Numpy

python

import numpy as np 

a = np.zeros(4);
# a = [0. 0. 0. 0.]
a = np.random.random_sample(4)
# [0.79854204 0.53395596 0.42365001 0.52982915]

python

a = np.arange(10)
# [0 1 2 3 4 5 6 7 8 9]
a[2] # 2
a[-1] # 9

python

#vector slicing operations
a = np.arange(10)
# a = [0 1 2 3 4 5 6 7 8 9]

#access 5 consecutive elements (start:stop:step)
c = a[2:7:1]; # [2 3 4 5 6]

# access 3 elements separated by two 
c = a[2:7:2]; # [2 4 6]

# access all elements index 3 and above
c = a[3:]; # [3 4 5 6 7 8 9]

# access all elements below index 3
c = a[:3]; # [0 1 2]

# access all elements
c = a[:]; # [0 1 2 3 4 5 6 7 8 9]

python

a = np.array([1,2,3,4])
# [1 2 3 4]

b = -a 
# [-1 -2 -3 -4]

# sum all elements of a, returns a scalar
b = np.sum(a) 
# 10

b = np.mean(a)
# 2.5

b = a**2
# [ 1  4  9 16]

python

# test 1-D
a = np.array([1, 2, 3, 4])
b = np.array([-1, 4, 3, 2])
c = np.dot(a, b)
print(f"NumPy 1-D np.dot(a, b) = {c}, np.dot(a, b).shape = {c.shape} ") 
c = np.dot(b, a)
print(f"NumPy 1-D np.dot(b, a) = {c}, np.dot(a, b).shape = {c.shape} ")

# NumPy 1-D np.dot(a, b) = 24, np.dot(a, b).shape = () 
# NumPy 1-D np.dot(b, a) = 24, np.dot(a, b).shape = ()

python

a = np.zeros((1, 5))                                       
print(f"a shape = {a.shape}, a = {a}")                     

a = np.zeros((2, 1))                                                                   
print(f"a shape = {a.shape}, a = {a}") 

a = np.random.random_sample((1, 1))  
print(f"a shape = {a.shape}, a = {a}") 

# a shape = (1, 5), a = [[0. 0. 0. 0. 0.]]
# a shape = (2, 1), a = [
# [0.], 
# [0.]]
# a shape = (1, 1), a = [[0.44236513]]

python

a = np.arange(6).reshape(-1, 2)
#reshape is a convenient way to create matrices
print(f"a.shape: {a.shape}, \na= {a}")
# a.shape: (3, 2), 
# a= [[0 1]
#  [2 3]
#  [4 5]]

python

#vector 2-D slicing operations
a = np.arange(20).reshape(-1, 10)
# a = 
# [[ 0  1  2  3  4  5  6  7  8  9]
#  [10 11 12 13 14 15 16 17 18 19]]

#access 5 consecutive elements (start:stop:step)
print("a[0, 2:7:1] = ", a[0, 2:7:1], ",  a[0, 2:7:1].shape =", a[0, 2:7:1].shape, "a 1-D array")
# a[0, 2:7:1] =  [2 3 4 5 6] ,  a[0, 2:7:1].shape = (5,) a 1-D array

#access 5 consecutive elements (start:stop:step) in two rows
print("a[:, 2:7:1] = \n", a[:, 2:7:1], ",  a[:, 2:7:1].shape =", a[:, 2:7:1].shape, "a 2-D array")
# a[:, 2:7:1] = 
#  [[ 2  3  4  5  6]
#  [12 13 14 15 16]] ,  a[:, 2:7:1].shape = (2, 5) a 2-D array

# access all elements
print("a[:,:] = \n", a[:,:], ",  a[:,:].shape =", a[:,:].shape)
# a[:,:] = 
#  [[ 0  1  2  3  4  5  6  7  8  9]
#  [10 11 12 13 14 15 16 17 18 19]] ,  a[:,:].shape = (2, 10)

# access all elements in one row (very common usage)
print("a[1,:] = ", a[1,:], ",  a[1,:].shape =", a[1,:].shape, "a 1-D array")
# a[1,:] =  [10 11 12 13 14 15 16 17 18 19] ,  a[1,:].shape = (10,) a 1-D array

# same as
print("a[1]   = ", a[1],   ",  a[1].shape   =", a[1].shape, "a 1-D array")
# a[1]   =  [10 11 12 13 14 15 16 17 18 19] ,  a[1].shape   = (10,) a 1-D array