plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | deisseroth-lab/multifiber-master | plotLogFile.m | .m | multifiber-master/plotLogFile.m | 559 | utf_8 | 286eefebbc8bf5065702c5693e99fd10 | % Plot a given .csv log file.
% Returns the timestamps and data.
function [time, data_AI] = plotLogFile(filename, prompt_user)
if nargin ~= 1
if nargin > 1 && prompt_user
[name, path] = uigetfile([filename '/*.csv']);
else
[name, path] = uigetfile('*.csv');
end
if length(path) == 1
... |
github | deisseroth-lab/multifiber-master | logAIData.m | .m | multifiber-master/logAIData.m | 548 | utf_8 | ba4d9832f7ec75268663129f22549376 | % Example callback function for analog input logging.
% This funcion is called once the number of acquired time points exceeds
% src.NotifyWhenDataAvailableExceeds.
% The latest analog input data will be written to the log .csv file.
% Use plotLogFile() to view the logged data.
function logAIData(src, event, filename... |
github | deisseroth-lab/multifiber-master | fipgui.m | .m | multifiber-master/fipgui.m | 40,706 | utf_8 | 6868a4c8aa118135f819598c77fb3d38 | function varargout = fipgui(varargin)
% FIPGUI MATLAB code for fipgui.fig
% FIPGUI, by itself, creates a new FIPGUI or raises the existing
% singleton*.
%
% H = FIPGUI returns the handle to a new FIPGUI or the handle to
% the existing singleton*.
%
% FIPGUI('CALLBACK',hObject,eventData,handles,... |
github | deisseroth-lab/multifiber-master | sample_generate_ao_waveform_stim.m | .m | multifiber-master/sample_scripts/sample_generate_ao_waveform_stim.m | 1,865 | utf_8 | 9f74f1f7c9d20b3c9d2e0baa2a56ae0d | % This produces an analog output waveform .mat for generating a single
% stimulation pulse train with a particular duty cycle.p on all channels.
% An analog output waveform .mat file must contain two variables:
% rate - int. samples per second, must match handles.s.Rate
% waveform - (N x 4) vector of voltage valu... |
github | deisseroth-lab/multifiber-master | sample_callback.m | .m | multifiber-master/sample_scripts/sample_callback.m | 670 | utf_8 | 15990c40241d429979988a3fbecd7c1a | % Sample callback function for real-time processing of signal data.
% data - double. new single data point
% channel - string. channel corresponding to the data point. a value of
% "test" is used to ensure the callback works.
function sample_callback(data, channel)
figure(5);
if strcmp(channel,'signal')
sub... |
github | deisseroth-lab/multifiber-master | subGuiTest.m | .m | multifiber-master/tests/subGuiTest.m | 3,691 | utf_8 | ffd92c1dd2fcf42d98081abcf1d04704 | function varargout = subGuiTest(varargin)
% SUBGUITEST MATLAB code for subGuiTest.fig
% SUBGUITEST, by itself, creates a new SUBGUITEST or raises the existing
% singleton*.
%
% H = SUBGUITEST returns the handle to a new SUBGUITEST or the handle to
% the existing singleton*.
%
% SUBGUITEST('CALL... |
github | Steve132/uraster-master | hackraster_interp.m | .m | uraster-master/mex/hackraster_interp.m | 507 | utf_8 | c1a26e7509cb5e5e01e9d1eab239302e | %interpolates 3D attributes according to the underlying barycentric coordinate
function [im]=hackraster_interp(vertmap,barymap,attributes)
im=zeros([size(vertmap,1),size(vertmap,2),size(attributes,1)]);
for k=1:size(attributes,1);
attr=attributes(k,:)';
attrim=zeros([size(vertmap,1),size(vertmap,2)]);
for dex=... |
github | Steve132/uraster-master | hackraster.m | .m | uraster-master/mex/hackraster.m | 2,483 | utf_8 | d5eeb2b7b545b99251f4de718bda9f58 | %hackraster:
%outputs:
% facemap: w x h x 1 int32 image such that each pixel contains the index of the face that it was taken from
% barymap: w x h x 3 float image such that each pixel contains the barycentric coordinate (0,1) of the linear interpolation of each vertex
% vertmap: w x h x 3 int32 image such that each ... |
github | sherna90/tracking-master | gen_cpp_cn.m | .m | tracking-master/src/libs/cn/gen_cpp_cn.m | 742 | utf_8 | adee622d3ea282fada96733d7e7d60da | % Matlab function which generates a c++ header that provides data for Color Names features
% color names data taken from https://github.com/ihpdep/samf
function gen_cpp_cn()
%load w2crs variable 32768x10
load w2crs.mat
fid = fopen('cn_data.cpp', 'w');
fprintf(fid, '#include "cnfeat.hpp" \n\n');
... |
github | lakid/libaria-master | example.m | .m | libaria-master/ArNetworking/matlab/example.m | 822 | utf_8 | 35fd48fa17fc50a815c2bce2c005b3ff |
function example
cleanupobj = onCleanup(@cleanup)
arnetc_init
c = arnetc_connect('localhost');
if c == 0
return
end
arnetc_request(c, 'gotoGoal', 'Hallway 2')
ru = arnetc_new_robot_update_handler(c);
while (true)
m = arnetc_robot_update_get_mode(ru);
... |
github | oyx15/semi-supervised-learning-master | INys_MDS.m | .m | semi-supervised-learning-master/lib/Improved_Nystrom_Method/INys_MDS.m | 974 | utf_8 | 10c6165d3a156712a616366b47e6b378 | % INys_MDS.m implments the multidimensional scaling using the improved nystrom
% low rank approximation.
%Input:
% data: n-by-dim data matrix;
% m: number of landmark points;
%Output:
% X: n-by-m embedding results.
function X = INys_MDS(data, m);
[n,dim] = size(data);
[idx, center, m] = eff_kmeans(data, m, 5); %#it... |
github | oyx15/semi-supervised-learning-master | INys_SpectrEmbed.m | .m | semi-supervised-learning-master/lib/Improved_Nystrom_Method/INys_SpectrEmbed.m | 1,731 | utf_8 | e9c25b020fc65cafee3b7d431ff6b287 | % Improved Nystrom method for Spectral Embedding
% This function implements the improved Nystrom method in <Improved Nystrom
% Low Rank Approximation and Error Analysis>, which can be used for Laplacian
% Eigenmap, Spectral Clustering, or Normalized cut.
% Input:
% data: n-by-dim data matrix;
% kernel: a struct with ... |
github | oyx15/semi-supervised-learning-master | INys_KPCA.m | .m | semi-supervised-learning-master/lib/Improved_Nystrom_Method/INys_KPCA.m | 1,348 | utf_8 | 6774b3e50fd7b00188da91657a391c8e | % Improved Nystrom method for Kernel PCA
% This function implements the improved Nystrom method in <Improved Nystrom
% Low Rank Approximation and Error Analysis>, which is used for Kernel PCA.
