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]
