Steepest descent optimization solver.
Kind: ‘opt.fmin_sd’
For common configuration parameters, see Solver.
Specific configuration parameters:
Parameters: | i_max : int (default: 10)
eps_rd : float (default: 1e-05)
eps_of : float (default: 0.0001)
eps_ofg : float (default: 1e-08)
norm : numpy norm (default: inf)
ls : bool (default: True)
ls_method : {‘backtracking’, ‘full’} (default: ‘backtracking’)
ls_on : float (default: 0.99999)
ls0 : 0.0 < float < 1.0 (default: 1.0)
ls_red : 0.0 < float < 1.0 (default: 0.5)
ls_red_warp : 0.0 < float < 1.0 (default: 0.1)
ls_min : 0.0 < float < 1.0 (default: 1e-05)
check : 0, 1 or 2 (default: 0)
delta : float (default: 1e-06)
output : function
yscales : list of str (default: [‘linear’, ‘log’, ‘log’, ‘linear’])
log : dict or None
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Interface to SciPy optimization solvers scipy.optimize.fmin_*.
Kind: ‘nls.scipy_fmin_like’
For common configuration parameters, see Solver.
Specific configuration parameters:
Parameters: | method : {‘fmin’, ‘fmin_bfgs’, ‘fmin_cg’, ‘fmin_cobyla’, ‘fmin_l_bfgs_b’, ‘fmin_ncg’, ‘fmin_powell’, ‘fmin_slsqp’, ‘fmin_tnc’} (default: ‘fmin’)
i_max : int (default: 10)
* : *
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