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github | jhausser/ParTI-master | givensrot.m | .m | ParTI-master/SeDuMi_1_3/givensrot.m | 1,768 | utf_8 | c06e2ebf2373bf05293d82dfbba507a1 | % y = givensrot(gjc,g,x,K)
% GIVENSROT
%
% ********** INTERNAL FUNCTION OF SEDUMI **********
%
% See also sedumi
function y = givensrot(gjc,g,x,K)
%
% This file is part of SeDuMi 1.1 by Imre Polik and Oleksandr Romanko
% Copyright (C) 2005 McMaster University, H... |
github | jhausser/ParTI-master | sparbwslv.m | .m | ParTI-master/SeDuMi_1_3/sparbwslv.m | 2,035 | utf_8 | 0549765090e0d9f6f70449eb65e4c1fb | % SPARBWSLV Solves block sparse upper-triangular system.
% y = sparbwslv(L,b) yields the same result as
% y(L.perm,:) = L.L'\b
% However, SPARBWSLV is faster than the built-in operator "\",
% because it uses dense linear algebra and loop-unrolling on
% supernodes.
%
% Typical use, wit... |
github | jhausser/ParTI-master | cellK.m | .m | ParTI-master/SeDuMi_1_3/cellK.m | 3,587 | utf_8 | 16c58714b6e3f669c6a2647fbfa79272 | % xcell = cellK(x,K)
% CELLK Stores SeDuMi cone K-vector in cell-array format.
%
% On output xcell.f and xcell.l are the free and >=0 components,
% xcell.q{k}, xcell.r{k} and xcell.s{k} contain the Lorentz,
% Rotated Lorentz, and PSD-components, resp.
% xc... |
github | jhausser/ParTI-master | prelp.m | .m | ParTI-master/SeDuMi_1_3/conversion/prelp.m | 3,887 | utf_8 | 8c7e67b2e1d395fd955562d7f31a033d | % PRELP Loads and preprocesses LP from an MPS file.
%
% > [A,b,c,lenx,lbounds] = PRELP('problemname')
% The above command results in an LP in standard form,
% - Instead of specifying the problemname, you can also use PRELP([]), to
% get the problem from the file /tmp/default.mat.
% - Also, you may ty... |
github | jhausser/ParTI-master | feasreal.m | .m | ParTI-master/SeDuMi_1_3/conversion/feasreal.m | 4,269 | utf_8 | 696a3a72691eca524fa51b16e3d66676 | % FEASREAL Generates a random sparse optimization problem with
% linear, quadratic and semi-definite constraints. Output
% can be used by SEDUMI. All data will be real-valued.
%
% The following two lines are typical:
% > [AT,B,C,K] = FEASREAL;
% > [X,Y,INFO] = SEDUMI(AT,B,C,K);
%
% An extended version i... |
github | jhausser/ParTI-master | sdpa2vec.m | .m | ParTI-master/SeDuMi_1_3/conversion/sdpa2vec.m | 2,413 | utf_8 | f31450c6f37447ae7b4723b129db9d4f | % x = sdpavec(E,K)
% Takes an SDPA type sparse data description E, i.e.
% E(1,:) = block, E(2,:) = row, E(3,:) = column, E(4,:) = entry,
% and transforms it into a "long" vector, with vectorized matrices for
% each block stacked under each other. The size of each matrix block
% is given in the field K.s.
% ****... |
github | jhausser/ParTI-master | blk2vec.m | .m | ParTI-master/SeDuMi_1_3/conversion/blk2vec.m | 1,699 | utf_8 | 75235ffac1810910d18fb37b99a3223a | % x = blk2vec(X,nL)
%
% Converts a block diagonal matrix into a vector.
%
% ********** INTERNAL FUNCTION OF FROMPACK **********
function x = blk2vec(X,nL)
%
% This file is part of SeDuMi 1.1 by Imre Polik and Oleksandr Romanko
% Copyright (C) 2005 McMaster University, Hamilton, CANADA (since 1.1)
%
% C... |
github | jhausser/ParTI-master | writesdp.m | .m | ParTI-master/SeDuMi_1_3/conversion/writesdp.m | 4,988 | utf_8 | 6377c90a7877157dfb9ec61ed8005def | % This function takes a problem in SeDuMi MATLAB format and writes it out
% in SDPpack format.
%
% Usage:
%
% writesdp(fname,A,b,c,K)
%
% fname Name of SDPpack file, in quotes
% A,b,c,K Problem in SeDuMi form
%
% Notes:
%
% Problems with complex data are not allowed. ... |
github | jhausser/ParTI-master | frompack.m | .m | ParTI-master/SeDuMi_1_3/conversion/frompack.m | 2,583 | utf_8 | 76beec126c8e1d01e6d87f189e024662 | % FROMPACK Converts a cone problem in SDPPACK format to SEDUMI format.
%
% [At,c] = frompack(A,b,C,blk) Given a problem (A,b,C,blk) in the
% SDPPACK-0.9-beta format, this produces At and c for use with
% SeDuMi. This lets you execute
%
% [x,y,info] = SEDUMI(At,b,c,blk);
%
% IMPORTANT: this function assumes... |
github | jhausser/ParTI-master | feascpx.m | .m | ParTI-master/SeDuMi_1_3/conversion/feascpx.m | 4,513 | utf_8 | 4de33ab70c8cb03bdda2f32a1796fe05 | % FEASCPX Generates a random sparse optimization problem with
% linear, quadratic and semi-definite constraints. Output
% can be used by SEDUMI. Includes complex-valued data.
