fittools - Tools for optimized fitting of functions
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Use it like:

.. code-block:: python

   def gauss_ridge((reff, r210), a=1., mu0=10., mu1=-0.5, mu2=+0.01, si0=1.):
       mu = mu0 + mu1*reff + mu2*reff**2
       g = a*sympy.exp(-0.5*(r210-mu)**2/si0**2)
       return g
   minimizable = compileTheanoMinimizable(gauss_ridge)
   xflat = <tuple containing 1d arrays of reff and r210>
   yflat = <tuple containing potential results of gauss_ridge>
   fmin = setData(minimizable, xflat, yflat)
   guess = [1.0, 5, -0.01, 0.00, 1.]

   fitres = scipy.optimize.minimize(fmin, guess, method="SLSQP", jac=True) #currently TNC and SLSQP are tested
   print fitres.x

.. automodule:: runmacs.spec.retrieval.fittools
   :members: