From 02645fc8b7530828de329b37f695c11776023c65 Mon Sep 17 00:00:00 2001
From: Eric Torrence <eric.torrence@cern.ch>
Date: Fri, 13 Sep 2019 08:49:36 -0700
Subject: [PATCH] First commit of the offline monitoring code
---
Monitoring/CMakeLists.txt | 15 ++
Monitoring/python/LegacySelector.py | 65 ++++++
Monitoring/python/Monitor1DValue.py | 200 ++++++++++++++++
Monitoring/python/MonitorValueBase.py | 253 +++++++++++++++++++++
Monitoring/python/MonitorValueManager.py | 200 ++++++++++++++++
Monitoring/python/README | 11 +
Monitoring/python/__init__.py | 2 +
Monitoring/share/simpleMonitoringTest.json | 106 +++++++++
Monitoring/share/simpleMonitoringTest.py | 41 ++++
9 files changed, 893 insertions(+)
create mode 100644 Monitoring/CMakeLists.txt
create mode 100644 Monitoring/python/LegacySelector.py
create mode 100755 Monitoring/python/Monitor1DValue.py
create mode 100644 Monitoring/python/MonitorValueBase.py
create mode 100755 Monitoring/python/MonitorValueManager.py
create mode 100644 Monitoring/python/README
create mode 100644 Monitoring/python/__init__.py
create mode 100644 Monitoring/share/simpleMonitoringTest.json
create mode 100755 Monitoring/share/simpleMonitoringTest.py
diff --git a/Monitoring/CMakeLists.txt b/Monitoring/CMakeLists.txt
new file mode 100644
index 00000000..7e33f8b8
--- /dev/null
+++ b/Monitoring/CMakeLists.txt
@@ -0,0 +1,15 @@
+################################################################################
+# Package: Monitoring
+# Contains python code to implement offline monitoring
+################################################################################
+
+
+# Declare the package name:
+atlas_subdir( Monitoring )
+
+# External dependencies:
+find_package( ROOT COMPONENTS Core Tree )
+
+# Install files from the package:
+atlas_install_python_modules( python/*.py )
+atlas_install_scripts( share/*.py )
diff --git a/Monitoring/python/LegacySelector.py b/Monitoring/python/LegacySelector.py
new file mode 100644
index 00000000..0481d7e6
--- /dev/null
+++ b/Monitoring/python/LegacySelector.py
@@ -0,0 +1,65 @@
+#
+# LegacySelector.py
+#
+# Class to select values from legacy ntuples
+#
+# E.Torrence, Sept. 2019
+#
+#
+# Use Python3-style print statements
+from __future__ import print_function
+
+class LegacySelector ():
+ """Class to select values from Legacy ntuple"""
+
+ def __init__(self):
+ """Constructor"""
+
+ self.conf = None
+
+ # Pass MonitorValue conf object
+ def init(self, conf):
+ """Initialization"""
+
+ # Just save full conf object
+ self.conf = conf
+
+ # Return list of values from data object event
+ def get1DValue(self, event, varName):
+
+ # print ("LegacySelector.get1DValue called for", varName)
+
+ values = []
+
+ #varName = self.conf.xvar
+
+ # Variable name should first give the list, followed by the specific parameter
+ # Only the event number doesn't follow this pattern
+ if varName == 'fEventNumber':
+ # OK, this is weird, event is actually the tree, while event.event is the FaserEvent class.
+ # For the lists, we can get them directly from event...
+ return event.event.GetEventNumber()
+
+ theListName = varName.split('.')[0]
+
+ theList = getattr(event, theListName)
+
+ # Loop over truth list
+ for obj in theList:
+ # Try to parse the variable string
+ # Find chunks separated by a point
+ # Each is either a method or an attribute
+ theObj = obj
+ varList = self.conf.xvar.split('.')[1:] # Skip the list [1:]
+ for varName in varList:
+ # Is this an attribute or a method?
