riga

<?
  // CHANGE ME: add your local www root here
  $local_root =	"/eos/home-i03/m/mrieger/www";

  // extensions to scan
  $additional_extensions = array("pdf", "cxx", "eps", "root", "txt");

  // mode for showing hits when searching
  // "all", "any" or empty
  $search_pattern_mode = "any";

riga

# coding: utf-8

"""
Helpers for loading remote files from CERN EOS.
"""

import os
import subprocess

import six

riga

# coding: utf-8

# import root into a cage
import ROOT
ROOT.PyConfig.IgnoreCommandLineOptions = True
ROOT.gROOT.SetBatch()


# preps
canvas = ROOT.TCanvas()

riga

CMS TDR documents on Overleaf

This gist demonstrates how to prepare CMS TDR documents to work on Overleaf.

All of the following files should be copied to the root directory of your project:

• build.sh: Compiles the document once and saves a tex document (and the current pdf) to a new directory, named "overleaf" by default, which can be used as a root document on Overleaf. Please note that changes to this document get lost once this build script is executed again.
• build_docker.sh: Executes the build script in a docker container using the official tdr build image.
• latexmkrc: Tells the LaTeX compiler on Overleaf where to find the tdr tool.

riga

# coding: utf-8

# This script showcases a few examples on how to simplify working with ROOT objects within law.
#
# Scope:
#   1. Usage of the low-level GuardedTFile
#   2. Reading and writing ROOT files via target formatters
#   3. Merging ROOT files with hadd_task

import law

riga

# coding: utf-8

"""
Example gist to be used with the cms_gist_runner. Execute via
> ~mrieger/public/bin/cms_gist_runner 522d2d08dab617a46444213fe202d919 -v CMSSW_11_1_2 -t
"""

import tensorflow as tf

riga

body.rise-enabled div.prompt_container {
    background-color: red !important;
}

div#notebook {
    background-color: green !important;
}

riga

# coding: utf-8

"""
Command to run the tasks:
luigi --module progress_tasks TaskB --workers 2
"""

import time
import luigi

riga

# coding: utf-8


import time

import law


def test_htcondor():
    # load the htcondor contrib package, making all exported objects available under law.htcondor

riga

/*
 * Performance test of the DeepJet model with both TensorFlow and ONNXRuntime.
 * Place this file into a cmssw test directory and add the following to the BuildFile.xml:
 *
 * <bin name="testTFDeepJetPerformance" file="testRunner.cpp,testDeepJetPerformance.cc">
 *     <use name="cppunit" />
 *     <use name="FWCore/Utilities" />
 *     <use name="PhysicsTools/TensorFlow" />
 *     <use name="PhysicsTools/ONNXRuntime" />
 * </bin>