Include MIP Mean vs. Interaction Rate Plot, Improve IR Calculations, Upgrade MC Template

TPCQCVis/reports/TPC_AQC_Template_Period.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "6ba04481",
    "metadata": {},
    "outputs": [],
@@ -44,7 +44,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "1e556f7f-d199-4a14-bb9f-0515fb139009",
    "metadata": {},
    "outputs": [],
@@ -193,7 +193,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "0b4c56f8-1009-40aa-8a1f-12c5bd2e1ffb",
    "metadata": {},
    "outputs": [],
@@ -406,7 +406,7 @@
    "metadata": {},
    "source": [
     "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
-    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Run-Parameters\"data-toc-modified-id=\"Run-Parameters-1\">Run Parameters</a></span></li></ul><ul class=\"toc-item\"><li><span><a href=\"#Quality-Observer\" data-toc-modified-id=\"Quality-Observer-1\">Quality Observer</a></span><ul class=\"toc-item\"><li><span><a href=\"#Clusters\" data-toc-modified-id=\"Clusters-1.1\">Clusters</a></span></li><li><span><a href=\"#Tracks\" data-toc-modified-id=\"Tracks-1.2\">Tracks</a></span></li></ul></li><li><span><a href=\"#Trendings\" data-toc-modified-id=\"Trendings-2\">Trendings</a></span><ul class=\"toc-item\"><li><span><a href=\"#Mean-phi-of-tracks\" data-toc-modified-id=\"Mean-phi-of-tracks-2.1\">Mean phi of tracks</a></span></li><li><span><a href=\"#Mean-eta-of-tracks\" data-toc-modified-id=\"Mean-eta-of-tracks-2.2\">Mean eta of tracks</a></span></li><li><span><a href=\"#Mean-tracks-transverse-momentum-of-tracks\" data-toc-modified-id=\"Mean-tracks-transverse-momentum-of-tracks-2.3\">Mean tracks transverse momentum of tracks</a></span></li><li><span><a href=\"#Mean-charge-sign-of-tracks\" data-toc-modified-id=\"Mean-charge-sign-of-tracks-2.4\">Mean charge sign of tracks</a></span></li><li><span><a href=\"#Mean-dEdxTot-of-MIPs-tracks\" data-toc-modified-id=\"Mean-dEdxTot-of-MIPs-tracks-2.5\">Mean dEdxTot of MIPs tracks</a></span></li></ul></li><li><span><a href=\"#Plots\" data-toc-modified-id=\"Plots-3\">Plots</a></span><ul class=\"toc-item\"><li><span><a href=\"#Clusters\" data-toc-modified-id=\"Clusters-3.1\">Clusters</a></span></li><li><span><a href=\"#Tracks\" data-toc-modified-id=\"Tracks-3.2\">Tracks</a></span><ul class=\"toc-item\"><li><span><a href=\"#Geometrical-distributions-of-tracks\" data-toc-modified-id=\"Geometrical-distributions-of-tracks-3.2.1\">Geometrical distributions of tracks</a></span></li><li><span><a href=\"#Track-properties\" data-toc-modified-id=\"Track-properties-3.2.2\">Track properties</a></span></li></ul></li><li><span><a href=\"#DCAr\" data-toc-modified-id=\"DCAr-3.3\">DCAr</a></span><ul class=\"toc-item\"><li><span><a href=\"#DCAr-vs-phi\" data-toc-modified-id=\"DCAr-vs-phi-3.3.1\">DCAr vs phi</a></span></li><li><span><a href=\"#DCAr-vs-eta\" data-toc-modified-id=\"DCAr-vs-eta-3.3.2\">DCAr vs eta</a></span></li><li><span><a href=\"#DCAr-vs-pT\" data-toc-modified-id=\"DCAr-vs-pT-3.3.3\">DCAr vs pT</a></span></li><li><span><a href=\"#DCAr-vs-nClusters\" data-toc-modified-id=\"DCAr-vs-nClusters-3.3.4\">DCAr vs nClusters</a></span></li></ul></li><li><span><a href=\"#PID\" data-toc-modified-id=\"PID-3.4\">PID</a></span><ul class=\"toc-item\"><li><span><a href=\"#dEdxTot-of-MIP\" data-toc-modified-id=\"dEdxTot-of-MIP-3.4.1\">dEdxTot of MIP</a></span></li><li><span><a href=\"#TPC-Gain-calibration\" data-toc-modified-id=\"TPC-Gain-calibration-3.4.2\">TPC Gain calibration</a></span></li><li><span><a href=\"#PID-Hypothesis-Profile\" data-toc-modified-id=\"PID-Hypothesis-Profile-3.4.3\">PID Hypothesis Profile</a></span></li></ul></li></ul></li></ul></div>"
