refactor(solve_one_instance): rename optimize and include refactor to function

docs/example_scripts.rst

 Optimize
 ========
 
-.. literalinclude:: examples/optimize.py
+.. literalinclude:: examples/solve_one_instance.py
 
 Solve chosen instances for several network architectures
 ========================================================

src/lp_nn_robustness_verification/examples/optimize.py → src/lp_nn_robustness_verification/examples/solve_one_instance.py

@@ -29,13 +29,15 @@ from lp_nn_robustness_verification.data_types import UncertainArray
 from lp_nn_robustness_verification.linear_program import RobustVerifier
 from lp_nn_robustness_verification.pre_processing import LinearInclusion
 
-if __name__ == "__main__":
-    SAMPLES_PER_SENSOR = 10
-    DEPTH = 1
-    zema_data = ZeMASamples(size_scaler=SAMPLES_PER_SENSOR, normalize=True)
+
+def optimize() -> None:
+    """Solve one specific hard coded instance and time the process"""
+    samples_per_sensor = 10
+    depth = 1
+    zema_data = ZeMASamples(size_scaler=samples_per_sensor, normalize=True)
     nn_params = generate_weights_and_biases(
         len(zema_data.values[0]),
-        construct_out_features_counts(len(zema_data.values[0]), depth=DEPTH),
+        construct_out_features_counts(len(zema_data.values[0]), depth=depth),
         seed=0,
     )
     for (values, uncertainties) in zip(zema_data.values, zema_data.uncertainties):
@@ -48,15 +50,26 @@ if __name__ == "__main__":
         optimization = RobustVerifier(linear_inclusion)
         optimization.solve()
         yappi.stop()
-        with open("timings.txt", "a", encoding="utf-8") as timings_file:
+        with open(
+            (
+                f"{samples_per_sensor * 11}_inputs_and_"
+                f"{depth}_layers_with_sample_0_and_seed_0_timings.txt"
+            ),
+            "a",
+            encoding="utf-8",
+        ) as timings_file:
             timings_file.write(
                 f"\n==================================================================="
                 f"===================\n"
-                f"Timings for {SAMPLES_PER_SENSOR * 11} inputs and {DEPTH} "
-                f"{'layers' if DEPTH > 1 else 'layer'}"
+                f"Timings for {samples_per_sensor * 11} inputs and "
+                f"{depth} {'layers' if depth > 1 else 'layer'} with sample 0 and seed 0"
                 f"\n==================================================================="
                 f"===================\n"
             )
-            yappi.get_func_stats().print_all(
+            yappi.get_func_stats().print_all(  # type: ignore[import]
                 out=timings_file, columns={0: ("name", 180), 3: ("ttot", 8)}
             )
+
+
+if __name__ == "__main__":
+    optimize()