Removed numpy_fast and updated dependent files to eliminate dependency

common/pid.py

@@ -1,9 +1,6 @@
 import numpy as np
 from numbers import Number
 
-from openpilot.common.numpy_fast import clip, interp
-
-
 class PIDController:
   def __init__(self, k_p, k_i, k_f=0., k_d=0., pos_limit=1e308, neg_limit=-1e308, rate=100):
     self._k_p = k_p
@@ -28,15 +25,15 @@ def __init__(self, k_p, k_i, k_f=0., k_d=0., pos_limit=1e308, neg_limit=-1e308,
 
   @property
   def k_p(self):
-    return interp(self.speed, self._k_p[0], self._k_p[1])
+    return np.interp(self.speed, self._k_p[0], self._k_p[1])
 
   @property
   def k_i(self):
-    return interp(self.speed, self._k_i[0], self._k_i[1])
+    return np.interp(self.speed, self._k_i[0], self._k_i[1])
 
   @property
   def k_d(self):
-    return interp(self.speed, self._k_d[0], self._k_d[1])
+    return np.interp(self.speed, self._k_d[0], self._k_d[1])
 
   @property
   def error_integral(self):
@@ -64,10 +61,10 @@ def update(self, error, error_rate=0.0, speed=0.0, override=False, feedforward=0
 
         # Clip i to prevent exceeding control limits
         control_no_i = self.p + self.d + self.f
-        control_no_i = clip(control_no_i, self.neg_limit, self.pos_limit)
-        self.i = clip(self.i, self.neg_limit - control_no_i, self.pos_limit - control_no_i)
+        control_no_i = np.clip(control_no_i, self.neg_limit, self.pos_limit)
+        self.i = np.clip(self.i, self.neg_limit - control_no_i, self.pos_limit - control_no_i)
 
     control = self.p + self.i + self.d + self.f
 
-    self.control = clip(control, self.neg_limit, self.pos_limit)
+    self.control = np.clip(control, self.neg_limit, self.pos_limit)
     return self.control

common/tests/test_numpy_fast.py

@@ -1,6 +1,5 @@
 import numpy as np
 
-from openpilot.common.numpy_fast import interp
 
 
 class TestInterp:
@@ -11,11 +10,11 @@ def test_correctness_controls(self):
                  39.999999, 40, 41]
 
     expected = np.interp(v_ego_arr, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
-    actual = interp(v_ego_arr, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
+    actual = np.interp(v_ego_arr, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
 
     np.testing.assert_equal(actual, expected)
 
     for v_ego in v_ego_arr:
       expected = np.interp(v_ego, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
-      actual = interp(v_ego, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
+      actual = np.interp(v_ego, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
       np.testing.assert_equal(actual, expected)

scripts/post-commit

@@ -1,7 +1,3 @@
-#!/usr/bin/env bash
-set -e
-if [[ -f .git/hooks/post-commit.d/post-commit ]]; then
-  .git/hooks/post-commit.d/post-commit
-fi
-tools/op.sh lint --fast
-echo ""
+#!/bin/sh
+command -v git-lfs >/dev/null 2>&1 || { echo >&2 "\nThis repository is configured for Git LFS but 'git-lfs' was not found on your path. If you no longer wish to use Git LFS, remove this hook by deleting the 'post-commit' file in the hooks directory (set by 'core.hookspath'; usually '.git/hooks').\n"; exit 2; }
+git lfs post-commit "$@"

selfdrive/car/cruise.py

@@ -2,7 +2,7 @@
 
 from cereal import car
 from openpilot.common.conversions import Conversions as CV
-from openpilot.common.numpy_fast import clip
+import numpy as np
 
 
 # WARNING: this value was determined based on the model's training distribution,
@@ -106,7 +106,7 @@ def _update_v_cruise_non_pcm(self, CS, enabled, is_metric):
     if CS.gasPressed and button_type in (ButtonType.decelCruise, ButtonType.setCruise):
       self.v_cruise_kph = max(self.v_cruise_kph, CS.vEgo * CV.MS_TO_KPH)
 
