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function [vmean, vstd] = procAB_driftVel(par)
%parameters
T = par{1};
v0 = par{3};
gamma = par{4};
N = par{5};
folder = par{6};
deter = par{7};
Nprof = par{8};
nbins = 200;
if deter == 0
mu = par{9};
end
%% empirical drift velocity
if deter == 1; range = 1; elseif deter == 0; range = 1:Nprof; end
counts = zeros(l... |
classdef TPA_MultiTrialTwoPhotonManager
% TPA_MultiTrialTwoPhotonManager - loads raw data from all trials.
% Computes transformations and extracts relevant info without ROIs
%-----------------------------
% Ver Date Who Descr
%-----------------------------
% 28.04 15.01.18 UD Pixel cor... |
classdef awgZeroCalibrator < qes.measurement.measurement
% measure awg zero offset
% Copyright 2017 Yulin Wu, University of Science and Technology of China
% mail4ywu@gmail.com/mail4ywu@icloud.com
properties
fine@logical scalar = false;
showProcess@logical scalar = false
end
propertie... |
function linescanImageViewer
cellDirs = uipickfiles;
for i =1:length(cellDirs)
if isdir(cellDirs{i}) %Check if directory
parseLineScans(cellDirs{i}) %pass to linescan parser
end
end
% -----Local Function-----
function parseLineScans(cellDir)
lsContents = dir('LineScan*');
for i=1:length(lsCo... |
function [X, y] = normalize (X, y)
n = size(X, 2);
m = size(X,1);
minX = min(X);
maxX = max(X);
for i = 1:m,
X(i,:) = ( X(i,:) - minX ) ./( maxX - minX );
end
y = ( y - min(y) ) ./ ( max(y) - min(y) );
end |
% rd_runNMOA.m
%% Set up the opts structure
op.stimCenters = [0 50 100];
op.stimWidth = 30;
%% Run model
R = attentionModel1D(op);
% opts.attnGainX = R;
opts = op; |
function matInitEddyViscositySolver( obj )
%> @brief Function to initialize the vertical eddy viscosity sover for both the three dimensional barotropic and baroclinic shallow water model
%> @details Function to initialize the vertical eddy viscosity sover for both the three dimensional barotropic and baroclinic shallo... |
% Op Pose class. Uses EulerXYZ coordinates
%
% Author : Jonathan EDEN
% Created : 2016
% Description :
classdef OperationalPoseEulerXYZ < OperationalSpaceBase
methods
% Constructor
function o = OperationalPoseEulerXYZ(id,name,link,offset,selection_matrix)
o.id ... |
function idxfl = nearfl(x, x0)
% Get the lowest index of the two points in
% vector x that bound the number x0.
dx = abs(x - x0);
flr = mink(dx, 2);
il = find(dx==flr(1)); il = il(1);
ir = find(dx==flr(2)); ir = ir(1);
idxfl = min([il ir]);
end
|
clear
close all
clc
lmbda = 0.5;
thetaF=[60;240];
delta_t = 0.001;
k=71000;
l1=1;
l2=1;
[Oe0,Ri0] = practical9_forkin(thetaF);
[pc,u,v,sd] = practical9_perspective(Ri0,Oe0);
% sd=s;
t = 0;
theta = [0;0];
e=1;
i=1;
while norm(e)>=0.003
[Oe0,Ri0] = practical9_forkin(theta);
[pc,u,v,s] = prac... |
cellSize = 50;
originalImage = imread('Images/autoSegments/train/MGF1-Cross-0009.tif');
[width, height, dim] = size(originalImage);
imshow(originalImage);
hold on;
Xboxes = fix(width / cellSize);
Yboxes = fix(height / cellSize);
row = 1;
for i = 1 : Xboxes
line([1, height], [row, row]);
row = row + cellSize;
end
c... |
function plot = draw_bar_plot(output, num_machines)
[common, freq] = mode(output(:,2)); % Get machine with highest number of jobs
new_data = zeros(num_machines,freq); % Create an array with machines x max jobs
for i = 1:num_machines % Assign machine-wise
machine_jobs = output(output(:,2) == i,1)';
... |
% function cond = cond_gaas(w)
% Changelog 4/28/2017
% Changes made to make conductivity ans epsilon signs consistent with
% electrical engineering notation of j = sqrt(-1);
%
% From Burke's paper
% High frequency conductivity of the high-mobility two-dimensional
% electron gas
%% Parameters
close all ; clc ; clear ... |
# pacote necessario
pkg load image;
# abrir a imagem
einstein = imread("imagem.jpg");
# função imhist retorna o histograma e os niveisIntensidade
[histograma, niveisIntensidade] = imhist(einstein);
# função size retorna as linhas e colunas de uma imagem
[linhas, colunas] = size(einstein);
# crio uma nova imagem pre... |
t = -1:0.01:1;
syms n
w1 = symsum(sin(n*t)/n,n,1,50);
w2 = symsum(sin(n*t)/n,n,1,100);
w3 = symsum(sin(n*t)/n,n,1,200);
% consider 9999 as infinite
S = symsum(sin(n*t) / n,n,1,9999);
plot(t,S);
hold on
plot(t,w1,'r');
hold on
plot(t,w2,'g');
hold on
plot(t,w3,'b'); |
function cv_result = CrossValidation(features_train, label_train, headers, max_depth, classification)
k = 10;
if classification
cv_result = zeros(2, k);
else
cv_result = zeros(1, k);
end
cv_result = zeros(1,k);
k_tree = cell(1,k);
rowsize = size(features_train,1);
rand = randperm(rowsize);
shuffled_features = f... |
function al_instructions(taskParam, whichPractice, subject)
%AL_INSTRUCTIONS This function runs the instructions for the cannon task.
