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% lats is a cell array, each item is a vector of latitudes for a given
% path. Similarly for longs.
% The route files were taken from .shp files from the Department
% of Transport, converted to KML (e.g. in ArcMap). Only lines with
% <coordinates> tags were kept, the tags were then removed and the Z
% coordinates remov... |
%This one requires running data from Non Learning condition
cd('/home/raleman/Documents/internship/26')
cd(nFF{3})
run('newest_load_data_nl.m')
%ran=randi(length(p),100,1);
sig1_nl=cell(7,1);
sig1_nl{1}=Mono17_nl;
sig1_nl{2}=Bip17_nl;
sig1_nl{3}=Mono12_nl;
sig1_nl{4}=Bip12_nl;
sig1_nl{5}=Mono9_nl;
sig1_nl{6}=Bip9_n... |
function model = make_ref_model_slice_beam(za,az,pol,tilemodelboresightgain)
model = zeros(length(za),1);
phioffset = 0;
if strcmp(pol,'ns')
phioffset = pi/2;
end
for i=1:length(za)
model(i) = 10*log10((1-sin(za(i))^2*sin(az(i)+phioffset)^2)*ground_screen_power_beam(za(i),... |
function boundaries = importBoundaries(filename, varargin)
persistent ip
if isempty(ip)
ip = inputParser;
ip.FunctionName = mfilename;
ip.addOptional('bbox' ,[429936,92169; 628999,280605],@(x) isnumeric(x) && isequal(size(x), [2,2]));
end
parse(ip,varargin{:})
bbox = ip.Results.bbox;
% Load
try
[~,ma... |
% fig2C: best clusters/cells? for an array of stim/motor regressors, GUI function
hfig = figure;
InitializeAppData(hfig);
ResetDisplayParams(hfig);
i_fish = 8;
LoadSingleFishDefault(i_fish,hfig);
%% regression with all regs
% ResetDisplayParams(hfig,i_fish);
setappdata(hfig,'stimrange',1:2);
UpdateTimeIndex(hfig);
i... |
function ShowWielHoff()
% function ShowWielHoff()
% The Wielandt-Hoffman theorem.
% GVL4: Theorem 8.1.4
clc
fprintf('Wielandt-Hoffman Theorem\n\n')
fprintf(' ||E||_F eig(A+E) \n')
fprintf('-----------------------------------------------------------------------------------\... |
%% heat maps
'heatmaps'
clear
close all
load data filename variables_to_include pvalue
% condition={'Acid','BHI','CSP','H2O2','O2','Paraquat','thermal'};
% for k=condition
eval(['load ' filename '_tnorm.mat tnorm cdf']);
%stoping point work on for loop below
for j={'control','Control','wildtype','Wild Type','WT','wt'... |
function u = uminus(a)
% - Unary minus.
% (Quaternion overloading of standard Matlab function.)
% Copyright © 2005, 2010 Stephen J. Sangwine and Nicolas Le Bihan.
% See the file : Copyright.m for further details.
error(nargchk(1, 1, nargin)), error(nargoutchk(0, 1, nargout))
u = a;
if ~isempty(u.w)
u.w = -u.w;... |
function [ns_RESULT, nsEntityInfo] = ns_GetEntityInfo(hFile, EntityID)
% ns_GetEntityInfo - Retrieves general entity information and type
%
% Usage:
% [ns_RESULT, nsEntityInfo] = ns_GetEntityInfo(hFile, EntityID)
%
% Description:
% Retrieves general information about the entity, EntityID, from the file
% referenced ... |
% V es una matriz que en cada fila tiene uno de los individuos (pesos de la red) ordenados con el de mayor fitness primero
% F es un vector con los fitness correspondientes a las entradas de V
function [R] = r_1(V, F)
global pc;
global pm;
global pbpp;
global crossover_counter_total;
global mutation_counter_total;
glo... |
function data_out = PolyExp_pipeline1(indata_src,indata_0_0,indata_0_1)
%----------------------
width = 200;
%----------------------
persistent rRam ctr;
if isempty(rRam)
p = fi([],1,72,0);
rRam = zeros(1,width,'like',p);
% rRam = zeros(1,width);
ctr = uint8(1);
end
%----------------------
% DataTypeMode: Fixed-poi... |
function pass = uq_Kriging_selftest(level)
% PASS = UQ_KRIGING_SELFTEST(LEVEL): suite of non-regression and consistency
% checks for the Kriging module of UQLab
%
% See also: uq_selftest_uq_metamodel
%% initialize test
uqlab('-nosplash');
if nargin < 1
level = 'normal'; % TBD: Time that the tests will take
en... |
function [dd, ds] = getFitData(this)
ft = getFitTime(this);
tt = nan(size(ft));
for i = 1:length(this.fields)
df = this.fields(i);
t = df.src.time;
idx = ismember(ft, t);
if isempty(t)
d = ones(size(ft)) * df.curr.val(1);
s = ones(size(ft)) * df.curr.std(1);
else
d = t... |
function phclqclistatrw(varargin);
% phclqclistatrw( [...] );
% QCL Istat rw
h = timeplot({'QCLI_rw'}, ...
