Convert FFT python to C#

I have a very little approach with coding in C# in asp.net please help converting this python code into c#.

# Python example - Fourier transform using numpy.fft method

import numpy as np

import matplotlib.pyplot as plotter



# How many time points are needed i,e., Sampling Frequency

samplingFrequency   = 100;



# At what intervals time points are sampled

samplingInterval       = 1 / samplingFrequency;



# Begin time period of the signals

beginTime           = 0;



# End time period of the signals

endTime             = 10; 



# Frequency of the signals

signal1Frequency     = 4;

signal2Frequency     = 7;



# Time points

time        = np.arange(beginTime, endTime, samplingInterval);



# Create two sine waves

amplitude1 = np.sin(2*np.pi*signal1Frequency*time)

amplitude2 = np.sin(2*np.pi*signal2Frequency*time)



# Create subplot

figure, axis = plotter.subplots(4, 1)

plotter.subplots_adjust(hspace=1)



# Time domain representation for sine wave 1

axis[0].set_title('Sine wave with a frequency of 4 Hz')

axis[0].plot(time, amplitude1)

axis[0].set_xlabel('Time')

axis[0].set_ylabel('Amplitude')





# Time domain representation for sine wave 2

axis[1].set_title('Sine wave with a frequency of 7 Hz')

axis[1].plot(time, amplitude2)

axis[1].set_xlabel('Time')

axis[1].set_ylabel('Amplitude')



# Add the sine waves

amplitude = amplitude1 + amplitude2



# Time domain representation of the resultant sine wave

axis[2].set_title('Sine wave with multiple frequencies')

axis[2].plot(time, amplitude)

axis[2].set_xlabel('Time')

axis[2].set_ylabel('Amplitude')



# Frequency domain representation

fourierTransform = np.fft.fft(amplitude)/len(amplitude)           # Normalize amplitude

fourierTransform = fourierTransform[range(int(len(amplitude)/2))] # Exclude sampling frequency



tpCount     = len(amplitude)

values      = np.arange(int(tpCount/2))

timePeriod  = tpCount/samplingFrequency

frequencies = values/timePeriod



# Frequency domain representation

axis[3].set_title('Fourier transform depicting the frequency components')



axis[3].plot(frequencies, abs(fourierTransform))

axis[3].set_xlabel('Frequency')

axis[3].set_ylabel('Amplitude')



plotter.show()