text stringlengths 8 6.12M |
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function [MFCCs] = calcMFCCs(sig, params)
% Define variables
Tw = 25; % analysis frame duration (ms)
Ts = 10; % analysis frame shift (ms)
alpha = 0.97; % preemphasis coefficient
M = 20; % number of filterbank channels
C = 12; % numb... |
function [state,isLoopClosed] = mpcNestedOptimizer(track,car,n,N,dt)
initState = car.state;
width = 1.25;
isLoopClosed = false;
xLast = []; % Last place computeall was called
myceq = []; % Use for nonlinear inequality constraint
myc = []; % Use for nonlinear equality constraint
... |
fs=10000;
A=[0.5 0.5];
F1=[350 440];
P=[0 0];
td1=4;
x1=SumOfSines(A,F1,P,td1,fs);
%sound(x1,fs);
F2 = [480 620];
td2=0.5;
b1=SumOfSines(A,F2,P,td2,fs);
disp(size(b1));
z1=zeros(length(b1),1);
x2=cat(1,b1,z1,b1,z1,b1,z1,b1,z1);
%sound(x2,fs);
F3=[440 480];
td3=2;
b2=SumOfSines(A,F3,P,2,fs);
z2=zeros(length(b2),1);... |
clear all; close all; clc;
fprintf("3.4 Ecuaciones stiff : explıcito vs implicito")
fprintf('\n')
fprintf("1.- Aplicar Euler implicito al PVI")
fprintf('\n')
%Genera [Tn Wn] con el metodo de Euler implicito
Tn=0:0.5:20; %Crea el espaciado con h=.5
Wn=zeros(1,size(Tn,2));
Wn(1)=0.5; %condicion inicial
for i=1:size(Tn,2)... |
caps_KCl;
[output] = extreme_GHK_elecoPoration_test(kcl_1M_bd,'KCl','Cation',1);
zrcl4_1M_breakdown;
[output] = extreme_GHK_elecoPoration_test(zrcl4_1M_breakdown,'ZrCl4','Anion',1);
zrcl4_100mM_breakdown;
[output] = extreme_GHK_elecoPoration_test(zrcl4_100mM_breakdown,'ZrCl4','Anion',1);
caps_graphene_etching;
[... |
%% Create layerstack from Optical Indices and SAR:
% M.Brechbühler, GEO441
% define your working directory
%DataDir = 'S:/course/geo441/data/2020_Camargue/';
DataDir = 'W:/Desktop/GEO441/output\2016_feb_stack/';
cd(DataDir);
coordRefSysCode = 32631;
% Multiple files
% get an overview of the data present
sf... |
function [ J ] = obj( S,b,G,S0,L )
%obj Computes the objective function
% J -> Value of the objective function at the given L
J = 0;
for i=1:size(S,2)
c2 = exp(-b*G(i,:)*L*L'*G(i,:)');
c1 = S(i) - S0*c2;
J = J + c1^2;
end
end
|
function x = quad(Coeff)
% Roots of the quadratic polynominal y=ax^2+bx+c
% Input: Vector with the polynominal coefficient [a b c]
% Output: Vector x=[x1, x2] with the two roots
% Example call of the function: A=quad([1 3 5])
D = sqrt(Coeff(2)^2-4*Coeff(1)*Coeff(3)); % Discriminant
x(1) = (-Coeff(2)+D)/(2*Coeff(1));... |
function V = numint2(y);
% NUMINT2
% MATLAB m-file for numerical integration using
% Simpson's rule
% Format: V = numint2(y)
% input: y = an odd-length row vector
%
% Timo Laakso 16.03.1992
% Last revised 16.01.1996
% y must be an odd-length row vector
%
Npt=length(y); Npt2=(Npt-1)/2;
cof=2*ones(1,Npt);
... |
function mean_spiking()
load('./result_data/result_data.mat')
num_neurons = size(results.metadata.iso_qual, 1);
percentiles = [80,85,90,95];
perc = 4;
% Neuron channels and iso qual conditions
PPC_region = results.metadata.channel_num <= 32;
PFC_region = results.metadata.channel_num > 32;
iso_qu... |
function y = ustep(t, ad)
%t: length of time
%ad: advance (positive), delay (negative) factor
y = [];
for i = t
i = i + ad;
if i<0
y = [y 0];
else
y = [y 1];
end
end
|
function ColNames = colnames(This)
% colnames Names of columns in namedmat object.
