Merge branch 'update_lp' of https://github.com/rkansal47/HHbbVV into …

…update_lp
rkansal47 · Jul 24, 2024 · b5a440a · b5a440a
2 parents c92da81 + a289b66
commit b5a440a
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diff --git a/README.md b/README.md
@@ -43,6 +43,7 @@ using the [coffea](https://coffeateam.github.io/coffea/) and
     - [PlotFits](#plotfits)
   - [Combine](#combine)
     - [CMSSW + Combine Quickstart](#cmssw--combine-quickstart)
+    - [Packages](#packages)
     - [Run fits and diagnostics locally](#run-fits-and-diagnostics-locally)
       - [F-tests locally for non-resonant](#f-tests-locally-for-non-resonant)
     - [Run fits on condor](#run-fits-on-condor)
@@ -272,6 +273,7 @@ Or to submit only the signal:
 
 ```bash
 python src/condor/submit.py --year 2018 --tag $TAG --sample TTbar --subsamples TTToSemiLeptonic --processor ttsfs --submit
+python src/condor/submit.py --year 2018 --tag $TAG --sample SingleTop --subsamples ST_tW_antitop_5f_NoFullyHadronicDecays ST_tW_top_5f_NoFullyHadronicDecays ST_s-channel_4f_leptonDecays ST_t-channel_antitop_4f_InclusiveDecays ST_t-channel_top_4f_InclusiveDecays --processor ttsfs --submit
 ```
 
 ## Condor Scripts

diff --git a/...HbbVV/postprocessing/TopAnalysisOld.ipynb → ...bVV/postprocessing/TopAnalysisLocal.ipynb b/...HbbVV/postprocessing/TopAnalysisOld.ipynb → ...bVV/postprocessing/TopAnalysisLocal.ipynb
@@ -50,7 +50,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "plot_dir = \"../../../plots/ttsfs/24Feb29_update_lps\"\n",
+    "plot_dir = \"../../../plots/ttsfs/24Mar1_update_lps\"\n",
     "\n",
     "import os\n",
     "\n",
@@ -89,48 +89,10 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "cutflow"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "utils.get_pickles(f\"{data_dir}/{year}/TTToSemiLeptonic/pickles\", year, \"TTToSemiLeptonic\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "utils.get_pickles(f\"{data_dir}/{year}/SingleMuon_Run2018C/pickles\", year, \"SingleMuon_Run2018D\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "utils.get_pickles(f\"{data_dir}/{year}/SingleMuon_Run2018D/pickles\", year, \"SingleMuon_Run2018D\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "9006700 / 10030532"
+    "HEM Veto Efficiency"
    ]
   },
   {
@@ -157,49 +119,39 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "3127 / 3774"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "679 / 796"
+    "scale_samples = [\"Top\", \"TTbar\", \"W+Jets\"]  # normalizations are off\n",
+    "\n",
+    "total_scale = 0\n",
+    "total_noscale = 0\n",
+    "for sample, events in events_dict.items():\n",
+    "    if sample in scale_samples:\n",
+    "        total_scale += events[\"weight\"].sum().values[0]\n",
+    "    elif sample != \"Data\":\n",
+    "        total_noscale += events[\"weight\"].sum().values[0]\n",
+    "\n",
+    "print(f\"Total MC: {total_scale + total_noscale}\")\n",
+    "\n",
+    "sf = (events_dict[\"Data\"][\"weight\"].sum().values[0] - total_noscale) / total_scale\n",
+    "for sample, events in events_dict.items():\n",
+    "    if sample in scale_samples:\n",
+    "        events[\"weight\"] *= sf\n",
+    "\n",
+    "total = 0\n",
+    "for sample, events in events_dict.items():\n",
+    "    if sample != \"Data\":\n",
+    "        total += events[\"weight\"].sum().values[0]\n",
+    "\n",
+    "print(f\"New Total MC: {total}\")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# total = 0\n",
-    "# for sample, events in events_dict.items():\n",
-    "#     if sample != \"Data\":\n",
-    "#         total += events[\"weight\"].sum().values[0]\n",
-    "\n",
-    "# print(f\"Total MC: {total}\")\n",
-    "\n",
-    "# sf = events[\"weight\"].sum().values[0] / total\n",
-    "# for sample, events in events_dict.items():\n",
-    "#     if sample != \"Data\":\n",
-    "#         events[\"weight\"] *= sf\n",
-    "\n",
-    "# total = 0\n",
-    "# for sample, events in events_dict.items():\n",
-    "#     if sample != \"Data\":\n",
-    "#         total += events[\"weight\"].sum().values[0]\n",
-    "\n",
-    "# print(f\"New Total MC: {total}\")"
+    "utils.add_to_cutflow(events_dict, \"Scale\", \"weight\", cutflow)\n",
+    "cutflow"
    ]
   },
   {
@@ -345,22 +297,6 @@
     "### Pre plots"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "var_hist"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -644,6 +580,15 @@
     "print(\"Abs: \", unc[binn] / pre_vals[binn])"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pre_hists"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -654,14 +599,14 @@
     "pre_MC_vals = (\n",
     "    pre_hists[tvar][sum, :].values()\n",
     "    - data_vals\n",
-    "    # - pre_hists[tvar][\"TTbar\", :].values()\n",
-    "    # - pre_hists[tvar][\"TTSL\", :].values()\n",
+    "    - pre_hists[tvar][\"TTbar\", :].values()\n",
+    "    - pre_hists[tvar][\"Top\", :].values()\n",
     ")\n",
     "post_lnN_MC_vals = (\n",
     "    post_lnN_hists[tvar][sum, :].values()\n",
     "    - data_vals\n",
-    "    # - post_lnN_hists[tvar][\"TTbar\", :].values()\n",
-    "    # - post_lnN_hists[tvar][\"TTSL\", :].values()\n",
+    "    - post_lnN_hists[tvar][\"TTbar\", :].values()\n",
+    "    - post_lnN_hists[tvar][\"Top\", :].values()\n",
     ")"
    ]
   },
@@ -681,11 +626,22 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "lb = 5\n",
+    "lb = 10\n",
     "print(\"Pre chi2:\", chisquare(pre_MC_vals[-lb:], data_vals[-lb:]))\n",
     "print(\"Post chi2:\", chisquare(post_lnN_MC_vals[-lb:], data_vals[-lb:]))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lb = 5\n",
+    "print(pre_MC_vals[-lb:], data_vals[-lb:])\n",
+    "print(post_lnN_MC_vals[-lb:], data_vals[-lb:])"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,