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 | Ziyi-Guo/ml_coursera-master | loadjson.m | .m | ml_coursera-master/machine-learning-ex3/ex3/lib/jsonlab/loadjson.m | 18,732 | ibm852 | ab98cf173af2d50bbe8da4d6db252a20 | function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% ... |
github | Ziyi-Guo/ml_coursera-master | loadubjson.m | .m | ml_coursera-master/machine-learning-ex3/ex3/lib/jsonlab/loadubjson.m | 15,574 | utf_8 | 5974e78e71b81b1e0f76123784b951a4 | function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id: loadubjson.m 460 2015-01-... |
github | Ziyi-Guo/ml_coursera-master | saveubjson.m | .m | ml_coursera-master/machine-learning-ex3/ex3/lib/jsonlab/saveubjson.m | 16,123 | utf_8 | 61d4f51010aedbf97753396f5d2d9ec0 | function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author... |
github | Ziyi-Guo/ml_coursera-master | submit.m | .m | ml_coursera-master/machine-learning-ex1/ex1/submit.m | 1,876 | utf_8 | 8d1c467b830a89c187c05b121cb8fbfd | function submit()
addpath('./lib');
conf.assignmentSlug = 'linear-regression';
conf.itemName = 'Linear Regression with Multiple Variables';
conf.partArrays = { ...
{ ...
'1', ...
{ 'warmUpExercise.m' }, ...
'Warm-up Exercise', ...
}, ...
{ ...
'2', ...
{ 'computeCost.m... |
github | Ziyi-Guo/ml_coursera-master | submitWithConfiguration.m | .m | ml_coursera-master/machine-learning-ex1/ex1/lib/submitWithConfiguration.m | 3,734 | utf_8 | 84d9a81848f6d00a7aff4f79bdbb6049 | function submitWithConfiguration(conf)
addpath('./lib/jsonlab');
parts = parts(conf);
fprintf('== Submitting solutions | %s...\n', conf.itemName);
tokenFile = 'token.mat';
if exist(tokenFile, 'file')
load(tokenFile);
[email token] = promptToken(email, token, tokenFile);
else
[email token] = p... |
github | Ziyi-Guo/ml_coursera-master | savejson.m | .m | ml_coursera-master/machine-learning-ex1/ex1/lib/jsonlab/savejson.m | 17,462 | utf_8 | 861b534fc35ffe982b53ca3ca83143bf | function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fa... |
github | Ziyi-Guo/ml_coursera-master | loadjson.m | .m | ml_coursera-master/machine-learning-ex1/ex1/lib/jsonlab/loadjson.m | 18,732 | ibm852 | ab98cf173af2d50bbe8da4d6db252a20 | function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% ... |
github | Ziyi-Guo/ml_coursera-master | loadubjson.m | .m | ml_coursera-master/machine-learning-ex1/ex1/lib/jsonlab/loadubjson.m | 15,574 | utf_8 | 5974e78e71b81b1e0f76123784b951a4 | function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id: loadubjson.m 460 2015-01-... |
github | Ziyi-Guo/ml_coursera-master | saveubjson.m | .m | ml_coursera-master/machine-learning-ex1/ex1/lib/jsonlab/saveubjson.m | 16,123 | utf_8 | 61d4f51010aedbf97753396f5d2d9ec0 | function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author... |
github | jaromiru/RL-master | findMaxA.m | .m | RL-master/4-9-gambler/findMaxA.m | 408 | utf_8 | b1dcf3ceaf2b11e4553cebaa73b81dc1 | % finds an action maximizing reward in given state and coresponding value
function [maxA, maxValue] = findMaxA(pw, y, v, s, r)
maxA = -1;
maxValue = -1;
for a = 0:min(s-1, 101-s) %action is number of $ to bet
val = pw * (r(s+a) + y*v(s+a)) + (1-pw) * (r(s-a) + y*v(s-a));
if val >= ma... |
github | xioTechnologies/NGIMU-MATLAB-Import-Logged-Data-Example-master | resampleSession.m | .m | NGIMU-MATLAB-Import-Logged-Data-Example-master/resampleSession.m | 4,087 | utf_8 | d07e00e2640f49fccecbf20c5c8990a3 | function [resampledSessionData, time] = resampleSession(sessionData, newSamplePeriod)
% Copy original structure
resampledSessionData = sessionData;
% Determine end time
endTime = -Inf;
for deviceIndex = 1:sessionData.numberOfDevices
deviceName = sessionData.deviceNames{deviceIndex};
... |
github | xioTechnologies/NGIMU-MATLAB-Import-Logged-Data-Example-master | importSession.m | .m | NGIMU-MATLAB-Import-Logged-Data-Example-master/importSession.m | 9,103 | utf_8 | c52cf61ef24c8886a482638a61a7cb4a | function sessionData = importSession(sessionDirectory, varargin)
% IMPORTSESSION Imports logged NGIMU data.
%
% sessionData = importSession(sessionDirectory), Imports a session
% directory containing data from one or more NGIMU.
%
% sessionData = importSession(sessionDirectory, 'FileNames', fileNames),
% Im... |
github | jonathanventura/SphericalMotion-master | solve_spherical_action_matrix.m | .m | SphericalMotion-master/solve_spherical_action_matrix.m | 9,509 | utf_8 | 08bfa73ad0f0bd912d08ca4ad47863a1 | function E = solve_spherical_action_matrix(u,v)
% u is observations in first frame (3xN)
% v is observations in second frame (3XN)
% E is 3x3x4 matrix of essential matrix solutions
if size(u,1) ~= 3 || size(v,1) ~= 3 || size(u,2) ~= size(v,2),
error('u and v must be size 3xN');
end
% build matrix of linear constr... |
github | jonathanventura/SphericalMotion-master | solve_spherical_polynomial.m | .m | SphericalMotion-master/solve_spherical_polynomial.m | 10,050 | utf_8 | 56b0666f6d922469010eaa83c7f8664e | function E = solve_spherical_polynomial(u,v)
% u is observations in first frame (3xN)
% v is observations in second frame (3XN)
% E is 3x3x4 matrix of essential matrix solutions
if size(u,1) ~= 3 || size(v,1) ~= 3 || size(u,2) ~= size(v,2),
error('u and v must be size 3xN');
end
% build matrix of linear constrain... |
github | irenne/MARA-master | eegplugin_MARA.m | .m | MARA-master/eegplugin_MARA.m | 2,829 | utf_8 | 59adbc9bc30ab05f7e938f9d86ee30cb | % eegplugin_MARA() - EEGLab plugin to classify artifactual ICs based on
% 6 features from the time domain, the frequency domain,
% and the pattern
%
% Inputs:
% fig - [integer] EEGLAB figure
% try_strings - [struct] "try" strings for menu callbacks.
