PDL::FAQ - Man Page

You can find the latest version of this document at  <http://pdl.perl.org/?docs=FAQ&title=Frequently%20Asked%20Questions> .

This is a considerably reworked version of the PDL FAQ. As such many errors might have crept in and many updates might not have made it in.  You are explicitly encouraged to let us know about questions which you think should be answered in this document but currently aren't.

Similarly, if you think parts of this document are unclear, please tell the FAQ maintainer about it. Where a specific answer is taken in full from someones posting the authorship should be indicated, let the FAQ maintainer know if it isn't. For more general information explicit acknowledgment is not made in the text, but rather there is an incomplete list of contributors at the end of this document. Please contact the FAQ maintainer if you feel hard done by.

Send your comments, additions, suggestions or corrections to the PDL mailing list at pdl-general@lists.sourceforge.net. See Q: 3.2 below for instructions on how to join the mailing lists.

PDL stands for  Perl Data  Language . To say it with the words of Karl Glazebrook, initiator of the PDL project:

    The PDL concept is to give standard perl5 the ability
    to COMPACTLY store and SPEEDILY manipulate the large
    N-dimensional data sets which are the bread and butter
    of scientific computing. e.g. $x=$y+$z can add two
    2048x2048 images in only a fraction of a second.

It provides tons of useful functionality for scientific and numeric analysis.

For readers familiar with other scientific data evaluation packages it may be helpful to add that PDL is in many respects similar to IDL, MATLAB and similar packages. However, it tries to improve on a number of issues which were perceived (by the authors of PDL) as shortcomings of those existing packages.

PDL is supported by its users. General informal support for PDL is provided through the PDL mailing list (pdl-general@lists.sourceforge.net , see below).

As a Perl extension (see Q: 2.5 below) it is devoted to the idea of free and open development put forth by the Perl community. PDL was and is being actively developed by a loosely knit group of people around the world who coordinate their activities through the PDL development mailing list (pdl-devel@lists.sourceforge.net , see Q: 3.2 below). If you would like to join in the ongoing efforts to improve PDL please join this list.

There are actually several reasons and everyone should decide for themselves which are the most important ones:

• PDL is "free software". The authors of PDL think that this concept has several advantages: everyone has access to the sources -> better debugging, easily adaptable to your own needs, extensible for your purposes, etc... In comparison with commercial packages such as MATLAB and IDL this is of considerable importance for workers who want to do some work at home and cannot afford the considerable cost to buy commercial packages for personal use.
• PDL is based on a powerful and well designed scripting language: Perl. In contrast to other scientific/numeric data analysis languages it has been designed using the features of  a proven language instead of having grown into existence from  scratch. Defining the control structures while features were  added during development leads to languages that often appear  clumsy and badly planned for most existing packages with  similar scope as PDL.
• Using Perl as the basis a PDL programmer has all the powerful features of Perl at their hand, right from the start. This includes regular expressions, associative arrays (hashes), well designed interfaces to the operating system, network, etc. Experience has shown that even in mainly numerically oriented programming it is often extremely handy if you have easy access to powerful semi-numerical or completely non-numerical functionality as well. For example, you might want to offer the results of a complicated computation as a server process to other processes on the network, perhaps directly accepting input from other processes on the network. Using Perl and existing Perl extension packages things like this are no problem at all (and it all will fit into your "PDL script").
• Extremely easy extensibility and interoperability as PDL is a Perl extension; development support for Perl extensions is an integral part of Perl and there are already numerous extensions to standard Perl freely available on the network.
• Integral language features of Perl (regular expressions, hashes, object modules) immensely facilitated development and implementation of key concepts of PDL. One of the most striking examples for this point is probably PDL::PP  (see Q: 6.16 below), a code generator/parser/pre-processor that generates PDL functions from concise descriptions.

• None of the existing data languages follow the Perl language rules, which the authors firmly believe in:

  • TIMTOWTDI: There is more than one way to do it. Minimalist languages are interesting for computer scientists, but for users, a little bit of redundancy makes things wildly easier to cope with and allows individual programming styles - just as people speak in different ways. For many people this will undoubtedly be a reason to avoid PDL ;)
  • Simple things are simple, complicated things possible: Things that are often done should be easy to do in the language, whereas seldom done things shouldn't be too cumbersome.

  All existing languages violate at least one of these rules.

• As a project for the future PDL should be able to use super computer features, e.g. vector capabilities/parallel processing, GPGPU acceleration. This will probably be achieved by having  PDL::PP (see Q: 6.16 below) generate appropriate code on such architectures to exploit these features.
• [ fill in your personal 111 favourite reasons here...]

