text stringlengths 8 6.12M |
|---|
% pressure in Pa (not hPa nor mbar)
% temperature in K (not in degree Celsius)
% humidity:
% - partial pressure of water vapor in Pa (not hPa nor mbar)
% - specific humidity in kg/kg (not g/kg)
% - mixing ratio in kg/kg (not g/kg)
% - relative humidity in percent
% - dew point temperature in K (not degree Celsiu... |
function q = plotRandViaPointTask()
axis([-10 10 -10 10])
hold on
q = [];
sx_max = 3;
sx_min = -3;
sy_max = 9;
sy_min = -9;
x = (sx_max - sx_min) * rand(1) + sx_min;
y = (sy_max - sy_min) * rand(1) + sy_min;
th = pi * rand(1) - pi/2;
quiver(x, y, 1*cos(th),1*sin(th), 'o');
q = [q, x, y, th];
sx_max = -4;
sx_min = ... |
depth=[0; 1;];
DATASET='MNIST';
ALPHA=0.5;
LR_LAMBDA=1;
Wd=load('MNIST Data/Simplified_MNIST_Dic.mat');
Wd=Wd.WDict;
data=load('MNIST Data/MNIST_Data.mat');
label=data.trls(1:5000);
test=data.tt_dat(:,1:1000);
test_lb=data.ttls(1:1000);
data=data.tr_dat(:,1:5000);
num_label=numel(unique(label));
S_cod=eye(size(Wd'*Wd))... |
function varargout = findspikes(varargin)
% function [ind,thresh] = findspikes(y, opts...)
% or findspikes(t,y, opts...)
%
% Locates spikes in a time series, based on a threshold. Optionally asks
% for the threshold
opt.nspike = 2;
opt.window = false;
opt.method = 'threshold';
opt.threshold = [];... |
function [disp_az, disp_el, disp_data] = plotsurf(xaxis, yaxis, data);
% PLOTSURF plots 2-d data using pcolor and corrects axes
% [disp_az, disp_el, disp_data] = plotsurf(xaxis, yaxis, spacedata);
% NOTE: THIS VERSION HAS BEEN UPDATED TO SHIFT NUMERICAL VALUES OF AXES
% RATHER THAN JUST THE LOCATION OF THE ... |
function [x, y] = mth_circle_tangent_line(v, t, r, dx, dy)
% MTH_CIRCLE_TANGENT_LINE generates the tangent line to a circle given
% as a function of an independent variable.
%
%-----------------------------------------------------------------------
% Copyright 2018 Kurt Motekew
%
% This Source Code Form is subject to t... |
function gettweets_nopost
% Set up paths to twitty and json parser
addpath(genpath('~/Desktop/twitter/creds')); % Credentials
addpath(genpath('~/Desktop/twitter/data')); % Data
addpath(genpath('~/Desktop/twitter/out')); % Output folder
addpath(genpath('~/Desktop/twitter/json/parse_json')); % Twitty's default json... |
% Part1.m
% Author: Charles Yang
% Signal&System 4.3(b)(c)(d)(e)(f)
%% (b)
load splat;
y=y(1:8192);
fs=8192;
Y=fftshift(fft(y));
Y1=conj(Y);
y1=ifft(fftshift(Y1));
subplot(211);plot(y);sound(y,fs);
pause(2);
subplot(212);plot(real(y1));sound(y1,fs);
%% (d)
load splat;
y=y(1:8192);
fs=8192;
Y=fftshift(fft(y));
Y2=abs(Y)... |
function ksurf(record,cm)
% function ksurf(record)
% makes a 3D surface plot of a LTSTM record
% Same as ltsurf but modified to my pleasure.
if ~isstruct(record)
t=record;
record=struct;
record.Data = t;
end
% Normalize to [0,1];
record = ltnorm(record);
surf(record.Data,'LineStyle','no... |
%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%
% Noss is Mean Squared Eigenvalue Error method used for obtaining optimum
% Number of Source Signals (NoSS): https://ieeexplore.ieee.org/document/8466044
% Reference Authors:
% Soosan Beheshti (soosan@ee.ryerson.ca) and Saba Sedghizadeh
% CITE... |
function y = sigFun(init_coeffs,x)
y = init_coeffs(1)./(1+exp((init_coeffs(2)-x)/init_coeffs(3))); |
% load('d:\hina\marathon\clusters\cluster2');
% load('d:\hina\marathon\embedding parameters\xparameters2');
% load('d:\hina\marathon\embedding parameters\yparameters2');
% load('d:\hina\marathon\timeseries\ts2');
% for j=1:67 %interpolation
% xm_=cell2mat(xm(1,j));
% ym_=cell2mat(ym(1,j));
% for i=1:size(x... |
clear all; close all; clc;
im = imread('http://i.imgur.com/TwDQZKO.jpg');
r = im(:,:, 1);
g = im(:,:, 2);
b = im(:,:, 3);
% green %
bwr = abs(double(r) - 80) <= 80;
bwg = abs(double(g) - 240) <= 80;
bwb = abs(double(b) - 60) <= 80;
bw = bwr .* bwg .* bwb;
bw = imfill(bw,'holes');
bw = bwareaopen(bw,80);
green ... |
% title_alt : Alternate title positioning
%
% Call :
% title_alt(string,isub,location,dw,w_out)
%
% title [str] : title string
% isub [int] : Number of subplot. 1-->'a)' is prepended to the title
% 2-->'b)' is prepended to the title..
% ... |
function [point_candidate, track_out, x1,y1] = search_candidate_point_1(dis_range, angle_range,x1,y1,x2,y2,x3,y3,track_out)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% step 1 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
point_candidate = [];
for i = 1:length(x1)
x = x1(i); y = y1(i);
dis = sqrt((x2 - x).^2 + (y2 - y).^2);
[a,b]... |
%calling function : logVriable;
function [avg_currency_rnd, currency1, currency2, currency3, currency4, currency5]=logCurrency(node,Id1,Id2,Id3,Id4,Id5)
% Collect currency of various nodes
% Retrieving network constants.
CONST=networkConstants();
n=CONST.n; % Total nodes in the network
% Total currency ... |
%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% En este script se seleccionara entre los 6 modos de trabajo que se desee
% para obtener el modelo del robot. En concreto se puede dar que:
% -> Robot ideal con Reductoras
% -> Robot ideal sin Reductoras
% -> Robot real solo encoder con Reductora... |
function [globalMap, cumulativeM] = constructGlobalMap(globalFrame, frame, M, globalM)
% TODO: Add explicit explanations here
[h, w] = size(frame);
t = M;
M(:,3) = t(3,:)';
M(3,:) = t(:,3)';
tform = affine2d(M);
Tinv = invert(tform);
cumulativeM= Tinv.T*globalM.T;
ble... |
mex ./persistence/comp_graph_persistence.cpp |
%%% Función para recorrer los clusters buscando clusters multielectrodo de p-valores
%%% Álvaro Cabana Junio 2017 - CIBPsi
%%% -------------------------------------------------------------------
%
% Función recursiva: algunos inputs deben ser fijados vacíos.
%
%
% entradas: ptable: salida de estadístico punto... |
function [] = plot_piano(maxFFT,low,high,A)
% plots the piano backdrop in the active figure
% maxFFT: the maximum amplitude, sets the y-limit of the piano plot
% low, high: the lowest and highest octave to be displayed
% A: the tuning of the piano, e.g. 442 Hz
NOTE_ABOVE_RATIO = 2^(1/12); % ... |
function [distortion]=CalDistortion_LUT_Compare(x0)%newton([0.8 0.8 0.8],0.00001,20)
global N dist bitlens imp y2fit z2fit a b c d
syms ri% 1/2 root of the 'inverse of rate'
per=eval(2^(-1.1^(d*ri^6+c*ri^4+b*ri^2+a)));%ri^4 for the sake of using newton method
y2_lot=min(y2fit):0.05:6;%max(y2fit);
for i=1:length(y2... |
function [R_s, R ,M,N] = GetHArrisMatrix( Sxx,Syy,Sxy,k,threshold)
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
[x,y] = size(Sxx);
R = zeros(x,y);
R_s = zeros(x,y);
for i = 2 : x - 1
for j = 2 : y - 1
xx = 0; yy = 0; xy = 0;
for wi = 1 : 3
for wj = 1 :... |
%% Q1
beta = 0.95;
delta = 0.5;
theta = 0.8;
alpha = 0.5;
A = 1;
k_star_old = ((1/beta+delta-1)/(alpha*A))^(1/(alpha-1));
c_star_old = A*k_star_old^alpha - delta*k_star_old;
k_star_old;
c_star_old;
%% capital before the shock
disp(k_star_old);
%% consumption before the shock
disp(c_star_old);
A = 1.1;
k_star_new = (... |
function [R] = get_CC_network(R)
fprintf('\t Getting correlation coefficient distribution (network-wide sampling)...\n');
corrcoef_sample_num = 10^3; %10^4; % number of sampling pairs
CC_kernel_width = 40; % ms, kernel length
% Dumpe fields
N = R.N;
spike_hist = R.reduced.spike_hist;
dt = R.reduced.dt;
Num_po... |
% This function is used to align the electrical pulse that is detected by
% the detector algorithm. Alignment can minimize the errors caused by
