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value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
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github | NOCIONS/letswave6-master | read_ctf_svl.m | .m | letswave6-master/external/fieldtrip/read_ctf_svl.m | 3,812 | utf_8 | d3442d0a013cf5e0a8d4277d99e45206 | % [data, hdr] = opensvl(filename)
%
% Reads a CTF SAM (.svl) file.
function [data, hdr] = read_ctf_svl(filename)
fid = fopen(filename, 'rb', 'ieee-be', 'ISO-8859-1');
if fid <= 0
error('Could not open SAM file: %s\n', filename);
end
% --------------------------------------------------------------... |
github | NOCIONS/letswave6-master | ft_struct2double.m | .m | letswave6-master/external/fieldtrip/ft_struct2double.m | 2,812 | utf_8 | 862ae4b495515d398d89bfab714c0e10 | function [x] = ft_struct2double(x, maxdepth)
% FT_STRUCT2DOUBLE converts all single precision numeric data in a structure
% into double precision. It will also convert plain matrices and
% cell-arrays.
%
% Use as
% x = ft_struct2double(x)
%
% Starting from MATLAB 7.0, you can use single precision data in your
% comp... |
github | NOCIONS/letswave6-master | read_erplabevent.m | .m | letswave6-master/external/fieldtrip/read_erplabevent.m | 1,786 | utf_8 | 40ece49ff6bd2afd6024b46f210e65fa | % read_erplabevent() - import ERPLAB dataset events
%
% Usage:
% >> event = read_erplabevent(filename, ...);
%
% Inputs:
% filename - [string] file name
%
% Optional inputs:
% 'header' - FILEIO structure header
%
% Outputs:
% event - FILEIO toolbox event structure
%
% Modified from read_eeglabevent
%12... |
github | NOCIONS/letswave6-master | read_edf_max.m | .m | letswave6-master/external/fieldtrip/read_edf_max.m | 18,090 | utf_8 | feb6a9d70eedebf7d46559c27c5c1fdf | function [dat] = read_edf_max(filename, hdr, begsample, endsample, chanindx)
% READ_EDF reads specified samples from an EDF datafile. It neglects all trial or
% data block boundaries as if the data was acquired in non-continous mode.
%
% Note that since FieldTrip only accommodates a single sampling rate in a given
% d... |
github | NOCIONS/letswave6-master | read_yokogawa_header_new.m | .m | letswave6-master/external/fieldtrip/read_yokogawa_header_new.m | 8,887 | utf_8 | 70f6185e29007e7790efc5a8cb91bf23 | function hdr = read_yokogawa_header_new(filename)
% READ_YOKOGAWA_HEADER_NEW reads the header information from continuous,
% epoched or averaged MEG data that has been generated by the Yokogawa
% MEG system and software and allows that data to be used in combination
% with FieldTrip.
%
% Use as
% [hdr] = read_yokogaw... |
github | NOCIONS/letswave6-master | ft_datatype_raw.m | .m | letswave6-master/external/fieldtrip/ft_datatype_raw.m | 11,088 | utf_8 | 77a0d4b35ed2377b47f86a75901614bb | function [data] = ft_datatype_raw(data, varargin)
% FT_DATATYPE_RAW describes the FieldTrip MATLAB structure for raw data
%
% The raw datatype represents sensor-level time-domain data typically
% obtained after calling FT_DEFINETRIAL and FT_PREPROCESSING. It contains
% one or multiple segments of data, each represente... |
github | NOCIONS/letswave6-master | getdimsiz.m | .m | letswave6-master/external/fieldtrip/getdimsiz.m | 2,235 | utf_8 | 340d495a654f2f6752aa1af7ac915390 | function dimsiz = getdimsiz(data, field)
% GETDIMSIZ
%
% Use as
% dimsiz = getdimsiz(data, field)
%
% If the length of the vector that is returned is smaller than the
% number of dimensions that you would expect from GETDIMORD, you
% should assume that it has trailing singleton dimensions.
%
% Example use
% dimord... |
github | NOCIONS/letswave6-master | ft_prepare_vol_sens.m | .m | letswave6-master/external/fieldtrip/ft_prepare_vol_sens.m | 21,812 | utf_8 | 3d4ec60e9298b697783ba3e3c1040a82 | function [vol, sens] = ft_prepare_vol_sens(vol, sens, varargin)
% FT_PREPARE_VOL_SENS does some bookkeeping to ensure that the volume
% conductor model and the sensor array are ready for subsequent forward
% leadfield computations. It takes care of some pre-computations that can
% be done efficiently prior to the lead... |
github | NOCIONS/letswave6-master | read_yokogawa_header.m | .m | letswave6-master/external/fieldtrip/read_yokogawa_header.m | 8,273 | utf_8 | ce0d6dbecc09597da7bbb311519c6c84 | function hdr = read_yokogawa_header(filename)
% READ_YOKOGAWA_HEADER reads the header information from continuous,
% epoched or averaged MEG data that has been generated by the Yokogawa
% MEG system and software and allows that data to be used in combination
% with FieldTrip.
%
% Use as
% [hdr] = read_yokogawa_heade... |
github | NOCIONS/letswave6-master | encode_nifti1.m | .m | letswave6-master/external/fieldtrip/encode_nifti1.m | 4,870 | utf_8 | 9cf92a03587c511a5cec2c8c76a3c2c3 | function blob = encode_nifti1(H)
%function blob = encode_nifti1(H)
%
% Encodes a NIFTI-1 header (=> raw 348 bytes (uint8)) from a Matlab structure
% that matches the C struct defined in nifti1.h.
%
% WARNING: This function currently ignores endianness !!!
% (C) 2010 S.Klanke
blob = uint8(zeros(1,348));
if ~isstruct(... |
github | NOCIONS/letswave6-master | dipole_fit.m | .m | letswave6-master/external/fieldtrip/dipole_fit.m | 10,473 | utf_8 | 16c0b6aa294c1a4e10ab576c83ce11e7 | function [dipout] = dipole_fit(dip, sens, vol, dat, varargin)
% DIPOLE_FIT performs an equivalent current dipole fit with a single
% or a small number of dipoles to explain an EEG or MEG scalp topography.
%
% Use as
% [dipout] = dipole_fit(dip, sens, vol, dat, ...)
%
% Additional input arguments should be specified ... |
github | NOCIONS/letswave6-master | read_nervus_header.m | .m | letswave6-master/external/fieldtrip/read_nervus_header.m | 34,403 | utf_8 | 5e6d0fe6794c0f0f793aa2e9adc1f19e | function output = read_nervus_header(filename)
% read_nervus_header Returns header information from Nicolet file.
%
% FILENAME is the file name of a file in the Natus/Nicolet/Nervus(TM)
% format (originally designed by Taugagreining HF in Iceland)
%
% Based on ieeg-portal/Nicolet-Reader
% at https://github.com... |
github | NOCIONS/letswave6-master | avw_hdr_read.m | .m | letswave6-master/external/fieldtrip/avw_hdr_read.m | 16,654 | utf_8 | f63f3dbd244a89c6108eff59453680c3 | function [ avw, machine ] = avw_hdr_read(fileprefix, machine, verbose)
% avw_hdr_read - read Analyze format data header (*.hdr)
%
% [ avw, machine ] = avw_hdr_read(fileprefix, [machine], [verbose])
%
% fileprefix - string filename (without .hdr); the file name
% can be given as a full path or relative to ... |
github | NOCIONS/letswave6-master | read_stl.m | .m | letswave6-master/external/fieldtrip/read_stl.m | 4,432 | utf_8 | 6aec08043b6655fd9efe5194e20bf28f | function [pnt, tri, nrm] = read_stl(filename)
% READ_STL reads a triangulation from an ascii or binary *.stl file, which
% is a file format native to the stereolithography CAD software created by
% 3D Systems.