Just in case you do not yet know what the main features of PDL are and what one could do with them, here is a (necessarily selective) list of key features:

PDL is well suited for matrix computations, general handling of multidimensional data, image processing, general scientific computation, numerical applications. It supports I/O for many popular image and data formats, 1D (line plots), 2D (images) and 3D (volume visualization, surface plots via OpenGL - for instance implemented using Mesa or video card OpenGL drivers), graphics display capabilities and implements many numerical and semi-numerical algorithms.

Through the powerful pre-processor it is also easy to interface Perl to your favorite C routines, more of that further below.

PDL is a Perl5 extension package. As such it needs an existing Perl5 installation (see below) to run. Furthermore, much of PDL is written in Perl (+ some core functionality that is written in C). PDL programs are (syntactically) just Perl scripts that happen to use some of the functionality implemented by the package "PDL".

Since PDL is just a Perl5 package you need first of all an installation of Perl5 on your machine. As of this writing PDL requires version 5.10.x of perl, or higher.  More information on where and how to get a Perl installation can be found at the Perl home page <http://www.perl.org> and at many CPAN sites (if you do not know what CPAN is, check the answer to the next question).

To build PDL you also need a working C compiler, support for Xsubs, and the package Extutils::MakeMaker. If you don't have a compiler there might be a binary distribution available, see "Binary distributions" below.

If you can (or cannot) get PDL working on a new (previously unsupported) platform we would like to hear about it. Please, report your success/failure to the PDL mailing list at  pdl-general@lists.sourceforge.net . We will do our best to assist you in porting PDL to a new system.

PDL is available as source distribution in the  Comprehensive Perl Archive Network (or CPAN) and from the GitHub project page at <https://github.com/PDLPorters/pdl>. The CPAN archives contains not only the PDL distribution but also just about everything else that is Perl-related.  CPAN is mirrored by dozens of sites all over the world.  The main site is <http://www.cpan.org>, and local CPAN sites (mirrors) can be found there. PDL's homepage is at <http://pdl.perl.org> and the latest version can also be downloaded from there.

We are delighted to be able to give you the nicest possible answer on a question like this: PDL is *free software* and all sources are publicly available. But still, there are some copyrights to comply with. So please, try to be as nice as we (the PDL authors) are and try to comply with them.

Oh, before you think it is *completely* free: you have to invest some time to pull the distribution from the net, compile and install it and (maybe) read the manuals.

The complete PDL documentation is available with the PDL distribution. Use the command perldoc PDL to start learning about PDL.

The easiest way by far, however, to get familiar with PDL is to use the PDL on-line help facility from within the PDL shell, pdl2  Just type pdl2 at your system prompt. Once you are inside the pdl2 shell type help .  Using the help and apropos commands inside the shell you should be able to find the way round the documentation.

Even better, you can immediately try your newly acquired knowledge about PDL by issuing PDL/Perl commands directly at the command line. To illustrate this process, here is the record of a typical pdl2 session of a PDL beginner (lengthy output is only symbolically reproduced in braces ( <... ...> ) ):

    unix> pdl2
    pdl> help
    < ... help output ... >
    pdl> help PDL::QuickStart
    < ... perldoc page ... >
    pdl> $x = pdl (1,5,7.3,1.0)
    pdl> $y = sequence float, 4, 4
    pdl> help inner
    < ... help on the 'inner' function ... >
    pdl> $c = inner $x, $y
    pdl> p $c
    [22.6 79.8 137 194.2]

For further sources of information that are accessible through the Internet see next question.

First of all, for all purely Perl-related questions there are tons of sources on the net. Good points to start are  <http://www.perl.com> and <http://www.perl.org> .

The PDL home site can be accessed by pointing your web browser to  <http://pdl.perl.org> . It has tons of goodies for anyone interested in PDL:

• PDL distributions
• On-line documentation
• Pointers to an HTML archive of the PDL mailing lists
• A list of platforms on which PDL has been successfully tested.
• News about recently added features, ported libraries, etc.
• Name of the current pumpkin holders for the different PDL modules (if you want to know what that means you better had a look at the web pages).

If you are interested in PDL in general you can join the pdl-general mailing list. This is a forum to discuss programming issues in PDL, report bugs, seek assistance with PDL related problems, etc.

If you are interested in all the technical details of the ongoing PDL development you can join the pdl-devel mailing list.

Subscription and current archive links to both mailing lists can be found at <http://pdl.perl.org/?page=mailing-lists>.

Cross-posting between these lists should be avoided unless there is a very good reason for doing that.

