Classe « Data »

Informations générales

Héritage

builtins.object
    Data

Définition

class Data(builtins.object):

help(Data)

The data to fit.

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.
we : array_like, optional
    If `we` is a scalar, then that value is used for all data points (and
    all dimensions of the response variable).
    If `we` is a rank-1 array of length q (the dimensionality of the
    response variable), then this vector is the diagonal of the covariant
    weighting matrix for all data points.
    If `we` is a rank-1 array of length n (the number of data points), then
    the i'th element is the weight for the i'th response variable
    observation (single-dimensional only).
    If `we` is a rank-2 array of shape (q, q), then this is the full
    covariant weighting matrix broadcast to each observation.
    If `we` is a rank-2 array of shape (q, n), then `we[:,i]` is the
    diagonal of the covariant weighting matrix for the i'th observation.
    If `we` is a rank-3 array of shape (q, q, n), then `we[:,:,i]` is the
    full specification of the covariant weighting matrix for each
    observation.
    If the fit is implicit, then only a positive scalar value is used.
wd : array_like, optional
    If `wd` is a scalar, then that value is used for all data points
    (and all dimensions of the input variable). If `wd` = 0, then the
    covariant weighting matrix for each observation is set to the identity
    matrix (so each dimension of each observation has the same weight).
    If `wd` is a rank-1 array of length m (the dimensionality of the input
    variable), then this vector is the diagonal of the covariant weighting
    matrix for all data points.
    If `wd` is a rank-1 array of length n (the number of data points), then
    the i'th element is the weight for the ith input variable observation
    (single-dimensional only).
    If `wd` is a rank-2 array of shape (m, m), then this is the full
    covariant weighting matrix broadcast to each observation.
    If `wd` is a rank-2 array of shape (m, n), then `wd[:,i]` is the
    diagonal of the covariant weighting matrix for the ith observation.
    If `wd` is a rank-3 array of shape (m, m, n), then `wd[:,:,i]` is the
    full specification of the covariant weighting matrix for each
    observation.
fix : array_like of ints, optional
    The `fix` argument is the same as ifixx in the class ODR. It is 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.
meta : dict, optional
    Free-form dictionary for metadata.

Notes
-----
Each argument is attached to the member of the instance of the same name.
The structures of `x` and `y` are described in the Model class docstring.
If `y` is an integer, then the Data instance can only be used to fit with
implicit models where the dimensionality of the response is equal to the
specified value of `y`.

The `we` argument weights the effect a deviation in the response variable
has on the fit. The `wd` argument weights the effect a deviation in the
input variable has on the fit. To handle multidimensional inputs and
responses easily, the structure of these arguments has the n'th
dimensional axis first. These arguments heavily use the structured
arguments feature of ODRPACK to conveniently and flexibly support all
options. See the ODRPACK User's Guide for a full explanation of how these
weights are used in the algorithm. Basically, a higher value of the weight
for a particular data point makes a deviation at that point more
detrimental to the fit.

Constructeur(s)

Signature du constructeur	Description
__init__(self, x, y=None, we=None, wd=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

Signature de la méthode	Description
__getattr__(self, attr)	Dispatch attribute access to the metadata dictionary. _{[extrait de __getattr__.__doc__]}
set_meta(self, **kwds)	Update the metadata dictionary with the keywords and data provided _{[extrait de set_meta.__doc__]}