README

Raku Data::Generators

This Raku package has functions for generating random strings, words, pet names, vectors, arrays, and (tabular) datasets.

Motivation

The primary motivation for this package is to have simple, intuitively named functions for generating random vectors (lists) and datasets of different objects.

Although, Raku has a fairly good support of random vector generation, it is assumed that commands like the following are easier to use:

say random-string(6, chars => 4, ranges => [ <y n Y N>, "0".."9" ] ).raku;

Random strings

The function random-string generates random strings.

Here is a random string:

use Data::Generators;
random-string

# eM

Here we generate a vector of random strings with length 4 and characters that belong to specified ranges:

say random-string(6, chars => 4, ranges => [ <y n Y N>, "0".."9" ] ).raku;

# ("0n57", "n489", "0yn5", "8Y84", "0n83", "7Y2Y")

Random words

The function random-word generates random words.

Here is a random word:

random-word

# mayfly

Here we generate a list with 12 random words:

random-word(12)

# (77 implantation Vespasian Porphyrula rainfly unhorse periphrastic stabilize milestone thorniness chat uniparous)

Here we generate a table of random words of different types:

use Data::Reshapers;
my @dfWords = do for <Any Common Known Stop> -> $wt { $wt => random-word(6, type => $wt) };
say to-pretty-table(@dfWords);

# +--------+-----------+----------+------------+-------------+-----------+----------+
# |        |     2     |    4     |     5      |      3      |     1     |    0     |
# +--------+-----------+----------+------------+-------------+-----------+----------+
# | Any    | logomania |  matzah  |  Bemidji   |    Elspar   |    chon   | haloform |
# | Common |  mantissa | hookworm |  ungainly  |   sneaker   |   ferry   | clematis |
# | Known  |    owl    | tripling | canecutter | merchantman | inclusive | doglike  |
# | Stop   |   while   |  you're  |    him     |     how     |   always  |  wasn't  |
# +--------+-----------+----------+------------+-------------+-----------+----------+

Remark: Whatever can be used instead of 'Any'.

Remark: The function to-pretty-table is from the package Data::Reshapers.

Random pet names

The function random-pet-name generates random pet names.

The pet names are taken from publicly available data of pet license registrations in the years 2015–2020 in Seattle, WA, USA. See [DG1].

Here is a random pet name:

random-pet-name

# Kili

The following command generates a list of six random pet names:

srand(32);
random-pet-name(6).raku

# ("Luther", "Millie", "Guinness", "Luther", "Professor Nibblesworth", "Atticus")

The named argument species can be used to specify specie of the random pet names. (According to the specie-name relationships in [DG1].)

Here we generate a table of random pet names of different species:

my @dfPetNames = do for <Any Cat Dog Goat Pig> -> $wt { $wt => random-pet-name(6, species => $wt) };
say to-pretty-table(@dfPetNames);

# +------+----------+-----------------+--------------+------------------------+---------+----------+
# |      |    4     |        2        |      0       |           1            |    5    |    3     |
# +------+----------+-----------------+--------------+------------------------+---------+----------+
# | Any  | Atticus  |     Guinness    |    Winnie    |         Rocket         |  Beans  |  Aggie   |
# | Cat  | Josefina |    Meow-Meow    | Parker Posey |   Katherine Hepburn    |  Chaco  | Mow Mow  |
# | Dog  | Minotaur |     Sputnik     |     Navy     |   Melian (mel-ee-un)   |  Draco  | Skidster |
# | Goat |  Grace   | Brussels Sprout |   Schmidt    | Professor Nibblesworth |  Darcy  |  Piper   |
# | Pig  |  Millie  |     Atticus     |    Millie    |         Millie         | Atticus | Guinness |
# +------+----------+-----------------+--------------+------------------------+---------+----------+

Remark: Whatever can be used instead of 'Any'.

The named argument (adverb) weighted can be used to specify random pet name choice based on known real-life number of occurrences:

srand(32);
say random-pet-name(6, :weighted).raku

# ("Millie", "Audrey Carroll Buchbinder Chia", "Moppet", "Millie", "Linda", "Linda")

The weights used correspond to the counts from [DG1].

Remark: The implementation of random-pet-name is based on the Mathematica implementation RandomPetName, [AAf1].

Random pretentious job titles

The function random-pretentious-job-title generates random pretentious job titles.

Here is a random pretentious job title:

random-pretentious-job-title

# Forward Identity Synergist

The following command generates a list of six random pretentious job titles:

random-pretentious-job-title(6).raku

# ("Customer Quality Synergist", "Principal Impact Designer", "District Team Manager", "Internal Communications Executive", "Corporate Research Specialist", "Corporate Program Associate")

The named argument number-of-words can be used to control the number of words in the generated job titles.

The named argument language can be used to control in which language the generated job titles are in. At this point, only Bulgarian and English are supported.

Here we generate pretentious job titles using different languages and number of words per title:

my $res = random-pretentious-job-title(12, number-of-words => Whatever, language => Whatever);
say ‌‌to-pretty-table($res.rotor(3));

# +--------------------------------------+------------------------+-----------------------+
# |                  0                   |           1            |           2           |
# +--------------------------------------+------------------------+-----------------------+
# |               Стратег                |        Директор        |  Configuration Agent  |
# |         Human Quality Agent          |   Assurance Director   |       Supervisor      |
# | Internal Infrastructure Orchestrator | Специалист по Отговори | Дизайнер по Парадигми |
# |    Директен Асистент по Отговори     | Lead Paradigm Analyst  |     Администратор     |
# +--------------------------------------+------------------------+-----------------------+

Remark: Whatever can be used as values for the named arguments number-of-words and language.

