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In [2]:

    
import numpy as np



In [3]:

    
x=np.zeros((3,4,5))

1D called vector 2D called matrix 3D nad so on tensor



In [4]:

    
print x









    



[[[ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]]

 [[ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]]

 [[ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]]]



In [5]:

    
type(x)









    Out[5]:





numpy.ndarray



In [6]:

    
y=np.ones((2,3))



In [7]:

    
print y









    



[[ 1.  1.  1.]
 [ 1.  1.  1.]]

I need a matrix like this

[[2,3],
         [4,5],
         [6,7]]



In [8]:

    
z=np.arange(2,8,1)
alpha=np.reshape(z,(3,2))
print alpha









    



[[2 3]
 [4 5]
 [6 7]]



In [9]:

    
beta= np.random.randn(3,4)
print beta









    



[[-0.60655405  0.6175917   1.6962759   1.89094038]
 [ 0.56150403 -1.25588071 -0.58245218  0.87327847]
 [ 0.49423431 -0.30754252 -0.56212643  1.129681  ]]



In [10]:

    
gamma=beta*2.0
print gamma









    



[[-1.21310811  1.23518339  3.3925518   3.78188075]
 [ 1.12300805 -2.51176142 -1.16490437  1.74655694]
 [ 0.98846862 -0.61508505 -1.12425287  2.259362  ]]



In [11]:

    
a=[3,4,5]
a=np.array(a)
type(a)









    Out[11]:





numpy.ndarray

np array operator



In [12]:

    
a=np.random.randint(0,10,(2,3))
b=np.random.randint(0,10,(2,3))
print a
print b









    



[[2 9 4]
 [1 6 0]]
[[4 6 4]
 [7 1 0]]



In [13]:

    
print "element-wise addition:\n%s"%(a + b)









    



element-wise addition:
[[ 6 15  8]
 [ 8  7  0]]



In [14]:

    
print "element-wise addition:\n%s"%(a * b)









    



element-wise addition:
[[ 8 54 16]
 [ 7  6  0]]



In [15]:

    
print a
print b.T
print '-----'
print np.dot(a,b.T)









    



[[2 9 4]
 [1 6 0]]
[[4 7]
 [6 1]
 [4 0]]
-----
[[78 23]
 [40 13]]

Sliccing



In [16]:

    
a=np.random.randint(0,10,(4,5))
print a









    



[[6 8 5 8 8]
 [7 8 9 4 1]
 [3 7 3 0 4]
 [0 5 1 9 8]]



In [17]:

    
a[0,2]









    Out[17]:





5



In [18]:

    
a[3,3]=9
print a









    



[[6 8 5 8 8]
 [7 8 9 4 1]
 [3 7 3 0 4]
 [0 5 1 9 8]]



In [19]:

    
print a[:,:3]









    



[[6 8 5]
 [7 8 9]
 [3 7 3]
 [0 5 1]]



In [20]:

    
print a[:3,:]









    



[[6 8 5 8 8]
 [7 8 9 4 1]
 [3 7 3 0 4]]



In [21]:

    
print a[:3,:3]









    



[[6 8 5]
 [7 8 9]
 [3 7 3]]



In [22]:

    
print a[-3:,-3:]









    



[[9 4 1]
 [3 0 4]
 [1 9 8]]



In [23]:

    
b=np.array([2,3,5,7,8])
print b









    



[2 3 5 7 8]



In [24]:

    
b[::-1]









    Out[24]:





array([8, 7, 5, 3, 2])



In [25]:

    
a=np.random.randint(0,10,(4,5))
print a









    



[[0 2 6 9 7]
 [3 9 6 3 3]
 [8 1 8 2 4]
 [4 5 3 2 3]]



In [26]:

    
a[::-1]









    Out[26]:





array([[4, 5, 3, 2, 3],
       [8, 1, 8, 2, 4],
       [3, 9, 6, 3, 3],
       [0, 2, 6, 9, 7]])



In [27]:

    
print np.fliplr(a)









    



[[7 9 6 2 0]
 [3 3 6 9 3]
 [4 2 8 1 8]
 [3 2 3 5 4]]



In [28]:

    
a.astype(float)









    Out[28]:





array([[ 0.,  2.,  6.,  9.,  7.],
       [ 3.,  9.,  6.,  3.,  3.],
       [ 8.,  1.,  8.,  2.,  4.],
       [ 4.,  5.,  3.,  2.,  3.]])

Goto opencv/build/python/2.7 folder.
Copy cv2.pyd to C:/Python27/lib/site-packeges.
http://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html



In [35]:

    
print np.arange(16)[::2]









    



[ 0  2  4  6  8 10 12 14]



In [45]:

    
(-1,)+(1,2,3)+(4,5)









    Out[45]:





(-1, 1, 2, 3, 4, 5)



In [ ]: