Remove tmp consistency metric

Author: lisehr

metis/__init__.py

@@ -1,41 +0,0 @@
-import pandas as pd
-from typing import List, Union
-
-from metis.utils.result import DQResult
-from metis.metric.metric import Metric
-
-class Consistency(Metric):
-    def assess(self, data: pd.DataFrame, reference: Union[pd.DataFrame, None] = None, metric_config: Union[str, None] = None) -> List[DQResult]:
-        """
-        Assess the consistency of the data by checking data values against a set of rules.
-        Consistency metrics implemented according to the definition of Hinrichs, H. (2002). Doctoral dissertation, Universität Oldenburg.
-        
-        :param data: DataFrame to assess.
-        :param metric_config: Mandatory configuration for the metric, which at least contains a list of rules and optional weights. 
-        :return: List of DQResult objects containing consistency results.
-        """
-        results = []
-        total_rows = len(data)
-        if metric_config is None or 'rules' not in metric_config:
-            raise ValueError("metric_config must contain 'rules' key with a list of rules.")
-        rules = metric_config['rules']
-        weight = metric_config['weights'] # TODO: set weights to 1 if not provided
-        valid_count = 0
-
-        for idx, row in data.iterrows:
-            is_valid = all(rule(row) for rule in rules)
-            if is_valid
-                valid_count += weight[idx] if idx < len(weight) else 1
-
-            consistency = valid_count / total_rows if total_rows > 0 else 0
-            
-            result = DQResult(
-                mesTime=pd.Timestamp.now(),
-                DQvalue=consistency,
-                DQdimension="Consistency",
-                DQmetric="Consistency",
-                columnNames=[column],
-            )
-            results.append(result)
-        
-        return results