diff --git a/latencyAnalysis.py b/latencyAnalysis.py
index d9b0214..ef5a7fa 100644
--- a/latencyAnalysis.py
+++ b/latencyAnalysis.py
@@ -8,11 +8,21 @@ import logging
 # Configure logging to show informational messages
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
-prefixImage = 'histograms/'
-
 def parse_args():
     parser = argparse.ArgumentParser(prog=__file__)
     parser.add_argument('-c', '--compensate', action="store_true")
+    parser.add_argument('--latency-csv', 
+                        type=str, 
+                        default='sample/latencyDataframenvh264enc.csv',
+                        help='Path to the latency results CSV file.')
+    parser.add_argument('-pd','--plot-dir', 
+                        type=str,
+                        default='plots/',
+                        help='Path to directory in which resulted plots should be saved')
+    parser.add_argument('-csv', '--csv-dir',
+                        type=str,
+                        default='results/',
+                        help='Path to directory in which resulted csv data should be saved')
     return parser.parse_args()
 
 cmd_args = None
@@ -56,7 +66,7 @@ def plot_latency_data(df):
     plt.grid(axis='y', linestyle='--', alpha=0.6)
 
     plt.tight_layout()
-    plt.savefig(prefixImage + f'combined_top_configurations_plot_{encoder_name}.png')
+    plt.savefig(get_args().plot_dir + f'combined_top_configurations_plot_{encoder_name}.png')
     plt.close()
 
     # Output Notes (for user interpretation)
@@ -64,6 +74,17 @@ def plot_latency_data(df):
     for index, note in max_notes.items():
         print(f"Index {index}: {note}")
 
+def plot_start_latency(df):
+    fig = plt.figure(figsize=(10, 6), dpi=300)
+    r1 = np.arange(len(df))
+    plt.plot(r1, df['max'])
+    plt.xlabel('Индекс конфигурации', fontweight='bold')
+    plt.ylabel('Общая задержка [мс]', fontweight='bold')
+    encoder_name = df.index.get_level_values(0)[0]
+    plt.title(f"Результаты стартовой задержки для {encoder_name}")
+    plt.tight_layout()
+    plt.savefig(get_args().plot_dir + f"start_latency_{encoder_name}.png")
+    plt.close()
 
 def analyze_latency_data(csv_path: str):
     """
@@ -122,14 +143,21 @@ def analyze_latency_data(csv_path: str):
 
     # 3. Filter the original summary DataFrame (df_summary) using the common indices
     df_common_top_performers = df_summary.loc[common_indices]
+    encoder_name = df_common_top_performers.index.get_level_values(0)[0]
+
     print(df_common_top_performers.head())
 
     plot_latency_data(df_common_top_performers)
+
+    plot_start_latency(df_common_top_performers)
+
+    # 4. Save top performers to csv
+    top_10_df = df_common_top_performers.head(10)
+    top_10_df.to_csv(get_args().csv_dir + f"{encoder_name}.csv")
     return
 
 if __name__ == '__main__':
-    parse_args()
-    # Set the path to your CSV file here.
-    csv_filename = 'sample/latencyDataframenvh264enc.csv'
-    analyze_latency_data(csv_filename)
+    os.makedirs(get_args().csv_dir, exist_ok=True)
+    os.makedirs(get_args().plot_dir, exist_ok=True)
+    analyze_latency_data(get_args().latency_csv)