% As we recently re-organized the instructions scripts,
% instructions are currently only working for the "chinese" and
% the "ARC" version. In particular, we divided the instructi... |
function y = nanmsem(x,varargin)
% Estimated standard error of the mean, based on median absolute
% deviation to increase outlier robustness (ignoring NANs)
m = nanmedian(x,varargin{:});
l = sum(~isnan(x),varargin{:});
s = nanmedian(abs(x - repmat(m,size(x)./size(m))),varargin{:}); % * 1.4826 % Factor of 1.4826 convert... |
%Full Body LG EKF and EUL EKF for the boxing CMU data
%Load up the generated model
addpath('..\..\');
%This is reading TRC files and stuff
addpath('C:\aslab\projects\AutoRehabSystem\Common');
addpath('C:\aslab\projects\AutoRehabSystem\Common\Classes');
%ADD MAGIC EKF STUFF
EKFCodePath = 'C:\aslab\projects\vjoukov\Gen... |
function [ x, w ] = ccn_compute_np ( n, np, x )
%*****************************************************************************80
%
%% CCN_COMPUTE_NP computes a nested Clenshaw Curtis quadrature rule.
%
% Licensing:
%
% This code is distributed under the GNU LGPL license.
%
% Modified:
%
% 07 March 2011
%
% Au... |
function writeExtConductanceSettingsHDF5(FID, pop_ind, mean, std, modify)
% write external Conductance settings
% FID: file id for writing data
% pop_ind: neuron population index
% mean: mean value for Gaussian conductance (uS) for each neuron
% std: std for Gaussian conductance (uS) for each neuron
if leng... |
function[cities]=city_size(cities)
%Code to determine the size of the cities
%Input parameters:
%cities: city matrix of format mx3, where the first column is filled with
%the degree of the city in the Network
%Output:
%cities: modified version of the input matrix. The city population
%(cities(:,2)) has been added
%A... |
n=0:250:6000;
vpm=zeros(25,1);
s=zeros(25,1);
l=zeros(25,1);
for i=1:25
[vpm(i),n(i)]=FHN2d_breaks100(n(i));
end
%subplot(2,1,1);errorbar(rho,Vp4,Vp4err,'.')
%subplot(2,1,2);plot(rho,lVp4,'*')
%subplot(2,1,3);plot(rho,Vp4err,'--')
%hist(Vp4)
%hold on
%plot(n/(200*0.02)^2,Vp2,'b')
%hold on
%plot(n/(200*0.02)^2,Vp3... |
function compile_cpp_files
% compile_cpp_files compiles the Kin2 toolbox.
% The C++ code is located in 6 files:
% Kin2.h: Kin2 class definition.
% Kin2_base.cpp: Kin2 class implementation of the base functionality including body data.
% Kin2_mapping.cpp: Kin2 class implementation of the mapping functionality
% ... |
L = 100; %Overall simulation interval
N = 2000; %Number of space subdivisions
h = L/N; %Size of mesh spacing
x = [0:h:(L-h)]; %Space mesh
tau = h^2/3; %Time step
u0 = A*H(1/2 - abs(x),L)
u = u0;
time = 10000
for ti=1:time
u(3:N-2)= -2*tau*(u(2:N).^2)./(h^2).*(u(1:N-1) -2*u(2:N) + u(3:N+1))...
