text stringlengths 8 6.12M |
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function [ u ] = perona( u0, nit , dt, alpha, n)
% PERONA applique l'algorithme de Perona Malik a l'image u0
u=u0;
tau=dt;
for i=1:nit
[gradx grady] = gradient(u);
norm_u = sqrt( gradx.^2 + grady.^2);
cu = cfunction(norm_u, alpha, n);
u=u + tau*divergence(cu.*gradx, cu.*grady);
... |
function x=logReg_GD(X,Y, x, C1, C2, term1, term2,lambda_logistic, gdStep, rho)
for j=1:100
% for i=1:size(X,1)
% mu(i,1)=1/(1+exp(X(i,:)*x));
% end
%mu=mu';
%temp=(Y./(1+exp(Y.*(X*x))));
g=-(X'*(Y./(1+exp(Y.*(X*x)))))+lambda_logistic*x-C1+C2+rho*x+term1+term2;
%g=X*(mu-Y)+lambda_logist... |
function b = testSolutions(M, b)
if(~exist('b'))
b = 0;
end
% On cherche un zéro
zero = min(find(M(:)==0));
if isempty(zero) % S'il n'y en a pas...
b = 1; % C'est qu'on a une solution !
else % Sinon, on teste tous les chiffres possibles dans la case
[i,j] = ind2sub([9,9],zero);
for k=1:9... |
function [] = CorrectUniformMeshes(Nels)
% CorrectUniformMeshes: Correction of Node vector for unoform mesh.
% opens and deletes corresponding file
% INPUTS:
% Nels : No of Elements
Ntyps = length(Nels);
for i=1:Ntyps
load(sprintf('UniformMesh%dElements.mat',Nels(i)));
Nds = OutputNodes;
... |
function [On Ar] = reorder_mod(A,M)
%REORDER_MOD Reorder connectivity matrix by modular structure
%
% On = reorder_mod(A,M);
% [On Ar] = reorder_mod(A,M);
%
% This function reorders the connectivity matrix by modular structure and
% may hence be useful in visualization of modular structure.
%
%... |
classdef NeighbourhoodGenerator < Generator
%Iteratively generates the neighbourhood of the current instance.
%
% For the k-exchange neighborhood:
% All paths and cycles that involve k machines, in which at least one
% of the k machines is loaded.
%
%The Neighbourhood of an instance can ... |
% Crea la matrice di filtraggio di una immagine per righe
%
% A = MATRIX_FILTER_ROW( H, EXT, M, N, TR )
%
% H = coefficienti del filtro
% EXT = variabile carattere per il tipo di estensione al bordo
% 'e' = estensione pari
% 'o' = estensione dispari
% 'z' = zero padding
% 'p' = periodica
% M = numer... |
close all
imagefiles = dir('*.jpg');
nfiles = length(imagefiles);
for index=1:nfiles
currentImage = rgb2gray(imread( imagefiles(index).name));
[x, y] = size(currentImage);
%calculate maxiumum size of area
minimumSize = uint32(x*0.09 * y*0.09);
MaximumSize = uint32(x*0.25 * y*0.25);
blurValue = ... |
% HW 9
%%
%6.1-1 part E
%signal
f = @(x) [x.*(0<=x & x<1) + (x+3).*(-3<=x & x<=-2)];
x = linspace(-4, 4);
axis([-4 4 -1 2])
xlabel('t'); ylabel('');
grid
n = 1:10; a_n(1) = 1/6; a_n(n+1) = (3./((2.*(pi.^2)*(n.^2)))).*(cos(2.*pi.*n./3)+(2*pi*n/3).*(sin(2*pi*n/3))-1);
b_n(1) = 0; b_n(n+1) = 0.504*8*n./(1+16*n.^2)... |
function runme_extra_PCLA(fitnum, data_savename, savename)
% Read in data
load('PCLA_Pt_Lobos_pre2007_31Aug2015_metadata');
load(strcat(data_savename,'_R',num2str(fitnum),'.mat'))
disp(strcat(data_savename,'_R',num2str(fitnum),'.mat'))
disp('it loaded mockdata!')
% Now make some adjustments reflecting the mock-... |
function output = average_FLIM_parameters(dname, nFrame, freq, pulses_to_average, threshold, threshold2)
%% Select the directory where you put your files
%Name of variables
%tau_m_Array
%n_tau_mArray: normalized tau_m, all data
%fraction2_Array
%n_fraction2_Array: normalized fraction2, all data
%int_int2_Array: inten... |
function compressPIVimage(in,out, ratio)
nfrcalc = 100;
info = aviinfo(in);
N = info.NumFrames;
cmap = repmat((0:255)'/255,[1 3]);
i = 2:info.Height-1;
j = 2:info.Width-1;
npix = info.Height*info.Width;
timedWaitBar(0,'Compressing...');
mov = avifile(out,'compression','none','quality',100);
for fr = 1:N,
I = fr... |
%myNanSum(X, dim)
%same as nansum, but dim can be a set of dimensions.
function M = myNanSum(X, dim)
M = X;
for i = 1:length(dim)
d = dim(i);
M = nansum(M, d);
end
end |
%%% LUT based log calculator
function log_ut = loglut(ln_in,f_int,f_lns)
%%% In hardware, check the MSB whether it is '1' or not to indicate whether
%%% the number is >1
%%% Here simply checking
shift = 0;
lut_prec=64;
lut = zeros(1,lut_prec);
ln_in_rnd = round(ln_in*2^f_int)/2^f_int;
%%% Calculating shift
for i=1:f... |
% This function finds the aspect ratio of connected regions. If the aspect
% ratio is approxiamtely (1), i.e the connected region is an ellipse
% Inputs:
%D = matrix containing coordinates of the connected region
%sortIndex: the connected regions sorted from the largest to
%smallst
... |
function [slft_data, pred_delay]=get_UNBRT(cdate,hobs)
doy=ymd2doy(cdate(1:3,1));
if floor(doy)<10
strdoy=[ '00' num2str(floor(doy))];
elseif floor(doy) >= 10 & floor(doy) < 100
strdoy=['0' num2str(floor(doy))];
else
strdoy=num2str(floor(doy));
end
filename=[lower(hobs.stn) '_mf' num2str(cdate... |
function k=kernelLinear(x,y,param)
% linear kernel
% Usage:
% k=kernelLinear(x,y)
% x,y: column vectors, or matrices.
% param: []
% k, scalar or matrix, the kernel values
k=x'*y;
end |
function [scores] = pred_dual_nystrom(X,y, opt)
% pred_dual_nystrom(X,y,opt)
% computes predictions of the input samples passed in the X matrix,
% using the predictor stored in opt.rls.
%
% INPUTS:
% -X: input data matrix
% -y: labels matrix
% -OPT: structure of options with the following fields (and subfields)... |
function g = flip_image(img)
%FLIP 此处显示有关此函数的摘要
% 此处显示详细说明
g = flipud(img);
end
|
function a = log10(a)
%LOG10 Taylor logarithm log10(a)
%
% written 05/22/09 S.M. Rump
%
a = log(a);
if isa(a.t,'intval')
global INTLAB_INTVAL_STDFCTS_LOG10_
a.t = a.t .* infsup(INTLAB_INTVAL_STDFCTS_LOG10_.INF,INTLAB_INTVAL_STDFCTS_LOG10_.SUP);
else
a.t = a.t / log(10);
end
|
classdef source
% class storing the forcing due to rainfall (or recharge following the problem)
properties(Access=public)
type % type of source term: steady, periodical, data_based, random, etc.
time % time_properties object storing the time properties of the simulation... |
function TorqueOut = DMSTorque(TorqueIn,GlassTorque,varargin)
%UNTITLED Summary of this function goes here
if nargin > 3
error('too many arguments.');
end
TorqueOut = TorqueIn;
TorqueOut.Analysis.GlassTemp = GlassTorque.Temp;
Angle = round(TorqueIn.Angle);
TField = TorqueIn.Field(1);
X = TorqueIn.X;
Y = TorqueI... |
cd('D:\XY_matdata\AllSessions')
aa1 = []; aa2 = []; smi = []; aa3 = []; tt1 = [];
d2 = dir('*.mat');
corrcut = 0; jumpcut = 1.1;
label = 'RP';
for id = 1:size(d2,1)
thisdir = d2(id).name;
% load(thisdir,[label '_pSSDarm'],[label '_moduarm'])
% if ~exist([label '_pSSDarm'],'var')
% get_PFC_... |
function OCECgo_Tab_Calibration(h)
% This function creates the fields within the calibration tab.