The PDL project, begun in the late 1990s, has undergone considerable evolution since that time, and the support for it has as well. Thus mailing-list archives are in several places.  Originally pdl-general was called 'perldl', and pdl-devel was called 'pdl-porters'.

|Time Period | URL                                                   | |------------|-------------------------------------------------------| |1996 - 2004 | http://www.xray.mpe.mpg.de/mailing-lists/perldl/      | |1997 - 2004 | http://www.xray.mpe.mpg.de/mailing-lists/pdl-porters/ | |2005 - 2015 | http://perldl.jach.hawaii.narkive.com/                | |2005 - 2015 | http://pdl-porters.jach.hawaii.narkive.com/           | |2015 -      | https://sourceforge.net/p/pdl/mailman/pdl-general/    | |2015 -      | https://sourceforge.net/p/pdl/mailman/pdl-devel/      | |--------------------------------------------------------------------|

As of this writing (FAQ version 1.008 of 21 May 2017) the latest stable version is 2.018.  The latest stable version should always be available from a CPAN mirror site near you (see Question 2.7 for info on where to get PDL).

The most current (possibly unstable) version of PDL can be obtained  from the Git repository, see Question 4.10 and periodic CPAN developers releases of the Git code will be made for testing purposes and more general availability.

Over its development, PDL has used both a single floating point version number (from the versions 1.x through 2.005) at which point it switched to a dotted triple version for 2.1.1 onward---EXCEPT for version 2.2 which came out which should have been 2.2.0.  To simplify and unify things, PDL has reverted to a single float version representation with PDL-2.006.  This can cause dependency problems for modules that set a minimum PDL version of 2.2.  The work around it, note that all extant PDL releases have version numbers greater than 2.2.1 so that using 0 as the minimum version will work.

Two ways that you could help almost immediately are (1) participate in CPAN Testers for PDL and related modules, and (2) proofreading and clarifying the PDL documentation so that it is most useable for PDL users, especially new users.

To participate in CPAN Testers and contribute test reports, the page <http://wiki.cpantesters.org/wiki/QuickStart> has instructions for starting for either CPAN or CPANPLUS users.

If you have a certain project in mind you should check if somebody else is already working on it or if you could benefit from existing modules. Do so by posting your planned project to the PDL developers mailing list at pdl-devel@lists.sourceforge.net . See the subscription instructions in Question 3.2.  We are always looking for people to write code and/or documentation.  The Developer Guide should get you started.

First, make sure that the bug/problem you came across has not already been dealt with somewhere else in this FAQ.  Secondly, you can check the searchable archive of the PDL mailing lists to find whether this bug has already been discussed.  If you still haven't found any explanations you can post a bug report to pdl-general@lists.sourceforge.net , or through the Bugs link on <http://pdl.perl.org> .  See the Bugs file in the PDL distribution for what information to include.  If you are unsure, discussions via the perldl mailing list can be most helpful.

First make sure you have read the file INSTALL in the distribution. This contains a list of common problems which are unnecessary to repeat here.

Next, check the file perldl.conf to see if by editing the configuration options in that file you will be able to successfully build PDL. Some of the modules need additional software installed, please refer to the file DEPENDENCIES for further details. Make sure to edit the location of these packages in perldl.conf if you have them in non-standard locations.

N.B. Unix shell specific: If you would like to save an edited perldl.conf for future builds just copy it as ~/.perldl.conf into your home directory where it will be picked up automatically during the PDL build process.

Also, check for another, pre-existing version of PDL on the build system.  Multiple PDL installs in the same PATH or @INC can cause puzzling test or build failures.

If you still can't make it work properly please submit a bug report including detailed information on the problems you encountered to the perldl mailing list ( pdl-general@lists.sourceforge.net , see also above). Response is often rapid.

Most users should not have to edit any configuration files manually. However, in some cases you might have to supply some information about awkwardly placed include files/libraries or you might want to explicitly disable building some of the optional PDL modules. Check the files INSTALL and perldl.conf for details.

If you had to manually edit perldl.conf and are happy with the results you can keep the file handy for future reference. Place it in ~/.perldl.conf where it will be picked up automatically or use perl Makefile.PL  PDLCONF=your_file_name next time you build PDL.

For the basic PDL functionality you don't need any additional software.  However, some of the optional PDL modules included in the distribution (notably most graphics and some I/O modules) require certain other libraries/programs to be installed. Check the file DEPENDENCIES in the distribution for details and directions on how to get these.

To install PDL in a non-standard location, use the INSTALL_BASE option in the perl Makefile.PL configure step.  For example, perl Makefile.PL INSTALL_BASE=/mydir/perl5 will configure PDL to install into the tree rooted at /mydir/perl5.  For more details see "How do I keep my own module/library directory?" in perlfaq8 and subsequent sections.  Another alternative is to use local::lib to do the heavy lifting for the needed configuration.

To guarantee a completely clean installation of PDL, you will need to first delete the current installation files and folders.  These will be all directories named PDL in the Perl @INC path, files named *Pdlpp* in any Inline directories, and the  programs pdl, pdldoc, pdl2, perldl, and pptemplate.  Then just build and install as usual.  This is much easier to keep track of if you always install PDL into a non-standard location.  See Q: 4.4 above.

