Python | Numpy np.ifft2() method (original) (raw)
Last Updated : 21 Nov, 2019
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 series of inverse fourier transformation by using this method.
import
numpy as np
a
=
np.array([[
5
,
4
,
6
,
3
,
7
], [
-
1
,
-
3
,
-
4
,
-
7
,
0
]])
gfg
=
np.fft.ifft2(a)
print
(gfg)
Output :
[[ 1. +0.j 0.80901699-0.21796276j -0.30901699-0.92330506j
-0.30901699+0.92330506j 0.80901699+0.21796276j]
[ 4. +0.j -0.5854102 +0.j 0.0854102 +0.j
0.0854102 +0.j -0.5854102 +0.j ]]
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.ifft2(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]]
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.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.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.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.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.isnat() method With the help of numpy.isnat() method, we can get the boolean value as true if date defined in a np.datetime64() method is not a time by using numpy.isnat() method. Syntax : numpy.isnat() Return : Return the boolean value if time is not found. Example #1 : In this example we can see that by using nu 1 min read
- Python | Numpy np.heaviside() method With the help of np.heaviside() method, we can get the heaviside step function by using np.heaviside() method. Syntax : np.heaviside(array1, array2 or value) Return : Return the heaviside series. Example #1 : In this example we can see that by using np.heaviside() method, we are able to get the arra 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 count_nonzero method | Python numpy.count_nonzero() function counts the number of non-zero values in the array arr. Syntax : numpy.count_nonzero(arr, axis=None) Parameters : arr : [array_like] The array for which to count non-zeros. axis : [int or tuple, optional] Axis or tuple of axes along which to count non-zeros. Default is 1 min read
- Python | Numpy ndarray.__imod__() With the help of Numpy ndarray.__imod__(), every element in an array is operated on binary operator i.e mod(%). Remember we can use any type of values in an array and value for mod is applied as the parameter in ndarray.__imod__(). Syntax: ndarray.__imod__($self, value, /) Return: self%=value Exampl 1 min read