added intermediate integration dataset generator

This commit is contained in:
joesharratt1229 2025-02-02 15:27:08 +00:00
parent d4706c7128
commit ed1492ba05

View file

@ -0,0 +1,234 @@
import random
from dataclasses import dataclass
from fractions import Fraction
from typing import List, Optional
import sympy
from ..factory import ProceduralDataset, register_dataset
@dataclass
class IntermediateIntegrationConfig:
problem_types: tuple = ("substitution", "by_parts")
substitution_types: tuple = (
"linear", # (ax + b)^n
"trigonometric", # sin**2(x)cos(x)
"exponential", # 2xe^x**2
"radical", # x (3x + 2)^1/2
)
# Integration by parts problem categories
by_parts_types: tuple = (
"polynomial_exp_trig", # e.g. x^2*e^x
"log_inverse_trig", # e.g. ln(x)/arctan(x)
"cyclic", # e.g. e^x*sinx requiring cyclic integration
"repeated_parts", # Requires multiple integration by parts
)
seed: Optional[int] = None
size: int = 500
linear_lower_bound: int = 1 # coefficient of linear expression
linear_upper_bound: int = 10
min_linear_degree: int = 2 # degree of linear expression in substitution problem
max_linear_degree: int = 4
outer_constant_min: int = 1 # multiplicative constant to multiply integrand by
outer_constant_max: int = 3
min_poly_degree: int = 1 # degree of polynomial in by parts problem
max_poly_degree: int = 3
symbols: tuple = ("x", "X")
operators: tuple = (
"+",
"-",
)
def validate(self) -> None:
"""Validate the configuration parameters of the integral problem"""
assert self.size > 0, "size must be positive"
assert self.linear_lower_bound > 0, "linear_lower_bound must be positive"
assert self.linear_upper_bound >= self.linear_lower_bound, "linear_upper_bound must be >= linear_lower_bound"
assert self.min_linear_degree > 0, "min_linear_degree must be positive"
assert self.max_linear_degree >= self.min_linear_degree, "max_linear_degree must be >= min_linear_degree"
assert self.outer_constant_min > 0, "outer_constant_min must be positive"
assert self.outer_constant_max >= self.outer_constant_min, "outer_constant_max must be >= outer_constant_min"
assert self.min_poly_degree > 0, "min_poly_degree must be positive"
assert self.max_poly_degree >= self.min_poly_degree, "max_poly_degree must be >= min_poly_degree"
assert all(op in ("+", "-") for op in self.operators), "invalid operator specified"
assert all(symbols in ("x", "X") for symbols in self.symbols), "invalid symbol specified"
assert all(t in ("substitution", "by_parts") for t in self.problem_types), "invalid problem type"
assert all(
t in ("linear", "trigonometric", "exponential", "radical") for t in self.substitution_types
), "invalid substitution type"
assert all(
t in ("polynomial_exp_trig", "log_inverse_trig", "cyclic", "repeated_parts") for t in self.by_parts_types
), "invalid by_parts type"
class IntermediateIntegrationDataset(ProceduralDataset):
"""Generates intermediate integration problem - either
by substitution or by parts"""
"""Add multiplicative constant"""
def __init__(self, config: IntermediateIntegrationConfig):
super().__init__(config=config, seed=config.seed, size=config.size)
self.prompt_template = [
"Find the indefinite integral: ∫ {integrand} dx",
"Calculate the antiderivative: ∫ {integrand} dx",
"Evaluate the indefinite integral: ∫ {integrand} dx",
]
def _get_outer_constant(self, rng: random.Random) -> int:
"""Helper to generate signed outer constant from config"""
value = rng.randint(self.config.outer_constant_min, self.config.outer_constant_max)
return -value if rng.choice(self.config.operators) == "-" else value
def _generate_linear_substitution_problem(self, rng: random.Random, x: sympy.Symbol) -> sympy.Expr:
"""Generate a linear substitution problem with outer constant"""
a = rng.randint(self.config.linear_lower_bound, self.config.linear_upper_bound)
b = rng.randint(self.config.linear_lower_bound, self.config.linear_upper_bound)
linear_function = a * x + (b if rng.choice(self.config.operators) == "+" else -b)
degree = rng.randint(self.config.min_linear_degree, self.config.max_linear_degree)
return self._get_outer_constant(rng) * linear_function**degree
def _generate_exponential_substitution(self, rng: random.Random, x: sympy.Symbol) -> sympy.Expr:
"""Generate exponential substitution problem with outer constant"""
exponent_type = rng.choice(["linear", "quadratic"])
# Generate terms with signs
num_terms = 2 if exponent_type == "linear" else 3
terms = [
(-1 if rng.choice(self.config.operators) == "-" else 1)
* rng.randint(self.config.linear_lower_bound, self.config.linear_upper_bound)
for _ in range(num_terms)
]
if exponent_type == "linear":
u = terms[0] * x + terms[1]
du_dx = terms[0]
else: # Quadratic
u = terms[0] * x**2 + terms[1] * x + terms[2]
