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from typing import Any |
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import numpy as np |
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from typish import SubscriptableType |
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from nptyping.types._nptype import NPType |
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def is_subarray_type(dtype: np.dtype) -> bool: |
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"""Detect if the type is a subarray.""" |
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return (hasattr(dtype, 'shape') |
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and isinstance(dtype.shape, tuple) |
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and len(dtype.shape) != 0) |
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View Code Duplication |
class _SubArrayTypeMeta(SubscriptableType): |
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def __hash__(cls) -> int: |
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return hash((cls.base, cls.shape)) |
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def __repr__(cls) -> str: |
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if cls.base is not None: |
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return 'SubArrayType[{0}, {1}]'.format(cls.base, cls.shape) |
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return 'SubArrayType' |
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def __eq__(cls, instance: Any) -> bool: |
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if hasattr(instance, 'base') and hasattr(instance, 'shape'): |
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return instance.base == cls.base and instance.shape == cls.shape |
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return False |
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def __instancecheck__(cls, instance: Any) -> bool: |
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from nptyping.functions._get_type import get_type |
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if is_subarray_type(instance): |
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if cls == instance: |
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return True |
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return cls == get_type(instance) |
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return False |
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__str__ = __repr__ |
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__subclasscheck__ = __eq__ |
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View Code Duplication |
class SubArrayType(NPType, metaclass=_SubArrayTypeMeta): |
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""" |
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Corresponds to the dtype of a NumPy subarray. |
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""" |
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base = None |
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shape = None |
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@classmethod |
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def _after_subscription(cls, args: Any) -> None: |
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from nptyping.functions._get_type import get_type |
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if isinstance(args, np.dtype): |
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cls.base = get_type(args.base) |
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cls.shape = args.shape |
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elif isinstance(args, tuple): |
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cls.base, cls.shape = args |
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else: |
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raise Exception( |
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'Incompatible arguments to SubArrayType: {}'.format(args)) |
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ramonhagenaars /
nptyping
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