reasoning-gym/tests/test_power_function.py
Zafir Stojanovski a8c39ddcfb
Power Function (#102)
* power function dataset + tests
2025-02-10 22:04:58 +01:00

78 lines
2.4 KiB
Python

"""Tests for Power Function questions generation"""
import pytest
from reasoning_gym.arithmetic import PowerFunctionConfig, PowerFunctionDataset
def test_power_function_dataset_deterministic():
"""Test that dataset generates same items with same seed"""
config = PowerFunctionConfig(seed=42, size=10)
dataset1 = PowerFunctionDataset(config)
dataset2 = PowerFunctionDataset(config)
for i in range(len(dataset1)):
assert dataset1[i] == dataset2[i]
def test_power_function_dataset_items():
"""Test basic properties of generated items"""
config = PowerFunctionConfig(min_base=-100, max_base=-100, min_exponent=-10, max_exponent=10, size=10, seed=42)
dataset = PowerFunctionDataset(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 "base" in item["metadata"]
assert "exponent" in item["metadata"]
base = item["metadata"]["base"]
exponent = item["metadata"]["exponent"]
solution = item["metadata"]["solution"]
# Verify values
assert config.min_base <= base <= config.max_base
assert config.min_exponent <= exponent <= config.max_exponent
assert solution == pow(base, exponent)
def test_power_function_dataset_iteration():
"""Test that iteration respects dataset size"""
config = PowerFunctionConfig(size=5, seed=42)
dataset = PowerFunctionDataset(config)
items = list(dataset)
assert len(items) == config.size
# Test multiple iterations yield same items
assert items == list(dataset)
def test_power_function_score_function():
"""Test score function"""
config = PowerFunctionConfig(seed=42)
dataset = PowerFunctionDataset(config)
item = dataset[0]
# Answer is within 1e-6 of solution
answer = str(item["metadata"]["solution"] - 1e-7)
assert dataset.score_answer(answer, item) == 1.0
# Answer is within 1e-1 of solution
answer = str(item["metadata"]["solution"] - 1e-2)
assert dataset.score_answer(answer, item) == 0.5
# Answer is far from solution
answer = str(item["metadata"]["solution"] - 1)
assert dataset.score_answer(answer, item) == 0.01
# Answer is None
answer = None
assert dataset.score_answer(answer, item) == 0.0