-(tau/(h^3))... |
%%%% MULTI ENERGY MATERIAL DECOMPOSITION CODE BARZILAI BORWEIN WITH NEW REGULARIZATION TERM %%%%
% Here I replace the matrix multiplications by matrix free functions
% Reconstruct two material phantom, imaged with two different energies, using Barzilai-Borwain
% optimization method. Second regularization term added!
cl... |
clear all;
close all;
clc;
%% Import the data
[~, ~, raw1] = xlsread('Tomo.xlsx','Tomography','H4:H19');
[~, ~, raw2] = xlsread('Tomo.xlsx','Tomography','J4:J19');
[~, ~, raw3] = xlsread('Tomo.xlsx','Tomography','D25:G40');
% Create output variable
n_phi_minus = cell2mat(raw1); %counts corresponding to the pr... |
function [total_centrality] = pseudo_inverse_RWBC(A);
[~,n] = size(A);
D = A*ones(n,1);
D = spdiags([D], 0, n, n);
L = D - A;
L_plus = pinv(L);
total_centrality = zeros(n,1);
for s=1:n
for t= 1:n
if s ~= t
s_index = zeros(n,1);
s_index(s) = 1;
s_index(t) = -1;
... |
load HistogramsAssignment3;
figure(1);
histogram(finalQueueLength0,'Normalization', 'Probability');
set(gca, 'FontName', 'Times New Roman')
set(gca,'xtick',0:10)
set(gca,'fontsize', 12)
title('Final Queue Length lambda=0.3')
xlabel('Final Queue Length');
ylabel('Probability');
figure(2);
histogram(finalQueueLength1,'... |
% Set random number generator
rng default;
mkdir('../working');
mkdir('../working/sim_geno_sim_pheno');
n_samples = 100;
%% Set up models
cutoffs = [10, 30, 100, 300, 1000, 3000, 10000];
models = cell(1, 1);
models{1}.name = 'Linear';
models{1}.m = Lin_model(false);
models{2}.name = 'Linear w/ PCs';
models{2}.m ... |
function ara_corrGB(fileStruct, paramStruct)
%% Initialize
% Initialize function-specific parameters
assignInputs(fileStruct.analysis.xcorr.globSig_BOLD, 'createOnly')
assignInputs(paramStruct.xcorr.globSig_BOLD, 'createOnly')
totalScans = length(cat(2, scans{:}));
%% Average Cross-Correlation Data Across All Subjec... |
function [Y_in_train,train_prediction,Y_in_test,test_prediction] = ModelInfer_I_O_HMM_one_input(modelFile,train_Data,test_Data,nT,nB)
%%% modelFile: DBN model file path
%%% input:
%%% train_Data: path for training data
%%% test_Data: path for test data
%%% nT: number of look back step
%%% nB: number of discrete nod... |
function [centres] = find_circle_centres(BW_image)
%This function finds the centres of each circle and retursn a matrix
%containing them.
%Identify objects in the image
CC = bwconncomp(BW_image);
%Holder matrix
BW2=zeros(CC.ImageSize);
%Identify information of objects
s = regionprops(CC, 'all');
%Holder Matr... |
%% mds4mmea
% classical multidimensional scaling applied to solutions of the mmea method
%%
function [y, e, parNm, dist] = mds4mmea(results)
% created at 2022/03/30 by Bas Kooijman
%% Syntax
% [y, e, parNms, dist] = <../mds4mmea.m *mds4mmea*> (results)
%% Description
% classical multidimensional scali... |
function Rho = GetRho (E, h, a)
dRho = 0.05;
r_max = 1;
r = 0;
Rho(1) = r;
while ((r+dRho) <= r_max)
r = r+dRho;
if sqrVr(E, h, r, a) >= 0
Rho = [Rho r];
end
end
%Удаляем 0
Rho(1) = [];
function result = sqrVr(... |
%%-------------------------%%
%% Parameter
delta = 0.5;
m = 5;
h = delta/m;
n = 1/h;
%% basis 1 continuous P1- P0
%% P1
Alpha = zeros(n-1, 2*n);
for i = 2:n-1
Alpha(i,2*(i-1)) = 1;
Alpha(i,2*i-1) = 1;
Alpha(i,2*i) = -1;
Alpha(i,2*i+1) = -1;
end
Alpha(1... |
% Align two images by affine transformation and homography
%% Load images
clear all;
close all;
clc;
datapath = '../../data/AlignmentTwoViews';
imname1 = fullfile(datapath, 'uttower_left.jpg');
imname2 = fullfile(datapath, 'uttower_right.jpg');
im1 = imread(imname1);
im2 = imread(imname2);
im1 = im2double(im1);
im2 =... |
function [h,m] = getUIData(FigHand)
% Get UI Handles
h.animal_id = findobj(FigHand,'tag','animalIDField');
h.other_id = findobj(FigHand,'tag','otherIDField');
h.dob = findobj(FigHand,'tag','dobField');