% catc... |
github | irenne/MARA-master | pop_visualizeMARAfeatures.m | .m | MARA-master/pop_visualizeMARAfeatures.m | 4,677 | utf_8 | e1940ed1cfcc781be628bc950524d2c7 | % pop_visualizeMARAfeatures() - Display features that MARA's decision
% for artifact rejection is based on
%
% Usage:
% >> pop_visualizeMARAfeatures(gcompreject, MARAinfo);
%
% Inputs:
% gcompreject - array <1 x nIC> containing 1 if component was rejected
% ... |
github | irenne/MARA-master | processMARA.m | .m | MARA-master/processMARA.m | 6,691 | utf_8 | f0901c7153f3beb9b1883f6eec54059d | % processMARA() - Processing for Automatic Artifact Classification with MARA.
% processMARA() calls MACA and saves the identified artifactual components
% in EEG.reject.gcompreject.
% The functions optionally filters the data, runs ICA, plots components or
% reject artifactual components immediately.
%... |
github | irenne/MARA-master | MARA.m | .m | MARA-master/MARA.m | 12,926 | utf_8 | c1302dd1818c461d1f20628eb3086168 | % MARA() - Automatic classification of multiple artifact components
% Classies artifactual ICs based on 6 features from the time domain,
% the frequency domain, and the pattern
%
% Usage:
% >> [artcomps, info] = MARA(EEG);
%
% Inputs:
% EEG - input EEG structure
%
% Outputs:
... |
github | irenne/MARA-master | pop_selectcomps_MARA.m | .m | MARA-master/pop_selectcomps_MARA.m | 7,828 | utf_8 | f6737a4dfdf7b50bc247f34e3beca6c3 | % pop_selectcomps_MARA() - Display components with checkbox to label
% them for artifact rejection
%
% Usage:
% >> EEG = pop_selectcomps_MARA(EEG, gcompreject_old);
%
% Inputs:
% EEG - Input dataset with rejected components (saved in
% EEG.reject.gcompr... |
github | irenne/MARA-master | pop_processMARA.m | .m | MARA-master/pop_processMARA.m | 5,210 | utf_8 | 772c3110dc56d452c01c57e1f55e8a75 | % pop_processMARA() - graphical interface to select MARA's actions
%
% Usage:
% >> [ALLEEG,EEG,CURRENTSET,com] = pop_processMARA(ALLEEG,EEG,CURRENTSET );
%
% Inputs and Outputs:
% ALLEEG - array of EEG dataset structures
% EEG - current dataset structure or structure array
% ... |
github | jacqu/rpit-master | setup.m | .m | rpit-master/setup.m | 24,343 | utf_8 | dbaa413b9a8e06d0d313590313e05086 | % Run this script to install the RPI target
% Author : jacques.gangloff@unistra.fr, July 2019
clear;
clc;
global rpitdir;
rpitdir = pwd;
disp( 'C O N F I G U R A T I O N O F R P I t' );
disp( '===========================================' );
disp( ' ' );
rpit_message({...
'IMPORTANT NOTES:';...
' - In what f... |
github | jacqu/rpit-master | ert_rpi_make_rtw_hook.m | .m | rpit-master/rpit/ert_rpi_make_rtw_hook.m | 11,203 | utf_8 | 6c0325e335ee9166d4ab857b43082653 | function ert_rpi_make_rtw_hook(hookMethod,modelName,rtwroot,templateMakefile,buildOpts,buildArgs)
% ERT_MAKE_RTW_HOOK - This is the standard ERT hook file for the RTW build
% process (make_rtw), and implements automatic configuration of the
% models configuration parameters. When the buildArgs option is specified
% as... |
github | jacqu/rpit-master | camera_anim.m | .m | rpit-master/demos/Xim_test/camera_anim.m | 8,138 | utf_8 | ae81094dc212f3f7728f39e46e00c353 | function [sys,x0,str,ts] = camera_anim(t,x,u,flag)
%CAMERA_ANIM S-function for animating the live image of an eye in hand cam.
%
% The 8 components of the vector u are the coordintaes of 4 points.
%
% Copyright 2012 Jacques Gangloff (jacques.gangloff@unistra.fr)
% $Revision: 0.1 $
% Plots every major integratio... |
github | jacqu/rpit-master | rtwmakecfg.m | .m | rpit-master/blocks/rtwmakecfg.m | 2,790 | utf_8 | c5106585019e4a83748af4178e5021c2 | function makeInfo=rtwmakecfg()
%RTWMAKECFG adds include and source directories to rtw make files.
% makeInfo=RTWMAKECFG returns a structured array containing
% following field:
% makeInfo.includePath - cell array containing additional include
% directories. Those directories will be
% ... |
github | jacqu/rpit-master | voltone_cb.m | .m | rpit-master/docs/Inspiring projects/VU_LRT1p02/VU-LRT/voltone_cb.m | 2,005 | utf_8 | 6c7a0ede789b020ac3433a18ce6b4ae3 | % voltone_cb(...)
