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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) 2009-2017 Pascal Dupuis <cdemills@gmail.com>
%%
%% This file is part of the dataframe package for Octave.
%%
%% This package 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.
%%
%% This package 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 package; see the file COPYING. If not,
%% see <http://www.gnu.org/licenses/>.
if (nargin < 4), coltype = []; end
try
NA = NA;
catch
NA = NaN;
end
switch dim
case 1
if (~isempty (df.x_name{1})),
if (length (df.x_name{1}) < df.x_cnt(1)+n)
%# generate a name for the new row(s)
df.x_name{1}(df.x_cnt(1)+(1:n), 1) = {'_'};
df.x_over{1}(1, df.x_cnt(1)+(1:n), 1) = true;
end
end
%# complete row indexes: by default, row number.
if (isempty (df.x_ridx))
(1:n);
dummy = ans(:);
else
dummy = vertcat (df.x_ridx, repmat (size (df.x_ridx, 1)+(1:n).', ...
1, size (df.x_ridx, 2)));
end
df.x_ridx = dummy;
%# pad every line
for indi = (1:min (size (df.x_data, 2), df.x_cnt(2)))
neff = n + df.x_cnt(1) - size (df.x_data{indi}, 1);
if (neff > 0)
m = max(1, size (df.x_data{indi}, 2));
switch df.x_type{indi}
case {'char'}
%# there is no 'string NA'
dummy = {}; dummy(1:neff, 1:m) = 'NA';
dummy = vertcat (df.x_data{indi}, dummy);
case { 'double'}
dummy = vertcat (df.x_data{indi}, repmat (NA, neff, m));
%# there is no 'NA' with logical values, avoid casting error
case {'logical'}
dummy = vertcat (df.x_data{indi}, repmat (false, neff, m));
otherwise
dummy = cast (vertcat (df.x_data{indi}, repmat (NA, neff, m)), ...
df.x_type{indi});
end
df.x_data{indi} = dummy;
if (isempty (df.x_rep{indi}))
df.x_rep{indi} = 1;
end
end
end
df.x_cnt(1) = df.x_cnt(1) + n;
case 2
%# create new columns
if (isempty (coltype))
error ('df_pad: dim equals 2, and coltype undefined');
end
if (length (n) > 1) %#second value is an offset
indc = n(2); n = n(1);
if (indc < df.x_cnt(2)),
%# shift to the right
df.x_name{2}(n + (indc+1:end)) = df.x_name{2}(indc+1:end);
df.x_over{2}(n + (indc+1:end)) = df.x_over{2}(indc+1:end);
dummy = cstrcat (repmat ('_', n, 1), ...
strjust (num2str(indc + (1:n).'), 'left'));
df.x_name{2}(indc + (1:n)) = cellstr (dummy);
df.x_over{2}(indc + (1:n)) = true;
df.x_type(n+(indc+1:end)) = df.x_type(indc+1:end);
df.x_type(indc + (1:n)) = NA;
df.x_data(n + (indc+1:end)) = df.x_data(indc+1:end);
df.x_rep(n + (indc+1:end)) = df.x_rep(indc+1:end);
df.x_data(indc + (1:n)) = NA;
df.x_rep(indc + (1:n)) = 1;
end
else
%# add new values after the last column
indc = min (size (df.x_data, 2), df.x_cnt(2));
end
if (~isa (coltype, 'cell')) coltype = {coltype}; end
if (isscalar (coltype) && n > 1)
coltype = repmat (coltype, 1, n);
end
for indi = (1:n)
switch coltype{indi}
case {'char'}
dummy = {repmat(NA, df.x_cnt(1), 1) };
dummy(:, 1) = '_';
case { 'double'}
dummy = repmat (NA, df.x_cnt(1), 1);
case {'logical'} %# there is no NA in logical type
dummy = repmat (false, df.x_cnt(1), 1);
otherwise
try
dummy = cast (repmat (NA, df.x_cnt(1), 1), coltype{indi});
catch
%# There was an issue -- transfer coltype to data
if (indc+indi > df.x_cnt(2))
dummy = {coltype{indi}}; coltype{indi} = 'char';
if (df.x_cnt(1) < 1)
%# nothing defined yet -- pad with one line
df.x_type{indc+indi} = coltype{indi};
df = df_pad (df, 1, 1);
end
else
dummy = sprintf ('Trying to change type of column %d, which was %s, to %s', ...
indc+indi, df.x_type{indi}, coltype{indi});
error (dummy);
end
end
end
df.x_data{indc+indi} = dummy;
df.x_rep{indc+indi} = 1;
df.x_type{indc+indi} = coltype{indi};
end
if (size (df.x_data, 2) > df.x_cnt(2)),
df.x_cnt(2) = size (df.x_data, 2);
end
if (length (df.x_name{2}) < df.x_cnt(2)),
%# generate a name for the new column(s)
dummy = cstrcat (repmat ('_', n, 1), ...
strjust (num2str (indc + (1:n).'), 'left'));
df.x_name{2}(indc + (1:n)) = cellstr (dummy);
df.x_over{2}(1, indc + (1:n)) = true;
end
case 3
if (n <= 0) return; end
if (isempty (coltype)),
coltype = 1:df.x_cnt(2);
end
dummy = max (n+cellfun (@length, df.x_rep(coltype)));
if (size (df.x_ridx, 2) < dummy),
df.x_ridx(:, end+1:dummy) = NA;
end
for indi = (coltype)
switch df.x_type{indi}
case {'char'}
if (isa (df.x_data{indi}, 'char')) %# pure char
dummy = horzcat (df.x_data{indi}(:, df.x_rep{indi}), ...
repmat({NA}, df.x_cnt(1), 1));
keyboard
else
dummy = horzcat (df.x_data{indi}(:, df.x_rep{indi}), ...
repmat({NA}, df.x_cnt(1), 1));
end
case {'double'}
dummy = horzcat (df.x_data{indi}(:, df.x_rep{indi}), ...
repmat (NA, df.x_cnt(1), 1));
case {'logical'}
%# there is no logical 'NA' -- fill empty elems with false
dummy = horzcat (df.x_data{indi}(:, df.x_rep{indi}), ...
repmat (false, df.x_cnt(1), 1));
otherwise
dummy = cast (horzcat (df.x_data{indi}(:, df.x_rep{indi}), ...
repmat (NA, df.x_cnt(1), 1)), ...
df.x_type{indi});
end
df.x_data{indi} = dummy;
df.x_rep{indi} = [df.x_rep{indi} length(df.x_rep{indi})+ones(1, n)];
try
assert (size(df.x_data{indi}, 2), max(df.x_rep{indi}))
catch
keyboard
end
end
df = df_thirddim (df);
otherwise
error ('Invalid dimension in df_pad');
end
end
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