Information about binary distributions of PDL can be found on <http://pdl.perl.org> .  At present there are binary distributions  of PDL for Linux (RedHat and Debian), FreeBSD, Mac OS X and Windows,  though they might not be the most recent version.

If someone is interested in providing binary distributions for other  architectures, that would be very welcome. Let us know on the  pdl-devel@lists.sourceforge.net mailing list. Also check your Linux distribution's package manager as many now include PDL.  PPMs for win32 versions (both 32bit and 64bit) are also available.

Yes, PDL does run on Linux and indeed much of the development has been done under Linux. On <http://pdl.perl.org> you can find  links to packages for some of the major distributions. Also  check your distribution's package manager (yum, apt, urpmi, ...) as PDL is now found by many of these.

PDL builds fine on Win32 using MinGW or Microsoft compilers.  See the win32/INSTALL file in the PDL source distribution for details. Other compilers have not been tested--input is welcome.  There is also a distribution of PDL through ActiveState's ppm, though it might not always be the latest version.  PDL-2.018 builds out of the box on Strawberry Perl and ActiveState Perl and there are  distributions of Strawberry Perl with bundled PDL (see <http://strawberryperl.com/releases.html>).

No.  PDL development was conducted with a CVS repository from December 1999 to April 2009.  In April 2009 the project switched to the Git version control system (see <http://git-scm.com>).

Assume you have Git installed on your system and want to download the project source code into the directory PDL. To get read-only access to the repository, you type at the command line

   git clone git://github.com/PDLPorters/pdl

If you wish to submit changes to PDL, you should "fork" the repository from <https://github.com/PDLPorters/pdl>, then clone your fork in the normal fashion.

To become an official PDL developer, you will need to be added to the GitHub "PDLPorters" organisation.

For official PDL developers, to get read/write access to the repository type at the command line

   git clone git://github.com/PDLPorters/pdl

They can still use their own fork; at least one active developer uses that model rather than branches on the main repository.

The best way is to check <https://github.com/PDLPorters/pdl/pulls> to see if somebody has submitted a pull request related to your problem.

In addition, if you are not subscribing to the mailing list, check the archive of the pdl-devel and pdl-general mailing lists. See Question 3.2 for details.

The first thing you should do is to read the Git documentation and learn the basics about Git. There are many sources available online. It is very important that you use Git "best practice", with branches, but fortunately this is very easy! Here are the basics.

Make sure your copy is up to date with the main repo:

   git checkout master
   git pull --rebase # rebase in case you wrongly changed your own master

Make a branch:

   git checkout -b mybranch-name

Commit your changes locally:

   git add <file1> <file2> ...
   git commit

or combine these two with:

   git commit -a

Test the PDL before you push it to the main repository.  If the code is broken for you, then it is most likely broken for others. Luckily, the rest of this process will test that automatically to help you catch such errors.

Then update the shared repository with your changes:

   git push -u origin mybranch-name

This will still leave your changes on a branch, but this is good. Now go to the GitHub page, <https://github.com/PDLPorters/pdl>. It will ask you whether you want to make a "pull request" - you do. Follow the prompts. This will then initiate the automated "continuous integration" tests, on Linux and Windows, with various versions of Perl, with various compilers. You will also want to get at least one other developer to review your changes.

Once this review process is successfully completed, you can merge your changes to the master branch!

Until 2.075, "threading" was used to refer to two ideas, but that ambiguity has now been resolved by using the now (as of 2022) industry-standard term "broadcasting" for the vectorisation / array-programming concept.

• When mentioned in the INSTALL directions and possibly during the build process we have the usual computer science meaning of multi-threading in mind (useful mainly on multiprocessor machines or clusters), currently (as of 2.074) POSIX threads (see PDL::ParallelCPU).
• PDL broadcasting of operations on ndarrays (as mentioned in the indexing docs) is the iteration of a basic operation over appropriate sub-slices of ndarrays, e.g. the inner product  inner $x, $y of a (3) pdl $x and a (3,5,4) pdl  $y results in a (5,4) ndarray where each value is the result of an inner product of the (3) pdl with a (3) sub-slice of the (3,5,4) ndarray.  For details check PDL::Indexing

The connection is that broadcasting divides up independent operations that can be done in parallel.

Well, PDL scalar variables (which are instances of a particular class of Perl objects, i.e. blessed thingies (see perldoc perlobj )) are in common PDL parlance often called ndarrays (for example, check the mailing list archives).  Err, clear?  If not, simply use the term ndarray when you refer to a PDL variable (an instance of a PDL object as you might remember) regardless of what actual data the PDL variable contains.

Sometimes perldl (pdl2) is used as a synonym for PDL. Strictly speaking, however, the name perldl (pdl2) is reserved for the little shell that comes with the PDL distribution and is supposed to be used for the interactive prototyping of PDL scripts. For details check perldl or pdl2.

