Object auto registration: Next steps

core/base/inc/TROOT.h

@@ -101,6 +101,7 @@ namespace ROOT {
    void EnableObjectAutoRegistration();
    void DisableObjectAutoRegistration();
    bool ObjectAutoRegistrationEnabled();
+   void SetObjectAutoRegistrationDefault(bool enabled);
    } // namespace Experimental
 }
 

core/base/src/TROOT.cxx

@@ -295,24 +295,29 @@ namespace {
       return moduleHeaderInfoBuffer;
    }
 
+   /// State helper for object auto registration.
    enum class AutoReg : unsigned char {
       kNotInitialised = 0,
       kOn,
       kOff,
    };
 
-   ////////////////////////////////////////////////////////////////////////////////
-   /// \brief Test if various objects (such as TH1-derived classes) should automatically register
-   /// themselves (ROOT 6 mode) or not (ROOT 7 mode).
-   /// A default can be set in a .rootrc using e.g. "Root.ObjectAutoRegistration: 1" or setting
-   /// the environment variable "ROOT_OBJECT_AUTO_REGISTRATION=0".
-   AutoReg &ObjectAutoRegistrationEnabledImpl()
+   /// Set or read the default state for object auto registration. This state is used to initialise the
+   /// auto-registration state for each thread that starts.
+   AutoReg ObjectAutoRegistrationDefault(AutoReg defaultState)
    {
       static constexpr auto rcName = "Root.ObjectAutoRegistration";    // Update the docs if this is changed
       static constexpr auto envName = "ROOT_OBJECT_AUTO_REGISTRATION"; // Update the docs if this is changed
-      thread_local static AutoReg tlsState = AutoReg::kNotInitialised;
+      static std::atomic<AutoReg> defaultFromAPI = AutoReg::kNotInitialised;
 
-      static const AutoReg defaultState = []() {
+      if (defaultState != AutoReg::kNotInitialised) {
+         defaultFromAPI = defaultState;
+      }
+      if (const auto apiDefault = defaultFromAPI.load(); apiDefault != AutoReg::kNotInitialised) {
+         return apiDefault;
+      }
+
+      static const AutoReg defaultFromEnvironment = []() {
          AutoReg autoReg = AutoReg::kOn; // ROOT 6 default
          std::stringstream infoMessage;
 
@@ -356,10 +361,18 @@ namespace {
          return autoReg;
       }();
 
-      if (tlsState == AutoReg::kNotInitialised) {
-         assert(defaultState != AutoReg::kNotInitialised);
-         tlsState = defaultState;
-      }
+      return defaultFromEnvironment;
+   }
+
+   ////////////////////////////////////////////////////////////////////////////////
+   /// \brief Test if various objects (such as TH1-derived classes) should automatically register
+   /// themselves (ROOT 6 mode) or not (ROOT 7 mode).
+   /// A default can be set in a .rootrc using e.g. "Root.ObjectAutoRegistration: 1" or setting
+   /// the environment variable "ROOT_OBJECT_AUTO_REGISTRATION=0".
+   AutoReg &ObjectAutoRegistrationEnabledImpl()
+   {
+      thread_local static AutoReg tlsState = ObjectAutoRegistrationDefault(AutoReg::kNotInitialised);
+      assert(tlsState != AutoReg::kNotInitialised);
 
       return tlsState;
    }
@@ -733,10 +746,14 @@ namespace Internal {
    ///
    /// ## Setting defaults
    ///
-   /// A default can be set in a .rootrc using e.g. `Root.ObjectAutoRegistration: 1` or setting
-   /// the environment variable `ROOT_OBJECT_AUTO_REGISTRATION=0`. Note that this default affects
-   /// all the threads that get started.
-   /// When a default is set using one of these methods, ROOT will notify with an Info message.
+   /// A default can be set (in order of precedence):
+   /// 1. Using \ref SetObjectAutoRegistrationDefault().
+   /// 2. Setting the environment variable `ROOT_OBJECT_AUTO_REGISTRATION=[01]`
+   /// 3. Setting `Root.ObjectAutoRegistration: [01]` in a .rootrc file.
+   ///
+   /// Note that this default affects all the threads that get started, but a running thread's behaviour
+   /// can only be changed using Enable/DisableObjectAutoRegistration().
+   /// When the default state is changed using the environment or .rootrc, ROOT issues a reminder.
    ///
    /// ## Difference to TH1::AddDirectoryStatus()
    ///
@@ -765,6 +782,16 @@ namespace Internal {
       assert(state != AutoReg::kNotInitialised);
       return state == AutoReg::kOn;
    }
+
+   ////////////////////////////////////////////////////////////////////////////////
+   /// Set default for object auto registration when a thread starts up.
+   /// Threads that are already running are *not* affected by this call, including
+   /// the calling thread.
+   /// \copydetails ROOT::Experimental::EnableObjectAutoRegistration()
+   void SetObjectAutoRegistrationDefault(bool enabled)
+   {
+      ObjectAutoRegistrationDefault(enabled ? AutoReg::kOn : AutoReg::kOff);
+   }
    } // namespace Experimental
 } // end of ROOT namespace
 

