Source code for gmxapi.datamodel

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"""gmxapi data types and interfaces.
"""
import gmxapi

__all__ = ['ndarray', 'NDArray']

import collections

import gmxapi.abc
from gmxapi import exceptions


[docs]class NDArray(gmxapi.abc.NDArray): """N-Dimensional array type. """ def __init__(self, data=None): self._values = [] self.dtype = None self.shape = () if data is not None: if hasattr(data, 'result') or ( isinstance(data, collections.abc.Iterable) and any([hasattr(item, 'result') for item in data])): raise exceptions.ValueError( 'Make a Future of type NDArray instead of NDArray of type Future, or call result() first.') if isinstance(data, (str, bytes)): data = [data] length = 1 else: try: length = len(data) except TypeError: # data is a scalar length = 1 data = [data] self._values = data if length > 0: self.dtype = type(data[0]) self.shape = (length,) def to_list(self): return self._values def __getitem__(self, i: int): return self._values[i] def __len__(self) -> int: return len(self._values)
[docs]def ndarray(data=None, shape=None, dtype=None): """Create an NDArray object from the provided iterable. Arguments: data: object supporting sequence, buffer, or Array Interface protocol .. versionadded:: 0.1 *shape* and *dtype* parameters If `data` is provided, `shape` and `dtype` are optional. If `data` is not provided, both `shape` and `dtype` are required. If `data` is provided and shape is provided, `data` must be compatible with or convertible to `shape`. See Broadcast Rules in `datamodel` documentation. If `data` is provided and `dtype` is not provided, data type is inferred as the narrowest scalar type necessary to hold any element in `data`. `dtype`, whether inferred or explicit, must be compatible with all elements of `data`. The returned object implements the gmxapi N-dimensional Array Interface. """ if data is None: array = NDArray() else: if isinstance(data, NDArray): return data # data is not None, but may still be an empty sequence. length = 0 try: length = len(data) except TypeError: # data is a scalar length = 1 data = [data] array = NDArray(data) return array