Mercurial > hg > octave-nkf
view scripts/plot/pareto.m @ 17136:e4968b4613a5
Overhaul default menubar (still not perfect).
* scripts/plot/figure.m: Always call __add_default_menu__.
* scripts/plot/private/__add_default_menu__.m: Check that toolkit is FLTK
before proceeding. Don't do redundant check that input is figure handle.
Don't turn off handlevisibility for submenus, they are already hidden
from above. Restrict findall() search to a depth of 1. Add __default_menu__
tags to Edit and Help menus so they can be identified. Don't call drawnow
unnecessarily in callback routines. Use gcbf() so that Save filename is
stored on a per figure basis rather than globally. Eliminate assigning
to unused variables. Add HACK to turn off menubar if property is set to
"none" on figure.
author | Rik <rik@octave.org> |
---|---|
date | Thu, 01 Aug 2013 10:18:54 -0700 |
parents | eaab03308c0b |
children | 6e8c621c3496 |
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## Copyright (C) 2007-2012 David Bateman ## Copyright (C) 2003 Alberto Terruzzi ## ## This file is part of Octave. ## ## Octave is 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 option) any later version. ## ## Octave 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. See the GNU ## General Public License for more details. ## ## You should have received a copy of the GNU General Public License ## along with Octave; see the file COPYING. If not, see ## <http://www.gnu.org/licenses/>. ## -*- texinfo -*- ## @deftypefn {Function File} {} pareto (@var{y}) ## @deftypefnx {Function File} {} pareto (@var{y}, @var{x}) ## @deftypefnx {Function File} {} pareto (@var{hax}, @dots{}) ## @deftypefnx {Function File} {@var{h} =} pareto (@dots{}) ## Draw a Pareto chart. ## ## A Pareto chart is a bar graph that arranges information in such a way ## that priorities for process improvement can be established; It organizes ## and displays information to show the relative importance of data. The chart ## is similar to the histogram or bar chart, except that the bars are arranged ## in decreasing magnitude from left to right along the x-axis. ## ## The fundamental idea (Pareto principle) behind the use of Pareto ## diagrams is that the majority of an effect is due to a small subset of the ## causes. For quality improvement, the first few contributing causes ## (leftmost bars as presented on the diagram) to a problem usually account for ## the majority of the result. Thus, targeting these "major causes" for ## elimination results in the most cost-effective improvement scheme. ## ## Typically only the magnitude data @var{y} is present in which case ## @var{x} is taken to be the range @code{1 : length (@var{y})}. If @var{x} ## is given it may be a string array, a cell array of strings, or a numerical ## vector. ## ## If the first argument @var{hax} is an axes handle, then plot into this axis, ## rather than the current axes returned by @code{gca}. ## ## The optional return value @var{h} is a 2-element vector with a graphics ## handle for the created bar plot and a second handle for the created line ## plot. ## ## An example of the use of @code{pareto} is ## ## @example ## @group ## Cheese = @{"Cheddar", "Swiss", "Camembert", ... ## "Munster", "Stilton", "Blue"@}; ## Sold = [105, 30, 70, 10, 15, 20]; ## pareto (Sold, Cheese); ## @end group ## @end example ## @seealso{bar, barh, hist, pie, plot} ## @end deftypefn function h = pareto (varargin) if (nargin != 1 && nargin != 2) print_usage (); endif x = varargin {1}(:).'; if (nargin == 2) y = varargin {2}(:).'; if (! iscell (y)) if (ischar (y)) y = cellstr (y); else y = cellfun ("num2str", num2cell (y), "uniformoutput", false); endif endif else y = cellfun ("int2str", num2cell (1 : numel (x)), "uniformoutput", false); endif [x, idx] = sort (x, "descend"); y = y (idx); cdf = cumsum (x); maxcdf = max (cdf); cdf = cdf ./ maxcdf; cdf95 = cdf - 0.95; idx95 = find (sign (cdf95(1:end-1)) != sign (cdf95(2:end)))(1); [ax, hbar, hline] = plotyy (1 : idx95, x (1 : idx95), 1 : length (cdf), 100 .* cdf, @bar, @plot); axis (ax(1), [1 - 0.6, idx95 + 0.6, 0, maxcdf]); axis (ax(2), [1 - 0.6, idx95 + 0.6, 0, 100]); set (ax(2), "ytick", [0, 20, 40, 60, 80, 100], "yticklabel", {"0%", "20%", "40%", "60%", "80%", "100%"}); set (ax(1), "xtick", 1 : idx95, "xticklabel", y (1: idx95)); set (ax(2), "xtick", 1 : idx95, "xticklabel", y (1: idx95)); if (nargout > 0) h = [hbar; hline]; endif endfunction %!demo %! clf; %! colormap (jet (64)); %! Cheese = {'Cheddar', 'Swiss', 'Camembert', 'Munster', 'Stilton', 'Blue'}; %! Sold = [105, 30, 70, 10, 15, 20]; %! pareto (Sold, Cheese); %!demo %! clf; %! % Suppose that we want establish which products makes 80% of turnover. %! Codes = {'AB4','BD7','CF8','CC5','AD11','BB5','BB3','AD8','DF3','DE7'}; %! Value = [2.35 7.9 2.45 1.1 0.15 13.45 5.4 2.05 0.85 1.65]'; %! SoldUnits = [54723 41114 16939 1576091 168000 687197 120222 168195, ... %! 1084118 55576]'; %! pareto (Value.*SoldUnits, Codes);