PDL::G...:Scilab(3pm)
PDL::G...:Scilab(3pm) — User Contributed Perl Documentation ✨
okay so bestie, welcome to the manual for PDL::Guide::Migration::Scilab (aka the PDL::G...:Scilab(3pm) page). This is your glow-up guide from Scilab to PDL, and it's giving main character energy. 💅
NAME 💫
PDL::Guide::Migration::Scilab — a guide for Scilab users. periodt. 🫶
INTRODUCTION 🌸
If you're a Scilab user, this page is literally for you. It explains the key differences between Scilab and PDL so you can get going as quickly as possible. No cap.
This document is not a tutorial. For that, go to PDL::QuickStart. This doc complements the Quick Start guide, because it highlights the key differences between Scilab and PDL. iykyk.
Perl 🐪
The key difference between Scilab and PDL is Perl.
Perl is a general purpose programming language with thousands of modules freely available on the web. PDL is an extension of Perl. This gives PDL programs access to more features than most numerical tools can dream of. At the same time, most syntax differences between Scilab and PDL are a result of its Perl foundation.
You do not have to learn much Perl to be effective with PDL. But if you wish to learn Perl, there is excellent documentation available on-line (http://perldoc.perl.org) or through the command perldoc perl. There is also a beginner's portal (http://perl-begin.org).
Perl's module repository is called CPAN (http://www.cpan.org) and it has a vast array of modules. Run perldoc cpan for more information.
TERMINOLOGY: NDARRAY 🔢
Scilab typically refers to vectors, matrices, and arrays. Perl already has arrays, and the terms "vector" and "matrix" typically refer to one- and two-dimensional collections of data. Having no good term to describe their object, PDL developers coined the term ndarray to give a name to their data type.
An ndarray consists of a series of numbers organized as an N-dimensional data set. ndarrays provide efficient storage and fast computation of large N-dimensional matrices. They are highly optimized for numerical work. slay.
For more information, see "ndarrays vs Perl Arrays" later in this document.
COMMAND WINDOW AND IDE 🖥️
PDL does not come with a dedicated IDE. It does however come with an interactive shell and you can use a Perl IDE to develop PDL programs.
PDL interactive shell 🐚
To start the interactive shell, open a terminal and run perldl. As in Scilab, the interactive shell is the best way to learn the language. To exit the shell, type exit, just like Scilab. bye bestie 👋
Writing PDL programs ✍️
One popular IDE for Perl is called Padre (http://padre.perlide.org). It is cross platform and easy to use.
Whenever you write a stand-alone PDL program (i.e. outside the perldl shell) you must start the program with use PDL;. This command imports the PDL module into Perl. Here is a sample PDL program:
use PDL; # Import main PDL module.
use PDL::NiceSlice; # Import additional PDL module.
$y = pdl [2,3,4]; # Statements end in semicolon.
$A = pdl [ [1,2,3],[4,5,6] ]; # 2-dimensional ndarray.
print $A x $y->transpose;Save this file as myprogram.pl and run it with:
perl myprogram.plNew: Flexible syntax 🆕
In very recent versions of PDL (version 2.4.7 or later) there is a flexible matrix syntax that can look extremely similar to Scilab:
- Use a
;to delimit rows:
$y = pdl q[ 2,3,4 ];
$A = pdl q[ 1,2,3 ; 4,5,6 ];- Use spaces to separate elements:
$y = pdl q[ 2 3 4 ];
$A = pdl q[ 1 2 3 ; 4 5 6 ];Basically, as long as you put a q in front of the opening bracket, PDL should "do what you mean". So you can write in a syntax that is more comfortable for you. obsessed.
A MODULE FOR SCILAB USERS 🧩
Here is a module that Scilab users will want to use:
PDL::NiceSlice
Gives PDL a syntax for slices (sub-matrices) that is shorter and more familiar to Scilab users.
// Scilab
b(1:5) --> Selects the first 5 elements from b.
# PDL without NiceSlice
$y->slice("0:4") --> Selects the first 5 elements from $y.
# PDL with NiceSlice
$y(0:4) --> Selects the first 5 elements from $y.BASIC FEATURES 🌟
This section explains how PDL's syntax differs from Scilab. Most Scilab users will want to start here.
General "gotchas" 😅
Indices 🔢
In PDL, indices start at '0' (like C and Java), not 1 (like Scilab). For example, if $y is an array with 5 elements, the elements would be numbered from 0 to 4.