% Input:
% data: n-by-dim data matrix;
% kernel: a struct with two elements;
% kernel.type: 'pol' or 'rbf';
% ... |
github | oyx15/semi-supervised-learning-master | INys.m | .m | semi-supervised-learning-master/lib/Improved_Nystrom_Method/INys.m | 1,059 | utf_8 | 999c9fc42d135fd59b43b56337ed7171 | % INys.m implments the improved nystrom low-rank approximation method in
% <Improved Nystrom low-rank Approximation and Error Analysis> by Zhang and
% Kwok, ICML 2008
%Input:
% data: n-by-dim data matrix;
% m: number of landmark points;
% kernel: (struct) kernel type and parameter
% s: 'r' for random sampling and 'k' ... |
github | oyx15/semi-supervised-learning-master | getLabelMatrixY.m | .m | semi-supervised-learning-master/src/util/getLabelMatrixY.m | 373 | utf_8 | b8f614035172119346bcd66fb64f462b | %%Function to get the Y matrix
function [Y] = getLabelMatrixY(mapTraining, c)
%get all the classes for the training set
%get the size of the training set
N_samples = numel(mapTraining);
%build Y matrix with the coressponding size
Y = zeros(N_samples, c);
for label=1:c
labelLocation = (mapTraining == label);
... |
github | oyx15/semi-supervised-learning-master | getSubwindowData.m | .m | semi-supervised-learning-master/src/util/getSubwindowData.m | 2,867 | utf_8 | 823e60a2ede38288d121b2362f034f5b | %%Function to get the matrix
function [X, newX, newY] = getSubwindowData(mapTraining, img, window)
%MATRIX Gets X-matrix and Y-matrix for parts (windows) of the whole image.
% This function allows the selection of a small window of the whole image
% and work on that part. At the same time the number of training samples... |
github | oyx15/semi-supervised-learning-master | getSpatialXs.m | .m | semi-supervised-learning-master/src/internal/getSpatialXs.m | 256 | utf_8 | 16e1fb39775bcff3a7c017d9f4b1bbb9 | %% function to get the spatial xs
function [Xs] = getSpatialXs(img) %use the original image hsi
[a,b,c]= size(img);
Xs = zeros(a,b,c);
A = zeros(a,b);
B = ones(3,3)/9;
for i = 1:c
A = img(:,:,i);
C = conv2(A,B,'same');
Xs(:,:,i) = C(:,:);
end
end |
github | oyx15/semi-supervised-learning-master | randomizedSetsClassistClassifier.m | .m | semi-supervised-learning-master/src/classifier/randomizedSetsClassistClassifier.m | 2,517 | utf_8 | 80fcb6d072c69e71c44f87cfe5a69e5f | function [ predictedLabels, F_star ] = randomizedSetsClassistClassifier( hsi, mapTrain, testSamplesIDX, alpha, sigma, nystroemFraction, RSVD, sectionSize )
%CLASSISTCLASSIFIER CLassification only with samples provided by training
%set (with labels) and test set (without labels).
% Idea: In the given image `hsi`, "bla... |
github | JusteRaimbault/CityNetwork-master | vertexpositions.m | .m | CityNetwork-master/Models/Utils/Matlab/pmfg/vertexpositions.m | 3,753 | utf_8 | f22878ece30ed9e81351e9b63019040b | % [xyz]=vertexpositions(A,d)
% find the coordinates to display a network defined by the NxN adjacency matrix A
% d is the space dimensionality (2 or 3 normally)
% [xyz]=vertexpositions(A,d,vertexList)
% vertexList is the oriented list of vertices -if d=3 and if the network embedding is known it should be empty otherwi... |
github | JusteRaimbault/CityNetwork-master | pmfg.m | .m | CityNetwork-master/Models/Utils/Matlab/pmfg/pmfg.m | 3,326 | utf_8 | 8e2646e87e8f2fa2bcca77213c5ad665 | % calculates the PMFG graph from a matrix of weights W (typically a similarity measure, e.g. correlations)
% PMFG = doPMFG(W) returns the palnar maximally filtered graph (PMFG)
% PMFG is a sparse matrix with PMFG(i,j)=W(i,j) if the edge i-j is present
% and PMFG(i,j)=0 if not
% W must be sparse, real, square ... |
github | JusteRaimbault/CityNetwork-master | drawPMFG3.m | .m | CityNetwork-master/Models/Utils/Matlab/pmfg/drawPMFG3.m | 2,291 | utf_8 | 05e7ad1b2ef6557e0417a4727a3b0ea2 | % [xyz,uniqueTri]=drawPMFG3(A,labels)
% demo on how to draw the PMFG graph in three dimensions
% A is the PMFG's adjacency matrix (output of pmfg)
% labels (optional) are the vertex labels to display
% xyz are the vetex coordinates
% uniqueTri is the ordered (planar embedding) list of vertices for each
% triangle in ... |
github | JusteRaimbault/CityNetwork-master | drawPMFG2.m | .m | CityNetwork-master/Models/Utils/Matlab/pmfg/drawPMFG2.m | 1,109 | utf_8 | c46368738ae68b674903a148493545f3 | % [xyz,uniqueTri]=drawPMFG2(A,labels)
% demo on how to draw the PMFG graph in two dimensions
% A is the PMFG's adjacency matrix (output of pmfg)
% labels (optional) are the vertex labels to display
% xyz are the vetex coordinates
% uniqueTri is the ordered (planar embedding) list of vertices for each
% triangle in th... |
github | peiy/ActiveLearning-master | calculateNMI.m | .m | ActiveLearning-master/relative comparison/clustering_evaluation/calculateNMI.m | 927 | utf_8 | 769c550a1bca6619a60fa17a65fcaa8f | function nmis=calculateNMI(classid, clusterids)
[instnum,runnum] = size(clusterids);
class1=formw(classid, 1, instnum);
classProb1=sum(class1)/instnum;
entr_class1 = sum(classProb1 .* log(classProb1));
nmis = zeros(1, runnum);
for i=1:runnum
class2=formw(clusterids(:,i), 1, instnum);
classProb2=sum(class2)/instnu... |
github | peiy/ActiveLearning-master | calculateNMI.m | .m | ActiveLearning-master/constraint clustering/clustering_evaluation/calculateNMI.m | 927 | utf_8 | 769c550a1bca6619a60fa17a65fcaa8f | function nmis=calculateNMI(classid, clusterids)
[instnum,runnum] = size(clusterids);
class1=formw(classid, 1, instnum);
classProb1=sum(class1)/instnum;
entr_class1 = sum(classProb1 .* log(classProb1));
nmis = zeros(1, runnum);
for i=1:runnum
class2=formw(clusterids(:,i), 1, instnum);
classProb2=sum(class2)/instnu... |
github | peiy/ActiveLearning-master | randomSelect.m | .m | ActiveLearning-master/constraint clustering/lib/randomSelect.m | 1,942 | utf_8 | 4e8c6f8415b327fa00139ab9a8b5d132 | function [pairs, neighbor] = randomSelect(data, numPair)
n = size (data, 1);
if (numPair > 0)
maxUni = n^2;
triNum = numPair;
pairs = zeros (numPair, 3);
count = 0;
while (triNum > 0)
vec = random('unid',maxUni,triNum,1);
vec = unique (vec);
vec = vec - 1;
if ~isempt... |
github | LeventhalLab/EphysToolbox-master | eegfilt.m | .m | EphysToolbox-master/eegfilt.m | 8,086 | utf_8 | bde1fb756fcf0a7a59ab5dea553a06d2 | % eegfilt() - (high|low|band)-pass filter data using two-way least-squares
% FIR filtering. Optionally uses the window method instead of
% least-squares. Multiple data channels and epochs supported.
