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annotate scripts/plot/pareto.m @ 14872:c2dbdeaa25df

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maint: use rows() and columns() to clarify m-files. * gradient.m, interp1q.m, rat.m, tsearchn.m, image.m, imwrite.m, area.m, contourc.m, hist.m, isocolors.m, isonormals.m, meshz.m, print.m, __bar__.m, __go_draw_axes__.m, __interp_cube__.m, __marching_cube__.m, __patch__.m, __print_parse_opts__.m, __quiver__.m, rose.m, shrinkfaces.m, stairs.m, surfnorm.m, tetramesh.m, text.m, deconv.m, spline.m, intersect.m, setdiff.m, setxor.m, union.m, periodogram.m, pcg.m, perms.m: Replace size (x,1) with rows (x) and size(x,2) with columns(x).
author Rik <octave@nomad.inbox5.com>
date Tue, 17 Jul 2012 13:34:19 -0700
parents 5d3a684236b0
children 64e7bb01fce2
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1 ## Copyright (C) 2007-2012 David Bateman
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2 ## Copyright (C) 2003 Alberto Terruzzi
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3 ##
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4 ## This file is part of Octave.
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5 ##
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6 ## Octave is free software; you can redistribute it and/or modify it
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7 ## under the terms of the GNU General Public License as published by
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8 ## the Free Software Foundation; either version 3 of the License, or (at
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9 ## your option) any later version.
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10 ##
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11 ## Octave is distributed in the hope that it will be useful, but
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12 ## WITHOUT ANY WARRANTY; without even the implied warranty of
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13 ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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14 ## General Public License for more details.
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15 ##
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16 ## You should have received a copy of the GNU General Public License
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17 ## along with Octave; see the file COPYING. If not, see
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18 ## <http://www.gnu.org/licenses/>.
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19
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20 ## -*- texinfo -*-
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21 ## @deftypefn {Function File} {} pareto (@var{x})
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22 ## @deftypefnx {Function File} {} pareto (@var{x}, @var{y})
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23 ## @deftypefnx {Function File} {} pareto (@var{h}, @dots{})
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24 ## @deftypefnx {Function File} {@var{h} =} pareto (@dots{})
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25 ## Draw a Pareto chart, also called ABC chart. A Pareto chart is a bar graph
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26 ## used to arrange information in such a way that priorities for process
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27 ## improvement can be established. It organizes and displays information
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28 ## to show the relative importance of data. The chart is similar to the
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29 ## histogram or bar chart, except that the bars are arranged in decreasing
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30 ## order from left to right along the abscissa.
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31 ##
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32 ## The fundamental idea (Pareto principle) behind the use of Pareto
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33 ## diagrams is that the majority of an effect is due to a small subset of the
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34 ## causes, so for quality improvement the first few (as presented on the
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35 ## diagram) contributing causes to a problem usually account for the majority
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36 ## of the result. Thus, targeting these "major causes" for elimination
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37 ## results in the most cost-effective improvement scheme.
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38 ##
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39 ## The data are passed as @var{x} and the abscissa as @var{y}. If @var{y} is
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40 ## absent, then the abscissa are assumed to be @code{1 : length (@var{x})}.
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41 ## @var{y} can be a string array, a cell array of strings or a numerical
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42 ## vector.
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43 ##
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44 ## The optional return value @var{h} is a 2-element vector with a graphics
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45 ## handle for the created bar plot and a second handle for the created line
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46 ## plot.
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47 ##
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48 ## An example of the use of @code{pareto} is
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49 ##
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50 ## @example
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51 ## @group
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52 ## Cheese = @{"Cheddar", "Swiss", "Camembert", ...
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53 ## "Munster", "Stilton", "Blue"@};
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54 ## Sold = [105, 30, 70, 10, 15, 20];
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55 ## pareto (Sold, Cheese);
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56 ## @end group
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57 ## @end example
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58 ## @end deftypefn
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59
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60 function h = pareto (varargin)
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61
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62 if (nargin != 1 && nargin != 2)
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63 print_usage ();
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64 endif
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65
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66 x = varargin {1}(:).';
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67 if (nargin == 2)
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68 y = varargin {2}(:).';
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69 if (! iscell (y))
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70 if (ischar (y))
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71 y = cellstr (y);
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72 else
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73 y = cellfun ("num2str", num2cell (y), "uniformoutput", false);
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74 endif
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75 endif
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76 else
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77 y = cellfun ("int2str", num2cell (1 : numel (x)),
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78 "uniformoutput", false);
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79 endif
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80
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81 [x, idx] = sort (x, "descend");
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82 y = y (idx);
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83 cdf = cumsum (x);
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84 maxcdf = max (cdf);
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85 cdf = cdf ./ maxcdf;
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86 cdf95 = cdf - 0.95;
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87 idx95 = find (sign (cdf95(1:end-1)) != sign (cdf95(2:end)))(1);
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88
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89 [ax, hbar, hline] = plotyy (1 : idx95, x (1 : idx95),
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90 1 : length (cdf), 100 .* cdf,
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91 @bar, @plot);
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92
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93 axis (ax(1), [1 - 0.6, idx95 + 0.6, 0, maxcdf]);
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94 axis (ax(2), [1 - 0.6, idx95 + 0.6, 0, 100]);
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95 set (ax(2), "ytick", [0, 20, 40, 60, 80, 100],
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96 "yticklabel", {"0%", "20%", "40%", "60%", "80%", "100%"});
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97 set (ax(1), "xtick", 1 : idx95, "xticklabel", y (1: idx95));
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98 set (ax(2), "xtick", 1 : idx95, "xticklabel", y (1: idx95));
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99
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100 if (nargout > 0)
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101 h = [hbar; hline];
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102 endif
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103
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104 endfunction
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105
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106
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107 %!demo
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108 %! clf;
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109 %! colormap (jet (64));
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110 %! Cheese = {'Cheddar', 'Swiss', 'Camembert', 'Munster', 'Stilton', 'Blue'};
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111 %! Sold = [105, 30, 70, 10, 15, 20];
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112 %! pareto (Sold, Cheese);
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113
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114 %!demo
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115 %! clf;
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116 %! % Suppose that we want establish which products makes 80% of turnover.
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117 %! Codes = {'AB4','BD7','CF8','CC5','AD11','BB5','BB3','AD8','DF3','DE7'};
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118 %! Value = [2.35 7.9 2.45 1.1 0.15 13.45 5.4 2.05 0.85 1.65]';
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119 %! SoldUnits = [54723 41114 16939 1576091 168000 687197 120222 168195, ...
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120 %! 1084118 55576]';
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121 %! pareto (Value.*SoldUnits, Codes);
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122