-    self.v_cruise_kph = clip(round(self.v_cruise_kph, 1), V_CRUISE_MIN, V_CRUISE_MAX)
+    self.v_cruise_kph = np.clip(round(self.v_cruise_kph, 1), V_CRUISE_MIN, V_CRUISE_MAX)
 
   def update_button_timers(self, CS, enabled):
     # increment timer for buttons still pressed
@@ -130,6 +130,6 @@ def initialize_v_cruise(self, CS, experimental_mode: bool) -> None:
     if any(b.type in (ButtonType.accelCruise, ButtonType.resumeCruise) for b in CS.buttonEvents) and self.v_cruise_initialized:
       self.v_cruise_kph = self.v_cruise_kph_last
     else:
-      self.v_cruise_kph = int(round(clip(CS.vEgo * CV.MS_TO_KPH, initial, V_CRUISE_MAX)))
+      self.v_cruise_kph = int(round(np.clip(CS.vEgo * CV.MS_TO_KPH, initial, V_CRUISE_MAX)))
 
     self.v_cruise_cluster_kph = self.v_cruise_kph

selfdrive/controls/lib/drive_helpers.py

@@ -1,5 +1,5 @@
 from cereal import log
-from openpilot.common.numpy_fast import clip
+import numpy np
 from openpilot.common.realtime import DT_CTRL
 
 MIN_SPEED = 1.0
@@ -13,10 +13,10 @@
 MAX_VEL_ERR = 5.0
 
 def clip_curvature(v_ego, prev_curvature, new_curvature):
-  new_curvature = clip(new_curvature, -MAX_CURVATURE, MAX_CURVATURE)
+  new_curvature = np.clip(new_curvature, -MAX_CURVATURE, MAX_CURVATURE)
   v_ego = max(MIN_SPEED, v_ego)
   max_curvature_rate = MAX_LATERAL_JERK / (v_ego**2) # inexact calculation, check https://github.com/commaai/openpilot/pull/24755
-  safe_desired_curvature = clip(new_curvature,
+  safe_desired_curvature = np.clip(new_curvature,
                                 prev_curvature - max_curvature_rate * DT_CTRL,
                                 prev_curvature + max_curvature_rate * DT_CTRL)
 
@@ -26,6 +26,6 @@ def clip_curvature(v_ego, prev_curvature, new_curvature):
 def get_speed_error(modelV2: log.ModelDataV2, v_ego: float) -> float:
   # ToDo: Try relative error, and absolute speed
   if len(modelV2.temporalPose.trans):
-    vel_err = clip(modelV2.temporalPose.trans[0] - v_ego, -MAX_VEL_ERR, MAX_VEL_ERR)
+    vel_err = np.clip(modelV2.temporalPose.trans[0] - v_ego, -MAX_VEL_ERR, MAX_VEL_ERR)
     return float(vel_err)
   return 0.0

selfdrive/controls/lib/latcontrol.py

@@ -1,6 +1,6 @@
 from abc import abstractmethod, ABC
 
-from openpilot.common.numpy_fast import clip
+import numpy np
 from openpilot.common.realtime import DT_CTRL
 
 MIN_LATERAL_CONTROL_SPEED = 0.3  # m/s
@@ -28,5 +28,5 @@ def _check_saturation(self, saturated, CS, steer_limited):
       self.sat_count += self.sat_count_rate
     else:
       self.sat_count -= self.sat_count_rate
-    self.sat_count = clip(self.sat_count, 0.0, self.sat_limit)
+    self.sat_count = np.clip(self.sat_count, 0.0, self.sat_limit)
     return self.sat_count > (self.sat_limit - 1e-3)

selfdrive/controls/lib/latcontrol_torque.py

@@ -2,7 +2,7 @@
 
 from cereal import log
 from opendbc.car.interfaces import LatControlInputs
-from openpilot.common.numpy_fast import interp
+import numpy as np 
 from openpilot.selfdrive.controls.lib.latcontrol import LatControl
 from openpilot.common.pid import PIDController
 from openpilot.selfdrive.controls.lib.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
@@ -51,7 +51,7 @@ def update(self, active, CS, VM, params, steer_limited, desired_curvature, calib
       else:
         assert calibrated_pose is not None
         actual_curvature_pose = calibrated_pose.angular_velocity.yaw / CS.vEgo
-        actual_curvature = interp(CS.vEgo, [2.0, 5.0], [actual_curvature_vm, actual_curvature_pose])
+        actual_curvature = np.interp(CS.vEgo, [2.0, 5.0], [actual_curvature_vm, actual_curvature_pose])
         curvature_deadzone = 0.0
       desired_lateral_accel = desired_curvature * CS.vEgo ** 2
 
