Metadata-Version: 2.1
Name: klove
Version: 0.1.0
Summary: Waves on elastic plates
Home-page: https://gitlab.com/benvial/klove
Author: Benjamin Vial
License: GPL-3.0-or-later
Project-URL: Code, https://gitlab.com/benvial/klove
Project-URL: Documentation, https://benvial.gitlab.io/klove
Project-URL: Issues, https://gitlab.com/benvial/klove/issues
Keywords: elastic plates,auto-differentiation,linear algebra
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Utilities
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: scikit-image
Provides-Extra: diff
Requires-Dist: numdiff>=0.0.1; extra == "diff"
Provides-Extra: full
Requires-Dist: klove[diff]; extra == "full"


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# KLOVE

**Numerical modelling of waves on thin elastic plates**

`klove` is a Python package designed to study wave propagation on thin elastic plates based on the 
Kirchhoff–Love theory. The plate can be loaded with elements that will affect the propagation of elastic waves: the aim 
is to find the solution to this problem numerically. Key features of the code are:


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- **Easy to use interface** --- simply define the plate and scatterers (pins, masses, mass-spring or beam resonators).
- **Multiple scattering simulations** --- with plane wave and point load excitation.
- **Far field quantities** --- with plane wave excitation.
- **Diffraction by gratings** --- with calculation of efficiencies.
- **Quasi-normal mode analysis and expansion** --- by solving a nonlinear eigenvalue problem.
- **Calculation of phononic band diagrams** --- with utilities to define the path along the edges of the Brillouin zone.
- **Auto-differentiable** --- allowing for gradient-based optimization of elastic wave propagation.


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## Documentation

See the website with API reference and some examples at [benvial.gitlab.io/klove](https://benvial.gitlab.io/klove).



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## Installation


### From Pypi

Simply run

```bash 
pip install klove
```
If you want more numerical backends (pytorch, autograd and jax), including 
auto-differentiation and GPU acceleration, install the full version:

```bash 
pip install klove[full]
```


### From conda/mamba

For the full installation including GPU/autodiff support

```bash 
mamba install -c pytorch -c nvidia pytorch pytorch-cuda=12.1 jaxlib=*=*cuda* jax 
pip install klove[full]
```

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### From source

Clone the repository

```bash 
git clone https://gitlab.com/benvial/klove.git
cd klove
```

Install the package locally

```bash 
pip install -e .
```

For the full version:

```bash 
pip install -e .[full]
```

### From gitlab

Basic:

```bash 
pip install -e git+https://gitlab.com/benvial/klove.git#egg=klove
```


Full:

```bash 
pip install -e git+https://gitlab.com/benvial/klove.git#egg=klove[full]
```




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