常用 API

本章按功能分组介绍了各常用的API。许多的API包含示例代码，这些示例代码演示了API的基本用法。

这些示例都是使用NumPy并且是通过这种方式导入NumPy：

>>> import numpy as np

::: tip 提示

执行示例的一种便捷的方法是 IPython 的 %doctest_mode 模式，它允许粘贴多行示例并保留缩进。

:::

• 创建数组
• Ones and zeros
• From existing data
• Creating record arrays (numpy.rec)
• Creating character arrays (numpy.char)
• Numerical ranges
• Building matrices
• The Matrix class
• 数组操作
• Basic operations
• Changing array shape
• Transpose-like operations
• Changing number of dimensions
• Changing kind of array
• Joining arrays
• Splitting arrays
• Tiling arrays
• Adding and removing elements
• Rearranging elements
• 二进制操作
• Elementwise bit operations
• Bit packing
• Output formatting
• 字符串操作
• String operations
• Comparison
• String information
• Convenience class
• C-Types外部函数接口(numpy.ctypeslib)
• 时间日期相关
• numpy.datetime_as_string
• numpy.datetime_data
• Business Day Functions
• 数据类型相关
• numpy.can_cast
• numpy.promote_types
• numpy.min_scalar_type
• numpy.result_type
• numpy.common_type
• numpy.obj2sctype
• Creating data types
• Data type information
• Data type testing
• Miscellaneous
• 可选的Scipy加速支持(numpy.dual)
• Linear algebra
• FFT
• Other
• 具有自动域的数学函数(numpy.emath)
• 浮点错误处理
• Setting and getting error handling
• Internal functions
• 离散傅立叶变换(numpy.fft)
• Standard FFTs
• Real FFTs
• Hermitian FFTs
• Helper routines
• Background information
• Implementation details
• Normalization
• Real and Hermitian transforms
• Higher dimensions
• References
• Examples
• 财金相关
• Simple financial functions
• 实用的功能
• numpy.apply_along_axis
• numpy.apply_over_axes
• numpy.vectorize
• numpy.frompyfunc
• numpy.piecewise
• 特殊的NumPy帮助功能
• Finding help
• Reading help
• 索引相关
• Generating index arrays
• Indexing-like operations
• Inserting data into arrays
• Iterating over arrays
• 输入和输出
• NumPy binary files (NPY, NPZ)
• Text files
• Raw binary files
• String formatting
• Memory mapping files
• Text formatting options
• Base-n representations
• Data sources
• Binary Format Description
• 线性代数(numpy.linalg)
• Matrix and vector products
• Decompositions
• Matrix eigenvalues
• Norms and other numbers
• Solving equations and inverting matrices
• Exceptions
• Linear algebra on several matrices at once
• 逻辑函数
• Truth value testing
• Array contents
• Array type testing
• Logical operations
• Comparison
• 操作掩码数组
• Constants
• Creation
• Inspecting the array
• Manipulating a MaskedArray
• Operations on masks
• Conversion operations
• Masked arrays arithmetics
• 数学函数
• Trigonometric functions
• Hyperbolic functions
• Rounding
• Sums, products, differences
• Exponents and logarithms
• Other special functions
• Floating point routines
• Rational routines
• Arithmetic operations
• Handling complex numbers
• Miscellaneous
• 矩阵库(numpy.matlib)
• numpy.matlib.empty
• numpy.matlib.zeros
• numpy.matlib.ones
• numpy.matlib.eye
• numpy.matlib.identity
• numpy.matlib.repmat
• numpy.matlib.rand
• numpy.matlib.randn
• 杂项
• Performance tuning
• Memory ranges
• Array mixins
• NumPy version comparison
• Utility
• Matlab-like Functions
• 填充数组
• numpy.pad
• 多项式
• Transition notice
• 随机抽样(numpy.random)
• Quick Start
• Introduction
• Concepts
• Features
• 集合操作
• Making proper sets
• Boolean operations
• 排序、搜索和计数
• Sorting
• Searching
• Counting
• 统计相关
• Order statistics
• Averages and variances
• Correlating
• Histograms
• 测试支持(numpy.testing)
• Asserts
• Decorators
• Test Running
• Guidelines
• 窗口函数
• Various windows