% Switchboard type function to handle all callbacks from the 'Volume Tone'
% dynamic masked block.
function voltone_cb(blk,volsrc,vol,freqsrc,freq)
switch volsrc
case 'External'
if strcmp(get_param([blk '/vol'],'BlockType'),'Constant')
replace([blk '/vol'],'built-in/Inport');
... |
github | jacqu/rpit-master | ecrobot_hooks.m | .m | rpit-master/docs/Inspiring projects/VU_LRT1p02/VU-LRT/ecrobot_hooks.m | 2,255 | utf_8 | a7581a61b8be05ae8dd1bf1ce6c24aad | % ecrobot_hooks(file)
% This function scans the user-created .mdl file as text and determines
% whether or not USB is used. If so, it places the 1ms usb process
% function in the type 2 isr hook function.
function ecrobot_hooks(inid)
% status variables
isr = '';
head = '';
f = 0;
g = 0;
fid = fopen('ecrobo... |
github | jacqu/rpit-master | installer.m | .m | rpit-master/docs/Inspiring projects/VU_LRT1p02/VU-LRT/installer.m | 19,289 | utf_8 | 76eed2a23acfa229dc55c1a9f004189d | function installer(cmd,rootInstallDir,downloadDir)
%INSTALLER Installs the VU-LEGO Real Time toolbox and associated third party tools
%
% INSTALLER (with no arguments) displays a menu of installation options.
% The tools are installed underneath the default root: C:\RTtargets
%
% INSTALLER(n) directly executes t... |
github | jacqu/rpit-master | servo_cb.m | .m | rpit-master/docs/Inspiring projects/VU_LRT1p02/VU-LRT/servo_cb.m | 1,908 | utf_8 | b71582aad3c5593a8be2fedbf7c2f463 | % servo_cb(...)
% Switchboard type function to handle all callbacks from the 'Servo Motor'
% dynamic masked block.
function servo_cb(blk, state, initrevsrc, initrev)
switch state
case 'init'
servo_init_cb(blk, initrevsrc, initrev);
case 'initrevsrc'
initrevsrc_cb(blk);
otherwise
... |
github | jacqu/rpit-master | openNXT.m | .m | rpit-master/docs/Inspiring projects/VU_LRT1p02/VU-LRT/openNXT.m | 2,458 | utf_8 | c5daa4dcea8c977b85a1bb37e214ca7d | function h = openNXT(port)
%Establishes a USB connection between the host and NXT brick
%Returns the created usb object
if nargin<1, port='USB'; end;
switch upper(port(1:3)),
case 'USB', h=openNXTusb;
case 'COM', h=openNXTbt(port);
otherwise
error(['Unrecognized port: ' port]);
end;
pause(0.2); %... |
github | jacqu/rpit-master | rtwmakecfg.m | .m | rpit-master/docs/Inspiring projects/VU_LRT1p02/VU-LRT/rtwmakecfg.m | 2,790 | utf_8 | c5106585019e4a83748af4178e5021c2 | function makeInfo=rtwmakecfg()
%RTWMAKECFG adds include and source directories to rtw make files.
% makeInfo=RTWMAKECFG returns a structured array containing
% following field:
% makeInfo.includePath - cell array containing additional include
% directories. Those directories will be
% ... |
github | jacqu/rpit-master | status_cb.m | .m | rpit-master/docs/Inspiring projects/VU_LRT1p02/VU-LRT/status_cb.m | 1,074 | utf_8 | bba7b52c3b5f8f88f73c92f6690984d7 | function status_cb(blk, statussrc)
switch statussrc
case 'Show'
if strcmp(get_param([blk '/status'],'BlockType'),'Terminator')
replace([blk '/status'],'built-in/Outport');
renumber(blk);
disp('show');
end
case 'Hide'
if strcmp(get_par... |
github | jacqu/rpit-master | cygwin_naming.m | .m | rpit-master/docs/Inspiring projects/VU_LRT1p02/VU-LRT/cygwin_naming.m | 438 | utf_8 | 9a154c26bfdf13344ca1722e166738af | % cygwin_naming(...)
% Converts files from using Windows naming conventions into using cygwin
% POSIX naming conventions.
function argout = cygwin_naming(varargin)
arg = strrep(varargin,'rt_logging.c','');
arg = strrep(arg,'c:','/cygdrive/c');
arg = strrep(arg,'C:','/cygdrive/c');
arg = strrep(arg,'\',... |
github | jacqu/rpit-master | set.m | .m | rpit-master/docs/Inspiring projects/VU_LRT1p02/VU-LRT/@w32serial/set.m | 3,410 | utf_8 | 0803f854f5b5b26c618f8faf747abe76 | function obj = set(obj,varargin)
%SET Set properties of W32SERIAL objects.
%
% OBJ = SET(OBJ,'PropertyName',VALUE) sets the property 'PropertyName' of
% the W32SERIAL object OBJ to the value VALUE.
%
% OBJ = SET(OBJ,'PropertyName',VALUE,'PropertyName',VALUE,..) sets multiple
% property values of the W32SERIAL object ... |
github | jacqu/rpit-master | qnxAfterMakeHook.m | .m | rpit-master/docs/Inspiring projects/qnx_ert_0_2/qnx_ert-0_2/qnx/qnxAfterMakeHook.m | 1,547 | utf_8 | 480cbbf72ef34502148aa36774b1491d | function [ ] = qnxAfterMakeHook( modelName )
if (strcmp(get_param(modelName,'SystemTargetFile') ,'ert_qnx.tlc') && ...
strcmp(get_param(modelName,'TemplateMakefile') ,'ert_qnx.tmf'))
% Check if user chose to Download to QNX in Settings
if verLessThan('matlab', '8.1')
makertwObj = get_param(gcs,... |
github | ToolboxHub/ToolboxToolbox-master | tbResetMatlabPath.m | .m | ToolboxToolbox-master/api/tbResetMatlabPath.m | 6,155 | utf_8 | 571dc0d102c4812eb43cb8d589b55150 | function [newPath, oldPath] = tbResetMatlabPath(varargin)
% Set the Matlab path to a consistent state.
