2. Advanced topics¶
This part of the Scipy lecture notes is dedicated to advanced usage. 它试图将熟练的Python编码人员教育成一个专家,解决各种具体问题。
- 2.1. Advanced Python Constructs
- 2.1.1. 迭代器、生成器表达式和生成器
- 2.1.2. 装饰器
- 2.1.2.1. Replacing or tweaking the original object
- 2.1.2.2. Decorators implemented as classes and as functions
- 2.1.2.3. Copying the docstring and other attributes of the original function
- 2.1.2.4. Examples in the standard library
- 2.1.2.5. 弃用函数
- 2.1.2.6. 删除
while
循环的装饰器 - 2.1.2.7. A plugin registration system
- 2.1.3. Context managers
- 2.2. Advanced NumPy
- 2.2.1. Life of ndarray
- 2.2.2. Universal functions
- 2.2.3. Interoperability features
- 2.2.4. Array siblings:
chararray
,maskedarray
,matrix
- 2.2.5. Summary
- 2.2.6. 贡献NumPy/Scipy
- 2.3. Debugging code
- 2.4. Optimizing code
- 2.5. Sparse Matrices in SciPy
- 2.5.1. Introduction
- 2.5.2. Storage Schemes
- 2.5.2.1. Common Methods
- 2.5.2.2. Sparse Matrix Classes
- 2.5.2.3. Summary
- 2.5.3. Linear System Solvers
- 2.5.4. Other Interesting Packages
- 2.6. Image manipulation and processing using Numpy and Scipy
- 2.7. Mathematical optimization: finding minima of functions
- 2.7.1. Knowing your problem
- 2.7.2. A review of the different optimizers
- 2.7.3. Practical guide to optimization with scipy
- 2.7.4. Special case: non-linear least-squares
- 2.7.5. Optimization with constraints
- 2.8. Interfacing with C