
try
[f,d] = im2sift(image_name_set{i});
locs{i} = f;
sifts{i} = d;
catch exception
locs{i} = -1;
sifts{i} = -1;
conti... |
function [xnew, ynew] = plotcone(y, x)
% Useful when all elements in y have the same x, and you want to plot y vs
% x. This function gives x_new and y_new that make the y vs x plot look
% like a nice gaussian cone (by adding small random values to the x of each
% element to separate the points).
%%
y = reshape(... |
fid = fopen('trip_data_2.csv'); %第一行 第六列开始读
title = textscan(fid, '%s %s %s %s %s %s %s %s %s %s %s %s %s %s',1,'delimiter', ',');
data = textscan(fid, '%s %s %s %s %s %s %s %d32 %d32 %d32 %d32 %d32 %d32 %d32','delimiter', ',');
fclose(fid);
disp(title{1});
%--------------------纽约------------------------
% [m,n] = size... |
mpath = which('sketching');
mpath(end-11:end) = []
cd(mpath)
pwd
fileFolder=fullfile('SmoothImage');
dirOutput=dir(fullfile(fileFolder,'*'));
fileNames={dirOutput.name}';
length = size(fileNames);
filesize = length(1, 1);
for i = 1 : 1 : filesize
if strcmp(fileNames{i, 1},'.') || strcmp(fileNames{i, 1},'..') ||... |
function [runs,miss]=plot_radscanmultisp(directory)
if directory(end-3:end)=='.dat'
dirlist={};
if not(exist(directory,'file'))
if directory(1)=='/'
directory=[getenv('SFINCS_HOME'),'/fortran/version3',directory];
else
directory=[getenv('SFINCS_HOME'),'/fortran/version3/',directory];
en... |
function [ Eff_M,x,y,y_fit ] = Effective_Mass( H,P,band,shift )
%EFFECTIVE_MASS Given a Path, P and SINGLE band Omega, fit parabola to get
%effective mass.
hbar=1.05457e-34; %m^2kg/s
a=4.3596e-10; %m
me=9.109e-31; %kg
N=200;
[k_line,k,~]=K_path(P,N);
%Compute Eigen values
for n = 1:length(k_line)
Omega(n,:) = sort(e... |
function IbuprofenTimeSeries();
clf;
fasted = csvread('FastedDigital.csv',6,0);
light = csvread('LightBreakfastDigital.csv',6,0);
heavy = csvread('HeavyBreakfastDigital.csv',6,0);
fasteds = csvread('FastedStomach.csv',6,0);
lights = csvread('LightStomach.csv',6,0);
heavys = csvread(... |
function [pvx, pvy] = GetNewPolygon(color)
%
% Return vertices of a user-defined polygon, drawn onto the current plot.
%
% This is intended to be an implementation of the GetSelPolygon function,
% using Matlab's new handle-graphics interface, particularly the impoly
% function.
%
% (C) 2015 Benjamin Naecker bnaecker@st... |
function h = errorbar_group(model_series,model_error)
% Plots errorbar on group bars
% Usage: errorbar_group(bar value,errorbar value)
%
%model_series = [10 40 50 60; 20 50 60 70; 30 60 80 90];
%model_error = [1 4 8 6; 2 5 9 12; 3 6 10 13];
h = bar(model_series,'BarWidth',1);
clr = [0.5 1 0.5;0.5 0.5 1;1 0 0... |
%Displaying the Frechet mean and an element of the sample set of graphs
A = sampleAdjSet{1};
A = A-1;
A = -1*A;
deg = sum(A);
[sorted,I] = sort(deg);
sortedA = A(I,I);
p_i = sort(p_i, 'descend');
frechetMean = rand_adj(p_i,q_i,n);
frechetMean = frechetMean-1;
frechetMean = -1*(frechetMean);
degMean = sum... |
1;
function k = gauss(beta, x1, x2)
x = x1 - x2;
k = exp(-beta * x^2);
endfunction
function mat_k = kernel_matrix(beta, vec_x)
mat_k = [];
for x1 = vec_x'
line = [];
for x2 = vec_x'
line = [line gauss(beta, x1, x2)];
end
mat_k = [mat_k; line];
end
endfunction
function r = square_error... |
fol_name = 'data/behav_analyzed_hgf_concat';
all = dir(strcat(fol_name,'/*.mat'));
for k = 1:length(all)
load(strcat(fol_name,'/',all(k).name));
plot(subject.hgf.sim_concat.traj.mu(:,2));
hold on;
end |
%HVISEMPTY
% [flag] = HVISEMPTY(iChnl, dasIn_1, dasIn_2, ... dasIn_N)
% where flag == TRUE if one or more of workspace data structures 'dasIn_n' are empty.
