NuclearDispersionSystem/ant-design-vue-jeecg/node_modules/fmin/test.py
2023-09-14 14:47:11 +08:00

48 lines
1.3 KiB
Python

import scipy.optimize
import math
def himmelblau(x, y):
return (x * x + y - 11) * ( x * x + y - 11) + (x + y * y - 7) * (x + y * y - 7)
def beale(x, y):
return math.pow(1.5 - x + x*y, 2) + math.pow(2.25 - x + x*y*y, 2) + math.pow(2.625 - x + x*y*y*y, 2);
def main():
if True:
initial = [-3.670609291875735,3.8585484651848674]
solution = scipy.optimize.fmin(lambda x: beale(x[0], x[1]),
initial, retall=True)
print "loss", beale(solution[0][0], solution[0][1])
elif False:
def banana(x, y):
return (1 - x) * (1 - x) + 100 * (y - x * x) * ( y - x * x)
initial = [-1.675793744623661,-1.945310341194272]
solution = scipy.optimize.fmin(lambda x: banana(x[0], x[1]),
initial, retall=True)
elif False:
initial = [4.474377192556858, 0.22207495383918285]
initial = [-7.185110699385405, 0.01616438291966915]
solution = scipy.optimize.fmin(lambda x: himmelblau(x[0], x[1]),
initial, retall=True)
else:
solution = scipy.optimize.fmin(lambda x: (x[0]-10) * (x[0]-10), [0], retall=True)
print solution[0]
for i, s in enumerate(solution[1]):
print str(i) + ":", s
if __name__ == "__main__":
main()