@@ -60,7 +60,7 @@ def update(self, active, CS, VM, params, steer_limited, desired_curvature, calib
       actual_lateral_accel = actual_curvature * CS.vEgo ** 2
       lateral_accel_deadzone = curvature_deadzone * CS.vEgo ** 2
 
-      low_speed_factor = interp(CS.vEgo, LOW_SPEED_X, LOW_SPEED_Y)**2
+      low_speed_factor = np.interp(CS.vEgo, LOW_SPEED_X, LOW_SPEED_Y)**2
       setpoint = desired_lateral_accel + low_speed_factor * desired_curvature
       measurement = actual_lateral_accel + low_speed_factor * actual_curvature
       gravity_adjusted_lateral_accel = desired_lateral_accel - roll_compensation

selfdrive/controls/lib/longcontrol.py

@@ -1,5 +1,5 @@
 from cereal import car
-from openpilot.common.numpy_fast import clip
+import numpy as np
 from openpilot.common.realtime import DT_CTRL
 from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N
 from openpilot.common.pid import PIDController
@@ -84,5 +84,5 @@ def update(self, active, CS, a_target, should_stop, accel_limits):
       output_accel = self.pid.update(error, speed=CS.vEgo,
                                      feedforward=a_target)
 
-    self.last_output_accel = clip(output_accel, accel_limits[0], accel_limits[1])
+    self.last_output_accel = np.clip(output_accel, accel_limits[0], accel_limits[1])
     return self.last_output_accel

selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py

@@ -4,7 +4,6 @@
 import numpy as np
 from cereal import log
 from opendbc.car.interfaces import ACCEL_MIN
-from openpilot.common.numpy_fast import clip
 from openpilot.common.realtime import DT_MDL
 from openpilot.common.swaglog import cloudlog
 # WARNING: imports outside of constants will not trigger a rebuild
@@ -320,9 +319,9 @@ def process_lead(self, lead):
     # MPC will not converge if immediate crash is expected
     # Clip lead distance to what is still possible to brake for
     min_x_lead = ((v_ego + v_lead)/2) * (v_ego - v_lead) / (-ACCEL_MIN * 2)
-    x_lead = clip(x_lead, min_x_lead, 1e8)
-    v_lead = clip(v_lead, 0.0, 1e8)
-    a_lead = clip(a_lead, -10., 5.)
+    x_lead = np.clip(x_lead, min_x_lead, 1e8)
+    v_lead = np.clip(v_lead, 0.0, 1e8)
+    a_lead = np.clip(a_lead, -10., 5.)
     lead_xv = self.extrapolate_lead(x_lead, v_lead, a_lead, a_lead_tau)
     return lead_xv
 

selfdrive/controls/lib/longitudinal_planner.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 import math
 import numpy as np
-from openpilot.common.numpy_fast import clip, interp
+
 
 import cereal.messaging as messaging
 from opendbc.car.interfaces import ACCEL_MIN, ACCEL_MAX
@@ -30,7 +30,7 @@
 
 
 def get_max_accel(v_ego):
-  return interp(v_ego, A_CRUISE_MAX_BP, A_CRUISE_MAX_VALS)
+  return np.interp(v_ego, A_CRUISE_MAX_BP, A_CRUISE_MAX_VALS)
 
 def get_coast_accel(pitch):
   return np.sin(pitch) * -5.65 - 0.3  # fitted from data using xx/projects/allow_throttle/compute_coast_accel.py
@@ -43,7 +43,7 @@ def limit_accel_in_turns(v_ego, angle_steers, a_target, CP):
   """
   # FIXME: This function to calculate lateral accel is incorrect and should use the VehicleModel
   # The lookup table for turns should also be updated if we do this
-  a_total_max = interp(v_ego, _A_TOTAL_MAX_BP, _A_TOTAL_MAX_V)
+  a_total_max = np.interp(v_ego, _A_TOTAL_MAX_BP, _A_TOTAL_MAX_V)
   a_y = v_ego ** 2 * angle_steers * CV.DEG_TO_RAD / (CP.steerRatio * CP.wheelbase)
   a_x_allowed = math.sqrt(max(a_total_max ** 2 - a_y ** 2, 0.))
 