'QCL Istat rw', ...
'rw', ...
{'QCLI\_rw'}, ...
varargin{:} );
|
function artifactTimes = detectArtifacts(eegTime,eegDat,Fs,varargin)
% artfactTimes = detectArtifacts(lfpTime,lfpDat,NAME,VALUE)
% detects artifacts by:
% a) Bandpass filtering the lfp trace at 50-400Hz, and marking
% artifacts as those points >5*st.dev. from the mean
artifactBand = ... |
function [ Yw ] = generate_weak_learner( Xtrain,Ytrain)
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
Yw = ceil(10*rand(size(Xtrain)));
Yw = ceil(10*rand(size(Xtrain,1),2000));
% for i = 1:size(Xtrain,2)
for i = 1:2000
i
kern_poly = @(x,x2) kernel_poly(x,x2,1);
... |
function Ind = CoincidenceIndex(STR1, STR2)
% Ind = CoincidenceIndex(STR1, STR2)
% Inputs: STR1, STR2 = two strings of the same length
% Output: Ind = thier incidence of coincidence.
Count = sum(STR1==STR2);
Ind = Count/length(STR1);
|
function varargout=calcClosedLoop
%CALCCLOSEDLOOP Calculates the closed loop response of a linear system given
%data with the modFreq, targetFreq, measured voltages, and times.
addpath('..');
%
% Load the closed loop data recorded using measureClosedLoopLinear
%
M = load('Closed loop response');
%
% Load open loop pa... |
function [hist_handle] = circadian_histogram(event_times, time_res)
% function HIST_HANDLE = CIRCADIAN_HISTOGRAM(EVENT_TIMES, TIME_RES)
%
% Plot a circular histogram of events in time bins around the 24 clock.
%
% INPUTS:
%
% EVENT_TIMES: Vector of datetimes specifying event times.
%
% TIME_RES: Temporal resolution... |
function [dest] = rotate_coeff(src, rotation, degree, dl)
%%=============================================================
%% Project: Spherical Harmonics
%% Module: $RCSfile: rotate_coeff.m,v $
%% Language: MATLAB
%% Author: $Author: bjian $
%% Date: $Date: 2007/12/27 06:23:36 $
%% Version: $Revi... |
function basisobj = basis(fdtype, rangeval, nbasis, params)
% BASIS Creates a functional data basis.
% Arguments
% FDTYPE ... a string indicating the type of basis. This may be one of
% 'Fourier', 'fourier', 'Fou', 'fou',
% 'Bspline', 'bspline', 'Bsp', 'bsp',
% 'pol', 'p... |
function [cAssignedEmployee rAssignedEmployee] = locate_employee(conflict,allele)
%% LOCATE_EMPLOYEE
%
% Based on a conflict matrix, this function selects the candidate employee
% to be assigned.
