reasoning-gym/reasoning_gym/algorithmic/count_primes.py
Oliver Stanley 7475a20700
include ranges rather than sampled values in difficulty metadata dicts (#387)
* update difficulty metadata for logic datasets

* update difficulty metadata for graph datasets

* update difficulty metadata for geometry datasets

* update difficulty metadata for games datasets

* update difficulty metadata for cognition datasets

* update difficulty metadata for arithmetic datasets

* update difficulty metadata for arc datasets

* update difficulty metadata for algorithmic datasets

* update difficulty metadata for algebra datasets

* use tuples

* update tests

* update tests
2025-03-20 10:27:03 +01:00

91 lines
3 KiB
Python

"""Count prime numbers in a given interval.
Solution obtained with Sieve of Eratosthenes:
https://en.wikipedia.org/wiki/Sieve_of_Eratosthenes
"""
import math
from dataclasses import dataclass
from random import Random
from typing import Optional
from ..coaching import BaseCurriculum, RangeAttributeDefinition
from ..factory import ProceduralDataset, register_dataset
QUESTION_TEMPLATE = """Count how many prime numbers there are between {start} and {end} (inclusive) ?"""
@dataclass
class CountPrimesConfig:
"""Configuration for Count Primes dataset generation"""
min_n: int = 1 # Lower bound for the interval
max_n: int = 10_000 # Upper bound for the interval
size: int = 500 # Virtual dataset size
seed: Optional[int] = None
def validate(self):
"""Validate configuration parameters"""
assert 1 <= self.min_n, "min_n must be at least 1"
assert self.min_n <= self.max_n, "min_n must be less than or equal to max_n"
class CountPrimesDataset(ProceduralDataset):
"""Generates Count Primes exercises with configurable difficulty"""
def __init__(self, config: CountPrimesConfig):
super().__init__(config=config, seed=config.seed, size=config.size)
self.primes = self._get_primes(config.max_n + 1)
def _get_primes(self, n: int) -> list[bool]:
if n <= 1:
return []
primes = [True] * n
primes[0] = primes[1] = False
for i in range(2, int(math.sqrt(n)) + 1):
if primes[i]:
for j in range(2 * i, n, i):
primes[j] = False
return primes
def __getitem__(self, idx: int) -> dict:
"""Generate a single Count Primes question"""
rng = Random(self.seed + idx)
start = rng.randint(self.config.min_n, self.config.max_n)
end = rng.randint(start, self.config.max_n)
primes = [i for i in range(start, end + 1) if self.primes[i]]
answer = len(primes)
return {
"question": QUESTION_TEMPLATE.format(start=start, end=end),
"answer": str(answer),
"metadata": {
"start": start,
"end": end,
"primes": primes,
"solution": answer,
"n": (start, end),
"difficulty": {
"n": (self.config.min_n, self.config.max_n),
},
},
}
class CountPrimesCurriculum(BaseCurriculum):
def __init__(self):
super().__init__(CountPrimesCurriculum.__name__, CountPrimesConfig)
# Define attributes
self._define_attributes(
RangeAttributeDefinition(
name="n",
levels=[1000, 10_000, 50_000, 100_000],
description="Up to which number to consider the primes",
lower_field_name="min_n",
upper_field_name="max_n",
)
)
register_dataset("count_primes", CountPrimesDataset, CountPrimesConfig, CountPrimesCurriculum)