diff --git a/.github/workflows/BTA_workflow.yml b/.github/workflows/BTA_workflow.yml index 9dd29337..660fd2f0 100644 --- a/.github/workflows/BTA_workflow.yml +++ b/.github/workflows/BTA_workflow.yml @@ -3,13 +3,24 @@ name: BTA output Workflows on: push: branches: [ master ] + paths: + - 'src/BTVNanoCommissioning/workflows/*BTA*' + - 'src/BTVNanoCommissioning/helpers/*' + - 'src/BTVNanoCommissioning/utils/*' + - '.github/workflows/BTA_workflow.yml' pull_request_target: branches: [ master ] + paths: + - 'src/BTVNanoCommissioning/workflows/*BTA*' + - 'src/BTVNanoCommissioning/helpers/*' + - 'src/BTVNanoCommissioning/utils/*' + - '.github/workflows/BTA_workflow.yml' workflow_dispatch: jobs: build: runs-on: ubuntu-latest + if: ${{ !contains(github.event.head_commit.message, '[skip ci]') }} strategy: max-parallel: 4 matrix: diff --git a/.github/workflows/ctag_DY_workflow.yml b/.github/workflows/ctag_DY_workflow.yml index 098d7f7b..df36124c 100644 --- a/.github/workflows/ctag_DY_workflow.yml +++ b/.github/workflows/ctag_DY_workflow.yml @@ -3,13 +3,24 @@ name: ctag DY+jets Workflow on: push: branches: [ master ] + paths: + - 'src/BTVNanoCommissioning/workflows/ctag_*DY*' + - 'src/BTVNanoCommissioning/helpers/*' + - 'src/BTVNanoCommissioning/utils/*' + - '.github/workflows/ctag_DY_workflow.yml' pull_request_target: branches: [ master ] + paths: + - 'src/BTVNanoCommissioning/workflows/ctag_*DY*' + - 'src/BTVNanoCommissioning/helpers/*' + - 'src/BTVNanoCommissioning/utils/*' + - '.github/workflows/ctag_DY_workflow.yml' workflow_dispatch: jobs: build: runs-on: ubuntu-latest + if: ${{ !contains(github.event.head_commit.message, '[skip ci]') }} strategy: max-parallel: 4 matrix: @@ -87,9 +98,31 @@ jobs: - name: ctag muon DY workflows with correctionlib run: | - python runner.py --workflow ctag_DY_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --year 2022 --overwrite + string=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow ctag_DY_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --year 2022 $opts - name: ctag electron DY workflows with correctionlib run: | - python runner.py --workflow ectag_DY_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --year 2022 --overwrite + string=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow ectag_DY_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --year 2022 $opts diff --git a/.github/workflows/ctag_Wc_workflow.yml b/.github/workflows/ctag_Wc_workflow.yml index e18b38c1..a268aefc 100644 --- a/.github/workflows/ctag_Wc_workflow.yml +++ b/.github/workflows/ctag_Wc_workflow.yml @@ -3,13 +3,26 @@ name: ctag W+c Workflow on: push: branches: [ master ] + paths: + - 'src/BTVNanoCommissioning/workflows/ctag_*Wc*' + - 'src/BTVNanoCommissioning/helpers/*' + - 'src/BTVNanoCommissioning/utils/*' + - '.github/workflows/ctag_Wc_workflow.yml' + pull_request_target: branches: [ master ] + paths: + - 'src/BTVNanoCommissioning/workflows/ctag_*Wc*' + - 'src/BTVNanoCommissioning/helpers/*' + - 'src/BTVNanoCommissioning/utils/*' + - '.github/workflows/ctag_Wc_workflow.yml' + workflow_dispatch: jobs: build: runs-on: ubuntu-latest + if: ${{ !contains(github.event.head_commit.message, '[skip ci]') }} strategy: max-parallel: 4 matrix: @@ -52,7 +65,7 @@ jobs: conda info conda env list conda list - + - name: Set up proxy # https://awesome-workshop.github.io/gitlab-cms/03-vomsproxy/index.html # continue-on-error: true @@ -89,8 +102,30 @@ jobs: - name: ctag muon W+c workflows with correctionlib run: | - python runner.py --workflow ctag_Wc_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --overwrite + string=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow ctag_Wc_sf --json metadata/test_bta_run3.json --campaign Summer22Run3 --executor iterative $opts - name: ctag electron W+c workflows with correctionlib run: | - python runner.py --workflow ectag_Wc_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --overwrite \ No newline at end of file + message=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow ectag_Wc_sf --json metadata/test_bta_run3.json --executor iterative --campaign Summer22Run3 --overwrite $opts \ No newline at end of file diff --git a/.github/workflows/ctag_ttbar_workflow.yml b/.github/workflows/ctag_ttbar_workflow.yml new file mode 100644 index 00000000..50fd28de --- /dev/null +++ b/.github/workflows/ctag_ttbar_workflow.yml @@ -0,0 +1,172 @@ +name: ctag ttbar workflows + +on: + push: + branches: [ master ] + paths: + - 'src/BTVNanoCommissioning/workflows/ctag*tt*' + - 'src/BTVNanoCommissioning/helpers/*' + - 'src/BTVNanoCommissioning/utils/*' + - '.github/workflows/ctag_ttbar_workflow.yml' + pull_request_target: + branches: [ master ] + paths: + - 'src/BTVNanoCommissioning/workflows/ctag*tt*' + - 'src/BTVNanoCommissioning/helpers/*' + - 'src/BTVNanoCommissioning/utils/*' + - '.github/workflows/ctag_ttbar_workflow.yml' + workflow_dispatch: + +jobs: + build: + runs-on: ubuntu-latest + if: ${{ !contains(github.event.head_commit.message, '[skip ci]') }} + strategy: + max-parallel: 4 + matrix: + python-version: ["3.8","3.10"] + + defaults: + run: + shell: "bash -l {0}" + + steps: + - uses: actions/checkout@v2 + - name: update submodules + env: + SSHKEY: ${{ secrets.GIT_CERN_SSH_PRIVATE }} + run: | + mkdir $HOME/.ssh + echo "$SSHKEY" > $HOME/.ssh/id_rsa + chmod 600 $HOME/.ssh/id_rsa + echo "HOST *" > ~/.ssh/config + echo "StrictHostKeyChecking no" >> ~/.ssh/config + git submodule update --init --recursive + - uses: cvmfs-contrib/github-action-cvmfs@v2 + with: + cvmfs_repositories: 'grid.cern.ch' + + - name: Set conda environment + uses: conda-incubator/setup-miniconda@v2 + with: + python-version: ${{ matrix.python-version }} + miniforge-variant: Mambaforge + channels: conda-forge,defaults + channel-priority: true + activate-environment: btv_coffea + environment-file: test_env.yml + auto-activate-base: false + + - name: Verify environment + run: | + conda info + conda env list + conda list + + - name: Set up proxy + # https://awesome-workshop.github.io/gitlab-cms/03-vomsproxy/index.html + # continue-on-error: true + env: + # To genereate secrets use (strip all \n) + # base64 -i ~/.globus/usercert.pem | awk NF=NF RS= OFS= + # base64 -i ~/.globus/userkey.pem | awk NF=NF RS= OFS= + # Cross check roundtrip by adding ``| base64 -d `` and see if same as input + GRID_USERKEY: ${{ secrets.GRID_USERKEY }} + GRID_USERCERT: ${{ secrets.GRID_USERCERT }} + # Read automatically by voms-proxy-init + X509_VOMS_DIR: /cvmfs/grid.cern.ch/etc/grid-security/vomsdir/ + X509_VOMSES: /cvmfs/grid.cern.ch/etc/grid-security/vomses/ + X509_DEFAULT_USER_CERT: $HOME/.globus/usercert.pem + X509_DEFAULT_USER_KEY: $HOME/.globus/userkey.pem + run: | + mkdir $HOME/.globus + printf $GRID_USERKEY | base64 -d > $HOME/.globus/userkey.pem + printf $GRID_USERCERT | base64 -d > $HOME/.globus/usercert.pem + # DEBUG: dump decoded cert, cert is public, but don't dump key! + # base64 -i $HOME/.globus/usercert.pem + chmod 400 $HOME/.globus/userkey.pem + openssl rand -out $HOME/.rnd -hex 256 + printf "${{secrets.GRID_PASSWORD}}" | voms-proxy-init --voms cms --vomses ${X509_VOMSES} --debug --pwstdin + + - name: Test xrootd + run: | + xrdcp root://eoscms.cern.ch//eos/cms/store/group/phys_btag/nano-commissioning/test_w_dj.root . + + - name: Install Repo + run: | + pip install -e . + + + - name: ctag semileptonic muon ttbar workflows with correctionlib + run: | + string=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow ctag_ttsemilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 $opts + + - name: ctag semileptonic electron ttbar workflows with correctionlib + run: | + string=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow ectag_ttsemilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 $opts + + - name: ctag dileptonic muon ttbar workflows with correctionlib + run: | + string=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow ctag_ttdilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 $opts + - name: ctag dileptonic electron ttbar workflows with correctionlib + run: | + string=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow ectag_ttdilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 $opts + - name: ctag dileptonic emu ttbar workflows with correctionlib + run: | + string=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow emctag_ttdilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 $opts + diff --git a/.github/workflows/ttbar_DL_workflow.yml b/.github/workflows/ttbar_DL_workflow.yml deleted file mode 100644 index 01cb900c..00000000 --- a/.github/workflows/ttbar_DL_workflow.yml +++ /dev/null @@ -1,101 +0,0 @@ -name: ttbar dileptonic Workflows - -on: - push: - branches: [ master ] - pull_request_target: - branches: [ master ] - workflow_dispatch: - -jobs: - build: - runs-on: ubuntu-latest - strategy: - max-parallel: 4 - matrix: - python-version: ["3.8","3.10"] - - defaults: - run: - shell: "bash -l {0}" - - steps: - - uses: actions/checkout@v2 - - name: update submodules - env: - SSHKEY: ${{ secrets.GIT_CERN_SSH_PRIVATE }} - run: | - mkdir $HOME/.ssh - echo "$SSHKEY" > $HOME/.ssh/id_rsa - chmod 600 $HOME/.ssh/id_rsa - echo "HOST *" > ~/.ssh/config - echo "StrictHostKeyChecking no" >> ~/.ssh/config - git submodule update --init --recursive - - uses: cvmfs-contrib/github-action-cvmfs@v2 - with: - cvmfs_repositories: 'grid.cern.ch' - - - name: Set conda environment - uses: conda-incubator/setup-miniconda@v2 - with: - python-version: ${{ matrix.python-version }} - miniforge-variant: Mambaforge - channels: conda-forge,defaults - channel-priority: true - activate-environment: btv_coffea - environment-file: test_env.yml - auto-activate-base: false - - - name: Verify environment - run: | - conda info - conda env list - conda list - - - name: Set up proxy - # https://awesome-workshop.github.io/gitlab-cms/03-vomsproxy/index.html - # continue-on-error: true - env: - # To genereate secrets use (strip all \n) - # base64 -i ~/.globus/usercert.pem | awk NF=NF RS= OFS= - # base64 -i ~/.globus/userkey.pem | awk NF=NF RS= OFS= - # Cross check roundtrip by adding ``| base64 -d `` and see if same as input - GRID_USERKEY: ${{ secrets.GRID_USERKEY }} - GRID_USERCERT: ${{ secrets.GRID_USERCERT }} - # Read automatically by voms-proxy-init - X509_VOMS_DIR: /cvmfs/grid.cern.ch/etc/grid-security/vomsdir/ - X509_VOMSES: /cvmfs/grid.cern.ch/etc/grid-security/vomses/ - X509_DEFAULT_USER_CERT: $HOME/.globus/usercert.pem - X509_DEFAULT_USER_KEY: $HOME/.globus/userkey.pem - run: | - mkdir $HOME/.globus - printf $GRID_USERKEY | base64 -d > $HOME/.globus/userkey.pem - printf $GRID_USERCERT | base64 -d > $HOME/.globus/usercert.pem - # DEBUG: dump decoded cert, cert is public, but don't dump key! - # base64 -i $HOME/.globus/usercert.pem - chmod 400 $HOME/.globus/userkey.pem - openssl rand -out $HOME/.rnd -hex 256 - printf "${{secrets.GRID_PASSWORD}}" | voms-proxy-init --voms cms --vomses ${X509_VOMSES} --debug --pwstdin - - - name: Test xrootd - run: | - xrdcp root://eoscms.cern.ch//eos/cms/store/group/phys_btag/nano-commissioning/test_w_dj.root . - - - name: Install Repo - run: | - pip install -e . - - - name: btag dileptonic ttbar workflows with correctionlib - run: | - python runner.py --workflow ttdilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --overwrite - - - name: ctag dileptonic muon ttbar workflows with correctionlib - run: | - python runner.py --workflow ctag_ttdilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --overwrite - - name: ctag dileptonic electron ttbar workflows with correctionlib - run: | - python runner.py --workflow ectag_ttdilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --overwrite - - name: ctag dileptonic emu ttbar workflows with correctionlib - run: | - python runner.py --workflow emctag_ttdilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --overwrite - diff --git a/.github/workflows/ttbar_SL_workflow.yml b/.github/workflows/ttbar_workflow.yml similarity index 62% rename from .github/workflows/ttbar_SL_workflow.yml rename to .github/workflows/ttbar_workflow.yml index 0e63a796..d3a2e7d7 100644 --- a/.github/workflows/ttbar_SL_workflow.yml +++ b/.github/workflows/ttbar_workflow.yml @@ -1,15 +1,26 @@ -name: ttbar semileptonic Workflows +name: ttbar bSF semileptonic/dileptonic Workflows on: push: branches: [ master ] + paths: + - 'src/BTVNanoCommissioning/workflows/tt*' + - 'src/BTVNanoCommissioning/helpers/*' + - 'src/BTVNanoCommissioning/utils/*' + - '.github/workflows/ttbar_workflow.yml' pull_request_target: branches: [ master ] + paths: + - 'src/BTVNanoCommissioning/workflows/tt*' + - 'src/BTVNanoCommissioning/helpers/*' + - 'src/BTVNanoCommissioning/utils/*' + - '.github/workflows/ttbar_workflow.yml' workflow_dispatch: jobs: build: runs-on: ubuntu-latest + if: ${{ !contains(github.event.head_commit.message, '[skip ci]') }} strategy: max-parallel: 4 matrix: @@ -87,13 +98,32 @@ jobs: - name: btag semileptonic ttbar workflows with correctionlib run: | - python runner.py --workflow ttsemilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --overwrite + string=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow ttsemilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 $opts - - name: ctag semileptonic muon ttbar workflows with correctionlib - run: | - python runner.py --workflow ctag_ttsemilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --overwrite - - name: ctag semileptonic electron ttbar workflows with correctionlib + - name: btag dileptonic ttbar workflows with correctionlib run: | - python runner.py --workflow ectag_ttsemilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isSyst all --isArray --overwrite + string=$(git log -1 --pretty=format:'%s') + if [[ $string == *"ci:skip array"* ]]; then + opts=$(echo "$opts" | sed 's/--isArray //g') + fi + if [[ $string == *"ci:skip syst"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all//g') + elif [[ $string == *"ci:JERC_split"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst JERC_split/g') + elif [[ $string == *"ci:weight_only"* ]]; then + opts=$(echo "$opts" | sed 's/--isSyst all/--isSyst weight_only/g') + fi + python runner.py --workflow ttdilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 $opts diff --git a/README.md b/README.md index 57ca10a7..ddfd86bf 100644 --- a/README.md +++ b/README.md @@ -145,13 +145,13 @@ After a small test, you can run the full campaign for a dedicated phase space, s - Dileptonic ttbar phase space : check performance for btag SFs, emu channel ``` - python runner.py --workflow ttdilep_sf --json metadata/data_Summer22_emu_BTV_Run3_2022_Comm_v1.json --campaign Summer22Run3 --year 2022 (--executor ${scaleout_site}) + python runner.py --workflow ttdilep_sf --json metadata/data_Summer22_Run3_2022_em_BTV_Comm_v2_NanoV12_noPF.json --campaign Summer22Run3 --year 2022 (--executor ${scaleout_site}) ``` - Semileptonic ttbar phase space : check performance for btag SFs, muon channel ``` -python runner.py --workflow ttsemilep_sf --json metadata/data_Summer22_mu_BTV_Run3_2022_Comm_v1.json --campaign Summer22Run3 --year 2022 (--executor ${scaleout_site}) +python runner.py --workflow ttsemilep_sf --json metadata/data_Summer22_Run3_2022_mu_BTV_Comm_v2_NanoV12_noPF.json --campaign Summer22Run3 --year 2022 (--executor ${scaleout_site}) ```

@@ -164,26 +164,26 @@ python runner.py --workflow ttsemilep_sf --json metadata/data_Summer22_mu_BTV_Ru - Dileptonic ttbar phase space : check performance for charm SFs, bjets enriched SFs, muon channel ``` -python runner.py --workflow ctag_ttdilep_sf --json metadata/data_Summer22_mumu_BTV_Run3_2022_Comm_v1.json --campaign Summer22Run3 --year 2022(--executor ${scaleout_site}) +python runner.py --workflow ctag_ttdilep_sf --json metadata/data_Summer22_Run3_2022_mu_BTV_Comm_v2_NanoV12_noPF.json --campaign Summer22Run3 --year 2022(--executor ${scaleout_site}) ``` - Semileptonic ttbar phase space : check performance for charm SFs, bjets enriched SFs, muon channel ``` -python runner.py --workflow ctag_ttsemilep_sf --json metadata/data_Summer22_mu_BTV_Run3_2022_Comm_v1.json --campaign Summer22Run3 --year 2022(--executor ${scaleout_site}) +python runner.py --workflow ctag_ttsemilep_sf --json metadata/data_Summer22_Run3_2022_mu_BTV_Comm_v2_NanoV12_noPF.json --campaign Summer22Run3 --year 2022(--executor ${scaleout_site}) ``` - W+c phase space : check performance for charm SFs, cjets enriched SFs, muon channel ``` -python runner.py --workflow ctag_Wc_sf --json metadata/data_Summer22_mu_BTV_Run3_2022_Comm_v1.json --campaign Summer22Run3 --year 2022(--executor ${scaleout_site}) +python runner.py --workflow ctag_Wc_sf --json metadata/data_Summer22_Run3_2022_mu_BTV_Comm_v2_NanoV12_noPF.json --campaign Summer22Run3 --year 2022(--executor ${scaleout_site}) ``` - DY phase space : check performance for charm SFs, light jets enriched SFs, muon channel ``` -python runner.py --workflow ctag_DY_sf --json metadata/data_Summer22_mumu_BTV_Run3_2022_Comm_v1.json --campaign Summer22Run3 --year 2022(--executor ${scaleout_site}) +python runner.py --workflow ctag_DY_sf --json metadata/data_Summer22_Run3_2022_mu_BTV_Comm_v2_NanoV12_noPF.json --campaign Summer22Run3 --year 2022(--executor ${scaleout_site}) ```

@@ -338,6 +338,8 @@ After executing the command, a new folder will be created, preparing the submiss Use `fetch.py` in folder `scripts/` to obtain your samples json files. You can create `$input_list` ,which can be a list of datasets taken from CMS DAS , and create the json contains `dataset_name:[filelist]`. One can specify the local path in that input list for samples not published in CMS DAS. `$output_json_name$` is the name of your output samples json file. +The `--whitelist_sites, --blacklist_sites` are considered for fetch dataset if multiple sites are available + ``` ## File publish in DAS python fetch.py --input ${input_DAS_list} --output ${output_json_name} (--xrd {prefix_forsite}) @@ -450,10 +452,10 @@ The official correction files collected in [jsonpog-integration](https://gitlab. # JMAR, IDs from JME- Following the scheme: "${SF_name}": "${WP}" "JMAR": {"PUJetID_eff": "L"}, "LSF": { - # Electron SF - Following the scheme: "${SF_name} ${year}": "${WP}" + # Electron SF - Following the scheme: "${SF_name} ${SF_map} ${year}": "${WP}" # https://github.com/cms-egamma/cms-egamma-docs/blob/master/docs/EgammaSFJSON.md - "ele_ID 2017": "wp90iso", - "ele_Reco 2017": "RecoAbove20", + "ele_ID 2017 UL-Electron-ID-SF": "wp90iso", + "ele_Reco 2017 UL-Electron-ID-SF": "RecoAbove20", # Muon SF - Following the scheme: "${SF_name} ${year}": "${WP}" # WPs : ['NUM_GlobalMuons_DEN_genTracks', 'NUM_HighPtID_DEN_TrackerMuons', 'NUM_HighPtID_DEN_genTracks', 'NUM_IsoMu27_DEN_CutBasedIdTight_and_PFIsoTight', 'NUM_LooseID_DEN_TrackerMuons', 'NUM_LooseID_DEN_genTracks', 'NUM_LooseRelIso_DEN_LooseID', 'NUM_LooseRelIso_DEN_MediumID', 'NUM_LooseRelIso_DEN_MediumPromptID', 'NUM_LooseRelIso_DEN_TightIDandIPCut', 'NUM_LooseRelTkIso_DEN_HighPtIDandIPCut', 'NUM_LooseRelTkIso_DEN_TrkHighPtIDandIPCut', 'NUM_MediumID_DEN_TrackerMuons', 'NUM_MediumID_DEN_genTracks', 'NUM_MediumPromptID_DEN_TrackerMuons', 'NUM_MediumPromptID_DEN_genTracks', 'NUM_Mu50_or_OldMu100_or_TkMu100_DEN_CutBasedIdGlobalHighPt_and_TkIsoLoose', 'NUM_SoftID_DEN_TrackerMuons', 'NUM_SoftID_DEN_genTracks', 'NUM_TightID_DEN_TrackerMuons', 'NUM_TightID_DEN_genTracks', 'NUM_TightRelIso_DEN_MediumID', 'NUM_TightRelIso_DEN_MediumPromptID', 'NUM_TightRelIso_DEN_TightIDandIPCut', 'NUM_TightRelTkIso_DEN_HighPtIDandIPCut', 'NUM_TightRelTkIso_DEN_TrkHighPtIDandIPCut', 'NUM_TrackerMuons_DEN_genTracks', 'NUM_TrkHighPtID_DEN_TrackerMuons', 'NUM_TrkHighPtID_DEN_genTracks'] @@ -492,12 +494,15 @@ You can specify `-v all` to plot all the variables in the `coffea` file, or use :new: non-uniform rebinning is possible, specify the bins with list of edges `--autorebin 50,80,81,82,83,100.5` +```bash +python scripts/plotdataMC.py -i a.coffea,b.coffea --lumi 41500 -p ttdilep_sf -v z_mass,z_pt +python scripts/plotdataMC.py -i "test*.coffea" --lumi 41500 -p ttdilep_sf -v z_mass,z_pt # with wildcard option need "" +``` +
more arguments

``` -python plotdataMC.py -i a.coffea,b.coffea --lumi 41500 -p ttdilep_sf -v z_mass,z_pt -python plotdataMC.py -i "test*.coffea" --lumi 41500 -p ttdilep_sf -v z_mass,z_pt options: -h, --help show this help message and exit @@ -522,6 +527,9 @@ options: --xrange XRANGE custom x-range, --xrange xmin,xmax --flow FLOW str, optional {None, 'show', 'sum'} Whether plot the under/overflow bin. If 'show', add additional under/overflow bin. If 'sum', add the under/overflow bin content to first/last bin. + --split {flavor,sample,sample_flav} + Decomposition of MC samples. Default is split to jet flavor(udsg, pu, c, b), possible to split by group of MC + samples. Combination of jetflavor+ sample split is also possible ```

@@ -532,13 +540,18 @@ options: You can specify `-v all` to plot all the variables in the `coffea` file, or use wildcard options (e.g. `-v "*DeepJet*"` for the input variables containing `DeepJet`) :exclamation_mark: If using wildcard for input, do not forget the quoatation marks! (see 2nd example below) -
more arguments -

+```bash +# with merge map, compare ttbar with data +python scripts/comparison.py -i "*.coffea" --mergemap '{"ttbar": ["TTto2L2Nu_TuneCP5_13p6TeV_powheg-pythia8","TTto4Q_TuneCP5_13p6TeV_powheg-pythia8","TTtoLNu2Q_TuneCP5_13p6TeV_powheg-pythia8],"data":["MuonRun2022C-27Jun2023-v1","MuonRun2022D-27Jun2023-v1"]}' -r ttbar -c data -v mu_pt -p ttdilep_sf +# if no mergemap, take the key name directly +python scripts/comparison.py -i datac.coffea,datad.coffea -r MuonRun2022C-27Jun2023-v1 -c MuonRun2022D-27Jun2023-v1 -v mu_pt -p ttdilep_sf ``` -python comparison.py -i a.coffea,b.coffea -p ttsemilep_sf -r SingleMuon_Run2017B-106X_PFNanov1 -c DYJetsToLL_M-50_TuneCP5_13TeV-madgraphMLM-pythia8 -v DeepJet_Cpfcan_BtagPf_trackJetDistVal_0 --shortref Run2017B --shortcomp DYJets (--sepflav True/False) -python comparison.py -i "test*.coffea" -p ttsemilep_sf -r SingleMuon_Run2017B-106X_PFNanov1 -c DYJetsToLL_M-50_TuneCP5_13TeV-madgraphMLM-pythia8 -v DeepJet_Cpfcan_BtagPf_trackJetDistVal_0 --shortref Run2017B --shortcomp DYJets (--sepflav True/False) +

more arguments +

+ + ``` options: -h, --help show this help message and exit -p {dilep_sf,ttsemilep_sf,ctag_Wc_sf,ctag_DY_sf,ctag_ttsemilep_sf,ctag_ttdilep_sf}, --phase {dilep_sf,ttsemilep_sf,ctag_Wc_sf,ctag_DY_sf,ctag_ttsemilep_sf,ctag_ttdilep_sf} @@ -554,9 +567,8 @@ options: variables to plot, splitted by ,. Wildcard option * available as well. Specifying `all` will run through all variables. --ext EXT prefix name --com COM sqrt(s) in TeV - --shortref SHORTREF short name for reference dataset for legend - --shortcomp SHORTCOMP - short names for compared datasets for legend, split by ',' + --mergemap MERGEMAP + Group list of sample(keys in coffea) as reference/compare set as dictionary format. Keys would be the new lables of the group --autorebin AUTOREBIN Rebin the plotting variables, input `int` or `list`. int: merge N bins. list of number: rebin edges(non-uniform bin is possible) --xlabel XLABEL rename the label for x-axis @@ -628,8 +640,20 @@ Yout can find the secret configuration in the direcotry : `Settings>>Secrets>>Ac 1. Create a ssh key pair with `ssh-keygen -t rsa -b 4096` (do not overwrite with your local one), add the public key to your CERN gitlab account 2. Copy the private key to the entry - `GRID_PASSWORD`: Add your grid password to the entry. -- `GRID_USERCERT` & `GRID_USERKEY`: Encrypt your grid user certification `base64 -i ~/.globus/userkey.pem` and `base64 -i ~/.globus/usercert.pem` and copy the output to the entry. +- `GRID_USERCERT` & `GRID_USERKEY`: Encrypt your grid user certification `base64 -i ~/.globus/userkey.pem | awk NF=NF RS= OFS=` and `base64 -i ~/.globus/usercert.pem | awk NF=NF RS= OFS=` and copy the output to the entry. +Special commit head messages could run different commands in actions (add the flag in front of your commit) +The default configureation is doing +``` +python runner.py --workflow emctag_ttdilep_sf --json metadata/test_bta_run3.json --limit 1 --executor iterative --campaign Summer22Run3 --isArray --isSyst all +``` + +- `[skip ci]`: not running ci at all in the commit message +- `ci:skip array` : remove `--isArray` option +- `ci:skip syst` : remove `--isSyst all` option +- `ci:JERC_split` : change systematic option to split JERC uncertainty sources `--isSyst JERC_split` +- `ci:weight_only` : change systematic option to weight only variations `--isSyst weight_only` + ### Running jupyter remotely 1. On your local machine, edit `.ssh/config`: ``` @@ -649,4 +673,3 @@ Host *_f jupyter notebook --ip=127.0.0.1 --port 8800 --no-browser ``` 4. URL for notebook will be printed, copy and open in local browser - diff --git a/condor/execute.sh b/condor/execute.sh index 7eb13e14..5da7a440 100755 --- a/condor/execute.sh +++ b/condor/execute.sh @@ -32,7 +32,7 @@ fi # Get arguments declare -A ARGS -for key in workflow output samplejson year campaign isCorr isSyst isJERC isArray noHist overwrite voms chunk retries outputXrootdDir remoteRepo; do +for key in workflow output samplejson year campaign isSyst isArray noHist overwrite voms chunk skipbadfiles outputXrootdDir remoteRepo; do ARGS[$key]=$(jq -r ".$key" $WORKDIR/arguments.json) done @@ -58,11 +58,11 @@ pip install psutil python -c "import json; json.dump(json.load(open('$WORKDIR/split_samples.json'))['$JOBID'], open('sample.json', 'w'), indent=4)" # Unparse arguments and send to runner.py -OPTS="--wf ${ARGS[workflow]} --year ${ARGS[year]} --campaign ${ARGS[campaign]} --chunk ${ARGS[chunk]} --retries ${ARGS[retries]}" +OPTS="--wf ${ARGS[workflow]} --year ${ARGS[year]} --campaign ${ARGS[campaign]} --chunk ${ARGS[chunk]}" if [ "${ARGS[voms]}" != "null" ]; then OPTS="$OPTS --voms ${ARGS[voms]}" fi -for key in isCorr isSyst isJERC isArray noHist overwrite; do +for key in isSyst isArray noHist overwrite skipbadfiles; do if [ "${ARGS[$key]}" == true ]; then OPTS="$OPTS --$key" fi @@ -78,12 +78,17 @@ python runner.py $OPTS # Transfer output if [[ ${ARGS[outputXrootdDir]} == root://* ]]; then - xrdcp --silent -p -f *.coffea ${ARGS[outputXrootdDir]}/ - xrdcp --silent -p -f *.root ${ARGS[outputXrootdDir]}/ + + xrdcp --silent -p -f -r hists_* ${ARGS[outputXrootdDir]}/ + if [[ "$OPTS" == *"isArray"* ]]; then + xrdcp --silent -p -f -r arrays_* ${ARGS[outputXrootdDir]}/ + fi else mkdir -p ${ARGS[outputXrootdDir]} - cp -p -f *.coffea ${ARGS[outputXrootdDir]}/ - cp -p -f *.root ${ARGS[outputXrootdDir]}/ + cp -p -f -r hists_* ${ARGS[outputXrootdDir]}/ + if [[ "$OPTS" == *"isArray"* ]]; then + cp -p -f -r arrays_* ${ARGS[outputXrootdDir]}/ + fi fi ### one can also consider origanizing the root files in the subdirectory structure ### diff --git a/condor/submitter.py b/condor/submitter.py index aaf99ecf..8ae104fd 100644 --- a/condor/submitter.py +++ b/condor/submitter.py @@ -81,7 +81,6 @@ def get_main_parser(): ], help="Dataset campaign, change the corresponding correction files", ) - parser.add_argument("--isCorr", action="store_true", help="Run with SFs") parser.add_argument( "--isSyst", default=None, @@ -89,17 +88,20 @@ def get_main_parser(): choices=[None, "all", "weight_only", "JERC_split"], help="Run with systematics, all, weights_only(no JERC uncertainties included),JERC_split, None", ) - parser.add_argument( - "--isJERC", action="store_true", help="JER/JEC implemented to jet" - ) parser.add_argument("--isArray", action="store_true", help="Output root files") + parser.add_argument( "--noHist", action="store_true", help="Not output coffea histogram" ) parser.add_argument( "--overwrite", action="store_true", help="Overwrite existing files" ) - + parser.add_argument( + "--only", + type=str, + default=None, + help="Only process/skip part of the dataset. By input list of file", + ) parser.add_argument( "--voms", default=None, @@ -114,13 +116,7 @@ def get_main_parser(): metavar="N", help="Number of events per process chunk", ) - parser.add_argument( - "--retries", - type=int, - default=25, - metavar="N", - help="Number of retries for coffea processor", - ) + parser.add_argument("--skipbadfiles", action="store_true", help="Skip bad files.") parser = get_condor_submitter_parser(parser) return parser @@ -182,7 +178,20 @@ def get_main_parser(): sample_dict = json.load(f) split_sample_dict = {} counter = 0 + only = [] + if args.only is not None: + if "*" in args.only: + only = [ + k + for k in sample_dict.keys() + if k.lstrip("/").startswith(args.only.rstrip("*")) + ] + else: + only.append(args.only) + for sample_name, files in sample_dict.items(): + if len(only) != 0 and sample_name not in only: + continue for ifile in range( (len(files) + args.condorFileSize - 1) // args.condorFileSize ): diff --git 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"root://cmsxrootd-kit.gridka.de:1094///store/user/milee/PFNano_Run3/data_2022FG_prompt/JetMET/Run2022F-PromptReco-v1_BTV_Run3_2022_Comm_v2_NANOV11/230830_214859/0000/nano_data2022FG_20.root" + "JetMETRun2022D-27Jun2023-v2": [ + "root://eoscms.cern.ch//eos/cms/store/group/cmst3/group/deepjet/PFNano_Run3_v12/data_2022CDE_rereco_JetMET/JetMET/Run2022D-27Jun2023-v2_BTV_Run3_2022_Comm_v2_NanoV12/230927_120318/0000/nano_data2022CDE_135.root" ], - "TTto4Q_TuneCP5_13p6TeV_powheg-pythia8":["root://eoscms.cern.ch//eos/cms/store/user/coli/PFNano/2022/mc/TTto4Q_TuneCP5_13p6TeV_powheg-pythia8/PFNano_v1_Run3Summer22MiniAODv3-124X_v12-v4/230629_163448/0000/nano_mcRun3_8.root"] - + "QCD_PT-120to170_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8":[ + "root://eoscms.cern.ch//store/group/phys_btag/PFNano_Run3/mc_summer22EE/QCD_PT-120to170_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8/Run3Summer22EEMiniAODv3-124X_mcRun3_2022_realistic_postEE_v1-v1_BTV_Run3_2022_Comm_v2_NanoV12/231001_184438/0000/nano_mcRun3_EE_1-1.root" + ] } diff --git a/runner.py b/runner.py index c834017c..6141d600 100644 --- a/runner.py +++ b/runner.py @@ -224,10 +224,20 @@ def get_main_parser(): args = parser.parse_args() print("Running with the following options:") print(args) + ogoutput = args.output + histoutdir = ogoutput.split(".")[0] + coffeaoutput = f"{histoutdir}/{ogoutput}" + outdir = histoutdir + basename = ogoutput.replace(".coffea", "").replace("hists_", "") if args.output == parser.get_default("output"): index = args.samplejson.rfind("/") + 1 sample_json = args.samplejson[index:] - args.output = f'hists_{args.workflow}_{(sample_json).rstrip(".json")}.coffea' + histoutdir = f"hists_{args.workflow}_{sample_json.rstrip('.json')}" + outdir = f"arrays_{args.workflow}_{sample_json.rstrip('.json')}" + coffeaoutput = ( + f'{histoutdir}/hists_{args.workflow}_{(sample_json).rstrip(".json")}.coffea' + ) + os.system(f"mkdir -p {histoutdir}") # load dataset with open(args.samplejson) as f: sample_dict = json.load(f) @@ -249,7 +259,19 @@ def get_main_parser(): if args.only is not None: if args.only in sample_dict.keys(): # is dataset sample_dict = dict([(args.only, sample_dict[args.only])]) - if "*" in args.only: # wildcard for datasets + coffeaoutput = coffeaoutput.replace(".coffea", f"_{key}.coffea") + elif args.only.isdigit(): + isamp = int(args.only) + nsamp = len(sample_dict.keys()) + if isamp >= nsamp: + print( + f"There are {nsamp} datasets, please use --only n with n<{nsamp}." + ) + key = list(sample_dict.keys())[isamp] + print(f"Will process only {key} instead of all {nsamp} datasets.") + sample_dict = dict([(key, sample_dict[key])]) + coffeaoutput = coffeaoutput.replace(".coffea", f"_{key}.coffea") + elif "*" in args.only: # wildcard for datasets _new_dict = {} print("Will only proces the following datasets:") for k, v in sample_dict.items(): @@ -311,7 +333,7 @@ def get_main_parser(): processor_instance = workflows[args.workflow]( args.year, args.campaign, - args.output.replace(".coffea", "").replace("hists_", ""), + outdir, args.isSyst, args.isArray, args.noHist, @@ -321,30 +343,14 @@ def get_main_parser(): ## create tmp directory and check file exist or not from os import path - if path.exists(f"{args.output}") and args.overwrite == False: - raise Exception(f"{args.output} exists") + if path.exists(f"{coffeaoutput}") and args.overwrite == False: + raise Exception(f"{coffeaoutput} exists") + if args.isArray: - ## create the directory - if ( - path.exists(args.output.replace(".coffea", "").replace("hists_", "")) - and args.overwrite == False - ): + if path.exists(outdir) and args.overwrite == False and args.only is None: raise Exception("Directory exists") else: - if path.exists( - path.exists(args.output.replace(".coffea", "").replace("hists_", "")) - ): - os.system( - f'rm -r {args.output.replace(".coffea", "").replace("hists_", "")}' - ) - else: - os.system( - f'mkdir -p {args.output.replace(".coffea", "").replace("hists_", "")}' - ) - for dataset in sample_dict.keys(): - os.system( - f"mkdir -p {args.workflow}_{(sample_json).rstrip('.json')}/{dataset}" - ) + os.system(f"mkdir -p {outdir}") if args.executor not in ["futures", "iterative", "dask/lpc", "dask/casa"]: """ @@ -687,7 +693,6 @@ def get_main_parser(): worker_extra_args=["--worker-port 10000:10100"], job_script_prologue=job_script_prologue, ) - print("setting here is correct") elif "slurm" in args.executor: cluster = SLURMCluster( queue="all", @@ -780,13 +785,13 @@ def get_main_parser(): if args.noHist == False: save( output, - args.output.replace( + coffeaoutput.replace( ".coffea", f"_{sindex}_{findex}.coffea" ), ) if not "lxplus" in args.executor: if args.noHist == False: - save(output, args.output) + save(output, coffeaoutput) if args.noHist == False: # print(output) - print(f"Saving output to {args.output}") + print(f"Saving output to {coffeaoutput}") diff --git a/scripts/comparison.py b/scripts/comparison.py index 07c2cd74..c0463c83 100644 --- a/scripts/comparison.py +++ b/scripts/comparison.py @@ -1,5 +1,5 @@ import numpy as np -import argparse, os, arrow, glob +import argparse, os, arrow, glob, json, re from coffea.util import load import matplotlib.pyplot as plt from matplotlib.offsetbox import AnchoredText @@ -64,18 +64,12 @@ help="str, optional {None, 'show', 'sum'} Whether plot the under/overflow bin. If 'show', add additional under/overflow bin. If 'sum', add the under/overflow bin content to first/last bin.", ) parser.add_argument("--ext", type=str, default="", help="prefix name/btv name tag") -parser.add_argument("--com", default="13", type=str, help="sqrt(s) in TeV") +parser.add_argument("--com", default="13.6", type=str, help="sqrt(s) in TeV") parser.add_argument( - "--shortref", - default="", - type=str, - help="short name for reference dataset for legend", -) -parser.add_argument( - "--shortcomp", - default="", + "--mergemap", + default=None, type=str, - help="short names for compared datasets for legend, split by ','", + help="Group list of sample(keys in coffea) as reference/compare set as dictionary format. Keys would be the new lables of the group", ) parser.add_argument( "--autorebin", @@ -109,21 +103,24 @@ time = arrow.now().format("YY_MM_DD") if not os.path.isdir(f"plot/BTV/{args.phase}_{args.ext}_{time}/"): os.makedirs(f"plot/BTV/{args.phase}_{args.ext}_{time}/") -if not any(".coffea" in o for o in output.keys()): - mergemap[args.ref] = [m for m in output.keys() if args.ref == m] - for c in args.compared.split(","): - mergemap[c] = [m for m in output.keys() if c == m] -else: - reflist = [] - for f in output.keys(): - reflist.extend([m for m in output[f].keys() if args.ref == m]) - mergemap[args.ref] = reflist - - for c in args.compared.split(","): - comparelist = [] +if args.mergemap is None: + if not any(".coffea" in o for o in output.keys()): + mergemap[args.ref] = [m for m in output.keys() if args.ref == m] + for c in args.compared.split(","): + mergemap[c] = [m for m in output.keys() if c == m] + else: + reflist = [] for f in output.keys(): - comparelist.extend([m for m in output[f].keys() if c == m]) - mergemap[c] = comparelist + reflist.extend([m for m in output[f].keys() if args.ref == m]) + mergemap[args.ref] = reflist + + for c in args.compared.split(","): + comparelist = [] + for f in output.keys(): + comparelist.extend([m for m in output[f].keys() if c == m]) + mergemap[c] = comparelist +else: + mergemap = json.loads(args.mergemap) collated = collate(output, mergemap) ### style settings if "Run" in args.ref: @@ -160,20 +157,34 @@ input_txt = input_txt + " ($\mu$)" if "ctag" in args.phase and "DY" not in args.phase: input_txt = input_txt + "\nw/ soft-$\mu$" -if args.shortref == "": - args.shortref = args.ref -if args.shortcomp == "": - args.shortcomp = args.compared if args.variable == "all": var_set = collated[args.ref].keys() elif "*" in args.variable: - var_set = [ - var - for var in collated[args.ref].keys() - if args.variable.replace("*", "") in var - ] + if args.variable.count("*") > 1: + var_set = [ + var + for var in collated[args.ref].keys() + if args.variable.replace("*", "") in var + ] + elif args.variable.startswith("*") or args.variable.endswith("*"): + var_set = [ + var + for var in collated[args.ref].keys() + if var.startswith(args.variable.replace("*", "")) + or var.endswith(args.variable.replace("*", "")) + ] + else: + var_set = [ + var + for var in collated[args.ref].keys() + if re.match( + f"^{args.variable.split('*')[0]}.