Just type help (shortcut = "?") at the pdl2 shell  prompt and proceed from there. Another useful command  is the apropos (shortcut = "??") command. Also try the demo command in the perldl or pdl2 shell if you are new to PDL.

See answer to the next question why the normal Perl array syntax doesn't work for ndarrays.

OK, you are right in a way. The docs say that ndarrays can be thought of arrays.  More specifically, it says ( PDL::QuickStart ):

    I find when using the Perl Data Language it is most useful
    to think of standard Perl @x variables as "lists" of generic
    "things" and PDL variables like $x as "arrays" which can be
    contained in lists or hashes.

So, while ndarrays can be thought of as some kind of multi-dimensional array they are   not arrays in the Perl sense. Rather, from the point of view of Perl they are some special class (which is currently implemented as an opaque pointer to some stuff in memory) and therefore need special functions (or 'methods' if you are using the OO version) to access individual elements or a range of elements. The functions/methods to check are  at / set (see the section 'Sections' in PDL::QuickStart ) or the powerful  slice function and friends (see PDL::Slices and  PDL::Indexing and especially PDL::NiceSlice ).

Finally, to confuse you completely, you can have Perl arrays of ndarrays, e.g. $spec[3] can refer to a pdl representing ,e.g, a spectrum, where $spec[3] is the fourth element of the Perl list (or array ;) @spec .  This may be confusing but is  very useful !

Most people will try to form new ndarrays from old ndarrays using some variation over the theme:  $x =  pdl([$y, 0, 2]).  This does work, but may not work in the way that a novice user would expect. (If $y has N dimensions then $x will have N+1 dimensions.) Other ways to concatenate ndarrays are to use the functions cat, append, and glue. Similarly you can split ndarrays using the command dog.

This question is related to the inplace function. From the documentation (see PDL::QuickStart):

    Most functions, e.g. log(), return a result which is a
    transformation of their argument. This makes for good
    programming practice. However many operations can be done
    "in-place" and this may be required when large arrays are in
    use and memory is at a premium. For these circumstances the
    operator inplace() is provided which prevents the extra copy
    and allows the argument to be modified. e.g.:
    
    $x = log($array);          # $array unaffected
    log( inplace($bigarray) ); # $bigarray changed in situ

And also from the doc !!:

    Obviously when used with some functions which can not be
    applied in situ (e.g. convolve()) unexpected effects may
    occur!

See next question on assignment in PDL.

This is caused by the fact that currently the assignment operator = allows only restricted overloading. For some purposes of PDL it turned out to be necessary to have more control over the overloading of an assignment operator. Therefore, PDL peruses the operator  .= for certain types of assignments.

In Perl 5.6.7 and higher this assignment can be made using lvalue subroutines:

    pdl> $x = sequence(5); p $x
    [0 1 2 3 4]
    pdl> $x->slice('1:2') .= pdl([5,6])
    pdl> p $x
    [0 5 6 3 4]

see PDL::Lvalue for more info.  PDL also supports a more matrix-like slice syntax via the PDL::NiceSlice module:

    pdl> $x(1:2) .= pdl([5,6])
    pdl> p $x
    [0 5 6 3 4]

With versions of Perl prior to 5.6.7 or when running under the perl debugger this has to be done using a temporary variable:

    pdl> $x = sequence(5); p $x
    [0 1 2 3 4]
    pdl> $tmp = $x->slice('1:2'); p $tmp;
    [1 2]
    pdl> $tmp .= pdl([5, 6]);    # Note .= !!
    pdl> p $x
    [0 5 6 3 4]

This can also be made into one expression, which is often seen in PDL code:

    pdl> ($tmp = $x->slice('1:2')) .= pdl([5,6])
    pdl> p $x
    [0 5 6 3 4]

Yes you can, but not in the way you probably tried first. It is not possible to use an ndarray directly in a conditional expression since this is usually poorly defined. Instead PDL has two very useful functions:  any and all . Use these to test if any or all elements in an ndarray fulfills some criterion:

    pdl> $x=pdl ( 1, -2, 3);
    pdl> print '$x has at least one element < 0' if (any $x < 0);
    $x has at least one element < 0
    
    pdl> print '$x is not positive definite' unless (all $x > 0);
    $x is not positive definite

It is a common problem that you try to make a mask array or something  similar using a construct such as

    $mask = which($ndarray > 1 && $ndarray < 2);   # incorrect

This does not work! What you are looking for is the bitwise  logical operators '|' and '&' which work on an element-by-element basis. So it is really very simple: Do not use logical operators on  multi-element ndarrays since that really doesn't make sense, instead  write the example as:

    $mask = which($ndarray > 1 & $ndarray < 2);

which works correctly.

null is a special token for 'empty ndarray'. A null pdl  can be used to flag to a PDL function that it should create  an appropriately sized and typed ndarray. Null ndarrays  can be used in places where a PDL function expects an  output or temporary argument. Output and  temporary arguments are flagged in the signature of a PDL function with the [o] and  [t] qualifiers (see next question if you don't know what  the signature of a PDL function is).  For example, you  can invoke the sumover function as follows:

    sumover $x, $y=null;

which is equivalent to

    $y = sumover $x;

If this seems still a bit murky check  PDL::Indexing and  PDL::PP for details about calling conventions, the signature and  broadcasting (see also below).