+ if callable(getattr(theObj, varName)):
+ theObj = getattr(theObj, varName)() # Method (function)
+ else:
+ theObj = getattr(theObj, varName) # Attribute (value)
+
+ # Once we have walked through the list, have our value
+ values.append(theObj)
+
+
+ return values
diff --git a/Monitoring/python/Monitor1DValue.py b/Monitoring/python/Monitor1DValue.py
new file mode 100755
index 00000000..1f43dc62
--- /dev/null
+++ b/Monitoring/python/Monitor1DValue.py
@@ -0,0 +1,200 @@
+#!/bin/env python
+#
+# Monitor1DValue.py
+#
+# Defines classes to implement monitored values
+#
+# Classes
+# Monitor1DValue
+# Monitor1DValueConfig
+#
+# E.Torrence, Aug. 2019
+#
+#
+# Use Python3-style print statements
+from __future__ import print_function
+
+import sys
+import ROOT
+
+from Monitoring.MonitorValueBase import MonitorValueBase, MonitorConfigBase
+
+#
+# 1D Monitoring class and configuration
+#
+class Monitor1DValueConfig(MonitorConfigBase):
+ """Configuration for Monitor1DValue"""
+
+ # Everything in this configuration must be simple values so JSON works
+
+ def __init__(self):
+ """Constructor providing default values"""
+
+ MonitorConfigBase.__init__(self)
+ # Defines tag, type, and desc
+
+ # Variable
+ self.selector = None # Text string describing selector class
+
+ self.xvar = None # Text string describing value to fill
+
+ # Scale factor
+ self.xscale = 1
+
+ # Histogram parameters
+ self.nbins = 0
+ self.xlo = 0.
+ self.xhi = 0.
+ self.xlabel = ""
+ self.ylabel = ""
+
+ # Plot under/overflows
+ self.overflow = True
+
+ # Draw as linear or log scale by default
+ self.logy = False
+
+ # Utility function to make it easier to define hist parameters
+ def setBinning(self, nbins, xlo, xhi, xlabel="", ylabel=""):
+ """Define histogram bins and range"""
+
+ # Utility function to set histogram parameters in one go
+ self.nbins = nbins
+ self.xlo = xlo
+ self.xhi = xhi
+ self.xlabel = xlabel
+ self.ylabel = ylabel
+
+
+class Monitor1DValue (MonitorValueBase):
+ """One dimensional monitored value class"""
+
+ def __init__(self, tag=''):
+ """Constructor, tag is a unique identification string"""
+
+ # Instantiate the configuration object
+ self.conf = Monitor1DValueConfig()
+
+ # Set the tag if provided
+ self.conf.tag = tag
+
+ def init(self):
+ """Initialize class and create histogram"""
+
+ # First call the base class, which checks a few things
+ MonitorValueBase.init(self)
+
+ # Now create our histogram with the parameters in self.conf
+ # Check if we want to store integers or floats
+ if isinstance(self.conf.xlo, int) and isinstance(self.conf.xhi, int):
+ self.hist = ROOT.TH1I(self.conf.tag+"_h", "",
+ self.conf.nbins, self.conf.xlo, self.conf.xhi)
+ else:
+ self.hist = ROOT.TH1D(self.conf.tag+"_h", "",
+ self.conf.nbins, self.conf.xlo, self.conf.xhi)
+
+ # Also set labels
+ self.hist.GetXaxis().SetTitle(self.conf.xlabel)
+ self.hist.GetYaxis().SetTitle(self.conf.ylabel)
+
+ def fill(self, event):
+ """Fill histogram from event object"""
+
+ self.fillValue(self.selector.get1DValue(event, self.conf.xvar))
+
+ #varstr = self.conf.xvar
+ #theVar = getattr(event, varstr)
+ #self.fillValue(theVar)
+
+ def fillValue(self, val):
+ """Fill histogram with one or more values"""
+
+ #print ("Monitor1DValue.fillValue called with", val)
+
+ # Check if this is a single value or an iterable sequence
+ if hasattr(val, '__iter__'):
+ for v in val:
+ self.hist.Fill(v*self.conf.xscale)
+ else:
+ self.hist.Fill(val*self.conf.xscale)
+
+
+ def plot(self, c):
+ """Plot histogram to canvas c"""
+
+ # Log or lin?
+ if self.conf.logy:
+ c.SetLogy(True)
+ else:
+ c.SetLogy(False)
+
+ # Do something fancy to draw the overflow?