*{args.variable.split('*')[1]}$", var + ) + != None + ] + else: var_set = args.variable.split(",") for index, discr in enumerate(var_set): @@ -269,70 +280,70 @@ hep.histplot( collated[args.ref][discr][laxis] + collated[args.ref][discr][puaxis], - label=args.shortref + "-l", + label=args.ref + "-l", color="b", histtype=hist_type, yerr=True, ax=ax, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) hep.histplot( collated[args.ref][discr][caxis], - label=args.shortref + "-c", + label=args.ref + "-c", color="g", histtype=hist_type, yerr=True, ax=ax, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) hep.histplot( collated[args.ref][discr][baxis], - label=args.shortref + "-b", + label=args.ref + "-b", yerr=True, color="r", histtype=hist_type, ax=ax, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) mindex = 0 ax.legend(ncol=3, loc=1) - for c, s in zip(args.compared.split(","), args.shortcomp.split(",")): + for c in args.compared.split(","): hep.histplot( collated[c][discr][laxis] + collated[c][discr][puaxis], - label=s + "-l", + label=c + "-l", color="b", marker=markers[mindex + 1], histtype="errorbar", yerr=True, ax=ax, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) hep.histplot( collated[c][discr][caxis], - label=s + "-c", + label=c + "-c", color="g", marker=markers[mindex + 1], histtype="errorbar", yerr=True, ax=ax, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) hep.histplot( collated[c][discr][baxis], - label=s + "-b", + label=c + "-b", yerr=True, color="r", marker=markers[mindex + 1], histtype="errorbar", ax=ax, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) # comparison splitted by flavor rax = plotratio( @@ -342,8 +353,8 @@ denom_fill_opts=None, error_opts={"color": "b", "marker": markers[mindex + 1]}, clear=False, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) rax2 = plotratio( collated[c][discr][caxis], @@ -352,8 +363,8 @@ denom_fill_opts=None, error_opts={"color": "g", "marker": markers[mindex + 1]}, clear=False, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) rax3 = plotratio( collated[c][discr][baxis], @@ -362,8 +373,8 @@ denom_fill_opts=None, error_opts={"color": "r", "marker": markers[mindex + 1]}, clear=False, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) mindex += 1 @@ -400,37 +411,36 @@ ax.set_xlabel(None) hep.histplot( collated[args.ref][discr][allaxis], - label=args.shortref + " (Ref)", + label=args.ref + " (Ref)", histtype=hist_type, yerr=True, ax=ax, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) - for c, s in zip(args.compared.split(","), args.shortcomp.split(",")): + + for i, c in enumerate(args.compared.split(",")): hep.histplot( collated[c][discr][allaxis], - label=s, + label=c, histtype=hist_type, yerr=True, ax=ax, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) - for i, c in enumerate(args.compared.split(",")): plotratio( collated[c][discr][allaxis], collated[args.ref][discr][allaxis], ax=rax, denom_fill_opts=None, - error_opts={"color": ax.get_lines()[i * 2 + 1].get_color()}, + error_opts={"color": ax.get_lines()[i + 1].get_color()}, clear=False, - xerr=do_xerr - # flow=args.flow, + xerr=do_xerr, + flow=args.flow, ) ## No error band used alls = collated[args.ref][discr][allaxis] - for c in args.compared.split(","): - alls = collated[c][discr][allaxis] + alls + xmin, xmax = autoranger(alls) rax.set_xlim(xmin, xmax) if args.xrange is not None: diff --git a/scripts/fetch.py b/scripts/fetch.py index 75e9c9e0..615d2481 100644 --- a/scripts/fetch.py +++ b/scripts/fetch.py @@ -1,7 +1,10 @@ import sys -from os import popen, listdir, makedirs, path, system +import os import json import argparse +from collections import defaultdict +import uproot +import numpy as np # Adapt some developments from Andrey Pozdnyakov in CoffeaRunner https://github.com/cms-rwth/CoffeaRunner/blob/master/filefetcher/fetch.py parser = argparse.ArgumentParser( @@ -23,9 +26,9 @@ ) parser.add_argument( "--xrd", - default="root://xrootd-cms.infn.it//", + default=None, type=str, - help="xrootd prefix string (default: %(default)s)", + help="xrootd prefix string otherwise get from available sites", ) parser.add_argument( @@ -34,11 +37,65 @@ help="For samples that are not published on DAS. If this option is set then the format of the --input file must be adjusted. It should be: \n dataset_name path_to_files.", default=False, ) +parser.add_argument( + "--whitelist_sites", + help="White list fot sites", + default=None, +) +parser.add_argument( + "--blacklist_sites", + help="Black list for sites", + default=None, +) +parser.add_argument( + "--save_", + help="Black list for sites", + default=None, +) + args = parser.parse_args() -# Adapt +# Based on https://github.com/PocketCoffea/PocketCoffea/blob/main/pocket_coffea/utils/rucio.py +def get_xrootd_sites_map(): + sites_xrootd_access = defaultdict(dict) + if not os.path.exists(".sites_map.json"): + print("Loading SITECONF info") + sites = [ + (s, "/cvmfs/cms.cern.ch/SITECONF/" + s + "/storage.json") + for s in os.listdir("/cvmfs/cms.cern.ch/SITECONF/") + if s.startswith("T") + ] + for site_name, conf in sites: + if not os.path.exists(conf): + continue + try: + data = json.load(open(conf)) + except: + continue + for site in data: + if site["type"] != "DISK": + continue + if site["rse"] == None: + continue + for proc in site["protocols"]: + if proc["protocol"] == "XRootD": + if proc["access"] not in ["global-ro", "global-rw"]: + continue + if "prefix" not in proc: + if "rules" in proc: + for rule in proc["rules"]: + sites_xrootd_access[site["rse"]][ + rule["lfn"] + ] = rule["pfn"] + else: + sites_xrootd_access[site["rse"]] = proc["prefix"] + json.dump(sites_xrootd_access, open(".sites_map.json", "w")) + + return json.load(open(".sites_map.json")) + + def getFilesFromDas(args): fset = [] with open(args.input) as fp: @@ -47,25 +104,39 @@ def getFilesFromDas(args): fset.append(line) fdict = {} - + if args.blacklist_sites is not None: + args.blacklist_sites = args.blacklist_sites.split(",") + print("blacklist sites:", args.blacklist_sites) + if args.whitelist_sites is not None: + args.whitelist_sites = args.whitelist_sites.split(",") + print("whitelist sites:", args.whitelist_sites) for dataset in fset: if dataset.startswith("#") or dataset.strip() == "": - # print("we skip this line:", line) continue dsname = dataset.strip().split("/")[1] # Dataset first name - Tier = dataset.strip().split("/")[ - 3 - ] # NANOAODSIM for regular samples, USER for private - if "SIM" not in Tier: - dsname = dataset.strip().split("/")[1] + "_" + dataset.split("/")[2] + Tier = dataset.strip().split("/")[3] + # NANOAODSIM for regular samples, USER for private + if "Run" in dataset and "pythia8" not in dataset: + dsname = ( + dataset.strip().split("/")[1] + + dataset.strip().split("/")[2][ + dataset.strip() + .split("/")[2] + .find("Run") : dataset.strip() + .split("/")[2] + .rfind("-") + ] + ) + dsname = dsname[: dsname.find("_BTV")] + # +dataset.strip().split("/")[2].find("Run") instance = "prod/global" if Tier == "USER": instance = "prod/phys03" print("Creating list of files for dataset", dsname, Tier, instance) flist = ( - popen( + os.popen( ( "/cvmfs/cms.cern.ch/common/dasgoclient -query='instance={} file dataset={}'" ).format(instance, fset[fset.index(dataset)].rstrip()) @@ -73,13 +144,61 @@ def getFilesFromDas(args): .read() .split("\n") ) + import json + + dataset = dataset[:-1] if "\n" in dataset else dataset + fetchsite = json.loads( + ( + os.popen( + f"/cvmfs/cms.cern.ch/common/dasgoclient -query='instance={instance} dataset={dataset} site' -json" + ).read() + ) + ) + + if instance == "prod/phys03": + possible_sites = [fetchsite[0]["site"][0]["name"]] + else: + possible_sites = [ + s["site"][0]["name"] + for s in fetchsite + if (s["site"][0]["replica_fraction"] == "100.00%") + & (s["site"][0]["block_completion"] == "100.00%") + & (s["site"][0]["kind"] == "DISK") + ] + + sites_xrootd_prefix = get_xrootd_sites_map() + xrd = None + + if args.xrd == None: + if args.whitelist_sites is not None: + # get first site in whitelist_site + for w_site in args.whitelist_sites: + if xrd is not None: + break + for site in possible_sites: + if site == w_site and type(sites_xrootd_prefix[site]) == str: + xrd = sites_xrootd_prefix[site] + else: + for site in possible_sites: + if ( + args.blacklist_sites is not None + and site in args.blacklist_sites + ): + continue + # get first site in possible_sites + elif type(sites_xrootd_prefix[site]) == str: + xrd = sites_xrootd_prefix[site] + else: + xrd = args.xrd + + if xrd is None: + raise Exception(f"No SITE available in the whitelist for file {dsname}") if dsname not in fdict: - fdict[dsname] = [args.xrd + f for f in flist if len(f) > 1] + fdict[dsname] = [xrd + f for f in flist if len(f) > 1] else: # needed to collect all data samples into one common key "Data" (using append() would introduce a new element for the key) - fdict[dsname].extend([args.xrd + f for f in flist if len(f) > 1]) + fdict[dsname].extend([xrd + f for f in flist if len(f) > 1]) - # pprint.pprint(fdict, depth=1) return fdict @@ -116,18 +235,17 @@ def getRootFilesFromPath(d, lim=None): allfiles = str( subprocess.check_output(["xrdfs", siteIP, "ls", pathToFiles]), "utf-8" ).split("\n") - # rootfiles = [siteIP+'/'+f for i,f in enumerate(allfiles) if f.endswith(".root") and (lim==None or i 0: + bad_sample_dict[sample] = all_invalid + f.write(f"{sample} Events: {np.sum(counts)}\n") + + if len(all_invalid) == 0: + f.write("No bad files found!") + else: + print(f"Found {len(all_invalid)} bad files.") + f.write(f"Found {len(all_invalid)} bad files.") + if remove_bad == True: + f.write( + "\n==========================BAD FILES==========================\n " + ) + + for sample in bad_sample_dict.keys(): + for bad_file in bad_sample_dict[sample]: + f.write(bad_file + "\n") + if bad_file[bad_file.find("root://") :] in sample_dict[sample]: + sample_dict[sample].remove(bad_file[bad_file.find("root://") :]) + + return sample_dict + + def main(args): if args.from_path: print("do it from path: ") @@ -168,6 +341,7 @@ def main(args): empty = False assert empty, "you have empty lists" output_file = "./%s" % (args.output) + fdict = remove_bad_files(fdict, args.output, True) # remove bad files with open(output_file, "w") as fp: json.dump(fdict, fp, indent=4) print("The file is saved at: ", output_file) diff --git a/scripts/plotdataMC.py b/scripts/plotdataMC.py index 1a4b621c..f69ff6de 100644 --- a/scripts/plotdataMC.py +++ b/scripts/plotdataMC.py @@ -1,5 +1,5 @@ import numpy as np -import argparse, os, arrow, glob +import argparse, os, arrow, glob, re from coffea.util import load import matplotlib.pyplot as plt from matplotlib.offsetbox import AnchoredText @@ -16,13 +16,15 @@ MCerrorband, autoranger, rebin_hist, + sample_mergemap, + color_map, ) bininfo = definitions() SV_bininfo = SV_definitions() parser = argparse.ArgumentParser(description="hist plotter for commissioning") parser.add_argument("--lumi", required=True, type=float, help="luminosity in /pb") -parser.add_argument("--com", default="13", type=str, help="sqrt(s) in TeV") +parser.add_argument("--com", default="13.6", type=str, help="sqrt(s) in TeV") parser.add_argument( "-p", "--phase", @@ -77,6 +79,13 @@ default="show", help="str, optional {None, 'show', 'sum'} Whether plot the under/overflow bin. If 'show', add additional under/overflow bin. If 'sum', add the under/overflow bin content to first/last bin.", ) +parser.add_argument( + "--split", + type=str, + default="flavor", + choices=["flavor", "sample", "sample_flav"], + help="Decomposition of MC samples. Default is split to jet flavor, possible to split by group of MC samples. Combination of jetflavor+ sample split is also possible", +) parser.add_argument( "--splitOSSS", type=int, @@ -85,21 +94,23 @@ ) -arg = parser.parse_args() +args = parser.parse_args() time = arrow.now().format("YY_MM_DD") -if not os.path.isdir(f"plot/BTV/{arg.phase}_{arg.ext}_{time}/"): - os.makedirs(f"plot/BTV/{arg.phase}_{arg.ext}_{time}/") -if len(arg.input.split(",")) > 1: - output = {i: load(i) for i in arg.input.split(",")} -elif "*" in arg.input: - files = glob.glob(arg.input) +if not os.path.isdir(f"plot/BTV/{args.phase}_{args.ext}_{time}/"): + os.makedirs(f"plot/BTV/{args.phase}_{args.ext}_{time}/") +if len(args.input.split(",")) > 1: + output = {i: load(i) for i in args.input.split(",")} +elif "*" in args.input: + files = glob.glob(args.input) output = {i: load(i) for i in files} else: - output = {arg.input: load(arg.input)} -output = scaleSumW(output, arg.lumi) + output = {args.input: load(args.input)} +output = scaleSumW(output, args.lumi) mergemap = {} - +## create merge map from sample set/data MC if not any(".coffea" in o for o in output.keys()): + if "sample" in args.split: + mergemap = sample_mergemap mergemap["data"] = [m for m in output.keys() if "Run" in m] mergemap["mc"] = [m for m in output.keys() if "Run" not in m] else: @@ -108,37 +119,44 @@ for f in output.keys(): datalist.extend([m for m in output[f].keys() if "Run" in m]) mclist.extend([m for m in output[f].keys() if "Run" not in m]) + if "sample" in args.split: + mergemap = sample_mergemap mergemap["mc"] = mclist mergemap["data"] = datalist + collated = collate(output, mergemap) + +for sample in mergemap.keys(): + if type(collated[sample]) is not dict: + del collated[sample] ### input text settings -if "Wc" in arg.phase: +if "Wc" in args.phase: input_txt = "W+c" - if arg.splitOSSS == 1: + if args.splitOSSS == 1: input_txt = input_txt + " OS" - elif arg.splitOSSS == -1: + elif args.splitOSSS == -1: input_txt = input_txt + " SS" else: input_txt = input_txt + " OS-SS" -elif "DY" in arg.phase: +elif "DY" in args.phase: input_txt = "DY+jets" elif "QCD" in arg.phase: input_txt = "QCD" elif "semilep" in arg.phase: input_txt = r"t$\bar{t}$ semileptonic" nj = 4 -elif "dilep" in arg.phase: +elif "dilep" in args.phase: input_txt = r"t$\bar{t}$ dileptonic" nj = 2 if ( - "njet" in arg.variable.split(",") - or "nbjet" in arg.variable.split(",") - or "mu" in arg.variable.split(",") + "njet" in args.variable.split(",") + or "nbjet" in args.variable.split(",") + or "mu" in args.variable.split(",") ): nj = 1 -if "emctag" in arg.phase: +if "emctag" in args.phase: input_txt = input_txt + " (e$\mu$)" -elif "ectag" in arg.phase: +elif "ectag" in args.phase: input_txt = input_txt + " (e)" elif "QCD" == arg.phase: input_txt = input_txt + " (multijets)" @@ -146,20 +164,42 @@ input_txt = input_txt + " (e$\mu$)" else: input_txt = input_txt + " ($\mu$)" -if "ctag" in arg.phase and "DY" not in arg.phase: +if "ctag" in args.phase and "DY" not in args.phase: input_txt = input_txt + "\nw/ soft-$\mu$" -if arg.variable == "all": - var_set = collated["mc"].keys() -elif "*" in arg.variable: +if args.variable == "all": var_set = [ - var for var in collated["mc"].keys() if arg.variable.replace("*", "") in var + var + for var in collated["mc"].keys() + if var not in ["fname", "run", "lumi", "sumw"] ] -else: - var_set = arg.variable.split(",") +elif "*" in args.variable: + if args.variable.count("*") > 1: + var_set = [ + var + for var in collated["mc"].keys() + if args.variable.replace("*", "") in var + ] + elif args.variable.startswith("*") or args.variable.endswith("*"): + var_set = [ + var + for var in collated["mc"].keys() + if var.startswith(args.variable.replace("*", "")) + or var.endswith(args.variable.replace("*", "")) + ] + else: + var_set = [ + var + for var in collated["mc"].keys() + if re.match( + f"^{args.variable.split('*')[0]}.*{args.variable.split('*')[1]}$", var + ) + != None + ] +else: + var_set = args.variable.split(",") for index, discr in enumerate(var_set): - if "sumw" == discr: - continue + ## remove empty if ( discr not in collated["mc"].keys() or discr not in collated["data"].keys() @@ -169,20 +209,20 @@ print(discr, "not in file or empty") continue + ## axis info allaxis = {} - if "Wc" in arg.phase: - if arg.splitOSSS is None: # OS-SS - collated["mc"][discr] = ( - collated["mc"][discr][{"osss": 0}] - + collated["mc"][discr][{"osss": 1}] * -1 - ) - collated["data"][discr] = ( - collated["data"][discr][{"osss": 0}] - + collated["data"][discr][{"osss": 1}] * -1 - ) - elif arg.splitOSSS == 1: + if "Wc" in args.phase: + if args.splitOSSS is None: # OS-SS + for sample in collated.keys(): + if discr not in collated[sample].keys(): + continue + collated[sample][discr] = ( + collated[sample][discr][{"osss": 0}] + + collated[sample][discr][{"osss": 1}] * -1 + ) + elif args.splitOSSS == 1: allaxis["osss"] = 0 # opposite sign - elif arg.splitOSSS == -1: + elif args.splitOSSS == -1: allaxis["osss"] = 1 # same sign if "flav" in collated["mc"][discr].axes.name: allaxis["flav"] = sum @@ -192,28 +232,31 @@ allaxis["syst"] = "nominal" SF_axis = allaxis noSF_axis = allaxis - systlist = [i for i in range(collated["mc"][discr].axes[0].size)] + systlist = [ + collated["mc"][discr].axes[0].value(i) + for i in range(collated["mc"][discr].axes[0].size) + ] if "noSF" in systlist: noSF_axis["syst"] = "noSF" + ## rebin config, add xerr do_xerr = False - if arg.autorebin is not None: - if arg.autorebin.isdigit(): - rebin = int(arg.autorebin) + if args.autorebin is not None: + if args.autorebin.isdigit(): + rebin = int(args.autorebin) else: - rebin = np.array([float(i) for i in arg.autorebin.split(",")]) + rebin = np.array([float(i) for i in args.autorebin.split(",")]) do_xerr = True - collated["mc"][discr] = rebin_hist( - collated["mc"][discr], collated["mc"][discr].axes[-1].name, rebin - ) - collated["data"][discr] = rebin_hist( - collated["data"][discr], collated["data"][discr].axes[-1].name, rebin - ) + for s in collated.keys(): + collated[s][discr] = rebin_hist( + collated[s][discr], collated[s][discr].axes[-1].name, rebin + ) + ## Rescale noSF & SF to same MC yields if ( "flav" in collated["mc"][discr].axes.name and "syst" in collated["mc"][discr].axes.name - and arg.SF + and args.SF ): scale_sf = np.sum(collated["mc"][discr][SF_axis].values()) / np.sum( collated["mc"][discr][noSF_axis].values() @@ -223,7 +266,7 @@ if ( "flav" in collated["mc"][discr].axes.name and "syst" in collated["mc"][discr].axes.name - and arg.SF + and args.SF ): print("============> fraction of each flavor in MC") print( @@ -252,29 +295,48 @@ ) fig.subplots_adjust(hspace=0.06, top=0.92, bottom=0.1, right=0.97) hep.cms.label( - "Preliminary", data=True, lumi=arg.lumi / 1000.0, com=arg.com, loc=0, ax=ax + "Preliminary", data=True, lumi=args.lumi / 1000.0, com=args.com, loc=0, ax=ax ) + ## w/ & w/o btag SF if ( "flav" in collated["mc"][discr].axes.name and "syst" in collated["mc"][discr].axes.name - and arg.SF + and args.SF + and args.split != "sample" ): - splitflav_stack = [] + splitflav_stack, labels, color_config = [], [], {} + color_config["color"], color_config["alpha"] = [], [] splitflav_axis = SF_axis - for i in range(4): - splitflav_axis["flav"] = i - splitflav_stack += [[collated["mc"][discr][splitflav_axis]]] + for sample in collated.keys(): + if sample == "data": + continue + if args.split == "flavor" and sample != "mc": + continue + elif args.split == "sample_flav" and sample == "mc": + continue + for i, t in enumerate(["udsg", "pu", "c", "b"]): + splitflav_axis["flav"] = i + splitflav_stack.append(collated[sample][discr][splitflav_axis]) + if args.split == "flavor": + labels.append(t) + color_config["color"].append(color_map[t]) + color_config["alpha"].append(1.0) + else: + labels.append(f"{sample} ({t})") + color_config["color"].append(color_map[sample]) + color_config["alpha"].append(1.0 - 0.2 * i) SF_axis["flav"] = sum hep.histplot( splitflav_stack, stack=True, - label=["udsg", "pileup", "c", "b"], + label=labels, histtype="fill", yerr=True, ax=ax, - # flow=arg.flow + flow=args.flow, + **color_config, ) hep.histplot( collated["mc"][discr][noSF_axis], @@ -283,7 +345,7 @@ width=2, yerr=True, ax=ax, - # flow=arg.flow + flow=args.flow, ) hep.histplot( collated["data"][discr][noSF_axis], @@ -292,17 +354,17 @@ label="Data", yerr=True, ax=ax, - xerr=do_xerr - # flow=arg.flow + xerr=do_xerr, + flow=args.flow, ) hmc = collated["mc"][discr][SF_axis] - MCerrorband(hmc, ax=ax, flow=arg.flow) # stat. unc. errorband - SFerror = SFerror(collated, discr, flow=arg.flow) + MCerrorband(hmc, ax=ax, flow=args.flow) # stat. unc. errorband + SFerror = SFerror(collated, discr, flow=args.flow) other = {"hatch": "\\\\", "lw": 0, "color": "r", "alpha": 0.4} MCerrorband( hmc, ax=ax, - flow=arg.flow, + flow=args.flow, ext_error=SFerror, label="SF unc.", fill_opts=other, @@ -311,7 +373,7 @@ collated["data"][discr][noSF_axis], collated["mc"][discr][noSF_axis], ax=rax, - flow=arg.flow, + flow=args.flow, xerr=do_xerr, ) plotratio( @@ -323,27 +385,47 @@ denom_fill_opts=other, clear=False, label="SF unc.", - flow=arg.flow, + flow=args.flow, xerr=do_xerr, ) elif ( - "syst" in collated["mc"][discr].axes.name and not arg.SF and "noSF" in systlist + "syst" in collated["mc"][discr].axes.name + and not args.SF + and "noSF" in systlist + and args.split != "sample" ): - splitflav_stack = [] + splitflav_stack, labels, color_config = [], [], {} + color_config["color"], color_config["alpha"] = [], [] splitflav_axis = noSF_axis - for i in range(4): - splitflav_axis["flav"] = i - splitflav_stack += [collated["mc"][discr][splitflav_axis]] + for sample in collated.keys(): + if sample == "data": + continue + if args.split == "flavor" and sample != "mc": + continue + elif args.split == "sample_flav" and sample == "mc": + continue + for i, t in enumerate(["udsg", "pu", "c", "b"]): + splitflav_axis["flav"] = i + splitflav_stack.append(collated[sample][discr][splitflav_axis]) + if args.split == "flavor": + labels.append(t) + color_config["color"].append(color_map[t]) + color_config["alpha"].append(1.0) + else: + labels.append(f"{sample} ({t})") + color_config["color"].append(color_map[sample]) + color_config["alpha"].append(1.0 - 0.2 * i) noSF_axis["flav"] = sum hep.histplot( splitflav_stack, stack=True, histtype="fill", - label=["udsg", "pileup", "c", "b"], + label=labels, yerr=True, ax=ax, - # flow=arg.flow + flow=args.flow, + **color_config, ) hep.histplot( collated["data"][discr][noSF_axis], @@ -352,30 +434,52 @@ label="Data", yerr=True, ax=ax, - xerr=do_xerr - # flow=arg.flow + xerr=do_xerr, + flow=args.flow, ) hmc = collated["mc"][discr][noSF_axis] - MCerrorband(hmc, ax=ax, flow=arg.flow) # stat. unc. errorband + MCerrorband(hmc, ax=ax, flow=args.flow) # stat. unc. errorband rax = plotratio( - collated["data"][discr][noSF_axis], hmc, ax=rax, flow=arg.flow, xerr=do_xerr + collated["data"][discr][noSF_axis], + hmc, + ax=rax, + flow=args.flow, + xerr=do_xerr, ) - elif "flav" in collated["mc"][discr].axes.name: - splitflav_stack = [] + elif "flav" in collated["mc"][discr].axes.name and args.split != "sample": + splitflav_stack, labels, color_config = [], [], {} + color_config["color"], color_config["alpha"] = [], [] splitflav_axis = allaxis - for i in range(4): - splitflav_axis["flav"] = i - splitflav_stack += [collated["mc"][discr][splitflav_axis]] + for sample in collated.keys(): + if sample == "data": + continue + if args.split == "flavor" and sample != "mc": + continue + elif args.split == "sample_flav" and sample == "mc": + continue + for i, t in enumerate(["udsg", "pu", "c", "b"]): + splitflav_axis["flav"] = i + splitflav_stack.append(collated[sample][discr][splitflav_axis]) + + if args.split == "flavor": + labels.append(t) + color_config["color"].append(color_map[t]) + color_config["alpha"].append(1.0) + else: + labels.append(f"{sample} ({t})") + color_config["color"].append(color_map[sample]) + color_config["alpha"].append(1.0 - 0.2 * i) allaxis["flav"] = sum hep.histplot( splitflav_stack, stack=True, histtype="fill", - label=["udsg", "pileup", "c", "b"], + label=labels, yerr=True, ax=ax, - # flow=arg.flow + flow=args.flow, + **color_config, ) hep.histplot( collated["data"][discr][allaxis], @@ -384,25 +488,43 @@ label="Data", yerr=True, ax=ax, - xerr=do_xerr - # flow=arg.flow + xerr=do_xerr, + flow=args.flow, ) hmc = collated["mc"][discr][allaxis] MCerrorband(hmc, ax=ax) rax = plotratio( - collated["data"][discr][allaxis], hmc, ax=rax, flow=arg.flow, xerr=do_xerr + collated["data"][discr][allaxis], hmc, ax=rax, flow=args.flow, xerr=do_xerr ) else: hmc = collated["mc"][discr][allaxis] - hep.histplot( - hmc, - color="tab:orange", - histtype="fill", - label=["MC"], - yerr=True, - ax=ax, - # flow=arg.flow - ) + if "sample" in args.split: + hep.histplot( + [ + collated[s][discr][allaxis] + for s in collated.keys() + if s != "mc" and s != "data" + ], + histtype="fill", + stack=True, + label=[s for s in collated.keys() if s != "mc" and s != "data"], + yerr=True, + ax=ax, + color=[ + color_map[s] for s in collated.keys() if s != "mc" and s != "data" + ], + flow=args.flow, + ) + else: + hep.histplot( + hmc, + color="tab:orange", + histtype="fill", + label=["MC"], + yerr=True, + ax=ax, + flow=args.flow, + ) hep.histplot( collated["data"][discr][allaxis], histtype="errorbar", @@ -410,12 +532,12 @@ label="Data", yerr=True, ax=ax, - xerr=do_xerr - # flow=arg.flow + xerr=do_xerr, + flow=args.flow, ) - MCerrorband(hmc, ax=ax, flow=arg.flow) # stat. unc. errorband + MCerrorband(hmc, ax=ax, flow=args.flow) # stat. unc. errorband rax = plotratio( - collated["data"][discr][allaxis], hmc, ax=rax, flow=arg.flow, xerr=do_xerr + collated["data"][discr][allaxis], hmc, ax=rax, flow=args.flow, xerr=do_xerr ) ax.set_xlabel(None) @@ -425,11 +547,13 @@ ax.get_yaxis().get_offset_text().set_position((-0.065, 1.05)) # FIXME: add wildcard option for xlabel xlabel = ( - arg.xlabel if arg.xlabel is not None else collated["data"][discr].axes[-1].label + args.xlabel + if args.xlabel is not None + else collated["data"][discr].axes[-1].label ) # Use label from stored hists ## FIXME: Set temporary fix for the x-axis - if arg.xlabel is not None: - arg.xlabel.split(",")[index] + if args.xlabel is not None: + args.xlabel.split(",")[index] elif "DeepJet" in discr or "DeepCSV" in discr or "PFCands" in discr: xlabel = ( bininfo[discr]["displayname"] @@ -454,47 +578,51 @@ xlabel = axes_name(discr) rax.set_xlabel(xlabel) - ax.legend() - rax.set_ylim(0, 2.0) + if "sample" in args.split: + ax.legend(ncols=2, prop={"size": 16}) + else: + ax.legend() + rax.set_ylim(0.5, 1.5) ax.set_ylim(bottom=0.0) rax.autoscale(True, axis="x", tight=True) xmin, xmax = autoranger( - collated["data"][discr][allaxis] + collated["mc"][discr][allaxis], flow=arg.flow + collated["data"][discr][allaxis] + collated["mc"][discr][allaxis], + flow=args.flow, ) - if arg.xrange is not None: - xmin, xmax = float(arg.xrange.split(",")[0]), float(arg.xrange.split(",")[1]) + if args.xrange is not None: + xmin, xmax = float(args.xrange.split(",")[0]), float(args.xrange.split(",")[1]) rax.set_xlim(xmin, xmax) - at = AnchoredText(input_txt + "\n" + arg.ext, loc=2, frameon=False) + at = AnchoredText(input_txt + "\n" + args.ext, loc=2, frameon=False) ax.add_artist(at) scale = "" - if arg.norm: + if args.norm: scale = "_norm" name = "all" hep.mpl_magic(ax=ax) - if arg.log: + if args.log: print( "creating:", - f"plot/BTV/{arg.phase}_{arg.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.png", + f"plot/BTV/{args.phase}_{args.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.png", ) ax.set_yscale("log") name = "log" ax.set_ylim(bottom=0.1) hep.mpl_magic(ax=ax) fig.savefig( - f"plot/BTV/{arg.phase}_{arg.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.pdf" + f"plot/BTV/{args.phase}_{args.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.pdf" ) fig.savefig( - f"plot/BTV/{arg.phase}_{arg.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.png" + f"plot/BTV/{args.phase}_{args.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.png" ) else: print( "creating:", - f"plot/BTV/{arg.phase}_{arg.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.png", + f"plot/BTV/{args.phase}_{args.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.png", ) fig.savefig( - f"plot/BTV/{arg.phase}_{arg.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.pdf" + f"plot/BTV/{args.phase}_{args.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.pdf" ) fig.savefig( - f"plot/BTV/{arg.phase}_{arg.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.png" + f"plot/BTV/{args.phase}_{args.ext}_{time}/unc_{discr}_inclusive{scale}_{name}.png" ) diff --git a/src/BTVNanoCommissioning/data/JME/Summer22Run3/compile_F.pkl.gz b/src/BTVNanoCommissioning/data/JME/Summer22Run3/compile_F.pkl.gz new file mode 100644 index 00000000..65748436 Binary files /dev/null and b/src/BTVNanoCommissioning/data/JME/Summer22Run3/compile_F.pkl.gz differ diff --git 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a/src/BTVNanoCommissioning/data/PU/Summer22Run3/puweight_Winter22Run3.histo.root b/src/BTVNanoCommissioning/data/PU/Summer22Run3/puweight_Winter22Run3-69p2mb.histo.root similarity index 100% rename from src/BTVNanoCommissioning/data/PU/Summer22Run3/puweight_Winter22Run3.histo.root rename to src/BTVNanoCommissioning/data/PU/Summer22Run3/puweight_Winter22Run3-69p2mb.histo.root diff --git a/src/BTVNanoCommissioning/helpers/definitions.py b/src/BTVNanoCommissioning/helpers/definitions.py index affdebf8..59f0585d 100644 --- a/src/BTVNanoCommissioning/helpers/definitions.py +++ b/src/BTVNanoCommissioning/helpers/definitions.py @@ -6398,84 +6398,128 @@ def axes_name(var_input): elif "soft_l" in var: obj = "soft-$\\mu$" elif "mujet" in var: - obj = "$\\mu$-Jet" - elif "jet" in var: - obj = "Jet" - elif "w_" in var: - obj = "W" - elif "z_" in var: - obj = "Z" - - if "pt" in var: - unit = " $p_T$ [GeV]" - elif "mass" in var: - unit = " mass [GeV]" - elif "eta" in var: - unit = " $\\eta$" - elif "phi" in var: - unit = " $\\phi$" - elif "dxy" in var: - unit = " $d_{xy}$ [cm]" - elif "dz" in var: - unit = " $d_{z}$ [cm]" - elif "pfRelIso" in var: - unit = " Rel. Iso" - elif "btagDeepCvL" in var: - unit = "Jet DeepCSV CvL" - elif "btagDeepCvB" in var: - unit = "Jet DeepCSV CvB" - elif "btagDeepB" in var: - if "_b_" in var: - unit = "Jet DeepCSV P(b)" - elif "_bb" in var: - unit = "Jet DeepCSV P(bb)" - else: - unit = "Jet DeepCSV b discriminator" - elif "btagDeepC" in var: - unit = "Jet DeepCSV CvsAll" - elif "btagDeepFlavCvL" in var: - unit = "Jet DeepJet CvL" - elif "btagDeepFlavCvB" in var: - unit = "Jet DeepJet CvB" - elif "btagDeepFlavB" in var: - if "_b_" in var: - unit = "Jet DeepJet P(b)" - elif "_bb" in var: - unit = "Jet DeepJet P(bb)" - elif "_lepb" in var: - unit = "Jet DeepJet P(lepb)" - else: - unit = "Jet DeepJet b discriminator" - elif "btagDeepFlavC" in var: - unit = "Jet DeepJet CvsAll" - - label = obj + unit - if var.endswith("0") or "jet0" in var: - if "btagDeepFlav" not in var: - label = label.replace("Jet", "$1^{st}$-Jet") - else: - label = label.replace("Jet", "$1^{st}$-Jet", 1) - elif var.endswith("1") or "jet1" in var: - if "btagDeepFlav" not in var: - label = label.replace("Jet", "$2^{nd}$-Jet") - else: - label = label.replace("Jet", "$2^{nd}$-Jet", 1) - elif var.endswith("2") or "jet2" in var: - if "btagDeepFlav" not in var: - label = label.replace("Jet", "$3^{rd}$-Jet") - else: - label = label.replace("Jet", "$3^{rd}$-Jet", 1) - elif var.endswith("3") or "jet3" in var: - if "btagDeepFlav" not in var: - label = label.replace("Jet", "$4^{th}$-Jet") - else: - label = label.replace("Jet", "$4^{th}$-Jet", 1) - if "ptratio" in var: - if var == "hl_ptratio": - label = "$p_T^{\\ell_1}/p_T^{Jet}$" - if var == "sl_ptratio": - label = "$p_T^{\\ell_2}/p_T^{Jet}$" - if var == "soft_l_ptratio": - label = "$p_T^{soft-\\mu}/p_T^{Jet}$" - output[var] = label - return output[var_input] + unit = "($\\mu$,Jet)" + elif "MET_" in var: + obj = "MET" + elif "ele_" in var: + obj = "e" + elif "posl_" in var: + obj = "$\\ell^+$" + elif "negl_" in var: + obj = "$\\ell^-$" + elif "mu_" in var: + obj = "$\\mu$" + elif "hl_" in var: + obj = "$\\ell_1$" + elif "sl_" in var: + obj = "$\\ell_2$" + elif "soft_l" in var: + obj = "soft-$\\mu$" + elif "mujet" in var: + obj = "$\\mu$-Jet" + elif "jet" in var: + obj = "Jet" + elif "w_" in var: + obj = "W" + elif "z_" in var: + obj = "Z" + if "pt" in var: + unit = " $p_T$ [GeV]" + elif "mass" in var: + unit = " mass [GeV]" + elif "eta" in var: + unit = " $\\eta$" + elif "phi" in var: + unit = " $\\phi$" + elif "dxy" in var: + unit = " $d_{xy}$ [cm]" + elif "dz" in var: + unit = " $d_{z}$ [cm]" + elif "pfRelIso" in var: + unit = " Rel. Iso" + elif "btag" in var: + unit = "Jet" + ## Negative tagger + if "Neg" in var: + unit = "Neg. " + unit + if "tanh" in var: + unit = "Trans. " + unit + ## Different taggers + if "DeepFlav" in var: + unit = unit + " DeepJet" + elif "RobustParTAK4" in var: + unit = unit + " RobustParTAK4" + elif "PNet" in var: + unit = unit + " PNet" + else: + unit = unit + " DeepCSV" + # output node + if "CvL" in var: + unit = unit + " CvL" + elif "CvB" in var: + unit = unit + " CvB" + elif "B_b" in var or "ProbB" in var: + unit = unit + " Prob(b)" + elif "B_bb" in var: + unit = unit + " Prob(bb)" + elif "B_lepb" in var: + unit = unit + " Prob(lepb)" + elif "B_lepb" in var: + unit = unit + " Prob(lepb)" + elif "QvG" in var or "QG" in var: + unit = unit + " QvG" + elif "G" in var: + unit = unit + " Prob(g)" + elif "UDS" in var: + unit = unit + " Prob(uds)" + elif "TauVJet" in var: + unit = unit + " $\\tau$vJ" + elif "B" in var: + unit = unit + " BvAll" + elif "C" in var: + unit = unit + " Prob(c)" + elif "PNetReg" in var: + unit = "Jet PNet Reg." + if "Corr" in var: + unit = " Corr" + elif "CorrNeutrino" in var: + unit = " Corr (w/$\\nu$)" + elif "RegPtRawRes" in var: + unit = " Resoultion" + elif "ProbaN" in var: + unit = "Neg. Jet Probability" + elif "Proba" in var: + unit = "Jet Probability" + elif "BprobN" in var: + unit = "Neg. b-Jet Probability" + elif "Bprob" in var: + unit = "b-Jet Probability" + label = obj + unit + if var.endswith("0") or "jet0" in var: + if "btagDeepFlav" not in var: + label = label.replace("Jet", "$1^{st}$-Jet") + else: + label = label.replace("Jet", "$1^{st}$-Jet", 1) + elif var.endswith("1") or "jet1" in var: + if "btagDeepFlav" not in var: + label = label.replace("Jet", "$2^{nd}$-Jet") + else: + label = label.replace("Jet", "$2^{nd}$-Jet", 1) + elif var.endswith("2") or "jet2" in var: + if "btagDeepFlav" not in var: + label = label.replace("Jet", "$3^{rd}$-Jet") + else: + label = label.replace("Jet", "$3^{rd}$-Jet", 1) + elif var.endswith("3") or "jet3" in var: + if "btagDeepFlav" not in var: + label = label.replace("Jet", "$4^{th}$-Jet") + else: + label = label.replace("Jet", "$4^{th}$-Jet", 1) + if "ptratio" in var: + if var == "hl_ptratio": + label = "$p_T^{\\ell_1}/p_T^{Jet}$" + if var == "sl_ptratio": + label = "$p_T^{\\ell_2}/p_T^{Jet}$" + if var == "soft_l_ptratio": + label = "$p_T^{soft-\\mu}/p_T^{Jet}$" + return label diff --git a/src/BTVNanoCommissioning/helpers/update_branch.py b/src/BTVNanoCommissioning/helpers/update_branch.py index 1bb8b4fa..c667b5e3 100644 --- a/src/BTVNanoCommissioning/helpers/update_branch.py +++ b/src/BTVNanoCommissioning/helpers/update_branch.py @@ -9,20 +9,39 @@ def missing_branch(events): if hasattr(events, "fixedGridRhoFastjetAll") else events.Rho.fixedGridRhoFastjetAll ) - - if not hasattr(events.Jet, "btagDeepFlavC"): + if not hasattr(events.Jet, "btagDeepFlavB"): + jets = events.Jet + jets["btagDeepFlavB"] = ( + events.Jet.btagDeepFlavB_b + + events.Jet.btagDeepFlavB_bb + + events.Jet.btagDeepFlavB_lepb + ) + events.Jet = update( + events.Jet, + {"btagDeepFlavB": jets.btagDeepFlavB}, + ) + if hasattr(events.Jet, "btagDeepFlavCvL") and not hasattr( + events.Jet, "btagDeepFlavC" + ): jets = events.Jet jets["btagDeepFlavC"] = ( events.Jet.btagDeepFlavCvL / (1.0 - events.Jet.btagDeepFlavCvL) ) * events.Jet.btagDeepFlavB + events.Jet = update( + events.Jet, + {"btagDeepFlavC": jets.btagDeepFlavC}, + ) + if hasattr(events.Jet, "btagDeepCvL") and not hasattr(events.Jet, "btagDeepC"): jets["btagDeepC"] = ( events.Jet.btagDeepCvL / (1.0 - events.Jet.btagDeepCvL) ) * events.Jet.btagDeepB events.Jet = update( events.Jet, - {"btagDeepFlavC": jets.btagDeepFlavC, "btagDeepC": jets.btagDeepC}, + {"btagDeepC": jets.btagDeepC}, ) - if not hasattr(events.Jet, "btagDeepFlavCvL"): + if hasattr(events.Jet, "btagDeepFlavC") and not hasattr( + events.Jet, "btagDeepFlavCvL" + ): jets = events.Jet jets["btagDeepFlavCvL"] = np.maximum( np.minimum( @@ -57,6 +76,21 @@ def missing_branch(events): ), -1, ) + events.Jet = update( + events.Jet, + { + "btagDeepFlavCvL": jets.btagDeepFlavCvL, + "btagDeepFlavCvB": jets.btagDeepFlavCvB, + }, + ) + if not hasattr(events.Jet, "btagDeepB"): + jets = events.Jet + jets["btagDeepB"] = events.Jet.btagDeepB_b + events.Jet.btagDeepB_bb + events.Jet = update( + events.Jet, + {"btagDeepB": jets.btagDeepB}, + ) + if hasattr(events.Jet, "btagDeepC") and not hasattr(events.Jet, "btagDeepCvL"): jets["btagDeepCvL"] = np.maximum( np.minimum( np.where( @@ -85,8 +119,6 @@ def missing_branch(events): events.Jet = update( events.Jet, { - "btagDeepFlavCvL": jets.btagDeepFlavCvL, - "btagDeepFlavCvB": jets.btagDeepFlavCvB, "btagDeepCvL": jets.btagDeepCvL, "btagDeepCvB": jets.btagDeepCvB, }, diff --git a/src/BTVNanoCommissioning/helpers/xs_scaler.py b/src/BTVNanoCommissioning/helpers/xs_scaler.py index 9b820517..112db5f8 100644 --- a/src/BTVNanoCommissioning/helpers/xs_scaler.py +++ b/src/BTVNanoCommissioning/helpers/xs_scaler.py @@ -3,6 +3,8 @@ from coffea.processor import accumulate import os from BTVNanoCommissioning.helpers.xsection import xsection + +# from BTVNanoCommissioning.helpers.xsection_13TeV import xsection_13TeV import numpy as np @@ -26,64 +28,30 @@ def scaleSumW(output, lumi): xs_dict[obj["process_name"]] = float(obj["cross_section"]) # if k-factor in the xsection: multiply by the k-factor if "kFactor" in obj.keys() and obj["kFactor"] != "": - xs_dict[obj["process_name"]] = xs_dict[obj["process_name"]] * obj["kFactor"] - duplicated_name = False - sumw = {} - flist = [] - for f in output.keys(): - flist.extend([m for m in output[f].keys() if "Run" not in m]) - for files in output.keys(): - if "sumw" not in output[files].keys() and len(flist) != len(set(flist)): - duplicated_name = True - for sample in output[files].keys(): - if "Run" in str(output[files][sample]): - continue - if sample in sumw.keys(): - sumw[sample] = sumw[sample] + float(output[files][sample]["sumw"]) + xs_dict[obj["process_name"]] = xs_dict[obj["process_name"]] * float( + obj["kFactor"] + ) + merged = {} + merged_output = accumulate([output[f] for f in output.keys()]) + + for sample, accu in merged_output.items(): + scaled[sample] = {} + for key, h_obj in accu.items(): + scaled[sample]["sumw"] = merged_output[sample]["sumw"] + if isinstance(h_obj, hist.Hist): + h = copy.deepcopy(h_obj) + if sample in xs_dict.keys(): + h = h * xs_dict[sample] * lumi / merged_output[sample]["sumw"] else: - sumw[sample] = float(output[files][sample]["sumw"]) - for files in output.keys(): - if "sumw" not in output[files].keys(): - scaled[files] = {} - for sample, accu in