

In [2]:

    
import numpy as np

slicing

start:stop:step



In [3]:

    
a = [1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4]



In [4]:

    
a[::2]









    Out[4]:





[1, 3, 1, 3, 1, 3]



In [5]:

    
a[0::2]









    Out[5]:





[1, 3, 1, 3, 1, 3]



In [6]:

    
a[::1]









    Out[6]:





[1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4]



In [7]:

    
a









    Out[7]:





[1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4]

nonzero

Return the indices of the elements that are non-zero.



In [8]:

    
print(np.nonzero([1,2,3,0,4,0]))









    



(array([0, 1, 2, 4]),)



In [9]:

    
arr = np.array([[1,0],[2,3]])



In [10]:

    
print(arr)









    



[[1 0]
 [2 3]]



In [11]:

    
arr.nonzero()









    Out[11]:





(array([0, 1, 1]), array([0, 0, 1]))



In [12]:

    
arr[arr.nonzero()]









    Out[12]:





array([1, 2, 3])



In [13]:

    
print(np.nonzero([1,2,3,0,4,0]))









    



(array([0, 1, 2, 4]),)

vstack



In [40]:

    
A = np.zeros((1, 300, 3))
B = np.zeros((1, 300))

#B = np.expand_dims(B, axis=2)
B = np.expand_dims(B, axis=-1)
print(A.shape)
print(B.shape)









    



(1, 300, 3)
(1, 300, 1)



In [41]:

    
A = A[0,:,:]
B = B[0,:,:]
print(A.shape)
print(B.shape)









    



(300, 3)
(300, 1)



In [42]:

    
C = np.hstack((A, B))
print(C.shape)
C = np.expand_dims(C, axis=0)
print(C.shape)









    



(300, 4)
(1, 300, 4)