%
% [newPath, oldPath] = tbResetMatlabPath('name', value, ...) sets the
% Matlab path to a consistent state as determined by the given name-value
% pairs.
%
% This function uses ToolboxToolbox shared parameters and pr... |
github | ToolboxHub/ToolboxToolbox-master | tbDeployToolboxes.m | .m | ToolboxToolbox-master/api/tbDeployToolboxes.m | 16,084 | utf_8 | def8b69e3854c9a35eb05e3524e66ebf | function [resolved, included] = tbDeployToolboxes(persistentPrefs, varargin)
% Fetch toolboxes and add them to the Matlab path.
%
% results = tbDeployToolboxes() fetches each toolbox from the default
% toolbox configuration adds each to the Matlab path. Returns a struct of
% results about what happened for each toolbo... |
github | ToolboxHub/ToolboxToolbox-master | tbDeploymentSnapshot.m | .m | ToolboxToolbox-master/api/tbDeploymentSnapshot.m | 3,116 | utf_8 | b93d0cbf1f547be7603109f907225ae2 | function snapshot = tbDeploymentSnapshot(config, persistentPrefs, varargin)
% Make a new config based on the given config, plus explicit flavors.
%
% The idea is to take an existing toolbox configuration and create a new
% configuration that is "version-pinned" or "snapshot". This is done by
% trying to detect the dep... |
github | ToolboxHub/ToolboxToolbox-master | tbLocateProject.m | .m | ToolboxToolbox-master/api/tbLocateProject.m | 2,756 | utf_8 | cb9551222d78c9c1ea3dbdad3365ff7b | function [projectPath, configPath, projectParent] = tbLocateProject(project, persistentPrefs, varargin)
% Locate the folder that contains the given project.
%
% projectPath = tbLocateProject(name) locates the project with the given
% string name and returns the path to that project. This will be a path
% within the co... |
github | ToolboxHub/ToolboxToolbox-master | tbGetToolboxNames.m | .m | ToolboxToolbox-master/api/tbGetToolboxNames.m | 1,593 | utf_8 | 7d260ab7f2f87e851da8fd0c728d5d8a | function [s, identifiers] = tbGetToolboxNames
%TBGETTOOLBOXNAMES Get struct containing the toolbox names
%
% [namesStruct, identifiers] = tbGetToolboxNames()
%
% OUTPUT
% namesStruct: returns a struct where each field corresponds to a toolbox
% . The field contains the toolbox name as a char array.
%... |
github | ToolboxHub/ToolboxToolbox-master | tbUse.m | .m | ToolboxToolbox-master/api/tbUse.m | 1,809 | utf_8 | 023405a3ed29b9f6f6ccb573e10f8f9a | function results = tbUse(registered, varargin)
% Deploy registered toolboxes by name.
%
% The goal here is to make it a one-liner to fetch toolboxes that are
% registerd on ToolboxHub and add them to the Matlab path. This should
% automate several steps that we usually do by hand, which is good for
% consistency and c... |
github | ToolboxHub/ToolboxToolbox-master | savejson.m | .m | ToolboxToolbox-master/external/jsonlab-1.2/jsonlab/savejson.m | 18,983 | utf_8 | 2f510ad749556cadd303786e2549f30a | function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fa... |
github | ToolboxHub/ToolboxToolbox-master | loadjson.m | .m | ToolboxToolbox-master/external/jsonlab-1.2/jsonlab/loadjson.m | 16,145 | ibm852 | 7582071c5bd7f5e5f74806ce191a9078 | function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% ... |
github | ToolboxHub/ToolboxToolbox-master | loadubjson.m | .m | ToolboxToolbox-master/external/jsonlab-1.2/jsonlab/loadubjson.m | 13,300 | utf_8 | b15e959f758c5c2efa2711aa79c443fc | function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id$
%
% input:
% fname: ... |
github | ToolboxHub/ToolboxToolbox-master | saveubjson.m | .m | ToolboxToolbox-master/external/jsonlab-1.2/jsonlab/saveubjson.m | 17,723 | utf_8 | 3414421172c05225dfbd4a9c8c76e6b3 | function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author... |
github | hrtavakoli/UHM-master | computeSaliency.m | .m | UHM-master/computeSaliency.m | 586 | utf_8 | 3434198bae217a4eed323d511a74b4e4 |
function saliency = computeSaliency(im, bias)
if nargin < 2
bias = true;
end
setup_globalSetting();
[x, y, ~] = size(im);
saliency = zeros(x, y);
for scale = 155:100:480
tmpSal = compute_glSaliency(im, scale);
tmpSal = exp(tmpSal)./sum(sum(exp(tmpSal)));
saliency = saliency + imresize(tmpSal... |
github | hrtavakoli/UHM-master | earth.m | .m | UHM-master/sc-master/earth.m | 1,336 | utf_8 | f5deedd73adb95d4e5e8b60755806064 | %EARTH Black-green-white colormap
%
% Examples:
% map = earth;
% map = earth(len);
% B = earth(A);
% B = earth(A, lims);
%
% A black to white colormap with several distinct shades, most of which
% have a green or brown tint. This colormap converts linearly to grayscale
% when printed in black & white... |
github | hrtavakoli/UHM-master | jet.m | .m | UHM-master/sc-master/jet.m | 1,090 | utf_8 | 4976aaec8bce807a73b57e2865b37b83 | %JET Variant of HSV colormap
%
% Examples:
% map = jet;
% map = jet(len);
% B = jet(A);
% B = jet(A, lims);
%
% Similar to MATLAB's jet function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
% a truecolor array usi... |
github | hrtavakoli/UHM-master | cool.m | .m | UHM-master/sc-master/cool.m | 915 | utf_8 | 0b3e6c50420e0ba36b35f068aeb29942 | %COOL Cyan-magenta colormap
%
% Examples:
% map = cool;
% map = cool(len);
% B = cool(A);
% B = cool(A, lims);
%
% Similar to MATLAB's cool function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
% a truecolor array... |
github | hrtavakoli/UHM-master | hsv2.m | .m | UHM-master/sc-master/hsv2.m | 948 | utf_8 | 3dd09ff7977c87dda30134f109e7df88 | %HSV2 Black to red variation of the hsv colormap
%
% Examples:
% map = hsv2;
% map = hsv2(len);
% B = hsv2(A);
% B = hsv2(A, lims);
%
% A variation of MATLAB's hsv colormap, which starts in black.
