OptimalSamplingMultiShellCNLO_singleRunΒΆ

% update gradients from an initial gradient set, such that the updated gradients are evenly distributed.
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% USAGE:
%   [gradCell, xopt, fopt, retcode] = OptimalSamplingMultiShellCNLO_singleRun(gradCellInitial, param)
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% INPUT (required)
%   gradCellInitial      :  N_k x 3 gradient matrices, where each row is a point in sphere. k=1,2,...,K
%   param.w              :  weight for single shell term. 0<w<1. 0.5 is the default value.
%
% INPUT (optional)
%   param.solver         :  'nlopt' (default): use sqp solver (SLSQP) in NLOPT.
%                           'matlab': use fmincon (sqp solver).
%   param.cartesian      :  true (default): use cartesian coordinate (with unit equality constraint);
%                           false: use spherical coordinate (no unit equality constraint).
%
%   param.localCon       :  0: do not use local constraint
%                           1 (default): use local constraint for the distance between samples in results and samples in initialization to reduce the inequality constraint.
%                                        It is faster, and with an appropriate localConAngle, it can obtain the same results as it is set as false.
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%   param.localConAngle  :  It is the maximal angular change between samples in results and samples in initialization.
%                           It is used when param.localCon is true. It is automatically set based on the upper bounds, if it is not given and param.localCon=true.
%                           If localConAngle>pi/2, then the result is the same as the results without localCon.
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% OUTPUT
%   gradCell             :  Kx1 cell, each element is a gradient matrix.
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% Reference:
%   1. "Single- and Multiple-Shell Uniform Sampling Schemes for Diffusion MRI Using Spherical Codes",
%       Jian Cheng, Dinggang Shen, Pew-Thian Yap, Peter J. Basser, IEEE Transactions on Medical Imaging, 2017.
%   2. "Novel single and multiple shell uniform sampling schemes for diffusion MRI using spherical codes",
%       Jian Cheng, Dinggang Shen, Pew-Thian Yap, Peter J. Basser, MICCAI 2015.
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% Copyright (c) 2014, Jian Cheng <jian.cheng.1983@gmail.com>
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