gusucode.com > datatypes 工具箱matlab源码程序 > datatypes/splitapply.m
function varargout = splitapply(fun,varargin)
% SPLITAPPLY Split data into groups and apply function
% Y = SPLITAPPLY(FUN,X,G) splits the variable X into groups specified by G
% and applies the function FUN to each group. SPLITAPPLY returns Y as a
% column vector where each row contains the output from FUN for each group.
% Specify G as a vector of positive integers. You can use FINDGROUPS
% to create G. If G contains NaN values, SPLITAPPLY discards the
% corresponding values in X.
%
% Y = SPLITAPPLY(FUN,X1,X2,...,G) splits variables X1,X2,... into groups
% specified by G and applies FUN to each group. SPLITAPPLY calls FUN once per
% group, with X1,X2,... as the input arguments to FUN.
%
% [Y1,Y2,...] = SPLITAPPLY(FUN,...) splits variables into groups and applies FUN
% to each group. FUN returns multiple output arguments. FUN can return output
% arguments that belong to different classes, but the class of each output must
% be the same each time FUN is called. You can use this syntax with any of the
% input arguments of the previous syntaxes. The number of output arguments need
% not equal the number of input data variables.
%
% Examples:
% % Load patients data.
% % List Height, Weight, Gender, and Smoker variables for patients.
% load patients;
% whos Height Weight Gender Smoker
%
% % Find groups of patients by gender and status as a smoker.
% % Make a table that lists the four group identifiers.
% [G,gender,smoker] = findgroups(Gender,Smoker);
% results = table(gender,smoker)
%
% % Split Weight into groups. Calculate mean weights for the groups
% % of patients.
% results.meanWeight = splitapply(@mean,Weight,G)
%
% % Find the average BMI by gender and status as a smoker.
% meanBMIFcn = @(h,w)mean((w ./ (h.^2)) * 703);
% results.meanBMI = splitapply(meanBMIFcn,Height,Weight,G)
%
% See also FINDGROUPS, UNIQUE, VARFUN, ROWFUN
% Copyright 2015-2016 MathWorks, Inc.
% Check number of inputs
narginchk(3,inf);
gnums = varargin{end};
varargin(end) = [];
% Check Function handle
if ~isa(fun,'function_handle')
error(message('MATLAB:splitapply:InvalidFunction'));
end
% Check indices
if isempty(gnums) || ~isnumeric(gnums) || ~isvector(gnums) || ...
any(gnums <= 0) || issparse(gnums)
error(message('MATLAB:splitapply:InvalidGroupNums'));
end
% Drop leading singleton dimensions to find dimension to split on
[gnums, shiftby] = shiftdim(gnums);
gsize = length( gnums );
gdim = shiftby + 1;
% Ensure that indices are sorted (for transparent accumarray behavior)
[gnums, sgnums] = sort( gnums );
% Account for NaN Groups
ngroups = max(gnums);
if isnan(ngroups) %for the case of gnums being all NaN
emptyGroup = 1;
else
emptyGroup = ngroups+1;
end
% Filter out empty group numbers
emptyIdx = emptyGroups(gnums);
sgnums(emptyIdx,:) = emptyGroup;
gnums(emptyIdx,:) = emptyGroup;
% Check for non-integer group numbers (after filtering out the data)
if any(floor(gnums) ~= gnums) || ~isreal(gnums)
error(message('MATLAB:splitapply:InvalidGroupNums'));
end
% Check data
for argnumber = 1:length(varargin)
argsize = size(varargin{argnumber},gdim);
if isscalar(gnums) || isequal( gsize, argsize )
continue; % Sizes match
end
% Different error messages depending on grouping vector orientation
if gdim == 1 %column vector gnums
error(message('MATLAB:splitapply:RowMismatch', gsize, argnumber, argsize));
elseif gdim == 2 %row vector gnums
error(message('MATLAB:splitapply:ColumnMismatch', gsize, argnumber,argsize));
end
end
% Check for non-continuous group numbers
% When sorted, valid group number vector will start at 1, and the numbers
% will not differ by more than 1
gdiffed = diff(gnums);
if ~isempty(gnums) && ((gnums(1) ~= 1) || ~all(gdiffed== 1 | gdiffed==0))
error(message('MATLAB:splitapply:MissingGroupNums'));
end
dataVars = {};
for argnumber = 1:length(varargin)
expandedVars = expandVariables(varargin{argnumber});
dataVars(end+1:end+size(expandedVars,2)) = expandedVars;
end
if isscalar(gnums)
% Vector of group numbers is a scalar, Use the first non-singleton
% dimension as the dimension to split data on.