%
% The function can additionally be used to convert a real-valued array into
% a truecolor array using... |
github | hrtavakoli/UHM-master | temp.m | .m | UHM-master/sc-master/temp.m | 1,511 | utf_8 | 9e77d70245232f80414a4e34d3a7f4c1 | %TEMP Blue-pale-dark red colormap
%
% Examples:
% map = temp
% map = temp(len)
% B = temp(A)
% B = temp(A, lims)
%
% A colormap designed by Light & Bartlein for visualizing data such as
% temperature, with good contrast for colorblind viewers.
%
% The function can additionally be used to convert a r... |
github | hrtavakoli/UHM-master | dusk.m | .m | UHM-master/sc-master/dusk.m | 9,996 | utf_8 | f61c7c434cd9f56b18d56f14fb0e607a | %DUSK Black-purple-blue-green-red-yellow-white colormap
%
% Examples:
% map = dusk;
% map = dusk(len);
% B = dusk(A);
% B = dusk(A, lims);
%
% A black to white colormap with several distinct pastel shades reminiscent
% of colors at dusk. This colormap has been designed to achieve perceptual
% uniform... |
github | hrtavakoli/UHM-master | bone.m | .m | UHM-master/sc-master/bone.m | 1,087 | utf_8 | 6eb6507df624b722f21dfa4e560c3daf | %BONE Black-blue-white colormap
%
% Examples:
% map = bone;
% map = bone(len);
% B = bone(A);
% B = bone(A, lims);
%
% Similar to MATLAB's bone function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
% a truecolor a... |
github | hrtavakoli/UHM-master | gray.m | .m | UHM-master/sc-master/gray.m | 1,048 | utf_8 | 3c6339d3976fd6ce314c7548126d7941 | %GRAY Black-white colormap
%
% Examples:
% map = gray;
% map = gray(len);
% B = gray(A);
% B = gray(A, lims);
%
% Similar to MATLAB's gray function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
% a truecolor array ... |
github | hrtavakoli/UHM-master | pastel.m | .m | UHM-master/sc-master/pastel.m | 1,099 | utf_8 | d6e99d2d3dd7264520a255dbfc93214e | %PASTEL Black-pastel-white colormap
%
% Examples:
% map = pastel;
% map = pastel(len);
% B = pastel(A);
% B = pastel(A, lims);
%
% A black to white colormap with several distinct pastel shades. This
% colormap converts linearly to grayscale when printed in black & white.
%
% The function can additio... |
github | hrtavakoli/UHM-master | real2rgb.m | .m | UHM-master/sc-master/real2rgb.m | 5,051 | utf_8 | 00f7a2a6f6aa767eb33de3013a6a4882 | %REAL2RGB Converts a real-valued matrix into a truecolor image
%
% Examples:
% B = real2rgb(A, cmap);
% B = real2rgb(A, cmap, lims);
% [B lims map] = real2rgb(...);
%
% This function converts a real-valued matrix into a truecolor image (i.e.
% double array with values between 0 and 1) using the colormap ... |
github | hrtavakoli/UHM-master | pink2.m | .m | UHM-master/sc-master/pink2.m | 1,325 | utf_8 | b0fbb0de7fc95769622ab5109bfed7fc | %PINK2 Black-pink-white colormap
%
% Examples:
% map = pink2;
% map = pink2(len);
% B = pink2(A);
% B = pink2(A, lims);
%
% A black to white colormap with several distinct shades, most of which
% have a pink tint. This colormap converts linearly to grayscale when
% printed in black & white.
%
% The... |
github | hrtavakoli/UHM-master | cold.m | .m | UHM-master/sc-master/cold.m | 1,086 | utf_8 | a74a00347ae198d1e4418bc6f6c15438 | %COLD Black-blue-cyan-white colormap
%
% Examples:
% map = cold;
% map = cold(len);
% B = cold(A);
% B = cold(A, lims);
%
% A black to white colormap through cold shades.
%
% The function can additionally be used to convert a real-valued array into
% a truecolor array using the colormap.
%
% IN:
... |
github | hrtavakoli/UHM-master | winter.m | .m | UHM-master/sc-master/winter.m | 929 | utf_8 | 076343331ff6a3c0afaf5a787329809d | %WINTER Blue-green colormap
%
% Examples:
% map = winter;
% map = winter(len);
% B = winter(A);
% B = winter(A, lims);
%
% Similar to MATLAB's winter function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
% a truec... |
github | hrtavakoli/UHM-master | autumn.m | .m | UHM-master/sc-master/autumn.m | 927 | utf_8 | c8d62741cc58bcccbb24c0ce35241237 | %AUTUMN Red-yellow colormap
%
% Examples:
% map = autumn;
% map = autumn(len);
% B = autumn(A);
% B = autumn(A, lims);
%
% Similar to MATLAB's autumn function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
% a truec... |
github | hrtavakoli/UHM-master | imsc.m | .m | UHM-master/sc-master/imsc.m | 1,513 | utf_8 | 4199c9d2ce01588994bf44f3d1373a4c | %IMSC Wrapper function to SC which replicates display behaviour of IMAGESC
%
% Examples:
% imsc(I, varargin)
% imsc(x, y, I, varargin)
% h = imsc(...)
%
% IN:
% x - 1xJ vector of x-axis bounds. If x(1) > x(2) the image is flipped
% left-right. If J > 2 then only the first and last values are us... |
github | hrtavakoli/UHM-master | thermal.m | .m | UHM-master/sc-master/thermal.m | 9,914 | utf_8 | db0fdb4a174b3730e65da091f18a4770 | %THERMAL Black-purple-red-yellow-white colormap
%
% Examples:
% map = thermal;
% map = thermal(len);
% B = thermal(A);
% B = thermal(A, lims);
%
% A colormap designed to replicate the tones of thermal images, as well as
% achieve perceptual uniformity.
