Outputs

hmc_perfomance.txt

This text file is appended with a new line every time the HMC is used. Each column has the following meaning:

epsilon used in the integrator
number of timesteps
variation of energy between first and last step (ΔH = H_final − H_initial). Please note that you actually want this one to be negative or order 1 as the acceptance is determined by the probability exp( − ΔH).
wall seconds taken to do the entire HMC run
scheme used to integrate
value of the final hamiltonian

log files

The log files are formatted by libLSS/tools/console.hpp. If you have not explicitly disabled the debug level, then all the messages emitted by the code are saved in those files. Otherwise, it is limited to verbose level. Each line starts with square brackets, with the level of the message indicated "[LEVEL]". Each new indentation corresponds to a new subcontext. If timing information were requested at compile time, each termination of context gives also the time taken in the context itself, including everything called inside this same context.

restart files

This file gives you access to the relevant infromation required to restart an MCMC run, such as the initial configuration. The ares framework creates one restart file per MPI task. Each file is suffixed by "_X" where X is the MPI task id. Most of the variables are just the same from one file to the other. The exception are the arrays explicitly sliced by the MPI parallelization which are only present by slab.

The file contains the following groups:

galaxy_catalog_0
galaxy_kecorrection_0
random_generator
scalars

The python script "scripts/merge_mpi_restart.py" can merge all these restart files into a single restart.h5 file. Be aware that it may consume quite a lot of memory. However it is a required step to allow the user to change the number of MPI task for an exisiting ARES run. The MPI run may be resumed with the option "SPECIAL_RESUME" instead of "RESUME" and it will read restart.h5 to recreate the set of "restart.h5_XX" files with the new number of MPI tasks.

MCMC files

Depending on length of run, a series of mcmc files will be produced with file names 'mcmc_chainNumber.h5'. All attributes of the file are contained within the group 'scalars', for example the following for the basic run in "examples":

catalog_foreground_coefficient_0
galaxy_bias_0
galaxy_nmean_0
powerspectrum
s_field
spectrum_c_eval_counter

For reference, these groups and attributes can be easily searched through a few lines of python:

import h5py as h5

# access mcmc file
hf = h5.File("mcmc_0.h5")
# list groups within file
list(hf.keys())
# list attributes within 'scalars' group
list(hf['scalars'].keys())

A tutorial to read and plot basic ARES outputs with python is available :ref:`here <tutorial_ares_basic_outputs>`.

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If one wishes to access the MCMC files in C++, functions are available in CosmoTool and LibLSS: see :ref:`this code tutorial <reading_in_meta_parameters_and_arrays>`.

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Outputs

hmc_perfomance.txt

log files

restart files

MCMC files

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