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Module « scipy.odr »

Classe « RealData »

Informations générales

Héritage

builtins.object
    Data
        RealData

Définition

class RealData(Data):

help(RealData)

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./np.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] = np.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=None)

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
__getattr__(self, attr)

Méthodes héritées de la classe Data

__init_subclass__, __subclasshook__, set_meta

Méthodes héritées de la classe object

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

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