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function League=CreateInitialLeague()
global ProblemSettings;
global SCASettings;
CostFunction=ProblemSettings.CostFunction;
VarSize=ProblemSettings.VarSize;
VarMin=ProblemSettings.VarMin;
VarMax=ProblemSettings.VarMax;
nTeam=SCASettings.nTeam;
nMainPlayer=SCASettings.nMainPlayer... |
function OK = WriteTFilesForReal(MCD)
nClusters = length(MCD.Clusters);
for x = 1:nClusters
TimeStamps = MCD.FeatureTimestamps(MCD.Clusters{x}.mySpikes);%%
save(fullfile(MCD.TTdn, [MCD.TTfn '_Cluster_' num2str(x)]), 'TimeStamps')
OK = 1;
end |
% Team 20 - Signal Detection
% Nov 14th, Simulation demo
% Louis Rosenblum, Cayden Seiler, Khristian Jones
%% Initialization
close all;
clear all;
%% Sensor placement
% Hardcoding sensor locations at (x,y) coordinates
s0 = [0 0];
s1 = [100 0];
s2 = [0 100];
s3 = [100 100];
%% Spatial grid design
% data structure ... |
function [ indices ] = mergesort_function( cols, N )
%MERGESORT_FUNCTION
addpath(genpath('../'));
indices = 1:N;
mergesort_helper_do_function(1, N);
function [] = mergesort_helper_do_function(low, high)
if low < high
middle = floor((low + high) / 2);
%middle = (int32(... |
function vAnat2Analyze
% convert a vAnatomy.dat file back to Analyze format
% expecting readVolAnat.m to return volume in IPR orientation
% re-orients to LAS for FSL compatibility
[vAnatFile,vAnatPath] = uigetfile('*.dat','pick vAnatomy');
if isnumeric(vAnatFile)
return
end
% img output is IPR oriented
[i... |
function varargout = MITOMIAnalysis_SetCoordinates(varargin)
% MITOMIANALYSIS_GUI MATLAB code for MITOMIAnalysis_GUI.fig
% MITOMIANALYSIS_GUI, by itself, creates a new MITOMIANALYSIS_GUI or raises the existing
% singleton*.
%
% H = MITOMIANALYSIS_GUI returns the handle to a new MITOMIANALYSIS_GUI or the ... |
% function zad3
clear
clc
M=19.9;
t0=89+273;
Ws=1.02;
t1=18+273;
ass=0.5:0.5:4.5;
ds=[0 0.038 0.146 0.309 0.5 0.691 0.854 0.942 1];
WP=1-ds;
c0=53.713;
c1=33.41;
% c0=54.849;
% c1=31.311;
W=100*M/(100+c0);
S0=c0*M/(100+c0);
S1=c1*M/(100+c0);
M1=S1+W;
m=S0-S1;
mp=m/1;
Wpp=1+mp;
dd=fsolve(@(x... |
function r = AGLQ(sub, x, a, b, c, d, p, ww, epsilon, C, k, type, varargin)
% AGLQ.m
% Adaptive Gauss-Legendre Quadrature
%
% Input: sub, 4 subscripts of the 4th order tensor T, 1 by 4 matrix; {????}
% x, 3 semi-axes of an inclusion, a 3 by 1 matrix;
% a,b, the integrating range of theta;
% ... |
%% Scripts for the vegetation rehabilitation model, according to figure order
% 1) Equilibrium and response to droughts (2 sections)
% 2) Impact of temporal noise (3 sections)
% 3) Simulations with parameters comparable to remote-sensing data (2 sections)
%% Initial setup (including perliminary simulations)
lamf=3.25... |
% Generated through Matlab
% Author: Killian Keller
% E-Mail: killian.keller@ief.ee.ethz.ch
% Organization: ETHZ ITET IEF
function [results] = QuantumEvaluation(model, varargin)
% Function to Evaluate the evolution of the bosonic wavefunction.
% Takes as arguments the model and the model ... |
function state=divideNlevel(val,max,min,n)
diff=(max-min)/n;
a=min;
for i=1:n
a=[a min+i*diff];
end
i=1;
while(val>=a(i)&&i~=length(a))
i=i+1;
end
state=i-1;
end |
function structures = loadRT(dcm, imstruct, varargin)
% loadRT loads a DICOM RT Structure Set (RTSS) file and
% extracts the voxel segmentation/mask and metadata. If the centre of the voxel is inside the rtstruct polygon it is included.