%
% Syntax
% =======
%
% ColNames = colnames(X)
%
% Input arguments
% ================
%
% * `X` [ namedmat ] - A namedmat object (array with named rows and
% columns) returned as output argument from some model function... |
%% Ex1 a)
clc
L = 2; %Linhas
N = 1e5; %Colunas
a = rand(L, N)>0.5;
b = sum(a)>=1;
respA = sum(b)/N
%% Ex1 b)
clc
respB = 1 - 1/4
%% Ex1 c)
clc
L = 2;
C = 1e5;
a = rand(L,C)>0.5;
b = sum(a) == 2;
c = sum(a) >= 1;
resp = sum(b)/sum(c)
%% Ex1 d)
clc
L = 2;
C = 1e5;
a = rand(L,C)>0.5;
b= sum(a) == 2;
c = a(1,... |
% - Get lists of clean fluorescence frames for each stimulus presentation period
cvnFluorFrameInds = arrayfun(@clean_frames, stimSet.('start_frame'), stimSet.('end_frame'), vbDirtyStart, vbDirtyEnd,vnFluoresenceTimeIndices, 'UniformOutput', false);
% - Helper function for computing the stimulus response metric over a... |
clc;clear all;
filePath = 'C:\Users\Cong\Desktop\t2\';
folderinfo = dir([filePath,'*.jpg']);
for i = 1:length(folderinfo)
fileName = [filePath,folderinfo(i).name];
fileName2 = strcat('gs2_',folderinfo(i).name);
eval(['!rename' 32 fileName 32 fileName2]);
end |
function [x, y] = separa_label(base)
% Separa a base em features e labels
% input:
% base: base de dados completa
% output:
% x: representa as features
% y: representa as labels
x = base(:, 1:end - 1);
y = base(:, end);
end |
function [RX_measure_report, Beam_index_report,tr_oh] = training_period_xyz(client_spec,cb_id)
%Loading Network Parameters
load global_params_incr.mat
N_u = size(client_spec,1);
RX_measure_report = NaN(Nap_bw,N_u);
Beam_index_report = -1*ones(Nap_bw,N_u);
t_tr_o = 0;
t_fb_o = 0;
cb_... |
%% audio recording and feature extraction
% want to determine frequencies of taps and extract these
TITLE = 'Glass-Tap1';
SAVE = true;
Fs = 44100;
Wsize = 4096;
recObj = audiorecorder(Fs, 16, 1);
disp('Start recording.')
recordblocking(recObj, 10);
disp('Done recoding');
% Store data in double-precision array.
data ... |
function writerObj_out=record_video(details,writerObj,action)
% Code created by Jamie M Johns 2019
% Github repository: https://github.com/JamieMJohns/Record-videos-of-animated-ouputs-Matlab-
%details={fps(double or single precis.),video_title,overwrite} (overwrite=1= overwrite if same name exist,overwrite=other = ... |
function [ u, X_, T_ ] = solver_1_5_9( Fxt, a, b, f, M, dt, varargin )
if (nargin > 6)
t = varargin{1};
else
t = 2;
end
nu = 0.1; x = 1;
dx = 1 / M;
T = round(1 / dt);
X = round(1 / dx);
N = t * T; t_real = t * dt * T;
r = nu * dt / dx / dx;
s = nu * dt / dx;
... |
%MODIFY_INPUT modifies the baseline input parameters according to
% user-specifications.
%
% Syntax
% ------
% ui.modify_input();
%
% Details
% -------
% This function obtains the modification to be made from the currently
% entered value in the modify input box.
%
% Examples
% --------
%
% See als... |
function [subject,properties] = get_activation_priors(subject,properties)
disp('=====================================================================');
disp('BC-V-->> Getting activation priors.');
disp('---------------------------------------------------------------------');
Lvj = subject.H... |
function [Head_x,Head_y,Head_z] = head3dFS(VxW_x,VxW_y,VxW_z)
% Subroutine for calculating the gradient of head of the flow
%Head = -grad(PI)
% Chiyu Jiang, Oct 15th, 2015.
global M N P Lx Ly Lz
sx = (2*pi)/Lx; sy = (2*pi)/Ly; sz = (2*pi)/Lz;
A = (1i*M*sx.*VxW_x+1i*N*sy.*VxW_y+1i*P*sz.*VxW_z)./(-(M*sx).^2-(N*sy).^2-P... |
clear;
h_bar = 6.636e-34/2/pi; % [m^2*kg/s)]
mass = 9.11e-31; % [kg]
omega = 2*pi*7.5e8;
param_a = mass*omega/(2*h_bar);
alpha_0 = 1e12;
% If alpha_0 < param_a, wavefunction is the narrowest when it is at the center of
% potential well
% If alpha_0 > param_a, wavefunction is the narrowest when at the extremal
... |
function res = sig_trace4(dstr, xfile, pars)
% Trace sliding fft signals.
