# Copyright (c) 2022 AIRBUS and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
from collections.abc import Hashable
from typing import Any, Optional
from discrete_optimization.coloring.problem import ColoringProblem
from discrete_optimization.datasets import get_data_home
from discrete_optimization.generic_tools.graph_api import Graph
[docs]
def get_data_available(
data_folder: Optional[str] = None, data_home: Optional[str] = None
) -> list[str]:
"""Get datasets available for coloring.
Params:
data_folder: folder where datasets for coloring whould be find.
If None, we look in "coloring" subdirectory of `data_home`.
data_home: root directory for all datasets. Is None, set by
default to "~/discrete_optimization_data "
"""
if data_folder is None:
data_home = get_data_home(data_home=data_home)
data_folder = f"{data_home}/coloring"
try:
datasets = [
os.path.abspath(os.path.join(data_folder, f))
for f in os.listdir(data_folder)
]
except FileNotFoundError:
datasets = []
return datasets
[docs]
def parse(input_data: str) -> ColoringProblem:
"""From a text input, initialise a coloring problem instance.
Args:
input_data: text input in the format of {data_home}/coloring files
Returns: a ColoringProblem instance
"""
# parse the input
lines = input_data.split("\n")
first_line = lines[0].split()
node_count = int(first_line[0])
edge_count = int(first_line[1])
edges: list[tuple[Hashable, Hashable, dict[str, Any]]] = []
nodes: list[tuple[Hashable, dict[str, Any]]] = [(i, {}) for i in range(node_count)]
for i in range(1, edge_count + 1):
line = lines[i]
parts = line.split()
edges.append((int(parts[0]), int(parts[1]), {}))
return ColoringProblem(
Graph(nodes, edges, undirected=True, compute_predecessors=False)
)
[docs]
def parse_file(file_path: str) -> ColoringProblem:
"""From an absolute path to a coloring text file, return the corresponding coloring instance
Args:
file_path (str): absolute path to the file
Returns: a ColoringProblem instance
"""
with open(file_path, "r", encoding="utf-8") as input_data_file:
input_data = input_data_file.read()
coloring_problem = parse(input_data)
return coloring_problem