[Data Analysis & Data Mining] create a matrix of

. 1  Import numpy AS NP
 2  
. 3  # matrix is a two-dimensional 
4  # used to create a matrix mat == asmatrix 
5  #
 6  # # string using the mat into a matrix 
. 7 M1 = np.mat ( " . 1 2. 3; 4 5 . 6;. 7. 8. 9 " )
 . 8  # np.asmatrix () is equivalent to np.mat () 
. 9  
10  # using nested list into the mat matrix 
. 11 M1 = np.mat ([[. 1, 2,. 3], [ . 4,. 5,. 6], [. 7,. 8,. 9 ]])
 12 is  # M1 = np.mat ([[[. 1, 2,. 3], [. 4,. 5,. 6], [. 7,. 8,. 9]] ]) # not possible, can not be converted to two nested lists matrix 
13 is  
14  # using the mat into an array matrix 
15= np.array ARR ([[. 1, 2,. 3], [. 4,. 5,. 6], [. 7,. 8,. 9 ]])
 16  # as long as the array, inside the real values are two-dimensional, it can be conversion matrix 
. 17 ARR = np.array ([[[. 1, 2,. 3], [. 4,. 5,. 6], [. 7,. 8,. 9]]]) # only three-dimensional array comprising a two-dimensional array, can be into matrix 
18 is  # ARR = np.array ([[[. 1, 2,. 3], [. 4,. 5,. 6], [. 7,. 8,. 9]], [[. 1, 2,. 3], [. 4, 5, 6], [7, 8, 9]]]) # not possible 
. 19 ARR = np.array ([[[[. 1, 2,. 3], [. 4, 5, 6], [7, 8, 9]]]]) # only two-dimensional array containing a four-dimensional array, can be converted into matrix 
20 is m1 = np.mat (ARR)
 21 is  Print ( " m1: \ n- " , m1)
 22 is  Print ( " type m1 of: \ the n- " , of the type (M1))
 23 
24  # using a matrix to create a matrix 
25  # can use the matrix to a string, nested list, a two-dimensional array into a matrix of 
26  # as long as the array of internal real value is two-dimensional, it can be transformed into a matrix 
27 M1 = NP .matrix ( " . 1 2. 3;. 4. 5. 6;. 7. 8. 9 " )
 28 M1 = np.matrix ([[. 1, 2,. 3], [. 4,. 5,. 6], [. 7,. 8,. 9 ]])
 29  # M1 = np.matrix ([[[. 1, 2,. 3], [. 4,. 5,. 6], [. 7,. 8,. 9]]]) is not # 
30 ARR = np.array ([[. 1 , 2,. 3], [. 4,. 5,. 6], [. 7,. 8,. 9 ]])
 31 is ARR = np.array ([[[. 1, 2,. 3], [. 4,. 5,. 6], [. 7 ,. 8,. 9 ]]])
 32 ARR = np.array ([[[[. 1, 2,. 3], [. 4,. 5,. 6], [. 7,. 8,. 9 ]]]])
 33 is M1 = NP. matrix (arr)
34 is  Print ( " m1: \ n- " , m1)
 35  Print ( " Type of m1: \ n- " , type (m1))
 36  # directly create a matrix can be used MAT asmatrix matrix 
37 [  # MAT and asmatrix same 
38  # than the matrix less a Copy 
39  # recommended mat or asmatrix 
40  
41 is  
42 is  # use bmat to combining matrix 
43 is L1 = [[. 1, 2], [2,. 1 ]]
 44 is L2 = [[0,. 1], [0,. 1 ]]
 45 of arr1 = np.array (L1)
 46 is arr2 is = np.array (L2)
 47 Print ( " of arr1: \ n- " , of arr1)
 48  Print ( " arr2 is: \ n- " , arr2 is)
 49  
50  # use an array of strings can BMAT --- string list conversion or combining matrix 
51 is M2 = np.bmat ( " of arr1 arr2 is; arr2 is of arr1 " )
 52 is M2 = np.bmat ( " L1 L2; L1 L2 " )
 53 is  # using bmat array may be a list, or a list of nested form into a matrix composition 
54 is M2 = np.bmat ( [[of arr1, arr2 is], [arr2 is, of arr1]])
 55 M2 = np.bmat ([[L1, L2], [L2, L1]])
 56 is  
57 is  # # arr = np.array(arr1, arr2)  # 不可以
58 print("~" * 60)
59 arr = np.array([[arr1, arr2], [arr2, arr1]])
60 print(arr)
61 print(arr.ndim)
62 # print(arr.shape)
63 print("~" * 60)
64 
65 # m2 = np.bmat(arr)
66 print("m2:\n", m2)
67 print("m2的类型：\n", type(m2))