This file is indexed.

/usr/share/octave/packages/statistics-1.3.0/boxplot.m is in octave-statistics 1.3.0-4.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
## Copyright (C) 2002 Alberto Terruzzi <t-albert@libero.it>
## Copyright (C) 2006 Alberto Pose <apose@alu.itba.edu.ar>
## Copyright (C) 2011 Pascal Dupuis <Pascal.Dupuis@worldonline.be>
## Copyright (C) 2012 Juan Pablo Carbajal <carbajal@ifi.uzh.ch>
## Copyright (C) 2016 Pascal Dupuis <cdemills@gmail.com>
##
## This program 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.
##
## This program 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
## this program; if not, see <http://www.gnu.org/licenses/>.

## -*- texinfo -*-
## @deftypefn {Function File} {@var{s} =} boxplot (@var{data}, @var{notched}, @
## @var{symbol}, @var{vertical}, @var{maxwhisker}, @dots{})
## @deftypefnx {Function File} {@var{s} =} boxplot (@var{data}, @var{group})
## @deftypefnx {Function File} {[@dots{} @var{h}]=} boxplot (@dots{})
##
## Produce a box plot.
##
## The box plot is a graphical display that simultaneously describes several
## important features of a data set, such as center, spread, departure from
## symmetry, and identification of observations that lie unusually far from
## the bulk of the data.
##
## @var{data} is a matrix with one column for each data set, or data is a cell
## vector with one cell for each data set.
##
## @var{notched} = 1 produces a notched-box plot. Notches represent a robust
## estimate of the uncertainty about the median.
##
## @var{notched} = 0 (default) produces a rectangular box plot.
##
## @var{notched} in (0,1) produces a notch of the specified depth.
## notched values outside (0,1) are amusing if not exactly practical.
##
## @var{symbol} sets the symbol for the outlier values, default symbol for
## points that lie outside 3 times the interquartile range is 'o',
## default symbol for points between 1.5 and 3 times the interquartile
## range is '+'.
##
## @var{symbol} = '.' points between 1.5 and 3 times the IQR is marked with
## '.' and points outside 3 times IQR with 'o'.
##
## @var{symbol} = ['x','*'] points between 1.5 and 3 times the IQR is marked with
## 'x' and points outside 3 times IQR with '*'.
##
## @var{vertical} = 0 makes the boxes horizontal, by default @var{vertical} = 1.
##
## @var{maxwhisker} defines the length of the whiskers as a function of the IQR
## (default = 1.5). If @var{maxwhisker} = 0 then @code{boxplot} displays all data
## values outside the box using the plotting symbol for points that lie
## outside 3 times the IQR.
##
## Supplemental arguments are concatenated and passed to plot.
##
## The returned matrix @var{s} has one column for each data set as follows:
##
## @multitable @columnfractions .1 .8
## @item 1 @tab Minimum
## @item 2 @tab 1st quartile
## @item 3 @tab 2nd quartile (median)
## @item 4 @tab 3rd quartile
## @item 5 @tab Maximum
## @item 6 @tab Lower confidence limit for median
## @item 7 @tab Upper confidence limit for median
## @end multitable
##
## The returned structure @var{h} has handles to the plot elements, allowing
## customization of the visualization using set/get functions.
##
## Example
##
## @example
## title ("Grade 3 heights");
## axis ([0,3]);
## set(gca (), "xtick", [1 2], "xticklabel", @{"girls", "boys"@});
## boxplot (@{randn(10,1)*5+140, randn(13,1)*8+135@});
## @end example
##
## @end deftypefn

function [s hs] = boxplot (data, varargin)

  ## assign parameter defaults
  if (nargin < 1)
    print_usage;
  endif

  %# default values
  maxwhisker = 1.5;
  vertical = 1;
  symbol = ['+', 'o'];
  notched = 0;
  plot_opts = {};
  groups = [];
  
