Source code for dantro.groups.time_series

"""Implements :py:class:`~dantro.groups.labelled.LabelledDataGroup`
specializations for time series data.

from . import is_group
from .labelled import LabelledDataGroup
from .ordered import IndexedDataGroup

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[docs]@is_group class TimeSeriesGroup(LabelledDataGroup, IndexedDataGroup): """A time-series group assumes that each stored member refers to one point in time, where the name is to be interpreted as the time coordinate. For more information on selection methods, see: * :py:meth:`~dantro.groups.labelled.LabelledDataGroup.sel` * :py:meth:`~dantro.groups.labelled.LabelledDataGroup.isel` """ LDG_DIMS = ("time",) """Expected dimension names. There is only one dimension in a TimeSeriesGroup: ``time``""" LDG_EXTRACT_COORDS_FROM = "name" """Where to extract time coordinates from. Here, the container name is expected to be the time coordinate."""
[docs]@is_group class HeterogeneousTimeSeriesGroup(TimeSeriesGroup): """This extends the :py:class:`~dantro.groups.time_series.TimeSeriesGroup` by configuring it such that it retrieves its coordinates not from the name of the members contained in it but from _their_ data. It still manages only the ``time`` dimension, which is now overlapping with the ``time`` dimension in the members of this group. However, the py:class:`~dantro.groups.labelled.LabelledDataGroup` can handle this overlap and provides a uniform selection interface that allows combining this heterogeneously stored data. This becomes especially useful in cases where the members of this group store data with the following properties: * Potentially different coordiantes than the coordinates of other members of the group. * Containing time information for more than a single time coordinate * No guarantee for overlaps between ``time`` dimension or any other dimension. As such it is suitable to work with data that represents ensembles that frequently change not only their size but also their identifying labels. Additionally, it supports them not being stored in regular intervals but only upon a change in coordinates. """ LDG_EXTRACT_COORDS_FROM = "data" """Where to extract coordinates from. Here, coordinates are extracted from the data directly, inspecting only the group-level dimensions (``time``). """