clophfit.prtecan.parsers
========================

.. py:module:: clophfit.prtecan.parsers

.. autoapi-nested-parse::

   Prtecan/prtecan.py.



Classes
-------

.. autoapisummary::

   clophfit.prtecan.parsers.Metadata


Functions
---------

.. autoapisummary::

   clophfit.prtecan.parsers.extract_metadata
   clophfit.prtecan.parsers.merge_md
   clophfit.prtecan.parsers.calculate_conc
   clophfit.prtecan.parsers.dilution_correction


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

.. py:class:: Metadata

   Represents the value of a metadata dictionary.

   :param value: The value for the dictionary key.
   :type value: int | str | float | None


   .. py:attribute:: unit
      :type:  collections.abc.Sequence[str | float | int] | None
      :value: None


      The first element represents the unit, while the following elements are only listed.


.. py:function:: extract_metadata(lines)

   Extract metadata into both Tecanfile and Labelblock.

   From a list of stripped lines takes the first field as the **key** of the
   metadata dictionary, remaining fields goes into a list of values with the
   exception of Label ([str]) and Temperature ([float]).

   :param lines: Lines (list_of_lines) that are a list of fields, typically from a
                 csv/xls file.
   :type lines: list[list[str | int | float]]

   :returns: Metadata for Tecanfile or Labelblock.
   :rtype: dict[str, Metadata]

   .. rubric:: Examples

   >>> lines = [
   ...     ["Shaking (Linear) Amplitude:", "", "", "", 2, "mm", "", "", "", "", ""]
   ... ]
   >>> extract_metadata(lines)
   {'Shaking (Linear) Amplitude:': Metadata(value=2, unit=['mm'])}

   >>> lines = [["", "Temperature: 26 °C", "", "", "", "", "", "", "", "", ""]]
   >>> extract_metadata(lines)
   {'Temperature': Metadata(value=26.0, unit=['°C'])}

   >>> lines = [["Excitation Wavelength", "", "", "", 400, "nm", "", "", "", "", ""]]
   >>> extract_metadata(lines)
   {'Excitation Wavelength': Metadata(value=400, unit=['nm'])}

   >>> lines = [["Label: Label1", "", "", "", "", "", "", "", "", "", "", "", ""]]
   >>> extract_metadata(lines)
   {'Label': Metadata(value='Label1', unit=None)}

   >>> lines = [["Mode", "", "", "", "Fluorescence Top Reading", "", "", "", "", ""]]
   >>> extract_metadata(lines)["Mode"].value
   'Fluorescence Top Reading'


.. py:function:: merge_md(mds)

   Merge a list of metadata dict if the key value is the same in the list.


.. py:function:: calculate_conc(additions, conc_stock, conc_ini = 0.0)

   Calculate concentration values.

   additions[0]=vol_ini; Stock concentration is a parameter.

   :param additions: Initial volume and all subsequent additions.
   :type additions: Sequence[float]
   :param conc_stock: Concentration of the stock used for additions.
   :type conc_stock: float
   :param conc_ini: Initial concentration (default=0).
   :type conc_ini: float

   :returns: Concentrations as vector.
   :rtype: ArrayF


.. py:function:: dilution_correction(additions)

   Apply dilution correction.

   :param additions: List of initial volume (index=0) followed by all additions.
   :type additions: list[float]

   :returns: Dilution correction vector.
   :rtype: ArrayF

   :raises ValueError: If additions list is empty or if initial volume is zero.