I would like to implement cubic spline interpolation using Intel MKL in FORTRAN. To make it clear, I coded up an equivalent Python code as follows:
###start of python code for cubic spline interpolation###
from numpy import *
from scipy.interpolate import CubicSpline
from matplotlib.pyplot import *
#Sample data, y_data=sin(x_data)
x_data = [0,1,2,3,4,5,6]
y_data = [ 0,0.84147098,0.90929743,0.14112001,-0.7568025,-0.95892427,-0.2794155]
#Defining interploation points
x = arange(0, 2*pi, 0.2)
#Building the cubic spline using CubicSpline class in scipy.interpolate
cs = CubicSpline(x_data, y_data, axis=0, bc_type='not-a-knot', extrapolate=False)
y_cubicSpline = cs(x)
#Computing the exact values at interpolation points for comparison purposes
y_exact = sin(x)
#Printing the results
print('x y_exact y_cubicSpline')
print('-----------------------------------------')
for i in range(len(x)):
print ("{:.1f} {:.15f} {:.15f}".format(x[i],y_exact[i],y_cubicSpline[i]))
#Plotting the results
plot(x_data, y_data, 'ko', label='Sample Data')
plot(x, y_cubicSpline,'b-', label="Cubic Spline Interpolation")
plot(x, y_exact,'r--', label='Exact Sine Function')
xlabel('x')
ylabel('Sin(x)')
legend(loc='best')
grid()
show()
###end of python code for cubic spline interpolation###
Results are as shown below:
The relevant files are attached as follows:
- cubic_spline_interpolation.txt
- results.txt
- Figure_1.pdf
As I understand, there are some examples regarding the implementation of cubic splines using MKL in FORTRAN in the following directory:
"C:\Program Files (x86)\IntelSWTools\compilers_and_libraries_2018.5.274\windows\mkl\examples\examples_core_f.zip\datafittingf"
However, I was not able to find the functionality demonstrated above in Python. Could you please help me re-produce the results of the Python code using Intel MKL functionalities in FORTRAN?
Thanks.
Link Copied
