* Bug fixes and documentation update.

Wirawan Purwanto 9 years ago
parent 64691c0425
commit a244c49256
  1. 27

@ -15,12 +15,26 @@ wpylib.math.fitting.stochastic module
Tools for stochastic curve fitting.
import numpy
import numpy.random
from wpylib.math.fitting import fit_func_base
from wpylib.math.stats.errorbar import errorbar
class StochasticFitting(object):
"""Standard stochastic fit procedure.
Class attributes:
* `func`: function ansatz to be fitted.
Set via init_func() method.
This `func` needs to be a descendant of the fit_func_base object,
or have an identical API, which are:
- method `fit`
- method `__call__` (i.e. a callable object)
debug = 0
dbg_guess_params = True
@ -42,20 +56,18 @@ class StochasticFitting(object):
- the uncertainty of the target points, dy
x = fit_func_base.domain_array(x)
if not (len(x[0]) == len(y) == len(dy)):
raise TypeError, "Length of x, y, dy arrays are not identical."
# fix (or, actually, provide an accomodation for) a common "mistake"
# for 1-D domain: make it standard by adding the "first" dimension
if len(x.shape) == 1:
x = x.reshape((1, x.shape[0]))
x = fit_func_base.domain_array(x)
self.samples_x = x
self.samples_y = numpy.array(y)
self.samples_dy = numpy.array(dy)
self.samples_wt = (self.samples_dy)**(-2)
if not (len(x[0]) == len(y) == len(dy)):
raise TypeError, "Length of x, y, dy arrays are not identical."
def init_rng(self, seed=None, rng_class=numpy.random.RandomState):
"""Initializes a standard random number generator for use in
the fitting routine."""
@ -94,7 +106,8 @@ class StochasticFitting(object):
raise RuntimeError, "Cannot determine the number of fit parameters."
def nlfit1(self):
"""Performs the non-stochastic, standard nonlinear fit."""
"""Performs the non-stochastic, standard nonlinear fit.
The output is given in `nlf_rec` attribute."""
from numpy.linalg import norm
if self.use_dy_weights: