Add csv tables feature

VSharp.ML.AIAgent/config.py

@@ -34,6 +34,18 @@ def create_save_path_if_not_exists(self):
             self.save_path.mkdir()
 
 
+@dataclass(slots=True, frozen=True)
+class SaveEpochsCoveragesFeature:
+    enabled: bool
+    save_path: Path
+
+    def create_save_path_if_not_exists(self):
+        if self.enabled:
+            if self.save_path.exists():
+                rmtree(self.save_path)
+            self.save_path.mkdir()
+
+
 class FeatureConfig:
     VERBOSE_TABLES = True
     SHOW_SUCCESSORS = True
@@ -43,3 +55,6 @@ class FeatureConfig:
     DUMP_BY_TIMEOUT = DumpByTimeoutFeature(
         enabled=True, timeout_seconds=1200, save_path=Path("./report/timeouted_agents/")
     )
+    SAVE_EPOCHS_COVERAGES = SaveEpochsCoveragesFeature(
+        enabled=True, save_path=Path("./report/epochs_tables/")
+    )

VSharp.ML.AIAgent/epochs_statistics/tables.py

@@ -1,4 +1,5 @@
 from collections import defaultdict
+from pathlib import Path
 
 import pandas as pd
 
@@ -11,7 +12,7 @@
 from config import FeatureConfig
 from epochs_statistics.common import Interval, Name2ResultViewModel
 from epochs_statistics.gen_stats import compute_euc_dist_to_full_coverage
-from selection.classes import AgentResultsOnGameMaps, Agent2Result
+from selection.classes import Agent2Result, AgentResultsOnGameMaps
 from selection.utils import invert_mapping_mrgm_gmmr
 
 
@@ -43,20 +44,27 @@ def create_stats(
 
 def create_pivot_table(
     model_map_results_mapping: AgentResultsOnGameMaps, sort: bool = True
-) -> pd.DataFrame:
+) -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
     map_results_with_models = invert_mapping_mrgm_gmmr(model_map_results_mapping)
     euc_dists2full_cov, avs, medians, intervals = create_stats(
         model_map_results_mapping
     )
 
     name_results_dict: defaultdict[int, list[Name2ResultViewModel]] = defaultdict(list)
+    epoch_percents_dict: defaultdict[int, list[Name2ResultViewModel]] = defaultdict(
+        list
+    )
 
     for map_obj, mutable2result_list in map_results_with_models.items():
         for mutable2result in mutable2result_list:
             name_results_dict[map_obj.Id].append(convert_to_view_model(mutable2result))
+            epoch_percents_dict[map_obj.Id].append(
+                mutable2result.game_result.actual_coverage_percent
+            )
 
     mutable_names = get_model_names_in_order(name_results_dict)
     df = pd.DataFrame(name_results_dict, index=mutable_names)
+    epochs_percent_df = pd.DataFrame(epoch_percents_dict, index=mutable_names)
     for col in df:
         df[col] = df[col].map(lambda name2result_vm: name2result_vm.pretty_result)
 
@@ -65,6 +73,7 @@ def create_pivot_table(
     )
 
     df.rename(columns=lambda map_id: maps_indexes[map_id], inplace=True)
+    epochs_percent_df.rename(columns=lambda map_id: maps_indexes[map_id], inplace=True)
     df[EUC_DIST2FULL_COV_COL_NAME] = euc_dists2full_cov
     df[AV_COVERAGE_COL_NAME] = avs
     df[MEDIAN_COVERAGE_COL_NAME] = medians
@@ -84,13 +93,17 @@ def create_pivot_table(
     df.drop([AV_COVERAGE_COL_NAME], axis=1, inplace=True)
     df.drop([MEDIAN_COVERAGE_COL_NAME], axis=1, inplace=True)
     df.drop([COV_DEVIATION_COL_NAME], axis=1, inplace=True)
-    return df, stats_df
+    return df, stats_df, epochs_percent_df
 
 
 def table_to_string(table: pd.DataFrame):
     return table.to_markdown(tablefmt="psql")
 
 
+def table_to_csv(table: pd.DataFrame, path: Path):
+    table.to_csv(path_or_buf=path)
+
+
 def convert_to_view_model(
     m2r_mapping: Agent2Result,
 ) -> Name2ResultViewModel:

VSharp.ML.AIAgent/learning/genetic_alorithm.py

@@ -60,6 +60,7 @@ def run(
     init_log_file()
     init_epochs_best_dir()
     FeatureConfig.DUMP_BY_TIMEOUT.create_save_path_if_not_exists()
+    FeatureConfig.SAVE_EPOCHS_COVERAGES.create_save_path_if_not_exists()
 
     ga_instance = pygad.GA(
         num_generations=num_generations,

VSharp.ML.AIAgent/learning/r_learn.py

@@ -20,7 +20,7 @@
 from conn.classes import Agent2ResultsOnMaps
 from conn.requests import recv_game_result_list, send_game_results
 from conn.socket_manager import game_server_socket_manager
-from epochs_statistics.tables import create_pivot_table, table_to_string
+from epochs_statistics.tables import create_pivot_table, table_to_csv, table_to_string
 from epochs_statistics.utils import (
     append_to_tables_file,
     create_epoch_subdir,
@@ -190,10 +190,16 @@ def on_generation(ga_instance):
     else:
         leader_table[best_solution_nnwrapper] = best_solution_results
 
-    _, stats = create_pivot_table(leader_table, sort=False)
+    _, stats, _ = create_pivot_table(leader_table, sort=False)
     rewrite_best_tables_file(table_to_string(stats) + "\n")
 
-    pivot, stats = create_pivot_table(info_for_tables_filtered)
+    pivot, stats, epoch_table = create_pivot_table(info_for_tables_filtered)
+    if FeatureConfig.SAVE_EPOCHS_COVERAGES.enabled:
+        path_to_save_to = (
+            FeatureConfig.SAVE_EPOCHS_COVERAGES.save_path
+            / f"{ga_instance.generations_completed}.csv"
+        )
+        table_to_csv(epoch_table, path=path_to_save_to)
     append_to_tables_file(table_to_string(pivot) + "\n")
     append_to_tables_file(table_to_string(stats) + "\n")
     mean, std = compute_statistics(load_times_array())