%
% Use as
% [pnt, tri, nrm] = read_stl(filename)
%
% The format is described at http://en.wikipedia.org/wi... |
github | NOCIONS/letswave6-master | read_itab_mhd.m | .m | letswave6-master/external/fieldtrip/read_itab_mhd.m | 12,518 | utf_8 | d0ebd0b4e1de627d76cb523010d16ec7 | function mhd = read_itab_mhd(filename)
fid = fopen(filename, 'rb');
% Name of structure
mhd.stname = fread(fid, [1 10], 'uint8=>char'); % Header identifier (VP_BIOMAG)
mhd.stver = fread(fid, [1 8], 'uint8=>char'); % Header version
mhd.stendian = fread(fid, [1 4], 'uint8=>char'); % ... |
github | NOCIONS/letswave6-master | ft_datatype_sens 2.m | .m | letswave6-master/external/fieldtrip/ft_datatype_sens 2.m | 6,866 | utf_8 | 20191bc55b7e6de738cf7f7f4fa42259 | function [sens] = ft_datatype_sens(sens, varargin)
% FT_DATATYPE_SENS describes the FieldTrip structure that represents
% an EEG, ECoG, or MEG sensor array. This structure is commonly called
% "elec" for EEG and "grad" for MEG, or more general "sens" for either
% one.
%
% The structure for MEG gradiometers and/or magn... |
github | NOCIONS/letswave6-master | ft_read_header_EDFMAX.m | .m | letswave6-master/external/fieldtrip/ft_read_header_EDFMAX.m | 104,110 | utf_8 | 823b491c236eba6bfbee55ec43fb9e92 | function [hdr] = ft_read_header_EDFMAX(filename, varargin)
% FT_READ_HEADER reads header information from a variety of EEG, MEG and LFP
% files and represents the header information in a common data-independent
% format. The supported formats are listed below.
%
% Use as
% hdr = ft_read_header(filename, ...)
%
% Add... |
github | NOCIONS/letswave6-master | ft_filetype.m | .m | letswave6-master/external/fieldtrip/ft_filetype.m | 68,462 | utf_8 | c47f8848548bddd896554cb00fefb82b | function [type] = ft_filetype(filename, desired, varargin)
% FT_FILETYPE determines the filetype of many EEG/MEG/MRI data files by
% looking at the name, extension and optionally (part of) its contents.
% It tries to determine the global type of file (which usually
% corresponds to the manufacturer, the recording syst... |
github | NOCIONS/letswave6-master | read_plexon_plx.m | .m | letswave6-master/external/fieldtrip/read_plexon_plx.m | 20,283 | utf_8 | ec115cb91003e60359655fdd73fdfdb6 | function [varargout] = read_plexon_plx(filename, varargin)
% READ_PLEXON_PLX reads header or data from a Plexon *.plx file, which
% is a file containing action-potential (spike) timestamps and waveforms
% (spike channels), event timestamps (event channels), and continuous
% variable data (continuous A/D channels).
%
%... |
github | NOCIONS/letswave6-master | read_neurosim_evolution.m | .m | letswave6-master/external/fieldtrip/read_neurosim_evolution.m | 4,493 | utf_8 | 611253a932a6acc90c0b61a442dc58a5 | function [hdr, dat] = read_neurosim_evolution(filename, varargin)
% READ_NEUROSIM_EVOLUTION reads the "evolution" file that is written
% by Jan van der Eerden's NeuroSim software. When a directory is used
% as input, the default filename 'evolution' is read.
%
% Use as
% [hdr, dat] = read_neurosim_evolution(filename... |
github | NOCIONS/letswave6-master | read_eeglabevent.m | .m | letswave6-master/external/fieldtrip/read_eeglabevent.m | 3,698 | utf_8 | d48c0efc8368b120e96562164a153a88 | % read_eeglabevent() - import EEGLAB dataset events
%
% Usage:
% >> event = read_eeglabevent(filename, ...);
%
% Inputs:
% filename - [string] file name
%
% Optional inputs:
% 'header' - FILEIO structure header
%
% Outputs:
% event - FILEIO toolbox event structure
%
% Author: Arnaud Delorme, SCCN, INC, ... |
github | NOCIONS/letswave6-master | read_bti_ascii.m | .m | letswave6-master/external/fieldtrip/read_bti_ascii.m | 2,240 | utf_8 | 560f3413b1fc96661f8ed42823efdc13 | function [file] = read_bti_ascii(filename)
% READ_BTI_ASCII reads general data from a BTI configuration file
%
% The file should be formatted like
% Group:
% item1 : value1a value1b value1c
% item2 : value2a value2b value2c
% item3 : value3a value3b value3c
% item4 : value4a value4b value4c ... |
github | NOCIONS/letswave6-master | eeg_leadfield1.m | .m | letswave6-master/external/fieldtrip/eeg_leadfield1.m | 3,861 | utf_8 | 1fb67278560820b9d4d494e6eebc6e78 | function [lf, lforig] = eeg_leadfield1(R, elc, vol);
% EEG_LEADFIELD1 electric leadfield for a dipole in a single sphere
%
% [lf] = eeg_leadfield1(R, elc, vol)
%
% with input arguments
% R position dipole (vector of length 3)
% elc position electrodes
% and vol being a structure with the elements
% vol... |
github | NOCIONS/letswave6-master | openbdf.m | .m | letswave6-master/external/fieldtrip/openbdf.m | 6,812 | utf_8 | cb49358a2a955b165a5c50127c25e3d8 | % openbdf() - Opens an BDF File (European Data Format for Biosignals) in MATLAB (R)
%
% Usage:
% >> EDF=openedf(FILENAME)
%
% Note: About EDF -> www.biosemi.com/faq/file_format.htm
%
% Author: Alois Schloegl, 5.Nov.1998
%
% See also: readedf()
% Copyright (C) 1997-1998 by Alois Schloegl
% a.schloegl@ieee.org
% ... |
github | talregev/ROS_MATLAB-master | msgs2mat.m | .m | ROS_MATLAB-master/+ros/msgs2mat.m | 1,116 | utf_8 | e43f492342df6828763d3e66bc28f97c | function [mat] = msgs2mat(msgs, accessor, converter)
% MSGS2MAT Convert ROS messages to a matrix
% MAT = MSGS2MAT(msgs, accessor) Returns an M-by-N matrix where M is the number
% of fields in each message and N is the length of msgs. accessor is a
% function which takes a message and returns a vector or a struct whose... |
github | talregev/ROS_MATLAB-master | pclviewer.m | .m | ROS_MATLAB-master/matpcl/pclviewer.m | 1,246 | utf_8 | f825864a48357a574c869e92c8dc313a | %PCLVIEWER View a point cloud using PCL
%
% PCLVIEWER(P) writes the point cloud P (MxN) to a temporary file and invokes
% the PCL point cloud viewer for fast display and visualization. The columns of P
% represent the 3D points.
