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README.md

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*Current version of PaddleScience is v1.0 Beta.*
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# PaddleScience
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# Introduction
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> *Developed with [PaddlePaddle](https://www.paddlepaddle.org.cn/)*
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PaddleScience extends the PaddlePaddle framework with reusable
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software components for developing novel scientific computing applications. Such new
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applications include Physics-informed Machine Learning, neural network based PDE solvers,
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machine learning for CFD, and so on. PaddleScience is currently under active development.
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Its design is evolving and its APIs are subject to change.
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[![Doc](https://img.shields.io/readthedocs/paddlescience-docs/latest)](https://paddlescience-docs.readthedocs.io/zh/latest/)
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[![License](https://img.shields.io/github/license/PaddlePaddle/PaddleScience)](./LICENSE)
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# Core features and organization
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[**PaddleScience使用文档**](https://paddlescience-docs.readthedocs.io/zh/latest/)
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PaddleScience currently focuses on the PINNs model. The core components are as follows.
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## 简介
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- PDE, delineating partial differential equations in symbolic forms. Specific PDEs derive the
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the base PDE class.
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PaddleScience 是一个基于深度学习框架 PaddlePaddle 开发的科学计算套件,利用深度神经网络的学习能力和 PaddlePaddle 框架的自动(高阶)微分机制,解决物理、化学、气象等领域的问题。支持物理机理驱动、数据驱动、数理融合三种求解方式,并提供了基础 API 和详尽文档供用户使用与二次开发。
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- Geometry, a declarative interface for defining the geometric domain. Automatic
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discretization is supported
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<div align="center">
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<img src="./docs/images/overview/panorama.png" width="80%" height="80%">
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</div>
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- Neural net, currently supporting fully connected layers with customizable size and depth.
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## 特性
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- Loss, defining what exact penalties are enforced during the training process. By default,
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the L2 loss is applied. In the current design, the total loss is a weighted sum of
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four parts, the equation loss, the boundary condition loss, the initial condition loss and the data loss.
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- 支持简单几何和复杂 STL 几何的采样与布尔运算。
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- 支持包括 Dirichlet、Neumann、Robin 以及自定义边界条件。
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- 支持物理机理驱动、数据驱动、数理融合三种问题求解方式。涵盖流体、结构、气象等领域 8+ 案例。
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- 支持结果可视化输出与日志结构化保存。
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- 完善的 type hints,用户使用和代码贡献全流程文档,经典案例 AI studio 快速体验,降低使用门槛,提高开发效率。
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- 更多特性正在开发中...
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- Optimizer, specifying which optimizer to use for training. Adam is the default option. More
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optimizers, such as BFGS, will be available in the future.
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## 安装使用
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- Solver, managing the training process given the training data in a batchly fashion.
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1. 执行以下命令,从 github 上克隆 PaddleScience 项目,进入 PaddleScience 目录,并将该目录添加到系统环境变量中
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- Visualization, an easy access to the graph drawing utilities.
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``` shell
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git clone https://github.com/PaddlePaddle/PaddleScience.git
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cd PaddleScience
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export PYTHONPATH=$PWD:$PYTHONPATH
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```
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# Getting started
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2. 安装必要的依赖包
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## Prerequisites
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``` shell
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pip install -r requirements.txt
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```
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Hardware requirements: NVIDIA GPU V100, NVIDIA GPU A100
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3. 验证安装
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Package dependencies: paddle, cuda (11.0 or higher), numpy, scipy, sympy, matplotlib, vtk, pyevtk, wget.
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``` py
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python -c "import ppsci; ppsci.utils.run_check()"
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```
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PaddleScience currently relies on new features of the Paddle framework so please be advised to download the latest version of Paddle on GitHub or on Gitee.
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4. 开始使用
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For more details on installation, please refer to the offical [PaddlePaddle repository on GitHub](https://github.com/PaddlePaddle/Paddle) or [PaddlePaddle repository on Gitee](https://gitee.com/paddlepaddle/Paddle).
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``` py
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import ppsci
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## Download and environment setup
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# write your code here...
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```
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``` shell
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Download from GitHub: git clone https://github.com/PaddlePaddle/PaddleScience.git
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Download from Gitee: git clone https://gitee.com/PaddlePaddle/PaddleScience.git
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更多安装方式请参考 [**安装与使用**](https://paddlescience-docs.readthedocs.io/zh/latest/zh/install_setup/)
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cd PaddleScience
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export PYTHONPATH=$PWD:$PYTHONPATH
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## 快速开始
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pip install -r requirements.txt
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```
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请参考 [**快速开始**](https://paddlescience-docs.readthedocs.io/zh/latest/zh/quickstart/)
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## Run examples
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## 经典案例
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Some examples are baked in for quick demonstration. Please find them in the `examples` directory. To run an example, just enter the subdirectory and run the demo code in Python commandline.
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请参考 [**经典案例**](https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/viv/)
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``` shell
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# Darcy flow (Poisson equation)
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cd examples/darcy
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python darcy2d.py
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## 支持
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# LDC steady (Steady Navier-Stokes eqution)
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cd examples/ldc
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python ldc2d_steady_train.py
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如使用过程中遇到问题或想提出开发建议,欢迎在 [**Issue**](https://github.com/PaddlePaddle/PaddleScience/issues/new) 页面新建 issue。
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# Lid Driven Cavity unsteady with continue-time method (Unsteady Navier-Stokes equation)
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cd examples/ldc
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python ldc2d_unsteady_t.py
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## 贡献代码
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# Flow around a circular cylinder with discrete-time method (Unsteady Navier-Stokes equation)
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cd examples/cylinder/3d_unsteady_discrete/baseline
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python cylinder3d_unsteady.py
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PaddleScience 项目欢迎并依赖开发人员和开源社区中的用户,请参阅 [**贡献指南**](https://paddlescience-docs.readthedocs.io/zh/latest/zh/contribute/)。
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```
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## 证书
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## Short tutorials on how to construct and solve a PINN model
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[A tutorial on Lid Driven Cavity flow](./examples/ldc/README.md)
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[A tutorial on Darcy flow in porous medium](./examples/darcy/README.md)
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[Apache License 2.0](https://github.com/PaddlePaddle/PaddleScience/blob/develop/LICENSE)
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