%
% The following two lines are typical:
% > [AT,B,C,K] = FEASCPX;
% > [X,Y,INFO] = SEDUMI(AT,B,C,K);
%
% An extended version is:... |
github | jhausser/ParTI-master | VCA.m | .m | ParTI-master/mvsa_demo/VCA.m | 6,902 | utf_8 | 9a6dbc371d8802fabaa638ad49228eb9 | function [Ae, indice, Rp] = VCA(R,varargin)
% Vertex Component Analysis
%
% [Ae, indice, Rp ]= vca(R,'Endmembers',p,'SNR',r,'verbose',v)
%
% ------- Input variables -------------
% R - matrix with dimensions L(channels) x N(pixels)
% each pixel is a linear mixture of p endmembers
% signatures R = M... |
github | jhausser/ParTI-master | VCA.m | .m | ParTI-master/sisal_demo/VCA.m | 6,901 | utf_8 | 199e5f4efaea0fa3496f9329ad174010 | function [Ae, indice, Rp] = VCA(R,varargin)
% Vertex Component Analysis
%
% [Ae, indice, Rp ]= vca(R,'Endmembers',p,'SNR',r,'verbose',v)
%
% ------- Input variables -------------
% R - matrix with dimensions L(channels) x N(pixels)
% each pixel is a linear mixture of p endmembers
% signatures R = M... |
github | jhausser/ParTI-master | MVES.m | .m | ParTI-master/MVES_code/MVES.m | 4,342 | utf_8 | 71a186219f617242b9caecd5c2f8f414 | %=====================================================================
% Programmer:
% Tsung-Han Chan, E-mail: chantsunghan@gmail.com
% Date: May 20, 2009
% -------------------------------------------------------
% Reference:
% T.-H. Chan, C.-Y. Chi, Y.-M. Huang and W.-K. Ma, ``A convex analysis
% based minim... |
github | Christiaanvandertol/Fluspect-master | fluspect_B_CX.m | .m | Fluspect-master/fluspect_B_CX.m | 9,957 | utf_8 | 6267d3fac6b4949c8516aa82e4550ff8 | function leafopt = fluspect_B_CX(spectral,leafbio,optipar)
%
% function [leafopt] = fluspect_B_Cx(spectral,leafbio,optipar)
% calculates reflectance and transmittance spectra of a leaf using FLUSPECT,
% plus four excitation-fluorescence matrices
%
% Authors: Wout Verhoef, Christiaan van der Tol (c.vandertol@utwente.n... |
github | Christiaanvandertol/Fluspect-master | numjacobian.m | .m | Fluspect-master/numjacobian.m | 684 | utf_8 | 015794f595dc83db4b6b9028006165a1 | function J=numjacobian(x,spectral,leafbio,optipar)
n=length(x);
[r,t]=calc_fluspect_bcar(x,spectral,leafbio,optipar); %
fx = [r,t];
step=1e-6; %
J = zeros(length(r),2,n);
for i=1:n
xstep = x;
xstep(i)=x(i)+step;
[r,t] = calc_fluspect_bcar(xstep,spectral,leafbio,optipar);
fxstep = [r,t];
J(:,:,i)= (... |
github | gustavla/caffe-weighted-samples-master | prepare_batch.m | .m | caffe-weighted-samples-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 | gustavla/caffe-weighted-samples-master | matcaffe_demo.m | .m | caffe-weighted-samples-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 | shyingCy/Financial-time-series-prediction-master | uninstall_emd.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/uninstall_emd.m | 2,128 | utf_8 | f1f4135f0d97101408694ab4f544d561 | % UNINSTALL_EMD.M uninstall the EMD package
% reverts the modifications made by INSTALL_EMD:
% removes the following locations from Matlab's path:
% <EMD_BASEDIR>
% <EMD_BASEDIR>/utils
% <EMD_BASEDIR>/examples/NSIP2003
% <EMD_BASEDIR>/examples/SPL2007
%
% where <EMD_BASEDIR> is the directory containing uninstall_emd.m
... |
github | shyingCy/Financial-time-series-prediction-master | install_emd.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/install_emd.m | 1,562 | utf_8 | edba7a4d545fe9776097f92bd1ed273e | %INSTALL_EMD.M install the EMD package
% add the following locations to Matlab's path:
% <EMD_BASEDIR>
% <EMD_BASEDIR>/emd
% <EMD_BASEDIR>/utils
% <EMD_BASEDIR>/examples/NSIP2003
% <EMD_BASEDIR>/examples/SPL2007
%
% where <EMD_BASEDIR> is the directory containing install_emd.m
%
% and compiles the C codes
%
% IMPORTANT... |
github | shyingCy/Financial-time-series-prediction-master | cemd_visu.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/cemd_visu.m | 2,823 | utf_8 | 5c2f5edbd41b0b0d83980d462bebf66c | %CEMD_VISU visualization of bivariate/complex EMD
%
% inputs : - x : complex analyzed signal
% - t : time instants
% - imf : set of complex IMFs
% - i (optional) : figure number for display
%
%
% The slider on the right hand side of the figure controls the direction on
% which the co... |
github | shyingCy/Financial-time-series-prediction-master | disp_hhs.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/disp_hhs.m | 1,583 | utf_8 | dd6aace2bcf71483ee9329121ce38729 | %DISP_HHS display Hilbert-Huang spectrum
%
% DISP_HHS(im,t,inf)
% displays in a new figure the spectrum contained in matrix "im"
% (amplitudes in dB).
%
% inputs: - im: image matrix (e.g., output of "toimage")
% - t (optional): time instants (e.g., output of "toimage")
% - inf (optional): -dynamic ... |
github | shyingCy/Financial-time-series-prediction-master | plotc.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/plotc.m | 3,243 | utf_8 | 9e878242623f66dbe1f061cca4f876b9 | %PLOTC plots a complex signal in 2D projection with variable projection angle.
%The angle can be modified at any time using the slider:
% slider at bottom: angle=0 the projection is the real part of the signal
% slider at 1/4: angle=pi/2 the projection is the imaginary part of the signal
% slider at top: angle=2pi sam... |
github | shyingCy/Financial-time-series-prediction-master | findtag.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/findtag.m | 1,044 | utf_8 | 7454c7afdd89ce124034fa98264cb74e | %FINDTAG locate objects with specific tag
%
% FINDTAG(STR)
% Locate objects with specific tag STR
%
% FINDTAG(OBJECT_HANDLES,STR)
% Restricts the search to objects listed in objhandles and their descendants.
%
% FINDTAG(...,'-depth',d)
% The depth argument d controls how many levels under the handles in objhandles
%... |
github | shyingCy/Financial-time-series-prediction-master | emd_visu.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/emd_visu.m | 3,216 | utf_8 | b14b325a26ce79c2d4107444497d6eee | %EMD_VISU visualization of EMD and partial reconstructions (fine to coarse & coarse to fine)
%
% inputs : - x : analyzed signal, if x is complex cemd_visu is called
% - t : time instants
% - imf : output of emd.m
% - i (optional) : figure number for display
%
% outputs : - f2c : fin... |
github | shyingCy/Financial-time-series-prediction-master | boundary_conditions_emd.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/boundary_conditions_emd.m | 3,546 | utf_8 | bde5088d1c5d540f2f15221e7130a453 | %BOUNDARY_CONDITIONS_EMD extends an extrema set to limit edge effects on the interpolations
%
%
% [TMIN,TMAX,ZMIN,ZMAX] = BOUNDARY_CONDITIONS_EMD(INDMIN,INDMAX,T,X,Z,NBSYM)
%
% inputs:
% - INDMIN, INDMAX: indices of minima and maxima in the real signal X
% - T: sampling times
% - X: real signal in which INDMIN ... |
github | shyingCy/Financial-time-series-prediction-master | plot3c.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/plot3c.m | 798 | utf_8 | 18cd6c9a1aa6a3a04e75a7a24b35a431 | %PLOT3C plots a complex signal in 3D
%
% use: same as plot
%
%
% See also
% plotc (another type of visualization of complex signals)
%
% G. Rilling, last modification 12.2006
% gabriel.rilling@ens-lyon.fr
function varargout = plot3c(varargin)
% if first arument is a handle to some axes object
if nargin >=2 && isscal... |
github | shyingCy/Financial-time-series-prediction-master | cemd_disp.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/cemd_disp.m | 2,547 | utf_8 | bcfc94ab889ec17222f5ac9d56aeebdd | %CEMD_DISP displays complex envelope curves and the corresponding tube envelope
%
%
%CEMD_DISP(T,X,ENV,MODE)
%
% inputs:
% - T: time instants
% - X: analyzed signal (complex)
% - ENV: matrix returned by cenvelope.m Each line is an envelope curve
% - MODE: 'render' -> 3D rendering of the tube en... |
github | shyingCy/Financial-time-series-prediction-master | extr.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/extr.m | 1,938 | utf_8 | b255b6a18f2f3ebfbd1655dfddc2017b | %EXTR finds extrema and zero-crossings
%
% [indmin, indmax, indzer] = EXTR(x,t)
%
% inputs : - x : analyzed signal
% - t (optional) : sampling times, default 1:length(x)
%
% outputs : - indmin = indices of minima
% - indmax = indices of maxima
% - indzer = indices of zero-crossings
%
% See... |
github | shyingCy/Financial-time-series-prediction-master | addtag.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/addtag.m | 791 | utf_8 | 7753834d0f8132b47b2646f9a79bde33 | %ADDTAG add a tag to an object
%
% ADDTAG(OBJ_HANDLE,STR)
%
% Adds the tag STR to the object referrenced by OBJ_HANDLE
% When OBJ_HANDLE is an array of handles, STR is added to all corresponding
% objects.
%
% Rem: In order for this to work properly, the object's tag field must be a string
% containing keywords (or... |
github | shyingCy/Financial-time-series-prediction-master | dirstretch.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/dirstretch.m | 1,248 | utf_8 | ac3b11257589d22ec8b3705e588d54a2 | %DIRSTRETCH variable directional stretching of a complex vector
%
% DIRSTRETCH(X,D) where X is a complex vector and D a complex scalar stretches X by abs(D) along the direction arg(D)
% if D is a vector the same size as X, then X(i) is stretched by abs(D(i)) along the direction arf(D(i))
% DIRSTRETCH(X,DIR,COEF) whe... |
github | shyingCy/Financial-time-series-prediction-master | hhspectrum.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/hhspectrum.m | 1,445 | utf_8 | a2e3601a6b074460a64f0ee5c73e4a9c | %HHSPECTRUM compute Hilbert-Huang spectrum
%
% [A,f,tt] = HHSPECTRUM(x,t,l,aff) computes the Hilbert-Huang spectrum
%
% inputs:
% - x : matrix with one signal per row
% - t : time instants
% - l : estimation parameter for instfreq (integer >=1 (1:default))
% - aff : if 1, displays the computation evolut... |
github | shyingCy/Financial-time-series-prediction-master | hastag.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/hastag.m | 659 | utf_8 | 98c2d59c6e9ddf7de584ddba67f6ec51 | %HASTAG tests if an object has a specific tag
%
% BOOL = HASTAG(OBJ_HANDLE,STR)
%
% Tests if the object corresponding to OBJ_HANDLE has the tag STR.
% When OBJ_HANDLE is an array of handles HASTAG returns a logical array of
% the same size.
%
% Rem: In order for this to work properly, the object's tag field must be ... |
github | shyingCy/Financial-time-series-prediction-master | rmtag.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/rmtag.m | 820 | utf_8 | c8cca7ed559bb8d9f89e3f8e3b34fc72 | %RMTAG removes tag from object
%
% RMTAG(OBJ_HANDLE,STR)
%
% Removes the tag STR from the object referrenced by OBJ_HANDLE
% When OBJ_HANDLE is an array of handles, the tag is removed from all
% corresponding objects.
%
% Rem: In order for this to work properly, the object's tag field must be a string
% containing ... |
github | shyingCy/Financial-time-series-prediction-master | toimage.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/utils/toimage.m | 3,003 | utf_8 | 82d44ccfe64bb1323e00c307e16baa67 | %TOIMAGE transforms a spectrum made of 1D functions in an 2D image
%
% [im,tt,ff] = TOIMAGE(A,f,t,splx,sply) transforms a spectrum made
% of 1D functions (e.g., output of "hhspectrum") in an 2D image
%
% inputs : - A : amplitudes of modes (1 mode per row of A)
% - f : instantaneous frequencies
% ... |
github | shyingCy/Financial-time-series-prediction-master | make_emdc.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/EMDs/make_emdc.m | 1,361 | utf_8 | 403408e17b436e17594d8a2bdd27ce6a | %MAKE_EMDC Compiles the C codes for Empirical Mode Decomposition
%
% Note: The compilation can fail on some systems (e.g. MacOS) if Matlab cannot find the C compiler.
% In this case, you should either install a C compiler or check Matlab configuration.
% The configuration files for compilation are mexopts.sh (Unix / M... |
github | shyingCy/Financial-time-series-prediction-master | bivariate_EMD_principle.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/examples/SPL2007/bivariate_EMD_principle.m | 3,936 | utf_8 | 8ce99e0c1f645e2df06b921e64862397 | %bivariate_EMD_principle.m
%shows principle of the bivariate EMD extension
%reproduces Fig. 1 in "Bivariate Empirical Mode Decomposition", G. Rilling,
%P. Flandrin, P. Goncalves and J. M. Lilly, IEEE Signal Processing Letters
%
%G. Rilling 3/2007 email: gabriel.rilling@ens-lyon.fr
function bivariate_EMD_principle
N =... |
github | shyingCy/Financial-time-series-prediction-master | dirstretch.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/examples/SPL2007/dirstretch.m | 614 | utf_8 | 6bd1c732deb536d078fbca3cc50b8d6e | %DIRSTRETCH variable directional stretching of a complex vector
function y=dirstretch(x,dir,coef)
if nargin == 3
if ~isreal(dir) && all(abs(dir) ~= 1)
warning('non unit modulus of direction argument ignored')
end
if isreal(dir) && any(abs(dir) ~= 1)
dir = exp(i*dir);
end
if any(dir==0)
error('inv... |
github | shyingCy/Financial-time-series-prediction-master | triangular_signal.m | .m | Financial-time-series-prediction-master/push5.2.7/indicatorLIB/package_emd/examples/NSIP2003/triangular_signal.m | 378 | utf_8 | 902a9084037dff3a52b19cd810a75795 | % TRIANG.M
%
% P. Flandrin, Mar. 13, 2003
%
% generates a triangular waveform
%
% inputs : - N : # of data samples
% - p : period
%
% output : - x : signal
function x = triang(N,p);
K = ceil(N/(2*p-2));
w = zeros(1,K*(2*p-2)+1);
rp = linspace(-1,1,p);
rn = linspace(1,-1,p);
r = [rp rn(2:p)];
for k = ... |
github | shyingCy/Financial-time-series-prediction-master | testmop.m | .m | Financial-time-series-prediction-master/push5.2.7/backTestLib/GAopt/testmop.m | 1,374 | utf_8 | ea01f7003b567d0df39a45ccf0794d63 | function mop = testmop( testname, dimension )
%Get test multi-objective problems from a given name.