%
% If M=3 then the rows are x, y, z.
% If M=6 then the rows are x, y, z, R, G, B where R,... |
github | talregev/ROS_MATLAB-master | loadpcd.m | .m | ROS_MATLAB-master/matpcl/loadpcd.m | 8,446 | utf_8 | 9ca2d26237c905d4aa1ccc9abd7bcbf4 | %LOADPCD Load a point cloud from a PCD format file
%
% P = LOADPCD(FNAME) is a set of points loaded from the PCD format
% file FNAME.
%
% For an unorganized point cloud the columns of P represent the 3D points,
% and the rows are: x, y, z, r, g, b, a depending on the FIELDS in the file.
%
% For an organized point clo... |
github | talregev/ROS_MATLAB-master | lzfd.m | .m | ROS_MATLAB-master/matpcl/lzfd.m | 2,169 | utf_8 | 1280ce0a291d2c9d98b06a4673a98535 | %LZFD LZF decompression
%
% OUT = LZFD(IN) is the decompressed version of the uint8 array IN.
%
% OUT = LZFD(IN, LEN) as above but sets the internal working buffer to length
% LEN which should exceed the expected uncompressed data size.
%
% Notes::
% - LZF is an algorithm that is efficient and gives reasonable compres... |
github | talregev/ROS_MATLAB-master | lspcd.m | .m | ROS_MATLAB-master/matpcl/lspcd.m | 2,071 | utf_8 | e67de9778584a673b9569720ea4c72f9 | %LSPCD List attributes of PCD format files
%
% LSPCD() list the attributes of all .PCD files in the current folder.
%
% LSPCD(FILESPEC) as above but list only files that match FILESPEC which
% might contain a directory name and/or a wildcard.
%
%
% See also pclviewer, loadpcd.
%
% Copyright (C) 2013, by Peter I. Corke... |
github | talregev/ROS_MATLAB-master | savepcd.m | .m | ROS_MATLAB-master/matpcl/savepcd.m | 4,547 | utf_8 | b6fc9de72f9c31f773ed98eb76072db1 | %SAVEPCD Write a point cloud to file in PCD format
%
% SAVEPCD(FNAME, P) writes the point cloud P to the file FNAME as an
% as a PCD format file.
%
% SAVEPCD(FNAME, P, 'binary') as above but save in binary format. Default
% is ascii format.
%
% If P is a 2-dimensional matrix (MxN) then the columns of P represent the
%... |
github | VisionandCognition/Tracker-master | Stimgui.m | .m | Tracker-master/TrackerT/Stimgui.m | 39,505 | utf_8 | 7f4319d53e9cdef7410fad4e5cd6ceb1 | function varargout = Stimgui(varargin)
% STIMGUI M-file for Stimgui.fig
% STIMGUI, by itself, creates a new STIMGUI or raises the existing
% singleton*.
%
% H = STIMGUI returns the handle to a new STIMGUI or the handle to
% the existing singleton*.
%
% STIMGUI('CALLBACK',hObject,eventData,handl... |
github | VisionandCognition/Tracker-master | tracker.m | .m | Tracker-master/TrackerT/tracker.m | 56,591 | utf_8 | 1b82f4d2d180736ca8cbe2c49f5e45a7 | function varargout = tracker(varargin)
% TRACKER M-file for tracker.fig
% TRACKER, by itself, creates a new TRACKER or raises the existing
% singleton*.
%
% H = TRACKER returns the handle to a new TRACKER or the handle to
% the existing singleton*.
%
% TRACKER('CALLBACK',hObject,eventData,handl... |
github | VisionandCognition/Tracker-master | cgTexture.m | .m | Tracker-master/TrackerT/cg/cgTexture.m | 4,536 | utf_8 | c881c6327baa859d93f51b1291655e63 | function tex = cgTexture(varargin)
% tex = cgTexture(varargin)
% function cgDrawTexture make a new texture
% function cgDrawTexture(tex, mode) edit a texture (mode = 'E')
% function cgDrawTexture(tex, Id, mode) edit, load , display texture
%
% tex is a structure with the entries
% tex.barWi... |
github | VisionandCognition/Tracker-master | cgbox.m | .m | Tracker-master/TrackerT/cg/cgbox.m | 8,593 | utf_8 | 6c307442ffd42f36af81fc3e39ec1270 | function Box = cgbox( varargin )
%function Box = cgbox( varargin )
if nargin > 0
Box = varargin{1};
if ~isstruct(Box)
disp('Invalid cgbox USAGE:')
help cgbox
return
end
Mode = 0; %adds to existing dots
else
Box = []; %new
Mode = 0;
end
if nargin > 1 %must be 2 or 3 ... |
github | VisionandCognition/Tracker-master | cgRandompattern.m | .m | Tracker-master/TrackerT/cg/cgRandompattern.m | 5,687 | utf_8 | 907815b1769696f8bb6c94e250ed2478 | function RP = cgRandompattern( varargin )
%random pattern generator with fixed pattern for receptive field location
%Call function with :
%RP = cgRandompattern , initializes randompattern
%RP = cgRandompattern(RF), initialize randompattern with receptive field data
%Receptive field format: RF = [center x, center y, w... |
github | VisionandCognition/Tracker-master | bmpui.m | .m | Tracker-master/TrackerT/cg/bmpui.m | 11,570 | utf_8 | 3f2b92062d4e6cb15d26599ba67c3451 | function varargout = bmpui(varargin)
% BMPUI M-file for bmpui.fig
% BMPUI, by itself, creates a new BMPUI or raises the existing
% singleton*.
%
% H = BMPUI returns the handle to a new BMPUI or the handle to
% the existing singleton*.
%
% BMPUI('CALLBACK',hObject,eventData,handles,...) calls th... |
github | VisionandCognition/Tracker-master | cgpolyline.m | .m | Tracker-master/TrackerT/cg/cgpolyline.m | 19,299 | utf_8 | df938adc0bfadfe404ef2a4d187495ec | function Polyline = cgpolyline( varargin )
%function Polygon = cgPolygon( varargin)
%Polygon.P.x :array of x and y positions
% .y
% .f : true or false; filled polygon or just lines
% .w :line width
% .c : color [r, g, b] (0-1)
%05-06-2008
%C van der Togt
%Vision and Cogn... |
github | VisionandCognition/Tracker-master | cgbezier.m | .m | Tracker-master/TrackerT/cg/cgbezier.m | 44,048 | utf_8 | 2bf5c513cf7db8703af29a0ff44f402f | function Bez = cgbezier( varargin )
% Bez = cgbezier( ) makes a new Bezier curve
% Bez = cgbezier( Bez ) adds to existing bezier
% exit function with ESC or C (to close the curve)
% cgbezier( Bez , 'B') %blit the bezier as a sprite
% cgbezier(Bez, 'S', Id) %make a sprite
% Bez = cgbez... |
github | VisionandCognition/Tracker-master | texui.m | .m | Tracker-master/TrackerT/cg/texui.m | 22,564 | utf_8 | e6fde8192236b15a3d9358e13569a434 | function varargout = texui(varargin)
% TEXUI M-file for texui.fig
% TEXUI, by itself, creates a new TEXUI or raises the existing
% singleton*.
%
% H = TEXUI returns the handle to a new TEXUI or the handle to
% the existing singleton*.
%
% TEXUI('CALLBACK',hObject,eventData,handles,...) calls th... |
github | eccarson/ca-ksms-master | cgs.m | .m | ca-ksms-master/utils/cgs.m | 1,990 | utf_8 | 579d0099467ac66fb41c7d632af1af2f | % Erin Carson
% cgs.m
% Edited 1/14/2015
% Run the CGS method to solve Ax=b
%Input:
%A: square, sparse matrix with dimension n
%b: right hand side of system to solve, Ax=b; vector of dimension n
%x0: initial guess for solution, vector of dimension n
%maxits: maximum number of iterations to complete before returning; ... |
github | eccarson/ca-ksms-master | lpcg.m | .m | ca-ksms-master/utils/lpcg.m | 2,158 | utf_8 | 6c0a6fd7cf1ae43bdf66c2e3a67d478d | % Erin Carson
% lpcg.m
% Edited 2021
% Run the left preconditioned CG method to solve Ax=b
%Input:
%A: square, sparse matrix with dimension n
%b: right hand side of system to solve, Ax=b; vector of dimension n
%x0: initial guess for solution, vector of dimension n
%M: left preconditioner
%maxits: maximum n... |
github | eccarson/ca-ksms-master | cg.m | .m | ca-ksms-master/utils/cg.m | 1,967 | utf_8 | 78e5643c625dfc013d0456191fd64c9d | % Erin Carson
% cg.m
% Edited 1/14/2015
% Run the CG method to solve Ax=b
%Input:
%A: square, sparse matrix with dimension n
%b: right hand side of system to solve, Ax=b; vector of dimension n
%x0: initial guess for solution, vector of dimension n
%maxits: maximum number of iterations to complete before returning; sh... |
github | eccarson/ca-ksms-master | deflationdriver.m | .m | ca-ksms-master/examples/deflationdriver.m | 3,512 | utf_8 | 7d927427982081aafe3e389fe33347d4 | % Erin Carson
% deflationdriver.m
% Edited 5/30/2015
%A is system matrix (SPD)
%b is right hand side to use for all systems
%basis is either 'monomial', 'newton', or 'chebyshev'
%s is #iterations per outer loop
%xlim is maximum #iterations
%example call: deflationdriver(gallery('poisson',16), rand(256,1), 'monomial',... |
github | eccarson/ca-ksms-master | cabicgstab.m | .m | ca-ksms-master/CAKrylovmethods/cabicgstab.m | 4,756 | utf_8 | a790e23ce2e0abee39071eb936a7f086 | % Erin Carson
% cabicgstab.m
% Edited 5/28/2015
% Run the s-step CABICGSTAB method to solve Ax=b for nonsymmetric A
%Input:
%A: square, sparse matrix with dimension n
%b: right hand side of system to solve, Ax=b; vector of dimension n
%s: number of inner-loop iterations per outer loop; the "s" in "s-step
%methods"
%x... |
github | eccarson/ca-ksms-master | cacg.m | .m | ca-ksms-master/CAKrylovmethods/cacg.m | 4,144 | utf_8 | cd4dc36ab4c14fac284eaed428257248 | % Erin Carson
% cacg.m
% Edited 1/14/2015
% Run the s-step CACG method to solve Ax=b
%Input:
%A: square, sparse matrix with dimension n
%b: right hand side of system to solve, Ax=b; vector of dimension n
%s: number of inner-loop iterations per outer loop; the "s" in "s-step
%methods"
%x0: initial guess for solution, ... |
github | eccarson/ca-ksms-master | pcacg.m | .m | ca-ksms-master/CAKrylovmethods/pcacg.m | 4,753 | utf_8 | ce90646ef60a290a50f330cafedaf017 | % Erin Carson
% pcacg.m
% Run the s-step left-preconditioned CACG method to solve Ax=b using
% monomial basis
%Input:
%A: square, sparse matrix with dimension n
%b: right hand side of system to solve, Ax=b; vector of dimension n
%s: number of inner-loop iterations per outer loop; the "s" in "s-step
%metho... |
github | eccarson/ca-ksms-master | cabicg.m | .m | ca-ksms-master/CAKrylovmethods/cabicg.m | 4,743 | utf_8 | c358104fc546e6099ecf15158b506802 | % Erin Carson
% cabicg.m
% Edited 5/26/2015
% Run the s-step CABICG method to solve Ax=b for nonsymmetric A
%Input:
%A: square, sparse matrix with dimension n
%b: right hand side of system to solve, Ax=b; vector of dimension n
%s: number of inner-loop iterations per outer loop; the "s" in "s-step
%methods"
%x0: initi... |
github | eccarson/ca-ksms-master | calsqr.m | .m | ca-ksms-master/CAKrylovmethods/calsqr.m | 5,524 | utf_8 | 4af01eb6c85534b9eb6302b0fd37c2c9 | % Erin Carson
% calsqr.m
% Edited 7/8/2015
% Run the s-step CALSQR method to solve min||Ax=b||
%Input:
%A: mxn sparse matrix
%b: right hand side of least squares system to solve, Ax=b; vector of dimension n
%s: number of inner-loop iterations per outer loop; the "s" in "s-step
%methods"
%maxits: maximum number of i... |
github | eccarson/ca-ksms-master | calsqr_alt.m | .m | ca-ksms-master/CAKrylovmethods/calsqr_alt.m | 4,984 | utf_8 | 380ff67426832dee3ff5d897142eeb3a | % Erin Carson
% calsqr_alt.m
% Edited 7/8/2015
% Run the s-step CALSQR method to solve min||Ax=b||
%Input:
%A: mxn sparse matrix
%b: right hand side of least squares system to solve, Ax=b; vector of dimension n
%s: number of inner-loop iterations per outer loop; the "s" in "s-step
%methods"
%maxits: maximum number ... |
github | eccarson/ca-ksms-master | pcg_cacg.m | .m | ca-ksms-master/CAKrylovmethods/pcg_cacg.m | 2,325 | utf_8 | 61d37c0d06d6dccfe17793df43ccec1e | % Erin Carson
% pcg_cacg.m
% Edited 6/23/2015
% Run the CG method to solve Ax=b, with CA-CG as preconditioner
%Input:
%A: square, sparse matrix with dimension n
%b: right hand side of system to solve, Ax=b; vector of dimension n
%x0: initial guess for solution, vector of dimension n
%maxits: maximum number of iterati... |
github | eccarson/ca-ksms-master | cadcg.m | .m | ca-ksms-master/CAKrylovmethods/cadcg.m | 5,044 | utf_8 | 246d6c7d1d794516f6fc0c284c62eb24 | % Erin Carson
% cadcg.m
% Edited 5/28/2015
% Run the s-step deflated CACG method to solve Ax=b
%Input:
%A is an nxn matrix, b is RHS (Ax=b)
%b is RHS
%s is the basis size (number of times we've unrolled the loop)
%t is the max number of outer iterations (s*t = max iterations)
%x_g is the initial guess (zero vector is... |