%
% Important: The mask corresponds to image data loaded by loadRThelper, which... |
wavname='C:\soundfiles\consonants\turner\ah-asha.wav';
wavname='c:\soundfiles\words\Words_diction\friends';
wavname2='c:\soundfiles\consonants\ah-aba-st.wav';
wavname2='c:\SoundFiles\sentences\timit\dr2_fram1_sx190.wav';
% Beginning Jan 25, 2012, T, C gains_dB and pw fields have elements
% aligned with p.electrocd... |
%% test the function spimpulse1207
% s-parameter contains all 1's
% construct sp column vector
sp = ones(1,11)';
fstep = 1; % here we assume fstep = fstart
[ires, tstep, err, errmsg] = spimpulse1207(sp,fstep);
tlist = [0:tstep:tstep*(length(ires)-1)];
irest = ires'; % transpose
plot(tlist, irest);
... |
%*****************************************************************
% Description: calculate q and m in the network
% Usage:
% [m, q, mG, qG, m_std, q_std] = diffInNetwork(diff, half_ind, area, signed)
% Input:
% diff£ºthe difference variance maps of SZ-HC with dimension N x length(half_ind)
% half_ind: t... |
% HF MODEL
% -----------
% ATRIBUTOS_PARA_ENTRENAMIENTO - DEFAULT INPUTS
SEL_SNPSH_DISP = ''; % Selection of snapshot displacements
% OPTIONS
% 1) SEL_SNPSH_DISP = ''; Ignores this variables (selection follows .mfl file indications)
% 2) SEL_SNPSH_DISP = 'ALL', the entire set of realizations of the displacement vecto... |
r1 = 10;
r2 = 6;
D = 8;
assistedRate = zeros(100,1);
rate = zeros(100,1);
SNR = zeros(10,1);
pdfRate = zeros(10,1);
directRate = zeros(10,1);
Ps = 1;
Pnoise = 1;
for i = 1:10
alpha1=0.5;
alpha2 = 1-alpha1;
Psb = alpha1*Ps;
Psm = alpha2*Ps;
% beta1 = 6.6*10^(-5);
% Psm1 = beta1*Psm... |
function [ all ] = hnak(op,ass,all)
%hnak - m/z analysis for the peaks found with H/Na/K adducts. For Luisa.
%I'll put a better description in here when I've worked out how the
%function is likely to work.
%
% INPUTs (* denotes optional input)
% op - from lipid analysis toolbox
% ass - also from lipid analysis too... |
function plot_cameras(fig, cameras, axis_length)
ax = gca(fig);
F = size(cameras, 3);
% Get camera centers.
centers = zeros(F, 3);
for t = 1:F
P = cameras(:, :, t);
R = P(:, 1:3);
d = P(:, 4);
centers(t, :) = (-R' * d)';
end
lim = axis_limits(centers);
init3(fig, lim);
for t = 1:F... |
function mtx = Normalize(mtx)
%% Function that normalize input matrix by column
%% each element x will be normalized by (x - mean) / stddev
M = mean(mtx, 1);
s = std(mtx, 1);
mtx = (mtx-M)./s;
end |
function x = addSumLoops( n )
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
tic;
i=size(n,1).*size(n,2);
y = 0;
for j=1:i
y=y + n(j);
end
x=toc;
end
|
function [ action ] = deterministicPolicy(state, mdp, weights,use_fast_VOC1_approximation)
if not(exist('use_fast_VOC1_approximation','var'))
use_fast_VOC1_approximation=true;
end
%Thompson sampling for contextual bandit problems
w_hat=weights;
[actions,mdp]=mdp.getActions(state);
for a=1:numel(actions) %parfor
... |
% Load dielectric function for interphase
function [] = comsol_load_epsilon_model(data)
global epmodel extra_E_infi
load(data);
% Read in the MTD from the output of Dynamfit
NumOfTerms = length(TemPR);
for i = 1 : NumOfTerms - 1
MTD_Coeff(2*i-1)=TemPR(i,2);
... |
clear;
clc;
load('peppers_bcsspl_dpcm_results.mat')
load('peppers_bcsspl_MFPQ_results.mat')
load('peppers_bcsspl_SDPC_ch8_results.mat')
load('peppers_bcsspl_SDPC_ch16_results.mat')
load('peppers_bcsspl_SDPC_results.mat')
rate_SDPC = sort(rate_SDPC)
rate_DPCM = sort(rate_DPCM);
rate_M... |
function dspcheck(Filename,Levels,PhotometerID,PortNum)
% Sample script dspcheck v1.33
%
% Check calculated XYZ values for monitor with photometer
%
% Usage:- dspcheck(DCFname,Levels,PhotometerID,PortNum) or
% dspcheck(DCFname,XYZ,PhotometerID,PortNum) or
% dspcheck(DCKname)
%
% DCFname = Display... |
function char2file(C,FName,Type)
% char2file [Not a public function] Write character string to text file.