% If iChnl > 0, iChnl is used to identify the channel currently being processed.
% Written by Chris Lewis, August 2002
%
function [iFlag] = HVISEMPTY(iChnl, v... |
function [G pred g] = psymodfun(b,Y,X,ML,nk,f,gnorm)
%% logfunX_ml_power
% psychometric model for sequential comparison tasks
% (c)Bernhard Spitzer, 2016
% weighting function
pownum=abs((b(2)+X(:,1:nk)).^b(3)).*sign(b(2)+X(:,1:nk)); % b(2): bias; b(3): kappa
% g normalization
g=sum... |
function[H]=emdprog(g)
g=load('S001.txt');
g=emd(g);
figure;
subplot(911)
plot(g(1,:))
title('IMF1')
subplot(912)
plot(g(2,:))
title('IMF2')
subplot(913)
plot(g(3,:))
title('IMF3')
subplot(914)
plot(g(4,:))
title('IMF4')
subplot(915)
plot(g(5,:))
title('IMF5')
subplot(916)
plot(g(6,:))
title('IMF6')
subplo... |
function [omega1,S_omega1,dRf1_0] = ang_vel(Rf_1_0, dRf1_0, q, dq)
% Derivative of rotation matrix
dRf1_0(:) = [jacobian(Rf_1_0(:,1), q)*dq, jacobian(Rf_1_0(:,2), q)*dq, jacobian(Rf_1_0(:,3), q)*dq];
dRf1_0 = simplify(dRf1_0,'IgnoreAnalyticConstraints',true);
% S(omega) = (transpose(R))*dR/dt
... |
% To create 2 Matricies and multiply them
% Condition : Inner dimenssions of Matricies must be same
% A(mxn) * B(n*p) = C(mxp)
% Define variables:
% n - row of first Matrix
% p - column of first Matrix and row of second Matrix
% A - first matrix
% B - second matrix
% C - product of A and B
n = in... |
%dividing the fourier transforms to deblur%
de_blurred = deblur(yj,h);
function X = deblur(y,H)
X = y./H;
end |
function [v,m,x,er] = llyod_max(levels,max_l,min_l,mu,sigma)
digits(50);
variance = sigma*sigma;
v = zeros(levels,1);
for i = 1:levels
v(i) = i/10; %Can be any initialization
end
m = zeros(levels+1,1);
m(1) = min_l;
m(levels+1) = max_l;
%generating pdfs for finding the expectation of the variable
pdf_gaus... |
function mapping = combineKeysAndValues(type, keys, values)
%COMBINEKEYSANDVALUES Combine keys and values into mapping.
% TODO: Do we need to check for invalid keys?
