feature: Added time summarizer

Author: iraedeus

experimental_env/analysis/analyze_summarizers/time_summarizer.py

@@ -0,0 +1,64 @@
+""" A module that provides a class that save data about how the time of estimation is distributed """
+
+from pathlib import Path
+
+import numpy as np
+import yaml
+
+from experimental_env.analysis.analyze_summarizers.analysis_summarizer import (
+    AnalysisSummarizer,
+)
+from experimental_env.experiment.experiment_description import ExperimentDescription
+from experimental_env.utils import round_sig
+
+
+class TimeSummarizer(AnalysisSummarizer):
+    """
+    A class that calculates the average error for a dataset using the selected metric.
+    """
+
+    def calculate(self, results: list[ExperimentDescription]) -> tuple:
+        """
+        Helper function for calculating mean and standard deviation of time
+        """
+        times = []
+        for result in results:
+            time = np.sum(step.time for step in result.steps)
+            times.append(time)
+
+        mean = np.sum(times) / len(times)
+        deviation = np.sqrt(np.sum((x - mean) ** 2 for x in times) / len(times))
+        return float(mean), float(deviation)
+
+    def analyze_method(self, results: list[ExperimentDescription], method: str):
+        mean, deviation = self.calculate(results)
+
+        info_dict = {
+            "mean": round_sig(mean, 3),
+            "standart_deviation": round_sig(deviation, 3),
+        }
+        yaml_path: Path = self._out_dir.joinpath("time_info.yaml")
+
+        with open(yaml_path, "w", encoding="utf-8") as file:
+            yaml.dump(info_dict, file)
+
+    def compare_methods(
+        self,
+        results_1: list[ExperimentDescription],
+        results_2: list[ExperimentDescription],
+        method_1: str,
+        method_2: str,
+    ):
+        mean_1, deviation_1 = self.calculate(results_1)
+        mean_2, deviation_2 = self.calculate(results_2)
+
+        info_dict = {
+            f"{method_1}_mean": round_sig(mean_1, 3),
+            f"{method_1}_standart_deviation": round_sig(deviation_1, 3),
+            f"{method_2}_mean": round_sig(mean_2, 3),
+            f"{method_2}_standart_deviation": round_sig(deviation_2, 3),
+        }
+        yaml_path: Path = self._out_dir.joinpath("time_info.yaml")
+
+        with open(yaml_path, "w", encoding="utf-8") as file:
+            yaml.dump(info_dict, file)