Module « scipy.interpolate »

Classe « interp1d »

Informations générales

Héritage

builtins.object
    _Interpolator1D
        interp1d

Définition

class interp1d(_Interpolator1D):

Description _{[extrait de interp1d.__doc__]}

    Interpolate a 1-D function.

    `x` and `y` are arrays of values used to approximate some function f:
    ``y = f(x)``. This class returns a function whose call method uses
    interpolation to find the value of new points.

    Parameters
    ----------
    x : (N,) array_like
        A 1-D array of real values.
    y : (...,N,...) array_like
        A N-D array of real values. The length of `y` along the interpolation
        axis must be equal to the length of `x`.
    kind : str or int, optional
        Specifies the kind of interpolation as a string or as an integer
        specifying the order of the spline interpolator to use.
        The string has to be one of 'linear', 'nearest', 'nearest-up', 'zero',
        'slinear', 'quadratic', 'cubic', 'previous', or 'next'. 'zero',
        'slinear', 'quadratic' and 'cubic' refer to a spline interpolation of
        zeroth, first, second or third order; 'previous' and 'next' simply
        return the previous or next value of the point; 'nearest-up' and
        'nearest' differ when interpolating half-integers (e.g. 0.5, 1.5)
        in that 'nearest-up' rounds up and 'nearest' rounds down. Default
        is 'linear'.
    axis : int, optional
        Specifies the axis of `y` along which to interpolate.
        Interpolation defaults to the last axis of `y`.
    copy : bool, optional
        If True, the class makes internal copies of x and y.
        If False, references to `x` and `y` are used. The default is to copy.
    bounds_error : bool, optional
        If True, a ValueError is raised any time interpolation is attempted on
        a value outside of the range of x (where extrapolation is
        necessary). If False, out of bounds values are assigned `fill_value`.
        By default, an error is raised unless ``fill_value="extrapolate"``.
    fill_value : array-like or (array-like, array_like) or "extrapolate", optional
        - if a ndarray (or float), this value will be used to fill in for
          requested points outside of the data range. If not provided, then
          the default is NaN. The array-like must broadcast properly to the
          dimensions of the non-interpolation axes.
        - If a two-element tuple, then the first element is used as a
          fill value for ``x_new < x[0]`` and the second element is used for
          ``x_new > x[-1]``. Anything that is not a 2-element tuple (e.g.,
          list or ndarray, regardless of shape) is taken to be a single
          array-like argument meant to be used for both bounds as
          ``below, above = fill_value, fill_value``.

          .. versionadded:: 0.17.0
        - If "extrapolate", then points outside the data range will be
          extrapolated.

          .. versionadded:: 0.17.0
    assume_sorted : bool, optional
        If False, values of `x` can be in any order and they are sorted first.
        If True, `x` has to be an array of monotonically increasing values.

    Attributes
    ----------
    fill_value

    Methods
    -------
    __call__

    See Also
    --------
    splrep, splev
        Spline interpolation/smoothing based on FITPACK.
    UnivariateSpline : An object-oriented wrapper of the FITPACK routines.
    interp2d : 2-D interpolation

    Notes
    -----
    Calling `interp1d` with NaNs present in input values results in
    undefined behaviour.

    Input values `x` and `y` must be convertible to `float` values like
    `int` or `float`.
    
    If the values in `x` are not unique, the resulting behavior is
    undefined and specific to the choice of `kind`, i.e., changing
    `kind` will change the behavior for duplicates.


    Examples
    --------
    >>> import matplotlib.pyplot as plt
    >>> from scipy import interpolate
    >>> x = np.arange(0, 10)
    >>> y = np.exp(-x/3.0)
    >>> f = interpolate.interp1d(x, y)

    >>> xnew = np.arange(0, 9, 0.1)
    >>> ynew = f(xnew)   # use interpolation function returned by `interp1d`
    >>> plt.plot(x, y, 'o', xnew, ynew, '-')
    >>> plt.show()
    

Constructeur(s)

Signature du constructeur	Description
__init__(self, x, y, kind='linear', axis=-1, copy=True, bounds_error=None, fill_value=nan, assume_sorted=False)	Initialize a 1-D linear interpolation class. [extrait de __init__.__doc__]

Liste des attributs statiques

Attributs statiques hérités de la classe _Interpolator1D

dtype

Liste des opérateurs

Opérateurs hérités de la classe object

__eq__, __ge__, __gt__, __le__, __lt__, __ne__

Méthodes héritées de la classe _Interpolator1D

__call__, __init_subclass__, __subclasshook__

Méthodes héritées de la classe object

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