[SciPy-User] _minimize_bfgs throws error: ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

[Schuldei, Andreas]

I seem to trigger an internal error in scipy.optimize.minimize, somehow.


This is the code that triggers the problem:


    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, -1.58613179, -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, -0.96717062,
                          -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()

and this is the traceback for it:

    "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, pcov = minimize(ellipse_func, p0, 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

I tried to take the suggestion in the traceback (to use `np.any()` or `np.all()`) on the return value of the `ellipse_func`, but just got the next internal scipy error.

What can I do to get my optimization running? I am open to using other functions besides `minimize()`.


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