core/base/test/TROOTTests.cxx

@@ -87,7 +87,26 @@ TEST(TROOT, AutoRegistrationTLS)
    EnableObjectAutoRegistration();
    EXPECT_EQ(ObjectAutoRegistrationEnabled(), true);
 
-   for (auto thread : {&t1, &t2, &t3, &t4}) {
+   const bool stateBeforeJoin = ObjectAutoRegistrationEnabled();
+
+   for (auto *thread : {&t1, &t2, &t3, &t4}) {
       thread->join();
    }
+
+   auto testAPIDefault = [](bool expectedState){
+      EXPECT_EQ(ObjectAutoRegistrationEnabled(), expectedState);
+   };
+   SetObjectAutoRegistrationDefault(true);
+   std::thread t5{testAPIDefault, true};
+
+   EXPECT_EQ(ObjectAutoRegistrationEnabled(), stateBeforeJoin);
+
+   t5.join();
+
+   SetObjectAutoRegistrationDefault(false);
+   std::thread t6{testAPIDefault, false};
+
+   EXPECT_EQ(ObjectAutoRegistrationEnabled(), stateBeforeJoin);
+
+   t6.join();
 }

math/mlp/inc/TMultiLayerPerceptron.h

@@ -15,8 +15,8 @@
 #include "TObject.h"
 #include "TString.h"
 #include "TObjArray.h"
-#include "TMatrixD.h"
 #include "TNeuron.h"
+#include "TMatrixDfwd.h"
 
 class TTree;
 class TEventList;

math/mlp/src/TMLPAnalyzer.cxx

@@ -350,6 +350,8 @@ void TMLPAnalyzer::DrawNetwork(Int_t neuron, const char* signal, const char* bg)
    // build event lists for signal and background
    TEventList* signal_list = new TEventList("__tmpSig_MLPA");
    TEventList* bg_list     = new TEventList("__tmpBkg_MLPA");
+   signal_list->SetDirectory(gDirectory);
+   bg_list->SetDirectory(gDirectory);
    data->Draw(">>__tmpSig_MLPA",signal,"goff");
    data->Draw(">>__tmpBkg_MLPA",bg,"goff");
 