%
% Copyright (C) 2020
%
% This program is free software; you can redistribute it and/or
% modify it under the terms of the... |
function f = Newton(x,y,x0)
%求已知数据点的牛顿插值多项式
%已知数据点的x坐标向量：x
%已知数据点的y坐标向量：y
%插值的x坐标：x0
%求得的牛顿插值多项式或在x0处的插值：f
syms t;
if(length(x) == length(y))
n = length(x);
c(1:n) = 0.0;
else
disp('x和y的维数不相等！');
return;
end
f = y(1);
y1 = 0;
l = 1;
for i=1:n-1
for j=i+1:n
y1(j) = (y(j)-y(i))/(x(j)-x(i));
... |
classdef al_objectClass
%AL_OBJECTCLASS This class definition file specifies the
% properties of an object that combines multiple objects
% in one object
% Properties of the object object
% -------------------------------
properties
gParam
cannon
circle
keys
... |
//hared
GPL : Alg+ [Src] [WEIGHTED___] Gtp BASE___ :: MainGpl ;
Gtp : DIRECTED___ | UNDIRECTED___ ;
Src: Src2 SEARCH___ :: SrcProg;
Src2 : BFS___ | DFS___ ;
Alg : NUMBER___ | CONNECTED___ | STRONGLYCONNECTED___ | CYCLE___ | MSTPRIM___ | MSTKRUSKAL___ | SHORTEST___ ;
%% // constraints
NUMBER___ implies (Gtp and Src);
... |
Im1=double(imread('test96.bmp'));
Im1=imbinarize(Im1);
h=[0,1,0;1,1,1;0,1,0];
Im1=imerode(Im1,h);
Im1=imopen(Im1,h);
[whiteMatrix, n]=bwlabel(Im1);
Im2=not(Im1);
[blackMatrix, n2]=bwlabel(Im2);
figure(1), imshow(whiteMatrix)
whiteProperties=regionprops(whiteMatrix,'all');
whiteProperties(1)=[];
blackProperties=regio... |
function ss = outer_sum(xx,yy)
%function ss = outer_sum(xx,yy)
% compute an "outer sum" x + y'
% that is analogous to the "outer product" x * y'
% in
% xx [nx,1]
% yy [1,ny]
% out
% ss [nx,ny] ss(i,j) = xx(i) + yy(j)
% Copyright 2001, Jeff Fessler, The University of Michigan
if ~nargin, help outer_sum, end
xx = xx(:... |
function [Q, R] = zhouseqr(A)
%compute the QR decomposition of square matrix A
% A = Q*R; Q is orthogonal matrix and R is upper trigular matrix
[m, n] = size(A);
if m ~= n
error('support squre matrix only')
end
temp = A;
Q = eye(n);
for k=1:n-1
[v, beta] = zhouse(temp(k:end, k));
reflector = eye(m-... |
function A_matrix = rolling_constraint_matrix(disk_center_vel, dqdt)
% Returns rolling constraint matrix (2 by 5)
coeff_velx_dqdt4 = coeffs(disk_center_vel(1),dqdt(4));
coeff_velx_dqdt5 = coeffs(disk_center_vel(1),dqdt(5));
coeff_velx_dqdt6 = coeffs(disk_center_vel(1),dqdt(6));
coeff_vely_... |
%-----------------------------------------------------------------------
% Job saved on 13-Oct-2014 00:17:23 by cfg_util (rev $Rev: 6134 $)
% spm SPM - SPM12 (6225)
% cfg_basicio BasicIO - Unknown
%-----------------------------------------------------------------------
matlabbatch{1}.spm.tools.longit{1}.series.vols = '... |
function plusfd = plus(fd1, fd2)
% PLUS Sum of two functional data objects having the same basis.
% Sum functional data object PLUSFD inherits the fdnames field of the
% first argument.
% last modified 1 July 1998
if ~(isa_fd(fd1) & isa_fd(fd2))
error('Both arguments are not functional data objects.');
end
... |
function centroids = clustering_pc(points, NC)
% points = matricea de coordonate a punctelor
% NC = numarul de clustere dorite
% centroids = centrele de masa ale clusterelor
[m n] = size(points);
% Se creeaza NC clustere conform regulei din cerinta
for i = 1 : NC
col = 1;
for j = i : NC : m
clusters(... |
function out = gpuinvfourier(inp)
% 1912.12302.B7
global lambda;
global beta;
b=beta;
lb=lambda;
n=gpuArray((-lb:lb-1)');
m=gpuArray((1:4*lb));
out=zeros(1,4*lambda,'gpuArray');
ip=inp(lb+1:3*lb);
out=ip*exp(-(pi.*1i.*(m-2*lb-1).*(n + 0.5))./lb);
%parfor m=1:4*lb
% aa=
% (m)=aa;
%end
out=out./b;
e... |
%%%assign all boutons to unique identification label
function [boutonrevised] = placeholderarray(bouton)
global CellThresholdParameter;
global CellconnectivitySize;
global CellSizeLengthParameter;
global CellSizeDistance;
global CellNumberofImages;
global GaussianFilterRadius;
global ConnectivitySize;
glob... |
addpath('..\');
for i =1:100
R(i)=1.7+(i)*0.01;
energy(i)=myCO_func(R(i));
end
plot(R,energy)
%%
title('Potential energy surface of CO')
xlabel('distance')
ylabel('Energy') |
function Log_plot_helper2(option,response,no_of_nodes,no_of_paths,fill)
global GUI start_time
persistent not_ready blanks
[current_nodes_states,current_node_activation_status,current_path_states,current_time]=data_decoder2(response,no_of_nodes,no_of_paths);
if((option==0)||(not_ready==1))%initialize various his... |
phns = ['E:\6-InputData\Calibrate_5_Peg\dvrk_Ground_Right.txt'];
phns_IMU = ['E:\6-InputData\Calibrate_5_Peg\dvrk_IMU_Right.txt'];
phns = ['E:\6-InputData\Calibrate_4_Range\dvrk_Ground_Right.txt'];