% Parameters:
% f0 - starting frequency (default: auto, right of two highest peaks)
% t1 t2 - time range (default: 0..end of signal)
% df - tracing freq window (default: 50Hz)
% dfs - tracing freq window (default: 10Hz)
% window ... |
%% Initial
clear all; addpath('../../routines');
input_file_folder='input';
output_file_folder='output';
%% th ELKC
input_file_name='gaussian_4D.es';
p=f_read_input(input_file_folder, input_file_name);
th_elkc=@(j,hs) f_elkc(j, p.geometrical, p.rf_distribution, p.rf_correlation, hs);
%% Plot
p.hitting_set.thresholds... |
function newTracklet = interpolateTracklet( tracklet, gpParams, tracklets )
% Uses Gaussian process propagation to fill in gaps in tracklet.
trackletVelocities = getTrackletVelocities(tracklets);
trackletData = [tracklets trackletVelocities];
newTracklet = tracklet;
inds = find(newTracklet(:,1));
% diffs = diff(i... |
%RF transmitter information
global f;
global Bw;
global Lamda;
global RFGain;
global SensorGain;
global IniPow;
%Sensor transmitter information
global Kappa;
global Delta;
global Psi;
global Gamma;
global PowTh;
global IniNumST;
global IniBS; |
%% Read images according to train.csv and categorized images into different subfolders according to labels.
% preconditions:
% 1. downloaded the following file into one folder from kaggle(https://www.kaggle.com/c/noaa-right-whale-recognition/data)
% train.csv, imgs.zip file and w_7489.jpg
%
% 2. put train.csv an... |
function project4b
clear all;
img = load('project4/project4bimg.txt');
[H W] = size(img);
inwavelet1 = zeros(H,W);
for i=0:H/8-1
for j=0:W/4-1
inwavelet1(2*i+1,j+1) = (2*img(i+1,j+1)+img(floor(H/8)+i+1, j+1))/2;
inwavelet1(2*i+2,j+1) = (2*img(i+1,j+1)-img(floor(H/8)+i+1, j+1))/2;
end
end
img(1:f... |
close all;
%type xing.txt;
%type ying.txt;
%type zing.txt;
%type timing.txt;
xfileID= fopen('xing.txt','r');
yfileID= fopen('ying.txt','r');
zfileID= fopen('zing.txt','r');
%tfileID= fopen('timing.txt','r');
formatSpec='%f';
x= fscanf(xfileID,formatSpec);
y= fscanf(yfileID,formatSpec);
z= fscanf(zfileID,formatSpec);
%t... |
function f = MPEC_objective(x0, auxdata)
%%%%%%%%%%%%%%
% GMM Objective function for the random coefficients Logit esitmated via MPEC.
%%%%%%%%%%%%%%
W=auxdata{2};
K=auxdata{3};
prods=auxdata{4};
T=auxdata{5};
numProdsTotal=auxdata{6};
x=auxdata{7};
IV=auxdata{8};
v=auxdata{9};
nn=auxdata{10};
share=auxdata{11};
pr... |
function [x1, y1] = linhas(x, y, c);
x1=[];, y1=[y(1)];
for i = 1:1:length(x)-1;
x1 = [x1, x(i), x(i), x(i)];
y1 = [y1, 0, y(i), y(i+1)];
end
x1 = [x1, x(end), x(end)];
y1 = [y1, 0];
end
|
function [ lat ] = estimate_latent_features_eig( A, d)
%estimate_latent_features_eig Returns estimated (undirected) latent features
% A is an (or many) nxn (or nxnxk) adjacency matrix). d optionally
% indicate the dimensions of the in and out feature vectors.
% The default is n for each. The feature vectors are ... |
%% we reproduce hte example from Thomas Most article
% April 12th, 2016
% Gurkan Sin @DTU Chemical Engineering
clear
clc
close all
%%
% In the first example a purely additive model is investigated
% f(y,z) = a1y + a2z.
% The input variables are normally distributed, have zero mean and the covariance
mu=[0 0]; % mu d... |
function [xdata,ydata,Wout,Weff,Wrdn,Win,Wirr] = ...
make_train_data(parm,T,Wout,Wrdn,Win,Wirr)
% Make training and test data set
% [xdata,ydata,Wout,Weff,Wrdn,Win,Wirr] = ...