+    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Run-Parameters\"data-toc-modified-id=\"Run-Parameters-1\">Run Parameters</a></span></li></ul><ul class=\"toc-item\"><li><span><a href=\"#Quality-Observer\" data-toc-modified-id=\"Quality-Observer-1\">Quality Observer</a></span><ul class=\"toc-item\"><li><span><a href=\"#Clusters\" data-toc-modified-id=\"Clusters-1.1\">Clusters</a></span></li><li><span><a href=\"#Tracks\" data-toc-modified-id=\"Tracks-1.2\">Tracks</a></span></li></ul></li><li><span><a href=\"#Trendings\" data-toc-modified-id=\"Trendings-2\">Trendings</a></span><ul class=\"toc-item\"><li><span><a href=\"#Mean-phi-of-tracks\" data-toc-modified-id=\"Mean-phi-of-tracks-2.1\">Mean phi of tracks</a></span></li><li><span><a href=\"#Mean-eta-of-tracks\" data-toc-modified-id=\"Mean-eta-of-tracks-2.2\">Mean eta of tracks</a></span></li><li><span><a href=\"#Mean-tracks-transverse-momentum-of-tracks\" data-toc-modified-id=\"Mean-tracks-transverse-momentum-of-tracks-2.3\">Mean tracks transverse momentum of tracks</a></span></li><li><span><a href=\"#Mean-charge-sign-of-tracks\" data-toc-modified-id=\"Mean-charge-sign-of-tracks-2.4\">Mean charge sign of tracks</a></span></li><li><span><a href=\"#Mean-dEdxTot-of-MIPs-tracks\" data-toc-modified-id=\"Mean-dEdxTot-of-MIPs-tracks-2.5\">Mean dEdxTot of MIPs tracks</a></span></li><li><span><a href=\"#MIP-Mean-vs.-Interaction-Rate\" data-toc-modified-id=\"MIP-Mean-vs.-Interaction-Rate-2.6\">MIP Mean vs. Interaction Rate</a></span></li></ul></li><li><span><a href=\"#Plots\" data-toc-modified-id=\"Plots-3\">Plots</a></span><ul class=\"toc-item\"><li><span><a href=\"#Clusters\" data-toc-modified-id=\"Clusters-3.1\">Clusters</a></span></li><li><span><a href=\"#Tracks\" data-toc-modified-id=\"Tracks-3.2\">Tracks</a></span><ul class=\"toc-item\"><li><span><a href=\"#Geometrical-distributions-of-tracks\" data-toc-modified-id=\"Geometrical-distributions-of-tracks-3.2.1\">Geometrical distributions of tracks</a></span></li><li><span><a href=\"#Track-properties\" data-toc-modified-id=\"Track-properties-3.2.2\">Track properties</a></span></li></ul></li><li><span><a href=\"#DCAr\" data-toc-modified-id=\"DCAr-3.3\">DCAr</a></span><ul class=\"toc-item\"><li><span><a href=\"#DCAr-vs-phi\" data-toc-modified-id=\"DCAr-vs-phi-3.3.1\">DCAr vs phi</a></span></li><li><span><a href=\"#DCAr-vs-eta\" data-toc-modified-id=\"DCAr-vs-eta-3.3.2\">DCAr vs eta</a></span></li><li><span><a href=\"#DCAr-vs-pT\" data-toc-modified-id=\"DCAr-vs-pT-3.3.3\">DCAr vs pT</a></span></li><li><span><a href=\"#DCAr-vs-nClusters\" data-toc-modified-id=\"DCAr-vs-nClusters-3.3.4\">DCAr vs nClusters</a></span></li></ul></li><li><span><a href=\"#PID\" data-toc-modified-id=\"PID-3.4\">PID</a></span><ul class=\"toc-item\"><li><span><a href=\"#dEdxTot-of-MIP\" data-toc-modified-id=\"dEdxTot-of-MIP-3.4.1\">dEdxTot of MIP</a></span></li><li><span><a href=\"#TPC-Gain-calibration\" data-toc-modified-id=\"TPC-Gain-calibration-3.4.2\">TPC Gain calibration</a></span></li><li><span><a href=\"#PID-Hypothesis-Profile\" data-toc-modified-id=\"PID-Hypothesis-Profile-3.4.3\">PID Hypothesis Profile</a></span></li></ul></li></ul></li></ul></div>"