%
% Syntax
% =======
%
% char2file(C,FName)
% char2file(C,FName,Type)
%
% Input arguments
% ================
%
% * `C` [ char ] - Character string that will be written to the file.
%
% * `FNa... |
function [img,H] = iradon(varargin)
%IRADON Compute inverse Radon transform.
% I = iradon(R,THETA) reconstructs the image I from projection
% data in the 2-D array R. The columns of R are parallel beam
% projection data. IRADON assumes that the center of rotation
% is the center point of the projections, wh... |
% Mixture Model BPS for T forecasts
clear; clc;
%====================%
% Forecasts and Data %
%====================%
load('bps_eurForecastsFull.mat');
f=f1; s=s1; k=k1; % one step ahead forecasts
% f=fh; s=sh; k=kh; % h step ahead forecasts
clear 'f1' 'fh' 's1' 'sh' 'k1' 'kh';
% choose which models t... |
%% 1. Una función que convierta de binario a base decimal.
function [d] = bintodec(b)
% BINTODEC
% Esta funcion convierte un numero binario a decimal.
% Formato de entrada: arreglo de numeros binarios ([(0|1) (0|1) ... (0|1) (0|1)]).
d = 0;
for i = length(b):-1:1
if(b(i) == 1)
d... |
function [handles] = plot_grand_averages_beamformer_masked(cfg, ...
input_variables)
% This function plots grand average beamfomers, first input variable should
% be grand average beamformer and second should be statistics
%
% cfg must contain:
%
% cfg.event_comp... |
function spectrogramData = preprocess_runs_spectrogram(runProcessedData,params_spectrogram)
spectrogramData = runProcessedData;
global verbose
nRun = numel(runProcessedData);
fs = runProcessedData{1}.rate;
win = params_spectrogram.mlength*fs;
noverlap = win - params_spectrogram.wshift*fs;
for iRun = 1:nRun
if v... |
% function Fig12_OutsideOut_AsymmetricCl_v2
%
% Show effect of asymmetric Cl concentration on anion current
% Outside-out pipette containing 150mM K+, 10mM Cl-, and 140mM gluconate
% Plot concentration and voltage-change at the end of pipette containing
% 150mM KCl as a function of IK+*Raccess, and |INa+... |
function traceOut = getTrace(finneeStc, address, varargin)
%% DESCRIPTION
% 1. INTRODUCTION
% GETTRACE is used to retrieve a trace (profile, MS spectra, ...) that has
% been save in the finneeStc. dataOut is the mxn array that contain all
% data related to the specified trace.
%
% 2. INPUT PARAMETERS:
% . re... |
% Function creates a subject folder. Automatically checks which repetition
% of the experiment it is and suggests to save session number
%
% Prespecified screen size and distance are necessary!
% Multiple outputs as structure 'screen' containing all initalized display
% properties
%
% v1 DJ: February 11, 2015
functio... |
function top_bul(resim)
I = imread(resim);
bw = im2bw(I);
[a,b] = bwlabel(bw);
c = (a==2);
s = regionprops(c, 'centroid')
sz = size(c)
merkez = s.Centroid
if merkez(1) < sz(2)/2
yon1 = 'sol';
else
yon1 = 'sağ';
end
if merkez(2) < sz(1)/2
... |
function [res, txtns] = compareScriptSolStudent(callerName,nameVars,apCleaned,apStudentSol)
%COMPARESCRIPTSOLSTUDENT A helperfunction for the testing the answers of
%students by comparing it to a Solution file.
%
% ------------------------------------------------------------------------
% Copyright (C) 2017 M. Sch... |
function l=prob_to_log_odds(p)
% Convert proability values p to the corresponding log odds l.
% p could be a scalar or a matrix.
