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values | md5 stringlengths 32 32 | text stringlengths 23 843k |
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github | svndl/mrC-master | errordlg2.m | .m | mrC-master/external/eeglab14_1_1b/functions/guifunc/errordlg2.m | 1,467 | utf_8 | 710e811cd40d8f506b5264089f50c95c | % errordlg2() - Makes a popup dialog box with the specified message and (optional)
% title.
%
% Usage:
% errordlg2(Prompt, Title);
%
% Example:
% errordlg2('Explanation of error','title of error');
%
% Input:
% Prompt - A text string explaning why the user is seeing this error message.
% Title ... |
github | svndl/mrC-master | questdlg2.m | .m | mrC-master/external/eeglab14_1_1b/functions/guifunc/questdlg2.m | 3,133 | utf_8 | d94e219e87da50c5af28fe1007906abc | % questdlg2() - questdlg function clone with coloring and help for
% eeglab().
%
% Usage: same as questdlg()
%
% Warning:
% Case of button text and result might be changed by the function
%
% Author: Arnaud Delorme, CNL / Salk Institute, La Jolla, 11 August 2002
%
% See also: inputdlg2(), errordlg2(), s... |
github | svndl/mrC-master | listdlg2.m | .m | mrC-master/external/eeglab14_1_1b/functions/guifunc/listdlg2.m | 3,771 | utf_8 | a0820fcb823bcb9968afa377c5582498 | % listdlg2() - listdlg function clone with coloring and help for
% eeglab().
%
% Usage: same as listdlg()
%
% Author: Arnaud Delorme, CNL / Salk Institute, La Jolla, 16 August 2002
%
% See also: inputdlg2(), errordlg2(), supergui(), inputgui()
% Copyright (C) Arnaud Delorme, CNL / Salk Institute, arno@s... |
github | svndl/mrC-master | finputcheck.m | .m | mrC-master/external/eeglab14_1_1b/functions/guifunc/finputcheck.m | 9,133 | utf_8 | fe838fecdd60e76a4006a13c7c1b20e4 | % finputcheck() - check Matlab function {'key','value'} input argument pairs
%
% Usage: >> result = finputcheck( varargin, fieldlist );
% >> [result varargin] = finputcheck( varargin, fieldlist, ...
% callingfunc, mode, verbose );
% Input:
% varargin - Cell array ... |
github | svndl/mrC-master | inputdlg2.m | .m | mrC-master/external/eeglab14_1_1b/functions/guifunc/inputdlg2.m | 2,497 | utf_8 | f37d94d5821140270d3242f0d5d06659 | % inputdlg2() - inputdlg function clone with coloring and help for
% eeglab().
%
% Usage:
% >> Answer = inputdlg2(Prompt,Title,LineNo,DefAns,funcname);
%
% Inputs:
% Same as inputdlg. Using the optional additionnal funcname parameter
% the function will create a help button. The help message will... |
github | svndl/mrC-master | inputgui.m | .m | mrC-master/external/eeglab14_1_1b/functions/guifunc/inputgui.m | 13,049 | utf_8 | 4d1fcb532034d20d2ab20e9c28f5da11 | % inputgui() - A comprehensive gui automatic builder. This function helps
% to create GUI very quickly without bothering about the
% positions of the elements. After creating a geometry,
% elements just place themselves in the predefined
% locations. It is especial... |
github | svndl/mrC-master | firfiltdcpadded.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/firfiltdcpadded.m | 2,137 | utf_8 | b21b4207bf032e32cc6f0597db3cb4fe | % firfiltdcpadded() - Pad data with DC constant and filter
%
% Usage:
% >> data = firfiltdcpadded(data, b, causal);
%
% Inputs:
% data - raw data
% b - vector of filter coefficients
% causal - boolean perform causal filtering {default 0}
%
% Outputs:
% data - smoothed data
%
% Note:
% f... |
github | svndl/mrC-master | minphaserceps.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/minphaserceps.m | 1,275 | utf_8 | 7b751637e7eed71e29f91a4ef6b586e6 | % rcepsminphase() - Convert FIR filter coefficient to minimum phase
%
% Usage:
% >> b = minphaserceps(b);
%
% Inputs:
% b - FIR filter coefficients
%
% Outputs:
% bMinPhase - minimum phase FIR filter coefficients
%
% Author: Andreas Widmann, University of Leipzig, 2013
%
% References:
% [1] Smith III, O. J. (20... |
github | svndl/mrC-master | firws.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/firws.m | 3,219 | utf_8 | 0ab4c517238d31712ba1d97ab2497f45 | %firws() - Designs windowed sinc type I linear phase FIR filter
%
% Usage:
% >> b = firws(m, f);
% >> b = firws(m, f, w);
% >> b = firws(m, f, t);
% >> b = firws(m, f, t, w);
%
% Inputs:
% m - filter order (mandatory even)
% f - vector or scalar of cutoff frequency/ies (-6 dB;
% pi rad / sample)
%
% O... |
github | svndl/mrC-master | pop_firma.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/pop_firma.m | 3,356 | utf_8 | e6d49147b8406a5ac3fed31ab0809194 | % pop_firma() - Filter data using moving average FIR filter
%
% Usage:
% >> [EEG, com] = pop_firma(EEG); % pop-up window mode
% >> [EEG, com] = pop_firma(EEG, 'forder', order);
%
% Inputs:
% EEG - EEGLAB EEG structure
% 'forder' - scalar filter order. Mandatory even
%
% Outputs:
% EEG - filtered ... |
github | svndl/mrC-master | pop_firpm.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/pop_firpm.m | 7,885 | utf_8 | c7719de703135804f12c5877e899956b | % pop_firpm() - Filter data using Parks-McClellan FIR filter
%
% Usage:
% >> [EEG, com, b] = pop_firpm(EEG); % pop-up window mode
% >> [EEG, com, b] = pop_firpm(EEG, 'key1', value1, 'key2', ...