% Requires the MATLAB Signal Processing Toolbox.
% Usage:
% >> [smoothdata] = ... |
github | LeventhalLab/EphysToolbox-master | plotSpikeRaster.m | .m | EphysToolbox-master/SpikeySpike/plotSpikeRaster.m | 22,200 | utf_8 | 86fbed9c512c19d4a114815566c36e52 | function [xPoints, yPoints] = plotSpikeRaster(spikes,varargin)
% PLOTSPIKERASTER Create raster plot from binary spike data or spike times
% Efficiently creates raster plots with formatting support. Faster than
% common implementations. Multiple plot types and parameters available!
% Look at Parameters section bel... |
github | LeventhalLab/EphysToolbox-master | getSpikeLocations.m | .m | EphysToolbox-master/SpikeySpike/getSpikeLocations.m | 7,384 | utf_8 | 869cb241644d6eb1dbb0fd6b07985837 | function allLocs = getSpikeLocations(data,validMask,Fs,varargin)
% data = nCh x nSamples
% allLocs = 1 x nLocs, in samples
onlyGoing = 'none';
windowSize = round(Fs/2400); %snle
snlePeriod = round(Fs/8000); %snle
minpeakdist = Fs/1000; %hardcoded deadtime
threshGain = 15;
for iarg = ... |
github | LeventhalLab/EphysToolbox-master | getSpikeLocationsAmpThresh.m | .m | EphysToolbox-master/SpikeySpike/getSpikeLocationsAmpThresh.m | 9,268 | utf_8 | 233b12209c85781cd85b18e1ded28082 | function allLocs = getSpikeLocationsAmpThresh(data,validMask,Fs,rawData,varargin)
% data = nCh x nSamples
% allLocs = 1 x nLocs, in samples
onlyGoing = 'none';
windowSize = round(Fs/2400); %snle
snlePeriod = round(Fs/8000); %snle
minpeakdist = 40; %hardcoded deadtime
threshGain = 15;
... |
github | LeventhalLab/EphysToolbox-master | simpleFFT.m | .m | EphysToolbox-master/SpikeySpike/simpleFFT.m | 952 | utf_8 | 26a60fa036f9650a259e7b25d06008d5 | function [A,f] = simpleFFT(data,Fs,varargin)
p = inputParser;
addOptional(p,'newFig',true,@islogical);
addOptional(p,'nSmooth',10,@isscalar);
parse(p,varargin{:});
inputs = p.Results;
if size(data,1) > 1
allA = [];
for ii=1:size(data)
[A,f] = getFFT(data(ii,:),Fs);
... |
github | LeventhalLab/EphysToolbox-master | TDTfilter.m | .m | EphysToolbox-master/TDTScripts/TDT2matExamples/TDTfilter.m | 12,671 | utf_8 | 8856c62dfb516f0d03094f43eeb45588 | function data = TDTfilter(data, epoc, varargin)
%TDTFILTER TDT tank data filter.
% data = TDTfilter(DATA, EPOC, 'parameter', value, ...), where DATA is
% the output of TDT2mat, EPOC is the name of the epoc to filter on,
% and parameter value pairs define the filtering conditions
%
% also create data.filt... |
github | LeventhalLab/EphysToolbox-master | sev_quick_read.m | .m | EphysToolbox-master/TDTScripts/TDT2matExamples/sev_quick_read.m | 1,715 | utf_8 | c276a10b8661f5c84bf57582ef9b5304 | function data = sev_quick_read(name, fmt, varargin)
%SEV_QUICK_READ bare SEV file extraction.
% data = sev_quick_read(NAME, FMT) where NAME and FMT are strings. If
% NAME is a directory, retrieves all sev data from directory NAME in
% format FMT. Each SEV file array is returned in one cell of the
% ret... |
github | LeventhalLab/EphysToolbox-master | TTIcallback.m | .m | EphysToolbox-master/TDTScripts/TTankInterfacesExamples/TTIcallback.m | 2,134 | utf_8 | 0ea5f91253ce206067e8ea3528eb97a2 | % handles all callbacks for TTImain
% there is usually no need to modify this
function TTIcallback(varargin)
% control handles
global hTTITank;
global hTTIBlock;
global hTTIEvent;
global hLabel;
% variables to hold current selections
global CurrentServer;
global CurrentTank;
global CurrentBlock;
global ... |
github | LeventhalLab/EphysToolbox-master | RunAnalysis.m | .m | EphysToolbox-master/TDTScripts/TTankInterfacesExamples/RunAnalysis.m | 307 | utf_8 | 0a22dec8bf1611014ca8ce278cbd083e | % This is the analysis function called by the TTI 'Run Analysis' button
function RunAnalysis()
global CurrentServer;
global CurrentTank;
global CurrentBlock;
global CurrentEvent;
global data;
disp('RunAnalysis')
data = TDT2mat(CurrentTank, CurrentBlock);
end |
github | LeventhalLab/EphysToolbox-master | ddt_write_v2.m | .m | EphysToolbox-master/RHD/ddt_write_v2.m | 827 | utf_8 | 8e84ea11a6d525fae12835a4e80280d7 | %.m to .ddt
function [errCode] = ddt_write_v2(filename, nch, npoints, freq, d)
% ddt_write_v(filename, nch, npoints, freq, d) Write data to a .ddt file
%
% [errCode] = ddt_write_v(filename, nch, npoints, freq, d)
%
% INPUT:
% filename - if empty string, will use File Open dialog
% nch - number of channels
% np... |
github | LeventhalLab/EphysToolbox-master | read_Intan_RHD2000_file.m | .m | EphysToolbox-master/RHD/read_Intan_RHD2000_file.m | 23,843 | utf_8 | caffbc7733473a1637e33692c337acb1 | function read_Intan_RHD2000_file(varargin)
% read_Intan_RHD2000_file
%
% Version 2.0, 20 October 2016
%
% Reads Intan Technologies RHD2000 data file generated by evaluation board
% GUI or Intan Recording Controller. Data are parsed and placed into
% variables that appear in the base MATLAB workspace. Therefo... |
github | LeventhalLab/EphysToolbox-master | read_Intan_RHD2000_file_LARGE.m | .m | EphysToolbox-master/RHD/read_Intan_RHD2000_file_LARGE.m | 23,745 | utf_8 | f5ab4fc30f2b8bbd2db20992782c7f84 | function read_Intan_RHD2000_file_LARGE(varargin)
% read_Intan_RHD2000_file
%
% Version 2.0, 20 October 2016
%
% Reads Intan Technologies RHD2000 data file generated by evaluation board
% GUI or Intan Recording Controller. Data are parsed and placed into
% variables that appear in the base MATLAB workspace. Therefore... |
github | LeventhalLab/EphysToolbox-master | dir2.m | .m | EphysToolbox-master/BackrUpr/Helpers/dir2/dir2.m | 5,346 | utf_8 | 1a964a0a4496406ca0b5dd145c47d972 | function dout = dir2(dn,varargin)
%DIR2 List directory.
