如何绘制 scipy 优化结果

Question

我有 python scipy 使用函数 f(x) = sin(x) 进行优化，我想绘制结果。我怎样才能做到这一点？我已经尝试过这段代码。但我收到此错误：TypeError: only length-1 arrays can be converted to Python scalars

这是我的代码：

'''Import Python math library'''
import math
import matplotlib.pyplot as plt
'''try and except ImportError handler will be printing message if you haven't install required python library'''
try:
    import scipy.optimize as opt
    import scipy
    from scipy.optimize import minimize
except ImportError:
    print "You must install Python scipy first before running this program"

try:
    import numpy as np
except ImportError:
    print "You must install Python numpy first before running this program"

'''function f(x) = sin(x)'''
def f(x):
    print x
    #return -x**(2)
    return math.sin(x)

'''
check here for fmin_l_bgfs_b docs : https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.fmin_l_bfgs_b.html#scipy.optimize.fmin_l_bfgs_b
and what params need to used.

or you can take a look at here : https://docs.scipy.org/doc/scipy/reference/optimize.html for other method and algorithm
'''
initial_guess = 1.0

minbound = -9
maxbound = 9

max_bounds_area = (minbound,maxbound)
max_x = opt.fmin_l_bfgs_b(lambda x: -f(x), initial_guess, bounds=[(max_bounds_area)],approx_grad=True)

# I want to plot the result. I try this but I get TypeError: only length-1 arrays can be converted to Python scalars
t = np.arange(minbound, maxbound, initial_guess)
s = f(t)
plt.plot(t, s)
plt.show()

Answer 1

math库不能对numpy arrays进行操作，必须使用numpy中实现的函数。

必须改变

return math.sin(x)

到

return np.sin(x)

如何绘制 scipy 优化结果

how to plot scipy optimize result

python

numpy

maximize

scipy