dacapo.store.local_array_store
==============================

.. py:module:: dacapo.store.local_array_store


Attributes
----------

.. autoapisummary::

   dacapo.store.local_array_store.logger


Classes
-------

.. autoapisummary::

   dacapo.store.local_array_store.LocalArrayStore


Module Contents
---------------

.. py:data:: logger

.. py:class:: LocalArrayStore(basedir)



   A local array store that uses zarr containers.

   .. attribute:: basedir

      The base directory where the store will write data.

   .. method:: best_validation_array

      Get the array identifier for the best validation array.

   .. method:: validation_prediction_array

      Get the array identifier for a particular validation prediction.

   .. method:: validation_output_array

      Get the array identifier for a particular validation output.

   .. method:: validation_input_arrays

      Get the array identifiers for the validation input raw/gt.

   .. method:: snapshot_container

      Get a container identifier for storage of a snapshot.

   .. method:: validation_container

      Get a container identifier for storage of a validation.

   .. method:: remove

      Remove a dataset from a container.
      
      


   .. py:attribute:: basedir


   .. py:method:: best_validation_array(run_name: str, criterion: str, index: Optional[str] = None) -> dacapo.store.array_store.LocalArrayIdentifier

      Get the array identifier for the best validation array.

      :param run_name: The name of the run.
      :type run_name: str
      :param criterion: The criterion for the validation array.
      :type criterion: str
      :param index: The index of the validation array. Defaults to None.
      :type index: str, optional

      :returns: The array identifier for the best validation array.
      :rtype: LocalArrayIdentifier

      :raises ValueError: If the container does not exist.

      .. rubric:: Examples

      >>> store.best_validation_array("run1", "loss")



   .. py:method:: validation_prediction_array(run_name: str, iteration: int, dataset: str) -> dacapo.store.array_store.LocalArrayIdentifier

      Get the array identifier for a particular validation prediction.

      :param run_name: The name of the run.
      :type run_name: str
      :param iteration: The iteration of the validation prediction.
      :type iteration: int
      :param dataset: The dataset of the validation prediction.
      :type dataset: str

      :returns: The array identifier for the validation prediction.
      :rtype: LocalArrayIdentifier

      :raises ValueError: If the container does not exist.

      .. rubric:: Examples

      >>> store.validation_prediction_array("run1", 0, "train")



   .. py:method:: validation_output_array(run_name: str, iteration: int, parameters: str, dataset: str) -> dacapo.store.array_store.LocalArrayIdentifier

      Get the array identifier for a particular validation output.

      :param run_name: The name of the run.
      :type run_name: str
      :param iteration: The iteration of the validation output.
      :type iteration: int
      :param parameters: The parameters of the validation output.
      :type parameters: str
      :param dataset: The dataset of the validation output.
      :type dataset: str

      :returns: The array identifier for the validation output.
      :rtype: LocalArrayIdentifier

      :raises ValueError: If the container does not exist.

      .. rubric:: Examples

      >>> store.validation_output_array("run1", 0, "params1", "train")



   .. py:method:: validation_input_arrays(run_name: str, index: Optional[str] = None) -> Tuple[dacapo.store.array_store.LocalArrayIdentifier, dacapo.store.array_store.LocalArrayIdentifier]

      Get the array identifiers for the validation input raw/gt.

      It would be nice to store raw/gt with the validation predictions/outputs.
      If we don't store these we would have to look up the datasplit config
      and figure out where to find the inputs for each run. If we write
      the data then we don't need to search for it.
      This convenience comes at the cost of some extra memory usage.

      :param run_name: The name of the run.
      :type run_name: str
      :param index: The index of the validation input. Defaults to None.
      :type index: str, optional

      :returns: The array identifiers for the validation input raw/gt.
      :rtype: Tuple[LocalArrayIdentifier, LocalArrayIdentifier]

      :raises ValueError: If the container does not exist.

      .. rubric:: Examples

      >>> store.validation_input_arrays("run1")



   .. py:method:: snapshot_container(run_name: str) -> dacapo.store.array_store.LocalContainerIdentifier

      Get a container identifier for storage of a snapshot.

      :param run_name: The name of the run.
      :type run_name: str

      :returns: The container identifier for the snapshot.
      :rtype: LocalContainerIdentifier

      :raises ValueError: If the container does not exist.

      .. rubric:: Examples

      >>> store.snapshot_container("run1")



   .. py:method:: validation_container(run_name: str) -> dacapo.store.array_store.LocalContainerIdentifier

      Get a container identifier for storage of a validation.

      :param run_name: The name of the run.
      :type run_name: str

      :returns: The container identifier for the validation.
      :rtype: LocalContainerIdentifier

      :raises ValueError: If the container does not exist.

      .. rubric:: Examples

      >>> store.validation_container("run1")



   .. py:method:: remove(array_identifier: dacapo.store.array_store.LocalArrayIdentifier) -> None

      Remove a dataset from a container.

      :param array_identifier: The array identifier of the dataset to remove.
      :type array_identifier: LocalArrayIdentifier

      :raises ValueError: If the container path does not end with '.zarr'.

      .. rubric:: Examples

      >>> store.remove(array_identifier)