  %# Optional arguments analysis
  numarg = nargin - 1;
  option_args = ['Notch'; 'Symbol'; 'Vertical'; 'Maxwhisker'];
  indopt = 1;
  while (numarg)
    dummy = varargin{indopt++};
    if (!ischar (dummy))
      %# MatLAB allows passing the second argument as a grouping vector
      if (length (dummy) > 1)
        if (2 ~= indopt)
          error ('Boxplot.m: grouping vector may only be passed as second arg');
        endif
        groups = dummy;
      else  
        %# old way: positional argument
        switch indopt
          case 2
            notched = dummy;
          case 4
            vertical = dummy;
          case 5
            maxwhisker = dummy;
          otherwise
            error("No positional argument allowed at position %d", --indopt);
        endswitch
      endif
      numarg--; continue;
    else
      if (3 == indopt && length (dummy) <= 2)
        symbol = dummy;  numarg--; continue;
      else
        tt = strmatch(dummy, option_args);
        switch (tt)
          case 1
            notched = varargin{indopt};
          case 2
            symbol = varargin{indopt};
          case 3
            vertical = varargin{indopt};
          case 4
            maxwhisker = varargin{indopt};
          otherwise
            %# take two args and append them to plot_opts
            plot_opts(1, end+1:end+2) = {dummy,  varargin{indopt}};
        endswitch
      endif
      indopt++; numarg -= 2;
    endif
  endwhile

  if (1 == length (symbol)) symbol(2) = symbol(1); endif

  if (1 == notched) notched = 0.25; endif
  a = 1-notched;

  ## figure out how many data sets we have
  if (isempty (groups))
    if (iscell (data))
      nc = length (data);
    else
      if (isvector (data)) data = data(:); endif
      nc = columns (data);
    endif
    groups = (1:nc);
  else
    if (~isvector (data))
      error ('Boxplot.m: with the formalism (data, group), both must be vectors');
    end
    nc = unique (groups); dummy = cell (1, length (nc));
    for indopt = (1:length (nc))
      dummy(indopt) = data(groups == nc(indopt));
    end
    data = dummy; groups = nc(:).'; nc = length (nc); 
  end

  ## compute statistics
  ## s will contain
  ##    1,5    min and max
  ##    2,3,4  1st, 2nd and 3rd quartile
  ##    6,7    lower and upper confidence intervals for median
  s = zeros (7, nc);
  box = zeros (1, nc);
  whisker_x = ones (2,1)*[groups, groups];
  whisker_y = zeros (2, 2*nc);
  outliers_x = [];
  outliers_y = [];
  outliers2_x = [];
  outliers2_y = [];

  for indi = (1:nc)
    ## Get the next data set from the array or cell array
    if (iscell (data))
      col = data{indi}(:);
    else
      col = data(:, indi);
    endif
    ## Skip missing data
    col(isnan (col) | isna (col)) = [];
    ## Remember the data length
    nd = length (col);
    box(indi) = nd;
    if (nd > 1)
      ## min,max and quartiles
      s(1:5, indi) = statistics (col)(1:5);
      ## confidence interval for the median
      est = 1.57*(s(4, indi)-s(2, indi))/sqrt (nd);
      s(6, indi) = max ([s(3, indi)-est, s(2, indi)]);
      s(7, indi) = min ([s(3, indi)+est, s(4, indi)]);
      ## whiskers out to the last point within the desired inter-quartile range
      IQR = maxwhisker*(s(4, indi)-s(2, indi));
      whisker_y(:, indi) = [min(col(col >= s(2, indi)-IQR)); s(2, indi)];
      whisker_y(:,nc+indi) = [max(col(col <= s(4, indi)+IQR)); s(4, indi)];
      ## outliers beyond 1 and 2 inter-quartile ranges
      outliers = col((col < s(2, indi)-IQR & col >= s(2, indi)-2*IQR) | (col > s(4, indi)+IQR & col <= s(4, indi)+2*IQR));
      outliers2 = col(col < s(2, indi)-2*IQR | col > s(4, indi)+2*IQR);
      outliers_x = [outliers_x; groups(indi)*ones(size(outliers))];
      outliers_y = [outliers_y; outliers];
      outliers2_x = [outliers2_x; groups(indi)*ones(size(outliers2))];
      outliers2_y = [outliers2_y; outliers2];
    elseif (1 == nd)
      ## all statistics collapse to the value of the point
      s(:, indi) = col;
      ## single point data sets are plotted as outliers.
      outliers_x = [outliers_x; groups(indi)];
      outliers_y = [outliers_y; col];
    else
      ## no statistics if no points
      s(:, indi) = NaN;
    end
  end