+ if self.conf.overflow:
+ # Must make a new histogram and fill under/overflow in first/last bins
+ h = self.hist.Clone()
+ nb = h.GetNbinsX()
+
+ under = h.GetBinContent(0)
+ h.SetBinContent(1, h.GetBinContent(1)+under)
+ over = h.GetBinContent(nb+1)
+ h.SetBinContent(nb, h.GetBinContent(nb)+over)
+
+ else:
+ h = self.hist
+
+ # Draw with default parameters
+ h.DrawCopy()
+
+# Testing code
+if __name__ == '__main__':
+
+ mv1 = Monitor1DValue('test1')
+ mv1.conf.setBinning(30, -3., 3.)
+ mv1.init()
+
+ mv2 = Monitor1DValue('test2')
+ mv2.conf.setBinning(30, -3., 3.)
+ mv2.init()
+
+ # Fill a list
+ import random
+ values = [random.gauss(0., 1.) for x in range(100)]
+ mv1.fill(values)
+
+ # Try one more
+ mv1.fill(random.gauss(0., 1.))
+
+ # Print something out
+ mv1.dump()
+
+ # Write to file
+ print()
+ print("Test writing to ROOT file")
+ tf = ROOT.TFile("test.root", "recreate")
+ mv1.writeRoot(tf)
+ mv2.writeRoot(tf)
+ #writeMonitorValue(tf, mv1)
+ #writeMonitorValue(tf, mv2)
+ tf.Close()
+
+ print()
+ print("Test reading from ROOT file")
+ tf = ROOT.TFile('test.root')
+
+ print()
+ print("Directory listing")
+ tf.ls()
+
+ from Monitoring.MonitorValueBase import readMonitorValueFromRoot
+
+ print()
+ print("Read objects back from ROOT file")
+ mvr1 = readMonitorValueFromRoot(tf, "test1")
+ mvr1.dump()
+ mvr2 = readMonitorValueFromRoot(tf, "test2")
+ mvr2.dump()
+ try:
+ readMonitorValueFromRoot(tf, "test3")
+ except Exception as e:
+ print(e)
+
diff --git a/Monitoring/python/MonitorValueBase.py b/Monitoring/python/MonitorValueBase.py
new file mode 100644
index 00000000..82220c35
--- /dev/null
+++ b/Monitoring/python/MonitorValueBase.py
@@ -0,0 +1,253 @@
+#
+# MonitorValueBase.py
+#
+# Defines base classes to implement monitored values
+#
+# Functions
+# readMonitorValueFromRoot - read MonitorValue from ROOT file
+# monitorValueFromJSON - construct MonitorValue from JSON
+#
+# Classes
+# MonitorValueBase
+# MonitorConfigBase
+#
+# E.Torrence, Aug. 2019
+#
+#
+# Use Python3-style print statements
+from __future__ import print_function
+
+import sys
+import ROOT
+import json
+
+# Utility function to create object instance from ROOT file
+def readMonitorValueFromRoot(f, tag):
+ """Read class named tag from open root file f"""
+
+ # Objects stored in subdirectory, make sure it exists
+ if not f.cd(tag):
+ print("Object", tag, "not present in file!")
+ f.ls()
+ raise ObjectNotFoundError("Error: directory not found for object "+tag+"!")
+
+ #print ("Changed to directory", tag)
+ #f.ls()
+
+ # Read histogram first
+ histName = tag+"_h"
+ #print("Reading histogram", histName)
+ hist = ROOT.gROOT.FindObject(histName)
+ if hist is None:
+ f.cd("..")
+ raise ObjectNotFoundError("Error: unable to read histogram", histName,"!")
+
+ # Read JSON string stored in a TNamed object
+ objectName = tag+"_j"
+ tobj = ROOT.gROOT.FindObject(objectName)
+ if tobj is None:
+ f.cd("..")
+ raise ObjectNotFoundError("Error: unable to read JSON from",objectName, "!")
+
+ # Get JSON string from TNamed
+ jsonString = tobj.GetTitle()
+
+ #print(jsonString)
+ #obj = pickle.loads(unicode(pickleString.GetTitle(), 'utf-8'))
+
+ # Call our utility function to create a new (un-initalized) object
+ obj = monitorValueFromJSON(json.loads(jsonString))
+
+ # And put the histogram back
+ obj.hist = hist
+
+ # Return to the parent directory in the ROOT file
+ f.cd("..")
