Analysis and postprocessing
(page under construction)
This page collects information on existing tools which can be used to analyse data produced using the Einstein Toolkit. See also Visualization of simulation results.
Contents
SimulationTools
Homepage  simulationtools.org 

Authors  Ian Hinder and Barry Wardell 
License  GPLv3 
Requirements  Mathematica (proprietary) 
Other info  Documentation, unit tests (automatic on commit) 
SimulationTools provides a functional interface to simulation data which deals transparently with merging output from different segments, and can read data from several different thorns, depending on what is available. The package supports reading Carpet HDF5 data and doing the required componentmerging etc. so that you can do analysis on the resulting data in Mathematica. This supports 1D, 2D and 3D data, but is essentially dimensionagnostic. It has a component called SimulationOverview which displays a panel summarising a BBH simulation, including run speed and memory usage as a function of coordinate time, BH trajectories, separation, waveforms, etc. SimulationTools is coupled to a C++ replacement for the Mathematica HDF5 reader.
SimulationTools is available under the GPL and is developed on BitBucket, and would be a good candidate for including in the Einstein Toolkit at some point.
A more detailed overview of the features in SimulationTools is available.
PostCactus
Homepage  https://github.com/wokast/PyCactus 

Authors  Wolfgang Kastaun 
License  GPLv3 
Requirements  Python 2.7, HDF5, H5Py, NumPy, SciPy 
Other info  Wiki 
This package contains modules to read and represent various CACTUS data formats in Python, and some utilities for data analysis. In detail,
 simdir is an abstraction of one or more CACTUS output directories, allowing access to data of various type by variable name, and seamlessly combining data split over several directories.
 cactus_grid_h5 reads 1,2 and 3D data from CACTUS hdf5 datasets.
 cactus_grid_omni uses whatever data source it finds, e.g. cut a 3D file to get xy plane data
 grid_data represents simple and mesh refinened datsets, common arithmetic operations on them, as well as interpolation.
 cactus_scalars reads CACTUS 0D/Reductions ASCII files representing timeseries.
 cactus_gwsignal reads GW data
 cactus_multipoles reads multipole decomposition data (ASCII)
 timeseries represents timeseries and provides resampling numerical differentiation.
 fourier_util performs FFT on timeseries and searches for peaks.
 unitconv performs unit conversion with focus on geometric units, including predefined CACTUS, PIZZA, and CGS systems.
yt
Homepage  yt project 

Authors  many 
License  BSD 3clause license 
Requirements  all in one install script 
Other info  Documentation 
Mostly a visualization toolkit with basic support to read Cactus data, however can do some data manipulation. The current version of the Einstein Toolkit frontend is available in Kacper Krowalik's fork of yt. It is a work in progress and highly experimental. Therefore many datasets will not be read in correctly. To attain it:
hg clone ssh://hg@bitbucket.org/xarthisius/yt cd yt hg bookmark cactus python setup.py build_ext i
if this works, you installed yt. Now just add $(pwd) to your PYTHONPATH.
Some example scripts for using and extending yt (and using the Einstein Toolkit frontend) can be found here.
PyCactus
Homepage  https://bitbucket.org/knarrff/pycactus 

Authors  Roberto De Pietri, Francesco Maione, Frank Löffler 
License  GPL 
Requirements  Python 
PyCactus are tools currently primarily developed to read Carpet ASCII and HDF5 data (especially 0D/1D) for usage in python and plotting using matplotlib. Documentation is essentially nonexistent at this point, but the scripts are not that long and for the most part should be understandable.
rugutils
Homepage  https://bitbucket.org/fguercilena/rugutils not working realastro fork of Guercilena's code 

Authors  Federico Guercilena 
License  GPLv3 
Requirements  Python 3, NumPy, Matplotlib, h5py, HDF5 
A minimalist set of tools to read and plot Carpet data, with an equally minimalist set of dependencies, written in Python 3. The tools allow to read and plot 0D, Scalar, 1D data in ASCII format and 2D data in HDF5 format. The focus of these tools is to allow quickly looking at large data sets in a hasslefree way, without worrying too much about producing beautiful, publication ready figures. The main piece of software is the "rug" script, with four subcommands (rope, freeze, snake and window) to deal with various kinds of data. Quite a lot of documentation is available on the command line by typing: 'rug doc command' where command is one of the available command names.
scidata
Homepage  https://bitbucket.org/dradice/scidata 