% DIR2('directory_name') lists the files in a directory. Pathnames and
% wildcards may be used. For example, DIR *.m lists all program files
% in the current directory.
%
% DIR2('directory_name','-r') Lists the files in a directory, and it's
% su... |
github | LeventhalLab/EphysToolbox-master | specscope.m | .m | EphysToolbox-master/chronux/spectral_analysis/specscope/specscope.m | 19,600 | utf_8 | 7a80433446556a39374dc808670147c4 | function outdata=specscope(indata)
% record and plot audio spectrogram
%
% Usage: outdata=specscope(indata)
%
% Input: indata (optional)
% Displays a recorded piece of data, if an argument is passed
% Otherwise displays audio data from an attached microphone
%
% Output: outdata (optional)
% If pres... |
github | LeventhalLab/EphysToolbox-master | rtf.m | .m | EphysToolbox-master/chronux/spectral_analysis/specscope/rtf.m | 5,158 | utf_8 | ef3f23be6203e99d6a822c63a1d42b6d | function rtf(plot_frq,flag_save)
close all
evalin('base','stop=0;');
%=========SET THE BASIC FIGURE=================
fig = figure('Position',[500,500,800,600],...
'NumberTitle','off',...
'Name','Scope',...
'doublebuffer','on',...
'HandleVisibility','on',...
'Ke... |
github | LeventhalLab/EphysToolbox-master | specscopepp.m | .m | EphysToolbox-master/chronux/spectral_analysis/specscope/specscopepp.m | 20,341 | utf_8 | d9fe57a8dd870b4a1832ba73ec208a29 | function outdata=specscopepp(indata)
global acq;
h=hamming(5);
mins=5e-008;
maxs=1e-004;
% record and plot audio spectrogram
%
% Usage: outdata=specscope(indata)
%
% Input: indata (optional)
% Displays a recorded piece of data, if an argument is passed
% Otherwise displays audio data from an att... |
github | LeventhalLab/EphysToolbox-master | lfgui.m | .m | EphysToolbox-master/chronux/locfit/m/lfgui.m | 4,018 | utf_8 | 3b6eace9dc5a0057fb2c8b221751aa6d | function varargout = lfgui(varargin)
% LFGUI M-file for lfgui.fig
% LFGUI, by itself, creates a new LFGUI or raises the existing
% singleton*.
%
% H = LFGUI returns the handle to a new LFGUI or the handle to
% the existing singleton*.
%
% LFGUI('CALLBACK',hObject,eventData,handles,...) calls th... |
github | LeventhalLab/EphysToolbox-master | auto_classify.m | .m | EphysToolbox-master/chronux/wave_browser/auto_classify.m | 25,074 | utf_8 | ba0678a9e6434290035fdb708a1d8009 | function varargout = auto_classify(varargin)
% AUTO_CLASSIFY M-file for auto_classify.fig
% AUTO_CLASSIFY, by itself, creates a new AUTO_CLASSIFY or raises the existing
% singleton*.
%
% H = AUTO_CLASSIFY returns the handle to a new AUTO_CLASSIFY or the handle to
% the existing singleton*.
%
... |
github | LeventhalLab/EphysToolbox-master | wave_browser.m | .m | EphysToolbox-master/chronux/wave_browser/wave_browser.m | 57,029 | utf_8 | 2587b6831317c05fd90c35f38a964c93 | function varargout = wave_browser(varargin)
% WAVE_BROWSER M-file for wave_browser.fig
% WAVE_BROWSER, by itself, creates a new WAVE_BROWSER or raises the existing
% singleton*.
%
% H = WAVE_BROWSER returns the handle to a new WAVE_BROWSER or the handle to
% the existing singleton*.
%
% ... |
github | LeventhalLab/EphysToolbox-master | classify_spectra.m | .m | EphysToolbox-master/chronux/wave_browser/classify_spectra.m | 108,297 | utf_8 | 93fe2f22d145ba63cb667b18b3b33d0d | function varargout = classify_spectra(varargin)
% CLASSIFY_SPECTRA M-file for classify_spectra.fig
% CLASSIFY_SPECTRA, by itself, creates a new CLASSIFY_SPECTRA or raises the existing
% singleton*.
%
% H = CLASSIFY_SPECTRA returns the handle to a new CLASSIFY_SPECTRA or
% the handle to
% the ex... |
github | LeventhalLab/EphysToolbox-master | configure_classify.m | .m | EphysToolbox-master/chronux/wave_browser/configure_classify.m | 17,864 | utf_8 | d66bfd4213ddebc5ac867dcafec8703a | function varargout = configure_classify(varargin)
% CONFIGURE_CLASSIFY M-file for configure_classify.fig
% CONFIGURE_CLASSIFY, by itself, creates a new CONFIGURE_CLASSIFY or raises the existing
% singleton*.
%
% H = CONFIGURE_CLASSIFY returns the handle to a new CONFIGURE_CLASSIFY or the handle to
... |
github | LeventhalLab/EphysToolbox-master | FAnalyze.m | .m | EphysToolbox-master/chronux/fly_track/FAnalyze/functions/FAnalyze.m | 28,275 | utf_8 | 00157164be68669eaae8ee557d8f0e27 | function varargout = FAnalyze(varargin)
% FANALYZE
% For all your trajectory analysis needs! . See documentation for usage details.
%Written by Dan Valente
%November 2007
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui... |
github | LeventhalLab/EphysToolbox-master | videoReader.m | .m | EphysToolbox-master/chronux/fly_track/videoIO/videoIO_2006b/@videoReader/videoReader.m | 5,758 | utf_8 | 66a56561d4e6c547cf2bac07861a94f6 | function vr = videoReader(url, varargin)
% videoReader class constructor
% Creates a object that reads video streams. We use a plugin
% architecture in the backend to do the actual reading. For example,
% on Windows, DirectShow will typically be used and on Linux, the
% ffmpeg library is often used.
... |
github | LeventhalLab/EphysToolbox-master | videoWriter.m | .m | EphysToolbox-master/chronux/fly_track/videoIO/videoIO_2006b/@videoWriter/videoWriter.m | 11,485 | utf_8 | 0869234180baa12b3217c3ac04df67ed | function vw = videoWriter(url, varargin)
% videoWriter class constructor
% Creates a object that writes video files. We use a plugin
% architecture in the backend to do the actual writing. For example,
% on Windows, DirectShow will typically be used and on Linux, the
% ffmpeg library is often used.
%... |
github | LeventhalLab/EphysToolbox-master | videoReader.m | .m | EphysToolbox-master/chronux/fly_track/videoIO/videoIO_2006a/@videoReader/videoReader.m | 5,758 | utf_8 | 66a56561d4e6c547cf2bac07861a94f6 | function vr = videoReader(url, varargin)
% videoReader class constructor
% Creates a object that reads video streams. We use a plugin
% architecture in the backend to do the actual reading. For example,
% on Windows, DirectShow will typically be used and on Linux, the
% ffmpeg library is often used.
... |
github | LeventhalLab/EphysToolbox-master | videoWriter.m | .m | EphysToolbox-master/chronux/fly_track/videoIO/videoIO_2006a/@videoWriter/videoWriter.m | 11,485 | utf_8 | 0869234180baa12b3217c3ac04df67ed | function vw = videoWriter(url, varargin)
% videoWriter class constructor
% Creates a object that writes video files. We use a plugin
% architecture in the backend to do the actual writing. For example,
% on Windows, DirectShow will typically be used and on Linux, the
% ffmpeg library is often used.
%... |
github | LeventhalLab/EphysToolbox-master | videoReader.m | .m | EphysToolbox-master/chronux/fly_track/videoIO/videoIO_2007a/@videoReader/videoReader.m | 5,758 | utf_8 | 66a56561d4e6c547cf2bac07861a94f6 | function vr = videoReader(url, varargin)
% videoReader class constructor
% Creates a object that reads video streams. We use a plugin
% architecture in the backend to do the actual reading. For example,
% on Windows, DirectShow will typically be used and on Linux, the
% ffmpeg library is often used.
... |
github | LeventhalLab/EphysToolbox-master | videoWriter.m | .m | EphysToolbox-master/chronux/fly_track/videoIO/videoIO_2007a/@videoWriter/videoWriter.m | 11,485 | utf_8 | 0869234180baa12b3217c3ac04df67ed | function vw = videoWriter(url, varargin)
% videoWriter class constructor
% Creates a object that writes video files. We use a plugin
% architecture in the backend to do the actual writing. For example,
% on Windows, DirectShow will typically be used and on Linux, the
% ffmpeg library is often used.
%... |
github | LeventhalLab/EphysToolbox-master | FTrack.m | .m | EphysToolbox-master/chronux/fly_track/FTrack/functions/FTrack.m | 20,317 | utf_8 | ec3ca4a2695761e114cd56210fe3ac51 | function varargout = FTrack(varargin)
% FTRACK
% For all your fly-tracking needs! . See documentation for usage details.
% Last Modified by GUIDE v2.5 26-Nov-2007 18:07:29
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui... |
github | LeventhalLab/EphysToolbox-master | extract_PLXtimestamps_sincInterp.m | .m | EphysToolbox-master/MatlabSpikeworks/extract_PLXtimestamps_sincInterp.m | 17,552 | utf_8 | 42e5ec3dd4a443a811539ffbfe8be34e | function extract_PLXtimestamps_sincInterp( hsdFile, targetDir, wireList, thresholds, varargin )
%
% usage: extract_timestamps( hsdFile, wireList, thresholds, varargin )
%
% INPUTS:
% hsdFile - string containing the name of the .hsd file (include the full
% path)
% targetDir - directory in which to save the .n... |
github | LeventhalLab/EphysToolbox-master | wavefilter.m | .m | EphysToolbox-master/MatlabSpikeworks/wavefilter.m | 1,525 | utf_8 | 17460583060e078e9e2a55be70fe8884 | % Matlab code for wavelet filtering.
% This function requires the Wavelet Toolbox.
function fdata = wavefilter(data, maxlevel, varargin)
%
% usage: fdata = wavefilter(data, maxlevel, varargin)
%
% INPUTS:
% data - an N x M array of continuously-recorded raw data
% where N is the number of channels, each containing ... |
github | LeventhalLab/EphysToolbox-master | extract_timestamps_sincInterp.m | .m | EphysToolbox-master/MatlabSpikeworks/extract_timestamps_sincInterp.m | 17,308 | utf_8 | 6b22de35ae52d19f4d2a101564bf62b0 | function extract_timestamps_sincInterp( hsdFile, targetDir, wireList, thresholds, varargin )
%
% usage: extract_timestamps( hsdFile, wireList, thresholds, varargin )
%
% INPUTS:
% hsdFile - string containing the name of the .hsd file (include the full
% path)
% targetDir - directory in which to save the .nex ... |
github | LeventhalLab/EphysToolbox-master | extract_timestamps.m | .m | EphysToolbox-master/MatlabSpikeworks/extract_timestamps.m | 9,920 | utf_8 | 94a7a857abb72998a8c22b72b4b3cba4 | function extract_timestamps( hsdFile, targetDir, wireList, thresholds, varargin )
%
% usage: extract_timestamps( hsdFile, wireList, thresholds, varargin )
%
% INPUTS:
% hsdFile - string containing the name of the .hsd file (include the full
% path)
% targetDir - directory in which to save the .nex file
% wi... |
github | marknabil/PCA_FaceRecognition-master | ImageNormalization.m | .m | PCA_FaceRecognition-master/ImageNormalization.m | 1,219 | utf_8 | fcee3431614125a9004ceecdd1b5e6d0 | %% normalization of images function
function [Ifinal] = ImageNormalization(Io, Fbar, Fimg)
I = rgb2gray(Io);
%% affine transformation and its six parameters
Ab = pinv([Fimg, [1; 1; 1; 1; 1]]) * Fbar;
A = Ab(1: 2, :);
b = Ab(3, :);
A = A';
b = b';
%% getting the output normal... |
github | marknabil/PCA_FaceRecognition-master | gui.m | .m | PCA_FaceRecognition-master/gui.m | 7,091 | utf_8 | 67b56bb9b93c7f1eaa9d0e3939ab0114 | function varargout = gui(varargin)
% GUI MATLAB code for gui.fig
% GUI, by itself, creates a new GUI or raises the existing
% singleton*.
%
% H = GUI returns the handle to a new GUI or the handle to
% the existing singleton*.
%
% GUI('CALLBACK',hObject,eventData,handles,...) calls the local
% ... |
github | petercorke/toolbox-common-matlab-master | protectfig.m | .m | toolbox-common-matlab-master/protectfig.m | 881 | utf_8 | 02ea9bf0328e3371f877b1e9e1b5be6d |
% Copyright (C) 1993-2017, by Peter I. Corke
%
% This file is part of The Robotics Toolbox for MATLAB (RTB).
%
% RTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Foundation, either version 3 of the License, o... |
github | petercorke/toolbox-common-matlab-master | Polygon.m | .m | toolbox-common-matlab-master/Polygon.m | 44,407 | utf_8 | 0f8730e021e78210d0e8ae7ff334f5e9 | %POLYGON Polygon class
%
% A general class for manipulating polygons and vectors of polygons.
%
% Methods::
% plot Plot polygon
% area Area of polygon
% moments Moments of polygon
% centroid Centroid of polygon
% perimeter Perimter of polygon
% transform Transform polygo... |
github | petercorke/toolbox-common-matlab-master | edgelist.m | .m | toolbox-common-matlab-master/edgelist.m | 4,737 | utf_8 | 3d7876f26f51a03f4c49328237250877 | %EDGELIST Return list of edge pixels for region
%
% EG = EDGELIST(IM, SEED) is a list of edge pixels (2xN) of a region in the
% image IM starting at edge coordinate SEED=[X,Y]. The edgelist has one column per
% edge point coordinate (x,y).
