From e65727913e435819a3fc26513d9892d179eab1f2 Mon Sep 17 00:00:00 2001 From: Mattias Ellert Date: Wed, 8 Jul 2020 19:32:51 +0200 Subject: [PATCH 3/5] Adjust parameter names in doxygen markup so they match the code Addresses warnings: argument '' of command @param is not found in the argument list of . --- .../pythonizations/src/PyzPythonHelpers.cxx | 2 +- bindings/r/inc/TRInterface.h | 4 +-- hist/hist/src/TF1.cxx | 5 ++- hist/hist/src/TGraph.cxx | 6 ++-- hist/histpainter/src/TPainter3dAlgorithms.cxx | 6 ++-- hist/histv7/inc/ROOT/RAxis.hxx | 11 +++---- hist/histv7/inc/ROOT/RHist.hxx | 2 +- hist/unfold/src/TUnfoldBinning.cxx | 24 +++++++------- hist/unfold/src/TUnfoldBinningXML.cxx | 2 +- hist/unfold/src/TUnfoldDensity.cxx | 2 +- hist/unfold/src/TUnfoldSys.cxx | 7 ++-- io/io/inc/ROOT/TBufferMerger.hxx | 2 +- math/mathcore/inc/Math/IntegratorMultiDim.h | 2 +- math/minuit2/inc/Minuit2/FCNBase.h | 4 +-- math/minuit2/inc/Minuit2/FumiliChi2FCN.h | 2 +- math/minuit2/inc/Minuit2/FumiliErrorUpdator.h | 2 +- .../inc/Minuit2/FumiliMaximumLikelihoodFCN.h | 2 +- roofit/roofit/src/RooExponential.cxx | 2 +- roofit/roofit/src/RooGExpModel.cxx | 32 +++++++++---------- roofit/roofit/src/RooGaussian.cxx | 2 +- roofit/roofit/src/RooJohnson.cxx | 2 +- roofit/roofit/src/RooLandau.cxx | 2 +- roofit/roofitcore/src/BatchData.cxx | 2 +- roofit/roofitcore/src/RooAbsPdf.cxx | 4 +-- roofit/roofitcore/src/RooAbsReal.cxx | 2 +- roofit/roofitcore/src/RooCustomizer.cxx | 4 +-- roofit/roofitcore/src/RooDataHist.cxx | 4 +-- roofit/roofitcore/src/RooDataSet.cxx | 10 +++--- roofit/roofitcore/src/RooFormulaVar.cxx | 2 +- roofit/roofitcore/src/RooSuperCategory.cxx | 2 +- roofit/roofitmore/src/RooHypatia2.cxx | 6 ++-- tmva/tmva/inc/TMVA/BDTEventWrapper.h | 4 +-- tmva/tmva/inc/TMVA/NeuralNet.h | 14 +++----- tmva/tmva/inc/TMVA/NeuralNet.icc | 2 +- tmva/tmva/inc/TMVA/RTensor.hxx | 2 +- .../inc/TMVA/TreeInference/BranchlessTree.hxx | 4 +-- tmva/tmva/inc/TMVA/TreeInference/Forest.hxx | 2 +- tmva/tmva/src/BDTEventWrapper.cxx | 2 +- tmva/tmva/src/CrossValidation.cxx | 2 +- tmva/tmva/src/CvSplit.cxx | 18 +++++------ tmva/tmva/src/Envelope.cxx | 12 +++---- tree/dataframe/inc/ROOT/RDF/RInterface.hxx | 16 +++++----- tree/dataframe/inc/ROOT/RDFHelpers.hxx | 2 +- tree/dataframe/inc/ROOT/RDataSource.hxx | 8 ++--- tree/dataframe/inc/ROOT/RResultPtr.hxx | 2 +- tree/dataframe/src/RArrowDS.cxx | 4 +-- tree/tree/inc/TTree.h | 2 +- tree/tree/src/TIOFeatures.cxx | 14 ++++---- 48 files changed, 131 insertions(+), 140 deletions(-) diff --git a/bindings/pyroot/pythonizations/src/PyzPythonHelpers.cxx b/bindings/pyroot/pythonizations/src/PyzPythonHelpers.cxx index 059debcee4..c5e354f300 100644 --- a/bindings/pyroot/pythonizations/src/PyzPythonHelpers.cxx +++ b/bindings/pyroot/pythonizations/src/PyzPythonHelpers.cxx @@ -99,7 +99,7 @@ PyObject *PyROOT::GetDataPointer(PyObject * /*self*/, PyObject *args) /// \brief Get endianess of the system /// \param[in] self Always null, since this is a module function. /// \param[in] args Pointer to an empty Python tuple. -/// \param[out] Endianess as Python string +/// \return Endianess as Python string /// /// This function returns endianess of the system as a Python integer. The /// return value is either '<' or '>' for little or big endian, respectively. diff --git a/bindings/r/inc/TRInterface.h b/bindings/r/inc/TRInterface.h index bdb559bfb5..e097007429 100644 --- a/bindings/r/inc/TRInterface.h +++ b/bindings/r/inc/TRInterface.h @@ -206,7 +206,7 @@ namespace ROOT { The command line arguments are by deafult argc=0 and argv=NULL, The verbose mode is by default disabled but you can enable it to show procedures information in stdout/stderr \note some time can produce so much noise in the output \param argc default 0 - \param args default null + \param argv default null \param loadRcpp default true \param verbose default false \param interactive default true @@ -226,7 +226,7 @@ namespace ROOT { /** Method to eval R code and you get the result in a reference to TRObject \param code R code - \param ands reference to TRObject + \param ans reference to TRObject \return an true or false if the execution was sucessful or not. */ Int_t Eval(const TString &code, TRObject &ans); // parse line, returns in ans; error code rc diff --git a/hist/hist/src/TF1.cxx b/hist/hist/src/TF1.cxx index a72b309c1e..0b7c0b5e45 100644 --- a/hist/hist/src/TF1.cxx +++ b/hist/hist/src/TF1.cxx @@ -1973,12 +1973,11 @@ Double_t TF1::GetProb() const /// F(x_{\frac{1}{2}}) = \prod(x < x_{\frac{1}{2}}) = \frac{1}{2} /// \f] /// -/// \param[in] this TF1 function /// \param[in] nprobSum maximum size of array q and size of array probSum +/// \param[out] q array filled with nq quantiles /// \param[in] probSum array of positions where quantiles will be computed. /// It is assumed to contain at least nprobSum values. -/// \param[out] return value nq (<=nprobSum) with the number of quantiles computed -/// \param[out] array q filled with nq quantiles +/// \return value nq (<=nprobSum) with the number of quantiles computed /// /// Getting quantiles from two histograms and storing results in a TGraph, /// a so-called QQ-plot diff --git a/hist/hist/src/TGraph.cxx b/hist/hist/src/TGraph.cxx index b6e05a4a9c..614c63d697 100644 --- a/hist/hist/src/TGraph.cxx +++ b/hist/hist/src/TGraph.cxx @@ -1900,9 +1900,9 @@ Int_t TGraph::IsInside(Double_t x, Double_t y) const /// Least squares polynomial fitting without weights. /// /// \param [in] m number of parameters -/// \param [in] ma array of parameters -/// \param [in] mfirst 1st point number to fit (default =0) -/// \param [in] mlast last point number to fit (default=fNpoints-1) +/// \param [in] a array of parameters +/// \param [in] xmin 1st point number to fit (default =0) +/// \param [in] xmax last point number to fit (default=fNpoints-1) /// /// based on CERNLIB routine LSQ: Translated to C++ by Rene Brun diff --git a/hist/histpainter/src/TPainter3dAlgorithms.cxx b/hist/histpainter/src/TPainter3dAlgorithms.cxx index e0dd1f28e4..a95ac36d2d 100644 --- a/hist/histpainter/src/TPainter3dAlgorithms.cxx +++ b/hist/histpainter/src/TPainter3dAlgorithms.cxx @@ -3122,8 +3122,8 @@ L500: /// Set light source /// /// \param[in] nl source number: 1 off all light sources, 0 set diffused light -/// \param[in] xl intensity of the light source -/// \param[in] xscr `yscr` `zscr` direction of the light (in respect of the screen) +/// \param[in] yl intensity of the light source +/// \param[in] xscr, yscr, zscr direction of the light (in respect of the screen) /// /// \param[out] irep reply (0 - O.K, -1 error) @@ -4074,7 +4074,7 @@ L500: /// \param[in] qqa diffusion coefficient for diffused light [0.,1.] /// \param[in] qqd diffusion coefficient for direct light [0.,1.] /// \param[in] qqs diffusion coefficient for reflected light [0.,1.] -/// \param[in] nncs power coefficient for reflected light (.GE.1) +/// \param[in] nnqs power coefficient for reflected light (.GE.1) /// /// Lightness model formula: Y = YD*QA + > YLi*(QD*cosNi+QS*cosRi) /// diff --git a/hist/histv7/inc/ROOT/RAxis.hxx b/hist/histv7/inc/ROOT/RAxis.hxx index 0371a06f97..52ed88b9d8 100644 --- a/hist/histv7/inc/ROOT/RAxis.hxx +++ b/hist/histv7/inc/ROOT/RAxis.hxx @@ -68,7 +68,7 @@ protected: /// determine the bin number taking into account how over/underflow /// should be handled. /// - /// \param[out] result status of the bin determination. + /// \param[in] rawbin for which to determine the bin number. /// \return Returns the bin number adjusted for potential over- and underflow /// bins. Returns `kInvalidBin` if the axis cannot handle the over- / underflow. /// @@ -390,7 +390,7 @@ protected: /// Determine the inverse bin width. /// \param nbinsNoOver - number of bins without unter-/overflow /// \param lowOrHigh - first axis boundary - /// \param lighOrLow - second axis boundary + /// \param highOrLow - second axis boundary static double GetInvBinWidth(int nbinsNoOver, double lowOrHigh, double highOrLow) { return nbinsNoOver / std::fabs(highOrLow - lowOrHigh); @@ -413,7 +413,7 @@ public: /// Initialize a RAxisEquidistant. /// \param[in] title - axis title used for graphics and text representation. - /// \param nbins - number of bins in the axis, excluding under- and overflow + /// \param nbinsNoOver - number of bins in the axis, excluding under- and overflow /// bins. /// \param low - the low axis range. Any coordinate below that is considered /// as underflow. The first bin's lower edge is at this value. @@ -427,13 +427,12 @@ public: {} /// Initialize a RAxisEquidistant. - /// \param nbins - number of bins in the axis, excluding under- and overflow + /// \param nbinsNoOver - number of bins in the axis, excluding under- and overflow /// bins. /// \param low - the low axis range. Any coordinate below that is considered /// as underflow. The first bin's lower edge is at this value. /// \param high - the high axis range. Any coordinate above that is considered /// as overflow. The last bin's higher edge is at this value. - /// \param canGrow - whether this axis can extend its range. explicit RAxisEquidistant(int nbinsNoOver, double low, double high) noexcept : RAxisEquidistant("", nbinsNoOver, low, high) {} @@ -505,6 +504,7 @@ struct AxisConfigToType { class RAxisGrow: public RAxisEquidistant { public: /// Initialize a RAxisGrow. + /// \param[in] title - axis title used for graphics and text representation. /// \param nbins - number of bins in the axis, excluding under- and overflow /// bins. This value is fixed over the lifetime of the object. /// \param low - the initial value for the low axis range. Any coordinate @@ -518,7 +518,6 @@ public: {} /// Initialize a RAxisGrow. - /// \param[in] title - axis title used for graphics and text representation. /// \param nbins - number of bins in the axis, excluding under- and overflow /// bins. This value is fixed over the lifetime of the object. /// \param low - the initial value for the low axis range. Any coordinate diff --git a/hist/histv7/inc/ROOT/RHist.hxx b/hist/histv7/inc/ROOT/RHist.hxx index 5567683b27..e2b7649975 100644 --- a/hist/histv7/inc/ROOT/RHist.hxx +++ b/hist/histv7/inc/ROOT/RHist.hxx @@ -219,9 +219,9 @@ struct RHistImplGen { /// /// Delegate to the appropriate MakeNextAxis instantiation, depending on the /// axis type selected in the RAxisConfig. + /// \param title - title of the derived object. /// \param axes - `RAxisConfig` objects describing the axis of the resulting /// RHistImpl. - /// \param statConfig - the statConfig parameter to be passed to the RHistImpl /// \param processedAxisArgs - the RAxisBase-derived axis objects describing the /// axes of the resulting RHistImpl. There are `IDIM` of those; in the end /// (`IDIM` == `GetNDim()`), all `axes` have been converted to diff --git a/hist/unfold/src/TUnfoldBinning.cxx b/hist/unfold/src/TUnfoldBinning.cxx index 3aecbf53c2..2500230dca 100644 --- a/hist/unfold/src/TUnfoldBinning.cxx +++ b/hist/unfold/src/TUnfoldBinning.cxx @@ -205,7 +205,7 @@ Int_t TUnfoldBinning::UpdateFirstLastBin(Bool_t startWithRootNode) /// Create a new node without axis. /// /// \param[in] name identifier of the node -/// \param[in] nBin number of unconnected bins (could be zero) +/// \param[in] nBins number of unconnected bins (could be zero) /// \param[in] binNames (optional) names of the bins separated by ';' TUnfoldBinning::TUnfoldBinning @@ -241,7 +241,7 @@ TUnfoldBinning::TUnfoldBinning /// Add a new binning node as last last child of this node. /// /// \param[in] name name of the node -/// \param[in] nBin number of extra bins +/// \param[in] nBins number of extra bins /// \param[in] binNames (optional) names of the bins separated by ';' /// /// this is a shortcut for AddBinning(new TUnfoldBinning(name,nBins,binNames)) @@ -695,11 +695,11 @@ Int_t TUnfoldBinning::GetTH1xNumberOfBins /// /// \param[in] histogramName name of the histogram which is created /// \param[in] originalAxisBinning if true, try to preserve the axis binning -/// \param[out] (default=0) binMap mapping of global bins to histogram bins. +/// \param[out] binMap (default=0) mapping of global bins to histogram bins. /// if(binMap==0), no binMap is created -/// \param[in] (default=0) histogramTitle title of the histogram. If zero, a title +/// \param[in] histogramTitle (default=0) title of the histogram. If zero, a title /// is selected automatically -/// \param[in] (default=0) axisSteering steer the handling of underflow/overflow +/// \param[in] axisSteering (default=0) steer the handling of underflow/overflow /// and projections /// /// returns a new histogram (TH1D, TH2D or TH3D) @@ -789,11 +789,11 @@ TH1 *TUnfoldBinning::CreateHistogram /// /// \param[in] histogramName name of the histogram which is created /// \param[in] originalAxisBinning if true, try to preserve the axis binning -/// \param[out] (default=0) binMap mapping of global bins to histogram bins. +/// \param[out] binMap (default=0) mapping of global bins to histogram bins. /// if(binMap==0), no binMap is created -/// \param[in] (default=0) histogramTitle title of the histogram. If zero, a title +/// \param[in] histogramTitle (default=0) title of the histogram. If zero, a title /// is selected automatically -/// \param[in] (default=0) axisSteering steer the handling of underflow/overflow +/// \param[in] axisSteering (default=0) steer the handling of underflow/overflow /// and projections /// /// returns a new TH2D. The options are described in greater detail @@ -832,7 +832,7 @@ TH2D *TUnfoldBinning::CreateErrorMatrixHistogram /// Create a TH2D histogram capable to hold the bins of the two /// input binning schemes on the x and y axes, respectively. /// -/// \paran[in] xAxis binning scheme for the x axis +/// \param[in] xAxis binning scheme for the x axis /// \param[in] yAxis binning scheme for the y axis /// \param[in] histogramName name of the histogram which is created /// \param[in] originalXAxisBinning preserve x-axis bin widths if possible @@ -1053,8 +1053,8 @@ Int_t *TUnfoldBinning::CreateEmptyBinMap(void) const { /// Set one entry in a bin map. /// /// \param[out] binMap to be used with TUnfoldSys::GetOutput() etc -/// \param[in] source bin, global bin number in this binning scheme -/// \param[in] destination bin in the output histogram +/// \param[in] globalBin source bin, global bin number in this binning scheme +/// \param[in] destBin destination bin in the output histogram void TUnfoldBinning::SetBinMapEntry (Int_t *binMap,Int_t globalBin,Int_t destBin) const { @@ -2075,7 +2075,7 @@ Int_t TUnfoldBinning::ToGlobalBin /// and bin numbers on the corresponding axes. /// /// \param[in] globalBin global bin number -/// \param[out] local bin numbers of the distribution's axes +/// \param[out] axisBins local bin numbers of the distribution's axes /// /// returns the distribution in which the globalBin is located /// or 0 if the globalBin is outside this node and its children diff --git a/hist/unfold/src/TUnfoldBinningXML.cxx b/hist/unfold/src/TUnfoldBinningXML.cxx index 28ce408128..a1daf58215 100644 --- a/hist/unfold/src/TUnfoldBinningXML.cxx +++ b/hist/unfold/src/TUnfoldBinningXML.cxx @@ -472,7 +472,7 @@ void TUnfoldBinningXML::AddAxisXML(TXMLNode *node) { /// Export a binning scheme to a stream in XML