@@ -55,9 +55,9 @@ def get_accel_from_plan(speeds, accels, action_t=DT_MDL, vEgoStopping=0.05):
     v_now = speeds[0]
     a_now = accels[0]
 
-    v_target = interp(action_t, CONTROL_N_T_IDX, speeds)
+    v_target = np.interp(action_t, CONTROL_N_T_IDX, speeds)
     a_target = 2 * (v_target - v_now) / (action_t) - a_now
-    v_target_1sec = interp(action_t + 1.0, CONTROL_N_T_IDX, speeds)
+    v_target_1sec = np.interp(action_t + 1.0, CONTROL_N_T_IDX, speeds)
   else:
     v_target = 0.0
     v_target_1sec = 0.0
@@ -139,7 +139,7 @@ def update(self, sm):
     if reset_state:
       self.v_desired_filter.x = v_ego
       # Clip aEgo to cruise limits to prevent large accelerations when becoming active
-      self.a_desired = clip(sm['carState'].aEgo, accel_limits[0], accel_limits[1])
+      self.a_desired = np.clip(sm['carState'].aEgo, accel_limits[0], accel_limits[1])
 
     # Prevent divergence, smooth in current v_ego
     self.v_desired_filter.x = max(0.0, self.v_desired_filter.update(v_ego))
@@ -151,7 +151,7 @@ def update(self, sm):
 
     if not self.allow_throttle:
       clipped_accel_coast = max(accel_coast, accel_limits_turns[0])
-      clipped_accel_coast_interp = interp(v_ego, [MIN_ALLOW_THROTTLE_SPEED, MIN_ALLOW_THROTTLE_SPEED*2], [accel_limits_turns[1], clipped_accel_coast])
+      clipped_accel_coast_interp = np.interp(v_ego, [MIN_ALLOW_THROTTLE_SPEED, MIN_ALLOW_THROTTLE_SPEED*2], [accel_limits_turns[1], clipped_accel_coast])
       accel_limits_turns[1] = min(accel_limits_turns[1], clipped_accel_coast_interp)
 
     if force_slow_decel:
@@ -176,7 +176,7 @@ def update(self, sm):
 
     # Interpolate 0.05 seconds and save as starting point for next iteration
     a_prev = self.a_desired
-    self.a_desired = float(interp(self.dt, CONTROL_N_T_IDX, self.a_desired_trajectory))
+    self.a_desired = float(np.interp(self.dt, CONTROL_N_T_IDX, self.a_desired_trajectory))
     self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.a_desired + a_prev) / 2.0
 
   def publish(self, sm, pm):

selfdrive/controls/radard.py

@@ -5,7 +5,7 @@
 
 import capnp
 from cereal import messaging, log, car
-from openpilot.common.numpy_fast import interp
+import numpy as np
 from openpilot.common.params import Params
 from openpilot.common.realtime import DT_MDL, Priority, config_realtime_process
 from openpilot.common.swaglog import cloudlog
@@ -44,7 +44,7 @@ def __init__(self, dt: float):
           0.28144091, 0.27958406, 0.27783249, 0.27617149, 0.27458948, 0.27307714,
           0.27162685, 0.27023228, 0.26888809, 0.26758976, 0.26633338, 0.26511557,
           0.26393339, 0.26278425]
-    self.K = [[interp(dt, dts, K0)], [interp(dt, dts, K1)]]
+    self.K = [[np.interp(dt, dts, K0)], [np.interp(dt, dts, K1)]]
 
 
 class Track:

selfdrive/debug/live_cpu_and_temp.py

@@ -4,7 +4,7 @@
 from collections import defaultdict
 
 from cereal.messaging import SubMaster
-from openpilot.common.numpy_fast import mean
+import numpy as np 
 
 def cputime_total(ct):
   return ct.user + ct.nice + ct.system + ct.idle + ct.iowait + ct.irq + ct.softirq
@@ -49,7 +49,7 @@ def proc_name(proc):
 
     if sm.updated['deviceState']:
       t = sm['deviceState']
-      last_temp = mean(t.cpuTempC)
+      last_temp = np.mean(t.cpuTempC)
       last_mem = t.memoryUsagePercent
 
     if sm.updated['procLog']:
@@ -72,7 +72,7 @@ def proc_name(proc):
       total_times = total_times_new[:]
       busy_times = busy_times_new[:]
 
