PDL::FAQ - Frequently asked questions about PDL
Current FAQ version: 0.6
This is version 0.6 of the PDL FAQ, a collection of frequently asked questions about PDL - the Perl Data Language.
You can find the latest version of this document at http://pdl.perl.org/faq.html . This FAQ will be monthly posted to the PDL mailing list perldl@jach.hawaii.edu .
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 someone's posting the authorship should be indicated, let the FAQ maintainer know if it isn't. For more general information explicit acknowledgement is not made in the text, but rather there is an incomplete list of contributors at the end of this docuement. Please contact the FAQ maintainer if you feel hard done by.
Send your comments, additions, suggestions or corrections to the PDL mailing list at perldl@jach.hawaii.edu or to the FAQ maintainer Jarle Brinchmann ( jarle@astro.ox.ac.uk ). See 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. $a=$b+$c can add two 2048x2048 images in only a fraction of a second.
It is hoped to eventually provide 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 ( perldl@jach.hawaii.edu , see below).
As a Perl extension (see 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-porters@jach.hawaii.edu , see 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 himself 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 language features of a proven language instead of having grown into existence from scratch defining the control structures while features were added during development (leading 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 his 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 below), a code generator/parser/pre-processor that generates PDL functions from concise descriptions.
None of the existing DLs 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. This will probably be achieved by having PDL::PP (, see 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 visualisation, surface plots via OpenGL - for instance impelmented using Mesa), graphics display capabilities and implements lots of numerical and semi-numerical algorithms.
Through the powerful pre-processor it is also easy to interface Perl to your favourite 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 Perl package you need first of all an installation of Perl on your machine. As of this writing PDL requires version 5.004 of Perl, version 5.004_4 or higher is strongly recommended. More information on where and how to get a Perl installation can be found at the Perl home page http://www.perl.com 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 and support for Xsubs the package Extutils::MakeMaker. See also http://pdl.perl.org/ports.html for a list of machines where PDL has been tested. If you don't have a compiler there might be a binary distribution availabe, 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 perldl@jach.hawaii.edu . 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. This archive 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 ftp://ftp.funet.fi . You can find a more local CPAN site by getting the file /pub/languages/perl/CPAN/MIRRORS from ftp://ftp.funet.fi . Alternatively, you can point your Web browser at http://www.perl.com and use its CPAN multiplex service. Within CPAN you find the latest released version of PDL in the directory CPAN/modules/by-module/PDL/. Another site that has the latest PDL distribution is http://pdl.perl.org . Thanks to the efforts of Frossie ( frossie@jach.hawaii.edu ) there is now a mirror site in the US at http://www.jach.hawaii.edu/~frossie/pdl-mirror/
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. If you have PDL installed on your machine and are on a unix like system then you can read the PDL manuals with the man command. man PDL::Intro will lead the way to other PDL manual pages. In any case (i.e. also on non-unixes) perldoc PDL::Intro should work.
man
man PDL::Intro
perldoc PDL::Intro
The easiest way by far, however, to get familiar with PDL is to use the PDL online help facility from within the perldl shell. Just type perldl at your system prompt. Once you are inside the perldl 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 perldl session of a PDL beginner (lengthy output is only symbolically reproduced in braces ( < ... ... > )):
perldl
help
apropos
unix> perldl perldl> help <.... help output ....> perldl> help PDL::Impatient <.... man page ....> perldl> $a = pdl (1,5,7.3,1.0) perldl> $b = sequence float, 4, 4 perldl> help inner <.... help on the 'inner' function ....> perldl> $c = inner $a, $b perldl> 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. A good point to start is http://www.perl.com .
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
Online 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).
Thanks to the efforts of Frossie ( frossie@jach.hawaii.edu ) there is now a mirror site in the US at http://www.jach.hawaii.edu/~frossie/pdl-mirror/ If you are interested in PDL in general you can join the PDL mailing list perldl@jach.hawaii.edu . This is a forum to discuss programming issues in PDL, report bugs, seek assistance with PDL related problems, etc. To subscribe, send a message to perldl-request@jach.hawaii.edu containing a string in the following format:
subscribe me@my.email.address
where you should replace the string me@my.email.address with your email address. Past messages can be retrieved in digest format by anonymous ftp from ftp://ftp.jach.hawaii.edu/pub/ukirt/frossie/pdlp/ . A searchable archive and a hypertext version of the traffic on this list can be found at http://www.xray.mpe.mpg.de/mailing-lists/perldl/ .