format. /// /// \param[in] binning the binning scheme to export -/// \param[out] stream to write to +/// \param[in] out stream to write to /// \param[in] writeHeader set true when writing the first binning /// scheme to this stream /// \param[in] writeFooter set true when writing the last binning diff --git a/hist/unfold/src/TUnfoldDensity.cxx b/hist/unfold/src/TUnfoldDensity.cxx index 9b32da0961..78c7ddbf14 100644 --- a/hist/unfold/src/TUnfoldDensity.cxx +++ b/hist/unfold/src/TUnfoldDensity.cxx @@ -1311,7 +1311,7 @@ const TUnfoldBinning *TUnfoldDensity::GetOutputBinning /// \param[out] scanResult the scanned function wrt log(tau) /// \param[in] mode 1st parameter for the scan function /// \param[in] distribution 2nd parameter for the scan function -/// \param[in] projectionMode 3rd parameter for the scan function +/// \param[in] axisSteering 3rd parameter for the scan function /// \param[out] lCurvePlot for monitoring, shows the L-curve /// \param[out] logTauXPlot for monitoring, L-curve(X) as a function of log(tau) /// \param[out] logTauYPlot for monitoring, L-curve(Y) as a function of log(tau) diff --git a/hist/unfold/src/TUnfoldSys.cxx b/hist/unfold/src/TUnfoldSys.cxx index 42bbc7751c..1e89445cde 100644 --- a/hist/unfold/src/TUnfoldSys.cxx +++ b/hist/unfold/src/TUnfoldSys.cxx @@ -463,7 +463,7 @@ Int_t TUnfoldSys::SetInput(const TH1 *hist_y,Double_t scaleBias, /// \param[in] bgr background distribution with uncorrelated errors /// \param[in] name identifier for this background source /// \param[in] scale normalisation factor applied to the background -/// \param[in] scaleError normalisation uncertainty +/// \param[in] scale_error normalisation uncertainty /// /// The contribution scale*bgr is subtracted from the /// measurement prior to unfolding. The following contributions are @@ -1045,7 +1045,6 @@ Bool_t TUnfoldSys::GetDeltaSysBackgroundScale /// Correlated one-sigma shifts from shifting tau. /// /// \param[out] hist_delta histogram to store shifts -/// \param[in] source identifier of the background source /// \param[in] binMap (default=0) remapping of histogram bins /// /// returns true if the background source was found. @@ -1100,8 +1099,8 @@ void TUnfoldSys::GetEmatrixSysSource //////////////////////////////////////////////////////////////////////////////// /// Covariance contribution from background normalisation uncertainty. /// -/// \param[inout] ematrix output histogram -/// \param[in] source identifier of the background source +/// \param[in,out] ematrix output histogram +/// \param[in] name identifier of the background source /// \param[in] binMap (default=0) remapping of histogram bins /// \param[in] clearEmat (default=true) if true, clear the histogram /// prior to adding the covariance matrix contribution diff --git a/io/io/inc/ROOT/TBufferMerger.hxx b/io/io/inc/ROOT/TBufferMerger.hxx index 27fe36d399..5e4cfe52cb 100644 --- a/io/io/inc/ROOT/TBufferMerger.hxx +++ b/io/io/inc/ROOT/TBufferMerger.hxx @@ -43,7 +43,7 @@ public: /** Constructor * @param name Output file name * @param option Output file creation options - * @param compression Output file compression level + * @param compress Output file compression level */ TBufferMerger(const char *name, Option_t *option = "RECREATE", Int_t compress = ROOT::RCompressionSetting::EDefaults::kUseCompiledDefault); diff --git a/math/mathcore/inc/Math/IntegratorMultiDim.h b/math/mathcore/inc/Math/IntegratorMultiDim.h index 0d2d56396e..7b14f96d8e 100644 --- a/math/mathcore/inc/Math/IntegratorMultiDim.h +++ b/math/mathcore/inc/Math/IntegratorMultiDim.h @@ -60,7 +60,7 @@ public: @param type integration type (adaptive, MC methods, etc..) @param absTol desired absolute Error @param relTol desired relative Error - @param size maximum number of sub-intervals + @param ncall number of function calls (apply only to MC integratioon methods) In case no parameter values are passed the default ones used in IntegratorMultiDimOptions are used */ diff --git a/math/minuit2/inc/Minuit2/FCNBase.h b/math/minuit2/inc/Minuit2/FCNBase.h index bf6c64bd9e..760df5b6f4 100644 --- a/math/minuit2/inc/Minuit2/FCNBase.h +++ b/math/minuit2/inc/Minuit2/FCNBase.h @@ -65,7 +65,7 @@ public: as it searches for the Minimum or performs whatever analysis is requested by the user. - @param par function parameters as defined by the user. + @param v function parameters as defined by the user. @return the Value of the function. @@ -75,7 +75,7 @@ public: */ - virtual double operator()(const std::vector& x) const = 0; + virtual double operator()(const std::vector& v) const = 0; /** diff --git a/math/minuit2/inc/Minuit2/FumiliChi2FCN.h b/math/minuit2/inc/Minuit2/FumiliChi2FCN.h index 6af985ef08..fac33baaf6 100644 --- a/math/minuit2/inc/Minuit2/FumiliChi2FCN.h +++ b/math/minuit2/inc/Minuit2/FumiliChi2FCN.h @@ -62,7 +62,7 @@ public: Sets the model function for the data (for example gaussian+linear for a peak) - @param modelFunction a reference to the model function. + @param modelFCN a reference to the model function. */ diff --git a/math/minuit2/inc/Minuit2/FumiliErrorUpdator.h b/math/minuit2/inc/Minuit2/FumiliErrorUpdator.h index 3eb5da9c36..4b620c57a8 100644 --- a/math/minuit2/inc/Minuit2/FumiliErrorUpdator.h +++ b/math/minuit2/inc/Minuit2/FumiliErrorUpdator.h @@ -67,7 +67,7 @@ public: @param fGradientCalculator the Gradient calculator used to retrieved the Parameter transformation - @param fFumiliFCNBase the function calculating the figure of merit. + @param lambda the Marquard lambda factor \todo Some nice latex mathematical formuli... diff --git a/math/minuit2/inc/Minuit2/FumiliMaximumLikelihoodFCN.h b/math/minuit2/inc/Minuit2/FumiliMaximumLikelihoodFCN.h index c6725ae350..1661bee94a 100644 --- a/math/minuit2/inc/Minuit2/FumiliMaximumLikelihoodFCN.h +++ b/math/minuit2/inc/Minuit2/FumiliMaximumLikelihoodFCN.h @@ -61,7 +61,7 @@ public: Sets the model function for the data (for example gaussian+linear for a peak) - @param modelFunction a reference to the model function. + @param modelFCN a reference to the model function. */ diff --git a/roofit/roofit/src/RooExponential.cxx b/roofit/roofit/src/RooExponential.cxx index dc211f5275..e16871c5eb 100644 --- a/roofit/roofit/src/RooExponential.cxx +++ b/roofit/roofit/src/RooExponential.cxx @@ -102,7 +102,7 @@ void compute(size_t n, double* __restrict output, Tx x, Tc c) { //////////////////////////////////////////////////////////////////////////////// /// Evaluate the exponential without normalising it on the given batch. -/// \param[in] batchIndex Index of the batch to be computed. +/// \param[in] begin Index of the batch to be computed. /// \param[in] batchSize Size of each batch. The last batch may be smaller. /// \return A span with the computed values. diff --git a/roofit/roofit/src/RooGExpModel.cxx b/roofit/roofit/src/RooGExpModel.cxx index 9c7f184b69..18f5688217 100644 --- a/roofit/roofit/src/RooGExpModel.cxx +++ b/roofit/roofit/src/RooGExpModel.cxx @@ -48,10 +48,10 @@ ClassImp(RooGExpModel); /// /// \param[in] name Name of this instance. /// \param[in] title Title (e.g. for plotting) -/// \param[in] x The convolution observable. -/// \param[in] mean The mean of the Gaussian. -/// \param[in] sigma Width of the Gaussian. -/// \param[in] rlife Lifetime constant \f$ \tau \f$. +/// \param[in] xIn The convolution observable. +/// \param[in] meanIn The mean of the Gaussian. +/// \param[in] sigmaIn Width of the Gaussian. +/// \param[in] rlifeIn Lifetime constant \f$ \tau \f$. /// \param[in] meanSF Scale factor for mean. /// \param[in] sigmaSF Scale factor for sigma. /// \param[in] rlifeSF Scale factor for rlife. @@ -81,9 +81,9 @@ RooGExpModel::RooGExpModel(const char *name, const char *title, RooAbsRealLValue /// /// \param[in] name Name of this instance. /// \param[in] title Title (e.g. for plotting) -/// \param[in] x The convolution observable. -/// \param[in] sigma Width of the Gaussian. -/// \param[in] rlife Lifetime constant \f$ \tau \f$. +/// \param[in] xIn The convolution observable. +/// \param[in] _sigma Width of the Gaussian. +/// \param[in] _rlife Lifetime constant \f$ \tau \f$. /// \param[in] nlo Include next-to-leading order for higher accuracy of convolution. /// \param[in] type Switch between normal and flipped model. RooGExpModel::RooGExpModel(const char *name, const char *title, RooAbsRealLValue& xIn, @@ -105,10 +105,10 @@ RooGExpModel::RooGExpModel(const char *name, const char *title, RooAbsRealLValue /// /// \param[in] name Name of this instance. /// \param[in] title Title (e.g. for plotting) -/// \param[in] x The convolution observable. -/// \param[in] sigma Width of the Gaussian. -/// \param[in] rlife Lifetime constant \f$ \tau \f$. -/// \param[in] srSF Scale factor for both sigma and tau. +/// \param[in] xIn The convolution observable. +/// \param[in] _sigma Width of the Gaussian. +/// \param[in] _rlife Lifetime constant \f$ \tau \f$. +/// \param[in] _rsSF Scale factor for both sigma and tau. /// \param[in] nlo Include next-to-leading order for higher accuracy of convolution. /// \param[in] type Switch between normal and flipped model. RooGExpModel::RooGExpModel(const char *name, const char *title, RooAbsRealLValue& xIn, @@ -134,11 +134,11 @@ RooGExpModel::RooGExpModel(const char *name, const char *title, RooAbsRealLValue /// /// \param[in] name Name of this instance. /// \param[in] title Title (e.g. for plotting) -/// \param[in] x The convolution observable. -/// \param[in] sigma Width of the Gaussian. -/// \param[in] rlife Lifetime constant \f$ \tau \f$. -/// \param[in] sigmaSF Scale factor for sigma. -/// \param[in] rlifeSF Scale factor for rlife. +/// \param[in] xIn The convolution observable. +/// \param[in] _sigma Width of the Gaussian. +/// \param[in] _rlife Lifetime constant \f$ \tau \f$. +/// \param[in] _sigmaSF Scale factor for sigma. +/// \param[in] _rlifeSF Scale factor for rlife. /// \param[in] nlo Include next-to-leading order for higher accuracy of convolution. /// \param[in] type Switch between normal and flipped model. RooGExpModel::RooGExpModel(const char *name, const char *title, RooAbsRealLValue& xIn, diff --git a/roofit/roofit/src/RooGaussian.cxx b/roofit/roofit/src/RooGaussian.cxx index 9d18be7354..aec93528ba 100644 --- a/roofit/roofit/src/RooGaussian.cxx +++ b/roofit/roofit/src/RooGaussian.cxx @@ -92,7 +92,7 @@ void compute(RooSpan output, Tx x, TMean mean, TSig sigma) { /// and if found, the computation will be batched over their /// values. If batch data are not found for one of the proxies, the proxies value is assumed to /// be constant over the batch. -/// \param[in] batchIndex Index of the batch to be computed. +/// \param[in] begin Index of the batch to be computed. /// \param[in] batchSize Size of each batch. The last batch may be smaller. /// \return A span with the computed values. diff --git a/roofit/roofit/src/RooJohnson.cxx b/roofit/roofit/src/RooJohnson.cxx index ba6686f698..1dd6de96b2 100644 --- a/roofit/roofit/src/RooJohnson.cxx +++ b/roofit/roofit/src/RooJohnson.cxx @@ -153,7 +153,7 @@ void compute(RooSpan output, TMass mass, TMu mu, TLambda lambda, TGamma /// and if found, the computation will be batched over their /// values. If batch data are not found for one of the proxies, the proxies value is assumed to /// be constant over the batch. -/// \param[in] batchIndex Index of the batch to be computed. +/// \param[in] begin Index of the batch to be computed. /// \param[in] maxSize Maximal size of the batches. May return smaller batches depending on inputs. /// \return A span with the computed values. diff --git a/roofit/roofit/src/RooLandau.cxx b/roofit/roofit/src/RooLandau.cxx index e59a923cf0..2dade45b3a 100644 --- a/roofit/roofit/src/RooLandau.cxx +++ b/roofit/roofit/src/RooLandau.cxx @@ -169,7 +169,7 @@ void compute( size_t batchSize, /// and if found, the computation will be batched over their /// values. If batch data are not found for one of the proxies, the proxies value is assumed to /// be constant over the batch. -/// \param[in] batchIndex Index of the batch to be computed. +/// \param[in] begin Index of the batch to be computed. /// \param[in] batchSize Size of each batch. The last batch may be smaller. /// \return A span with the computed values. diff --git a/roofit/roofitcore/src/BatchData.cxx b/roofit/roofitcore/src/BatchData.cxx index fd05343076..5bbe34e20b 100644 --- a/roofit/roofitcore/src/BatchData.cxx +++ b/roofit/roofitcore/src/BatchData.cxx @@ -73,7 +73,7 @@ bool BatchData::setStatus(std::size_t begin, std::size_t size, Status_t stat, /// Retrieve an existing batch. /// /// \param[in] begin Begin index of the batch. -/// \param[in] size Requested size. Batch may come out smaller than this. +/// \param[in] maxSize Requested size. Batch may come out smaller than this. /// \param[in] normSet Optional normSet pointer to distinguish differently normalised computations. /// \param[in] ownerTag Optional owner tag. This avoids reusing batch memory for e.g. getVal() and getLogVal(). /// \return Non-mutable contiguous batch data. diff --git a/roofit/roofitcore/src/RooAbsPdf.cxx b/roofit/roofitcore/src/RooAbsPdf.cxx index 9f68b1cdb7..9e7eb69e09 100644 --- a/roofit/roofitcore/src/RooAbsPdf.cxx +++ b/roofit/roofitcore/src/RooAbsPdf.cxx @@ -711,7 +711,7 @@ bool checkInfNaNNeg(const T& inputs) { //////////////////////////////////////////////////////////////////////////////// /// Scan through outputs and fix+log all nans and negative values. -/// \param[in/out] outputs Array to be scanned & fixed. +/// \param[in,out] outputs Array to be scanned & fixed. /// \param[in] begin Begin of event range. Only needed to print the correct event number /// where the error occurred. void RooAbsPdf::logBatchComputationErrors(RooSpan& outputs, std::size_t begin) const { @@ -734,7 +734,7 @@ void RooAbsPdf::logBatchComputationErrors(RooSpan& outputs, std::s /// Compute the log-likelihoods for all events in the requested batch. /// The arguments are passed over to getValBatch(). /// \param[in] begin Start of the batch. -/// \param[in] size Maximum size of the batch. Depending on data layout and memory, the batch +/// \param[in] maxSize Maximum size of the batch. Depending on data layout and memory, the batch /// may come back smaller. /// \return Returns a batch of doubles that contains the log probabilities. RooSpan RooAbsPdf::getLogValBatch(std::size_t begin, std::size_t maxSize, diff --git a/roofit/roofitcore/src/RooAbsReal.cxx b/roofit/roofitcore/src/RooAbsReal.cxx index 2d2ceeaf2d..6cac5f5897 100644 --- a/roofit/roofitcore/src/RooAbsReal.cxx +++ b/roofit/roofitcore/src/RooAbsReal.cxx @@ -4294,7 +4294,7 @@ RooAbsMoment* RooAbsReal::moment(RooRealVar& obs, Int_t order, Bool_t central, B /// \param[in] order Order of the moment /// \param[in] central If true, the central moment is given by \f$ \langle (x- \langle x \rangle )^2 \rangle \f$ /// \param[in] takeRoot Calculate the square root -/// \param[in] intNormOb If true, the moment of the function integrated over all normalization observables is returned. +/// \param[in] intNormObs If true, the moment of the function integrated over all normalization observables is returned. RooAbsMoment* RooAbsReal::moment(RooRealVar& obs, const RooArgSet& normObs, Int_t order, Bool_t central, Bool_t