% Check inputs
checkForDuplicateNames(keys)
% Build output
typeMap.map = @createMap;
typeMap.struct = @createStruct;
typeMap.cell = @createCell;
if is... |
function x_rect=rectify(x,x_min,x_max)
x_rect=min(x_max,max(x_min,x));
end
|
fontsize = 16;
linewidth = 2;
output_offset_ada{j} = importdata([fileSave filesep 'output_offset_ADA.mat']);
prob_offset_session_offline_ada{j} = importdata([fileSave filesep 'prob_offset_ADA.mat']);
if iFolder == nFolder
%%
nSubject = length(output_offset_ada);
accuracy_mean = nan(nSubje... |
function [ ] = GetSpikeStats( SimValues,PopParams,timewin )
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
%
% timewin window to show raster (ms)
%% Calcualte each cell's spike rate and rate sortings
cellrates = cellfun(@length,SimValues.spikesbycell)./(SimValues.t(end)./1000);
[~,... |
function findSSD(Meta_savename)
%find the stable size distribution for Central California Coast blue
%rockfish, uses recruitment magnitude from IPM fits from White et al. 2016
load(Meta_savename)
load(Meta.Ffit_savename)
F=Post.F_mean;
fixparm = Meta.fixparm;
meshsize = Meta.IPM.meshsize;
meshmin = Meta.IPM.meshmin... |
function residuals = rodriguesResidual(P_init,p1,p2,K1,K2,M_diff,R1,t1,x)
% rodriguesResidual:
% Inputs:
% P - Nx3 matrix of 3D coordinates
% p1 - Nx2 set of points in left camera
% p2 - Nx2 set of points in right camera
% K1 - 3x3 camera calibration matrix 1 of left camera
% K2 - 3x3 camera calibration matr... |
function [double_sorted_data] = yearly_double_sort_2x4(quantile_data,estimation_data,control_var,sort_var)
%This function constructs double-sorted 2x4 portfolios, i.e., above and
%below median
%
quantile_data = sortrows(quantile_data, {'year','permno','time'});
quantile_data.control_quantile= yearly_quantile... |
%---------------------- BEGIN CODE ----------------------
% Clear all the previously used variables, close all
% figures and clear screen
close all ; clear all ; clc ;
l = 1e3;
EbNodB=[7];
EbNo=10.^(EbNodB/10);
n=1;
% In-phase symbol generation
si=2*(round(rand(1,l))-0.5);
% Quadrature symbol generation
sq=2*(round... |
% Compute the error of a pose-landmark constraint
% x 3x1 vector (x,y,theta) of the robot pose
% l 2x1 vector (x,y) of the landmark
% z 2x1 vector (x,y) of the measurement, the position of the landmark in
% the coordinate frame of the robot given by the vector x
%
% Output
% e 2x1 error of the constraint
% A 2x3 Jaco... |
m = 0.111;
R = 0.015;
g = -9.8;
L = 1.0;
d = 0.03;
J = 9.99e-6;
s = tf('s');
TF = -2*m*g*d/L/(J/R^2+m)/s^2;
rlocus(TF)
sgrid(0.70, 1.45)
axis([-5 5 -2 2])
zo = 0.01;
po = 4;
C=tf([1 zo],[1 po]);
rlocus(C*TF)
sgrid(0.70, 1.45)
[k,poles]=rlocfind(C*TF)
%k=80.1815
%sys_cl=feedback(k*C*TF... |
function [peak_T, P, p, threshold, deltaP] = Lomb_Scargle(t, Y, a, zero)
%This function uses the Lomb_Scargle method to detect periodic components
%in a given signal.
%
%The arguments required are t, Y, a, and zero.
%t is the times (in hours) of your points
%Y is the array of points (i.e., the Y(t) values)
%a is the er... |
function Handles
%HANDLES 此处显示有关此函数的摘要
% 此处显示详细说明
clear,close,clc;
f=@(x) exp(-2*x);
x=0:0.1:2;
plot(x,f(x));
end
|
function extract_timecourses(save_path,mask_path,h5_path,tiff_path)
% extract_timecourses(save_path,mask_path,h5_path,tiff_path)
% Extract average timeseries from ROIs specified by pixel masks.
%
% All arguments are optional parameters. User will be prompted if
% unspecified.
%
% JG 2018
if nargin<1
savefi... |
function VAR_sim = estimateVAR(data,settings)
% Least-squares VAR estimation
% preliminaries
n_x = size(data,2);
T = size(data,1);
% select lag length
if settings.select_VAR_simlaglength == 1
p = selectlag_IC(data,settings.max_simlaglength,settings.penalty);
elseif settings.select_VAR_simlaglength == 0
p =... |
function all_feats = getCNNFeature_img_gpu(im, all_boxes, net)
all_feats = [];
nCandidates = size(all_boxes,1);
imGlobal_ = single(im) ; % note: 255 range
im_w = size(im ,2); im_h = size(im ,1);
p = 0;
batchSize = 512;
numBatches = ceil(nCandidates/batchSize);
for k = 1:numBatches
cur_batchSize = min(nC... |
%% PDE Simulation Tester
%{
Author: Avishai Halev
Advisor: Nancy Rodriguez-Bunn
Last modified: Keshav Patel
Date modified: 09/04/2018
This file runs the "continuumSimulation.m" file and plots the solution. A
movie is saved at completion of the script
%}
close all
clearvars -except oldResult pResult
... |
function dodoMain_Reduced_Resolution( im_tag )
% dodoMain_Reduced_Resolution generates low resolution PANchromatic
% (PAN) and MultiSpectral (MS) images according to the Wald's protocol for
% im_tag image from Pérez-Bueno, F. paper image dataset following the same procedure as
% Vivone, G. paper.
%
% Input arguments:
... |
%% Aligned-Face Recognition Poject:
%% MATLAB initializations:
clc
clear all
close all
%% Add paths of functions:
addpath('functions_ASM');
addpath('functions_CLNF/demo');
addpath('functions_warp');
addpath('functions_LDA');
addpath('functions_preprocessing');
%% Ask user about some settings:
do_crop_aligned_dataset... |
function [] = xeno_canto()
% dataDir = './data/xeno_canto/';
dataDir = '/Volumes/ALEX/data/xeno_canto/';
species = {
'Ring-billed+gull',
'Great+egret'
'Common+yellowthroat',
'Red-winged+blackbird',
'Ruddy+duck',
'Double-crested+cormorant',
'Mallard',
'Mute+swan',
'House+finch',
... |
% linear programming (CPLEX) implementation for evaluating WFW.
%
% Author : Chen SONG
% Created : 2019
% Description : Run LP (CPLEX) to check the feasibility of each desired
% wrench inside the given set
function inWorkspace = wrench_feasible_linear_programming_CPLEX(desired_wrench_set,dynamics)
... |
function filtered = myMeanLPF(image,radius)
filter_size = 2 * radius + 1;
kernel = ones(filter_size,filter_size,filter_size) / (filter_size ^ 3);
filtered = imfilter3d(image,kernel);
end
|
% RES = RMSE(ACTUAL, EXPECTED)
%
% Root Mean Squared Error
%
% ACTUAL - acctual value
% PREDICTED - predicted value
% RES - Root Mean Squared Error, if error occurrs it's set to -1
function res = rmse(actual, expected)
if( length(actual)~=length(expected) ),
disp('ERROR! Actual and Predicted need to be equal... |
%Plot the DIFFERENCE between conditions
%
%important - setup so that taskY - taskX.
%Thus if taskX is the 'good' condition (RH, Free vision)
%And taskY is 'bad' (LH, Per vision)
%Then taskY - taskX = how bad is the 'impairment'
%i.e. higher positive score shows greater impairment
%e.g. for Per - Free, higher positive ... |
%% Electomagnetic Fields: Electrostatic problem (Integral and MoM)
% "a" sugarú huzalból "R" sugarú kört hajlítunk (a<<R).
% A kör síkjában, annak középpontjától "h" távolságban
% egy "Q" nagyságú ponttöltés áll, levegöben. A huzal össztöltése zérus.
% Írjanak Matlab függvényt, amely a momentum módszerrel kiszámítja a ... |
function [ output_args ] = imzmlJSON(fp,fn,varargin)
%imzmlJSON - create a JSON file for any imzML file so that it can be
%uploaded to the METASPACE engine using the batch functionality.
% Get the stuff from the input arguments
[opts] = readArgsData(varargin);
% Now we can print out the JSON file...