% Get parent
pnt1 = findobj(h, 'tag', 'Tab_Cal');
%% CREATE DATA SECTION
% Create panel
str = '1) Calibration Data';
pnt2 = uipanel(pnt1, 'Units', 'pixels', 'Position', [5 375 440 260], 'Title', str, 'FontSize', 16);
ax... |
function [PCF, r, error] = SingleImageUnNormalized2DPCF (xy_pairs, dr)
% disp('*** SingleImageUnNormalized2DPCF')
n_of_particles = numel(xy_pairs(:, 1));
max_x_distance = max(xy_pairs(:, 1)) - min(xy_pairs(:, 1));
max_y_distance = max(xy_pairs(:, 2)) - min(xy_pairs(:, 2));
max_r = sqrt(max_x_distanc... |
% This function computes the classification error
% Input: Y, W, X
% Output: Percentage classfication error
function [ pct_err ] = ClassificationError( Y, W, X )
d = size(X, 1);
% Check if 1 is appended
if (size(W, 1) > size(X, 2))
X = [ones(d, 1) X];
end
O = repmat(W', d , 1).*X;
O = sum(O, 2);
... |
function q = gauss3_bersusun(a,b)
%input = a dan b batas integral, N banyak subinterval
%output = nilai aproksimasi dengan integrasi gauss bersusun
N = 0;
while N<1000
N=N+1;
h = (b-a)/N;
xx = a:h:b; %partisi domain
t = [0.7745966692, 0,-0.7745966692]; %absis
c = [0.5555555556, 0.888888889,0.555555... |
%% Opdracht 8
% Gegeven: een rijvector met tijdstippen waarop een rugbyspeler een bal
% vast heeft (1) en de bal door niemand wordt vastgehouden (0).
%
% De positie van de bal (de x-coordinaat) wordt gegeven in Pos.
%
% Geef de indexen van de tijdstippen waarop een speler de bal vast heeft en
% naar achter rent. Zo'n... |
%RANDOMSTATEGENERATOR Generates N number of random states that are valid in
%the Sherpa_TT leg's configuration space.
%
%Inputs:
%-N: The number of random states to be generated.
%-jointLimits: A 2x10 array of joint angular limits and angular positions.
%-kC: A structure containing the kinematic constants of the Sherpa... |
classdef conv2d_adv_gq < conv2d
%CONV2D_ADV_GQ Summary of this class goes here
% Detailed explanation goes here
properties(Constant)
x0 = -0.5;
y0 = -0.5;
u0 = 0.5;
v0 = 0.5;
end
properties
uq, vq % flow variables at quadrature points
end
... |
function [m, v] = meanvar(X)
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
N = length(X);
m = sum(X) / N;
T = zeros;
for i = 1:N
T(i) = (X(i) - m)^2;
end
v = (1/(N-1))*(sum(T));
end
|
function [app] = compSimpsons(f, left, right, n)
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
if mod(n, 2) ~= 0
error('Input n must be an even number: %d given', n);
end
step = ( right - left ) / n;
fA = f(left);
fB = f(right);
f1 = 0;
f2 = 0;
for i = 1 : n - 1
x = left ... |
clear vars;
LF=zeros(512,512,9,9,3);
imgPath='hci_dataset/training/boxes/';
num=1;
for i=1:9
for j=1:9
imgDir = dir([imgPath '*.png']);
LF(:,:,i,j,:)=imread([imgPath imgDir(num).name]);
num=num+1;
end
end
LF_pinhole=reshape(permute(LF,[3 1 4 2 5]),[9*512 9*512 3]);
%LF_pinhole=reshape(permu... |
function H = hessian(VI_dW_dp, N_p, w)
% HESSIAN - Compute Hessian
% H = HESSIAN(VI_DW_DP, N_P, W)
% Iain Matthews, Simon Baker, Carnegie Mellon University, Pittsburgh
% $Id: hessian.m,v 1.1.1.1 2003/08/20 03:07:36 iainm Exp $
if nargin<3 error('Not enough input arguments'); end
H = zeros(N_p, N_p);
for i=1:N_p
h... |
function matrice_tabou = maj_matrice_tabou(matrice_tabou, permutation,...
taille_tabou)
% fonction qui met à jour la matrice tabou (contenant les permutations
% interdites) entre deux itérations.
% matrice_tabou : matrice_tabou(i,j) est le nbre d'itération durant
% laquell... |
%子函数：在L_index+1到R_index-1个可能的边界点中寻找熵最小的划分点
%Revised by JLM on 2020-05-26
function [IndexBestCut,Index_left,Index_right,EntS1,EntS2,EntS,Entropy_min,L1,L2]=Get_best(BoundaryPoints,L_index,R_index,X,Label_Mass,Num_Initial)
Num_boundary=R_index-L_index-1;
Index_left=cell(Num_boundary,1); %存储在每个边界点左边的数据索引位置
Index_ri... |
function heid = hv2he(hvid, mesh, mode)
%%HV2HE : map half-vertex <hvid> to incident half-edge
% hv2he(hvid,mesh,mode)
% mode == 'any' : id of some half-edge starting at the vertex
% corresponding to <hvid>, 0, if there is no such edge in <mesh>
% mode == 'match' : id of ha... |
%% select
% gets list of species that belongs to a taxon
%%
function Species = select(taxon)
% created 2015/09/18 by Bernd Brandt
% modified 2015/10/07 by Dina Lika; 2016/11/08, 2021/11/24 by Bas Kooijman
%% Syntax
% Species = <../select.m *select*> (taxon)
%% Description
% gets all species in the add_my_pet collec... |
function ia_plot1(level_difference,time_difference,direction_matrix,...
n_directions,frq_axis,single_plane)
% function ia_plot1(level_difference,time_difference,direction_matrix,...
