analysis.fitting_toolkit.fit
__init__
add_point
add_points
arg_count
arraysexist
atype
auto_deriv_steps
check_arrays
chi2
clear_resampling
compute_chi2
compute_fit
compute_funcvals
covariance_matrix
currentlen
damped_svd_fit_step
DefaultArrayType
deriv_step
derivs
firstpass
fitmat
fitvector
freeze_parameter
frozen
funcparams
funcvals
get_random_list
hessian_compute_fit
initialize_random_generator
lm_fit_step
lm_lambda
lm_lambda_recipe
numeric_deriv
param_count
pointcount
pointhint
randoms
reduced_chi2
resample
residuals
saved_xarray
saved_yarray
scalar_weights
set_initial_params
set_weights
setup_resampling
singular_value_edit
svd_covariance_matrix
svd_damping
svd_damping_recipe
svd_hessian_compute_fit
svd_u
svd_v
svd_winv
unfreeze_parameter
weight_func
weights
weights_multiply
xarray
yarray
def auto_deriv_steps (   self,
  deriv_step 
)

Define the step sizes to be used by auto_derivs()

Parameters:
deriv_step an indexable object with the same number of elements as free parameters.

Definition at line 291 of file fitting_toolkit.py.

00291                                           :
00292         "set the step sizes used for each parameter if numerical derivatives are to be used"
00293         self.deriv_step=array(deriv_step, self.atype)
00294 
    ##

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