Chris Marshall
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2.093
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2.019
(CHM on 2018-05-05)
2.018_02 DEV
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2.018_01 DEV
(CHM on 2018-04-13)
2.018
(CHM on 2017-05-21)
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2.092
(ETJ on 2024-09-07)
2.091
(ETJ on 2024-09-06)
2.090
(ETJ on 2024-08-23)
2.089_02 DEV
(ETJ on 2024-06-26)
2.089_01 DEV
(ETJ on 2024-06-05)
2.089
(ETJ on 2024-05-11)
2.088
(ETJ on 2024-04-21)
2.087
(ETJ on 2024-04-05)
2.086
(ETJ on 2024-03-31)
2.085_02 DEV
(ETJ on 2024-03-25)
2.085_01 DEV
(ETJ on 2024-02-10)
2.085
(ETJ on 2024-01-30)
2.084
(ETJ on 2023-05-21)
2.083
(ETJ on 2023-04-30)
2.082_01 DEV
(ETJ on 2023-04-27)
2.082
(ETJ on 2023-03-22)
2.081_03 DEV
(ETJ on 2023-03-20)
2.081_02 DEV
(ETJ on 2023-03-14)
2.081_01 DEV
(ETJ on 2023-02-27)
2.081
(ETJ on 2022-10-25)
2.080_02 DEV
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2.080_01 DEV
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2.080
(ETJ on 2022-05-28)
2.079
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2.078
(ETJ on 2022-04-10)
2.077
(ETJ on 2022-03-16)
2.076
(ETJ on 2022-02-25)
2.075
(ETJ on 2022-02-19)
2.074
(ETJ on 2022-02-08)
2.073
(ETJ on 2022-02-07)
2.072
(ETJ on 2022-01-30)
2.071
(ETJ on 2022-01-29)
2.070
(ETJ on 2022-01-28)
2.069
(ETJ on 2022-01-28)
2.068_07 DEV
(ETJ on 2022-01-28)
2.068_06 DEV
(ETJ on 2022-01-25)
2.068_05 DEV
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2.068_04 DEV
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2.068_03 DEV
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2.068_02 DEV
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2.068_01 DEV
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2.068
(ETJ on 2022-01-14)
2.067
(ETJ on 2022-01-13)
2.066
(ETJ on 2022-01-10)
2.065
(ETJ on 2022-01-10)
2.064
(ETJ on 2022-01-08)
2.063_05 DEV
(ETJ on 2022-01-08)
2.063_04 DEV
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2.063_03 DEV
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2.063_02 DEV
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2.063_01 DEV
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2.063
(ETJ on 2021-11-19)
2.062
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2.061
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2.060
(ETJ on 2021-11-08)
2.059
(ETJ on 2021-11-08)
2.058
(ETJ on 2021-11-06)
2.057_05 DEV
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2.057_04 DEV
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2.057
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2.056
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2.055
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(ETJ on 2021-07-26)
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(ETJ on 2021-07-04)
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(ETJ on 2021-06-14)
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(ETJ on 2021-05-31)
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(ETJ on 2021-05-08)
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(ETJ on 2021-05-04)
2.045
(ETJ on 2021-05-03)
2.044
(ETJ on 2021-05-01)
2.043
(ETJ on 2021-04-30)
2.042
(ETJ on 2021-04-30)
2.041
(ETJ on 2021-04-29)
2.040_02 DEV
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(ETJ on 2021-04-28)
2.040
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2.034
(ETJ on 2021-03-31)
2.033
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2.030
(ETJ on 2021-03-21)
2.029
(ETJ on 2021-03-12)
2.028_01 DEV
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2.028
(ETJ on 2021-03-07)
2.027
(ETJ on 2021-03-06)
2.026_04 DEV
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2.026_03 DEV
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2.026_02 DEV
(ETJ on 2021-02-25)
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2.026
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2.025
(ETJ on 2020-11-19)
2.024
(ETJ on 2020-09-17)
2.023
(ETJ on 2020-09-14)
2.022
(ETJ on 2020-09-06)
2.021
(ETJ on 2020-03-01)
2.020_05 DEV
(ETJ on 2019-12-29)
2.020_04 DEV
(ETJ on 2019-12-28)
2.020_03 DEV
(ETJ on 2019-12-27)
2.020_02 DEV
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2.020_01 DEV
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2.020
(ETJ on 2019-12-12)
2.019_06 DEV
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2.019_05 DEV
(ETJ on 2019-12-02)
2.019_04 DEV