+
+ # Return the recreated object
+ return obj
+
+
+# Utility to create a new class from a JSON description
+# This does not initialize the class
+def monitorValueFromJSON(jsonDict):
+
+ # jsonDict = json.loads(jsonString)
+
+ # Get the object class name
+ className = jsonDict.get('type', None)
+ if className is None:
+ print ("monitorValueFromJSON: no class type specified!")
+ return None
+
+ # Find the class object in our module
+ # This is some voodoo
+ # Monitoring is the package name
+ # className is both the class but also the submodule to search in
+ # The fromlist=[] needs to specify the submodules
+ # So this works as long as each MV type has a unique module
+ # Need a better way to do this (perhaps using __init__.py?
+ class_ = getattr(__import__("Monitoring."+className, fromlist=[className]), className)
+
+ # Instantiate this class
+ obj = class_()
+
+ if obj is None:
+ f.cd("..")
+ raise ObjectNotFoundError("Error: unable to instantiate object", objectName, "!")
+
+ # Update the configuration from the JSON file
+ obj.conf.fromJSON(jsonDict)
+
+ # Also instantiate the selector
+ className = jsonDict.get('selector', None)
+
+ if className is None:
+ obj.selector = None
+ print ("monitorValueFromJSON: No selector specified for value", jsonDict["tag"])
+
+ else:
+ # Find the class name in our module
+ class_ = getattr(__import__("Monitoring."+className, fromlist=[className]), className)
+ # And instantiate this class
+ obj.selector = class_()
+
+ if obj.selector is None:
+ raise ObjectNotFoundError("Error: unable to instantiate object", objectName, "!")
+
+ # Done with selector object
+
+ # Don't call obj.init here, make user do this
+ return obj
+
+# Error in case histogram can't be read
+class ObjectNotFoundError(KeyError):
+ pass
+
+class MonitorValueBase ():
+ """Base class for monitored values"""
+
+ def __init__(self):
+ """Dummy Constructor"""
+
+ # Configuration object to store all needed parameters
+ self.conf = None
+
+ # Histogram (or other ROOT class) containing data
+ self.hist = None
+
+ # Selector class to fill histogram
+ self.selector = None
+
+ # Common init functions
+ def init(self):
+
+ if self.conf is None:
+ print ("MonitorValueBase: init() called with no valid configuration!")
+ return
+
+ # Set type if not configured
+ actualType = self.__class__.__name__
+ if self.conf.type == None:
+ self.conf.type = actualType
+
+ # Check that type is correct
+ elif actualType != self.conf.type:
+ print ("actualType", actualType, "does not match configured type", self.conf.type,"!")
+ print ("...overriding conf.type")
+ self.conf.type = actualType
+
+ # Initialize the selector
+ if self.selector is not None:
+ self.selector.init(self.conf)
+
+
+ def fill(self, v):
+ # Dummy fill function
+ pass
+
+ def plot(self, c):
+ # Dummy plot function, must pass canvas in case we want to make log scale
+ pass
+
+ def dump(self):
+ """Write histogram to specified stream (stdout by default)"""
+
+ #print("Dump called for", self.conf.tag)
+ print(self.conf)
+ if self.hist is not None:
+ self.hist.Print()
+
+ def __str__(self):
+ return str(self.conf)
+
+ def writeRoot(self, f):
+ """Write hist and conf to open root file f"""
+
+ # Make a subdirectory to contain the components and switch
+ cwd = f.mkdir(self.conf.tag)
+ cwd.cd()
+
+ # Write the histogram first (if it isn't NULL)
+ if self.hist is not None:
+ self.hist.Write()
+
+ # Also write the conf JSON to TString
+ # ROOT name is tag_p
+ jsonString = self.conf.toJSON()
+ ts = ROOT.TNamed(self.conf.tag+"_j", jsonString)
+ ts.Write()
+
+ # Also write pickled object to TString
+ # pickleString = pickle.dumps(self)
+ # ts = ROOT.TNamed(self.tag+"_p", pickleString.decode("utf-8"))
+ # ts.Write()
+
+ # Now go back to starting directory to not screw things up
+ cwd.cd("..")