h.dow = findobj(FigHand,'tag','dowField');
h.parent1 = findobj(FigHand,'tag','parent1Field');
h.parent2 = findobj(Fi... |
function [mu,pc,ev] = Compute(data)
%Compute Summary of this function goes here
% Detailed explanation goes here
n_data = size(data,2);
mu = mean(data,2);
cent_data = data - repmat(mu,[1,n_data]);
[pc,ev] = myGPCA(cent_data,n_data,0,0);
end |
function [indCluster,numIter,tElapsed,finalResidual]=NMFCluster(X,k,option)
% NMF based clustering
% Usage:
% [indCluster,numIter,tElapsed,finalResidual]=NMFCluster(X) % in this case, X is coefficient matrix obtained by a NMF outside this function
% [indCluster,numIter,tElapsed,finalResidual]=NMFCluster(X,k)
% [in... |
function RUN_4_CellStateCompare_Path(basefolder, folders, dates,marker_name, antibody_rounds, marker_cycle, HSF1round, canceround, antibody_type, max_rows, well_nums, sol_thresh)
%This program chooses the fields with good staining then plots the
%frequency of HSF1 foci per core using the good fields
% PLOT THE FRE... |
function [hitted,missed,totalGT] = calculateHitMissACPR(realGT,prunnedSet)
totalGT = length(realGT);
matchedCnt = 0;
for ii = 1:1:size(realGT,1)
% tempGT = realGT{1,ii};
tempGT = realGT{ii,1};
flag = 0;
for jj = 1:1:size(prunnedSet,1)
testGT = prunnedSet{jj,1};
[~, name, ~] ... |
clear;clc;
%% generate random synthetic data
n = 1000; p = 1000; sparse_ratio = 0.01;
A = randn(n,p);
beta = randn(p,1);
beta(randperm(p,round((1-sparse_ratio)*p)))=0;beta0 = randn;
b = beta0 + A*beta + randn(n,1);
lambda = 0.1;
%% straightforward method with cvx
% cvx_begin
% variable x_bi(p,1)
% minimize(0.5*norm(... |
clear; clc;
h = 1;
sum1 = (1+cos(1))/2;
n = 1;
int_exact = quad(@mycos,0,1,1.e-12,1.e-12);
for i = 1:10
t = h/2;
for j = 1:n
sum1 = sum1 + cos(t^2);
t = t+h;
end
n = 2*n;
h = h/2;
integ = h*sum1;
h
err_abs = abs(integ-int_exact)
end |
function assert_numeric_scalar_nonnegative(x)
assert(isnumeric(x) && isscalar(x) && (x >= 0), 'Value must be nonnegative, scalar, and numeric.');
end
|
clf;clear all; close all;
N = 10;
sig = randi([0,1],1,N);
sig((sig==0)) = -1;
load('./filter/IIR_filter')
symbol_rate = 1e6;
carrier_frequency = 8e6/symbol_rate;
freq_DAC = 16e6/symbol_rate;
freq_DMA = 32e6/symbol_rate;
group_delay = 1;
srrc_16 = srrc_pulse(16, 5, 0.3);
srrc_2 = srrc_pulse(2,5,0.3);
srrc_16_delay ... |
function plotScan(scan,cmap,dosaturation,withlights)
%% https://github.com/psapirstein/mesh-comparing
% This code is distributed under an Apache License 2.0
% Author: Philip Sapirstein, UNL
%
% The subroutine supports the collection of tools for processing 3D meshes
% and assessing their repeatability accompanying the ... |
tol = 1e-10;
%% Tri: N = 3
N = 3;
tri = StdRegions.Triangle(N);
facelist = [1,2,3,4; 4, 7, 9, 10; 10, 8, 5, 1]';
for i = 1:tri.nFaceNode
assert( abs(tri.Fmask(i) - facelist(i)) <= tol);
end% for
%% Tri: N = 4
N = 4;
tri = StdRegions.Triangle(N);
facelist = [1,2,3,4,5; 5,9,12,14,15;15,13,10,6,1]';
for i = 1:tri.nF... |
function void = assignmentTwo()
% Second assignment of Offline-2
% collection of data from given data file and processing data for further operations are done first
% then, main operations are accomplished using processed data
%
% Input:
% this function has no input
% Output:
% this function returns... |
function trialVec = vecTrials(stimExpt,frameRate)
if ~exist('frameRate','var') || isempty(frameRate)
frameRate = 29.55;
end
nTrials = numel(stimExpt.trialOrder);
% trialVec.stimFrames = stimExpt.ITI:stimExpt.ITI:stimExpt.ITI*nTrials;
vecOrder = stimExpt.trialOrder';
trialVec.vecOrder = vecOrder(:);
trialVec.nRep... |
function doneOr = checkStatus_local(jobID)
%--------------------------------------------------------------------
%This routine is to check if the submitted job is done or not
%One needs to do a little edit based on your own case.
