scipy.interpolate.BSpline.integrate¶
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BSpline.integrate(self, a, b, extrapolate=None)[source]¶
- Compute a definite integral of the spline. - Parameters
- afloat
- Lower limit of integration. 
- bfloat
- Upper limit of integration. 
- extrapolatebool or ‘periodic’, optional
- whether to extrapolate beyond the base interval, - t[k] .. t[-k-1], or take the spline to be zero outside of the base interval. If ‘periodic’, periodic extrapolation is used. If None (default), use self.extrapolate.
 
- Returns
- Iarray_like
- Definite integral of the spline over the interval - [a, b].
 
 - Examples - Construct the linear spline - x if x < 1 else 2 - xon the base interval \([0, 2]\), and integrate it- >>> from scipy.interpolate import BSpline >>> b = BSpline.basis_element([0, 1, 2]) >>> b.integrate(0, 1) array(0.5) - If the integration limits are outside of the base interval, the result is controlled by the extrapolate parameter - >>> b.integrate(-1, 1) array(0.0) >>> b.integrate(-1, 1, extrapolate=False) array(0.5) - >>> import matplotlib.pyplot as plt >>> fig, ax = plt.subplots() >>> ax.grid(True) >>> ax.axvline(0, c='r', lw=5, alpha=0.5) # base interval >>> ax.axvline(2, c='r', lw=5, alpha=0.5) >>> xx = [-1, 1, 2] >>> ax.plot(xx, b(xx)) >>> plt.show()   