du_dx = 2 * terms[0] * x + terms[1]
return self._get_outer_constant(rng) * du_dx * sympy.exp(u)
def _generate_radical_substitution(self, rng: random.Random, x: sympy.Symbol) -> sympy.Expr:
"""Generate radical substitution problem with outer constant"""
# Generate linear expression under radical: ax + b with possible negative coefficients
a = (-1 if rng.choice(self.config.operators) == "-" else 1) * rng.randint(
self.config.linear_lower_bound, self.config.linear_upper_bound
)
b = (-1 if rng.choice(self.config.operators) == "-" else 1) * rng.randint(
self.config.linear_lower_bound, self.config.linear_upper_bound
)
u = a * x + b
derivative = a # du/dx
integrand = derivative * sympy.sqrt(u)
return self._get_outer_constant(rng) * integrand
def _generate_trigonometric_substitution(self, rng: random.Random, x: sympy.Symbol) -> sympy.Expr:
"""Generate trigonometric substitution with outer constant"""
trig_func = rng.choice(["sin", "cos"])
# Generate signed coefficients
a = (-1 if rng.choice(self.config.operators) == "-" else 1) * rng.randint(
self.config.linear_lower_bound, self.config.linear_upper_bound
)
b = (-1 if rng.choice(self.config.operators) == "-" else 1) * rng.randint(
self.config.linear_lower_bound, self.config.linear_upper_bound
)
inner = a * x + b
power = rng.randint(1, 4)
if trig_func == "sin":
integrand = a * sympy.cos(inner) * sympy.sin(inner) ** power
else:
integrand = -a * sympy.sin(inner) * sympy.cos(inner) ** power
return self._get_outer_constant(rng) * integrand
def _generate_polynomial_exp_trig(self, rng: random.Random, x: sympy.Symbol) -> sympy.Expr:
"""Generate polynomial × exponential/trigonometric integrand"""
poly_degree = rng.randint(self.config.min_poly_degree, self.config.max_poly_degree)
func_type = rng.choice(["exp", "sin", "cos"])
if func_type == "exp":
transcendental = sympy.exp(x)
else:
coefficient = rng.randint(1, 3)
transcendental = sympy.Function(func_type)(coefficient * x)
polynomial = x**poly_degree
integrand = polynomial * transcendental
return self._get_outer_constant(rng) * integrand
def _generate_log_inverse_trig(self, rng: random.Random, x: sympy.Symbol) -> sympy.Expr:
"""Generate logarithmic or inverse trigonometric integrand"""
func_type = rng.choice(["log", "asin", "atan"])
if func_type == "log":
log_arg = x if rng.random() < 0.8 else x ** rng.randint(2, 3)
func = sympy.ln(log_arg)
else:
coefficient = rng.randint(1, 3)
func = sympy.Function(func_type)(coefficient * x)
return self._get_outer_constant(rng) * func
def _generate_cyclic_integral(self, rng: random.Random, x: sympy.Symbol) -> sympy.Expr:
"""Generate cyclic integral (e.g., e^x * sinx)"""
func_pair = rng.choice(
[(sympy.exp(x), sympy.sin(x)), (sympy.exp(x), sympy.cos(x)), (sympy.sin(x), sympy.cos(x))]
)
integrand = func_pair[0] * func_pair[1]
return self._get_outer_constant(rng) * integrand
def _generate_repeated_parts(self, rng: random.Random, x: sympy.Symbol):
"""Generate problem requiring multiple integration by parts"""
poly_degree = rng.randint(3, self.config.max_poly_degree)
transcendental = rng.choice([sympy.sin(x), sympy.cos(x), sympy.exp(x)])
integrand = x**poly_degree * transcendental
return self._get_outer_constant(rng) * integrand
def __getitem__(self, index: int):
"""Generate either substitution or by-parts problem"""
rng = random.Random(self.seed + index)
problem_type = rng.choice(self.config.problem_types)
x = sympy.Symbol(rng.choice(self.config.symbols))
if problem_type == "substitution":
substitution_type = rng.choice(self.config.substitution_types)
if substitution_type == "linear":
integrand = self._generate_linear_substitution_problem(rng, x)
elif substitution_type == "trigonometric":
integrand = self._generate_trigonometric_substitution(rng, x)
elif substitution_type == "exponential":
integrand = self._generate_exponential_substitution(rng, x)
elif substitution_type == "radical":
integrand = self._generate_radical_substitution(rng, x)
else:
parts_type = rng.choice(self.config.by_parts_types)
if parts_type == "polynomial_exp_trig":
integrand = self._generate_polynomial_exp_trig(rng, x)
elif parts_type == "log_inverse_trig":
integrand = self._generate_log_inverse_trig(rng, x)
elif parts_type == "cyclic":
integrand = self._generate_cyclic_integral(rng, x)
elif parts_type == "repeated_parts":
integrand = self._generate_repeated_parts(rng, x)
answer = sympy.integrate(integrand, x)
return {
"question": rng.choice(self.prompt_template).format(integrand=integrand),
"answer": str(answer) + " + C",
"metadata": {
"integrand": str(integrand),
"problem_type": problem_type,
"variable": str(x),
"type": substitution_type if problem_type == "substitution" else parts_type,
},
}