%1 : whichCluster (0: no-job-script, 1: local submission, 2: remote submission)
%-------... |
function [images, labels, num_row, num_col] = loadModelImages(filename, sampling, balance)
if nargin<2
sampling =0;
end
fp = fopen(filename, 'rb');
assert(fp ~= -1, ['Could not open ', filename, '']);
line1=fgetl(fp); %unused
line2=fgetl(fp); %unused
numberOfImages = fscanf(fp,'%d',1);
if sampling == 0
s... |
function [grad]= network_gradient_wu(W,metric_type,varargin)
n=size(W,1);
O=ones(n);
H=O-eye(n);
if any(strcmp(metric_type,{'trans' 'transitivity'}))
alfa=trace(W^3);
beta=trace(W*H*W');
grad=((3*beta*W^2-alfa*(W*H+H*W))/beta^2 ).*H;
elseif any(strcmp(metric_type,{'clust' 'clustering'}))
... |
function [a, b, c, e_train] = model_training(xi, xk, with_bias, ...
model, max_iter, b_init)
% [a, b, c, e_train] = model_training(xi, xk, with_bias, max_iter, model, b_init)
% Train model parameters, and calculate training error.
% The details of the model can be seen at
% https://github.com/ronghanghu/compbio... |
../../src/process/user_camera.m |
function [nv, nf, tris, sibhes, v2he] = split_edge_surf(heid, nv, nf, ...
tris, sibhes, v2he) %#codegen
%SPLIT_EDGE_SURF Split an edge and insert a new vertex.
%
% [NV, NF, TRIS, SIBHES] = SPLIT_EDGE_SURF(HEID, NV, NF, TRIS, SIBHES)
% [NV, NF, TRIS, SIBHES, V2HE] = SPLIT_EDGE_SURF(HEID, NV, NF, TRIS, SIBHE... |
function [ v,h,dispmap ] = disparitymap( imageA, imageB )
%DISPARITYMAP Summary of this function goes here
% Detailed explanation goes here
sampleSize = 4;
windowSize = 8;
%imageA = imread('C:\Users\Fraser\Desktop\leftsmall.bmp');
imageA = padarray(imageA, [round(sampleSize/2),round(sampleSize/2)]);
%imageB = imre... |
% this scripts evaluate the performance of VDB-SE on real cluster of
% batteries. Data are provided by RSE.
close all; clear; clc;
load('lookup_fieldexperiments.mat');
load('data_fieldexperiments.mat');
dt = 1;
time = 9599;
timewindow = 0.4; % interval of soc to consider in each estimation batch
moving_step = 0.2;
n... |
function rhs = rhs_bvp_2(x,y)
global c0 a0 g delta p pw wd r0 z0 f0 aF
% spontaneous curvature
%c = -0.5*c0*(1 - tanh(g*(flip(x) - a0)));
%c = -0.5*c0*(1 - tanh(g*(x - a0)));
%c = -0.5*c0*(tanh(g*(x - z0/r0*0.5 + a0)))+0.5*c0*(tanh(g*(x - z0/r0*0.5- a0))) ;
c = -c0/2 * ( 1./(1+exp((x-a0)/0.005)));
% derivative of ... |
function [worldZ,Zica,W,T,mu] = getKinICs(worldPoints,varargin)
%% GETKINICS Get Kinematic independent components
%% DEFAULTS
VAR_IDX = [1,3,4,6];
R = 3;
DO_ICA = true;
%% PARSE VARARGIN
for iV = 1:2:numel(varargin)
eval([upper(varargin{iV}) '=varargin{iV+1};']);
end
%%
nTrials = numel(worldPoints);
nSamples = ... |
% 315CA Dinu Ion-Irinel
function r = fy (f, x, y)
% =============================================== =======================
% Approximation of the derivative to y of f at point (x, y).