% make_train_data(parm,T,Wout,Wrdn,Win,Wirr)
% - Output
% xdata : Xdim x Tsample x Ntrial
% ydata : Ydim x Tsample x Ntrial
% Wo... |
clc, clear, close;
set(0,'DefaultFigureWindowStyle','docked');
addpath(genpath(pwd));
% FILE FOR DEBUGGING ONLY. PLEASE USE THE mainACS.m file in the parent
% directory
% load field
load hand
% draw field
field.drawField({1 1 1});
% pick information
fitnessFn.start
fitnessFn.goal
fitnessFn.limitsA
fitnessFn.limit... |
function decision_boundary()
load hw1boundary.mat
data1 = zeros(10201,2);
i=1;
for a=0:0.01:1
for b=0:0.01:1
data1(i,:) = [a,b];
i = i+1;
end
end
data = data1(1:10000,:);
size(data)
meanData = mean(data);
stdData = std(data);
normData_grid = size(data);
for row=1:size(data,1)
for col=1:s... |
function plotderivation()
[X, Y] = meshgrid(-2:0.2:2);
plotfigure(X, Y, @f1, 'task3-f1');
plotfigure(X, Y, @f1derivatedx, 'task3-f1-derivatedX');
plotfigure(X, Y, @f1derivatedy, 'task3-f1-derivatedY');
plotwithquiver(X, Y, @f1, @f1derivatedx, @f1derivatedy, 'task3-f1-quiver');
plotfigure(X, Y, @f2, 'task3-... |
function [ EPST ] = EPST( X, SC, HX )
%EPST STEP
%
% REAL FUNCTION EPST ( X, SC, HX )
% -------------------------------------------------------------- STEP
% COMMON/ARGEXP/ARGMAX
lim = SC*IRI2012.ARGMAX;
if X < HX-lim || X > HX+lim
if X > HX
EPST = 1.;
else
EPST = 0.;
end
el... |
function delta_u = Delta(u,type1,type2)
%% Discrete Forward & Backward difference operator
%% TGV method
%% Input: u, matrix, image
%% type1: integer, 1 = x direction, 2 = y direction
%% type2: integer, 1 = forward difference, 2 = backward difference
%%
%% Output: delta_u, matrix, x/y direvative of... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Author: Alexander Gomez Villa - SUPSI
% Compute spectrum
% -------------------------------------------------------------------------
% dataMatrix: Two row matrix containing PPG and ECG respectevely
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
#Filtro Narrow Band
#
# Características:
# - possui 5 coeficientes;
# - são filtros tipo rejeita-faixa ou passa faixa com banda estreita
# - a resposta em frequência pode ser melhorada se usar múlti-plos estágios em cascata
function [y] = iir_single_pole_passa_faixa(sinal, fs, f_central, largura_banda)
# Sin... |
function grad = grad_logistic(x, W, Y)
% Logistic Loss
n = length(Y);
grad = zeros(size(W,2), 1);
for i=1:n
w = W(i,:);
y = Y(i);
v = exp(-y* (w*x));
% grad = grad + (-y*v) /(1 + v) *(w');
grad = grad + (-y) /(1 + 1/v) *(w');
end |
function output=circuit2exp(circuit,measure)
% This function is to convert quantum circuit into experimental waveform
% blocks.