Displaying an object 👀
Scilab normally displays object contents automatically. In PDL you display objects explicitly with the print command or the shortcut p:
Scilab:
--> a = 12
a = 12.
--> b = 23; // Suppress output.
-->PerlDL:
pdl> $x = 12 # No output.
pdl> print $x # Print object.
12
pdl> p $x # "p" is a shorthand for "print" in the shell.
12Creating ndarrays 🛠️
Variables in PDL 💲
Variables always start with the $ sign.
Scilab: value = 42
PerlDL: $value = 42Basic syntax 📝
Use the pdl constructor to create a new ndarray.
Scilab: v = [1,2,3,4]
PerlDL: $v = pdl [1,2,3,4]
Scilab: A = [ 1,2,3 ; 3,4,5 ]
PerlDL: $A = pdl [ [1,2,3] , [3,4,5] ]Simple matrices 🔢
Here's the vibe for basic matrices:
- Matrix of ones — Scilab:
ones(5,5)✨ PDL:ones 5,5 - Matrix of zeros — Scilab:
zeros(5,5)✨ PDL:zeros 5,5 - Random matrix — Scilab:
rand(5,5)✨ PDL:random 5,5 - Linear vector — Scilab:
1:5✨ PDL:sequence 5
Notice that in PDL the parenthesis in a function call are often optional. It is important to keep an eye out for possible ambiguities. For example:
pdl> p zeros 2, 2 + 2Should this be interpreted as zeros(2,2) + 2 or as zeros 2, (2+2)? Both are valid statements:
pdl> p zeros(2,2) + 2
[
[2 2]
[2 2]
]
pdl> p zeros 2, (2+2)
[
[0 0]
[0 0]
[0 0]
[0 0]
]Rather than trying to memorize Perl's order of precedence, it is best to use parentheses to make your code unambiguous. fr fr.
Linearly spaced sequences 📏
Scilab: --> linspace(2,10,5)
ans = 2. 4. 6. 8. 10.
PerlDL: pdl> p zeroes(5)->xlinvals(2,10)
[2 4 6 8 10]Explanation: Start with a 1-dimensional ndarray of 5 elements and give it equally spaced values from 2 to 10.
Scilab has a single function call for this. On the other hand, PDL's method is more flexible:
pdl> p zeros(5,5)->xlinvals(2,10)
[
[ 2 4 6 8 10]
[ 2 4 6 8 10]
[ 2 4 6 8 10]
[ 2 4 6 8 10]
[ 2 4 6 8 10]
]
pdl> p zeros(5,5)->ylinvals(2,10)
[
[ 2 2 2 2 2]
[ 4 4 4 4 4]
[ 6 6 6 6 6]
[ 8 8 8 8 8]
[10 10 10 10 10]
]
pdl> p zeros(3,3,3)->zlinvals(2,6)
[
[
[2 2 2]
[2 2 2]
[2 2 2]
]
[
[4 4 4]
[4 4 4]
[4 4 4]
]
[
[6 6 6]
[6 6 6]
[6 6 6]
]
]Slicing and indices ✂️
Extracting a subset from a collection of data is known as slicing. The PDL shell and Scilab have a similar syntax for slicing, but there are two important differences:
- PDL indices start at 0, as in C and Java. Scilab starts indices at 1.
- In Scilab you think "rows and columns". In PDL, think "x and y".
Scilab PerlDL
------ ------
--> A pdl> p $A
A = [
1. 2. 3. [1 2 3]
4. 5. 6. [4 5 6]
7. 8. 9. [7 8 9]
]
-------------------------------------------------------
(row = 2, col = 1) (x = 0, y = 1)
--> A(2,1) pdl> p $A(0,1)
ans = [
4. [4]
]
-------------------------------------------------------
(row = 2 to 3, col = 1 to 2) (x = 0 to 1, y = 1 to 2)
--> A(2:3,1:2) pdl> p $A(0:1,1:2)
ans = [
4. 5. [4 5]
7. 8. [7 8]
]Warning ⚠️
When you write a stand-alone PDL program you have to include the PDL::NiceSlice module. See the previous section "MODULES FOR SCILAB USERS" for more information.
use PDL; # Import main PDL module.
use PDL::NiceSlice; # Nice syntax for slicing.
$A = random 4,4;
print $A(0,1);Matrix Operations 🧮
Matrix multiplication ✖️
Scilab: A * B
PerlDL: $A x $BElement-wise multiplication ✖️
Scilab: A .* B
PerlDL: $A * $BTranspose 🔄
Scilab: A'
PerlDL: $A->transposeFunctions that aggregate data 📊
Some functions (like sum, max and min) aggregate data for an N-dimensional data set. Scilab and PDL both give you the option to apply these functions to the entire data set or to just one dimension.
Scilab — In Scilab, these functions work along the entire data set by default, and an optional parameter r or c makes them act over rows or columns.
--> A = [ 1,5,4 ; 4,2,1 ]
A = 1. 5. 4.
4. 2. 1.
--> max(A)
ans = 5
--> max(A, "r")
ans = 4. 5. 4.
--> max(A, "c")
ans = 5.
4.PDL — PDL offers two functions for each feature.
sum vs sumover
avg vs average
max vs maximum
min vs minimumThe long name works over a dimension, while the short name works over the entire ndarray.
pdl> p $A = pdl [ [1,5,4] , [4,2,1] ]
[
[1 5 4]
[4 2 1]
]
pdl> p $A->maximum
[5 4]
pdl> p $A->transpose->maximum
[4 5 4]
pdl> p $A->max
5Higher dimensional data sets 🌈
okay this one's a whole vibe shift, bestie. It's all about how Scilab and PDL think about higher-dimensional data differently.
Scilab was designed for 1D vectors and 2D matrices, and then higher-dimensional stuff got bolted on top later. PDL, meanwhile, was built for N-dimensional ndarrays from day one. So you get a few lil surprises in Scilab that just… don't happen in PDL. 🤷♀️
Scilab sees a vector as a 2D matrix.
Scilab PerlDL
------ ------
--> vector = [1,2,3,4]; pdl> $vector = pdl [1,2,3,4]
--> size(vector) pdl> p $vector->dims
ans = 1 4 4So Scilab looks at [1,2,3,4] and goes "ah yes, a 2D matrix, 1x4." PDL looks at the same thing and goes "that's a 1D vector, babes — a single dimension of size 4." 💅
But Scilab ignores the last dimension of a 4x1x1 matrix.
Scilab PerlDL
------ ------
--> A = ones(4,1,1); pdl> $A = ones 4,1,1
--> size(A) pdl> p $A->dims
ans = 4 1 4 1 1And Scilab treats a 4x1x1 matrix differently from a 1x1x4 matrix.
Scilab PerlDL
------ ------
--> A = ones(1,1,4); pdl> $A = ones 1,1,4
--> size(A) pdl> p $A->dims
ans = 1 1 4 1 1 4Scilab has no direct syntax for N-D arrays.
pdl> $A = pdl [ [[1,2,3],[4,5,6]], [[2,3,4],[5,6,7]] ]
pdl> p $A->dims
3 2 2Feature support.
In Scilab, lowkey a bunch of features just don't exist for N-D arrays. In PDL? Basically anything that works on 1D and 2D ndarrays works exactly the same on N-dimensional ndarrays. There's usually no distinction at all:
Scilab PerlDL
------ ------
--> A = ones(3,3,3); pdl> $A = ones(3,3,3);
--> A' pdl> transpose $A
=> ERROR => OKLoop Structures 🔁
Perl has so many loop structures, but we're only gonna show you the one that feels most familiar if you come from Scilab:
Scilab PerlDL
------ ------
for i = 1:10 for $i (1..10) {
disp(i) print $i
end }NOTE: Never, ever use for-loops for numerical work. Perl's for-loops are faster than Scilab's, sure, but they both pale next to a "vectorized" operation. PDL has a ton of tools that make writing vectorized programs easy. Those are beyond the scope of this guide, but if you wanna learn more, go look at:PDL::Indexing,PDL::Broadcasting, andPDL::PP.
