if x.shape == (1,1): return x.item(0,0)
return x
+ def set_measure_cov(self, R):
+ if type(R) != type(np.matrix([0])): R = np.matrix(R)
+ if np.all(R >= np.zeros([2,2])):
+ self.R = R
+
if __name__ == '__main__':
import random
for i in range(0, 100):
# Messwert
- a = p.run(np.array([[y1[i], y2[i]]]).T)
- x1.append(a.item((0, 0)))
- x2.append(a.item((1, 0)))
+ result = p.run(np.array([[y1[i], y2[i]]]).T)
+ x1.append(result.item((0, 0)))
+ x2.append(result.item((1, 0)))
plot(orig1, label="Orig")
plot(orig2, label="Orig")