% The method get testing or benchmark problems for Multi-Objective
% Optimization. The implemented problems included ZDT, OKA, KNO.
% User get the corresponding test problem, which is an instance of class
% mop, ... |
github | BrainDynamicsUSYD/nftsim-master | read.m | .m | nftsim-master/+nf/read.m | 3,778 | utf_8 | 764f4890af3172dde2bc821f21bb6aa5 | %% Read a nftsim output file and return a nftsim output struct.
%
% ARGUMENTS:
% fname -- The name of the nftsim output file to read (absolute
% or relative path).
%
% OUTPUT:
% obj -- A nftsim output struct. A Matlab struct containing data
% and parameters from a simulation.... |
github | BrainDynamicsUSYD/nftsim-master | spatial_spectrum.m | .m | nftsim-master/+nf/spatial_spectrum.m | 6,208 | utf_8 | bdfe9b366d0ab57ab639a71fb8e71652 | %% Given a grid of voltages, applies a spatial filter
%
% Returns the spatially summed spectrum.
%
% ARGUMENTS:
% obj -- nf object | a 3D matrix of values
% p -- trace to use | sampling rate
% kmax -- is the number of k-values to use. This should match with whatever kmax is set to in the analytic s... |
github | BrainDynamicsUSYD/nftsim-master | movie.m | .m | nftsim-master/+nf/movie.m | 5,326 | utf_8 | d848944f5fff28aef40cb6aa1d54a530 | %% Script to generate a movie of a field with spatial variation.
%
% This script assumes the nodes are continuous, and the grid is a square.
%
% ARGUMENTS:
% obj -- a structure returned by nf.read('config_name.conf')
% tracename -- is a string with the name of the variable to plot e.g. "Propagator.2.ph... |
github | BrainDynamicsUSYD/nftsim-master | report.m | .m | nftsim-master/+nf/report.m | 879 | utf_8 | 49f50c85f6613482dfa15d603cf62c47 | %% Given a nftsim output struct, print some information about it.
%
% ARGUMENTS:
% obj -- A nftsim output struct (a Matlab struct containing data
% from a simulation).
%
% OUTPUT: Prints to terminal.
%
% AUTHOR:
% Romesh Abeysuriya (2012-03-22).
%
% USAGE:
%{
%
%}
%%%%%%%%%%%%%%%%%%%%%%%%%%... |
github | BrainDynamicsUSYD/nftsim-master | spectrum.m | .m | nftsim-master/+nf/spectrum.m | 3,131 | utf_8 | c9000abf4f7801e77a12a65bd526db1b | %% Returns the frequency vector and frequency power spectrum of a given nftsim structure.
% By default this function returns the one-sided power spectrum from 0 to fs/2, where fs is the
% sampling frequency.
% ARGUMENTS:
% obj -- A nftsim output struct (a Matlab struct containing data
% from a si... |
github | BrainDynamicsUSYD/nftsim-master | rfft.m | .m | nftsim-master/+nf/rfft.m | 3,260 | utf_8 | 2f627e153c2f972a62cbd0fd1ed36d99 | %% Fourier transform
%
% Heavily based on Chris Rennie's notes, see REFERENCES below.
%
% The normalization is such that sum(abs(y).^2)/length(y) = trapz(f,P)
%
% ARGUMENTS:
% y -- a 2D array of size (timepoints x N), where N is the number of signals/timeseries or traces.
% fs -- sampling frequency (Hz) ... |
github | BrainDynamicsUSYD/nftsim-master | run.m | .m | nftsim-master/+nf/run.m | 3,445 | utf_8 | 2fd1673511949f6f9ca25ca553d6c661 | %% Function to run nftsim and return a nftsim output struct.
%
% Provided a configuration file-name (fname.conf), run the nftsim
% executable, generating an output file (fname.output). Optionally, if an
% output argument is provided then, parse the output file and return a
% nftsim output struct containing the simulati... |
github | BrainDynamicsUSYD/nftsim-master | partition.m | .m | nftsim-master/+nf/partition.m | 2,416 | utf_8 | 0076489b8fc79ea3f9e54187a639e067 | %% Partition a list of n items into m groups.
%
% This function calculates the boundaries of each group e.g 16 elements
% with pool=4 means that id=1,2,3,4 returns [1 4] [5 8] [9 12] and [13 16]
% respectively.
%
% ARGUMENTS:
% n_items -- .
% pool -- total number of partitions
% id -- the ID of thi... |
github | BrainDynamicsUSYD/nftsim-master | get_frequencies.m | .m | nftsim-master/+nf/get_frequencies.m | 2,634 | utf_8 | bcb4d50db18eba8ce258fe45bac00466 | %% Take in the size of the data matrix, the sampling rate, and spatial distances
% Return corresponding grids of frequencies and positions
%
% ARGUMENTS:
% data -- an 1D or 3D array of size space points along x, space points along y, tim points,
% fs -- sampling temporal frequency in [Hz]
% Lx -- ... |
github | BrainDynamicsUSYD/nftsim-master | field.m | .m | nftsim-master/+nf/field.m | 589 | utf_8 | 3ded4ba55784f7d2bc995cb84c328603 | %% Returns field name according to the pre-/postfix and array of indices.
%
% ARGUMENTS:
% prefix -- .
% index -- .
% postfix -- .
%
% OUTPUT:
% ret -- .
%
% AUTHOR:
% Romesh Abeysuriya (2012-03-22).
%
% USAGE:
%{
%
%}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
github | BrainDynamicsUSYD/nftsim-master | grid.m | .m | nftsim-master/+nf/grid.m | 1,903 | utf_8 | c0c5ee8d5ce1a196baaa2c6b81d64f64 | %% This function reshapes a 2D array into a 3D array, with the 1st and 2nd dimensions,
% corresponding to X and Y coordinates and the 3rd dimension corresponding to time.
%
% e.g. data = nf.grid(nf,'Propagator.2.phi') will return the data for Propagator.2.phi
% as a 3D matrix, with X and Y coordinates referring to g... |
github | BrainDynamicsUSYD/nftsim-master | plot_timeseries.m | .m | nftsim-master/+nf/plot_timeseries.m | 3,934 | utf_8 | dfa8c8910e5bbe2798a2db1afd7451e0 | %% Plots time-series formatted like a typical EEG view.
