"""
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Test extension array that has custom attribute information (not stored on the dtype).
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"""
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from __future__ import annotations
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import numbers
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import numpy as np
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from pandas._typing import type_t
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from pandas.core.dtypes.base import ExtensionDtype
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import pandas as pd
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from pandas.core.arrays import ExtensionArray
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class FloatAttrDtype(ExtensionDtype):
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type = float
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name = "float_attr"
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na_value = np.nan
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@classmethod
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def construct_array_type(cls) -> type_t[FloatAttrArray]:
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"""
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Return the array type associated with this dtype.
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Returns
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-------
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type
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"""
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return FloatAttrArray
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class FloatAttrArray(ExtensionArray):
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dtype = FloatAttrDtype()
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__array_priority__ = 1000
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def __init__(self, values, attr=None) -> None:
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if not isinstance(values, np.ndarray):
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raise TypeError("Need to pass a numpy array of float64 dtype as values")
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if not values.dtype == "float64":
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raise TypeError("Need to pass a numpy array of float64 dtype as values")
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self.data = values
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self.attr = attr
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@classmethod
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def _from_sequence(cls, scalars, dtype=None, copy=False):
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data = np.array(scalars, dtype="float64", copy=copy)
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return cls(data)
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def __getitem__(self, item):
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if isinstance(item, numbers.Integral):
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return self.data[item]
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else:
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# slice, list-like, mask
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item = pd.api.indexers.check_array_indexer(self, item)
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return type(self)(self.data[item], self.attr)
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def __len__(self) -> int:
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return len(self.data)
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def isna(self):
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return np.isnan(self.data)
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def take(self, indexer, allow_fill=False, fill_value=None):
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from pandas.api.extensions import take
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data = self.data
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if allow_fill and fill_value is None:
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fill_value = self.dtype.na_value
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result = take(data, indexer, fill_value=fill_value, allow_fill=allow_fill)
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return type(self)(result, self.attr)
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def copy(self):
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return type(self)(self.data.copy(), self.attr)
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@classmethod
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def _concat_same_type(cls, to_concat):
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data = np.concatenate([x.data for x in to_concat])
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attr = to_concat[0].attr if len(to_concat) else None
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return cls(data, attr)
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