% value2, 'keyn', valuen);
%
% Inputs:
% EEG - EEGLAB EEG structure
% 'fcutoff' -... |
github | svndl/mrC-master | pop_eegfiltnew.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/pop_eegfiltnew.m | 8,458 | utf_8 | 568c652401a53a0b370d55e248775e5a | % pop_eegfiltnew() - Filter data using Hamming windowed sinc FIR filter
%
% Usage:
% >> [EEG, com, b] = pop_eegfiltnew(EEG); % pop-up window mode
% >> [EEG, com, b] = pop_eegfiltnew(EEG, locutoff, hicutoff, filtorder,
% revfilt, usefft, plotfreqz, minphase);
%
% Inputs:
% EEG ... |
github | svndl/mrC-master | pop_xfirws.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/pop_xfirws.m | 10,425 | utf_8 | d0777a1329eeb3b766e505a0b61242c9 | % pop_xfirws() - Design and export xfir compatible windowed sinc FIR filter
%
% Usage:
% >> pop_xfirws; % pop-up window mode
% >> [b, a] = pop_xfirws; % pop-up window mode
% >> pop_xfirws('key1', value1, 'key2', value2, 'keyn', valuen);
% >> [b, a] = pop_xfirws('key1', value1, 'key2', value2, 'keyn', valuen);
%... |
github | svndl/mrC-master | firfiltsplit.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/firfiltsplit.m | 2,363 | utf_8 | 8e58b4fa2694a8b1d55b8fcddcf94b4f | % firfiltsplit() - Split data at discontinuities and forward to dc padded
% filter function
%
% Usage:
% >> EEG = firfiltsplit(EEG, b);
%
% Inputs:
% EEG - EEGLAB EEG structure
% b - vector of filter coefficients
% causal - scalar boolean perform causal filtering {d... |
github | svndl/mrC-master | eegplugin_firfilt.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/eegplugin_firfilt.m | 2,667 | utf_8 | 681ba5e0933cafd6bb95672f910816cd | % eegplugin_firfilt() - EEGLAB plugin for filtering data using linear-
% phase FIR filters
%
% Usage:
% >> eegplugin_firfilt(fig, trystrs, catchstrs);
%
% Inputs:
% fig - [integer] EEGLAB figure
% trystrs - [struct] "try" strings for menu callbacks.
% catchstrs - [struct] "catc... |
github | svndl/mrC-master | windows.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/windows.m | 2,876 | utf_8 | 581c2f660f641935667a234f9b024f3a | % windows() - Returns handle to window function or window
%
% Usage:
% >> h = windows(t);
% >> h = windows(t, m);
% >> h = windows(t, m, a);
%
% Inputs:
% t - char array 'rectangular', 'bartlett', 'hann', 'hamming',
% 'blackman', 'blackmanharris', or 'kaiser'
%
% Optional inputs:
% m - scalar window len... |
github | svndl/mrC-master | pop_firpmord.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/pop_firpmord.m | 3,145 | utf_8 | f4dae3b8e73f8ab3d73c2d207506ddd8 | % pop_firpmord() - Estimate Parks-McClellan filter order and weights
%
% Usage:
% >> [m, wtpass, wtstop] = pop_firpmord(f, a); % pop-up window mode
% >> [m, wtpass, wtstop] = pop_firpmord(f, a, dev);
% >> [m, wtpass, wtstop] = pop_firpmord(f, a, dev, fs);
%
% Inputs:
% f - vector frequency band edges
% ... |
github | svndl/mrC-master | firfilt.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/firfilt.m | 4,262 | utf_8 | d5703bbd52180bfb0661e6db5e649967 | % firfilt() - Pad data with DC constant, filter data with FIR filter,
% and shift data by the filter's group delay
%
% Usage:
% >> EEG = firfilt(EEG, b, nFrames);
%
% Inputs:
% EEG - EEGLAB EEG structure
% b - vector of filter coefficients
%
% Optional inputs:
% nFrames -... |
github | svndl/mrC-master | pop_firws.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/pop_firws.m | 10,634 | utf_8 | 830347cf85c318140462a11e9257b53b | % pop_firws() - Filter data using windowed sinc FIR filter
%
% Usage:
% >> [EEG, com, b] = pop_firws(EEG); % pop-up window mode
% >> [EEG, com, b] = pop_firws(EEG, 'key1', value1, 'key2', ...
% value2, 'keyn', valuen);
%
% Inputs:
% EEG - EEGLAB EEG structure
% 'fcutoff' - v... |
github | svndl/mrC-master | plotfresp.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/plotfresp.m | 3,898 | utf_8 | 71a74a912328b37353e1523b662840fa | % plotfresp() - Plot FIR filter's impulse, step, frequency, magnitude,
% and phase response
%
% Usage:
% >> plotfresp(b, a, n, fs);
%
% Inputs:
% b - vector filter coefficients
%
% Optional inputs:
% a - currently unused, reserved for future compatibility with IIR
% filters {defaul... |
github | svndl/mrC-master | pop_firwsord.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/pop_firwsord.m | 5,354 | utf_8 | 5150d668b377feb0d9e95b49486978ca | % pop_firwsord() - Estimate windowed sinc filter order depending on
% window type and requested transition band width
%
% Usage:
% >> [m, dev] = pop_firwsord; % pop-up window mode
% >> m = pop_firwsord(wtype, fs, df);
% >> m = pop_firwsord('kaiser', fs, df, dev);
%
% Inputs:
% wtype - char arra... |
github | svndl/mrC-master | pop_kaiserbeta.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/pop_kaiserbeta.m | 2,315 | utf_8 | 9a8a6636653865493068a0e901deeda6 | % pop_kaiserbeta() - Estimate Kaiser window beta
%
% Usage:
% >> [beta, dev] = pop_kaiserbeta; % pop-up window mode
% >> beta = pop_kaiserbeta(dev);
%
% Inputs:
% dev - scalar maximum passband deviation/ripple
%
% Output:
% beta - scalar Kaiser window beta
% dev - scalar maximum passband devi... |
github | svndl/mrC-master | findboundaries.m | .m | mrC-master/external/eeglab14_1_1b/plugins/firfilt1.6.2/findboundaries.m | 1,867 | utf_8 | b4b28dadb5f28c802c41266f791d942c | % findboundaries() - Find boundaries (data discontinuities) in event
% structure of continuous EEG dataset
%
% Usage:
% >> boundaries = findboundaries(EEG.event);
%
% Inputs:
% EEG.event - EEGLAB EEG event structure
%
% Outputs:
% boundaries - scalar or vector of boundary event latencies... |
github | svndl/mrC-master | pop_dipfit_manual.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/pop_dipfit_manual.m | 1,755 | utf_8 | eba5714bbc90a749dad3cbbf6d51a4d7 | % pop_dipfit_manual() - interactively do dipole fit of selected ICA components
% Function deprecated. Use pop_dipfit_nonlinear()
% instead
% Usage:
% >> OUTEEG = pop_dipfit_manual( INEEG )
%
% Inputs:
% INEEG input dataset
%
% Outputs:
% OUTEEG output dataset... |
github | svndl/mrC-master | eeglab2fieldtrip.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/eeglab2fieldtrip.m | 5,810 | utf_8 | bebbd3c516538fee4fe6182dcd06e54c | % eeglab2fieldtrip() - do this ...
%
% Usage: >> data = eeglab2fieldtrip( EEG, fieldbox, transform );
%
% Inputs:
% EEG - [struct] EEGLAB structure
% fieldbox - ['preprocessing'|'freqanalysis'|'timelockanalysis'|'companalysis']
% transform - ['none'|'dipfit'] transform channel locations for DIPFIT
% ... |
github | svndl/mrC-master | dipfit_reject.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/dipfit_reject.m | 1,823 | utf_8 | 7d157ab7d3da320a78bb851d5d3b5669 | % dipfit_reject() - remove dipole models with a poor fit
%
% Usage:
% >> dipout = dipfit_reject( model, reject )
%
% Inputs:
% model struct array with a dipole model for each component
%
% Outputs:
% dipout struct array with a dipole model for each component
%
% Author: Robert Oostenveld, SMI/FCDC, Nijmegen 2003
... |
github | svndl/mrC-master | pop_dipplot.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/pop_dipplot.m | 8,649 | utf_8 | f0e67d40c3bd34a95443673ebb76b95b | % pop_dipplot() - plot dipoles.