% TODO: compute l.
l = log(p./(1-p));
end
|
clear
close all
clc
file_name = 'lost.plt';
m=importdata(file_name,' ',6);% 6 rows for the column header.
lost=m.data;
[~,thet,zet,x,z,en,ptch,P,P0,mu_times_B,~,V,~,~] = valuation(lost);
n=length(thet);
k=0;
t0=-pi/30; % FILD position midplane [-thet,thet], -thet=t0, thet=tm
tm=pi/30; % or FILD position [t0, tm]
phi... |
% add path of feature extraction
addpath(genpath('/tmp3/yuchen/BoAP_Adaboost/gbvs'));
load('/tmp3/yuchen/BoAP_Adaboost/data/flickr_dataset/model.mat', 'model');
[id, url, x, y, w, h, vote] = textread('/tmp3/yuchen/flickr_dataset/crop/test_0.1.txt', '%u %s %u %u %u %u %u');
%[id, url, x0, y0, w0, h0, x1, y1, w1, h1, vo... |
function [prob_y_given_x] = Apply_MIL(x,h,no_of_classifiers)
h_best = zeros(no_of_classifiers,size(x,2));
prob_y_given_x = zeros(size(x,2),1);
for k = 1:size(h,2)
m = h(1,k);
for i=1:size(x,2)
prob_f_given_y1 = normpdf(x(m,i),h(2,k),h(3,k));
prob_f_given_y0 = normpdf(x(m,i),h(4,k),h(5,k));
h_b... |
function A=makeLowRankMatrix(n,k)
U=2*rand(n,k)-1.0;
N=sqrt(sum(U.^2)).^(-1);
U=U.*(ones(n,1)*N);
%V=2*rand(m,k)-1.0;
%N=sqrt(sum(V.^2)).^(-1);
%V=V.*(ones(m,1)*N);
A=U*U';
end |
function poly=rotatePoly(poly,R)
for i=1:length(poly)
poly(i).xy=poly(i).xy*R;
end |
unction [ Recall ] = getRecall( Target, Output, varargin )
%Compute Recal (Sensitivity) Baseline Predicted Label and Actual Label
% Recall = recall(Actual, Predicted);
%
% J. Cagle, University of Florida, 2016
TruePositive = sum(Output(Target == 1));
TotalPositive = sum(Target == 1);
Recall = TruePositive/TotalPos... |
function I_s = spatialInertiaTensor(I_com, r_com, m)
r_comM = vecX3D(r_com);
I_O = I_com - m*r_comM*r_comM;
I_s = [I_O m*r_comM;
m*r_comM' m*eye(3)];
end |
function add_raw_data_to_database( outerfolder, varargin )
% ADD_RAW_DATA_TO_DATABASE -- Add un-processed behavioral data (and
% references to neural data) to the sqlite database.
%
% add_raw_data_to_database( outerfolder ) adds all data in the
% subfolders of `outerfolder` to the database.
%
% IN:
%... |
function ret = loss(model, data)
% mean cross-entropy loss.
% Your code here.
xpn=data.inputs; %训练数据集
xln=data.targets; %数据标签
wih=model.input_to_hid; %从输入到隐藏层的权重矩阵
whc=model.hid_to_class; %从隐藏层到输出层的权重矩阵
% 先正向传播求取网络输出(softmax)；
sj=wih*xpn;
xj=1./(1+exp(-sj));
si=whc*... |
% Solucion del problema de minimos cuadrados con la factorizacion QR.
% Sea A una matriz de tamaņo 5x3.
A = [ 1, -1, 3;
3, 1, 4;
1, 2, 3;
-1, -2, -5;
4, 3, 1];
% Obtener la factorizacion QR.
[Q,R]=qr(A);
% Para confirmar que Q es una matriz ortogonal, hay que multiplicar Q por
% su tra... |
function CreateTableMediationResults(LocalMaxima,InputImage)
% Input is a text file created from FSL
% InputImage is the file used to create the list of local maxima
[PathName FileName] = fileparts(InputImage);
if ~isempty(PathName)
cd(PathName);
end
load(fullfile(PathName,'data','ModelInfo'));
Vpath = spm_vol(I... |
function [ VAR,SING ] = LSKNM( N, M, M0, M1, HM, SC, HX, W,X,Y )
%LSKNM DETERMINES LAY-FUNCTIONS AMPLITUDES FOR A NUMBER OF CONSTRAINTS
%
% SUBROUTINE LSKNM ( N, M, M0, M1, HM, SC, HX, W,X,Y,VAR,SING)
% --------------------------------------------------------------------
% DETERMINES LAY-FUNCTIONS AMPLITUDES F... |
start = clock;
clf
[x,y] = meshgrid(-4:0.1:4);
z = x.^3 +- y.^3;
%%% mesh(x,y,z);
meshc(x,y,z);
elapse = etime(clock,start) |
function state = state_snew(rate,shape,gram,m,covtype,Sind)
% does basically the same than updateW and updateOmega, but approximately,
% and using the accumulated sufficient statistics
state = struct();
state.W = struct();
ndim = size(m,2); npred = size(gram,1);
fullcovmat = strcmp(covtype,'full') || strcmp(covtype,'u... |
/*
* Copyright (c) 2015 Lutz Hofmann
* Licensed under the MIT license, see LICENSE.txt for details.