output[files].items(): - scaled[files][sample] = {} - scaled[files][sample]["sumw"] = output[files][sample]["sumw"] + if ("data" in sample) or ("Run" in sample) or ("Double" in sample): + h = h + else: + raise KeyError( + sample, + "is not found in xsection.py. If you're using 13TeV samples, please use xsection_13TeV.py", + ) - if duplicated_name: - scaled[files][sample]["sumw"] = sumw[sample] - for key, h_obj in accu.items(): - if isinstance(h_obj, hist.Hist): - h = copy.deepcopy(h_obj) - if sample in xs_dict.keys(): - h = ( - h - * xs_dict[sample] - * lumi - / scaled[files][sample]["sumw"] - ) - else: - if not (("data" in sample) or ("Run" in sample)): - raise KeyError(sample, "is not found in xsection.py") - else: - h = h - scaled[files][sample][key] = h - else: - for sample, accu in output[files].items(): - scaled[sample] = {} - for key, h_obj in accu.items(): - scaled[sample]["sumw"] = output[files]["sumw"] - if isinstance(h_obj, hist.Hist): - h = copy.deepcopy(h_obj) - if sample in xs_dict.keys(): - h = h * xs_dict[sample] * lumi / output[files]["sumw"] - else: - if not (("data" in sample) or ("Run" in sample)) or ( - "Double" in sample - ): - raise KeyError(sample, "is not found in xsection.py") - else: - h = h - scaled[sample][key] = h + scaled[sample][key] = h return scaled @@ -117,19 +85,11 @@ def additional_scale(output, scale, sample_to_scale): return scaled -def collate(output, mergemap): +def collate(merged_output, mergemap): out = {} - merged = {} - merged_output = accumulate([output[f] for f in output.keys()]) - for files in merged_output.keys(): - if "sumw" not in merged_output[files].keys(): - for m in output[files].keys(): - merged[m] = dict(merged_output[files][m].items()) - else: - merged[files] = dict(merged_output[files].items()) for group, names in mergemap.items(): out[group] = accumulate( - [v for k, v in merged.items() if k.split("_FNAME_")[0] in names] + [v for k, v in merged_output.items() if k.split("_FNAME_")[0] in names] ) return out diff --git a/src/BTVNanoCommissioning/helpers/xsection.py b/src/BTVNanoCommissioning/helpers/xsection.py index e8c8c98b..5c1b3aaa 100644 --- a/src/BTVNanoCommissioning/helpers/xsection.py +++ b/src/BTVNanoCommissioning/helpers/xsection.py @@ -1,1188 +1,4 @@ xsection = [ - { - "id": "61641f28294617432cff1379", - "process_name": "QCD_Pt-30to50_EMEnriched_TuneCP5_13TeV_pythia8", - "cross_section": "6447000.0", - "total_uncertainty": "19870.0", - "equivalent_lumi": "0.0001551", - "matrix_generator": "none", - "energy": "13", - }, - { - "id": "61641f29294617432cff137a", - "process_name": "QCD_Pt-50to80_EMEnriched_TuneCP5_13TeV_pythia8", - "cross_section": "1988000.0", - "total_uncertainty": "5961.0", - "equivalent_lumi": "0.0005029", - "matrix_generator": "none", - "energy": "13", - }, - { - "id": "61641f2a294617432cff137b", - "process_name": "QCD_Pt-80to120_EMEnriched_TuneCP5_13TeV_pythia8", - "cross_section": "367500.0", - "total_uncertainty": "1091.0", - "equivalent_lumi": "0.002721", - "matrix_generator": "none", - "energy": "13", - }, - { - "id": "61641f25294617432cff1374", - "process_name": "QCD_Pt-120to170_EMEnriched_TuneCP5_13TeV_pythia8", - "cross_section": "66590.0", - "total_uncertainty": "196.6", - "equivalent_lumi": "0.01502", - "matrix_generator": "none", - "energy": "13", - }, - { - "id": "61641f26294617432cff1376", - "process_name": "QCD_Pt-170to300_EMEnriched_TuneCP5_13TeV_pythia8", - "cross_section": "16620.0", - "total_uncertainty": "49.1", - "equivalent_lumi": "0.06016", - "matrix_generator": "none", - "energy": "13", - }, - { - "id": "61641f28294617432cff1378", - "process_name": "QCD_Pt-300toInf_EMEnriched_TuneCP5_13TeV_pythia8", - "cross_section": "1104.0", - "total_uncertainty": "3.282", - "equivalent_lumi": "0.9057", - "matrix_generator": "none", - "energy": "13", - }, - { - "id": "5b44aa73f368576cbd3d4d07", - "process_name": "QCD_Pt-15To20_MuEnrichedPt5_TuneCP5_13TeV_pythia8", - "cross_section": "3820000", - "total_uncertainty": "8817.0", - "DAS": "/QCD_Pt-15to20_MuEnrichedPt5_TuneCP5_13TeV_pythia8/RunIIFall17MiniAODv2-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/MINIAODSIM", - "energy": "13", - }, - { - "id": "5b44aa76f368576cbd3d4d0c", - "process_name": "QCD_Pt-20To30_MuEnrichedPt5_TuneCP5_13TeV-pythia8", - "cross_section": "2960000", - "total_uncertainty": "7955.0", - "DAS": "/QCD_Pt-20to30_MuEnrichedPt5_TuneCP5_13TeV_pythia8/RunIIFall17MiniAODv2-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/MINIAODSIM", - "energy": "13", - }, - { - "id": "5b44aa79f368576cbd3d4d10", - "process_name": "QCD_Pt-30To50_MuEnrichedPt5_TuneCP5_13TeV_pythia8", - "cross_section": "1652471", - "total_uncertainty": "4275.0", - "DAS": "/QCD_Pt-30to50_MuEnrichedPt5_TuneCP5_13TeV_pythia8/RunIIFall17MiniAODv2-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/MINIAODSIM", - "energy": "13", - }, - { - "id": "5b44aa7cf368576cbd3d4d15", - "process_name": "QCD_Pt-50To80_MuEnrichedPt5_TuneCP5_13TeV_pythia8", - "cross_section": "437504", - "total_uncertainty": "1178.0", - "DAS": "/QCD_Pt-50to80_MuEnrichedPt5_TuneCP5_13TeV_pythia8/RunIIFall17MiniAODv2-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/MINIAODSIM", - "energy": "13", - }, - { - "id": "5b44aa7df368576cbd3d4d16", - "process_name": "QCD_Pt-80To120_MuEnrichedPt5_TuneCP5_13TeV_pythia8", - "cross_section": "106033", - "total_uncertainty": "276.1", - "DAS": "/QCD_Pt-80to120_MuEnrichedPt5_TuneCP5_13TeV_pythia8/RunIIFall17MiniAODv2-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/MINIAODSIM", - "energy": "13", - }, - { - "id": "5b44aa71f368576cbd3d4d05", - "process_name": "QCD_Pt-120To170_MuEnrichedPt5_TuneCP5_13TeV_pythia8", - "cross_section": "24720", - "total_uncertainty": "65.63", - "DAS": "/QCD_Pt-120to170_MuEnrichedPt5_TuneCP5_13TeV_pythia8/RunIIFall17MiniAODv2-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/MINIAODSIM", - "energy": "13", - }, - { - "id": "5b44aa75f368576cbd3d4d0a", - "process_name": "QCD_Pt-170To300_MuEnrichedPt5_TuneCP5_13TeV_pythia8", - "cross_section": "8654", - "total_uncertainty": "21.62", - "DAS": "/QCD_Pt-170to300_MuEnrichedPt5_TuneCP5_13TeV_pythia8/RunIIFall17MiniAODv2-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/MINIAODSIM", - "energy": "13", - }, - { - "id": "5f6c27c8f368571e6ae3c3c5", - "process_name": "QCD_Pt-300To470_MuEnrichedPt5_TuneCP5_13TeV_pythia8", - "cross_section": "797", - "total_uncertainty": "1.889", - "DAS": "/QCD_Pt-300to470_MuEnrichedPt5_TuneCP5_13TeV_pythia8/RunIIFall17MiniAODv2-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/MINIAODSIM", - "matrix_generator": "none", - "energy": "13", - }, - { - "id": "5b44aa7bf368576cbd3d4d13", - "process_name": "QCD_Pt-470To600_MuEnrichedPt5_TuneCP5_13TeV_pythia8", - "cross_section": " 79", - "total_uncertainty": "0.1789", - "DAS": "/QCD_Pt-470to600_MuEnrichedPt5_TuneCP5_13TeV_pythia8/RunIIFall17MiniAODv2-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/MINIAODSIM", - "energy": "13", - }, - { - "id": "5f6c27c9f368571e6ae3c3c6", - "process_name": "QCD_Pt-600To800_MuEnrichedPt5_TuneCP5_13TeV_pythia8", - "cross_section": "25", - "total_uncertainty": "0.05469", - "DAS": 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"13", + }, +] diff --git a/src/BTVNanoCommissioning/utils/AK4_parameters.py b/src/BTVNanoCommissioning/utils/AK4_parameters.py index 9e1d4cdb..6ee044dc 100644 --- a/src/BTVNanoCommissioning/utils/AK4_parameters.py +++ b/src/BTVNanoCommissioning/utils/AK4_parameters.py @@ -24,8 +24,8 @@ "JME": "jec_compiled.pkl.gz", "BTV": {"deepCSV": "shape", "deepJet": "shape"}, "LSF": { - "ele_ID 2017": "wp90iso", - "ele_Reco 2017": "RecoAbove20", + "ele_ID 2017 UL-Electron-ID-SF": "wp90iso", + "ele_Reco 2017 UL-Electron-ID-SF": "RecoAbove20", "mu_Reco 2017_UL": "NUM_TrackerMuons_DEN_genTracks", "mu_HLT 2017_UL": "NUM_IsoMu27_DEN_CutBasedIdTight_and_PFIsoTight", "mu_ID 2017_UL": "NUM_TightID_DEN_TrackerMuons", @@ -41,13 +41,39 @@ }, "Summer22Run3": { "lumiMask": "Cert_Collisions2022_355100_362760_Golden.json", - "PU": "puweight_Winter22Run3.histo.root", # use same 69.2mb for Summer22 + "PU": "puweight_Winter22Run3-69p2mb.histo.root", # use same 80.0mb for Summer22 "JME": "winter_jec_compiled.pkl.gz", # not this is from Winter22Run3 since this is not yet finished + "LSF": { + "mu_json": "ScaleFactors_Muon_trackerMuons_Z_2022_Prompt_ID_ISO_schemaV2.json", + "mu_ID": "NUM_TightID_DEN_TrackerMuons", + "mu_Iso": "NUM_TightPFIso_DEN_TightID", + }, + "JPCalib": { + "Run2022C": "calibeHistoWrite_Data2022C_NANO130X_v1.root", + "Run2022D": "calibeHistoWrite_Data2022D_NANO130X_v1.root", + "MC": "calibeHistoWrite_MC2022_NANO130X_v2.root", + }, }, "Summer22EERun3": { "lumiMask": "Cert_Collisions2022_355100_362760_Golden.json", - "PU": "puweight_Summer22EERun3.histo.root", # 80mb - "JME": "jec_compiled.pkl.gz", + "PU": "puweight_Summer22EERun3-80p0mb.histo.root", # 69.2mb + # "JME": "jec_compiled.pkl.gz", + "LSF": { + "ele_json": "electron.json.gz", + "mu_json": "ScaleFactors_Muon_trackerMuons_Z_2022EE_Prompt_ID_ISO_schemaV2.json", + "mu_ID": "NUM_TightID_DEN_TrackerMuons", + "mu_Iso": "NUM_TightPFIso_DEN_TightID", + "ele_ID 2022FG 2022FG-Electron-ID-SF": "Tight", + "ele_Reco_low 2022FG 2022FG-Electron-ID-SF": "RecoBelow20", + "ele_Reco_med 2022FG 2022FG-Electron-ID-SF": "Reco20to75", + "ele_Reco_high 2022FG 2022FG-Electron-ID-SF": "RecoAbove75", + }, + "JPCalib": { + "Run2022E": "calibeHistoWrite_Data2022F_NANO130X_v1.root", + "Run2022F": "calibeHistoWrite_Data2022F_NANO130X_v1.root", + "Run2022G": "calibeHistoWrite_Data2022G_NANO130X_v1.root", + "MC": "calibeHistoWrite_MC2022EE_NANO130X_v1.root", + }, }, "2018_UL": {#for QCD workflow "lumiMask": "Cert_314472-325175_13TeV_Legacy2018_Collisions18_JSON.txt", diff --git a/src/BTVNanoCommissioning/utils/correction.py b/src/BTVNanoCommissioning/utils/correction.py index 43789c61..064a622a 100644 --- a/src/BTVNanoCommissioning/utils/correction.py +++ b/src/BTVNanoCommissioning/utils/correction.py @@ -7,6 +7,7 @@ import re import numpy as np import awkward as ak +import uproot from coffea.lookup_tools import extractor, txt_converters, rochester_lookup from coffea.lumi_tools import LumiMask @@ -18,7 +19,7 @@ def load_SF(campaign, syst=False): - correction_map = {} + correction_map = {"campaign": campaign} for SF in config[campaign].keys(): if SF == "lumiMask": continue @@ -42,13 +43,36 @@ def load_SF(campaign, syst=False): correction_map["PU"] = cloudpickle.load(fin)[ "2017_pileupweight" ] + elif str(filename).endswith(".json.gz"): + correction_map["PU"] = correctionlib.CorrectionSet.from_file( + importlib.resources.path( + f"BTVNanoCommissioning.data.PU.{campaign}", filename + ) + ) elif str(filename).endswith(".histo.root"): ext = extractor() ext.add_weight_sets([f"* * {filename}"]) ext.finalize() correction_map["PU"] = ext.make_evaluator()["PU"] + ## btag weight elif SF == "BTV": + if "btag" in config[campaign]["BTV"].keys() and config[campaign]["BTV"][ + "btag" + ].endswith(".json.gz"): + correction_map["btag"] = correctionlib.CorrectionSet.from_file( + importlib.resources.path( + f"BTVNanoCommissioning.data.BTV.{campaign}", filename + ) + ) + if "ctag" in config[campaign]["BTV"].keys() and config[campaign]["BTV"][ + "btag" + ].endswith(".json.gz"): + correction_map["btag"] = correctionlib.CorrectionSet.from_file( + importlib.resources.path( + f"BTVNanoCommissioning.data.BTV.{campaign}", filename + ) + ) if os.path.exists( f"src/BTVNanoCommissioning/jsonpog-integration/POG/BTV/{campaign}" ): @@ -67,19 +91,21 @@ def load_SF(campaign, syst=False): _btag_path, config[campaign]["BTV"][tagger] ) as filename: if "B" in tagger: - correction_map["btag"][tagger] = BTagScaleFactor( - filename, - BTagScaleFactor.RESHAPE, - methods="iterativefit,iterativefit,iterativefit", - ) - else: - if campaign == "Rereco17_94X": - correction_map["ctag"][tagger] = ( - "BTVNanoCommissioning/data/BTV/" - + campaign - + "/" - + config[campaign]["BTV"][tagger] + if filename.endswith(".json.gz"): + correction_map[ + "btag" + ] = correctionlib.CorrectionSet.from_file(filename) + else: + correction_map["btag"][tagger] = BTagScaleFactor( + filename, + BTagScaleFactor.RESHAPE, + methods="iterativefit,iterativefit,iterativefit", ) + else: + if filename.endswith(".json.gz"): + correction_map[ + "ctag" + ] = correctionlib.CorrectionSet.from_file(filename) else: correction_map["ctag"][tagger] = BTagScaleFactor( filename, @@ -89,10 +115,14 @@ def load_SF(campaign, syst=False): ## lepton SFs elif SF == "LSF": correction_map["MUO_cfg"] = { - mu: f for mu, f in config[campaign]["LSF"].items() if "mu" in mu + mu: f + for mu, f in config[campaign]["LSF"].items() + if "mu" in mu and "_json" not in mu } correction_map["EGM_cfg"] = { - e: f for e, f in config[campaign]["LSF"].items() if "ele" in e + e: f + for e, f in config[campaign]["LSF"].items() + if "ele" in e and "_json" not in e } ## Muon if os.path.exists( @@ -107,13 +137,27 @@ def load_SF(campaign, syst=False): correction_map["EGM"] = correctionlib.CorrectionSet.from_file( f"src/BTVNanoCommissioning/jsonpog-integration/POG/EGM/{campaign}/electron.json.gz" ) + if any( + np.char.find(np.array(list(config[campaign]["LSF"].keys())), "mu_json") + != -1 + ): + correction_map["MUO"] = correctionlib.CorrectionSet.from_file( + f"src/BTVNanoCommissioning/data/LSF/{campaign}/{config[campaign]['LSF']['mu_json']}" + ) + if any( + np.char.find(np.array(list(config[campaign]["LSF"].keys())), "ele_json") + != -1 + ): + correction_map["EGM"] = correctionlib.CorrectionSet.from_file( + f"src/BTVNanoCommissioning/data/LSF/{campaign}/{config[campaign]['LSF']['ele_json']}" + ) + ### Check if any custom corrections needed # FIXME: (some low pT muons not supported in jsonpog-integration at the moment) - if ( - ".json" in "\t".join(list(config[campaign]["LSF"].values())) - or ".txt" in "\t".join(list(config[campaign]["LSF"].values())) - or ".root" in "\t".join(list(config[campaign]["LSF"].values())) + "histo.json" in "\t".join(list(config[campaign]["LSF"].values())) + or "histo.txt" in "\t".join(list(config[campaign]["LSF"].values())) + or "histo.root" in "\t".join(list(config[campaign]["LSF"].values())) ): _mu_path = f"BTVNanoCommissioning.data.LSF.{campaign}" ext = extractor() @@ -121,9 +165,9 @@ def load_SF(campaign, syst=False): inputs, real_paths = [ k for k in correction_map["MUO_cfg"].keys() - if ".json" in correction_map["MUO_cfg"][k] - or ".txt" in correction_map["MUO_cfg"][k] - or ".root" in correction_map["MUO_cfg"][k] + if "histo.json" in correction_map["MUO_cfg"][k] + or "histo.txt" in correction_map["MUO_cfg"][k] + or "histo.root" in correction_map["MUO_cfg"][k] ], [ stack.enter_context(importlib.resources.path(_mu_path, f)) for f in correction_map["MUO_cfg"].values() @@ -138,9 +182,9 @@ def load_SF(campaign, syst=False): [ f"{paths} {file}" for paths, file in zip(inputs, real_paths) - if ".json" in str(file) - or ".txt" in str(file) - or ".root" in str(file) + if "histo.json" in str(file) + or "histo.txt" in str(file) + or "histo.root" in str(file) ] ) if syst: @@ -162,21 +206,21 @@ def load_SF(campaign, syst=False): inputs, real_paths = [ k for k in correction_map["EGM_cfg"].keys() - if ".json" in correction_map["EGM_cfg"][k] - or ".txt" in correction_map["EGM_cfg"][k] - or ".root" in correction_map["EGM_cfg"][k] + if "histo.json" in correction_map["EGM_cfg"][k] + or "histo.txt" in correction_map["EGM_cfg"][k] + or "histo.root" in correction_map["EGM_cfg"][k] ], [ stack.enter_context(importlib.resources.path(_ele_path, f)) for f in correction_map["EGM_cfg"].values() - if ".json" in f or ".txt" in f or ".root" in f + if "histo.json" in f or ".txt" in f or ".root" in f ] ext.add_weight_sets( [ f"{paths} {file}" for paths, file in zip(inputs, real_paths) - if ".json" in str(file) - or ".txt" in str(file) - or ".root" in str(file) + if "histo.json" in str(file) + or "histo.txt" in str(file) + or "histo.root" in str(file) ] ) if syst: @@ -191,6 +235,7 @@ def load_SF(campaign, syst=False): ) ext.finalize() correction_map["EGM_custom"] = ext.make_evaluator() + ## rochester muon momentum correction elif SF == "roccor": if "2016postVFP_UL" == campaign: @@ -332,7 +377,7 @@ def load_lumi(campaign): ext_jetvetomap.add_weight_sets( [ f"RunCD jetvetomap {stack.enter_context(importlib.resources.path('BTVNanoCommissioning.data.JME.Winter22Run3','Winter22Run3_RunCD_v1.histo.root'))}", - f"RunE jetvetomap {stack.enter_context(importlib.resources.path('BTVNanoCommissioning.data.JME.Winter22Run3','Winter22Run3_RunE_v1.histo.root'))}", + f"RunE jetvetomap_eep {stack.enter_context(importlib.resources.path('BTVNanoCommissioning.data.JME.Winter22Run3','Winter22Run3_RunE_v1.histo.root'))}", ] ) @@ -850,12 +895,13 @@ def btagSFs(jet, correct_map, weights, SFtype, syst=False): ### Lepton SFs def eleSFs(ele, correct_map, weights, syst=True, isHLT=False): allele = ele if ele.ndim > 1 else ak.singletons(ele) + for sf in correct_map["EGM_cfg"].keys(): ## Only apply SFs for lepton pass HLT filter if not isHLT and "HLT" in sf: continue sf_type = sf[: sf.find(" ")] - if "low" in sf: + if "low" in sf or "high" in sf: continue for nele in range(ak.num(allele.pt)[0]): ele = allele[:, nele] @@ -872,92 +918,192 @@ def eleSFs(ele, correct_map, weights, syst=True, isHLT=False): if "correctionlib" in str(type(correct_map["EGM"])): ## Reco SF -splitted pT if "Reco" in sf: - ele_pt = np.where(ele.pt < 20.0, 20.0, ele.pt) - ele_pt_low = np.where(ele.pt >= 20.0, 19.9, ele.pt) - - sfs_low = np.where( - (~mask) & (~masknone), - correct_map["EGM"][list(correct_map["EGM"].keys())[0]].evaluate( - sf[sf.find(" ") + 1 :], - "sf", - "RecoBelow20", - ele_eta, - ele_pt_low, - ), - 1.0, - ) - sfs = np.where( - mask & (~masknone), - correct_map["EGM"][list(correct_map["EGM"].keys())[0]].evaluate( - sf[sf.find(" ") + 1 :], "sf", "RecoAbove20", ele_eta, ele_pt - ), - sfs_low, - ) - sfs = np.where(masknone, 1.0, sfs) - - if syst: - sfs_up_low = np.where( - ~mask & ~masknone, - correct_map["EGM"][ - list(correct_map["EGM"].keys())[0] - ].evaluate( - sf[sf.find(" ") + 1 :], - "sfup", + if "Summer22" not in correct_map["campaign"]: + ele_pt = np.where(ele.pt < 20.0, 20.0, ele.pt) + ele_pt_low = np.where(ele.pt >= 20.0, 19.9, ele.pt) + sfs_low = np.where( + (~mask) & (~masknone), + correct_map["EGM"][correct_map["EGM_cfg"][sf]].evaluate( + sf.split(" ")[1], + "sf", "RecoBelow20", ele_eta, ele_pt_low, ), - 0.0, + 1.0, ) - sfs_down_low = np.where( - ~mask & ~masknone, - correct_map["EGM"][ - list(correct_map["EGM"].keys())[0] - ].evaluate( - sf[sf.find(" ") + 1 :], - "sfdown", + sfs = np.where( + mask & (~masknone), + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], "sf", "RecoAbove20", ele_eta, ele_pt + ), + sfs_low, + ) + sfs = np.where(masknone, 1.0, sfs) + + if syst: + sfs_up_low = np.where( + ~mask & ~masknone, + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sfup", + "RecoBelow20", + ele_eta, + ele_pt_low, + ), + 0.0, + ) + sfs_down_low = np.where( + ~mask & ~masknone, + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sfdown", + "RecoBelow20", + ele_eta, + ele_pt_low, + ), + 0.0, + ) + sfs_up = np.where( + mask & ~masknone, + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sfup", + "RecoAbove20", + ele_eta, + ele_pt, + ), + sfs_up_low, + ) + sfs_down = np.where( + mask & ~masknone, + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sfdown", + "RecoAbove20", + ele_eta, + ele_pt, + ), + sfs_down_low, + ) + sfs_up, sfs_down = np.where( + masknone, 1.0, sfs_up + ), np.where(masknone, 1.0, sfs_down) + else: + ele_pt = np.clip(ele.pt, 20.1, 74.9) + ele_pt_low = np.where(ele.pt >= 20.0, 19.9, ele.pt) + ele_pt_high = np.clip(ele.pt, 75.0, 500.0) + + sfs_low = np.where( + (ele.pt <= 20.0) & (~masknone), + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sf", "RecoBelow20", ele_eta, ele_pt_low, ), - 0.0, + 1.0, ) - sfs_up = np.where( - mask & ~masknone, - correct_map["EGM"][ - list(correct_map["EGM"].keys())[0] - ].evaluate( - sf[sf.find(" ") + 1 :], - "sfup", - "RecoAbove20", + sfs_high = np.where( + (ele.pt > 75.0) & (~masknone), + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sf", + "RecoAbove75", ele_eta, - ele_pt, + ele_pt_high, ), - sfs_up_low, + sfs_low, ) - sfs_down = np.where( - mask & ~masknone, - correct_map["EGM"][ - list(correct_map["EGM"].keys())[0] - ].evaluate( - sf[sf.find(" ") + 1 :], - "sfdown", - "RecoAbove20", - ele_eta, - ele_pt, + sfs = np.where( + (ele.pt > 20.0) & (ele.pt <= 75.0) & (~masknone), + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], "sf", "Reco20to75", ele_eta, ele_pt ), - sfs_down_low, - ) - sfs_up, sfs_down = np.where(masknone, 1.0, sfs_up), np.where( - masknone, 1.0, sfs_down + sfs_high, ) + + sfs = np.where(masknone, 1.0, sfs) + + if syst: + sfs_up_low = np.where( + (ele.pt <= 20.0) & ~masknone, + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sfup", + "RecoBelow20", + ele_eta, + ele_pt_low, + ), + 0.0, + ) + sfs_down_low = np.where( + (ele.pt <= 20.0) & ~masknone, + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sfdown", + "RecoBelow20", + ele_eta, + ele_pt_low, + ), + 0.0, + ) + sfs_up_high = np.where( + (ele.pt > 20.0) & (ele.pt <= 75.0) & ~masknone, + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sfup", + "RecoAbove75", + ele_eta, + ele_pt_high, + ), + sfs_up_low, + ) + sfs_down_high = np.where( + (ele.pt > 20.0) & (ele.pt <= 75.0) & ~masknone, + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sfdown", + "RecoAbove75", + ele_eta, + ele_pt_high, + ), + sfs_down_low, + ) + sfs_up = np.where( + (ele.pt > 20.0) & (ele.pt <= 75.0) & ~masknone, + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sfup", + "Reco20to75", + ele_eta, + ele_pt, + ), + sfs_up_high, + ) + sfs_down = np.where( + (ele.pt > 20.0) & (ele.pt <= 75.0) & ~masknone, + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], + "sfdown", + "Reco20to75", + ele_eta, + ele_pt, + ), + sfs_down_high, + ) + + sfs_up, sfs_down = np.where( + masknone, 1.0, sfs_up + ), np.where(masknone, 1.0, sfs_down) ## Other files else: sfs = np.where( masknone, 1.0, - correct_map["EGM"][list(correct_map["EGM"].keys())[0]].evaluate( - sf[sf.find(" ") + 1 :], + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], "sf", correct_map["EGM_cfg"][sf], ele_eta, @@ -969,10 +1115,8 @@ def eleSFs(ele, correct_map, weights, syst=True, isHLT=False): sfs_up = np.where( masknone, 1.0, - correct_map["EGM"][ - list(correct_map["EGM"].keys())[0] - ].evaluate( - sf[sf.find(" ") + 1 :], + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], "sfup", correct_map["EGM_cfg"][sf], ele_eta, @@ -982,10 +1126,8 @@ def eleSFs(ele, correct_map, weights, syst=True, isHLT=False): sfs_down = np.where( masknone, 1.0, - correct_map["EGM"][ - list(correct_map["EGM"].keys())[0] - ].evaluate( - sf[sf.find(" ") + 1 :], + correct_map["EGM"][sf.split(" ")[2]].evaluate( + sf.split(" ")[1], "sfdown", correct_map["EGM_cfg"][sf], ele_eta, @@ -1063,12 +1205,14 @@ def muSFs(mu, correct_map, weights, syst=False, isHLT=False): mu = allmu[:, nmu] masknone = ak.is_none(mu.pt) - mu_pt = np.where(mu.pt < 15, 15, mu.pt) - mu_eta = np.where(np.abs(mu.eta) >= 2.4, 2.39, np.abs(mu.eta)) + mu_pt = np.clip(mu.pt, 15.0, 199.9) + mu_eta = np.clip(np.abs(mu.eta), 0.0, 2.4) mask = mu_pt > 30 sfs = 1.0 if "correctionlib" in str(type(correct_map["MUO"])): - if "ID" in sf or "Reco" in sf: + if ("ID" in sf or "Reco" in sf) and "Summer22" not in correct_map[ + "campaign" + ]: mu_pt = ak.fill_none(np.where(mu.pt < 30, 30, mu.pt), 30) mu_pt_low = ak.fill_none(np.where(mu.pt >= 30, 30, mu.pt), 30) sfs_low = np.where( @@ -1116,29 +1260,56 @@ def muSFs(mu, correct_map, weights, syst=False, isHLT=False): ) else: - sfs = np.where( - masknone, - 1.0, - correct_map["MUO"][correct_map["MUO_cfg"][sf]].evaluate( - sf[sf.find(" ") + 1 :], mu_eta, mu_pt, "sf" - ), - ) - - if syst: - sfs_up = np.where( + if "Summer22" not in correct_map["campaign"]: + sfs = np.where( masknone, 1.0, correct_map["MUO"][correct_map["MUO_cfg"][sf]].evaluate( - sf[sf.find(" ") + 1 :], mu_eta, mu_pt, "systup" + correct_map["MUO_cfg"][sf.split(" ")[1]], + mu_eta, + mu_pt, + "sf", ), ) - sfs_down = np.where( + else: + sfs = np.where( masknone, 1.0, correct_map["MUO"][correct_map["MUO_cfg"][sf]].evaluate( - sf[sf.find(" ") + 1 :], mu_eta, mu_pt, "systdown" + mu_eta, mu_pt, "nominal" ), ) + if syst: + if "Summer22" not in correct_map["campaign"]: + sfs_up = np.where( + masknone, + 1.0, + correct_map["MUO"][correct_map["MUO_cfg"][sf]].evaluate( + correct_map["MUO_cfg"][sf.split(" ")[1]], + mu_eta, + mu_pt, + "systup", + ), + ) + sfs_down = np.where( + masknone, + 1.0, + correct_map["MUO"][correct_map["MUO_cfg"][sf]].evaluate( + correct_map["MUO_cfg"][sf.split(" ")[1]], + mu_eta, + mu_pt, + "systdown", + ), + ) + else: + sf_unc = np.where( + masknone, + 0.0, + correct_map["MUO"][correct_map["MUO_cfg"][sf]].evaluate( + mu_eta, mu_pt, "syst" + ), + ) + sfs_up, sfs_down = 1.0 + sf_unc, 1.0 - sf_unc else: if "mu" in sf: sfs = np.where( @@ -1352,3 +1523,130 @@ def add_scalevar_3pt(weights, lhe_weights): down = np.ones(len(weights.weight())) weights.add("scalevar_3pt", nom, up, down) + + +# JP calibration utility +class JPCalibHandler(object): + def __init__(self, campaign, isRealData, dataset): + r""" + A tool for calculating the track probability and jet probability + campaign: campaign name + isRealData: whether the dataset is real data + dataset: dataset name from events.metadata["dataset"] + """ + if isRealData: + for key in config[campaign]["JPCalib"]: + if key in dataset: + filename = config[campaign]["JPCalib"][key] + break + else: + raise ValueError(f"No JPCalib file found for dataset {dataset}") + else: + filename = config[campaign]["JPCalib"]["MC"] + + # print(f'Using JPCalib file {filename}') + + templates = uproot.open( + f"src/BTVNanoCommissioning/data/JPCalib/{campaign}/{filename}" + ) + self.ipsig_histo_val = np.array( + [templates[f"histoCat{i}"].values() for i in range(10)] + ) + self.ipsig_histo_tot = np.sum(self.ipsig_histo_val, axis=1) + self.values_cumsum = np.cumsum(self.ipsig_histo_val[:, ::-1], axis=1)[:, ::-1] + self.edges = templates["histoCat0"].axes[0].edges() + + def flatten(self, array): + r""" + Get the fully flattened array and its layout for each layer + """ + layouts = [] + array_fl = array + while str(ak.type(array_fl)).count("*") > 1: + layouts.append(ak.num(array_fl)) + array_fl = ak.flatten(array_fl) + return array_fl, layouts + + def unflatten(self, array_fl, layouts): + r""" + Recover a flattened array using the original layouts + """ + array = array_fl + for layout in layouts[::-1]: + array = ak.unflatten(array, layout) + return array + + def calc_track_proba(self, ipsig: ak.Array, cat: ak.Array): + r""" + Calculate the track probability from the integral of the track IPsig templates, given the IPsig and category. + Reference code: https://github.com/cms-sw/cmssw/blob/CMSSW_13_0_X/RecoBTag/TrackProbability/src/HistogramProbabilityEstimator.cc + ipsig: IP significance array + cat: category array (0-9) + """ + + if ak.any(cat < 0) or ak.any(cat > 9): + raise ValueError("Category out of range [0, 9]") + + # get the fully flattened array of the input while storing its layouts for later recovery + ipsig_fl, layouts = self.flatten(ipsig) + cat_fl = ak.flatten(cat, axis=None) + + # index of the IPsig bins + ipsig_fl = abs(ipsig_fl) + ipsig_fl_index = np.minimum( + np.searchsorted(self.edges, ipsig_fl), self.ipsig_histo_val.shape[1] - 1 + ) + + # retrieve the cumsum value (\int_{ipsig}^{inf} p(ipsig') d(ipsig')) from the correct template + ipsig_cumsum_fl = self.values_cumsum[cat_fl, ipsig_fl_index] + + # calculate the track probability as (\int_{ipsig}^{inf} ..) / (\int_{0}^{inf} ..) * sign(IPsig) + proba_fl = (ipsig_cumsum_fl / self.ipsig_histo_tot[cat_fl]) * np.sign(ipsig_fl) + + # recover the original layout + proba = self.unflatten(proba_fl, layouts) + return proba + + def calc_jet_proba(self, proba): + # Calculate jet probability (JP) + # according to jetProbability func in https://github.com/cms-sw/cmssw/blob/CMSSW_13_0_X/RecoBTag/ImpactParameter/interface/TemplatedJetProbabilityComputer.h + + # minium proba = 0.5% + proba = np.maximum(proba, 0.005) # dim: (evt, jet, trk) + + ntrk = ak.num(proba, axis=-1) # dim: (evt, jet), the number of tracks in a jet + prodproba_log = ak.sum( + np.log(proba), axis=-1 + ) # dim: (evt, jet), the log(Π(proba)) of all tracks in a jet + prodproba_log_m_log = ak.where( + (ak.num(proba, axis=-1) >= 2) & (prodproba_log < 0), + np.log(-prodproba_log), + 0, + ) # log(-logΠ), if >=2 tracks in a jet + + # now calculating Σ_tr{0..N-1} ((-logΠ)^tr / tr!) + trk_index = ak.local_index(proba) + fact_array = ak.concatenate( + [ + [1.0], + np.arange(1, max(5, ak.max(trk_index) + 1), dtype=np.float64).cumprod(), + ] + ) # construct a factorial array + trk_index_fl, _layouts = self.flatten(trk_index) + lfact = self.unflatten( + fact_array[trk_index_fl], _layouts + ) # dim: (evt, jet, trk), nested factorial array given the track index + + prob = ak.sum( + np.exp(trk_index * prodproba_log_m_log - np.log(lfact)), axis=-1 + ) # dim: (evt, jet), Σ_tr{0..N-1} ((-logΠ)^tr / tr!) + + prob_jet = np.minimum( + np.exp(np.maximum(np.log(np.maximum(prob, 1e-30)) + prodproba_log, -30.0)), + 1.0, + ) # dim: (evt, jet), calculating Π * Σ_tr{0..N-1} ((-logΠ)^tr / tr!) + + prob_jet = ak.where(prodproba_log < 0, prob_jet, 1.0) + prob_jet = np.maximum(prob_jet, 1e-30) + + return prob_jet diff --git a/src/BTVNanoCommissioning/utils/histogrammer.py b/src/BTVNanoCommissioning/utils/histogrammer.py index 31778f61..dbf16f2c 100644 --- a/src/BTVNanoCommissioning/utils/histogrammer.py +++ b/src/BTVNanoCommissioning/utils/histogrammer.py @@ -29,7 +29,15 @@ def histogrammer(events, workflow): n_axis = Hist.axis.Integer(0, 10, name="n", label="N obj") osss_axis = Hist.axis.IntCategory([1, -1], name="osss", label="OS(+)/SS(-)") ### Workflow specific - if "validation" == workflow: + if "example" == workflow: + obj_list = [ + "jet", + "mu", + ] # store basic 4-vector, pt,eta, phi, mass for the object + _hist_dict[f"dr_mujet"] = Hist.Hist( + syst_axis, flav_axis, dr_axis, Hist.storage.Weight() + ) # create cutstomize histogram + elif "validation" == workflow: obj_list = ["jet0", "jet1"] elif "QCD" == workflow: obj_list = ["jet0"] @@ -123,7 +131,6 @@ def histogrammer(events, workflow): _hist_dict[f"{i}_ptratio"] = Hist.Hist( syst_axis, flav_axis, ptratio_axis, Hist.storage.Weight() ) - elif "ctag_ttsemilep_sf" in workflow: obj_list = ["hl", "soft_l", "MET", "z", "w", "mujet"] _hist_dict["z_mass"] = Hist.Hist( @@ -170,7 +177,6 @@ def histogrammer(events, workflow): _hist_dict[f"{i}_ptratio"] = Hist.Hist( syst_axis, flav_axis, ptratio_axis, Hist.storage.Weight() ) - elif "Wc_sf" in workflow: obj_list = ["hl", "soft_l", "MET", "z", "w", "mujet"] _hist_dict["SV_charge"] = Hist.Hist( @@ -231,7 +237,6 @@ def histogrammer(events, workflow): _hist_dict[f"{i}_ptratio"] = Hist.Hist( syst_axis, flav_axis, osss_axis, ptratio_axis, Hist.storage.Weight() ) - elif "DY_sf" in workflow: obj_list = ["posl", "negl", "z", "jet"] _hist_dict["z_mass"] = Hist.Hist( @@ -248,7 +253,8 @@ def histogrammer(events, workflow): syst_axis, dxy_axis, Hist.storage.Weight() ) _hist_dict[f"{i}_dz"] = Hist.Hist(syst_axis, dz_axis, Hist.storage.Weight()) - ### Common kinematic variables + + ### Common kinematic variables histogram creation if "Wc_sf" not in workflow: _hist_dict["njet"] = Hist.Hist(syst_axis, n_axis, Hist.storage.Weight()) if "ctag_tt" in workflow: @@ -375,17 +381,54 @@ def histogrammer(events, workflow): disc_list = [ "btagDeepB", "btagDeepC", - "btagDeepFlavB", - "btagDeepFlavC", + "btagDeepB_b", + "btagDeepB_bb", "btagDeepCvL", "btagDeepCvB", + "btagDeepFlavB", + "btagDeepFlavC", + "btagTransDeepFlavB", + "btagTransDeepFlavC", "btagDeepFlavCvL", "btagDeepFlavCvB", - "btagDeepB_b", - "btagDeepB_bb", "btagDeepFlavB_b", "btagDeepFlavB_bb", - "btagDeepFlavB_lepb", + "btagTransDeepFlavB_lepb", + "btagTransDeepFlavB_b", + "btagTransDeepFlavB_bb", + "btagTransDeepFlavB_lepb", + "btagPNetB", + "btagTransPNetB", + "btagPNetCvB", + "btagPNetCvL", + "btagPNetProbB", + "btagPNetProbC", + "btagPNetProbG", + "btagPNetProbUDS", + "btagTransPNetProbB", + "btagTransPNetProbC", + "btagTransPNetProbG", + "btagTransPNetProbUDS", + "btagPNetQvG", + "btagPNetTauVJet", + "btagRobustParTAK4B", + "btagRobustParTAK4B_b", + "btagRobustParTAK4B_bb", + "btagRobustParTAK4B_lepb", + "btagRobustParTAK4C", + "btagRobustParTAK4G", + "btagRobustParTAK4UDS", + "btagTransRobustParTAK4B", + "btagTransRobustParTAK4B_b", + "btagTransRobustParTAK4B_bb", + "btagTransRobustParTAK4B_lepb", + "btagTransRobustParTAK4C", + "btagTransRobustParTAK4G", + "btagTransRobustParTAK4UDS", + "btagRobustParTAK4CvB", + "btagRobustParTAK4CvL", + "btagRobustParTAK4QG", + ## Negative tagger "btagNegDeepFlavB", "btagNegDeepFlavB_b", "btagNegDeepFlavB_bb", @@ -413,25 +456,7 @@ def histogrammer(events, workflow): "btagNegRobustParTAK4G", "btagNegRobustParTAK4QG", "btagNegRobustParTAK4UDS", - "btagPNetB", - "btagPNetCvB", - "btagPNetCvL", - "btagPNetProbB", - "btagPNetProbC", - "btagPNetProbG", - "btagPNetProbUDS", - "btagPNetQvG", - "btagPNetTauVJet", - "btagRobustParTAK4B", - "btagRobustParTAK4B_b", - "btagRobustParTAK4B_bb", - "btagRobustParTAK4B_lepb", - "btagRobustParTAK4C", - "btagRobustParTAK4CvB", - "btagRobustParTAK4CvL", - "btagRobustParTAK4G", - "btagRobustParTAK4QG", - "btagRobustParTAK4UDS", + # other prob info "PNetRegPtRawCorr", "PNetRegPtRawCorrNeutrino", "PNetRegPtRawRes", @@ -440,7 +465,7 @@ def histogrammer(events, workflow): "ProbaN", ] for disc in disc_list: - if disc not in events.Jet.fields: + if disc not in events.Jet.fields and "Trans" not in disc: continue njet = 1 if "ttdilep_sf" in workflow: @@ -449,12 +474,20 @@ def histogrammer(events, workflow): njet = 4 for i in range(njet): if "Wc_sf" in workflow: - if "btag" in disc or "ProbaN" == disc: + if "Trans" in disc: _hist_dict[f"{disc}_{i}"] = Hist.Hist( syst_axis, flav_axis, osss_axis, - Hist.axis.Regular(30, -0.2, 1, name="discr", label=disc), + Hist.axis.Regular(40, 0, 8, name="discr", label=disc), + Hist.storage.Weight(), + ) + elif "btag" in disc or "ProbaN" == disc: + _hist_dict[f"{disc}_{i}"] = Hist.Hist( + syst_axis, + flav_axis, + osss_axis, + Hist.axis.Regular(60, -0.2, 1, name="discr", label=disc), Hist.storage.Weight(), ) elif "Bprob" in disc: @@ -483,6 +516,13 @@ def histogrammer(events, workflow): ) else: + if "Trans" in disc: + _hist_dict[f"{disc}_{i}"] = Hist.Hist( + syst_axis, + flav_axis, + Hist.axis.Regular(40, 0, 8, name="discr", label=disc), + Hist.storage.Weight(), + ) if "btag" in disc or "ProbaN" == disc: _hist_dict[f"{disc}_{i}"] = Hist.Hist( syst_axis, diff --git a/src/BTVNanoCommissioning/utils/plot_utils.py b/src/BTVNanoCommissioning/utils/plot_utils.py index 55ea0b83..e9ba53ad 100644 --- a/src/BTVNanoCommissioning/utils/plot_utils.py +++ b/src/BTVNanoCommissioning/utils/plot_utils.py @@ -12,7 +12,120 @@ "alpha": 0.4, } markers = [".", "o", "^", "s", "+", "x", "D", "*"] - +color_map = { + "$t\\bar{t}$": "#008695", + "Single top": "#3969ac", + "VV": "#7f3c8d", + "Z+jets": "#e68310", + "W+jets": "#80ba5a", + "QCD": "#e73f74", + "QCD($\\mu$)": "#a5aa99", + "udsg": "tab:blue", + "pu": "tab:orange", + "c": "tab:green", + "b": "tab:red", +} +sample_mergemap = { + # ttbar + "$t\\bar{t}$": [ + "TTto2L2Nu_TuneCP5_13p6TeV_powheg-pythia8", + "TTto4Q_TuneCP5_13p6TeV_powheg-pythia8", + "TTtoLNu2Q_TuneCP5_13p6TeV_powheg-pythia8", + "TTTo2J1L1Nu_CP5_13p6TeV_powheg-pythia8", + ], + # single top + "Single top": [ + "TbarBQ_t-channel_4FS_CP5_13p6TeV_powheg-madspin-pythia8", + "TBbarQ_t-channel_4FS_CP5_13p6TeV_powheg-madspin-pythia8", + "TWminus_DR_AtLeastOneLepton_CP5_13p6TeV_powheg-pythia8", + "TbarBQ_t-channel_4FS_CP5_13p6TeV_powheg-madspin-pythia8", + "TbarWplus_DR_AtLeastOneLepton_CP5_13p6TeV_powheg-pythia8", + # decay + "TWminusto4Q_TuneCP5_13p6TeV_powheg-pythia8", + "TWminustoLNu2Q_TuneCP5_13p6TeV_powheg-pythia8", + "TWminusto2L2Nu_TuneCP5_13p6TeV_powheg-pythia8", + "TbarWplusto4Q_TuneCP5_13p6TeV_powheg-pythia8", + "TbarWplustoLNu2Q_TuneCP5_13p6TeV_powheg-pythia8", + "TbarWplusto2L2Nu_TuneCP5_13p6TeV_powheg-pythia8", + "TBbarQ_t-channel_4FS_TuneCP5_13p6TeV_powheg-madspin-pythia8", + "TbarBQ_t-channel_4FS_TuneCP5_13p6TeV_powheg-madspin-pythia8", + ], + # diboson + "VV": [ + "WW_TuneCP5_13p6TeV-pythia8", + "WZ_TuneCP5_13p6TeV-pythia8", + "ZZ_TuneCP5_13p6TeV-pythia8" + # decay + "ZZto2L2Q_TuneCP5_13p6TeV_powheg-pythia8", + "ZZto2Nu2Q_TuneCP5_13p6TeV_powheg-pythia8", + "ZZto4L_TuneCP5_13p6TeV_powheg-pythia8", + "ZZto2L2Nu_TuneCP5_13p6TeV_powheg-pythia8", + "WZtoLNu2Q_TuneCP5_13p6TeV_powheg-pythia8", + "WZto2L2Q_TuneCP5_13p6TeV_powheg-pythia8", + "WZto3LNu_TuneCP5_13p6TeV_powheg-pythia8", + "WWto4Q_TuneCP5_13p6TeV_powheg-pythia8", + "WWtoLNu2Q_TuneCP5_13p6TeV_powheg-pythia8", + "WWto2L2Nu_TuneCP5_13p6TeV_powheg-pythia8", + ], + "Z+jets": [ + "DYto2L-2Jets_MLL-10to50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8", + "DYto2L-2Jets_MLL-50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8", + "DYJetsToLL_M-10to50_TuneCP5_13p6TeV-madgraphMLM-pythia8", + "DYJetsToLL_M-50_TuneCP5_13p6TeV-madgraphMLM-pythia8", + ], + "W+jets": [ + "WJetsToLNu_TuneCP5_13p6TeV-madgraphMLM-pythia8", + "WtoLNu-4Jets_TuneCP5_13p6TeV_madgraphMLM-pythia8", + # jet binned sample + "WtoLNu-4Jets_1J_TuneCP5_13p6TeV_madgraphMLM-pythia8", + "WtoLNu-4Jets_2J_TuneCP5_13p6TeV_madgraphMLM-pythia8", + "WtoLNu-4Jets_3J_TuneCP5_13p6TeV_madgraphMLM-pythia8", + ], + # QCD + "QCD": [ + "QCD_PT-15to30_TuneCP5_13p6TeV_pythia8", + "QCD_PT-30to50_TuneCP5_13p6TeV_pythia8", + "QCD_PT-50to80_TuneCP5_13p6TeV_pythia8", + "QCD_PT-50to80_TuneCP5_13p6TeV_pythia8", + "QCD_PT-80to120_TuneCP5_13p6TeV_pythia8", + "QCD_PT-120to170_TuneCP5_13p6TeV_pythia8", + "QCD_PT-170to300_TuneCP5_13p6TeV_pythia8", + "QCD_PT-170to300_TuneCP5_13p6TeV_pythia8", + "QCD_PT-300to470_TuneCP5_13p6TeV_pythia8", + "QCD_PT-300to470_TuneCP5_13p6TeV_pythia8", + "QCD_PT-470to600_TuneCP5_13p6TeV_pythia8", + "QCD_PT-470to600_TuneCP5_13p6TeV_pythia8", + "QCD_PT-600to800_TuneCP5_13p6TeV_pythia8", + "QCD_PT-600to800_TuneCP5_13p6TeV_pythia8", + "QCD_PT-800to1000_TuneCP5_13p6TeV_pythia8", + "QCD_PT-800to1000_TuneCP5_13p6TeV_pythia8", + "QCD_PT-1000to1400_TuneCP5_13p6TeV_pythia8", + "QCD_PT-1000to1400_TuneCP5_13p6TeV_pythia8", + "QCD_PT-1400to1800_TuneCP5_13p6TeV_pythia8", + "QCD_PT-1400to1800_TuneCP5_13p6TeV_pythia8", + "QCD_PT-1800to2400_TuneCP5_13p6TeV_pythia8", + "QCD_PT-1800to2400_TuneCP5_13p6TeV_pythia8", + "QCD_PT-2400to3200_TuneCP5_13p6TeV_pythia8", + "QCD_PT-2400to3200_TuneCP5_13p6TeV_pythia8", + "QCD_PT-3200_TuneCP5_13p6TeV_pythia8", + "QCD_PT-3200_TuneCP5_13p6TeV_pythia8", + ], + # QCD