%
% That is, nodes are displayed with vertical space between lines. By
% default, for each time-step the spatial average is removed -- this
% corresponds to a rereferencing to the "grand average". One figure window
% is created for each trace.
%
% ARGUMENTS:
%... |
github | BrainDynamicsUSYD/nftsim-master | extract.m | .m | nftsim-master/+nf/extract.m | 3,904 | utf_8 | 35363066623a82b4c145827cfcbe859f | %% Extract a specific subset of data from a nftsim output struct.
%
% The subset can be specified in terms of: traces; times; and nodes.
%
% ARGUMENTS:
% obj -- A nftsim output struct (a Matlab struct containing data
% from a simulation).
% traces -- A cell array or a comma separated string ... |
github | gerac83/clifford_toolbox-master | AlgoCDE.m | .m | clifford_toolbox-master/MATLAB/cliffordv07/CDE/AlgoCDE.m | 1,729 | utf_8 | ebd3f19c96d3a0197eca990315d9ab0f | function [c, B] = AlgoCDE(A, treshold, verbose)
if nargin < 2 || isempty(treshold)
treshold = eps;
end
if nargin < 3
verbose = 1;
end
if verbose
disp('**************************************************');
disp('A:');
disp(num2str(A));
end
AT = A';
CanonicalB = [zeros(length(AT),... |
github | gerac83/clifford_toolbox-master | NestReflectByHyper.m | .m | clifford_toolbox-master/MATLAB/cliffordv07/CDE/NestReflectByHyper.m | 828 | utf_8 | 4e9d2f76945c5fa71d6bd9d24d0a3b99 | function out = NestReflectByHyper(v, a, h)
if h - 1 > 1
if ~isempty(Coefficient(v{h-1}))
% ReflectByHyper[v[[h - 1]], NestReflectByHyper[v, a, h - 1]]
out = ReflectByHyper(v{h - 1}, NestReflectByHyper(v, a, h - 1));
return;
else
% ReflectByHyper[v[[h - 2]], NestReflectBy... |
github | gerac83/clifford_toolbox-master | phi.m | .m | clifford_toolbox-master/MATLAB/cliffordv07/CDE/phi.m | 1,365 | utf_8 | dcf269ed745133be170752bfaad9585c | function out = phi(s,B)
if size(B,1) < 2
error('TBD!');
end
if s == 0
out = eye(size(B,1));
return;
end
one = -1 / getScalar(GAproduct(s,s));
res = zeros(size(B,1),size(B,1));
for l = 1:size(B,1)
for j = 1:size(B,1)
if l == j
two = getScalar(GAinner(s,B(j,:))) ^ ... |
github | gerac83/clifford_toolbox-master | transform.m | .m | clifford_toolbox-master/MATLAB/cliffordv07/Extra/transform.m | 2,581 | utf_8 | 208e24fb8200ce3f2f0275a9f36c5319 | function out = transform(in)
%TRANSFORM(IN) transforms IN from quaternion to Clifford algebra
% representation
%
% Version: 1.0 (Nov, 2010)
% Copyright (c) 2010, Aragon-Camarasa, G., Aragon-Gonzalez, G.;
% Aragon J. L. & Rodriguez-Andrade, M. A.
if ~ischar(in)
error('Input must be a string!');
end
i... |
github | gerac83/clifford_toolbox-master | untransform.m | .m | clifford_toolbox-master/MATLAB/cliffordv07/Extra/untransform.m | 2,083 | utf_8 | 49937baff82144c359750f81a2f036f4 | function out = untransform(in)
%UNTRANSFORM(IN) untransforms IN from Clifford algebra to quaternion
% representation
%
% Version: 1.0 (Nov, 2010)
% Copyright (c) 2010, Aragon-Camarasa, G., Aragon-Gonzalez, G.;
% Aragon J. L. & Rodriguez-Andrade, M. A.
if ischar(in)
in = GAstring2mat(in);
end
tuples ... |
github | gerac83/clifford_toolbox-master | GAstring2mat.m | .m | clifford_toolbox-master/MATLAB/cliffordv07/Extra/GAstring2mat.m | 4,915 | utf_8 | 401c3e197e38aba1f697f87b1493cceb | function out = GAstring2mat(str)
%GASTRING2MAT(STRING) transforms from a string to an array
%representation
%
% Version: 1.0 (Nov, 2010)
% Copyright (c) 2010, Aragon-Camarasa, G., Aragon-Gonzalez, G.;
% Aragon J. L. & Rodriguez-Andrade, M. A.
if ~ischar(str)
error('Input must be a string!');
end
% E... |
github | gerac83/clifford_toolbox-master | ToVector.m | .m | clifford_toolbox-master/MATLAB/cliffordv07/Core/ToVector.m | 961 | utf_8 | 3e8cc5e344e834607e21df0b4b05fe77 | function out = ToVector(x,n)
%TOVECTOR(X,N) transform the n-dimensional vector x from a*e[1]+b*e[2]+... to
% the standard Mathematica form {a,b,...}. The defaul value of n is the
% highest of all e[i]'s.
%
% Based on: Clifford Algebra with Mathematica (2008) http://arxiv.org/abs/0810.2412
% Version: 0.7 (Oct, 2... |
github | gerac83/clifford_toolbox-master | GeometricProduct.m | .m | clifford_toolbox-master/MATLAB/cliffordv07/Core/GeometricProduct.m | 3,851 | utf_8 | f580ae676a64a31271212d630f59d326 | function [out, out1] = GeometricProduct(varargin)
%GEOMETRICPRODUCT(A1,A2,...) calculates the geometric product of
% multivectors m1,m2,..., mn
%
% INPUTS
% Inputs may be a string or a matrix. They are explained below...
% STRING: it should be expresed in terms of the geometric algrabra basis.
% See example be... |
github | feigl/gipht-master | fitvalley4.m | .m | gipht-master/obsolete/fitvalley4.m | 4,308 | utf_8 | 8a2712f13e83375d5cecf36765b87e3c | function [xvalley,yvalley] = fitvalley3(xvals,yvals)
% given a set of values, find the valley function (bottom envelope)
% 20200526 Kurt Feigl
narginchk(2,2);
nargoutchk(2,2);
if numel(xvals) == numel(yvals)
nvals = numel(xvals);
%% find convex hull
% dt = delaunayTriangulation(xvals,yvals);
% k1 = convexHull(dt); ... |
github | feigl/gipht-master | fitvalley2.m | .m | gipht-master/obsolete/fitvalley2.m | 3,075 | utf_8 | 973bc0241093410e79d8799ac3488cb4 | function [xvalley,yedges] = fitvalley2(xvals,yvals)
% given a set of values, find the valley function (bottom envelope)
% 20200526 Kurt Feigl
narginchk(2,2);
nargoutchk(2,2);
if numel(xvals) == numel(yvals)
nvals = numel(xvals);
% [N,edges,bin] = histcounts(___) also returns an index array, bin, using any of the pr... |
github | feigl/gipht-master | funseparable27.m | .m | gipht-master/obsolete/funseparable27.m | 42,622 | utf_8 | e5c3a18bbdc46b30963d0d6d4e7ed9c9 | function varargout = funseparable27(varargin)
%function varargout = funseparable27(varargin)
%
%% separable model for range change
% p == parameter vector (1 column)
% xyzm == easting, northing, up in m [3 rows]
% tepochs == unique times in decimal years [1 row]
% bpest == orbital separation w.r.t. vir... |
github | feigl/gipht-master | fitvalley3.m | .m | gipht-master/obsolete/fitvalley3.m | 3,248 | utf_8 | 8670cb9c6485f559160677e309402c52 | function [xvalley,yvalley] = fitvalley3(xvals,yvals)
% given a set of values, find the valley function (bottom envelope)
% 20200526 Kurt Feigl
narginchk(2,2);
nargoutchk(2,2);
if numel(xvals) == numel(yvals)
nvals = numel(xvals);
% find convex hull
dt = delaunayTriangulation(xvals,yvals);
k1 = convexHull(dt);
% %... |
github | feigl/gipht-master | fitvalley.m | .m | gipht-master/obsolete/fitvalley.m | 2,780 | utf_8 | 5a54a978639194f2a049afc2529159ad | function [xvalley,yedges] = fitvalley(xvals,yvals)
% given a set of values, find the valley function (bottom envelope)
% 20200526 Kurt Feigl
narginchk(2,2);
nargoutchk(2,2);
if numel(xvals) == numel(yvals)
nvals = numel(xvals);
% [N,edges,bin] = histcounts(___) also returns an index array, bin, using any of the pre... |
github | feigl/gipht-master | start_mli0.m | .m | gipht-master/comfemat/start_mli0.m | 3,519 | utf_8 | 31ea7d4f9daa63f6efb4a711869197a8 |
function status1 = start_mli(verbose)
% start matlab live link with comsol on Mac
% 20200526 Kurt Feigl
narginchk(0,1);
nargoutchk(0,1);
if nargin < 1
help(sprintf('%s',mfilename));
end
if nargin < 1
verbose = 0;
end
%% Comsol server must be started
switch computer
case 'MACI64'
[status0, output... |
github | feigl/gipht-master | source.m | .m | gipht-master/comfemat/source.m | 231 | utf_8 | 30e294ead4c0b291a1df28d37e4e77d4 | function q=source(x,y)
% vector inputs and outputs
for i=1:length(x)
q(i) = calcsource(x(i), y(i));
end
function q=calcsource(x,y)
% scalar inputs and outputs
r = sqrt(x^2+y^2);
if r<0.5
q = 1000;
else
q = 500;
end
|
github | feigl/gipht-master | grdinfo4.m | .m | gipht-master/extern/grdinfo4.m | 7,599 | utf_8 | d69062da7d45d9594840cf8c041e7a25 | function INFO = grdinfo4(file)
%GRDINFO2 Print information about a GMT grdfile (netCDF format, GMT v3 or v4)
%
% Uses NetCDF libraries to display information about a GMT grid file.
% Duplicates (some) functionality of the program grdinfo (which requires
% compilation as a mexcdf function on each architecture) using
% ... |
github | feigl/gipht-master | anneal6.m | .m | gipht-master/extern/anneal6.m | 13,300 | utf_8 | b7aca663cd67c3a38985a828425cba2f | %function [mhat,F,store,energy,count,msig]=anneal6(FUN,bounds,OPTIONS,varargin)
function [mhat,F,store,energy,count,msig] = anneal6(objfun,OPTIONS,DST,PST,TST)
%ANNEAL [mhat,F,store,energy,count]=anneal5(objfun,bounds,OPTIONS,x1,x2...,xn)
%Simulated annealing algorithm that tries to find a minimum to the functio... |
github | feigl/gipht-master | anneal5.m | .m | gipht-master/extern/anneal5.m | 12,393 | utf_8 | 1a19af1275cd415e2ff3e1910e4dde0a | function [mhat,F,store,energy,count,msig]=anneal5(FUN,bounds,OPTIONS,varargin)
%ANNEAL [mhat,F,store,energy,count]=anneal5(FUN,bounds,OPTIONS,x1,x2...,xn)
%Simulated annealing algorithm that tries to find a minimum to the function 'FUN'.
%
%INPUTS:
%
%'FUN' specifies the objective function. This function sho... |
github | feigl/gipht-master | xml2struct.m | .m | gipht-master/extern/xml2struct.m | 6,955 | utf_8 | 58f0b998cc71b30b4a6a12b330cfe950 | function [ s ] = xml2struct( file )
%Convert xml file into a MATLAB structure
% [ s ] = xml2struct( file )
%
% A file containing:
% <XMLname attrib1="Some value">
% <Element>Some text</Element>
% <DifferentElement attrib2="2">Some more text</Element>
% <DifferentElement attrib3="2" attrib4="1">Even more t... |
github | feigl/gipht-master | grdinfo3.m | .m | gipht-master/extern/grdinfo3.m | 5,852 | utf_8 | 6fd07a897fa81465b9bc4192009679ef | function INFO = grdinfo3(file)
%GRDINFO2 Print information about a GMT grdfile (netCDF format, GMT v3 or v4)
%
% Uses NetCDF libraries to display information about a GMT grid file.
% Duplicates (some) functionality of the program grdinfo (which requires
% compilation as a mexcdf function on each architecture) using
% ... |
github | feigl/gipht-master | bookfonts.m | .m | gipht-master/extern/bookfonts.m | 199 | utf_8 | 848f2398e2f9199755c411de4cedec2e | % Parameter Estimation and Inverse Problems, 2nd edition, 2011
% by R. Aster, B. Borchers, C. Thurber
% Set figure fontsizes for book size
function bookfonts
set(gca,'FontSize',18,'LineWidth',1.0);
|
github | feigl/gipht-master | derivest.m | .m | gipht-master/extern/derivest.m | 22,656 | utf_8 | 53b8b903ce69d613a113720690d9fe08 | function [der,errest,finaldelta] = derivest(fun,x0,varargin)
% DERIVEST: estimate the n'th derivative of fun at x0, provide an error estimate
% usage: [der,errest] = DERIVEST(fun,x0) % first derivative
% usage: [der,errest] = DERIVEST(fun,x0,prop1,val1,prop2,val2,...)