phns_IMU = ['E:\6-InputData\Calibrate_4_Range\dvrk_IMU_Right.txt'];
phns_Slave = ['E:\6-InputData\Calibrate_4_Range\dvr... |
vocab=fileread('merged_vocab.txt');
vocab=strsplit(vocab);
load merged_docword.csv
x_fmt = merged_docword; % each row is different document. each column represents all possible words
[U_svd,S_svd,V_svd] = svds(x_fmt); % svd
n_dim = 2; % number of dimensions
x_princ = U_svd(:,1:n_dim)*S_svd(1:n_dim,1:n_dim); % get... |
function [syn,deltat,estParam,hyper_params]=synapse_xcorr_conv(Tlist,hyper_params)
% syn_params(1) = latency
% syn_params(2) = time constant
% syn_params(3) = weight
if isfield(hyper_params,'bin_width')
bin_width = hyper_params.bin_width;
else
bin_width = .00002;
end
t = linspace(-hyper_params.coupling_times... |
function [E,gradEbeta] = Eimage(Sbeta,Sopt,Sprior)
I=Sopt.I; % log of image
uu=Sopt.uu;
vv=Sopt.vv;
scalefac=Sopt.scalefac;
theta0=Sprior.theta0;
theta1=Sprior.theta1;
[nrow,ncol]=size(I);
C=curve_to_regions(Sbeta.beta,scalefac,nrow,ncol);
x0=I(C==0);
x1=I(C==1);
E=-skewLogisticLikelihood(theta0,x0)-ske... |
function output = normalizedCorrelation(image,kernel)
kernelNormalized = normalization(kernel);
imageSize = size(image);
kernelSize = size(kernel);
outputSize = imageSize-kernelSize+1;
output = zeros(outputSize);
for i = 1:outputSize(1)
for j = 1:outputSize(2)
normalizedImage = normalizatio... |
classdef GaitDataForces
properties
% Force columns stored from the excel
Time
LGRFX
LGRFY
LGRFZ
ToeOffPercentage
end
methods
function obj = GaitDataForces(csvFileName)
% Make sure the file exists here
if (exist(csvFi... |
function idx_pkts_collapsed = collapsePacketBoundaries(idx_pkts,grace_period)
collapsed_start = idx_pkts(1,1);
proposed_stop = idx_pkts(1,2);
idx_pkts_collapsed = [];
jj = 2; numrows = size(idx_pkts,1);
while jj <= numrows
% next packet within grace period
if ( idx_pkts(jj,2) - proposed_stop ) <=... |
%DriverBasic_LM
function [pars optpars Init xhist error HR_LM] = Func_DriverBasic_LM(data,INDMAP)
% clear all
%close all
%% Get nominal parameter values
[pars,low,hi] = load_global(data, INDMAP);
%Global parameters
ALLPARS = pars;
ODE_TOL = 1e-8;
DIFF_INC = sqrt(ODE_TOL... |
clc;
clear;
close all;
%% Set Seed
rng(0);
%% Constants
% Dimension of signal
n = 256;
% Number of experiments
nexp = 100;
%% Initialize Overcomplete Dictionary
% DCT matrix
dctmat = dctmtx(n);
% Over-complete dictionary for cosine + spikes
A = [dctmat eye(n)];
%% Varying sigma
tic;
% Initialize experiment results... |
% Limpiamos nuestro ambiente de trabajo
clear all
clc
% 4. Utilice Matlab (software) para graficar las funciones y explique:
% a) x[n] = u[n] - 2u[n-1] + u[n-4]
% Primero establecemos el número de muestras (tiempo discreto)
n = -5:5; % habrá 11 valores discretos de tiempo
% Para el primer término
x1 = (n>=0);
% Par... |
function [center] = centroid(pts)
% calculates the centroid of an arbitrary number of points
% pts is a 1 to 3 - column matrix, where each row represents a new coordinate
% column 1 = x, column 2 = y, column 3 = z
center = zeros(1,size(pts,2));
% basically, all you do is average the coordinate values
fo... |
cd('F:\Jacket\data\raw\');
list=dir();
clc
clear all
close all
format bank
spike_files=dir('*.txt');
fid = fopen('F:\Jacket\data\euleranglesummary.txt','w');
fprintf( fid, '%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s\n','Applied angle','aX','aY','aZ','bX','bY','bZ','cX','cY','cZ','dX','dY','dZ');
for i = 1:length(spike_... |
% function enco = huffman_encoder(sig, dict)
clc
clear
% im = imread('/Users/INNOCENTBOY/Documents/MATLAB/pic/256/4.1.01.tiff');
% im = rgb2gray(im);
A = [1,2,3;3,5,9];
B = A(:);
%% UNIQUE
a1 = A(:).';
a2 = sort(a1);
a3 = diff(a2);
a4 = a3 ~= 0;
a4 = [true, a4];
C = a2(a4);
%% BSXFUN , Calculating no of time a pix... |
% general ED bose-hubbard code
% last cleaned up 9/24/2018
% author: Matthew Rispoli
close all
clear all
clc
addpath('functions');
%load('plot_colormaps\alex_cmap.mat');
%cmapAlex=ccs; clear ccs;
% tunneling
J=38.1911/1000; %8Er tunneling rate; defined in Hz/(2 pi)
% disorder strengths
NW=10;
Ws=li... |
function singles = find_singles(celldatas)
for cell_i = 1:length(celldatas)
singles(cell_i) = ~isempty(strfind(celldatas(cell_i).cell_types,'SINGLE'));
end
end |
function [f_sup]=afc_sup(X_sup,F,l);
%USAGE [f_sup]=afc_sup(X_sup,F,l); correspondence analysis
%Compute supplementary elements for
% Correspondence analysis
% need X_sup: the matrix of elements to compute
% ALWAYS SUPPOSED TO BE ROWS!!!
