Pythonic wrappers for the IMAS Access Layer
IMASPy is (yet another) pure-python library to handle arbitrarily nested data structures. IMASPy is designed for, but not necessarily bound to, interacting with Interface Data Structures (IDSs) as defined by the Integrated Modelling & Analysis Suite (IMAS) Data Model.
- An easy-to-install and easy-to-get started package by
- Not requiring an IMAS installation
- Not strictly requiring matching a Data Dictionary (DD) version
- An pythonic alternative to the IMAS Python High Level Interface (HLI)
- Checking of correctness on assign time, instead of database write time
- Dynamically created in-memory pre-filled data trees from DD XML specifications
A word of caution
Clone the repository on your local machine. To set up SSH keys for GitLab, look here: https://docs.gitlab.com/ee/ssh/
git clone firstname.lastname@example.org:klimex/imaspy.git # Using SSH keys git clone https://gitlab.com/klimex/imaspy.git # Using username/password
Install IMASPy in developer mode with all the optional components it can find:
cd imaspy pip install --user -e .[all]
For now, let's assume you have a Data Dictionary specification available, and managed to compile the AL.
# Initialize an empty IDS import imaspy as imas idsdef_dir = <path to IDSDef.xml> idsdef = os.path.join(idsdef_dir, 'IDSDef.xml') shot = 1234 run_in = 0 imas_entry = imas.ids(shot, run_in, xml_path=idsdef, verbosity=2)
We end up with a
IDSRoot instance that is pre-filled with all defaults and
data structures defined in the given DD XML. We could've not given
to create an empty
IDSRoot. No interaction with any LL-AL has happened yet!
Create a PulseFile. This creates an empty PulseFile with the specified backend. This will overwrite pulsefiles with the same path. This does need an access layer, IMASPy does not provide one out of the box currently.
from imas_entry._libs.imasdef import * input_user_or_path = <path to pulsefiles, for example your username> input_database = <database, for example 'iter' > imas_entry.create_env_backend(input_user_or_path, input_database, '3', MDSPLUS_BACKEND)
Now that the pulse file exists, put some data in our Python structure:
ids = imas_entry.equilibrium ids.ids_properties.homogeneous_time = 'special' #Whoops! This crashes, wrong type! ids.ids_properties.homogeneous_time = IDS_TIME_MODE_HETEROGENEOUS # This field needs to be filled for all valid IDSs ids.time = [0.1, 0.2, 0.3] ids.time += 2 # Let's offset this by 2
No database interaction has happened yet. We need to explicitly send it to the MDSPLUS pulsefile:
ids.put() # This removes the pulsefile, and rebuilds it with our in-memory structure!
And now we can interact with the regular IMAS tools, for example to plot the structures with IMASViz.
IMASPy is a standalone python package with optional dependencies. All needed
python packages can be found in
requirements.txt, and should all be publicly
available. A simple
pip install should take care of everything.
Being IMAS DD compatible
To check IMAS DD compatible, one needs the IDS definition XML file. This file
can usually be found at
$IMAS_PREFIX/include/IDSDef.xml on your IMAS-enabled
system. Otherwise, they can be build from source from the
ITER IMAS Core Data Dictionary repository.
Interacting with IMAS AL
Interaction with the IMAS AL is provided by Cython and Python wrappers provided
by the Python High Level Interface. As Cython code, it needs to be compiled on
your local system. First make sure you can access the
ITER IMAS Access Layer repository
A copy of this repository will be cloned into
src during build.
Get the prerequisites:
pip install numpy cython gitpython
Install in verbose mode. After installing, you should have a
directory in your root. If not, something went wrong. Be sure to browse
the verbose log or open a ticket.
pip install --user -e .[all] -v
Where does IMASPy live in IMAS ecosystem?
IMASPy tries to fill a slightly different niche than existing tools. It aims to be an alternative to Python HLI instead of a wrapper. It tries to be dynamic instead of pre-generated. Is hopes to be extendable instead of wrappable.
A small, biased, and wildly incomplete of some common IMAS tools, and where they live with respect to IMASPy.
classDiagram MDSPLUS_DATABASE .. LL_AL : puts MDSPLUS_DATABASE .. LL_AL : gets MDSPLUS_DATABASE .. LL_HDC : puts MDSPLUS_DATABASE .. LL_HDC : gets IMAS DD <.. PythonHLI: build dep IMAS DD <-- IMASPy: runtime dep LL_HDC <-- HDC_python_bindings : calls LL_AL <-- Cython_HLI : calls Python_helpers <-- IMASPy: calls HDC_python_bindings <.. IMASPy: Could call Cython_HLI <-- Python_helpers : calls Python_helpers <-- Python HLI: calls IMASDD <.. IMASviz_codegen: build dep IMASviz_codegen <.. IMASviz: build dep PythonHLI <-- OMAS: calls OMAS <-- OMFIT: calls OMFIT <-- IMASgo : calls PythonHLI <-- pyAL: calls PythonHLI <-- JINTRAC_WORKFLOWS : calls pyAL <-- HnCD_WORKFLOWS : calls PythonHLI <-- HnCD_WORKFLOWS : calls PythonHLI <-- IMASviz: calls
This project is licensed under the MIT License - see the LICENSE file for details
Inspired and bootstrapped by existing tools, notably the IMAS Python HLI, IMAS Python workflows, and OMAS.
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