Flatten A list of NumPy arrays

16 Sep, 2021
Prerequisite Differences between Flatten() and Ravel() Numpy Functions, numpy.ravel() in Python, 
In this article, we will see how we can flatten a list of numpy arrays. NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
Flatten a list of NumPy array means to combine the multiple dimensional NumPy arrays into a single array or list, below is the example 
List of numpy array : [array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]])]
Flatten numpy array : array([ 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654])  
Method 1 Using numpy’s concatenate method  
Python3
# importing numpy as npimport numpy as np # list of numpy arraylist_array = [np.array([[1]]),               np.array([[2]]),               np.array([[3]]),               np.array([[4]]),               np.array([[5]]),               np.array([[6]]),               np.array([[7]]),               np.array([[8]]),               np.array([[9]]),               np.array([[10]]),               np.array([[11]]),               np.array([[12]]),               np.array([[13]]),               np.array([[14]]),               np.array([[15]]),               np.array([[16]])] # concatenating all the numpy arrayflatten = np.concatenate(list_array) # printing the ravel flatten arrayprint(flatten.ravel())
Output : 
[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16]
Method 2 Using numpy’s flatten method 
Python3
# importing numpy as npimport numpy as np # list of numpy arraylist_array = [np.array([[1]]),               np.array([[2]]),               np.array([[3]]),               np.array([[4]]),               np.array([[5]]),               np.array([[6]]),               np.array([[7]]),               np.array([[8]]),               np.array([[9]]),               np.array([[10]]),               np.array([[11]]),               np.array([[12]]),               np.array([[13]]),               np.array([[14]]),               np.array([[15]]),               np.array([[16]])] # flatten the numpy arrayflatten = np.array(list_array).flatten() # printing the flatten arrayprint(flatten)
Output : 
[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16]
Method 3 Using numpy’s ravel method 
Python3
# importing numpy as npimport numpy as np # list of numpy arraylist_array = [np.array([[1]]),               np.array([[2]]),               np.array([[3]]),               np.array([[4]]),               np.array([[5]]),               np.array([[6]]),               np.array([[7]]),               np.array([[8]]),               np.array([[9]]),               np.array([[10]]),               np.array([[11]]),               np.array([[12]]),               np.array([[13]]),               np.array([[14]]),               np.array([[15]]),               np.array([[16]])] # flatten the numpy array using ravel methodflatten = np.array(list_array).ravel() # printing the flatten arrayprint(flatten)
Output : 
[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16]
Method 4 Using numpy’s reshape method  
Python3
# importing numpy as npimport numpy as np # list of numpy arraylist_array = [np.array([[1]]),               np.array([[2]]),               np.array([[3]]),               np.array([[4]]),               np.array([[5]]),               np.array([[6]]),               np.array([[7]]),               np.array([[8]]),               np.array([[9]]),               np.array([[10]]),               np.array([[11]]),               np.array([[12]]),               np.array([[13]]),               np.array([[14]]),               np.array([[15]]),               np.array([[16]])] # flatten the numpy array using reshape methodflatten = np.array(list_array).reshape(-1) # printing the flatten arrayprint(flatten)
Output : 
[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16]
 
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