%
% Derivest will perform numerical differentiatio... |
github | feigl/gipht-master | fmincon_test.m | .m | gipht-master/extern/fmincon_test.m | 1,524 | utf_8 | 5b84d8b3b6fc0beaac714381382a7b1a | function x = fmincon_test
% To optimize for specific values of a1 and a2, first assign the values
% to these two parameters. Then create two one-argument anonymous
% functions that capture the values of a1 and a2, and call myfun and
% mycon with two arguments. Finally, pass these anonymous functions to... |
github | feigl/gipht-master | OkadaSol.m | .m | gipht-master/extern/OkadaSol.m | 5,516 | utf_8 | 2fe11d1c7d29e2becc8ad76be85a2999 | % This file is distributed in the hope that it will be useful, but
% WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
% -----------------------------------------------------------------------
% Matlab program for the Okada solution computation
% ... |
github | feigl/gipht-master | okada85_checklist.m | .m | gipht-master/extern/okada85_checklist.m | 3,768 | utf_8 | bb7b0783b2698a29e501f3e2c947bf85 | function okada_checklist
% Checks consistency of OKADA85 results using the "Checklist for numerical calculations"
% from Table 2 [Okada, 1985] page 1149.
%
% References:
% Okada Y., Surface deformation due to shear and tensile faults in a
% half-space, Bull. Seismol. Soc. Am., 75:4, 1135-1154, 1985.
%
% Author... |
github | feigl/gipht-master | grdinfo2.m | .m | gipht-master/extern/grdinfo2.m | 5,272 | utf_8 | 090b1dc21214900d6a3b016c7b77f1c4 | function d = grdinfo2(file);
%GRDINFO2 Print information about a GMT grdfile (netCDF format, GMT v3 or v4)
%
% Uses NetCDF libraries to display information about a GMT grid file.
% Duplicates (some) functionality of the program grdinfo (which requires
% compilation as a mexcdf function on each architecture) using
% Ma... |
github | feigl/gipht-master | unit.m | .m | gipht-master/extern/UnitConversion_rev2/unit.m | 95,108 | utf_8 | 23969e4e61d56d98b995ee6c37dda5fe | classdef unit
% "unit" attaches physical units to a variable.
% Examples:
% unit(1,'mile')
%
% ans =
% 1609.34 m
%
% y=unit('furlongs/fortnight')
%
% ans =
% 0.00016631 m/s
%
% Any variable defined by "unit"... |
github | feigl/gipht-master | convConstant.m | .m | gipht-master/extern/UnitConversion_rev2/convConstant.m | 18,722 | utf_8 | 89f6d3f9c828f7541790de15812982ee | classdef convConstant
% Maintains the conversion constants used by the class "unit"
%
% An excellent reference, by Prof. Russ Rowlett, University of
% North Carolina at Chapel Hill, is available on the Web at:
% http://www.unc.edu/~rowlett/units
%
% AUTHOR:
% John... |
github | feigl/gipht-master | boxplot_custom.m | .m | gipht-master/extern/boxplot_custom/boxplot_custom.m | 22,974 | utf_8 | b896db717cd8af9a6de538ada2958a49 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Generate basic and special boxplots. Aside from the simple boxplots, you
% can create horizontal boxplots, alternate y axis, multiple bars, and
% ignore empty samples. You can also add the mean over the boxplot, and
% select the method... |
github | feigl/gipht-master | natsort.m | .m | gipht-master/extern/natsortfiles/natsort.m | 12,982 | utf_8 | 78209edfeb3527a783d5d0f246a00d17 | function [Y,ndx,dbg] = natsort(X,rgx,varargin)
% Natural-order / alphanumeric sort strings or character vectors or categorical.
%
% (c) 2012-2021 Stephen Cobeldick
%
% Sorts text by character code and by number value. By default matches
% integer substrings and performs a case-insensitive ascending sort.
% Optio... |
github | feigl/gipht-master | natsortfiles.m | .m | gipht-master/extern/natsortfiles/natsortfiles.m | 8,148 | utf_8 | 0442391290855f74a8d3514aeb67d0ea | function [Y,ndx,dbg] = natsortfiles(X,rgx,varargin)
% Natural-order / alphanumeric sort of filenames or foldernames.
%
% (c) 2014-2021 Stephen Cobeldick
%
% Sorts text by character code and by number value. File/folder names, file
% extensions, and path directories (if supplied) are sorted separately to
% ensure... |
github | feigl/gipht-master | test_generalized_paretos.m | .m | gipht-master/src/test_generalized_paretos.m | 4,713 | utf_8 | 1af19d9e0dda290d5d7f62290ba6b7df | function crit69 = test_generalized_paretos(sample1,mean1)
%function P = testGPmeans(gpmean1, n1, gpmean2, n2)
% Return critical value of mean for sample2 drawn from
% a Generalized Pareto (GP) distribution
% such that sample2 is significantly different from sample1
%
% Kurt Feigl 2011-OCT-11
%
% INPUTS:
% gpmean1, g... |
github | feigl/gipht-master | estimate_uncertainty.m | .m | gipht-master/src/estimate_uncertainty.m | 6,266 | utf_8 | bcc09eebd2cb1c979e9253a1519d3450 |
function msig = estimate_uncertainty(crit68,p0,p1,cost0,cost1,acosts1,atemps,atrials,lb,ub,pnames,objfun,fitfun,xdata,ydata,ysigma)
%function msig = estimate_uncertainty(crit68,p0,p1,cost0,cost1,acosts1,atemps,atrials,lb,ub,pnames,objfun,fitfun,xdata,ydata,ysigma)
% estimate uncertainties from width of cost valley
% K... |
github | feigl/gipht-master | testkappas3.m | .m | gipht-master/src/testkappas3.m | 3,475 | utf_8 | f5ae08cc0db86f1b1b6fdc1ca030b69b | function P = testkappas3(Rbar1, n1, Rbar2, n2)
%function P = testkappas3(Rbar1, n1, Rbar2, n2)
%Test equality of concentration parameters
% Mardia and Jupp, Directional Statistics, Wiley, 1999
% chap. 7.3.2 Tests of Equality of Concentration Parameters, pages 133-134
% Null hypothesis is that concentration parameters ... |
github | feigl/gipht-master | read_geometry_from_h5_v1.m | .m | gipht-master/src/read_geometry_from_h5_v1.m | 9,112 | utf_8 | 324f3a81e3fc5c8339ad2329d79cd194 | <<<<<<< HEAD
function GEOM = read_geometry_from_h5(fname,doplots)
=======
function GEOM = read_geometry_from_h5(fname,varargin)
>>>>>>> c0a77c90e8512fa2eda6314b5513fb71fb565958
% read an H5 file from MINTPY and return structure with arrays containing geometry
% sources of information
% https://github.com/insarlab/MintP... |
github | feigl/gipht-master | vonmisesness.m | .m | gipht-master/src/vonmisesness.m | 4,858 | utf_8 | b753d116719ade42cc5d3ade25dc546f | function [S, teststring] = vonmisesness(theta1)
%function [S, teststring] = vonmisesness(theta)
% Test if directional data theta in radians follow Von Mises distribution
%
% Mardia and Jupp, Directional Statistics, Wiley, 1999
% chap. 7.5 Testing Von Misesness, pages 142-143
% (As printed in this textbook, the expressi... |
github | feigl/gipht-master | funfit28.m | .m | gipht-master/src/funfit28.m | 42,887 | utf_8 | 2b646674590392035d6116e715d435e6 | function varargout = funfit28(varargin)
%function varargout = funfit28(varargin)
%
%% separable model for range change
% p == parameter vector (1 column)
% xyzm == easting, northing, up in m [3 rows]
% tepochs == unique times in decimal years [1 row]
% bpest == orbital separation w.r.t. virutal orbit i... |
github | feigl/gipht-master | read_table.m | .m | gipht-master/src/read_table.m | 3,750 | utf_8 | 5fd8e52d6bc70997fb706e0557faefc5 | function [values, name] = read_table(filename,nheaders,ncols,iname)
%function [values,name]=read_table(filename,nheaders,ncols,iname)
% read an ascii table of data
% return parameters as column vectors
%
% ncols = number of columns in table, including name
% nheader = number of header lines to skip
% iname =... |
github | ivanceras/balisong-master | bresenham.m | .m | balisong-master/src/bresenham.m | 4,492 | utf_8 | 96e60cdb87326c9ad3d893fdc1508d63 | % Generate X Y Z coordinates of a 3D Bresenham's line between
% two given points.