*/
freeze;
declare verbose buildingQuotient, 1;
import "buildingLib.m" : FiniteFldListAddOne;
// quotient building of G \ Gamma0
QuotientBuildingRec := recformat <
representatives : SeqEnum, // a sequence of r... |
function [child1_binx, child1_biny, child2_binx, child2_biny] = point_crossover(parent1_binx, parent1_biny, parent2_binx, parent2_biny, cross_over_index)
% single-point crossover
child1_binx = [parent1_binx(1:cross_over_index) parent2_binx(cross_over_index+1:end)];
child2_binx = [parent2_binx(1:cross_over_i... |
%% Wake rollup calculations
if (Rollup == 1 && i_t > 1)
if i_t > Nlump*Nstep + 1
lump = 1;
else
lump = [];
end
[u,w] = WakeRollupVelocity2D([xw(2:wakeInd+1) lump*xl(1)],[zw(2:wakeInd+1) lump*zl(1)],mu(:,1)',muTE(1),[muW(1:wakeInd) lump*muLump(1)],muLEt,muLEb,sigma',xp',zp',vt',vn',xTE'... |
function lw_wave(type)
% One-Dimensional Wave Eqution Using Lax-Wendroff Scheme
Nx = 501;
Nt = 1501;
L = 1;
% Setup
x = linspace(0,L,Nx);
dx = L/(Nx-1);
a = 0.3;
dt = a*dx;
u = zeros(Nx,Nt);
ux = zeros(Nx,Nt);
ut = zeros(Nx,Nt);
% Initial Condition
if strcmp(type,'triangle')
for i = 1:Nx
xi = dx*(i-1);
... |
function [xs, tris] = readmesh(filename)
fid = fopen(filename, 'r');
%check if file was opened
if (fid == -1)
filename = ['can not open the file ' filename];
error(filename);
end
s='';
while ~strcmp(s,'Vertices')
s = get_nextline(fid);
end
s = get_nextline(fid);
nnodes=strread(s,'%d');
xs=zeros(nnodes,3);
f... |
load('ex7faces.mat');
[m, n] = size(X);
[X_norm, mu, sigma] = myFeatureNormalize(X);
U = pca(X_norm);
displayData(X(1:100, :));
Z = projectData(X_norm, U, 100);
X_rec = recoverData(Z, U, 100);
figure;
subplot(1, 2, 1);
displayData(X_norm(1:100, :));
hold on;
subplot(1, 2, 2);
displayData(X_rec(1:100, :));
|
P = 40; % real power, MW
V = 30/sqrt(3)+ j*0; % phase voltage, kV
Zs = j*9; % synchronous impedance
ang = acos(0.4);
theta=ang:-0.01:-ang; % Angle from 0.4 leading to 0.4 lagging pf
P= P*ones(1,length(theta)); ... |
% Plots surface elevation for the given ITTC spectra
H_significant = 2.5;
T_peak = 9.0;
omega_peak = 2.0 * pi / T_peak; % in Hz
omega_peak = 2.0 * pi * omega_peak; % in rad/s
omega_low = 0.2;
omega_high = 3.0 * omega_peak;
g_accel = 9.81;
PLT_NUM = 150;
dw = (omega_high - omega_low) / PLT_NUM;... |
x=[10.0002 10.000029]
e=[0.0001 9.99*10^(-8)]
p=errorbar(x,e)
h = findobj (p, "type", "line");
delete(h(1))
ylim([10 10.0004])
text (1, x(1), " Oscilloscopio");
text (2, x(2), " Contatore");
|
function [alignedBScan flatline transformline] = alignAScans(bscan, params, line)
% ALIGNASCANS: Aligns A-Scan according to a given firstline. The Image is cut to
% given values above or below, or a second firstline can be igiven, that is for
% sure also included in the image.
