olaf.processing.spaced_temp_csv
===============================

.. py:module:: olaf.processing.spaced_temp_csv


Classes
-------

.. autoapisummary::

   olaf.processing.spaced_temp_csv.SpacedTempCSV


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

.. py:class:: SpacedTempCSV(folder_path, num_samples, includes = ('base', ), excludes = ('frozen', ), date_col = 'Date')

   Bases: :py:obj:`olaf.utils.data_handler.DataHandler`


   .. py:method:: create_temp_csv(dict_to_sample_dilution, temp_step = 0.5, temp_col = 'Avg_Temp', save = True)

      Creates a .csv file that contains the number of frozen wells per sample at
      temperatures with intervals off "temp_steps" (default: 0.5 C).
      folder (...). This function is automatically ran after the last image is
      reviewed and the GUI closes. It uses the data file to find the first frozen well.
      The logic is as follows:
      1. find the first row with a non-zero value for least diluted sample.
      2. Round this value to 1 decimal (first_frozen)
      3. Floor this value to the nearest 0.5 (round_temp_frozen)
      4. subtract temp_step from that value (start_temp)
      5. Add (3) and (4) as first rows to df, add (2) in first loop of (7).
      6. Increment the temperature by temp_step until the end of the data.
      7. For each temperature, look at the band of temperatures that round to 1 decimal
         and find the (highest) number of frozen wells for each sample in that band.
      8. Save the data in a separate .csv file with the same name as the experiment.
      The data is saved in a separate .csv file with the same name as the experiment
      :param temp_step: The interval of temperatures to save (default: 0.5)
      :param temp_col: The column in the data file that contains the temperature values
      :param save: Whether to save the data to a .csv file (default: True)

      :returns: Dataframe, and saves the data in a .csv file if save is True