expected_size_difference_from_table#

er_evaluation.expected_size_difference_from_table(error_table)[source]#

Compute expected size difference from record error table.

See er_evaluation.error_analysis.expected_size_difference().

Parameters:

error_table (DataFrame) – Record error table.

Returns:

Expected size difference for each reference cluster.

Return type:

Series

Examples

>>> prediction = pd.Series(index=[1,2,3,4,5,6,7,8], data=[1,1,2,3,2,4,4,4])
>>> sample = pd.Series(index=[1,2,3,4,5,6,7], data=["c1", "c1", "c1", "c2", "c2", "c3", "c3"])
>>> error_table = record_error_table(prediction, sample)
>>> expected_size_difference_from_table(error_table)
reference
c1   -1.0
c2   -0.5
c3    1.0
Name: expected_size_diff, dtype: float64

The result is the same as calling er_evaluation.error_analysis.expected_size_difference() on prediction and sample:

>>> from er_evaluation.error_analysis import expected_size_difference
>>> expected_size_difference(prediction, sample)
reference
c1   -1.0
c2   -0.5
c3    1.0
Name: expected_size_diff, dtype: float64