From c41ab8d299561b729f2307e0ab54fc8636f4d18b Mon Sep 17 00:00:00 2001
From: Fabian Joswig <fabian.joswig@ed.ac.uk>
Date: Sun, 7 Nov 2021 21:03:08 +0000
Subject: [PATCH] README updated

---
 README.md            | 42 +++++++-----------------------------------
 pyerrors/__init__.py |  6 ++++++
 2 files changed, 13 insertions(+), 35 deletions(-)

diff --git a/README.md b/README.md
index 6e53ea35..abf327a3 100644
--- a/README.md
+++ b/README.md
@@ -1,17 +1,10 @@
 [![flake8](https://github.com/fjosw/pyerrors/actions/workflows/flake8.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/flake8.yml) [![pytest](https://github.com/fjosw/pyerrors/actions/workflows/pytest.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/pytest.yml) [![](https://img.shields.io/badge/python-3.6+-blue.svg)](https://www.python.org/downloads/)
 # pyerrors
 `pyerrors` is a python package for error computation and propagation of Markov chain Monte Carlo data.
-It is based on the **gamma method** [arXiv:hep-lat/0306017](https://arxiv.org/abs/hep-lat/0306017). Some of its features are:
-* **automatic differentiation** as suggested in [arXiv:1809.01289](https://arxiv.org/abs/1809.01289) (partly based on the [autograd](https://github.com/HIPS/autograd) package)
-* **treatment of slow modes** in the simulation as suggested in [arXiv:1009.5228](https://arxiv.org/abs/1009.5228)
-* coherent **error propagation** for data from **different Markov chains**
-* **non-linear fits with x- and y-errors** and exact linear error propagation based on automatic differentiation as introduced in [arXiv:1809.01289]
-* **real and complex matrix operations** and their error propagation based on automatic differentiation (cholesky decomposition, calculation of eigenvalues and eigenvectors, singular value decomposition...)
 
-There exist similar implementations of gamma method error analysis suites in
-- [Fortran](https://gitlab.ift.uam-csic.es/alberto/aderrors)
-- [Julia](https://gitlab.ift.uam-csic.es/alberto/aderrors.jl)
-- [Python 3](https://github.com/mbruno46/pyobs)
+- **Documentation:** https://fjosw.github.io/pyerrors/pyerrors.html
+- **Examples**: https://github.com/fjosw/pyerrors/tree/develop/examples
+- **Contributing:** https://github.com/fjosw/pyerrors/blob/develop/CONTRIBUTING.md
 
 ## Installation
 To install the most recent release of `pyerrors` run
@@ -23,31 +16,10 @@ to install the current `develop` version run
 pip install git+https://github.com/fjosw/pyerrors.git@develop
 ```
 
-## Usage
-The basic objects of a pyerrors analysis are instances of the class `Obs`. They can be initialized with an array of Monte Carlo data (e.g. `samples1`) and a name for the given ensemble (e.g. `'ensemble1'`). The `gamma_method` can then be used to compute the statistical error, taking into account autocorrelations. The `print` method  outputs a human readable result.
-```python
-import pyerrors as pe
-
-obs1 = pe.Obs([samples1], ['ensemble1'])
-obs1.gamma_method()
-obs1.print()
-```
-Often one is interested in secondary observables which can be arbitrary functions of primary observables. `pyerrors` overloads most basic math operations and `numpy` functions such that the user can work with `Obs` objects as if they were floats
-```python
-import numpy as np
-
-obs3 = 12.0 / obs1 ** 2 - np.exp(-1.0 / obs2)
-obs3.gamma_method()
-obs3.print()
-```
-
-More detailed examples can be found in  the `examples` folder:
-
-* [01_basic_example](examples/01_basic_example.ipynb)
-* [02_correlators](examples/02_correlators.ipynb)
-* [03_pcac_example](examples/03_pcac_example.ipynb)
-* [04_fit_example](examples/04_fit_example.ipynb)
-* [05_matrix_operations](examples/05_matrix_operations.ipynb)
+There exist similar implementations of gamma method error analysis suites in
+- [Fortran](https://gitlab.ift.uam-csic.es/alberto/aderrors)
+- [Julia](https://gitlab.ift.uam-csic.es/alberto/aderrors.jl)
+- [Python 3](https://github.com/mbruno46/pyobs)
 
 ## License
 [MIT](https://choosealicense.com/licenses/mit/)
diff --git a/pyerrors/__init__.py b/pyerrors/__init__.py
index dc02fd04..b8f3d149 100644
--- a/pyerrors/__init__.py
+++ b/pyerrors/__init__.py
@@ -1,6 +1,12 @@
 r'''
 # What is pyerrors?
 `pyerrors` is a python package for error computation and propagation of Markov chain Monte Carlo data.
+It is based on the **gamma method** [arXiv:hep-lat/0306017](https://arxiv.org/abs/hep-lat/0306017). Some of its features are:
+- **automatic differentiation** as suggested in [arXiv:1809.01289](https://arxiv.org/abs/1809.01289) (partly based on the [autograd](https://github.com/HIPS/autograd) package)
+- **treatment of slow modes** in the simulation as suggested in [arXiv:1009.5228](https://arxiv.org/abs/1009.5228)
+- coherent **error propagation** for data from **different Markov chains**
+- **non-linear fits with x- and y-errors** and exact linear error propagation based on automatic differentiation as introduced in [arXiv:1809.01289]
+- **real and complex matrix operations** and their error propagation based on automatic differentiation (cholesky decomposition, calculation of eigenvalues and eigenvectors, singular value decomposition...)
 
 ## Getting started