[json] = jsonPart... |
function [p_delta,values]=deltaDistribution(delta_value,values)
p_delta=zeros(size(values));
p_delta(values==delta_value)=1;
end |
clear;
constants;
ang = deg2rad([-10 -100 -100]');
[~, pos, ~] = FK3links(ang,"R",robot);
fullMatOld = pos;
newAngles = IK3links(fullMatOld,"R",robot);
rad2deg(newAngles)
fullMatOld
for curAngles=newAngles
% rad2deg(curAngles)
[~, pos, ~] = FK3links(curAngles,"R",robot);
fullMatNew = roundn(pos - fullMatO... |
function [pd,keynodes] = getKeyPd(recon,type)
A = recon.A;
subs = recon.subs;
soma = find(sum(A,2)==0);
% regular = A==1;
junction = find(sum(A)>1);
tip=find(sum(A,1)==0);
keynodes = unique([soma,junction,tip]);
if nargin<2 | isempty(type)
pd = pdist(subs(keynodes,:));
elseif type=='geo'
% geo dist
G = grap... |
% rotate p about a point o in 2D by angle da
%
% p = [x y 1; x y 1; x y 1 ...]
function rotp = rotateAroundPoint(p, o, da)
removeCol = false;
if size(p, 2) == 2
p(:,3) = 1;
removeCol = true;
end
if size(o, 2) == 2
o(3) = 0;
end
matrix = vrrotvec2mat([0 0 1 da]);
rotp = bsxfun(@plus,matrix*bsxfun(@minus,p... |
function [ count ] = faceTest(k )
%UNTITLED4 Summary of this function goes here
% Detailed explanation goes here
test = load('testset.mat');
testset = test.testset;
[V_hat, xbar, alpha] = faceRecognition(k);
z = testset-repmat(xbar, [1, size(testset,2)]);
l = size(alpha,2);
%disp(size(alpha));
count = ... |
%Cèl·lules vermelles
clc;
I = imread('normal-blood1.jpg');
BW = rgb2gray(I);
%imshow(BW);
B = BW < 180;
%figure;imshow(B);
F = imfill(B,'holes');
%figure;imshow(F);
[sX sY] = size(B);
M = zeros(size(B));
M(:,1) = 1; M(1,:) = 1;
M(:,sY) = 1; M(sX,:) = 1;
M = logical(M);
IR = imreconstruct(M, F);
%figure; imshow(IR);... |
% -------------------------------------------------------------------
% Generated by MATLAB on 11-Oct-2017 18:19:12
% MATLAB version: 9.2.0.556344 (R2017a)
% -------------------------------------------------------------------
clear all;
close all;
clc;
functionData = LoadFunctionData();
SIZE_VARIABLE = 3;
CONSTANT_... |
function vals = depack_cellofcells(values)
vals = cell(1,length(values));
for i = 1:length(values)
vals{i} = values{i}{1};
end
end |
%% Range of movement of Spine in Lateral Box Transfer
% Code AUTHOR: Yaiza Benito Molpeceres. DATE: January-May 2020.
% Adapted to Octave by Guillermo Asín Prieto
% Exoskeleton trials segmentation: 54, 55, 56, 62.
