From e65727913e435819a3fc26513d9892d179eab1f2 Mon Sep 17 00:00:00 2001
From: Mattias Ellert <mattias.ellert@physics.uu.se>
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 '<name>' of command @param is not found in the argument list
of <function>.
---
.../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<RAxisConfig::kEquidistant> {
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 <b>scale</b>*<b>bgr</b> 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<double>& x) const = 0;
+ virtual double operator()(const std::vector<double>& 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<double> 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<double> 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<const double>& outputs, std::size_t begin) const {
@@ -734,7 +734,7 @@ void RooAbsPdf::logBatchComputationErrors(RooSpan<const double>& 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<const double> 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 `<parameterNameToBeReplaced>_<category>`.
@@ -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<double>::max(), true);
if (zeta.getVal() == 0. && zeta.isConstant()) {
RooHelpers::checkRangeOfParameters(this, {&lambda}, -std::numeric_limits<double>::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 <typename LAYERDATA>
* \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<std::size_t> 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 <typename T>
inline T BranchlessTree<T>::Inference(const T *input, const int stride)
{
@@ -105,7 +105,7 @@ inline void BranchlessTree<T>::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 <typename T>
inline std::string BranchlessTree<T>::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<T, std::function<void (const T
/// \param[in] filename Filename of the ROOT file
/// \param[in] output Load trees corresponding to the given output node of the forest
/// \param[in] sortTrees Flag to indicate sorting the input trees by the cut value of the first node of each tree
-/// \param[out] Return jitted code as string
+/// \return Return jitted code as string
template <typename T>
inline std::string
BranchlessJittedForest<T>::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<UInt_t> 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<std::vector<TMVA::Event *>>
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 <typename T>
- RResultPtr<T> Fill(T &&model, const ColumnNames_t &bl)
+ RResultPtr<T> Fill(T &&model, const ColumnNames_t &columnList)
{
auto h = std::make_shared<T>(std::forward<T>(model));
if (!RDFInternal::HistoUtils<T>::HasAxisLimits(*h)) {
throw std::runtime_error("The absence of axes limits is not supported yet.");
}
- return CreateAction<RDFInternal::ActionTags::Fill, RDFDetail::RInferredType>(bl, h, bl.size());
+ return CreateAction<RDFInternal::ActionTags::Fill, RDFDetail::RInferredType>(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<RDisplay>` 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 <typename NodeType>
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<std::string> &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<arrow::Table> inTable, std::vector<std::string> 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