github | eccarson/ca-ksms-master | pcg_cg.m | .m | ca-ksms-master/CAKrylovmethods/pcg_cg.m | 2,315 | utf_8 | 4e13fc6c2e67f643e0a0620e73c574ca | % Erin Carson
% pcg_cg.m
% Edited 6/23/2015
% Run the CG method to solve Ax=b, with CG as variable preconditioner
%Input:
%A: square, sparse matrix with dimension n
%b: right hand side of system to solve, Ax=b; vector of dimension n
%x0: initial guess for solution, vector of dimension n
%maxits: maximum number of ite... |
github | eccarson/ca-ksms-master | cacgs.m | .m | ca-ksms-master/CAKrylovmethods/cacgs.m | 4,027 | utf_8 | 298d1548d70738a37931621c0d8b63d2 | % Erin Carson
% cacgs.m
% Edited 5/27/2015
% Run the s-step CACGS method to solve Ax=b for nonsymmetric A
%Input:
%A: square, sparse matrix with dimension n
%b: right hand side of system to solve, Ax=b; vector of dimension n
%s: number of inner-loop iterations per outer loop; the "s" in "s-step
%methods"
%x0: initial... |
github | eccarson/ca-ksms-master | basisparamsreal.m | .m | ca-ksms-master/basiscomputation/basisparamsreal.m | 1,886 | utf_8 | 37d74987718c2ca6eb5bb0944a21886f | % Erin Carson
% basisparams.m
% Edited 1/14/2015
% Compute s-step basis parameters for basis specified in basis_type, based on
% properties of A
%Input:
%A: matrix we want to compute basis parameters for
%s: number of basis parameters to compute
%basis_type: string denoting which basis to use. Acceptable values are
%... |
github | eccarson/ca-ksms-master | basisparams.m | .m | ca-ksms-master/basiscomputation/basisparams.m | 1,996 | utf_8 | bf07f4dc4c408d6698b2e731eac82bd0 | % Erin Carson
% basisparams.m
% Edited 5/13/2015
%Find basis parameters to generate (s+1)-dimension Krylov basis for matrix A for selected basis type
%Input:
%A: square, sparse matrix with dimension n
%s: number of basis vectors to be generated (not counting the starting vector)
%basis_type: string denoting which bas... |
github | eccarson/ca-ksms-master | basisparamscomplex.m | .m | ca-ksms-master/basiscomputation/basisparamscomplex.m | 2,415 | utf_8 | 516cbca85dff28dc4e1c2443323eb2a1 | % Erin Carson
% basisparamscomplex.m
% Edited 5/13/2015
%Find basis parameters to generate (s+1)-dimension Krylov basis for matrix
%A for selected basis type when A has complex eigenvalues
%Input:
%s: number of basis vectors to be generated (not counting the starting vector)
%evec: vector containing eigenvalues of A
... |
github | eccarson/ca-ksms-master | computeBasis.m | .m | ca-ksms-master/basiscomputation/computeBasis.m | 798 | utf_8 | b8c4bc4559e236c9663e7c4fbe474368 | % Erin Carson
% computeBasis.m
% Edited 1/14/2015
%Input:
%A: matrix with which to compute Krylov basis
%x: starting vector
%s: number of SpMVs to perform; resulting basis is of size s+1
%alp, bet, gam: parameters for basis recurrence
%Output:
%V: matrix of dimension n by (s+1) whose columns are basis for the desired... |
github | eccarson/ca-ksms-master | computeBasis_alt.m | .m | ca-ksms-master/basiscomputation/computeBasis_alt.m | 923 | utf_8 | 27d7003a09538b51f77814a274cb7ea2 | % Erin Carson
% computeBasis_alt.m
% Edited 7/8/2015
%Input:
%A: matrix with which to compute Krylov basis
%z1: starting vector
%y1: starting vector
%s: number of total SpMVs to perform; resulting basis is of size s+1
%alp, bet, gam: parameters for basis recurrence
%Output:
%Z,Y: matrices of dimension n by (s+1) whos... |
github | eccarson/ca-ksms-master | lejapointscomplex.m | .m | ca-ksms-master/basiscomputation/lejapointscomplex.m | 3,173 | utf_8 | 89be9848e52939be4c8e7dd62bebeae3 | %Erin Carson
%lejapointscomplex.m
%Edited 5/13/2015
%Input:
%a: vector containing real parts of eigenvalues
%b: vector containing imaginary parts of eigenvalues. So a(j) + i*b(j) are
%eigenvalues of A
%s: number of leja points returned
%Output:
%ljapnts: vector of s Leja points to be used in basis computation (comple... |
github | eccarson/ca-ksms-master | lejapointsreal.m | .m | ca-ksms-master/basiscomputation/lejapointsreal.m | 1,888 | utf_8 | bb0348213693a384f24dee6ede14d528 | % Erin Carson
% lejapoints.m
% Edited 10/28/2012
% Compute n leja points in the real interval [a,b]
function xleja = lejapointsreal(n,a,b)
options = [];
xleja = zeros(n,1);
xmaxloc = zeros(n-2,1);
fmaxloc = xmaxloc;
xleja(1) = b;
xleja(2) = a;
xsort = xleja;
for k = 3:1:n
xsort = sort(xsort(1:k-1));
for i ... |
github | caoyue10/icml-caffe-master | prepare_batch.m | .m | icml-caffe-master/matlab/caffe/prepare_batch.m | 1,298 | utf_8 | 68088231982895c248aef25b4886eab0 | % ------------------------------------------------------------------------
function images = prepare_batch(image_files,IMAGE_MEAN,batch_size)
% ------------------------------------------------------------------------
if nargin < 2
d = load('ilsvrc_2012_mean');
IMAGE_MEAN = d.image_mean;
end
num_images = length... |
github | caoyue10/icml-caffe-master | matcaffe_demo_vgg.m | .m | icml-caffe-master/matlab/caffe/matcaffe_demo_vgg.m | 3,036 | utf_8 | f836eefad26027ac1be6e24421b59543 | function scores = matcaffe_demo_vgg(im, use_gpu, model_def_file, model_file, mean_file)
% scores = matcaffe_demo_vgg(im, use_gpu, model_def_file, model_file, mean_file)
%
% Demo of the matlab wrapper using the networks described in the BMVC-2014 paper "Return of the Devil in the Details: Delving Deep into Convolutional... |
github | caoyue10/icml-caffe-master | matcaffe_demo.m | .m | icml-caffe-master/matlab/caffe/matcaffe_demo.m | 3,344 | utf_8 | 669622769508a684210d164ac749a614 | function [scores, maxlabel] = matcaffe_demo(im, use_gpu)
% scores = matcaffe_demo(im, use_gpu)
%
% Demo of the matlab wrapper using the ILSVRC network.