% Five phases shown in figure 1:
% 1: Subject picks up the box in the sagittal plane (idxO1:idxF1)
... |
function [ indexes ] = intersectspheres( p1, p2, c, r )
%INTERSECTSPHERES пересечение луча со сферами
% Функция возвращает индексы в массивах c, r для сфер имеющих пересечение
% с лучом заданным точками p1, p2
% p1 - точка начала луча
% p2 - вторая точка луча
% c - центры сфер
% r - радиусы сфер
% index... |
function [simaverage, simerror, simratio] = mctaskmelt(data, prob, uncert, meltdata, Liquid_mass, T, P, binedges, nbins)
samplerows=size(data,1);
sdata=NaN(samplerows,size(data,2));
i=1;
while i<samplerows
% select weighted sample of data
r=rand(length(prob),1);
tempdata=data(prob>r,:);
if i+size... |
function [child_net,Flag] = func_check(child_net)
% to check the #input<=Kmax; if not, remove some inputs
% child_net: 1 x (ngenes*ngenes)
% to improve: just need to check the part around "cut_point"
global num_gene;
global Kmax;
Flag = 0; % =1 means there are some #input > Kmax
for i=1:num_gene
input = ch... |
%% * Transceiver
% diode k-parameter
k2 = 0.0034;
k4 = 0.3829;
% antenna resistance
resistance = 50;
% scale ratio of SMF
alpha = 2;
% coefficients on current terms
beta2 = k2 * resistance;
beta4 = k4 * resistance ^ 2;
% number of transmit and receive antennas
nTxs = 1;
nRxs = 1;
% number of users
nUsers = 1;
% average... |
clear;clc;
%%% define the parameters
K =10;
N = 1;
sigma1 = 0.3;
sigma2 = 0.25;
phi = 0;
TruePosition = [-0.3;0.5];
theta = 2*pi/K;
landmark = [cos(((1:K)-1)*theta);sin(((1:K)-1)*theta)];
distance = sqrt((landmark(1,:)-TruePosition(1)).*(landmark(1,:)-TruePosition(1))+(landmark(2,:)-TruePosition(2)).*(landmark(2,:)-Tru... |
% Data files
database_files = {'data/Phil_Image_Short_bw_100ms_cut.csv', 'data/Phil_Image_Long_bw_100ms_cut.csv', 'data/Phil_Moving_Short_bw_100ms_cut.csv', 'data/Phil_Moving_Long_bw_100ms_cut.csv'};
testset1_files = {'data/Yellow_Image_Short_bw_100ms_cut.csv', 'data/Yellow_Image_Long_bw_100ms_cut.csv', 'data/Yellow_Mo... |
function [z,dz,pe,rhoe] = fmodlvls(p,sfctemp,atm)
% Model height and pressure levels
%% Levels, pressure
n = 1000; % # of levels
h = 15000; % height m
z = linspace(0,h,n)'; % levels m
dz = z(2)-z(1); % m
[pe,rhoe] = fpres(p,sfctemp,z,atm); % pressure profile
end
|
function S = combineSpikeTrains(SpikeTimesCell_1T, SpikeTimesCell_2T);
sizeNew = max(size(SpikeTimesCell_1T)) + max(size(SpikeTimesCell_2T));
for i = 1:sizeNew
if i <= max(size(SpikeTimesCell_1T))
S{i} = SpikeTimesCell_1T{i};
else
S{i} = SpikeTimesCell_2T{i - ma... |
function [A,b] = upperTriangularPP(A,b)
[m,~] = size(A);
for i = 1:m-1
for j = i+1:m
[~,k] = max(A(j:m,i));
k = j+k-1;
%zamenjuj j-tu vrstu sa k-tom vrstom
temp = A(j,:);
A(j, :) = A(k,:);
A(k,:) = temp;
tmp = b(j);
b(j) = b(k);
b(k) = tmp;
... |
% Non-linear transfer function
function result = phi( x )
result = (2 ./ (1 + exp(-x)) ) - 1;
end
|
% function result = membrane_current_constant(params, rho, V)
%
% Molecular flow across membrane for constant current.
% Note need to be cautious using this as large currents can cause
% unphysical (i.e. negative) concentrations.
%
% Inputs
% params -> state of system
% params.membrane_J ... |
% transformSig4noisy.m
%
% transformSig4noisy(base_sig, candidate_sig, noisy, T, pk_base,pk_cand)
% for ECG signals
% This functions transforms noisy to base_sig. The reference
% signal, base_sig and candidate_sig, are verified for each window
% within RR peaks. The size of noisy and T are equated to th... |
function [ I1, I2 ] = genSquareTest(S1,S2,t1,t2,ang1,ang2)
% Generates a pair of binary images that are square phantoms of
% specified size, XY rotation, and translation from the image center.
%
% Input
% --------------------
% S1,S2 Length of the squares in pixels.