% =============================================== =======================
% if y is on the edge of the derived ima... |
function notes = findNote(cent,lines,dividedImage, median)
notes = "";
for i = 1:length(cent)
for j = 1:length(cent{i})
% Index the note
indexOfNote = nearestPoint(cent{1,i}(j,2),cell2mat(lines{1,i}(:,1)));
% Check if sixteen or eight
... |
%--------------------------------------------------------------------------
%
% Example script for sinf_1D.m and sinf_3D.m
%
% Author : dr.ir. Emanuel A.P. Habets
% Date : 16-09-2010
%
% Related paper : E.A.P. Habets and S. Gannot, 'Generating sensor signals
% in isotropic noise fields',... |
%% RELIABILITY: TIME VARIANCE
% In this example, UQLab is used to compute the outcrossing rate $\nu^+$ in a non-stationary time-variant
% reliability problem using the so-called PHI2 method.
%
% See also: B. Sudret (2008), Analytical derivation of the outcrossing rate
% in time-variant reliability problems. Structure ... |
function batch_master(LFP_or_neur, which_units, varargin)
% 1) batch_master(LFP_or_neur, which_units, func)
% 2) batch_master(LFP_or_neur, which_units, func1, func2)
%
% This is the master function used to call a specified function on individual
% electrodes or neurons, all of them, just the significant encoders, or a... |
%ADD_PLOT adds a measure and plot type to the list of measures to be
% plotted.
%
% Syntax
% ------
% ui.add_plot();
%
% Details
% -------
% This function combines the currently selected measure and plot type into
% a single measure/plot combination, adding it to the list of measures to
% plot.
%
% Examp... |
function [eigenvectors, meanvector, eigenvalues] = prmi_pca(varargin)
% PRMI_PCA Principal Components Analysis.
% [eigenvectors, meanvector, eigenvalues]=prmi_pca(X) performs PCA on data
% matrix X whose columns consist of observations. The columns of eigenvectors
% are sorted in descending order of the correspondi... |
function result = histogram(I,r,c)
histo = zeros(1,256);
for i = 1 : r
for j = 1 : c
pval = I(i,j);
histo(pval + 1) = histo (pval + 1) + 1;
end
end
result = histo;
end |
function [ alpha,details_LS ] = WolfCndVersion3( obj,Grad,Z,Y,d,ops)
%
% This function is the line search algorithm statisfying the decrease
% condition in the Wolfe conditions. The cost fuction at f(x+alpha d)<=f(x)
% and the gradient condition. Check it because it does not has the
% zoom-step
%
% Syntax : [ alpha ]... |
function code = dark_freerews_progratio % MB: 8/6/18
%deliver small size rewards automatically every X # of seconds for
%habituation. however, offer pseudorandom rew sizes (sm/md/lg) for prog
%ratio running to train to run
% Begin header code - DO NOT EDIT
code.initialization = @initializationCodeFun;
code.runtime =... |
function viewVennDiagram(circleAreas,overlapAreas,totalArea,varargin)
% Makes Venn diagram plot.
% Biafra Ahanonu
% originally started: 2017.03.08 [22:29:33]
% branched 2018.04.28 [15:50:00], taken from older calciumImagingAnalysis method.
% inputs
% circleAreas
% A [c1 c2 c3] integer or float vector contain... |
% HISTFEATURES First order statistics from gray-level histogram.
% [X,FEATS] = HISTFEATURES(I,BW) computes 13 histogram features from the
% gray-level image I masked by the binary image BW: average histogram (AHg),
% average gray level (AG), modified energy (MEgy), modified entropy (Metp),
% modified standar... |
function [result, ambient, diffuse, specular, fnc] = evc_phong( V, L, N, ia, id, is, ka, kd, ks, alpha )
fnc.compute_reflection = @( L, N ) evc_compute_reflection( L, N );
fnc.compute_lighting = @( V, L, N, R, ia, id, is, ka, kd, ks, alpha ... |
function dy = ecuacion(x, y)
dy = -2*x^3 + 12*x^2- 20*x + 8.5;
end |
%
addpath('/home/xyy/code/point-neuron-network-simulator/mfile');
data_sw = load('sw_3dim.mat');
W = data_sw.W;
n1 = data_sw.n1;
n2 = data_sw.n2;
n3 = data_sw.n3;
pm = [];
pm.neuron_model = 'IF-jump';
pm.simu_method = 'auto';
pm.net = W;
pm.nI = length(W);
pm.scee_mV = 0.0;
pm.scie_mV = 0.0;
pm.scei_mV = 1.0;
pm... |
% The input must be a function in the coefficient space
function plotSolution(usr_par,u)
figure; clf
trisurf(usr_par.mesh.t,usr_par.mesh.p(:,1), ...