sz = size(dataVars{1});
gdim = find(sz == 1,1,'first');
if isempty(gdim)
gdim = 1;
end
end
splitData = localsplit(dataVars,gnums,sgnums,gdim);
varargout = localapply(fun,splitData,gdim,nargout);
% Clean up NaN Groups
if any(emptyIdx)
for ii = 1:length(varargout)
% Preserve shape along non-grouping dimension when cleaning out NaN groups
emptyGroupIdx = repmat({':'}, 1, ndims(varargout{ii}));
emptyGroupIdx{gdim} = emptyGroup;
varargout{ii}(emptyGroupIdx{:}) = [];
end
end
end
%-------------------------------------------------------------------------------
function varRows = getVarRows(datavar,i,gdim)
if isscalar(datavar)
varRows = datavar;
elseif matlab.internal.datatypes.istabular(datavar)
varRows = datavar(i,:);
elseif ismatrix(datavar) && gdim == 1
varRows = datavar(i,:);
elseif ismatrix(datavar) && gdim == 2
varRows = datavar(:,i);
else
% Each var could have any number of dims, no way of knowing,
% except how many rows they have. So just treat them as 2D to get
% the necessary rows, and then reshape to their original dims.
indexVar = repmat({':'}, 1, ndims(datavar));
indexVar{gdim} = i;
varRows = datavar(indexVar{:});
end
end
%-------------------------------------------------------------------------------
function out = localsplit(datavars,gnums,sgnums,gdim)
if isscalar(gnums)
out = datavars; % all datvariables are the observations if gnums is scalar
else
gmax = gnums(end);
for i = 1:length(datavars)
groupNums = accumarray(gnums,sgnums,[gmax,1],@(ii){ii});
if i==1
out = cell(length(groupNums),length(datavars));
end
for j=1:length(groupNums)
out{j,i} = getVarRows(datavars{i},groupNums{j},gdim);
end
end
end
end
%-------------------------------------------------------------------------------
function finalOut = localapply(fun,dataVars,gdim,nout)
import matlab.internal.tableUtils.ordinalString;
% Call function passing parameters
[numGroups,numVars] = size(dataVars);
funOut = cell(numGroups,nout);
if (gdim > 1)
funOut = funOut';
end
for curGroup = 1:numGroups
try
% Invoke the function based on the number of output arguments
if nout > 0
if gdim == 1
[funOut{curGroup,:}] = fun(dataVars{curGroup,:});
else
[funOut{:,curGroup}] = fun(dataVars{curGroup,:});
end
else
clear ans;
fun(dataVars{curGroup,:});
% did the call to 'fun' above output to ans?
% If so pass it through.
if exist('ans','var')
funOut{1} = ans; %#ok<NOANS>
nout = 1;
end
end
catch ME
funStr = func2str(fun);
throwAsCaller(MException(message('MATLAB:splitapply:FunFailed', funStr, ordinalString(curGroup), ME.message)));
end
if nout > 0
for curVar=1:nout
if gdim == 1
var = funOut{curGroup,curVar};
else
var = funOut{curVar,curGroup};
end
if isscalar(var) || (size(var,gdim) == 1)
% Output is Uniform
continue;
end
% Construct a suggested correction to be included in the
% error message
funStr = func2str(fun);
if strcmp(funStr(1), '@') % anonymous function
funTokens = regexp(funStr, '(@\([^\(\)]*\))(.*)', 'tokens', 'once');
funSuggest = [funTokens{1}, '{',funTokens{2},'}'];
else % simple function handle
funArgs = strjoin( strcat('x', strsplit(int2str(1:numVars)) ), ',');
funSuggest = ['@(',funArgs,'){',funStr,'(',funArgs,')}'];
end
throwAsCaller(MException(message('MATLAB:splitapply:OutputNotUniform', funStr, ordinalString(curGroup), funSuggest)));
end
end
end
finalOut = cell(1,nout);
for curVar = 1:nout
if gdim == 1
finalOut{curVar} = vertcat(funOut{:,curVar});
else
finalOut{curVar} = horzcat(funOut{curVar,:});
end
end
end
%-------------------------------------------------------------------------------
function emptyIdx = emptyGroups(gnums)
emptyIdx = isnan(gnums);
end
%-------------------------------------------------------------------------------
function out = expandVariables(inVar)
if matlab.internal.datatypes.istabular(inVar)
out = table2cell(varfun(@(x){x}, inVar));
else
out = {inVar};
end
end