% [ALIGNEDIMAGE FLATLINE TRANSFORMLINE] = ... |
function [attentionweights, associationweights] = UPDATE(associationweights, ...
attentionweights, target, outputactivation, hiddenactivation, ...
exemplars, networkinput, params)
%--------------------------------------------------------------------------
% This script updates the weights of an ALCOVE network based o... |
function X = dec_2_bin(num,bits)
% converts decimal number "num" to binary, represented as a vector of bits,
% length specified by input "bits"
X = zeros(bits,1);
for i = bits : -1 : 1
if num >= 2^(i-1)
X(i) = 1;
num = num - 2^(i-1);
end
end
|
clear;
% Input image
tools = few256;
% smooth tools
tools_smoothed = discgaussfft(tools, 4);
% 1 for the simple differences operator
% 2 for the central differences operator
% 3 for the Roberts cross edge operator
% 4 for the Sobel operator
gradmagntools_1 = sqrt(Lv(tools_smoothed, 1));
gradmagntools_2 = sqrt(Lv(too... |
function [ choice ] = Chicken_30485493( history )
% Defines a strategy for the chicken or dare game a
% assuming the number of rounds is one thousand
% The key advanatge of this strategy to my taste is that it shifts
% between very different tactics based on a more long term experience
%=== Strategy types ===
%P - pea... |
%% ======================= Building Response Time =======================
% This script identifies the start and the end of the trail. It integreats
% the start stop data with it with results from the Feedbacktype script and performs core
% statistical inferences computationsfrom
% proband=1 ;
% all = all2(proban... |
l=0.085;
lb=0.075;
mb=0.419;
mw=0.204;
Ib=3.34*10^-3;
Iw=0.57*10^-3;
Cb=1.02*10^-3;
Cw=0.05*10^-3;
Km=25.1*10^-3;
g=9.81;
T=0.02;
A=[0,1,0;(mb*lb+mw*l)*g/(Ib+mw*(l^2)),-Cb/(Ib+mw*(l^2)),Cw/(Ib+mw*(l^2));-(mb*lb+mw*l)*g/(Ib+mw*(l^2)),Cb/(Ib+mw*(l^2)),-Cw*(Ib+Iw+mw*(l^2))/(Ib+mw*(l^2))/Iw];
B=[0;-Km/(Ib+mw*(l... |
person = struct( 'name ', 'Per ', ' date_of_birth ', date , 'phone ', 48151623);
|
function scnds = sekonds(sim, act)
if sim == 1
scnds = 0;
elseif sim == 2
scnds = act;
end
|
function [bins, binwidth, psth] = buildpsth(prestimdur, poststimdur, totRelSpks)
% bin data into 5ms bins & determine firing rate
binwidth = 0.001;
bins = -prestimdur:binwidth:poststimdur;
binned = nan(1,length(bins)-1);
for bi = 1:length(bins)-1
thisDataIdx = totRelSpks > bins(bi) & totRelSpks < bins(bi+1);
... |
function [lst]=utc2lst(mjd,longitude)
[year,month,day,hour,minute,secs,ticks] = mjd2utc(mjd);
lst = mod(hour+minute/60+(secs+ticks)/60/60+longitude/15.0,24.0);
|
% readdata.m:
% This file is used to read data from file 'Ddatak8' produced by readdatak8.m, as k=4.
% The raw data can be found here:
% https://github.com/undersunshine/machine_learning_algorithms/blob/master/Matrix_Factorization/data.csv
% Copyright (c) 2018 CHEN Tianyang
% more info contact: tychen@w... |
function keypoints = upscale_keypoints_to_full_image_size (keypoints)
% keypoints = UPSCALE_KEYPOINTS_TO_FULL_IMAGE_SIZE (keypoints)
%
% Upscale keypoints, obtained on half-sized images, to full image size.
% This function adjusts both keypoint location and size by factor 2.
% The location is also a... |
% Function for Plotting The Plots
function [spikes_baseline, spikes, mean_baseline, mean1] = plot_data(baseline_start, baseline_stop, start, stop, type)
global action_threshold
global samplingRate
[voltage_baseline, time_baseline] = get_voltage(baseline_start, baseline_stop);
length(voltage_baseline);
... |
je_base=g1{1};
je_plus=g1{4};
% Select direction
je_base=squeeze(je_base(3,1,:));
je_plus=squeeze(je_plus(3,1,:));
diffo=je_plus-je_base;
[oud]=isoutlier(diffo);
ind=find(oud);
Ind=zeros(size(diffo));
Ind(ind)=1;
%%
plot(je_base)
hold on
plot(je_plus)
stripes(Ind,0.2)
ylim([0 max(max([je_base je_plus]))])
xlim([2... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Wenan Chen
% September, 2007
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function center the image with the given center.
function centered_img=centerimg(img,center,method)
% input: img is the image to be centered, center is the coordinate with
... |
function [a_sync, b_sync, a_ind, b_ind] = sync(a, b, thres)
%{
Synchronize two vectors. Used to synchronize the color and depth (or
point cloud) messages.
Inputs:
- a: first vector.
- b: second vector.
Returns:
- a_sync: vector a with only the synchronized elements.
- b_sync: vector b ... |
function soundSegment=findSegment(express)
if express(1)==0
voicedIndex=find(express); % Find the position of 1 in express
else
voicedIndex=express;
end
soundSegment = [];
k = 1;
soundSegment(k).begin = voicedIndex(1); % Set the starting position of the first group of segments
for i=1:length(voicedIndex)... |
function [ accuracy ] = get_accuracy(predictions)
%GET_ACCURACY Given the predictions and the testing data, calculate the
%accuracy of the predictions.
% accuracy = GET_ACCURACY(predictions) will return the correctness
% (between 0 and 1) of a given model's predictions.
num_classes = size(predictions, 2);
num_sam... |
% load the baseline data
load outdata/measuredField_at_shot_32_with_freq_8/baseline_data.mat
% load the monitor data
load outdata/measuredField_at_shot_32_with_freq_8/monitor_data.mat
% load the time-lapse data
load outdata/measuredField_at_shot_32_with_freq_8/residuals_recorded.mat %% d1-d0
% I do not want to worr... |
%% --------
% QC_01_08_CumulativeEventCount(MeasCat)
% Cumulative Event Count
% Input: MeasCat - Measured catalogue
function NumberOfEventsCumul = QC_01_08_CumulativeEventCount(MeasCat)
% close all
if ~isnumeric(MeasCat)
error('Load catagoue in the correct format (see readme for description)')
end
%% definit... |
function data=nut_sampledata(par,trlval)
data_loc=cell(length(par.run),1);
for r=1:length(par.run)
data_loc{r}=ns_fif2ft(par,par.run(r));
%% select trials based on trlval
data_loc{r}.trial=data_loc{r}.trial(find(ismember(data_loc{r}.trialinfo,trlval))');
data_loc{r}.trialinfo=data_loc{r}.trialinfo(find(... |
%function [pearson,spearman]=assessment(result,subject,flag_plot)
%090119 ģ���������۲���
clc;
%绘制传统方法曲线专用
fid1=fopen('/media/s408/GLORIA/ACMM/code/niqe/niqe_scores.txt');
fid2=fopen('/media/s408/GLORIA/ACMM/code/niqe/niqe_val.txt');
c1=textscan(fid1,'%f');
c2=textscan(fid2,'%f');
fclose(fid1);
fclose(f... |
function test_example_DBN
load mnist_uint8;
train_x = double(train_x) / 255;
test_x = double(test_x) / 255;
train_y = double(train_y);
test_y = double(test_y);
%% ex1 train a 100 hidden unit RBM and visualize its weights
% rand('state',0)
% dbn.sizes = [100];
% opts.numepochs = 50;
% opts.batchsize = 100;
% opt... |
function [y1] = Battery_Classifier(x1)
%MYNEURALNETWORKFUNCTION neural network simulation function.
%
% Generated by Neural Network Toolbox function genFunction, 22-Jun-2017 23:26:16.