usr_par.mesh.p(:,2),u,'facecolor','interp')
title(' u_{exp} (target / experimental / observed states) ');
xlabel('x'); ylabel('y');
%axis([-1 1 -1 1 -... |
function [val] = meanAbsDiff(inMat)
% each column of inMat is a distinct vector
distance = 'minkowski';
minkVal = 1;
% first compute mean vector
meanVec = mean(inMat,2);
dists = zeros(1, size(inMat,2));
for i = 1:size(inMat,2)
dists(i) = pdist([inMat(:,i) meanVec]', distance, minkVal);
end
val = mean(dists); |
function theta = normalEquations(x, y)
theta = pinv(X' * X) * X' * y;
endfunction
|
function histogram = getHistogram(C, I),
% threshold = 250;
C = C';
histogram = zeros(size(C, 2),1);
I = single(rgb2gray(I));
[f,d] = vl_sift(I) ; %C : 128xsomething
d = double(d);
% fprintf('d then C \n');
% size(d)
% size(C)
for i = 1:size(d,2), %d : 128xsomething
idx = 1;
min_distance = norm(d(:,i) - C... |
function img_blue = seleciona_cor(path_img_original)
%{
* Script que troca a escala de uma imagem de RBG para Gray.
path_img_original: string - caminho para a imagem a ser transformada
img_cinza: uint8 - versao, em escala de cinza da imagem
%}
% leitura da imagem
img_original = imread(path_img_original);
% con... |
%% TestNUFTaccuracy.m
%
% Testing the accuracy of several implementations of the matrix-vector
% multiplications m = E*x, y = EH*m, and z = M*x, where E is a particular
% non uniform discrete Fourier transform matrix, EH is its Hermitian transpose
% and M = EH*E (with a specific implementation).
% The reference impleme... |
function identify_SU_allcells
animalid = '150910';
block = 11;
lcol = 'r'; %lasercolor
onlymod = 0;
printyn = 0;
sfc = 0;
supath = ['C:\Users\Julia\work\data\' animalid '\singleunits\'];
% supath = ['C:\Users\Julia\work\data\' animalid '\multiunits\'];
basename = [animalid '_block' int2str(block) '_tet'];
files = d... |
function [out] = d(x, y)
% Simple function to calculate the sum of a roll of a Y sided die X times
out = 0;
for i = 1:x
out = out + randi(y);
end
end |
function [HtMat] = ifft_3dmat(Data, N_line, N_bins)
HtMat = zeros(N_line,N_line,N_line,N_bins);
for ir = 1 : N_line
for icol = 1:N_line
for iz = 1:N_line
curBin = Data{ir}{icol}{iz};
% reverse FFT for each space location i
curHt = ifft(curBin);... |
%fft of gyroscopes
function [result,Y] = doGyroFFT(data,doPlot)
% data(1) = data1;
% data(2) = data2;
% data(3) = data3;
[L,S] = size(data);
Fs = 100;
T = 1/Fs;
t = (0:L-1)*T;
for i = 1:S
Y(:,i) = fft(data(:,i));
P2 = abs(Y(:,i)/L);
P1(:,i) = P2(1:floor(L/2+1));
P1(2:end-1,i) = 2*P1(2:end-1,i);
... |
function [p_argmax,sigma_argmax]=distributionOfArgMax(mu,sigma)
nr_samples=1000;
samples=mvnrnd(mu(:),diag(sigma),nr_samples);
p_argmax=histc(argmax(samples'),1:numel(mu))/nr_samples;
for i=1:numel(p_argmax);
sigma_argmax(i)=sqrt(p_argmax(i)*(1-p_argmax(i)));
end
end |
reg_results = load(fullfile(files_path, 'postprocessed_data', 'ephys_regression_results.mat'));
nCells = length(reg_results.bad_glm);
nRegs = 10;
window_size = 1;
%% Compute port-entry CPDs for each regressor
for cell_i = 1:nCells
for lock_i = 1:4
entry_bins = abs(reg_results.bin_mids... |
rib_data; close all
%% Convert weights to volumes
wts = [1350 420 500 370 92 22]'; % http://faculty.washington.edu/chudler/facts.html
vols = [1298 337 383 407 79 23]'; %rilling & insel, 1999
figure;
subplot(1,2,1); pwt = allometric_regression(vols, wts); hold on; title('vol vs wt');
subplot(1,2,2); pvol = allom... |
function [ V, theta, eps_all, time, convergence ] = f_SE_NR_algorithm_v2017 ( V, theta, topo, Y_bus, z, W, Wsqrt, ...
