vhartman

import matplotlib.pyplot as plt
import numpy as np

import time

def twod(xs, xf, cb, overlay_polytope = False, show_box = False):
    pts = []

    for i in range(10000):
        x = (np.random.rand(2)-0.5) * 10

vhartman

import filterpy
from filterpy import kalman
import numpy as np

def fx(x, dt):
    # state transition function - predict next state based
    # on constant velocity model x = vt + x_0
    F = np.array([[1.]], dtype=np.float32)
    return np.dot(F, x)