def plot_g_h_results(measurements, filtered_data,
title="", z_label="Scale",):
bp.plot_measurements(measurements, label=z_label)
bp.plot_filter(filtered_data)
plt.legend(loc=4)
plt.title(title)
plt.gca().set_xlim(left=0,right=len(measurements))
plt.show()
def plot_g_h_results(
measurements,
filtered_data,
title="",
z_label="Scale",
):
bp.plot_measurements(measurements, label=z_label)
bp.plot_filter(filtered_data)
plt.legend(loc=4)
plt.title(title)
plt.gca().set_xlim(left=0, right=len(measurements))
plt.show()
tracker.R = np.array([[5,0],
[0,5]])
tracker.Q = np.eye(4) * 0.1
tracker.P = np.eye(4) * 500
count = 80
tx, ty = [],[]
xs, ys = [],[]
pxs, pys = [],[]
sensor = PosSensor1([0,0], (2,2), 1)
for i in range(count):
tp = sensor.getPos()
tx.append(tp[0]*.3084)
ty.append(tp[1]*.3084)
pos = sensor.read()
z = np.array([[pos[0]], [pos[1]]])
tracker.predict()
tracker.update(z)
xs.append(tracker.x[0,0])
ys.append(tracker.x[2,0])
pxs.append(pos[0]*.3084)
pys.append(pos[1]*.3084)
plt.plot(tx,ty)
bp.plot_filter(xs, ys)
bp.plot_measurements(pxs, pys)
plt.legend(loc="best")
plt.show()
tracker.H = np.array([[1 / 0.3084, 0, 0, 0], [0, 0, 1 / 0.3084, 0]])
tracker.R = np.array([[5, 0], [0, 5]])
tracker.Q = np.eye(4) * 0.1
tracker.P = np.eye(4) * 500
count = 80
tx, ty = [], []
xs, ys = [], []
pxs, pys = [], []
sensor = PosSensor1([0, 0], (2, 2), 1)
for i in range(count):
tp = sensor.getPos()
tx.append(tp[0] * .3084)
ty.append(tp[1] * .3084)
pos = sensor.read()
z = np.array([[pos[0]], [pos[1]]])
tracker.predict()
tracker.update(z)
xs.append(tracker.x[0, 0])
ys.append(tracker.x[2, 0])
pxs.append(pos[0] * .3084)
pys.append(pos[1] * .3084)
plt.plot(tx, ty)
bp.plot_filter(xs, ys)
bp.plot_measurements(pxs, pys)
plt.legend(loc="best")
plt.show()
