revert filter to master

common/filter_simple.py

@@ -15,75 +15,3 @@ class FirstOrderFilter:
       self.initialized = True
       self.x = x
     return self.x
-
-
-# low pass the raw jerk
-class JerkEstimator1:
-  def __init__(self, dt):
-    self.dt = dt
-    self.prev_x = 0.0
-    self.initialized = False
-    self.filter = FirstOrderFilter(0.0, 0.08, dt, initialized=False)
-
-  @property
-  def x(self):
-    return self.filter.x
-
-  def update(self, x):
-    if not self.initialized:
-      self.prev_x = x
-      self.initialized = True
-
-    self.filter.update((x - self.prev_x) / self.dt)
-    self.prev_x = x
-    return self.filter.x
-
-
-# use a kalman filter to estimate jerk
-class JerkEstimator2:
-  def __init__(self, dt):
-    self.dt = dt
-    self.initialized = False
-    from opendbc.car.common.simple_kalman import KF1D, get_kalman_gain
-    import numpy as np
-
-    DT_CTRL = 0.01
-
-    Q = [[0.0, 0.0], [0.0, 100.0]]
-    R = 0.3
-    A = [[1.0, DT_CTRL], [0.0, 1.0]]
-    C = [[1.0, 0.0]]
-    x0 = [[0.0], [0.0]]
-    K = get_kalman_gain(DT_CTRL, np.array(A), np.array(C), np.array(Q), R)
-    self.kf = KF1D(x0=x0, A=A, C=C[0], K=K)
-
-  @property
-  def x(self):
-    return self.kf.x[1][0] if self.initialized else 0.0
-
-  def update(self, x):
-    if not self.initialized:
-      self.kf.set_x([[x], [0.0]])
-      self.initialized = True
-    self.kf.update(x)
-    return self.kf.x[1][0]
-
-
-class JerkEstimator3:
-  def __init__(self, dt):
-    from collections import deque
-    self.dt = dt
-    self.xs = deque(maxlen=int(0.2 / dt))
-    self._x = 0
-
-  @property
-  def x(self):
-    return self._x
-
-  def update(self, x):
-    self.xs.append(x)
-    if len(self.xs) < 2:
-      return 0.0
-
-    self._x = (self.xs[-1] - self.xs[0]) / ((len(self.xs) - 1) * self.dt)
-    return self._x