%
% input
% im color image as uint8 HxWx3
% use_gpu 1 to use the GPU, 0 to use the CPU
%
% output
% scores 1000-dimensional ILSVRC score vector
%
% You m... |
github | caoyue10/icml-caffe-master | matcaffe_demo_vgg_mean_pix.m | .m | icml-caffe-master/matlab/caffe/matcaffe_demo_vgg_mean_pix.m | 3,069 | utf_8 | 04b831d0f205ef0932c4f3cfa930d6f9 | function scores = matcaffe_demo_vgg_mean_pix(im, use_gpu, model_def_file, model_file)
% scores = matcaffe_demo_vgg(im, use_gpu, model_def_file, model_file)
%
% Demo of the matlab wrapper based on the networks used for the "VGG" entry
% in the ILSVRC-2014 competition and described in the tech. report
% "Very Deep Convo... |
github | AhmedAKhan/OCR-master | solveOneTestCase.m | .m | OCR-master/octaveFiles/solveOneTestCase.m | 637 | utf_8 | 90ffd70e4bf09ecbc993b88aa6704950 | #! /bin/octave -qf
input = [];
arg_list = argv ();
for i = 1:nargin
input = [input, arg_list{i}];
endfor
load('ThetaValues.txt') % load the theta values
% start predicting
h1 = sigmoid([ones(size(input, 1), 1) input] * Theta1');
h2 = sigmoid([ones(size(input, 1), 1) h1] * Theta2');
[dummy, p] = max(h2, [], 2);
... |
github | znah/caffe-master | prepare_batch.m | .m | caffe-master/matlab/caffe/prepare_batch.m | 1,298 | utf_8 | 68088231982895c248aef25b4886eab0 | % ------------------------------------------------------------------------
function images = prepare_batch(image_files,IMAGE_MEAN,batch_size)
% ------------------------------------------------------------------------
if nargin < 2
d = load('ilsvrc_2012_mean');
IMAGE_MEAN = d.image_mean;
end
num_images = length... |
github | znah/caffe-master | matcaffe_demo_vgg.m | .m | caffe-master/matlab/caffe/matcaffe_demo_vgg.m | 3,036 | utf_8 | f836eefad26027ac1be6e24421b59543 | function scores = matcaffe_demo_vgg(im, use_gpu, model_def_file, model_file, mean_file)
% scores = matcaffe_demo_vgg(im, use_gpu, model_def_file, model_file, mean_file)
%
% Demo of the matlab wrapper using the networks described in the BMVC-2014 paper "Return of the Devil in the Details: Delving Deep into Convolutional... |
github | znah/caffe-master | matcaffe_demo.m | .m | caffe-master/matlab/caffe/matcaffe_demo.m | 3,344 | utf_8 | 669622769508a684210d164ac749a614 | function [scores, maxlabel] = matcaffe_demo(im, use_gpu)
% scores = matcaffe_demo(im, use_gpu)
%
% Demo of the matlab wrapper using the ILSVRC network.
%
% input
% im color image as uint8 HxWx3
% use_gpu 1 to use the GPU, 0 to use the CPU
%
% output
% scores 1000-dimensional ILSVRC score vector
%
% You m... |
github | znah/caffe-master | matcaffe_demo_vgg_mean_pix.m | .m | caffe-master/matlab/caffe/matcaffe_demo_vgg_mean_pix.m | 3,069 | utf_8 | 04b831d0f205ef0932c4f3cfa930d6f9 | function scores = matcaffe_demo_vgg_mean_pix(im, use_gpu, model_def_file, model_file)
% scores = matcaffe_demo_vgg(im, use_gpu, model_def_file, model_file)
%
% Demo of the matlab wrapper based on the networks used for the "VGG" entry
% in the ILSVRC-2014 competition and described in the tech. report
% "Very Deep Convo... |
github | thanospol/MARIE-master | Gauss_2D_CIE.m | .m | MARIE-master/src_sie/src_coupling/src_quadraturemex/Gauss_2D_CIE.m | 750 | utf_8 | cd018c962b99575cf0e7f8aa1ac9f89a |
function [Npg,wt,Z1,Z2,Z3] = Gauss_2D_CIE(Np)
format long
[w,z] = Gauss_1D_CIE (Np);
Npg = Np * Np;
Z1 = zeros(Npg,1);
Z2 = zeros(Npg,1);
Z3 = zeros(Npg,1);
wt = zeros(Npg,1);
ctr=1;
for I=1:Np
for J=1:Np
W = w(I)*w(J);
x = z(I);
y = z(J);
zi = (1-y)/8;
... |
github | thanospol/MARIE-master | incident_field.m | .m | MARIE-master/scripts/vie_solver_mie/src_mie/incident_field.m | 364 | utf_8 | 62899f8d2477c070ff762dbeada96ea6 |
function [Einc, Hinc] = incident_field(r, theta, phi, k, omega, mu, E0)
% to calculate incident field through the expansion
n = 1:40;
En = E0*(-1i).^n .* (2*n+1) ./(n.*(n+1));
[Mo, Me, No, Ne] = calc_MNpot_bj(theta, phi, r, k, n);
temp_Einc = Mo + 1i*Ne;
Einc = (En * temp_Einc.').';
temp_Hinc = -k/(omega*mu) ... |
github | thanospol/MARIE-master | getHarmVecs1.m | .m | MARIE-master/src_numeric/src_iterative/getHarmVecs1.m | 1,042 | utf_8 | 6411ca4206431b6ba1bc3fc4179fc6ea | % getHarmVecs1 For use with GCRODR
%
% Determines harmonic Ritz vectors using matrix H computed from a
% GMRES iteration. For this case, the harmonic Ritz values are the
% eigenvalues of H
%
% INPUT: M dimension of upper Hessenburg matrix H
% K select and return basis for space spann... |
github | thanospol/MARIE-master | getHarmVecs2.m | .m | MARIE-master/src_numeric/src_iterative/getHarmVecs2.m | 1,237 | utf_8 | d8cdbf984d9d31161b4cbb0380dd616d | % getHarmVecs2 For use with GCRODR
%
% Determines harmonic Ritz vectors using matrices computed from
% GMRES iteration.
%
% INPUT: M dimension of upper Hessenburg matrix H
% K select and return basis for space spanned by K harmonic
% Ritz vectors corresponding to K ... |
github | thanospol/MARIE-master | pgmresDR_iter.m | .m | MARIE-master/src_numeric/src_iterative/pgmresDR_iter.m | 3,700 | utf_8 | 969b3b50f015420c9929cf9499dc84cc | % Preconditioned GMRES internal iteration routine
%
% Generates Arnoldi relation A V(:,1:m) = V(:,1:m+1) H
% Applies relation (I - C*C') V(:,1:m) = V(:,1:m+1) H if deflation exists
%
% INPUT: A N-by-N matrix
% r N-by-1 preconditioned residual vector
% m number of GMRES iterations ... |
github | thanospol/MARIE-master | pgmresDR.m | .m | MARIE-master/src_numeric/src_iterative/pgmresDR.m | 8,902 | utf_8 | 5f4b751445128cf5b05d9e6961a1a2aa |
% modified Preconditioned GMRES DR
% Version by J. Fernandez Villena
% Computational Prototyping Group, RLE at MIT
% original code from ML Parks, Sandia Labs.
% Can use double Left and/or Righ Preconditioners
% Can use function handle for A and preconditioners
% Uses deflated restart
%
... |
github | thanospol/MARIE-master | pgmres_iter.m | .m | MARIE-master/src_numeric/src_iterative/pgmres_iter.m | 3,823 | utf_8 | e8ac1b59f84ed426c5bb9ef6a379d33c | % Preconditioned GMRES internal iteration routine
%
% Solves A z = r for z, then returns x + z
% Generates Arnoldi relation A V(:,1:m) = V(:,1:m+1) H
%
% INPUT: A N-by-N matrix
% x current solution vector
% r N-by-1 preconditioned residual vector
% m number of GMRES ... |
github | thanospol/MARIE-master | pgmres.m | .m | MARIE-master/src_numeric/src_iterative/pgmres.m | 6,284 | utf_8 | 1d24eb4f591abff05d3424d4bd946966 |
% modified GMRES with Left and Righ Preconditioners, and standard restart
% Version by J. Fernandez Villena
% Computational Prototyping Group, RLE at MIT
% Can use double Left and/or Righ Preconditioners
% Can use function handle for A and preconditioners
%
% INPUT: A N-by-N matrix o... |
github | thanospol/MARIE-master | DIRECT_WS_VA_RWG.m | .m | MARIE-master/src_vie/src_operators/cubatures/DIRECT_WS_VA_RWG.m | 7,310 | utf_8 | 1901fee071e65dcf344c8625ff9c5c45 | function [I_DE] = DIRECT_WS_VA_RWG(r1,r2,r3,r4,r5,Np_1D)
%% Main body of the DIRECT EVALUATION method for the
% evaluation of the vertex adjacent 4-D weakly singular integrals over planar
% triangular elements.
