دانلود کتاب Guide to NumPy

فهرست مطالب :

I NumPy from Python
Origins of NumPy
Object Essentials
Data-Type Descriptors
Basic indexing (slicing)
Memory Layout of ndarray
Contiguous Memory Layout
Non-contiguous memory layout
Universal Functions for arrays
Summary of new features
Summary of differences with Numeric
First-step changes
Second-step changes
Updating code that uses Numeric using alter_codeN
Changes to think about
Summary of differences with Numarray
First-step changes
Import changes
Attribute and method changes
Second-step changes
Additional Extension modules
The Array Object
ndarray Attributes
Memory Layout attributes
Data Type attributes
Other attributes
Array Interface attributes
ndarray Methods
Array conversion
Array shape manipulation
Array item selection and manipulation
Array calculation
Array Special Methods
Methods for standard library functions
Basic customization
Container customization
Arithmetic customization
Binary
In-place
Unary operations
Array indexing
Basic Slicing
Advanced selection
Integer
Boolean
Flat Iterator indexing
Basic Routines
Creating arrays
Operations on two or more arrays
Printing arrays
Functions redundant with methods
Dealing with data types
Additional Convenience Routines
Shape functions
Basic functions
Polynomial functions
Set Operations
Array construction using index tricks
Other indexing devices
Two-dimensional functions
More data type functions
Functions that behave like ufuncs
Miscellaneous Functions
Utility functions
Scalar objects
Attributes of array scalars
Methods of array scalars
Defining New Types
Data-type (dtype) Objects
Attributes
Construction
Methods
Standard Classes
Special attributes and methods recognized by NumPy
Matrix Objects
Memory-mapped-file arrays
Character arrays (numpy.char)
Record Arrays (numpy.rec)
Masked Arrays (numpy.ma)
Standard container class
Array Iterators
Default iteration
Flat iteration
N-dimensional enumeration
Iterator for broadcasting
Universal Functions
Description
Broadcasting
Output type determination
Use of internal buffers
Error handling
Optional keyword arguments
Attributes
Casting Rules
Methods
Reduce
Accumulate
Reduceat
Outer
Available ufuncs
Math operations
Trigonometric functions
Bit-twiddling functions
Comparison functions
Floating functions
Basic Modules
Linear Algebra (linalg)
Discrete Fourier Transforms (fft)
Random Numbers (random)
Discrete Distributions
Continuous Distributions
Miscellaneous utilities
Matrix-specific functions (matlib)
Ctypes utiltity functions (ctypeslib)
Testing and Packaging
Testing
NumPy Distutils
misc_util
Other modules
Conversion of .src files
Fortran files
Named repeat rule
Short repeat rule
Pre-defined names
Other files
II C-API
New Python Types and C-Structures
New Python Types Defined
PyArray_Type
PyArrayDescr_Type
PyUFunc_Type
PyArrayIter_Type
PyArrayMultiIter_Type
PyArrayFlags_Type
ScalarArrayTypes
Other C-Structures
PyArray_Dims
PyArray_Chunk
PyArrayInterface
Internally used structures
PyUFuncLoopObject
PyUFuncReduceObject
PyUFunc_Loop1d
PyArrayMapIter_Type
Complete API
Configuration defines
Guaranteed to be defined
Possible defines
Array Data Types
Enumerated Types
Defines
Max and min values for integers
Number of bits in data types
Bit-width references to enumerated typenums
Integer that can hold a pointer
C-type names
Boolean
(Un)Signed Integer
(Complex) Floating point
Bit-width names
Printf Formatting
Array API
Array structure and data access
Data access
Creating arrays
From scratch
From other objects
Dealing with types
General check of Python Type
Data-type checking
Converting data types
New data types
Special functions for PyArray_OBJECT
Array flags
Basic Array Flags
Combinations of array flags
Flag-like constants
Flag checking
Array method alternative API
Conversion
Shape Manipulation
Item selection and manipulation
Calculation
Functions
Array Functions
Other functions
Array Iterators
Broadcasting (multi-iterators)
Array Scalars
Data-type descriptors
Conversion Utilities
For use with PyArg_ParseTuple
Other conversions
Miscellaneous
Importing the API
Internal Flexibility
Memory management
Threading support
Priority
Default buffers
Other constants
Miscellaneous Macros
Enumerated Types
UFunc API
Constants
Macros
Functions
Generic functions
Importing the API
How to extend NumPy
Writing an extension module
Required subroutine
Defining functions
Functions without keyword arguments
Functions with keyword arguments
Reference counting
Dealing with array objects
Converting an arbitrary sequence object
Creating a brand-new ndarray
Getting at ndarray memory and accessing elements of the ndarray
Example
Beyond the Basics
Iterating over elements in the array
Basic Iteration
Iterating over all but one axis
Iterating over multiple arrays
Broadcasting over multiple arrays
Creating a new universal function
User-defined data-types
Adding the new data-type
Registering a casting function
Registering coercion rules
Registering a ufunc loop
Subtyping the ndarray in C
Creating sub-types
Specific features of ndarray sub-typing
The __array_finalize__ method
The __array_priority__ attribute
The __array_wrap__ method
Using Python as glue
Calling other compiled libraries from Python
Hand-generated wrappers
f2py
Creating source for a basic extension module
Creating a compiled extension module
Improving the basic interface
Inserting directives in Fortran source
A filtering example
Calling f2py from Python
Automatic extension module generation
Conclusion
weave
Speed up code involving arrays (also see scipy.numexpr)
Inline C-code
Simplify creation of an extension module
Conclusion
Pyrex
Pyrex-add
Pyrex-filter
Conclusion
ctypes
Having a shared library
Loading the shared library
Converting arguments
Calling the function
Complete example
Conclusion
Additional tools you may find useful
SWIG
SIP
Boost Python
Instant
PyInline
PyFort
Code Explanations
Memory model
Data-type encapsulation
N-D Iterators
Broadcasting
Array Scalars
Advanced (``Fancy\'\') Indexing
Fancy-indexing check
Fancy-indexing implementation
Creating the mapping object
Binding the mapping object
Getting (or Setting)
Universal Functions
Setup
Function call
One Loop
Strided Loop
Buffered Loop
Final output manipulation
Methods
Setup
Reduce
Accumulate
Reduceat