The signature of a function is an important concept in PDL. Many (but not all) PDL function have a signature which  specifies the arguments and their (minimal) dimensionality. As  an example, look at the signature of the maximum function:

    'a(n); [o] b;'

this says that maximum takes two arguments, the first of which is (at least) one-dimensional while the second one is zero-dimensional and an output argument (flagged by the [o] qualifier). If the function is called with ndarrays of higher dimension the function will be repeatedly called with slices of these ndarrays of appropriate dimension(this is called  broadcasting in PDL).

For details and further explanations consult  PDL::Indexing and PDL::PP .

The short answer is: read PDL::Objects (e.g. type  help PDL::Objects in the perldl or pdl2 shell).

The longer answer (extracted from PDL::Objects ):  Since a PDL object is an opaque reference to a C struct, it is not  possible to extend the PDL class by e.g. extra data via sub-classing  (as you could do with a hash based Perl object).  To circumvent this  problem PDL has built-in support to extend the PDL class via the  has-a relation for blessed hashes. You can get the HAS-A to behave like IS-A simply in that you assign the PDL object to the attribute named PDL and redefine the method initialize(). For example:

    package FOO;
    
    @FOO::ISA = qw(PDL);
    sub initialize {
       my $class = shift;
       my $self = {
          creation_time => time(),  # necessary extension :-)
          PDL => PDL->null,         # used to store PDL object
       };
       bless $self, $class;
    }

For another example check the script  t/subclass.t in the PDL distribution.

Dataflow is an experimental project that you don't need to concern yourself with (it should not interfere with your usual programming).  However, if you want to know, have a look at  PDL::Dataflow . There are applications which will benefit from this feature (and it is already at work behind the scenes).

Simple answer: PDL::PP is both a glue between external libraries and PDL and a concise language for writing PDL functions.

Slightly longer answer: PDL::PP is used to compile very concise definitions into XSUB routines implemented in C that can easily be called from PDL and which automatically support broadcasting, dataflow and other things without you having to worry about it.

For further details check PDL::PP and the section below on Extensions of PDL.

ndarrays behave like Perl references in many respects. So when you say

    $x = pdl [0,1,2,3];
    $y = $x;

then both $y and $x point to the same object, e.g. then saying

    $y++;

will *not* create a copy of the original ndarray but just increment in place, of which you can convince yourself by saying

    print $x;
    [1 2 3 4]

This should not be mistaken for dataflow which connects several *different* objects so that data changes are propagated between the so linked ndarrays (though, under certain circumstances, dataflowed ndarrays can share physically the same data).

It is important to keep the "reference nature" of ndarrays in mind when passing ndarrays into subroutines. If you modify the input ndarrays you modify the original argument, not a copy of it. This is different from some other array processing languages but makes for very efficient passing of ndarrays between subroutines. If you do not want to modify the original argument but rather a copy of it just create a copy explicitly (this example also demonstrates how to properly check for an explicit request to process inplace, assuming your routine can work inplace):

    sub myfunc {
       my $pdl = shift;
       if ($pdl->is_inplace) {
          $pdl->set_inplace(0)
       } else {
          # modify a copy by default
          $pdl = $pdl->copy
       }
       $pdl->set(0,0);
       return $pdl;
    }

The current versions of PDL already support quite a number of different I/O formats.  However, it is not always obvious which module implements which formats.  To help you find the right module for the format you require, here is a short list of the current list of I/O formats and a hint in which module to find the implementation:

• A home brew fast raw (binary) I/O format for PDL is implemented by the FastRaw module

• The FlexRaw module implements generic methods for the input and output of `raw' data arrays.  In particular, it is designed to read output from FORTRAN 77 UNFORMATTED files and the low-level C write function, even if the files are compressed or gzipped.

  It is possible that the FastRaw functionality will be included in the FlexRaw module at some time in the future.

• FITS I/O is implemented by the wfits/rfits functions in PDL::IO::FITS .
• ASCII file I/O in various formats can be achieved by using the  rcols and rgrep functions, also in PDL::IO::Misc .
• PDL::IO::Pic implements an interface to the NetPBM/PBM+ filters to read/write several popular image formats; also supported is output of image sequences as MPEG movies, animated GIFs and a wide variety of other video formats.
• On CPAN you can find the PDL::NetCDF module that works with PDL 2.007.

