Sunsetting.

README.md

@@ -1,9 +1,10 @@
-
 # heman
 
-[![Build Status](https://travis-ci.org/prideout/heman.svg?branch=master)](https://travis-ci.org/prideout/heman) [![Documentation](https://readthedocs.org/projects/heman/badge/?version=latest)](http://heman.readthedocs.org/en/latest/)
-
-This is a tiny MIT-licensed C library of image utilities for dealing with **he**ight **ma**ps, **n**ormal maps, distance fields, and the like.  It has a very low-level API, where an "image" is simply a flat array of floats.  It's pretty fast too, since it's parallelized with OpenMP.
+This toy project is a tiny MIT-licensed C library of image utilities for dealing with **he**ight
+**ma**ps, **n**ormal maps, distance fields, and the like.  It has a very low-level API, where an
+"image" is simply a flat array of floats.  It's pretty fast too, since it's parallelized with
+OpenMP. There are no dependencies and [only one header
+file](https://github.com/prideout/heman/blob/master/include/heman.h).
 
 ![](https://github.com/prideout/heman/blob/master/docs/_static/islands.png)
 
@@ -20,14 +21,12 @@ This is a tiny MIT-licensed C library of image utilities for dealing with **he**
 
 Heman implements some really nice 21st-century algorithms:
 
-- Ambient occlusion is generated using Sean Barrett's efficient method that makes 16 sweeps over the height field.
-- Distance field computation uses the beautiful algorithm from _Distance Transforms of Sampled Functions_ (Felzenszwalb and Huttenlocher).
-- Density field samples are generated using Robert Bridson's _Fast Poisson Disk Sampling in Arbitrary Dimensions_.
-
-### Python and JavaScript too!
-Unit tests are performed using the Python bindings, which live in [prideout/heman-python](https://github.com/prideout/heman-python).
-
-Heman also provides emscripten bindings for its API.  The JavaScript demo is [here](http://prideout.github.io/heman).
+- Ambient occlusion is generated using Sean Barrett's efficient method that makes 16 sweeps over the
+  height field.
+- Distance field computation uses the beautiful algorithm from _Distance Transforms of Sampled
+  Functions_ (Felzenszwalb and Huttenlocher).
+- Density field samples are generated using Robert Bridson's _Fast Poisson Disk Sampling in
+  Arbitrary Dimensions_.
 
 ## Example
 
@@ -51,65 +50,5 @@ heman_image* albedo = heman_color_apply_gradient(elevation, -0.5, 0.5, grad);
 heman_image* final = heman_lighting_apply(elevation, albedo, ...);
 ```
 
-For the unabridged version, see `test_lighting` in [test/test_heman.c](https://github.com/prideout/heman/blob/master/test/test_heman.c).
-
-## Documentation
-
-The latest Sphinx-generated docs are hosted [here](http://heman.readthedocs.org/en/latest/).  You can also take a look at heman's one and only [header file](https://github.com/prideout/heman/blob/master/include/heman.h).
-
-## Building
-
-Heman has no dependencies, so it should be easy just to incorporate the code directly into your project.
-
-For building a shared library in OS X, you can do this:
-```
-brew install scons
-scons lib
-```
-
-Note that this will not use OpenMP or build any tests.
-
-Linux is required for OpenMP and tests.  If you are not using a Linux machine but you want OpenMP support, take a look at the provided [Dockerfile](https://github.com/prideout/heman/blob/master/Dockerfile).
-
-There's a script in the repo, [env.sh](https://github.com/prideout/heman/blob/master/env.sh), that makes using Docker easy.  It calls `docker-machine` and builds a container.  Here's how to use it:
-
-```bash
-brew install docker-machine
-. env.sh
-# Lots of stuff spews out as it builds the container...
-heman-bash
-# You're now inside the VM -- press enter twice for the prompt.
-scons && build/test_heman
-# You can now look at the generated images:
-ls build/*.png
-```
-
-## Roadmap
-
-Here are some to-be-done items:
-- Provide "Exponentially Distributed Noise", in addition to Simplex.
-- Flesh out the [Python Bindings](https://github.com/prideout/heman-python) and provide docstrings.
-- Implement a contour extractor:
-   - `heman_ops_extract_contour(image, threshold, thickness)`
-   - this just does a Sobel operator, that's all
-- More distance field stuff.
-  - Allow non-monochrome source images.
-  - Allow computation of unsigned, squared distance.
-  - [Spherical distance](http://experilous.com/1/blog/post/generating-spherical-distance-fields-from-polygons).
-- Smarter Mesh Output
-  - Create a hull from poisson samples
-  - Sobel + (Step => Sobel) => Density Field => Poisson Samples
-  - Do not use marching squares!
-  - Two meshes: overwater and underwater
-- Provide gamma decode and encode functions.
-- More noise routines!
-    - Bridson's Curl noise (and a routine that performs advection?)
-    - Worley noise (useful for billows as seen in _Real-time Volumetric Cloudscapes of Horizon_)
-    - Analytic noise normals
-    - Wavelet Noise
-- **heman_image_sample** doesn't do any interpolation.  Maybe it should at least do a 2x2 box filter.
-- Provide functionality from _Scalable Height-Field Self-Shadowing_
-- If we need more string handling, we can integrate [SDS](https://github.com/antirez/sds).
-- Integrate aaOcean, or some other implementation of Tessendorf waves.
-- If we need to read JSON, we might use [this](https://github.com/sheredom/json.h) or [this](https://github.com/mitsuhiko/johanson).
-- There are cool data structures in http://concurrencykit.org/
+For the unabridged version, see `test_lighting` in
+[test/test_heman.c](https://github.com/prideout/heman/blob/master/test/test_heman.c).