Numarray
An Open Source project
Previous:
Legal Notice
Up:
Numarray An Open Source
Next:
1 Numerical Python
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
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
4.9.1 Integer computations
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 Ufuncs
5.2.4 Comparisons
5.2.5 Ufunc shorthands
6. Pseudo Indices
7. Array Functions
8. Array Methods
9. Array Attributes
10. C extension API
10.1 Accessing the numarray C-API
10.1.1 include numarray.h
10.1.2 import libnumarray
10.2 Fundamental data structures
10.2.1 Numarray Numerical Data Types
10.2.2 NumarrayType
10.2.3 PyArray_Descr
10.2.4 PyArrayObject
10.2.5 Flag Bits
10.3 High-level API
10.3.1 High-level functions
10.3.2 Behaved-ness Requirements
10.3.3 Example
10.4 Element-wise API
10.4.1 Element-wise functions
10.4.2 Example
10.5 One-dimensional API
10.6 Numeric emulation API
10.6.1 Emulation Functions
10.6.2 Numeric Compatible Functions
10.6.3 Unsupported Numeric Features
10.7 New numarray functions
2 Extension modules
11. Convolution
11.1 Convolution functions
11.2 Global constants
12. Fast-Fourier-Transform
12.1 Installation
12.1.1 Installation using FFTPACK
12.2 FFT Python Interface
12.3 fftpack Python Interface
13. Linear Algebra
13.1 Installation
13.1.1 Installation using LAPACK
13.2 Python Interface
14. Masked Arrays
14.1 What is a masked array?
14.2 Installing and using MA
14.3 Class MaskedArray
14.3.1 Attributes of masked arrays
14.3.2 Methods on masked arrays
14.3.3 Constructing masked arrays
14.3.4 What are masks?
14.3.5 Working with masks
14.3.6 Operations
14.3.7 Copying or not?
14.3.8 Behaviors
14.3.9 Indexing and Slicing
14.3.10 Indexing in assignments
14.3.11 Operations that produce a scalar result
14.3.12 Assignment to elements and slices
14.4 MaskedArray Attributes
14.5 MaskedArray Functions
14.5.1 Unary functions
14.5.2 Binary functions
14.5.3 Comparison operators
14.5.4 Logical operators
14.5.5 Special array operators
14.5.6 Controlling the size of the string representations
14.6 Helper classes
14.6.1 The constant masked
14.6.2 The constant masked_print_option
14.7 Examples of Using MA
14.7.1 Data with a given value representing missing data
14.7.2 Filling in the missing data
14.7.3 Numerical operations
14.7.4 Seeing the mask
14.7.5 Filling it your way
14.7.6 Ignoring extreme values
14.7.7 Averaging an entire multidimensional array
15. Random Numbers
15.1 General functions
15.2 Special random number distributions
15.2.1 Random floating point number distributions
15.2.2 Random integer number distributions
15.3 Examples
16. Multi-dimensional image processing
16.1 Introduction
16.2 Filter functions
16.2.1 Correlation and convolution
16.2.2 Smoothing filters
16.2.3 Filters based on order statistics
16.2.4 Derivatives
16.2.5 Fourier space filters
16.3 Interpolation functions
16.3.1 Spline pre-filters
16.3.2 Interpolation functions
16.4 Morphology
16.4.1 Binary morphology
16.4.2 Grey-scale morphology
16.5 Object measurements
A. Glossary
Index
Numarray
An Open Source project
Previous:
Legal Notice
Up:
Numarray An Open Source
Next:
1 Numerical Python
Release 0.7, documentation updated on August 22, 2003.
Send comments to the
NumArray community
.