%
% EG = EDGELIST(IM, SEED, DIRECTION) as above, but the direction of edge
% ... |
github | petercorke/toolbox-common-matlab-master | diff2.m | .m | toolbox-common-matlab-master/diff2.m | 1,285 | utf_8 | d2018ea5bfa0dc51016c7c936df1b4d1 | %DIFF2 First-order difference
%
% D = DIFF2(V) is the first-order difference (1xN) of the series data in
% vector V (1xN) and the first element is zero.
%
% D = DIFF2(A) is the first-order difference (MxN) of the series data in
% each row of the matrix A (MxN) and the first element in each row is zero.
%
% Notes::
% ... |
github | petercorke/toolbox-common-matlab-master | rvccheck.m | .m | toolbox-common-matlab-master/rvccheck.m | 2,868 | utf_8 | 0a6c6a7bbb84d1de106fefff5323bd67 | function rvccheck(verbose)
if nargin == 0
verbose = true;
end
% display current versions of MATLAB
year = version('-release');
if verbose
fprintf('You are using:\n - MATLAB release %s\n', year);
end
% check how old it is
today = datevec(now);
age = tod... |
github | petercorke/toolbox-common-matlab-master | filt1d.m | .m | toolbox-common-matlab-master/filt1d.m | 2,048 | utf_8 | bc8104a2b86eb158bb26e4ed77ac7e0f | %FILT1D 1-dimensional rank filter
%
% Y = FILT1D(X, OPTIONS) is the minimum, maximum or median value (1xN) of the
% vector X (1xN) compute over an odd length sliding window.
%
% Options::
% 'max' Compute maximum value over the window (default)
% 'min' Compute minimum value over the window
% 'median' ... |
github | petercorke/toolbox-common-matlab-master | yaxis.m | .m | toolbox-common-matlab-master/yaxis.m | 1,310 | utf_8 | 0db9a465f805810b37b09d08336176c6 | %YAYIS set Y-axis scaling
%
% YAXIS(MAX) set y-axis scaling from 0 to MAX.
%
% YAXIS(MIN, MAX) set y-axis scaling from MIN to MAX.
%
% YAXIS([MIN MAX]) as above.
%
% YAXIS restore automatic scaling for y-axis.
%
% See also YAXIS.
% Copyright (C) 1993-2017, by Peter I. Corke
%
% This file is part of The Robotics Toolb... |
github | petercorke/toolbox-common-matlab-master | colorname.m | .m | toolbox-common-matlab-master/colorname.m | 5,777 | utf_8 | c7a519e639e1ff6b85516095712405d9 | %COLORNAME Map between color names and RGB values
%
% RGB = COLORNAME(NAME) is the RGB-tristimulus value (1x3) corresponding to
% the color specified by the string NAME. If RGB is a cell-array (1xN) of
% names then RGB is a matrix (Nx3) with each row being the corresponding
% tristimulus.
%
% XYZ = COLORNAME(NAME, 'xy... |
github | petercorke/toolbox-common-matlab-master | polydiff.m | .m | toolbox-common-matlab-master/polydiff.m | 1,119 | utf_8 | 3358d9e6a460f1a769fc034f0a00897f | %POLYDIFF Differentiate a polynomial
%
% PD = POLYDIFF(P) is a vector of coefficients of a polynomial (1xN-1) which is the
% derivative of the polynomial P (1xN).
%
% p = [3 2 -1];
% polydiff(p)
% ans =
% 6 2
%
% See also POLYVAL.
% Copyright (C) 1993-2017, by Peter I. Cork... |
github | petercorke/toolbox-common-matlab-master | randinit.m | .m | toolbox-common-matlab-master/randinit.m | 978 | utf_8 | 118aaf915c94e7df6953a8a937ba88f8 | %RANDINIT Reset random number generator
%
% RANDINIT resets the defaul random number stream.
%
% See also RandStream.
% Copyright (C) 1993-2017, by Peter I. Corke
%
% This file is part of The Robotics Toolbox for MATLAB (RTB).
%
% RTB is free software: you can redistribute it and/or modify
% it under the terms of th... |
github | petercorke/toolbox-common-matlab-master | xaxis.m | .m | toolbox-common-matlab-master/xaxis.m | 1,832 | utf_8 | aeb2d1ed8dcaf8d74d9cfff5546879cf | %XAXIS Set X-axis scaling
%
% XAXIS(MAX) set x-axis scaling from 0 to MAX.
%
% XAXIS(MIN, MAX) set x-axis scaling from MIN to MAX.
%
% XAXIS([MIN MAX]) as above.
%
% XAXIS restore automatic scaling for x-axis.
%
% See also YAXIS.
% Copyright (C) 1993-2017, by Peter I. Corke
%
% This file is part of The Robotics Tool... |
github | petercorke/toolbox-common-matlab-master | dockfigs.m | .m | toolbox-common-matlab-master/dockfigs.m | 1,180 | utf_8 | 55bce19340194193b60ce661b658894a | %DOCKFIGS Control figure docking in the GUI
%
% dockfigs causes all new figures to be docked into the GUI
%
% dockfigs(1) as above.
%
% dockfigs(0) causes all new figures to be undocked from the GUI
% Copyright (C) 1993-2017, by Peter I. Corke
%
% This file is part of The Robotics Toolbox for MATLAB (RTB).
%
% RTB ... |
github | petercorke/toolbox-common-matlab-master | usefig.m | .m | toolbox-common-matlab-master/usefig.m | 348 | utf_8 | c47f23a7a2dcad028e840e34500f5959 | %USEFIG Named figure windows
%
% usefig('Foo') makes figure 'Foo' the current figure, if it doesn't
% exist create it.
%
% h = usefig('Foo') as above, but returns the figure handle
function H = usefig(name)
h = findobj('Name', name);
if isempty(h),
h = figure;
set(h, 'Name', name);
else
figure(h);
end
if... |
github | petercorke/toolbox-common-matlab-master | circle.m | .m | toolbox-common-matlab-master/circle.m | 2,075 | utf_8 | 6a9dea8240a3f9b5329ef331aef61802 | %CIRCLE Compute points on a circle
%
% CIRCLE(C, R, OPTIONS) plots a circle centred at C (1x2) with radius R on the current
% axes.
%
% X = CIRCLE(C, R, OPTIONS) is a matrix (2xN) whose columns define the
% coordinates [x,y] of points around the circumferance of a circle
% centred at C (1x2) and of radius R.
%
% C is... |
github | petercorke/toolbox-common-matlab-master | stlRead.m | .m | toolbox-common-matlab-master/stlRead.m | 11,483 | utf_8 | 152f25d793763b55b15b646992987e02 | %STLREAD reads any STL file not depending on its format
%
% [v, f, n, name] = stlRead(fileName) reads the STL format file (ASCII or
% binary) and returns vertices V, faces F, normals N and NAME is the name
% of the STL object (NOT the name of the STL file).