If you are interested in all the technical details of the ongoing PDL development you can join the PDL developers mailing list pdl-porters@jach.hawaii.edu . To subscribe, send a message to pdl-porters-request@jach.hawaii.edu containing a string in the following format:
where you should replace the string me@my.email.address with your email address. Past messages can be retrieved in digest format by anonymous ftp from ftp://ftp.jach.hawaii.edu/pub/ukirt/frossie/pdlp/ . A searchable archive and a hypertext version of the traffic on this list can be found at http://www.xray.mpe.mpg.de/mailing-lists/pdl-porters/ .
Crossposting between these lists should be avoided unless there is a very good reason for doing that.
As of this writing (FAQ version 0.6 of 01/06/2000 ) the latest released version is 2.006 . The latest versions should always be available from a CPAN mirror site near you (see above for info on where to get PDL).
The most current version of PDL can be obtained from the CVS repository see ""CVS availability of PDL"" below.
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-porters@jach.hawaii.edu . To subscribe, send a message to pdl-porters-request@jach.hawaii.edu containing a string in the following format:
where you should replace the string me@my.email.address with your email address. You can also read past and current mails in the searchable hypertext version of the mailing list at http://www.xray.mpe.mpg.de/mailing-lists/pdl-porters/ . We are always looking for people to write code and/or documentation ;).
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 list at whether this bug has already been discussed. If you still haven't found any explanations you can post a bug report to perldl@jach.hawaii.edu .
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.
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.
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 ( perldl@jach.hawaii.edu , 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 akwardly 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.
perl Makefile.PL PDLCONF=your_file_name
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.
Error: PL_na not declared
You have probably upgraded perl to 5.6 and tried to recompile an old version of PDL. The solution to this problem is to upgrade to a version ( > 2.005) which should have this fixed.
If the latest version of PDL does not fix this problem for you, and you have made sure your old installation is not interfering, you should post a message to the mailing-list.
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 and Windows. If someone is interested in providing binary distributions for other architectures, that would be very welcome. Let us know on the pdl-porters@jach.hawaii.edu mailing list.
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 Debian packages, as well as the more actively updated RedHat packages. These should also work with Mandrake, and can possibly be converted to Debian using alien .
alien
To some extent is probably the fairest answer. There is no official effort to port PDL to Windows with each release of the software, and a volunteering effort would be much appreciated. However a port of ( 2.001 ) does already exist thanks to Christian Soeller. A main worry on Windows platforms is the lack of a good graphics interface, any help with this would be very welcome.
It is also important to note that there is no distribution of PDL through ActiveState's ppm. Such a compilation would be very welcome!
Yes, as of December 1999, PDL is available at the CVS repository on http://www.sourceforge.net . The tree is updated by developers who have accounts on Sourceforge and snapshots of the tree are released regularly by the pumpkin holder (the pumpking).
If you wish to access the CVS repository and install PDL from there all you need are two simple commands, however make sure you read some of the documentation on Sourceforge as well for full information, but the basic command is:
cvs -d:pserver:anonymous@cvs.PDL.sourceforge.net:/cvsroot/PDL login cvs -z3 -d:pserver:anonymous@cvs.PDL.sourceforge.net:/cvsroot/PDL co PDL
When prompted for a password just press the Enter key. Note however that the CVS tree is to be considered a development release and as such you are very welcome to try it out, but it is not recommended for mission critical use and might crash unexpectedly.
The Sourceforge system contains a patch-manager which contains patches that have not yet been applied to the distribution. This can be accessed by first accessing the Sourceforge web site and search for PDL. This will show you the project page for PDL and will give you access to the Patch manager.
