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TABLE OF CONTENTS:
  1. DIRECTORY CONTENTS
  2. USAGE
  3. BUILD INSTRUCTIONS
  4. DATA CONTENTS & SCRIPTS

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1. DIRECTORY CONTENTS
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This folder contains the source code for HHT. Below is a summary of 
it's contents:
-main.cpp       Implementation of function main(), handles command-
   line options and user I/O.
-tail_map.cpp   Implementation for St
-tail_map.hpp   Header file to export those objects/methods
-head_map.cpp   Implementation for Sh
-head_map.hpp   Header file to export those objects/methods
-Makefile       Makefile to build HHT, this is the only file that
   a user should have to edit.
-data/          Directory containing all the experimental data.
-scripts/       Directory containing scripts outlined in section 4.
-shll/          Directory containing all of the implementation for the
   sliding HyperLogLog counters, much of it is taken from 
   Google's HyperLogLog++ and dialtr's libcount on GitHub.

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2. USAGE
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NAME
       hht - run hht algorithm on a given graph stream

SYNOPSIS
       hht [OPTION] [ARG]

DESCRIPTION
       To run hht, a number of parameters are needed. These are 
       specified as arguments to command line options. For a full
       description of the options available with HHT, run 
          >$ ./hht --help
       The most important options are as follows:
       --input [File] 	Specify input file for graph stream. If input
                	is not specified, HHT looks for multigraph.txt
       --output [File]	Specify output file. If output is not specified
                     	output is written to myoutput
       See the --help option for info on how to set ph and pt.

OUTPUT
       The output will be printed to the specified value with the 
       following at the beginning of each file.
       >File : [input], length = [last timestamp read in], Head size = 
        [number of nodes in Sh], Tail size = [num nodes in St] ph = 
        [prob], pt = [prob]
       For each query to HHT, the output file will contain output of 
       the form
       >   [Estimate|True distro], window = [window queried]
       >      xs = [ [x-coord 1], [x-coord 2], ...]
       >      ys = [ [y-coord 1], [y-coord 2], ...]
       >      [dthr = [num]]
       This last line will only appear if it is showing the ccdh for an
       estimate and not for the true ccdh.

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3. BUILD INSTRUCTIONS
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DEPENDENCIES
        HHT is written in C++ using the C++11 standard. It requires 
        the program_options module from the C++ Boost libraries. In 
        addition, the hash functions use the SHA-1 hash from the 
        openssl library. This can be modified in shll/shll.cc file.

        The Makefile assumes a C++17 compliant version of the g++ 
        compiler. However, this has been compiled with clang, and minor
        modifications to the Makefile should allow it to be built using
        the clang compiler. 

MAKEFILE MODIFICATIONS
        The Makefile macro CXX can be changed to clang if desired. The 
        macros CXXFLAGS and LDFLAGS assume that Boost is in 
        ~/build/boost_1_61_0. This may need to be modified if the Boost
        libraries are installed in a different directory.

TO BUILD
        Enter at the command prompt:
        >$ make hht
        This should be all that is required when all the prerequisites
        are met. This installs the program hht in the current directory.

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4. DATA CONTENTS & SCRIPTS
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FORMAT
       All of the experimental datasets are pickled DataFrames from the
       Python pandas package. They are pickled using Python3's default
       pickle.dump() options. Each individual query is a row in the 
       dataset and the column names should explain the information
       contained therein.

DATASETS
       -p_tests.pkl     Information on all 28,000+ runs on Zeta3 
                        streams with various windows and constant ph 
                        and pt values

SCRIPTS 
       -rhcalculator.py - Python package with methods to compute RH
                          distance of ccdhs
       -calculate_distance.py - python script to take HHT output and
                                create pandas DataFrame
       -old_utility.py - python package to aid calculate_distance.py
       -ChungLu.py - python script to generate graph streams