if nargin<1
S='S';H='H';CZ='CZ';I='I';Sd='Sd';
mX='X2m';
mY='Y2p';
mZ='I';
mI='I';
g1={mX,mZ,mZ,mX,mI};
g2={mI,mX,mZ,mZ,mX};
g3={mX,mI,mX,mZ,mZ};
g4={mZ,mX... |
function [ OPEN_candidate, flag1] = do_search(rob_mat, tar_mat, hn, CLOSED, map)
%UNTITLED5 Summary of this function goes here
% Detailed explanation goes here
count = 1;
OPEN_candidate = [];
flag1 = 0; % flag = 0 represents no feasible solution found
% search the 8 blocks beside the successor
for i = 1:-1:-1
f... |
function rep=representation_specularpaths(eddatafile,reflpathsfile,order,fuente_imagen)
[eddatafilepath,eddatafile,fileext] = fileparts(eddatafile);
eddatafile = [eddatafile,fileext];
Filestem = EDB2strpend(eddatafile,'_eddata');
[reflpathsfilepath,reflpathsfile,fileext] = fileparts(reflpathsfile);
reflpathsfile = [re... |
nodes = [1, 5, 10, 15, 20];
througput = [0.999834, 4.99917 ,9.99629 ,14.9873, 19.9815 ];
%plot (nodes, througput);
per_node_thput = [0, 0, 0, 0, 0];
total_thput_normalized = [0, 0, 0, 0, 0];
% hold on;
for i = 1: 5
per_node_thput(i) = througput(i)/nodes(i);
total_thput_normalized(i) = througput(i)/nodes(i);
e... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 本函数用于计算年化跟踪误差
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function trackingError = annualizetrackingerror(R,Rm,Step)
loc = isnan(R) | isnan(Rm);
R (loc) = [];
Rm (loc) = [];
trackingError = (sum((R-Rm).^2)/... |
noOfParam = 8;
numCol = 1+noOfParam+((noOfParam-1)*noOfParam/2);
if ~exist('dataPath','var')
dataPath='../data';
end
if isTraining == 1
load(fullfile(dataPath,'aesthetics',vidName),'colour','cont','quality');
load(fullfile(dataPath,'faceDetection',vidName),'face','person','frCount');
load(fullfile(dataP... |
function out = H(sfIdx,cutoff)
sfLateralSquared = sfIdx.^2 + (sfIdx').^2; % implicit expansion into 2 dims
% Compute diffraction-limited CTF
out = single(sfLateralSquared < cutoff.^2); |
clear all
% Lorenz's parameters (chaotic)
sigma = 10;
beta = 8/3;
rho = 28;
% Initial condition - large cube of points
xvec = -20:2:20;
yvec = -20:2:20;
zvec = -20:2:20;
[x0,y0,z0] = meshgrid(xvec,yvec,zvec);
yIC(1,:,:,:) = x0;
yIC(2,:,:,:) = y0;
yIC(3,:,:,:) = z0;
plot3(yIC(1,:),yIC(2,:),yIC(3,:),'r.','LineWidth',2... |
function out = tcaForce(delta,temp)
%alright this time I think the model should be correct
%the last fix essentially assumed the diameter of the helix was
%constant which is wrong and I think the initial one may have some
%mistake in the terms
%however no analytic solution for (F,temp) -> delta, hav... |
function rgb = task_green
rgb = [31, 119, 82] / 255;
end |
function[d, fs, l, r, c, b] = rd_audio(filename, filetype, fs)
% RD_AUDIO - Program to read audio files
% [d, fs, l, r, c, b] = rd_audio(filename, filetype)
% reads SPHERE(NIST) or WAVE(Microsoft Wave Format-RIFF) files.
% If the file is of type NIST then the function rdsphere is called.
% [y, Fs, N, W, A, C, B... |
function [train, train_label, test, test_label] = split_train_test(data, label, train_num)
% 在data中随机取train_num作为训练集，剩余做测试集
% 输入：
% data=[N X d]，每行一个d维样本
% label=[N X 1]
% train_num 随机取train_num个样本当做训练集
% 输出：
% train = [train_num X d]
% train_label = [train_num X 1]
% test = [N-train_num X d]
% test_label = [N-train_nu... |
function y = get_r(data)
y = linspace(-data.R, data.R, 2*data.Nr+1);
end |
%Adaboost
%/////////////////read train image and integral
%trainread;
%////////////////compute all image's filter value
Root = 'C:\Users\Pei-Chun\Desktop\STAT231\project2\';
load([Root 'error_h.mat']);
load([Root 'threshold.mat']);
load([Root 'face_values.mat']);
load([Root 'nonface_values.mat']);
load([Root 'D_face.m... |
% EXAMPLEDETECTOR Example class implementing a generic detector
% obj = affineDetectors.exampleDetector();
% obj.detectPoints(img);
%
% This is an example class that demonstrates how to create a trivial
% interest point detector. Modify it to wrap around your own detector
% implementation. This class implemen... |
function ImOut = unifqtz(img, numPartition)
img = double(img);
ImOut = zeros(size(img));
[m, n] = size(img);
tmin = min(img(:));
tmax = max(img(:));
stepsz = (tmax-tmin)/numPartition;
t = tmin:stepsz:tmax;
for i=1:m
for j=1:n
dists = abs(img(i,j)-t);
[~,idx1] = min(dists);
if i... |
function vars = rat_data(validate_data, visualize_data)
%
% Cross-species primate brain data from Rilling & Insel (1999a),
% largely complementary to callosal data in 1999b.
% Includes:
% * Brain volume
% * Grey & white matter volumes
if ~exist('validate_data', 'var'), validate_data = true; end;
if ~exist('v... |
function [bk lik_r]=NETFIT_glm(n,H,fr,x0,par)
%Function fits GLM to spiking data.
% [bk lik_r]=NETFIT_glm(n,H[,fr,x0,options]) fits GLM with parameters bk
% to explain spike train n with spike histories H. n is 1xT vector and
% H is NxT matrix; x0 may be passed as initial guess for bk; fr is 1xT
% vector of freque... |
function [reconStructIn, popAssignInds] = assignPopSpikes(popStruct, simSpikes, simSpikesInds, stimParms)
numSignals = stimParms.numSignals;
numStimStats = stimParms.numStimStats;
% numSimRepeats = simSpikesInds.numSimRepeats;
numSignalsPerStat = numSignals/numStimStats;
numPops = length(popStruct);
clear popAssignI... |
function [points] = generate_coordinates(R,N)
points =[];
for i = 1:N
r = R * sqrt(rand());
theta = rand() * 2 * pi;
pt.x = r * cos(theta);
pt.y = r * sin(theta);
points = [points,pt];
end
|
clear;
for i = 1:43
d0 = (2.8 + (i-1)*0.1) * 0.1;
AA(i) = VdwGaussian(d0, 0, 'gaussian');
AB(i) = VdwGaussian(d0, 3.1415926/2/90 * 60, 'gaussian');
HM(i) = VdwGaussian(d0, 0, 'homogenized');
end
AA = AA./10000;
AB = AB./10000;
HM = HM./10000;
plot(2.8 : 0.1 : 7, AA, 'r--o');
hold on
plot(2.8 :... |
%----------------------------------------------------------------------------
% make_icesst_norm.m
%
% This script opens files with historical sst data starting at 1860 and
% a control run with forcing from 1860
% a simple linear regression to compute the change of temperature between
% 1860 and 2010 is computed.
%... |
%Salvar como "sigmoide"
function g = sigmoide(z)
g = 1./(1+exp(-z));
end
|
clear all
close all
im = imread('imagenes\lily_gray.tif');
im2 = im2bw(im,100/255);
im3 = imresize(im,0.5);
x = size(1);
y = size(2);
c = [x/4, y/4, 3*x/4, 3*y/4];
im4=im(c(1):c(3),c(2):c(4));
subplot(2,2,1);
imshow(im);
title('Original image');
subplot(2,2,2);
imshow(im2);
title('Thresholdized image (t=100)'... |
function fprintfM_Sci(s,A)
% function fprintfM_Sci(s,A)
% Displays the matrix A in "matrix scientific notation''
% according to print format specified by the string s,
% For example, if
% A = [ 45 1234; -34 0]
% and
% s = '%7.4f'
% then the display would be
%
% 0.0450 1.2340
% ... |
function [] = bq_demo()
% A very simple Bayesian quadrature (BQ) implementation and test case in 1d.
%
% We first compute probabilistically the integral
%
% I_1 = int{f(x)pi(x)}dx,
%
% where pi is a known Gaussian density, f is an expensive black-box function and where the
% integration is over the real numbers. GP... |
%%%Clear console, variables and close all windows%%%
clc;
clear ;
close all;
%%% Carregar dados e inicializacao das variaveis %%%
data= load('formantdata.mat');
x0 = data.D;
y0 = data.L;
x1 = [];
x2 = [];
mu1 = [randn randn];
mu2 = [randn randn];
epsilon = 0.001;
max = 10;
J_old = 100000;
J = zeros(max,1);
%%% Defini... |
function Logical = IsDefined(String,StringSet)
Logical = sum(strcmpi(String,StringSet)) > 0;
end |
function [G, Ae] = observer(A,B,C,Pe)
% H. Saadat, 1998
clc
% discr=[
%' This function is used for the computation of the estimator gain '
%' gain vector G based on the Ackermann`s formula. A is the system '
%' matrix, B is the input column vector & C is the output row vector. '
%' Pe is the row vec... |
% ber generic ostbc tx1
% missing argument b
% y=Hx+n
%
function ber = ber_ostbc_t1(a,b,SNR)
load precision.mat
% a and b must have the same dimensions, obviously
sizea=size(a);
k=sizea(3);
t=sizea(1);
n=sizea(2);
x=zeros(1,BLOCK_SIZE);
x_hold=zeros(1,t);
s=zeros... |
clear all;
file_name_list = dir;
count = size(file_name_list, 1);
buf_er = 0;
for i=1:count
if strfind(file_name_list(i).name, 'jpg') > 0,
name = sprintf('sushi_%03d.jpg',i-buf_er);
movefile(file_name_list(i).name, name);
else
buf_er = buf_er+1;
end;
end; |
function [gains, data] = collateStats(directory)
folders = dir(directory);
data = [];
t = 1;
for f = 1:length(folders)
foldername = folders(f).name;
if strncmp(foldername,'.',1) || ~strcmp(foldername((end-8):(end-4)),'stats')
continue
end
statsname = sprintf('./%s/%s',directory, foldername)... |
function [Ts,p] = genShortTimeParamVector( postSynNrn ,preSynNrns)
synType = 10*preSynNrns + postSynNrn ;
% RS = 1, LS = 2, FS=3, LTS = 4, TS= 5, TI= 6, TRN =7
state150_06 = (synType == 11) + (synType == 13) ...