math/mlp/src/TMultiLayerPerceptron.cxx

@@ -242,6 +242,7 @@ neurons, hidden layers and inputs/outputs that does not apply to TMultiLayerPerc
 #include "TH2.h"
 #include "TGraph.h"
 #include "TLegend.h"
+#include "TMatrixD.h"
 #include "TMultiGraph.h"
 #include "TDirectory.h"
 #include "TSystem.h"
@@ -458,12 +459,12 @@ TMultiLayerPerceptron::TMultiLayerPerceptron(const char * layout, TTree * data,
    fCurrentTree = -1;
    fCurrentTreeWeight = 1;
    {
-      TDirectory::TContext ctxt;
+      TDirectory::TContext ctxt{nullptr};
       fTraining = new TEventList(Form("fTrainingList_%zu",(size_t)this));
    }
    fTrainingOwner = true;
    {
-      TDirectory::TContext ctxt;
+      TDirectory::TContext ctxt{nullptr};
       fTest = new TEventList(Form("fTestList_%zu",(size_t)this));
    }
    fTestOwner = true;
@@ -478,8 +479,12 @@ TMultiLayerPerceptron::TMultiLayerPerceptron(const char * layout, TTree * data,
    fManager = nullptr;
    if (data) {
       BuildNetwork();
+      fTraining->SetDirectory(gDirectory);
+      fTest->SetDirectory(gDirectory);
       data->Draw(Form(">>fTrainingList_%zu",(size_t)this),training,"goff");
       data->Draw(Form(">>fTestList_%zu",(size_t)this),(const char *)testcut,"goff");
+      fTraining->SetDirectory(nullptr);
+      fTest->SetDirectory(nullptr);
       AttachData();
    }
    else {
@@ -537,12 +542,12 @@ TMultiLayerPerceptron::TMultiLayerPerceptron(const char * layout,
    fCurrentTree = -1;
    fCurrentTreeWeight = 1;
    {
-      TDirectory::TContext ctxt;
+      TDirectory::TContext ctxt{nullptr};
       fTraining = new TEventList(Form("fTrainingList_%zu",(size_t)this));
    }
    fTrainingOwner = true;
    {
-      TDirectory::TContext ctxt;
+      TDirectory::TContext ctxt{nullptr};
       fTest = new TEventList(Form("fTestList_%zu",(size_t)this));
    }
    fTestOwner = true;
@@ -557,8 +562,12 @@ TMultiLayerPerceptron::TMultiLayerPerceptron(const char * layout,
    fManager = nullptr;
    if (data) {
       BuildNetwork();
+      fTraining->SetDirectory(gDirectory);
+      fTest->SetDirectory(gDirectory);
       data->Draw(Form(">>fTrainingList_%zu",(size_t)this),training,"goff");
       data->Draw(Form(">>fTestList_%zu",(size_t)this),(const char *)testcut,"goff");
+      fTraining->SetDirectory(nullptr);
+      fTest->SetDirectory(nullptr);
       AttachData();
    }
    else {
@@ -645,12 +654,14 @@ void TMultiLayerPerceptron::SetTrainingDataSet(const char * train)
 {
    if(fTraining && fTrainingOwner) delete fTraining;
    {
-      TDirectory::TContext ctxt;
+      TDirectory::TContext ctxt{nullptr};
       fTraining = new TEventList(Form("fTrainingList_%zu",(size_t)this));
    }
    fTrainingOwner = true;
    if (fData) {
+      fTraining->SetDirectory(gDirectory);
       fData->Draw(Form(">>fTrainingList_%zu",(size_t)this),train,"goff");
+      fTraining->SetDirectory(nullptr);
    }
    else {
       Warning("TMultiLayerPerceptron::TMultiLayerPerceptron","Data not set. Cannot define datasets");
@@ -672,7 +683,9 @@ void TMultiLayerPerceptron::SetTestDataSet(const char * test)
    }
    fTestOwner = true;
    if (fData) {
+            fTraining->SetDirectory(gDirectory);
       fData->Draw(Form(">>fTestList_%zu",(size_t)this),test,"goff");
+            fTraining->SetDirectory(nullptr);
    }
    else {
       Warning("TMultiLayerPerceptron::TMultiLayerPerceptron","Data not set. Cannot define datasets");

roottest/root/tree/cache/variableCluster.C

@@ -220,26 +220,13 @@ Long64_t checkBoundary(TTree *tree, Long64_t entry)
    TTree::TClusterIterator clusterIter = tree->GetClusterIterator(entry);
    fEntryCurrent = clusterIter();
    fEntryNext = clusterIter.GetNextEntry();
-   
+
 //   fprintf(stdout,"finds = %lld %lld\n",fEntryCurrent,fEntryNext);
-   
+
    if (fEntryCurrent < fEntryMin) fEntryCurrent = fEntryMin;
    if (fEntryMax <= 0) fEntryMax = tree->GetEntries();
    if (fEntryNext > fEntryMax) fEntryNext = fEntryMax;
-
-   // Check if owner has a TEventList set. If yes we optimize for this
-   // Special case reading only the baskets containing entries in the
-   // list.
-//   TEventList *elist = fOwner->GetEventList();
-//   Long64_t chainOffset = 0;
-//   if (elist) {
-//      if (fOwner->IsA() ==TChain::Class()) {
-//         TChain *chain = (TChain*)fOwner;
-//         Int_t t = chain->GetTreeNumber();
-//         chainOffset = chain->GetTreeOffset()[t];
-//      }
-//   }
-
+
    Int_t flushIntervals = 0;
    Long64_t minEntry = fEntryCurrent;
    Long64_t prevNtot;

