mirror of
https://github.com/open-thought/reasoning-gym.git
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252 lines
8.1 KiB
Python
252 lines
8.1 KiB
Python
import pytest
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from reasoning_gym.arithmetic import DecimalChainSumConfig, DecimalChainSumDataset
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def test_decimal_chain_sum_config_validation():
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"""Test that invalid configs raise appropriate errors"""
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with pytest.raises(AssertionError):
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config = DecimalChainSumConfig(min_terms=0)
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config.validate()
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with pytest.raises(AssertionError):
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config = DecimalChainSumConfig(min_terms=3, max_terms=2)
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config.validate()
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def test_decimal_chain_sum_deterministic():
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"""Test that dataset generates same items with same seed"""
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config = DecimalChainSumConfig(seed=42, size=10)
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dataset1 = DecimalChainSumDataset(config)
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dataset2 = DecimalChainSumDataset(config)
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for i in range(len(dataset1)):
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assert dataset1[i] == dataset2[i]
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def test_decimal_chain_sum_items():
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"""Test basic properties of generated items"""
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config = DecimalChainSumConfig(
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min_terms=2,
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max_terms=4,
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min_digits=1,
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max_digits=2,
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min_decimal_places=1,
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max_decimal_places=2,
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size=100,
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seed=42,
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)
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dataset = DecimalChainSumDataset(config)
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for i in range(len(dataset)):
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item = dataset[i]
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assert isinstance(item, dict)
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assert "question" in item
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assert "answer" in item
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assert "metadata" in item
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# Verify only + and - are used
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expression = item["metadata"]["expression"]
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assert all(op in ["+", "-", " ", "."] or op.isdigit() for op in expression)
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# Check for floating point errors
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numbers = [n for n in expression.split() if any(c.isdigit() for c in n)]
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for num in numbers:
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# Verify no numbers have more decimal places than max_decimal_places
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if "." in num:
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decimal_places = len(num.split(".")[-1])
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assert decimal_places <= config.max_decimal_places, f"Number {num} has more decimal places than allowed"
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# Verify answer has correct precision
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answer_str = item["answer"]
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if "." in answer_str:
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decimal_places = len(answer_str.split(".")[-1])
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assert (
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decimal_places <= config.max_decimal_places
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), f"Answer {answer_str} has more decimal places than allowed"
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# Verify mathematical correctness within epsilon
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expected = eval(expression)
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assert (
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abs(float(item["answer"]) - expected) < 1e-10
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), f"Answer {item['answer']} doesn't match expected {expected}"
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def test_chain_sum_number_ranges():
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"""Test that generated numbers respect digit constraints"""
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# Test 3-digit numbers
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config = DecimalChainSumConfig(
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min_terms=2,
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max_terms=2, # Fix to 2 terms for easier testing
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min_digits=3,
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max_digits=3,
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min_decimal_places=1,
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max_decimal_places=4,
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size=50,
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seed=42,
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)
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dataset = DecimalChainSumDataset(config)
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for i in range(len(dataset)):
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item = dataset[i]
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expression = item["metadata"]["expression"]
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numbers = [int(n) for n in expression.split() if n.isdigit()]
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for num in numbers:
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assert 100 <= num <= 999, f"Number {num} outside valid range for 3 digits"
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# Test 1-digit numbers
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config = DecimalChainSumConfig(
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min_terms=2,
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max_terms=2,
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min_digits=1,
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max_digits=1,
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min_decimal_places=1,
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max_decimal_places=4,
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size=50,
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seed=42,
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)
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dataset = DecimalChainSumDataset(config)
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for i in range(len(dataset)):
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item = dataset[i]
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expression = item["metadata"]["expression"]
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numbers = [int(n) for n in expression.split() if n.isdigit()]
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for num in numbers:
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assert 0 <= num <= 9, f"Number {num} outside valid range for 1 digit"
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def test_decimal_chain_sum_negation():
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"""Test that negation is properly handled"""
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config = DecimalChainSumConfig(
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min_terms=2,
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max_terms=2,
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min_digits=1,
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max_digits=1,
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min_decimal_places=1,
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max_decimal_places=4,
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allow_negation=True,