takeRoot, Bool_t intNormObs) { diff --git a/roofit/roofitcore/src/RooCustomizer.cxx b/roofit/roofitcore/src/RooCustomizer.cxx index 97d6d3176c..818991873d 100644 --- a/roofit/roofitcore/src/RooCustomizer.cxx +++ b/roofit/roofitcore/src/RooCustomizer.cxx @@ -198,7 +198,7 @@ static Int_t init() /// replaceArg() and splitArg() functionality. /// \param[in] pdf Proto PDF to be customised. /// \param[in] masterCat Category to be used for splitting. -/// \param[in/out] splitLeafs All nodes created in +/// \param[in,out] splitLeafs All nodes created in /// the customisation process are added to this set. /// The user can provide nodes that are *taken* /// from the set if they have a name that matches `_`. @@ -209,7 +209,7 @@ static Int_t init() /// auto yield1 = new RooFormulaVar("yieldSig_BBG1m2T","sigy1","M/3.360779",mass); /// customisedLeafs.addOwned(*yield1); /// ``` -/// \param[in/out] splitLeafsAll All leafs that are used when customising are collected here. +/// \param[in,out] splitLeafsAll All leafs that are used when customising are collected here. /// If this set already contains leaves, they will be used for customising if the names match /// as above. /// diff --git a/roofit/roofitcore/src/RooDataHist.cxx b/roofit/roofitcore/src/RooDataHist.cxx index 1c8b517b0d..8c90dd0ade 100644 --- a/roofit/roofitcore/src/RooDataHist.cxx +++ b/roofit/roofitcore/src/RooDataHist.cxx @@ -632,8 +632,8 @@ void RooDataHist::_adjustBinning(RooRealVar &theirVar, const TAxis &axis, /// observable to binning in given reference TH1. Used by constructors /// that import data from an external TH1. /// Both the variables in vars and in this RooDataHist are adjusted. -/// @param List with variables that are supposed to have their binning adjusted. -/// @param Reference histogram that dictates the binning +/// @param vars List with variables that are supposed to have their binning adjusted. +/// @param href Reference histogram that dictates the binning /// @param offset If not nullptr, a possible bin count offset for the axes x,y,z is saved here as Int_t[3] void RooDataHist::adjustBinning(const RooArgList& vars, const TH1& href, Int_t* offset) diff --git a/roofit/roofitcore/src/RooDataSet.cxx b/roofit/roofitcore/src/RooDataSet.cxx index 1e54dfbde0..f03ec78a0d 100644 --- a/roofit/roofitcore/src/RooDataSet.cxx +++ b/roofit/roofitcore/src/RooDataSet.cxx @@ -765,7 +765,7 @@ RooDataSet::RooDataSet(const char *name, const char *title, TTree *theTree, /// /// \param[in] name Name of this dataset. /// \param[in] title Title for e.g. plotting. -/// \param[in] tree Tree to be imported. +/// \param[in] theTree Tree to be imported. /// \param[in] vars Defines the columns of the data set. For each dimension /// specified, the TTree must have a branch with the same name. For category /// branches, this branch should contain the numeric index value. Real dimensions @@ -1205,11 +1205,11 @@ void RooDataSet::add(const RooArgSet& data, Double_t wgt, Double_t wgtError) //////////////////////////////////////////////////////////////////////////////// /// Add a data point, with its coordinates specified in the 'data' argset, to the data set. /// Any variables present in 'data' but not in the dataset will be silently ignored. -/// \param[in] data Data point. -/// \param[in] wgt Event weight. The current value of the weight variable is ignored. +/// \param[in] indata Data point. +/// \param[in] inweight Event weight. The current value of the weight variable is ignored. /// \note To obtain weighted events, a variable must be designated `WeightVar` in the constructor. -/// \param[in] wgtErrorLo Asymmetric weight error. -/// \param[in] wgtErrorHi Asymmetric weight error. +/// \param[in] weightErrorLo Asymmetric weight error. +/// \param[in] weightErrorHi Asymmetric weight error. /// \note This requires including the weight variable in the set of `StoreAsymError` variables when constructing /// the dataset. diff --git a/roofit/roofitcore/src/RooFormulaVar.cxx b/roofit/roofitcore/src/RooFormulaVar.cxx index 90ee32d619..947c505598 100644 --- a/roofit/roofitcore/src/RooFormulaVar.cxx +++ b/roofit/roofitcore/src/RooFormulaVar.cxx @@ -66,7 +66,7 @@ ClassImp(RooFormulaVar); /// Constructor with formula expression and list of input variables. /// \param[in] name Name of the formula. /// \param[in] title Title of the formula. -/// \param[in] formula Expression to be evaluated. +/// \param[in] inFormula Expression to be evaluated. /// \param[in] dependents Variables that should be passed to the formula. /// \param[in] checkVariables Check that all variables from `dependents` are used in the expression. RooFormulaVar::RooFormulaVar(const char *name, const char *title, const char* inFormula, const RooArgList& dependents, diff --git a/roofit/roofitcore/src/RooSuperCategory.cxx b/roofit/roofitcore/src/RooSuperCategory.cxx index 4c0b705e50..e5668ffb98 100644 --- a/roofit/roofitcore/src/RooSuperCategory.cxx +++ b/roofit/roofitcore/src/RooSuperCategory.cxx @@ -54,7 +54,7 @@ RooSuperCategory::RooSuperCategory() : /// Construct a super category from other categories. /// \param[in] name Name of this object /// \param[in] title Title (for e.g. printing) -/// \param[in] inputCatList RooArgSet with category objects. These all need to derive from RooAbsCategoryLValue, *i.e.* +/// \param[in] inputCategories RooArgSet with category objects. These all need to derive from RooAbsCategoryLValue, *i.e.* /// one needs to be able to assign to them. RooSuperCategory::RooSuperCategory(const char *name, const char *title, const RooArgSet& inputCategories) : RooAbsCategoryLValue(name, title), diff --git a/roofit/roofitmore/src/RooHypatia2.cxx b/roofit/roofitmore/src/RooHypatia2.cxx index 691aa6073d..7d550b2753 100644 --- a/roofit/roofitmore/src/RooHypatia2.cxx +++ b/roofit/roofitmore/src/RooHypatia2.cxx @@ -119,21 +119,21 @@ /// \param[in] a2 Start of right tail. /// \param[in] n2 Shape parameter of right tail (\f$ n2 \ge 0 \f$). With \f$ n2 = 0 \f$, the function is constant. RooHypatia2::RooHypatia2(const char *name, const char *title, RooAbsReal& x, RooAbsReal& lambda, - RooAbsReal& zeta, RooAbsReal& beta, RooAbsReal& sigm, RooAbsReal& mu, RooAbsReal& a, + RooAbsReal& zeta, RooAbsReal& beta, RooAbsReal& sigma, RooAbsReal& mu, RooAbsReal& a, RooAbsReal& n, RooAbsReal& a2, RooAbsReal& n2) : RooAbsPdf(name, title), _x("x", "x", this, x), _lambda("lambda", "Lambda", this, lambda), _zeta("zeta", "zeta", this, zeta), _beta("beta", "Asymmetry parameter beta", this, beta), - _sigma("sigma", "Width parameter sigma", this, sigm), + _sigma("sigma", "Width parameter sigma", this, sigma), _mu("mu", "Location parameter mu", this, mu), _a("a", "Left tail location a", this, a), _n("n", "Left tail parameter n", this, n), _a2("a2", "Right tail location a2", this, a2), _n2("n2", "Right tail parameter n2", this, n2) { - RooHelpers::checkRangeOfParameters(this, {&sigm}, 0.); + RooHelpers::checkRangeOfParameters(this, {&sigma}, 0.); RooHelpers::checkRangeOfParameters(this, {&zeta, &n, &n2, &a, &a2}, 0., std::numeric_limits::max(), true); if (zeta.getVal() == 0. && zeta.isConstant()) { RooHelpers::checkRangeOfParameters(this, {&lambda}, -std::numeric_limits::max(), 0., false, diff --git a/tmva/tmva/inc/TMVA/BDTEventWrapper.h b/tmva/tmva/inc/TMVA/BDTEventWrapper.h index 7d4c4f8dd6..2c99341dd9 100644 --- a/tmva/tmva/inc/TMVA/BDTEventWrapper.h +++ b/tmva/tmva/inc/TMVA/BDTEventWrapper.h @@ -40,14 +40,14 @@ namespace TMVA { // Set the accumulated weight, for sorted signal/background events /** - * @param fType - true for signal, false for background + * @param type - true for