%
% Authors::
% - from MATLAB File Exchange by Pau Mico... |
github | petercorke/toolbox-common-matlab-master | pickregion.m | .m | toolbox-common-matlab-master/pickregion.m | 3,137 | utf_8 | f282eb7d77ff4e8df065d73a0c7d9e37 | %PICKREGION Pick a rectangular region of a figure using mouse
%
% [p1,p2] = PICKREGION() initiates a rubberband box at the current click point
% and animates it so long as the mouse button remains down. Returns the first
% and last coordinates in axis units.
%
% Options::
% 'axis',A The axis to select from (defaul... |
github | petercorke/toolbox-common-matlab-master | mplot.m | .m | toolbox-common-matlab-master/mplot.m | 7,123 | utf_8 | 1b7af413e24c0753dcef8934378925e1 | %MPLOT Plot time-series data
%
% A convenience function for plotting time-series data held in a matrix.
% Each row is a timestep and the first column is time.
%
% MPLOT(Y, OPTIONS) plots the time series data Y(NxM) in multiple
% subplots. The first column is assumed to be time, so M-1 plots are
% produced.
%
% MPLOT(... |
github | petercorke/toolbox-common-matlab-master | runscript.m | .m | toolbox-common-matlab-master/runscript.m | 8,329 | utf_8 | 1a60ae9f2904735bde6dca3af52d4e0a | %RUNSCRIPT Run an M-file in interactive fashion
%
% RUNSCRIPT(SCRIPT, OPTIONS) runs the M-file SCRIPT and pauses after every
% executable line in the file until a key is pressed. Comment lines are shown
% without any delay between lines.
%
% Options::
% 'delay',D Don't wait for keypress, just delay of D seconds (de... |
github | petercorke/toolbox-common-matlab-master | rvcpath.m | .m | toolbox-common-matlab-master/rvcpath.m | 1,137 | utf_8 | f1b242a7ae5a23962546beba760c6ae1 | %RVCPATH Install location of RVC tools
%
% p = RVCPATH is the path of the top level folder for the installed RVC
% tools.
%
% p = RVCPATH(FOLDER) is the full path of the specified FOLDER which is relative to the
% installed RVC tools.
%
% Copyright (C) 1993-2017, by Peter I. Corke
%
% This file is part of The Robotics... |
github | petercorke/toolbox-common-matlab-master | mmlabel.m | .m | toolbox-common-matlab-master/mmlabel.m | 1,458 | utf_8 | 6bb8d41bb64488913bcc3a1ae684d829 | %MMLABEL labels for mplot style graph
%
% mmlabel({lab1 lab2 lab3})
%
% Notes::
% - was previously (rev 9) named mlabel() but changed to avoid clash with the
% Mapping Toolbox.
% Copyright (C) 1993-2017, by Peter I. Corke
%
% This file is part of The Robotics Toolbox for MATLAB (RTB).
%
% RTB is free software: you... |
github | petercorke/toolbox-common-matlab-master | plotp.m | .m | toolbox-common-matlab-master/plotp.m | 1,573 | utf_8 | 820ce5525622153db6f6a564377af983 | %PLOTP Plot trajectory
%
% Convenience function to plot points stored columnwise.
%
% PLOTP(P) plots a set of points P, which by Toolbox convention are stored
% one per column. P can be 2xN or 3xN. By default a linestyle of 'bx'
% is used.
%
% PLOTP(P, LS) as above but the line style arguments LS are passed to plot.
... |
github | petercorke/toolbox-common-matlab-master | mtools.m | .m | toolbox-common-matlab-master/mtools.m | 1,847 | utf_8 | bc44bea8453c76d09fb4f2c4fee81dbd | %MTOOLS add simple/useful tools to all windows in figure
%
% Copyright (C) 1993-2017, by Peter I. Corke
%
% This file is part of The Robotics Toolbox for MATLAB (RTB).
%
% RTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the F... |
github | petercorke/toolbox-common-matlab-master | bresenham.m | .m | toolbox-common-matlab-master/bresenham.m | 3,069 | utf_8 | 433dcd2346920722c37d9bbed814dbe8 | %BRESENHAM Generate a line
%
% P = BRESENHAM(X1, Y1, X2, Y2) is a list of integer coordinates (2xN) for
% points lying on the line segment joining the integer coordinates (X1,Y1)
% and (X2,Y2).
%
% P = BRESENHAM(P1, P2) as above but P1=[X1; Y1] and P2=[X2; Y2].
%
% Notes::
% - Endpoint coordinates must be integer value... |
github | petercorke/toolbox-common-matlab-master | gaussfunc.m | .m | toolbox-common-matlab-master/gaussfunc.m | 2,159 | utf_8 | ce83ce3f5a887482ea5ec66c52e5f2d7 | %GAUSSFUNC Gaussian kernel
%
% G = GAUSSFUNC(MEAN, VARIANCE, X) is the value of the normal
% distribution (Gaussian) function with MEAN (1x1) and VARIANCE (1x1), at
% the point X.
%
% G = GAUSSFUNC(MEAN, COVARIANCE, X, Y) is the value of the bivariate
% normal distribution (Gaussian) function with MEAN (1x2) and COVA... |
github | petercorke/toolbox-common-matlab-master | PluckerTest.m | .m | toolbox-common-matlab-master/unit_test/PluckerTest.m | 790 | utf_8 | 2ba1dac6e1882a015dc1371045aa13bd |
function tests = PluckerTest
tests = functiontests(localfunctions);
end
function constructor_test(tc)
end
function methods_test(tc)
% intersection
px = Plucker([0 0 0], [1 0 0]); % x-axis
py = Plucker([0 0 0], [0 1 0]); % y-axis
px1 = Plucker([0 1 0], [1 1 0]); % offset x-axis
verify... |
github | petercorke/toolbox-common-matlab-master | plotXTest.m | .m | toolbox-common-matlab-master/unit_test/plotXTest.m | 10,075 | utf_8 | 5e0c1a61709cdd8015d7777373ef326a | % 2d outline, filled case
% 3d outlien, filled case
% with LS or edgecolor, color options etc.
function tests = plotXTest
tests = functiontests(localfunctions);
close all
end
function teardownOnce(tc)
close all
end
function plotpoint_test(tc)
% simple
points = rand(2,5);
clf; plo... |
github | petercorke/toolbox-common-matlab-master | tboptparseTest.m | .m | toolbox-common-matlab-master/unit_test/tboptparseTest.m | 8,306 | utf_8 | 7663089541e7d9d2c91c64363ab51eb9 | function tests = tboptparseTest()
tests = functiontests(localfunctions);
end
function setupOnce(tc)
opt.foo = false;
opt.bar = true;
opt.blah = [];
opt.stuff = {};
opt.choose = {'this', 'that', 'other'};
opt.select = {'#no', '#yes'};
opt.old = '@foo';
opt.d_3d = false;
tc.TestData.opt = ... |
github | blueCFD/waves2Foam-master | cnoidalFirst.m | .m | waves2Foam-master/applications/utilities/misc/matlab/preprocessing/cnoidalFirst.m | 3,170 | utf_8 | c4a106f70447a3c23db45dd81d844143 | function cnoidalFirst(h, H, T, stream, g)
% cnoidal(h, H, T, g)
%
% Solves for the parameter "m" used in the elliptic integrals and the
% jacobian elliptic functions. Bi-section is used above Matlab's solvers,
% as the elliptic functions and integrals are undefined for m >= 1 and the
% solvers are not readily available... |
github | blueCFD/waves2Foam-master | StreamFunctionCoefficientsPeriod.m | .m | waves2Foam-master/applications/utilities/misc/matlab/preprocessing/StreamFunctionCoefficientsPeriod.m | 2,590 | utf_8 | 47882058131f399330328eff1a2a8e56 | function [eta, B, Q, c, k, R, uBar] = StreamFunctionCoefficientsPeriod(N,H,h,T,uEorS,EorS,nsteps,g)
% This implementation of the streamfunction follows David R. Fuhrman's
% lecture notes from the course 'Linear and non-linear wave theory' given
% at the Technical University of Denmark.
