gusucode.com > datatypes 工具箱matlab源码程序 > datatypes/@categorical/histogram.m
function h = histogram(varargin)
%HISTOGRAM Plots a histogram for a categorical array.
% HISTOGRAM(X) plots a histogram of a categorical array X. A bar is
% plotted for each category in X.
%
% HISTOGRAM(X,CATEGORIES), plots only the categories specified by
% CATEGORIES. CATEGORIES is a categorical vector with unique elements
% or a cell array of unique character vectors.
%
% HISTOGRAM(...,'Normalization',NM) specifies the normalization scheme
% of the histogram values. The normalization scheme affects the scaling
% of the histogram along the vertical axis (or horizontal axis if
% Orientation is 'horizontal'). NM can be:
% 'count' The height of each bar is the number of
% elements in each category, and the sum of the
% bar heights is NUMEL(X) or
% SUM(ISMEMBER(X(:),CATEGORIES)). This is the
% default.
% 'countdensity' Returns the same result as 'count' for categorical
% histograms.
% 'probability' The height of each bar is the relative
% number of observations (number of elements in
% category / number of elements in all categories),
% and the sum of the bar heights is 1.
% 'pdf' Probability density function estimate. Returns
% the same result as 'probability' for categorical
% histograms.
% 'cumcount' The height of each bar is the cumulative
% number of elements in each category and all
% previous categories. The height of the last bar
% is NUMEL(X) or SUM(ISMEMBER(X(:),CATEGORIES)).
% 'cdf' Cumulative density function estimate. The height
% of each bar is the cumulative relative number
% of observations in each category and all
% previous categories. The height of the last bar is 1.
%
% HISTOGRAM(...,'DisplayStyle',STYLE) specifies the display style of the
% histogram. STYLE can be:
% 'bar' Display a histogram bar plot. This is the default.
% 'stairs' Display a stairstep plot, which shows the
% outlines of the histogram without filling the
% interior.
%
% HISTOGRAM(...,'Orientation',ORIENTATION) specifies the orientation of
% the histogram. ORIENTATION can be:
% 'vertical' Histogram bars are drawn vertically towards
% the positive Y axis direction. This is the
% default.
% 'horizontal' Histogram bars are drawn horizontally towards
% the positive X axis direction.
%
% HISTOGRAM('Categories', CATEGORIES, 'BinCounts', COUNTS) where COUNTS
% is a vector of the same length as CATEGORIES, manually specifies
% the bin counts. HISTOGRAM plots the counts and does not do any data binning.
%
% HISTOGRAM(...,NAME,VALUE) set the property NAME to VALUE.
%
% HISTOGRAM(AX,...) plots into AX instead of the current axes.
%
% H = HISTOGRAM(...) also returns a histogram object. Use this to inspect
% and adjust the properties of the histogram.
%
% See also CATEGORICAL/HISTCOUNTS, matlab.graphics.chart.primitive.categorical.Histogram
% Copyright 1984-2016 The MathWorks, Inc.
[cax,args] = axescheck(varargin{:});
% Check whether the first input is an axes input, which would have been
% stripped by the axescheck function
firstaxesinput = (rem(length(varargin) - length(args),2) == 1);
x = args{1};
args(1) = [];
if ~iscategorical(x)
error(message('MATLAB:categorical:histogram:NonCategoricalX'));
end
[opts,args] = parseinput(x,args,firstaxesinput+1);
cax = newplot(cax);
if ~ishold(cax)
cax.Box = 'on';
end
[~,autocolor] = specgraphhelper('nextstyle',cax,true,false,false);
optscell = binspec2cell(opts);
hObj = matlab.graphics.chart.primitive.categorical.Histogram('Parent', cax, ...
'Data', x, 'AutoColor', autocolor, optscell{:}, args{:});
% disable brushing, basic fit, and data statistics
hbrush = hggetbehavior(hObj,'brush');
hbrush.Enable = false;
hbrush.Serialize = true;
hdatadescriptor = hggetbehavior(hObj,'DataDescriptor');
hdatadescriptor.Enable = false;
hdatadescriptor.Serialize = true;
if nargout > 0
h = hObj;
end
end
function [opts,passthrough] = parseinput(x,input,inputoffset)
import matlab.internal.datatypes.isCharStrings
opts = struct;
bincountsmode = [];
funcname = mfilename;
passthrough = {};
% Parse second input in the function call
if ~isempty(input)
in = input{1};
if ~ischar(in)
validateattributes(in,{'cell','categorical'},{}, ...