+ (synType == 31) + (synType == 33);
state150_07 = (synType == 51) ;
sta... |
function y = bisection(func, lower, upper, max_iteration, max_error)
% Finds the root of a function using the bisection approach.
% Inputs are the func- tion(anonymous), upper and lower limits,
% maximum number of iterations, and maximum absolute relative error.
% The outputs should be the root and a table of i... |
clc;clear;close all
load('m4.mat');
load('m5.mat');
device02=m4(1:600,:);
device01=m5(1:1200,:);
%% test data
test_num=200;
[device21] = mapminmax(device01(1:test_num,:));
[device22] = mapminmax(device02(1:test_num,:));
y1=[ones(test_num,1);2*ones(test_num,1)];
data_t = [device21;device22]';
data... |
function evaluate_model(model, dataset)
gt = dataset.OrientationFlags;
predictions = model.predictFcn(dataset);
cm = confmat(string(gt), string(predictions));
labels = strrep(cm.labels, '*', '_');
plabels = strcat('P', cellstr(labels));
tlabels = strcat('T', cellstr(labels));
... |
function element=getElementAtIndex(vector,index)
element=vector(index);
end |
classdef KdeDist < MultivarDist & NonFiniteParamModel
%#NotYetImplemented
properties
dof;
ndimensions;
params;
prior;
end
methods
function model = KdeDist(varargin)
%
end
function cov(model,varargin)
%
notYetImplemented('KdeDist.cov()');
end
function entropy(model,varargin)
%
... |
function [val,Fs,gain,description,ecg_idx,bp_idx] = mvqrs_loadrecord(recordName)
%
% [val,Fs,gain,description,ecg_idx,bp_idx] = mvqrs_loadrecord(recordName)
%
% Load physiological data using wfdb toolbox
%
% Required Parameters:
%
% recordName
% String specifying the name of the record in the WFDB path or
% ... |
%% this function connects to Arduino
function connectToArduino(arduinoSerial)
% Preparing for connection with Arduino
% Make sure all connections with the Arduino are cleared up for a clean connection
fclose(arduinoSerial);
disp('All connections with Arduino cleared.');
% Connecting with Ard... |
classdef hartleyFF < handle
% Hartley FF (Full Field)
properties
numTrials
trial
display
design
sessionTrialIdx=[]
end
methods
function h = hartleyFF(PDS, varargin)
stim = 'hartley';
... |
function [Hx,Hy,Hz]= spiral_coil_efficent_calc_matrix(I,x_points,y_points,z_points,Px,Py,Pz)
%I=Filament current
%a_start=x,y,z coor of start of filament
%a_end=x,y,z coord ofned of filament
%P=x,y,z,obseration point
%Function to calculate the magnetic field due a straight currrent filament
%at an arbitary orientatio... |
function Impresion2(X,Y)
acepta = find(Y==1);
rechaza = find(Y==0);
plot(X(acepta,1),X(acepta,2),"bx","MarkerSize",5);
hold on;
plot(X(rechaza,1),X(rechaza,2),"ro","MarkerSize",5)
end |
function [allResp, allTarg,sdRand]=Exp2_restruc(data,center)
% Turn the data into responses and targets
% 4.8.2015-Created
allResp=nan(length(data),1,10,2); % subj x session x objects x dim
allTarg=nan(length(data),1,10,2);
numSubj=length(data);
numSess=[3 4 5]; % identify testing sessions
for is=1:numSubj
for i... |
function marker_str = parseMarker(d, CLim, colormap)
%build marker struct
marker_str = [];
if isfield(d, 'Marker')
isClosed = false;
switch d.Marker
case '.'