Also: likewise, never use1..10for numerical work either, even outside a for-loop.1..10is a Perl array. Perl arrays are designed for flexibility, not speed. Use ndarrays instead. Want the tea on that? It's literally the next section. 🫖
ndarrays vs Perl Arrays 🍓
It's super important to clock the difference between an ndarray and a Perl array. Perl has a general-purpose array object that can hold any type of element:
@perl_array = 1..10;
@perl_array = ( 12, "Hello" );
@perl_array = ( 1, 2, 3, \@another_perl_array, sequence(5) );Perl arrays let you build powerful data structures (see Data structures below), but they are not designed for numerical work. For that, use ndarrays:
$pdl = pdl [ 1, 2, 3, 4 ];
$pdl = sequence 10_000_000;
$pdl = ones 600, 600;For example:
$points = pdl 1..10_000_000 # 4.7 seconds
$points = sequence 10_000_000 # millisecondsTIP: You can use underscores in numbers (10_000_000reads better than10000000). 💖
Conditionals 🤔
Perl has a bunch of conditionals too, but we're only gonna show the one that's most familiar to Scilab girlies:
Scilab PerlDL
------ ------
if value > MAX if ($value > $MAX) {
disp("Too large") print "Too large\n";
elseif value < MIN } elsif ($value < $MIN) {
disp("Too small") print "Too small\n";
else } else {
disp("Perfect!") print "Perfect!\n";
end }NOTE: Here's a lil "gotcha" for you:text Scilab: elseif PerlDL: elsifIf your conditional is throwing a syntax error, double-check that you spelled yourelsif's right. it's giving sneaky. 😭
TIMTOWDI (There Is More Than One Way To Do It) ✨
One of the most interesting differences between PDL and other tools is just how expressive the Perl language is. TIMTOWDI — "There Is More Than One Way To Do It" — is literally Perl's motto. 👑
Perl was written by a linguist, and one of its defining properties is that statements can be formulated in different ways to give the language a more natural feel. Like, you're unlikely to say to a friend:
"While I am not finished, I will keep working."
Human language is more flexible than that. Instead, you'd probably say:
"I will keep working until I am finished."
Because of its linguistic roots, Perl is the only programming language with this sort of flexibility. For example, Perl has traditional while-loops and if-statements:
while ( ! finished() ) {
keep_working();
}
if ( ! wife_angry() ) {
kiss_wife();
}But it also offers the alternative until and unless statements:
until ( finished() ) {
keep_working();
}
unless ( wife_angry() ) {
kiss_wife();
}And Perl lets you write loops and conditionals in "postfix" form:
keep_working() until finished();
kiss_wife() unless wife_angry();So in this way, Perl often lets you write more natural, easy-to-understand code than is possible in more restrictive programming languages. slay. 💅
Functions 🧚
PDL's syntax for declaring functions is wildly different from Scilab's:
Scilab PerlDL
------ ------
function retval = foo(x,y) sub foo {
retval = x.**2 + x.*y my ($x, $y) = @_;
endfunction return $x**2 + $x*$y;
}Don't be intimidated by all the new syntax, bestie — here's a quick run-through of a function declaration in PDL: 🫶
substands for "subroutine".mydeclares variables to be local to the function.@_is a special Perl array that holds all the function parameters. This might seem like a strange way to do functions, but it lets you make functions that take a variable number of parameters. For example, the following function takes any number of parameters and adds them all together:
sub mysum {
my ($i, $total) = (0, 0);
for $i (@_) {
$total += $i;
}
return $total;
}- You can assign values to several variables at once using the syntax:
($x, $y, $z) = (1, 2, 3);So, in the previous examples:
# This declares two local variables and initializes them to 0.
my ($i, $total) = (0, 0);
# This takes the first two elements of @_ and puts them in $x and $y.
my ($x, $y) = @_;- The
returnstatement gives the return value of the function, if any.
💖 ADDITIONAL FEATURES 💖
okay bestie, this is the bonus round — the lil extras that make PDL hit different. get comfy. 🌸
🧺 Data structures
so Scilab builds its fancy data structures out of lists and structs, right? and literally, Perl's arrays and hashes do the exact same job. this section is just a lil snack-sized overview of what Perl has going on. wanna go deeper? be my guest: <http://perldoc.perl.org/perldata.html> or just run perldoc perldata. 💅
Arrays
Perl arrays are giving Scilab's lists, fr fr — both are sequential data structures that can hold absolutely any data type. no cap. ✨
Scilab:
list( 1, 12, "hello", zeros(3,3) , list( 1, 2) );PerlDL:
@array = ( 1, 12, "hello" , zeros(3,3), [ 1, 2 ] )not me pointing out that Perl arrays start with the @ prefix instead of the $ that ndarrays use 👀 iconic little sigil moment.
to actually learn Perl arrays, go to <http://perldoc.perl.org/perldata.html> or run the command perldoc perldata. 🫶
Hashes
Perl hashes are lowkey the same vibe as Scilab's structure arrays. slay.