funcname, 'categories', 2)
if ~(isvector(in) || isempty(in))
error(message('MATLAB:categorical:histogram:NonVectorCategories'));
end
if length(in)~=length(unique(in))
error(message('MATLAB:categorical:histogram:RepeatedCategories'));
end
if ~isa(in,'categorical')
if ~isCharStrings(in)
error(message('MATLAB:categorical:histogram:InvalidCategories'));
end
opts.Categories = reshape(in,1,[]); % a row
if isordinal(x)
[lia,locb] = ismember(in,x.categoryNames);
if ~all(lia)
error(message('MATLAB:categorical:histogram:UnrecognizedCategories'));
elseif ~issorted(locb)
error(message('MATLAB:categorical:histogram:InvalidCategoryOrder'));
end
end
elseif x.isOrdinal == in.isOrdinal %% isa(categories,'categorical')
% If categories is categorical, its ordinalness has to match x, and if they are
% ordinal, their categories have to match.
if isordinal(x) && ~isequal(x.categoryNames,in.categoryNames)
error(message('MATLAB:categorical:histogram:OrdinalCategoriesMismatch'));
end
% The histogram bins will be based on categories' values, not its categories
% Filter out undefined categories before extracting category names
in.codes(in.codes==0) = [];
opts.Categories = cellstr(reshape(in,1,[])); % a column
else
error(message('MATLAB:categorical:histogram:OrdinalMismatch'));
end
input(1) = [];
inputoffset = inputoffset + 1;
end
% All the rest are name-value pairs
if rem(length(input),2) ~= 0
error(message('MATLAB:histogram:ArgNameValueMismatch'))
end
% compile the list of all settable property names, filtering out the
% read-only properties
names = setdiff(properties('matlab.graphics.chart.primitive.categorical.Histogram'),...
{'Children','Values','Type','Annotation','BeingDeleted'});
inputlen = length(input);
for i=1:2:inputlen
name = validatestring(input{i},names);
value = input{i+1};
switch name
case 'Categories'
validateattributes(value,{'cell','categorical'},{'vector'}, ...
funcname, 'categories', i+1+inputoffset)
if length(value)~=length(unique(value))
error(message('MATLAB:categorical:histogram:RepeatedCategories'));
end
if ~isa(value,'categorical')
if ~isCharStrings(value)
error(message('MATLAB:categorical:histogram:InvalidCategories'));
end
opts.Categories = reshape(value,1,[]); % a row
if isordinal(x)
[lia,locb] = ismember(value,x.categoryNames);
if ~all(lia)
error(message('MATLAB:categorical:histogram:UnrecognizedCategories'));
elseif ~issorted(locb)
error(message('MATLAB:categorical:histogram:InvalidCategoryOrder'));
end
end
elseif x.isOrdinal == value.isOrdinal %% isa(categories,'categorical')
% If categories is categorical, its ordinalness has to match x, and if they are
% ordinal, their categories have to match.
if isordinal(x) && ~isequal(x.categoryNames,value.categoryNames)
error(message('MATLAB:categorical:histogram:OrdinalCategoriesMismatch'));
end
% The histogram bins will be based on categories' values, not its categories
% Filter out undefined categories before extracting category names
value.codes(value.codes==0) = [];
opts.Categories = cellstr(reshape(value,1,[])); % a column
else
error(message('MATLAB:categorical:histogram:OrdinalMismatch'));
end
case 'Normalization'
opts.Normalization = validatestring(value, {'count', 'countdensity', 'cumcount',...
'probability', 'pdf', 'cdf'}, funcname, 'Normalization', i+1+inputoffset);
case 'BinCounts'
validateattributes(value,{'numeric','logical'},{'real', ...
'vector','nonnegative','finite'}, funcname, 'BinCounts', i+1+inputoffset)
opts.BinCounts = reshape(value,1,[]); % ensure row
case 'BinCountsMode'
bincountsmode = validatestring(value, {'auto', 'manual'});
otherwise
% all other options are passed directly to the object
% constructor, making sure we pass in the full property names
passthrough = [passthrough {name} input(i+1)]; %#ok<AGROW>
end
end
% error checking about consistency between properties
if ~isempty(bincountsmode)
if strcmp(bincountsmode, 'auto')
if isfield(opts, 'BinCounts')
error(message('MATLAB:categorical:histogram:NonEmptyBinCountsAutoMode'));
end
else % manual
if ~isfield(opts,'BinCounts')
error(message('MATLAB:categorical:histogram:EmptyBinCountsManualMode'));
end
end
passthrough = [passthrough {'BinCountsMode' bincountsmode}];
end
if isfield(opts,'BinCounts')
if isfield(opts,'Categories')
numcats = length(opts.Categories);
else
numcats = length(categories(x));
end
if numcats ~= length(opts.BinCounts)
error(message('MATLAB:categorical:histogram:BinCountsInvalidSize'))
end
if ~isempty(x)
error(message('MATLAB:categorical:histogram:MixedDataBinCounts'))
end
end
end
end
function binargs = binspec2cell(binspec)
% Construct a cell array of name-value pairs given a binspec struct
binspecn = fieldnames(binspec); % extract field names
binspecv = struct2cell(binspec);
binargs = [binspecn binspecv]';
end