gusucode.com > bigdata 工具箱 matlab源码程序 > bigdata/@tall/standardizeMissing.m
function out = standardizeMissing(in, varargin) %STANDARDIZEMISSING Insert standard missing data indicators into a table. % % B = STANDARDIZEMISSING(A,INDICATORS) % B = STANDARDIZEMISSING(A,INDICATORS,'DataVariables',DATAVARS) % % See also: STANDARDIZEMISSING, TALL/ISMISSING. % Copyright 2015-2016 The MathWorks, Inc. narginchk(2,4); if nargin>1 checkNotTall(upper(mfilename), 1, varargin{:}); % Check that the indicators are sane at parse time. Indicators must be % a double array, a cellstr or a cell containing mixed strings and % doubles. if ~isValidIndicator(varargin{1}) error(message('MATLAB:ismissing:IndicatorsInvalidType', class(varargin{1}))); end end in = tall.validateType(in, mfilename, {'table'}, 1); % All inputs except the first are broadcast and the operation is % effectively elementwise in that it preserves all dimensions. out = elementfun(@(x) standardizeMissing(x,varargin{:}), in); out.Adaptor = in.Adaptor; end function tf = isValidIndicator(arg) % Check whether the input argument is a valid missing value indicator tf = isStringOrDouble(arg) ... || iscellstr(arg) ... || (iscell(arg) && all(cellfun(@isStringOrDouble, arg))); end function tf = isStringOrDouble(in) tf = ischar(in) || isstring(in) || isa(in,'double'); end