numpy知識點補充

import numpy as np

a = np.zeros((2,2))   #建立2x2的全零矩陣
print(a)
b = np.ones((1,2))    #建立1x2的全一矩陣
print(b)              
c = np.full((2,2), 7)  #建立2x2的全為7的矩陣
print(c)               
d = np.eye(2)        #建立全1的2x2對角矩陣
print(d)            
e = np.random.random((2,2))  #建立2x2的隨機數矩陣
print(e)
[[0. 0.]
[0. 0.]]
[[1. 1.]]
[[7 7]
[7 7]]
[[1. 0.]
[0. 1.]]
[[0.57761083 0.61231605]
[0.10407747 0.88935241]]

a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])

b = a[:2, 1:3] #獲取前兩行，第二列第三列的資料
[[2 3]
[6 7]]
a = np.array([[1,2], [3, 4], [5, 6]])
print(a[[0, 1, 2], [0, 1, 0]])  
[1 4 5]

import numpy as np

a = np.array([[1,2], [3, 4], [5, 6]])
bool_idx = (a > 2)   
print(bool_idx)     
print(a[bool_idx])  # prints "[3 4 5 6]"
print(a[a > 2])     # prints "[3 4 5 6]"

import numpy as np

x = np.array([1, 2])   
print(x.dtype)         # prints "int64"
x = np.array([1.0, 2.0])   
print(x.dtype)             # prints "float64"
x = np.array([1, 2], dtype=np.int64)   
print(x.dtype)                         # prints "int64"

import numpy as np

x = np.array([[1,2],[3,4]])
print(np.sum(x))  # prints "10"
print(np.sum(x, axis=0))  # prints "[4 6]"
print(np.sum(x, axis=1))  # prints "[3 7]"
print(x.t)  # prints "[[1 3]
#          [2 4]]"
print(x.dot(v))
print(np.dot(x, v))  #向量內積

import numpy as np

x = np.array([[1,2,3], [4,5,6], [7,8,9], [10, 11, 12]])
v = np.array([1, 0, 1])
y = np.empty_like(x)   # 建立乙個維度與x一樣的空矩陣
# x的每一行都加上v向量
for i in range(4):
y[i, :] = x[i, :] + v
print(y)
# [[ 2  2  4]
#  [ 5  5  7]
#  [ 8  8 10]
#  [11 11 13]]

import numpy as np

x = np.array([[1,2,3], [4,5,6], [7,8,9], [10, 11, 12]])
v = np.array([1, 0, 1])
vv = np.tile(v, (4, 1))   # 堆疊行4次
print(vv)                 # prints "[[1 0 1]
#          [1 0 1]
#          [1 0 1]
#          [1 0 1]]"
y = x + vv 
print(y)  # prints "[[ 2  2  4
#          [ 5  5  7]
#          [ 8  8 10]
#          [11 11 13]]"
#當前版本可直接加
x = np.array([[1,2,3], [4,5,6], [7,8,9], [10, 11, 12]])
v = np.array([1, 0, 1])
y = x + v  
print(y)  # prints "[[ 2  2  4]
#          [ 5  5  7]
#          [ 8  8 10]
#          [11 11 13]]"

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