%
% The function can additionally be used to co... |
github | hrtavakoli/UHM-master | hicontrast.m | .m | UHM-master/sc-master/hicontrast.m | 1,322 | utf_8 | 8fb0fd043572c4b4ee3024c3f7b8323b | %HICONTRAST Black-blue-red-magenta-green-cyan-yellow-white colormap
%
% Examples:
% map = hicontrast;
% map = hicontrast(len);
% B = hicontrast(A);
% B = hicontrast(A, lims);
%
% A colormap designed to maximize the range of colors used in order to
% improve contrast between intensity levels, while con... |
github | hrtavakoli/UHM-master | bled.m | .m | UHM-master/sc-master/bled.m | 993 | utf_8 | 1604e27352c81356e2d752e13c577c43 | %BLED Black to red variation of the hsv colormap
%
% Examples:
% map = bled;
% map = bled(len);
% B = bled(A);
% B = bled(A, lims);
%
% A variation of MATLAB's hsv colormap, which starts in black and gradually
% increases in color saturation.
%
% The function can additionally be used to convert a re... |
github | hrtavakoli/UHM-master | summer.m | .m | UHM-master/sc-master/summer.m | 935 | utf_8 | 9a4979feb050ab340489c0a5c876af8b | %SUMMER Green-yellow colormap
%
% Examples:
% map = summer;
% map = summer(len);
% B = summer(A);
% B = summer(A, lims);
%
% Similar to MATLAB's summer function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
% a tru... |
github | hrtavakoli/UHM-master | pink.m | .m | UHM-master/sc-master/pink.m | 1,165 | utf_8 | b46de092932a69bbf13cc3d4aaa324cc | %PINK Black-pink-white colormap
%
% Examples:
% map = pink
% map = pink(len)
% B = pink(A)
% B = pink(A, lims)
%
% Similar to MATLAB's pink colormap, but the function can additionally be
% used to convert a real-valued array into a truecolor array using the
% colormap.
%
% IN:
% len - Scalar len... |
github | hrtavakoli/UHM-master | whed.m | .m | UHM-master/sc-master/whed.m | 993 | utf_8 | 7a551507f6815182fb1ec2715b739506 | %WHED White to red variation of the hsv colormap
%
% Examples:
% map = whed;
% map = whed(len);
% B = whed(A);
% B = whed(A, lims);
%
% A variation of MATLAB's hsv colormap, which starts in white and gradually
% increases in color saturation.
%
% The function can additionally be used to convert a re... |
github | hrtavakoli/UHM-master | imdisp.m | .m | UHM-master/sc-master/imdisp.m | 22,190 | utf_8 | 0658e0c3cf30cffe09aa6ea0a275fed6 | %IMDISP Display one or more images nicely
%
% Examples:
% imdisp
% imdisp(I)
% imdisp(I, map)
% imdisp(I, lims)
% imdisp(I, map, lims)
% imdisp(..., param1, value1, param2, value2, ...)
% h = imdisp(...)
%
% This function displays one or more images nicely. Images can be defined
% by arrays, ... |
github | hrtavakoli/UHM-master | copper2.m | .m | UHM-master/sc-master/copper2.m | 9,950 | utf_8 | 84c40ed439b5d03ac469b9d2425b085d | %COPPER2 Black-copper-white colormap
%
% Examples:
% map = copper2;
% map = copper2(len);
% B = copper2(A);
% B = copper2(A, lims);
%
% A brighter variation of MATLAB's copper colormap, which also continues on
% to white. This colormap has been designed to achieve perceptual
% uniformity.
%
% The f... |
github | hrtavakoli/UHM-master | bright.m | .m | UHM-master/sc-master/bright.m | 1,106 | utf_8 | 48ff8393daa5e4d4a59b06bdf4d55152 | %BRIGHT Black-bright-white colormap
%
% Examples:
% map = bright
% map = bright(len)
% B = bright(A)
% B = bright(A, lims)
%
% A black to white colormap with several distinct shades of bright color.
% This colormap converts linearly to grayscale when printed in black &
% white.
%
% The function can... |
github | hrtavakoli/UHM-master | disparity.m | .m | UHM-master/sc-master/disparity.m | 4,085 | utf_8 | 8b12291fb64a3d945baf51c85ba8c5a6 | %DISPARITY High contrast colormap with subtle gradient discontinuities
%
% Examples:
% map = disparity;
% map = disparity(len);
% B = disparity(A);
% B = disparity(A, lims);
%
% A colormap designed for depth and disparity maps. It has subtle gradient
% discontinuities to bring out contours, and maximi... |
github | hrtavakoli/UHM-master | sepia.m | .m | UHM-master/sc-master/sepia.m | 9,925 | utf_8 | 3f957977163731bbb655ad202b6cc7a6 | %SEPIA Black-brown-white colormap
%
% Examples:
% map = sepia;
% map = sepia(len);
% B = sepia(A);
% B = sepia(A, lims);
%
% A colormap designed to replicate the sepia tones of old photographs, as
% well as achieve perceptual uniformity.
%
% The function can additionally be used to convert a real-va... |
github | hrtavakoli/UHM-master | bone2.m | .m | UHM-master/sc-master/bone2.m | 9,878 | utf_8 | a1cd8ae7677dc71fecd91e4fb24415d3 | %BONE2 Black-blue-white colormap
%
% Examples:
% map = bone2;
% map = bone2(len);
% B = bone2(A);
% B = bone2(A, lims);
%
% Similar to MATLAB's bone function, this colormap has been designed to
% achieve perceptual uniformity.
