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Merge pull request #110 from jakobj/maint/ordered-primitives
Replace dictionary in Primitives with tuple and turn Primitives into frozen dataclass
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,81 +1,76 @@ | ||
| from dataclasses import dataclass, field | ||
| import numpy as np | ||
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| from typing import Iterator, List, Tuple, Type | ||
| from typing import Iterator, Tuple, Type | ||
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| from .node import Node | ||
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| @dataclass(frozen=True) | ||
| class Primitives: | ||
| """Class collecting primitives of the Cartesian Genetic Programming framework. | ||
| """ | ||
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| _max_arity = 0 | ||
| _primitives: dict = {} | ||
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| def __init__(self, primitives: List[Type[Node]]) -> None: | ||
| """Init function. | ||
| """Convenience class to manage primitives, i.e., Node classes. | ||
| Parameters | ||
| ---------- | ||
| primitives : List[Type[Node]] | ||
| List of primitives. | ||
| """ | ||
| for i in range(len(primitives)): | ||
| if not isinstance(primitives[i], type): | ||
| raise TypeError(f"expected class but received {type(primitives[i])}") | ||
| if not issubclass(primitives[i], Node): | ||
| raise TypeError(f"expected subclass of Node but received {primitives[i].__name__}") | ||
| """ | ||
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| self._primitives = {} | ||
| for i in range(len(primitives)): | ||
| self._primitives[i] = primitives[i] | ||
| _primitives: Tuple[Type[Node], ...] | ||
| _max_arity: int = field(init=False) | ||
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| # hide primitives dict behind MappingProxyType to make sure it | ||
| # is not changed after construction | ||
| # unfortunately not supported by pickle, necessary for | ||
| # multiprocessing; another way to implement this? | ||
| # self._primitives = types.MappingProxyType(self._primitives) | ||
| def __post_init__(self): | ||
| self._check_types() | ||
| self.__dict__[ | ||
| "_max_arity" | ||
| ] = self._determine_max_arity() # avoid using use __setattr_ since dataclass is frozen | ||
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| self._determine_max_arity() | ||
| def _check_types(self): | ||
| if not isinstance(self._primitives, tuple): | ||
| raise TypeError(f"expected tuple but received {type(self._primitives)}") | ||
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| def __iter__(self) -> Iterator: | ||
| return iter([self[i] for i in range(len(self._primitives))]) | ||
| for i in range(len(self._primitives)): | ||
| if not isinstance(self._primitives[i], type): | ||
| raise TypeError( | ||
| f"expected class but received instance of {type(self._primitives[i])}" | ||
| ) | ||
| if not issubclass(self._primitives[i], Node): | ||
| raise TypeError( | ||
| f"expected subclass of Node but received class {self._primitives[i].__name__}" | ||
| ) | ||
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| def _determine_max_arity(self) -> None: | ||
| def _determine_max_arity(self) -> int: | ||
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| arity = 1 # minimal possible arity (output nodes need one input) | ||
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| for idx, p in self._primitives.items(): | ||
| for p in self._primitives: | ||
| if arity < p._arity: | ||
| arity = p._arity | ||
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| self._max_arity = arity | ||
| return arity | ||
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| def __iter__(self) -> Iterator[Type[Node]]: | ||
| return iter(self._primitives) | ||
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| def sample(self, rng: np.random.RandomState) -> int: | ||
| """Sample a random primitive. | ||
| def sample_allele(self, rng: np.random.RandomState) -> int: | ||
| """Sample a random primitive index. | ||
| Parameters | ||
| ---------- | ||
| rng : numpy.RandomState | ||
| Random number generator instance to use for crossover. | ||
| Random number generator instance. | ||
| Returns | ||
| ------- | ||
| int | ||
| Index of the sample primitive | ||
| Index of the sampled primitive. | ||
| """ | ||
| return rng.choice(self.alleles) | ||
| return rng.randint(len(self._primitives)) | ||
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| def __getitem__(self, key: int) -> Type[Node]: | ||
| if key < 0 or key >= len(self._primitives): | ||
| raise IndexError("primitive index out of bounds") | ||
| return self._primitives[key] | ||
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| @property | ||
| def max_arity(self) -> int: | ||
| return self._max_arity | ||
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| @property | ||
| def alleles(self) -> Tuple: | ||
| return tuple(self._primitives.keys()) | ||
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| def __len__(self): | ||
| return len(self._primitives) | ||
| def is_valid_allele(self, allele: int) -> bool: | ||
| return (allele >= 0) and (allele < len(self._primitives)) |
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