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Evaluation

danield5732 edited this page Apr 26, 2021 · 1 revision

The following methods are used to curate and visualize the results gained by robustness testing. This is called evaluation functionalities.


1. Methods

1.1 summarize

summarize(path, select_groups = [], condense_results = True, sort_samples = False)

Parameters:

  • path: str.

Optional:

  • select_groups: list. default []
  • condense_results: boolean. default True
  • sort_samples: boolean. default False

1.2 concatenate

concatenate(dfs, sample_order = [])

Parameters:

  • dfs: list.

Optional:

  • sample_order: list. default []

1.3 bar_plot_results

bar_plot_results(df, show_groups = [], group_by = 'samples', y_unit = 'mymol_per_g', x_gap = 1, save = False, title = True)

Parameters:

  • reference: str. Default 'load' Unique root name of reference measurement. If default, tries to read reference from Samplelog.xlsx.

Optional:

  • show_groups: list. default []
  • group_by: {'samples', 'groups'}. default 'samples'
  • y_unit: str. default 'mymol_per_g'
  • x_gap: float. default 1
  • save: boolean. default False
  • title: boolean. default True

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