tmva/tmva/src/Classification.cxx

@@ -34,7 +34,6 @@
 #include <TKey.h>
 #include <TLeaf.h>
 #include <TBranch.h>
-#include <TEventList.h>
 #include <TGraph.h>
 #include <TMatrixF.h>
 #include <TMatrixDSym.h>

tmva/tmva/src/DataInputHandler.cxx

@@ -36,12 +36,9 @@ Class that contains all the data information.
 #include "TMVA/DataLoader.h"
 #include "TMVA/MsgLogger.h"
 #include "TMVA/Types.h"
-#include "TEventList.h"
 #include "TCut.h"
 #include "TTree.h"
 
-#include "TMVA/Configurable.h"
-
 #include <vector>
 #include <fstream>
 

tmva/tmva/src/DataSetFactory.cxx

@@ -41,26 +41,17 @@ Class that contains all the data information
 #include <iostream>
 
 #include <algorithm>
-#include <functional>
-#include <numeric>
-#include <random>
 
 #include "TMVA/DataSetFactory.h"
 
-#include "TEventList.h"
 #include "TFile.h"
 #include "TRandom3.h"
-#include "TMatrixF.h"
-#include "TVectorF.h"
 #include "TMath.h"
 #include "TTree.h"
 #include "TBranch.h"
 
 #include "TMVA/MsgLogger.h"
 #include "TMVA/Configurable.h"
-#include "TMVA/VariableIdentityTransform.h"
-#include "TMVA/VariableDecorrTransform.h"
-#include "TMVA/VariablePCATransform.h"
 #include "TMVA/DataSet.h"
 #include "TMVA/DataSetInfo.h"
 #include "TMVA/DataInputHandler.h"

tmva/tmva/src/DataSetInfo.cxx

@@ -31,14 +31,8 @@ Class that contains all the data information.
 
 */
 
-#include <vector>
-
-#include "TEventList.h"
 #include "TH2.h"
-#include "TRandom3.h"
 #include "TMatrixF.h"
-#include "TVectorF.h"
-#include "TROOT.h"
 
 #include "TMVA/MsgLogger.h"
 #include "TMVA/Tools.h"
@@ -50,6 +44,8 @@ Class that contains all the data information.
 #include "TMVA/Types.h"
 #include "TMVA/VariableInfo.h"
 
+#include <vector>
+
 ////////////////////////////////////////////////////////////////////////////////
 /// constructor
 

tmva/tmva/src/Factory.cxx

@@ -71,26 +71,23 @@ evaluation phases.
 #include "TMVA/ResultsClassification.h"
 #include "TMVA/ResultsRegression.h"
 #include "TMVA/ResultsMulticlass.h"
-#include <list>
-#include <bitset>
-#include <set>
 
 #include "TMVA/Types.h"
 
 #include "TROOT.h"
 #include "TFile.h"
-#include "TLeaf.h"
-#include "TEventList.h"
 #include "TH2.h"
 #include "TGraph.h"
 #include "TStyle.h"
-#include "TMatrixF.h"
-#include "TMatrixDSym.h"
-#include "TMultiGraph.h"
 #include "TPrincipal.h"
 #include "TMath.h"
 #include "TSystem.h"
 #include "TCanvas.h"
+#include "TMultiGraph.h"
+
+#include <bitset>
+#include <list>
+#include <set>
 
 const Int_t MinNoTrainingEvents = 10;
 // const Int_t  MinNoTestEvents     = 1;

tmva/tmva/src/MethodTMlpANN.cxx

@@ -46,7 +46,6 @@ for details on this ANN.
 #include "TMVA/MethodTMlpANN.h"
 
 #include "TMVA/Config.h"
-#include "TMVA/Configurable.h"
 #include "TMVA/DataSet.h"
 #include "TMVA/DataSetInfo.h"
 #include "TMVA/IMethod.h"
@@ -58,8 +57,6 @@ for details on this ANN.
 #include "TMVA/ClassifierFactory.h"
 #include "TMVA/Tools.h"
 
-#include "TLeaf.h"
-#include "TEventList.h"
 #include "TROOT.h"
 #include "TMultiLayerPerceptron.h"
 #include "ThreadLocalStorage.h"