    ]
   },
   {
@@ -420,7 +420,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "ddd293fc",
    "metadata": {},
    "outputs": [],
@@ -563,7 +563,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "id": "4052a354",
    "metadata": {},
    "outputs": [],
@@ -580,7 +580,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "69a20633",
    "metadata": {},
    "outputs": [],
@@ -602,7 +602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "293f06ea",
    "metadata": {},
    "outputs": [],
@@ -663,7 +663,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "id": "0969cccc",
    "metadata": {},
    "outputs": [],
@@ -890,6 +890,14 @@
     "canvas.Draw()\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "198e2c7d",
+   "metadata": {},
+   "source": [
+    "### MIP Mean vs. Interaction Rate"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -919,7 +927,7 @@
     "n_bins = len(MIPdata)\n",
     "hMIP_IR = ROOT.TH1F(\n",
     "    \"hMIP_vs_IntRate\",\n",
-    "    \"MIP Mean vs Interaction Rate;IR (Hz);MIP Mean\",\n",
+    "    \"MIP Mean vs Interaction Rate;IR (kHz);MIP Mean\",\n",
     "    n_bins,\n",
     "    0,\n",
     "    n_bins\n",
@@ -934,12 +942,16 @@
     "    hMIP_IR.SetBinContent(bin_idx, mip_mean)\n",
     "    hMIP_IR.SetBinError(bin_idx, mip_sigma)\n",
     "    if isinstance(int_rate, (float)):\n",
-    "        label = f\"#splitline{{{int_rate:.2f}}}{{(run {run})}}\"\n",
-    "    else:\n",
-    "        label = f\"#splitline{{{int_rate}}}{{(run {run})}}\"\n",
+    "#         label = f\"#splitline{{{int_rate/1000:.1f}}}{{({run})}}\"\n",
+    "        label = f\"{int_rate/1000:.1f} [{run}]\"\n",
+    "\n",
+    "    else: # \"?\", for example\n",
+    "#         label = f\"#splitline{{{int_rate}}}{{(run {run})}}\"\n",
+    "        label = f\"{int_rate} [{run}]\"\n",
     "    hMIP_IR.GetXaxis().SetBinLabel(bin_idx, label)\n",
+    "    hMIP_IR.GetXaxis().SetTitleOffset(1.5)\n",
     "# hMIP_IR.LabelsOption(\"v\")\n",
-    "MIP_IR_canvas = ROOT.TCanvas(\"MIP_IR_canvas\",\"MIP Mean vs. Interaction Rate\",1100,400)\n",
+    "MIP_IR_canvas = ROOT.TCanvas(\"MIP_IR_canvas\",\"MIP Mean vs. Interaction Rate\",1000,400)\n",
     "hMIP_IR.Draw(\"EL\")\n",
     "MIP_IR_canvas.Draw()"
    ]
@@ -1012,7 +1024,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 25,
    "id": "824fe439",
    "metadata": {},
    "outputs": [],
@@ -1160,7 +1172,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "id": "94dac685",
    "metadata": {},
    "outputs": [],
@@ -1518,7 +1530,8 @@
     "    pad1.SetGridy(1)\n",
     "    canvas.SetCanvasSize(1000,400)\n",
     "    updateColors(hist,cols)\n",
-    "    legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "#     legend.SetHeader(\"Normalized to integral\\n#Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "    legend.AddEntry(\"\", \"#Run polarity IRstart IRmid IRend\", \"\")\n",
     "    legend.Draw()\n",
     "    canvas.Draw()"
    ]
@@ -1560,7 +1573,8 @@
     "\n",
     "    pad1.SetGridy(1)\n",
