icecube.clsim.util.interpolate module¶
Classes for interpolating values.
- class icecube.clsim.util.interpolate.interp1d(x, y, kind='linear', axis=-1, copy=True, bounds_error=True, fill_value=nan)¶
Bases:
object
- interp1d(x, y, kind=’linear’, axis=-1, copy=True, bounds_error=True,
fill_value=np.nan)
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 (array_like) – A 1-D array of monotonically increasing real values.
y (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 (‘linear’,’nearest’) 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, an error is thrown 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.
fill_value (float, optional) – If provided, then this value will be used to fill in for requested points outside of the data range. If not provided, then the default is NaN.
See also
UnivariateSpline
A more recent wrapper of the FITPACK routines.
splrep
,splev
,interp2d
Examples
>>> 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()