reasoning-gym/tests/test_palindrome_partitioning.py
2025-02-06 21:42:39 +01:00

111 lines
3.9 KiB
Python

"""Tests for Palindrome Partitioning questions generation"""
import json
from reasoning_gym.algorithmic.palindrome_partitioning import (
PalindromePartitioningConfig,
PalindromePartitioningDataset,
)
def test_palindrome_partitioning_dataset_deterministic():
"""Test that dataset generates same items with same seed"""
config = PalindromePartitioningConfig(seed=42, size=10)
dataset1 = PalindromePartitioningDataset(config)
dataset2 = PalindromePartitioningDataset(config)
for i in range(len(dataset1)):
assert dataset1[i] == dataset2[i]
def test_palindrome_partitioning_dataset_items():
"""Test basic properties of generated items"""
config = PalindromePartitioningConfig(size=10, seed=42)
dataset = PalindromePartitioningDataset(config)
for i in range(len(dataset)):
item = dataset[i]
# Check item structure
assert isinstance(item, dict)
assert "question" in item
assert "answer" in item
assert "metadata" in item
# Check metadata
assert "string" in item["metadata"]
assert "solution" in item["metadata"]
string = item["metadata"]["string"]
solution = item["metadata"]["solution"]
# Verify string is not empty
assert len(string) > 0
# At least one partitioning exists (each letter is a palindrome)
assert len(solution) >= 1
# Verify each partitioning reconstructs the original string
assert all(len(partitioning) > 0 for partitioning in solution)
assert all("".join(partitioning) == string for partitioning in solution)
def test_palindrome_partitioning_dataset_iteration():
"""Test that iteration respects dataset size"""
config = PalindromePartitioningConfig(size=5, seed=42)
dataset = PalindromePartitioningDataset(config)
items = list(dataset)
assert len(items) == config.size
# Test multiple iterations yield same items
assert items == list(dataset)
def test_palindrome_partitioning_answer():
"""Test the _palindrome_partitioning method"""
config = PalindromePartitioningConfig(seed=42)
dataset = PalindromePartitioningDataset(config)
# General use case
word = "afternoon"
correct = [
["a", "f", "t", "e", "r", "n", "o", "o", "n"],
["a", "f", "t", "e", "r", "n", "oo", "n"],
["a", "f", "t", "e", "r", "noon"],
]
assert json.dumps(dataset._palindrome_partitioning(word)) == json.dumps(correct)
# Single letter word
word = "a"
correct = [["a"]]
assert json.dumps(dataset._palindrome_partitioning(word)) == json.dumps(correct)
# Empty string
word = ""
correct = []
assert json.dumps(dataset._palindrome_partitioning(word)) == json.dumps(correct)
def test_palindrome_partitioning_score_answer():
"""Test the score_answer method"""
config = PalindromePartitioningConfig(seed=42)
dataset = PalindromePartitioningDataset(config)
# Verify the scoring function is permutation invariant
answer = json.dumps([["n", "o", "o", "n"], ["no", "on"], ["noon"]])
item = {"metadata": {"solution": [["no", "on"], ["noon"], ["n", "o", "o", "n"]]}}
assert dataset.score_answer(answer, item) == 1
# Verify the score is 0.01 when incorrect
answer = json.dumps([["n", "o", "o", "n"], ["no", "on"]])
item = {"metadata": {"solution": [["no", "on"], ["noon"], ["n", "o", "o", "n"]]}}
assert dataset.score_answer(answer, item) == 0.01
# Verify the score is 0 when answer is None
answer = None
item = {"metadata": {"solution": [["no", "on"], ["noon"], ["n", "o", "o", "n"]]}}
assert dataset.score_answer(answer, item) == 0
# Verify the score is 0 when answer is malformed JSON
answer = '["n", "o", "o", "n"], ["no", "on"], ["noon"]'
item = {"metadata": {"solution": [["no", "on"], ["noon"], ["n", "o", "o", "n"]]}}
assert dataset.score_answer(answer, item) == 0