In addition, if you are not subscribing to the mailinglist, check the archive of the pdl-porters and perldl mailing lists.
pdl-porters
The first you should do is to read the Sourceforge documentation and learn the basics about CVS. But assuming you know this here is a quick intro from Karl Glazebrook:
Delete your entire CVS directory structure and START AGAIN (there is state) In a clean directory: setenv CVS_RSH ssh setenv CVSROOT kgb@cvs.PDL.sourceforge.net:/cvsroot/PDL cvs co PDL You will need to type your password. every time you issue a cvs command. there is no way around this if you use non-anon access and you can't mix the two. Howevery cvs committs will now work and write back to the server. You will continue to have to type your password until you upload a key to the sourcefourve web page. Once you have done this it becomes painless.
Unfortunately, in the context of PDL the term threading can have two different (but related) meanings:
When mentioned in the INSTALL directions and possible during the build process we have the usual computer science meaning of multithreading in mind (useful mainly on multiprocessor machines or clusters)
PDL threading of operations on piddles (as mentioned in the indexing docs) is the iteration of a basic operation over appropriate subslices of piddles, e.g. the inner product inner $a, $b of a (3) pdl $a and a (3,5,4) pdl $b results in a (5,4) piddle where each value is the result of an inner product of the (3) pdl with a (3) subslice of the (3,5,4) piddle. For details check "PDL::Indexing"
inner $a, $b
$a
$b
PDL threading leads naturally to potentially parallel code which can make use of multithreading on multiprocessor machines/networks; there you have the connection between the two types of use of the term.
(;)
Well, PDL scalar variables (which are instances of a particular class of perl objects, i.e. blessed thingies (see "man perlobj" )) are in common PDL parlance often called piddles (for example, check the mailing list archives). Err, clear? If not, simply use the term piddle 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 is used as a synonym for PDL. Strictly speaking, however, the name perldl 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 the perldl man page.
Just type help (shortcut = "?") at the perldl prompt and proceed from there. Another useful command is the apropos (shortcut = "??") command.
Also try the demo command in the perldl shell if you are new to PDL.
demo
See answer to the next question why the normal perl array syntax doesn't work for pdls.
Ok, you are right in a way. The docs say that pdls can be thought of arrays. More specifically, it says ( "PDL::Impatient" ):
I find when using perlDL 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 pdls 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::Impatient" ) or the powerful slice function and friends (see "PDL::Slices" and "PDL::Indexing" ).
at
set
slice
Finally, to confuse you completely, you can have perl arrays of plds, 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 !
@spec
Most people will try to form new piddles from old piddles using some variation over the theme: $a = pdl([$b, 0, 2]) , but this does not work. The way to concatenate piddles is to use the function cat . Similarly you can split piddles using the command dog .
$a = pdl([$b, 0, 2])
cat
dog
This question is related to the inplace function. From the documentation (see "PDL::Impatient" manpage):
inplace
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!
Check the list of PDL functions at the end of PDL.pod which points out inplace -safe functions.
.=
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.
=
With versions of Perl prior to 5.6 this has to be done using a temporary variable.
perldl> $a = sequence(5); p $a [0 1 2 3 4] perldl> $tmp = $a->slice('1:2'); p $tmp; [1 2] perldl> $tmp .= pdl([5, 6]); # Note .= !! perldl> p $a [0 5 6 3 4]
This can also be made into one expression, which is often seen in PDL code:
perldl> ($tmp = $a->slice('1:2')) .= pdl([5,6]) perldl> p $a [0 5 6 3 4]
In Perl 5.6 this assignment can be simplified using lvalue subroutines, and this will be incorporated into PDL when 5.6 is more widespread.
Yes you can, but not in the way you probably tried first. It is not possible to use a piddle 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 a piddle fulfils some criterion:
any
all
perldl> $a=pdl ( 1, -2, 3); perldl> print '$a has at least one element < 0' if (any $a < 0); $a has at least one element < 0 perldl> print '$a is not positive definite' unless (all $a > 0); $a 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
$mask = which($piddle > 1 && $piddle < 2);
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 logial operators on multi-element piddles since that really doesn't make sense, instead write the example as:
$mask = which($piddle > 1 & $piddle < 2);
which works correctly.