+
+ # These aren't needed any more
+ # Remove hist from elements to pickle (we save this separately)
+ def __getstate__(self):
+ state = self.__dict__.copy()
+ # Don't pickle hist
+ del state["hist"]
+ return state
+
+ def __setstate__(self, state):
+ self.__dict__.update(state)
+ # Add hist back since it doesn't exist in the pickle
+ self.hist = None
+
+#
+# Base class for configuration objects
+class MonitorConfigBase:
+
+ def __init__(self):
+ """Constructor provides default values"""
+ self.tag = "" # Unique identifier string
+ self.type = None # Class name of instantiated MonitorValue object
+ self.desc = "" # Helpful description string
+
+ def toJSON(self, indentLevel=0):
+ """Return JSON string describing values in this class"""
+ return json.dumps(self, default=lambda o: o.__dict__,
+ sort_keys=True, indent=indentLevel)
+
+ def fromJSONStr(self, jsonString):
+ """Update class attributes using values read in from JSON string"""
+
+ # Note, values not specified will not be changed
+ jsonDict = json.loads(jsonString)
+ self.fromJSON(jsonDict)
+
+ def fromJSON(self, jsonDict):
+ """Update class attributes using values in parsed JSON dict"""
+
+ # This will only work for simple parameters
+ for (key, val) in jsonDict.iteritems():
+ setattr(self, key, val)
+
+ def __str__(self):
+ return self.toJSON(indentLevel=2)
+
diff --git a/Monitoring/python/MonitorValueManager.py b/Monitoring/python/MonitorValueManager.py
new file mode 100755
index 00000000..af869e22
--- /dev/null
+++ b/Monitoring/python/MonitorValueManager.py
@@ -0,0 +1,200 @@
+#!/bin/env python
+#
+# MonitorValueManager.py
+#
+# Defines the MonitorValueManager class that coordinates actions
+# for a large set of instantiated MonitorValue objects
+#
+# Classes
+# MonitorValueManager
+#
+# E.Torrence, Aug. 2019
+#
+# Use python3-style print statements
+from __future__ import print_function
+
+import ROOT
+import json
+
+from Monitoring.MonitorValueBase import monitorValueFromJSON
+
+# Need to import all defined MV types so we can find them below
+from Monitoring.Monitor1DValue import Monitor1DValue
+
+
+class MonitorValueManager:
+ """Class to instantiate and manage a large set of MonitorValue objects"""
+
+ def __init__(self):
+ """Constructor"""
+
+ # Flag to print out some monitoring information
+ self.debug = True
+
+ # dict containing all MonitorValues, tags are used for keys
+ self.mvalDict = dict()
+
+ # Key list, used to keep order straight
+ self.tagList = []
+
+ def addValue(self, val):
+ """Add an instantiated MonitorValue to the dictionary"""
+
+ tag = val.conf.tag
+ if tag in self.mvalDict.keys():
+ print("Value with tag", tag,"already exists!")
+ print(self.mvalDict[tag].conf)
+ return
+
+ self.mvalDict[tag] = val
+ self.tagList.append(tag)
+
+ def initValues(self):
+ """Call the init method on all stored MVs"""
+ # Loop through all MonitorValues defined and call the init() function
+ for val in self.mvalDict.itervalues():
+ if (self.debug):
+ print("Initializing value", val.conf.tag)
+
+ val.init()
+
+ def fillValues(self, event):
+ """Call the fill method on all stored MVs"""
+ for val in self.mvalDict.itervalues():
+ val.fill(event)
+
+ def writeValues(self, filename):
+ """Write out value histograms to file"""
+
+ # Simplest implementation for now
+ # Add some directory structure later
+ f = ROOT.TFile(filename, "RECREATE")
+
+ for val in self.mvalDict.itervalues():
+ val.writeRoot(f)
+
+ # Cleanup
+ f.Close()
+
+ def plotValuesToPDF(self, filename):
+ """Call the plot methods with output going to a PDF file"""
+
+ # Lets see if this works
+ c = ROOT.TCanvas()
+ c.Print(filename+"[")
+
+ for tag in self.tagList:
+ val = self.mvalDict[tag]
+ val.plot(c)
+ c.Print(filename)
+
+ c.Print(filename+"]")
+
+ def createValuesFromJSON(self, filename):
+ """ Create values from JSON file of name filename"""
+
+ if self.debug: print("Opening JSON file", filename)
+ # Open file
+ try:
+ f = open(filename)
+ except Exception as e:
+ print("Error opening file", filename)
+ print(e)
+ return
+
+ # Parse JSON
+ if self.debug: print("Parsing JSON")
+ jsonList = json.load(f)
+
+ # Close the file
+ f.close()
+
+ # Keep track of what we are doing
+ count = 0
+ if self.debug: print("Creating objects from JSON")
+ for item in jsonList:
+ try:
+ newval = monitorValueFromJSON(item)
+ except Exception as e:
+ # On error, print error and continue
+ print("MonitorValueManager.createValuesFromJSON - Error creating object", item, "!")
