style: fix import ordering with isort

benchmark_accuracy.py

@@ -9,21 +9,23 @@
 4. Obstacle clearance
 """
 
-import numpy as np
 import sys
 
+import numpy as np
+
 sys.path.insert(0, "/home/user/Eigen-Geometric-Control")
 
+import pandas as pd
+
 from src import (
-    run_arm_simulation,
-    detect_oscillation,
-    lightlike_damping_factor,
-    forward_kinematics,
+    compute_change_stability,
     compute_ds2,
     compute_gradient,
-    compute_change_stability,
+    detect_oscillation,
+    forward_kinematics,
+    lightlike_damping_factor,
+    run_arm_simulation,
 )
-import pandas as pd
 
 
 def run_arm_with_lightlike_damping(

benchmark_adaptive_twophase.py

@@ -14,20 +14,22 @@
 This is Priority 1 from UPGRADE_ROADMAP.md
 """
 
-import numpy as np
 import sys
 
+import numpy as np
+
 sys.path.insert(0, "/home/user/Eigen-Geometric-Control")
 
+import pandas as pd
+
 from src import (
     adaptive_control_parameters,
-    detect_oscillation,
-    lightlike_damping_factor,
-    forward_kinematics,
     compute_ds2,
     compute_gradient,
+    detect_oscillation,
+    forward_kinematics,
+    lightlike_damping_factor,
 )
-import pandas as pd
 
 
 def run_fixed_eta_control(

benchmark_coherent_decomposition.py

@@ -10,8 +10,8 @@
 - Coherent Filtering: Decompose and suppress incoherent noise
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 from src.eigen_decomposition import (
     coherent_control_step,

benchmark_dynamic.py

@@ -13,20 +13,22 @@
 observer should provide significant benefit.
 """
 
-import numpy as np
 import sys
 
+import numpy as np
+
 sys.path.insert(0, "/home/user/Eigen-Geometric-Control")
 
+import pandas as pd
+
 from src import (
-    detect_oscillation,
-    lightlike_damping_factor,
-    forward_kinematics,
+    compute_change_stability,
     compute_ds2,
     compute_gradient,
-    compute_change_stability,
+    detect_oscillation,
+    forward_kinematics,
+    lightlike_damping_factor,
 )
-import pandas as pd
 
 
 def run_dynamic_baseline(

benchmark_dynamic_adaptation.py

@@ -14,8 +14,8 @@
 - Medium robot (baseline)
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 from src.eigen_adaptive import adaptive_control_step
 

benchmark_geodesic_planning.py

@@ -14,8 +14,8 @@
 - Corridor navigation (obstacles on sides)
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 from src.eigen_geodesic import (
     Obstacle,

benchmark_landing.py

@@ -21,20 +21,22 @@
 - Safety critical (oscillations = crash)
 """
 
-import numpy as np
 import sys
 
+import numpy as np
+
 sys.path.insert(0, "/home/user/Eigen-Geometric-Control")
 
+import pandas as pd
+
 from src import (
-    detect_oscillation,
-    lightlike_damping_factor,
-    forward_kinematics,
+    compute_change_stability,
     compute_ds2,
     compute_gradient,
-    compute_change_stability,
+    detect_oscillation,
+    forward_kinematics,
+    lightlike_damping_factor,
 )
-import pandas as pd
 
 
 def run_landing_baseline(

benchmark_mars_landing.py

@@ -23,20 +23,22 @@
 - One shot → stability > speed
 """
 
-import numpy as np
 import sys
 
+import numpy as np
+
 sys.path.insert(0, "/home/user/Eigen-Geometric-Control")
 
+import pandas as pd
+
 from src import (
-    detect_oscillation,
-    lightlike_damping_factor,
-    forward_kinematics,
+    compute_change_stability,
     compute_ds2,
     compute_gradient,
-    compute_change_stability,
+    detect_oscillation,
+    forward_kinematics,
+    lightlike_damping_factor,
 )
-import pandas as pd
 
 
 def run_mars_baseline(

benchmark_moving_targets.py

@@ -9,12 +9,12 @@
 - Predictive (Lorentz): Estimate velocity and move toward predicted position
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 from src.eigen_lorentz import (
-    moving_target_control_step,
     estimate_target_velocity,
+    moving_target_control_step,
 )
 