% variation of timing and voltage baseline
function stim_align()
end |
%Q3 (a)
clc;
clear all;
img = imread('image path''circular_stroke.tif');
imshow(img); title('Input image');
[row col] = size(img);
w = (1/81)*(ones(9)); % 9x9 averaging filter
g = imfilter(img, w, 'conv'); % smooth image
figure(); imshow(g); title('Smooth image'); % displ... |
clear all;
S1 = imread('car-plate (5).jpg');
S2 = rgb2gray(S1);
S3 = medfilt2(S2, [3 3]);
E1 = edge(S3, 'sobel');
[sx, sy] = size(E1);
E2 = imdilate(E1, ones(3));
L = bwlabel(E2, 8);
N = 4;
[yN, xN] = find(L == N);
G = zeros(sx, sy);
for i = 1:length(yN)
G(yN... |
function [im_out PSNR SSIM ] = Centralized_SR_Denoising_IDR2( par )
time0 = clock;
nim = par.nim;
[h w] = size(nim);
par.step = 1;
par.h = h;
par.w = w;
ori_im = zeros(h,w);
n_im = nim;
if isfield(par, 'I')
ori_im = par.I... |
close all
clear
clc
fs=1000;
n=0:1/fs:2
x=sin(2*pi*20*n);
subplot(211);
plot(n,x)
N=2^nextpow2(length(x));
m=-N/2:(N/2)-1;
w=2*pi*fs*m/N;
X=x*exp(-1i*2*pi*n'*m*fs/N);
subplot(212);
plot(w/(2*pi),abs(X))
xlim([-70 70]) |
function [ signal ] = highPass( signal, Fs, sigma )
%HIGHPASS Summary of this function goes here
% sigma: standard deviation of gaussian high pass filter
% l = length(signal);
% [f, femg, nfft] = fourier(signal, Fs);
% %plot(f(:), abs(femg(1:nfft/2+1)));
%
% % Gaussian filter in Fourier domain
% % standard deviatio... |
m = 100; % dimension of hidden state
eta = 0.1; % learning rate
seq_length = 25; % length of input sequence
sig = 0.01;
%Parameters in a model
RNN.b = zeros(m,1); %Changed dimension (K,1) -> (m,1) think its wrong in assignement
RNN.c = zeros(K,1);
RNN.U = randn(m, K) * sig;
RNN.W = randn(m, m) * sig;
RNN.V = randn(K,... |
function [measures, best] = distilate(Z, param1_name, skinny, ref_fsimc)
[~, N] = size(Z);
if nargin < 3
skinny = true;
end
measures.param1 = zeros(1, N);
measures.psnr = zeros(1, N);
measures.fsim = zeros(1,N);
measures.ssim = zeros(1,N);
measures.msam = zeros(1,N);
measures.rel_norm = zeros(1, N);
if nargin <... |
function [strSPL, strSpec1, strSpec2] = stimdispMBL(Stim)
% stimdispMBL - strings describing specific parameters of MBL stimulus
% [strSPL, strSpec1, strSpec2] = stimdispMBL(Stim) returns strings
% strSPL, strSpec1, strSpec2 describing the stimulus parameters of the
% MBL stimulus. Stim is the struct containin... |
% Revolute joint in the X axis
%
% Author : Darwin LAU
% Created : 2012
% Description :
classdef RevoluteX < JointBase
properties (Constant = true)
numDofs = 1;
numVars = 1;
q_default = [0];
q_dot_default = [0];
q_ddot_default = [0];
q_lb = [-pi... |
%dynamics
A=[1 0 .1 0;
0 1 0 .1;
0 0 .5 0;
0 0 0 .5;];
B=[0 0; 0 0;
1 0; 0 1];
H = [1 0 0 0;
0 1 0 0];
%starting
x0=zeros(4,1);
%way points
w=[1 5 10 12 6 2 3;
2 3 4 5 8 7 10];
k=[4 10 19 30 40 45 50];
% H = [0 0 1 0;
% 0 0 0 1];
numIter = size(w,2);
Ap = []
zeroBuffer = zeros(2, 2)... |
function y = odd_finder(a)
s = size(a);
row = s(1,1); column=s(1,2);
for i = 1: row
for j = 1:column
if rem(a(i,j),2) ~= 0
b(i,j) = a(i,j);
end
end
end
y = b;
end |
function pts = getPoints3D(I, pointsPerSlice, viewX, viewY, viewZ, interpScale)
% lets you select points from a 3D image, slice by slice
% only the part of the image defined by I(viewX, viewY, viewZ) is shown.