%
% Usage:
% >> pop_dipplot( EEG ); % pop up interactive window
% >> pop_dipplot( EEG, comps, 'key1', 'val1', 'key2', 'val2', ...);
%
% Graphic interface:
% "Components" - [edit box] enter component number to plot. By
% all the localized components are plotted. Comma... |
github | svndl/mrC-master | dipplot.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/dipplot.m | 61,455 | utf_8 | 1bc351e760494d6b9df714acf3a089ed | % dipplot() - Visualize EEG equivalent-dipole locations and orientations
% in the MNI average MRI head or in the BESA spherical head model.
% Usage:
% >> dipplot( sources, 'key', 'val', ...);
% >> [sources X Y Z XE YE ZE] = dipplot( sources, 'key', 'val', ...);
%
% Inputs:
% sources - structure a... |
github | svndl/mrC-master | fieldtripchan2eeglab.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/fieldtripchan2eeglab.m | 1,612 | utf_8 | 0328813bbaaba65a3bcfde10ecb26e8b | % fieldtripchan2eeglab() - convert Fieldtrip channel location structure
% to EEGLAB channel location structure
%
% Usage:
% >> chanlocs = fieldtripchan2eeglab( fieldlocs );
%
% Inputs:
% fieldlocs - Fieldtrip channel structure. See help readlocs()
%
% Outputs:
% chanlocs - EEGLAB channel... |
github | svndl/mrC-master | sph2spm.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/sph2spm.m | 3,331 | utf_8 | 67c8de53ef88fdbaa69eea504e17997b | % sph2spm() - compute homogenous transformation matrix from
% BESA spherical coordinates to SPM 3-D coordinate
%
% Usage:
% >> trans = sph2spm;
%
% Outputs:
% trans - homogenous transformation matrix
%
% Note: head radius for spherical model is assumed to be 85 mm.
%
% Author: Robert Oostenveld, SMI/FC... |
github | svndl/mrC-master | homogenous2traditional.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/homogenous2traditional.m | 5,576 | utf_8 | 1cd0a7b795501f24b35360ecec62e420 | function f = homogenous2traditional(H)
% HOMOGENOUS2TRADITIONAL estimates the traditional translation, rotation
% and scaling parameters from a homogenous transformation matrix. It will
% give an error if the homogenous matrix also describes a perspective
% transformation.
%
% Use as
% f = homogenous2traditional(H)
... |
github | svndl/mrC-master | electroderealign.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/electroderealign.m | 26,943 | utf_8 | c09b21089e582b6d28a1fc065011b317 | function [norm] = electroderealign(cfg);
% ELECTRODEREALIGN rotates and translates electrode positions to
% template electrode positions or towards the head surface. It can
% either perform a rigid body transformation, in which only the
% coordinate system is changed, or it can apply additional deformations
% to the i... |
github | svndl/mrC-master | pop_dipfit_nonlinear.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/pop_dipfit_nonlinear.m | 19,264 | utf_8 | 38b5b9d5f0129b1a4aaf3230c2578eac | % pop_dipfit_nonlinear() - interactively do dipole fit of selected ICA components
%
% Usage:
% >> EEGOUT = pop_dipfit_nonlinear( EEGIN )
%
% Inputs:
% EEGIN input dataset
%
% Outputs:
% EEGOUT output dataset
%
% Author: Robert Oostenveld, SMI/FCDC, Nijmegen 2003
% Arnaud Delorme, SCCN, La Jolla... |
github | svndl/mrC-master | dipfit_1_to_2.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/dipfit_1_to_2.m | 2,252 | utf_8 | 1a1a49c9adb0d94ff59b4a2206a3f2f4 | % dipfit_1_to_2() - convert dipfit 1 structure to dipfit 2 structure.
%
% Usage:
% >> EEG.dipfit = dipfit_1_to_2(EEG.dipfit);
%
% Note:
% For non-standard BESA models (where the radii or the conductances
% have been modified, users must create a new model in Dipfit2 from
% the default BESA model.
%
% Author: Arnaud D... |
github | svndl/mrC-master | dipfit_gridsearch.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/dipfit_gridsearch.m | 4,519 | utf_8 | cc77806c9d0a7de350e540a72dc1c033 | % dipfit_gridsearch() - do initial batch-like dipole scan and fit to all
% data components and return a dipole model with a
% single dipole for each component.
%
% Usage:
% >> EEGOUT = dipfit_gridsearch( EEGIN, varargin)
%
% Inputs:
% ...
%
% Optional inputs:
% 'com... |
github | svndl/mrC-master | eegplugin_dipfit.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/eegplugin_dipfit.m | 4,444 | utf_8 | 2bcef6898d8184014480e6ed4f2e170b | % eegplugin_dipfit() - DIPFIT plugin version 2.0 for EEGLAB menu.
% DIPFIT is the dipole fitting Matlab Toolbox of
% Robert Oostenveld (in collaboration with A. Delorme).
%
% Usage:
% >> eegplugin_dipfit(fig, trystrs, catchstrs);
%
% Inputs:
% fig - [integer] eegla... |
github | svndl/mrC-master | pop_multifit.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/pop_multifit.m | 10,370 | utf_8 | dd98129d0df98fcdfc6532ff87983696 | % pop_multifit() - fit multiple component dipoles using DIPFIT
%
% Usage:
% >> EEG = pop_multifit(EEG); % pop-up graphical interface
% >> EEG = pop_multifit(EEG, comps, 'key', 'val', ...);
%
% Inputs:
% EEG - input EEGLAB dataset.
% comps - indices component to fit. Empty is all components.
%... |
github | svndl/mrC-master | pop_dipfit_gridsearch.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/pop_dipfit_gridsearch.m | 4,833 | utf_8 | 39566131e1f04827a5eaf4dd7994f07f | % pop_dipfit_gridsearch() - scan all ICA components with a single dipole
% on a regular grid spanning the whole brain. Any dipoles that explains
% a component with a too large relative residual variance is removed.
%
% Usage:
% >> EEGOUT = pop_dipfit_gridsearch( EEGIN ); % pop up interactive window
% >> EEGO... |
github | svndl/mrC-master | dipfit_erpeeg.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/dipfit_erpeeg.m | 3,634 | utf_8 | c387b5b84e9f4ee03b832f289837c1a2 | % dipfit_erpeeg - fit multiple component dipoles using DIPFIT
%
% Usage:
% >> [ dipole model EEG] = dipfit_erpeeg(data, chanlocs, 'key', 'val', ...);
%
% Inputs:
% data - input data [channel x point]. One dipole per point is
% returned.
% chanlocs - channel location structure (returned by ... |
github | svndl/mrC-master | pop_dipfit_batch.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/pop_dipfit_batch.m | 2,342 | utf_8 | 349fbd140a3ba8c11fce24b8db9fa20c | % pop_dipfit_batch() - interactively do batch scan of all ICA components
% with a single dipole
% Function deprecated. Use pop_dipfit_gridsearch()
% instead
%
% Usage:
% >> OUTEEG = pop_dipfit_batch( INEEG ); % pop up interactive window
% >> OUTEEG = pop... |
github | svndl/mrC-master | dipfit_nonlinear.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/dipfit_nonlinear.m | 4,979 | utf_8 | 74c08245e5fcd0c004b5c7b3357238cf | % dipfit_nonlinear() - perform nonlinear dipole fit on one of the components
% to improve the initial dipole model. Only selected dipoles
% will be fitted.
%
% Usage:
% >> EEGOUT = dipfit_nonlinear( EEGIN, optarg)
%
% Inputs:
% ...
%
% Optional inputs are specified in key/value ... |
github | svndl/mrC-master | adjustcylinder2.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/adjustcylinder2.m | 2,197 | utf_8 | 34ff5cb12c3fc11a2456e7d82aedd980 | % adjustcylinder() - Adjust 3d object coordinates to match a pair of points
%
% Usage:
% >> [x y z] = adjustcylinder( x, y, z, pos1, pos2);
%
% Inputs:
% x,y,z - 3-D point coordinates
% pos1 - position of first point [x y z]
% pos2 - position of second point [x y z]
%
% Outputs:
% x,y,z - up... |
github | svndl/mrC-master | pop_dipfit_settings.m | .m | mrC-master/external/eeglab14_1_1b/plugins/dipfit2.3/pop_dipfit_settings.m | 20,001 | utf_8 | 7ef22305183621c09beb2691d0250fd9 | % pop_dipfit_settings() - select global settings for dipole fitting through a pop up window
%
% Usage:
% >> OUTEEG = pop_dipfit_settings ( INEEG ); % pop up window
% >> OUTEEG = pop_dipfit_settings ( INEEG, 'key1', 'val1', 'key2', 'val2' ... )
%
% Inputs:
% INEEG input dataset
%
% Optional inputs:
% 'hdmfile' ... |
github | dbindel/cs6210-f16-master | arnoldi.m | .m | cs6210-f16-master/lec/code/iter/arnoldi.m | 711 | utf_8 | 76d701193f6f177df1b9325c6cac9f36 | % [Q,H] = arnoldi(A,b)
%
% Compute an Arnoldi decomposition
%
% A*Q(:,1:end-1) = Q*H
%
% where H is a k+1-by-k upper Hessenberg matrix and Q has
% orthonormal columns.
%
function [Q,H] = arnoldi(A,b,k)
n = length(A);
Q = zeros(n,k+1); % Orthonormal basis
H = zeros(k+1,k); % Upper Hessenberg matrix
Q(:,1... |
github | dbindel/cs6210-f16-master | idst.m | .m | cs6210-f16-master/lec/code/iter/idst.m | 136 | utf_8 | 7fb137a23e8750dd1176f8e12ac05267 | % [TX] = idst(X)
%
% The inverse DST is X = 2/(n+1) * dst(TX).
%
function [X] = idst(TX)
m = size(TX,1);
X = 2/(m+1) * dst(TX);
end
|
github | dbindel/cs6210-f16-master | solve_dst.m | .m | cs6210-f16-master/lec/code/iter/solve_dst.m | 292 | utf_8 | d1cf1628b70c27876cfc849d2bd5184c | % [X] = solve_dst(F)
%
% Use discrete sine transforms to solve the 2D Poisson problem
% T*X + X*T = F
%
function [X] = solve_dst(F)
n = size(F,1);
lambda = zeros(n,1);
lambda(:) = 2*(1-cos(pi/(n+1)*(1:n)));
e = ones(n,1);
L = lambda*e' + e*lambda';
X = idst2d(dst2d(F)./L);
end
|
github | dbindel/cs6210-f16-master | sweep_gs_rb.m | .m | cs6210-f16-master/lec/code/iter/sweep_gs_rb.m | 391 | utf_8 | 07fe8c1064ddb5a4a2acda2d8b35ed25 | % [U] = sweep_gs_rb(U, F)
%
% Run one Gauss-Seidel sweep for 2D Poisson (red-black ordering)
%
function [U] = sweep_gs_rb(U, F);
n = size(U,1)-2;
h2 = 1/(n+1)^2;
for c = 0:1
for j = 2:n+1
for i = 2:n+1
if mod(i+j,2) == c
U(i,j) = (U(i-1,j) + U(i+1,j) + ...
U(i,j-... |
github | dbindel/cs6210-f16-master | convert_v2m.m | .m | cs6210-f16-master/lec/code/iter/convert_v2m.m | 266 | utf_8 | b03f2fff699ab6bcb06a87a5795339a3 | % [U] = convert_v2m(u)
%
% Convert from a vec'd representation of a field on a 2D mesh
% to a 2D array representation (with zero padding at boundary)
%
function [U] = convert_v2m(u)
n = sqrt(length(u));
U = zeros(n+2,n+2);
U(2:n+1,2:n+1) = reshape(u,n,n);
end
|
github | dbindel/cs6210-f16-master | lanczos.m | .m | cs6210-f16-master/lec/code/iter/lanczos.m | 648 | utf_8 | 6a97fd242faa8dfdbae54fea95be59a7 | % [Q,alpha,beta] = lanczos(A,b)
%
% Compute an Lanczos decomposition
%
% A*Q(:,1:end-1) = Q*T
%
% where T is a k+1-by-k tridiagonal matrix with diagonal
% entries alpha and super/subdiagonals beta, and Q has
% orthonormal columns.
%
function [Q,H] = lanczos(A,b,k)
n = length(A);
Q = zeros(n,k+1); % Orthonormal... |
github | dbindel/cs6210-f16-master | arnoldi2.m | .m | cs6210-f16-master/lec/code/iter/arnoldi2.m | 1,147 | utf_8 | 4dd12ff97f3f5d6fe7711afd650ee0b4 | % [Q,H] = arnoldi2(A,b)
%
% Compute an Arnoldi decomposition
%
% A*Q(:,1:end-1) = Q*H
%
% where H is a k+1-by-k upper Hessenberg matrix and Q has
% orthonormal columns. We use MGS, and make a second
% re-orthogonalization pass if there is enough cancellation
% in the first pass.
