Add npy file for AgBot case

dtree_synth_agbot.py

@@ -2,7 +2,7 @@
 
 import itertools
 import json
-from typing import Dict, Hashable, Literal
+from typing import Dict, Hashable, Iterable, Literal, Tuple
 
 import numpy as np
 from dtree_synth import DataSet, search_part, synth_dtree_per_part
@@ -11,7 +11,7 @@ from agbot_stanley_teacher import DTreeAgBotStanleyGurobiTeacher
 
 
 def load_examples_from_numpy_array(
-        data_5d_numpy: np.ndarray,
+        data_5d: Iterable[Tuple[float, ...]],
         teacher: DTreeAgBotStanleyGurobiTeacher,
         partition) -> Dict[Hashable, DataSet]:
     # x_arr[:-1], except the last one, x_arr[1:] except the first one
@@ -19,7 +19,7 @@ def load_examples_from_numpy_array(
     ret = {part: DataSet() for part in itertools.product(*bound_list)}
 
     num_excl_samples = 0
-    for dpoint in data_5d_numpy:
+    for dpoint in data_5d:
         vehicle_state = dpoint[0:teacher.state_dim]
         part = search_part(partition, vehicle_state)
         if part is None:
@@ -28,19 +28,19 @@ def load_examples_from_numpy_array(
         if np.any(np.isnan(dpoint)):
             ret[part].num_nan_dps += 1
         elif teacher.is_safe_state(dpoint):
-            ret[part].safe_dps.append(tuple(dpoint))
+            ret[part].safe_dps.append(dpoint)
         else:
-            ret[part].unsafe_dps.append(tuple(dpoint))
+            ret[part].unsafe_dps.append(dpoint)
     print("# samples not in any selected parts:", num_excl_samples)
     return ret
 
 
 def main(dom: Literal["concat", "diff"], ult_bound: float):
-    NPZ_FILE_PATH = "data/perceptor-agbot-collect_images_2021-10-29-01-37-44-0.0-50.0.npz"
+    NPY_FILE_PATH = "data/400_truths-uniform_partition_20x20-0.228m-pi_6-agbot-2021-10-29-01-37-44.npy"
 
-    print("Loading examples from .npz")
-    with np.load(NPZ_FILE_PATH) as npz_data:
-        data_5d_numpy = npz_data['dps_arr']
+    print("Loading examples from .npy")
+    data_5d_structured_arr = np.load(NPY_FILE_PATH)
+    data_5d = data_5d_structured_arr[['x', 'y', 'yaw', 'cte', 'psi']].tolist()
 
     # Partitions on prestate
 
@@ -48,11 +48,11 @@ def main(dom: Literal["concat", "diff"], ult_bound: float):
     X_ARR = np.array([-X_LIM, X_LIM])
 
     PRE_Y_LIM = 0.228
-    NUM_Y_PARTS = 10
+    NUM_Y_PARTS = 5
     Y_ARR = np.linspace(-PRE_Y_LIM, PRE_Y_LIM, NUM_Y_PARTS + 1)
 
     PRE_YAW_LIM = np.pi / 6
-    NUM_YAW_PARTS = 10
+    NUM_YAW_PARTS = 5
     YAW_ARR = np.linspace(-PRE_YAW_LIM, PRE_YAW_LIM, NUM_YAW_PARTS + 1)
 
     PARTITION = (X_ARR, Y_ARR, YAW_ARR)
@@ -62,7 +62,7 @@ def main(dom: Literal["concat", "diff"], ult_bound: float):
     NORM_ORD = 1
 
     teacher = DTreeAgBotStanleyGurobiTeacher(norm_ord=NORM_ORD, ultimate_bound=ULT_BOUND)
-    part_to_examples = load_examples_from_numpy_array(data_5d_numpy, teacher, PARTITION)
+    part_to_examples = load_examples_from_numpy_array(data_5d, teacher, PARTITION)
 
     # Print statistics about training data points
     print("#"*80)
@@ -75,7 +75,7 @@ def main(dom: Literal["concat", "diff"], ult_bound: float):
 
         if len(unsafe_dps) > 0:
             print(f"Part Index {i}:", f"y in [{lb[1]:.03}, {ub[1]:.03}] (m);", f"θ in [{lb[2]:.03}, {ub[2]:.03}] (deg);",
-                  f"# safe: {len(safe_dps)}", f"# unsafe: {len(unsafe_dps):03}", f"# NaN: {num_nan}")
+                  f"# safe: {len(safe_dps)}", f"# unsafe: {len(unsafe_dps)}", f"# NaN: {num_nan}")
 
     return
 
@@ -102,4 +102,4 @@ def main(dom: Literal["concat", "diff"], ult_bound: float):
 
 
 if __name__ == "__main__":
-    main("concat", 0.0)
+    main("concat", 0.5)
\ No newline at end of file