em-app 0.2.7

A package for Electromagnetic applications using MTFLibrary.

em-simulation-platform

EM simulation tools for electromagnetic field analysis, visualization, and benchmarking.

Features

• Modular solvers for EM field calculations (Python, C, and Optimized C++ backends)
• Source modeling (dipoles, wires, loops/RingCoil, solenoids)
• Advanced plotting and visualization
• Demo scripts for validation and exploration
• Benchmarking utilities
• Extensible architecture for research and teaching

Installation

This project uses pyproject.toml to manage dependencies. For development, it is recommended to install the package in "editable" mode along with the development extras.

# Clone the repository
git clone https://github.com/shashi-manikonda/em-simulation-platform.git
cd em-simulation-platform

# (Recommended) Create a virtual environment
python3 -m venv .venv
source .venv/bin/activate

# Install the package in editable mode with all development dependencies
pip install -e .[dev,benchmark]

The [dev] extra includes dependencies for running tests and building the documentation. The [benchmark] extra includes dependencies for running the benchmark scripts.

Usage

Run all demos

python scripts/run_all_demos.py

Run a specific demo

To run a specific demo, you can execute the script directly. For notebooks, you can use a tool like jupytext to run it as a script:

jupytext --execute demos/em/01_validation_demo.ipynb

Run tests

pytest

Building the Documentation

This project uses Sphinx to generate API documentation from the source code. The necessary dependencies are included in the [dev] extra.

Build Script

A helper script is provided to simplify the build process. To build the documentation, run the following command from the project root:

./docs/build_docs.sh

The script will clean the previous build and generate the HTML documentation in the docs/_build/html directory.

Viewing the Documentation

To view the documentation, open the docs/_build/html/index.html file in your web browser.

Example: Calculate and Plot the Magnetic Field of a Ring Coil

This example demonstrates how to define a current source, calculate its magnetic field on a grid, and visualize the results.

import numpy as np
import matplotlib.pyplot as plt
from em_app.sources import RingCoil
from em_app.solvers import calculate_b_field, Backend
from mtflib import mtf

# Initialize the MTF library (Optional - defaults to Order 4, Dim 3 if omitted)
# mtf.initialize_mtf(max_order=1, max_dimension=4)

# --- 1. Setup the Coil Geometry ---
coil = RingCoil(
    current=1.0,
    radius=0.5,
    num_segments=20,
    center_point=np.array([0, 0, 0]),
    axis_direction=np.array([0, 0, 1]),
)

# --- 2. Define the Field Points for Calculation ---
grid_size = 1.0
num_points = 15
x_points = np.linspace(-grid_size, grid_size, num_points)
z_points = np.linspace(-grid_size, grid_size, num_points)
X, Z = np.meshgrid(x_points, z_points)
field_points = np.vstack([X.ravel(), np.zeros_like(X.ravel()), Z.ravel()]).T

# --- 3. Calculate the Magnetic Field ---
# --- 3. Calculate the Magnetic Field ---
# You can specify the backend explicitly using the Backend Enum
b_field = calculate_b_field(coil, field_points, backend=Backend.PYTHON)
b_vectors = np.array([b.to_numpy_array() for b in b_field._vectors_mtf])

# --- 4. Plot the Results ---
fig = plt.figure(figsize=(8, 8))
ax = fig.add_subplot(111, projection="3d")

# Plot the coil geometry
coil.plot(ax, color="b", wire_thickness=0.02)

# Plot the magnetic field vectors
ax.quiver(
    field_points[:, 0],
    field_points[:, 1],
    field_points[:, 2],
    b_vectors[:, 0],
    b_vectors[:, 1],
    b_vectors[:, 2],
    length=0.2,
    normalize=True,
    color="gray",
)

# --- 5. Customize and Show the Plot ---
ax.set_title("Magnetic Field of a Ring Coil")
ax.set_xlabel("X (m)")
ax.set_ylabel("Y (m)")
ax.set_zlabel("Z (m)")
ax.view_init(elev=20.0, azim=-60)
plt.show()

Live Demos

For more detailed examples, see the demo scripts in the demos/em directory. These scripts cover topics such as solver validation, dipole approximation, and advanced plotting.

You can run all demos at once using the following command:

python scripts/run_all_demos.py

This will generate output files and plots in the runoutput directory.

Project Structure

• src/em_app/ - Core library modules
• demos/em/ - Demo scripts
• benchmarks/ - Performance and accuracy benchmarks
• tests/ - Unit tests

License

MIT