Readme and Release notes update

.gitignore

@@ -41,7 +41,6 @@ coverage.xml
 
 # documentation build artifacts
 
-docs/*.md
 docs/api
 site/
 mkdocs.yml

README.md

@@ -1,21 +1,107 @@
-# arrayfire-py
-
-Arrayfire python wrapper
-
-## Coverage
-
-- [x] Computer Vision
-- [] Events
-- [x] Functions to Create and Modify Arrays
-- [x] Functions to Work with Internal Array Layout
-- [x] Image Processing
-  - [x] Features
-- [x] Input and Output Functions
-- [x] Interface Functions
-- [x] Linear Algebra
-- [x] Machine Learning
-- [x] Mathematical Functions
-- [x] Signal Processing
-- [x] Statistics
-- [x] Unified API Functions
-- [x] Vector Algorithms
+# arrayfire-py (WIP)
+<p align="center"><a href="http://arrayfire.com/"><img src="http://arrayfire.com/logos/arrayfire_logo_whitebkgnd.png" width="800"></a></p>
+
+[ArrayFire](https://github.com/arrayfire/arrayfire) is a high performance library for parallel computing with an easy-to-use API. It enables users to write scientific computing code that is portable across CUDA, OpenCL and CPU devices.  
+
+This project is a **work in progress**. It is meant to provide a numpy-like Python interface for the ArrayFire C library, i.e, it provides array functionality, math operations, printing, etc. This is the front-end python library for using ArrayFire. It is currently supported on Python 3.10+.
+
+Here is an example of the library at work:
+```py
+# Set backend and device (optional: 'cuda', 'opencl', 'oneapi', 'cpu')
+af.setBackend(af.BackendType.cuda)
+af.setDevice(0)
+
+# Create two 5x5 arrays on the GPU
+a = af.randu((5, 5))
+b = af.randu((5, 5))
+
+# Perform element-wise addition and matrix multiplication
+c = a + b
+d = af.matmul(a, b)
+
+# Print the result
+print(c, "Element-wise Sum")
+print(d, "Matrix Product")
+```
+
+# Installing
+
+**Requirement Details**
+This project is separated into 3 different parts:
+```
+arrayfire-py -> arrayfire-binary-python-wrapper -> ArrayFire C Libraries
+```
+This means that arrayfire with python each of these parts is needed:
+- [`arrayfire-py`](https://github.com/arrayfire/arrayfire-py) is the `thin` wrapper that provides the numpy-like interface to execute math and array operations. *** This is the intended User Interface ***
+- [`arrayfire-binary-python-wrapper`](https://github.com/arrayfire/arrayfire-binary-python-wrapper) is the `binary` wrapper that provides rough direct access to the functions in the C library.
+- [`ArrayFire C Libraries`](https://github.com/arrayfire/arrayfire) are the binaries obtained from compiling the [ArrayFire C/C++ Project](https://github.com/arrayfire/arrayfire)
+
+**Install the last stable version of python wrapper:**
+```sh
+pip install arrayfire_binary_python_wrapper-0.8.0+af3.10.0-py3-none-linux_x86_64.whl # install required binary wrapper with the 3.10 ArrayFire binaries included 
+pip install arrayfire-py # install arrayfire python interface library
+```
+
+**Install a pre-built wheel:**
+```
+pip install arrayfire-py -f https://repo.arrayfire.com/python/wheels/arrayfire-py/0.1.0
+```
+
+# Building
+Building this interface is straight forward using [scikit-build-core](https://github.com/scikit-build/scikit-build-core):
+```
+python -m pip install -r dev-requirements.txt
+python -m build --wheel
+```
+
+**Note: Building this project does not require the arrayfire-binary-python-wrapper package; however, the binary wrapper is needed to run any projects with it**
+
+# Running Tests
+
+Tests are located in folder [tests](tests).
+
+To run the tests, use:
+```bash
+python -m pytest tests/
+```
+
+# Contributing
+
+If you are interested in using ArrayFire through python, we would appreciate any feedback and contributions.
+
+The community of ArrayFire developers invites you to build with us if you are
+interested and able to write top-performing tensor functions. Together we can
+fulfill [The ArrayFire
+Mission](https://github.com/arrayfire/arrayfire/wiki/The-ArrayFire-Mission-Statement)
+for fast scientific computing for all.
+
+Contributions of any kind are welcome! Please refer to [the
+wiki](https://github.com/arrayfire/arrayfire/wiki) and our [Code of
+Conduct](33) to learn more about how you can get involved with the ArrayFire
+Community through
+[Sponsorship](https://github.com/arrayfire/arrayfire/wiki/Sponsorship),
+[Developer
+Commits](https://github.com/arrayfire/arrayfire/wiki/Contributing-Code-to-ArrayFire),
+or [Governance](https://github.com/arrayfire/arrayfire/wiki/Governance).
+
+# Citations and Acknowledgements
+
+If you redistribute ArrayFire, please follow the terms established in [the
+license](LICENSE).
+
+ArrayFire development is funded by AccelerEyes LLC and several third parties,
+please see the list of [acknowledgements](ACKNOWLEDGEMENTS.md) for an
+expression of our gratitude.
+
+# Support and Contact Info
+
+* [Slack Chat](https://join.slack.com/t/arrayfire-org/shared_invite/MjI4MjIzMDMzMTczLTE1MDI5ODg4NzYtN2QwNGE3ODA5OQ)
+* [Google Groups](https://groups.google.com/forum/#!forum/arrayfire-users)
+* ArrayFire Services:  [Consulting](http://arrayfire.com/consulting)  |  [Support](http://arrayfire.com/download)   |  [Training](http://arrayfire.com/training)
+
+# Trademark Policy
+
+The literal mark "ArrayFire" and ArrayFire logos are trademarks of AccelerEyes
+LLC (dba ArrayFire). If you wish to use either of these marks in your own
+project, please consult [ArrayFire's Trademark
+Policy](http://arrayfire.com/trademark-policy/)