muon enriched + "QCD($\\mu$)": [ + "QCD_PT-15to20_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-20to30_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-30to50_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-50to80_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-80to120_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-120to170_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-170to300_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-300to470_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-470to600_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-600to800_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-800to1000_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + "QCD_PT-1000_MuEnrichedPt5_TuneCP5_13p6TeV_pythia8", + ], +} ### copy functions coffea.hist.plotratio https://github.com/CoffeaTeam/coffea/blob/master/coffea/hist/plot.py to boost-hist ################ ## ratio plot ## diff --git a/src/BTVNanoCommissioning/utils/selection.py b/src/BTVNanoCommissioning/utils/selection.py index 4abede55..daed3fb7 100644 --- a/src/BTVNanoCommissioning/utils/selection.py +++ b/src/BTVNanoCommissioning/utils/selection.py @@ -30,28 +30,19 @@ def jet_id(events, campaign): ## FIXME: Electron cutbased Id & MVA ID not exist in Winter22Run3 sample def ele_cuttightid(events, campaign): - if "Run3" not in campaign: - elemask = ( - (abs(events.Electron.eta) < 1.4442) - | ((abs(events.Electron.eta) < 2.5) & (abs(events.Electron.eta) > 1.566)) - ) & (events.Electron.cutBased > 3) - else: - elemask = (abs(events.Electron.eta) < 1.4442) | ( - (abs(events.Electron.eta) < 2.5) & (abs(events.Electron.eta) > 1.566) - ) + elemask = ( + (abs(events.Electron.eta) < 1.4442) + | ((abs(events.Electron.eta) < 2.5) & (abs(events.Electron.eta) > 1.566)) + ) & (events.Electron.cutBased > 3) return elemask def ele_mvatightid(events, campaign): - if "Run3" not in campaign: - elemask = ( - (abs(events.Electron.eta) < 1.4442) - | ((abs(events.Electron.eta) < 2.5) & (abs(events.Electron.eta) > 1.566)) - ) & (events.Electron.mvaFall17V2Iso_WP80 > 0.5) - else: - elemask = (abs(events.Electron.eta) < 1.4442) | ( - (abs(events.Electron.eta) < 2.5) & (abs(events.Electron.eta) > 1.566) - ) + elemask = ( + (abs(events.Electron.eta) < 1.4442) + | ((abs(events.Electron.eta) < 2.5) & (abs(events.Electron.eta) > 1.566)) + ) & (events.Electron.mvaIso_WP80 > 0.5) + return elemask @@ -90,4 +81,4 @@ def jet_cut(events, campaign): & (events.Jet.pt > 180) & (events.Jet.jetId >= 5) ) - return multijetmask \ No newline at end of file + return multijetmask diff --git a/src/BTVNanoCommissioning/workflows/BTA_producer.py b/src/BTVNanoCommissioning/workflows/BTA_producer.py index c31c2ea7..d4a754d0 100644 --- a/src/BTVNanoCommissioning/workflows/BTA_producer.py +++ b/src/BTVNanoCommissioning/workflows/BTA_producer.py @@ -1,4 +1,4 @@ -import collections +import collections, os import awkward as ak import numpy as np import uproot @@ -14,7 +14,7 @@ calc_ip_vector, ) from BTVNanoCommissioning.helpers.func import update -from BTVNanoCommissioning.utils.correction import load_SF, JME_shifts +from BTVNanoCommissioning.utils.correction import load_SF, JME_shifts, JPCalibHandler ## Based on coffea_array_producer.ipynb from Congqiao @@ -404,21 +404,69 @@ def process_shift(self, events, shift_name): # 'pileup_tightID':ak.values_astype((jet.puId & (1 << 0) > 0) | (jet.pt > 50.), int) , # 'pileup_mediumID': ak.values_astype((jet.puId & (1 << 1) > 0) | (jet.pt > 50.), int) , # 'pileup_looseID': ak.values_astype((jet.puId & (1 << 2) > 0) | (jet.pt > 50.), int) , - # taggers/vars // JP/JBP to be calibrated.. !!! + # taggers/vars "area": jet.area, - "Proba": jet.Proba, - "ProbaN": jet.ProbaN, - "Bprob": jet.Bprob, - "BprobN": jet.BprobN, - # Deep Jet + # DeepJet "DeepFlavourBDisc": jet.btagDeepFlavB, "DeepFlavourCvsLDisc": jet.btagDeepFlavCvL, "DeepFlavourCvsBDisc": jet.btagDeepFlavCvB, + "DeepFlavourBDisc_b": jet.btagDeepFlavB_b, + "DeepFlavourBDisc_bb": jet.btagDeepFlavB_bb, + "DeepFlavourBDisc_lepb": jet.btagDeepFlavB_lepb, "DeepFlavourCDisc": jet.btagDeepFlavC, + "DeepFlavourUDSDisc": jet.btagDeepFlavUDS, + "DeepFlavourGDisc": jet.btagDeepFlavG, "DeepFlavourBDiscN": jet.btagNegDeepFlavB, "DeepFlavourCvsLDiscN": jet.btagNegDeepFlavCvL, "DeepFlavourCvsBDiscN": jet.btagNegDeepFlavCvB, + "DeepFlavourBDisc_bN": jet.btagNegDeepFlavB_b, + "DeepFlavourBDisc_bbN": jet.btagNegDeepFlavB_bb, + "DeepFlavourBDisc_lepbN": jet.btagNegDeepFlavB_lepb, + "DeepFlavourQGDiscN": jet.btagNegDeepFlavQG, "DeepFlavourCDiscN": jet.btagNegDeepFlavC, + "DeepFlavourUDSDiscN": jet.btagNegDeepFlavUDS, + "DeepFlavourGDiscN": jet.btagNegDeepFlavG, + # ParticleNet + "PNetBDisc": jet.btagPNetB, + "PNetCvsLDisc": jet.btagPNetCvL, + "PNetCvsBDisc": jet.btagPNetCvB, + "PNetQvsGDisc": jet.btagPNetQvG, + "PNetTauvsJetDisc": jet.btagPNetTauVJet, + "PNetRegPtRawCorr": jet.PNetRegPtRawCorr, + "PNetRegPtRawCorrNeutrino": jet.PNetRegPtRawCorrNeutrino, + "PNetRegPtRawRes": jet.PNetRegPtRawRes, + "PNetBDisc_b": jet.btagPNetProbB, + "PNetCDisc": jet.btagPNetProbC, + "PNetUDSDisc": jet.btagPNetProbUDS, + "PNetGDisc": jet.btagPNetProbG, + "PNetBDiscN": jet.btagNegPNetB, + "PNetCvsLDiscN": jet.btagNegPNetCvL, + "PNetCvsBDiscN": jet.btagNegPNetCvB, + "PNetBDisc_bN": jet.btagNegPNetProbB, + "PNetCDiscN": jet.btagNegPNetProbC, + "PNetUDSDiscN": jet.btagNegPNetProbUDS, + "PNetGDiscN": jet.btagNegPNetProbG, + # ParticleTransformer + "ParTBDisc": jet.btagRobustParTAK4B, + "ParTCvsLDisc": jet.btagRobustParTAK4CvL, + "ParTCvsBDisc": jet.btagRobustParTAK4CvB, + "ParTQvsGDisc": jet.btagRobustParTAK4QG, + "ParTBDisc_b": jet.btagRobustParTAK4B_b, + "ParTBDisc_bb": jet.btagRobustParTAK4B_bb, + "ParTBDisc_lepb": jet.btagRobustParTAK4B_lepb, + "ParTCDisc": jet.btagRobustParTAK4C, + "ParTUDSDisc": jet.btagRobustParTAK4UDS, + "ParTGDisc": jet.btagRobustParTAK4G, + "ParTBDiscN": jet.btagNegRobustParTAK4B, + "ParTCvsLDiscN": jet.btagNegRobustParTAK4CvL, + "ParTCvsBDiscN": jet.btagNegRobustParTAK4CvB, + "ParTQvsGDiscN": jet.btagNegRobustParTAK4QG, + "ParTBDisc_bN": jet.btagNegRobustParTAK4B_b, + "ParTBDisc_bbN": jet.btagNegRobustParTAK4B_bb, + "ParTBDisc_lepbN": jet.btagNegRobustParTAK4B_lepb, + "ParTCDiscN": jet.btagNegRobustParTAK4C, + "ParTUDSDiscN": jet.btagNegRobustParTAK4UDS, + "ParTGDiscN": jet.btagNegRobustParTAK4G, } ) if isRealData: @@ -441,10 +489,15 @@ def process_shift(self, events, shift_name): ) # genJet pT - genJetIdx = jet.genJetIdx.mask[ - (jet.genJetIdx >= ak.num(events.GenJet)) & (jet.genJetIdx < 0) - ] # in case the genJet index out of range - Jet["genpt"] = ak.fill_none(events.GenJet[genJetIdx].pt, -1) + genJetIdx = ak.where( + (jet.genJetIdx < ak.num(events.GenJet)) & (jet.genJetIdx != -1), + jet.genJetIdx, + zeros, + ) # in case the genJet index out of range + + Jet["genpt"] = ak.where( + jet.genJetIdx != -1, events.GenJet[genJetIdx].pt, -99 + ) # gen-level jet cleaning aginst prompt leptons genlep_prompt = genlep[(Genlep.mother != 0) & (Genlep.mother % 10 == 0)] @@ -466,9 +519,257 @@ def process_shift(self, events, shift_name): # jet cleaning aginst pileup Jet["flavourCleaned"] = ak.where( - Jet["genpt"] < 8.0, zeros, Jet["flavourCleaned"] + (Jet["genpt"] < 8.0) & (Jet["genpt"] > 0.0), + zeros, + Jet["flavourCleaned"], + ) + + # Re-calculate jet probability (JP) and jet B probability (JBP) taggers + + # select full track collection based on CandIPProducer + # reference code https://github.com/cms-sw/cmssw/blob/master/RecoBTag/ImpactParameter/plugins/IPProducer.h + trkj = events.JetPFCands[ + (events.JetPFCands.pf.trkQuality != 0) & (events.JetPFCands.pt > 1.0) + ] + + # selection based on CandIPProducer & BTA + trkj = trkj[ + (trkj.pf.numberOfHits >= 0) + & (trkj.pf.numberOfPixelHits >= 1) + & (trkj.pf.trkChi2 <= 5) + & (abs(trkj.dxyFromPV) < 0.2) + & (abs(trkj.dzFromPV) < 17) + & (abs(trkj.btagJetDistVal) <= 0.07) + & (trkj.btagDecayLenVal < 5) + ] + + pair = ak.cartesian( + [jet, trkj], axis=1, nested=True + ) # dim: (event, jet, pfcand) + + # first loosely matches tracks with jets with deltaR < 0.4 + # for calculating JP, deltaR < 0.3 is further required + matched = (pair["0"].pt_orig == pair["1"].jet.pt) & ( + pair["0"].delta_r(pair["1"].pf) < 0.4 + ) + + trkj_jetbased = pair["1"][matched] # dim: (event, jet, pfcand) + + # calculate basic kinematics + trkj_jetbased["pvec"] = ak.zip( + { + "pt": trkj_jetbased.pf.trkPt, + "eta": trkj_jetbased.pf.trkEta, + "phi": trkj_jetbased.pf.trkPhi, + "mass": trkj_jetbased.pf.mass, + }, + behavior=vector.behavior, + with_name="PtEtaPhiMLorentzVector", + ) + # deltaR(jet, track) used for further selection + trkj_jetbased["dr_jet"] = trkj_jetbased.pf.delta_r(jet) + + # calculate IP variables + # (same with PFMuon, use the jet direction as reference to determine the IP signs) + ip2dvec = calc_ip_vector( + trkj_jetbased.pf, + trkj_jetbased.dxyFromPV, + trkj_jetbased.dzFromPV, + is_3d=False, + ) + ip3dvec = calc_ip_vector( + trkj_jetbased.pf, + trkj_jetbased.dxyFromPV, + trkj_jetbased.dzFromPV, + is_3d=True, + ) + trkj_jetbased["sign2D"] = ak.values_astype(np.sign(ip2dvec.dot(jet)), int) + trkj_jetbased["sign3D"] = ak.values_astype(np.sign(ip3dvec.dot(jet)), int) + trkj_jetbased["IP3D"] = ip3dvec.p + + trkj_jetbased["isHitL1"] = ak.values_astype( + trkj_jetbased.pf.lostInnerHits == -1, int + ) # according to definition of lostInnerHits + + # assign categories (findCat in BTA) + cats = { + 0: dict( + withFirstPixel=-1, + nPixelHitsRange=(1, 99), + etaRange=(0.0, 4.5), + pRange=(1.0, 999.0), + nHitsRange=(1, 50), + chiRange=(0, 5), + ), + 1: dict( + withFirstPixel=1, + nPixelHitsRange=(1, 3), + etaRange=(0.0, 4.5), + pRange=(1.0, 999.0), + nHitsRange=(1, 50), + chiRange=(0, 5), + ), + 2: dict( + withFirstPixel=1, + nPixelHitsRange=(4, 99), + etaRange=(0.0, 1.0), + pRange=(1.0, 3.0), + nHitsRange=(1, 50), + chiRange=(0, 5), + ), + 3: dict( + withFirstPixel=1, + nPixelHitsRange=(4, 99), + etaRange=(0.0, 1.0), + pRange=(3.0, 6.0), + nHitsRange=(1, 50), + chiRange=(0, 5), + ), + 4: dict( + withFirstPixel=1, + nPixelHitsRange=(4, 99), + etaRange=(0.0, 1.0), + pRange=(6.0, 999.0), + nHitsRange=(1, 50), + chiRange=(0, 5), + ), + 5: dict( + withFirstPixel=1, + nPixelHitsRange=(4, 99), + etaRange=(1.0, 2.0), + pRange=(1.0, 6.0), + nHitsRange=(1, 50), + chiRange=(0, 5), + ), + 6: dict( + withFirstPixel=1, + nPixelHitsRange=(4, 99), + etaRange=(1.0, 2.0), + pRange=(6.0, 12.0), + nHitsRange=(1, 50), + chiRange=(0, 5), + ), + 7: dict( + withFirstPixel=1, + nPixelHitsRange=(4, 99), + etaRange=(1.0, 2.0), + pRange=(12.0, 999.0), + nHitsRange=(1, 50), + chiRange=(0, 5), + ), + 8: dict( + withFirstPixel=1, + nPixelHitsRange=(4, 99), + etaRange=(2.0, 4.5), + pRange=(1.0, 18.0), + nHitsRange=(1, 50), + chiRange=(0, 5), + ), + 9: dict( + withFirstPixel=1, + nPixelHitsRange=(4, 99), + etaRange=(2.0, 4.5), + pRange=(18.0, 999.0), + nHitsRange=(1, 50), + chiRange=(0, 5), + ), + } + pass_cat = lambda t, i: ( + ( + ((cats[i]["withFirstPixel"] == 1) & (t.isHitL1 == 1)) + | ((cats[i]["withFirstPixel"] == -1) & (t.isHitL1 == 0)) + | (cats[i]["withFirstPixel"] == 0) + ) + & ( + (t.pf.numberOfPixelHits >= cats[i]["nPixelHitsRange"][0]) + & (t.pf.numberOfPixelHits <= cats[i]["nPixelHitsRange"][1]) + ) + & ( + (abs(t.pf.trkEta) >= cats[i]["etaRange"][0]) + & (abs(t.pf.trkEta) <= cats[i]["etaRange"][1]) + ) + & ((t.pvec.p >= cats[i]["pRange"][0]) & (t.pvec.p <= cats[i]["pRange"][1])) + & ( + (t.pf.numberOfHits >= cats[i]["nHitsRange"][0]) + & (t.pf.numberOfHits <= cats[i]["nHitsRange"][1]) + ) + & ( + (t.pf.trkChi2 >= cats[i]["chiRange"][0]) + & (t.pf.trkChi2 <= cats[i]["chiRange"][1]) + ) + ) + + zeros = ak.zeros_like(trkj_jetbased.pt, dtype=int) + trkj_jetbased["category"] = zeros - 1 # initial category index: -1 + for idx in range(0, 10): + trkj_jetbased["category"] = ak.where( + (trkj_jetbased["category"] == -1) & pass_cat(trkj_jetbased, idx), + zeros + idx, + trkj_jetbased["category"], ) + # calculate track probability, based on IPsig and category + jpc = JPCalibHandler(self._campaign, isRealData, dataset) + trkj_jetbased["proba"] = jpc.calc_track_proba( + trkj_jetbased.btagSip3dSig, + ak.where(trkj_jetbased.category >= 0, trkj_jetbased.category, 0), + ) + + # then calculate JP/JBP + + # (a) obtain track probabilities used to calculate JP + # only select positive/negative IP tracks for positive/negative JP tagger + # also requiring dR < 0.3 + # reference code: https://github.com/cms-sw/cmssw/blob/CMSSW_13_0_X/RecoBTag/ImpactParameter/interface/TemplatedJetProbabilityComputer.h + trk_proba_pos = abs(trkj_jetbased["proba"])[ + (trkj_jetbased.btagSip3dSig > 0) + & (trkj_jetbased.dr_jet < 0.3) + & ((trkj_jetbased.category >= 0) & (trkj_jetbased.category < 10)) + ] + trk_proba_neg = abs(trkj_jetbased["proba"])[ + (trkj_jetbased.btagSip3dSig < 0) + & (trkj_jetbased.dr_jet < 0.3) + & ((trkj_jetbased.category >= 0) & (trkj_jetbased.category < 10)) + ] + Jet["Proba"] = -np.log10(jpc.calc_jet_proba(trk_proba_pos)) / 4.0 + Jet["ProbaN"] = -np.log10(jpc.calc_jet_proba(trk_proba_neg)) / 4.0 + + # (b) obtain track probabilities used to calculate positive JBP tagger + # use two sets: probabilities and probabilitiesB (select 4 highest IPsig tracks) + # reference code: https://github.com/cms-sw/cmssw/blob/CMSSW_13_0_X/RecoBTag/ImpactParameter/interface/TemplatedJetBProbabilityComputer.h + trk_proba_jbp_all = abs(trkj_jetbased["proba"])[ + ((trkj_jetbased.category >= 0) & (trkj_jetbased.category < 10)) + ] + trk_proba_jbp_pos = abs(trkj_jetbased["proba"])[ + (trkj_jetbased.btagSip3dSig > 0) + & ((trkj_jetbased.category >= 0) & (trkj_jetbased.category < 10)) + ] + trk_proba_jbp_neg = abs(trkj_jetbased["proba"])[ + (trkj_jetbased.btagSip3dSig < 0) + & ((trkj_jetbased.category >= 0) & (trkj_jetbased.category < 10)) + ] + trk_Bproba_jbp_pos = ak.sort(trk_proba_jbp_pos)[ + ak.local_index(trk_proba_jbp_pos) < 4 + ] # select up to 4 tracks + trk_Bproba_jbp_neg = ak.sort(trk_proba_jbp_neg)[ + ak.local_index(trk_proba_jbp_neg) < 4 + ] # select up to 4 tracks + + # for positive JBP tagger: probabilities include both pos+neg IP tracks; for negative JBP: use neg IP tracks only + Jet["Bprob"] = ( + -np.log(jpc.calc_jet_proba(trk_Bproba_jbp_pos)) / 4.0 + - np.log(jpc.calc_jet_proba(trk_proba_jbp_all)) / 4.0 + ) + Jet["BprobN"] = ( + -np.log(jpc.calc_jet_proba(trk_Bproba_jbp_neg)) / 4.0 + - np.log(jpc.calc_jet_proba(trk_proba_jbp_neg)) / 4.0 + ) + + # Jet["ProbaN"] = -np.log10(jpc.calc_jet_proba(trk_proba_neg)) / 4.0 + + ################# + # TagVarCSV # + ################# # CSV inputs per jets: retreived from the DeepCSV input given they are the same TagVarCSV = ak.zip( { @@ -695,192 +996,14 @@ def process_shift(self, events, shift_name): # Track # ############### - # select full track collection based on CandIPProducer - # reference code https://github.com/cms-sw/cmssw/blob/master/RecoBTag/ImpactParameter/plugins/IPProducer.h - - trkj = events.JetPFCands[ - (events.JetPFCands.pf.trkQuality != 0) & (events.JetPFCands.pt > 1.0) - ] - - # selection based on CandIPProducer & BTA - trkj = trkj[ - (trkj.pf.numberOfHits >= 0) - & (trkj.pf.numberOfPixelHits >= 1) - & (trkj.pf.trkChi2 <= 5) - & (abs(trkj.dxyFromPV) < 0.2) - & (abs(trkj.dzFromPV) < 17) - & (abs(trkj.btagJetDistVal) <= 0.07) - & (trkj.btagDecayLenVal < 5) - ] - - pair = ak.cartesian( - [jet, trkj], axis=1, nested=True - ) # dim: (event, jet, pfcand) - matched = (pair["0"].pt_orig == pair["1"].jet.pt) & ( - pair["0"].delta_r(pair["1"].pf) < 0.3 - ) # use deltaR < 0.3 according to BTA - - trkj_jetbased = pair["1"][matched] # dim: (event, jet, pfcand) - - # calculate basic kinematics - trkj_jetbased["pvec"] = ak.zip( - { - "pt": trkj_jetbased.pf.trkPt, - "eta": trkj_jetbased.pf.trkEta, - "phi": trkj_jetbased.pf.trkPhi, - "mass": trkj_jetbased.pf.mass, - }, - behavior=vector.behavior, - with_name="PtEtaPhiMLorentzVector", - ) - - # calculate IP variables - # (same with PFMuon, use the jet direction as reference to determine the IP signs) - ip2dvec = calc_ip_vector( - trkj_jetbased.pf, - trkj_jetbased.dxyFromPV, - trkj_jetbased.dzFromPV, - is_3d=False, - ) - ip3dvec = calc_ip_vector( - trkj_jetbased.pf, - trkj_jetbased.dxyFromPV, - trkj_jetbased.dzFromPV, - is_3d=True, - ) - trkj_jetbased["sign2D"] = ak.values_astype(np.sign(ip2dvec.dot(jet)), int) - trkj_jetbased["sign3D"] = ak.values_astype(np.sign(ip3dvec.dot(jet)), int) - trkj_jetbased["IP3D"] = ip3dvec.p - - trkj_jetbased["isHitL1"] = ak.values_astype( - trkj_jetbased.pf.lostInnerHits == -1, int - ) # according to definition of lostInnerHits - - # assign categories (findCat in BTA) - cats = { - 0: dict( - withFirstPixel=-1, - nPixelHitsRange=(1, 99), - etaRange=(0.0, 4.5), - pRange=(1.0, 999.0), - nHitsRange=(1, 50), - chiRange=(0, 5), - ), - 1: dict( - withFirstPixel=1, - nPixelHitsRange=(1, 3), - etaRange=(0.0, 4.5), - pRange=(1.0, 999.0), - nHitsRange=(1, 50), - chiRange=(0, 5), - ), - 2: dict( - withFirstPixel=1, - nPixelHitsRange=(4, 99), - etaRange=(0.0, 1.0), - pRange=(1.0, 3.0), - nHitsRange=(1, 50), - chiRange=(0, 5), - ), - 3: dict( - withFirstPixel=1, - nPixelHitsRange=(4, 99), - etaRange=(0.0, 1.0), - pRange=(3.0, 6.0), - nHitsRange=(1, 50), - chiRange=(0, 5), - ), - 4: dict( - withFirstPixel=1, - nPixelHitsRange=(4, 99), - etaRange=(0.0, 1.0), - pRange=(6.0, 999.0), - nHitsRange=(1, 50), - chiRange=(0, 5), - ), - 5: dict( - withFirstPixel=1, - nPixelHitsRange=(4, 99), - etaRange=(1.0, 2.0), - pRange=(1.0, 6.0), - nHitsRange=(1, 50), - chiRange=(0, 5), - ), - 6: dict( - withFirstPixel=1, - nPixelHitsRange=(4, 99), - etaRange=(1.0, 2.0), - pRange=(6.0, 12.0), - nHitsRange=(1, 50), - chiRange=(0, 5), - ), - 7: dict( - withFirstPixel=1, - nPixelHitsRange=(4, 99), - etaRange=(1.0, 2.0), - pRange=(12.0, 999.0), - nHitsRange=(1, 50), - chiRange=(0, 5), - ), - 8: dict( - withFirstPixel=1, - nPixelHitsRange=(4, 99), - etaRange=(2.0, 4.5), - pRange=(1.0, 18.0), - nHitsRange=(1, 50), - chiRange=(0, 5), - ), - 9: dict( - withFirstPixel=1, - nPixelHitsRange=(4, 99), - etaRange=(2.0, 4.5), - pRange=(18.0, 999.0), - nHitsRange=(1, 50), - chiRange=(0, 5), - ), - } - pass_cat = lambda t, i: ( - ( - ((cats[i]["withFirstPixel"] == 1) & (t.isHitL1 == 1)) - | ((cats[i]["withFirstPixel"] == -1) & (t.isHitL1 == 0)) - | (cats[i]["withFirstPixel"] == 0) - ) - & ( - (t.pf.numberOfPixelHits >= cats[i]["nPixelHitsRange"][0]) - & (t.pf.numberOfPixelHits <= cats[i]["nPixelHitsRange"][1]) - ) - & ( - (abs(t.pf.trkEta) >= cats[i]["etaRange"][0]) - & (abs(t.pf.trkEta) <= cats[i]["etaRange"][1]) - ) - & ( - (t.pvec.p >= cats[i]["pRange"][0]) - & (t.pvec.p <= cats[i]["pRange"][1]) - ) - & ( - (t.pf.numberOfHits >= cats[i]["nHitsRange"][0]) - & (t.pf.numberOfHits <= cats[i]["nHitsRange"][1]) - ) - & ( - (t.pf.trkChi2 >= cats[i]["chiRange"][0]) - & (t.pf.trkChi2 <= cats[i]["chiRange"][1]) - ) - ) - - zeros = ak.zeros_like(trkj_jetbased.pt, dtype=int) - trkj_jetbased["category"] = zeros - 1 # initial category index: -1 - for idx in range(0, 10): - trkj_jetbased["category"] = ak.where( - (trkj_jetbased["category"] == -1) & pass_cat(trkj_jetbased, idx), - zeros + idx, - trkj_jetbased["category"], - ) + # stored tracks: requring dR < 0.3 + trkj_jetbased_store = trkj_jetbased[trkj_jetbased.dr_jet < 0.3] # flatten jet-based track arrays trkj_jetbased_flat = ak.flatten( - trkj_jetbased, axis=2 + trkj_jetbased_store, axis=2 ) # dim: (event, pfcand) - trkj_jetbased_num = ak.num(trkj_jetbased, axis=2) + trkj_jetbased_num = ak.num(trkj_jetbased_store, axis=2) Track = ak.zip( { @@ -920,6 +1043,8 @@ def process_shift(self, events, shift_name): * trkj_jetbased_flat.sign3D, -99.0, ), + # track probability from IPsig and category + "Proba": ak.fill_none(trkj_jetbased_flat.proba, -99), # hits in tracker "nHitAll": ak.fill_none(trkj_jetbased_flat.pf.numberOfHits, -99), "nHitPixel": ak.fill_none( @@ -963,7 +1088,8 @@ def process_shift(self, events, shift_name): output["DHadron"] = DHadron output["Genlep"] = Genlep output["GenV0"] = GenV0 - fname = f"{dataset}_f{events.metadata['filename'].split('_')[-1].replace('.root','')}_{int(events.metadata['entrystop']/self.chunksize)}.root" + os.system(f"mkdir -p {dataset}") + fname = f"{dataset}/f{events.metadata['filename'].split('_')[-1].replace('.root','')}_{int(events.metadata['entrystop']/self.chunksize)}.root" with uproot.recreate(fname) as fout: output_root = {} for bname in output.keys(): @@ -975,7 +1101,6 @@ def process_shift(self, events, shift_name): b_nest[n] = ak.packed(ak.without_parameters(output[bname][n])) output_root[bname] = ak.zip(b_nest) fout["btagana/ttree"] = output_root - return {dataset: len(events)} def postprocess(self, accumulator): diff --git a/src/BTVNanoCommissioning/workflows/BTA_ttbar_producer.py b/src/BTVNanoCommissioning/workflows/BTA_ttbar_producer.py index 44affbf2..aedf6573 100644 --- a/src/BTVNanoCommissioning/workflows/BTA_ttbar_producer.py +++ b/src/BTVNanoCommissioning/workflows/BTA_ttbar_producer.py @@ -10,6 +10,7 @@ ) from BTVNanoCommissioning.helpers.func import update from BTVNanoCommissioning.utils.correction import load_SF, JME_shifts +import os ## Based on coffea_array_producer.ipynb from Congqiao @@ -72,6 +73,8 @@ def process_shift(self, events, shift_name): "Evt": events.event, "LumiBlock": events.luminosityBlock, "rho": events.fixedGridRhoFastjetAll, + "npvs": events.PV.npvs, + "npvsGood": events.PV.npvsGood, } if not isRealData: basic_vars["nPU"] = events.Pileup.nPU @@ -383,7 +386,7 @@ def process_shift(self, events, shift_name): Jet = ak.zip( { # basic kinematics - "pT": jet.pt, + "pt": jet.pt, "eta": jet.eta, "phi": jet.phi, "mass": jet.mass, @@ -423,10 +426,15 @@ def process_shift(self, events, shift_name): ) # genJet pT - genJetIdx = jet.genJetIdx.mask[ - (jet.genJetIdx >= ak.num(events.GenJet)) & (jet.genJetIdx < 0) - ] # in case the genJet index out of range - Jet["genpt"] = ak.fill_none(events.GenJet[genJetIdx].pt, -1) + genJetIdx = ak.where( + (jet.genJetIdx < ak.num(events.GenJet)) & (jet.genJetIdx != -1), + jet.genJetIdx, + zeros, + ) # in case the genJet index out of range + + Jet["genpt"] = ak.where( + jet.genJetIdx != -1, events.GenJet[genJetIdx].pt, -99 + ) # gen-level jet cleaning aginst prompt leptons genlep_prompt = genlep[(Genlep.mother != 0) & (Genlep.mother % 10 == 0)] @@ -448,7 +456,7 @@ def process_shift(self, events, shift_name): # jet cleaning aginst pileup Jet["flavourCleaned"] = ak.where( - Jet["genpt"] < 8.0, zeros, Jet["flavourCleaned"] + (Jet["genpt"] < 8.0) & (Jet["genpt"] > 0), zeros, Jet["flavourCleaned"] ) # define Jet_clean: special for BTA ttbar workflow which cleans jets against selected leptons @@ -511,7 +519,8 @@ def process_shift(self, events, shift_name): output["ttbar_ps_w"] = ps_w_arrays[passEvent] # customize output file name: __.root - fname = f"{dataset}_{events.metadata['filename'].split('/')[-1].replace('.root','')}_{int(events.metadata['entrystop']/self.chunksize)}.root" + fname = f"{dataset}/{events.metadata['filename'].split('/')[-1].replace('.root','')}_{int(events.metadata['entrystop']/self.chunksize)}.root" + os.system(f"mkdir -p {dataset}") with uproot.recreate(fname) as fout: output_root = {} for bname in output.keys(): @@ -523,6 +532,21 @@ def process_shift(self, events, shift_name): b_nest[n] = ak.packed(ak.without_parameters(output[bname][n])) output_root[bname] = ak.zip(b_nest) fout["btagana/ttree"] = output_root + if isRealData: + fout["sumw"] = {"total_events": ak.Array([len(events)])} + else: + fout["sumw"] = { + "total_events": ak.Array([len(events)]), + "total_pos_events": ak.Array([ak.sum(events.genWeight > 0)]), + "total_neg_events": ak.Array([-1.0 * ak.sum(events.genWeight < 0)]), + "total_wei_events": ak.Array([ak.sum(events.genWeight)]), + "total_poswei_events": ak.Array( + [ak.sum(events.genWeight[events.genWeight > 0.0])] + ), + "total_negwei_events": ak.Array( + [ak.sum(events.genWeight[events.genWeight < 0.0])] + ), + } return {dataset: len(events)} diff --git a/src/BTVNanoCommissioning/workflows/__init__.py b/src/BTVNanoCommissioning/workflows/__init__.py index 7855b340..fa5aa4f7 100644 --- a/src/BTVNanoCommissioning/workflows/__init__.py +++ b/src/BTVNanoCommissioning/workflows/__init__.py @@ -84,7 +84,7 @@ workflows["ectag_DY_sf"] = CTAGeDYValidSFProcessor # Tutorial -# workflows["example"] = ExampleProcessor +workflows["example"] = ExampleProcessor # BTA producers workflows["BTA"] = BTA_processor workflows["BTA_addPFMuons"] = partial(BTA_processor, addPFMuons=True) diff --git a/src/BTVNanoCommissioning/workflows/ctag_DY_valid_sf.py b/src/BTVNanoCommissioning/workflows/ctag_DY_valid_sf.py index bda1aa37..8d996393 100644 --- a/src/BTVNanoCommissioning/workflows/ctag_DY_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ctag_DY_valid_sf.py @@ -268,7 +268,7 @@ def process_shift(self, events, shift_name): btagSFs(sel_jet, self.SF_map, weights, "DeepCSVB", syst_wei) btagSFs(sel_jet, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sel_jet.pt) + genflavor = ak.zeros_like(sel_jet.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/ctag_Wc_valid_sf.py b/src/BTVNanoCommissioning/workflows/ctag_Wc_valid_sf.py index 221ade92..ebd23945 100644 --- a/src/BTVNanoCommissioning/workflows/ctag_Wc_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ctag_Wc_valid_sf.py @@ -205,7 +205,7 @@ def process_shift(self, events, shift_name): # Other cuts req_pTratio = (soft_muon[:, 0].pt / mu_jet[:, 0].pt) < 0.4 - + idx = np.where(iso_muon.jetIdx == -1, 0, iso_muon.jetIdx) req_QCDveto = ( (iso_muon.pfRelIso04_all < 0.05) & (abs(iso_muon.dz) < 0.01) @@ -257,7 +257,12 @@ def process_shift(self, events, shift_name): with_name="PtEtaPhiMLorentzVector", ) Wmass = MET + iso_muon - req_Wmass = Wmass.mass > 55 + # modified to transverse mass + req_mtw = ( + np.sqrt(2 * iso_muon.pt * MET.pt * (1 - np.cos(iso_muon.delta_phi(MET)))) + > 55 + ) + # Wmass.mass > 55 event_level = ( req_trig @@ -267,9 +272,9 @@ def process_shift(self, events, shift_name): & req_softmu & req_dilepmass & req_mujet - & req_Wmass + & req_mtw & req_dilepveto - & req_QCDveto + # & req_QCDveto & req_pTratio ) event_level = ak.fill_none(event_level, False) @@ -333,8 +338,8 @@ def process_shift(self, events, shift_name): btagSFs(smuon_jet, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) - smflav = ak.zeros_like(smuon_jet.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) + smflav = ak.zeros_like(smuon_jet.pt, dtype=int) # Systematics information if shift_name is None: @@ -429,7 +434,7 @@ def process_shift(self, events, shift_name): flatten(smuon_jet[histname.replace("mujet_", "")]), weight=weight, ) - elif "btag" in histname: + elif "btag" in histname and "Trans" not in histname: for i in range(2): if ( str(i) not in histname @@ -459,6 +464,16 @@ def process_shift(self, events, shift_name): ), weight=weight, ) + elif "btag" in histname and "Trans" in histname: + for i in range(2): + histname = histname.replace("Trans", "").replace(f"_{i}", "") + h.fill( + syst="noSF", + flav=smflav, + osss=osss, + discr=1.0 / np.tanh(smuon_jet[histname]), + weight=weights.partial_weight(exclude=exclude_btv), + ) output["njet"].fill(syst, osss, njet, weight=weight) output["nmujet"].fill(syst, osss, nmujet, weight=weight) @@ -540,8 +555,9 @@ def process_shift(self, events, shift_name): out_branch, np.where( (out_branch == "SoftMuon") - # | (out_branch == "MuonJet") + | (out_branch == "MuonJet") | (out_branch == "dilep") + | (out_branch == "OtherJets") ), ) @@ -550,7 +566,7 @@ def process_shift(self, events, shift_name): "Muon", "Jet", "SoftMuon", - # "MuonJet", + "MuonJet", "dilep", "charge", "MET", @@ -568,7 +584,7 @@ def process_shift(self, events, shift_name): # write to root files os.system(f"mkdir -p {self.name}/{dataset}") with uproot.recreate( - f"{self.name}/{dataset}/{systematics[0]}_{int(events.metadata['entrystop']/self.chunksize)}.root" + f"{self.name}/{dataset}/{systematics[0]}_{events.metadata['filename'].split('/')[-1].replace('.root','')}_{int(events.metadata['entrystop']/self.chunksize)}.root" ) as fout: fout["Events"] = uproot_writeable(pruned_ev, include=out_branch) diff --git a/src/BTVNanoCommissioning/workflows/ctag_dileptt_valid_sf.py b/src/BTVNanoCommissioning/workflows/ctag_dileptt_valid_sf.py index b0a2d972..4943e245 100644 --- a/src/BTVNanoCommissioning/workflows/ctag_dileptt_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ctag_dileptt_valid_sf.py @@ -301,8 +301,8 @@ def process_shift(self, events, shift_name): btagSFs(smuon_jet, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) - smflav = ak.zeros_like(smuon_jet.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) + smflav = ak.zeros_like(smuon_jet.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/ctag_eDY_valid_sf.py b/src/BTVNanoCommissioning/workflows/ctag_eDY_valid_sf.py index 905ab9d1..b9dd81c5 100644 --- a/src/BTVNanoCommissioning/workflows/ctag_eDY_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ctag_eDY_valid_sf.py @@ -268,7 +268,7 @@ def process_shift(self, events, shift_name): btagSFs(sel_jet, self.SF_map, weights, "DeepCSVB", syst_wei) btagSFs(sel_jet, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sel_jet.pt) + genflavor = ak.zeros_like(sel_jet.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/ctag_eWc_valid_sf.py b/src/BTVNanoCommissioning/workflows/ctag_eWc_valid_sf.py index df0d34bf..39670667 100644 --- a/src/BTVNanoCommissioning/workflows/ctag_eWc_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ctag_eWc_valid_sf.py @@ -324,8 +324,8 @@ def process_shift(self, events, shift_name): btagSFs(smuon_jet, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) - smflav = ak.zeros_like(smuon_jet.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) + smflav = ak.zeros_like(smuon_jet.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/ctag_edileptt_valid_sf.py b/src/BTVNanoCommissioning/workflows/ctag_edileptt_valid_sf.py index a2766dee..03308887 100644 --- a/src/BTVNanoCommissioning/workflows/ctag_edileptt_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ctag_edileptt_valid_sf.py @@ -296,8 +296,8 @@ def process_shift(self, events, shift_name): btagSFs(sjets, self.SF_map, weights, "DeepCSVB", syst_wei) btagSFs(sjets, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) - smflav = ak.zeros_like(smuon_jet.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) + smflav = ak.zeros_like(smuon_jet.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/ctag_emdileptt_valid_sf.py b/src/BTVNanoCommissioning/workflows/ctag_emdileptt_valid_sf.py index d49f10ef..854c7591 100644 --- a/src/BTVNanoCommissioning/workflows/ctag_emdileptt_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ctag_emdileptt_valid_sf.py @@ -344,8 +344,8 @@ def process_shift(self, events, shift_name): btagSFs(sjets, self.SF_map, weights, "DeepCSVB", syst_wei) btagSFs(sjets, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) - smflav = ak.zeros_like(smuon_jet.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) + smflav = ak.zeros_like(smuon_jet.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/ctag_ettsemilep_valid_sf.py b/src/BTVNanoCommissioning/workflows/ctag_ettsemilep_valid_sf.py index ab3788c9..1c32c895 100644 --- a/src/BTVNanoCommissioning/workflows/ctag_ettsemilep_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ctag_ettsemilep_valid_sf.py @@ -339,8 +339,8 @@ def process_shift(self, events, shift_name): btagSFs(smuon_jet, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) - smflav = ak.zeros_like(smuon_jet.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) + smflav = ak.zeros_like(smuon_jet.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/ctag_semileptt_valid_sf.py b/src/BTVNanoCommissioning/workflows/ctag_semileptt_valid_sf.py index 2ed6da8b..b7af4fe0 100644 --- a/src/BTVNanoCommissioning/workflows/ctag_semileptt_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ctag_semileptt_valid_sf.py @@ -355,8 +355,8 @@ def process_shift(self, events, shift_name): btagSFs(smuon_jet, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) - smflav = ak.zeros_like(smuon_jet.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) + smflav = ak.zeros_like(smuon_jet.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/example.py b/src/BTVNanoCommissioning/workflows/example.py index dcda3b7e..e3d2072f 100644 --- a/src/BTVNanoCommissioning/workflows/example.py +++ b/src/BTVNanoCommissioning/workflows/example.py @@ -147,16 +147,28 @@ def process_shift(self, events, shift_name): ## Muon cuts # muon twiki: https://twiki.cern.ch/twiki/bin/view/CMS/SWGuideMuonIdRun2 - ## Electron cuts - # electron twiki: https://twiki.cern.ch/twiki/bin/viewauth/CMS/CutBasedElectronIdentificationRun2 + muon_sel = (events.Muon.pt > 15) & (mu_idiso(events, self._campaign)) + event_mu = events.Muon[muon_sel] + req_muon = ak.num(event_mu.pt) == 1 - ## Jet cuts + # Electron cut + ele_sel = (events.Electron.pt > 15) & (ele_cuttightid(events, self._campaign)) + event_e = events.Electron[ele_sel] + req_ele = ak.num(event_e.pt) == 1 + + req_leadlep_pt = ak.any(event_e.pt > 25, axis=-1) | ak.any( + event_mu.pt > 25, axis=-1 + ) + ## Jet cuts + jet_sel = (events.Jet.pt > 30) & (jet_id(events, self._campaign)) + event_jet = events.Jet[jet_sel] + req_jet = ak.num(event_jet) >= 1 ## Other cuts ## Apply all selections event_level = ( - req_trig & req_lumi # & req_muon & req_ele & req_jets & req_opposite_charge + req_trig & req_lumi & req_jet & req_muon & req_ele & req_leadlep_pt ) event_level = ak.fill_none(event_level, False) # Skip empty events @@ -166,9 +178,9 @@ def process_shift(self, events, shift_name): #################### # Selected objects # : Pruned objects with reduced event_level #################### - smu = events.Muon[event_level] - sele = events.Electron[event_level] - sjets = events.Jet[event_level] + smu = event_mu[event_level] + sjets = event_jet[event_level] + sele = event_e[event_level] #################### # Weight & Geninfo # : Add weight to selected events #################### @@ -203,7 +215,7 @@ def process_shift(self, events, shift_name): btagSFs(sjets, self.SF_map, weights, "DeepCSVB", syst_wei) btagSFs(sjets, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) # Systematics information (add name of systematics) if shift_name is None: # weight variations @@ -230,17 +242,25 @@ def process_shift(self, events, shift_name): if syst == "nominal" or syst == shift_name else weights.weight(modifier=syst) ) # shift up/down for weight systematics - output["$VAR"].fill() + # fill the histogram (check axis defintion in histogrammer and following the order) + output["jet_pt"].fill( + syst, flatten(genflavor[:, 0]), flatten(sjets[:, 0].pt), weight=weight + ) + output["mu_pt"].fill(syst, flatten(smu[:, 0].pt), weight=weight) + output["dr_mujet"].fill( + syst, + flatten(genflavor[:, 0]), # the fill content should always flat arrays + flatten(sjets[:, 0].delta_r(smu[:, 0])), + weight=weight, + ) ####################### # Create root files # : Save arrays in to root file, keep axis structure ####################### if self.isArray: # Keep the structure of events and pruned the object size pruned_ev = events[event_level] # pruned events - pruned_ev.Electron = ( - sele # replace electron collections with selected electron - ) + pruned_ev.Muon = smu # replace muon collections with selected muon # Add custom variables if not isRealData: pruned_ev["weight"] = weights.weight() @@ -252,7 +272,7 @@ def process_shift(self, events, shift_name): out_branch = np.setdiff1d( np.array(pruned_ev.fields), np.array(events.fields) ) # stored customed variables - out_branch = np.append(out_branch, ["Jet_btagDeep*", "Electron_pt"]) + out_branch = np.append(out_branch, ["Jet_btagDeep*", "Muon_pt"]) # write to root files os.system(f"mkdir -p {self.name}/{dataset}") with uproot.recreate( diff --git a/src/BTVNanoCommissioning/workflows/ttbar_validation.py b/src/BTVNanoCommissioning/workflows/ttbar_validation.py index 3883eedf..edb71779 100644 --- a/src/BTVNanoCommissioning/workflows/ttbar_validation.py +++ b/src/BTVNanoCommissioning/workflows/ttbar_validation.py @@ -204,7 +204,7 @@ def process_shift(self, events, shift_name): btagSFs(sjets, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/ttdilep_valid_sf.py b/src/BTVNanoCommissioning/workflows/ttdilep_valid_sf.py index a674acd9..3159e9cb 100644 --- a/src/BTVNanoCommissioning/workflows/ttdilep_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ttdilep_valid_sf.py @@ -275,7 +275,7 @@ def process_shift(self, events, shift_name): btagSFs(sjets, self.SF_map, weights, "DeepCSVB", syst_wei) btagSFs(sjets, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/ttsemilep_valid_sf.py b/src/BTVNanoCommissioning/workflows/ttsemilep_valid_sf.py index d2fa3773..91212028 100644 --- a/src/BTVNanoCommissioning/workflows/ttsemilep_valid_sf.py +++ b/src/BTVNanoCommissioning/workflows/ttsemilep_valid_sf.py @@ -252,7 +252,7 @@ def process_shift(self, events, shift_name): btagSFs(sjets, self.SF_map, weights, "DeepCSVB", syst_wei) btagSFs(sjets, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) # Systematics information if shift_name is None: diff --git a/src/BTVNanoCommissioning/workflows/validation.py b/src/BTVNanoCommissioning/workflows/validation.py index c10708d9..db2c735e 100644 --- a/src/BTVNanoCommissioning/workflows/validation.py +++ b/src/BTVNanoCommissioning/workflows/validation.py @@ -208,7 +208,7 @@ def process_shift(self, events, shift_name): btagSFs(sjets, self.SF_map, weights, "DeepCSVB", syst_wei) btagSFs(sjets, self.SF_map, weights, "DeepCSVC", syst_wei) else: - genflavor = ak.zeros_like(sjets.pt) + genflavor = ak.zeros_like(sjets.pt, dtype=int) # Systematics information if shift_name is None: