mdsh5 0.0.1

A higher level python package that uses mdsthin to read MDSPlus data and store it in hdf5 formate for easy caching, viewing, distribution, and analysis.

mdsh5

A higher level python package that uses mdsthin to read MDSPlus data and store it in hdf5 formate for easy caching, viewing, distribution, and analysis.

Usage:

No installation required

You can download the read_mds.py file from mdsh5 directory and use it directly or import it in your python code as per your need. You'll need to install h5py, PyYaml, and mdsthin. For your convinience, a conda environment is provided in this repository to install the required packages in a separate environment. To use:

conda env create -f conda_env.yml
conda activate mdsh5

Installation

If you plan to use this package often, you can install it locally using PyPi.

pip install mdsh5

This will also install a script read_mds in your bin that you can call as:

read_mds

No need to even write python and you can call this script from anywhere in your computer. Note that if you installed this package in a conda environment, the script would go to conda environment's bin directory which is typically present in $HOME/anaconda3/envs/<env_name>/bin and this might not be in your path by default.

Purpose

If you want to run custom analysis on your shot data from the device, it can become tedious to download data using existing tools. To this end, mdsthin now provides an excellent pythonic solution to download MDSPlus data from remote servers.

This package is one level higher data management tool. It uses mdsthin to download data but provides a functionality to provide required shot numbers, tree names, and point names in an organized yaml format and creates a fast transversible data dictionary in HDF5 format. HDF5 is simple self-describing fiole format which is supported on multiple platforms and has well developed libraries for reading and writing in almost all programming languages. The msot important aspect is that when python opens an HDF5 file, it can navigate through the data dictionary and read only the required portion of the data file. Thus it requires much less RAM and even if the accumulated data is in GigaBytes, you can read small particular portions of it very fast.

Additionally, if you use VSCode, I highly recomment installing the H5Web extension which let's you quickly visualize the data stored in the HDF5 files created by this package.

Documentation

Additional documentation would come soon. For now, please refer to the config_examples to get started on how to provide the input configuration. Additionally, use the help flag to print out the help message from read_mds.py:

(mdsh5)% python mdsh5/read_mds.py -h                          
usage: read_mds.py [-h] [-n SHOT_NUMBERS [SHOT_NUMBERS ...]] [-t TREES [TREES ...]] [-p POINT_NAMES [POINT_NAMES ...]] [-s SERVER] [-r RESAMPLE [RESAMPLE ...]]
                   [--rescale RESCALE [RESCALE ...]] [-o OUT_FILENAME] [--reread_data] [-v] [-c CONFIG]

Read MDSplus channel

options:
  -h, --help            show this help message and exit
  -n, --shot_numbers SHOT_NUMBERS [SHOT_NUMBERS ...]
                        Shot number(s)
  -t, --trees TREES [TREES ...]
                        Tree name(s)
  -p, --point_names POINT_NAMES [POINT_NAMES ...]
                        Point name(s)
  -s, --server SERVER   Server address. Default is 203.230.126.231:8005
  -r, --resample RESAMPLE [RESAMPLE ...]
                        Resample signal(s) by providing a list of start, stop, and increment values. For negative value, enclose them withing double quotes and add a space at the
                        beginning.Example: --resample " -0.1" 10.0 0.1
  --rescale RESCALE [RESCALE ...]
                        Rescale time dimension of trees to ensure that all of are in same units. Especially important if resample is used. Provide a rescaling factor to be multiplied
                        by time axis for each tree provides in trees option.Example: --resample " -0.1" 10.0 0.1
  -o, --out_filename OUT_FILENAME
                        Output filename for saving data in file. Default is None. in which case it does not save files.
  --reread_data         Will overwrite on existing data for corresponding data entries in out_file. Default behavior is to skip readingpointnames whose data is present.
  -v, --verbose         Print verbose messages
  -c, --config CONFIG   Configuration file containing shot_numbers, trees, point_names, server, and other settings. If provided, corresponding command line arguments are ignored.

For queries, contanct Anchal Gupta ([e-mail]).

Required ssh configurations

This software does not take care of ssh tunneling often required to reach the "super secure" MDSPlus servers of various tokamaks in the world. Here I provide a simple language solution of what you would need to do:

If the MDSPlus server is only available in a closed of network whose gateway node is gate.xyz.com, add following to your ~/.ssh/config:

Host <MDSPlusServerShortName> <MDSPlusServerFullAddress>
	Hostname <MDSPlusServerFullAddress>
	User <your_username>
	ProxyCommand ssh -q <GatewayNodeAddress> nc %h %p

It would be very useful if you can access the Gateway node without password. For setting that up, do:

Create ssh key pair if you donot have it already

ssh-keygen -t rsa -b 4096 -C "[e-mail]"

Copy the public key to Gateway node

ssh-copy-id remote_username@GatewayNodeAddress -i path_to_creates_ssh_id_file

This step will prompt you for password of the Gateway node. Once this step is completed, you should be able to ssh into the gateway node without need of password using:

ssh remote_username@GatewayNodeAddress

Add gateway to ssh config for ease (Optional)

Host <GatewayShortName> <GatewayNodeAddress>
  Hostname <GatewayNodeAddress>
  IdentityFile <path_to_creates_ssh_id_file>
  User <your_username>
  Port <required_port_if_different_from_22>