pts = zeros(0, pointsPerSlice, 3);
[~,~,numImages] = size(I);
scrsz = get(0,'ScreenSize');
figure('Position',... |
img = imread('lena512.bmp');
[row,col] = size(img);
for i=1:row
for j=1:col
if(img(i,j)>128)
img(i,j)=1;
else
img(i,j)=0;
end
if((i>=1 && i<=10) || (j>=1 && j<=10) || (i>=row-10 && i<=row) || (j>=col-10 && j<=col))
img(i,j)=0;
end
end
e... |
function onset=odByVol(wObj, odPrm, plotOpt)
% tpByVol: Onset detection of tapping by volume
% Usage: onset=odByVol(y, fs, odPrm, plotOpt)
%
% For example:
% waveFile='tapping.wav';
% [y, fs, nbits, opts, cueLabel]=wavReadInt(waveFile);
% plotOpt=1;
% odPrm=odPrmSet;
% onset=odByVol(y, fs, odPrm, plotOpt);
% subp... |
clear; % Remove all workspace variables
T = 32;
L = 64;
t = 0:L-1;
Ts = t(2)-t(1); % Sampling period
fs = 1/Ts; % Sampling frequency
y = cos(2*pi/T*t);
fy = fft(y,128);
yz= [y zeros(1,L)];
fyz= fft(yz);
freqs = FftShiftedFreqs(numel(fy), fs);
figure(5); clf;
subplot(2... |
function fid = open(obj,permission)
%OPEN Open a FILE object for reading/writing/appending.
% This method opens a file and returns the FID. The FID is also stored in
% the file object. Note only one instance of the file can be open by this
% method.
%
% PERMISSION is optional and should be 'r', 'w', or 'a' for... |
% функция для определения мгновенного угла тангажа аппарата каждой ступени
function [Theta_t] = Tangagh_corner (t, Stage_Time_Interval, ...
Theta_Stage_Bound, PP_1, PP_2, t_0)
% - веменные интервалы закона изменения тангажа
% t_0 - время начала работы ступени
%
t = t - t_0;
% Stage_Time_Interval представ... |
%Lotanna Ezenwa, Problem Set 2, #2
%PS2_2.m
%% Due Wednesday, April 6th, 2016
clear
me = LotaEzenwa();
code = me.id;
PS_2_1 %To get Initial Values
PS2_1 %To obtain Eigenvalues for Part B
syms ir1 ir2 V1 V2 ic1 ic2
syms B D E F G R C
B = 5;
D = 6;
E = 6;
F = 7;
G = 2;
R = 1; %Ohm
C = 1; %Farads
V1_0 = .5; %Volts
V... |
close all, clear all
[sim_vars,bot,target] = init_vars();
t_end = sim_vars.t_end;
t_step = sim_vars.t_step;
t = [0:t_step:t_end];
for i = 1:3
traj = gen_trajectories(sim_vars,target.speed,i);
subplot(3,1,i); hold on;
plot(traj(1,:),traj(2,:),'r');
plot(traj(1,end),traj(2,end),'r','marker','x');
... |
function [trainMatrix, speciesVec] = buildTrainMatrix(train, im2gray)
% Argument:
% train: a cell array containing FishImage objects for the training
% set
% im2gray: a function handle that converts the image from RGB to
% grayscale
%
% Return:
% trainMatrix: ... |
function [individual_best,fval_best] = de(problem)
%DE 此处显示有关此函数的摘要
% input: problem
% problem.dimension: 变量维度
% problem.objective: 目标函数句柄
% problem.lb: 下界，如[-1,-1]
% problem.ub: 上界，如[1,1]
m = problem.dimension;
f = problem.objective;
lb = problem.lb;
ub = problem.ub;
% init
size_population = 20;
genera... |
%% Example Title
% Summary of example objective
% 退出行情服务器连接
clear all; rehash;
delete(timerfindall);
mdlogout
pause(2);
%% 初始化：counter， book
% counter, 多初始化几个
c_opt = CounterCTP.huaxi_opt3;
c_opt2 = CounterCTP.huaxi_opt4;
% c_etf = CounterCTP.HuaXiETFTest;
c_opt.login;
c_opt2.login;
%% 初始化：quote, volsurf： 手工
%% ... |
function I = preprocess(I, pipeline, methods, colorMode)
numSteps = numel(pipeline);
assert(any(ismember(colorMode,{'RGB','HSV'})),'Wrong colorMode.');
for s=1:numSteps
step = pipeline{s};
if strcmpi(step,'cc')
I = preprocessColorConstancy(I, methods.cc, colorMode);
elseif strcmpi(step,'heq')
... |
clear all
%%% settings %%%
N = 20; % oscillators placed along one dimension of the grid
Nn = N^2; % total number of oscillators
levels = 20;
total_sims = levels^2;
dt = 1e-2; % integration time step
t_sim = 1; ... |
function v = VAR(this, select, range, varargin)
% VAR Population VAR for selected model variables.
%
% Syntax
% =======
%
% V = VAR(M,List,Range,...)
%
% Input arguments
% ================
%
% * `M` [ model ] - Solved model object.
