auto column detection when initializing gaze

[dkrako]

Description of the problem

When working with local datasets we have to setup a bunch of different column names in the DatasetDefinition.
It would be much nicer if standard column namings could be inferred.

Description of a solution

In some cases column names could be guessed. As a starting point we could reuse our internal standard for preprocessed files:

pymovements/src/pymovements/dataset/dataset_files.py

Lines 283 to 296 in cb9ef95

	# suffixes as ordered after using GazeDataFrame.unnest()
	component_suffixes = ['x', 'y', 'xl', 'yl', 'xr', 'yr', 'xa', 'ya']
	pixel_columns = ['pixel_' + suffix for suffix in component_suffixes]
	pixel_columns = [c for c in pixel_columns if c in gaze_df.frame.columns]
	position_columns = ['position_' + suffix for suffix in component_suffixes]
	position_columns = [c for c in position_columns if c in gaze_df.frame.columns]
	velocity_columns = ['velocity_' + suffix for suffix in component_suffixes]
	velocity_columns = [c for c in velocity_columns if c in gaze_df.frame.columns]
	acceleration_columns = ['acceleration_' + suffix for suffix in component_suffixes]
	acceleration_columns = [c for c in acceleration_columns if c in gaze_df.frame.columns]

This would also very much simplify #714 as there's no need for an auto_nest argument then.

So I would propose to add a new argument to the init, for instance:

class GazeDataFrame:
    def __init__(
        ...
         auto_column_detect: bool = False,
        ...
    ):

The default could also be set to True but that could be a breaking change so I'm ambivalent.

For each attribute, for example pixel, we would then write something like this:

 component_suffixes = ['x', 'y', 'xl', 'yl', 'xr', 'yr', 'xa', 'ya'] 

if auto_column_detect and pixel_columns is None:  # I would vote for not overwriting specified columns
   column_canditates = ['pixel_' + suffix for suffix in component_suffixes] 
   pixel_columns = [c for c in column_canditates if c in gaze_df.frame.columns]

if pixel_columns:  # this part is from GazeDataFrame.__init__() and is false if the list is empty
   self._check_component_columns(pixel_columns=pixel_columns)
   self.nest(pixel_columns, output_column='pixel')
   column_specifiers.append(pixel_columns)

This is flexible enough for extending the column_candidates in a potential follow up.

Minimum acceptance criteria

• auto detect columns if adhering to the internal column naming standard for preprocessed csv files

[prassepaul]

fixed by #719