355 lines
10 KiB
YAML
355 lines
10 KiB
YAML
openapi: 3.0.3
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info:
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version: 0.3.0
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title: Schemata for command instructions
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servers:
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- url: "."
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paths: {}
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components:
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schemas:
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Commands
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Commands:
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description: |-
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List of commands to test algorithms/datastructures.
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type: array
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items:
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$ref: "#/components/schemas/Command"
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default: []
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Command
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Command:
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description: |-
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Instructions for command to call
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type: object
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required:
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- name
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properties:
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name:
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$ref: '#/components/schemas/EnumAlgorithmNames'
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additionalProperties: true
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Algorithm: Tarjan
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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CommandTarjan:
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description: |-
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Instructions for execution of Tarjan-Algorithm
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type: object
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required:
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- name
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- nodes
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- edges
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properties:
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name:
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$ref: '#/components/schemas/EnumAlgorithmNames'
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nodes:
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type: array
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items:
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anyOf:
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- type: integer
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- type: number
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- type: string
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edges:
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type: array
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items:
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type: array
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minItems: 2
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maxItems: 2
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items:
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anyOf:
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- type: integer
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- type: number
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- type: string
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Algorithm: TSP
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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CommandTsp:
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description: |-
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Instructions for execution of TSP-Algorithm
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type: object
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required:
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- name
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- optimise
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- dist
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properties:
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name:
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$ref: '#/components/schemas/EnumAlgorithmNames'
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dist:
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type: array
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items:
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type: array
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items:
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type: number
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optimise:
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$ref: '#/components/schemas/EnumOptimiseMode'
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Algorithm: Hirschberg
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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CommandHirschberg:
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description: |-
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Instructions for execution of Hirschberg-Algorithm
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type: object
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required:
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- name
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- word1
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- word2
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properties:
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name:
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$ref: '#/components/schemas/EnumAlgorithmNames'
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word1:
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description: Word that gets placed vertically in algorithm.
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type: string
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word2:
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description: Word that gets placed horizontally in algorithm
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type: string
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once:
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type: boolean
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default: false
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Algorithm: Rucksack Branch & Bound
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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CommandRucksack:
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description: |-
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Instructions for execution of Branch & Bound-Algorithm for the Rucksack-Problem
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type: object
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required:
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- name
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- algorithm
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- max-cost
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- costs
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- values
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properties:
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name:
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$ref: '#/components/schemas/EnumAlgorithmNames'
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algorithm:
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$ref: '#/components/schemas/EnumRucksackAlgorithm'
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allow-fractional:
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type: boolean
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default: false
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max-cost:
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description: Upper bound for total cost of rucksack.
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type: number
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minimum: 0
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costs:
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description: Array of cost for each item (e.g. volume, weight, price, time, etc.).
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type: array
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items:
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type: number
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exclusiveMinimum: 0
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values:
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description: Value extracted from each item (e.g. energy, profit, etc.).
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type: array
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items:
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type: number
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items:
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description: Optional names of the items (if empty, defaults to 1-based indexes).
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type: array
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items:
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type: string
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default: []
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Algorithm: Random Walk
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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CommandRandomWalk:
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description: |-
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Instructions for execution of random walks to determine local extrema in a fitness landscape
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type: object
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required:
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- name
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- algorithm
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- landscape
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- optimise
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properties:
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name:
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$ref: '#/components/schemas/EnumAlgorithmNames'
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algorithm:
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$ref: '#/components/schemas/EnumWalkMode'
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landscape:
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$ref: '#/components/schemas/DataTypeLandscapeGeometry'
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optimise:
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$ref: '#/components/schemas/EnumOptimiseMode'
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coords-init:
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description: Initial co-ordinates to start the algorithm.
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type: array
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items:
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type: integer
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minItems: 1
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temperature-init:
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type: float
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default: 1.
