scipy.interpolate.interp1d¶

class
scipy.interpolate.
interp1d
(x, y, kind='linear', axis=1, copy=True, bounds_error=None, fill_value=nan, assume_sorted=False)[source]¶ Interpolate a 1D 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.Note that calling
interp1d
with NaNs present in input values results in undefined behaviour.Parameters:  x : (N,) array_like
A 1D array of real values.
 y : (…,N,…) array_like
A ND 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 (‘linear’, ‘nearest’, ‘zero’, ‘slinear’, ‘quadratic’, ‘cubic’, ‘previous’, ‘next’, where ‘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) or as an integer specifying the order of the spline interpolator to use. 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 unlessfill_value="extrapolate"
. fill_value : arraylike or (arraylike, 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 arraylike must broadcast properly to the dimensions of the noninterpolation axes.
If a twoelement tuple, then the first element is used as a fill value for
x_new < x[0]
and the second element is used forx_new > x[1]
. Anything that is not a 2element tuple (e.g., list or ndarray, regardless of shape) is taken to be a single arraylike argument meant to be used for both bounds asbelow, above = fill_value, fill_value
.New in version 0.17.0.
If “extrapolate”, then points outside the data range will be extrapolated.
New in version 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.
See also
UnivariateSpline
 An objectoriented wrapper of the FITPACK routines.
interp2d
 2D interpolation
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()
Attributes: fill_value
The fill value.
Methods
__call__
(x)Evaluate the interpolant