%
function [Q,H] = arnoldi2(A,b,k)
... |
github | dbindel/cs6210-f16-master | sweep_adi.m | .m | cs6210-f16-master/lec/code/iter/sweep_adi.m | 487 | utf_8 | 2f7a63b71cf11150ae879ce51e9139e1 | % [U] = sweep_adi(U, F)
%
% Run one ADI sweep for 2D Poisson (single shift)
%
function [U] = sweep_adi(U, F);
n = size(U,1)-2;
I = 2:n+1;
h2 = 1/(n+1)^2;
dt = 1/(n+1);
Ts = spdiags(ones(n,1)*[-1, 2+dt, -1], [-1, 0, 1], n, n);
% Iterate on Ts*U + U*Ts = h^2*F + 2*dt*U where Ts = T+dt*I:
% Ts*U = h^2*F... |
github | dbindel/cs6210-f16-master | dst.m | .m | cs6210-f16-master/lec/code/iter/dst.m | 345 | utf_8 | f70faa1558c40c16ae45eac7c05851c0 | % [TX] = dst(X)
%
% Use FFTs to compute T*X where T is the discrete sine transform
% matrix with entries
%
% T(i,j) = sin(i*j*pi/(n+1));
%
% The inverse DST is X = 2/(n+1) * dst(TX).
%
function [TX] = dst(X)
[m,n] = size(X);
Y = zeros(2*m+2,n);
Y(2:m+1,:) = X;
Y(m+3:end,:) = -flipud(X);
TX = imag(fft(Y)/2);... |
github | dbindel/cs6210-f16-master | model2d_resid.m | .m | cs6210-f16-master/lec/code/iter/model2d_resid.m | 249 | utf_8 | 955523e94baec7f440d75eaa747cf64f | % [R] = model2d_resid(U, F)
%
% Compute residual r = T*u-h^2*f
%
function [R] = model2d_resid(U, F);
n = size(U,1);
h2 = 1/(n+1)^2;
I = 2:n+1;
R = 4*U(I,I) - U(I,I-1) - U(I,I+1) ...
- U(I-1,I) - U(I+1,I) - h2*F(I,I);
end
|
github | dbindel/cs6210-f16-master | sweep_gs.m | .m | cs6210-f16-master/lec/code/iter/sweep_gs.m | 289 | utf_8 | 1ba41df2ad542c47166e11b75098b5db | % [U] = sweep_gs(U, F)
%
% Run one Gauss-Seidel sweep for 2D Poisson
%
function [U] = sweep_gs(U, F);
n = size(U,1)-2;
h2 = 1/(n+1)^2;
for j = 2:n+1
for i = 2:n+1
U(i,j) = (U(i-1,j) + U(i+1,j) + ...
U(i,j-1) + U(i,j+1) + h2*F(i,j))/4;
end
end
end
|
github | dbindel/cs6210-f16-master | sweep_jacobi.m | .m | cs6210-f16-master/lec/code/iter/sweep_jacobi.m | 307 | utf_8 | e4b041665ff97ff9ddd22498a69117e4 | % [Unew] = sweep_jacobi(U, F)
%
% Run one Jacobi sweep for 2D Poisson
%
function [Un] = sweep_jacobi(U, F);
n = size(U,1)-2;
h2 = 1/(n+1)^2;
Un = U;
for j = 2:n+1
for i = 2:n+1
Un(i,j) = (U(i-1,j) + U(i+1,j) + ...
U(i,j-1) + U(i,j+1) + h2*F(i,j))/4;
end
end
end
|
github | dbindel/cs6210-f16-master | convert_m2v.m | .m | cs6210-f16-master/lec/code/iter/convert_m2v.m | 202 | utf_8 | d0b26db71e83c17a4451ab98b963ade8 | % [u] = convert_m2v(U)
%
% Convert from a 2D mesh representation of a field to a vec'd
% representation
%
function [u] = convert_v2m(U)
n = size(U,1)-2;
u = reshape(U(2:end-1,2:end-1), n*n, 1);
end
|
github | dbindel/cs6210-f16-master | model2d.m | .m | cs6210-f16-master/lec/code/iter/model2d.m | 840 | utf_8 | 73b39bd06b57a5c00187cef5b3ee9df7 | % [T, u, f, h] = model2d(n)
%
% Set up
% h^-2 * T * u = f
% where h^{-2} T is the discretized 2D Poisson problem on [0,1]^2
% with Dirichlet BCs using an (n+2)-by-(n+2) grid (including the
% constrained boundary nodes).
%
function [h, T, f, u] = model2d(n)
% Construct the (sparse) 1D model matrix
B = -ones(n,3)... |
github | dbindel/cs6210-f16-master | idst2d.m | .m | cs6210-f16-master/lec/code/iter/idst2d.m | 164 | utf_8 | 495979fbb865ea7c456fa0b008dbd82a | % [TX] = idst2d(X)
%
% The inverse DST is X = 4/(n+1)/(m+1) * dst2d(TX).
%
function [X] = idst2d(TX)
[m,n] = size(TX);
X = 4/prod((m+1)*(n+1)) * dst2d(TX);
end
|
github | dbindel/cs6210-f16-master | hessqr_basic.m | .m | cs6210-f16-master/lec/code/eigen/hessqr_basic.m | 616 | utf_8 | cff03c5ccf926476668b7ddac9f53c16 | % [H] = hessqr_basic(H)
%
% Compute one basic (unshifted) implicit Hessenberg QR step via
% Householder transformations.
%
function H = hessqr_basic(H)
n = length(H);
V = zeros(2,n-1);
% Compute the QR factorization
for j = 1:n-1
% -- Find W_j = I-2vv' to put zero into H(j+1,j)
u = H(j:j+1,j);
... |
github | dbindel/cs6210-f16-master | hessred.m | .m | cs6210-f16-master/lec/code/eigen/hessred.m | 620 | utf_8 | 731704d011f6fa652b7fa9cae0ae57ed | % [H,Q] = hessred(A)
%
% Compute the Hessenberg decomposition H = Q'*A*Q using
% Householder transformations.
%
function [H,Q] = hessred(A)
n = length(A);
Q = eye(n); % Orthogonal transform so far
H = A; % Transformed matrix so far
for j = 1:n-2
% -- Find W = I-2vv' to put zeros below H(j+... |
github | dbindel/cs6210-f16-master | subspace.m | .m | cs6210-f16-master/lec/code/eigen/subspace.m | 1,288 | utf_8 | 25ebe9934e8c72cd885422097a7393c8 | % [v,lambda] = subspace(A, k, V, maxiter, rtol)
%
% Orthogonal iteration to compute the dominant invariant subspace of A.
%
% Inputs:
% A: Matrix to be analyzed
% k: Dimension of subspace
% v: Start vector (default random)
% maxiter: Maximum number of iterations allowed (default 1000)
% rtol: Rel residual tol... |
github | dbindel/cs6210-f16-master | hessqr.m | .m | cs6210-f16-master/lec/code/eigen/hessqr.m | 554 | utf_8 | 1c72178c417aeddf3c128080479e4a70 | % [H] = hessqr(H)
%
% Toy implementation of Hessenberg QR iteration with Francis double
% shift strategy and deflation.