signal, false for background * @param weight - the total weight */ void SetCumulativeWeight( Bool_t type, Double_t weight ); // Get the accumulated weight /** - * @param fType - true for signal, false for background + * @param type - true for signal, false for background * @return the cumulative weight for sorted signal/background events */ Double_t GetCumulativeWeight( Bool_t type ) const; diff --git a/tmva/tmva/inc/TMVA/NeuralNet.h b/tmva/tmva/inc/TMVA/NeuralNet.h index bae98a48b2..a11b543b59 100644 --- a/tmva/tmva/inc/TMVA/NeuralNet.h +++ b/tmva/tmva/inc/TMVA/NeuralNet.h @@ -478,10 +478,8 @@ namespace TMVA * \param size size of the layer * \param itWeightBegin indicates the start of the weights for this layer on the weight vector * \param itGradientBegin indicates the start of the gradients for this layer on the gradient vector - * \param itFunctionBegin indicates the start of the vector of activation functions for this layer on the - * activation function vector - * \param itInverseFunctionBegin indicates the start of the vector of activation functions for this - * layer on the activation function vector + * \param activationFunction indicates activation functions for this layer + * \param inverseActivationFunction indicates the inverse activation functions for this layer * \param eModeOutput indicates a potential tranformation of the output values before further computation * DIRECT does not further transformation; SIGMOID applies a sigmoid transformation to each * output value (to create a probability); SOFTMAX applies a softmax transformation to all @@ -500,8 +498,7 @@ namespace TMVA * * \param size size of the layer * \param itWeightBegin indicates the start of the weights for this layer on the weight vector - * \param itFunctionBegin indicates the start of the vector of activation functions for this layer on the - * activation function vector + * \param activationFunction indicates the activation function for this layer * \param eModeOutput indicates a potential tranformation of the output values before further computation * DIRECT does not further transformation; SIGMOID applies a sigmoid transformation to each * output value (to create a probability); SOFTMAX applies a softmax transformation to all @@ -679,9 +676,6 @@ namespace TMVA /*! \brief c'tor for defining a Layer * * - * \param itInputBegin indicates the start of the input node vector - * \param itInputEnd indicates the end of the input node vector - * */ Layer (size_t numNodes, EnumFunction activationFunction, ModeOutputValues eModeOutputValues = ModeOutputValues::DIRECT); @@ -1141,7 +1135,7 @@ namespace TMVA /*! \brief executes one training cycle * - * \param minimizier the minimizer to be used + * \param minimizer the minimizer to be used * \param weights the weight vector to be used * \param itPatternBegin the pattern to be trained with * \param itPatternEnd the pattern to be trainied with diff --git a/tmva/tmva/inc/TMVA/NeuralNet.icc b/tmva/tmva/inc/TMVA/NeuralNet.icc index 95cad21e26..e511e49d43 100644 --- a/tmva/tmva/inc/TMVA/NeuralNet.icc +++ b/tmva/tmva/inc/TMVA/NeuralNet.icc @@ -933,7 +933,7 @@ template * \param minimizer the minimizer to be used (e.g. SGD) * \param weights the weight container with all the synapse weights * \param itPatternBegin begin of the pattern container - * \parama itPatternEnd the end of the pattern container + * \param itPatternEnd the end of the pattern container * \param settings the settings for this training (e.g. multithreading or not, regularization, etc.) * \param dropContainer the data for dropping-out nodes (regularization technique) */ diff --git a/tmva/tmva/inc/TMVA/RTensor.hxx b/tmva/tmva/inc/TMVA/RTensor.hxx index c131384ae2..7d9773b457 100644 --- a/tmva/tmva/inc/TMVA/RTensor.hxx +++ b/tmva/tmva/inc/TMVA/RTensor.hxx @@ -73,7 +73,7 @@ inline std::vector ComputeStridesFromShape(const T &shape, MemoryLa } /// \brief Compute indices from global index -/// \param[in] Shape vector +/// \param[in] shape Shape vector /// \param[in] idx Global index /// \param[in] layout Memory layout /// \return Indice vector diff --git a/tmva/tmva/inc/TMVA/TreeInference/BranchlessTree.hxx b/tmva/tmva/inc/TMVA/TreeInference/BranchlessTree.hxx index 4ac460be64..a1c6fdf773 100644 --- a/tmva/tmva/inc/TMVA/TreeInference/BranchlessTree.hxx +++ b/tmva/tmva/inc/TMVA/TreeInference/BranchlessTree.hxx @@ -72,7 +72,7 @@ struct BranchlessTree { /// Perform inference on a single input vector /// \param[in] input Pointer to data containing the input values /// \param[in] stride Stride to go from one input variable to the next one -/// \param[out] Tree score, result of the inference +/// \return Tree score, result of the inference template inline T BranchlessTree::Inference(const T *input, const int stride) { @@ -105,7 +105,7 @@ inline void BranchlessTree::FillSparse() /// /// \param[in] funcName Name of the function /// \param[in] typeName Name of the type used for the computation -/// \param[out] Code of the inference function as string +/// \return Code of the inference function as string template inline std::string BranchlessTree::GetInferenceCode(const std::string& funcName, const std::string& typeName) { diff --git a/tmva/tmva/inc/TMVA/TreeInference/Forest.hxx b/tmva/tmva/inc/TMVA/TreeInference/Forest.hxx index 70d1e3eb68..18b385a8e0 100644 --- a/tmva/tmva/inc/TMVA/TreeInference/Forest.hxx +++ b/tmva/tmva/inc/TMVA/TreeInference/Forest.hxx @@ -195,7 +195,7 @@ struct BranchlessJittedForest : public ForestBase inline std::string BranchlessJittedForest::Load(const std::string &key, const std::string &filename, const int output, const bool sortTrees) diff --git a/tmva/tmva/src/BDTEventWrapper.cxx b/tmva/tmva/src/BDTEventWrapper.cxx index 63171c886b..9702660936 100644 --- a/tmva/tmva/src/BDTEventWrapper.cxx +++ b/tmva/tmva/src/BDTEventWrapper.cxx @@ -48,7 +48,7 @@ BDTEventWrapper::~BDTEventWrapper() { //////////////////////////////////////////////////////////////////////////////// /// Set the accumulated weight, for sorted signal/background events /// -/// @param fType - true for signal, false for background +/// @param type - true for signal, false for background /// @param weight - the total weight void BDTEventWrapper::SetCumulativeWeight(Bool_t type, Double_t weight) { diff --git a/tmva/tmva/src/CrossValidation.cxx b/tmva/tmva/src/CrossValidation.cxx index 453927c5b7..58bd9130d1 100644 --- a/tmva/tmva/src/CrossValidation.cxx +++ b/tmva/tmva/src/CrossValidation.cxx @@ -99,7 +99,7 @@ TMultiGraph *TMVA::CrossValidationResult::GetROCCurves(Bool_t /*fLegend*/) /// /// \note You own the returned pointer. /// -/// \param numSamples[in] Number of samples used for generating the average ROC +/// \param[in] numSamples Number of samples used for generating the average ROC /// Curve. Avg. curve will be evaluated only at these /// points (using interpolation if necessary). /// diff --git a/tmva/tmva/src/CvSplit.cxx b/tmva/tmva/src/CvSplit.cxx index d6d44ac1cc..9eedcf3d72 100644 --- a/tmva/tmva/src/CvSplit.cxx +++ b/tmva/tmva/src/CvSplit.cxx @@ -227,15 +227,15 @@ UInt_t TMVA::CvSplitKFoldsExpr::GetSpectatorIndexForName(DataSetInfo &dsi, TStri //////////////////////////////////////////////////////////////////////////////// /// \brief Splits a dataset into k folds, ready for use in cross validation. -/// \param numFolds[in] Number of folds to split data into -/// \param stratified[in] If true, use stratified splitting, balancing the +/// \param[in] numFolds Number of folds to split data into +/// \param[in] stratified If true, use stratified splitting, balancing the /// number of events across classes and