remove old params learner (#1918)

old-commit-hash: e0e7c7486d653a550c596f9dca7e5b6424d4c05d

selfdrive/locationd/test/test_params_learner.py

@@ -1,50 +0,0 @@
-#!/usr/bin/env python3
-
-import numpy as np
-import unittest
-
-from selfdrive.car.honda.interface import CarInterface
-from selfdrive.car.honda.values import CAR
-from selfdrive.controls.lib.vehicle_model import VehicleModel
-from selfdrive.locationd.liblocationd_py import liblocationd  # pylint: disable=no-name-in-module, import-error
-
-
-class TestParamsLearner(unittest.TestCase):
-  def setUp(self):
-
-    self.CP = CarInterface.get_params(CAR.CIVIC)
-    bts = self.CP.to_bytes()
-
-    self.params_learner = liblocationd.params_learner_init(len(bts), bts, 0.0, 1.0, self.CP.steerRatio, 1.0)
-
-  def test_convergence(self):
-    # Setup vehicle model with wrong parameters
-    VM_sim = VehicleModel(self.CP)
-    x_target = 0.75
-    sr_target = self.CP.steerRatio - 0.5
-    ao_target = -1.0
-    VM_sim.update_params(x_target, sr_target)
-
-    # Run simulation
-    times = np.arange(0, 15*3600, 0.01)
-    angle_offset = np.radians(ao_target)
-    steering_angles = np.radians(10 * np.sin(2 * np.pi * times / 100.)) + angle_offset
-    speeds = 10 * np.sin(2 * np.pi * times / 1000.) + 25
-
-    for i, _ in enumerate(times):
-      u = speeds[i]
-      sa = steering_angles[i]
-      psi = VM_sim.yaw_rate(sa - angle_offset, u)
-      liblocationd.params_learner_update(self.params_learner, psi, u, sa)
-
-    # Verify learned parameters
-    sr = liblocationd.params_learner_get_sR(self.params_learner)
-    ao_slow = np.degrees(liblocationd.params_learner_get_slow_ao(self.params_learner))
-    x = liblocationd.params_learner_get_x(self.params_learner)
-    self.assertAlmostEqual(x_target, x, places=1)
-    self.assertAlmostEqual(ao_target, ao_slow, places=1)
-    self.assertAlmostEqual(sr_target, sr, places=1)
-
-
-if __name__ == "__main__":
-  unittest.main()