Remark: The implementation uses the job title phrases in https://www.bullshitjob.com . It is, more-or-less, based on the Mathematica implementation RandomPretentiousJobTitle, [AAf2].

Random reals

This module provides the function random-real that can be used to generate lists of real numbers using the uniform distribution.

Here is a random real:

say random-real();

# 0.781896535292538

Here is a random real between 0 and 20:

say random-real(20);

# 13.072422505045779

Here are six random reals between -2 and 12:

say random-real([-2,12], 6);

# (11.864258861917264 4.890701998281822 7.1509704636994975 2.856699299326742 -1.2772229946471956 11.4367816302763)

Here is a 4-by-3 array of random reals between -3 and 3:

say random-real([-3,3], [4,3]);

# [[2.3294489626915276 -1.0950408598600314 -2.2898051328754807]
#  [-1.9248193884428577 0.7775337323750455 0.5662577115435008]
#  [2.793892442816027 -2.8554755650301713 2.3260442949686357]
#  [-2.8095178343640743 -2.4967975502939384 -1.0154613861655881]]

Remark: The signature design follows Mathematica's function RandomReal.

Random variates

This module provides the function random-variate that can be used to generate lists of real numbers using distribution specifications.

Here are examples:

say random-variate(NormalDistribution.new(:mean(10), :sd(20)), 5);

# (-27.659188870179968 4.048485095109329 4.44985806317876 -4.534662024009972 1.7386988216711394)

say random-variate(NormalDistribution.new( µ => 10, σ => 20), 5);

# (1.900787217179996 14.630607569797847 -7.012234809766465 6.296428231434105 5.123221681439648)

say random-variate(UniformDistribution.new(:min(2), :max(60)), 5);

# (8.71131881757636 42.992275827793456 36.47696163225245 46.38138517633746 7.321302330277626)

Remark: Only Normal distribution and Uniform distribution are implemented at this point.

Remark: The signature design follows Mathematica's function RandomVariate.

Here is an example of 2D array generation:

say random-variate(NormalDistribution.new, [3,4]);

# [[-0.5103182521990548 -0.5829429151529076 -0.5940839041945513 -1.0927896811728377]
#  [-0.43767702086129184 2.0452658692233983 -0.8459908693989825 1.1106283004104134]
#  [0.8070535406316326 -0.5660945212157695 0.6845858560140593 0.12401565911386467]]

Random tabular datasets

The function random-tabular-dataset can be used generate tabular datasets.

Remark: In this module a dataset is (usually) an array of arrays of pairs. The dataset data structure resembles closely Mathematica's data structure [Dataset]https://reference.wolfram.com/language/ref/Dataset.html), [WRI2].

Remark: The programming languages R and S have a data structure called "data frame" that corresponds to dataset. (In the Python world the package pandas provides data frames.) Data frames, though, are column-centric, not row-centric as datasets. For example, data frames do not allow a column to have elements of heterogeneous types.

Here are basic calls:

random-tabular-dataset();
random-tabular-dataset(Whatever):row-names;
random-tabular-dataset(Whatever, Whatever);
random-tabular-dataset(12, 4);
random-tabular-dataset(Whatever, 4);
random-tabular-dataset(Whatever, <Col1 Col2 Col3>):!row-names;

Here is example of a generated tabular dataset that column names that are cat pet names:

my @dfRand = random-tabular-dataset(5, 3, column-names-generator => { random-pet-name($_, species => 'Cat') });
say to-pretty-table(@dfRand);

# +----------+-----------+-----------+
# | Canella  |    Opie   | Sunnyside |
# +----------+-----------+-----------+
# | eolithic | 21.871253 | 12.476871 |
# | shipside |  6.670374 | 16.933138 |
# |  holly   |  7.161387 |  7.932595 |
# | Romance  |  7.684871 | -8.726944 |
# |   silo   |  6.362423 | 23.188637 |
# +----------+-----------+-----------+

The display function to-pretty-table is from Data::Reshapers.

Remark: At this point only wide format datasets are generated. (The long format implementation is high in my TOOD list.)

Remark: The signature design and implementation are based on the Mathematica implementation RandomTabularDataset, [AAf3].

TODO

TODO Random tabular datasets generation
- DONE Row spec
- DONE Column spec that takes columns count and column names
- DONE Column names generator
- DONE Wide form implementation only
- DONE Generators of column values
  - DONE Column-generator hash
  - DONE List of generators
  - DONE Single generator
  - DONE Turn "generators" that are lists into sampling pure functions
- TODO Long form implementation
- TODO Max number of values
- TODO Min number of values
- TODO Form (long or wide)
- DONE Row names (automatic)
DONE Random reals vectors generation
TODO Figuring out how to handle and indicate missing values
TODO Random reals vectors generation according to distribution specs
- DONE Uniform distribution
- DONE Normal distribution
- TODO Poisson distribution
- TODO Skew-normal distribution
- TODO Triangular distribution
DONE RandomReal-like implementation
- See random-real.
TODO Selection between roll and pick for:
- TODO RandomWord
- TODO RandomPetName