%
% * `List` [ cellstr | char ] - List of variables selected for the V... |
# Venturi tube calculator
# calculates area ratio depending on flow constants
# Damon Printz
# 8/11/2020
clc; clear;
P1 = 20 * 6894.76; % incoming pressure (Pa)
P2 = 10 * 6894.76; % pressure in the neck (Pa)
V2 = 343; % speed through the venturi neck (m/s)
rho = 1.225; % air density (kg/m^3)
if( P2/rho-P1/rho+V... |
function [distance] = euclidean_distance(u,v)
%EUCLIDEAN_DISTANCE Return the euclidean distance between two points
% points are vectors
squared_distance = sum((u-v).^2);
distance = squared_distance^0.5;
end
|
var_mat = NaN(3,3);
corr_mat = NaN(3,3);
prod_l_mat = NaN(3,6);
prod_m_mat = NaN(3,6);
prod_s_mat = NaN(3,6);
wl_mat = NaN(3,6);
wm_mat = NaN(3,6);
ws_mat = NaN(3,6);
emp_l_mat = NaN(3,6);
emp_m_mat = NaN(3,6);
emp_s_mat = NaN(3,6);
rel_wage_l_mat = NaN(3,6);
rel_wage_s_mat = NaN(3,6);
nl_mat = NaN(3,6);
nm_mat = NaN(3... |
function M = logmap(r, x1)
X(1) = x1;
for i=1:19
X(i+1) = r * X(i) * (1 - X(i));
end
M = X;
end
|
%% Vassilis Palassopoulos
% Helper function for running Python (mymod.py) within MATLAB
function mymod()
mymod = py.importlib.import_module('mymod');
py.importlib.reload(mymod);
end
%clear classes
%if count(py.sys.path,'') == 0
% insert(py.sys.path,int32(0),'');
%end
|
% this script states and solves the floor dual for function g. The Ordering
% of the indicies in the Matrix is given by the functions getIndex5Vars and
% getSets5Vars. The coefficiants are in the variable c except for
% c_emptySet_emptySet which is given in floorDualVal!
n = 5; % number of variables
binCoeff = nchoosek... |
clc;
clear;
close all;
choice = input('<< Welcome to MNA-MAT - A SPICE netlist simulation tool >> \n 1. Standard Analysis \n 2. Monte Carlo Analysis \n 3. View the results of previous simulation \n');
switch(choice)
case{1}
run('Standard_Analysis.m');
case{2}
run('MonteCarlo.m');
case{3}
... |
function llk_trial=Exp1_TrialLikelihood(llk_responses)
%% Collapse llk by trial
llk_trial=squeeze(nansum(log(llk_responses+eps),2));
|
clear all;
clc;
syms y;
fx=42*(5-y)*2*sqrt(25-(y-5)^2);
n=5;
a=0;
b=5;
R=zeros(n,n);
fa=subs(fx,a);
fb=subs(fx,b);
for j=1:n
h(j)=(b-a)/(2^(j-1));
end
h
R(1,1)=(h(1)/2)*(fa+fb);
for j=2:n
Sum=0;
for i=1:(2^(j-2))
c=(a+((2*i-1)*h(j)));
fc=subs(fx,c);
Sum=Sum+fc;
end
R(j,1)=(1/... |
clear;
clc;
r = 1024;
c = 1024;
padX = 3;
padY = 3;
blockX = 16;
blockY = 16;
totalFrame = 100;
NBx = ceil( ( c - padX ) / (blockX + padX) );
NBy = ceil( ( r - padY ) / (blockY + padY) );
GW = NBx * blockX + (NBx+1) * padX;
GH = NBy * blockY + (NBy+1) * padY;
diffH = GH - r;
diffW = GW - c;
H = GH;
W = GW;
dataSet ... |
%%%%%%%%%%%%%%%%%%%%%%% pMelts equil. batch melting %%%%%%%%%%%%%%%%%%%%%%%
H2O=0.15; % Initial Water
Pi=33000; % Initial Pressure
% Starting composition
sc=[44.8030; 0.1991; 4.4305; 0.9778; 0.3823; 7.1350; 0.1344; 37.6345; 0.2489; 0.0129; 3.5345; 0.3584; 0.0289; 0.0209; H2O;]; %mcdbse (McDonough Pyrolite)
% Elements t... |
dat=[10,2,4,5,20,34,5,10,23,88,4,2,5,1,19,30] % Example short time series.
in=dat;
bin_len=round(length(in)/2)-1; % This is for the 'default' binning. User can comment this out
% if they prefer assigning specific bins to
% the MSCV analysis. If user wants ... |
function [dZ] = backward_activation(Z, Sigma)
%BACKWARD_ACTIVATION Compute the derivative of the activation function
%evaluated in Z
% inputs:
% o Z (NxM) Z value, input of the activation function. The size N
% depends of the number of neurons at the considered layer but is
% irrelevant here.
