ashlaban

import argparse

from collections import namedtuple as Namedtuple

class ArgumentParserDelegator(argparse.ArgumentParser):
    '''Supports mutliple nested subparsers (structured parser)

    A structured parser is one that supports multiple 'stages', or
    'subcommands'.

ashlaban

#include <memory>
#include <vector>

int main(int argc, char** argv) {
    // Create a unique pointer
    auto a = std::make_unique<int>(argc);

    // One can get a reference to its contents!
    int const & b = *a;

ashlaban

#
# NOTE: Requires that you have run `python create_dataset.py`
#       from https://github.com/stwunsch/tmva_mnist first.
#

import ROOT

from resnet import ResnetBuilder

# Setup TMVA

ashlaban

from __future__ import division

import six
from keras.models import Model
from keras.layers import (
    Input,
    Reshape,
    Activation,
    Dense,
    Flatten

ashlaban

# version 1
def function_with_snake_case_and_long_name(fix_param1, fix_param2,
                                           keyword_param1='some default',
                                           keyword_param2='some other defualt'):
    # TODO: Implement function body
    pass

# version 2
def function_with_snake_case_and_long_name(

ashlaban

void test() {
   // === Provokes error
   // root -l -q test.C
   // or
   // lldb -- root.exe -l -q test.C
   // break set --name TH1::KolmogorovTest

   const size_t NBINS = 200;

ashlaban

# Configuring and building ROOT
#
# The three lines for Python is to make cmake pick up the brew installation 
# instead of the system one (important if you want to use pyROOT).
# Modify as you please.
#

cd /path/to/where/you/build/root

cmake /path/to/root/src \