null is a special token for 'empty piddle'. A null pdl can be used to flag to a PDL function that it should create an appropriately sized and typed piddle. Null piddles 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:
null
[o]
[t]
sumover
sumover $a, $b=null;
which is equivalent to
$b = sumover $a;
If this seems still a bit murky check "PDL:Indexing" and "PDL::PP" for details about calling conventions, the signature and threading (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:
maximum
'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 pdls of higher dimension the function will be repeatedly called with slices of these pdls of appropriate dimension(this is called threading 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 shell).
help PDL::Objects
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 subclassing (as you could do with a hash based perl object). To circumvent this problem PDL has built-in support to extent the PDL class via the has-a relation for blessed hashes. You can get the HAS-A behave like IS-A simply in that you assign the PDL object to the attribute named PDL and redefine the method initialize(). For example:
PDL
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 threading, dataflow and other things without you having to worry about it.
For further details check "PDL::PP" and the section on "Extensions of PDL".
Piddles behave like perl references in many respects. So when you say
$a = pdl [0,1,2,3]; $b = $a;
then both $b and $a point to the same object, e.g. then saying
$b++;
will *not* create a copy of the original piddle but just increment in place, of which you can convince yourself by saying
print $a; [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 piddles (though, under certain circumstances, dataflown piddles can share physically the same data).
It is important to keep the " reference nature " of piddles in mind when passing piddles into subroutines. If you modify the input pdls 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 piddles 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::Misc.
Ascii file I/O in various formats can be achieved by using the rcols and rgrep functions, also in PDL::IO::Misc.
rcols
rgrep
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.
On CPAN you can find the PDL-NetCDF module that works with the current released version of PDL 2.004.
For further details consult the documentation in the individual modules.
Assuming all arrays are of the same size and in some format recognised 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 piddle for (0..$#names) {($tmp = $cube->slice(":,:,($_)")) .= PDL->rpic($names[$_])}
The for loop reads the actual images into a temporary 2D piddle whose values are then assigned (using the overloaded .= operator) to the approriate slices of the 3D piddle $cube .
$cube
This answer applies mainly to PDL::Graphics::TriD (PDL's device independent 3D graphics model) which is the trickiest one in this respect. You find some test scripts in Demos/TriD in the distribution. After you have built PDL just change to that directory and try
perl -Mblib <testfile>
where < testfile > ; should match the pattern test[0-9].p and watch the results. Some of the tests should bring up a window where you can control (twiddle) the 3D objects with the mouse. Try using MB1 for turning the objects in 3D space and MB3 to zoom in and out.
< testfile
test[0-9].p
If you have a VRML viewer plugin for netscape you can also try tvrml*.p for PDL generated dynamic VRML.
tvrml*.p
Some demos of 3D graphics with PDL can also be invoked using the demo command within the perldl shell.
Questions like this should be a thing of the past with the PDL online help system in place. Just try (after installation):
un*x> perldl perldl> apropos trid
Check the output for promising hits and then try to look up some of them, e.g.
perldl> help PDL::Graphics::TriD
Note that case matters with help but not with apropos .
The first stop is again perldl or the PDL documentation. There is already a lot of functionality in PDL which you might be aware of. The easiest way to look for functionality is to use the apropos command:
perldl> 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-prosessor 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.
pp_def
pp_end
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 .
.pd
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($a());' ); # Always make sure that you finish your PP declarations with # pp_done pp_done();
A peculiarity with our example is that we have included the entire code with pp_addhdr instead of linking it in. This is only for the purposes of example, in a typical application you will use pp_addhdr to include header files. Note that the argument to pp_addhdr is enclosed in quotes.
pp_addhdr
What is most important in this example is however the pp_def command. The first argument to this is the name of the new function eight , then comes a hash which the real meat:
This gives the input parameters (here a ) and the output parameters (here b ). The latter are indicated by the [o] specifier. Both arguments can have a type specification as shown here.
a
b
Many variations and further flexibility in the interface can be specified. See the manpage for details.
This switch contains the code that should be executed. As you can see this is a rather peculiar mix of C and Perl, but essentially it is just as you would write it in C, but the variables that are passed from PDL are treated differently and have to be referred to with a preceding '$'.