% n_directions,frq_axis,single_plane)
%
% IA_PLOT1 plots the interaural level difference ... |
%sujets = { 's01','s02','s03','s04','s05', 's06', 's07', 's08', 's09'};%,'s02','s03','s04','s06','s07','s08','s09'}; %inserer le noms des fichier des sujets
sujets = {'s11', 's12'};
eventsOI = {'_UnPred','_Pred','_Scramb'};
min_freq = 2;
max_freq = 80;
num_frex = 40;
freq = linspace(min_freq,max_freq,num_frex);
lo... |
function [ issym, err ] = issymmetric( M, use_epsilon )
% [ issym, err ] = issymmetric( M, use_epsilon )
% returns 1 if M is symmetric (within tolerance use_epsilon)
if ~exist('use_epsilon','var')
use_epsilon = sqrt(eps);
end
err = sum(sum(abs(M-M')));
if err > use_epsilon
issym = 0;
else
is... |
function pyout=pydec(C,h)
%X=pydec(C,h)
%Takes C as an input a cell: Y0,Y1,...,Yn,X(n+1), returns the set of low pass
%images Z as a cell in the following format:(Zn,...,Z0)
[m,n]=size(C);
pyout{1}=C{n-1}+interpolate(C{n},h);
for i=2:(n-1)
pyout{i}=C{n-i}+interpolate(pyout{i-1},h);
end
end
funct... |
%% Build the Design Matrix
%% experiment date: 10.26.09
TR = 4;
doASLmod=1;
exp_duration = 1144;
% 150 * TR;
% add three seconds for instructions on each trial
%shifts = [1:5]*3;
onsets{1} = [
13
66
303
380
681
1046 ] -7;
durations{1} = [
48
96
72
48
72
96];
onsets{2} = [
167
468
604
758
870
958... |
function match_gc_to_fc(gc_lb,gc_ub)
% tm 11/2/98
% match gc spd and trq range to that of the fc
assignin('base','gc_spd_scale',round(evalin('base','max(fc_map_spd*fc_spd_scale)/(max(gc_map_spd)*0.95)')*1000)/1000);
assignin('base','gc_trq_scale',min(max(round(evalin('base',...
'max(fc_max_trq*fc_trq_scale)/interp... |
%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%
%&% %&%
%&% Simulation and Control Algorithms %&%
%&% %&%
%&% Deformable Body Model %&%
%&% ... |
% PlotTCPBEL4s is a slice-plot version of PlotTCPBEL expand
% to the basis { |00> |10> |01> |11> }.
% Author: Yulin Wu
% Date: 2009/8/14
% Email: mail4ywu@gmail.com
function PlotTCPBEL4s(Ec1,Ec2,Em,Ej1,Ej2,varargin)
NgLim=[0.25 0.8]; % Default ploting range: Ng, [-0.25 0.8],
nP=400; % 400... |
function [I] = light_intensity_matrix(p,I,A)
% Calculates the light intensity at all grid points with Beer-Lamberts law,
% using the trapezoidal method to compute the integrals.