% F : the coordinates of the other set
% (i.e.,... |
%% Load and unpack data
%Spliced file created in epoch splicing
clear
close all
participant = 'A01';
load("Data/spliced" + participant);
%% Getting it ready for classifier
% % We need to grab the labels for each trial, multiply them by 3 and prep
% % each component
% %
% % Set num to what kind of spat... |
function [pos, neg] = demo2( )
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
reqToolboxes = {'Computer Vision System Toolbox', 'Image Processing Toolbox'};
if( ~checkToolboxes(reqToolboxes) )
error('detectFaceParts requires: Computer Vision System Toolbox and Image Processing Toolbox.... |
function [x, NbIter] = romp(y, A, s, varargin)
if size(varargin, 2)
if iscell(varargin{1})
[checkArgs, MaxNbIter, TolRes] = parse_Varargin(varargin{1});
else
disp('USAGE: ''parameter_name'', paramenter_value pairs expected in a cell.');
disp(['Ignoring arguments:... |
for ci=1:numel(subj)
eval([subj{ci} '_sERP=mean(' subj{ci} '_sEEG,3);']);
eval(['X=' subj{ci} '_sERP;']);
for ch=1:size(X,1)
p=find_chirplets(X(ch,:),1,2,64,0);
chirp_param(:,:,ch)=real(p);
cEEG(ch,:)=real(chirplets(64,p));
end
eval([subj{ci} '_cERP=... |
function varm=varmat(mat)
% takes a 3d matrix and returns the variance along the
% first dimension
% usage: varm=varmat(mat)
for coln=1:size(mat,2)
varm(coln,:)=var(squeeze(mat(:,coln,:)));
end
|
clear all
close all
plotN = 10;
col = jet( plotN )';
col = col*0.95;
%% Grandma's soo MAADLAB, yeah!
%% What parents expects:
%parameters
Fs = 44100;
T = 4;
%generate stuff
t = 0:1/Fs:T;
s = chirp( t, 50, T, 5000 );
%this is what she expets to hear:
%sound( s*0.1, 44100 ); %Turn down for what? Eh ok.
%or as a plo... |
% HW 4 problem 3
% Last Edited Sept 28 2013
f = [1 -3 -10 27 10 -24];
a = roots(f);
fprintf('\nThe roots are %.3f, %.3f, %.3f, %.3f, %.3f\n',a);
x = -4:.1:4;
plot(x,x.^5-3.*x.^4-10.*x.^3+27.*x.^2+10.*x-24);
axis([-4 4 -10 60]);
grid on
figure(1) |
function [ pikovi ] = udarci(treshold,signal_1,signal_2,signal_3,signal_4)
%Trazimo odnos prvog signala u odnosu na sve
%
odnos=[];
for i=1:length(signal_1)
odnos(i,1)=i;
odnos(i,2)=signal_1(i)/signal_2(i);
odnos(i,3)=signal_1(i)/signal_3(i);
odnos(i,4)=signal_1(i)/signal_4(i);
end
pikovi=[];
v=1;... |
function res = opdracht_5_versie_3_CHECK(apStudentSol)
%%========== PLACE SOLUTION IN COMMENTS HERE
% % % % % % % % % % % kniehoekHardloper = [61 9 62 118 87 104 131 46 105 123 61 74 92 66 26 32 58 3 106 9];
% % % % % % % % % % % indKniehoeken = find(kniehoekHardlop... |
function y = mat2huff(x)
%MAT2HUFF Huffman encodes a matrix.