benchmarks/README.md

@@ -0,0 +1,8 @@
+# Benchmarks Results
+Here are some graphs comparing ArrayFire Python against other packages for some common operations:
+
+<p align="center"><img src="img/comparison_afcuda_t4.png" width="800"></a></p>
+<p align="center"><img src="img/comparison_afopencl_t4.png" width="800"></a></p>
+<p align="center"><img src="img/comparison_afoneapi_b580.png" width="800"></a></p>
+
+These graphs were generated with this benchmark code using the ArrayFire C Libraries v3.10

docs/release_notes.md

@@ -0,0 +1,21 @@
+Release Notes {#releasenotes}
+==============
+
+v0.1.0
+======
+Welcome to the ArrayFire Python Bindings! These are the currently supported features:
+
+- Support for all backends (cpu, opencl, oneapi, cuda)
+- Computer Vision
+- Functions to Create and Modify Arrays
+- Functions to Work with Internal Array Layout
+- Image Processing with Features
+- Input and Output Functions
+- Interface Functions
+- Linear Algebra
+- Machine Learning
+- Mathematical Functions
+- Signal Processing
+- Statistics
+- Unified API Functions
+- Vector Algorithms

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta"
 [project]
 name = "arrayfire"
 version = "0.1.0"
-dependencies = ["arrayfire-binary-python-wrapper == 0.7.0"]
+dependencies = ["arrayfire-binary-python-wrapper >= 0.7.0"]
 requires-python = ">=3.10"
 description = "ArrayFire Python"
 readme = "README.md"

requirements.txt

@@ -1 +1 @@
-arrayfire-binary-python-wrapper==0.7.0+af3.9.0
+arrayfire-binary-python-wrapper>=0.7.0+af3.9.0