Complete implementation of number_rows and number_groups remodeling operations

[Copilot]

Overview

This PR completes the implementation of the number_rows and number_groups remodeling operations that were previously in a half-finished state. The validation and parameter handling were already implemented, but the actual operation logic was commented out.

Changes

NumberRowsOp (hed/tools/remodeling/operations/number_rows_op.py)

• Uncommented and activated the implementation code in the do_op() method
• Added numpy import for NaN handling
• Enhanced documentation with detailed parameter descriptions
• Fixed code quality issue by renaming filter to filter_mask (avoids shadowing Python builtin)
• Applied PEP8 formatting for line length compliance

Functionality: Numbers rows in a dataframe sequentially (1, 2, 3...). Supports optional filtering to only number rows where a specified column matches a given value, and can overwrite existing columns when configured.

NumberGroupsOp (hed/tools/remodeling/operations/number_groups_op.py)

• Implemented complete do_op() method logic for group numbering
• Added numpy import for NaN handling
• Enhanced documentation with detailed parameter descriptions
• Fixed critical bug: reads source column values from original dataframe when overwriting to prevent data loss
• Applied PEP8 formatting for line length compliance

Functionality: Numbers groups of rows based on start/stop markers in a source column. Supports configurable inclusion/exclusion of marker rows in the groups, and handles the edge case where the source and destination columns are the same.

Test Files

• Uncommented all test assertions in test_number_rows_op.py and test_number_groups.py
• Added required imports (numpy, pandas)
• Added missing if __name__ == '__main__': block to test_number_groups.py

Testing

• ✅ All 92 tests in tests/tools/remodeling/operations pass
• ✅ All code passes flake8 linting
• ✅ Both operations now have full test coverage with working assertions

Example Usage

import pandas as pd
from hed.tools.remodeling.operations.number_rows_op import NumberRowsOp

# Number all rows
df = pd.DataFrame({'onset': [1.0, 2.0, 3.0], 'code': ['A', 'B', 'A']})
op = NumberRowsOp({'number_column_name': 'row_num'})
df_new = op.do_op(None, df, 'test')
# Result: row_num column with values [1, 2, 3]

# Number only matching rows
op = NumberRowsOp({
    'number_column_name': 'trial_num',
    'match_value': {'column': 'code', 'value': 'A'}
})
df_new = op.do_op(None, df, 'test')
# Result: trial_num column with values [1, NaN, 2]

Closes #1123

Original prompt

Please finish the initial plan and don't try fixing test data. The initial plan (as stated in #1123) was only half completed.

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[qltysh]

2 new issues

Tool	Category	Rule	Count
qlty	Structure	Deeply nested control flow (level = 4)	2

[VisLab]

I didn't want you to try to implement this remodeling code.