TIGER

TIGER is a Python module for directly accessing Exodus and Nemesis file data as numpy arrays. Examples demonstrate how to generate high quality figures using matplotlib and the TIGER interface.

Querying variables

When reading multiple Exodus files, ExodusReader combines available variable names from each file. The resulting lists are exposed on the multi-file reader via nodal_var_names and elem_var_names. These attributes show all nodal and elemental variables that may be requested with APIs such as get_data_at_time. These APIs also accept an optional block_id to restrict queries to a specific element block. For example::

x, y, z, c = reader.get_data_at_time('c_Cr', time, block_id=1)

This returns coordinates and values only for block 1.

Quick Start

Clone the repository and run the setup script:

git clone https://github.com/chaitanyaBhave26/TIGER.git
cd TIGER
bash setup.sh

Activate the environment (required each time you use TIGER):

source tiger_env/bin/activate

That's it! TIGER is now ready to use.

Installation Details

The setup.sh script:

1. Creates a Python virtual environment (tiger_env/)
2. Installs all required dependencies
3. Installs TIGER in development mode

Manual installation (if you prefer):

python3 -m venv tiger_env
source tiger_env/bin/activate
pip install -r requirements.txt
pip install -e .

Optional dependencies (for video generation):

pip install -r requirements-optional.txt

Context Manager Usage (Recommended)

For proper resource management, use ExodusReader as a context manager:

with ExodusReader(filenames) as reader:
    times = reader.global_times
    x, y, z, c = reader.get_data_at_time('temperature', times[-1])
    # Process data...
# Reader is automatically closed

This ensures the underlying netCDF dataset is properly closed even if errors occur.

Working with Multiple Element Blocks

For meshes with multiple element blocks (e.g., multi-material simulations):

with ExodusReader('mesh.e') as reader:
    # See available blocks
    print(f"Blocks: {list(reader.block_connect.keys())}")

    # Extract data from specific block
    x, y, z, c = reader.get_data_at_time('stress', time, block_id=1)

    # Compare across blocks
    for block_id in reader.block_connect.keys():
        x, y, z, c = reader.get_data_at_time('temperature', time, block_id=block_id)
        # Analyze block-specific data...

The block_id parameter restricts queries to a specific element block. If omitted, data from all blocks is returned.

Running Examples

Example scripts are located in the examples/ directory. Before running:

1. Activate the virtual environment: source tiger_env/bin/activate
2. Create subdirectories for output: mkdir -p examples/{1D,2D,3D}
3. Place your Exodus data files in the appropriate directories
4. Run examples: python examples/1d_plot.py

See examples/README.md for detailed information about each example.

Deactivating the Environment

When done working with TIGER:

deactivate

Alternative Installation Methods

Option A - Conda installation:

If you prefer Conda over venv:

1. Install Conda from the Conda website
2. Create the TIGER environment:

   conda create --name tiger_env "h5py=*=mpi*" "netcdf4=1.6.*=mpi*" matplotlib scipy numpy pytest cmcrameri mpi4py -c conda-forge

3. Activate and install TIGER:

   conda activate tiger_env
   cd TIGER
   pip install -e .

Option B - HPC with module system:

For HPC systems with environment modules:

1. Load required modules:

   module load python
   module load mpi

2. Follow the manual installation steps above