一、* dot() multiply()
1, 对于array来说，* 和 dot()运算不同，* 和 multiply()运算相同
*和multiply() 是每个元素对应相乘
dot() 是矩阵乘法
2, 对于matrix来说，* 和 multiply() 运算不同
* 和dot() 是矩阵乘法
multiply() 是每个元素对应相乘
3, 混合的时候（与矩阵同）
multiply 为对应乘
*为 矩阵乘法（但无下述适应性）
dot为矩阵乘法（矩阵在前数组在后时，均为一维时数组可适应，即能做矩阵乘法）
Python 3.6.4 (default, Jan 7 2018, 03:52:16)
[GCC 4.2.1 Compatible Android Clang 5.0.300080 ] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> a1=np.array([1,2,3])
>>> a1*a1
array([1, 4, 9])
>>> np.dot(a1,a1)
14
>>> np.multiply(a1,a1)
array([1, 4, 9])
>>> m1 = np.mat(a1)
>>> m1
matrix([[1, 2, 3]])
>>> m1*m1
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/data/data/com.termux/files/usr/lib/python3.6/site-packages/numpy-1.13.3-py3.6-linux-aarch64.egg/numpy/matrixlib/defmatrix.py", line 309, in __mul__
return N.dot(self, asmatrix(other))
ValueError: shapes (1,3) and (1,3) not aligned: 3 (dim 1) != 1 (dim 0)
>>> np.dot(m1,m1)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: shapes (1,3) and (1,3) not aligned: 3 (dim 1) != 1 (dim 0)
>>> np.multiply(m1,m1)
matrix([[1, 4, 9]])
>>> np.multiply(a1,m1)
matrix([[1, 4, 9]])
>>> np.multiply(m1,a1)
matrix([[1, 4, 9]])
>>> np.dot(a1,m1)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: shapes (3,) and (1,3) not aligned: 3 (dim 0) != 1 (dim 0)
>>> np.dot(m1,a1)
matrix([[14]])
>>> a1*m1
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/data/data/com.termux/files/usr/lib/python3.6/site-packages/numpy-1.13.3-py3.6-linux-aarch64.egg/numpy/matrixlib/defmatrix.py", line 315, in __rmul__
return N.dot(other, self)
ValueError: shapes (3,) and (1,3) not aligned: 3 (dim 0) != 1 (dim 0)
>>> m1*a1
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/data/data/com.termux/files/usr/lib/python3.6/site-packages/numpy-1.13.3-py3.6-linux-aarch64.egg/numpy/matrixlib/defmatrix.py", line 309, in __mul__
return N.dot(self, asmatrix(other))
ValueError: shapes (1,3) and (1,3) not aligned: 3 (dim 1) != 1 (dim 0)
>>> a1,m1
(array([1, 2, 3]), matrix([[1, 2, 3]]))
>>>