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.
pp_done()
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(); $package = ["eight.pd",Eight,PDL::Eight]; %hash = pdlpp_stdargs($package); WriteMakefile( %hash ); sub MY::postamble {pdlpp_postamble($package)};
The code above should go in a file called Makefile.PL, which should subsequently be called in the standard Perl way: perl Makefile.PL . This should give you a Makefile and running make should compile the module for you and make install will install it for you.
perl Makefile.PL
make
make install
This question is closely related to the previous one, and as we said there, the "PDL::PP" pre-processor is the standard way of interfacing external packages with PDL. The most usual way to use PDL::PP is to write a short interface routine, see the "PDL::PP" manpage and the answer to the previous question for examples.
However it is also possible to interface a package to PLD by re-writing your function in PDL::PP directly. This can be convenient in certain situations, in particular if you have a routine that expects a function as input and you would like to pass the function a Perl function for convenience.
The "PDL::PP" manpage is the main source of information for writing PDL::PP extensions, but it is very useful to look for files in the distribution of PDL as many of the core functions are written in PDL::PP. Look for files that end in .pd which is the generally accepted suffix for PDL::PP files. But we also have a simple example here
The following example will show you how to write a simple function that automatically allows threading. To make this concise the example is of an almost trivial function, but the intention is to show the basics of writing a PDL::PP interface.
We will write a simple function that calculates the minimum, maximum and average of a piddle. On my machine the resulting function is 8 times faster than the built-in function stats (of course the latter also calculates the median).
stats
Let's jump straight in. Here is the code (from a file called quickstats.pd )
quickstats.pd
# pp_def('quickstats', Pars => 'a(n); [o]avg(); [o]max(); [o]min()', Code => '$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 .
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.
a(n)
a(n,n)
a(n,m)
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.
$GENERIC
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.
loop(n)
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(); $package = ["quickstats.pd",Quickstats,PDL::Quickstats]; %hash = pdlpp_stdargs($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 .
perl Makefile.PL; make
You should experiment with this function, changing the calculations and input and output parameters. In conjunction with the PDL::PP manpage this should allow you to quickly write more advanced routines directly in PDL::PP.
markers for alpha stage functionality removed
restructured description
development/support of PDL
PDL and online help
subclassing piddles
new INSTALLATION section
how to stack 2D piddles - > 3D piddle
questions regarding TriD
use of perl5.004 is now required
PDL I/O formats
piddles behave like perl references
null PDL's and output arguments
signature
questions about pdls and perl array syntax
added requirement for C compiler in answer to 'what machines...' question
PDL jargon section
piddles
upgraded released/alpha version numbers
added another WYANDL reason
split into perldl/pdl-porters mailing lists
initial revision
If you find any inaccuracies in this document (or disfunctional URLs) please report to the perldl mailing list perldl@jach.hawaii.edu or to the current FAQ maintainer Jarle Brinchmann ( jarle@astro.ox.ac.uk ).
Achim Bohnet ( ach@mpe.mpg.de ) for suggesting CoolHTML as a prettypodder (although we have switched to XML now) and various other improvements. Suggestions for some questions were taken from Perl Faq and adapted for PDL.
Many people have contributed or given feedback on the current version of the FAQ, here is an incomplete list of individuals whose contributions or posts to the mailing-list have improved this FAQ at some point in time alphabetically listed by first name: Christian Soeller, Doug Burke, Doug Hunt, Frank Schmauder, Jarle Brinchmann, John Cerney, Karl Glazebrook, Kurt Starsinic, Thomas Yengst, Tuomas J. Lukka.
This document emerged from a joint effort of several PDL developers (Karl Glazebrook ( kgb@aaoepp.aao.gov.au ), Tuomas J. Lukka ( lukka@iki.fi ), Christian Soeller ( c.soeller@auckland.ac.nz )) to compile a list of the most frequently asked questions about PDL with answers. Permission is granted for verbatim copying (and formatting) of this material as part of PDL. Permission is explicitly not granted for distribution in book or any corresponding form. Email the current FAQ maintainer Jarle Brinchmann ( jarle@astro.ox.ac.uk ) or ask on the PDL mailing list perldl@jach.hawaii.edu if some of the issues covered in here are unclear.
To install PDL, copy and paste the appropriate command in to your terminal.
cpanm
cpanm PDL
CPAN shell
perl -MCPAN -e shell install PDL
For more information on module installation, please visit the detailed CPAN module installation guide.