271 lines
8.5 KiB
Python
271 lines
8.5 KiB
Python
from math import floor
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from pkgutil import get_data
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from random import Random
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from typing import Any, Collection, Dict, FrozenSet, Iterable, List, Optional, Set, Tuple, TypeVar
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T = TypeVar("T")
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# A WitnessRule is just an or-chain of and-conditions.
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# It represents the set of all options that could fulfill this requirement.
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# E.g. if something requires "Dots or (Shapers and Stars)", it'd be represented as: {{"Dots"}, {"Shapers, "Stars"}}
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# {} is an unusable requirement.
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# {{}} is an always usable requirement.
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WitnessRule = FrozenSet[FrozenSet[str]]
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def cast_not_none(value: Optional[T]) -> T:
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assert value is not None
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return value
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def weighted_sample(world_random: Random, population: List[T], weights: List[float], k: int) -> List[T]:
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positions = range(len(population))
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indices: List[int] = []
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while True:
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needed = k - len(indices)
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if not needed:
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break
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for i in world_random.choices(positions, weights, k=needed):
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if weights[i]:
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weights[i] = 0.0
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indices.append(i)
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return [population[i] for i in indices]
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def build_weighted_int_list(inputs: Collection[float], total: int) -> List[int]:
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"""
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Converts a list of floats to a list of ints of a given length, using the Largest Remainder Method.
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"""
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# Scale the inputs to sum to the desired total.
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scale_factor: float = total / sum(inputs)
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scaled_input = [x * scale_factor for x in inputs]
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# Generate whole number counts, always rounding down.
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rounded_output: List[int] = [floor(x) for x in scaled_input]
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rounded_sum = sum(rounded_output)
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# If the output's total is insufficient, increment the value that has the largest remainder until we meet our goal.
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remainders: List[float] = [real - rounded for real, rounded in zip(scaled_input, rounded_output)]
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while rounded_sum < total:
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max_remainder = max(remainders)
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if max_remainder == 0:
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break
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# Consume the remainder and increment the total for the given target.
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max_remainder_index = remainders.index(max_remainder)
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remainders[max_remainder_index] = 0
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rounded_output[max_remainder_index] += 1
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rounded_sum += 1
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return rounded_output
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def define_new_region(region_string: str) -> Tuple[Dict[str, Any], Set[Tuple[str, WitnessRule]]]:
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"""
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Returns a region object by parsing a line in the logic file
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"""
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region_string = region_string[:-1]
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line_split = region_string.split(" - ")
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region_name_full = line_split.pop(0)
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region_name_split = region_name_full.split(" (")
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region_name = region_name_split[0]
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region_name_simple = region_name_split[1][:-1]
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options = set()
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for _ in range(len(line_split) // 2):
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connected_region = line_split.pop(0)
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corresponding_lambda = line_split.pop(0)
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options.add(
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(connected_region, parse_lambda(corresponding_lambda))
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)
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region_obj = {
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"name": region_name,
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"shortName": region_name_simple,
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"entities": [],
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"physical_entities": [],
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}
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return region_obj, options
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def parse_lambda(lambda_string: str) -> WitnessRule:
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"""
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Turns a lambda String literal like this: a | b & c
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into a set of sets like this: {{a}, {b, c}}
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The lambda has to be in DNF.