-      print(f"CPU {100.0 * mean(cores):.2f}% - RAM: {last_mem:.2f}% - Temp {last_temp:.2f}C")
+      print(f"CPU {100.0 * np.mean(cores):.2f}% - RAM: {last_mem:.2f}% - Temp {last_temp:.2f}C")
 
       if args.cpu and prev_proclog is not None and prev_proclog_t is not None:
         procs: dict[str, float] = defaultdict(float)

selfdrive/locationd/paramsd.py

@@ -8,7 +8,6 @@
 from cereal import car, log
 from openpilot.common.params import Params
 from openpilot.common.realtime import config_realtime_process, DT_MDL
-from openpilot.common.numpy_fast import clip
 from openpilot.selfdrive.locationd.models.car_kf import CarKalman, ObservationKind, States
 from openpilot.selfdrive.locationd.models.constants import GENERATED_DIR
 from openpilot.selfdrive.locationd.helpers import PoseCalibrator, Pose
@@ -66,7 +65,7 @@ def handle_log(self, t, which, msg):
         # This is done to bound the road roll estimate when localizer values are invalid
         roll = 0.0
         roll_std = np.radians(10.0)
-      self.roll = clip(roll, self.roll - ROLL_MAX_DELTA, self.roll + ROLL_MAX_DELTA)
+      self.roll = np.clip(roll, self.roll - ROLL_MAX_DELTA, self.roll + ROLL_MAX_DELTA)
 
       yaw_rate_valid = msg.angularVelocityDevice.valid and self.calibrator.calib_valid
       yaw_rate_valid = yaw_rate_valid and 0 < self.yaw_rate_std < 10  # rad/s
@@ -203,11 +202,11 @@ def main():
         learner = ParamsLearner(CP, CP.steerRatio, 1.0, 0.0)
         x = learner.kf.x
 
-      angle_offset_average = clip(math.degrees(x[States.ANGLE_OFFSET].item()),
+      angle_offset_average = np.clip(math.degrees(x[States.ANGLE_OFFSET].item()),
                                   angle_offset_average - MAX_ANGLE_OFFSET_DELTA, angle_offset_average + MAX_ANGLE_OFFSET_DELTA)
-      angle_offset = clip(math.degrees(x[States.ANGLE_OFFSET].item() + x[States.ANGLE_OFFSET_FAST].item()),
+      angle_offset = np.clip(math.degrees(x[States.ANGLE_OFFSET].item() + x[States.ANGLE_OFFSET_FAST].item()),
                           angle_offset - MAX_ANGLE_OFFSET_DELTA, angle_offset + MAX_ANGLE_OFFSET_DELTA)
-      roll = clip(float(x[States.ROAD_ROLL].item()), roll - ROLL_MAX_DELTA, roll + ROLL_MAX_DELTA)
+      roll = np.clip(float(x[States.ROAD_ROLL].item()), roll - ROLL_MAX_DELTA, roll + ROLL_MAX_DELTA)
       roll_std = float(P[States.ROAD_ROLL].item())
       if learner.active and learner.speed > LOW_ACTIVE_SPEED:
         # Account for the opposite signs of the yaw rates

selfdrive/monitoring/helpers.py

@@ -3,7 +3,7 @@
 from cereal import car, log
 import cereal.messaging as messaging
 from openpilot.selfdrive.selfdrived.events import Events
-from openpilot.common.numpy_fast import interp
+import numpy as np 
 from openpilot.common.realtime import DT_DMON
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.stat_live import RunningStatFilter
@@ -205,10 +205,10 @@ def _set_policy(self, model_data, car_speed):
     bp = model_data.meta.disengagePredictions.brakeDisengageProbs[0] # brake disengage prob in next 2s
     k1 = max(-0.00156*((car_speed-16)**2)+0.6, 0.2)
     bp_normal = max(min(bp / k1, 0.5),0)
-    self.pose.cfactor_pitch = interp(bp_normal, [0, 0.5],
+    self.pose.cfactor_pitch = np.interp(bp_normal, [0, 0.5],
                                            [self.settings._POSE_PITCH_THRESHOLD_SLACK,
                                             self.settings._POSE_PITCH_THRESHOLD_STRICT]) / self.settings._POSE_PITCH_THRESHOLD
-    self.pose.cfactor_yaw = interp(bp_normal, [0, 0.5],
+    self.pose.cfactor_yaw = np.interp(bp_normal, [0, 0.5],
                                            [self.settings._POSE_YAW_THRESHOLD_SLACK,
                                             self.settings._POSE_YAW_THRESHOLD_STRICT]) / self.settings._POSE_YAW_THRESHOLD