% Assumes A is a matrix with the dimensions [p.Yn, p.Xn]
% returns a matrix I with dimensions [p.Yn, p.Xn]
for x = 1:p.Xn-1
integral = 0;... |
function ClusterFunctions(action,hfig)
global selWidth unselWidth
selWidth = 2;
unselWidth = 0.5;
mstyle = 's';
msize = 2;
if (nargin < 2)
hfig = gcbf;
end
hmembership = findobj(hfig,'Tag','memberline');
delete(hmembership);
% Notes:
% Figure contains a number of user properties with the following names:
% clustnums:... |
function [scanpath_out] = normalize_scanpath_rate(scanpath, samplerate)
if size(scanpath,1)<1
scanpath_out=[];
return;
end
tstart=scanpath(1,3);
tend=scanpath(end,3);
timeintervals=tstart:samplerate:tend;
totaltime=tend-tstart;
scanpath_out(:,1)=interp1(scanpath(:,3),scanpath(:,1),timeintervals,'linear... |
function [ mz2,sp2,sp3 ] = jsmPeakPick(mz,sp,method)
%jsmPeakPick - perform various peak picking methods (eventually)
%
%
% INPUTs
% mz
% sp
% method - simple so far
% Save the original data
spOrig = sp;
snr = 10;
% Determine reference spectrum
sp = 1000000 * bsxfun(@rdivide,sp,nansum(sp,2));
refSp = nanmean(sp,1);
... |
clear members
members=properties(gNLv);
idx=strmatch('all',members);
members(idx)=[];
for i=1:numel(members)
if ( strcmp( class( gNLv.( members{ i } ) ) , 'Subject' ) && ~strcmp( members{ i } , 'all' ) )
xl_s2m_rateL( i) = gjpsv_all.default.apply_classifier( gNLv.( members{i}).default , 'name' , 'groupL' , 'targe... |
%% Intitializations
clear;
clc;
prompt = {'Enter the file name of the network to be analyzed'};
title1 = 'Input';
dims = [1 50];
definput = {'ko04141'};
answer = inputdlg(prompt,title1,dims,definput);
filename1=strcat('D:\rishika\4_work_boolean_logic\KEGG_data\',answer,'.xml');
filename=char(filename1);
fid=... |
%
% Script ECCN Tutorial: Tasks 1 - 3
%
% Task 1
[XA,XB,XC,YA,YB,YC] = ecnn_data(0); % Load data
Net = ecnn_train(XA,XB,YA,YB,0.0001,1.1,100,true); % Train ECNN
Z = ecnn_test(Net,XC,YC); % Test ECNN
plot_class_boundaries(Net,XC,YC,Z); % Plots
% Task 2
ecnn_analysis(Net); % Feature Importance Analysis
% Task 3
% learn... |
function control = raftcontrol(theta,thetaOld,dt,thetades, thetaError,IError)
%Simple PID controller for raft heading, for testing purposes
Kp = 5;
Kd = 2;
Ki = 0;
% dt = 0.1;
% thrustmax = pi;
offset = 30; %to account for motor not moving for commands less than offset
thrust = -Kp*(thetaError) - Kd*(theta ... |
close all;
good = load('lab_bioimaging/imT2.mat');
seg = load('t2.mat');
seg = double(seg.scirunnrrd.data(:,:,1));
x1 = good.imT2(:,:,1).*seg;
x2 = good.imT2(:,:,2).*seg;
x3 = good.imT2(:,:,3).*seg;
x4 = good.imT2(:,:,4).*seg;
x5 = good.imT2(:,:,5).*seg;
x6 = good.imT2(:,:,6).*seg;
x7 = good.imT2(:,:,7).*seg;
x8 = ... |
function [packet,dataBitsCrc]=genPacket(Mbps,Bytes)
[p, ref] = generate_preamble;
[data_sym,dataBitsCrc] = txData(Mbps,Bytes);
bytes = length(dataBitsCrc)/8;
signal_sym = txSignal(Mbps,bytes);
data_sym=data_sym(:);
packet = [p(1:end-1);signal_sym; data_sym];
%%add noise
% Pnoise = -94.797;
% numSa... |
function [S,labels]=score_image(A,ref)
S=zeros(1,4);
%MSE
S(1)=immse(A,ref);
%PSNR and SNR
[S(2),S(3)]=psnr(A,ref);
%SSIM
S(4)=ssim(A,ref);
labels={'MSE','PSNR','SNR','SSIM'};
|
clc;
clear;
close all;
L(1) = Link([ 0 0.147 0 0 ], 'modified' );
L(2) = Link([ 0 0 0.033 pi/2 ], 'modified');
L(3) = Link([ 0 0 0.155 0 ], 'modified');
L(4) = Link([ 0 0 0.135 0], 'modified');
L(5) = Link([ 0 0.218 0 -pi/2], 'modified') ;
youbot = SerialLink(L, 'name', 'youbot');... |
function grid_rectangular(a)
%%
% I started writing a post today about the |ConvexImage| property returned
% by |regionprops|. But I got sidetracked along the way, and this post
% turned into a description of how to overlay a pixel grid on an image.
% (I'll come back to the original |ConvexImage| idea in a future post.... |
clear
%This script simulates a three-link headless human figure on a slackline
%in the frontal plane,
%as used in assignment 5 of the course "human and robot locomotion", 2020.