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"""
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if lambda_string == "True":
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return frozenset([frozenset()])
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split_ands = set(lambda_string.split(" | "))
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return frozenset({frozenset(a.split(" & ")) for a in split_ands})
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_adjustment_file_cache = {}
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def get_adjustment_file(adjustment_file: str) -> List[str]:
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if adjustment_file not in _adjustment_file_cache:
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data = get_data(__name__, adjustment_file)
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if data is None:
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raise FileNotFoundError(f"Could not find {adjustment_file}")
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_adjustment_file_cache[adjustment_file] = [line.strip() for line in data.decode("utf-8").split("\n")]
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return _adjustment_file_cache[adjustment_file]
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def get_disable_unrandomized_list() -> List[str]:
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return get_adjustment_file("settings/Exclusions/Disable_Unrandomized.txt")
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def get_early_caves_list() -> List[str]:
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return get_adjustment_file("settings/Early_Caves.txt")
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def get_early_caves_start_list() -> List[str]:
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return get_adjustment_file("settings/Early_Caves_Start.txt")
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def get_symbol_shuffle_list() -> List[str]:
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return get_adjustment_file("settings/Symbol_Shuffle.txt")
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def get_complex_doors() -> List[str]:
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return get_adjustment_file("settings/Door_Shuffle/Complex_Doors.txt")
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def get_simple_doors() -> List[str]:
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return get_adjustment_file("settings/Door_Shuffle/Simple_Doors.txt")
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def get_complex_door_panels() -> List[str]:
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return get_adjustment_file("settings/Door_Shuffle/Complex_Door_Panels.txt")
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def get_complex_additional_panels() -> List[str]:
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return get_adjustment_file("settings/Door_Shuffle/Complex_Additional_Panels.txt")
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def get_simple_panels() -> List[str]:
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return get_adjustment_file("settings/Door_Shuffle/Simple_Panels.txt")
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def get_simple_additional_panels() -> List[str]:
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return get_adjustment_file("settings/Door_Shuffle/Simple_Additional_Panels.txt")
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def get_boat() -> List[str]:
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return get_adjustment_file("settings/Door_Shuffle/Boat.txt")
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def get_laser_shuffle() -> List[str]:
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return get_adjustment_file("settings/Laser_Shuffle.txt")
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def get_audio_logs() -> List[str]:
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return get_adjustment_file("settings/Audio_Logs.txt")
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def get_ep_all_individual() -> List[str]:
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return get_adjustment_file("settings/EP_Shuffle/EP_All.txt")
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def get_ep_obelisks() -> List[str]:
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return get_adjustment_file("settings/EP_Shuffle/EP_Sides.txt")
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def get_obelisk_keys() -> List[str]:
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return get_adjustment_file("settings/Door_Shuffle/Obelisk_Keys.txt")
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def get_ep_easy() -> List[str]:
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return get_adjustment_file("settings/EP_Shuffle/EP_Easy.txt")
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def get_ep_no_eclipse() -> List[str]:
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return get_adjustment_file("settings/EP_Shuffle/EP_NoEclipse.txt")
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def get_vault_exclusion_list() -> List[str]:
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return get_adjustment_file("settings/Exclusions/Vaults.txt")
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def get_discard_exclusion_list() -> List[str]:
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return get_adjustment_file("settings/Exclusions/Discards.txt")
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def get_caves_except_path_to_challenge_exclusion_list() -> List[str]:
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return get_adjustment_file("settings/Exclusions/Caves_Except_Path_To_Challenge.txt")
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def get_elevators_come_to_you() -> List[str]:
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return get_adjustment_file("settings/Door_Shuffle/Elevators_Come_To_You.txt")
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def get_entity_hunt() -> List[str]:
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return get_adjustment_file("settings/Entity_Hunt.txt")
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def get_sigma_normal_logic() -> List[str]:
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return get_adjustment_file("WitnessLogic.txt")
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def get_sigma_expert_logic() -> List[str]:
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return get_adjustment_file("WitnessLogicExpert.txt")
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def get_umbra_variety_logic() -> List[str]:
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return get_adjustment_file("WitnessLogicVariety.txt")
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def get_vanilla_logic() -> List[str]:
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return get_adjustment_file("WitnessLogicVanilla.txt")
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def get_items() -> List[str]:
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return get_adjustment_file("WitnessItems.txt")
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def optimize_witness_rule(witness_rule: WitnessRule) -> WitnessRule:
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"""Removes any redundant terms from a logical formula in disjunctive normal form.
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This means removing any terms that are a superset of any other term get removed.
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This is possible because of the boolean absorption law: a | (a & b) = a"""
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to_remove = set()
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for option1 in witness_rule:
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for option2 in witness_rule:
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if option2 < option1:
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to_remove.add(option1)
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return witness_rule - to_remove
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def logical_and_witness_rules(witness_rules: Iterable[WitnessRule]) -> WitnessRule:
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"""
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performs the "and" operator on a list of logical formula in disjunctive normal form, represented as a set of sets.
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A logical formula might look like this: {{a, b}, {c, d}}, which would mean "a & b | c & d".
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These can be easily and-ed by just using the boolean distributive law: (a | b) & c = a & c | a & b.
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"""
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current_overall_requirement: FrozenSet[FrozenSet[str]] = frozenset({frozenset()})
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for next_dnf_requirement in witness_rules:
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new_requirement: Set[FrozenSet[str]] = set()
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for option1 in current_overall_requirement:
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for option2 in next_dnf_requirement:
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new_requirement.add(option1 | option2)
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current_overall_requirement = frozenset(new_requirement)
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return optimize_witness_rule(current_overall_requirement)
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def logical_or_witness_rules(witness_rules: Iterable[WitnessRule]) -> WitnessRule:
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return optimize_witness_rule(frozenset.union(*witness_rules))
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