+ print(e)
+ continue
+
+ self.addValue(newval)
+ count += 1
+
+ # Print out some results
+ if (self.debug):
+ print("Created", count, "new values")
+ print("Full list of MonitorValue tags:")
+ for key in sorted(self.mvalDict.keys()):
+ print(key)
+
+ def listValues(self):
+ """Print out type and tags for all defined values"""
+
+
+ print ("Listing of MonitorValues")
+
+ if len(self.mvalDict) == 0:
+ print("Value list is empty!")
+ return
+
+
+ print("Tag ValueType")
+ print("--- ---------")
+ for tag in self.tagList:
+ print(tag, self.mvalDict[tag].conf.type)
+
+ def dumpValues(self):
+ """Print out verbose information for all defined values"""
+
+ if len(self.mvalDict) == 0:
+ print("Value list is empty!")
+ return
+
+ for tag in self.tagList: # Sort to get alphabetical listing
+ print()
+ print(tag, self.mvalDict[tag].conf.type)
+ self.mvalDict[tag].dump()
+
+ def writeJSON(self, stream):
+ """Write out JSON for all configured objects to specified stream"""
+
+ jsonList = []
+ for tag in self.tagList:
+ val = self.mvalDict[tag]
+ jsonList.append(val.conf)
+
+ json.dump(jsonList, stream, default=lambda o: o.__dict__,
+ sort_keys=True, indent=2)
+
+# Testing code
+if __name__ == '__main__':
+
+ from Monitoring.Monitor1DValue import Monitor1DValue
+
+ mv1 = Monitor1DValue('test1')
+ mv1.conf.setBinning(30, -3., 3.)
+
+ mv2 = Monitor1DValue('test2')
+ mv2.conf.setBinning(60, -3., 3.)
+
+ mvm = MonitorValueManager()
+
+ mvm.addValue(mv1) # Add already defined mv
+ mvm.addValue(mv2)
+ mvm.initValues() # Initialize all values
+ mvm.listValues() # Brief printout of all values
+ mvm.dumpValues()
+
+
+ import sys
+ mvm.writeJSON(sys.stdout)
+ print()
+
+ mvm.createValuesFromJSON('test.json')
+
+ mvm.listValues()
+
diff --git a/Monitoring/python/README b/Monitoring/python/README
new file mode 100644
index 00000000..fb7bb8fe
--- /dev/null
+++ b/Monitoring/python/README
@@ -0,0 +1,11 @@
+Things to do:
+-) Add some structure to the JSON config file, in particular, create
+ some kind of set structure that will be reflected in ROOT file,
+ but also groups monitored quantities by type.
+
+-) Remove JSON text from ROOT file (or store in separate structure)
+
+-) Figure out how to read ntuple variables. Possibly have a 'handler' by
+ data type, i.e. TruthParticle or SpacePoints. These will know how to
+ decode variables by simple string, and also might have their own config
+ parameters to be set.
