Interpolation in SciPy

In the following code example, x can be viewed as the x axis with a set of values from 0 to 10, while the vertical axis is y, where y = exp(-x/3). We intend to interpolate between different y(i) values by applying two methods: linear and cubic. The following lines of code are an example from SciPy Reference Guide:

>>>import numpy as np
>>>import matplotlib.pyplot as plt
>>>from scipy.interpolate import interp1d
>>>x = np.linspace(0, 10, 10)
>>>y = np.exp(-x/3.0)
>>>f = interp1d(x, y)
>>>f2 = interp1d(x, y, kind='cubic')
>>>xnew = np.linspace(0, 10, 40)
>>>plt.plot(x,y,'o',xnew,f(xnew),'-', xnew, f2(xnew),'--')
>>>plt.legend(['data', 'linear', 'cubic'], loc='best')
>>>plt.show()

In the preceding program, we use the np.linspace() function to generate evenly spaced numbers—40 values—over a specified interval, from 0 to 10 in this case. The related output is shown as follows...