  ## Note which boxes don't have enough stats
  chop = find (box <= 1);

  ## Draw a box around the quartiles, with width proportional to the number of
  ## items in the box. Draw notches if desired.
  box *= 0.4/max (box);
  quartile_x = ones (11,1)*groups + [-a;-1;-1;1;1;a;1;1;-1;-1;-a]*box;
  quartile_y = s([3,7,4,4,7,3,6,2,2,6,3],:);

  ## Draw a line through the median
  median_x = ones (2,1)*groups + [-a;+a]*box;
  median_y = s([3,3],:);

  ## Chop all boxes which don't have enough stats
  quartile_x(:, chop) = [];
  quartile_y(:, chop) = [];
  whisker_x(:,[chop, chop+nc]) = [];
  whisker_y(:,[chop, chop+nc]) = [];
  median_x(:, chop) = [];
  median_y(:, chop) = [];

  ## Add caps to the remaining whiskers
  cap_x = whisker_x;
  cap_x(1, :) -= 0.05;
  cap_x(2, :) += 0.05;
  cap_y = whisker_y([1, 1], :);

  #quartile_x,quartile_y
  #whisker_x,whisker_y
  #median_x,median_y
  #cap_x,cap_y

  ## Do the plot
  if (vertical)
    if (isempty (plot_opts))
     h = plot (quartile_x, quartile_y, "b;;",
            whisker_x, whisker_y, "b;;",
            cap_x, cap_y, "b;;",
            median_x, median_y, "r;;",
            outliers_x, outliers_y, [symbol(1), "r;;"],
            outliers2_x, outliers2_y, [symbol(2), "r;;"]);
    else
    h = plot (quartile_x, quartile_y, "b;;",
          whisker_x, whisker_y, "b;;",
          cap_x, cap_y, "b;;",
          median_x, median_y, "r;;",
            outliers_x, outliers_y, [symbol(1), "r;;"],
            outliers2_x, outliers2_y, [symbol(2), "r;;"], plot_opts{:});
    endif
  else
    if (isempty (plot_opts))
     h = plot (quartile_y, quartile_x, "b;;",
            whisker_y, whisker_x, "b;;",
            cap_y, cap_x, "b;;",
            median_y, median_x, "r;;",
            outliers_y, outliers_x, [symbol(1), "r;;"],
            outliers2_y, outliers2_x, [symbol(2), "r;;"]);
    else
    h = plot (quartile_y, quartile_x, "b;;",
          whisker_y, whisker_x, "b;;",
          cap_y, cap_x, "b;;",
          median_y, median_x, "r;;",
            outliers_y, outliers_x, [symbol(1), "r;;"],
            outliers2_y, outliers2_x, [symbol(2), "r;;"], plot_opts{:});
    endif
  endif

  % Distribute handles
  nq = 1:size(quartile_x,2);
  hs.box = h(nq);
  nw = nq(end) + [1:2*size(whisker_x,2)];
  hs.whisker = h(nw);
  nm = nw(end)+ [1:size(median_x,2)];
  hs.median = h(nm);

  no = nm;
  if ~isempty (outliers_y)
    no = nm(end) + [1:size(outliers_y,2)];
    hs.outliers = h(no);
  end
  if ~isempty (outliers2_y)
    no2 = no(end) + [1:size(outliers2_y,2)];
    hs.outliers2 = h(no2);
  end

endfunction

%!demo
%! axis ([0,3]);
%! boxplot ({randn(10,1)*5+140, randn(13,1)*8+135});
%! set(gca (), "xtick", [1 2], "xticklabel", {"girls", "boys"})
%! title ("Grade 3 heights");