Metadata-Version: 2.1
Name: angler
Version: 0.0.14
Summary: Adjoint Nonlinear Gradients
Home-page: https://github.com/fancompute/angler
Author: Tyler Hughes, Momchil Minkov, Ian Williamson
Author-email: tylerwhughes91@gmail.com
License: UNKNOWN
Description: <link rel="icon" href="/img/favicon.png" type="image/x-icon" />
        <img src="/img/anglerlogos/rainbow.png" title="Angler" alt="Angler">
        
        # angler
        
        `angler` (named for '**a**djoint **n**onlinear **g**radients') is a package for simulating and optimizing optical structures.
        
        It provides a finite-difference frequency-domain (FDFD) solver for simulating for linear and nonlinear devices in the frequency domain.
        
        It also provides an easy to use package for adjoint-based inverse design and optimization of linear and nonlinear devices.  For example, you can inverse design optical switches to transport power to different ports for different input powers:
        
        <img src="/img/Tport.gif" title="Fields" alt="Fields">
        
        `angler` is released as part of a paper `Adjoint method and inverse design for nonlinear optical devices`, which can be viewed [here](https://arxiv.org/abs/1811.01255).
        
        ## Installation
        
        One can install the most stable version of `angler` and all of its dependencies (apart from MKL) using
        
        	pip install angler
        	
        Alternatively, to use the most current version
        
        	git clone https://github.com/fancompute/angler.git
        	pip install -e angler
        
        And then this directory can be added to path to import angler, i.e.
        
        	import sys
        	sys.path.append('path/to/angler')
        
        
        ## Make angler faster
        
        The most computationally expensive operation in `angler` is the sparse linear system solve.  This is done with [`scipy.sparse.linalg.spsolve()`](https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.sparse.linalg.spsolve.html) by default.  If MKL is installed, `angler` instead uses this with a python wrapper [`pyMKL`](https://github.com/dwfmarchant/pyMKL), which makes things significantly faster, depending on the problem.  The best way to install MKL, if using anaconda, is
        
        	conda install MKL
        	
        (pyMKL does not work when MKL is pip installed.)
        
        ## Examples / Quickstart
        
        There are several jupyter notebook examples in the `Notebooks/` directory.
        
        For a good introduction, try:
        
        	Notebooks/Splitter.ipynb
        
        For more specific applications:
        
        #### Electromagnetic simulations
        
        For modeling linear devices with our FDFD solver (no optimization), see
        
        	Notebooks/Linear_system.ipynb
        
        For modeling nonlinear devices with FDFD (no optimization), see 
        
        	Notebooks/Nonlinear_system.ipynb
        
        #### Inverse design & optimization
        
        For examples of optimizing linear devices, see 
        
        	Notebooks/Splitter.ipynb
        	Notebooks/Accelerator.ipynb
        
        For examples of optimizing nonlinear devices, see
        
        	Notebooks/2_port.ipynb
        	Notebooks/3_port.ipynb
        	Notebooks/T_port.ipynb
        
        ## Package Structure
        
        `angler` provides two main classes, `Simulation` and `Optimization`, which perform most of the functionality.
        
        Generally, `Simulation` objects are used to perform FDFD simulations, and `Optimization` classes run inverse design and optimization algorithms over `Simulation`s.  To learn more about how `angler` works and how to use it, please take a look at [angler/README.md](angler/README.md) for a more detailed explanation.
        
        ## Tests
        
        To run all tests:
        
        	python -m unittest discover tests
        
        Or to run individually:
        	
        	python tests/individual_test.py
        
        ## Contributing
        
        `angler` is under development and we welcome suggestions, pull-requests, feature-requests, etc.
        
        If you contribute a new feature, please also write a few tests and document your changes in [angler/README.md](angler/README.md) or the wiki.
        
        ## Authors
        
        `angler` was written by Tyler Hughes, Momchil Minkov, and Ian Williamson.
        
        ## Citing
        
        If you use `angler`, please cite us using
        
        	@misc{hughes2018adjoint,
        	Author = {Tyler W. Hughes and Momchil Minkov and Ian A. D. Williamson and Shanhui Fan},
        	Title = {Adjoint method and inverse design for nonlinear nanophotonic devices},
        	Year = {2018},
        	Eprint = {arXiv:1811.01255},
        	}
        
        ## License
        
        This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details. Copyright 2018 Tyler Hughes.
        
        ## Acknowledgments
        
        * our logo was made by [Nadine Gilmer](http://nadinegilmer.com/)
        * RIP Ian's contributions before the code merge
        * We made use of a lot of code snippets (and advice) from [Jerry Shi](https://yujerryshi.github.io/index.html)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