folds. If false, /// no such balancing is done. For -/// \param splitExpr[in] Expression used to split data into folds. If `""` a +/// \param[in] splitExpr Expression used to split data into folds. If `""` a /// random assignment will be done. Otherwise the /// expression is fed into a TFormula and evaluated per /// event. The resulting value is the the fold assignment. -/// \param seed[in] Used only when using random splitting (i.e. when +/// \param[in] seed Used only when using random splitting (i.e. when /// `splitExpr` is `""`). Seed is used to initialise the random /// number generator when assigning events to folds. /// @@ -282,9 +282,9 @@ void TMVA::CvSplitKFolds::MakeKFoldDataSet(DataSetInfo &dsi) //////////////////////////////////////////////////////////////////////////////// /// \brief Generates a vector of fold assignments -/// \param nEntires[in] Number of events in range -/// \param numFolds[in] Number of folds to split data into -/// \param seed[in] Random seed +/// \param[in] nEntries Number of events in range +/// \param[in] numFolds Number of folds to split data into +/// \param[in] seed Random seed /// /// Randomly assigns events to `numFolds` folds. Each fold will hold at most /// `nEntries / numFolds + 1` events. @@ -311,8 +311,8 @@ std::vector TMVA::CvSplitKFolds::GetEventIndexToFoldMapping(UInt_t nEntr //////////////////////////////////////////////////////////////////////////////// /// \brief Split sets for into k-folds -/// \param oldSet[in] Original, unsplit, events -/// \param numFolds[in] Number of folds to split data into +/// \param[in] oldSet Original, unsplit, events +/// \param[in] numFolds Number of folds to split data into /// std::vector> diff --git a/tmva/tmva/src/Envelope.cxx b/tmva/tmva/src/Envelope.cxx index 5fab98c13b..8a0c6b23f4 100644 --- a/tmva/tmva/src/Envelope.cxx +++ b/tmva/tmva/src/Envelope.cxx @@ -37,8 +37,8 @@ this is a generic one protected. \param file optional file to save the results. \param options extra options for the algorithm. */ -Envelope::Envelope(const TString &name, DataLoader *dalaloader, TFile *file, const TString options) - : Configurable(options), fDataLoader(dalaloader), fFile(file), fModelPersistence(kTRUE), fVerbose(kFALSE), +Envelope::Envelope(const TString &name, DataLoader *dataloader, TFile *file, const TString options) + : Configurable(options), fDataLoader(dataloader), fFile(file), fModelPersistence(kTRUE), fVerbose(kFALSE), fTransformations("I"), fSilentFile(kFALSE), fJobs(1) { SetName(name.Data()); @@ -120,7 +120,7 @@ DataLoader *Envelope::GetDataLoader(){ return fDataLoader.get();} //_______________________________________________________________________ /** Method to set the pointer to TMVA::DataLoader object. -\param dalaloader pointer to TMVA::DataLoader object. +\param dataloader pointer to TMVA::DataLoader object. */ void Envelope::SetDataLoader(DataLoader *dataloader) @@ -146,7 +146,7 @@ void TMVA::Envelope::SetModelPersistence(Bool_t status){fModelPersistence=status /** Method to book the machine learning method to perform the algorithm. \param method enum TMVA::Types::EMVA with the type of the mva method -\param methodtitle String with the method title. +\param methodTitle String with the method title. \param options String with the options for the method. */ void TMVA::Envelope::BookMethod(Types::EMVA method, TString methodTitle, TString options){ @@ -156,8 +156,8 @@ void TMVA::Envelope::BookMethod(Types::EMVA method, TString methodTitle, TString //_______________________________________________________________________ /** Method to book the machine learning method to perform the algorithm. -\param methodname String with the name of the mva method -\param methodtitle String with the method title. +\param methodName String with the name of the mva method +\param methodTitle String with the method title. \param options String with the options for the method. */ void TMVA::Envelope::BookMethod(TString methodName, TString methodTitle, TString options){ diff --git a/tree/dataframe/inc/ROOT/RDF/RInterface.hxx b/tree/dataframe/inc/ROOT/RDF/RInterface.hxx index b5e39251a8..da09c0be3c 100644 --- a/tree/dataframe/inc/ROOT/RDF/RInterface.hxx +++ b/tree/dataframe/inc/ROOT/RDF/RInterface.hxx @@ -568,7 +568,7 @@ public: //////////////////////////////////////////////////////////////////////////// /// \brief Save selected columns in memory /// \tparam ColumnTypes variadic list of branch/column types. - /// \param[in] columns to be cached in memory. + /// \param[in] columnList columns to be cached in memory. /// \return a `RDataFrame` that wraps the cached dataset. /// /// This action returns a new `RDataFrame` object, completely detached from @@ -603,7 +603,7 @@ public: //////////////////////////////////////////////////////////////////////////// /// \brief Save selected columns in memory - /// \param[in] columns to be cached in memory + /// \param[in] columnList columns to be cached in memory /// \return a `RDataFrame` that wraps the cached dataset. /// /// See the previous overloads for more information. @@ -660,7 +660,7 @@ public: //////////////////////////////////////////////////////////////////////////// /// \brief Save selected columns in memory - /// \param[in] columns to be cached in memory. + /// \param[in] columnList columns to be cached in memory. /// \return a `RDataFrame` that wraps the cached dataset. /// /// See the previous overloads for more information. @@ -1528,13 +1528,13 @@ public: /// ~~~ /// template - RResultPtr Fill(T &&model, const ColumnNames_t &bl) + RResultPtr Fill(T &&model, const ColumnNames_t &columnList) { auto h = std::make_shared(std::forward(model)); if (!RDFInternal::HistoUtils::HasAxisLimits(*h)) { throw std::runtime_error("The absence of axes limits is not supported yet."); } - return CreateAction(bl, h, bl.size()); + return CreateAction(columnList, h, columnList.size()); } //////////////////////////////////////////////////////////////////////////// @@ -2134,7 +2134,7 @@ public: /// \brief Provides a representation of the columns in the dataset /// \tparam ColumnTypes variadic list of branch/column types. /// \param[in] columnList Names of the columns to be displayed. - /// \param[in] rows Number of events for each column to be displayed. + /// \param[in] nRows Number of events for each column to be displayed. /// \return the `RDisplay` instance wrapped in a `RResultPtr`. /// /// This function returns a `RResultPtr` containing all the entries to be displayed, organized in a tabular @@ -2165,7 +2165,7 @@ public: //////////////////////////////////////////////////////////////////////////// /// \brief Provides a representation of the columns in the dataset /// \param[in] columnList Names of the columns to be displayed. - /// \param[in] rows Number of events for each column to be displayed. + /// \param[in] nRows Number of events for each column to be displayed. /// \return the `RDisplay` instance wrapped in a `RResultPtr`. /// /// This overload automatically infers the column types. @@ -2181,7 +2181,7 @@ public: //////////////////////////////////////////////////////////////////////////// /// \brief Provides a representation of the columns in the dataset /// \param[in] columnNameRegexp A regular expression to select the columns. - /// \param[in] rows Number of events for each column to be displayed. + /// \param[in] nRows Number of events for each column to be displayed. /// \return the `RDisplay` instance wrapped in a `RResultPtr`. /// /// The existing columns are matched against the regular expression. If the string provided diff --git a/tree/dataframe/inc/ROOT/RDFHelpers.hxx b/tree/dataframe/inc/ROOT/RDFHelpers.hxx index 2193e1772e..63a0f90cab 100644 --- a/tree/dataframe/inc/ROOT/RDFHelpers.hxx +++ b/tree/dataframe/inc/ROOT/RDFHelpers.hxx @@ -138,7 +138,7 @@ void SaveGraph(NodeType node, const std::string &outputFile) // clang-format off /// Cast a RDataFrame node to the common type ROOT::RDF::RNode -/// \param[in] Any node of a RDataFrame graph +/// \param[in] node Any node of a RDataFrame graph // clang-format on template RNode AsRNode(NodeType node) diff --git a/tree/dataframe/inc/ROOT/RDataSource.hxx b/tree/dataframe/inc/ROOT/RDataSource.hxx index f4af9abded..04f7dc850c 100644 --- a/tree/dataframe/inc/ROOT/RDataSource.hxx +++ b/tree/dataframe/inc/ROOT/RDataSource.hxx @@ -126,14 +126,14 @@ public: virtual const std::vector &GetColumnNames() const = 0; /// \brief Checks if the dataset has a certain column - /// \param[in] columnName The name of the column - virtual bool HasColumn(std::string_view) const = 0; + /// \param[in] colName The name of the column + virtual bool HasColumn(std::string_view colName) const = 0; // clang-format off /// \brief Type of a column as a string, e.g. `GetTypeName("x") == "double"`. Required for jitting e.g. `df.Filter("x>0")`. - /// \param[in] columnName The name of the column + /// \param[in] colName The name of the column // clang-format on - virtual std::string GetTypeName(std::string_view) const = 0; + virtual std::string GetTypeName(std::string_view colName) const = 0; // clang-format off /// Called at most once per column by RDF. Return vector of pointers to pointers to column values - one per slot. diff --git a/tree/dataframe/inc/ROOT/RResultPtr.hxx b/tree/dataframe/inc/ROOT/RResultPtr.hxx index 8358832b14..8acb2bfae6 100644 --- a/tree/dataframe/inc/ROOT/RResultPtr.hxx +++ b/tree/dataframe/inc/ROOT/RResultPtr.hxx @@ -262,7 +262,7 @@ public: /// Register a callback that RDataFrame will execute in each worker thread concurrently on that thread's partial result. /// /// \param[in] everyNEvents Frequency at which the callback will be called by each thread, as a number of events processed - /// \param[in] a callable with signature `void(unsigned int, Value_t&)` where Value_t is the type of the value contained in this RResultPtr + /// \param[in] callback A callable with signature `void(unsigned int, Value_t&)` where Value_t is the type of the value contained in this RResultPtr /// \return this RResultPtr, to allow chaining of OnPartialResultSlot with other calls /// /// See `OnPartialResult` for a generic explanation of the callback mechanism. diff --git a/tree/dataframe/src/RArrowDS.cxx b/tree/dataframe/src/RArrowDS.cxx index d9e2fae32f..0152b9a813 100644 --- a/tree/dataframe/src/RArrowDS.cxx +++ b/tree/dataframe/src/RArrowDS.cxx @@ -382,8 +382,8 @@ public: //////////////////////////////////////////////////////////////////////// /// Constructor to create an Arrow RDataSource for RDataFrame. -/// \param[in] table the arrow Table to observe. -/// \param[in] columns the name of the columns to use +/// \param[in] inTable the arrow Table to observe. +/// \param[in] inColumns the name of the columns to use /// In case columns is empty, we use all the columns found in the table RArrowDS::RArrowDS(std::shared_ptr inTable, std::vector const &inColumns) : fTable{inTable}, fColumnNames{inColumns} diff --git a/tree/tree/inc/TTree.h b/tree/tree/inc/TTree.h index 8560e28ab5..e95d4ce301 100644 --- a/tree/tree/inc/TTree.h +++ b/tree/tree/inc/TTree.h @@ -357,7 +357,7 @@ public: /// possible, unless e.g. type conversions are needed. /// /// \param[in] name Name of the branch to be created. - /// \param[in] obj Array of the objects to be added. When calling Fill(), the current value of the type/object will be saved. + /// \param[in] addobj Array of the objects to be added. When calling Fill(), the current value of the type/object will be saved. /// \param[in] bufsize he buffer size in bytes for this branch. When the buffer is full, it is compressed and written to disc. /// The default value of 32000 bytes and should be ok for most simple types. Larger buffers (e.g. 256000) if your Tree is not split and each entry is large (Megabytes). /// A small value for bufsize is beneficial if entries in the Tree are accessed randomly and the Tree is in split mode. diff --git a/tree/tree/src/TIOFeatures.cxx b/tree/tree/src/TIOFeatures.cxx index 681f2172bd..ca292fb30a 100644 --- a/tree/tree/src/TIOFeatures.cxx +++ b/tree/tree/src/TIOFeatures.cxx @@ -51,7 +51,7 @@ using namespace ROOT; //////////////////////////////////////////////////////////////////////////// /// \brief Clear a specific IO feature from this set. -/// \param[in] enum_bits The specific feature to disable. +/// \param[in] input_bits The specific feature to disable. /// /// Removes a feature from the `TIOFeatures` object; emits an Error message if /// the IO feature is not supported by this version of ROOT. @@ -62,7 +62,7 @@ void TIOFeatures::Clear(Experimental::EIOFeatures input_bits) //////////////////////////////////////////////////////////////////////////// /// \brief Clear a specific IO feature from this set. -/// \param[in] enum_bits The specific feature to disable. +/// \param[in] input_bits The specific feature to disable. /// /// Removes a feature from the `TIOFeatures` object; emits an Error message if /// the IO feature is not supported by this version of ROOT. @@ -73,7 +73,7 @@ void TIOFeatures::Clear(Experimental::EIOUnsupportedFeatures input_bits) //////////////////////////////////////////////////////////////////////////// /// \brief Clear a specific IO feature from this set. -/// \param[in] enum_bits The specific feature to disable. +/// \param[in] input_bits The specific feature to disable. /// /// Removes a feature from the `TIOFeatures` object; emits an Error message if /// the IO feature is not supported by this version of ROOT. @@ -115,7 +115,7 @@ static std::string GetUnsupportedName(TBasket::EUnsupportedIOBits enum_flag) //////////////////////////////////////////////////////////////////////////// /// \brief Set a specific IO feature. -/// \param[in] enum_bits The specific feature to enable. +/// \param[in] input_bits The specific feature to enable. /// /// Sets a feature in the `TIOFeatures` object; emits an Error message if /// the IO feature is not supported by this version of ROOT. @@ -129,7 +129,7 @@ bool TIOFeatures::Set(Experimental::EIOFeatures input_bits) //////////////////////////////////////////////////////////////////////////// /// \brief Set a specific IO feature. -/// \param[in] enum_bits The specific feature to enable. +/// \param[in] input_bits The specific feature to enable. /// /// Sets a feature in the `TIOFeatures` object; emits an Error message if /// the IO feature is not supported by this version of ROOT. @@ -221,7 +221,7 @@ void TIOFeatures::Print() const //////////////////////////////////////////////////////////////////////////// /// \brief Test to see if a given feature is set -/// \param[in] enum_bits The specific feature to test. +/// \param[in] input_bits The specific feature to test. /// /// Returns kTRUE if the feature is enables in this object and supported by /// this version of ROOT. @@ -232,7 +232,7 @@ bool TIOFeatures::Test(Experimental::EIOFeatures input_bits) const //////////////////////////////////////////////////////////////////////////// /// \brief Test to see if a given feature is set -/// \param[in] enum_bits The specific feature to test. +/// \param[in] input_bits The specific feature to test. /// /// Returns kTRUE if the feature is enables in this object and supported by /// this version of ROOT. -- 2.26.2