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README: Add brief info how to read data.

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Signed-off-by: Grzegorz Kowal <grzegorz@amuncode.org>
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Grzegorz Kowal 2020-05-01 15:34:33 -03:00
parent 775537cecf
commit 62b835ccf8
1 changed files with 30 additions and 5 deletions
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README.md
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@ -60,17 +60,17 @@ Requirements
runs, tested with version 1.8 or newer.
* Optional [HDF5 libraries](https://www.hdfgroup.org/solutions/hdf5/), tested
with version 1.10 or newer. The code now uses the new XML-binary snapshot
format. However, if you still wants to use older HDF5 snapshot format, you
format. However, if you still want to use older HDF5 snapshot format, you
will need these libraries.
Environment Variables
=====================
If the HDF5 libraries are not installed in the default location, i.e. in the
system directory **/usr**, make sure that the environment variable _HDF5DIR_ is
set in your **~/.bashrc** (or **~/.cshrc**) and pointing to the location where
the HDF5 libraries have been installed.
If you need to use the HDF5 libraries and they are not installed in the default
location, i.e. in the system directory **/usr**, make sure that the environment
variable _HDF5DIR_ is set in your **~/.bashrc** (or **~/.cshrc**) and pointing
to the location where the HDF5 libraries have been installed.
Compilation
@ -109,3 +109,28 @@ In order to run parallel version (after compiling the code with MPI support),
type in your terminal:
`mpirun -n N ./amun.x -i ./params.in`,
where N is the number of processors to use.
Reading data
============
By default, the code uses new XML+binary snapshot data format. It can also be
forced by setting parameter **snapshot_format** to **xml**.
In order to read produced data in this format, you will need to install the
provided Python module. Simply change to **python/** directory and run
`python setup.py install --user`
to install the module in your home directory.
Import the module in your python script using
`from amunpy import *`,
and then initiate the interface using
`snapshot = AmunXML(<path to the snapshot directory>)`
and read desired variable using
`var = snapshot.dataset(<variable>)`.
The function **dataset()** returns rescaled uniform mesh variable as NumPy
array.
If you want to read data from HDF5 snapshot, just use
`var = amun_dataset(<snapshot HDF5 file>, <variable>)`.