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annealing:
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type: boolean
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default: false
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one-based:
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type: boolean
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default: false
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Algorithm: Genetic Algorithm
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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CommandGenetic:
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description: |-
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Instructions for execution of the Genetic algorithm
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type: object
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required:
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- name
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- population
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properties:
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name:
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$ref: '#/components/schemas/EnumAlgorithmNames'
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population:
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type: array
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items:
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type: array
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items:
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type: string
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minItems: 2
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# maxItems: 2 # FIXME: does not work!
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Algorithm: Euklidean algorithm
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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CommandEuklid:
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description: |-
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Instructions for execution of the Euklidean gcd-algorithm
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type: object
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required:
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- name
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- numbers
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properties:
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name:
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$ref: '#/components/schemas/EnumAlgorithmNames'
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numbers:
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type: array
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items:
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type: integer
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exclusiveMinimum: 0
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minItems: 2
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maxItems: 2
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Algorithm: Pollard's rho
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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CommandPollard:
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description: |-
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Instructions for execution of the Pollard's rho algorithm
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type: object
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required:
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- name
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- number
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properties:
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name:
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$ref: '#/components/schemas/EnumAlgorithmNames'
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number:
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type: integer
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exclusiveMinimum: 0
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x-init:
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type: integer
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default: 2
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minimum: 2
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Data-type Landscape Geometry, Landscape Values
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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DataTypeLandscapeGeometry:
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description: |-
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Structure for the geometry of a fitness landscape
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type: object
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required:
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- neighbourhoods
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- labels
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- values
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properties:
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neighbourhoods:
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$ref: '#/components/schemas/DataTypeLandscapeNeighbourhoods'
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labels:
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type: array
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items:
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type: string
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minItems: 1
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values:
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$ref: '#/components/schemas/DataTypeLandscapeValues'
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DataTypeLandscapeNeighbourhoods:
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description: |-
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Options for the definition of discrete neighbourhoods of a fitness landscape
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type: object
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required:
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- metric
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properties:
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radius:
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type: number
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minimum: 1
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default: 1
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metric:
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$ref: '#/components/schemas/EnumLandscapeMetric'
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DataTypeLandscapeValues:
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description: |-
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A (potentially multi-dimensional) array of values for the fitness landscape.
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oneOf:
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- type: array
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items:
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type: number
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- type: array
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items:
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$ref: '#/components/schemas/DataTypeLandscapeValues'
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Enum Algorithm Names
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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EnumAlgorithmNames:
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description: |-
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Enumeration of possible algorithm options.
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type: string
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enum:
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- TARJAN
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- TSP
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- HIRSCHBERG
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- RUCKSACK
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- RANDOM-WALK
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- GENETIC
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- EUKLID
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- POLLARD-RHO
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Enum Optimise Mode
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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EnumOptimiseMode:
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description: |-
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Enumeration of optimisation modi.
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type: string
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enum:
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- MIN
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- MAX
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Enum Rucksack mode for algorithm
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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EnumRucksackAlgorithm:
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description: |-
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Enumeration of mode for Rucksack problem
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type: string
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enum:
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- GREEDY
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- BRANCH-AND-BOUND
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Enum Type of walk mode for fitness walk algorithm
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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EnumWalkMode:
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description: |-
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Enumeration of walk mode for fitness walk algorithm
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- `ADAPTIVE` - points uniformly randomly chosen from nbhd.
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- `GRADIENT` - points uniformly randomly chosen amongst points in nbhd with steepest gradient.
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- `METROPOLIS` - points uniformly randomly chosen from nbhd. or by entropy.
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type: string
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enum:
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- ADAPTIVE
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- GRADIENT
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- METROPOLIS
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Enum for metric for neighbourhoods in fitness landscape
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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EnumLandscapeMetric:
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description: |-
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Enumeration of mode for Rucksack problem
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- `MAXIMUM` - `Q` is a neighbour of `P` <==> `max_i d(P_i, Q_i) <= r`
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- `MANHATTAN` - `Q` is a neighbour of `P` <==> `sum_i d(P_i, Q_i) <= r`
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type: string
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enum:
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- MAXIMUM
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- MANHATTAN
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