%
% [y1] = myNeuralNetworkFunction(x1) takes these arguments:
% x = 2xQ matrix, input #1
% and returns:
% y = 3xQ matrix, output #1
... |
function [outputStruct] = processSpikeTrainProperties(inputStruct)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Description:
% for given cell spike properties/times, advances to next processing stage of
% spike train properties (AC, XC with other trains, ISI distribution, ... |
clear;
clc;
%读入Train文件中所有文件名
fileRoot = pwd;%当前工作路径
fileFolder=fullfile([pwd '\Final Proj\SISR\Train']);
fileCluster = fullfile([pwd '\Final Proj\SISR\Cluster1\cluster.txt']);
dirOutput=dir(fullfile(fileFolder,'*.jpg'));
fileNames={dirOutput.name}';
img_num = length(fileNames);
sf = 3;
HRtoVECTOR = [1:81];
%patch的大... |
% limiar para pixel activo
global T;
T = 0.1;
% area minima para ser considerada regiao
global minarea;
minarea = 50;
% primeira frame
global fframe;
fframe = 0;
% ultima frame
global lframe;
lframe = 549;
% numero minimo de regioes emparelhadas para ser considerado segmento
global strokeThr;
strok... |
%Frequency domain Low pass filter
clc;
clear all;
close all;
a=imread('dewdrop.jpg');
[m n]=size(a);
mask=zeros(m,n);
for i=150:180
for j=210:240
mask(i,j)=1;
end
end
c=fftshift(mask);
b=fft2(a);
d=b.*c;
e=abs(ifft2(d));
subplot(2,2,1),imshow(a),title('original image')
subplot(2,2,2),im... |
function gaborResult = l1(img, gaborArray,u,v,x,y)
gaborResult = cell(u,v);
for i = 1:u
for j = 1:v
gaborResult{i,j} = (abs(conv2((img),(gaborArray{i,j}),'same')));
% chave � cell e parenteses � a matriz naquela posi��o da c�lula
% Faz a troca
% for a = 1... |
function price = barrier_opt_pricing_formula(sigma, K, H)
% STs final stock price
% K is the strike price
% H the barrier
% q dividend rate
global rf_r;
global T;
global initial_capital;
S0 = initial_capital;
q = 0;
m1 = (log(S0 / K) + (rf_r - q + sigma^2 / 2) ... |
function [distance, coefficient] = It_bhattacharyya(mean1, mean2, cov1, cov2)
cov1 = (cov1);
cov2 = (cov2);
covP = (cov1 + cov2) / 2;
% coefNeperiano1 = det(covP/chol(cov1*cov2));
coefNeperiano2 = det(covP) / sqrt(det(cov1)*det(cov2));
distance = (1/8) * ((mean1-mean2)*pinv(covP))*(mean1-mean2)' + (1/2) * log(coefN... |
s = niftiread('/Users/stefangrivalsky/dataset/MICCAI_BraTS17_Data_Training/LGG/Brats17_TCIA_623_1/Brats17_TCIA_623_1_flair.nii.gz');
sizeO = size(s);
disp(size0)
figure;
slice(double(mriVolumeOriginal),sizeO(2)/2,sizeO(1)/2,sizeO(3)/2);
shading interp, colormap gray;
title('Original'); |
%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Sam Feig
% Vladimir Zhdanov
%
% CSCI 4831/5722
% Homework 1
% Instructor: Ioana Fleming
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ outImg ] = addRandomNoise_NL(inImg)
inImg = double(inImg);
% Generate random noise
noise = randi([-255, 255], size(inImg, 1), size(inImg, ... |
% Final Project - Interest Points Detection and Image Matching
% Author: CÚline Bensoussan & Jill Perreault
% Course: Computer Vision
% Date: April 15, 2013
function SSD_table = SSD(d_im1, d_im2, M)
% SSD: Generates the sum of the squared difference of all descriptors of all
% points from image1 and image2
... |
function [NewPoints, removedPtNum, keepAskingBoolean] = TrackNext(img,ROIsize,TrackPoints,remPoints, maxTravel, increaseROINum, soundOption)
%TrackNext Tracks points selected in SelectPoints for a different image
% TrackNext(img,TrackPoints). img: image to find points in, TrackPoints:
% points selected previously.
... |
%%% this code implements the Greedy Gradient based Max-Cut algorithm
%%% updating by pick up the most possible samples; This version is robust
%%% to weight matrix;
function [predict, error]=ggmc(data,gnd,labeled_ind,graph)
gnd=reshape(gnd,1,length(gnd));
data_num=length(gnd);
class_num=length(unique(gn... |
function phi = Phi_Calculation(state, mu, sigma)
x = state(1,1);
v = state(2,1);
%figLocal = figure();
%figure(figLocal);
%hold on
%scatter(mu(:,1),mu(:,2), 'filled');
phi = zeros(length(mu),1);
% For each centrum
for i = 1:length(mu)
c_x = mu(i,1);
c_v = mu(i... |
%3D grid (prototype)
clf;
[x,y,z] = meshgrid(0:1);
V=x.*y.*z;
a = axes;
daspect([1 1 1]);
view(3);
hold on;
for i=0:50
for j=0:50
for k=0:10
hSlice = slice(x+i,y+j,z+k,V,i+1,j+1,[0 k+1]);
hSlice = slice(x+i,y+j,z+k,V,i,j,[0 k+1]);
end
end
end
|
% GardnerReverbFaderTest.m
% clear;clc;
[in,Fs] = audioread('AcGtr.wav');
verb = GardnerReverbFader();
size = 1;
gain = 1;
mix = 0.8;
verb.setFs(Fs);
verb.setSize(size);
verb.setGain(gain);
verb.setMix(mix);
out = verb.process(in);
plot(out);
|
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