(ETJ on 2019-11-27)
2.019_03 DEV
(ETJ on 2019-11-25)
2.019_02 DEV
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2.019_01 DEV
(ETJ on 2019-11-10)
2.017_02 DEV
(CHM on 2017-05-18)
2.017_01 DEV
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2.017
(CHM on 2016-10-08)
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2.016
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(CHM on 2015-10-12)
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2.013_02 DEV
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2.013_01 DEV
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2.012
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2.010
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2.009_01 DEV
(CHM on 2015-05-31)
2.009
(CHM on 2015-05-29)
2.008
(CHM on 2015-05-24)
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2.007_02 DEV
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2.007
(CHM on 2013-10-12)
2.006_92 DEV
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2.006_91 DEV
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2.006_90 DEV
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PDL-2.014_01
River stage three
• 96 direct dependents
• 105 total dependents
58 ++
/
PDL::Tutorials
NAME
PDL::Tutorials - A guide to PDL's tutorial documentation.
MIGRATION
These are our migration guides for users familiar with other types of numerical analysis software.
PDL::MATLAB
Migration guide for MATLAB users. This page explains the key differences between MATLAB and PDL from the point of view of a MATLAB user.
PDL::Scilab
Migration guide for Scilab users. This page explains the key differences between Scilab and PDL from the point of view of a Scilab user.
FOUNDATION
PDL::Philosophy
Why did we write PDL? This document explains some of the history and motivation behind the Perl Data Language. It is an attempt to answer the question "Why PDL?".
PDL::QuickStart
Quick introduction to PDL features. A hands-on guide suitable for complete beginners. This page assumes no previous knowledge of Perl or PDL.
PDL::Indexing
After you have read the QuickStart guide, you should follow up with this document. This guide goes more deeply into the concepts of "indexing" and "slicing" and how they form the core of numerical analysis with PDL.
PDL::Threading
Threading is one of PDL's most powerful features. If you know MATLAB, you've heard of "vectorizing". Well, threading is like "vectorizing on steroids". It lets you make very fast and compact code by avoiding nested loops. All vector-based languages do this, but PDL generalizes the technique to all sorts of applications.
This tutorial introduces PDL's threading feature, and it shows an example implementing Conway's Game of Life in 10 lines and 80 times faster than a classical implementation.
PDL::BadValues
Sometimes it is useful to specify that a certain value is "bad" or "missing". Scientific instruments some times include portions of invalid data. For example, a CCD camera might produce an image with over-exposed pixels. PDL's "bad values" feature gives you an easy way to deal with this sort of imperfect data.
PDL::Tips
Tips and suggestions for using PDL. This page is an assorted collection of programming tidbits that some PDL users have found useful. Some of these tips might be of help when you write your programs.
ADVANCED
PDL::PP
PDL's Pre-Processor is one of PDL's most powerful features. You write a function definition in special markup and the preprocessor generates real C code which can be compiled. With PDL:PP you get the full speed of native C code without having to deal with the full complexity of the C language.
PDL::API
A simple cookbook explaining how to create piddle manually, either from Perl or from C/XS code. This page covers the PDL core routines that comprise the PDL API. If you need to access piddles from C/XS, this is the document for you.
PDL::Internals
Description of the inner workings of the PDL module. Very few people need to see this. This page is mainly for PDL developers, or people interested in debugging PDL or changing the internals of PDL. If you can read this document and understand all of it, and you additionally understand PDL::PP , you will be awarded the title of "PDL Guru".
COPYRIGHT
Copyright 2010 Daniel Carrera (dcarrera@gmail.com). You can distribute and/or modify this document under the same terms as the current Perl license.
See: http://dev.perl.org/licenses/