Numarray
An Open Source project
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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
4.6 Getting and Setting array values
4.7 Slicing Arrays
4.8 Index Arrays
4.9 Exception Handling
5. Ufuncs
5.1 What are Ufuncs?
5.1.1 Ufuncs can take output arguments
5.1.2 Ufuncs have special methods
5.1.3 Ufuncs always return new arrays
5.2 Which are the Ufuncs?
5.2.1 Unary Mathematical Ufuncs
5.2.2 Binary Mathematical Ufuncs
5.2.3 Logical and bitwise ufuncs
5.2.4 Comparisons
5.2.5 Ufunc shorthands
5.3 Writing your own ufuncs!
6. Pseudo Indices
7. Array Functions
8. Array Methods
9. Array Attributes
10. Character Array
10.1 Introduction
10.2 Character array stripping, padding, and truncation
10.3 Character array functions
10.4 Character array methods
11. Record Array
11.1 Introduction
11.2 Record array functions
11.3 Record array methods
11.4 Record object
12. Object Array
12.1 Introduction
12.2 Object array functions
12.3 Object array methods
13. C extension API
13.1 Numarray extension basics
13.1.1 Include libnumarray.h
13.1.2 Alternate include method
13.1.3 Import libnumarray
13.1.4 Writing a simple setup.py file for a numarray extension
13.2 Fundamental data structures
13.2.1 Numarray Numerical Data Types
13.2.2 NumarrayType
13.2.3 PyArray_Descr
13.2.4 PyArrayObject
13.2.5 Flag Bits
13.3 Numeric simulation API
13.3.1 Simulation Functions
13.3.2 Numeric Compatible Functions
13.3.3 Unsupported Numeric Features
13.4 High-level API
13.4.1 High-level functions
13.4.2 Behaved-ness Requirements
13.4.3 Example
13.5 Element-wise API
13.5.1 Element-wise functions
13.5.2 Example
13.6 One-dimensional API
13.7 New numarray functions
2 Extension modules
14. Convolution
14.1 Convolution functions
14.2 Global constants
15. Fast-Fourier-Transform
15.1 Installation
15.1.1 Installation using FFTPACK
15.2 FFT Python Interface
15.3 fftpack Python Interface
16. Linear Algebra
16.1 Installation
16.1.1 Installation using LAPACK
16.2 Python Interface
17. Masked Arrays
17.1 What is a masked array?
17.2 Using numarray.ma
17.3 Class MaskedArray
17.3.1 Attributes of masked arrays
17.3.2 Methods on masked arrays
17.3.3 Constructing masked arrays
17.3.4 What are masks?
17.3.5 Working with masks
17.3.6 Operations
17.3.7 Copying or not?
17.3.8 Behaviors
17.3.9 Indexing and Slicing
17.3.10 Indexing in assignments
17.3.11 Operations that produce a scalar result
17.3.12 Assignment to elements and slices
17.4 MaskedArray Attributes
17.5 MaskedArray Functions
17.5.1 Unary functions
17.5.2 Binary functions
17.5.3 Comparison operators
17.5.4 Logical operators
17.5.5 Special array operators
17.5.6 Controlling the size of the string representations
17.6 Helper classes
17.6.1 The constant masked
17.6.2 The constant masked_print_option
17.7 Examples of Using numarray.ma
17.7.1 Data with a given value representing missing data
17.7.2 Filling in the missing data
17.7.3 Numerical operations
17.7.4 Seeing the mask
17.7.5 Filling it your way
17.7.6 Ignoring extreme values
17.7.7 Averaging an entire multidimensional array
18. Mlab
18.1 Matlab(tm) compatible functions
19. Random Numbers
19.1 General functions
19.2 Special random number distributions
19.2.1 Random floating point number distributions
19.2.2 Random integer number distributions
19.3 Examples
20. Multi-dimensional image processing
20.1 Introduction
20.2 Filter functions
20.2.1 Correlation and convolution
20.2.2 Smoothing filters
20.2.3 Filters based on order statistics
20.2.4 Derivatives
20.2.5 Generic filter functions
20.3 Fourier domain filters
20.4 Interpolation functions
20.4.1 Spline pre-filters
20.4.2 Interpolation functions
20.5 Binary morphology
20.6 Grey-scale morphology
20.7 Distance transforms
20.8 Segmentation and labeling
20.9 Object measurements
20.10 Extending nd_image in C
20.10.1 C callback functions
20.10.2 Functions that support C callback functions
21. Memory Mapping
21.1 Introduction
21.2 Opening a Memmap
21.3 Slicing a Memmap
21.4 Creating an array from a MemmapSlice
21.5 Resizing a MemmapSlice
21.6 Forcing file updates and closing the Memmap
21.7 numarray.memmap functions
21.8 Memmap methods
21.9 MemmapSlice methods
A. Glossary
Index
Numarray
An Open Source project
Previous:
Legal Notice
Up:
Numarray An Open Source
Next:
1 Numerical Python
Release 1.1, documentation updated on September 10, 2004.
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