% t1,t2 1x2 v... |
%% Setup Drone
m = 0.2
I = [[0.1,0,0];[0,0.1,0];[0,0,0.08]]
% sample time
ts = 0.01
% Initial States (Initial XYZ is generated by XYZsignal script)
Euler_0 = [0;0;0]
% XYZ_0 should not be [0;0;0] because the initial target point is set to
% [0;0;0]
XYZ_0 = [1;2;0]
body_rate_0 = [0;0;0]
% Set surround rate (if 0: fo... |
# Author: Valentin Andrei
# E-Mail: am_valentin@yahoo.com
function [flat_S, v_f, v_t] = get_speech_spectrogram (x, FS)
% Usage: S = get_speech_spectrogram(x, FS)
%
% Input:
%
% x - Input Signal
% FS - Sampling Frequency
%
% Output:
%
% flat_S - Spectrogram as a column vector
debug... |
function [x] = ifft3(X)
%IFFT3 Summary of this function goes here
% Detailed explanation goes here
x = ifft(ifft(ifft(X, [], 3), [], 2), [], 1);
end
|
classdef DicomImageLoadSpecification < ether.process.LoadSpecification
%DICOMIMAGELOADSPECIFICATION Summary of this class goes here
% Detailed explanation goes here
properties
patient = [];
end
properties(Access=private)
overrideMap;
end
methods
%-------------------------------------------------------... |
% Follow this Wikipedia page for model equations:
% https://en.wikipedia.org/wiki/Kalman_filter#Example_application.2C_technical
% State vector definition: x_k = [p_k; v_k], i.e. position and velocity.
% Evolution of state vector: x_k = F*x_km1 + G*a_k, a_k is random accel.
% This is the same as: x_k = F*x_km1 + w_... |
clear all
outpath = 'C:\Users\jaker\Pictures\Oregon_Eclipse\code\matlab\out';
dirname = 'C:\Users\jaker\Pictures\Oregon_Eclipse\16bit\png';
offsets = load(fullfile(outpath,'offsets.mat'));
etimes = exposure_times();
% Get the two test images
fi = 16;
img_nums = [fi,fi+1];
fnames = get_files(dirname,'png');
cli_header(... |
% Normalization of 2d-pts
% Inputs:
% x1s = 2d points
% Outputs:
% nxs = normalized points
% T = normalization matrix
function [nxs, T] = normalizePoints2d(x1s)
xy_centroid = [mean(x1s(1,:)); mean(x1s(2,:)); 1];
% First shift the point to the origin
shifted_xy = x1s - xy_centroid;
d... |
function tree_output = kd_buildtree(X,plot_stuff,parent_number,split_dimension)
% pramod vemulapalli 02/08/2010
% inspired by the work done by Jan Nunnink, 2003.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% INPUTS
% X --- contains the data (nxd) matrix , where n is ... |
function dnaseq = protein2dnaOptimized(protseq)
% Input a protein sequence (using three letter abbreviations, no spaces e.g. MetArgLeu)and returns the corresponding
% DNA sequence (in the case of degenerate codons, a random codon is chosen).
protseq=upper(protseq);
codonTable=readtable('codons.csv');
codonArray=upper(... |
classdef PCATransform < ATransform
% Pricipal Component Analysis transform class
properties
%The different components
U = [];
m = [];
%How many components are used (-1 means calculate the elbow of eigenvalues)
degree = -1;
elbow = [];
threshold = 0;... |
function statsLDADraw(~,~,fig,window)
%statsLDADraw - draw the plots from LDA
% Guidata
sts = guidata(fig.fig);
% Determine the components...
try
cs = [get(window.comp1,'Value') get(window.comp2,'Value')];
catch
cs = [1 2];
end
% Plot the ellipses?