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size=50,
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seed=42,
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)
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dataset = DecimalChainSumDataset(config)
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has_positive = False
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has_negative = False
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for i in range(len(dataset)):
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item = dataset[i]
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expression = item["metadata"]["expression"]
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numbers = [float(n) for n in expression.split() if n.replace(".", "").replace("-", "").isdigit()]
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for num in numbers:
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if num > 0:
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has_positive = True
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if num < 0:
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has_negative = True
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assert has_positive and has_negative, "Expected both positive and negative numbers with allow_negation=True"
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def test_decimal_chain_sum_iteration():
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"""Test that iteration respects dataset size"""
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config = DecimalChainSumConfig(
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min_terms=2,
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max_terms=2,
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min_digits=1,
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max_digits=1,
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min_decimal_places=1,
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max_decimal_places=4,
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size=5,
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seed=42,
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)
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dataset = DecimalChainSumDataset(config)
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items = []
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for item in dataset:
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items.append(item)
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assert len(items) == config.size, "Iterator should yield exactly size items"
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items = list(dataset)
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assert len(items) == config.size, "Iterator should yield exactly size items"
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first_items = list(dataset)
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second_items = list(dataset)
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assert first_items == second_items, "Multiple iterations should yield same items"
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def test_decimal_places_generation():
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"""Test that generated decimal numbers have correct number of decimal places"""
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# Test fixed decimal places
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config = DecimalChainSumConfig(
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min_terms=2,
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max_terms=2,
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min_digits=1,
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max_digits=2,
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min_decimal_places=2,
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max_decimal_places=2,
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size=50,
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seed=42,
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)
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dataset = DecimalChainSumDataset(config)
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for item in dataset:
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expression = item["metadata"]["expression"]
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# Extract numbers including decimals
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numbers = [n for n in expression.split() if any(c.isdigit() for c in n)]
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for num in numbers:
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decimal_part = num.split(".")[-1]
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assert len(decimal_part) == 2, f"Number {num} should have exactly 2 decimal places"
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# Test varying decimal places
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config = DecimalChainSumConfig(
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min_terms=2,
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max_terms=2,
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min_digits=1,
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max_digits=2,
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min_decimal_places=1,
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max_decimal_places=3,
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size=50,
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seed=42,
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)
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dataset = DecimalChainSumDataset(config)
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for item in dataset:
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expression = item["metadata"]["expression"]
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numbers = [n for n in expression.split() if any(c.isdigit() for c in n)]
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for num in numbers:
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decimal_part = num.split(".")[-1]
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assert 1 <= len(decimal_part) <= 3, f"Number {num} should have between 1 and 3 decimal places"
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def test_decimal_precision_scoring():
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"""Test that scoring handles decimal precision correctly"""
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config = DecimalChainSumConfig(
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min_terms=2,
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max_terms=2,
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min_digits=1,
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max_digits=2,
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min_decimal_places=2,
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max_decimal_places=3,
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size=1,
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seed=42,
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)
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dataset = DecimalChainSumDataset(config)
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item = dataset[0]
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# Test exact matches with different representations
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assert dataset.score_answer("1.200", {"answer": "1.2"}) == 1.0
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assert dataset.score_answer("1.20", {"answer": "1.200"}) == 1.0
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assert dataset.score_answer("-0.5", {"answer": "-0.500"}) == 1.0
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# Test floating point precision edge cases
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assert dataset.score_answer("0.1", {"answer": "0.100"}) == 1.0
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assert dataset.score_answer("0.3", {"answer": "0.300"}) == 1.0
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# Test incorrect answers
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assert dataset.score_answer("1.200000001", {"answer": "1.200"}) == 0.01
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assert dataset.score_answer("1.199999999", {"answer": "1.200"}) == 0.01
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# Test invalid inputs
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assert dataset.score_answer(None, {"answer": "1.200"}) == 0.0
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assert dataset.score_answer("", {"answer": "1.200"}) == 0.0
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assert dataset.score_answer("invalid", {"answer": "1.200"}) == 0.01
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assert dataset.score_answer("1.2.3", {"answer": "1.200"}) == 0.01
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