%
function [H] = hessqr(H)
n = length(H);
tol = norm(H,'fro') * 1e-8;
k = 0;
while n > 2
if abs(H(n,n-1)) < tol
fprintf('At step %d: Deflated 1-by-1 block\n', k);
H(n,n-1) = 0... |
github | dbindel/cs6210-f16-master | hessqr_francis.m | .m | cs6210-f16-master/lec/code/eigen/hessqr_francis.m | 977 | utf_8 | fef8ae6fdfefc615d748ff5e98d34156 | % [H] = hessqr_francis(H)
%
% Compute a (double) implicit Hessenberg QR step with Francis shift.
% Compare to hessqr_basic.
%
function [H] = hessqr_francis(H)
% Implicit QR step using a Francis double shift
% (there should really be some re-scalings for floating point)
% Compute double-shift poly and initial col... |
github | dbindel/cs6210-f16-master | jacobi_rot.m | .m | cs6210-f16-master/lec/code/eigen/jacobi_rot.m | 424 | utf_8 | 9e990d2834390fdad0e5e1f212beaaa2 | % [J] = jacobi(alpha, beta, gamma)
%
% Compute the Jacobi rotation
%
% [ c -s ] [ alpha beta ] [ c s ] = [ alpha_new 0 ]
% [ s c ] [ beta gamma ] [ -s c ] [ 0 beta_new ]
%
function [J] = jacobi_rot(alpha, beta, gamma)
if beta == 0
J = [1, 0; 0, 1];
else
b = (gamma-alpha)/2/beta;
... |
github | dbindel/cs6210-f16-master | francis_poly.m | .m | cs6210-f16-master/lec/code/eigen/francis_poly.m | 801 | utf_8 | 8a04b9224c1ba752310bcc82763bca19 | % [b,c] = francis_poly(H)
%
% Compute b, c s.t. z^2 + b*z + c = (z-sigma)(z-conj(sigma))
% where sigma is the Francis double shift for H.
%
function [b,c] = francis_poly(H)
% Get shifts via trailing submatrix
HH = H(end-1:end,end-1:end);
trHH = HH(1,1)+HH(2,2);
detHH = HH(1,1)*HH(2,2)-HH(1,2)*HH(2,1);
i... |
github | dbindel/cs6210-f16-master | power.m | .m | cs6210-f16-master/lec/code/eigen/power.m | 1,350 | utf_8 | d774370e81bc8fe786f28c3384e53d16 | % [v,lambda] = power(A, v, maxiter, rtol)
%
% Run power iteration to compute the dominant eigenvalue of A and
% an associated eigenvector. This will fail in general if there are
% multiple dominant eigenvalues (e.g. from a complex conjugate pair).
%
% Inputs:
% A: Matrix to be analyzed
% v: Start vector (default r... |
github | dbindel/cs6210-f16-master | jacobi_sweep.m | .m | cs6210-f16-master/lec/code/eigen/jacobi_sweep.m | 393 | utf_8 | b546180803c0c870b0115f53b23cb1a5 | % [A] = jacobi_sweep(A, nsweeps)
%
% Apply nsweeps Jacobi iteration sweeps (default is 1).
%
function [A] = jacobi_sweep(A, nsweeps)
n = length(A);
if nargin < 2, nsweeps = 1; end
for sweep = 1:nsweeps
for k = 2:n
for l = 1:k-1
J = jacobi_rot(A(k,k), A(k,l), A(l,l));
A([k l], :) = J'*A... |
github | dbindel/cs6210-f16-master | rqi.m | .m | cs6210-f16-master/lec/code/eigen/rqi.m | 1,312 | utf_8 | 6af04d86151d699dcd3bc3a2c63c491a | % [v,lambda] = rqi(A, sigma, v, maxiter, rtol)
%
% Run Rayleigh quotient iteration to compute an eigenpair of A.
%
% Inputs:
% A: Matrix to be analyzed
% sigma: Initial shift
% v: Start vector (default random)
% maxiter: Maximum number of iterations allowed (default 1000)
% rtol: Rel residual tolerance for co... |
github | apennisi/fast_face_detector-master | acfDetectIntegral.m | .m | fast_face_detector-master/matlab/acfDetectIntegral.m | 3,863 | utf_8 | bb6d6109e536b454b799cc34e9ababed | function bbs = acfDetectIntegral( I, detector, fileName )
% Run aggregate channel features object detector on given image(s).
%
% The input 'I' can either be a single image (or filename) or a cell array
% of images (or filenames). In the first case, the return is a set of bbs
% where each row has the format [x y w h sc... |
github | apennisi/fast_face_detector-master | chnsComputeIntegral.m | .m | fast_face_detector-master/matlab/chnsComputeIntegral.m | 9,681 | utf_8 | fcf635200b3a6a74008820aeca526d20 | function chns = chnsComputeIntegral( I, G, varargin )
% Compute channel features at a single scale given an input image.
%
% Compute the channel features as described in:
% P. Doll?r, Z. Tu, P. Perona and S. Belongie
% "Integral Channel Features", BMVC 2009.
% Channel features have proven very effective in sliding wi... |
github | apennisi/fast_face_detector-master | jitterImage.m | .m | fast_face_detector-master/matlab/jitterImage.m | 5,252 | utf_8 | 3310f8412af00fd504c6f94b8c48992c | function IJ = jitterImage( I, varargin )
% Creates multiple, slightly jittered versions of an image.
%
% Takes an image I, and generates a number of images that are copies of the
% original image with slight translation, rotation and scaling applied. If
% the input image is actually an MxNxK stack of images then applie... |
github | apennisi/fast_face_detector-master | chnsPyramidIntegral.m | .m | fast_face_detector-master/matlab/chnsPyramidIntegral.m | 11,130 | utf_8 | 7efb00042e5fc572ee75bca1441b64ea | function pyramid = chnsPyramidIntegral( I, varargin )
% Compute channel feature pyramid given an input image.
%
% While chnsCompute() computes channel features at a single scale,
% chnsPyramid() calls chnsCompute() multiple times on different scale
% images to create a scale-space pyramid of channel features.
%
% In it... |
github | apennisi/fast_face_detector-master | acfTrainIntegral.m | .m | fast_face_detector-master/matlab/acfTrainIntegral.m | 17,026 | utf_8 | 798c35725887fd71d470aa74e78d806b | function detector = acfTrainIntegral( varargin )
% Train aggregate channel features object detector.
%
% Train aggregate channel features (ACF) object detector as described in:
% P. Doll?r, R. Appel, S. Belongie and P. Perona
% "Fast Feature Pyramids for Object Detection", PAMI 2014.