try
doEllipse = get(window.ellipse,'Value');
catch
d... |
function p = objective(A, b, lambda, cum_part, x, z)
obj = 0;
start_ind = 1;
for i = 1:length(cum_part),
sel = start_ind:cum_part(i);
obj = obj + norm(z(sel));
start_ind = cum_part(i) + 1;
end
p = ( 1/2*sum((A*x - b).^2) + lambda*obj );
end
|
function elt = quad2d_elt()
% function elt = quad2d_elt()
%
% Returns the quadratic 2-D (6-point) element data structure
nvars = [1;1;1;1;1;1];
flist = [1 0 0;
2 0 0;
3 0 0;
1 2 0;
1 3 0;
2 3 0];
vnodes = [0 0;
1 0;
0 1;
1/2 0;
... |
function [AA,BB,Ts,Ti,ks,err_of_BDCSD_A,err_of_BDCSD_B,flag] = bdcsd(A,B,tol,for_sd_ds)
%BDCSD Block Diagonal Controllable Structural Decomposition
%
% [At,Bt,Ts,Ti,ks] = bdcsd(A,B)
%
% transforms a controllable pair (A,B) into the block diagonal
% controllable structural decomposition form.
%
% ... |
function [natureArray] = JuliaSetPoints(complexArray,c,cutOff)
%This function determines if each point in grid value is associated with
%specified complex value c and is a member of julia set. It returns a 2D
%array where it had evaluated each grid point and grid points which are in
%Julia set have a value of 0 whi... |
% % LAB4 Ex.1
function xk = dfs2(xn,n,k)
len = length(xn);
Xn(1:len) = 1:len;
xk = Xn*exp(-j*pi/k(end)).^n'*k;
end
|
%
function bplt(x,y,u,ux,uy,uz,Tm,visc,cname,bgtname,bgt)
if(strcmp(cname,'sww'))
casename = 'Smooth Wavy Wall';
elseif(strcmp(cname,'rww'))
casename = 'Rough Wavy Wall';
end
if(strcmp(bgt,'rs'))
s = 1/(Tm);
ttl = ['$$\frac{\eta_{ij}}{u_\tau^2}$$'];
else
s = 1/(Tm*Tm/visc);
ttl = ['$$\frac{\dot{\eta_{ij}}}{u_\t... |
close all;
clear all;
clc;
disp('7.Q1');
q1 = rand(3,10);
Htrue = [10 0 -1; 1 10 20; .01 0 3];
q2 = Htrue * q1;
q1 = normalize2D(homogenize2D(q1));
q2 = normalize2D(homogenize2D(q2));
Hest = computeHomography(q1, q2);
q2est = Hest * q1;
%s = q2(1,1)/q2est(1,1);
%q2est = q2est * s;
q2est(1,:) = q2est(1,:) ./ q2est(... |
%% Artificial Neural Networks and other Learning Systems - Lab 2
%% 1. Introduction
%
% In this lab we use Radial Basis Functions (RBF) to approximate some simple
% functions of one variable. Suppose we have the function $f: R
% \to R$. RBF introduces a hidden layer such that $\hat{f}:
% R \to R^n \to R$, where $n$... |
function dx = KTmodel_E(tt,x)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
% global k t r s ke te
k = 0.335;
t = 23.348;
% k=3*10^(-6)*v^2+0.032*v+0.0001;
% t=13.192*v^2-313.67*v+2049.9;
r = -0.603;
s = 0.157;
ke = 1;
te = 0.69;
dx = zeros(4,1);
dx(1) = x(2);
dx(2) = (k/t)*(x(3)+r)... |
function [Wl,Wr,G,Xlr,fval] = MTML_imputation_fs(y,Xl,Xr_bar,lambda1,lambda2,lambda3,lambda4,coords,G_init,maxiter,toler)
%solving MTMLa with regional variable imputation
%input:
% y: cell of n*1 vector; Xl: cell of n*dl matrix, Xr_bar: r*dr matrix,
% Xlr: cell of n*dr matrix, lambda1:hyperparamet... |
function [sys,x0,str,ts] = sfunsinda(t,x,u,flag,sindafile)
%function [sys,x0,str,ts] = sfunsinda(t,x,u,flag)
persistent FirstCall
% Determine if it is the beginning of the simulation
if (flag == 0) & isempty(FirstCall)
FirstCall = 1;
elseif flag == 9
FirstCall=[];
else
FirstCall=0;
end
%
% Original File i... |
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