calc.lib.cache.zarrmodels
=========================

.. py:module:: calc.lib.cache.zarrmodels

.. autoapi-nested-parse::

   Pydantic models for loading and saving data from zarr attributes (metadata)

   These models help to read and write structured data about variants and samples
   This data is helpful when working with the genotype array (variants = row names,
   samples = column names).



Attributes
----------

.. autoapisummary::

   calc.lib.cache.zarrmodels.logger


Classes
-------

.. autoapisummary::

   calc.lib.cache.zarrmodels.ZarrSampleMetadata
   calc.lib.cache.zarrmodels.ZarrVariantMetadata


Functions
---------

.. autoapisummary::

   calc.lib.cache.zarrmodels.is_valid_allele


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

.. py:class:: ZarrSampleMetadata



   .. py:attribute:: root
      :type:  list[str]


.. py:class:: ZarrVariantMetadata



   A dataframe-y model, suitable for ingesting with pandas / polars / databases

   Useful for saving / loading data about variants into a group-level zarr attribute.

   Each target genome file will have its own variant metadata.


   .. py:method:: check_even_length() -> ZarrVariantMetadata


   .. py:method:: merge(other: ZarrVariantMetadata) -> ZarrVariantMetadata


   .. py:method:: to_df() -> polars.DataFrame


   .. py:method:: to_numpy() -> collections.abc.Mapping[str, numpy.typing.NDArray[Any]]

      Convert the dataframe into 1D arrays

      Handles converting strings to a consistent fixed width dtype



   .. py:attribute:: alts
      :type:  Annotated[list[list[str] | None], AfterValidator(is_valid_allele)]


   .. py:attribute:: chr_name
      :type:  list[str]


   .. py:attribute:: chr_pos
      :type:  list[pydantic.PositiveInt]


   .. py:attribute:: ref
      :type:  Annotated[list[str | None], AfterValidator(is_valid_allele)]


   .. py:attribute:: variant_id
      :type:  list[str]


.. py:function:: is_valid_allele(alleles: list[list[str] | None] | list[str | None]) -> list[list[str] | None] | list[str | None]

.. py:data:: logger