Rooc runtime

Inside Rooc, you can use the functions defined inside of the runtime to perform operations on the data. There are 3 kinds of functions:

Normal functions: They accept an input and return an output
Block functions: They have a block where you can write an expression, and the block function will do some operation over the block
Block scoped functions: Like block functions, but they have an iteration scope. Inside of the scope you can define how to iterate over the data, and it will be available in the block for you to use.

Functions

They are functions that accept parameters and return a value, you can use them inside blocks, assignments or in expressions

Returns the length of the iterable

Enumerates the iterable, returning a tuple of the element and its index

Returns the edges of a graph

Returns the nodes of a graph

Returns the neighbour edges of a node

Returns the neighbour edges of a node name in a graph

Returns an iterable of integers from `from` to `to` (inclusive or exclusive)

Zips two or more iterables together, returning a tuple of the elements, the length of the resulting iterable is the length of the shortest iterable

Returns the difference of two iterables

Returns the union of two iterables

Returns the intersection of two iterables

Block functions

They are blocks which have one or more expressions separated by a comma, they will use those expressions to perform a transformation, like the avg (average) block

Computes the inner expression as the minimum of all elements

Computes the inner expression as the maximum of all elements

Computes the inner expression as the average of all elements

Block scoped functions

They are function blocks, it has as parameters one or more iterators over iterable data, they will declare a variable (or more using tuples destructuring) for each iterator and then execute the block.
If there are more than one iterators, they will behave as nested iterators, where the first iterator is the outermost one

Expands the inner expression into a sum of all elements

Expands the inner expression into a product of all elements

Expands the inner expression into the minimum of all elements

Expands the inner expression into the maximum of all elements

Expands the inner expression into the average of all elements

Execution pipes

Other than the model, you can define an execution pipeline that you can customise to do what you need.
There are some presets you can choose from, but in general, each pipe step has an input and produces an output, each step of the pipeline will be executed one after the other in the order they are defined, and each result will be shown as the output.

Name:

Compiler

Input:

String

Output:

Parser

Compiles the code

Name:

Pre Model

Input:

Parser

Output:

Pre Model

Generates a model from the compiler output

Name:

Model

Input:

Pre Model

Output:

Model

Run the Pre Model to generate the static model

Name:

Linear model

Input:

Model

Output:

Linear Model

Transforms the model into a linear model

Name:

Standard linear model

Input:

Linear Model

Output:

Standard Linear Model

Transforms the linear model into a model in standard form

Name:

Tableau for simplex

Input:

Standard Linear Model

Output:

Tableau

Transforms the standard linear model into a tableau that can be used in the simplex algorithm, it creates artificial variables to find the initial basis

Name:

Real solver

Input:

Linear Model

Output:

Real Solution

Runs a real variable solver to find the optimal solution, the variables must be real or non negative real

Name:

Simplex solver with steps

Input:

Tableau

Output:

Optimal Tableau with Steps

Runs the simplex algorithm to find the optimal solution and returns the tableau at each step

Name:

Binary solver

Input:

Linear Model

Output:

Binary Solution

Runs a binary variable solver to find the optimal solution, the variables must be binary

Name:

Integer binary solver

Input:

Linear Model

Output:

Integer Binary Solution

Runs a binary and integer variable solver to find the optimal solution, the variables must be binary or integer

Name:

MILP solver

Input:

Linear Model

Output:

MILP Solution

Runs a solver that allows for real, integer and binary variables to find the optimal solution.

Name:

Auto solver

Input:

Linear Model

Output:

MILP Solution

Automatically picks the best solver to run for this model