Documentation clean-up and fixes
more clean-up and polishing after some further test regarding the topic of timing measurements Improved handling: filter test cases to be performed
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3 changed files with 45 additions and 3 deletions
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@ -253,6 +253,17 @@ public:
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});
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}
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void dropLastRow()
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{
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if (not empty())
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forEach(TAB::allColumns(),
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[](auto& col)
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{
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size_t siz = col.data.size();
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col.data.resize(siz>0? siz-1 : 0);
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});
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}
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void reserve(size_t expectedCapacity)
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{
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forEach(TAB::allColumns(),
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@ -282,6 +293,7 @@ public:
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fs::rename(filename_, oldFile);
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}
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fs::rename(newFilename, filename_);
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filename_ = consolidated(filename_); // lock onto absolute path
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}
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@ -32,9 +32,12 @@
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#include <regex>
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#include <string>
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#include <optional>
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namespace util {
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using std::regex;
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using std::smatch;
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using std::string;
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@ -43,7 +46,7 @@ using std::string;
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struct MatchSeq
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: std::sregex_iterator
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{
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MatchSeq(string const& toParse, std::regex const& regex)
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MatchSeq(string const& toParse, regex const& regex)
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: std::sregex_iterator{toParse.begin(), toParse.end(), regex}
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{ }
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@ -53,5 +56,32 @@ struct MatchSeq
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};
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/** encapsulated regex buildable from string */
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class Matcher
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{
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std::optional<regex> pattern_;
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public:
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Matcher() = default;
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Matcher(string const& regexDefinition)
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: pattern_{regexDefinition.empty()? std::nullopt
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: std::make_optional<regex>(regexDefinition, regex::optimize)}
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{ }
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// standard copy acceptable
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explicit operator bool() const
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{
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return bool(pattern_);
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}
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bool matchesWithin(string probe) const
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{
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return pattern_? std::regex_search(probe, *pattern_)
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: true; // undefined pattern matches everything
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}
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};
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}//(End)namespace util
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#endif /*TESTRUNNER_UTIL_REGEX_HPP_*/
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@ -243,7 +243,7 @@ inline auto computeLinearRegression(DataSpan<RegressionPoint> const& points)
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double socket = ym - gradient * xm; // Regression line: Y-ym = gradient · (x-xm) ; set x≔0 yields socket
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// Correlation (Pearson's r)
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double correlation = wyysum==0.0? 0.0 : gradient * sqrt(varx/vary);
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double correlation = wyysum==0.0? 1.0 : gradient * sqrt(varx/vary);
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// calculate error Δ for all measurement points
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size_t n = points.size();
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@ -304,7 +304,7 @@ inline auto computeTimeSeriesLinearRegression(DataSpan<D> const& series)
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double socket = ym - gradient * im; // Regression line: Y-ym = Gradient · (i-im) ; set i≔0 yields socket
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// Correlation (Pearson's r)
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double correlation = yysum==0.0? 0.0 : gradient * sqrt(varx/vary);
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double correlation = yysum==0.0? 1.0 : gradient * sqrt(varx/vary);
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return make_tuple(socket,gradient,correlation);
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}
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