Python | Numpy np.fftn() method (original) (raw)

Last Updated : 21 Nov, 2019

With the help of **np.fftn()** method, we can get the N-D Fourier Transform by using np.fftn() method.

Syntax : np.fftn(Array)
Return : Return a N-D series of fourier transformation.

Example #1 :
In this example we can see that by using np.fftn() method, we are able to get the N-D series of fourier transformation by using this method.

import numpy as np

a = np.array([ - 1 , 3 , - 4 , 7 , 0 ])

gfg = np.fft.fftn(a)

print (gfg)

Output :

[ 5. +0.j -2.5 +3.61246823j -2.5-12.22497744j -2.5+12.22497744j
-2.5 -3.61246823j]

Example #2 :

import numpy as np

a = np.array([[ - 5.5 , 4.4 , - 6.6 , 3.3 , - 7.7 ], [ 1.1 , - 3.3 , 4.4 , - 7.7 , 0 ]])

gfg = np.fft.fftn(a)

print (gfg)

Output :

[[-17.6 +0.j -1.1 -9.6624249j -1.1 -3.08018588j
-1.1 +3.08018588j -1.1 +9.6624249j ]
[ -6.6 +0.j -6.6 -1.7149948j -6.6-29.97513624j
-6.6+29.97513624j -6.6 +1.7149948j ]]

Similar Reads

• Python | Numpy np.fft() method With the help of np.fft() method, we can get the 1-D Fourier Transform by using np.fft() method. Syntax : np.fft(Array) Return : Return a series of fourier transformation. Example #1 : In this example we can see that by using np.fft() method, we are able to get the series of fourier transformation b 1 min read
• Python | Numpy np.ifftn() method With the help of np.ifftn() method, we can get the N-D Inverse Fourier Transform by using np.fftn() method. Syntax : np.ifftn(Array) Return : Return a N-D series of inverse fourier transformation. Example #1 : In this example we can see that by using np.ifftn() method, we are able to get the N-D ser 1 min read
• Python | Numpy np.fft2() method With the help of np.fft2() method, we can get the 2-D Fourier Transform by using np.fft2() method. Syntax : np.fft2(Array) Return : Return a 2-D series of fourier transformation. Example #1 : In this example we can see that by using np.fft2() method, we are able to get the 2-D series of fourier tran 1 min read
• Python | Numpy np.ifft() method With the help of np.ifft() method, we can get the 1-D Inverse Fourier Transform by using np.ifft() method. Syntax : np.ifft(Array) Return : Return a series of inverse fourier transformation. Example #1 : In this example we can see that by using np.ifft() method, we are able to get the series of inve 1 min read
• Python | Numpy np.ifft2() method With the help of np.ifft2() method, we can get the 2-D Inverse Fourier Transform by using np.ifft2() method. Syntax : np.fft2(Array) Return : Return a 2-D series of inverse fourier transformation. Example #1 : In this example we can see that by using np.ifft2() method, we are able to get the 2-D ser 1 min read
• Python | Numpy np.hermone() method With the help of np.hermone() method, we can use hermone instead of np.ones by using np.hermone() method. Syntax : np.hermone() Return : Return array([1]) Example #1 : In this example we can see that by using np.hermone() method, we are able to get the functionality of np.ones as same as this method 1 min read
• numpy.interp() function - Python numpy.interp() function returns the one-dimensional piecewise linear interpolant to a function with given discrete data points (xp, fp), evaluated at x. Syntax : numpy.interp(x, xp, fp, left = None, right = None, period = None) Parameters : x : [array_like] The x-coordinates at which to evaluate the 2 min read
• numpy bartlett() in Python The Bartlett window is very similar to a triangular window, except that the endpoints are at zero. It is often used in signal processing for tapering a signal, without generating too much ripple in the frequency domain. Parameters(numpy.bartlett(M)): M : int Number of points in the output window. If 2 min read
• numpy.i0() function | Python numpy.i0() function is the modified Bessel function of the first kind, order 0. it's usually denoted by I0. Syntax : numpy.i0(x) Parameters : x : [array_like, dtype float or complex] Argument of the Bessel function. Return : [ndarray, shape = x.shape, dtype = x.dtype] The modified Bessel function ev 1 min read
• numpy.hypot() in Python This mathematical function helps user to calculate hypotenuse for the right angled triangle, given its side and perpendicular. Result is equivalent to Equivalent to sqrt(x1**2 + x2**2), element-wise. Syntax : numpy.exp2(arr1, arr2[, out]) = ufunc 'hypot') : Parameters : arr1, arr2 : [array_like] Leg 2 min read