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Les fondamentaux
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Module « scipy.odr »

Classe « ODR »

Informations générales

Héritage

builtins.object
    ODR

Définition

class ODR(builtins.object):

help(ODR)

The ODR class gathers all information and coordinates the running of the
main fitting routine.

Members of instances of the ODR class have the same names as the arguments
to the initialization routine.

Parameters
----------
data : Data class instance
    instance of the Data class
model : Model class instance
    instance of the Model class

Other Parameters
----------------
beta0 : array_like of rank-1
    a rank-1 sequence of initial parameter values. Optional if
    model provides an "estimate" function to estimate these values.
delta0 : array_like of floats of rank-1, optional
    a (double-precision) float array to hold the initial values of
    the errors in the input variables. Must be same shape as data.x
ifixb : array_like of ints of rank-1, optional
    sequence of integers with the same length as beta0 that determines
    which parameters are held fixed. A value of 0 fixes the parameter,
    a value > 0 makes the parameter free.
ifixx : array_like of ints with same shape as data.x, optional
    an array of integers with the same shape as data.x that determines
    which input observations are treated as fixed. One can use a sequence
    of length m (the dimensionality of the input observations) to fix some
    dimensions for all observations. A value of 0 fixes the observation,
    a value > 0 makes it free.
job : int, optional
    an integer telling ODRPACK what tasks to perform. See p. 31 of the
    ODRPACK User's Guide if you absolutely must set the value here. Use the
    method set_job post-initialization for a more readable interface.
iprint : int, optional
    an integer telling ODRPACK what to print. See pp. 33-34 of the
    ODRPACK User's Guide if you absolutely must set the value here. Use the
    method set_iprint post-initialization for a more readable interface.
errfile : str, optional
    string with the filename to print ODRPACK errors to. If the file already
    exists, an error will be thrown. The `overwrite` argument can be used to
    prevent this. *Do Not Open This File Yourself!*
rptfile : str, optional
    string with the filename to print ODRPACK summaries to. If the file
    already exists, an error will be thrown. The `overwrite` argument can be
    used to prevent this. *Do Not Open This File Yourself!*
ndigit : int, optional
    integer specifying the number of reliable digits in the computation
    of the function.
taufac : float, optional
    float specifying the initial trust region. The default value is 1.
    The initial trust region is equal to taufac times the length of the
    first computed Gauss-Newton step. taufac must be less than 1.
sstol : float, optional
    float specifying the tolerance for convergence based on the relative
    change in the sum-of-squares. The default value is eps**(1/2) where eps
    is the smallest value such that 1 + eps > 1 for double precision
    computation on the machine. sstol must be less than 1.
partol : float, optional
    float specifying the tolerance for convergence based on the relative
    change in the estimated parameters. The default value is eps**(2/3) for
    explicit models and ``eps**(1/3)`` for implicit models. partol must be less
    than 1.
maxit : int, optional
    integer specifying the maximum number of iterations to perform. For
    first runs, maxit is the total number of iterations performed and
    defaults to 50. For restarts, maxit is the number of additional
    iterations to perform and defaults to 10.
stpb : array_like, optional
    sequence (``len(stpb) == len(beta0)``) of relative step sizes to compute
    finite difference derivatives wrt the parameters.
stpd : optional
    array (``stpd.shape == data.x.shape`` or ``stpd.shape == (m,)``) of relative
    step sizes to compute finite difference derivatives wrt the input
    variable errors. If stpd is a rank-1 array with length m (the
    dimensionality of the input variable), then the values are broadcast to
    all observations.
sclb : array_like, optional
    sequence (``len(stpb) == len(beta0)``) of scaling factors for the
    parameters. The purpose of these scaling factors are to scale all of
    the parameters to around unity. Normally appropriate scaling factors
    are computed if this argument is not specified. Specify them yourself
    if the automatic procedure goes awry.
scld : array_like, optional
    array (scld.shape == data.x.shape or scld.shape == (m,)) of scaling
    factors for the *errors* in the input variables. Again, these factors
    are automatically computed if you do not provide them. If scld.shape ==
    (m,), then the scaling factors are broadcast to all observations.
work : ndarray, optional
    array to hold the double-valued working data for ODRPACK. When
    restarting, takes the value of self.output.work.
iwork : ndarray, optional
    array to hold the integer-valued working data for ODRPACK. When
    restarting, takes the value of self.output.iwork.
overwrite : bool, optional
    If it is True, output files defined by `errfile` and `rptfile` are
    overwritten. The default is False.

Attributes
----------
data : Data
    The data for this fit
model : Model
    The model used in fit
output : Output
    An instance if the Output class containing all of the returned
    data from an invocation of ODR.run() or ODR.restart()

Constructeur(s)

Signature du constructeur Description
__init__(self, data, model, beta0=None, delta0=None, ifixb=None, ifixx=None, job=None, iprint=None, errfile=None, rptfile=None, ndigit=None, taufac=None, sstol=None, partol=None, maxit=None, stpb=None, stpd=None, sclb=None, scld=None, work=None, iwork=None, overwrite=False)

Liste des opérateurs

Opérateurs hérités de la classe object

__eq__, __ge__, __gt__, __le__, __lt__, __ne__

Liste des méthodes

Toutes les méthodes Méthodes d'instance Méthodes statiques Méthodes dépréciées
Signature de la méthodeDescription
restart(self, iter=None) Restarts the run with iter more iterations. [extrait de restart.__doc__]
run(self) Run the fitting routine with all of the information given and with ``full_output=1``. [extrait de run.__doc__]
set_iprint(self, init=None, so_init=None, iter=None, so_iter=None, iter_step=None, final=None, so_final=None) Set the iprint parameter for the printing of computation reports. [extrait de set_iprint.__doc__]
set_job(self, fit_type=None, deriv=None, var_calc=None, del_init=None, restart=None)

Méthodes héritées de la classe object

__delattr__, __dir__, __format__, __getattribute__, __getstate__, __hash__, __init_subclass__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

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