% Licensing: This code is distributed under the GNU LGPL license.
% Modified: 19 October 2011
... |
github | thanospol/MARIE-master | MARIE_PlotSlice_Multi.m | .m | MARIE-master/src_gui/MARIE_PlotSlice_Multi.m | 23,795 | utf_8 | 541604bcb65d09f94c789e0fca0d6c73 | function varargout = MARIE_PlotSlice_Multi(varargin)
% MARIE_PLOTSLICE_MULTI MATLAB code for MARIE_PlotSlice_Multi.fig
% MARIE_PLOTSLICE_MULTI, by itself, creates a new MARIE_PLOTSLICE_MULTI or raises the existing
% singleton*.
%
% H = MARIE_PLOTSLICE_MULTI returns the handle to a new MARIE_PLOTSLICE_MUL... |
github | thanospol/MARIE-master | MARIE_Analyze.m | .m | MARIE-master/src_gui/MARIE_Analyze.m | 8,394 | utf_8 | fd8bf5cde76d897c685ec6bce1de9d76 | function varargout = MARIE_Analyze(varargin)
% MARIE_ANALYZE MATLAB code for MARIE_Analyze.fig
% MARIE_ANALYZE, by itself, creates a new MARIE_ANALYZE or raises the existing
% singleton*.
%
% H = MARIE_ANALYZE returns the handle to a new MARIE_ANALYZE or the handle to
% the existing singleton*.
%
% ... |
github | thanospol/MARIE-master | MARIE_RHBMLoad.m | .m | MARIE-master/src_gui/MARIE_RHBMLoad.m | 11,179 | utf_8 | 2d571b7f624bb12082e87251c119fd42 | function varargout = MARIE_RHBMLoad(varargin)
% MARIE_RHBMLOAD MATLAB code for MARIE_RHBMLoad.fig
% MARIE_RHBMLOAD, by itself, creates a new MARIE_RHBMLOAD or raises the existing
% singleton*.
%
% H = MARIE_RHBMLOAD returns the handle to a new MARIE_RHBMLOAD or the handle to
% the existing singleton... |
github | thanospol/MARIE-master | MARIE_PlotFreq.m | .m | MARIE-master/src_gui/MARIE_PlotFreq.m | 19,577 | utf_8 | d60e48dc26e14cbdf843de68ce2d488e | function varargout = MARIE_PlotFreq(varargin)
% MARIE_PLOTFREQ MATLAB code for MARIE_PlotFreq.fig
% MARIE_PLOTFREQ, by itself, creates a new MARIE_PLOTFREQ or raises the existing
% singleton*.
%
% H = MARIE_PLOTFREQ returns the handle to a new MARIE_PLOTFREQ or the handle to
% the existing singleton... |
github | thanospol/MARIE-master | MARIE_Visualize.m | .m | MARIE-master/src_gui/MARIE_Visualize.m | 25,407 | utf_8 | 90cec5d6e1ee378567f60f2fe5a0b06a | function varargout = MARIE_Visualize(varargin)
% MARIE_VISUALIZE MATLAB code for MARIE_Visualize.fig
% MARIE_VISUALIZE, by itself, creates a new MARIE_VISUALIZE or raises the existing
% singleton*.
%
% H = MARIE_VISUALIZE returns the handle to a new MARIE_VISUALIZE or the handle to
% the existing si... |
github | thanospol/MARIE-master | MARIE_WCOILProperties.m | .m | MARIE-master/src_gui/MARIE_WCOILProperties.m | 10,796 | utf_8 | 9f4626365a46dcb13dc3aa8bddd7d53e | function varargout = MARIE_WCOILProperties(varargin)
% MARIE_WCOILPROPERTIES MATLAB code for MARIE_WCOILProperties.fig
% MARIE_WCOILPROPERTIES, by itself, creates a new MARIE_WCOILPROPERTIES or raises the existing
% singleton*.
%
% H = MARIE_WCOILPROPERTIES returns the handle to a new MARIE_WCOILPROPERTI... |
github | thanospol/MARIE-master | MARIE_COILModify.m | .m | MARIE-master/src_gui/MARIE_COILModify.m | 10,593 | utf_8 | 19b33f6badc9dd2ed5512b4cf2a8109b | function varargout = MARIE_COILModify(varargin)
% MARIE_COILMODIFY MATLAB code for MARIE_COILModify.fig
% MARIE_COILMODIFY, by itself, creates a new MARIE_COILMODIFY or raises the existing
% singleton*.
%
% H = MARIE_COILMODIFY returns the handle to a new MARIE_COILMODIFY or the handle to
% the exis... |
github | thanospol/MARIE-master | MARIE_ExportSnP.m | .m | MARIE-master/src_gui/MARIE_ExportSnP.m | 8,344 | utf_8 | 34d0f4da99ccfa89e1c11f01c6d37e97 | function varargout = MARIE_ExportSnP(varargin)
% MARIE_EXPORTSNP MATLAB code for MARIE_ExportSnP.fig
% MARIE_EXPORTSNP, by itself, creates a new MARIE_EXPORTSNP or raises the existing
% singleton*.
%
% H = MARIE_EXPORTSNP returns the handle to a new MARIE_EXPORTSNP or the handle to
% the existing si... |
github | thanospol/MARIE-master | MARIE_PlotSlice.m | .m | MARIE-master/src_gui/MARIE_PlotSlice.m | 19,851 | utf_8 | cceb47f3d8b70211362020937ac6d1e0 | function varargout = MARIE_PlotSlice(varargin)
% MARIE_PLOTSLICE MATLAB code for MARIE_PlotSlice.fig
% MARIE_PLOTSLICE, by itself, creates a new MARIE_PLOTSLICE or raises the existing
% singleton*.
%
% H = MARIE_PLOTSLICE returns the handle to a new MARIE_PLOTSLICE or the handle to
% the existing si... |
github | thanospol/MARIE-master | MARIE_RHBMGenerate.m | .m | MARIE-master/src_gui/MARIE_RHBMGenerate.m | 14,287 | utf_8 | 72315d12b9966dd6a0cd616930452418 | function varargout = MARIE_RHBMGenerate(varargin)
% MARIE_RHBMGENERATE MATLAB code for MARIE_RHBMGenerate.fig
% MARIE_RHBMGENERATE, by itself, creates a new MARIE_RHBMGENERATE or raises the existing
% singleton*.
%
% H = MARIE_RHBMGENERATE returns the handle to a new MARIE_RHBMGENERATE or the handle to
%... |
github | thanospol/MARIE-master | MARIE_Pulse.m | .m | MARIE-master/src_gui/MARIE_Pulse.m | 10,249 | utf_8 | b0fed60d0e32cbae8bdcfa716d731d59 | function varargout = MARIE_Pulse(varargin)
% MARIE_PULSE MATLAB code for MARIE_Pulse.fig
% MARIE_PULSE, by itself, creates a new MARIE_PULSE or raises the existing
% singleton*.