% Initial quess on wave number ... |
github | blueCFD/waves2Foam-master | processData.m | .m | waves2Foam-master/tutorials/waveFoam/bejiBattjes/matlab/processData.m | 1,945 | utf_8 | abcdffe317c7d8af1d202202ed6d63db | function processData( toolpath )
close all, clear all, clc
homeDir = pwd;
if nargin == 0
addpath(sprintf('%s/../../../../applications/utilities/misc/matlab/postprocessing',pwd));
else
addpath( toolpath );
end
%% Load the numerical simulation
cd ../surfaceElevation/
h = dir('0*');
cd ..
[time, x, y, z, eta]... |
github | blueCFD/waves2Foam-master | waveNumber5thOrderStokes.m | .m | waves2Foam-master/src/waves2Foam/waveTheories/regular/stokesFifth/waveNumber5thOrderStokes.m | 3,316 | utf_8 | 318f966d2a22ecd66dad47bcc9ced386 | function [k,eta] = waveNumber5thOrderStokes(H,T,h,EulerOrStokes,valOfEuOrStok)
format long g
format compact
g = 9.81;
kInit = fsolve(@(k) (2 * pi / T)^2 - g * k * tanh(k * h),1);
EulerOrStokes
if strcmp(EulerOrStokes,'Euler')
elseif strcmp(EulerOrStokes,'Stokes')
k = fsolve(@(k) stokes(k,H,T,h,valOfEuOrStok... |
github | elvalord/Image-Text-Detection-master | SaliencySR.m | .m | Image-Text-Detection-master/my thesis_code final/SaliencySR.m | 487 | utf_8 | a120a097e541a6128a15a2e60ffd250b | %%From author
%clear
%clc
function [saliencyMap]=SaliencySR(Is)
%% Read image from file
inImg = im2double(Is);
%% Spectral Residual
myFFT = fft2(inImg);
myLogAmplitude = log(abs(myFFT));
myPhase = angle(myFFT);
mySpectralResidual = myLogAmplitude - imfilter(myLogAmplitude, fspecial('average', 5), 'replicate');
sali... |
github | bhargavvader/CASApythonPort-master | decompose_kernel.m | .m | CASApythonPort-master/nmf/decompose_kernel.m | 6,611 | utf_8 | 291001d43251aec7a2797b476a6883bb | function [k1,kn,err] = decompose_kernel(h_orig)
% This function does the decomposition of a separable nD kernel into
% its 1D components, such that a convolution with each of these
% components yields the same result as a convolution with the full nD
% kernel, at a drastic reduction in computational cost.
%
% SYNTAX:
%... |
github | LaurentBerger/opencv_contrib-master | modelConvert.m | .m | opencv_contrib-master/doc/tutorials/ximgproc/training/scripts/modelConvert.m | 2,117 | utf_8 | dd8b0dc376b1da49ced7529a9e3a7723 | function modelConvert(model, outname)
%% script for converting Piotr's matlab model into YAML format
outfile = fopen(outname, 'w');
fprintf(outfile, '%%YAML:1.0\n\n');
fprintf(outfile, ['options:\n'...
' numberOfTrees: 8\n'...
' numberOfTreesToEvaluate: 4\n'...
... |
github | LaurentBerger/opencv_contrib-master | modelConvert.m | .m | opencv_contrib-master/modules/ximgproc/tutorials/scripts/modelConvert.m | 2,117 | utf_8 | dd8b0dc376b1da49ced7529a9e3a7723 | function modelConvert(model, outname)
%% script for converting Piotr's matlab model into YAML format
outfile = fopen(outname, 'w');
fprintf(outfile, '%%YAML:1.0\n\n');
fprintf(outfile, ['options:\n'...
' numberOfTrees: 8\n'...
' numberOfTreesToEvaluate: 4\n'...
... |
github | lrascius/MoneyDetection-master | billsCoinsDetection.m | .m | MoneyDetection-master/billsCoinsDetection.m | 13,041 | utf_8 | 67d71eb01050862e1c660f858a4d630f | % Project -- CSc 47900
% Presented to : Prof. J.Wei
% Presented by: Lukas Rascius & Markous Soliman
% Comments are provided.
% -----------------------------------------------------------%
function [] = billsCoinsDetection()
% First, let's clean up the session
clear;clc;clf;close all;
format long;
... |
github | lrascius/MoneyDetection-master | coinsNames.m | .m | MoneyDetection-master/coinsNames.m | 528 | utf_8 | 86d7d7bf4d9b72976bc3990ef642e37c | % Function that stores the strings of coins' names in a string array.
function [ratio2str] = coinsNames
ratio2str = {};
ratio2str{1,1} = 'Dime';
ratio2str{2,1} = 'Dime';
ratio2str{3,1} = 'Dime';
ratio2str{1,2} = 'Penny';
ratio2str{4,1} = 'Penny';
ratio2str{5,1} = 'Penny';
... |
github | jonathf/matlab2cpp-master | function_reference_2.m | .m | matlab2cpp-master/test/data/function_reference_2.m | 118 | utf_8 | bd3eaf225081f9a5a72658943122a0e6 | function [y,z]=f(a,b)
y = a+2
z = b-3
end
function g()
a = [1,2,3]
b = [4;5;6]
[y,z] = f(a,b)
end
|
github | jonathf/matlab2cpp-master | function_reference.m | .m | matlab2cpp-master/test/data/function_reference.m | 78 | utf_8 | 707f8fcac3ed7f2418740ad75a49284c | function y=f(x)
y = x+2
end
function g()
x = [1,2,3]
y = f(x)
end
|
github | jonathf/matlab2cpp-master | fx_decon.m | .m | matlab2cpp-master/test/data/fx_decon.m | 1,364 | utf_8 | a81a33a961a6db95b7b743243ab45472 | function [DATA_f] = fx_decon(DATA,dt,lf,mu,flow,fhigh);
[nt,ntraces] = size(DATA);
nf = 2^nextpow2(nt);
DATA_FX_f = zeros(nf,ntraces);
DATA_FX_b = zeros(nf,ntraces);
ilow = floor(flow*dt*nf)+1;
if ilow<1;
ilow=1;
end;
ihigh = floor(fhigh*dt*nf)+1;
if ihigh > floor(nf/2)+1;
ihigh=floor(nf/2)+1;
... |
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