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function resu = df_mapper2(func, df, varargin)
%# resu = df_mapper2(func, df)
%# small interface to iterate some vector func over the elements of a
%# dataframe. This one is specifically adapted to all functions where
%# the first argument, if numeric, is 'dim'.
%% 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/>.
dim = []; resu = []; vout = varargin;
%# take care of constructs as min(x, [], dim); sum(x, 2, 'native')
for indi = (nargin-2:-1:1)
if (isscalar (varargin{indi}))
if (isnumeric (varargin{indi}))
dim = varargin{indi};
%# the 'third' dim is the second on stored data
if (3 == dim) vout(indi-2) = 2; end
end
end
break;
end
if (isempty (dim))
%# iterates on the first non-singleton dim
dim = find (df.x_cnt > 1)(1);
end
switch (dim)
case {1}
resu = df_colmeta (df); %# don't copy all the information
for indi = (1:df.x_cnt(2))
resu.x_data{indi} = feval (func, df.x_data{indi}(:, df.x_rep{indi}), ...
vout{:});
resu.x_rep{indi} = 1:size (resu.x_data{indi}, 2);
end
resu.x_cnt(1) = max (cellfun ('size', resu.x_data, 1));
if (resu.x_cnt(1) == df.x_cnt(1))
%# the func was not contracting
resu.x_ridx = df.x_ridx;
resu.x_name{1} = resu.x_name{1}; resu.x_over{1} = resu.x_over{1};
else
%# select the first value
if (~isempty (resu.x_name{1}))
resu.x_name{1} = resu.x_name{1}(1);
end
if (~isempty (resu.x_over{1}))
resu.x_over{1} = resu.x_over{1}(1);
end
end
case {2}
switch func
case @sum
contract = true; func = @plus;
case @cumsum
contract = false; func = @plus;
case @prod
contract = true; func = @times;
case @cumprod
contract = false; func = @times;
case @any
contract = true; func = @or;
case @all
contract = true; func = @and;
otherwise
error ('Operation not implemented');
end
if (contract)
resu = df_allmeta (df, [df.x_cnt(1) 1]);
else
resu = df_allmeta(df);
end
resu.x_data{1} = df.x_data{1}(:, df.x_rep{1});
resu.x_rep{1} = df.x_rep{1};
if (contract)
for indi = (2:df.x_cnt(2))
%# this call is 'unfolding'
resu.x_data{1} = feval (func, resu.x_data{1}(:, df.x_rep{1}), ...
df.x_data{indi}(:, df.x_rep{indi}));
resu.x_rep{1} = 1:size (resu.x_data{1}, 2);
end
else
for indi = (2:df.x_cnt(2))
resu.x_data{indi} = feval (func, resu.x_data{indi-1}(:, df.x_rep{indi-1}), ...
df.x_data{indi}(:, df.x_rep{indi}));
resu.x_rep{indi} = 1:size (resu.x_data{indi}, 2);
end
end
%# type may have changed
resu.x_type = cellfun(@(x) class(x(1)), resu.x_data, 'UniformOutput', false);
case {3}
resu = df_allmeta(df);
for indi = (1:df.x_cnt(2))
resu.x_data{indi} = feval (func, df.x_data{indi}(:, df.x_rep{indi}), ...
vout{:});
resu.x_rep{indi} = 1:size (resu.x_data{indi}, 2);
end
otherwise
error ('Invalid dimension %d', dim);
end
resu = df_thirddim (resu);
end
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