diff --git a/Monitoring/python/__init__.py b/Monitoring/python/__init__.py
new file mode 100644
index 00000000..447ad57d
--- /dev/null
+++ b/Monitoring/python/__init__.py
@@ -0,0 +1,2 @@
+#
+__author__ = "Eric Torrence"
diff --git a/Monitoring/share/simpleMonitoringTest.json b/Monitoring/share/simpleMonitoringTest.json
new file mode 100644
index 00000000..60e8fe25
--- /dev/null
+++ b/Monitoring/share/simpleMonitoringTest.json
@@ -0,0 +1,106 @@
+[
+ {
+ "tag": "eventNumber",
+ "type": "Monitor1DValue",
+ "desc": "Event Number",
+ "selector": "LegacySelector",
+ "xvar": "fEventNumber",
+ "nbins": 1000,
+ "xlo": 0,
+ "xhi": 10000,
+ "xlabel": "Event Number",
+ "ylabel": "Entries",
+ "overflow": true,
+ "logy": false
+ },
+ {
+ "tag": "pdgCode",
+ "type": "Monitor1DValue",
+ "desc": "Truth particle PDG Code",
+ "selector": "LegacySelector",
+ "xvar": "fParticles.PdgCode",
+ "nbins": 53,
+ "xlo": -12,
+ "xhi": 40,
+ "xlabel": "PDG Code",
+ "ylabel": "Entries",
+ "overflow": true,
+ "logy": true
+ },
+ {
+ "tag": "truthEnergy",
+ "type": "Monitor1DValue",
+ "desc": "Truth particle energy",
+ "selector": "LegacySelector",
+ "xvar": "fParticles.Energy",
+ "xscale": 0.001,
+ "nbins": 50,
+ "xlo": 0.0,
+ "xhi": 1000.0,
+ "xlabel": "Energy (GeV)",
+ "ylabel": "Entries",
+ "overflow": true,
+ "logy": false
+ },
+ {
+ "tag": "truthVertexX",
+ "type": "Monitor1DValue",
+ "desc": "Truth particle X Vertex",
+ "selector": "LegacySelector",
+ "xvar": "fParticles.Vertex.x",
+ "xscale": 0.001,
+ "nbins": 50,
+ "xlo": -0.5,
+ "xhi": 0.5,
+ "xlabel": "Truth Vertex X (m)",
+ "ylabel": "Entries",
+ "overflow": true,
+ "logy": false
+ },
+ {
+ "tag": "truthVertexY",
+ "type": "Monitor1DValue",
+ "desc": "Truth particle Y Vertex",
+ "selector": "LegacySelector",
+ "xvar": "fParticles.Vertex.y",
+ "xscale": 0.001,
+ "nbins": 50,
+ "xlo": -0.5,
+ "xhi": 0.5,
+ "xlabel": "Truth Vertex Y (m)",
+ "ylabel": "Entries",
+ "overflow": true,
+ "logy": false
+ },
+ {
+ "tag": "truthVertexZ",
+ "type": "Monitor1DValue",
+ "desc": "Truth particle Z Vertex",
+ "selector": "LegacySelector",
+ "xvar": "fParticles.Vertex.z",
+ "xscale": 0.001,
+ "nbins": 50,
+ "xlo": -2.5,
+ "xhi": 2.5,
+ "xlabel": "Truth Vertex Z (m)",
+ "ylabel": "Entries",
+ "overflow": true,
+ "logy": false
+ },
+
+ {
+ "tag": "trackerDigiPlane",
+ "type": "Monitor1DValue",
+ "desc": "Tracker Digi Plane",
+ "selector": "LegacySelector",
+ "xvar": "fTrackerDigis.Plane",
+ "nbins": 11,
+ "xlo": -1,
+ "xhi": 10,
+ "xlabel": "Plane",
+ "ylabel": "Digis",
+ "overflow": true,
+ "logy": false
+ }
+
+]
\ No newline at end of file
diff --git a/Monitoring/share/simpleMonitoringTest.py b/Monitoring/share/simpleMonitoringTest.py
new file mode 100755
index 00000000..f33301e0
--- /dev/null
+++ b/Monitoring/share/simpleMonitoringTest.py
@@ -0,0 +1,41 @@
+#!/bin/env python
+#
+# simpleMonitoringTest.py
+#
+# Example of simple monitoring job using hte MonitorValueManager
+# Need JSON file simpleMonitoringTest.json and a TDR-style
+# ntuple in the run directory
+#
+# E. Torrence, Aug. 2019
+#
+# Use python3-style print statements
+from __future__ import print_function
+
+from Monitoring.MonitorValueManager import MonitorValueManager
+
+import ROOT
+
+# Start by instantiating mvm
+mvm = MonitorValueManager()
+
+# Load the configuration
+mvm.createValuesFromJSON('simpleMonitoringTest.json')
+mvm.initValues()
+# mvm.listValues() # Check what we have
+mvm.dumpValues() # Check what we have
+
+# Open ntuple
+tf = ROOT.TFile('ntuple.root')
+tt = tf.Get('faser')
+
+# Loop over events
+for event in tt:
+ mvm.fillValues(event)
+
+tf.Close()
+
+# Write to file
+mvm.writeValues('simpleMonitoringTest.root')
+
+# Plot values
+mvm.plotValuesToPDF('simpleMonitoringTest.pdf')
--
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