%
% The function can additionally be used to convert a real-valued array ... |
github | hrtavakoli/UHM-master | disco.m | .m | UHM-master/sc-master/disco.m | 4,034 | utf_8 | ad1b311ec08539c3679035930bec2c45 | %DISCO High contrast colormap with strong gradient discontinuities
%
% Examples:
% map = disco;
% map = disco(len);
% B = disco(A);
% B = disco(A, lims);
%
% A colormap designed to highlight contours. It has strong gradient
% discontinuities, and maximizes the range of colors used in order to
% imp... |
github | hrtavakoli/UHM-master | hsv.m | .m | UHM-master/sc-master/hsv.m | 1,105 | utf_8 | cf63c383bb17229c1d0b2cc82a5ab9a9 | %HSV Red-yellow-green-cyan-blue-magenta-red colormap
%
% Examples:
% map = hsv;
% map = hsv(len);
% B = hsv(A);
% B = hsv(A, lims);
%
% Similar to MATLAB's hsv function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
... |
github | hrtavakoli/UHM-master | sc.m | .m | UHM-master/sc-master/sc.m | 32,713 | utf_8 | 5af05d6fc450ee7c96e0624fe6f256f7 | %SC Display/output truecolor images with a range of colormaps
%
% Examples:
% sc(image)
% sc(image, limits)
% sc(image, map)
% sc(image, limits, map)
% sc(image, map, limits)
% sc(..., col1, mask1, col2, mask2,...)
% out = sc(...)
% [out, clim map] = sc(...)
% sc
%
% Generates a truecolo... |
github | hrtavakoli/UHM-master | copper.m | .m | UHM-master/sc-master/copper.m | 958 | utf_8 | 8f5712b758b6ddebc2c49f6bcc228894 | %COPPER Black-copper colormap
%
% Examples:
% map = copper;
% map = copper(len);
% B = copper(A);
% B = copper(A, lims);
%
% Similar to MATLAB's copper function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
% a tru... |
github | hrtavakoli/UHM-master | hot.m | .m | UHM-master/sc-master/hot.m | 1,076 | utf_8 | 9b8439b6451e64afb88c2ede9fbaec31 | %HOT Black-red-yellow-white colormap
%
% Examples:
% map = hot;
% map = hot(len);
% B = hot(A);
% B = hot(A, lims);
%
% Similar to MATLAB's hot function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
% a truecolor a... |
github | hrtavakoli/UHM-master | spring.m | .m | UHM-master/sc-master/spring.m | 931 | utf_8 | 4410b62539c0372abd022ee56dc9b4ae | %SPRING Magenta-yellow colormap
%
% Examples:
% map = spring;
% map = spring(len);
% B = spring(A);
% B = spring(A, lims);
%
% Similar to MATLAB's spring function, but also able to return a concise
% colormap table.
%
% The function can additionally be used to convert a real-valued array into
% a t... |
github | hrtavakoli/UHM-master | dawn.m | .m | UHM-master/sc-master/dawn.m | 9,986 | utf_8 | 2a07bc4c62f6e5889557f340c528c632 | %DAWN Black-purple-blue-green-yellow-white colormap
%
% Examples:
% map = dawn;
% map = dawn(len);
% B = dawn(A);
% B = dawn(A, lims);
%
% A black to white colormap with several distinct pastel shades reminiscent
% of colors at dawn. This colormap has been designed to achieve perceptual
% uniformity.... |
github | hrtavakoli/UHM-master | rescale.m | .m | UHM-master/sc-master/private/rescale.m | 1,696 | utf_8 | 80080f5fafb2105da3f4093111409ec3 | function [B, lims] = rescale(A, lims, out_lims)
%RESCALE Linearly rescale values in an array
%
% Examples:
% B = rescale(A)
% B = rescale(A, lims)
% B = rescale(A, lims, out_lims)
% [B lims] = rescale(A)
%
% Linearly rescales values in an array, saturating values outside limits.
%
% IN:
% A - Inp... |
github | hrtavakoli/UHM-master | feedForward.m | .m | UHM-master/src/nn_functions/feedForward.m | 437 | utf_8 | e7d90f751f4df2bb6730cb60c77dbb17 |
function output = feedForward(X, sLayer, dLayer, inputType)
% now let us just feedforward the data and compute the output
% X is the input data
% s is the source layer
% d is the destination layer
% here simply apply the transform and feed forward the data
switch lower(inputType)
case 'video'
error('vi... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | goldsteinpricefcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/goldsteinpricefcn.m | 1,021 | utf_8 | e709a70454ce5bfc1ec593c05bc95c5c | % Computes the value of GOldstein-Price benchmark function.
% SCORES = GOLDSTEINPRICEFCN(X) computes the value of the GOLDSTEINPRICEFCN
% function at point X. GOLDSTEINPRICEFCN accepts a matrix of size M-by-2
% and returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresp... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | wolfefcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/wolfefcn.m | 788 | utf_8 | 693a290ec8cf45a5dd4a3f8bd35f774a | % Computes the value of the Wolfe function.
% SCORES = WOLFEFCN(X) computes the value of the Wolfe
% function at point X. WOLFEFCN accepts a matrix of size M-by-3 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% For more information, please... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | schaffern4fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/schaffern4fcn.m | 945 | utf_8 | 9c9397240a065d99da474b97664feb10 | % Computes the value of the Schaffer N. 4 function.
% SCORES = SCHAFFERN4FCN(X) computes the value of the Schaffer N. 4
% function at point X. SCHAFFERN4FCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% F... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | crossintrayfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/crossintrayfcn.m | 931 | utf_8 | 39213f0de854488cda6afc7e2cf25e4a | % Computes the value of the Cross-in-tray benchmark function.
% SCORES = CROSSINTRAYFCN(X) computes the value of the Cross-in-tray
% function at point X. CROSSINTRAYFCN accepts a matrix of size M-by-2
% and returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding ro... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | schwefel220fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/schwefel220fcn.m | 562 | utf_8 | e482821e4396d8cca7cfcc17e19abf3c | % Computes the value of the Schwefel 2.20 function.