%
%Dimensions and weight of segments are inspired by anthropometric data
%(mass of arm equivalent to two arms, mass of trunk contain... |
%% Process and fit the distributions
clear
% % ------ Gamma
%
% % Optimization settings
% options=optimset('Display','iter','TolX', 1e-16, 'TolFun', 1e-16, 'MaxFunEvals', 500);
% % Initial values - [shape, scale]
% x0=[1e-2, 10.0];
% % Optimization
% [x,fval]=fminsearch(@gamma_search, x0, options);
%
% data = load(... |
function runAllTests()
import matlab.unittest.*
import matlab.unittest.plugins.*
import matlab.unittest.plugins.codecoverage.*
try
artifacts = "artifacts";
mkdir(artifacts);
junitResults = fullfile(artifacts, "junit");
mkdir(junitResults);
covRe... |
function [blob, im_scales] = get_image_blob(conf, im)
[ims, im_scales] = arrayfun(@(x) prep_im_for_blob(im, conf.image_means, x, conf.test_max_size), conf.test_scales, 'UniformOutput', false);
im_scales = cell2mat(im_scales);
blob = im_list_to_blob(ims);
end |
function [GNCout] = ChooseNS(GNCin)
% Choose number of sensors
global NSMAX
for ns = 1:NSMAX
GNCout(ns) = GNCin;
GNCout(ns).NS = ns;
end
return;
|
function Stimulator2
%prepares the setup
getSetup;
Priority(5); %Make sure priority is set to "real-time"
% priorityLevel=MaxPriority(w);
% Priority(priorityLevel);
mList=moduleListSlave;
configurePstate(mList{1}{1}) %Use grater as the default when opening
configureMstate;
configCom_tcp; %configures communicat... |
function random_paths
h = figure(1);
handles.start = [];
handles.goal = [];
handles.region_p = [];
handles.region_e = [];
handles.region_seed = [];
handles.traj = [];
handles.obs = [];
clf
% Configuration
start = [-17;0];
% goal = [16;-15];
% goal_iregion_idx = 2;
goal = [16;18];
goal_iregion_idx = 3;
% goal = [-16... |
function Y = vl_mysoftmaxloss(X,c,dzdy)
% classNum = size(c,2);
% s = X;
% s = bsxfun(@minus, s, max(s, [], 1));
% s = exp(s);
% s = s + 1e-8; %avoid NaN
% y = s./repmat(sum(s,1),[classNum 1]);
% if nargin < 3
% loss = -c'.* log(y);
% Y = sum(loss(:));
% else
% % gradient computation
% ... |
% Simon Mekonend
% 12/9/18
% ECE 202: Project 1 - part 6
% Power Series Expansion of cosine function
% f(t) = A * cos(wt)
clear
format shortG
% ----- ANSWERS TO QUESTIONS ------
% a) Number of terms = 10
%
% b) The function seems to rapidly decrease. I think this happens because
% the polynomial from the power s... |
% parcellation_colormap.m
%
% Code here to make a nice aparc colormap that can be used for a number of things
% Assumes that you have 82 regions i.e. 34 Desikan killany regions Left: 7 Subcortical regions (from aparc) for each hemi
%
% 2020
% Kevin Aquino <aquino.km@gmail.com>
%
function cmap_aparc = parcellation_c... |
% WBL 25 Sep 2002 Use P450 training data to train Matlab MLP Neural Network
versn = '$Revision: 1.7 $'; %$Date: 2002/10/31 11:17:37 $
%read training data, one training case per line,
%each case has the same number of attributes,
%numbers are separated by spaces.
in = load('TRAIN+11_FULLtrn'); in = in';
%read ... |
function intervals = cleanUpIntervals(endpts)
% VARIABLES
% endpts: J x 2 table which mark the start and end indices of a
% jump for a particular experiment.
%
% Takes endpts and removes any jump intervals which are nested.
% Clean up nested intervals.
endpts = sortrows(endpts);... |
%-------------------------------------------%
% BEGIN: function brachistochroneEndpoint.m %
%-------------------------------------------%
function output = osimOptimalTrackingEndpoint(input)
% % Variables at Start and Terminus of Phase 1
t0{1} = input.phase(1).initialtime;
tf{1} = input.phase(1).finaltime;
x0{1} = inp... |
function [X, info] = IRrestart(A, b, varargin)
% IRrestart Restarted Krylov subspace methods
%
% options = IRrestart('defaults')
% [X,info] = IRrestart(A,b)
% [X,info] = IRrestart(A,b,K)
% [X,info] = IRrestart(A,b,options)
% [X,info] = IRrestart(A,b,K,options)
%
% This function provides a general framework for a varie... |
function [Pav] = advection(A,B,L,Ncells,t_final)
% This function solves 1D transport equation using finite volume method.
% Input arguments
% A,B Constants in Gaussian function (as initial condition)
% L The length of interest
% Ncells Number of cells
% dt Time step
% t_... |
% ======== Loading Data ======== %
Y = load('course-ratings.txt');
% Y is a 15x80 matrix, containing ratings (1-10) of 15 courses on
% 80 students.
% Courses which are not rated by a particular student are given a rating
% of 0.