% The ACF detector is fast (30 f... |
github | apennisi/fast_face_detector-master | checkNumArgs.m | .m | fast_face_detector-master/matlab/checkNumArgs.m | 3,796 | utf_8 | 726c125c7dc994c4989c0e53ad4be747 | function [ x, er ] = checkNumArgs( x, siz, intFlag, signFlag )
% Helper utility for checking numeric vector arguments.
%
% Runs a number of tests on the numeric array x. Tests to see if x has all
% integer values, all positive values, and so on, depending on the values
% for intFlag and signFlag. Also tests to see if ... |
github | apennisi/fast_face_detector-master | acfModifyIntegral.m | .m | fast_face_detector-master/matlab/acfModifyIntegral.m | 4,243 | utf_8 | d891959c6fe88e79177dcf7c8fa44b9d | function detector = acfModify( detector, varargin )
% Modify aggregate channel features object detector.
%
% Takes an object detector trained by acfTrain() and modifies it. Only
% certain modifications are allowed to the detector and the detector should
% never be modified directly (this may cause the detector to be in... |
github | apennisi/fast_face_detector-master | bbGt.m | .m | fast_face_detector-master/matlab/bbGt.m | 34,046 | utf_8 | 69e66c9a0cc143fb9a794fbc9233246e | function varargout = bbGt( action, varargin )
% Bounding box (bb) annotations struct, evaluation and sampling routines.
%
% bbGt gives access to two types of routines:
% (1) Data structure for storing bb image annotations.
% (2) Routines for evaluating the Pascal criteria for object detection.
%
% The bb annotation sto... |
github | apennisi/fast_face_detector-master | bbApply.m | .m | fast_face_detector-master/matlab/bbApply.m | 21,195 | utf_8 | 8c02a6999a84bfb5fcbf2274b8b91a97 | function varargout = bbApply( action, varargin )
% Functions for manipulating bounding boxes (bb).
%
% A bounding box (bb) is also known as a position vector or a rectangle
% object. It is a four element vector with the fields: [x y w h]. A set of
% n bbs can be stores as an [nx4] array, most funcitons below can handle... |
github | xioTechnologies/NGIMU-MATLAB-Real-Time-Example-master | getOscMessages.m | .m | NGIMU-MATLAB-Real-Time-Example-master/getOscMessages.m | 4,243 | utf_8 | 844fd296180eab6d15346a21536750df | function oscMessages = getOscMessages(charArray)
oscMessages = processOscPacket(charArray, NaN, []);
end
function oscMessages = processOscPacket(charArray, timestamp, oscMessages)
switch charArray(1)
% OSC contents is an OSC message
case '/'
oscMessage = processOscMessage(charArray);
... |
github | xioTechnologies/NGIMU-MATLAB-Real-Time-Example-master | gui.m | .m | NGIMU-MATLAB-Real-Time-Example-master/gui.m | 8,109 | utf_8 | 5b8ac5edaf2292d60c45f744e7a9cc38 | 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,... |
github | johndevitis/st7api-master | init.m | .m | st7api-master/init.m | 539 | utf_8 | aaf0da0bc289f8c600019293bfe69784 | %% init
%
% when called, this startup fcn adds all folders and subfolders in its root
% directory to matlab's search path
%
% jdv 06/22/2016
function init()
%% init
%
% when called, this startup fcn adds all folders and subfolders in its root
% directory to matlab's search path
%
% jdv 06/22/2016
% add all folders... |
github | johndevitis/st7api-master | PSO.m | .m | st7api-master/thirdparty/PSO.m | 14,601 | utf_8 | 580af5d4a21d0b84e5eea815399260fd | function [X,FVAL,EXITFLAG,OUTPUT] = PSO(FUN,X0,LB,UB,OPTIONS,varargin)
% PSO.m modified by John DeVitis - johndevitis@gmail.com - 5/24/2012
% - out dated random number seeding removed
%
%PSO finds a minimum of a function of several variables using the particle swarm
% optimization (PSO) algorithm originally intr... |
github | johndevitis/st7api-master | PSOGET.m | .m | st7api-master/thirdparty/PSOGET.m | 3,627 | utf_8 | 5c8948dc18db8e3bdce1d8c7adc8c6be | function VAL = PSOGET(OPTIONS,name,default,flag)
%PSOGET Get PSO OPTIONS parameters.
% VAL = PSOGET(OPTIONS,'NAME') extracts the value of the named parameter
% from optimization options structure OPTIONS, returning an empty matrix if
% the parameter value is not specified in OPTIONS. It is sufficient to
% type... |
github | johndevitis/st7api-master | makeindex.m | .m | st7api-master/thirdparty/makeindex.m | 9,848 | utf_8 | 6d8165ac6d835f02581f50b4dd18b87d | %% Function makeindex
%
% *Description*: Developed so to enable users to quickly publish directories
% of code and details of the cross function and global variable dependancies.
%
%% Details
%
% * Using the freely avalable grep tool this function parses m files in the
% current directory:
% * It will determine all... |
github | johndevitis/st7api-master | rdir.m | .m | st7api-master/thirdparty/rdir.m | 11,997 | utf_8 | c12efe1d6178d62af7ffb6db8365e7c1 | function [varargout] = rdir(rootdir,varargin)
% RDIR - Recursive directory listing
%
% D = rdir(ROOT)
% D = rdir(ROOT, TEST)
% D = rdir(ROOT, TEST, RMPATH)
% D = rdir(ROOT, TEST, 1)
% D = rdir(ROOT, '', ...)
% [D, P] = rdir(...)
% rdir(...)
%
%
% *Inputs*
%
% * ROOT
%
% rdir(ROOT) lists the specified files.
% R... |
github | johndevitis/st7api-master | apish.m | .m | st7api-master/code/apish.m | 3,016 | utf_8 | f4df4c042569f3369bf569e742f15eb1 | function apish(main,sys,model,opts,objectName)
%% Self-contained API execution wrapper
% SYNTAX: model = apish(main,model)
%
% default wrapper for handling API errors. can be used to copy/paste into a
% project for quick api work
%
%
% model.
% sys.
% pathname - root path
% filename - fe model file name
% scratc... |
github | johndevitis/st7api-master | main2.m | .m | st7api-master/code/main2.m | 2,812 | utf_8 | 6b56d4f6b1f31135cdeba306250e4440 | %% Update Function
% to be used with apish.m
% jbb
function results = main2(uID,model)
%% Main function, edit as you like.
% model contains all model parameters to be altered as well as any solver
% and system info
%% Get porperty names for material and section classes for future string comparison
info_m = ?materia... |
github | johndevitis/st7api-master | main.m | .m | st7api-master/code/main.m | 4,107 | utf_8 | c904c8b0fab7876598feff1a8b86386b | %% Main Function
% to be used with apish.m
% jdv
function results = main(uID,model)
%% Main function, edit as you like.
%% Node
% note the convention:
% node() is the object,
% nodes is the instance of the object.