For further details consult the more detailed list in the PDL::IO documentation or the documentation for the individual modules.

Assuming all arrays are of the same size and in some format recognized by rpic (see PDL::IO::Pic ) you could say:

    use PDL::IO::Pic;
    @names = qw/name1.tif .... nameN.tif/;  # some file names
    $dummy = PDL->rpic($names[0]);
    $cube = PDL->zeroes($dummy->type,$dummy->dims,$#names+1); # make 3D ndarray
    for (0..$#names) {
        # this is the slice assignment
        ($tmp = $cube->slice(":,:,($_)")) .= PDL->rpic($names[$_]);
    }

or

    $cube(:,:,($_)) .= PDL->rpic($names[$_]);

for the slice assignment using the new PDL::NiceSlice syntax and Lvalue assignments.

The for loop reads the actual images into a temporary 2D ndarray whose values are then assigned (using the overloaded .= operator) to the appropriate slices of the 3D ndarray $cube .

The demo programs can be run most easily from the perldl or pdl2 interactive shell:

    perl -Mblib perldl  or  perl -Mblib Perldl2/pdl2

followed by demo 3d or demo 3d2 at the prompt. demo by itself will give you a list of the available PDL demos.

Questions like this should be a thing of the past with the PDL on-line help system in place. Just try (after installation):

    un*x> pdl2
    pdl> apropos trid

Check the output for promising hits and then try to look up some of them, e.g.

    pdl> help PDL::Graphics::TriD

Note that case matters with help but not with apropos .

As of 2.086, PDL's PGPLOT-using modules are now all supplied with the PGPLOT module itself.

The first stop is again perldl or pdl2 and the on-line help or the PDL documentation. There is already a lot of functionality in PDL which you might not be aware of.  The easiest way to look for functionality is to use the apropos command:

    pdl> apropos 'integral'
    ceil            Round to integral values in floating-point format
    floor           Round to integral values in floating-point format
    intover         Project via integral to N-1 dimensions
    rint            Round to integral values in floating-point format

Since the apropos command is no sophisticated search engine make sure that you search on a couple of related topics and use short phrases.

However there is a good chance that what you need is not part of the PDL distribution. You are then well advised to check out <http://pdl.perl.org> where there is a list of packages using PDL. If that does not solve your problem, ask on the mailing-list, if nothing else you might get assistance which will let you interface your package with PDL yourself, see also the next question.

Yes, you can, in fact it is very simple for many simple applications. What you want is the PDL pre-processor PP (PDL::PP ). This will allow you to make a  simple interface to your C routine.

The two functions you need to learn (at least first) are  pp_def which defines the calling interface to the function,  specifying input and output parameters, and contains the code  that links to the external library. The other command is  pp_end which finishes the PP definitions.  For details see the PDL::PP man-page, but we also have a worked  example here.

    double eight_sum(int n)
    {
         int i;
         double sum, x;
    
         sum = 0.0; x=0.0;
         for (i=1; i<=n; i++) {
           x++;
           sum += x/((4.0*x*x-1.0)*(4.0*x*x-1.0));
         } 
         return 1.0/sum;
    }

We will here show you an example of how you interface C code with PDL. This is the first example and will show you how to approximate the number 8...

The C code is shown above and is a simple function returning a double, and expecting an integer - the number of terms in the sum - as input. This function could be defined in a library or, as we do here, as an inline function.

We will postpone the writing of the Makefile till later. First we will construct the  .pd file. This is the file containing PDL::PP code. We call this  eight.pd .

    # 
    # pp_def defines a PDL function. 
    #
    pp_addhdr (
    '
    double eight_sum(int n)
    {
      int i;
      double sum, x;
    
      sum = 0.0; x=0.0;
      for (i=1; i<=n; i++) {
       x++; 
       sum += x/((4.0*x*x-1.0)*(4.0*x*x-1.0));
      }
     return 1.0/sum; 
    
    }  
    '); 
    
    pp_def (
            'eight',
         Pars => 'int a(); double [o]b();',
            Code => '$b()=eight_sum($a());'
           );
    
    # Always make sure that you finish your PP declarations with
    # pp_done
    
    pp_done();

A peculiarity with our example is that we have included the entire code with  pp_addhdr instead of linking it in. This is only for the purposes of example, in a typical application you will use  pp_addhdr to include header files. Note that the argument to  pp_addhdr is enclosed in quotes.

What is most important in this example is however the pp_def command. The first argument to this is the name of the new function  eight , then comes a hash which the real meat:

• This gives the input parameters (here  a) and the output parameters (here  b). The latter are indicated by the  [o] specifier. Both arguments can have a type specification as shown here.

