Display tract profiles grouped by var_interest #136
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| def plot_profiles_by_group( | ||
| tracto_df:pd.DataFrame, |
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Type annotations! We haven't done any of those yet, but it's a good step into the future!
| tracto (pd.DataFrame): tractometry dataframe. | ||
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| Returns: | ||
| pd.DataFrame: tractometry dataframe, with embelishments for |
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This sentence seems to be curtailed.
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| def optimize(df:pd.DataFrame) -> pd.DataFrame: |
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This function name is rather generic. What does "optimize" mean here?
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And please add a docstring
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| """Utility functions to manipulate tractometry type dataframe | |||
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I think that these functions could be added to the existing "utils.py" file.
| def center_cut(df: pd.DataFrame, cut: tuple=(25,75)) -> pd.DataFrame: | ||
| """ Returns dataframe where the nodeID is cut between two indicated values. | ||
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| Args: |
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Please use the numpy docstring standard (used in other functions you wrote) here as well.
| sessions=1, | ||
| tracts=2, | ||
| ) -> pd.DataFrame: | ||
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| tractometry data | ||
| var_df : pd.DataFrame | ||
| dataframe with categorical or pseudocontinuous variable of interest | ||
| center_cut : bool, optional |
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Maybe we can allow center_cut to be a number between 0 and 1 that tells how much of the center to cut?
Prototype of generic function to display tract profiles, grouped by a variable of interest.
Todos: