pgfinder.pgio
=============

.. py:module:: pgfinder.pgio

.. autoapi-nested-parse::

   PG Finder I/O operations

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Attributes
----------

.. autoapisummary::

   pgfinder.pgio.LOGGER


Functions
---------

.. autoapisummary::

   pgfinder.pgio.ms_file_reader
   pgfinder.pgio.ftrs_reader
   pgfinder.pgio._select_and_order_columns
   pgfinder.pgio.theo_masses_reader
   pgfinder.pgio.maxquant_file_reader
   pgfinder.pgio.dataframe_to_csv_metadata
   pgfinder.pgio.default_filename
   pgfinder.pgio.read_yaml


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

.. py:data:: LOGGER

.. py:function:: ms_file_reader(file: str | pathlib.Path) -> pandas.DataFrame

   
   Read mass spec data.

   :param file: Path to be loaded.
   :type file: str | Path

   :returns: File loaded as Pandas Dataframe.
   :rtype: pd.DataFrame















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.. py:function:: ftrs_reader(file: str | pathlib.Path, columns: dict = COLUMNS) -> pandas.DataFrame

   
   Reads Features file from Byos.

   :param file: Feature file to be read.
   :type file: str | Path
   :param columns: Dictionary of columns, this defaults to the global COLUMNS which is read from 'config/columns.yaml' and
   :type columns: dict
   :param simplifies extension to new formats.:

   :returns: Pandas DataFrame of features.
   :rtype: pd.DataFrame















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.. py:function:: _select_and_order_columns(df: pandas.DataFrame, columns: dict = COLUMNS) -> pandas.DataFrame

   
   Select (renamed) columns and order them.

   :param df: Full dataframe from which a subset of variables is to be returned.
   :type df: pd.DataFrame
   :param columns: Dictionary of columns, this defaults to the global COLUMNS which is read from 'config/columns.yaml' and
   :type columns: dict
   :param simplifies extension to new formats.:

   :returns: Subset of data frame with selected columns in specified order.
   :rtype: pd.DataFrame















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.. py:function:: theo_masses_reader(file: str | pathlib.Path) -> pandas.DataFrame

   
   Reads theoretical masses files (csv) returning a Panda Dataframe

   :param file: Path to file to be loaded.
   :type file: str | Path

   :returns: Pandas DataFrame of theoretical masses.
   :rtype: pd.DataFrame















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.. py:function:: maxquant_file_reader(file: str | pathlib.Path, columns: dict = COLUMNS)

   
   Reads maxquant files and outputs data as a dataframe.

   :param filepath: Path to a text file.
   :type filepath: str | Path
   :param columns: Dictionary of columns, this defaults to the global COLUMNS which is read from 'config/columns.yaml' and
   :type columns: dict
   :param simplifies extension to new formats.:

   :returns: Pandas Data frame.
   :rtype: pd.DataFrame















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.. py:function:: dataframe_to_csv_metadata(output_dataframe: pandas.DataFrame, save_filepath: str | pathlib.Path = None, filename: str | pathlib.Path = None, float_format: str = '%.4f') -> str | None

   
   Convert dataframe to CSV with metadata.

   If save_filepath is specified return the relative path of the output file, including the filename, otherwise
   return the .csv in the form of a string.

   :param output_dataframe: Dataframe to output.
   :type output_dataframe: pd.DataFrame
   :param save_filepath: Path to save to.
   :type save_filepath: str | Path
   :param filename: Filename to save to.
   :type filename: str | Path
   :param float_format: Format for floating point numbers (default 4 decimal places).
   :type float_format: str

   :returns: Either returns the path to write data to or writes it to CSV.
   :rtype: str | None















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.. py:function:: default_filename(prefix: str = 'results_') -> str

   
   Generate a default filename based on the current date/time.

   :param prefix: String to use as a prefix, default is 'results_'.
   :type prefix: str

   :returns: Filename with format 'results_YYYY-MM-DD-hh-mm-ss.csv'.
   :rtype: str















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.. py:function:: read_yaml(filename: str | pathlib.Path) -> dict

   
   Read a YAML file.

   :param filename: YAML file to read.
   :type filename: str | Path

   :returns: Dictionary of the file.
   :rtype: dict















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