Authors  David Radice 
License  GPLv3 
Requirements  Python 3, NumPy, h5py 
Simple, highperformance, Cactus/Carpet data reader for python2.7. It serves as the underpinning of pyGraph.
pyGWAnalysis
Homepage  https://svn.einsteintoolkit.org/pyGWAnalysis/ 

Authors  Christian Reisswig 
License  MIT 
Requirements  Python 2.7, NumPy 
A simple set of GW analysis tools in python. Can be made to read Multipole date when using h5py for example in pyGWAnalysis/Examples/integratemodesffi.py:
t = dataset[:,0] RePsi4 = dataset[:,1] ImPsi4 = dataset[:,2] WF[l][m] = WaveFunction(t, RePsi4, ImPsi4) # WF[l][m].Load("rPsi4_l"+str(l)+"m"+str(m)+".dat")
POWER
Homepage  https://git.ncsa.illinois.edu/elihu/Gravitational_Waveform_Extractor/ 

Authors  Daniel Johnson, E. A. Huerta, Roland Haas 
License  NCSA 
Requirements  Python 2.7, NumPy,h5py 
A simple set of GW analysis tools in python that computes strain from Psi4 using fixedfrequency integration and extrapolates to scrI+. Can be made to read Multipole date when using h5py.
./power.py simulations/J0040_N40
SkyNet
SkyNet is a generalpurpose nuclear reaction network that was specifically designed for rprocess nucleosynthesis calculations, but SkyNet is also applicable to other astrophysical scenarios.
Homepage  https://jonaslippuner.com/research/skynet/ 

Authors  Jonas Lippuner, Luke Roberts 
License  BSD 3Clause License 
Requirements  cmake, hdf5, gsl, boost 
Kuibit
kuibit is a Python library to analyze simulations performed with the Einstein Toolkit largely inspired by Wolfgang Kastaun's PostCactus. kuibit can read simulation data and represent it with highlevel classes. kuibit comes with a number of scripts that can be immediately used (e.g., to make plots, extract gravitational waves).
Partial list of features (for a full list, see documentation):
 Read and organize simulation data. Checkpoints and restarts are handled transparently.
 Work with scalar data as produced by CarpetIOASCII).
 Analyze the multipolar decompositions output by Multipoles .
 Analyze gravitational waves extracted with the NewmanPenrose formalism computing, among the other things, strains, overlaps, energy lost.
 Work with the power spectral densities of known detectors.
 Represent and manipulate time series. Examples of functions available for time series: integrate, derive, resample, to_FrequencySeries (Fourier transform).
 Represent and manipulate frequency series, like Fourier transforms of time series. Inverse Fourier transform is available.
 Manipulate and analyze gravitationalwaves. For example, compute energies, mismatches, or extrapolate waves to infinity.
 Work with 1D, 2D, and 3D grid functions as output by CarpetIOHDF5 or CarpetIOASCII.
 Work with horizon data from as output by QuasiLocalMeasures and AHFinderDirect.
 Handle unit conversion, in particular from geometrized to physical.
 Write commandline scripts.
 Visualize data with matplotlib.
Homepage  https://github.com/Sbozzolo/kuibit 

Authors  Gabriele Bozzola 
License  GPLv3 
Requirements  Python 3.6, packages listed in poetry.lock 
Documentation  Documentation, Tutorials, Examples 
Other Info  Available on PyPI, same design as PostCactus in Wolfgang Kastaun's PyCactus, Unit tests (automatic on commit) 
watpy
The CoRe python package for the analysis of gravitational waves based on scidata, Matlab's WAT and pyGWAnalysis
Requirements
The Python Waveform Analysis Tools are compatible with Python3 (Old versions of watpy were Python2 compatible).
Features
 Classes for multipolar waveform data
 Classes to work with the CoRe database
 Gravitationalwave energy and angular momentum calculation routines
 Psi4toh via FFI or time integral routines
 Waveform alignment and phasing routines
 Waveform interpolation routines
 Waveform's spectra calculation
 Richardson extrapolation
 Wave objects contain already information on merger quantities (time, frequency)
 Unit conversion package
 Compatible file formats: BAM, Cactus (WhiskyTHC / FreeTHC), CoRe database
Homepage  https://git.tpi.unijena.de/core/watpy 

Authors  Andrea Endrizzi, Sebastiano Bernuzzi, and others 
License  unknown 
Requirements  Python 3.X, packages listed on https://git.tpi.unijena.de/core/watpy 
Documentation  examples 
Other Info  Install via pip install git+https://git.tpi.unijena.de/core/watpy