% SCORES = SCHWEFEL220FCN(X) computes the value of the Schwefel 2.20
% function at point X. SCHWEFEL220FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | eggholderfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/eggholderfcn.m | 939 | utf_8 | 5b6dc9dd2ea429e480bd55eba1dfe99d | % Computes the value of the Eggholder benchmark function.
% SCORES = EGGHOLDERFCN(X) computes the value of the Eggholder
% function at point X. EGGHOLDERFCN accepts a matrix of size M-by-2
% and returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X. For m... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | xinsheyangn1fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/xinsheyangn1fcn.m | 728 | utf_8 | 4fbe60a7d688c7c5e084202eeeeb200e | % Computes the value of the Xin-She Yang function.
% SCORES = XINSHEYANGN1FCN(X) computes the value of the Xin-She Yang
% function at point X. XINSHEYANGN1FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% F... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | easomfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/easomfcn.m | 825 | utf_8 | fe7cff3c7dfed56cbbb96fdce069277c | % Computes the value of the Easom benchmark function.
% SCORES = EASOMFCN(X) computes the value of the Easom function at point X.
% EASOMFCN accepts a matrix of size M-by-2 and returns a vetor SCORES of
% size M-by-1 in which each row contains the function value for the
% corresponding row of X. For more information ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | alpinen2fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/alpinen2fcn.m | 661 | utf_8 | 127676c59fe1c2f045bcf70e16f4b913 | % Computes the value of the Alpine N. 2 function.
% SCORES = ALPINEN2FCN(X) computes the value of the Alpine N. 2
% function at point X. ALPINEN2FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% For more in... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | xinsheyangn4fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/xinsheyangn4fcn.m | 721 | utf_8 | 7a7e74091bd0e64dd06862d48c814697 | % Computes the value of the Xin-She Yang N. 4 function.
% SCORES = XINSHEYANGN4FCN(X) computes the value of the Xin-She Yang N. 4
% function at point X. XINSHEYANGN4FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | ackleyn3fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/ackleyn3fcn.m | 769 | utf_8 | 52d499d4e9fac965abd719eb955de7f8 | % Computes the value of the Ackley N. 3 function.
% SCORES = ACKLEYN3FCN(X) computes the value of the Ackley N. 3
% function at point X. ACKLEYN3FCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%
% Author: ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | bohachevskyn1fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/bohachevskyn1fcn.m | 773 | utf_8 | dfbf831bd06ab99fee0f3f209911ffa8 | % Computes the value of Bohachevsky N. 1 benchmark function.
% SCORES = BOHACHEVSKYN1FCN(X) computes the value of the Bohachevsky N. 1
% function at point X. BOHACHEVSKYFCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for each row of X.
% ... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | ackleyn4fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/ackleyn4fcn.m | 769 | utf_8 | c33bb5d297dabed25641787c8d30c82c | % Computes the value of Ackley N. 4 benchmark function.
% SCORES = ACKLEYN4FCN(X) computes the value of the Ackey function at point
% X. ACKLEYN4FCN accepts a matrix of size M-by-N and returns a vetor SCORES
% of size M-by-1 in which each row contains the function value for each row
% of X.
%
% Author: Mazhar Ansari A... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | shubert3fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/shubert3fcn.m | 678 | utf_8 | c3d74120331fc28f84e8ed6b98b36e69 | % Computes the value of the Shubert 3 function.
% SCORES = SHUBEERT3FCN(X) computes the value of the Shubert 3
% function at point X. SHUBEERT3FCN accepts a matrix of size M-by-N and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
%
% Author: Ma... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | pichenyfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/pichenyfcn.m | 1,148 | utf_8 | 8bbb0a99d12059a406059c84342da03e | % Computes the value of the Picheny benchmark function.
% SCORES = PICHENYFCN(X) computes the value of the Beale function at
% point X. PICHENYFCN accepts a matrix of size M-by-2 and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row of X.
% For more in... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | surffcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/surffcn.m | 1,887 | utf_8 | ee79b3b108583fca5f511039a3eb6d93 | % Draws surf of a functionon the 3-dimensional space
%
% surffcn(FCN, X, Y) draws the surf of the function given by the
% handle FCN in the x-y plane defined over the intervals specified by X
% and Y
%
% surffcn(FCN, X, Y, X_LABEL) draws the surf and uses X_LABEL as the
% label of x-axis
%
% surffcn(FCN, X, Y, X_... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | zakharovfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/zakharovfcn.m | 727 | utf_8 | b3daf6ec4e1fc047c960a6d72bb75154 | % Computes the value of Zakharov benchmark function.
% SCORES = ZAKHAROVFCN(X) computes the value of the Zakharov function at
% point X. ZAKHAROVFCN accepts a matrix of size M-by-N and returns a vetor
% SCORES of size M-by-1 in which each row contains the function value for
% each row of X.
%
% Author: Mazhar Ansari... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | adjimanfcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/adjimanfcn.m | 713 | utf_8 | fcaba92678360ddcd72a86c24bf0c775 | % Computes the value of the Adjiman benchmark function.
% SCORES = ADJIMANHFCN(X) computes the value of the Adjiman function at
% point X. ADJIMANHFCN accepts a matrix of size M-by-2 and returns a
% vetor SCORES of size M-by-1 in which each row contains the function value
% for the corresponding row of X.
%
% Auth... |
github | mazhar-ansari-ardeh/BenchmarkFcns-master | schaffern3fcn.m | .m | BenchmarkFcns-master/benchmarks/matlab/schaffern3fcn.m | 945 | utf_8 | 50c72691974bd8a1e9ff175bb52a9ef9 | % Computes the value of the Schaffer N. 3 function.
% SCORES = SCHAFFERN3FCN(X) computes the value of the Schaffer N. 3
% function at point X. SCHAFFERN3FCN accepts a matrix of size M-by-2 and
% returns a vetor SCORES of size M-by-1 in which each row contains the
% function value for the corresponding row of X.
% F... |
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