     "    canvas.SetCanvasSize(1000,400)\n",
-    "    legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "#     legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "    legend.AddEntry(\"\", \"#Run polarity IRstart IRmid IRend\", \"\")\n",
     "    legend.Draw()\n",
     "    canvas.Draw()"
    ]
@@ -1592,7 +1606,8 @@
     "\n",
     "    pad1.SetGrid(1)\n",
     "    canvas.SetCanvasSize(700,400)\n",
-    "    legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "#     legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "    legend.AddEntry(\"\", \"#Run polarity IRstart IRmid IRend\", \"\")\n",
     "    legend.Draw()\n",
     "    canvas.Draw()"
    ]
@@ -1659,7 +1674,8 @@
     "    updateColors(hist,cols)\n",
     "    pad1.SetGrid(1)\n",
     "    canvas.SetCanvasSize(700,400)\n",
-    "    legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "#     legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "    legend.AddEntry(\"\", \"#Run polarity IRstart IRmid IRend\", \"\")\n",
     "    legend.Draw()\n",
     "    canvas.Draw()"
    ]
@@ -1690,7 +1706,8 @@
     "    updateColors(hist,cols)\n",
     "    pad1.SetGrid(1)\n",
     "    canvas.SetCanvasSize(700,400)\n",
-    "    legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "#     legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "    legend.AddEntry(\"\", \"#Run polarity IRstart IRmid IRend\", \"\")\n",
     "    legend.Draw()\n",
     "    canvas.Draw()"
    ]
@@ -1721,7 +1738,8 @@
     "    updateColors(hist,cols)\n",
     "    pad1.SetGrid(1)\n",
     "    canvas.SetCanvasSize(700,400)\n",
-    "    legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "#     legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "    legend.AddEntry(\"\", \"#Run polarity IRstart IRmid IRend\", \"\")\n",
     "    legend.Draw()\n",
     "    canvas.Draw()"
    ]
@@ -1761,13 +1779,16 @@
     "    bigCanvas.cd(1)\n",
     "    ROOT.gPad.SetGrid(1)\n",
     "    for hist in hist1 : hist.Draw(\"SAME L\")\n",
-    "    legend1.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "#     legend1.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "    legend1.AddEntry(\"\", \"#Run polarity IRstart IRmid IRend\", \"\")\n",
+    "    \n",
     "    legend1.Draw()\n",
     "    histoOut, canvasOut = outlierDetection(objectName,hist2,runList)\n",
     "    bigCanvas.cd(2)\n",
     "    ROOT.gPad.SetGrid(1)\n",
     "    for hist in hist2 : hist.Draw(\"SAME L\")\n",
-    "    legend2.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "#     legend2.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "    legend2.AddEntry(\"\", \"#Run polarity IRstart IRmid IRend\", \"\")\n",
     "    legend2.Draw()\n",
     "    histoOut, canvasOut = outlierDetection(objectName,hist3,runList)\n",
     "    bigCanvas.cd(3)\n",
@@ -2301,7 +2322,8 @@
     "        targets[i].SetLineColor(3)\n",
     "        targets[i].SetLineWidth(3)\n",
     "    targets[0].Draw()\n",
-    "    legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "#     legend.SetHeader(\"Normalized to integral, #Run polarity IRstart IRmid IRend\", \"C\")\n",
+    "    legend.AddEntry(\"\", \"#Run polarity IRstart IRmid IRend\", \"\")\n",
     "    legend.Draw()\n",
     "    rightPad = c.cd(2)\n",
     "    rightPad.Divide(2,2)\n",

