title: numpy ndarray error in lmfit when mdel is passed using sympy
body: <p>I got the following error:</p>
  <blockquote>
  <p>&lt;lambdifygenerated-1&gt;:2: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.return numpy.array((A1<em>exp(-1/2</em>(x - xc1)**2/sigma1**2), 0, 0))</p>
  </blockquote>
  <p>Here I have just one model but this code is written for model combination in fitting by the lmfit Please kindly let me know about it.</p>
  <pre><code>import matplotlib.pyplot as plt
  import numpy as np
  import sympy
  from sympy.parsing import sympy_parser
  import lmfit
  
  gauss_peak1 = sympy_parser.parse_expr('A1*exp(-(x-xc1)**2/(2*sigma1**2))')
  gauss_peak2 = 0
  exp_back = 0
  
  model_list = sympy.Array((gauss_peak1, gauss_peak2, exp_back))
  model = sum(model_list)
  print(model)
  
  
  
  model_list_func = sympy.lambdify(list(model_list.free_symbols), model_list)
  model_func = sympy.lambdify(list(model.free_symbols), model)
  
  
  np.random.seed(1)
  x = np.linspace(0, 10, 40)
  param_values = dict(x=x, A1=2, sigma1=1, xc1=2)
  y = model_func(**param_values)
  yi = model_list_func(**param_values)
  yn = y + np.random.randn(y.size)*0.4
  
  plt.plot(x, yn, 'o')
  plt.plot(x, y)
  
  
  lm_mod = lmfit.Model(model_func, independent_vars=('x'))
  res = lm_mod.fit(data=yn, **param_values)
  res.plot_fit()
  plt.plot(x, y, label='true')
  plt.legend()
  plt.show()
  </code></pre>