Update README.md
Signed-off-by: Grzegorz Kowal <grzegorz@amuncode.org>
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README.md
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README.md
@ -12,23 +12,26 @@ following features are already implemented:
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* hydrodynamic and magnetohydrodynamic set of equations (HD and MHD),
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* both classical and special relativity cases for the above equations,
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* Cartesian coordinate system,
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* Cartesian coordinate system so far,
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* uniform and adaptive mesh generation and update,
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* 2nd to 4th order time integration using Strong Stability Preserving
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Runge-Kutta methods,
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* 2nd order TVD interpolation with number of limiters and higher order
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reconstructions,
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* a number of time integration methods, from 2nd to 5th order Runge-Kutta
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methods: Strong Stability Preserving and Embedded (with the error control),
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* high order reconstructions: from 2nd to 9th order WENO and MP, both explicit
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and compact methods, the 2nd order TVD interpolation has a number of limiters
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supported,
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* Riemann solvers of Roe- and HLL-types (HLL, HLLC, and HLLD),
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* standard boundary conditions: periodic, open, reflective, hydrostatic, etc.
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* turbulence driving using Alvelius or Ornstein–Uhlenbeck methods,
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* viscous and resistive source terms,
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* support for passive scalars (up to 100),
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* data stored in internal XML+binary or HDF5 format,
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* support for Zstandard, LZ4, and LZMA compression in XML+binary format,
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* Python interface to read snapshots in both formats,
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* support for passive scalars,
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* data stored in an internal XML+binary or the HDF5 format,
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* data integrity of the XML+binary format guaranteed by the XXH64 or XXH3 hashes;
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* support for Zstandard, LZ4, and LZMA compressions in the XML+binary format,
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* support for Deflate, Zstandard, and ZFP compressions in the HDF5 format,
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* easy and consistend Python interface to read snapshots in both formats,
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* MPI parallelization,
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* completely written in Fortran 2008,
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* simple Makefile or CMake for executable building,
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* simple Makefile or CMake for building the code executable,
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* minimum requirements, only Fortran compiler and Python are required to
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prepare, run, and analyze your simulations.
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@ -62,63 +65,58 @@ Requirements
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compiler version 9.0 or newer.
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- [NVIDIA HPC](https://developer.nvidia.com/hpc-sdk) compiler version 21.9.
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Warning: I could not make it run with the included MPI libraries.
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* Optional, but recommended, [OpenMPI](https://www.open-mpi.org/) for parallel
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runs, tested with version 1.8 or newer.
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* Optional support for XML-binary format compression requires:
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* Recommended, although optional, [OpenMPI](https://www.open-mpi.org/) for
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parallel runs, tested with version 1.8 or newer.
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* Optional [CMake](https://cmake.org) version 3.16 or newer, for advanced
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compilation option selection.
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* Optionally, the XML-binary format compression requires:
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[LZ4 library](https://lz4.github.io),
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[Zstandard library](http://facebook.github.io/zstd/), or
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[LZMA library](https://tukaani.org/xz/)
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[XXHASH library](http://www.xxhash.com/).
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* Optional [HDF5 libraries](https://www.hdfgroup.org/solutions/hdf5/), tested
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with version 1.10 or newer. The code now uses the new XML-binary snapshot
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format. However, if you still want to use older HDF5 snapshot format, you
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will need these libraries.
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* Optional [CMake](https://cmake.org) version 3.16 or newer, for managing the
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build process.
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Environment Variables
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=====================
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If you need to use the HDF5 libraries and they are not installed in the default
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location, i.e. in the system directory **/usr**, make sure that the environment
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variable _HDF5DIR_ is set in your **~/.bashrc** (or **~/.cshrc**) and pointing
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to the location where the HDF5 libraries have been installed.
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* Deflate compression is natively supported in HDF5 libraries, however,
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optionally these compression formats are supported through filters:
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[HDF5Plugin-Zstandard](https://github.com/gkowal/HDF5Plugin-Zstandard),
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[H5Z-ZFP](https://github.com/LLNL/H5Z-ZFP).