% ... |
clear all;
close all;
clc;
m=input('Enter the basis matrix dimension: ');
n=m;
alpha2=ones(1,n)*sqrt(2/n);
alpha2(1)=sqrt(1/n);
alpha1=ones(1,m)*sqrt(2/m);
alpha(1)=sqrt(1/m);
for u=0:m-1
for v=0:n-1
for x=0:m-1
for y=0:n-1
a{u+1,v+1}(x+1,y+1)=alpha1(u+1)*alpha2(v+1)... |
% Use the Open File Dialog
[filename, pathname] = uigetfile('*.out', 'Pick the image file: ');
% Check For Selected Files
if isequal(pathname,0)
disp('No Data Files Were Selected !!')
else
% Read Image File
imageRaw = dlmread(filename,'\t');
[imgX imgY] = size(imageRaw);
% Plot Orig... |
%temp =
%csvread('../data/control_group/2018-04-30T12-54-31/virus-over-time.csv');
% SETUP
virusMin = 50;
virusMax = 500;
% Get config group names
cd ../data/
files = dir;
configGroups = {files([files.isdir]).name};
configGroups = configGroups(~ismember(configGroups,{'.','..'}));
% Enter each group. Take the average... |
%target side
plot(tc_dva(1),tc_dva(2),'-or')
hold on; axis([-5,5,-5,5]);
plot(dc_dva(1,1),dc_dva(1,2),'-ob')
plot(dc_dva(2,1),dc_dva(2,2),'-ob')
%unrotated target stuff
plot(targ_coor_struct.point_3(1),targ_coor_struct.point_3(2),'*r')
plot(targ_coor_struct.point_2(1),targ_coor_struct.point_2(2),'*g')
plot(targ_coor_st... |
% Final Project - Interest Points Detection and Image Matching
% Author: CÚline Bensoussan & Jill Perreault
% Course: Computer Vision
% Date: April 15, 2013
function [r, c, harris] = harrisCornerDetector(im, sigma, n, disp)
% HARRIS CORNER DETECTOR: detects n interest points of an image
%
% [fig, r, c, harr... |
function cir_plot(c,r)
cir_x=[];
cir_y=[];
for j=0:pi/500:2*pi % ²ÎÊý·½³Ì»Ô²
aa_x= r*cos(j)+c(1);
aa_y= r*sin(j)+c(2);
cir_x=[cir_x,aa_x];
cir_y=[cir_y,aa_y];
end
plot(cir_x,cir_y,'k--','LineWidth',1.5);
|
function [left_, right_] = calc_dynamicBEP(self, tau_)
% 计算动态的BEP函数
%输出
% 左BEP和右BEP
left_ = nan;
right_ = nan;
call = self.call;
put = self.put;
if isempty(call) || isempty(put)
else
if ~exist('tau_', 'var')
tau_ = call.tau;
end
[left_init_, right_init_] = self.calc_payoffBEP;
% 计算的函数句柄
... |
function pspm_contrasts(modelname, modelfile)
% function for batch running contrasts in PsPM
%%
%==========================================================================
% User Defined Contrasts
%==========================================================================
% User Defined Contrasts
%... |
function [Light_Dark_Box] = createLDBstruc_Godfrey(T_Food_Complete,T_Light_Complete,T_Difference_Complete,T_Weight_Complete)
%{
Removing mice that were exclded for various reasons. Total of 10 mice in
Fasted groups and 11 mice in Control groups.
Used in the function CreateStrucLDB_Godfrey.m
Uses the following function... |
clear all;
theta = [0,0];
thetax = zeros(1000,2);
Jthetax = zeros(1000,2);
for i=1:1000
Jtheta = 0.5*[5*theta(1) + 3*theta(2) - 7, 3*theta(1) + 2*theta(2) - 4];
theta = theta - 0.1*Jtheta;
thetax(i,:) = theta;
Jthetax(i,:) = Jtheta;
end |
clear, clc
syms u1 u2 u3 s
u = [u1; u2; u3];
R = (2 * s * s - 1) * eye(3) + 2 * (u * transpose(u) - s * skew(u));
q = transpose(sym('q%d%d', [4, 3]));
qq = transpose(sym('qq%d%d', [4, 3]));
% gc_zp_data(4, false, [symvar([q, qq]), sym('s')]);
% q = eval(q);
% qq = eval(qq);
% R = eval(R);
eqs = sym(zeros(5, 1));
e... |
clear all
close all
%this will be used to flag how you want to be assessed
fname = 'EGB339_prac_exam_group_16.json';
flags = jsondecode(fileread(fname));
%change this for different input sheets
init_image = imread('TestSheet1.jpg');
dest_image = imread('TestSheet8.jpg');
%this will not be made available b... |
function [F,labels] = featureExtractor(my_dir,name)
fprintf('\n\n\n\t\t%s\n\n',upper(name));
Bt = 20;
Nc = 9;
folderInfo =dir(my_dir);
folderInfo(1:2) = [];
num_images = length(folderInfo);
labels = repmat(name, num_images, 1);
labels = mat2cell(labels, ones(size(labels, 1), 1), size(labels, 2));
disp(['Total:... |
function [wijt xijt] = get_i_j_cooccurrences(output,Xframes,i,j,sign_test_flag)
if j<i
[i j] = swap_values(i,j);
end
if ~exist('sign_test_flag','var')
sign_test_flag = false;
end
T = length(output);
wijt = zeros(T,1);
xijt = zeros(T,1);
for t=1:T
xi = Xframes(i,t);
xj = Xframes(j,t);
xijt(t) = m... |
function bestVal = findBestThreshVal(vmin, vmax, dv, nExp, windowSize)
if nargin < 4
nExp = 1;
end
if nargin < 5
windowSize = 50;
end
vals = vmin:dv:vmax;
[~,Tshape] = plotResults(nExp, vmin, windowSize, false);
bestVal = [vmin mean(Tshape) std(Tshape) length(Tshape)];
values = [bestVal; zeros(length(vals)-1... |
%変数リスト
B=1.2;
delta_K=0.1;
delta_H=0.05;
theta=2;
low=0.05;
alpha=0.33;
a11 = (B + delta_K - delta_H)/alpha;
a21 = 1/theta*(delta_K*(1-theta)+low);
a31 = (1-alpha)/alpha*(delta_H - B - delta_K);
A = [a11 a21 a31]' ;
Slope_SS = [1 0 0; (alpha-theta)/theta 1 0; 0 -1 B];
%x= -10;
%y= 10;
% if (x>0) & (y>0)
% disp('x ... |
function []=plot_possibilistic(number_of_clusters, centers, data, plottitle)
figure()
scatter(data(:,1),data(:,2),1, '.c');
hold on
for i=1:number_of_clusters
plot(centers(i,1),centers(i,2),'xk','MarkerSize',7,'LineWidth',1)
hold on
end
title(plottitle)
hold off
end |
syms y(x) c
DY = diff(y);
% (a)
cond = y(2) == 0.5;
ode = DY == 8*x^2 + 5;
getY(ode,cond,x, '(a)');
% (b)
cond = y(0) == pi/5;
ode = DY == 5*x*sin(y)^2;
getY(ode,cond,x,'(b)');
% (c)
disp('(c)')
cond = y(0) == c;
ode = DY == 7*x*(cos(y)^2);
ySol(x) = dsolve(ode,cond);
disp(ySol(x));
% (d)
cond = y(0) == 3;
ode = DY... |
% Simon's code
nCuts_no = length(unique(nCuts));
nTrees_no = length(unique(nTrees));
nCutsRS = reshape(nCuts,length(unique(nTrees)),length(unique(nCuts)))
nTreesRS = reshape(nTrees,length(unique(nTrees)),length(unique(nCuts)))
ROCintRS = reshape(ROCint,length(unique(nTrees)),length(unique(nCuts)))
surf(nCutsRS,nTre... |
function [e] = test14(cleanup, level)
%TEST14 Unicode tests, You need your machine set up and the level needs to
%be higher than 1. For windows, install the Asian fonts and switch to
%Japanese mode.
% Thomas Ruark, 5/10/2006
% Copyright 2006 Adobe Systems, Inc.
if level > 1
% J characters
j = [2... |
function W=initLayer(m,n)
W=zeros(m,n);
end |
%% HW 4
%% 1. ...Produce a short Matlab script to test your answer.
sol=inv([7,2,1;0,3,-1;-3,4,-2]);
%% 2.a. Implement the bisection scheme to solve for E.
for i=1:1
w=.017; %set up values
e=.07;
t=50;
f=@(E) (w.*t)+(e.*sin(E))-E;
a=1.5.*10.^8;
b=-1.*10.^8;
error=10.^-3;
E_bi_a=bisectionMethod(f,a,b,error);
disp('The... |
function [k,f] = LBFGS_k(k0,ffo,fmo,rho,Dissimilarity,Spacing,delta,ZU_diff,M_lbgfs )
maxFunEvals = M_lbgfs;
fprintf('Result after %d evaluations of limited-memory solvers on 2D rosenbrock:\n',maxFunEvals);
% fprintf('---------------------------------------\n');
options = [];% 元素为空
options.display = 'none';
optio... |
%1
%traversal file
pathroot='G:\GranduationProject\sport\dFC\pingpong_dfc\FCM';
list=dir(fullfile(pathroot));%得到20个运动员被试文件夹名
index=1;
A=zeros(20,104,116*116);%得到20个104*（116*116）的矩阵
for i=3:size(list,1)
traversalFileName=list(i).name;%得到20个运动员文件夹子文件名
sublist=dir(fullfile([pathroot,'\',list(i).name]));
for j=... |
%P3
subplot(2,2,1);
t=0:0.002:15; %de la 0 la 15; 0.002=2 ms rezolutia temporala; mai poate fi 0.02=20ms si 0.2=200ms;
amplit=[-1 1];
hold on
grid
title('Graficul 1')
xlabel('timp (s) ')
ylabel('amplit(V)')
for n=0:0.25:15
y=datasample(amplit,1) %genereaza un numar aleator intre -1 si 1(am specificat ... |
function val = get(c, astr_propName)
%
% NAME
%
% function val = get(c, astr_propName)
%
% ARGUMENTS
% INPUT
% c class cortical parellation class
% astr_propName string One of:
% rows
% cols
% slices
%
% OPTIONAL
%
% DESCRIPTION
%
% 'get' accesses the internals of the class to stdout.
%
% NOTE:
%
% ... |
function thetatrig_FR(thisdir)
disp('Start thetatrigFR')
load(thisdir,'times_armon_thetaof_headingarm_lap_thetahalf_all','PFCthetaspikes_binned');
Th = times_armon_thetaof_headingarm_lap_thetahalf_all;
clear times_armon_thetaof_headingarm_lap_thetahalf_all
binsize = .02;
window = [-2 2];
ind = [window(1):binsi... |
pwd()
pkg load image
rgb = imread("animal.jpg");
figure('Name', 'RGB');
imshow(rgb);
%%
[X,map] = rgb2ind(rgb);
figure('Name', 'Indexed');
imshow(X, map);
%%
figure('Name', 'Gray from rgb')
gray = rgb2gray(rgb);
imshow(gray);
%%
figure('Name', 'Gray from indexed');
ga = ind2gray(X, map);
imshow(ga... |
%% Runs The Experiment (Block 2)
function player_struct = rtanx_experiment_block2(player_struct, w, debug, rootFolder, quitmarker, par)
%% Input data for experiment_data
% 1 = Trial
% 2 = Time
% 3 = Block id
% 4 = Stim 1 p(win)- BLOCK ORDERING FROM INTIALISE
% 5 = Stim 2 p(lose,- BLOCK ORDERING FR... |
function [ z ] = fitfunction( a,b,c,x )
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
z=atan(a*x^2 + b*x + c)/pi + 0.5;
end
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%-% ------------------------------------------------------------------- %-%
%-% Approximates the solution to the small dispersion CH equation,given %-%
%-% u_t +2*Ku_x+ 3uu_x - ep^2(u_{xxt}+2u_xu_{xx}+uu_{xxx})= 0. The %-%
%-% spatial doma... |
% figure('Name','Scatter Plot of Sigma and T');
% scatter(sigma5,T5,64,'b','o');
% hold on
% scatter(sigma28,T28,64,'b','o');
% a = [0.3927 0.3927];
% b = [0 50];
% %p = plot(a,b,'r');
% %p.LineWidth = 1.5;
% xlim([0,1.6])
% ylim([0,50])
% xlabel('Drifting Tendency \sigma_d','FontSize',18);
% ylabel('Optimal... |
function [ticks,lims] = getDecentTicks(xx,minNumTicks)
% xx contains the values to be shown on the axis, e.g., the data points
% themselves, the most extremal points, or preselected axis limits.
%
% See also getTicks
%
% @ Matt Golub, 2018.
if nargin==1
minNumTicks = 5; % Guaranteed to have at least this many tick... |
% Slow Potassium channel
%
% modeled after Mahon2000
% Note: in tau_h, mahon2000 has 2930 instead of 293.0
%
% using n and alpha, beta formulation
% returns also steady-state value
%
% $Revision:$
%
function [I_KAs, dm, dh, m_inf, h_inf] = ikas(V_m, m, h)
E_As = -85; % mV
g_As = 0.32; % mS/cm^2
I_KAs = g_As*m*h*... |
%% 颜色空间的对比图
clc;
close all;
clear;
imgdata = imread('data\\10.jpg');
rgbdata = 255 * im2double(imgdata);
labdata = stpRgb2Lab(imgdata);
figure;
imshow(imgdata);
title('彩色图像');
[m, n, ~] = size(rgbdata);
N = 1000;
rgbd = reshape(rgbdata, m*n, 3);
labd = reshape(labdata, m*n, 3);
labd(:, 1) = labd(:, 1) - 50;
rgbdat... |
function [numOfDeleted] = deleteTemporaryFiles(alsoDelete)
%DELETETEMPORARYFILES A simple function that deletes temporarily created
%files with certain postfixes in current folder.
%
% ------------------------------------------------------------------------
% Copyright (C) 2017 M. Schrauwen (markschrauwen@gmail.com... |
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