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      import math

      import numpy as np

      from bin16 import *

      def power_of_2(number):

      	if number == 0:

      		return 0 

      	while(number % 2 == 0):

      		number = number / 2

      	if number > 1:

      		return 0 

      	return 1

      #here we simply do the FFT algorithm, using the Cooley-Tukey idea of divide and conquer and quantizing the values (working with integers)

      #note that the output result will be already divided by N, which is not what happens for the np.fft routine

      def fft_CT(x):

      	N = len(x)

      	if N == 1:

      		return x

      	x_e = x[::2]

      	x_o = x[1::2]

      	X_e = fft_CT(x_e)

      	X_o = fft_CT(x_o)

      	X = np.zeros(N,'complex')

      	M = N/2

      	for k in range(M):

      		X[k] = X_e[k] + X_o[k] * pow(math.e,-2j*math.pi*k/N)

      		a = X[k].real/2

      		b = X[k].imag/2

      		a = int(a)

      		a = trunc16(a)

      		b = int(b)

      		b = trunc16(b)

      		c = complex(a,b)

      		X[k] = c

      	for k in range(M,N):

      		X[k] = X_e[k-M] - X_o[k-M] * pow(math.e,-2j*math.pi*(k-M)/N)

      		a = X[k].real/2

      		b = X[k].imag/2

      		a = int(a)

      		a = trunc16(a)

      		b = int(b)

      		b = trunc16(b)

      		c = complex(a,b)

      		X[k] = c

      	return X

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				import math
				import numpy as np
				from bin16 import *

				def power_of_2(number):
				if number == 0:
				return 0
				while(number % 2 == 0):
				number = number / 2
				if number > 1:
				return 0
				return 1

				#here we simply do the FFT algorithm, using the Cooley-Tukey idea of divide and conquer and quantizing the values (working with integers)
				#note that the output result will be already divided by N, which is not what happens for the np.fft routine
				def fft_CT(x):

				N = len(x)

				if N == 1:
				return x

				x_e = x[::2]
				x_o = x[1::2]
				X_e = fft_CT(x_e)
				X_o = fft_CT(x_o)

				X = np.zeros(N,'complex')

				M = N/2
				for k in range(M):
				X[k] = X_e[k] + X_o[k] * pow(math.e,-2jmath.pik/N)
				a = X[k].real/2
				b = X[k].imag/2
				a = int(a)
				a = trunc16(a)
				b = int(b)
				b = trunc16(b)
				c = complex(a,b)
				X[k] = c
				for k in range(M,N):
				X[k] = X_e[k-M] - X_o[k-M] * pow(math.e,-2jmath.pi(k-M)/N)
				a = X[k].real/2
				b = X[k].imag/2
				a = int(a)
				a = trunc16(a)
				b = int(b)
				b = trunc16(b)
				c = complex(a,b)
				X[k] = c
				return X