TPCQCVis/src/drawHistograms.py

@@ -72,8 +72,9 @@ def logScale(log):
     if legend:
         leg = ROOT.TLegend()
         if normalize : leg.SetHeader("Normalized to integral")
-        if files > 10 : leg.SetNColumns(2)
-
+        MaxRunsPerLegColumn = 10
+        if files > 10:
+            leg.SetNColumns(math.ceil(files/MaxRunsPerLegColumn))
     for i in range(files):
         if i==0 or not addHistos :
             hist = getHistogram(fileList[i], histogram)
@@ -127,6 +128,9 @@ def logScale(log):
             if ratio:
                 if type(hist) in (ROOT.TH1D, ROOT.TH1F, ROOT.TH1C, ROOT.TH2D, ROOT.TH2F, ROOT.TH2C):
                     histRatio = hist.Clone("hRatio_"+str(i))
+                    if histRatio.GetNbinsX() != histComp.GetNbinsX():
+                        print("Histograms have different numbers of bins. Skipping creation of ratio plots.")
+                        ratio = False
                     histRatio.Divide(histComp)
                     histRatio.SetTitle("Ratio")
                     histRatio.SetStats(0)

TPCQCVis/src/utility.py

@@ -34,19 +34,40 @@ def recursiveGetHistogram(folder, title):
                 return hist
     return None
 
+# Older version, which does not check every file
+# def checkIfExists(files, title):
+#     title = title.split(";")[0] 
+#     objectAvailable = False
+#     hist = None
+#     if type(files) is list:
+#         file = files[0]
+#     else:
+#         file = files
+#     hist = getHistogram(file, title)
+#     if hist:
+#         return True
+#     else:
+#         print(title,"not found")
+#         return False
+
 def checkIfExists(files, title):
     title = title.split(";")[0] 
-    objectAvailable = False
+    objectAvailable = True
+    problematicFiles = []
     hist = None
-    if type(files) is list:
-        file = files[0]
-    else:
-        file = files
-    hist = getHistogram(file, title)
-    if hist:
+    if type(files) is not list:
+        files=[files]
+    for file in files:
+        hist = getHistogram(file, title)
+        if not hist:
+            objectAvailable = False
+            problematicFiles.append(file.GetName())
+    if objectAvailable:
         return True
     else:
-        print(title,"not found")
+        print(title, "not found in the following files:")
+        for file in problematicFiles:
+            print(file)
         return False
 
 def drawMovingWindowOverlay(histograms,timestamps,normalize=False):

TPCQCVis/tools/downloadSim.py

@@ -23,7 +23,8 @@
 import time
 
 DATADIR = os.environ['TPCQCVIS_DATA']
-LOCALDIR = DATADIR+"/sim/"
+# LOCALDIR = DATADIR+"/sim/"
+LOCALDIR = DATADIR+"/sim"
 
 def getPaths(path):
     runs = subprocess.run(["alien_ls", path], capture_output=True)

TPCQCVis/tools/generateMCComparisonReports.py

@@ -37,14 +37,23 @@ def replace_in_ipynb(file_path, temp, patterns, replacements):
         temp_run_path = temp_run.name
 
     ### Part to set
-    path = f"{DATADIR}/sim/2024/"
+    path = f"{DATADIR}/sim/2024"
     period = "LHC24e2" 
     passName = "" #keep empty ("") if MC
-    pathComparison = f"{DATADIR}/2023/"
+    pathComparison = f"{DATADIR}/2023"
     periodListComparison =  ["LHC23zzf","LHC23zzg","LHC23zzh"]
     passNameListComparison = ["apass3","apass3","apass3"]
     #passNameListComparison = ["" for period in periodListComparison] #keep empty ("") if MC
 
+
+    # path = f"{DATADIR}/sim/2024"
+    # period = "LHC24f4" 
+    # passName = "0" #keep empty ("") if MC
+    # pathComparison = f"{DATADIR}/2024"
+    # periodListComparison =  ["LHC24af"]
+    # passNameListComparison = ["apass1_skimmed"]
+    # passNameListComparison = ["" for period in periodListComparison] #keep empty ("") if MC
+
     # Loop over the comparison periods
     for i,periodComparison in enumerate(periodListComparison):
         passNameComparison = passNameListComparison[i]