marker_str.symbol = 'circle';
case 'o'
marker_str.symbol = 'circle';
isClosed = true;
case '... |
%%
%% Test
% Test
% clear; close all;
%
% % Creates a 2D Mesh to plot surface
% x=linspace(0,1,100);
% [X,Y] = meshgrid(x,x);
% DELAY = 0.05;
% N=100; % Number of frames
% for i = 1:N
% % Example of plot
% Z = sin(2*pi*(X-i/N)).*sin(2*pi*(Y-i/N));
%
% subplot(1,2,1)
% surf(X,Y,Z);view(2);
%
% subplo... |
function out = getStimulusTrace( obj, key )
if nargin<2
key = fetch(obj);
key = key(1);
end
% Load times of the traces
[times out.mouse_id out.scan_idx] = fetch1(VisStims(key).*StatsSites,'frame_timestamps','mouse_id','scan_idx');
out.fps = round(1/mean(diff(times))*1000); % calculate fps
% stim times and ty... |
function [ rho_sphere, rho_sphere_gradient] = rho_sphere( R, c, O)
%UNTITLED6 Summary of this function goes here
% Detailed explanation goes here
Ox = O(1);
Oy = O(2);
Oz = O(3);
Cx = c(1);
Cy = c(2);
Cz = c(3);
%denominator of b
b_den = sqrt((Ox-Cx)^2 + (Oy-Cy)^2 +(Oz-Cz)^2);
b = [(Ox-Cx)/b_den*R +... |
function [X,Y,XX,YY] = fevd(This,Time,varargin)
% fevd Forecast error variance decomposition for SVAR variables.
%
% Syntax
% =======
%
% [X,Y,XX,YY] = fevd(V,NPer)
% [X,Y,XX,YY] = fevd(V,Range)
%
%
% Input arguments
% ================
%
% * `V` [ VAR ] - Structural VAR model.
%
% * `NPer` [ num... |
function [s11,s21,s12,s22,frequency] = s2pToComplexSParam(filename,filelength)
headerOffset = 9;
frequency = dlmread(filename,' ',headerOffset,0,[headerOffset 0 filelength 0]);
mag11 = dlmread(filename,' ',headerOffset,1,[headerOffset 1 filelength 1]);
phase11 = dlmread(filename,' ',headerOffset,2,[headerOffset 2 filel... |
% Position #1
rtp = [ 1 ; 0 ; 0 ];
Artp = [ 1 ; 0 ; 0 ];
[ Ax Ay Az ] = asph2rec(Artp(1), Artp(2), Artp(3), rtp(1), rtp(2), rtp(3));
assert(max(abs([ Ax ; Ay ; Az ] - [ 0 ; 0 ; 1 ])) < 1e-10)
Artp = [ 1 ; 1 ; 0 ];
[ Ax Ay Az ] = asph2rec(Artp(1), Artp(2), Artp(3), rtp(1), rtp(2), rtp(3));
assert(max(abs([ Ax ; Ay ; ... |
function [hits] = fileFinderAll(locn,type,omitFirst)
% fileFinderAll - determine all of the files of a specific type in a folder
% and subfolders
if strcmp(locn(end),filesep)
locn = locn(1:end-1);
end
% Can we do it purely iteratively and dynamically, rather than going
% through all folders at the beginning...
[h... |
function R3 = R3 (k);
R3 = [cos(k) -sin(k) 0; sin(k) cos(k) 0 ; 0 0 1];
end |
function [Epr] = m1_Epr(t,Qm,a,b,c1,c2,n,w,grid)
if Qm == 0 && c2 == c1+t;
Epr = w^2*(n-(1-0.5^n))/(n*(n+1)*(n+2));
else
th1s = mp(0,w,grid);
th2s = mp(0,w,grid);
Epr_sum = 0;
for ii=1:grid;
th1 = th1s(ii);
% For each theta1, we find the expected value conditio... |
function y = baseb_sub(u,v,b)
% y = baseb_sub(u,v,b)
%inputs = u, v = two vectors representing base b expansions of positive
%integers, with u > v, b = a postive integer > 1, the base
%output = y = a vector representing the base b expansion of the difference u - v
%computed using Algorithm 6.3
%First pad one vector wi... |
% This is the repository for the Matlab codes of the numerical simulations
% of plasmid dynamics in complex communities. The scripts can be used to
% generate Supplementary Figure 7 in
% "Variability of plasmid fitness effects contributes to plasmid persistence in bacterial communities."
%
% December 16, 2020
% rpm@ccg... |
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