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Fix range of sigma in normal distribution to exclude 0. * normcdf.m, normpdf.m: Correct 's >= 0' to 's > 0'.
author Rik <octave@nomad.inbox5.com>
date Thu, 16 Jun 2011 21:05:10 -0700
parents c792872f8942
children 63d06af0376a
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John W. Eaton <jwe@octave.org>
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1 ## Copyright (C) 2004-2011 Paul Kienzle
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2 ##
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3 ## This file is part of Octave.
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4 ##
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5 ## Octave is free software; you can redistribute it and/or modify it
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6 ## under the terms of the GNU General Public License as published by
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7 ## the Free Software Foundation; either version 3 of the License, or (at
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8 ## your option) any later version.
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9 ##
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10 ## Octave is distributed in the hope that it will be useful, but
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11 ## WITHOUT ANY WARRANTY; without even the implied warranty of
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12 ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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13 ## General Public License for more details.
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14 ##
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15 ## You should have received a copy of the GNU General Public License
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16 ## along with Octave; see the file COPYING. If not, see
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17 ## <http://www.gnu.org/licenses/>.
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18 ##
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19 ## Original version by Paul Kienzle distributed as free software in the
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20 ## public domain.
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21
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22 ## -*- texinfo -*-
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23 ## @deftypefn {Function File} {} sprand (@var{m}, @var{n}, @var{d})
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24 ## @deftypefnx {Function File} {} sprand (@var{s})
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25 ## Generate a random sparse matrix. The size of the matrix will be
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26 ## @var{m} by @var{n}, with a density of values given by @var{d}.
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27 ## @var{d} should be between 0 and 1. Values will be uniformly
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28 ## distributed between 0 and 1.
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29 ##
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30 ## Note: sometimes the actual density may be a bit smaller than @var{d}.
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31 ## This is unlikely to happen for large, truly sparse, matrices.
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32 ##
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33 ## If called with a single matrix argument, a random sparse matrix is
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34 ## generated wherever the matrix @var{S} is non-zero.
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35 ## @seealso{sprandn}
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36 ## @end deftypefn
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37
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38 ## Author: Paul Kienzle <pkienzle@users.sf.net>
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39 ##
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40 ## Changelog:
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41 ##
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42 ## Piotr Krzyzanowski <przykry2004@users.sf.net>
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43 ## 2004-09-27 use Paul's hint to allow larger random matrices
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44 ## at the price of sometimes lower density than desired
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45 ## David Bateman
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46 ## 2004-10-20 Texinfo help and copyright message
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47
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48 function S = sprand (m, n, d)
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49
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50 if (nargin != 1 && nargin != 3)
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51 print_usage ();
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52 endif
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53
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54 if (nargin == 1)
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55 [i, j, v] = find (m);
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56 [nr, nc] = size (m);
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57 S = sparse (i, j, rand (size (v)), nr, nc);
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58 return;
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59 endif
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60
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61 if (!(isscalar (m) && m == fix (m) && m > 0))
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62 error ("sprand: M must be an integer greater than 0");
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63 endif
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64
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65 if (!(isscalar (n) && n == fix (n) && n > 0))
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66 error ("sprand: N must be an integer greater than 0");
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67 endif
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68
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69 if (d < 0 || d > 1)
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70 error ("sprand: density D must be between 0 and 1");
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71 endif
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72
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73 mn = m*n;
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74 ## how many entries in S would be satisfactory?
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75 k = round (d*mn);
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76 idx = unique (fix (rand (min (k*1.01, k+10), 1) * mn)) + 1;
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77 ## idx contains random numbers in [1,mn]
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78 ## generate 1% or 10 more random values than necessary in order to
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79 ## reduce the probability that there are less than k distinct
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80 ## values; maybe a better strategy could be used but I don't think
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81 ## it's worth the price
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82
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83 ## actual number of entries in S
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84 k = min (length (idx), k);
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85 j = floor ((idx(1:k)-1)/m);
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86 i = idx(1:k) - j*m;
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87 if (isempty (i))
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88 S = sparse (m, n);
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89 else
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90 S = sparse (i, j+1, rand (k, 1), m, n);
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91 endif
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92
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93 endfunction
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94