Error: _vhstack_dispatcher() takes 1 positional argument but 9 were given

[alexfrol86]

Hi!

I have a system of 10 nonlinear ODE with 10 variables (y[0], y[1], ... y[9]), there are 10 initial conditions for y[i] for x=0 and 4 conditions for x = 6.804.

I try to solve a boundary value problem using scipy.integrate.solve_bvp according to the following algorithm: https://docs.scipy.org/doc/scipy/referen...e_bvp.html
I get the error "_vhstack_dispatcher() takes 1 positional argument but 9 were given" though I tried to use np.dstack instead of np.hstack. Please help to fix the error.

My code is below:

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import numpy as np from scipy.integrate import solve_bvp import matplotlib.pyplot as plt from scipy.constants import g   def fun(x, y):     return np.vstack((ptb / y[4] * y[5] / np.sqrt(y[5]**2 + y[6]**2) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes) - 1 / y[2]**2 + y[1]**2 / y[2],                       ptb / y[4] * y[6] / np.sqrt(y[5]**2 + y[6]**2) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes) - y[0] * y[1] / y[2]),                      y[0], y[1] / y[2],                       -mqb * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes), y[6] * y[1] / y[2] - y[7], -y[5] * 2.0 * y[1] / y[2] + y[6] * y[0] / y[2] - y[8] * 1.0 / y[2],                       y[5] * (-2.0 / y[2]**3 + y[1]**2 / y[2]**2) + y[6] * (-y[0] * y[1]) / y[2] + y[8] * y[1] / y[2]**2, 0,                        ptb / y[4]**2 * (np.sqrt(y[5]**2 + y[6]**2)) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes))         #Implement evaluation of the boundary condition residuals:   def bc(ya, yb):     return np.array([ya[-0.03899746484, 1.05800280714, -0.30648856279, -0.605427, 1, -0.065851, 1.361805, 1.419320, -8.219418e-5, 0.6], yb[3.230021179060866e-17, 0.5519654178809713, 2.221001221001221, np.pi]]) #Define the initial mesh with 20 nodes:   x = np.linspace(0.0, 6.804, 20)   #To obtain solutions, different initial guesses for y are used. They are denoted by subscripts a and b. y_a = np.zeros((10, x.size)) y_b = np.zeros((10, x.size)) y_b[0] = 3.230021179060866e-17   res_a = solve_bvp(fun, bc, x, y_a) res_b = solve_bvp(fun, bc, x, y_b)   x_plot = np.linspace(0, 6.804, 100) y_plot_a = res_a.sol(x_plot)[0] y_plot_b = res_b.sol(x_plot)[0] #plt.plot(x_plot, y_plot_a, label='y_a') #plt.plot(x_plot, y_plot_b, label='y_b') plt.legend() plt.xlabel("x") plt.ylabel("y") plt.show()

[deanhystad]

Please post error message and trace.

The documentation for vstack says it takes one tuple.

https://numpy.org/doc/stable/reference/g...stack.html

You are providing 9 arguments.

Let's count.

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(ptb / y[4] * y[5] / np.sqrt(y[5]**2 + y[6]**2) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes) - 1 / y[2]**2 + y[1]**2 / y[2],  ptb / y[4] * y[6] / np.sqrt(y[5]**2 + y[6]**2) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes) - y[0] * y[1] / y[2]),  #1                   y[0],  #2   y[1] / y[2],  #3           -mqb * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes),  #4           y[6] * y[1] / y[2] - y[7],  #5           -y[5] * 2.0 * y[1] / y[2] + y[6] * y[0] / y[2] - y[8] * 1.0 / y[2],  #6   y[5] * (-2.0 / y[2]**3 + y[1]**2 / y[2]**2) + y[6] * (-y[0] * y[1]) / y[2] + y[8] * y[1] / y[2]**2,  #7           0,  #8           ptb / y[4]**2 * (np.sqrt(y[5]**2 + y[6]**2)) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes)  #9 )

I count 9.

Number 1 is a doozy. Unlike the others, it is a tuple all by iteself, and it does this twice:

1	ptb / y[4] * y[5] / np.sqrt(y[5]**2 + y[6]**2) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes)

[alexfrol86]

Thanks, I corrected equations. Now, there are 10 arguments:

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def fun(x, y):     return np.vstack(ptb / y[4] * y[5] / np.sqrt(y[5]**2 + y[6]**2) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes) - 1 / y[2]**2 + y[1]**2 / y[2],                       ptb / y[4] * y[6] / np.sqrt(y[5]**2 + y[6]**2) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes) - y[0] * y[1] / y[2],                      y[0], y[1] / y[2],                       -mqb * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes), y[6] * y[1] / y[2] - y[7], -y[5] * 2.0 * y[1] / y[2] + y[6] * y[0] / y[2] - y[8] * 1.0 / y[2],                       y[5] * (-2.0 / y[2]**3 + y[1]**2 / y[2]**2) + y[6] * (-y[0] * y[1]) / y[2] + y[8] * y[1] / y[2]**2, 0,                        ptb / y[4]**2 * (np.sqrt(y[5]**2 + y[6]**2)) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes))

Here are error message and trace:

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TypeError                                 Traceback (most recent call last) <ipython-input-7-5b67a8d7cfc5> in <module>()      19 # y = myFn(R, x, cc)      20 ---> 21 res_a = solve_bvp(fun, bc, x, y_a)      22 res_b = solve_bvp(fun, bc, x, y_b)      23   2 frames <ipython-input-6-6f15cb472e1d> in fun(x, y)       5                       -mqb * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes), y[6] * y[1] / y[2] - y[7], -y[5] * 2.0 * y[1] / y[2] + y[6] * y[0] / y[2] - y[8] * 1.0 / y[2],       6                       y[5] * (-2.0 / y[2]**3 + y[1]**2 / y[2]**2) + y[6] * (-y[0] * y[1]) / y[2] + y[8] * y[1] / y[2]**2, 0, ----> 7                        ptb / y[4]**2 * (np.sqrt(y[5]**2 + y[6]**2)) * function_deo(y[4], y[5], y[6], y[9], ptb, mqb, pes))   <__array_function__ internals> in vstack(*args, **kwargs)   TypeError: _vhstack_dispatcher() takes 1 positional argument but 10 were given

How can I change the code to fix the error? Is there something I could use instead of vstack?

[deanhystad]

As far as vstack is concerned you are passing 10 numbers. It wants a tuple. How can you change 10 numbers into a tuple (list is acceptable too)?