Scilab:
--> drink = struct('type', 'coke', 'size', 'large', 'myarray', ones(3,3,3))
--> drink.type = 'sprite'
--> drink.price = 12 // Add new field to structure array.PerlDL:
pdl> %drink = ( type => 'coke' , size => 'large', myndarray => ones(3,3,3) )
pdl> $drink{type} = 'sprite'
pdl> $drink{price} = 12 # Add new field to hash.and yes, notice how hashes start with the % prefix instead of the @ for arrays and the $ for ndarrays. three whole sigils. main character energy tbh. 👑
to learn about Perl hashes, please go to <http://perldoc.perl.org/perldata.html> or run the command perldoc perldata.
⚡ Performance
PDL has powerful performance features, some of which you just don't normally get in numerical computation tools. the following pages will walk you through them. let's gooo 🔥
PDL::Indexing
Level: Beginner
this beginner tutorial covers the standard "vectorization" feature that you already know from Scilab. use this page to learn how to avoid for-loops and make your program more efficient. periodt.
PDL::Broadcasting
Level: Intermediate
PDL's "vectorization" feature goes beyond what most numerical software can even do. in this tutorial you'll learn how to "broadcast" over higher dimensions, which lets you vectorize your program further than is possible in Scilab. it's giving upgraded. 💜
Benchmarks
Level: Intermediate
Perl comes with an easy to use benchmarks module to help you find how long it takes to execute different parts of your code. it is a great tool to help you focus your optimization efforts. you can read about it online (<http://perldoc.perl.org/Benchmark.html>) or through the command perldoc Benchmark.
PDL::PP
Level: Advanced
PDL's Pre-Processor is one of PDL's most powerful features — genuinely, no exaggeration. you write a function definition in special markup and the pre-processor 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. ate. 😭
📈 Plotting
PDL has full-featured plotting abilities. unlike Scilab though, PDL relies more on third-party libraries (pgplot and PLplot) for its 2D plotting features. its 3D plotting and graphics uses OpenGL for performance and portability. PDL has three main plotting modules:
PDL::Graphics::Simple
Best for: Plotting 2D functions and data sets.
provides a simple library for line graphics and image display, giving a uniform plotting interface to PGPLOT, PLplot, Gnuplot, and Prima. one interface, four backends. we love to see it. 💖
PDL::Graphics::PLplot
Best for: Plotting 2D functions as well as 2D and 3D data sets.
this is an interface to the PLplot plotting library. PLplot is a modern, open source library for making scientific plots. it supports plots of both 2D and 3D data sets. PLplot is best supported for unix/linux/macosx platforms. it has an active developers community and support for win32 platforms is improving. 🌈
PDL::Graphics::TriD
Best for: Plotting 3D functions.
the native PDL 3D graphics library using OpenGL as a backend for 3D plots and data visualization. with OpenGL, it is easy to manipulate the resulting 3D objects with the mouse in real time. like, you can just grab them. with your mouse. iconic. 🦋
🎀 Writing GUIs
through Perl, PDL has access to all the major toolkits for creating a cross platform graphical user interface. one popular option is wxPerl (http://wxperl.sourceforge.net). these are the Perl bindings for wxWidgets, a powerful GUI toolkit for writing cross-platform applications.
wxWidgets is designed to make your application look and feel like a native application in every platform. for example, the Perl IDE Padre is written with wxPerl. bestie, that's the whole dream. ✨
🧚 Xcos / Scicos
Xcos (formerly Scicos) is a graphical dynamical system modeler and simulator. it is part of the standard Scilab distribution.
and here's the tea: PDL and Perl do not have a direct equivalent to Scilab's Xcos. if this feature is important to you, you should probably keep a copy of Scilab around for that. no shame in it. 💀
📜 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/
and that's the whole page, bestie, we made it 🥹 this lil masterpiece is from PDL::G...:Scilab(3pm) in the User Contributed Perl Documentation, built on perl v5.42.3, dated 2026-08-20. go forth and vectorize. 💖✨🎀
📦 where this page comes from
- ubuntu stonking: pdl 1:2.106-1build1 · Artistic-1.0-Perl OR GPL-1.0-or-later
- 💖 girlified by deepseek-ai/DeepSeek-V4.1-Flash on : a language model's rewrite of the original, under its terms