* wpylib.math.fitting.fit_func_base: changed default fitting method to leastsq.
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@@ -41,8 +41,8 @@ The following methods are currently supported for scipy.optimize:
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See the documentation of `scipy.optimize` for more details.
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The `fmin` algorithm is the slowest although it is fairly foor proof to
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converge it (it may take many iterations).
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The leastsq` algorithm is the best but it requires parameter guess that is
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converge it (it may take very many iterations).
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The `leastsq` algorithm is the best, but it requires parameter guess that is
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reasonable.
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I don't have much success with `anneal`--it seems to behave erratically in
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my limited experience. YMMV.
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@@ -492,7 +492,7 @@ class fit_func_base(object):
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fit_default_opts["lmfit:leastsq"] = dict(xtol=1e-8, epsfcn=1e-6)
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debug = 0
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dbg_params = 1
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fit_method = 'fmin'
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fit_method = 'leastsq' # changed 20150529 from fmin. Leastsq is much faster.
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fit_opts = fit_default_opts
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#fit_opts = dict(xtol=1e-5, maxfun=100000, maxiter=10000, disp=0)
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def fit(self, x, y, dy=None, fit_opts=None, Funct_hook=None, Guess=None):
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