ind_meas, N_meas, eps_tol, Max_iter, H_decoupled, H_sparse, linsolver )
%**************************************************************************
%DESCRIPTION OF FUNCTION (VERSION 2017)
%*****... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Author : Sandeep Manandhar
% University of Burgundym France
% MSCV6
% Radon Transform
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% inputs:
% image
% minimum value for angle
% maximum value for angle
% toggle guides and axis
... |
v1 = input('a aracın hızı kaç:');
v2 = input('b aracaın hızı kaç:');
uzunluk = input('A ile B şehirleri arasındaki mesafe ne kadar:');
%%maximum süre şimdilik 10 olsun
for t=0 : 10
if v1*t < uzunluk
fprintf ('saat %d :',t);
fprintf('a aracının konumu %d \n' ,v1*t);
elseif v1*t == uzunluk
... |
function [ model ] = randomSampling( X, y)
[~,k] = size(y);
[n,d] = size(X);
%Find the cumulative distribution function.
p(1) = (sum(X(1,:) == 1) + sum(X(2:n,d) == 1))/(n+d);
for i = 2:k-1
p(i) = p(i-1) + (sum(X(1,:) == i) + sum(X(2:n,d) == i))/(n+d-1);
end
p(k) = 1;
model.p = p;
model.k = k;
model.predict = @(mo... |
function y = clasifi1(net)
if (net >= 0)
y = 1;
else
y = -1;
end
return
|
close all;
clearvars;
clc;
% m is unique for everyone
% find addend such that specs are met by looking at plot
% remove semicolon to see the value printed
% Specs
m = 74;
q_m = floor(0.1*m);
r_m = m - 10*q_m;
BL = 25+1.7*q_m + 6.1*r_m;
BH = BL + 20;
trans_bw = 4*10^3;
% Band Edge specifications
fs1 = BL*10^3-trans_b... |
b0 = 1.70710;
b1 = [1 -1*exp(1i*(pi/4))];
b2 = [1 -1*exp(-1i*(pi/4))];
a1 = [1 0];
a2 = [1 0];
b = b0*conv(b1,b2);
a = conv(a1,a2);
fvtool(b,a)
[h,w] = freqz(b,a,'whole',2001);
disp(w);
figure;
subplot(2,1,1);
plot(1:2001,20*log10(abs(h)))
title('FIR')
xlabel('Frequency')
ylabel('Magnitude (dB)')
subplot(2,1,2);
plot... |
function oo = study(o,varargin) % Do Some Studies
%
% STUDY Several studies
%
% oo = study(o,'Menu') % setup study menu
%
% oo = study(o,'Study1') % raw signal
% oo = study(o,'Study2') % raw & filtered signal
% oo = study(o,'Study3') % filtered
% oo = study(o,'Stud... |
%This file was created as a templete for MSE 429 Advanced Kinematics of
%Robotics Systems at SFU
%
%Created by Flavio Firmani, Fall 2020
%1. INITIALIZATION (NO CHANGES ARE NECESSARY except for section 1.3)
%clear variables and close figures
clc; clear all; close all;
%1.1. Define size of figure and create ... |
noOfFlights = 9;
noOfDimentions = 3;
goal = zeros(noOfFlights,noOfDimentions);
for i = 1:noOfFlights
goal(i,:) = floor(rand(1,3)*10)*100;
end
goalOrigin = goal;
goalSortedByX = sortrows(goal,1);
plot3(goalSortedByX(:,1),goalSortedByX(:,2),goalSortedByX(:,3),'o')
hold on
plot3(goalSortedByX(:,1),goalSortedByX(:,2)... |
% IndividualDifferences.m
%
% Runs a battery of measures of individual differences in cognitive &
% psycholinguistic abilities.
%
% How to use the battery:
% 1) First, use File->Save As... to save a COPY of this file and call it
% something like YourProjectName.m . Then, just edit this COPY so you
% can leav... |
function [ F10 ] = function_F10( alpha )
%FUNCTION_F10 Summary of this function goes here
% Detailed explanation goes here
j = sqrt(-1);
J0 = besselj(0,alpha*(j)^(3/2));
J1 = besselj(1,alpha*(j)^(3/2));
F10 = (2*J1)/((alpha*(j)^(3/2))*J0);
end
|
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