numarray
User's Manual
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Contents
1 Numerical Python
1. Introduction
1.1 Where to get information and code
1.2 Acknowledgments
2. Installing numarray
2.1 Testing the Python installation
2.2 Testing the Numarray Python Extension Installation
2.3 Installing numarray
2.3.1 Installing on Unix, Linux, and Mac OSX
2.3.2 Installing on Windows
2.4 At the SourceForge...
3. High-Level Overview
3.1 Numarray Objects
3.2 Universal Functions
3.3 Convenience Functions
3.4 Differences between numarray and Numeric.
4. Array Basics
4.1 Basics
4.2 Creating arrays from scratch
4.2.1 array() and types
4.2.2 Multidimensional Arrays
4.3 Creating arrays with values specified ``on-the-fly''
4.3.1 Creating an array from a function
4.4 Coercion and Casting
4.4.1 Automatic Coercions and Binary Operations
4.4.2 The type value table
4.4.3 Long: the platform relative type
4.4.4 Deliberate casts (potentially down)
4.5 Operating on Arrays
4.5.1 Simple operations
4.5.2 In-place operations
5. Array Indexing
5.1 Getting and Setting array values
5.2 Slicing Arrays
5.3 Pseudo Indices
5.4 Index Arrays
6. Intermediate Topics
6.1 Rank-0 Arrays
6.2 Exception Handling
6.3 IEEE-754 Not a Number (NAN) and Infinity
7. Ufuncs
7.1 What are Ufuncs?
7.1.1 Ufuncs can take output arguments
7.1.2 Ufuncs have special methods
7.1.3 Ufuncs always return new arrays
7.2 Which are the Ufuncs?
7.2.1 Unary Mathematical Ufuncs
7.2.2 Binary Mathematical Ufuncs
7.2.3 Logical and bitwise ufuncs
7.2.4 Comparisons
7.2.5 Ufunc shorthands
7.3 Writing your own ufuncs!
7.3.1 Runtime components of a ufunc
7.3.2 Source components of a ufunc
7.3.3 Ufunc code generation
7.3.4 Type signatures and signature ordering
7.3.5 Forms
7.3.6 Ufunc Generation Example
8. Array Functions
9. Array Methods
10. Array Attributes
11. Character Array
11.1 Introduction
11.2 Character array stripping, padding, and truncation
11.3 Character array functions
11.4 Character array methods
12. Record Array
12.1 Introduction
12.2 Record array functions
12.3 Record array methods
12.4 Record object
13. Object Array
13.1 Introduction
13.2 Object array functions
13.3 Object array methods
14. C extension API
14.1 Numarray extension basics
14.1.1 Include libnumarray.h
14.1.2 Alternate include method
14.1.3 Import libnumarray
14.1.4 Writing a simple setup.py file for a numarray extension
14.2 Fundamental data structures
14.2.1 Numarray Numerical Data Types
14.2.2 NumarrayType
14.2.3 PyArray_Descr
14.2.4 PyArrayObject
14.2.5 Flag Bits
14.3 Numeric simulation API
14.3.1 Simulation Functions
14.3.2 Numeric Compatible Functions
14.3.3 Unsupported Numeric Features
14.4 High-level API
14.4.1 High-level functions
14.4.2 Behaved-ness Requirements
14.4.3 Example
14.5 Element-wise API
14.5.1 Element-wise functions
14.5.2 Example
14.6 One-dimensional API
14.7 New numarray functions
2 Extension modules
15. Convolution
15.1 Convolution functions
15.2 Global constants
16. Fast-Fourier-Transform
16.1 Installation
16.1.1 Installation using FFTPACK
16.2 FFT Python Interface
16.3 fftpack Python Interface
17. Linear Algebra
17.1 Installation
17.1.1 Installation using LAPACK
17.2 Python Interface
18. Masked Arrays
18.1 What is a masked array?
18.2 Using numarray.ma
18.3 Class MaskedArray
18.3.1 Attributes of masked arrays
18.3.2 Methods on masked arrays
18.3.3 Constructing masked arrays
18.3.4 What are masks?
18.3.5 Working with masks
18.3.6 Operations
18.3.7 Copying or not?
18.3.8 Behaviors
18.3.9 Indexing and Slicing
18.3.10 Indexing in assignments
18.3.11 Operations that produce a scalar result
18.3.12 Assignment to elements and slices
18.4 MaskedArray Attributes
18.5 MaskedArray Functions
18.5.1 Unary functions
18.5.2 Binary functions
18.5.3 Comparison operators
18.5.4 Logical operators
18.5.5 Special array operators
18.5.6 Controlling the size of the string representations
18.6 Helper classes
18.6.1 The constant masked
18.6.2 The constant masked_print_option
18.7 Examples of Using numarray.ma
18.7.1 Data with a given value representing missing data
18.7.2 Filling in the missing data
18.7.3 Numerical operations
18.7.4 Seeing the mask
18.7.5 Filling it your way
18.7.6 Ignoring extreme values
18.7.7 Averaging an entire multidimensional array
19. Mlab
19.1 Matlab(tm) compatible functions
20. Random Numbers
20.1 General functions
20.2 Special random number distributions
20.2.1 Random floating point number distributions
20.2.2 Random integer number distributions
20.3 Examples
21. Multi-dimensional image processing
21.1 Introduction
21.2 Properties shared by all functions
21.3 Filter functions
21.3.1 Correlation and convolution
21.3.2 Smoothing filters
21.3.3 Filters based on order statistics
21.3.4 Derivatives
21.3.5 Generic filter functions
21.4 Fourier domain filters
21.5 Interpolation functions
21.5.1 Spline pre-filters
21.5.2 Interpolation functions
21.6 Binary morphology
21.7 Grey-scale morphology
21.8 Distance transforms
21.9 Segmentation and labeling
21.10 Object measurements
21.11 Extending nd_image in C
21.11.1 C callback functions
21.11.2 Functions that support C callback functions
22. Memory Mapping
22.1 Introduction
22.2 Opening a Memmap
22.3 Slicing a Memmap
22.4 Creating an array from a MemmapSlice
22.5 Resizing a MemmapSlice
22.6 Forcing file updates and closing the Memmap
22.7 numarray.memmap functions
22.8 Memmap methods
22.9 MemmapSlice methods
A. Glossary
Index
numarray
User's Manual
Previous:
Legal Notice
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numarray User's Manual
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1 Numerical Python
Release 1.5, documentation updated on November 2, 2005.
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