% Converting R to logical matrix
R = logical(Y);
% R is a 15x80 matrix, where R... |
function [w_id,unique_w_id,w_ii] = getXstar(w,X,r)
w_id = zeros(size(w,1),r);
w_ii = zeros(size(w,1),1);
for i = 1:size(w,1)
[u,uid] = sort(w(i,:)*X','descend');
w_id(i,:) = uid(1:r);
end
unique_w_id = unique(w_id,'rows');
for i = 1:size(w,1)
for j = 1:size(uniqu... |
function [outputArg1,outputArg2,outputArg3,outputArg4] = batchClassify(Job,params,allocate)
%BATCHCLASSIFY Summary of this function goes here
%first input is [Job] 1 to compute 0 to avoid
%Job.classify =1
% Job.predict=1
%second input is [params]
%supplied with data so there is no need to change
%third input ... |
val_data = readmatrix('a0_valueset_dist_n0.csv');
figure;
lhp = plot3(val_data(:,1),val_data(:,2),val_data(:,4), '.', 'DisplayName', 'Lower half');
lhp.Color = '#0072BD';
hold on;
uhp = plot3(val_data(:,1),val_data(:,2),val_data(:,5), '.', 'DisplayName', 'Upper half');
uhp.Color = '#EDB120';
title('Fraction of... |
classdef NdgFlatBottomNonhydrostaticBoundaryValueTest < NdgFlatBottomWetDryTestWithWallBoundary
%UNTITLED 此处显示有关此类的摘要
% 此处显示详细说明
properties
end
methods
function obj = NdgFlatBottomNonhydrostaticBoundaryValueTest(N, cellType)
obj = obj@NdgFlatBottomWetDryTestWithWallBo... |
clear all; % clear all variables from the workspace
video = mmread('Video1.mpeg'); % call the function mmread to load the video.
% The variable video is a structure with different fields. Type 'video'on Matlab command and see what metadata is associated
% to this structure.
number_of_frames=video.nrFramesTotal; % nrF... |
function ShowImage(result,bounds,spacing,f_hand,title_string,cscale)
if bounds(5) == bounds(6)
Show2DImage(result,bounds,f_hand,title_string,cscale,'X (m)','Y (m)');
elseif bounds(1) == bounds(2)
bounds = bounds(1,3:end);
Show2DImage(squeeze(result).',bounds,f_hand,title_string,cscale,'Y (m)','Z (m)'... |
function rot = rotate_image(img, theta)
rot = zeros(size(img)); % we set the values inside the matrix to zero
n = size(img);
for i = 1:n(1)
for j =1:n(2)
mire = [cos(theta), sin(theta);-sin(theta), cos(theta)];
rots = (inv(mire))*([i;j]-[n(1)/2;n(2)/2])+[n(1)/2;n(2)/2];... |
function subobj_weights = RBES_get_array_subobj_weights()
global params
w = params.subobj_weights;
np = length(w);
no_vec = cell2mat(cellfun(@length,params.obj_weights,'UniformOutput',false));
subobj_weights = zeros(1000,1);
ii = 1;
for p = 1:np
for o = 1:no_vec(p)
sobj = params.subobj_weights{p}{o};
... |
% Calculate inertial parameters regressor of coriolis matrix for
% %RN%
% Use Code from Maple symbolic Code Generation
%
% Input:
% %INPUT_QJ%
% %INPUT_QJD%
% %INPUT_PKIN%
%
% Output:
% cmat_reg [(%NQJ%*%NQJ%)x(%NQJ%*10)]
% inertial parameter regressor of coriolis matrix
% %VERSIONINFO%
function cmat_reg = %FN%(q... |
function [ResultStruct, ResultStructBW]=HistEqualization_Enhance(CDataSetInfo, Param)
%%%Doc Starts%%%
%-Description:
%This method is to perform 3D contrast enhancement using histogram equalization.
%-Parameters:
%1. NBins: The number of bins.
%-Formula:
%Matlab build-in function histeq is used.
