Module « scipy.interpolate »

Classe « interp2d »

Informations générales

Héritage

builtins.object
    interp2d

Définition

class interp2d(builtins.object):

Description _{[extrait de interp2d.__doc__]}

    interp2d(x, y, z, kind='linear', copy=True, bounds_error=False,
             fill_value=None)

    Interpolate over a 2-D grid.

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

    If `x` and `y` represent a regular grid, consider using
    `RectBivariateSpline`.

    If `z` is a vector value, consider using `interpn`.

    Note that calling `interp2d` with NaNs present in input values results in
    undefined behaviour.

    Methods
    -------
    __call__

    Parameters
    ----------
    x, y : array_like
        Arrays defining the data point coordinates.

        If the points lie on a regular grid, `x` can specify the column
        coordinates and `y` the row coordinates, for example::

          >>> x = [0,1,2];  y = [0,3]; z = [[1,2,3], [4,5,6]]

        Otherwise, `x` and `y` must specify the full coordinates for each
        point, for example::

          >>> x = [0,1,2,0,1,2];  y = [0,0,0,3,3,3]; z = [1,2,3,4,5,6]

        If `x` and `y` are multidimensional, they are flattened before use.
    z : array_like
        The values of the function to interpolate at the data points. If
        `z` is a multidimensional array, it is flattened before use.  The
        length of a flattened `z` array is either
        len(`x`)*len(`y`) if `x` and `y` specify the column and row coordinates
        or ``len(z) == len(x) == len(y)`` if `x` and `y` specify coordinates
        for each point.
    kind : {'linear', 'cubic', 'quintic'}, optional
        The kind of spline interpolation to use. Default is 'linear'.
    copy : bool, optional
        If True, the class makes internal copies of x, y and z.
        If False, references may be used. The default is to copy.
    bounds_error : bool, optional
        If True, when interpolated values are requested outside of the
        domain of the input data (x,y), a ValueError is raised.
        If False, then `fill_value` is used.
    fill_value : number, optional
        If provided, the value to use for points outside of the
        interpolation domain. If omitted (None), values outside
        the domain are extrapolated via nearest-neighbor extrapolation.

    See Also
    --------
    RectBivariateSpline :
        Much faster 2-D interpolation if your input data is on a grid
    bisplrep, bisplev :
        Spline interpolation based on FITPACK
    BivariateSpline : a more recent wrapper of the FITPACK routines
    interp1d : 1-D version of this function

    Notes
    -----
    The minimum number of data points required along the interpolation
    axis is ``(k+1)**2``, with k=1 for linear, k=3 for cubic and k=5 for
    quintic interpolation.

    The interpolator is constructed by `bisplrep`, with a smoothing factor
    of 0. If more control over smoothing is needed, `bisplrep` should be
    used directly.

    Examples
    --------
    Construct a 2-D grid and interpolate on it:

    >>> from scipy import interpolate
    >>> x = np.arange(-5.01, 5.01, 0.25)
    >>> y = np.arange(-5.01, 5.01, 0.25)
    >>> xx, yy = np.meshgrid(x, y)
    >>> z = np.sin(xx**2+yy**2)
    >>> f = interpolate.interp2d(x, y, z, kind='cubic')

    Now use the obtained interpolation function and plot the result:

    >>> import matplotlib.pyplot as plt
    >>> xnew = np.arange(-5.01, 5.01, 1e-2)
    >>> ynew = np.arange(-5.01, 5.01, 1e-2)
    >>> znew = f(xnew, ynew)
    >>> plt.plot(x, z[0, :], 'ro-', xnew, znew[0, :], 'b-')
    >>> plt.show()
    

Constructeur(s)

Signature du constructeur	Description
__init__(self, x, y, z, kind='linear', copy=True, bounds_error=False, fill_value=None)

Liste des opérateurs

Opérateurs hérités de la classe object

__eq__, __ge__, __gt__, __le__, __lt__, __ne__

Méthodes héritées de la classe object

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