% nodes = node(); % create instance of node class
% nodes.getUCSinfo(uI... |
github | johndevitis/st7api-master | update.m | .m | st7api-master/code/update.m | 2,601 | utf_8 | 24d3ea60efbdd5adbb6fb5c4cdfc1515 | %% Update Function
% to be used with apish.m
% jbb
function update(uID,optrun)
%% Updating function
%% -- Outdated --
% Use setModelProp and solver
%% Get porperty names for material and section classes for future string comparison
info_m = ?material;
matprop = {info_m.PropertyList.Name};
info_s = ?section;
sxnprop ... |
github | johndevitis/st7api-master | getBeamInfo.m | .m | st7api-master/code/@beam/getBeamInfo.m | 2,179 | utf_8 | 23136d905329d1b529f7cacffb9449c8 | function beam = getBeamInfo(uID,beamNum)
%% getBeamInfo
%
%
%
% author: john devitis
% create date: 15-Aug-2016 11:59:19
[propNum,propName] = getPropertyInfo(uID,beamNum);
materialName = getMaterialName(uID,propNum);
sectionName = getSectionName(uID,propNum);
[element,section,material] = getBeamP... |
github | johndevitis/st7api-master | getBeamResults.m | .m | st7api-master/code/results/getBeamResults.m | 3,818 | utf_8 | 77ef85b44f3d934cc38c1cb99c42b8ec | function results = getBeamResults(model,res,beamNums,lcNums)
%%
%
% returns:
% [beamNum, beamDesc, beamID]
%
% jdv 06152016
uID = 1; % default st7 model id
results = []; % make sure this exists
%-- API Execution Wrapper --%
try
results = Main(uID,model,res,lcNums,beamNums);
... |
github | johndevitis/st7api-master | plotPropVsFreq.m | .m | st7api-master/code/util/plotPropVsFreq.m | 788 | utf_8 | 2e56b7599a9b31e338f318a2b0eeed0c | %% plotSpringsVsFreq
%
% used for api sensitivity studies
%
% author: john braley
% create date: 13-Sep-2016
function plotPropVsFreq(model)
fh = figure('PaperPositionMode','auto');
ah = axes;
hold on
steps = length(model);
lins = {'+b','or','xg','*m'};
for ii = 1:steps
res... |
github | johndevitis/st7api-master | plotDeckMaterialVsFreq.m | .m | st7api-master/code/util/plotDeckMaterialVsFreq.m | 753 | utf_8 | 9c6440a1df2b7a3753cd4e9e89a97222 | %% plotDeckMaterialVsFreq
%
% used for api sensitivity studies
%
% author: john braley
% create date: 13-Sep-2016
function plotDeckMaterialVsFreq(results)
fh = figure('PaperPositionMode','auto');
ah = axes;
hold on
steps = length(results);
lins = {'+b','or','xg','*m'};
for jj = 1:... |
github | johndevitis/st7api-master | plotSpringsVsFreq.m | .m | st7api-master/code/util/plotSpringsVsFreq.m | 787 | utf_8 | 7d07315cfa3b386db1f2f8569290839c | %% plotSpringsVsFreq
%
% used for api sensitivity studies
%
% author: john devitis
% create date: 14-Aug-2016 14:58:56
function plotSpringsVsFreq(results)
fh = figure('PaperPositionMode','auto');
ah = axes;
hold on
steps = length(results);
lins = {'+b','or','xg','*m','ob'};
for jj ... |
github | johndevitis/st7api-master | snapcoords.m | .m | st7api-master/code/util/snapcoords.m | 677 | utf_8 | 71e86a6aa2cbff80b552571152c6f7bf | %% check/snap user coords to model coords
function slave = snapcoords(master,slave)
% error screen empty coords
if ~isfield(slave,'coords')
% if no coords, default to all nodes
slave.coords = master.coords;
slave.ind = master.coords(:,4);
elseif size(slave.coords,2) < 3
... |
github | johndevitis/st7api-master | plotSectionVsFreq.m | .m | st7api-master/code/util/plotSectionVsFreq.m | 758 | utf_8 | ec80c83836e31256a9040299e7084ff9 | %% plotSectionVsFreq
%
% used for api sensitivity studies
%
% author: john braley
% create date: 13-Sep-2016
function plotSectionVsFreq(results,field)
fh = figure('PaperPositionMode','auto');
ah = axes;
hold on
steps = length(results);
lins = {'+b','or','xg','*m'};
for jj = 1:resu... |
github | johndevitis/st7api-master | setModelProp.m | .m | st7api-master/code/util/setModelProp.m | 2,201 | utf_8 | b137da25f4df38cf92d2416496eadedb | %% SetModelProp Function
% to be used with apish.m
% jbb
% model - cell array of propmeter objects
function setModelProp(uID,model)
%% Get porperty names for material and section classes for future string comparison
info_m = ?material;
matprop = {info_m.PropertyList.Name};
info_s = ?section;
sxnprop = {info_s.Property... |
github | johndevitis/st7api-master | solver.m | .m | st7api-master/code/util/solver.m | 663 | utf_8 | 9ee1ee9576557ea4101065f924f95d20 | %% solver Function
% to be used with apish.m
% solvers - cell array with all of the solver instances
% jbb
function solver(uID,solvers)
% Loop through cell array
for ii = 1:length(solvers)
if isa(solvers,'cell')
solver = solvers{ii};
else
solver = solvers(ii);
en... |
github | johndevitis/st7api-master | plotDeckVsFreq.m | .m | st7api-master/code/util/plotDeckVsFreq.m | 737 | utf_8 | 7f741dc5218615496f4eb97a78871ab5 | %% plotSpringsVsFreq
%
% used for api sensitivity studies
%
% author: john braley
% create date: 13-Sep-2016
function plotDeckVsFreq(results)
fh = figure('PaperPositionMode','auto');
ah = axes;
hold on
steps = length(results);
lins = {'+b','or','xg','*m'};
for jj = 1:results(1).nf... |
github | johndevitis/st7api-master | plotCompVsFreq.m | .m | st7api-master/code/util/plotCompVsFreq.m | 805 | utf_8 | b262c5887df723e9a8f88a1e380eb453 | %% plotSectionVsFreq
%
% used for api sensitivity studies
%
% author: john braley
% create date: 13-Sep-2016
function plotCompVsFreq(results,field)
fh = figure('PaperPositionMode','auto');
ah = axes;
hold on
steps = length(results);
lins = {'+b','or','xg','*m','+r','og','xm','*b'};
... |
github | johndevitis/st7api-master | plotMaterialVsFreq.m | .m | st7api-master/code/util/plotMaterialVsFreq.m | 875 | utf_8 | d3f8c14f4eb4cad3a01888d268b7e12f | %% plotSpringsVsFreq
%
% used for api sensitivity studies
%
% author: john braley
% create date: 13-Sep-2016
function plotMaterialVsFreq(model)
fh = figure('PaperPositionMode','auto');
ah = axes;
hold on
steps = length(model);
lins = {'+b','or','xg','*m'};
for jj = 1:model(1).solv... |
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