% Y = MAT2HUFF(X) Huffman encodes matrix x using symbol probabilities in
% unit-width histogram bins between X's minimum and maximum values. The
% encoded data is returned as a structure Y:
% Y.code The Huffman.encoded values of X, stored in a uint16 vect... |
function indices=strmatch_array(pattern_list,search_list,force_error_on_NotFound)
if nargin<3,
force_error_on_NotFound=[];
end;
if isempty(force_error_on_NotFound),
force_error_on_NotFound=true;
end;
if iscell(pattern_list),
N=length(pattern_list);
else
N=size(pattern_list,1);
end;
if iscell(search_list),... |
function [ output_args ] = SizeLimit( value,min,max )
%SIZELIMIT 此处显示有关此函数的摘要
% 此处显示详细说明
if(value<min)
output_args=int32(min);
else if(value>max)
output_args=int32( max);
else
output_args=int32(value);
end
end
|
%{
load('ex8data1.mat');
[m, n] = size(X);
[mu sigma2] = estimateGaussian(X);
pval = multivariateGaussian(Xval, mu, sigma2);
epsilon = min(pval) + (max(pval) - min(pval)) / 1000;
my = pval < epsilon;
tp = sum((yval == 1) & (my == 1));
fp = sum((yval == 0) & (my == 1));
fn = sum((yv... |
function hourlyClearnessIndexes = synthesiseHourlyClearnessIndexes(time, location, dailyClearnessIndexes, varargin )
% SYNTHESISE_HOURLY_CLEARNESS_INDEXES Synthesises a sequence of hourly clearness
% indices (Kt) using the mean daily clearness index and the time-dependent,
% autoregressive, Gaussian (TAG) model [1]
... |
function [Iout1,param1] = CDLMRI(Img, Q, sigmai,sigma,DLMRIparams)
% =========================================================================
% Coupled Dictionary Learning for Multi-contrast MRI Reconstruction
% =========================================================================
%
%The software is used to ... |
function [classifier, classifierLabel] = classifierProcessing(classifierSelect, aggregatorSelect, trainingDataStruct, dimReduct)
switch classifierSelect.name
case 'kNN'
if ~isfield(classifierSelect, 'k')
classifierSelect.k = 5;
classifierSelect.distanceMetric = '... |
function [fitresult, gof] = createFit_LOESS(x1, x2, y)
%CREATEFIT1(X1,X2,Y)
% Create a fit.
%
% Data for 'LOESS_fit' fit:
% X Input : x1
% Y Input : x2
% Z Output: y
% Output:
% fitresult : a fit object representing the fit.
% gof : structure with goodness-of fit info.
%
% See a... |
% Algoritmo di Cooley-Tukey per il calcolo della FFT (direct call)
%
% Descrizione:
% Calcola la DFT di un vettore x di dimensione n=p^t utilizzando l'algoritmo
% di Cooley-Tukey e il metodo della chiamata diretta per il calcolo dei
% twiddle factors.
%
% Uso:
% X = dcctfft(x)
%
% Parametri di ingresso:
% x:... |
function D = BuildDiffusionMatrix2Periodic(parts,Eta_m,Kappa,kT,boxSize)
% coder.extrinsic('bessely');
% coder.extrinsic('besselj');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Build the full diffusion matrix for all of the paticles
%@in parts : Nx2 - particle position array
%@in Eta_m me... |
PsychRTBox('CloseAll'); |
function [V, I, S, DeltaPhase, SE] = subsetEPFLdata(NumPMU, MeasIdx, SelectedPhase, PCC, DATA)
% Extract a desired subset of data from the preloaded set of EPFL data
%
% Args:
% NumPMU: number of PMU
% MeasIdx: indices of measurement to extract
% SelectedPhase: phase to extract from the 3-phase data
% PCC: inde... |
function MUA_population_sizecohere
% % PV Halo population
% animalids = {'150730', '150731', '150804', '150818', '150820', '150824', '151104'};
% blocks = [4, 3, 4, 3, 3, 3, 5];
% animal = [1, 2, 3, 4, 5, 6, 7];
% cen... |
%load data_users
[avg_prevalent_freq, std_prevalent_freq] = calculate_prevalent_freq(data, fs);
hold on;
eixo = 3;
%% join dynamic static in group
avg_static = 0;
std_static = 0;
for at = 4:6
avg_static = avg_static + avg_prevalent_freq(at,eixo);
std_static = std_static + std_prevalent_freq(at,eixo)^2;
end
av... |
clear all
T=readtable('../Summary_Data_800_Gals/PatientInfo07132021.csv');
load('../Summary_Data_800_Gals/summary.mat','uniqueTimes');
hut_possibles=cell(872,1);
count=1;
c=0;
for pt=3:872
T{pt,1}{1}
if (isfile(strcat('/Volumes/GoogleDrive/Shared drives/REU shared/LSA/HUT/',T{pt,1}{1},'_HUT_WS.mat')) && an... |
function BS = bezierOneSub (B,t)
% Opis : beziersub izvede subdivizijo Bezierjeve krivulje
%%Definicija :
% BS = beziersub (B,t)
%%Vhodni podatki :
% B matrika kontrolnih tock Bezierjeve krivulje , v
% kateri vsaka vrstica predstavlja eno kontrolno
% tocko ,
% t parameter subdivizije Bezierjeve krivulje
%%Izhodni podat... |
% assinging a vector to A
A = [ 4 5 3 7 ];
% assigning empty vectors to B and C
B = [];
C = [];
% loop to find the distance
for i = 1 : length(A)
% loop to find the distance for each row a number at a time
for j = 1 : length(A)
C(j) = abs(A(i)-A(j));
end
% concatinating C to the next rom of B
... |
PRE_Points;
k=4;
RUNS = 100;
NumOfReps = 32;
hitCONN = zeros(RUNS,1);
NumOfEdgesCONN = zeros(RUNS,1);
for run=1:RUNS
PRE_Points;
RUN_Points(X, 'kmeans+CHL', NumOfReps, false, false, false,'CONN','CostDBIOverLambdaPCA',k);
POST_Points;
hitCONN(run) = hitrate;
NumOfEdgesCONN(run) = NumOfE... |
function C = new_center(cluster_n, class_n, data, m, U)
%C = zeros(cluster_n,size(data,2));
for i = 1:cluster_n
b = zeros(1,size(data,2));
c = 0;
for j = 1:class_n
a = sum(data((j-1)*32+1:j*32,:));
b = b + (U(i,j)^m)*a;
c = c + U(i,j)^m;
end
C(i,:)... |
file_dir = './orl_faces';
w = 92; h = 112;
n = 40;
data = zeros(n * 10, w * h);
k = 1;
for i = 1:n
for j = 1:10
name = [file_dir, '/s', int2str(i), '/', int2str(j),'.pgm'];
pic = imread(name);
d = reshape(pic, 1 , w * h);
data(k, :) = d;
k = k + 1;
end
end
X = zeros(n * 7, w * h);
k = 1;
for i = 1:n
for... |
%Read an Image A(Template)
A1 = imread('benten.jpg');
%Read the Target Image
B1 = imread('watch.jpg');
A = A1(:,:,1);
B = B1(:,:,1);
normx_corrmap=normxcorr2(B(:,:,1),A(:,:,1));
maxptx = max(normx_corrmap(:));
[x1,y1]=find(normx_corrmap==maxptx);
figure,
imagesc(A1(x1-size(B,1):x1,y1-size(B,2):y1,:)... |
function [Ans] = Flags(NotePos, Staffline, BW)
ImageBW = RemoveHorizontalLines(BW,4);
imshow(ImageBW)
Xpos = round(NotePos(1,1));
Ypos = round(NotePos(1,2));
if(Staffline <=12)
SmallBW = ImageBW(Ypos+15:Ypos+25, Xpos-10:Xpos+10);
imshow(SmallBW);
else
S... |
% Intrinsic and Extrinsic Camera Parameters
%
% This script file can be directly executed under Matlab to recover the camera intrinsic and extrinsic parameters.
% IMPORTANT: This file contains neither the structure of the calibration objects nor the image coordinates of the calibration points.
% All thos... |
%% Winer take all classifer for solvable subjects
% Combining three classifers.