  Many variations and further flexibility in the interface can be specified. See perldoc PDL::PP for details.

• This switch contains the code that should be executed. As you can see this is a rather peculiar mix of C and Perl, but essentially it is just as you would write it in C, but the variables that are passed from PDL are treated differently and have to be referred to with a preceding '$'.

  There are also simple macros to pass pointers to data and to obtain the values of other Perl quantities, see the manual page for further details.

Finally note the call to   pp_done() at the end of the file. This is necessary in all PP files.

OK. So now we have a file with code that we dearly would like to use in Perl via PDL. To do this we need to compile the function, and to do that we need a Makefile.

    use PDL::Core::Dev;
    use ExtUtils::MakeMaker;
    PDL::Core::Dev->import();
    
    $package = ["eight.pd",Eight,PDL::Eight,'',1];
    %hash = pdlpp_stdargs($package);
    
    WriteMakefile( %hash );
    
    sub MY::postamble {pdlpp_postamble($package)}

The code above should go in a file called Makefile.PL, which should subsequently be called in  the standard Perl way:  perl Makefile.PL . This should give you a Makefile and running  make should compile the module for you and  make install will install it for you.

The fifth element in the $package array-ref is true. This tells PDL to generate one C file per PP function, which with the right make options can be compiled in parallel, for a useful speedup of development / installation.

This question is closely related to the previous one, and as we said there, the  PDL::PP pre-processor is the standard way of interfacing external packages with PDL. The most usual way to use PDL::PP is to write a short interface routine, see the PDL::PP perldoc page and the answer to the previous question for examples.

However it is also possible to interface a package to PDL by re-writing your function in PDL::PP directly. This can be convenient in certain situations, in particular if you have a routine that expects a function as input and you would like to pass the function a Perl function for convenience.

The PDL::PP perldoc page is the main source of information for writing PDL::PP extensions, but it is very useful to look for files in the distribution of PDL as many of the core functions are written in PDL::PP. Look for files that end in .pd which is the generally accepted  suffix for PDL::PP files. But we also have a simple example here.

The following example will show you how to write a simple function that automatically allows broadcasting. To make this concise the example is of an almost trivial function, but the intention is to show the basics of writing a PDL::PP interface.

We will write a simple function that calculates the minimum, maximum and average of an ndarray. On my machine the resulting function is 8 times faster than the built-in function  stats (of course the latter also calculates the median).

Let's jump straight in. Here is the code (from a file called quickstats.pd )

    #
    pp_def('quickstats',
         Pars => 'a(n); [o]avg(); [o]max(); [o]min()',
         Code => '$GENERIC(a) curmax, curmin;
                  $GENERIC(a) tmp=0;
                     loop(n) %{
                       tmp += $a();
                       if (!n || $a() > curmax) { curmax = $a();}
                       if (!n || $a() < curmin) { curmin = $a();}
                     %}
                     $avg() = tmp/$SIZE(n);
                  $max() = curmax;
                  $min() = curmin;
                    '
         );
    
    pp_done();

The above might look like a confusing mixture of C and Perl, but behind the peculiar syntax lies a very powerful language. Let us take it line by line.

The first line declares that we are starting the definition of a PDL:PP function called quickstats .

The second line is very important as it specifies the input and output parameters of the function.   a(n) tells us that there is one input parameter that we will refer to as  a which is expected to be a vector of length n (likewise matrices, both square and rectangular would be written as  a(n,n) and a(n,m) respectively). To indicate that something is an output parameter we put [o] in front of their names, so referring back to the code we see that avg, max and min are three output parameters, all of which are scalar (since they have no dimensional size indicated.

The third line starts the code definition which is essentially pure C but with a couple of convenient functions.  $GENERIC is a function that returns the C type of its argument - here the input parameter a. Thus the first two lines of the code section are variable declarations.

The  loop(n) construct is a convenience function that loops over the dimension called n in the parameter section. Inside this loop we calculate the cumulative sum of the input vector and keep track of the maximum and minimum values. Finally  we assign the resulting values to the output parameters.

Finally we finish our function declaration with  pp_done() .

To compile our new function we need to create a Makefile, which we will just list since its creation is discussed in an earlier question.

    use PDL::Core::Dev;
    use ExtUtils::MakeMaker;
    PDL::Core::Dev->import();
    
    $package = ["quickstats.pd",Quickstats,PDL::Quickstats,'',1];
    %hash = pdlpp_stdargs($package);
    
    WriteMakefile( %hash );
    
    sub MY::postamble {pdlpp_postamble($package)}

An example Makefile.PL

Our new statistic function should now compile using the tried and tested Perl way:  perl Makefile.PL; make .

You should experiment with this function, changing the calculations and input and output parameters. In conjunction with the PDL::PP perldoc page this should allow you to quickly write more advanced routines directly in PDL::PP.