Module « scipy.odr »

Classe « RealData »

Informations générales

Héritage

builtins.object
    Data
        RealData

Définition

class RealData(Data):

Description _{[extrait de RealData.__doc__]}

    The data, with weightings as actual standard deviations and/or
    covariances.

    Parameters
    ----------
    x : array_like
        Observed data for the independent variable of the regression
    y : array_like, optional
        If array-like, observed data for the dependent variable of the
        regression. A scalar input implies that the model to be used on
        the data is implicit.
    sx : array_like, optional
        Standard deviations of `x`.
        `sx` are standard deviations of `x` and are converted to weights by
        dividing 1.0 by their squares.
    sy : array_like, optional
        Standard deviations of `y`.
        `sy` are standard deviations of `y` and are converted to weights by
        dividing 1.0 by their squares.
    covx : array_like, optional
        Covariance of `x`
        `covx` is an array of covariance matrices of `x` and are converted to
        weights by performing a matrix inversion on each observation's
        covariance matrix.
    covy : array_like, optional
        Covariance of `y`
        `covy` is an array of covariance matrices and are converted to
        weights by performing a matrix inversion on each observation's
        covariance matrix.
    fix : array_like, optional
        The argument and member fix is the same as Data.fix and ODR.ifixx:
        It is an array of integers with the same shape as `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.
    meta : dict, optional
        Free-form dictionary for metadata.

    Notes
    -----
    The weights `wd` and `we` are computed from provided values as follows:

    `sx` and `sy` are converted to weights by dividing 1.0 by their squares.
    For example, ``wd = 1./numpy.power(`sx`, 2)``.

    `covx` and `covy` are arrays of covariance matrices and are converted to
    weights by performing a matrix inversion on each observation's covariance
    matrix. For example, ``we[i] = numpy.linalg.inv(covy[i])``.

    These arguments follow the same structured argument conventions as wd and
    we only restricted by their natures: `sx` and `sy` can't be rank-3, but
    `covx` and `covy` can be.

    Only set *either* `sx` or `covx` (not both). Setting both will raise an
    exception. Same with `sy` and `covy`.

    

Constructeur(s)

Signature du constructeur	Description
__init__(self, x, y=None, sx=None, sy=None, covx=None, covy=None, fix=None, meta={})

Liste des opérateurs

Opérateurs hérités de la classe object

__eq__, __ge__, __gt__, __le__, __lt__, __ne__

Méthodes héritées de la classe Data

__init_subclass__, __subclasshook__, set_meta

Méthodes héritées de la classe object

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