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Silas Labor Zizou
280
Functions/helper_functions_community/mat2tikz/test/codeReport.m
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280
Functions/helper_functions_community/mat2tikz/test/codeReport.m
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function [ report ] = codeReport( varargin )
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%CODEREPORT Builds a report of the code health
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%
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% This function generates a Markdown report on the code health. At the moment
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% this is limited to the McCabe (cyclomatic) complexity of a function and its
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% subfunctions.
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%
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% This makes use of |checkcode| in MATLAB.
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%
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% Usage:
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%
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% CODEREPORT('function', functionName) to determine which function is
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% analyzed. (default: matlab2tikz)
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%
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% CODEREPORT('complexityThreshold', integer ) to set above which complexity, a
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% function is added to the report (default: 10)
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%
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% CODEREPORT('stream', stream) to set to which stream/file to output the report
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% (default: 1, i.e. stdout). The stream is used only when no output argument
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% for `codeReport` is specified!.
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%
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% See also: checkcode, mlint
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SM = StreamMaker();
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%% input options
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ipp = m2tInputParser();
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ipp = ipp.addParamValue(ipp, 'function', 'matlab2tikz', @ischar);
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ipp = ipp.addParamValue(ipp, 'complexityThreshold', 10, @isnumeric);
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ipp = ipp.addParamValue(ipp, 'stream', 1, SM.isStream);
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ipp = ipp.parse(ipp, varargin{:});
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stream = SM.make(ipp.Results.stream, 'w');
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%% generate report data
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data = checkcode(ipp.Results.function,'-cyc','-struct');
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[complexityAll, mlintMessages] = splitCycloComplexity(data);
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%% analyze cyclomatic complexity
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categorizeComplexity = @(x) categoryOfComplexity(x, ...
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ipp.Results.complexityThreshold, ...
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ipp.Results.function);
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complexityAll = arrayfun(@parseCycloComplexity, complexityAll);
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complexityAll = arrayfun(categorizeComplexity, complexityAll);
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complexity = filter(complexityAll, @(x) strcmpi(x.category, 'Bad'));
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complexity = sortBy(complexity, 'line', 'ascend');
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complexity = sortBy(complexity, 'complexity', 'descend');
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[complexityStats] = complexityStatistics(complexityAll);
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%% analyze other messages
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%TODO: handle all mlint messages and/or other metrics of the code
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%% format report
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dataStr = complexity;
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dataStr = arrayfun(@(d) mapField(d, 'function', @markdownInlineCode), dataStr);
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if ~isempty(dataStr)
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dataStr = addFooterRow(dataStr, 'complexity', @sum, {'line',0, 'function',bold('Total')});
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end
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dataStr = arrayfun(@(d) mapField(d, 'line', @integerToString), dataStr);
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dataStr = arrayfun(@(d) mapField(d, 'complexity', @integerToString), dataStr);
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report = makeTable(dataStr, {'function', 'complexity'}, ...
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{'Function', 'Complexity'});
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%% command line usage
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if nargout == 0
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if ismember(stream.name, {'stdout','stderr'})
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stream.print('%s\n', codelinks(report, ipp.Results.function));
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else
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stream.print('%s\n', report);
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end
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figure('name',sprintf('Complexity statistics of %s', ipp.Results.function));
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h = statisticsPlot(complexityStats, 'Complexity', 'Number of functions');
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for hh = h
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plot(hh, [1 1]*ipp.Results.complexityThreshold, ylim(hh), ...
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'k--','DisplayName','Threshold');
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end
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legend(h(1),'show','Location','NorthEast');
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clear report
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end
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end
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%% CATEGORIZATION ==============================================================
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function [complexity, others] = splitCycloComplexity(list)
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% splits codereport into McCabe complexity and others
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filter = @(l) ~isempty(strfind(l.message, 'McCabe complexity'));
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idxComplexity = arrayfun(filter, list);
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complexity = list( idxComplexity);
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others = list(~idxComplexity);
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end
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function [data] = categoryOfComplexity(data, threshold, mainFunc)
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% categorizes the complexity as "Good", "Bad" or "Accepted"
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TOKEN = '#COMPLEX'; % token to signal allowed complexity
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try %#ok
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helpStr = help(sprintf('%s>%s', mainFunc, data.function));
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if ~isempty(strfind(helpStr, TOKEN))
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data.category = 'Accepted';
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return;
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end
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end
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if data.complexity > threshold
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data.category = 'Bad';
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else
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data.category = 'Good';
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end
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end
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%% PARSING =====================================================================
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function [out] = parseCycloComplexity(in)
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% converts McCabe complexity report strings into a better format
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out = regexp(in.message, ...
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'The McCabe complexity of ''(?<function>[A-Za-z0-9_]+)'' is (?<complexity>[0-9]+).', ...
