Python | Numpy np.ifftn() method Last Updated : 21 Nov, 2019 Comments Improve Suggest changes Like Article Like Report 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 series of inverse fourier transformation by using this method. Python3 1=1 # import numpy import numpy as np a = np.array([-1, 3, -4, 7, 0]) # using np.ifftn() method gfg = np.fft.ifftn(a) print(gfg) Output : [ 1. +0.j -0.5-0.72249365j -0.5+2.44499549j -0.5-2.44499549j -0.5+0.72249365j] Example #2 : Python3 1=1 # import numpy 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]]) # using np.ifftn() method gfg = np.fft.ifftn(a) print(gfg) Output : [[-1.76+0.j -0.11+0.96624249j -0.11+0.30801859j -0.11-0.30801859j -0.11-0.96624249j] [-0.66+0.j -0.66+0.17149948j -0.66+2.99751362j -0.66-2.99751362j -0.66-0.17149948j]] Comment More infoAdvertise with us Next Article Python | Numpy np.ifftn() method J Jitender_1998 Follow Improve Article Tags : Python Python-numpy Python numpy-Matrix Function Practice Tags : python Similar Reads 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.fftn() method 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 tran 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.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.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.lookfor() method With the help of numpy.lookfor() method, we can get the information about the module in the numpy by using numpy.lookfor() method. Syntax : numpy.lookfor(module_name) Return : Return the information about the module. Example #1 : In this example we can see that by using numpy.lookfor() method, we ar 1 min read numpy.finfo() function – Python numpy.finfo() function shows machine limits for floating point types. Syntax : numpy.finfo(dtype) Parameters : dtype : [float, dtype, or instance] Kind of floating point data-type about which to get information. Return : Machine parameters for floating point types. Code #1 : Python3 # Python program 1 min read numpy.flatnonzero() in Python numpy.flatnonzero()function is used to Compute indices that are non-zero in the flattened version of arr. Syntax : numpy.flatnonzero(arr) Parameters : arr : [array_like] Input array. Return : ndarray Output array, containing the indices of the elements of arr.ravel() that are non-zero. Code #1 : Wor 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.nonzero() in Python numpy.nonzero()function is used to Compute the indices of the elements that are non-zero. It returns a tuple of arrays, one for each dimension of arr, containing the indices of the non-zero elements in that dimension. The corresponding non-zero values in the array can be obtained with arr[nonzero(ar 2 min read Like