clear; clc;
%% First, Find subjects that are solvable for all labels
type = 'HF';
solvableSub = find(solvAll(type) == 1);
numSub = size(solvableSub,2);
%% Computs HIT / FALSE
% Get a solvable subject
for i = 1: numSub
subNum = s... |
function out = get_condor_job_text_output(filename, idx, condor_session_obj, tail_num_lines)
job_list = kv_get('job_list', condor_session_obj);
task_dir = get_parent_dir(job_list{idx});
text_file = [task_dir filesep filename];
if(exist('tail_num_lines','var'))
cmds = {'tail -n', num2str(tail_num_lines), text_fil... |
# Plot the matrix factorization error versus iterations
load 'error.mat'
plot(error);
title('Matrix approximation error versus # iteration');
print -djpg 'error.jpg';
|
function x_boot = Get_boot(data, n_boot)
%data = imgobj.dFF_s_each(:,:,k)
n_data = size(data, 2);
x_boot = zeros(n_boot, n_data);
%remove NaN resample data
parfor i = 1:n_data
x = rmmissing(data(:,i));
if length(x) >= 2
x_boot_ = bootstrp(n_boot, @mean, x);
else
x_boot_ = repmat(max(x), n_... |
%Plots cdf of messages fwd per node, for stealth and normal
[norm1 norm2 norm3 data1 data2 data3] = normvsstealth();
f = figure('Position', [200 200 658 420]);
set(f,'defaultaxesfontsize', 14);
nodefwds = [data1.nodefwds; data2.nodefwds; data3.nodefwds];
[y, x] = ecdf(nodefwds);
semilogx(x, y, 'k-', 'LineWi... |
function [ A,observe,truth ] = makeSBM(n,m,Lam)
% [ A,observe,truth ] = makeSBM(n,m,Lam)
% makes a realization from stochastic block model
% coordinates of (vector) n are number of nonseeds in the blocks
% coordinates of (vector) m are number of seeds in the blocks
% Lam is the communication matrix
% A is adja... |
function [isCollided] = isRobotCollided(q, map, robot)
% ISROBOTCOLLIDED Detect if a configuration of the Lynx is in collision
% with any obstacles on the map.
%
% INPUTS:
% q - a 1x6 configuration of the robot
% map - a map strucutre containing axis-aligned-boundary-box obstacles
% robot - a structure... |
function l=zad3_vapour_heat_Carruth(t,tc,omega)
R=8.3144;
%Reduced temperature
tr=t./tc;
%Equation
l=R.*tc.*(7.08.*(1-tr).^0.354+10.95.*omega.*(1-tr).^0.456); |
%% Plot for force feeback
% Position tracking
from=1;%7859;
to=length(time);%14000;
time_fix=time-time(from);
hold on;
refp = plot(time_fix(from:to),ref(from:to),'r', 'LineWidth',2);
currentp = plot(time_fix(from:to),current(from:to),'b');
currentp.Color(4) = 0.4;
legend('Referencia','Corriente');
xlabel('Tiempo (s)');... |
function [success] = convertInscopixIsxdToHdf5(inputFilePath,varargin)
% Converts Inscopix proprietary ISXD to HDF5.
% By default all dropped frames are included in the output as a frame full of zeros.
% Biafra Ahanonu
% started: 2019.01.15 [21:17:45]
% inputs
% inputMoviePath - char: path to ISXD file.
% outpu... |
function [A,B,b0] = linear_constraints(model,V,s)
[a,b,~,~]=vert2lcon(V);
a(abs(a)<1E-6) = 0;
b(abs(b)<1E-6) = 0;
a = round(a);
order = [1 0 0;
0 1 0;
0 0 1;
-1 0 0;
0 -1 0;
0 0 -1];
A = zeros(size(a));
B = zeros(size(b));
if isempty(s)
b0 = zeros(6,1);
else
... |
% calculate PDC
function pdc = PDC(X, m, fftlen)
if ~exist('fftlen','var')
fftlen = 1024;
end
[p, len] = size(X);
covz = getcovzpd(X, m);
[A2d, D] = ARregressionpd(covz, p);
pdc = PDC_A(A2d, D, fftlen);
|
%%%% This file generates voxels and initial centerline from image %%%%
% Input: *.stl format image
% Output: VolumePixel
% (OUTPUTgrid: 3d binary matrix, where 1: object, 0: background;
% gridCOx, gridCOy, gridCOz: x,y,z coordinate)
% skeleton (skel: binary matrix, where 1: centreline, 0: other... |
% This function is used to calculate (d cosh(alpha))/(d r).
function f = dcoshalphadr(R,r,theta)
f = 4*R.^2.*r.*(R.^2-r.^2).*sin(theta).^2./(R.^2+r.^2).^3.*(1-(2*R.*r.*sin(theta)./(R.^2+r.^2)).^2).^(-1.5);
end |
function self=zeros(self,dim,m)
assert( isscalar(dim) && isscalar(m) );
assert( dim>0 && m>0 );
self.dim=dim;
self.m=m;
self.H=cell(m,m);
end |
function fermi_filter_isodim2_memfix_obj(large_array,w1,w2,bool_2D_mode,output_field)
% -------------------------------------------------------------------------
% function fermi_filter_isodim2_memfix_obj(large_array,w1,w2,2D_switch)
% kspace_filter(iraw) generates the 3D filtered kspace image. Only filter
% function ... |
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