[Numpy] csr_matrix | .todense() | .tocoo() |
csr_matrix
通过csr_matrix构建得到的是稀疏矩阵。
csr_matrix(((数据np, (行list, 列list)))
其中，数据是numpy形式，行和列是list，三者的长度要一致。
行、列一起定位数据的坐标位置。没有数据、坐标的部分，默认为0。
.todense()
将稀疏矩阵转为稠密矩阵。
.tocoo()
将稠密矩阵转为稀疏矩阵。
例子：
from scipy.sparse import *
import numpy as np
row = [0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2] # 行指标(user)
col = [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2] # 列指标(items)
data1 = np.ones(11) # len(row) = len(col) = 11
data2 = np.array([1,2,3,4,5,6,7,8,9,10,11])
team1 = csr_matrix((data1, (row, col)), shape=(3, 4))
team2 = csr_matrix((data2, (row, col)), shape=(3, 4))
print('team1:\n', team1)
print('team2:\n', team2)
print('team1(dense):\n', team1.todense())
print('team2(dense):\n', team2.todense())
team_coo1 = team1.tocoo() # 返回稀疏矩阵的coo_matrix形式
team_coo2 = team2.tocoo() # 返回稀疏矩阵的coo_matrix形式
print('team1(tocoo):\n', team_coo1)
print('team2(tocoo):\n', team_coo2)
输出结果：
team1:
(0, 0) 1.0
(0, 1) 1.0
(0, 2) 1.0
(0, 3) 1.0
(1, 0) 1.0
(1, 1) 1.0
(1, 2) 1.0
(1, 3) 1.0
(2, 0) 1.0
(2, 1) 1.0
(2, 2) 1.0
team2:
(0, 0) 1
(0, 1) 2
(0, 2) 3
(0, 3) 4
(1, 0) 5
(1, 1) 6
(1, 2) 7
(1, 3) 8
(2, 0) 9
(2, 1) 10
(2, 2) 11
team1(dense):
[[1. 1. 1. 1.]
[1. 1. 1. 1.]
[1. 1. 1. 0.]]
team2(dense):
[[ 1 2 3 4]
[ 5 6 7 8]
[ 9 10 11 0]]
team1(tocoo):
(0, 0) 1.0
(0, 1) 1.0
(0, 2) 1.0
(0, 3) 1.0
(1, 0) 1.0
(1, 1) 1.0
(1, 2) 1.0
(1, 3) 1.0
(2, 0) 1.0
(2, 1) 1.0
(2, 2) 1.0
team2(tocoo):
(0, 0) 1
(0, 1) 2
(0, 2) 3
(0, 3) 4
(1, 0) 5
(1, 1) 6
(1, 2) 7
(1, 3) 8
(2, 0) 9
(2, 1) 10
(2, 2) 11