[WIP] update docs

README.md

@@ -1,14 +1,22 @@
+# IDRLnet
+
 [![License](https://img.shields.io/github/license/analysiscenter/pydens.svg)](https://www.apache.org/licenses/LICENSE-2.0)
-[![Python](https://img.shields.io/badge/python-3.8-blue.svg)](https://python.org)
+[![Python](https://img.shields.io/badge/python-3.7/3.8/3.9-blue.svg)](https://python.org)
 [![Documentation Status](https://readthedocs.org/projects/idrlnet/badge/?version=latest)](https://idrlnet.readthedocs.io/en/latest/?badge=latest)
-
-# IDRLnet
+[![PyPI version](https://badge.fury.io/py/idrlnet.svg)](https://badge.fury.io/py/idrlnet)
+[![DockerHub](https://img.shields.io/docker/pulls/idrl/idrlnet.svg)](https://hub.docker.com/r/idrl/idrlnet)
+[![CodeFactor](https://www.codefactor.io/repository/github/idrl-lab/idrlnet/badge/master)](https://www.codefactor.io/repository/github/idrl-lab/idrlnet/overview/master)
 
 
 **IDRLnet** is a machine learning library on top of [PyTorch](https://pytorch.org/). Use IDRLnet if you need a machine
 learning library that solves both forward and inverse differential equations via physics-informed neural
 networks (PINN). IDRLnet is a flexible framework inspired by [Nvidia Simnet](https://developer.nvidia.com/simnet>).
 
+## Docs
+
+- [Full docs](https://idrlnet.readthedocs.io/en/latest/)
+- [Tutorial](https://idrlnet.readthedocs.io/en/latest/user/get_started/tutorial.html)
+
 ## Installation
 
 Choose one of the following installation methods.
@@ -27,11 +35,16 @@ Note: To avoid version conflicts, please use some tools to create a virtual envi
 
 ```bash
 docker pull idrl/idrlnet:latest
+docker run idrl/idrlnet:latest
 ```
 
 ### Anaconda
 
-
+```bash
+conda create -n idrlnet_dev python=3.8 -y
+conda activate idrlnet_dev
+pip install idrlnet
+```
 
 ### From Source
 

docs/index.rst

@@ -12,8 +12,8 @@ Welcome to idrlnet's documentation!
 Features
 --------
 
-IDRLnet is a machine learning library on top of `Pytorch <https://www.tensorflow.org/>`_. Use IDRLnet if you need a machine
-learning library that solves both forward and inverse partial differential equations (PDEs) via physics-informed neural
+IDRLnet is a machine learning library on top of `PyTorch <https://pytorch.org/>`_. Use IDRLnet if you need a machine
+learning library that solves both forward and inverse differential equations via physics-informed neural
 networks (PINN). IDRLnet is a flexible framework inspired by `Nvidia Simnet <https://developer.nvidia.com/simnet>`_.
 
 IDRLnet supports

docs/user/installation.md

@@ -2,13 +2,38 @@
 
 We recommend using conda to manage the environment.
 Other methods may also work well such like using docker or virtual env.
+
+Choose one of the following installation methods.
+
+## PyPI
+
+Simple installation from PyPI
+
+```bash
+pip install -U idrlnet
+```
+
+Note: To avoid version conflicts, please use some tools to create a virtual environment first.
+
+## Docker
+
+```bash
+docker pull idrl/idrlnet:latest
+docker run idrl/idrlnet:latest
+```
+
 ## Anaconda
 
 ```bash
-git clone https://git.idrl.site/pengwei/idrlnet
-cd idrlnet
 conda create -n idrlnet_dev python=3.8 -y
 conda activate idrlnet_dev
-pip install -r requirements.txt
+pip install idrlnet
+```
+
+## From Source
+
+```
+git clone https://github.com/idrl-lab/idrlnet
+cd idrlnet
 pip install -e .
 ```

requirements.txt

@@ -17,5 +17,5 @@ sympy==1.5.1
 pyevtk==1.1.1
 flask==1.1.2
 requests==2.25.0
-torch==1.7.1
+torch>=1.7.1
 networkx==2.5.1