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'names');
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out.complexity = str2double(out.complexity);
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out.line = in.line;
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end
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%% DATA PROCESSING =============================================================
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function selected = filter(list, filterFunc)
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% filters an array according to a binary function
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idx = logical(arrayfun(filterFunc, list));
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selected = list(idx);
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end
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function [data] = mapField(data, field, mapping)
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data.(field) = mapping(data.(field));
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end
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function sorted = sortBy(list, fieldName, mode)
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% sorts a struct array by a single field
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% extra arguments are as for |sort|
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values = arrayfun(@(m)m.(fieldName), list);
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[dummy, idxSorted] = sort(values(:), 1, mode); %#ok
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sorted = list(idxSorted);
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end
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function [stat] = complexityStatistics(list)
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% calculate some basic statistics of the complexities
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stat.values = arrayfun(@(c)(c.complexity), list);
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stat.binCenter = sort(unique(stat.values));
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categoryPerElem = {list.category};
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stat.categories = unique(categoryPerElem);
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nCategories = numel(stat.categories);
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groupedHist = zeros(numel(stat.binCenter), nCategories);
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for iCat = 1:nCategories
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category = stat.categories{iCat};
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idxCat = ismember(categoryPerElem, category);
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groupedHist(:,iCat) = hist(stat.values(idxCat), stat.binCenter);
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end
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stat.histogram = groupedHist;
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stat.median = median(stat.values);
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end
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function [data] = addFooterRow(data, column, func, otherFields)
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% adds a footer row to data table based on calculations of a single column
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footer = data(end);
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for iField = 1:2:numel(otherFields)
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field = otherFields{iField};
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value = otherFields{iField+1};
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footer.(field) = value;
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end
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footer.(column) = func([data(:).(column)]);
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data(end+1) = footer;
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end
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%% FORMATTING ==================================================================
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function str = integerToString(value)
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% convert integer to string
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str = sprintf('%d',value);
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end
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function str = markdownInlineCode(str)
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% format as inline code for markdown
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str = sprintf('`%s`', str);
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end
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function str = makeTable(data, fields, header)
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% make a markdown table from struct array
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nData = numel(data);
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str = '';
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if nData == 0
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return; % empty input
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end
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%TODO: use gfmTable from makeTravisReport instead to do the formatting
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% determine column sizes
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nFields = numel(fields);
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table = cell(nFields, nData);
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columnWidth = zeros(1,nFields);
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for iField = 1:nFields
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field = fields{iField};
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table(iField, :) = {data(:).(field)};
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columnWidth(iField) = max(cellfun(@numel, table(iField, :)));
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end
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columnWidth = max(columnWidth, cellfun(@numel, header));
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columnWidth = columnWidth + 2; % empty space left and right
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columnWidth([1,end]) = columnWidth([1,end]) - 1; % except at the edges
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% format table inside cell array
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table = [header; table'];
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for iField = 1:nFields
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FORMAT = ['%' int2str(columnWidth(iField)) 's'];
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for jData = 1:size(table, 1)
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table{jData, iField} = strjust(sprintf(FORMAT, ...
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table{jData, iField}), 'center');
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end
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end
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% insert separator
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table = [table(1,:)
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arrayfun(@(n) repmat('-',1,n), columnWidth, 'UniformOutput',false)
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table(2:end,:)]';
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% convert cell array to string
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FORMAT = ['%s' repmat('|%s', 1,nFields-1) '\n'];
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str = sprintf(FORMAT, table{:});
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end
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function str = codelinks(str, functionName)
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% replaces inline functions with clickable links in MATLAB
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str = regexprep(str, '`([A-Za-z0-9_]+)`', ...
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['`<a href="matlab:edit ' functionName '>$1">$1</a>`']);
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%NOTE: editing function>subfunction will focus on that particular subfunction
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% in the editor (this also works for the main function)
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end
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function str = bold(str)
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str = ['**' str '**'];
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end
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%% PLOTTING ====================================================================
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function h = statisticsPlot(stat, xLabel, yLabel)
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% plot a histogram and box plot
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nCategories = numel(stat.categories);
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colors = colorscheme;
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h(1) = subplot(5,1,1:4);
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hold all;
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hb = bar(stat.binCenter, stat.histogram, 'stacked');
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for iCat = 1:nCategories
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category = stat.categories{iCat};
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set(hb(iCat), 'DisplayName', category, 'FaceColor', colors.(category), ...
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'LineStyle','none');
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end
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%xlabel(xLabel);
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ylabel(yLabel);
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h(2) = subplot(5,1,5);
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hold all;
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boxplot(stat.values,'orientation','horizontal',...
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'boxstyle', 'outline', ...
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'symbol', 'o', ...
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'colors', colors.All);
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xlabel(xLabel);
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xlims = [min(stat.binCenter)-1 max(stat.binCenter)+1];
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c = 1;
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ylims = (ylim(h(2)) - c)/3 + c;
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set(h,'XTickMode','manual','XTick',stat.binCenter,'XLim',xlims);
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set(h(1),'XTickLabel','');
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set(h(2),'YTickLabel','','YLim',ylims);
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linkaxes(h, 'x');
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end
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function colors = colorscheme()
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% recognizable color scheme for the categories
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colors.All = [ 0 113 188]/255;
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colors.Good = [118 171 47]/255;
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colors.Bad = [161 19 46]/255;
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colors.Accepted = [236 176 31]/255;
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end
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