%
% A very useful application of this algorithm can be found in the
% implementation of Fischer's Bresenham interpolation method in my
% another program that can rotate three dimensional image volume
% with an affine matrix:
% http... |
github | babrooks/SGSolve-master | sgmexbuild.m | .m | SGSolve-master/MATLAB/sgmexbuild.m | 2,189 | utf_8 | f76d80357b374d642167a0c1a7730609 | % This file is part of the SGSolve library for stochastic games
% Copyright (C) 2016 Benjamin A. Brooks
%
% SGSolve free software: you can redistribute it and/or modify it
% under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your ... |
github | babrooks/SGSolve-master | sgmexbuild2.m | .m | SGSolve-master/MATLAB/sgmexbuild2.m | 2,196 | utf_8 | 226b1937902ff23afdb1d540a0c3fd75 | % This file is part of the SGSolve library for stochastic games
% Copyright (C) 2016 Benjamin A. Brooks
%
% SGSolve free software: you can redistribute it and/or modify it
% under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your ... |
github | babrooks/SGSolve-master | con2vert.m | .m | SGSolve-master/MATLAB/con2vert.m | 5,476 | utf_8 | dac5963bef461b93fbcfb7878ce13300 | function [V,nr] = con2vert(A,b)
% CON2VERT - convert a convex set of constraint inequalities into the set
% of vertices at the intersections of those inequalities;i.e.,
% solve the "vertex enumeration" problem. Additionally,
% identify redundant entries in the list of inequalities.
... |
github | babrooks/SGSolve-master | abstwist.m | .m | SGSolve-master/MATLAB/abstwist.m | 41,637 | utf_8 | 566150a604b65b728670780931165be3 | % This file is part of the SGSolve library for stochastic games
% Copyright (C) 2016 Benjamin A. Brooks
%
% SGSolve free software: you can redistribute it and/or modify it
% under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your ... |
github | babrooks/SGSolve-master | kocherlakota.m | .m | SGSolve-master/MATLAB/kocherlakota.m | 4,797 | utf_8 | 70a5a8eefc2d72405d3c9e95667df7e8 | function [P,LR,ATK] = kocherlakota
%% Ben's file for kocherlakota style simulations
% 8-19-2015
numEndowments = 5; % Should be odd?
consumptionToEndowments = 25;
% P = linspace(0,10,numEndowments);
% P=0:20;
P=0:0.25:12.75;
% P=[13 13.25 13.5 13.75 14];
LR = zeros(numel(P),2);
ATK=LR;
delta=0.9;
numSimulations = 1e8;... |
github | se4u/mvlsa-master | convnfft.m | .m | mvlsa-master/src/MRDS/convnfft.m | 6,182 | utf_8 | b126295d4ec48b4308c041f512591036 | function A = convnfft(A, B, shape, dims, options)
% CONVNFFT FFT-BASED N-dimensional convolution.
% C = CONVNFFT(A, B) performs the N-dimensional convolution of
% matrices A and B. If nak = size(A,k) and nbk = size(B,k), then
% size(C,k) = max([nak+nbk-1,nak,nbk]);
%
% C = CONVNFFT(A, B, SHAPE) controls the s... |
github | se4u/mvlsa-master | tom_test_impl.m | .m | mvlsa-master/src/evaluate/tom_test_impl.m | 3,042 | utf_8 | d5481d33645a4bccafd85423c2eec1b9 | function [n_total, n_attempt, n_correct_cosadd, n_correct_cosmul]=tom_test_impl(...
word, word_map, get_emb, dataset_fn, U)
scws_file=getenv(dataset_fn);
[w1, w2, w3, w4]=textread(scws_file, '%s %s %s %s');
n_total=0;
n_attempt=0;
n_correct_cosadd=0;
n_correct_cosmul=0;
nonlinear_transform=@(x) x;
normalize_vec... |
github | se4u/mvlsa-master | normalize_embedding.m | .m | mvlsa-master/src/evaluate/normalize_embedding.m | 145 | utf_8 | a719669db504da0b2806a98480131cf6 | % HELP 1
function embedding=normalize_embedding(embedding)
for i=1:size(embedding, 1)
embedding(i,:)=embedding(i,:)/norm(embedding(i,:));
end |
github | se4u/mvlsa-master | batch_incremental_pca.m | .m | mvlsa-master/src/general_utility/batch_incremental_pca.m | 613 | utf_8 | 04342407df497ef2121687bf4bd13288 | function [Ut_new, St_new]=batch_incremental_pca(x, U, S)
r = size(U, 2);
b = size(x, 2);
xh = U'*x;
H = x - U*xh;
[J, W] = qr(H, 0);
Q = [diag(S) xh ;...
zeros(b,r) W];
[Ut_new, St_new, ~]=fastsvd(Q);
St_new=St_new(1:r);
Ut_new=[U J] * Ut_new(:, 1:r);
end
function [U, S, V]=fastsvd(M) %#ok<INUSD>
% Ideally... |
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