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Recommended compilation (using CMake)
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=====================================
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1. Clone the AMUN source code:
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- from Bitbucket:
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`git clone https://grzegorz_kowal@bitbucket.org/amunteam/amun-code.git`,
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- from GitLab:
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`git clone https://gitlab.com/gkowal/amun-code.git`
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- from Bitbucket:
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`git clone https://grzegorz_kowal@bitbucket.org/amunteam/amun-code.git`,
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- or unpack the archive downloaded from page
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[Downloads](https://bitbucket.org/amunteam/amun-code/downloads/).
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2. Create a directory for compilation in any location,
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e.g. `mkdir cmake-build && cmake-build`.
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2. Create the build directory, e.g. `mkdir amun-build && cd amun-build`.
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3. Call `ccmake <path to amun-code>`, e.g. `ccmake ..`, and press 'c' once.
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Configure available options. Press 'c' once again, and 'g' to
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generate makefiles. Alternatively, just call `ccmake <path to amun-code>`
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for default options.
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Set available options, if necessary. Press 'c' once again, and 'g' to
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generate makefiles.
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4. Compile the code using `make`. The executable file **amun.x** should be
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created.
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available in a few moments.
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Alternative compilation (using `make.conf`)
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Alternative compilation (using `make`)
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===========================================
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1. Clone the AMUN source code:
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- from Bitbucket:
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`git clone https://grzegorz_kowal@bitbucket.org/amunteam/amun-code.git`,
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- from GitLab:
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`git clone https://gitlab.com/gkowal/amun-code.git`
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- from Bitbucket:
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`git clone https://grzegorz_kowal@bitbucket.org/amunteam/amun-code.git`,
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- or unpack the archive downloaded from page
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[Downloads](https://bitbucket.org/amunteam/amun-code/downloads/).
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2. Go to directory **build/hosts/** and copy file **default** to a new file named
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exactly as your host name, i.e. `cp default $HOSTNAME`.
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2. Go to directory **build/hosts/** and copy file **default** to a new file
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named exactly as your host name, i.e. `cp default $HOSTNAME`.
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3. Customize your compiler and compilation options in your new host file.
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4. Go up to directory **build/** and copy file **make.default** to **make.config**.
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4. Go up to the directory **build/** and copy file **make.default** to
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**make.config**.
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5. Customize compilation time options in **make.config**.
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6. Compile sources by typing `make` in directory **build/**. The executable file
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**amun.x** should be created there.
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@ -147,23 +145,24 @@ where N is the number of processors to use.
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Reading data
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============
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By default, the code uses new XML+binary snapshot data format. It can also be
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forced by setting parameter **snapshot_format** to **xml**.
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By default, the code uses the new XML+binary snapshot data format. Parameter
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**snapshot_format** set to either **xml** or **h5** controls which file format
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is used.
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In order to read produced data in this format, you will need to install the
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provided Python module. Simply change to **python/** directory and run
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`python setup.py install --user`
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In order to read the data produced in this format, you will need to install the
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Python module AmunPy included in subdirectory **python/amunpy**. Simply go to
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this directory and run
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`python ./setup.py install --user`
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to install the module in your home directory.
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Import the module in your python script using
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`from amunpy import *`,
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and then initiate the interface using
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and then initiate the interface to the XML+binary snapshots using
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`snapshot = AmunXML(<path to the snapshot directory>)`
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and read desired variable using
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or to the HDF5 files using
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`snapshot = AmunH5(<path to any HDF5 snapshot file>)`
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and read desired variables using function
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`var = snapshot.dataset(<variable>)`.
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The function **dataset()** returns rescaled uniform mesh variable as NumPy
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array.
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If you want to read data from HDF5 snapshot, just use
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`var = amun_dataset(<snapshot HDF5 file>, <variable>)`.
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The function **dataset()** returns the requested variable mapped on the uniform
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mesh as a NumPy array.
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