问题描述
这是触发问题的代码：
import numpy as np
from scipy.optimize import minimize
def find_vector_of_minor_axis_from_chunk(data):
n = 20 # number of points
guess_center_point = data.mean(1)
guess_center_point = guess_center_point[np.newaxis,:].transpose()
guess_a_phase = 0.0
guess_b_phase = 0.0
guess_a_axis_vector = np.array([[1.0],[0.0],[0.0]])
guess_b_axis_vector = np.array([[0.0],[1.0],[0.0]])
p0 = np.array([guess_center_point,guess_a_axis_vector,guess_a_phase,guess_b_axis_vector,guess_b_phase])
def ellipse_func(x,data):
center_point = x[0]
a_axis_vector = x[1]
a_phase = x[2]
b_axis_vector = x[3]
b_phase = x[4]
t = np.linspace(0,2 * np.pi,n)
error = center_point + a_axis_vector * np.sin(t * a_phase) + b_axis_vector * np.sin(t + b_phase) - data
error_sum = np.sum(error ** 2)
return np.any(error_sum)
popt,pcov = minimize(ellipse_func,p0,args=data)
center_point,a_axis_vector,a_phase,b_axis_vector,b_phase = popt
print(str(a_axis_vector + "," + b_axis_vector))
shorter_vector = a_axis_vector
if np.abs(a_axis_vector) > np.aps(b_axis_vector):
shorter_vector = b_axis_vector
return shorter_vector
def main():
data = np.array([[-4.62767933,-4.6275775,-4.62735346,-4.62719652,-4.62711625,-4.62717975,-4.62723845,-4.62722407,-4.62713901,-4.62708749,-4.62703238,-4.62689101,-4.62687185,-4.62694013,-4.62701082,-4.62700483,-4.62697488,-4.62686825,-4.62675683,-4.62675204],[-1.58625998,-1.58625039,-1.58619648,-1.58617611,-1.58620606,-1.5861833,-1.5861821,-1.58619169,-1.58615814,-1.58616893,-1.58613179,-1.58615934,-1.58611262,-1.58610782,-1.58614017,-1.58613059,-1.58612699,-1.58607428,-1.58610183],[-0.96714786,-0.96713827,-0.96715984,-0.96715145,-0.96716703,-0.96712869,-0.96716104,-0.96713228,-0.96719698,-0.9671838,-0.96717062,-0.96715744,-0.96707717,-0.96709275,-0.96706519,-0.96715026,-0.96711791,-0.96713588,-0.96714786]])
print(str(find_vector_of_minor_axis_from_chunk(data)))
if __name__ == '__main__':
main()
这是它的回溯：
"C:\Users\X\PycharmProjects\lissajous-achse\venv\Scripts\python.exe" "C:/Users/X/PycharmProjects/lissajous-achse/ellipse_fit.py"
Traceback (most recent call last):
File "C:/Users/X/PycharmProjects/lissajous-achse/ellipse_fit.py",line 57,in <module>
main()
File "C:/Users/X/PycharmProjects/lissajous-achse/ellipse_fit.py",line 53,in main
print(str(find_vector_of_minor_axis_from_chunk(data)))
File "C:/Users/X/PycharmProjects/lissajous-achse/ellipse_fit.py",line 29,in find_vector_of_minor_axis_from_chunk
popt,args=data)
File "C:\Users\X\PycharmProjects\lissajous-achse\venv\lib\site-packages\scipy\optimize\_minimize.py",line 604,in minimize
return _minimize_bfgs(fun,x0,args,jac,callback,**options)
File "C:\Users\X\PycharmProjects\lissajous-achse\venv\lib\site-packages\scipy\optimize\optimize.py",line 1063,in _minimize_bfgs
if isinf(rhok): # this is patch for numpy
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
Process finished with exit code 1
我试图在回溯中建议使用np.any()的返回值（使用np.all()或ellipse_func，但仅收到下一个内部scipy错误。
我该怎么做才能使优化运行？我愿意使用minimize()以外的其他功能。
解决方法
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