 

benchmark_qec.py

@@ -14,13 +14,13 @@
 - High sensor failure rate (50%)
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 from src.eigen_qec import (
-    simulate_sensor_array,
     correct_measurement_errors,
     qec_control_step,
+    simulate_sensor_array,
 )
 
 

benchmark_scaling.py

@@ -13,20 +13,22 @@
 5. Optimized oscillation detection parameters
 """
 
-import numpy as np
 import sys
 
+import numpy as np
+
 sys.path.insert(0, "/home/user/Eigen-Geometric-Control")
 
+import pandas as pd
+
 from src import (
-    detect_oscillation,
-    lightlike_damping_factor,
-    forward_kinematics,
+    compute_change_stability,
     compute_ds2,
     compute_gradient,
-    compute_change_stability,
+    detect_oscillation,
+    forward_kinematics,
+    lightlike_damping_factor,
 )
-import pandas as pd
 
 
 def run_arm_with_tuned_lightlike(

benchmark_stereo_lorentz.py

@@ -18,25 +18,27 @@
 not just Euclidean position - this is where lightlike observer should work!
 """
 
-import numpy as np
 import sys
 
+import numpy as np
+
 sys.path.insert(0, "/home/user/Eigen-Geometric-Control")
 
+import pandas as pd
+
 from src import (
-    detect_oscillation,
-    lightlike_damping_factor,
-    forward_kinematics,
+    compute_change_stability,
     compute_ds2,
     compute_gradient,
-    compute_change_stability,
+    detect_oscillation,
+    forward_kinematics,
+    lightlike_damping_factor,
 )
 from src.eigen_lorentz import (
-    stereo_to_lorentz,
     lorentz_to_stereo,
     regime_classification,
+    stereo_to_lorentz,
 )
-import pandas as pd
 
 
 def simulate_stereo_measurement(true_target, noise_level=0.01):

benchmark_terminal_descent.py

@@ -16,20 +16,22 @@
 - Focus on final precision
 """
 
-import numpy as np
 import sys
 
+import numpy as np
+
 sys.path.insert(0, "/home/user/Eigen-Geometric-Control")
 
+import pandas as pd
+
 from src import (
-    detect_oscillation,
-    lightlike_damping_factor,
-    forward_kinematics,
+    compute_change_stability,
     compute_ds2,
     compute_gradient,
-    compute_change_stability,
+    detect_oscillation,
+    forward_kinematics,
+    lightlike_damping_factor,
 )
-import pandas as pd
 
 
 def run_terminal_descent(

benchmark_visual_servoing.py

@@ -18,20 +18,22 @@
 control better than standard approaches.
 """
 
-import numpy as np
 import sys
 
+import numpy as np
+
 sys.path.insert(0, "/home/user/Eigen-Geometric-Control")
 
+import pandas as pd
+
 from src import (
-    detect_oscillation,
-    lightlike_damping_factor,
-    forward_kinematics,
+    compute_change_stability,
     compute_ds2,
     compute_gradient,
-    compute_change_stability,
+    detect_oscillation,
+    forward_kinematics,
+    lightlike_damping_factor,
 )
-import pandas as pd
 
 
 def add_stereo_noise(target_pos, noise_level=0.01, occlusion_prob=0.0, tick=0):

benchmark_weak_stereo.py

@@ -9,8 +9,8 @@
 - Weak measurement: Preserves coherence → continuous observations → smooth control
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 from src.eigen_weak_measurement import (
     coherence_metric,

benchmark_weak_stereo_noisy.py

@@ -9,8 +9,8 @@
 to the noisy observation and create jittery motion.
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 from src.eigen_weak_measurement import (
     coherence_metric,

benchmark_xor.py

@@ -6,21 +6,23 @@
 This tests if the lightlike observer can actually break it.
 """
 
-import numpy as np
 import sys
 
+import numpy as np
+
 sys.path.insert(0, "/home/user/Eigen-Geometric-Control")
 
+import pandas as pd
+
 from src import (
-    run_xor_simulation,
-    detect_oscillation,
-    lightlike_damping_factor,
-    forward_kinematics,
+    compute_change_stability,
     compute_ds2,
     compute_gradient,
-    compute_change_stability,
+    detect_oscillation,
+    forward_kinematics,
+    lightlike_damping_factor,
+    run_xor_simulation,
 )
-import pandas as pd
 
 
 def run_xor_with_lightlike_damping(