import numpy as np
def numpywork1(): # 矩陣的求和運算
one = np.array([[1, 0, 1, 3, 4, 1],
[2, 1, 4, 2, 3, 0],
[3, 5, 4, 1, 3, 2],
[2, 6, 3, 1, 3, 8],
[9, 1, 2, 1, 5, 0],
])two = np.sum(one, axis= 0) # 每一列求和，得到的新矩陣
three = np.sum(one, axis= 1) # 每一行求和，得到的新矩陣
print('two=', two)
print('three=', three)
return
def numpywork2(): # 兩個向量相乘
one = np.array([3, 5, 8, 10, 9, 2, 4, 5, 1])
two = np.array([2, 3, 4, 2, 6, 7, 9, 10, 2])
three = np.multiply(one, two)
print('three=', three)
return
def numpywork3(): # 矩陣的歐氏距離
one = np.array([[1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 3, 9, 7, 8, 9], [1, 2, 6, 4, 8, 6, 7, 8, 9]])
two = np.array([[2, 3, 4, 5, 6, 7, 8, 9, 10], [2, 3, 4, 8, 6, 7, 12, 9, 10], [2, 3, 4, 9, 2, 7, 8, 9, 10]])
dist1 = np.linalg.norm(one - two) # 矩陣的歐氏距離
dist2 = np.square(one - two)
print('one=', one)
print('two=', two)
print('dist1=', dist1) # 此處為乙個數值
print('dist2=', dist2)
return
def euclideandistances(a, b): # 兩個矩陣求歐氏距離 - - - 偏慢（網上提供的方法）
bt = b.transpose()
vecprod = a * bt
sqa = a.geta()**2
sumsqa = np.matrix(np.sum(sqa, axis=1))
sumsqaex = np.tile(sumsqa.transpose(), (1, vecprod.shape[1]))
sqb = b.geta()**2
sumsqb = np.sum(sqb, axis=1)
sumsqbex = np.tile(sumsqb, (vecprod.shape[0], 1))
sqed = sumsqbex + sumsqaex - 2*vecprod
ed = (sqed.geta())**0.5
return np.matrix(ed)
def euclideandistancesbetter(): # 矩陣與向量的歐氏距離計算速度很快，根據數學公式計算的，算起來較快，推薦使用
one = np.array([[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
[2, 3, 4, 5, 6, 7, 8, 9, 10, 11],
[15, 16, 17, 18, 19, 20, 21, 22, 23, 24],
[1, 2, 1, 2, 1, 2, 1, 2, 1, 2],
])two = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
result_ed1 = np.linalg.multi_dot([one, two]) # 兩個矩陣向量的歐氏距離
result_ed2 = 1 / (1 + result_ed1)
print('result_ed1= ', result_ed1) # result_ed1= [ 385 440 1155 85]
print('result_ed2= ', result_ed2) # result_ed2= [0.00259067 0.00226757 0.00086505 0.01162791]
return
#numpywork1(): # 矩陣的求和運算
#numpywork2(): # 兩個向量相乘
#numpywork3() # 矩陣的歐氏距離
#euclideandistances(a, b): # 兩個矩陣求歐氏距離 - - - 偏慢
#euclideandistancesbetter() # 矩陣與向量的歐氏距離計算速度很快（推薦使用）
python numpy 矩陣堆疊
在實際操作中，遇到了矩陣堆疊的操作，本來想著自己寫乙個函式，後來想，應該有庫函式，於是一陣找尋 import numpy as np a np.array 1,2,3 b np.array 4,5,6 np.stack a,b 預設行堆疊 輸出 array 1,2,3 4,5,6 np.vstack...
python numpy 矩陣運算
轉置np.transpose x 乘np.dot x,y a.dot b dot c 逆np.linalg.inv x 轉為1維 a.flatten 除 就是乘矩陣的逆a b a.dot np.linalg.inv b 刪除一列axis 1 行axis 0 np.delete t1,j,axis 0...
python numpy包 矩陣運算
下面簡要介紹python和matlab處理數學問題的幾個不同點。1.matlab的基本是矩陣，而numpy的基本型別是多為陣列，把matrix看做是array的子類。2.matlab的索引從1開始，而numpy從0開始。1.建立矩陣 a1 np.array 1,2,3 dtype int 建立乙個一...