import numpy as np
import scipy.linalg as sl
m, n = 10, 9
A = np.random.random((m,n))
b = np.random.random(m)
x = sl.lstsq(A, b)[0]
print(np.linalg.norm(x))
import numpy as np
import scipy.optimize as op
f = lambda x : -(np.sin(x - 2) ** 2) * (np.exp(-(x**2)))
ans = op.minimize_scalar(f)
ans['fun'] = -ans['fun']
print(ans)
import numpy as np
import scipy.optimize as op
import scipy.spatial.distance as dst
cities = np.random.random((5,2))
ans = dst.cdist(cities, cities)
print("Cities' coordinate:")
print(cities)
print("DIstance:")
print(ans)