Fast array processing functions
Project description
- Copyright:
- 2014 - 2015
- License:
This document may be distributed under the Apache 2.0 License.
- Language:
Python 3.x
Releases
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Introduction
The arrayfunc module provides high speed array processing functions for use with the standard Python array module. These functions are patterned after the functions in the standard Python Itertools module together with some additional ones from other sources.
The purpose of these functions is to perform mathematical calculations on arrays faster than using native Python.
Functions
Summary
The functions fall into several categories.
Filling Arrays
Function |
Description |
|---|---|
count |
Fill an array with evenly spaced values using a start and step values. |
cycle |
Fill an array with evenly spaced values using a start, stop, and step values, and repeat until the array is filled. |
repeat |
Fill an array with a specified value. |
Filtering Arrays
Function |
Description |
|---|---|
afilter |
Select values from an array based on a boolean criteria. |
compress |
Select values from an array based on another array of boolean values. |
dropwhile |
Select values from an array starting from where a selected criteria fails and proceding to the end. |
takewhile |
Like dropwhile, but starts from the beginning and stops when the criteria fails. |
Examining and Searching Arrays
Function |
Description |
|---|---|
aany |
Returns True if any element in an array meets the selected criteria. |
aall |
Returns True if all element in an array meet the selected criteria. |
amax |
Returns the maximum value in the array. |
amin |
Returns the minimum value in the array. |
findindex |
Returns the index of the first value in an array to meet the specified criteria. |
findindices |
Searches an array for the array indices which meet the specified criteria and writes the results to a second array. Also returns the number of matches found. |
Operating on Arrays
Function |
Description |
|---|---|
amap |
Apply an operator to each element of an array, together with an optional second parameter (for operators taking two parameters). The results are written to a second array. |
amapi |
Like amap, but the results are written in place to the input array. |
starmap |
Like amap, but where a second array acts as the second parameter. The results are written to an output array. |
starmapi |
Like starmap, but the results are written in place to the first input array. |
asum |
Calculate the arithmetic sum of an array. |
Amap and amapi support more than 70 different operations. Starmap and starmapi support more than two dozen different operations.
Data Conversion
Function |
Description |
|---|---|
convert |
Convert arrays between data types. The data will be converted into the form required by the output array. |
Attributes
In addition to functions, a set of attributes are provided representing the platform specific maximum and minimum numerical values for each array type. These attributes are part of the “arraylimits” module.
Supported Array Types
Arrayfunc supports all standard Python 3.x array types, as well as the ‘bytes’ type.
Performance
Performance will vary depending on the function, operation, array data type used, and whether overflow checking is enabled.
Average performance increase for amap is 95 times faster than native Python. For functions other than amap, amapi, starmap, and starmapi is 63 times faster than native Python. However, some functions and operations may be more than 350 times faster than native Python.
Detailed performance figures are listed in the documentation.
Platform support
Arrayfunc is written in ‘C’ and uses the standard C libraries to implement the underlying math functions. Arrayfunc has been tested on the following platforms.
OS |
Bits |
Compiler |
Python Version Tested |
|---|---|---|---|
Ubuntu 14.04 LTS |
64 bit |
GCC |
3.4 |
Debian 8 |
32 bit |
GCC |
3.4 |
FreeBSD 10 |
64 bit |
LLVM |
3.4 |
MS Windows 8.1 |
32 bit |
MS Visual Studio C 2010 |
3.4 |
Some amap and amapi operations are not supported on MS Windows due to lack of compiler support. See the documentation for details.
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