%
% H = MARIE_PULSE returns the handle to a new MARIE_PULSE or the handle to
% the existing singleton*.
%
% MARIE_PUL... |
github | thanospol/MARIE-master | MARIE_SolveMR.m | .m | MARIE-master/src_gui/MARIE_SolveMR.m | 18,728 | utf_8 | 373c8b1c40c34bdc8baa1fc5229141f8 | function varargout = MARIE_SolveMR(varargin)
% MARIE_SOLVEMR MATLAB code for MARIE_SolveMR.fig
% MARIE_SOLVEMR, by itself, creates a new MARIE_SOLVEMR or raises the existing
% singleton*.
%
% H = MARIE_SOLVEMR returns the handle to a new MARIE_SOLVEMR or the handle to
% the existing singleton*.
%
% ... |
github | thanospol/MARIE-master | MARIE_RHBMModify.m | .m | MARIE-master/src_gui/MARIE_RHBMModify.m | 16,483 | utf_8 | 2de7abae46aaadd18ac99ff76b38d55a | function varargout = MARIE_RHBMModify(varargin)
% MARIE_RHBMMODIFY MATLAB code for MARIE_RHBMModify.fig
% MARIE_RHBMMODIFY, by itself, creates a new MARIE_RHBMMODIFY or raises the existing
% singleton*.
%
% H = MARIE_RHBMMODIFY returns the handle to a new MARIE_RHBMMODIFY or the handle to
% the exis... |
github | thanospol/MARIE-master | MARIE_SCOILProperties.m | .m | MARIE-master/src_gui/MARIE_SCOILProperties.m | 13,576 | utf_8 | fc249818ab53a04567633e05de383baf | function varargout = MARIE_SCOILProperties(varargin)
% MARIE_SCOILPROPERTIES MATLAB code for MARIE_SCOILProperties.fig
% MARIE_SCOILPROPERTIES, by itself, creates a new MARIE_SCOILPROPERTIES or raises the existing
% singleton*.
%
% H = MARIE_SCOILPROPERTIES returns the handle to a new MARIE_SCOILPROPERTI... |
github | thanospol/MARIE-master | MARIE_SolveScat.m | .m | MARIE-master/src_gui/MARIE_SolveScat.m | 37,260 | utf_8 | 49f0e49f633fdaddfb6974acce24cbcc | function varargout = MARIE_SolveScat(varargin)
% MARIE_SOLVESCAT MATLAB code for MARIE_SolveScat.fig
% MARIE_SOLVESCAT, by itself, creates a new MARIE_SOLVESCAT or raises the existing
% singleton*.
%
% H = MARIE_SOLVESCAT returns the handle to a new MARIE_SOLVESCAT or the handle to
% the existing si... |
github | thanospol/MARIE-master | MARIE_License.m | .m | MARIE-master/src_gui/MARIE_License.m | 4,682 | utf_8 | fce1c9c63e0744f0c3c27777033fc01d | function varargout = MARIE_License(varargin)
% MARIE_LICENSE MATLAB code for MARIE_License.fig
% MARIE_LICENSE, by itself, creates a new MARIE_LICENSE or raises the existing
% singleton*.
%
% H = MARIE_LICENSE returns the handle to a new MARIE_LICENSE or the handle to
% the existing singleton*.
%
% ... |
github | thanospol/MARIE-master | MARIE_COILLoad.m | .m | MARIE-master/src_gui/MARIE_COILLoad.m | 11,553 | utf_8 | 76006ca9b52f76efedb7316b7efaac24 | function varargout = MARIE_COILLoad(varargin)
% MARIE_COILLOAD MATLAB code for MARIE_COILLoad.fig
% MARIE_COILLOAD, by itself, creates a new MARIE_COILLOAD or raises the existing
% singleton*.
%
% H = MARIE_COILLOAD returns the handle to a new MARIE_COILLOAD or the handle to
% the existing singleton... |
github | thanospol/MARIE-master | MARIE_SCOILGenerate.m | .m | MARIE-master/src_gui/MARIE_SCOILGenerate.m | 48,332 | utf_8 | 14ae068473a09428afbad97fe2453894 | function varargout = MARIE_SCOILGenerate(varargin)
% MARIE_SCOILGENERATE MATLAB code for MARIE_SCOILGenerate.fig
% MARIE_SCOILGENERATE, by itself, creates a new MARIE_SCOILGENERATE or raises the existing
% singleton*.
%
% H = MARIE_SCOILGENERATE returns the handle to a new MARIE_SCOILGENERATE or the hand... |
github | thanospol/MARIE-master | MARIE_RHBMAddhomogen.m | .m | MARIE-master/src_gui/MARIE_RHBMAddhomogen.m | 34,079 | utf_8 | 20e24ed1779111630eb7f23dd452e517 | function varargout = MARIE_RHBMAddhomogen(varargin)
% MARIE_RHBMADDHOMOGEN MATLAB code for MARIE_RHBMAddhomogen.fig
% MARIE_RHBMADDHOMOGEN, by itself, creates a new MARIE_RHBMADDHOMOGEN or raises the existing
% singleton*.
%
% H = MARIE_RHBMADDHOMOGEN returns the handle to a new MARIE_RHBMADDHOMOGEN or t... |
github | thanospol/MARIE-master | MARIE_Visualize_pulse.m | .m | MARIE-master/src_gui/MARIE_Visualize_pulse.m | 25,300 | utf_8 | 86958edf71457163e1e5e5a04715760e | function varargout = MARIE_Visualize_pulse(varargin)
% MARIE_VISUALIZE_PULSE MATLAB code for MARIE_Visualize_pulse.fig
% MARIE_VISUALIZE_PULSE, by itself, creates a new MARIE_VISUALIZE_PULSE or raises the existing
% singleton*.
%
% H = MARIE_VISUALIZE_PULSE returns the handle to a new MARIE_VISUALIZE_PUL... |
github | thanospol/MARIE-master | MARIE_SolveFreq.m | .m | MARIE-master/src_gui/MARIE_SolveFreq.m | 11,822 | utf_8 | e90cffbae6ac4ac02736aca3ec1c8338 | function varargout = MARIE_SolveFreq(varargin)
% MARIE_SOLVEFREQ MATLAB code for MARIE_SolveFreq.fig
% MARIE_SOLVEFREQ, by itself, creates a new MARIE_SOLVEFREQ or raises the existing
% singleton*.
%
% H = MARIE_SOLVEFREQ returns the handle to a new MARIE_SOLVEFREQ or the handle to
% the existing si... |
github | thanospol/MARIE-master | MARIE_RHBMProperties.m | .m | MARIE-master/src_gui/MARIE_RHBMProperties.m | 28,237 | utf_8 | c72aafdad8f9b8236b4a8e893c7c8a47 | function varargout = MARIE_RHBMProperties(varargin)
% MARIE_RHBMPROPERTIES MATLAB code for MARIE_RHBMProperties.fig
% MARIE_RHBMPROPERTIES, by itself, creates a new MARIE_RHBMPROPERTIES or raises the existing
% singleton*.
%
% H = MARIE_RHBMPROPERTIES returns the handle to a new MARIE_RHBMPROPERTIES or t... |
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