--- /dev/null
+function df = df_pad(df, dim, n, coltype=[])
+ %# function resu = df_pad(df, dim, n, coltype = [])
+ %# given a dataframe, insert n rows or columns, and adjust everything
+ %# accordingly. Coltype is a supplemental argument:
+ %# dim = 1 => not used
+ %# dim = 2 => type of the added column(s)
+ %# dim = 3 => index of columns receiving a new sheet (default: all)
+
+ %% Copyright (C) 2009-2012 Pascal Dupuis <Pascal.Dupuis@uclouvain.be>
+ %%
+ %% 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 2, 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,
+ %% write to the Free Software Foundation, 51 Franklin Street -
+ %% Fifth Floor, Boston, MA 02110-1301, USA.
+
+ %#
+ %# $Id: df_pad.m 9585 2012-02-05 15:32:46Z cdemills $
+ %#
+
+ switch dim
+ case 1
+ if (!isempty(df._name{1})),
+ if (length(df._name{1}) < df._cnt(1)+n),
+ %# generate a name for the new row(s)
+ df._name{1}(df._cnt(1)+(1:n), 1) = {'_'};
+ df._over{1}(1, df._cnt(1)+(1:n), 1) = true;
+ endif
+ endif
+ %# complete row indexes: by default, row number.
+ if (isempty(df._ridx)),
+ dummy = (1:n)(:);
+ else
+ dummy = vertcat(df._ridx, repmat(size(df._ridx, 1)+(1:n)(:), ...
+ 1, size(df._ridx, 2)));
+ endif
+ df._ridx = dummy;
+ %# pad every line
+ for indi = 1:min(size(df._data, 2), df._cnt(2)),
+ neff = n + df._cnt(1) - size(df._data{indi}, 1);
+ if (neff > 0),
+ m = size(df._data{indi}, 2);
+ switch df._type{indi}
+ case {'char'}
+ dummy = {}; dummy(1:neff, 1:m) = NA;
+ dummy = vertcat(df._data{indi}, dummy);
+ case { 'double' }
+ dummy = vertcat(df._data{indi}, repmat(NA, neff, m));
+ otherwise
+ dummy = cast(vertcat(df._data{indi}, repmat(NA, neff, m)), ...
+ df._type{indi});
+ endswitch
+ df._data{indi} = dummy;
+ endif
+ endfor
+ df._cnt(1) = df._cnt(1) + n;
+
+ case 2
+ %# create new columns
+ if (isempty(coltype))
+ error("df_pad: dim equals 2, and coltype undefined");
+ endif
+ if (length(n) > 1), %#second value is an offset
+ indc = n(2); n = n(1);
+ if (indc < df._cnt(2)),
+ %# shift to the right
+ df._name{2}(n + (indc+1:end)) = df._name{2}(indc+1:end);
+ df._over{2}(n + (indc+1:end)) = df._over{2}(indc+1:end);
+ dummy = cstrcat(repmat('_', n, 1), ...
+ strjust(num2str(indc + (1:n).'), 'left'));
+ df._name{2}(indc + (1:n)) = cellstr(dummy);
+ df._over{2}(indc + (1:n)) = true;
+ df._type(n+(indc+1:end)) = df._type(indc+1:end);
+ df._type(indc + (1:n)) = NA;
+ df._data(n + (indc+1:end)) = df._data(indc+1:end);
+ df._rep(n + (indc+1:end)) = df._rep(indc+1:end);
+ df._data(indc + (1:n)) = NA;
+ df._rep(indc + (1:n)) = 1;
+ endif
+ else
+ %# add new values after the last column
+ indc = min(size(df._data, 2), df._cnt(2));
+ endif
+ if (!isa(coltype, 'cell')), coltype = {coltype}; endif
+ if (isscalar(coltype) && n > 1),
+ coltype = repmat(coltype, 1, n);
+ endif
+ for indi = (1:n),
+ switch coltype{indi}
+ case {'char'}
+ dummy = {repmat(NA, df._cnt(1), 1) };
+ dummy(:, 1) = '_';
+ case { 'double'}
+ dummy = repmat(NA, df._cnt(1), 1);
+ case {'logical'} %# there is no NA in logical type
+ dummy = repmat(false, df._cnt(1), 1);
+ otherwise
+ dummy = cast(repmat(NA, df._cnt(1), 1), coltype{indi});
+ endswitch
+ df._data{indc+indi} = dummy;
+ df._rep{indc+indi} = 1;
+ df._type{indc+indi} = coltype{indi};
+ endfor
+
+ if (size(df._data, 2) > df._cnt(2)),
+ df._cnt(2) = size(df._data, 2);
+ endif
+ if (length(df._name{2}) < df._cnt(2)),
+ %# generate a name for the new column(s)
+ dummy = cstrcat(repmat('_', n, 1), ...
+ strjust(num2str(indc + (1:n).'), 'left'));
+ df._name{2}(indc + (1:n)) = cellstr(dummy);
+ df._over{2}(1, indc + (1:n)) = true;
+ endif
+
+ case 3
+ if (n <= 0), return; endif
+ if (isempty(coltype)),
+ coltype = 1:df._cnt(2);
+ endif
+ dummy = max(n+cellfun(@length, df._rep(coltype)));
+ if (size(df._ridx, 2) < dummy),
+ df._ridx(:, end+1:dummy) = NA;
+ endif
+ for indi = coltype,
+ switch df._type{indi}
+ case {'char'}
+ if (isa(df._data{indi}, 'char')),
+ dummy = horzcat(df._data{indi}(:, df._rep{indi}), \
+ {repmat(NA, df._cnt(1), 1)});
+ else
+ dummy = df._data{indi};
+ endif
+ case { 'double' }
+ dummy = horzcat(df._data{indi}(:, df._rep{indi}), \
+ repmat(NA, df._cnt(1), 1));
+ case { 'logical' }
+ %# there is no logical 'NA' -- fill empty elems with false
+ dummy = horzcat(df._data{indi}(:, df._rep{indi}), \
+ repmat(false, df._cnt(1), 1));
+ otherwise
+ dummy = cast(horzcat(df._data{indi}(:, df._rep{indi}), \
+ repmat(NA, df._cnt(1), 1)), \
+ df._type{indi});
+ endswitch
+ df._data{indi} = dummy;
+ df._rep{indi} = [df._rep{indi} length(df._rep{indi})+ones(1, n)];
+ endfor
+ df = df_thirddim(df);
+ otherwise
+ error('Invalid dimension in df_pad');
+ endswitch
+
+endfunction