%-Revi... |
clc
clear all
close all
[file,path] = uigetfile('*.txt');
if isequal(file,0)
return;
end
fid = fopen(fullfile(path,file),'r');
x16=fread(fid,Inf,'uint16');%Persian
fclose(fid);
fid = fopen(fullfile(path,file),'r');
x8=fread(fid,Inf,'uint8');%English
fclose(fid);
hist(x8,max(x8)-min(x8)+1)
x8u=unique(x8... |
for j = 1:8
delete(figure(j));
end
warning('off','all')
preSample = [1000,10000,25000,50000,75000,100000,150000,200000,300000,400000,500000,750000,1000000,1500000,2000000];
%preSample = [1000,2000,3000,4000,5000,6000,7000,8000,9000,10000,11000,12000,13000,14000,15000];
%for k = 1:500
%preSample(k) = k*25000;
%end
for ... |
function r = cap_range(r, low, high)
% Clips the value between high and low
r = min(r, high);
r = max(r, low);
end |
O = zeros(1,K,10) ;
M = zeros(1,ndim,K,10) ;
C = zeros(ndim,ndim,K,10) ;
O(:,:,1) = o1 ;
M(:,:,:,1) = m1 ;
C(:,:,:,1) = c1 ;
O(:,:,2) = o2 ;
M(:,:,:,2) = m2 ;
C(:,:,:,2) = c2 ;
O(:,:,3) = o3 ;
M(:,:,:,3) = m3 ;
C(:,:,:,3) = c3 ;
O(:,:,4) = o4 ;
M(:,:,:,4) = m4 ;
C(:,:,:,4) = c4 ;
O(:,:,5) = o5 ;
M(:,:,:,... |
function signal(varargin)
%SIGNAL
% Define custom signals for the plant formulation, e.g. define a
% reference input. Multidimensional signals can also be declared as e.g.
% r(3), for a (reference) signal of dimension 3 or e(2) for an (error)
% signal of dimension 2. Omitting (.) creates a 1-dimensional signal.... |
function writeStructureToRhinoScript(self, structure, path)
memberNum = size(structure, 1);
[Cn, Nd] = self.generateCnAndNdList(structure);
[radius, nodeRadiusList] = self.getRadiusList(structure);
fileName = [path, '\createStructure.py'];
fid = fopen( fileName, 'wt' );
fprintf(fid, 'import Rhin... |
function M = RateCorrelation(SimValues)
%%
poprate.dt = 50; overlap = 1; winsize = poprate.dt.*overlap;
[spikemat,t_rate,~] = SpktToSpkmat(SimValues.spikesbycell, [], poprate.dt,overlap);
N = length(SimValues.EcellIDX)+length(SimValues.IcellIDX);
rate = zeros(length(t_rate),N);
for ii = 1:N
rate(:,ii) = sum(... |
% +INIT Package for initializing dataset for code applied to population analyses using Kalman filter approach
% MATLAB Version 9.7 (R2019b Update 5) 29-Aug-2020
%
% Functions
% spikeData - Initialize spike data
% lfpData - Initialize LFP data
% kinData - Initialize kinematic data... |
function[x_real, y_real] = interpolacion_lut_funcion(lut, x_ccd, y_ccd)
datos_y = importdata(lut, '\t', 1);
datos_y = datos_y.data;
x = datos_y(:, 1);
y = datos_y(:, 2);
px = datos_y(:, 3);
py = datos_y(:, 4);
% Interpolo Y en función de px, py
%%%%%%%%%%%%%
F_y = scat... |
clear all
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%55
%
% Aufgabe b
%
% Für Jacobi:
% F1 nach x1: 3/|x|
% F1 nach x2: -2*x2
% F2 nach x1: 4x1 - x2 - 5
% F2 nach x2: -x1
x=[2;2];
F=[1;1];
zahl=1;
k=0;
while (norm(F)>=10^(-10)),
F=[x(1)-x(2)^2+3*log(abs(x(1)));2*x(1)^2-x(1)*x(2)-5*x(1)+1];... |
%Part 1
Part1
%Part 3
Gompertzian
|
classdef IPGrayImage < SYObject
properties
end
methods(Static)
function result = grayImage(image,range)
% result = grayImage(image,range)
% Class method to convert given image to gray scale image.
% Argument image is either bitmap raw data or SYImage instance.
% Argument (double[2]) range.
% Return value is (uint8[... |
function [ climstruct_out ] = reduce_climstruct_data_by_obs_nr( climstruct_in, obs_min )
%A function to reduce the ace data according to the provided observation
% number minimum. Data that do not correspond to the indices are changed to
% NaNs.
% *INPUT*
% climstruct_in: STRUCTURE - the ace climatology data... |
agent = UTMPlane4D([0 -2 0 0], pi/10, 3, 0, [1:4], 5, 0.1);
dt=0.05;
T = 20;
close all;
for i=0:dt:T
%agent.updateState([pi/10,0], dt);
agent.updateState([0,0.01],dt);
extraArgs.Color = 'red';
extraArgs.ArrowLength = 3; %j prev 1
extraArgs.LineStyle = 'none';
extraArgs.LineWidth = 0.1; %j
ex... |
% Bode plot for one amplitude bins of a neuron which requires recordings at
% different frequencies of stimulation.
%% Input filename is 'Trials_freq_dep.mat', range is the FNames range in the struct
function plot_ampbins_bode(filename,range)
H=load(filename);
S=struct();
FNames=fieldnames(H);
count=1;
... |
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