Source code for geoh5py.data.text_data

#  Copyright (c) 2024 Mira Geoscience Ltd.
#
#  This file is part of geoh5py.
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#  geoh5py is free software: you can redistribute it and/or modify
#  it under the terms of the GNU Lesser General Public License as published by
#  the Free Software Foundation, either version 3 of the License, or
#  (at your option) any later version.
#
#  geoh5py is distributed in the hope that it will be useful,
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#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#  GNU Lesser General Public License for more details.
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from __future__ import annotations

import json

import numpy as np

from .data import Data
from .primitive_type_enum import PrimitiveTypeEnum


[docs] class TextData(Data): _values: np.ndarray | str | None @property def nan_value(self): """ Nan-Data-Value to be used in arrays """ return ""
[docs] @classmethod def primitive_type(cls) -> PrimitiveTypeEnum: return PrimitiveTypeEnum.TEXT
@property def values(self) -> np.ndarray | str | None: """ :obj:`str` Text value. """ if (getattr(self, "_values", None) is None) and self.on_file: values = self.workspace.fetch_values(self) if isinstance(values, np.ndarray) and values.dtype == object: values = np.array( [v.decode("utf-8") if isinstance(v, bytes) else v for v in values] ) if isinstance(values, (np.ndarray, str, type(None))): self._values = values return self._values @values.setter def values(self, values: np.ndarray | str | None): if isinstance(values, bytes): values = values.decode() if isinstance(values, np.ndarray) and values.dtype == object: values = values.astype(str) if (not isinstance(values, (str, type(None), np.ndarray))) or ( isinstance(values, np.ndarray) and values.dtype.kind not in ["U", "S"] ): raise ValueError( f"Input 'values' for {self} must be of type {np.ndarray} str or None." ) self._values = values self.workspace.update_attribute(self, "values")
[docs] class CommentsData(Data): """ Comments added to an Object or Group. Stored as a list of dictionaries with the following keys: .. code-block:: python comments = [ { "Author": "username", "Date": "2020-05-21T10:12:15", "Text": "A text comment." }, ] """
[docs] @classmethod def primitive_type(cls) -> PrimitiveTypeEnum: return PrimitiveTypeEnum.TEXT
@property def values(self) -> list[dict] | None: """ :obj:`list` List of comments """ if (getattr(self, "_values", None) is None) and self.on_file: comment_str = self.workspace.fetch_values(self) if isinstance(comment_str, str): self._values = json.loads(comment_str)["Comments"] return self._values @values.setter def values(self, values): self.workspace.update_attribute(self, "values") if values is not None: for value in values: assert isinstance(value, dict), ( f"Error setting CommentsData with expected input of type list[dict].\n" f"Input {type(values)} provided." ) assert list(value.keys()) == ["Author", "Date", "Text"], ( f"Comment dictionaries must include keys 'Author', 'Date' and 'Text'.\n" f"Keys {list(value.keys())} provided." ) self._values = values self.workspace.update_attribute(self, "values")
[docs] class MultiTextData(Data): _values: np.ndarray | str | None
[docs] @classmethod def primitive_type(cls) -> PrimitiveTypeEnum: return PrimitiveTypeEnum.MULTI_TEXT
@property def values(self) -> np.ndarray | str | None: """ :obj:`str` Text value. """ if (getattr(self, "_values", None) is None) and self.on_file: values = self.workspace.fetch_values(self) if isinstance(values, (np.ndarray, str, type(None))): self._values = values return self._values @values.setter def values(self, values: np.ndarray | str | None): self._values = values if not isinstance(values, (np.ndarray, str, type(None))): raise ValueError( f"Input 'values' for {self} must be of type {np.ndarray} str or None." ) self.workspace.update_attribute(self, "values")