calc.lib.scorefile
==================

.. py:module:: calc.lib.scorefile


Attributes
----------

.. autoapisummary::

   calc.lib.scorefile.logger


Classes
-------

.. autoapisummary::

   calc.lib.scorefile.Scorefiles


Functions
---------

.. autoapisummary::

   calc.lib.scorefile.get_position_df
   calc.lib.scorefile.load_scoring_files


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

.. py:class:: Scorefiles(paths: calc.lib.types.Pathish | calc.lib.types.PathishList)

   One or more scoring files processed with the `pgscatalog-format` program.


   .. py:method:: get_unique_positions(chrom: str | None = None, zarr_group: zarr.Group | None = None) -> list[tuple[str, int]]


   .. py:attribute:: column_types


   .. py:property:: paths
      :type: list[pathlib.Path]


      Return the list of scoring file paths.



.. py:function:: get_position_df(zarr_group: zarr.Group) -> polars.DataFrame

   Get variants from the "meta" zarr group array


.. py:function:: load_scoring_files(db_path: calc.lib.types.Pathish, scorefile_paths: calc.lib.types.PathishList, max_memory_gb: str, threads: int) -> None

   Load scoring files into the score_variant_table

   Parameters
   ----------
   db_path : Pathish
       Path to the DuckDB database file.
   scorefile_paths : PathishList
       A list of Pathish objects to the scoring CSV file(s). Scoring files must be
       in a  structured format as created by pgscatalog-format.
   max_memory_gb : str
       Maximum memory DuckDB is allowed to use (e.g., "4GB").
   threads : int
       Number of threads for DuckDB to use.

   Notes
   -----
   The score_variant_table is created or replaced each time this function is called.

   Effect weights are stored as double precision floating-point numbers
   (np.float64 equivalent). All previous processing (e.g. by pgscatalog.core) treats
   effect weights as strings to prevent precision problems.

   pgscatalog-format can process scoring files from the PGS Catalog or custom scoring
   files.


.. py:data:: logger